U.S. patent application number 14/197014 was filed with the patent office on 2014-09-04 for method and kit for characterizing microorganisms.
The applicant listed for this patent is Fry Laboratories, LLC. Invention is credited to Jeremy Ellis, Stephen E. Fry.
Application Number | 20140249037 14/197014 |
Document ID | / |
Family ID | 50483475 |
Filed Date | 2014-09-04 |
United States Patent
Application |
20140249037 |
Kind Code |
A1 |
Fry; Stephen E. ; et
al. |
September 4, 2014 |
METHOD AND KIT FOR CHARACTERIZING MICROORGANISMS
Abstract
The present disclosure provides methods of characterizing one or
more microorganisms and kits for characterizing at least one
microorganism. Exemplary methods include preparing an amplicon
library, sequencing a characteristic gene sequence to obtain a gene
sequence, and characterizing the one or more microorganisms based
on the gene sequence using a computer-based genomic analysis of the
gene sequence. Exemplary kits include at least one forward primer
including an adapter sequence and a priming sequence, for a target
sequence, and at least one reverse primer.
Inventors: |
Fry; Stephen E.;
(Scottsdale, AZ) ; Ellis; Jeremy; (Mesa,
AZ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Fry Laboratories, LLC |
Scottsdale |
AZ |
US |
|
|
Family ID: |
50483475 |
Appl. No.: |
14/197014 |
Filed: |
March 4, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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61772425 |
Mar 4, 2013 |
|
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Current U.S.
Class: |
506/2 |
Current CPC
Class: |
C12Q 1/6888 20130101;
C12Q 2600/16 20130101; C12N 15/1093 20130101; C12Q 1/6869 20130101;
G16B 30/00 20190201; C12Q 1/689 20130101; G16B 20/00 20190201; C12Q
1/6804 20130101; C12Q 1/6804 20130101; C12Q 2531/113 20130101; C12Q
2535/122 20130101; C12Q 1/6869 20130101; C12Q 2531/113 20130101;
C12Q 2535/122 20130101 |
Class at
Publication: |
506/2 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; G06F 19/18 20060101 G06F019/18 |
Claims
1. A method of identifying a plurality of microorganisms in a
biological sample comprising: a) extracting nucleic acids from the
biological sample; b) preparing an ion amplicon library with a
polymerase chain reaction (PCR) reaction of the nucleic acids; c)
purifying the ion amplicon library from the PCR reaction; d)
sequencing a 16S ribosomal RNA (16S rRNA) gene in the ion amplicon
library with an ion semiconductor sequencing platform; and e)
identifying the species of the plurality of microorganisms with a
computer-based genomic analysis of the 16S rRNA gene sequence.
2. The method of claim 1, wherein the PCR reaction uses a forward
primer comprising a barcode, a barcode adapter, and a target
sequence.
3. The method of claim 2, wherein the barcode comprises a sequence
selected from the group consisting of SEQ ID NO: 1, SEQ ID NO: 2,
SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO:
7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID
NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, and SEQ ID NO:
16.
4. The method of claim 2, wherein the barcode adaptor is SEQ ID NO:
17.
5. The method of claim 2, wherein the target sequence comprises a
sequence from the 16S rRNA gene.
6. The method of claim 5, wherein the sequence from the 16S rRNA is
selected from the group consisting of SEQ ID NO: 18, SEQ ID NO: 19,
SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID
NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28,
SEQ ID NO: 29, and SEQ ID NO: 30.
7. The method of claim 6, wherein the target sequence comprises SEQ
ID NO: 18.
8. The method of claim 6, wherein the target sequence comprises SEQ
ID NO: 19.
9. The method of claim 2, wherein the forward primer comprises a
sequence selected from the group consisting of SEQ ID NO: 35, SEQ
ID NO: 36, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO:
40, SEQ ID NO: 41, SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 44, SEQ
ID NO: 45, SEQ ID NO: 46, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO:
49, and SEQ ID NO: 50.
10. The method of claim 9, wherein the PCR reaction uses a reverse
primer comprising SEQ ID NO: 33.
11. The method of claim 2, wherein the forward primer comprises a
sequence selected from the group consisting of SEQ ID NO: 51, SEQ
ID NO: 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO:
56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ
ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64, SEQ ID NO:
65, and SEQ ID NO: 66.
12. The method of claim 11, wherein the PCR reaction uses a reverse
primer comprising SEQ ID NO: 34.
13. The method of claim 1, wherein the biological sample is
selected from a urine sample, a blood sample, a bronchioalveolar
lavage, a nasal swab, cerebrospinal fluid, synovial fluid, brain
tissue, cardiac tissue, bone, skin, a lymph node tissue, and a
dental tissue.
14. The method of claim 13, wherein the dental tissue is a tooth, a
soft tissue, or dental pulp.
15. The method of claim 1, wherein the plurality of microorganisms
comprises a bacterial pathogen.
16. The method of claim 1, wherein the plurality of microorganisms
comprises a nonculturable pathogen.
17. The method of claim 1, wherein the plurality of microorganisms
comprises a pathogenic community of microorganisms.
18. The method of claim 1, further comprising generating a report
with the species of the plurality of microorganisms.
19. The method of claim 18, wherein the report includes antibiotic
resistance information for each species.
20. The method of claim 1, wherein the computer-based genomic
analysis comprises application of a procedural algorithm to
sequencing data.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of provisional
application Ser. No. 61/772,425, entitled PAN-BACTERIAL
METAGENOMICS ASSAY, and filed Mar. 4, 2013, the contents of which
are hereby incorporated by reference.
TECHNICAL FIELD
[0002] The present disclosure generally relates to methods and kits
suitable for use in the diagnostic field for identification of one
or more microorganisms.
BACKGROUND
[0003] A variety of diagnostic tests are used to assist in the
treatment of patients with infections. Currently, there are four
main modalities to test for the presence of bacterial infections,
which are centered on a main diagnostic technology core. These four
main modalities are:
[0004] 1. Microscopy;
[0005] 2. Serology;
[0006] 3. Molecular; and
[0007] 4. Culture.
[0008] Each of these modalities has strengths and weaknesses.
Microscopy can detect a large number of infections; however, it
often lacks specificity to identify which species or even genus to
which a particular infection belongs. Serology can remotely detect
the body's immune response to an infectious agent; however, this
technique assumes the patient is immuno-competent and only assays a
specific bacterium at a time. Molecular diagnostics, typically
based on PCR methods, is highly sensitive, but it suffers a similar
issue as serology, whereby it only tests for a specific organism
(or sometimes only a specific strain) at a time. Culture methods
are unable to detect many strains of organisms that are currently
unculturable.
[0009] Many clinical microbiological identification methods rely on
passing through legacy technologies. One such technology is the
culture method used as a primary enrichment step. Culture depends
partially on the assumption that a disease-causing organism is
cultivatable. Non-culturable organisms may be entirely missed as an
etiologic agent and emerging or unique organisms could easily be
misidentified. Molecular identification tests rely upon the
amplification of pathogen specific DNA. These tests are sensitive;
however, they usually can only detect only a limited number of
organisms or genetic variants. Moreover, the starting material for
molecular identification typically relies on culture methods. It is
fairly well accepted that the majority of bacteria are present in
polymicrobial communities and cannot be cultivated.
[0010] A number of microbial detection and identification systems
have been developed. New protein-based diagnostics such as MALDI
TOF mass spectroscopy systems are now approved in Europe and are
pending approval in the United States. These systems include the
Bruker and bioMerieux systems. These systems usually require
culture first, rely on a limited reductionist diagnostic approach,
or have a limited throughput.
[0011] Blood stream infections (BSIs) are now the most expensive
type of hospital-acquired infection (HAI). A patient's average
length of hospital stay is also affected with sepsis patients
staying an average of about 23.3 days. Furthermore, it is estimated
that up to 40% of patients receive inadequate initial antibiotic
treatment that generates its complications and considerations.
Every hour that appropriate antibiotic treatment is delayed adds to
a patient's mortality rate. Delaying appropriate antibiotic
treatment by up to 45 hours is an independent predicting factor for
mortality in patients with S. aureus infections. This is
particularly compelling when culture-based microorganism
identification and the susceptibility of the identified
microorganism to specific antibiotics often requires between 24 to
72 hours.
[0012] Rapid microorganism identification would improve patient
outcomes. Mortality can be reduced for patients, and even more so
with ICU patients. Length-of-stay reductions could also be
realized; studies show that length of hospital stays could be
reduced by 2 days per patient or 7 days for an ICU patient with
another study showing an overall reduction by 6.2 days per patient.
Another study found significant cost savings per patient for
pharmacy, laboratory, and bed-related costs when rapid
infection-causing microorganism identification was implemented.
[0013] Some rapid diagnostic technologies include advanced MALDI
TOF, single organism PCR interrogation, and the PCR platform,
Biofire. Unfortunately, most of these technologies require
preceding culture methods, in which case, as noted above,
uncultivable organisms are missed. Second, some of these systems
have sensitivity and reproducibility issues such as a relatively
high error rate in the most advanced MALDI TOF systems.
Furthermore, these systems can suffer from sample volume throughput
issues whereby single samples or even single colony isolates are
processed one at a time. Finally, these technologies usually do not
achieve adequate processing turn-around times.
[0014] One approach to identify bacteria has been to clone
full-length 16S rRNA genes after polymerase chain reaction (PCR)
with primers that would amplify genes from a wide range of
organisms. Cloned 16S rRNA genes were sequenced by the Sanger
method, which requires two or three reads to cover the entire gene.
Accuracy is important because sequencing errors can lead to
misclassification. The cost and effort required for the Sanger
method limits the extent of sampling, and studies often produced
about 100 sequences per sample. This method identifies the dominant
microorganisms in a sample, but analysis of less abundant
microorganisms is limited.
[0015] Accordingly: methods and kits are desired that can (1)
reliably identify one or more microorganisms in a time-efficient
manner, and/or (2) rapidly sequence multiple regions within
microorganism genes (e.g., hypervariable regions of the genes) to
reliably identify one or more microorganisms that may be
present.
SUMMARY OF THE INVENTION
[0016] Various embodiments of the present disclosure relate to
methods and kits that can be used to characterize or identify one
or more microorganisms. In general, various embodiments of the
disclosure provide methods and kits that can be used to
characterize and/or identify one or more microorganisms in a
relatively short amount of time. The exemplary methods and kits can
be used to characterize one or more types of microorganisms, such
as bacteria, fungi, protozoa, and viruses and/or one or more
species of microorganisms within one or more types of
microorganisms. Exemplary methods and systems can evaluate a
plurality of microorganisms at the same time, in parallel, to
further reduce the amount of time associated with identification or
characterization of multiple microorganisms. Further, exemplary
methods and kits can be used to characterize or identify one or
more microorganisms without requiring a culture step. Because the
microorganisms can be characterized or identified in a short amount
of time, exemplary methods and kits described herein are suitable
for clinical applications, where rapid identification of the
microorganism(s) is desired. Further, results from use of exemplary
systems and kits can provide care givers with suggested treatments
and/or sensitivity and/or therapy resistance information relating
to various treatments for the characterized or identified
microorganism(s) in a manner that is easy to read and interpret. As
used herein "characterized" or "identified" microorganisms refers
to a genus or a species of the characterized or identified
microorganism(s) or the microorganism itself.
[0017] In accordance with exemplary embodiments of the disclosure,
a method of characterizing one or more microorganisms includes the
steps of (a) preparing an amplicon library with a polymerase chain
reaction (PCR) of nucleic acids; (b) sequencing a characteristic
gene sequence in the amplicon library to obtain a gene sequence;
and (c) characterizing the one or more microorganisms based on the
gene sequence using a computer-based genomic analysis of the gene
sequence. In accordance with various aspects of these embodiments,
the method further includes a step of extracting nucleic acids from
a biological sample of a subject. In accordance with additional
aspects, the method includes a step of purifying the amplicon
library from the PCR reaction. As noted above, the microorganisms
can include one or more of bacteria, fungi, protozoa, and viruses.
In the case of bacteria, a characteristic gene can be 16S ribosomal
RNA (16S rRNA). Exemplary techniques for sequencing a
characteristic gene include using an ion semiconductor sequencing
platform or a platform based on stepwise addition of reversible
terminator nucleotides. In accordance with various aspects of these
embodiments, the amplicon library is an ion amplicon library.
Various methods can be used to identify one or more microorganisms
and/or to characterize one or more microorganisms or DNA fragments
thereof based on, for example, a nearest known microorganism or DNA
fragment thereof.
[0018] Exemplary methods of the present disclosure may further
comprise the step of generating a report with microorganisms
characterized or identified and treatment (e.g., antibiotic,
antifungal, antiprotozoal, and/or antiviral) resistance and
susceptibility information for each identified genus and/or species
and/or microorganism. The method may also further comprise treating
the subject with a treatment identified in the report.
[0019] In certain aspects, the PCR reaction uses a forward primer
that comprises a target sequence. In the case of bacteria
characterization, the target sequence may include a sequence from
the 16S rRNA gene such as a hypervariable region selected from the
group consisting of V1, V2, V4, and V5.
[0020] In certain implementations, the biological sample is a urine
sample, a blood sample, a bronchioalveolar lavage, a nasal swab,
cerebrospinal fluid, synovial fluid, brain tissue, cardiac tissue,
bone, skin, a lymph node tissue or a dental tissue. In some
embodiments, the dental tissue is a tooth, a soft tissue, a joint
sample, or a dental sample.
[0021] In another implementation, the computer-based genomic
analysis comprises application of a procedural algorithm to
sequencing data. The procedural algorithm may exclude sequences
that are present less than five times or constitute less than 1% of
the sequencing data.
[0022] In accordance with additional exemplary embodiments of the
disclosure, a kit for characterizing at least one microorganism
includes (a) at least one forward primer comprising an adapter
sequence and a priming sequence, for a target sequence, wherein the
target sequence comprises a sequence from a characteristic gene
sequence; and (b) at least one reverse primer. If one or more
suspected microorganisms include bacteria, the target sequence can
be from the 16S rRNA gene and a hypervariable region selected from
the group consisting of V1, V2, V4, and V5. In certain aspects, the
reverse primer comprises a sequence selected from the group
consisting of SEQ ID NO: 33 and SEQ ID NO: 34.
[0023] In some implementations, the kit comprises a first forward
primer and a second forward primer, each of which can include a
barcode, a barcode adapter, and a target sequence. By way of
example, a target sequence of the first forward primer can include
a sequence beginning in V1 and extending towards V2 and the target
sequence of the second forward primer can include a sequence
beginning in V5 and extending towards V4.
[0024] Various additional embodiments of the present disclosure
relate to electronic systems and methods that can be used to
characterize or identify one or more microorganisms. For example, a
method of characterizing one or more microorganisms includes the
step of selecting, by a computer, a digital file comprising one or
more digital DNA sequences, wherein each of the one or more digital
DNA sequences corresponds to a microorganism to be characterized.
The computer segments each of the one or more digital DNA sequences
into one or more first portions, performs a set of alignments by
comparing the one or more first portions to information stored in a
first database, determines sequence portions from among the one or
more first portions that have an alignment match to the information
stored in the first database, performs a set of alignments by
comparing the one or more first portions or one or more second
portions to information stored in a second database, determines
sequence portions from among the one or more first portions or the
one or more second portions that have an alignment match to the
information stored in the second database, and characterizes one or
more microorganisms or DNA fragments thereof based on the alignment
match to the information stored in one or more of the first
database and the second database.
[0025] In accordance with various aspects of these embodiments, the
method can be used to characterize multiple microorganisms
simultaneously or in parallel, such that multiple microorganisms
can be identified in a relatively short amount of time--e.g.,
preferably in less than forty-eight or less than twenty-four
hours.
[0026] In accordance with further exemplary embodiments of the
disclosure, an article of manufacture including a non-transitory
computer readable medium having instructions stored thereon that,
in response to execution by a computing device, cause the computing
device to perform operations comprising the steps described in the
above paragraph.
[0027] In accordance with additional exemplary embodiments of the
disclosure, a system includes a computer to perform one or more
steps, such as the method steps noted above.
[0028] In accordance with further exemplary embodiments of the
disclosure, a method of automatically characterizing one or more
microorganisms can be performed using one or more databases.
Exemplary methods include the steps of detecting a sequence run
that generates a digital DNA sequence of one or more
microorganisms; selecting, by a computer, a digital file comprising
one or more digital DNA sequences, wherein each of the one or more
digital DNA sequences corresponds to a microorganism to be
characterized; segmenting, by the computer, each of the one or more
digital DNA sequences into one or more portions; performing, by the
computer, a set of alignments by comparing the one or more portions
to information stored in one or more databases; determining, by the
computer, sequence portions from among the one or more portions
that have an alignment match to the information stored in the one
or more databases; and characterizing one or more microorganism(s)
or DNA fragments thereof based on the alignment match. In
accordance with various aspects of these embodiments, the method
can be used to characterize multiple microorganisms simultaneously,
such that multiple microorganisms can be identified in a relatively
short amount of time--e.g., preferably in less than forty-eight or
less than twenty-four hours.
[0029] In accordance with yet additional exemplary embodiments of
the disclosure, an article of manufacture including a
non-transitory computer readable medium having instructions stored
thereon that, in response to execution by a computing device, cause
the computing device to perform operations comprising the steps
described in the above paragraph.
[0030] In accordance with yet additional exemplary embodiments, a
system for automatic computerized generation of microorganism
characterization information includes a computer configured to
perform the steps of the preceding paragraph.
BRIEF DESCRIPTION OF THE DRAWINGS
[0031] A more complete understanding of exemplary embodiments of
the present disclosure can be derived by referring to the detailed
description and claims when considered in connection with the
following illustrative figures.
[0032] FIG. 1 illustrates bidirectional sequencing using the fusion
method. Two primer pairs per target region generate two libraries
to enable bidirectional sequencing of the target region.
[0033] FIG. 2 illustrates fusion PCR primers for bidirectional
sequencing.
[0034] FIG. 3 illustrates example primers and amplicon design.
[0035] FIG. 4 illustrates results of a computer-based genomics
analysis of a patient sample with Prevotella spp. as the most
abundant microorganisms identified.
[0036] FIG. 5 illustrates results of a computer-based genomics
analysis of a patient sample with Capnocytophaga gingivalis as the
most abundant microorganisms identified.
[0037] FIG. 6 presents the results of a computer-based genomics
analysis of a patient sample with Actinomyces naeslundii as the
most abundant microorganisms identified.
[0038] FIG. 7A is a graph illustrating the length of sequencing
reads versus the percentage of accurate identifications of the
bacterium Ralstonia solanacearum in a control sample. FIG. 7B is a
bar graph illustrating that as the cutoff for the length of the
sequencing reads increases, the number of available reads at these
higher cutoffs decreases.
[0039] FIG. 8 is a bar graph of the cutoff lengths of sequencing
reads using the V1/2 and V5/4 oligonucleotides plotted against the
percentage of accurate genus identification with a control sample
containing Ralstonia solanacearum.
[0040] FIGS. 9A, 9B, 10A, and 10B depict line graphs demonstrating
that a consistent result is obtained when looking at the two
selected 16S rRNA regions of V1/2 and V5/4.
[0041] FIG. 11 presents the results of a computer-based genomics
analysis of a patient sample with Sphingomonas paucimobilis as the
most abundant microorganisms identified.
[0042] FIG. 12 illustrates a system in accordance with various
embodiments of the disclosure.
[0043] FIG. 13 illustrates a method in accordance with exemplary
embodiments of the disclosure.
[0044] FIG. 14 illustrates a method for automatic sequencing run
acquisition in accordance with further exemplary embodiments of the
disclosure.
[0045] FIG. 15 illustrates another method in accordance with
further exemplary embodiments of the disclosure.
[0046] FIGS. 16-17 illustrate examples of information output in an
exemplary report generated in accordance with exemplary embodiments
of the disclosure.
[0047] FIGS. 18-21 illustrate results of a computer-based genomics
analysis is accordance with further exemplary embodiments of the
disclosure.
[0048] It will be appreciated that elements in the figures are
illustrated for simplicity and clarity and have not necessarily
been drawn to scale. For example, the dimensions of some of the
elements in the figures may be exaggerated relative to other
elements to help to improve the understanding of illustrated
embodiments of the present disclosure.
DETAILED DESCRIPTION
[0049] The description of embodiments provided below is merely
exemplary and is intended for purposes of illustration only; the
following description is not intended to limit the scope of the
disclosure or the claims. Moreover, recitation of multiple
embodiments having stated features is not intended to exclude other
embodiments having additional features or other embodiments
incorporating different combinations of the stated features.
[0050] The following disclosure provides methods and kits for
characterizing one or more microorganisms. Various examples
disclosed herein provide methods and kits for characterizing one or
more microorganisms or DNA fragments thereof, such as for example,
pathogenic microorganisms in an efficient and timely manner, such
that the systems and methods are suitable for use in clinical
settings. Exemplary methods and kits can also provide treatment
and/or treatment sensitivity information related to the one or more
identified microorganism, such that a care provider can use such
information. In addition, exemplary methods and kits do not require
culturing samples.
[0051] As used herein, the verb "comprise" as is used in this
description and in the claims and its conjugations are used in its
non-limiting sense to mean that items following the word are
included, but items not specifically mentioned are not excluded. In
addition, reference to an element by the indefinite article "a" or
"an" does not exclude the possibility that more than one of the
elements are present, unless the context clearly requires that
there is one and only one of the elements. The indefinite article
"a" or "an" thus usually means "at least one."
[0052] As used herein, the term "subject" or "patient" refers to
any vertebrate including, without limitation, humans and other
primates (e.g., chimpanzees and other apes and monkey species),
farm animals (e.g., cattle, sheep, pigs, goats and horses),
domestic mammals (e.g., dogs and cats), laboratory animals (e.g.,
rodents such as mice, rats, and guinea pigs), and birds (e.g.,
domestic, wild and game birds such as chickens, turkeys and other
gallinaceous birds, ducks, geese, and the like). In some
embodiments, the subject is a mammal. In other embodiments, the
subject is a human.
[0053] As used herein, the term "biological sample" may include but
is not limited to urine, fluid or tissue samples such as blood
(e.g., whole blood, blood serum, etc.), bronchioalveolar lavage,
nasal swabs, cerebrospinal fluid, synovial fluid, brain and other
neurological tissues, cardiac tissue, bone, skin, lymph nodes,
dental tissue, and the like from a subject. The dental tissue may
be a tooth, a soft tissue, or dental pulp.
[0054] Unless denoted otherwise, whenever a oligonucleotide
sequence is represented, it will be understood that the nucleotides
are in 5' to 3' order from left to right and that "A" denotes
deoxyadenosine, "C" denotes deoxycytidine, "G" denotes
deoxyguanosine, "T" denotes thymidine, and "U" denotes
deoxyuridine. Oligonucleotides are said to have "5' ends" and "3'
ends" because mononucleotides are typically reacted to form
oligonucleotides via attachment of the 5' phosphate or equivalent
group of one nucleotide to the 3' hydroxyl or equivalent group of
its neighboring nucleotide, optionally via a phosphodiester or
other suitable linkage. Nucleotides may also be identified as
indicated as shown below in Table 1.
TABLE-US-00001 TABLE 1 List of Nucleotide Abbreviations Symbol
Meaning Origin of designation A A adenine G G guanine C C cytosine
T T thymine U U uracil R G or A purine Y T/U or C pyrimidine M A or
C amino K G or T/U keto S G or C strong interactions 3H-bonds W A
or T/U weak interactions 2H-bonds B G or C or T/U not a D A or G or
T/U not c H A or C or T/U not g V A or G or C not t, not u N A or G
or C or T/U, any unknown, or other
[0055] Various embodiments of the present disclosure provide
metagenomic testing methods that use direct DNA sequencing and
computational analysis to enable the detection, characterization or
identification, and in the case of novel or divergent organisms the
identification of the nearest characterized microorganism,
microorganism species, and/or microorganism genus of multiple
organisms at the same time. This stands in stark contrast to the
myriad of current indirect testing technologies, including
serology, T-cell stimulation assays, FISH, and ELISA. Furthermore,
exemplary methods can provide a relative measure of the
microorganism contribution and diversity within a given sample. In
these certain respects, the method may be called Pan-Microbial
Metagenomics as it aims to identify the genetic composition and
diversity across multiple microorganisms in a sample,
simultaneously.
[0056] Various exemplary methods can characterize, identify, and/or
survey the organisms of an unknown or polymicrobial infection. By
using direct DNA sequencing and computational analysis, these
methods allow for the characterization or identification of the
nearest relative to any detected bacteria in a given clinical
sample. Furthermore, the methods may also provide a relative
measure of the various microbial contribution and diversity within
a given sample in addition to presenting literature based treatment
suggestions. Adoption of the disclosed methods in clinical use will
have far reaching implications not only by providing superior,
unbiased, sequence based diagnosis, but also in reducing patient
mortality, morbidity, length of stay, and associated hospital and
healthcare costs. In accordance with some examples, ion
semiconductor sequencing platforms or similar techniques are
utilized to carry out the method because they enable an important
aspect of this diagnostic method: speed. In certain aspects, the
disclosed diagnostic method enables a turnaround time for results
from a patient sample of about 12 hours, about 24 hours, about 48
hours, or about 72 hours. This disclosed method may be performed as
a Laboratory Developed Test (LDT) in a Clinical Laboratory
Improvement Amendments (CLIA) regulated diagnostics laboratory.
[0057] In some implementations, the disclosure provides a system
consisting of seven main steps resulting in a CLIA compliant
diagnostic billable procedure. These steps include: [0058] 1. Point
of Care Sampling--Infected tissues and/or fluid samples may be
submitted for analysis. Proper collection techniques are used to
minimize contamination of the sample by non-targeted bacterial
populations. Blood draw sites are cleaned thoroughly with
disinfectants to remove bacterial and/or other microbial DNA and
cells, while tissue samples are collected using aseptic techniques.
The disclosed system is supported with industry standard collection
kits if required by the collection facility. [0059] 2. Rapid
Courier Service--Rapid sample transport to the laboratory is
desired to obtain an accurate snapshot of the microbial
communities. Extended transport or storage times may result in
drifts of the bacterial community that could lead to misleading or
distorted results. [0060] 3. DNA Extraction--Total DNA content is
purified appropriately from a wide range of tissue, fluid, bone and
sample types that are adequate for subsequent processing. [0061] 4.
Molecular Tagging and Amplification--Microbial type specific DNA
fragments are selectively amplified for distinct genomic regions
and tagged with patient specific molecular markers. These enriched
samples of DNA are pooled together in, for example, equimolar
amounts to allow even sequencing results across patients and
between the genomic regions of interest. [0062] 5. Next-Generation
DNA Sequencing--Millions of DNA reads are produced through the use
of semiconductor sequencing. The sequencing procedure is monitored
by a variety of methods to ensure optimal performance and
sequencing coverage for each sample. The sequences are sorted based
on the molecular tags allowing for consistent and easy
identification of the sample source. [0063] 6. Bioinformatics
Analysis--Software that automatically interfaces with the
sequencing software and analyzes the results with the selected
sequences, chemistry, and methods can be used with the disclosed
methods and system. Such software may utilize industry standard
formats and methods of analysis, thus providing reliable and
result-based methods. [0064] 7. Results Reporting--The software may
output the results into a variety of formats and automatically
backup intermediary work files documenting the analysis process.
Computational metrics may be presented to the analysis technician
for review and final report building. In addition to bacterial
findings, the disclosed system may provide literature based
treatment recommendations with the associated references.
[0065] In accordance with various embodiments of the disclosure, a
method of characterizing one or more microorganisms includes the
steps of preparing an amplicon library with a polymerase chain
reaction (PCR) of nucleic acids; sequencing a characteristic gene
sequence in the amplicon library to obtain a gene sequence; and
characterizing the one or more microorganisms based on the gene
sequence using a computer-based genomic analysis of the gene
sequence.
[0066] In certain aspects, the present disclosure is directed to a
test that combines three main components together to provide a
unique diagnostic capability that is currently unavailable in the
market and that specifically seeks to exploit the exceptional
sensitivity of the molecular based assays with a broad spectrum of
detection and identification. The three main components are Sample
and Library Preparation, DNA Sequencing, and Computer-Based Genomic
Analysis.
[0067] Accordingly, in one aspect the method of the present
disclosure comprises: Sample and Library Preparation, DNA
Sequencing, and Computer-Based Genomic Analysis. In one embodiment,
the Sample and Library Preparation consists of five steps:
1. DNA Extraction
2. Amplification and Barcoding
3. DNA Purification
4. IonSphere Particle Labeling
5. IonSphere Particle Enrichment
[0068] However, each of the five steps is not required to practice
all embodiments of the disclosure.
[0069] DNA extraction may be accomplished by any method available
in the art. Nucleic acids can be extracted from a biological sample
by a variety of techniques such as those described by Maniatis et
al., Molecular Cloning: A Laboratory Manual, Cold Spring Harbor,
N.Y., pp. 280-281, (1982), the contents of which is incorporated by
reference herein in its entirety. In one embodiment, DNA is
extracted from the biological sample with the QIAamp.RTM. DNA Mini
Kit.
[0070] Sample and Library Preparation may also involve the running
of a polymerase chain reaction (PCR). PCR is a technique in
molecular biology to amplify a single or few copies of a piece of
DNA across several orders of magnitude, generating thousands to
millions of copies of a particular DNA sequence. The method relies
on thermal cycling, consisting of cycles of repeated heating and
cooling of the reaction for DNA melting and enzymatic replication
of the DNA. Primers (short DNA fragments) containing sequences
complementary to the target region along with a DNA polymerase
(after which the method is named) are components to enable
selective and repeated amplification. As PCR progresses, the DNA
generated is itself used as a template for replication, setting in
motion a chain reaction in which the DNA template is exponentially
amplified. PCR can be extensively modified to perform a wide array
of genetic manipulations.
[0071] Most PCR applications employ a heat-stable DNA polymerase,
such as Taq polymerase, an enzyme originally isolated from the
bacterium Thermus aquaticus. This DNA polymerase enzymatically
assembles a new DNA strand from DNA building blocks, the
nucleotides, by using single-stranded DNA as a template and DNA
oligonucleotides (also called DNA primers), which are used for
initiation of DNA synthesis. The vast majority of PCR methods use
thermal cycling, i.e., alternately heating and cooling the PCR
sample to a defined series of temperature steps. These thermal
cycling steps are necessary first to physically separate the two
strands in a DNA double helix at a high temperature in a process
called DNA melting. At a lower temperature, each strand is then
used as the template in DNA synthesis by the DNA polymerase to
selectively amplify the target DNA. The selectivity of PCR results
from the use of primers that are complementary to the DNA region
targeted for amplification under specific thermal cycling
conditions. In one embodiment, the present disclosure contemplates
a method comprising amplifying a plurality of a complex mixture
("library") of DNA molecules by PCR.
[0072] PCR is used to amplify a specific region of a DNA strand
(the DNA target) Most PCR methods typically amplify DNA fragments
of up to .about.10 kilo base pairs (kb), although some techniques
allow for amplification of fragments up to 40 kb in size. A basic
PCR set up usually involves several components and reagents. These
components may include, but are not limited to: i) DNA template
that contains the DNA region (target) to be amplified; ii) two
primers that are complementary to the 3' ends of each of the sense
and anti-sense strand of the DNA target; iii) Taq polymerase or
another DNA polymerase with a temperature optimum at around
70.degree. C.; iv) deoxynucleoside triphosphates (dNTPs; also very
commonly and erroneously called deoxynucleotide triphosphates), the
building blocks from which the DNA polymerases synthesizes a new
DNA strand; v) buffer solution, providing a suitable chemical
environment for optimum activity and stability of the DNA
polymerase; vi) divalent cations, magnesium or manganese ions;
generally Mg.sup.2+ is used, but Mn.sup.2+ can be utilized for
PCR-mediated DNA mutagenesis, as higher Mn.sup.2+ concentration may
increase the error rate during DNA synthesis; and vii) monovalent
cation potassium ions.
[0073] The PCR is commonly carried out in a reaction volume of
10-200 .mu.l in small reaction tubes (0.2-0.5 ml volumes) in a
thermal cycler. The thermal cycler heats and cools the reaction
tubes to achieve the temperatures at each step of the reaction.
Many modern thermal cyclers make use of the Peltier effect which
permits both heating and cooling of the block holding the PCR tubes
simply by reversing the electric current. Thin-walled reaction
tubes permit favorable thermal conductivity to allow for rapid
thermal equilibration. Most thermal cyclers have heated lids to
prevent condensation at the top of the reaction tube, but a layer
of oil or a ball of wax may also be effective.
[0074] In some embodiments, the method of the present disclosure
comprises preparing an ion amplicon library. This may be
accomplished with the fusion PCR method using fusion primers to
attach the Ion A and truncated P1 (trP1) Adapters to the amplicons
as they are generated in PCR (see FIG. 1). The fusion primers
contain the A and trP1 sequences at their 5'-ends adjacent to the
target-specific portions of the primers (see FIG. 2). The target
region is the portion of the genome that will be sequenced in the
samples of interest. For example the target region could be an
exon, a portion of an exon, or a non-coding region of the genome.
Primers are designed so that any sequence variants of interest are
located between the primers and so those variants are not masked by
the template-specific part of the primer sequences (see FIG. 3).
The length of the target region is also carefully considered. In
one example, bidirectional sequencing is used. In another example,
sequencing proceeds in a single direction.
[0075] For bidirectional sequencing, the fusion PCR method for
preparing an amplicon library generally uses four fusion primers:
two pairs of forward and reverse primers per target region. If
sequencing proceeds in a single direction, only one pair of forward
and reverse primers per target may be used. The amplicons are
designed so that their length, including the fusion primers with
adapter sequences, is shorter than the median library size for the
target read length of the library (see Table 2).
TABLE-US-00002 TABLE 2 Design of Amplicon Length Target Read Length
Median Library Size 200 bases (200 base-read library) ~330 bp 100
bases (100 base-read library) ~200 bp
[0076] One fusion primer pair has the A adapter region followed by
the proximal end of the target sequence, and the other has the trP1
adapter region followed by the distal end of the target sequence.
The other fusion primer pair has the adapter sequences A and trP1
swapped. The target-specific portion of each primer should include
15-20 nucleotides of the target region.
[0077] In some embodiments, the fusion primer contains a "barcode."
The term "barcode" as used herein, refers to any unique,
non-naturally occurring, nucleic acid sequence that may be used to
identify the originating genome of a nucleic acid fragment. Such
barcodes may be sequences including but not limited to: CTAAGGTAAC
(SEQ ID NO: 1), TAAGGAGAAC (SEQ ID NO: 2), AAGAGGATTC (SEQ ID NO:
3), TACCAAGATC (SEQ ID NO: 4), CAGAAGGAAC (SEQ ID NO: 5),
CTGCAAGTTC (SEQ ID NO: 6), TTCGTGATTC (SEQ ID NO: 7), TTCCGATAAC
(SEQ ID NO: 8), TGAGCGGAAC (SEQ ID NO: 9), CTGACCGAAC (SEQ ID NO:
10), TCCTCGAATC (SEQ ID NO: 11), TAGGTGGTTC (SEQ ID NO: 12),
TCTAACGGAC (SEQ ID NO: 13), TTGGAGTGTC (SEQ ID NO: 14), TCTAGAGGTC
(SEQ ID NO: 15), or TCTGGATGAC (SEQ ID NO: 16). Barcodes may,
optionally, be followed by a barcode adapter, for example, GAT (SEQ
ID NO: 17). While exemplary barcodes are listed, any barcode of an
appropriate length containing an arbitrary DNA sequence may be used
with the method of the present disclosure. An appropriate length
for the barcode may be about 5 nucleotides, about 6 nucleotides,
about 7 nucleotides, about 8 nucleotides, about 9 nucleotides,
about 10 nucleotides, about 15 nucleotides or about 20
nucleotides.
[0078] In accordance with various aspects of the present
disclosure, the target sequence is a segment from the 16S rRNA gene
of a microorganism. In some implementations, the target sequence
may comprise one or more hypervariable regions from the 16S rRNA
gene selected from V1, V2, V3, V4, V5, V6, V7, V8, and V9. For
example, the target sequence comprises a sequence from any one of
V1, V2, V4, and V5. In another implementation, the target sequence
may comprise a sequence beginning in V1 and extending towards V2, a
sequence beginning in V2 and extending towards V1, a sequence
beginning in V4 and extending towards V5, or a sequence beginning
in V5 and extending towards V4. The target sequence may be anywhere
from about 5 nucleotides in length to about 40 nucleotides in
length, from about 10 nucleotides in length to about 30 nucleotides
in length, from about 15 nucleotides in length to about 25
nucleotides in length, etc. In some implementations, the target
sequence is about 5 nucleotides in length, about 10 nucleotides in
length, about 15 nucleotides in length, about 20 nucleotides in
length, about 25 nucleotides in length, about 30 nucleotides in
length, about 35 nucleotides in length, or about 40 nucleotides in
length. Non-limiting examples of 16S rRNA target sequences that may
be used in the fusion primers are listed in Table 3.
TABLE-US-00003 TABLE 3 16S rRNA Target Sequences for Fusion Primers
Primer Name Sequence (5'-3') SEQ ID NO: V1/2 AGAGTTTGATCCTGGCTCAG
SEQ ID NO: 18 V5/4 CCGTCAATTYYTTTRAGTTT SEQ ID NO: 19 U1492R
GGTTACCTTGTTACGACTT SEQ ID NO: 20 928F TAAAACTYAAAKGAATTGACGGG SEQ
ID NO: 21 336R ACTGCTGCSYCCCGTAGGAGTCT SEQ ID NO: 22 1100F
YAACGAGCGCAACCC SEQ ID NO: 23 1100R GGGTTGCGCTCGTTG SEQ ID NO: 24
337F GACTCCTACGGGAGGCWGCAG SEQ ID NO: 25 907R CCGTCAATTCCTTTRAGTTT
SEQ ID NO: 26 785F GGATTAGATACCCTGGTA SEQ ID NO: 27 805R
GACTACCAGGGTATCTAATC SEQ ID NO: 28 533F GTGCCAGCMGCCGCGGTAA SEQ ID
NO: 29 518R GTATTACCGCGGCTGCTGG SEQ ID NO: 30
[0079] In another aspect of the present disclosure, the target
sequence is a segment of an antibiotic resistance gene.
Non-limiting examples of such antibiotic resistance genes include
bla.sub.tem, bla.sub.shv, bla.sub.rob, bla.sub.oxa, blaZ, aadB,
aacC1, aacC2, aacC3, aac6'-IIa, aacA4, aad(6'), vanA, vanB, vanC,
msrA, sarA, aac(6') aph(2''), vat, vga, ermA, ermB, ermC, mecA,
int, sul, mecA, aac2ia, aac2ib, aac2ic, aac2id, aac2i, aac3ia,
aac3iia, aac3iib, aac3iii, aac3iv, aac3ix, aac3vi, aac3viii,
aac3vii, aac3x, aac6i, aac6ia, aac6ib, aac6ic, aac6ie, aac6 if,
aac6ig, aac6iia, aac6iib, aad9, aad9ib, aadd, acra, acrb, adea,
adeb, adec, amra, amrb, ant2ia, ant2ib, ant3ia, ant4iia, ant6ia,
aph33ia, aph33ib, aph3ia, aph3ib, aph3ic, aph3iiia, aph3iva,
aph3va, aph3vb, aph3via, aph3viia, aph4ib, aph6ia, aph6ib, aph6ic,
aph6id, arna, baca, bcra, bcrc, bl1_acc, bl1_ampc, bl1_asba,
bl1_ceps, bl1_cmy2, bl1_ec, bl1_fox, bl1_mox, bl1_och, bl1_pao,
bl1_pse, bl1_sm, bl2a.sub.--1, bl2a_exo, bl2a_iii2, bl2a_iii,
bl2a_kcc, bl2a_nps, bl2a_okp, bl2a_pc, bl2be_ctxm, bl2be_oxyl,
bl2be_per, bl2be_shv2, bl2b_rob, bl2b_tem1, bl2b_tem2, bl2b_tem,
bl2b_tle, bl2b_ula, bl2c_bro, bl2c_pse1, bl2c_pse3, bl2d_lcr1,
bl2d_moxa, bl2d_oxa10, bl2d_oxa1, bl2d_oxa2, bl2d_oxa5, bl2d_oxa9,
bl2d_r39, bl2e_cbla, bl2e_cepa, bl2e_cfxa, bl2e_fpm, bl2e_y56,
bl2f_nmca, bl2f_sme1, bl2_ges, bl2_kpc, bl2_len, bl2_veb, bl3_ccra,
bl3_cit, bl3_cpha, bl3_gim, bl3_imp, bl3.sub.--1, bl3_shw, bl3_sim,
bl3_vim, ble, blt, bmr, cara, cata10, cata11, cata12, cata13,
cata14, cata15, cata16, cata1, cata2, cata3, cata4, cata5, cata6,
cata7, cata8, cata9, catb1, catb2, catb3, catb4, catb5, ceoa, ceob,
cml_e1, cml_e2, cml_e3, cml_e4, cml_e5, cml_e6, cml_e7, cml_e8,
dfra10, dfra12, dfra13, dfra14, dfra15, dfra16, dfra17, dfra19,
dfra1, dfra20, dfra21, dfra22, dfra23, dfra24, dfra25, dfra25,
dfra25, dfra26, dfra5, dfra7, dfrb1, dfrb2, dfrb3, dfrb6, emea,
emrd, emre, erea, ereb, erma, ermb, ermc, ermd, erme, ermf, ermg,
ermh, ermn, ermo, ermq, ermr, erms, ermt, ermu, ermv, ermw, ermx,
ermy, fosa, fosb, fosc, fosx, fusb, fush, ksga, lmra, lmrb, lnua,
lnub, lsa, maca, macb, mdte, mdtf, mdtg, mdth, mdtk, mdtl, mdtm,
mdtn, mdto, mdtp, meca, mecrl, mefa, mepa, mexa, mexb, mexc, mexd,
mexe, mexf, mexh, mexi, mexw, mexx, mexy, mfpa, mpha, mphb, mphc,
msra, norm, oleb, opcm, opra, oprd, oprj, oprm, oprn, otra, otrb,
pbpla, pbplb, pbp2b, pbp2, pbp2x, pmra, qac, qaca, qacb, qnra,
qnrb, qnrs, rosa, rosb, smea, smeb, smec, smed, smee, smef, srmb,
sta, str, sul1, sul2, sul3, tcma, tcr3, tet30, tet31, tet32, tet33,
tet34, tet36, tet37, tet38, tet39, tet40, teta, tetb, tetc, tetd,
tete, tetg, teth, tetj, tetk, tetl, tetm, teto, tetpa, tetpb, tet,
tetq, tets, tett, tetu, tetv, tetw, text, tety, tetz, tlrc, tmrb,
tolc, tsnr, vana, vanb, vanc, vand, vane, yang, vanha, vanhb,
vanhd, vanra, vanrb, vanrc, vanrd, vanre, vanrg, vansa, vansb,
vansc, vansd, vanse, vansg, vant, vante, vantg, vanug, vanwb,
vanwg, vanxa, vanxb, vanxd, vanxyc, vanxye, vanxyg, vanya, vanyb,
vanyd, vanyg, vanz, vata, vatb, vatc, vatd, vate, vgaa, vgab, vgba,
vgbb, vph, ykkc, and ykkd (see the Antibiotic Resistance Genes
Database (ARDB) available online).
[0080] When barcodes are incorporated into PCR primers for
bidirectional sequencing, the primers may comprise the following
sequences:
Forward Primer #1:
[0081] 5'-CCATCTCATCCCTGCGTGTCTCCGACTCAG-3' (SEQ ID NO: 31)
followed by a barcode, a barcode adapter, and a stretch of about 20
nucleotides from the target sequence;
Reverse Primer #1:
[0082] 5'-CCATCTCATCCCTGCGTGTCTCCGACTCAG-3' (SEQ ID NO: 31)
followed by a barcode, a barcode adapter, and a stretch of about 20
nucleotides from the target sequence;
Forward Primer #2:
[0083] 5'-CCTCTCTATGGGCAGTCGGTGAT-3' (SEQ ID NO: 32) followed by a
stretch of about 20 nucleotides from the target sequence;
Reverse Primer #2:
[0084] 5'-CCTCTCTATGGGCAGTCGGTGAT-3' (SEQ ID NO: 32) followed by a
stretch of about 20 nucleotides from the target sequence.
[0085] In some aspects of the present disclosure, sequencing
proceeds in one direction and the reverse primers do not include a
barcode sequence or a barcode adapter.
[0086] The forward and reverse primers may comprise SEQ ID NO: 31
or SEQ ID NO: 32 and a stretch of about 5 nucleotides, about 10
nucleotides, about 15 nucleotides, about 20 nucleotides, about 25
nucleotides, or about 30 nucleotides from the target sequence.
[0087] In certain embodiments, the reverse primer comprises a
sequence selected from CCTCTCTATGGGCAGTCGGTGATCTGCTGCCTYCCGTA (SEQ
ID NO: 33) and CCTCTCTATGGGCAGTCGGTGATAYTGGGYDTAAAGNG (SEQ ID NO:
34).
[0088] In certain embodiments, the method of the present disclosure
comprises sequencing 16S ribosomal RNA (16S rRNA) or other sequence
with an ion semiconductor sequencing platform. The term "ion
semiconductor sequencing platform" refers to any device and/or
method that detects the production of hydrogen ions during a
chemical condensation reaction. The device and/or method
quantitates the production of hydrogen ions by changes in the pH of
a mixture and/or solution. For example, nucleic acids may be
sequenced by measuring pH fluctuations in a mixture during
amplification of a nucleic acid sequence.
[0089] There are several probes or primers that may be used in
accordance with the present disclosure. These probes/primers can
take on a variety of configurations and may have a variety of
structural components described in more detail below. The first
step probe may be an allele specific probe or locus specific probe.
"Allele specific" probe or primer refers to a probe or primer that
hybridizes to a target sequence and discriminates between alleles
or hybridizes to a target sequence and is modified in an allele
specific manner. "Locus specific" probe or primer refers to a probe
or primer that hybridizes to a target sequence in a locus specific
manner, but does not necessarily discriminate between alleles. A
locus specific primer also may be modified, i.e., extended as
described below, such that it includes information about a
particular allele, but the locus specific primer does not
discriminate between alleles.
[0090] In many embodiments, the probes or primers comprise one or
more universal priming site(s) and/or adapters, both of which are
described below.
[0091] A size of the primer and probe nucleic acid may vary with
each portion of the probe and the total length of the probe in
general varying from 5 to 500 nucleotides in length. Each portion
can be between 10 and 100, between 15 and 50, or 10 to 35,
depending on the use and amplification technique. Thus, for
example, the universal priming site(s) of the probes can each be
about 15-20 nucleotides in length, or 18 nucleotides. The adapter
sequences of the probes can be from 15-25 nucleotides in length, or
about 20 nucleotides. The target specific portion of the probe can
be from 15-50 nucleotides in length. In addition, the primer may
include an additional amplification priming site.
[0092] In accordance with some examples of the disclosure, the
allele or locus specific probe or probes comprise a target domain
substantially complementary to a first domain of the target
sequence. In general, probes of the present disclosure are designed
to be complementary to a target sequence (either the target
sequence of the sample or to other probe sequences, as is described
herein), such that hybridization of the target and the probes of
the present disclosure occurs. This complementarity need not be
perfect; there may be any number of base pair mismatches that will
interfere with hybridization between the target sequence and the
single stranded nucleic acids of the present disclosure. However,
if the number of mutations is so great that no hybridization can
occur under even the least stringent of hybridization conditions,
the sequence is not a complementary target sequence. Thus,
"substantially complementary" as used herein means that the probes
are sufficiently complementary to the target sequences to hybridize
under the selected reaction conditions.
[0093] In one embodiment the target specific portion includes a
combinatorial mixture of each nucleotide at each position. In
addition the primer includes a universal priming sequence and an
allele specific position. The universal priming sequence can be
specific for the particular nucleotide at the allele specific
position. That is, the locus-specific allele selectivity portions
of the primer can be replaced with a universal targeting domain
that includes a region where each position is represented by a
combinatorial mixture of nucleotides. One of the positions in the
universal region (not necessarily the 3' position) is paired with
the genomic region to be analyzed.
[0094] In another example, one of the probes further comprises an
adapter sequence, (sometimes referred to in the art as "zip codes"
or "bar codes"). Adapters facilitate immobilization of probes to
allow the use of "universal arrays." That is, arrays (either solid
phase or liquid phase arrays) are generated that contain capture
probes that are not target specific, but rather specific to
individual (preferably) artificial adapter sequences.
[0095] Thus, an "adapter sequence" is a nucleic acid that is
generally not native to the target sequence, i.e. is exogenous, but
is added or attached to the target sequence. It should be noted
that in this context, the "target sequence" can include the primary
sample target sequence, or can be a derivative target such as a
reactant or product of the reactions outlined herein; thus for
example, the target sequence can be a PCR product, a first ligation
probe or a ligated probe in an OLA reaction, etc. The terms
"barcodes," "adapters," "addresses," "tags," and "zip codes" have
all been used to describe artificial sequences that are added to
amplicons to allow separation of nucleic acid fragment pools. One
exemplary form of adapters is hybridization adapters, which can be
chosen so as to allow hybridization to the complementary capture
probes on a surface of an array. Adapters serve as unique
identifiers of the probe and thus of the target sequence. In
general, sets of adapters and the corresponding capture probes on
arrays are developed to minimize cross-hybridization with both each
other and other components of the reaction mixtures, including the
target sequences and sequences on the larger nucleic acid sequences
outside of the target sequences (e.g. to sequences within genomic
DNA). Other forms of adapters are mass tags that can be separated
using mass spectroscopy, electrophoretic tags that can be separated
based on electrophoretic mobility, etc. Some adapter sequences are
outlined in U.S. Ser. No. 09/940,185, filed Aug. 27, 2001, hereby
incorporated by reference in its entirety to the extent the
contents thereof do not conflict with the present disclosure.
Exemplary adapters are those that meet the following criteria. They
are not found in a genome, preferably a human or microbial genome,
and they do not have undesirable structures, such as hairpin
loops.
[0096] As will be appreciated by those in the art, the attachment,
or joining, of the adapter sequence to the target sequence can be
done in a variety of ways. In one embodiment, the adapter sequences
are added to the primers of the reaction (extension primers,
amplification primers, readout probes, genotyping primers, Rolling
Circle primers, etc.) during the chemical synthesis of the primers.
The adapter then gets added to the reaction product during the
reaction; for example, the primer gets extended using a polymerase
to form the new target sequence that now contains an adapter
sequence. Alternatively, the adapter sequences can be added
enzymatically. Furthermore, the adapter can be attached to the
target after synthesis; this post-synthesis attachment can be
either covalent or non-covalent. In another embodiment the adapter
is added to the target sequence or associated with a particular
allele during an enzymatic step. That is, to achieve the level of
specificity necessary for highly multiplexed reactions, the product
of the specificity or allele specific reaction preferably also
includes at least one adapter sequence.
[0097] One or more of the specificity primers can include a first
portion comprising the adapter sequence and a second portion
comprising the priming sequence. Extending the amplification primer
results in target sequences that comprise the adapter sequences.
The adapter sequences are designed to be substantially
complementary to capture probes.
[0098] In addition, the adapter can be attached either on the 3' or
5' ends, or in an internal position, depending on the configuration
of the system.
[0099] In accordance with one example, the use of adapter sequences
allows the creation of more "universal" surfaces; that is, one
standard array, comprising a finite set of capture probes can be
made and used in any application. The end-user can customize the
array by designing different soluble target probes, which, as will
be appreciated by those in the art, is generally simpler and less
costly. In an exemplary embodiment, an array of different and
usually artificial capture probes are made; that is, the capture
probes do not have to be complementarity to known target sequences.
The adapter sequences can then be incorporated in the target
probes.
[0100] As can be appreciated, the length of the adapter sequences
will vary, depending on the desired "strength" of binding and the
number of different adapters desired. In accordance with various
examples, an adapter sequences range from about 6 to about 500
basepairs in length, or 8 to about 100 basepairs, or about 10 to
about 25 basepairs.
[0101] In one example, the adapter sequence uniquely identifies the
target analyte to which the target probe binds. That is, while the
adapter sequence need not bind itself to the target analyte, the
system allows for identification of the target analyte by detecting
the presence of the adapter. Accordingly, following a binding or
hybridization assay and washing, the probes including the adapters
are amplified. Detection of the adapter then serves as an
indication of the presence of the target analyte.
[0102] In one embodiment, the adapter includes both an identifier
region and a region that is complementary to capture probes on a
universal array as described above. In this embodiment, the
amplicon hybridizes to capture probes on a universal array.
Detection of the adapter can be accomplished following
hybridization with a probe that is complementary to the adapter
sequence. The probe can be labeled as described herein.
[0103] In general, unique adapter sequences are used for each
unique target analyte. That is, the elucidation or detection of a
particular adapter sequence allows the identification of the target
analyte to which the target probe containing that adapter sequence
bound. However, in some cases, it is possible to "reuse" adapter
sequences and have more than one target analyte share an adapter
sequence.
[0104] The adapters can contain different sequences or properties
that are indicative of a particular target molecule. That is, each
adapter can uniquely identify a target sequence. As described
above, the adapters can be amplified to form amplicons. The adapter
is detected as an indication of the presence of the target analyte,
i.e. the particular target nucleic acid. The use of adapters in
combination with amplification following a specific binding event
allows for highly multiplexed reactions to be performed.
[0105] Also, the probes are constructed so as to contain the
desired priming site or sites for the subsequent amplification
scheme. For example, the priming sites can be universal priming
sites. By "universal priming site" or "universal priming sequences"
herein is meant a sequence of the probe that will bind a primer for
amplification.
[0106] By way of example, when amplification methods requiring two
primers such as PCR are used, each probe can comprise an upstream
universal priming site (UUP) and a downstream universal priming
site (DUP). Again, "upstream" and "downstream" are not meant to
convey a particular 5'-3', orientation, and will depend on the
orientation of the system. Only a single UUP sequence and a single
DUP sequence can be used in a probe set, although different assays
or different multiplexing analysis may utilize a plurality of
universal priming sequences. In some embodiments, probe sets may
comprise different universal priming sequences. In addition, the
universal priming sites are preferably located at the 5' and 3'
termini of the target probe (or the ligated probe), as only
sequences flanked by priming sequences will be amplified.
[0107] In addition, universal priming sequences are generally
chosen to be as unique as possible given the particular assays and
host genomes to ensure specificity of the assay. However, as will
be appreciated, sets of priming sequences/primers may be used.
[0108] When two priming sequences are used, the orientation of the
two priming sites can be generally different. That is, one PCR
primer will directly hybridize to the first priming site, while the
other PCR primer will hybridize to the complement of the second
priming site. Stated differently, the first priming site is in
sense orientation, and the second priming site is in antisense
orientation.
[0109] In general, highly multiplexed reactions can be performed,
with all of the universal priming sites being the same for all
reactions. Alternatively, "sets" of universal priming sites and
corresponding probes can be used, either simultaneously or
sequentially. The universal priming sites are used to amplify the
modified probes to form a plurality of amplicons that are then
detected in a variety of ways, as outlined herein.
[0110] Accordingly, various examples of the present disclosure
provide first target probe sets. By "probe set" herein is meant a
plurality of target probes that are used in a particular
multiplexed assay. First target probe sets can each comprise at
least a first universal priming site.
[0111] The target probe may also comprise a label sequence, i.e. a
sequence that can be used to bind label probes and is substantially
complementary to a label probe. Such system is sometimes referred
to in the art as "sandwich-type" assays. That is, by incorporating
a label sequence into the target probe, which is then amplified and
present in the amplicons, a label probe comprising primary (or
secondary) detection labels can be added to the mixture, either
before addition to the array or after. This allows the use of high
concentrations of label probes for efficient hybridization. It is
possible to use the same label sequence and label probe for all
target probes on an array; alternatively, different target probes
can have a different label sequence. Similarly, the use of
different label sequences can facilitate quality control; for
example, one label sequence (and one color) can be used for one
strand of the target, and a different label sequence (with a
different color) for the other; and in this case only if both
colors are present at the same basic level is a positive
called.
[0112] Thus, the present disclosure provides target probes that
comprise any, all or any combination of universal priming
sequences, bioactive agents (e.g. target specific portion(s)),
adapter sequence(s), optionally an additional amplification priming
sequence and optionally label sequences. These target probes can
then added to the target sequences to form hybridization complexes.
When nucleic acids are the target, the hybridization complexes can
contain portions that are double stranded (the target-specific
sequences of the target probes hybridized to a portion of the
target sequence) and portions that are single stranded (the ends of
the target probes comprising the universal priming sequences and
the adapter sequences, and any unhybridized portion of the target
sequence).
[0113] In some embodiments, the purified DNA from the sample is
analyzed by Sequencing by Synthesis (SBS) techniques. SBS
techniques generally involve the enzymatic extension of a nascent
nucleic acid strand through the iterative addition of nucleotides
against a template strand. In traditional methods of SBS, a single
nucleotide monomer may be provided to a target nucleotide in the
presence of a polymerase in each delivery. However, in some of the
methods described herein, more than one type of nucleotide monomer
can be provided to a target nucleic acid in the presence of a
polymerase in a delivery.
[0114] SBS can utilize nucleotide monomers that have a terminator
moiety or those that lack any terminator moieties. Methods
utilizing nucleotide monomers lacking terminators include, for
example, pyrosequencing and sequencing using
.gamma.-phosphate-labeled nucleotides. In methods using nucleotide
monomers lacking terminators, the number of different nucleotides
added in each cycle can be dependent upon the template sequence and
the mode of nucleotide delivery. For SBS techniques that utilize
nucleotide monomers having a terminator moiety, the terminator can
be effectively irreversible under the sequencing conditions used as
is the case for traditional Sanger sequencing which utilizes
dideoxynucleotides, or the terminator can be reversible as is the
case for sequencing methods developed by Solexa (now Illumina,
Inc.). In some methods a terminator moiety can be reversibly
terminating.
[0115] SBS techniques can utilize nucleotide monomers that have a
label moiety or those that lack a label moiety. Accordingly,
incorporation events can be detected based on a characteristic of
the label, such as fluorescence of the label; a characteristic of
the nucleotide monomer such as molecular weight or charge; a
byproduct of incorporation of the nucleotide, such as release of
pyrophosphate; or the like. In embodiments, where two or more
different nucleotides are present in a sequencing reagent, the
different nucleotides can be distinguishable from each other, or
alternatively, the two or more different labels can be the
indistinguishable under the detection techniques being used. For
example, the different nucleotides present in a sequencing reagent
can have different labels and they can be distinguished using
appropriate optics as exemplified by the sequencing methods
developed by Solexa (now Illumina, Inc.). However, it is also
possible to use the same label for the two or more different
nucleotides present in a sequencing reagent or to use detection
optics that do not necessarily distinguish the different labels.
Thus, in a doublet sequencing reagent having a mixture of A/C both
the A and C can be labeled with the same fluorophore. Furthermore,
when doublet delivery methods are used all of the different
nucleotide monomers can have the same label or different labels can
be used, for example, to distinguish one mixture of different
nucleotide monomers from a second mixture of nucleotide monomers.
For example, using the [First delivery nucleotide monomers]+[Second
delivery nucleotide monomers] nomenclature set forth above and
taking an example of A/C+(1/T), the A and C monomers can have the
same first label and the G and T monomers can have the same second
label, wherein the first label is different from the second label.
Alternatively, the first label can be the same as the second label
and incorporation events of the first delivery can be distinguished
from incorporation events of the second delivery based on the
temporal separation of cycles in an SBS protocol. Accordingly, a
low resolution sequence representation obtained from such mixtures
will be degenerate for two pairs of nucleotides (T/G, which is
complementary to A and C, respectively; and C/A which is
complementary to G/T, respectively).
[0116] Some embodiments include pyrosequencing techniques.
Pyrosequencing detects the release of inorganic pyrophosphate (PPi)
as particular nucleotides are incorporated into the nascent strand
(Ronaghi, M., Karamohamed, S., Pettersson, B., Uhlen, M. and Nyren,
P. (1996) "Real-time DNA sequencing using detection of
pyrophosphate release." Analytical Biochemistry 242(1), 84-9;
Ronaghi, M. (2001) "Pyrosequencing sheds light on DNA sequencing."
Genome Res. 11(1), 3-11; Ronaghi, M., Uhlen, M. and Nyren, P.
(1998) "A sequencing method based on real-time pyrophosphate."
Science 281(5375), 363; U.S. Pat. No. 6,210,891; U.S. Pat. No.
6,258,568 and U.S. Pat. No. 6,274,320, the disclosures of which are
incorporated herein by reference in their entireties). In
pyrosequencing, released PPi can be detected by being immediately
converted to adenosine triphosphate (ATP) by ATP sulfurylase, and
the level of ATP generated is detected via luciferase-produced
photons.
[0117] In another example type of SBS, cycle sequencing is
accomplished by stepwise addition of reversible terminator
nucleotides containing, for example, a cleavable or photobleachable
dye label as described, for example, in U.S. Pat. No. 7,427,67,
U.S. Pat. No. 7,414,1163 and U.S. Pat. No. 7,057,026, the
disclosures of which are incorporated herein by reference. This
approach is being commercialized by Solexa (now Illumina Inc.), and
is also described in WO 91/06678 and WO 07/123,744 (filed in the
United States patent and trademark Office as U.S. Ser. No.
12/295,337), each of which is incorporated herein by reference in
their entireties. The availability of fluorescently-labeled
terminators in which both the termination can be reversed and the
fluorescent label cleaved facilitates efficient cyclic reversible
termination (CRT) sequencing. Polymerases can also be co-engineered
to efficiently incorporate and extend from these modified
nucleotides.
[0118] In other embodiments, Ion Semiconductor Sequencing is
utilized to analyze the purified DNA from the sample. Ion
Semiconductor Sequencing is a method of DNA sequencing based on the
detection of hydrogen ions that are released during DNA
amplification. This is a method of "sequencing by synthesis,"
during which a complementary strand is built is based on the
sequence of a template strand.
[0119] For example, a microwell containing a template DNA strand to
be sequenced can be flooded with a single species of
deoxyribonucleotide (dNTP). If the introduced dNTP is complementary
to the leading template nucleotide it is incorporated into the
growing complementary strand. This causes the release of a hydrogen
ion that triggers a hypersensitive ion sensor, which indicates that
a reaction has occurred. If homopolymer repeats are present in the
template sequence multiple dNTP molecules will be incorporated in a
single cycle. This leads to a corresponding number of released
hydrogens and a proportionally higher electronic signal.
[0120] This technology differs from other sequencing technologies
in that no modified nucleotides or optics are used. Ion
semiconductor sequencing may also be referred to as ion torrent
sequencing, pH-mediated sequencing, silicon sequencing, or
semiconductor sequencing. Ion semiconductor sequencing was
developed by Ion Torrent Systems Inc. and may be performed using a
bench top machine. It is believed that hydrogen ion release occurs
during nucleic acid amplification because of the formation of a
covalent bond and the release of pyrophosphate and a charged
hydrogen ion. Ion semiconductor sequencing exploits these facts by
determining if a hydrogen ion is released upon providing a single
species of dNTP to the reaction.
[0121] For example, microwells on a semiconductor chip that each
contain one single-stranded template DNA molecule to be sequenced
and one DNA polymerase can be sequentially flooded with unmodified
A, C, G or T dNTP. The hydrogen ion that is released in the
reaction changes the pH of the solution, which is detected by a
hypersensitive ion sensor. The unattached dNTP molecules are washed
out before the next cycle when a different dNTP species is
introduced.
[0122] Beneath the layer of microwells is an ion sensitive layer,
below which is a hypersensitive ISFET ion sensor. All layers are
contained within a CMOS semiconductor chip, similar to that used in
the electronics industry. Each released hydrogen ion triggers the
ISFET ion sensor. The series of electrical pulses transmitted from
the chip to a computer is translated into a DNA sequence, with no
intermediate signal conversion required. Each chip contains an
array of microwells with corresponding ISFET detectors. Because
nucleotide incorporation events are measured directly by
electronics, the use of labeled nucleotides and optical
measurements are avoided.
[0123] An example of a Ion Semiconductor Sequencing technique
suitable for use in the methods of the provided disclosure is Ion
Torrent sequencing (U.S. Patent Application Numbers 2009/0026082,
2009/0127589, 2010/0035252, 2010/0137143, 2010/0188073,
2010/0197507, 2010/0282617, 2010/0300559), 2010/0300895,
2010/0301398, and 2010/0304982), the content of each of which is
incorporated by reference herein in its entirety to the extent such
contents do not conflict with the present disclosure. In Ion
Torrent sequencing, DNA is sheared into fragments of approximately
300-800 base pairs, and the fragments are blunt ended.
Oligonucleotide adaptors are then ligated to the ends of the
fragments. The adaptors serve as primers for amplification and
sequencing of the fragments. The fragments can be attached to a
surface and are attached at a resolution such that the fragments
are individually resolvable. Addition of one or more nucleotides
releases a proton (H.sup.+), which signal detected and recorded in
a sequencing instrument. The signal strength is proportional to the
number of nucleotides incorporated. User guides describe in detail
the Ion Torrent protocol(s) that are suitable for use in methods of
the disclosure, such as Life Technologies' literature entitled "Ion
Sequencing Kit for User Guide v. 2.0" for use with their sequencing
platform the Personal Genome Machine.TM. (PCG), the contents of
which are incorporated herein by reference, to the extent such
contents do not conflict with the present disclosure.
[0124] In accordance with various examples, Ion Semiconductor
Sequencing is used to maximize detection of specific microorganisms
by sequencing, for example, 16S rRNA hypervariable regions on the
Ion Torrent PGM platform (Life Technologies, Carlsbad, Calif.). A
primary PCR step is carried out using chimeric primers containing a
sequence specific portion for amplifying the exons 16S rRNA
hypervariable regions interest along with adapter sequences for
sequencing analysis. Suitable sequence specific primers can be
designed using any suitable method. The primary consideration is
the Tm of the sequence specific portion. For example, primers with
target specific Tm values ranging from about 52.degree. C. to about
68.degree. C. may generate successful amplification products with
chimeric oligonucleotides. Another consideration for primer design
is the size of the amplicon.
[0125] In some embodiments, as a part of the sample preparation
process, "barcodes" may be associated with each sample. In this
process, short oligos are added to primers, where each different
sample uses a different oligo in addition to a primer.
[0126] The term "library", as used herein refers to a library of
genome-derived sequences. The library may also have sequences
allowing amplification of the "library" by the polymerase chain
reaction or other in vitro amplification methods well known to
those skilled in the art. The library may also have sequences that
are compatible with next-generation high throughput sequencers such
as an ion semiconductor sequencing platform.
[0127] In certain embodiments, the primers and barcodes are ligated
to each sample as part of the library generation process. Thus
during the amplification process associated with generating the ion
amplicon library, the primer and the short oligo are also
amplified. As the association of the barcode is done as part of the
library preparation process, it is possible to use more than one
library, and thus more than one sample. Synthetic DNA barcodes may
be included as part of the primer, where a different synthetic DNA
barcode may be used for each library. In some embodiments,
different libraries may be mixed as they are introduced to a flow
cell, and the identity of each sample may be determined as part of
the sequencing process. Sample separation methods can be used in
conjunction with sample identifiers. For example a chip could have
4 separate channels and use 4 different barcodes to allow the
simultaneous running of 16 different samples.
[0128] In some embodiments, the method of the present disclosure
comprises classifying the species or genus of the microorganism
with a computer-based genomic analysis of the sequence data from
the ion semiconductor sequencing platform. The method may further
comprise generating a report with the species of microorganisms
identified and antibiotic resistance information for each species.
Exemplary systems and methods for characterizing, identifying,
and/or classifying the microorganisms are discussed below.
[0129] In some aspects of the present disclosure, the
computer-based genomic analysis makes use of a procedural
algorithm. By way of particular example, an Ion Sequencing data can
be imported into CLC Workbench and the sequences sorted.
[0130] Sequences that are less than 100 bp in length can be
removed. The entire data set (e.g., >100 bp) is then BLASTed to
a local 16S library of named bacteria or other type of
microorganism. In the case of bacteria, the local 16S library can
be compiled from data available from the National Center for
Biotechnology Information (NCBI). The resulting data can be sorted
by BLAST hit length. The distribution of the sequence reads from
the sequencer is analyzed to determine an appropriate cut-off to
obtain a significant number of reads. Less than 20 reads is can be
deemed not acceptable. Generally, hundreds if not thousands of high
quality long reads are included. The returned species greater than
the cut-off can be tabulated for the number of times they occur as
a BLAST result. Typically, sequences can be present 5 or more times
and can constitute at least 1% of the sample to be reported. Any
sequence that does not meet both of these requirements may not be
reported. Depending on the cut-off used, a confidence percentage is
applied to the resulting species, genus, or microorganism calls.
This data may be presented graphically. In one example, a maximum
of six of the top species with a complete listing in tabular format
is reported. Treatment (e.g., antibacterial, antifungal, antiviral,
and/or antiprotozoal) susceptibilities for each
genus/species/microorganism characterized or identified may also be
reported. The references for all of the treatment susceptibilities
may be listed in the report.
[0131] Classification of bacteria has been greatly revised by
analysis of nucleic acid sequences. The section below contains a
classification of bacteria that are human pathogens that may be
identified in accordance with the present disclosure.
Gram-Positive Eubacteria
Actinobacteria
[0132] Actinobacteria are high G+C Gram-positive eubacteria. order:
Actinomycetales [0133] suborder: Actinomycineae [0134] family:
Actinomyecetaceae [0135] Actinomyces israelii (Streptothrix israeli
Kruse 1896) Lachner-Sandoval 1898 (actinomycosis) [0136]
Actinomyces naeslundi Thompson & Lovestedt 1951 (actinomycosis)
[0137] Actinomyces meyeri (Actinobacterium meyeri Prevot 1938) E.
P. Cato et al. 1984 (actinomycosis) [0138] Actinomyces
odontolyticus Batty 1958 (actinomycosis) [0139] Actinomyces
viscosus (Odontomyces viscosus Howell et al. 1965) Georg et al.
1969 (actinomycosis) [0140] suborder: Propionibacterineae [0141]
family: Propionibacteriaceae [0142] Propionibacterium acnes
(Bacillus acnes Gilchrist 1900) Douglas & Gunter 1946
(actinomycosis) [0143] suborder; Micrococcineae [0144] family:
Cellulomonadaceae [0145] Tropheryma whipplei (Tropheryma whippelii
1991) La Scola et al. 2001 (Whipple disease) [0146] suborder:
Streptosporangineae [0147] family: Thermomonosporaceae [0148]
Actinomadura madurae (Streptothrix madurae Vincent 1894)
Lechevalier and Lechevalier 1968 (actinomycetoma) [0149]
Actinomadura pelletieri (Micrococcus pelletieri Layeran 1906)
Lechevalier and Lechevalier 1968 (actinomycetoma) [0150]
Nocardiopsaceae [0151] Nocardiopsis dassonvillei (Streptothrix
dassonvillei Brocq-Rousseau 1904) Meyer 1976 (actinomycetoma)
[0152] suborder: Streptomycineae [0153] family: Streptomycetaceae
[0154] Streptomyces somaliensis (Indiella somaliensis Brumpt 1906)
Waksman and Henrici 1948 (actinomycetoma) [0155] suborder:
Corynebacterineae [0156] family: Nocardiaceae [0157] Nocardia
asteroides (Cladothrix asteroides Eppinger 1891) Blanchard 1896
(nocardiosis, actinomycetoma) [0158] Nocardia brasiliensis
(Discomyces brasiliensis Lindenberg 1909) Pinoy 1913 (nocardiosis,
actinomycetoma) [0159] Nocardia otitidiscaviarum Snijders 1924
(nocardiosis, actinomycetoma) [0160] Nocardia transvalensis Pijper
and Pullinger 1927 (nocardiosis) [0161] Rhodococcus equi
(Corynebacterium equi Magnusson 1923) Goodfellow & Alderson
1977 [0162] family: Mycobacteriaceae [0163] Mycobacterium leprae
Hansen, 1874 (leprosy) [0164] Mycobacterium tuberculosis complex
[0165] Mycobacterium tuberculosis Zopf 1883 (tuberculosis) [0166]
Mycobacterium africanum Castets et al. 1969 (tuberculosis) [0167]
Mycobacterium bovis Karlson & Lessel 1970 (tuberculosis) [0168]
Mycobacterium avium complex (MAC) [0169] Mycobacterium avium
Chester 1901 [0170] Mycobacterium intracellulare (Nocardia
intracellularis Cuttino and McCabe 1949) Runyon 1965 [0171]
Mycobacterium scrofulaceum Prissick and Masson 1956 [0172]
Mycobacterium fortuitum complex (MFC) [0173] Mycobacterium
fortuitum da Costa Cruz 1938 [0174] Mycobacterium chelonae Bergey
et al. 1923 [0175] Mycobacterium kansasii Hauduroy 1955 [0176]
Mycobacterium ulcerans MacCallum et al. 1950 (Buruli ulcer) [0177]
Mycobacterium abscessus Moore and Frerichs 1953 [0178]
Mycobacterium haemophilum Sompolinsky et al. 1978 [0179]
Mycobacterium marinum Aronson 1926 [0180] Mycobacterium simiae
Karassova et al. 1965 [0181] Mycobacterium xenopi Schwabacher 1959
[0182] family: Corynebacteriaceae [0183] Corynebacterium
diphtheriae (Bacillus diphtheriae Kruse 1886) Lehmann and Neumann
1896 (diphtheria) [0184] Corynebacterium minutissimum Sarkany et
al. 1962 (erythrasma) [0185] Corynebacterium jeikeium Jackman et
al. 1988 order: Bifidobacteriales [0186] family: Bifidobacteriaceae
[0187] Gardnerella vaginalis (Haemophilus vaginalis Gardner and
Dukes 1955) Greenwood and Pickett 1980 (bacterial vaginitis)
Firmicutes
[0188] Firmicutes are usually described as low G+C gram-positive
Eubacteria, but they also include Eubacteria that lack a cell wall
(e.g., Mycoplasma) class: Bacilli [0189] order: Lactobacillales
[0190] family: Streptococcaceae [0191] Streptococcus pyogenes
Rosenbach 1884 (Lancefield Group A; (3-hemolytic) (scarlet fever,
erysipelas, rheumatic fever, pharyngitis, cellulitis) [0192]
Streptococcus agalactiae Lehmann and Neumann 1896 (Lancefield Group
B; .beta.-hemolytic) (sepsis of the newborn) [0193] Streptococcus
dysgalactiae group [0194] S. dysgalactiae Diernhofer 1932 [0195] S.
equi Sand and Jensen 1888 (includes S. equi zooepidemicus) [0196]
Streptococcus equinus Andrewes and Horder 1906 (aka S. bovis;
.gamma.-hemolytic) [0197] Streptococcus canis Devriese et al. 1986
[0198] Streptococcus pneumoniae (Micrococcus pneumoniae Klein 1884)
Chester 1901 (.alpha.-hemolytic); pneumococcal infection) [0199]
Streptococcus viridans group (.alpha.-hemolytic or non-hemolytic)
[0200] S. mitis Andrewes and Horder 1906 [0201] S. mutans Clarke
1924 [0202] S. oxalis Bridge and Sneath 1982 [0203] S. sanguinis
White and Niven 1946 [0204] S. sobrinus Coykendall 1974 [0205]
Streptococcus milleri group (Lancefield Group F) S. anginosus
Andrewes and Horder 1906 S. constellatus (Diplococcus constellatus
Prevot 1924) Holdeman & Moore 1974 S. intermedius Prevot 1925
[0206] family: Enterococcaceae [0207] Enterococcus faecalis
(Streptococcus faecalis Andrewes and Horder 1906) Schleifer &
Kilpper-Balz 1984 (.gamma.-hemolytic) [0208] Enterococcus faecium
(Streptococcus faecium Orla-Jensen 1919) Schleifer &
Kilpper-Balz 1984 (.gamma.-hemolytic; vancomycin-resistant
enterococcus) [0209] order: Bacillales [0210] family:
Staphylococcaceae [0211] Staphylococcus aureus Rosenbach 1884
(cellulitis, Staphylococcal scalded skin syndrome, toxic shock
syndrome, food poisoning) [0212] Staphylococcus epidermidis
(Albococcus epidermidis Winslow & Winslow 1908) Evans 1916
[0213] Staphylococcus saprophyticus Fairbrother 1940 (urinary tract
infection) [0214] family: Bacillaceae [0215] Bacillus anthracis
Cohn 1872 (anthrax) [0216] Bacillus cereus Frankland &
Frankland 1887 (food poisoning) [0217] family: Listeriaceae [0218]
Listeria monocytogenes (Bacterium monocytogenes Murray et al. 1926)
Pirie 1940 (Listeriosis) class: Clostridia [0219] order:
Clostridiales [0220] family: Clostridiaceae [0221] Clostridium
botulinum (Bacillus botulinus van Ermengem 1896) Bergey et al. 1923
(botulism) [0222] Clostridium difficile (Bacillus difficilis Hall
& O'Toole 1935) Prevot 1938 (pseudomembranous colitis) [0223]
Clostridium perfringens (Bacillus perfringens Veillon & Zuber
1898) Hauduroy et al. 1937 (gas gangrene, clostridial necrotizing
enteritis) [0224] Clostridium tetani (Bacillus tetani F11igge 1886)
Bergey et al. 1923 (tetanus) [0225] family: Peptostreptococcaceae
[0226] Peptostreptococcus sp. class: Mollicutes This group of
eubacteria is characterized by the absence of a cell wall
(aphragmabacteria). They were previously classified as Tenericutes,
a sister group to Firmicutes, before being reassigned as a class
within Firmicutes. [0227] order: Mycoplasmatales [0228] family:
Mycoplasmataceae [0229] Mycoplasma genitalium Tully et al., 1983
[0230] Mycoplasma pneumoniae Somerson et al., 1963 (mycoplasmal
pneumonia, primary atypical pneumonia) [0231] Mycoplasma
arthriditis [0232] Mycoplasma fermentans [0233] Ureaplasma
urealyticum Shepard et al., 1974 (Ureaplasma infection, urethritis)
[0234] order: Anaeroplasmatales (or Erysipelotrichales) [0235]
family: Erysipelotrichaceae [0236] Erysipelothrix rhusiopathiae
(Bacterium rhusiopathiae Migula 1900) Buchanan 1918 (erysipeloid)
[0237] order: Acholeplasmatales [0238] family: Acholeplasmataceae
[0239] Acholeplasma axanthum [0240] Acholeplasma brassicae [0241]
Acholeplasma cavigenitalium [0242] Acholeplasma entomophilum [0243]
Acholeplasma equifetale [0244] Acholeplasma florum [0245]
Acholeplasma granularum [0246] Acholeplasma hippikon [0247]
Acholeplasma laidlawii [0248] Acholeplasma modicum [0249]
Acholeplasma morum [0250] Acholeplasma multilocale [0251]
Acholeplasma oculi [0252] Acholeplasma palmae [0253] Acholeplasma
parvum [0254] Acholeplasma pleciae [0255] Acholeplasma seiffertii
[0256] Acholeplasma vituli
Bacteroidetes
[0257] class: Bacteroidetes [0258] order: Bacteroidales [0259]
family: Bacteroidaceae [0260] Bacteroides fragilis (Bacillus
fragilis Veillon and Zuber 1898) Castellani and Chalmers 1919
[0261] family: Porphyromonadaceae [0262] Tannerella forsythia
(Bacteroides forsythus Tanner et al. 1986) Sakamoto et al. 2002
[0263] Porphyromonas gingivalis (Bacteroides gingivalis Coykendall
et al. 1980) Shah and Collins 1988 [0264] family: Prevotellaceae
[0265] Prevotella intermedia (Bacteroides melaminogenicus
intermedius Holdeman and Moore 1970) Shah and Collins 1990 class:
Flavobacteria [0266] order: Flavobacteriaceae [0267] family:
Flavobacteriales [0268] Capnocytophaga canimorsus Brenner et al.
1990
Chlamydiae
[0268] [0269] order: Chlamydiales [0270] family: Chlamydiaceae
[0271] Chlamydia trachomatis (Rickettsia trachomae Busacca 1935)
Rake 1957 (lymphogranuloma venereum, trachoma) [0272] Chlamydophila
psittaci (Rickettsia psittaci Lillie 1930) Everett et al. 1999
(psittacosis) [0273] Chlamydophila pneumoniae (Chlamydia pneumoniae
Grayston et al. 1989) Everett et al. 1999
Fusobacteria
[0273] [0274] order: Fusobacteriales [0275] family:
Fusobacteriaceae [0276] Fusobacterium necrophorum (Bacillus
necrophorus Flugge 1886) Moore and Holdeman 1969 (Lemierre's
syndrome) [0277] Fusobacterium nucleatum (Bacillus fusiformis
Veillon and Zuber 1898) Knorr 1922 [0278] Fusobacterium nucleatum
nucleatum Knorr 1922 [0279] Fusobacterium nucleatum polymorphum
(Fusobacterium polymorphum Knorr 1922) Dzink et al. 1990 [0280]
Streptobacillus moniliformis (Streptothrix muris ratti Schottmuller
1914) Levaditi et al. 1925 (Actinobacillus muris Wilson and Miles
1955; rat bite fever)
Proteobacteria
[0281] class: Alpha Proteobacteria [0282] order: Rickettsiales
[0283] family: Rickettsiaceae [0284] Rickettsia--spotted fever
group [0285] Rickettsia rickettsii (Dermacentroxenus rickettsii
Wolbach 1919) Brumpt 1922 (Rocky Mountain spotted fever) [0286]
Rickettsia conorii Brumpt 1932 (Boutonneuse fever) [0287]
Rickettsia akari Huebner et al. 1946 (rickettsialpox) [0288]
Rickettsia--typhus group [0289] Rickettsia typhi (Dermacentroxenus
typhi Wolbach and Todd 1920) Philip 1943 (murine typhus) [0290]
Rickettsia prowazekii da Rocha-Lima 1916 (epidemic typhus) [0291]
Orientia tsutsugamushi (Theileria tsutsugamushi Hayashi 1920)
Tamura et al. 1995 (scrub typhus) [0292] family: Anaplasmataceae
(or Ehrlichiaceae) (Ehrlichiosis and Anaplasmosis) [0293] Anaplasma
phagocytophilum (Rickettsia phagocytophila ovis Foggie 1949) Dumler
et al. 2001 (human granulocytic ehrlichiosis) [0294] Ehrlichia
chaffeensis Anderson et al. 1992 (human monocytic ehrlichiosis)
[0295] order Rhizobiales [0296] family: Brucellaceae [0297]
Brucella abortus (Bacterium abortus Schmidt 1901) Meyer and Shaw
1920 (Brucellosis) [0298] family: Bartonellaceae [0299] Bartonella
bacilliformis (Bartonia bacilliformis Strong et al. 1913) Strong et
al. 1915 (Carrion's disease) [0300] Bartonella henselae
(Rochalimaea henselae Regnery et al. 1992) Brenner et al. 1993 (cat
scratch fever; bacillary angiomatosis) [0301] Bartonella quintana
(Rickettsia quintana Schmincke 1917) Brenner et al. 1993 (trench
fever; bacillary angiomatosis) class: Beta Proteobacteria [0302]
order: Neisseriales [0303] family: Neisseriaceae [0304] Neisseria
meningitidis (Micrococcus meningitidis cerebrospinalis Albrecht
& Ghon 1901) Murray 1929 (meningococcal disease,
Waterhouse-Friderichsen syndrome) [0305] Neisseria gonorrhoeae
(Merismopedia gonorrhoeae Zopf 1885) Trevisan 1885 (gonorrhea)
[0306] Eikenella corrodens (Bacteroides corrodens Eiken 1958)
Jackson and Goodman 1972 [0307] Kingella kingae (Moraxella kingii
Henriksen and Bovre 1968) Henriksen and Bovre 1976 [0308] order:
Burkholderiales [0309] family: Burkholderiaceae [0310] Burkholderia
pseudomallei group [0311] B. pseudomallei (Bacillus pseudomallei
Whitmore 1913) Yabuuchi et al. 1993 (aka Pseudomonas pseudomallei
Haynes 1957; melioidosis) [0312] B. mallei (Bacillus mallei Zopf
1885) Yabuuchi et al. 1993 (aka Pseudomonas mallei Redfearn et al.
1966; glanders) [0313] Burkholderia cepacia complex [0314] B.
cepacia (Pseudomonas cepacia Burkholder 1950) Yabuuchi et al. 1993
[0315] B. vietnamiensis Gillis et al. 1995 [0316] B. multivorans
Vandamme et al. 1997 [0317] B. stabilis Vandamme et al. 2000 [0318]
B. ambifaria Coenye et al. 2001 [0319] B. anthina Vandamme et al.
2002 [0320] B. cenocepacia Vandamme et al. 2003 [0321] B. dolosa
Vermis et al. 2004 [0322] B. pyrrocinia (Pseudomonas pyrrocinia
Imanaka et al. 1965) Vandamme et al. 1997 [0323] family:
Alcaligenaceae [0324] Bordetella pertussis (Hemophilus pertussis
Bergey et al. 1923) Moreno-Lopez 1952 (pertussis or whooping cough)
[0325] Bordetella parapertussis (Bacillus parapertussis Eldering
and Kendrick 1938) Moreno-Lopez 1952 (parapertussis) [0326] Family:
Ralstoniaceae [0327] Ralstonia basilensis [0328] Ralstonia
campinensis [0329] Ralstonia eutropha [0330] Ralstonia gilardii
[0331] Ralstonia insidiosa [0332] Ralstonia mannitolilytica [0333]
Ralstonia metallidurans [0334] Ralstonia paucula [0335] Ralstonia
pickettii [0336] Ralstonia respiraculi [0337] Ralstonia
solanacearum [0338] Ralstonia syzygii [0339] Ralstonia taiwanensis
[0340] order: Nitrosomonadales [0341] family: Spirillaceae [0342]
Spirillum minus (Rat-bite fever) class: Gamma Proteobacteria [0343]
order: Enterobacteriales [0344] family: Enterobacteriaceae [0345]
Enterobacter cloacae (Bacillus cloacae Jordan 1890) Hormaeche and
Edwards 1960 [0346] Escherichia coli (Bacillus coli Migula 1895)
Castellani and Chalmers 1919 [0347] Klebsiella granulomatis
(Calymmatobacterium granulomatis Arago & Vianna 1913) Carter et
al. 1999 (granuloma inguinale or donovanosis) [0348] Klebsiella
oxytoca (Bacillus oxytocus perniciosus Flugge 1886) Lautrop 1956
[0349] Klebsiella pneumoniae (Hyalococcus pneumoniae Schroeter
1886) Trevisan 1887 (rhinoscleroma, Klebsiella pneumonia) [0350]
Plesiomonas shigelloides (Pseudomonas shigelloides Bader 1954) Habs
and Schubert 1962 (aka Aeromonas shigelloides Ewing et al. 1961)
[0351] Proteus mirabilis Hauser 1885 [0352] Proteus vulgaris Hauser
1885 [0353] Salmonella enterica (Bacillus cholerae-suis Smith 1894)
Kauffmann & Edwards 1952 (typhoid fever, paratyphoid fever,
Salmonellosis) [0354] Serratia marcescens Bizio 1823 (Serratia
infection) [0355] Shigella dysenteriae (Bacillus dysentericus Shiga
1897) Castellani & Chalmers 1919 (Shigellosis, bacillary
dysentery) [0356] Shigella flexneri Castellani & Chalmers 1919
(Shigellosis, bacillary dysentery) [0357] Shigella sonnei
(Bacterium sonnei Levine 1920) Weldin 1927 (Shigellosis, bacillary
dysentery) [0358] Yersinia enterocolitica (Bacterium
enterocoliticum Schleifstein & Coleman 1939) Frederiksen 1964
[0359] Yersinia pestis (Bacterium pestis Lehmann & Neumann,
1896) van Loghem 1944 (aka Pasteurella pestis Bergey et al. 1923;
plague/bubonic plague) [0360] Yersinia pseudotuberculosis (Bacillus
pseudotuberkulosis Pfeiffer 1889) Smith & Thal 1965 [0361]
order: Cardiobacteriales [0362] family: Cardiobacteriaceae [0363]
Cardiobacterium hominis Slotnick and Dougherty 1964 [0364] order:
Legionellales [0365] family: Legionellaceae [0366] Legionella
pneumophila Brenner et al. 1979 (Legionellosis) [0367] Legionella
longbeachae McKinney et al. 1982 (Legionellosis) [0368] family:
Coxiellaceae [0369] Coxiella burnetii (Rickettsia burneti Derrick
1939) Philip 1948 (Q fever) [0370] order: Pasteurellales [0371]
family: Pasteurellaceae [0372] Haemophilus influenzae (Bacterium
influenzae Lehmann & Neumann 1896) Winslow et al. 1917
(Haemophilus meningitis, Brazilian purpuric fever) [0373]
Haemophilus ducreyi (Bacillus ulceris cancrosi Kruse 1896) Bergey
et al. 1923 (chancroid) [0374] Pasteurella multocida (Bacterium
multocidum Lehmann and Neumann 1899) Rosenbusch and Merchant 1939
(Pasteurellosis) [0375] Actinobacillus ureae (Pasteurella ureae
Jones 1962) Mutters et al. 1986 (Actinobacillosis) [0376]
Actinobacillus hominis Friis-Mller 1985 (Actinobacillosis) [0377]
Aggregatibacter actinomycetemcomitans (Bacterium actinomycetem
comitans Klinger 1912) Norskov-Lauritsen and Kilian 2006 (aka
Actinobacillus actinomycetemcomitans Topley and Wilson 1929) [0378]
order: Pseudomonadales [0379] family: Pseudomonadaceae [0380]
Pseudomonas aeruginosa (Bacterium aeruginosum Schroter 1872) Migula
1900 (Pseudomonas infection) [0381] family: Moraxellaceae [0382]
Moraxella catarrhalis (Mikrokkokus catarrhalis Frosch and Kolle
1896) Henriksen and Bovre 1968 (aka Branhamella catarrhalis Catlin
1970) [0383] Acinetobacter baumannii Bouvet and Grimont 1986 [0384]
order: Thiotrichales [0385] family: Francisellaceae [0386]
Francisella tularensis (Bacterium tularense McCoy and Chapin 1912)
Dorofe'ev 1947 (tularemia) [0387] order: Vibrionales [0388] family:
Vibrionaceae [0389] Vibrio cholerae Pacini 1854 (cholera) [0390]
Vibrio vulnificus (Beneckea vulnifica Reichelt et al. 1979) Farmer
1980 [0391] Vibrio parahaemolyticus (Pasteurella parahaemolytica
Fujino et al. 1951) Sakazaki et al. 1963 (aka Beneckea
parahaemolytica Baumann et al. 1971) [0392] order: Xanthomonadales
[0393] family: Xanthomonadaceae [0394] Stenotrophomonas maltophilia
(Pseudomonas maltophilia Hugh and Ryschenkow 1961) Palleroni &
Bradbury 1993 class: Epsilon Proteobacteria [0395] order:
Campylobacterales [0396] family: Campylobacteraceae [0397]
Campylobacter jejuni (Vibrio jejuni Jones et al. 1931) Veron &
Chatelain 1973 (Campylobacteriosis) [0398] Campylobacter coli
(Vibrio coli Doyle 1948) Veron and Chatelain 1973 [0399]
Campylobacter lari (Campylobacter laridis Benjamin et al. 1983)
Benjamin et al. 1984 [0400] Campylobacter fetus (Vibrio fetus Smith
and Taylor 1919) Sebald and Veron 1963 [0401] family:
Helicobacteraceae [0402] Helicobacter pylori (Campylobacter
pyloridis Marshall et al. 1985) Goodwin et al. 1989 (peptic ulcer)
[0403] Helicobacter cinaedi (Campylobacter cinaedi Totten et al.
1988) Vandamme et al. 1991 [0404] Helicobacter fennelliae
(Campylobacter fennelliae Totten et al. 1988) Vandamme et al.
1991
Spirochaetes
[0404] [0405] order: Spirochaetales [0406] family: Spirochaetaceae
[0407] Treponema pallidum (Spirochaeta pallida Schaudinn and
Hoffmann 1905) Schaudinn 1905 [0408] Treponema pallidum pallidum
(syphilis) [0409] Treponema pallidum endemicum (bejel) [0410]
Treponema pallidum pertenue (yaws) [0411] Treponema carateum
(pinta) [0412] Treponema denticola (Spirochaete denticola Flugge
1886) Chan et al. 1993 [0413] Borrelia recurrentis (Spirochaete
recurrentis Lebert 1874) Bergey et al. 1925 (relapsing fever)
[0414] Borrelia burgdorferi Johnson et al. 1984 (Lyme disease,
erythema chronicum migrans, neuroborreliosis) [0415] family:
Leptospiraceae [0416] Leptospira interrogans (Spirochaeta
interrogans Stimson 1907) Wenyon 1926 (leptospirosis)
[0417] In certain aspects, the disclosed system and methods are
used to analyze a dental sample and any of the following organism
genera may be detected: Bacteroides, Tannerella, Prevotella,
Peptostreptococcus, Streptococcus, Staphylococcus, Porphyromonas,
Fusobacterium, Clostridium, Treponema, Atopobium, Cryptobacterium,
Eubacterium, Mogibacterium, Filifactor, Dialister, Centipeda,
Selenomonas, Granulicatella, and Kingella and/or other bacteria,
viruses, fungi, and/or protozoa. A "dental sample" may comprise a
tooth, a soft tissue, and/or dental pulp.
[0418] In other aspects, the disclosed system and methods are used
to analyze a joint sample and any of the following organism genera
may be detected: Staphylococcus, Streptococcus, Kingella,
Aeromonas, Mycobacterium, Actinomyces, Fusobacterium, Salmonella,
Haemophilus, Borrelia, Neisseria, Escherichia, Brucella,
Pseudomonas, Mycoplasma, Salmonella, Propionibacterium,
Acinetobacter, Treponema, and Erysipelothrix and/or other bacteria,
viruses, fungi, and/or protozoa. A "joint sample" may comprise
tissue and/or fluid (e.g., synovial fluid) removed from a
joint.
[0419] In yet other aspects, the disclosed system and methods are
used to analyze a blood, sample and any of the following organism
genera may be detected: Capnocytophaga, Rickettsia, Staphylococcus,
Streptococcus, Neisseria, Mycobacterium, Klebsiella, Haemophilus,
Fusobacterium, Chlamydia, Enterococcus, Escherichia, Enterobacter,
Proteus, Legionella, Pseudomonas, Clostridium, Listeria, Serratia,
and Salmonella and/or other bacteria, viruses, fungi, and/or
protozoa. A "blood sample" may comprise blood, serum, and/or
plasma.
[0420] Certain microorganisms are "nonculturable" pathogens. As
used herein, the term "nonculturable" refers to microorganisms that
are alive but do not produce visible colonies on classical liquid
or solid media (e.g., Luria Broth, thioglycollate broth, blood
culture, etc.) within 96 hours after inoculation at about
30.degree. C. under aerobic or anaerobic conditions. Examples of
such nonculturable microorganisms are Bartonella henselae, the
causative agent of bacillary angiomatosis; Tropheryma whipplei, the
etiologic agent in Whipple's disease; and Bartonella quintana and
Coxiella burnetii, which are both associated with endocarditis.
Exemplary methods of the present disclosure may be used to identify
such nonculturable pathogens in a biological sample.
[0421] Exemplary methods of the present disclosure may also be used
to identify a "pathogenic community of microorganisms." As used
herein, a "pathogenic community of microorganisms" is a group of
microorganisms where the individuals are not pathogenic but
together they constitute an invasive, pathogenic population. The
study of population-level virulence traits among communal bacteria
represents an emerging discipline in the field of bacterial
pathogenesis. It has become clear that bacteria exhibit many of the
hallmarks of multicellular organisms when they are growing as
biofilms and communicating among each other using quorum-sensing
systems. Each of these population-level behaviors provides for
multiple expressions of virulence that individual free-swimming
bacteria do not possess. Population-level virulence traits are
often associated with chronic or persistent infections, whereas
individual bacterial virulence traits are generally associated with
acute infections.
[0422] In certain aspects, the present disclosure provides a method
and kit that qualifies as a high complexity test under CLIA
guidelines and may be validated as a Laboratory Developed Test
(LDT). As an LDT, the diagnostic system and methods may be required
to meet several compliance guidelines regarding accuracy, validity,
and performance parameters.
[0423] In certain aspects, the following control checks are in
place for the disclosed system and methods:
Run-to-Run Controls
[0424] Sample Quality--The quality and quantity of received samples
are scrutinized for visible signs of contamination or other
concerns that would preclude processing. Hemolyzed blood samples,
clearly contaminated tissues or fluids, and inappropriately shipped
or stored samples are rejected from analysis.
[0425] DNA Extraction--DNA is extracted from the submitted samples
and the total recovered DNA content is analyzed for concentration
and purity. If a minimum of about 5 ng/.mu.L total DNA
concentration is not obtained analysis may not be performed as the
quantity or quality of the provided sample may not be sufficient.
Furthermore, the 260.lamda./280.lamda. and 260.lamda./230.lamda.
ratios are observed to assess for contaminating proteins or other
potential inhibitors.
[0426] Molecular Tagging and Amplification--DNA amplification
reactions are performed in parallel with negative amplification
controls for each patient sample and with a master positive control
of a known microbial sample from the ATCC bioresource bank. The
positive control species is rotated for each run ensuring continual
efficacy across multiple species. The positive control samples from
each tagging and amplification run are carried forward with the
accompanying patient samples and analyzed to ensure amplification
through reporting generates the properly identified bacterium.
Lastly, the resulting DNA is purified and again analyzed for purity
and concentration prior to entering into the sequencing
protocols.
[0427] Next Generation DNA Sequencing--The sequencing reactions are
preferably monitored and filtered by several overlapping control
procedures at both the analysis and sequencing level. In certain
implementations, tirst, the DNA fragments are linked to Ion Sphere
Particles (ISPs) using a controlled concentration to yield the
highest resulting monoclonal ISP/DNA population. The efficiency of
labeling the ISPs may be assayed using fluorescent probes whereby
the ratios of leading and trailing sequences are measured and the
ratios compared. In some aspects, initial labeling must surpass
about 10% prior to ISP enrichment. Enrichment consistently raises
the ISP labeled monoclonal ISP level to greater than about 80%,
thus ensuring sufficient DNA reads for proper analysis. In addition
to controlling for the proper template and ISP assembly the
sequencing reaction itself must be controlled. The semiconductor
chip is automatically tested by the system hardware to ensure this
consumable is working properly. Next, the sequencing reaction
chemistry is assayed for performance by the addition of control
ISPs into the generated DNA library. Problems with sequencing
efficiency, noise, chemistry, or contamination may be determined by
observing the results from the control ISPs. Finally, the chip
loading and performance is analyzed by the end of the run to
identify any problems resulting from any of the preceding
preparation steps. The resulting quality and number of sequence
reads should preferably surpass expected parameters to be
acceptable for analysis depending on the semiconductor chip size
selected for the test run.
[0428] Bioinformatics Analysis--In certain implementations, the
bioinformatics analysis is entirely computer executed with minimal
human input or guidance, thus minimizing operator induced errors
during the complex mathematical analysis of the resulting DNA
sequence information. Resulting sequence reads that do not meet
specific quality requirements are preferably removed prior to
analysis. Subsequent DNA sequences may be identified independently
using internationally curated databases and the closes matches are
selected. Depending on the resulting strength of the identification
the best match for each sequence is recorded and collated. The top
result matches can meet additional quality metrics prior to being
accepted as legitimate results. Furthermore, non-target DNA
sequences such as human contaminants can be screened out. Finally,
the most significant and highest probability results can be
presented for report building. Using these methods the genus can be
correctly identified greater than about 60%, about 65%, about 70%,
about 75%, about 80%, about 85%, about 90%, or about 95% of the
time, while the specific species may be correctly identified
greater than about 20%, about 25%, about 30%, about 35%, about 40%,
about 45%, about 50%, about 55% about 60%, about 65%, about 70%,
about 75%, about 80%, about 85%, about 90%, or about 95% of the
time. Treatment recommendations may be presented based on
literature searches across the identified genus and/or species.
Samples that fail to meet these requirements can be rejected from
analysis as, for example, a "No Significant Sequences Detected"
result.
[0429] Result Report Building--Lastly, both a sequencing technician
and the Laboratory Director may review the resulting data prior to
result reporting. Reports can be scrutinized for evidence of
contamination, carryover, or failure of control parameters. Once
these criteria are met, the reports may be released to physicians
or healthcare providers as, for example, a password protected PDF
document.
System Validity
[0430] In addition to run-to-run performance controls listed above
the disclosed system and methods have undergone significant
validation for identification of naturally occurring and synthetic
bacterial populations in a variety of sample types. For each pooled
patient DNA library a known microorganism slated for identification
can be included and the assay can be partially perpetually
validated with the appropriate identification of the included
positive control species. The source material for these cells or
DNA may be provided from the American Type Culture Collection
(ATCC) bioresource catalogue of well-studied and characterized
standards. The selected control species include and rotate through
known pathogens such as Borrelia burgdorferi, Mycoplasma
arthriditis, Eschericia coli, Bartonella henselae, Coxiella
brunetii, and Bartonella bacilliformis. Additionally, the
performance metrics for the assay are selected to provide the most
accurate picture of organism ratios in a given sample. Simply,
known combinations of organisms have been generated, and the best
quality cutoffs to best replicate actual DNA contribution from
mixed populations have been determined. In addition to single or
combinatorial validation, a large number of real world samples from
a variety of sources have been processed. These include blood
samples, tissue biopsies, synovial fluid, serum, cerebrospinal
fluid, abscess material, and even dental infections. As expected
the detected microbial populations reflect and are in congruence
with previously published microbial populations appropriate for the
sample type; however, as also expected the identified ratios and
specific bacterial contributors vary from sample to sample with
unique and identifying characteristics. Furthermore, dental
abscesses have been identified having the main contributors from
both the Streptococcus and Staphylococcus genera consistent with
published expected results.
[0431] In some implementations, reports are distributed the day
after a successful sequencing run and may include the following
information.
Page 1
[0432] 1. Patient, physician, and other pertinent test information
is presented at the top of the report for convenience in line with
standard laboratory reports. 2. A bar graph displaying, for
example, up to 6 of the top significant microbial species or
microbials identified by the sequence analysis. This bar graph
takes into account the strength of the identified result. DNA
sequences of which a high probability match are found can be
indicated as "Close Match" and can be represented as a solid bar,
while DNA sequences that are divergent but are the closest match to
the organism can be indicated as a "Potential Novel" and can be
represented, for example, as a hatched bar on the graph. The
relative percent contribution is indicated underneath the bar graph
for easy reference. 3. A table of, for example, up to 6 of the top
significant identified species including Genus specific treatments
(e.g., antibiotics, antifungals, antivirals, or antiprotozoals) and
any noted treatment resistance for organisms in that Genus. It is
important to note that these are not drug sensitivities derived
from sequence information, but literature derived suggestions as to
what therapies show efficacy in vivo or in vitro. Furthermore,
treatments for the Genus may also show up in the noted resistance
column, as the results are not mutually exclusive. 4. A following
Notes section can include performance characteristics of this assay
both general and specific to the submitted sample.
Page 2+
[0433] 5. The first section on Page 2 can include a complete
listing of the all of the significant identified microbes including
total sequence counts and percentages in addition to "Close Match"
and "Potential Novel" counts and percentages. These may exceed the
total of 6 organisms presented in the bar graph on Page 1. 6.
Finally detailed treatment susceptibility with references can be
listed for each identified Genus and can be ordered in the order of
contribution to the sample. This allows for easy reference to
confirm or obtain detailed information about previous literature
studying the susceptibility of various bacterial Genera. This
section may extend for several pages of detailed reference
information.
[0434] In certain aspects, the present disclosure provides kits for
the identifying a plurality of microorganisms in a biological
sample. Exemplary kits includes a) at least one forward primer
comprising an adapter sequence and a priming sequence, for a target
sequence, wherein the target sequence comprises a sequence from a
characteristic gene sequence; and b) at least one reverse
primer.
[0435] The kits may be used with an ion semiconductor sequencing
platform. The kits may comprise any of the primers disclosed
herein, for example but limited to, a forward primer comprising a
barcode, a barcode adapter, and a target sequence comprising a
sequence from the 16S rRNA gene. The kit may also comprise
nucleotides, buffers and/or a DNA polymerase.
[0436] Further exemplary embodiments of the disclosure provide
systems and methods for characterizing one or more microorganisms
that may be utilized on a traditional or mobile computerized
interfaces or network capable of providing the disclosed
processing, querying, and displaying functionalities. Various
examples of the disclosed systems and methods may be carried out
through the use of one or more computers, processors, servers,
databases, and the like. Various examples disclosed herein provide
highly efficient computerized systems and methods for
characterizing one or more microorganisms or DNA fragments thereof,
such as for example, pathogenic microorganisms in an efficient and
timely manner, such that the systems and methods are suitable for
use in clinical settings. Exemplary systems and methods can also
provide treatment and/or treatment sensitivity information related
to the one or more identified microorganism, such that a care
provider can use such information. FIG. 12 illustrates a system 100
in accordance with exemplary embodiments of the disclosure. As
illustrated, system 100 includes a computer 102, which can be
connected to a network 104. System 100 can also include one or more
databases 106-110, which may form part of one or more servers, such
as servers 112-116. Although illustrated as part of separate
servers, databases 106-110 can form part of the same server or part
of a computer, such as computer 102 or another computer.
[0437] Computer 102 can include any suitable devices that performs
the computer functions noted below. For example, computer 102 can
be or include a desktop computer, notebook computer, workstation,
network computer, personal data assistant, minicomputer, mainframe
computer, server, supercomputer, mobile device, awearable computer,
a sequencing (e.g., DNA sequencing) device, or other device having
suitable computing capabilities.
[0438] Network 104 can be or include a local area network (LAN), a
wide area network, a personal area network, a campus area network,
a metropolitan area network, a global area network, or the like.
Network 104 can be coupled to one or more computers 102, servers
112-116, other networks, and/or other devices using an Ethernet
connection, other wired connections, a WiFi interface, other
wireless interfaces, or other suitable connection.
[0439] Servers 112-116 can include any suitable computing device,
including devices described above in connection with computer 102.
Similarly, databases 106-110 can include any suitable database,
such as those described in more detail below.
[0440] FIG. 13 illustrates a method 200 of characterizing one or
more microorganisms in accordance with various examples of the
disclosure. Method 200 includes the steps of selecting, by a
computer, a digital file comprising one or more digital DNA
sequences, wherein each of the one or more digital DNA sequences
corresponds to a microorganism to be characterized (step 202);
segmenting, by the computer, each of the one or more digital DNA
sequences into one or more first portions (step 204); performing,
by the computer, a set of alignments by comparing the one or more
first portions to information stored in a first database (step
206); determining, by the computer, sequence portions from among
the one or more first portions that have an alignment match to the
information stored in the first database (step 208); optionally
further segmenting, by the computer, each of the one or more
digital DNA sequences into one or more second portions (step 210);
performing, by the computer, a set of alignments by comparing the
one or more first portions or the one or more second portions to
information stored in a second database (step 212); determining, by
the computer, sequence portions from among the one or more first
portions or the one or more second portions that have an alignment
match to the information stored in the second database (step 214);
and characterizing one or more microorganisms or DNA fragments
thereof based on the alignment match to the information stored in
one or more of the first database and the second database (step
216). Each of the steps can be performed using, for example,
computer 102 of system 100.
[0441] In accordance with some examples of these embodiments,
method 200 may also include a step of automatically detecting a
sequence run prior to step 202. FIG. 14 illustrates an exemplary
sequence run and detection process 300 suitable for use with method
200 and for method 400, described below. In a situation in which a
genetic sequencing run is in progress, an in-progress run may be
detected--e.g., by a computer (step 302). In response to the
detection, the computer may query, for example, a server (e.g., on
of servers 112-116) or other computing device on which the
sequencing process is occurring to verify completion of the
sequencing run (step 304). While it is contemplated that any
appropriate file format may be used, in some implementations, the
processed sequence file may optionally be converted from one format
to another (step 306). For example, an original file may be in a
BAM format which can then be converted to a FASTQ file format for
further processing and/or data manipulation. Alternatively, the
processed sequence file may be in an SFF, FASTQ, or any other
appropriate format that is convertible to a FASTQ file format. The
file(s) can then be downloaded or otherwise transferred to a
computing device for further analysis (step 308), such as for use
with method 200. Alternatively, method 200 can employ a sequence
file that is, e.g., in FASTQ or other appropriate format from a
previously completed sequencing run. Regardless of whether a file
is manually selected by a user or automatically detected by the
computing device in accordance with FIG. 3, an implementation of
the method may then convert the FASTQ or other file format into one
or more easily usable FASTA formatted or other appropriately
formatted files, illustrated as step 310 in FIG. 3. During step
310, during the file conversion, the sequencing device type and/or
the microorganism type can be detected. This allows the method
(e.g., method 200 or 400) to automatically process the sequences
based on an incoming data (e.g., for a sequencer type) and/or
microorganism type.
[0442] Referring again to FIG. 13, during step 202, a digital file
comprising one or more digital DNA sequences is selected. The
digital file can include a plurality of DNA sequences from the one
or more files (e.g., FASTA files) that can comprise a predetermined
number of base pairs (bp) or otherwise have a predetermined length.
In some implementations, 100 bp may be a preferred number of base
pairs at which to set this selection threshold, however, any other
number of base pairs that allows for adequate processing and
elimination of sequence portions that are unlikely to lead to
meaningful analysis may also be selected. For example, greater than
or equal to 50 bp, 100 bp, or 150 bp may be used.
[0443] During step 204, the selected DNA sequence file(s) are
segmented into one or more first portions, which may be of equal
size or length. While any number of (e.g., equal) portions may be
used, in some implementations, it may be desirable to match the
number of portions to the number of processing cores to be used by
a system for processing. For example, when using an analysis
computer that has 32 cores, it may be desirable to use 30 of those
cores for processing while keeping the remaining two cores in
reserve for data management and other processing functions. By way
of particular example, it may then be preferable to divide the
(e.g., FASTA) sequence file into 30 equal portions, such that one
portion of the file may be processed by each desired processing
core.
[0444] Once the division of one or more digital DNA sequences into
one or more first portions is complete, a set of alignments is
performed by comparing the one or more first portions to
information stored in a first database (step 206). The alignments
can be performed using a variety of techniques, including Basic
Local Alignment Search Tool (BLAST), OTU, G-BLASTN, mpiBLAST,
BLASTX, PAUDA, USEARCH, LAST, BLAT, or other suitable
technique.
[0445] The first database (e.g., one of databases 106-110) can
include a database that includes nucleic acid information (e.g.,
DNA and/or RNA information) corresponding to one or more types of
microorganism--e.g., bacteria, viruses, protozoa, or fungi. By way
of examples, the first database can include a bacterial nucleic
acid database, such as an 16S Microbial DNA Database.
[0446] By way of particular examples, step 206 can include
performing a set of alignments using BLAST by comparing each of the
sequence file portions to a say a DNA database of 16S rRNA
Microbial sequences (Bacteria and Archaea) (hereinafter referred to
as "16S") database, such as the National Center for Biotechnology
Information (NCBI) 16S database.
[0447] The alignments may in some implementations occur
substantially simultaneously. It may also be preferable to perform
the alignments during step 206 using a relatively small comparison
window (e.g., 10 bp or 11 bp) as the first database may be
relatively small and thus, the processing time does not become
prohibitive even with relatively small comparison windows. Although
not illustrated, method 200 can include collating the aggregate
results and eliminating any duplicates present. This may be done,
for example, when the alignments are complete at step 206.
[0448] During step 208, a computer determines sequence portions
from among the one or more first portions that have an alignment
match to the information stored in the first database. The step of
determining may be based on a predetermined criteria or tolerance
for a match.
[0449] During step 210, each of the one or more digital DNA
sequences from step 202 are optionally further segmented into one
or more second portions. Step 210 can be performed in substantially
the same way as step 204. During this optional step, the sequence
files can be divided into a second plurality of sequence portions,
which may be of equal size and/or the number of portions may be
determined by a preferred number of processing cores to be used. In
accordance with some exemplary embodiments, the second portions
differ or are exclusive of the first portions.
[0450] During step 212, a set of alignments by comparing the one or
more first portions or the one or more second portions (if optional
step 210 is performed) to information stored in a second database
is performed. Step 212 is similar to step 206, except either first
portions or second portions are compared to a second database.
[0451] The second database may be relatively large relative to the
first database. As such, to reduce processing time, it may be
desirable to use a comparison window that is relatively large
(e.g., 65 bp, 100 bp, or the like), especially for a first run of
step 212. The second database can be or include, for example, a
comprehensive nucleic acids database, such as a comprehensive DNA
database, a comprehensive RNA database, a eukaryotic DNA database,
an NT database, a fungi DNA database, a protozoa DNA database, a
comprehensive bacterial nuecleic acids database, or a viral nucleic
acids database.
[0452] As shown in FIG. 13, steps 210-214 can be repeated--e.g., in
an iterative manner, wherein a comparison window for determining a
match decreases as the number (n) of runs increases. For example,
the initial comparison window size can start at 65 bp, and decrease
to 40 bp, 25 bp, 10 bp with subsequent runs.
[0453] The alignment results from step 212 can be collated and any
duplicates removed. The results can then be checked to determine if
all of the sequence file portions were aligned through the running
of the alignments.
[0454] Step 214 can be performed in a manner similar to or the same
as step 208. If the alignments performed on the second portions are
done using a large comparison window, the results of these
alignments may not produce a match between the sequence of the file
portion and the second database, due to the low level of
stringency. If there are any of the sequence file portions for
which the alignment did not identify a match within the second
database, a size of a comparison window can be adjusted (e.g.,
automatically) to increase the stringency--i.e., decrease a size of
a comparison window--of a subsequent alignment. The previously
unidentified sequence portions are then passed iteratively back
into the file segmentation stage 210 where they may then be
segmented into any desired number of (e.g., equally) sized sequence
portions and alignments are then run for each of the portions.
These steps may be iteratively repeated and the stringency
increased (comparison window size decreased) each time step 212 is
performed and fails to produce a resulting match in step 214. By
starting with a lower stringency (e.g., large comparison window)
and increasing the stringency (e.g., decreasing the comparison
window)--e.g., in a manner that is directly proportional to the
number of times which a portion of the sequence has passed through
an alignment and failed to find a match, significant processing
time may be saved. For example, beginning with a low stringency
having a comparison window of 65 bp and then iteratively increasing
the stringency by decreasing the comparison window to, for example,
40 bp, 25 bp, and finally 10 bp rather than simply running all of
the second database alignments with a comparison window of 10 bp
from the start may reduce processing time by many hours or even
days. The method may also utilize a maximum stringency (minimum
comparison window size) setting in which any leftover sequence
portions that have not resulted in a second database match after
having been aligned at the highest designated stringency level are
discarded to prevent unnecessary processing from continuing.
[0455] Table 1 below illustrates the effect of window size on speed
and rate at which sequences are characterized in addition to the
ratio of contaminating human sequences vs the target microbial
sequences.
TABLE-US-00004 TABLE 1 Comparison Human/ Window % Time Non- Size
Recovery (min) Human NonHuman Seq/Min %/Min Human 200 13.4% 2.7
11500 57 4344.7 5.1% 201.8 150 35.7% 4.4 30538 148 7022.0 8.2%
206.3 100 63.5% 4.7 54231 311 11679.2 13.6% 174.4 90 71.9% 4.7
61433 376 13039.9 15.2% 163.4 80 79.4% 5.3 67848 422 12832.7 14.9%
160.8 75 85.2% 4.7 72811 466 15524.8 18.1% 156.2 70 88.6% 4.8 75222
920 15896.0 18.5% 81.8 65 90.5% 4.9 76724 1026 15932.4 18.5% 74.8
64 90.8% 5.0 76991 1041 15606.4 18.2% 74.0 63 91.4% 5.4 77481 1064
14681.3 17.1% 72.8 62 91.9% 5.0 77917 1096 15834.3 18.4% 71.1 60
92.6% 5.8 78472 1146 13822.6 16.1% 68.5 50 96.0% 5.8 81078 1460
14304.7 16.6% 55.5 40 98.6% 8.8 82945 1849 9592.1 11.2% 44.9 25
99.9% 48.7 83349 2508 1763.7 2.1% 33.2
[0456] At step 216, one or more microorganisms are characterized.
The characterization can include identifying the one or more
microorganisms or finding a close match of an unknown microorganism
to a known or unknown microorganism in a database.
[0457] Exemplary methods can also include a comparison of results
from the two alignments determination steps 208 and 214. For
example, once collation and removal of duplicate results has been
accomplished for both the first database alignments results and the
second database (optionally iteratively performed) aligned results,
the results of the two databases alignments can be compared. In
some implementations of the method, the first database alignment
results may first be examined to determine if there are any
complete, or 100%, matches. If so, these are assumed to be
correctly identified microorganisms due to their high degree of
matching and can be placed into a first list. The first database
results can then re-analyzed to find matches having a slightly
lesser degree of completeness, but for which there is still a
reasonably high probability that the microorganism has been
correctly identified and these results are also added to the first
list. For example, the matches can be 100%, 98%, 97%, 95%, or 90%.
For the remaining first database results that fall below the
predetermined threshold of reliability for the results to become a
member of the first list, a comparison can made with the
corresponding second database results for each particular sequence
portion to determine whether the second database result (e.g., a
match during step 214) or the first database result (from step 208)
provides a closer match. In some implementation, this may be
accomplished by comparing one or more variables, such as for
example, one or more of a percentage identity and sequence E-value,
to determine which of the two database alignments result in the
closest match. Once it is determined which is the closer match, the
results can further analyzed to characterize and/or identify any of
the closest matches that do not fall above a predetermined
threshold (e.g., 100%, 98%, 97%, 95%, or 90%) of certainty and
these results may be categorized as results that do not correspond
with the characterized microorganism(s).
[0458] A quality of the results of comparisons of matches from
steps 208 and 214 can be checked by limiting the analysis to
sequence portions that have a predetermined length. For example,
either a minimum threshold for sequence length could be set such
as, for example, a minimum sequence length of 100 bp, or the
results may be limited such that only those above which fall into a
certain percentage of the longest sequences, for example, the top
100%, 50%, 30%, 20%, 15%, or 10% of all run sequence lengths may be
selected on which to base the remaining analysis. By way of one
example, the top 8.6% of sequence lengths can be used. The results
can then be tabulated to determine how many matches correspond to
each characterized or identified microorganism and any region
information can also be tabulated to determine the number of
matches for each region analyzed.
[0459] The system can then query a database of treatment
information that may contain information such as the treatment
(e.g., antibiotic, antiviral, antifungal, antiprotozoal) treatment
and sensitivity and/or therapy resistance of the treatment(s)
corresponding to each identified microorganism and the retrieved
information may then be used to generate a final report. As shown
in FIGS. 16-17, the output of the final report may display
information such as, but not limited to: patient information,
medical professional information, sample type, collection date,
graphical or numerical data relating to one or more characterized
or identified microorganisms, a percentage or other numerical
indicator of contribution amount of each identified microorganism,
a quantitative indicator for a match (e.g., an E-value or %
Identity), a description of identified and/or unidentified (novel)
microorganisms, and/or treatment sensitivity and/or therapy
resistance information.
[0460] It may be advantageous to implement the disclosed system and
methods in a language or other format that is compatible with a
sequencing platform, such as an ionssemiconductor sequencing
platform--e.g., an an IonTorent Server or an Illumina sequencer, as
this may provide added efficiencies to the overall
implementation.
[0461] Turning now to FIG. 15, a method 400 of automatically
characterizing one or more microorganisms is illustrated. Method
400 is similar to method 200, except method 400 includes a step of
detecting a sequence run that generates a digital DNA sequence of
one or more microorganism (step 402) and does not necessarily, but
can, include a performing a set of alignments by comparing the one
or more sequence portions to information stored in a second
database.
[0462] In the illustrated example, method 400 includes the steps of
detecting a sequence run that generates a digital DNA sequence of
one or more microorganisms (step 402); selecting, by a computer, a
digital file comprising one or more digital DNA sequences, wherein
each of the one or more digital DNA sequences corresponds to a
microorganism to be characterized (step 404); segmenting, by the
computer, each of the one or more digital DNA sequences into one or
more portions (step 406); performing, by the computer, a set of
alignments by comparing the one or more portions to information
stored in one or more databases (step 408); determining, by the
computer, sequence portions from among the one or more portions
that have an alignment match to the information stored in the one
or more databases (step 410); and characterizing one or more
microorganisms or DNA fragments thereof based on the alignment
match (step 412).
[0463] Step 402 includes automatically detecting a sequence run
that generates a digital DNA sequence of one or more
microorganisms. This can be done as described above in connection
with process 300. Steps 404-412 can be the same or similar to steps
202-208 and 216 of method 200.
[0464] Method 400 can also include steps of optionally further
segmenting, by the computer, each of the one or more digital DNA
sequences into one or more second portions (wherein the portions
noted above become first portions); performing, by the computer, a
set of alignments by comparing the one or more first portions or
the one or more second portions to information stored in a database
(e.g., a second database); and determining, by the computer,
sequence portions from among the one or more first portions or the
one or more second portions that have an alignment match to the
information stored in a database (e.g., the second database).
Similar to method 200, these steps can be iteratively repeated with
a comparison window decreasing in size with each run. Additional
steps noted above in connection with method 200 can also be
includes in method 400.
[0465] In accordance with various embodiments of the disclosure,
method 200 or method 400 can be performed on a computer on a local
network. By performing the processing functions of the disclosed
systems or methods locally within the system, an Internet
connection is not needed to sustain the processing. This offers
additional security and reduces networking requirements.
Implementations of the disclosed system and method are intended to
integrate with existing and future Next Generation Sequencing
software platforms such as, for example, Illumina.RTM. software
applications such as Illumina MiSeq.RTM. and Illumina HiSeq.RTM.;
LifeTechnologies Proton.RTM.; LifeTechnologies Personal Genome
Machine, and PacBioRS II NGS sequencing systems.
[0466] Exemplary methods of the present disclosure described above
may be implemented as one or more software processes executable by
one or more processors and/or one or more firmware applications.
The processes and/or firmware are configured to operate on one or
more general purpose microprocessors or controllers, a field
programmable gate array (FPGA), an application specific integrated
circuit (ASIC), or other hardware capable of performing the actions
describe above. In an exemplary embodiment of the present
disclosure, software processes are executed by a CPU in order to
perform the actions of the present disclosure. Additionally, the
present disclosure is not described with reference to any
particular programming language. It will be appreciated that a
variety of programming languages may be used to implement the
teachings of the disclosure as described herein.
[0467] Any of the methods herein may be employed with any form of
memory device including all forms of sequential, pseudo-random, and
random access storage devices. Storage devices as known within the
current art include all forms of random access memory, magnetic and
optical tape, magnetic and optical disks, along with various other
forms of solid-state mass storage devices. The current disclosure
applies to all forms and manners of memory devices including, but
not limited to, storage devices utilizing magnetic, optical, and
chemical techniques, or any combination thereof.
[0468] This disclosure is further illustrated by the following
additional examples that should not be construed as limiting. It
can be appreciated that many changes can be made to the specific
embodiments which are disclosed and still obtain a like or similar
result without departing from the spirit and scope of the
disclosure.
EXAMPLES
Example 1
General DNA Extraction Procedures
[0469] Tissues, fluids, other biopsy material, environmental, or
industrial material that is suspected of containing bacterial cells
can be extracted using one of three main methods:
[0470] Bone or Tough Tissue Preparation [0471] 1) .about.200 mg of
bone or tissue is placed in a sterile 50 mL conical tube and 5 mL
of molecular grade water is added to the sample. [0472] 2) The
tissue is sonicated in 5-10 second bursts for a minimum of 5
minutes using a sterile sonicator probe at 10-14 watts. [0473] 3)
200 .mu.L of supernatant and any remaining bone/tissue fragments
are transferred to a sterile 2 mL screw cap tube and 50-100 .mu.L
of 1 mm uneven stainless steel beads, 200 .mu.L of Qiagen Buffer
AL, and 20 .mu.L of Proteinase K is added to the sample. [0474] 4)
The tube is then processed using a percussion based bead
homogenizer for 5 minutes at medium speed.
[0475] 5) 600 .mu.L of the resulting supernatant is run through an
inert filter column to remove beads. [0476] 6) 200 .mu.L of 100%
Ethanol is added to the sample. [0477] 7) From here the remaining
steps are carried out as described in the Qiagen QIAamp DNA Blood
Mini Kit protocol. [0478] 8) Final DNA is eluted in 30 .mu.L.
[0479] 9) Concentration of the extracted DNA is determined by
NanoDrop analysis (Thermo Scientific, Wilmington, Del.) of 4
.mu.L.
[0480] Soft Tissue Preparation [0481] 1) 200 mg of soft tissue and
200 .mu.L of molecular grade water is transferred to a sterile 2 mL
screw cap tube and 50-100 .mu.L of 1 mm glass beads, 200 .mu.L of
Qiagen Buffer AL, and 20 .mu.L of Proteinase K is added to the
sample. [0482] 2) The tube is then processed using a percussion
based bead homogenizer for 5 minutes at medium speed. [0483] 3)
.about.600 .mu.L of the resulting supernatant is run through an
inert filter column to remove beads. [0484] 4) 200 .mu.L of 100%
Ethanol is added to the sample. [0485] 5) From here the remaining
steps are carried out as described in the Qiagen QIAamp DNA Blood
Mini Kit protocol. [0486] 6) Final DNA is eluted in 30 .mu.L.
[0487] 7) Concentration of the extracted DNA is determined by
NanoDrop analysis (Thermo Scientific, Wilmington, Del.) of 4
.mu.L.
[0488] Fluid Preparation [0489] 1) 200 .mu.L of blood or fluid is
transferred to a sterile 2 mL screw cap tube and 50-100 .mu.L of 1
mm glass beads, 200 .mu.L of Qiagen Buffer AL, and 20 .mu.L of
Proteinase K is added to the sample. [0490] 2) The tube is then
processed using a percussion based bead homogenizer for 5 minutes
at medium speed. [0491] 3) .about.400 .mu.L of the resulting
supernatant is run through an inert filter column to remove beads.
[0492] 4) 200 .mu.L of 100% Ethanol is added to the sample. [0493]
5) From here the remaining steps are carried out as described in
the Qiagen QIAamp DNA Blood Mini Kit protocol. [0494] 6) Final DNA
is eluted in 30 .mu.L. [0495] 7) Concentration of the extracted DNA
is determined by NanoDrop analysis (Thermo Scientific, Wilmington,
Del.) of 4 .mu.L.
Example 2
DNA Purification from Tissues with the QIAamp.RTM. DNA Mini Kit
[0496] DNA can be purified from tissues using the QIAamp.RTM. DNA
Mini Kit (QIAGEN, Germantown, Md.).
[0497] Important points before starting: [0498] All centrifugation
steps can be carried out at room temperature (.about.15-25.degree.
C.). [0499] Use carrier DNA if the sample contains <10,000
genome equivalents. [0500] Avoid repeated freezing and thawing of
stored samples, since this leads to reduced DNA size.
[0501] Transcriptionally active tissues, such as liver and kidney,
contain high levels of RNA which will copurify with genomic DNA.
RNA may inhibit some downstream enzymatic reactions, but will not
inhibit PCR. If RNA-free genomic DNA is required, include an RNase
A digest.
[0502] Things to do before starting: [0503] Equilibrate the sample
to room temperature (.about.15-25.degree. C.). [0504] Heat 2 water
baths or heating blocks: one to 56.degree. C. for use in step 3,
and one to 70.degree. C. for use in step 5. [0505] Equilibrate
Buffer AE or distilled water to room temperature for elution in
step 11. [0506] Ensure that Buffers AW1 and AW2 have been prepared.
[0507] If a precipitate has formed in Buffer ATL or Buffer AL,
dissolve by incubating at 56.degree. C.
Exemplary Procedure
[0508] 1. Excise the tissue sample or remove it from storage.
Determine the amount of tissue. Do not use more than 25 mg (10 mg
spleen). Weighing tissue is the most accurate way to determine the
amount. If DNA is prepared from spleen tissue, no more than 10 mg
should be used. The yield of DNA will depend on both the amount and
the type of tissue processed. 1 mg of tissue will yield
approximately 0.2-1.2 .mu.g of DNA.
[0509] 2. Cut up (step 2a), grind (step 2b), or mechanically
disrupt (step 2c) the tissue sample. The QIAamp procedure requires
no mechanical disruption of the tissue sample, but lysis time will
be reduced if the sample is ground in liquid nitrogen (step 2b) or
mechanically homogenized (step 2c) in advance.
[0510] 2a. Cut up to 25 mg of tissue (up to 10 mg spleen) into
small pieces. Place in a 1.5 ml microcentrifuge tube, and add 180
.mu.l of Buffer ATL. Proceed with step 3. It is important to cut
the tissue into small pieces to decrease lysis time. 2 ml
microcentrifuge tubes may be better suited for lysis.
[0511] 2b. Place up to 25 mg of tissue (10 mg spleen) in liquid
nitrogen, and grind thoroughly with a mortar and pestle. Decant
tissue powder and liquid nitrogen into 1.5 ml microcentrifuge tube.
Allow the liquid nitrogen to evaporate, but do not allow the tissue
to thaw, and add 180 .mu.l of Buffer ATL. Proceed with step 3.
[0512] 2c. Add up to 25 mg of tissue (10 mg spleen) to a 1.5 ml
microcentrifuge tube containing no more than 80 .mu.l PBS.
Homogenize the sample using the TissueRuptor or equivalent
rotor-stator homogenizer. Add 100 .mu.l Buffer ATL, and proceed
with step 3. Some tissues require undiluted Buffer ATL for complete
lysis. In this case, grinding in liquid nitrogen is recommended.
Samples cannot be homogenized directly in Buffer ATL, which
contains detergent.
[0513] 3. Add 20 .mu.l proteinase K, mix by vortexing, and incubate
at 56.degree. C. until the tissue is completely lysed. Vortex
occasionally during incubation to disperse the sample, or place in
a shaking water bath or on a rocking platform. Note: Proteinase K
can be used. QIAGEN Protease has reduced activity in the presence
of Buffer ATL. Lysis time varies depending on the type of tissue
processed. Lysis is usually complete in 1-3 h. Lysis overnight is
possible and does not influence the preparation. In order to ensure
efficient lysis, a shaking water bath or a rocking platform can be
used. If not available, vortexing 2-3 times per hour during
incubation is recommended.
[0514] 4. Briefly centrifuge the 1.5 ml microcentrifuge tube to
remove drops from the inside of the lid.
[0515] 5. If RNA-free genomic DNA is desired, follow step 5a.
Otherwise, follow step 5b. Transcriptionally active tissues, such
as liver and kidney, contain high levels of RNA which will copurify
with genomic DNA. RNA may inhibit some downstream enzymatic
reactions, but will not inhibit PCR.
[0516] 5a. First add 4 .mu.l RNase A (100 mg/ml), mix by
pulse-vortexing for 15 s, and incubate for 2 min at room
temperature. Briefly centrifuge the 1.5 ml microcentrifuge tube to
remove drops from inside the lid before adding 200 .mu.l Buffer AL
to the sample. Mix again by pulse-vortexing for 15 s, and incubate
at 70.degree. C. for 10 min. Briefly centrifuge the 1.5 ml
microcentrifuge tube to remove drops from inside the lid. It is
desirable that the sample and Buffer AL are mixed thoroughly to
yield a homogeneous solution. A white precipitate may form on
addition of Buffer AL. In most cases the precipitate will dissolve
during incubation at 70.degree. C. The precipitate does not
interfere with the QIAamp procedure or with any subsequent
application.
[0517] 5b. Add 200 .mu.l Buffer AL to the sample, mix by
pulse-vortexing for 15 s, and incubate at 70.degree. C. for 10 min.
Briefly centrifuge the 1.5 ml microcentrifuge tube to remove drops
from inside the lid. It is desirable that the sample and Buffer AL
are mixed thoroughly to yield a homogeneous solution. A white
precipitate may form on addition of Buffer AL, which in most cases
will dissolve during incubation at 70.degree. C. The precipitate
does not interfere with the QIAamp procedure or with any subsequent
application.
[0518] 6. Add 200 .mu.l ethanol (96-100%) to the sample, and mix by
pulse-vortexing for 15 s. After mixing, briefly centrifuge the 1.5
ml microcentrifuge tube to remove drops from inside the lid. It is
essential that the sample, Buffer AL, and the ethanol are mixed
thoroughly to yield a homogeneous solution. A white precipitate may
form on addition of ethanol. It is desirable to apply all of the
precipitate to the QIAamp Mini spin column. This precipitate does
not interfere with the QIAamp procedure or with any subsequent
application. Use alcohols other than ethanol may result in reduced
yields.
[0519] 7. Carefully apply the mixture from step 6 (including the
precipitate) to the QIAamp Mini spin column (in a 2 ml collection
tube) without wetting the rim. Close the cap, and centrifuge at
6000.times.g (8000 rpm) for 1 min. Place the QIAamp Mini spin
column in a clean 2 ml collection tube, and discard the tube
containing the filtrate. Close each spin column to avoid aerosol
formation during centrifugation. It is desirable to apply all of
the precipitate to the QIAamp Mini spin column. Centrifugation is
performed at 6000.times.g (8000 rpm) in order to reduce noise.
Centrifugation at full speed will not affect the yield or purity of
the DNA. If the solution has not completely passed through the
membrane, centrifuge again at a higher speed until all the solution
has passed through.
[0520] 8. Carefully open the QIAamp Mini spin column and add 500
.mu.l Buffer AW1 without wetting the rim. Close the cap, and
centrifuge at 6000.times.g (8000 rpm) for 1 min. Place the QIAamp
Mini spin column in a clean 2 ml collection tube, and discard the
collection tube containing the filtrate.
[0521] 9. Carefully open the QIAamp Mini spin column and add 500
.mu.l Buffer AW2 without wetting the rim. Close the cap and
centrifuge at full speed (20,000.times.g; 14,000 rpm) for 3
min.
[0522] 10. Recommended: Place the QIAamp Mini spin column in a new
2 ml collection tube and discard the old collection tube with the
filtrate. Centrifuge at full speed for 1 min. This step helps to
eliminate the chance of possible Buffer AW2 carryover.
[0523] 11. Place the QIAamp Mini spin column in a clean 1.5 ml
microcentrifuge tube, and discard the collection tube containing
the filtrate. Carefully open the QIAamp Mini spin column and add
200 .mu.l Buffer AE or distilled water. Incubate at room
temperature for 1 min, and then centrifuge at 6000.times.g (8000
rpm) for 1 min.
[0524] 12. Repeat step 11. A 5 min incubation of the QIAamp Mini
spin column loaded with Buffer AE or water, before centrifugation,
generally increases DNA yield. A third elution step with a further
200 .mu.l Buffer AE will increase yields by up to 15%. Volumes of
more than 200 .mu.l should not be eluted into a 1.5 ml
microcentrifuge tube because the spin column will come into contact
with the eluate, leading to possible aerosol formation during
centrifugation. Elution with volumes of less than 200 .mu.l
increases the final DNA concentration in the eluate significantly,
but slightly reduces the overall DNA yield. Eluting with
4.times.100 .mu.l instead of 2.times.200 .mu.l does not increase
elution efficiency. For long-term storage of DNA, eluting in Buffer
AE and placing at .about.20.degree. C. is recommended, since DNA
stored in water is subject to acid hydrolysis. Yields of DNA can
depend both on the amount and the type of tissue processed. 25 mg
of tissue can yield approximately 10-30 .mu.g of DNA in 400 .mu.l
of water (25-75 ng/.mu.l), with an A.sub.260/A.sub.280 ratio of
1.7-1.9.
Example 3
DNA Purification from Blood with the QIAamp.RTM. DNA Mini Kit
[0525] DNA can be purified from blood using the QIAamp.RTM. DNA
Mini Kit (QIAGEN, Germantown, Md.).
[0526] This protocol can be for purification of total (genomic,
mitochondrial, and viral) DNA from whole blood, plasma, serum,
buffy coat, lymphocytes, and body fluids using a
microcentrifuge.
[0527] Important points before starting: [0528] All centrifugation
steps are carried out at room temperature (.about.15-25.degree.
C.). [0529] Use carrier DNA if the sample contains <10,000
genome equivalents. [0530] 200 .mu.l of whole blood yields 3-12
.mu.g of DNA. Preparation of buffy coat is recommended if a higher
yield is desired.
[0531] Things to do before starting: [0532] Equilibrate samples to
room temperature. [0533] Heat a water bath or heating block to
56.degree. C. for use in step 4. [0534] Equilibrate Buffer AE or
distilled water to room temperature for elution in step 11. [0535]
Ensure that Buffer AW1, Buffer AW2, and QIAGEN Protease have been
prepared. [0536] If a precipitate has formed in Buffer AL, dissolve
by incubating at 56.degree. C.
Exemplary Procedure
[0537] 1. Pipet 20 .mu.l QIAGEN Protease (or proteinase K) into the
bottom of a 1.5 ml microcentrifuge tube.
[0538] 2. Add 200 .mu.l sample to the microcentrifuge tube. Use up
to 200 .mu.l whole blood, plasma, serum, buffy coat, or body
fluids, or up to 5.times.106 lymphocytes in 200 .mu.l PBS. If the
sample volume is less than 200 .mu.l, add the appropriate volume of
PBS. QIAamp Mini spin columns copurify RNA and DNA when both are
present in the sample. RNA may inhibit some downstream enzymatic
reactions, but not PCR. If RNA-free genomic DNA is desired, 4 .mu.l
of an RNase A stock solution (100 mg/ml) should be added to the
sample before addition of Buffer AL. Note: It is possible to add
QIAGEN Protease (or proteinase K) to samples that have already been
dispensed into microcentrifuge tubes. In this case, it is desirable
to ensure proper mixing after adding the enzyme.
[0539] 3. Add 200 .mu.l Buffer AL to the sample. Mix by
pulse-vortexing for 15 s. In order to ensure efficient lysis, it is
desirable that the sample and Buffer AL are mixed thoroughly to
yield a homogeneous solution. If the sample volume is larger than
200 .mu.L, increase the amount of QIAGEN Protease (or proteinase K)
and Buffer AL proportionally; for example, a 400 .mu.l sample will
use 40 .mu.l QIAGEN Protease (or proteinase K) and 400 .mu.l Buffer
AL. If sample volumes larger than 400 .mu.l are desired, use of
QIAamp DNA Blood Midi or Maxi Kits is recommended; these can
process up to 2 ml or up to 10 ml of sample, respectively. Note: Do
not add QIAGEN Protease or proteinase K directly to Buffer AL.
[0540] 4. Incubate at .about.56.degree. C. for .about.10 min. DNA
yield reaches a maximum after lysis for .about.10 min at
.about.56.degree. C. Longer incubation times have may no effect on
yield or quality of the purified DNA.
[0541] 5. Briefly centrifuge the 1.5 ml microcentrifuge tube to
remove drops from the inside of the lid.
[0542] 6. Add 200 .mu.l ethanol (96-100%) to the sample, and mix
again by pulse-vortexing for 15 s. After mixing, briefly centrifuge
the 1.5 ml microcentrifuge tube to remove drops from the inside of
the lid. If the sample volume is greater than 200 .mu.l, increase
the amount of ethanol proportionally; for example, a 400 .mu.l
sample can use 400 .mu.l of ethanol.
[0543] 7. Carefully apply the mixture from step 6 to the QIAamp
Mini spin column (in a 2 ml collection tube) without wetting the
rim. Close the cap, and centrifuge at 6000.times.g (8000 rpm) for 1
min. Place the QIAamp Mini spin column in a clean 2 ml collection
tube, and discard the tube containing the filtrate. Close each spin
column in order to avoid aerosol formation during centrifugation.
Centrifugation is performed at 6000.times.g (8000 rpm) in order to
reduce noise. Centrifugation at full speed will not affect the
yield or purity of the DNA. If the lysate has not completely passed
through the column after centrifugation, centrifuge again at higher
speed until the QIAamp Mini spin column is empty. Note: When
preparing DNA from buffy coat or lymphocytes, centrifugation at
full speed is recommended to avoid clogging.
[0544] 8. Carefully open the QIAamp Mini spin column and add 500
.mu.l Buffer AW1 without wetting the rim. Close the cap and
centrifuge at 6000.times.g (8000 rpm) for 1 min. Place the QIAamp
Mini spin column in a clean 2 ml collection tube, and discard the
collection tube containing the filtrate. It is not necessary to
increase the volume of Buffer AW1 if the original sample volume is
larger than 200 .mu.l.
[0545] 9. Carefully open the QIAamp Mini spin column and add 500
.mu.l Buffer AW2 without wetting the rim. Close the cap and
centrifuge at full speed (20,000.times.g; 14,000 rpm) for 3
min.
[0546] 10. Recommended: Place the QIAamp Mini spin column in a new
2 ml collection tube and discard the old collection tube with the
filtrate. Centrifuge at full speed for 1 min. This step helps to
eliminate the chance of possible Buffer AW2 carryover.
[0547] 11. Place the QIAamp Mini spin column in a clean 1.5 ml
microcentrifuge tube, and discard the collection tube containing
the filtrate. Carefully open the QIAamp Mini spin column and add
200 .mu.l Buffer AE or distilled water. Incubate at room
temperature (15-25.degree. C.) for 1 min, and then centrifuge at
6000.times.g (8000 rpm) for 1 min. Incubating the QIAamp Mini spin
column loaded with Buffer AE or water for 5 min at room temperature
before centrifugation generally increases DNA yield. A second
elution step with a further 200 .mu.l Buffer AE will increase
yields by up to 15%. Volumes of more than 200 .mu.l should not be
eluted into a 1.5 ml microcentrifuge tube because the spin column
will come into contact with the eluate, leading to possible aerosol
formation during centrifugation. Elution with volumes of less than
200 .mu.l increases the final DNA concentration in the eluate
significantly, but slightly reduces the overall DNA yield. For
samples containing less than 1 .mu.g of DNA, elution in 50 .mu.l
Buffer AE or water is recommended. Eluting with 2.times.100 .mu.l
instead of 1.times.200 .mu.l does not increase elution efficiency.
For long-term storage of DNA, eluting in Buffer AE and storing at
.about.20.degree. C. is recommended, since DNA stored in water is
subject to acid hydrolysis. A 200 .mu.l sample of whole human blood
(approximately 5.times.106 leukocytes/ml) typically yields 6 .mu.g
of DNA in 200 .mu.l water (30 ng/.mu.l) with an A260/A280 ratio of
1.7-1.9.
Example 4
Amplification and Barcoding of Extracted DNA
[0548] PCR amplification reactions are set up for two 16S regions
per sample. Each sample is designated by its own DNA barcode. The
following reactions are generated for each sample including one
positive and one negative amplification control:
TABLE-US-00005 Region V1/2 Region V5/4 3.48 .mu.L dH2O 3.48 .mu.L
dH2O 5.00 .mu.L ENA 5.00 .mu.L ENA 0.26 .mu.L A_BarcodeX_V1/2_F
0.26 .mu.L A_BarcodeX_V5/4_F 0.26 .mu.L P1_V1/2_R 0.26 .mu.L
P1_V5/4_R 1.00 .mu.L Template DNA 1.00 .mu.L Template DNA
[0549] Note that in the above PCR reaction mixtures that ENA are
2'-O,4'-C-ethylene bridged nucleic acids; A_BarcodeX_V1/2_F and
A_BarcodeX_V5/4_F are forward primers; and P1_V.sub.--1/2_R and
P1_V5/4_R are reverse primers. The V1/2 primers are selected from
Table 4, and the V5/4 primers are selected from Table 5.
TABLE-US-00006 TABLE 4 Examples of V1/2 Primers. Barcodes are
underlined, and the 16S Variable Region Homology is in bold.
Forward Primer (Primer A-Barcode 1-V1/2) (SEQ ID NO: 35)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCTAAGGTAACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 2-V1/2) (SEQ ID NO: 36)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTAAGGAGAACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 3-V1/2) (SEQ ID NO: 37)
CCATCTCATCCCTGCGTGTCTCCGACTCAGAAGAGGATTCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 4-V1/2) (SEQ ID NO: 38)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTACCAAGATCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 5-V1/2) (SEQ ID NO: 39)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCAGAAGGAACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 6-V1/2) (SEQ ID NO: 40)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGCAAGTTCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 7-V1/2) (SEQ ID NO: 41)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCGTGATTCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 8-V1/2) (SEQ ID NO: 42)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCCGATAACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 9-V1/2) (SEQ ID NO: 43)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTGAGCGGAACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 10-V1/2) (SEQ ID NO: 44)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGACCGAACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 11-V1/2) (SEQ ID NO: 45)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCCTCGAATCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 12-V1/2) (SEQ ID NO: 46)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTAGGTGGTTCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 13-V1/2) (SEQ ID NO: 47)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAACGGACGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 14-V1/2) (SEQ ID NO: 48)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTTGGAGTGTCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 15-V1/2) (SEQ ID NO: 49)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAGAGGTCGATAGAGTTTGATCCTGGCTCAG
Forward Primer (Primer A-Barcode 16-V1/2) (SEQ ID NO: 50)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTGGATGACGATAGAGTTTGATCCTGGCTCAG
Reverse Primer (Primer P1-V1/2) (SEQ ID NO: 33)
CCTCTCTATGGGCAGTCGGTGATCTGCTGCCTYCCGTA
TABLE-US-00007 TABLE 5 Examples of V5/4 Primers. Barcodes are
underlined, and the 16S Variable Region Homology is in bold.
Forward Primer (Primer A-Barcode 1-V5/4) (SEQ ID NO: 51)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCTAAGGTAACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 2-V5/4) (SEQ ID NO: 52)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTAAGGAGAACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 3-V5/4) (SEQ ID NO: 53)
CCATCTCATCCCTGCGTGTCTCCGACTCAGAAGAGGATTCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 4-V5/4) (SEQ ID NO: 54)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTACCAAGATCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 5-V5/4) (SEQ ID NO: 55)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCAGAAGGAACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 6-V5/4) (SEQ ID NO: 56)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGCAAGTTCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 7-V5/4) (SEQ ID NO: 57)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCGTGATTCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 8-V5/4) (SEQ ID NO: 58)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCCGATAACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 9-V5/4) (SEQ ID NO: 59)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTGAGCGGAACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 10-V5/4) (SEQ ID NO: 60)
CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGACCGAACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 11-V5/4) (SEQ ID NO: 61)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCCTCGAATCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 12-V5/4) (SEQ ID NO: 62)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTAGGTGGTTCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 13-V5/4) (SEQ ID NO: 63)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAACGGACGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 14-V5/4) (SEQ ID NO: 64)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTTGGAGTGTCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 15-V5/4) (SEQ ID NO: 65)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAGAGGTCGATCCGTCAATTYYTTTRAGTTT
Forward Primer (Primer A-Barcode 16-V5/4) (SEQ ID NO: 66)
CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTGGATGACGATCCGTCAATTYYTTTRAGTTT
Reverse Primer (Primer P1-V5/4) (SEQ ID NO: 34)
CCTCTCTATGGGCAGTCGGTGATAYTGGGYDTAAAGNG
[0550] The PCR is then run with the Thermocycler set to the
following conditions:
TABLE-US-00008 Step# Temp. Time Notes 1) 96.degree. C. 1 minute 2)
96.degree. C. 20 seconds 3) 42.degree. C. 30 seconds 4) 72.degree.
C. 30 seconds 5) -- -- Repeat 2-4 40x 6) 4.degree. C.
Indefinitely
Example 5
Purification of DNA from PCR Reactions
[0551] After barcoding and amplification of the extracted DNA, the
resulting DNA reactions are purified to remove extraneous DNA
sequences that are not the targets for sequencing with standard gel
electrophoresis and gel extraction. Gel extraction is performed
using the QiaPrep Gel Extraction Mini kit (QIAGEN, Germantown,
Md.).
Example 6
IonSphere Particle Labeling
[0552] All purified DNA samples from the PCR reactions are pooled
together in equimolar ratios determined by NanoDrop (Thermo
Scientific, Wilmington, Del.) and the known DNA fragment sizes. The
pooled library is diluted to precisely 0.08 .mu.M and used as the
DNA template for the OneTouch IonSphere Particle Labeling protocol
as listed in the Ion OneTouch 200 Template Kit v2 DL (Pub#
MAN0007112, Revision: 5.0) in conjunction with the Ion OneTouch 200
Template Kit v2 DL kit.
[0553] The OneTouch IonSphere Particle (ISP) Labeling protocol is
followed with a few modifications to the "Add Ion OneTouch Reaction
Oil" loading step and the "Recover the Template-Positive ISPs"
step. The changes are as follows:
[0554] Add Ion OneTouch Reaction Oil
[0555] Add Ion OneTouch.TM. Reaction Oil through the sample port:
[0556] a. Set a P1000 pipette to 750 .mu.L, and attach a new
1000-.mu.L tip to the pipette. [0557] b. Fill the tip with 750
.mu.L of Reaction Oil. [0558] c. Insert the tip firmly into the
sample port so that the tip is perpendicular to the Ion
OneTouch.TM. Plus Reaction Filter Assembly and fully inserted into
the sample port to form a tight seal. [0559] d. Gently pipet 750
.mu.L of the Reaction Oil through the sample port. Keep the plunger
of the pipette depressed to avoid aspirating solution from the Ion
PGM.TM. OneTouch Plus Reaction Filter Assembly. [0560] e. With the
plunger still depressed, remove the tip from the sample port, then
appropriately discard the tip. [0561] f. Set the P1000 pipette to
750 .mu.L, and attach a new 1000-.mu.L tip to the pipette. [0562]
g. Fill the tip with 750 .mu.L of Reaction Oil. [0563] h. Insert
the tip firmly into the sample port so that the tip is
perpendicular to the Ion OneTouch.TM. Plus Reaction Filter Assembly
and fully inserted into the sample port to form a tight seal.
[0564] i. Gently pipet 750 .mu.L of the Reaction Oil through the
sample port, then keep the plunger of the pipette depressed. [0565]
j. With the plunger still depressed, remove the tip from the sample
port, then appropriately discard the tip. [0566] k. If desired,
gently dab a Kimwipes.RTM. disposable wiper around the ports to
remove any liquid.
[0567] Recover the Template-Positive ISPs [0568] 1. At the end of
the run, ensure that you centrifuged the samples. (Ensure that you
have touched Next on the Centrifuge screen to centrifuge the
samples and that the home screen displays after the
centrifugation.) [0569] 2. Immediately after the centrifuge stops,
remove and discard the Recovery Router. [0570] 3. Carefully remove
both Recovery Tubes from the instrument, and put the two Recovery
Tubes in a tube rack. You may see some cloudiness in the tube,
which is normal. [0571] 4. Label a new 1.5-mL LoBind Tube for the
template-positive ISPs. [0572] 5. Use a pipette to remove all but
.about.100 .mu.L of Ion OneTouch.TM. Recovery Solution from each
Ion OneTouch.TM. Recovery Tube. Do not disturb the pellet of
template-positive ISPs. [0573] 6. Add 1 mL of Ion OneTouch Wash
solution to one Recovery Tube with the ISP pellet and resuspend the
pellet by gently pipetting up and down. [0574] 7. Transfer the Ion
OneTouch Wash solution and resuspended ISPs to the other Recovery
Tube and resuspend the pellet by gently pipetting up and down.
[0575] 8. Transfer the .about.1.2 mL suspension to the new labeled
tube.
[0576] Stopping Point: The template-positive ISPs with Ion
OneTouch.TM. Wash Solution may be stored at 2.degree. C. to
8.degree. C. for up to 3 days. After storage, proceed to step 10.
[0577] Do not store the recovered ISPs in Ion OneTouch.TM. Recovery
Solution. [0578] 9. Centrifuge the template-positive ISP suspension
for 2.5 minutes at 15,500.times.g. [0579] 10. Remove all but 100
.mu.L of supernatant. [0580] 11. Vortex the pellet for 30 seconds
to completely resuspend the template-positive ISPs. [0581] 12.
(Optional) Assess the quality of the unenriched, template-positive
ISPs. [0582] 13. Enrich the template-positive ISPs.
Example 7
IonSphere Particle Enrichment and DNA Sequencing IonSphere Particle
Enrichment
[0583] The IonSphere Particle Enrichment protocol is performed as
listed in the Ion OneTouch 200 Template Kit v2 DL (Pub# MAN0007112,
Revision: 5.0) in conjunction with the Ion OneTouch 200 Template
Kit v2 DL kit (Life Technologies, Carlsbad, Calif.).
DNA Sequencing
[0584] The DNA Sequencing protocol is performed as listed in the
Ion PGM Sequencing Kit manuals for the appropriate sequencing
length kit in conjunction with the Ion PGM Sequencing Kits. The
only variation to the protocol is a modification of the total flow
cycle numbers whereby the total flow cycle number is increased by
80 flows above the kit specifications.
Example 8
Computer-Based Genomic Analysis
[0585] Once sequencing is complete, individually barcoded sequence
sets may be downloaded from the Ion Torrent Browser interface.
These are imported as FASTQ files into CLC Workbench. Each sequence
set is then preferably processed according to the following
steps:
[0586] 1. Sequences of a specific barcode are length selected and
only 100 bp length sequences or greater are retained.
[0587] 2. These sequences are BLASTed against a local 16S database
of known, named, and non-redundant Eubacteria.
[0588] 3. The resulting BLAST results are size sorted.
[0589] 4. A size cut-off is selected for each BLAST results based
on three factors. [0590] a. Distribution of the reads obtained for
that given barcode and the first "cluster" of sequence read lengths
is selected with the cut-off as high as possible to include this
sequence cluster. [0591] b. If no cluster of sequences is apparent
then approximately 100 of the longest sequences are selected for
reporting. [0592] c. Sequences less than 100 bp are not used for
reporting.
[0593] 5. The following statistical information is reported based
on the provided cut-off values: [0594] a. >100 bp--The species
for an individual sequence read is correctly identified greater
than 10% of the time. [0595] b. >150 bp--The species for an
individual sequence read is correctly identified greater than 15%
of the time. [0596] c. >175 bp--The species for an individual
sequence read is correctly identified greater than 25% of the time.
[0597] d. >250 bp--The species for an individual sequence read
is correctly identified greater than 30% of the time. [0598] e.
>300 bp--The species for an individual sequence read is
correctly identified greater than 35% of the time. [0599] f.
>355 bp--The species for an individual sequence read is
correctly identified greater than 95% of the time.
[0600] 6. Repeat positive results increased the chances of a
correctly called sample. Therefore, sequences are only reported if
they comprise >1% of the total identified sequence reads and are
represented by >5 sequences in total. In this case a sample
comprising 1% of a total sequence read with a cut-off at 100 bp
would have much less than a 1% chance (All 5 wrong out of 100,000
chances=0.005%) of incorrectly identifying the species as an
aggregate. Often times there are hundreds or thousands of sequences
that identify the same species, thus it is a statistical certainty
that the species are correctly identified on the highest ends of
the reporting ranges.
[0601] 7. A report is generated that graphically displays the
proportion of the top 6 or less species identified. A table is also
provided that lists the sequence counts and relative percentages of
all significant sequences (>1% contribution and 5 or more
sequences). Treatment resistance information is provided for each
identified genus including scientific and medical references
containing that information.
Example 9
Pan-Bacterial Metagenomics Analysis No. 1
[0602] A dental sample from a patient was processed to extract the
nucleic acids, prepare an ion amplicon library, purify the ion
amplicon library, sequence the 16S rRNA in the library, and
identify the species of microorganisms present in the biological
sample with a computer-based genomic analysis using the procedures
described in Examples 1-8. PCR primers were selected from those
listed in Tables 4 and 5.
[0603] Sequence Information: 365,254 sequence reads were obtained
for the given sample. The longest 252 sequences were analyzed and
compared to all available prokaryotic species.
[0604] Results Confidence Profile (355): At the provided quality
control cut-off it is estimated that >95% of the sequence reads
correctly list the genus, while >95% of the sequence reads
correctly list the species.
[0605] The identified species are shown in Table 6 and FIG. 4.
TABLE-US-00009 TABLE 6 Species identified by computer-based
genomics analysis Number of Species Sequences % Prevotella oralis
46 18% Prevotella nigrescens 40 16% Prevotella oris 23 9%
Selenomonas infelix 23 9% Porphyromonas endodontalis 17 7%
Prevotella multiformis 13 5% Fusobacterium nucleatum 12 5%
Selenomonas sputigena 12 5% Prevotella intermedia 10 4% Prevotella
dentalis 8 3% Prevotella oulorum 6 2%
[0606] The antibiotic susceptibility was determined and reported
based on the genera identified with the computer-based genomic
analysis. The results are shown in Table 7.
TABLE-US-00010 TABLE 7 Antibiotic susceptibilities Description
Genus Antibiotics Noted Resistance Prevotella oralis Metronidazole,
Metronidazole, amoxicillin, amoxycillin/clavulanate,
amoxycillin/clavulanate, doxycycline, ureidopenicilins,
ureidopenicilins, carbapenems, carbapenems, cephalosporins,
cephalosporins, clindamycin, clindamycin, and clarithromycin,
chloramphenicol, chloramphenicol. moxifloxacin, and levofloxacin.
Prevotella nigrescens Refer to Prevotella oralis. Refer to
Prevotella oralis. Prevotella oris Refer to Prevotella oralis.
Refer to Prevotella oralis. Selenomonas infelix Azithromycin.
Erythromycin. Porphyromonas Penicillins (ampicillin, Unknown
endodontalis amoxicillin, ticarcillin), cephaloridine, cephalothin,
cefamandole, cefotaxime, cefoxitin, cefuroxime, imipenem,
piperacillin, erythromycin, oleandomycin, spiramycin, clindamycin,
tetracycline, metronidazole, azithromycin, and doxycycline.
Prevotella multiformis Refer to Prevotella oralis. Refer to
Prevotella oralis.
Prevotella Species:
[0607] Antibiotics: Antibiotic susceptibility varies among
Prevotella species. Antibiotics used to treat Prevotella infections
include: metronidazole, amoxycillin/clavulanate, doxycycline,
ureidopenicilins, carbapenems, cephalosporins, clindamycin, and
chloramphenicol. Resistance: Resistance to metronidazole,
amoxicillin, amoxycillin/clavulanate, ureidopenicilins,
carbapenems, cephalosporins, clindamycin, clarithromycin,
chloramphenicol, moxifloxacin, and levofloxacin have been
reported.
References:
[0608] Flynn, M. J., Li, G., Slots, J. (1994). Mitsuokella dentalis
in human periodontitis. Oral Microbiol. Immunol. 9, 248-250. [0609]
Mosca A, Miragliotta L, Iodice M A, et al. Antimicrobial profiles
of Prevotella spp. and Fusobacterium nucleatum isolated form
periodontal infections in a selected area of southern Italy. Int J
of Antimicro Agents December 2007; 30(6):521-4. [0610] Shah, H. N.,
Collins, D. M. (1990). Prevotella, a new genus to include
Bacteroides melaminogenicus and related species formerly classified
in the genus Bacterioides. Int. J. syst. Bacteriol. 40,
205-208.
Selenomonas Species:
[0611] Antibiotics: Active antibiotics include: Azithromycin.
Resistance: Inactive antibiotics: Erythromycin.
References:
[0612] Comparative in-vitro activity of azithromycin, macrolides
(erythromycin, clarithromycin and spiramycin) and streptogramin RP
59500 against oral organisms. Williams, J. D., Maskell, J. P.,
Shain, H., Chrysos, G., Sefton, A. M., Fraser, H. Y., Hardie, J. M.
J. Antimicrob. Chemother. (1992).
Porphyromonas Species:
[0613] Antibiotics: Antibiotic susceptibility varies among
Porphyromonas species. Antibiotics used to treat Peptostreptococcus
infections include: Penicillins (ampicillin, amoxicillin,
ticarcillin), cephaloridine, cephalothin, cefamandole, cefotaxime,
cefoxitin, cefuroxime, imipenem, piperacillin, erythromycin,
oleandomycin, spiramycin, clindamycin, tetracycline, metronidazole,
azithromycin, and doxycycline. Resistance: Resistance to
antibiotics has not been reported to a significant degree.
References:
[0614] Andres M T, Chung W O, Roberts M C, and Fierro J F.
Antimicrobial susceptibilities of Porphyromonas gingivalis,
Prevotella intermedia, and Prevotella nigrescens spp. Isolated in
Spain. Antimicrob Agents Chemoth. November 1998; 42(11):3022-3.
[0615] Japoni A, Vazin A, Noushadi S, Kiany F, et al. Antibacterial
susceptibility patterns of Porphyromonas gingivalis isolated from
chronic periodontitis patients. November 2011; 16(7):e1031-5.
[0616] Kulik E M, Lenkeit K, Chenaux S, and Meyer J. Antimicrobial
susceptibility of periodontopathogenic bacteria. J Antimicrob
Chemother March 2008; 61(5): 1087-91. [0617] Pajukanta R, Asikainen
S, Forsblom B, Saarela M, Jousimies-Somer H. .beta.-Lactamase
production and in vitro antimicrobial susceptibility of
Porphyromonas gingivalis. FEMS Immunol Med. Microbiol. 1993;
6:241-244.
Fusobacterium Species:
[0618] Antibiotics: Antibiotic susceptibility varies among
Fusobacterium species. Treatment of Fusobacterium infections
depends on the site of infections. Antibiotics used to treat
Fusobacterium infections include: Metronidazole,
piperacillin/tazobactum, ticarcillin/clavulanate,
amoxicillin/sulbactum, ampicillin/sulbactum, ertupenem, imipenem,
meropenem, clindamycin, and cefoxitin. Resistance: Some
resistantance to penicillin noted with widespread resistance to
erythromycin and other macrolides.
References:
[0619] Citron, D. M., Poxton, I. R., & Baron, E. J. (2007).
Bacteroides, Porphyromonas, Prevotella, Fusobacterium, and Other
Anaerobic Gram-Negative Rods. In P. R. Murray, E. J. Baron, M. L.
Landry, J. H. Jorgensen & M. A. Pfaller (Eds.), Manual of
Clinical Microbiology (9th ed., pp. 911-932). Washington, D.C.: ASM
Press. [0620] Riordan, T. (2007). Human infection with
Fusobacterium necrophorum (Necrobacillosis), with a focus on
Lemierre's syndrome. Clinical Microbiology Reviews, 20(4), 622-659.
doi:10.1128/CMR.00011-07. [0621] Boyanova, L., Kolarov, R., &
Mitov, I. (2007). Antimicrobial resistance and the management of
anaerobic infections. Expert Review of Anti-Infective Therapy,
5(4), 685-701.
Example 10
Pan-Bacterial Metagenomics Analysis No. 2
[0622] A dental sample from a patient was processed to extract the
nucleic acids, prepare an ion amplicon library, purify the ion
amplicon library, sequence the 16S rRNA in the library, and
identify the species of microorganisms present in the biological
sample with a computer-based genomic analysis using the procedures
described in Examples 1-8. PCR primers were selected from those
listed in Tables 4 and 5.
[0623] Sequence Information: 177,821 sequence reads were obtained
for the given sample. The longest 285 sequences were analyzed and
compared to all available prokaryotic species.
[0624] Results Confidence Profile (355): At the provided quality
control cut-off it is estimated that >95% of the sequence reads
correctly list the genus, while >95% of the sequence reads
correctly list the species.
[0625] The identified species are shown in Table 8 and FIG. 5.
TABLE-US-00011 TABLE 8 Species identified by computer-based
genomics analysis Number of Species Sequences % Capnocytophaga
gingivalis 56 20% Prevotella oris 55 19% Gemella sanguinis 53 19%
Neisseria bacilliformis 37 13% Leptotrichia shahii 22 8% Prevotella
oulorum 10 4% Selenomonas infelix 8 3% Alysiella filiformis 5 2%
Streptococcus intermedius 5 2%
[0626] The antibiotic susceptibility was determined and reported
based on the genera identified with the computer-based genomic
analysis. The results are shown in Table 9.
TABLE-US-00012 TABLE 9 Antibiotic susceptibilities Description
Genus Antibiotics Noted Resistance Capnocytophaga Penicillin G,
ampicillin, third Gentamycin and Penicillin G. gingivalis
generation cephalosporins, tetracyclines, clindamycin, and
chloromphenicol Prevotella oris Metronidazole, Metronidazole,
amoxicillin, amoxycillin/clavulanate, amoxycillin/clavulanate,
doxycycline, ureidopenicilins, ureidopenicilins, carbapenems,
carbapenems, cephalosporins, cephalosporins, clindamycin,
clindamycin, and clarithromycin, chloramphenicol, chloramphenicol.
moxifloxacin, and levofloxacin Gemella sanguinis Penicillin,
ampicillin, Sulfonamides and trimethoprim, cephalosporins,
tetracyclines, and aminoglycosides. chloramphenicol, lincomycins
and tetrasulfathiazole. Neisseria bacilliformis Cefotaxime and
ceftriaxone Penicillin Leptotrichia shahii Unknown Unknown
Prevotella oulorum Metronidazole, Metronidazole, amoxicillin,
amoxycillin/clavulanate, amoxycillin/clavulanate, doxycycline,
ureidopenicilins, ureidopenicilins, carbapenems, carbapenems,
cephalosporins, cephalosporins, clindamycin, clindamycin, and
chloramphenicol clarithromycin, chloramphenicol, moxifloxacin, and
levofloxacin.
Capnocytophaa Species:
[0627] Antibiotics: Capnocytophaga is susceptible to penicillin G,
ampicillin, third generation cephalosporins, tetracyclines,
clindamycin, and chloromphenicol. Resistance: Species has shown
resistance to gentamycin and penicillin G in some cases.
References:
[0628] Brenner D J, Hollis D G, Fanning G R, and Weaver R E. 1989.
Capnocytophaga canimorsus sp. nov. (Formerly CDC Group DF-2), a
Cause of Septicemia following Dog Bite, and C. cynodegmi sp. nov.,
a Cause of Localized Wound Infection following Dog Bite. Journal of
Clinical Microbiology 27 (2): 231-235. [0629] Lion C, Escande F and
Burdin J C. 1996. Capnocytophaga canimorsus Infections in Human:
Review of the Literature and Cases Report. European Journal of
Epidemiology 12 (5): 521-533.
Prevotella Species:
[0630] Antibiotics: Antibiotic susceptibility varies among
Prevotella species. Antibiotics used to treat Prevotella infections
include: metronidazole, amoxycillin/clavulanate, doxycycline,
ureidopenicilins, carbapenems, cephalosporins, clindamycin, and
chloramphenicol. Resistance: Resistance to metronidazole,
amoxicillin, amoxycillin/clavulanate, ureidopenicilins,
carbapenems, cephalosporins, clindamycin, clarithromycin,
chloramphenicol, moxifloxacin, and levofloxacin have been
reported.
References:
[0631] Flynn, M. J., Li, G., Slots, J. (1994). Mitsuokella dentalis
in human periodontitis. Oral Microbiol. Immunol. 9, 248-250. [0632]
Mosca A, Miragliotta L, Iodice M A, et al. Antimicrobial profiles
of Prevotella spp. and Fusobacterium nucleatum isolated form
periodontal infections in a selected area of southern Italy. Int J
of Antimicro Agents December 2007; 30(6):521-4. [0633] Shah, H. N.,
Collins, D. M. (1990). Prevotella, a new genus to include
Bacteroides melaminogenicus and related species formerly classified
in the genus Bacterioides. Int. J. syst. Bacteriol. 40,
205-208.
Gemella Species:
[0634] Antibiotics: Active antibiotics include: penicillin,
ampicillin, cephalosporins, tetracyclines, chloramphenicol,
lincomycins and tetrasulfathiazole. Resistance: Inactive
antibiotics include: sulfonamides and trimethoprim, and
aminoglycosides.
References:
[0635] Collins, M. D. (2006). The Genus Gemella. In M. Dworkin, S.
Falkow, E. Rosenberg, K. H. Schleifer & E. Stackebrandt (Eds.),
The Prokaryotes (3rd ed., pp. 511-518). New York: Springer. [0636]
Collins, M. D. (2006). The Genus Gemella. In M. Dworkin, S. Falkow,
E. Rosenberg, K. H. Schleifer & E. Stackebrandt (Eds.), The
Prokaryotes (3rd ed., pp. 511-518). New York: Springer. [0637]
Buu-Hoi, A., Sapoetra, A., Branger, C., & Acar, J. F. (1982).
Antimicrobial susceptibility of Gemella haemolysans isolated from
patients with subacute endocarditis. European Journal of Clinical
Microbiology, 1(2), 102-106. [0638] Hamrah, P., Ritterband, D.,
Seedor, J., & Eiferman, R. A. (2006). Ocular infection
secondary to gemella. Graefe's Archive for Clinical and
Experimental Ophthalmology=Albrecht Von Graefes Archiv Fur
Klinische Und Experimentelle Ophthalmologic, 244(7), 891-892.
Neisseria Species:
[0639] Antibiotics: Active antibiotics for Neisseria include
third-generation cephalosporin antibiotics such as cefotaxime and
ceftriaxone. Resistance: Some species have been shown to be
resistant to the penicillin family of antibiotics.
References:
[0640] Tunkel A R, Hartman B J, Kaplan S L, Kaufman B A, Roos K L,
Scheld W M, Whitley R J (November 2004). "Practice guidelines for
the management of bacterial meningitis". Clin Infect Dis 39 (9):
1267-84. "UK doctors advised gonorrhoea has turned drug resistant
BBC News. 10 Oct. 2011.
Leptotrichia Species:
[0641] Antibiotics: Antibiotic susceptibility for Leptotrichia has
not been extensively studied. Resistance: Antibiotic resistance for
Leptotrichia has not been extensively studied.
References:
[0642] Eribe E R, Paster B J, Caugant D A, Dewhirst F E, Stromberg
V K, Lacy G H, Olsen I. Genetic diversity of Leptotrichia and
description of Leptotrichia goodfellowii sp. nov., Leptotrichia
hofstadii sp. nov., Leptotrichia shahii sp. nov. and Leptotrichia
wadei sp. November Institute of Oral Biology, Dental Faculty,
University of Oslo, POB 1052, Blindern, N-0316 Oslo, Norway.
Prevotella Species:
[0643] Antibiotics: Antibiotic susceptibility varies among
Prevotella species. Antibiotics used to treat Prevotella infections
include: metronidazole, amoxycillin/clavulanate, doxycycline,
ureidopenicilins, carbapenems, cephalosporins, clindamycin, and
chloramphenicol. Resistance: Resistance to metronidazole,
amoxicillin, amoxycillin/clavulanate, ureidopenicilins,
carbapenems, cephalosporins, clindamycin, clarithromycin,
chloramphenicol, moxifloxacin, and levofloxacin have been
reported.
References:
[0644] Flynn, M. J., Li, G., Slots, J. (1994). Mitsuokella dentalis
in human periodontitis. Oral Microbiol. Immunol. 9, 248-250. [0645]
Mosca A, Miragliotta L, Iodice M A, et al. Antimicrobial profiles
of Prevotella spp. and Fusobacterium nucleatum isolated form
periodontal infections in a selected area of southern Italy. Int J
of Antimicro Agents December 2007; 30(6):521-4. [0646] Shah, H.N.,
Collins, D. M. (1990). Prevotella, a new genus to include
Bacteroides melaminogenicus and related species formerly classified
in the genus Bacterioides. Int. J.
Selenomonas Species:
[0647] Antibiotics: Active antibiotics include: Azithromycin.
Resistance: Inactive antibiotics: Erythromycin.
References:
[0648] Comparative in-vitro activity of azithromycin, macrolides
(erythromycin, clarithromycin and spiramycin) and streptogramin RP
59500 against oral organisms. Williams, J. D., Maskell, J. P.,
Shain, H., Chrysos, G., Sefton, A. M., Fraser, H. Y., Hardie, J. M.
J. Antimicrob. Chemother. (1992).
Alysiella Species:
[0649] Antibiotics: Antibiotic susceptibility for Alysiella has not
been extensively studied. Resistance: Antibiotic resistance for
Alysiella has not been extensively studied.
References:
[0650] Cheng-Hui Xie and Akira Yokota, Transfer of the misnamed
[Alysiella] sp. IAM 14971 (=ATCC 29468) to the genus Moraxella as
Moraxella oblonga sp. nov., International Journal of Systematic and
Evolutionary Microbiology, January 2005 Vol. 55 no. 1 331-334.
Streptococcus Species:
[0651] Antibiotics: Active antibiotics for Streptococcus include:
penicillin, amoxicillin, intramuscular benzathine pencicillin G,
erythromycin, clindamycin, cephalosporins, cephalexin, cefuroxime
axetil, and cefdinir. Resistance: Penicillin has been reported to
be ineffective in some cases. B-lactams and macrolides have been
reported as an inactive antibiotics.
References:
[0652] Hooton T M. A comparison of azithromycin and penicillin V
for the treatment of streptococcal pharyngitis. Am J. Med. 1991
Sep. 12; 91(3A):23S-26S.PubMed Cohen R, Reinert P, De La Rocque F,
Levy C, Boucherat M, Robert M, Navel M, Brahimi N, Deforche D,
Palestro B, Bingen E. Comparison of two dosages of azithromycin for
three days versus penicillin V for ten days in acute group A
streptococcal tonsillopharyngitis. Pediatr Infect Dis J. 2002
April; 21(4):297-303. [0653] Casey J R, Pichichero M E.
Meta-analysis of cephalosporin versus penicillin treatment of group
A streptococcal tonsillopharyngitis in children. Pediatrics. 2004
April; 113(4):866-82. [0654] Scholz H. Streptococcal-A
tonsillopharyngitis: a 5-day course of cefuroxime axetil versus a
10-day course of penicillin V. results depending on the children's
age. Chemotherapy. Baltimore RS (February 2010). "Re-evaluation of
antibiotic treatment of streptococcal pharyngitis". Curr. Opin.
Pediatr. 22 (1): 77-82. [0655] Shulman, S T; Bisno, A L; Clegg, H
W; Gerber, M A; Kaplan, E L; Lee, G; Martin, J M; Van Beneden, C
(2012 Sep. 9). "Clinical Practice Guideline for the Diagnosis and
Management of Group A Streptococcal Pharyngitis: 2012 Update by the
Infectious Diseases Society of America.". Clinical infectious
diseases: an official publication of the Infectious Diseases
Society of America. [0656] Choby B A (March 2009). "Diagnosis and
treatment of streptococcal pharyngitis". Am Fam Physician 79 (5):
383-90. [0657] Albrich, W; Monnet, D L; Harbarth, S (2004).
"Antibiotic selection pressure and resistance in Streptococcus
pneumoniae and Streptococcus pyogenes". Emerging Infect. Dis. 10
(3): 514-7. PMC 3322805. PMID 15109426.
Example 11
Pan-Bacterial Metagenomics Analysis No. 3
[0658] A dental sample from a patient was processed to extract the
nucleic acids, prepare an ion amplicon library, purify the ion
amplicon library, sequence the 16S rRNA in the library, and
identify the species of microorganisms present in the biological
sample with a computer-based genomic analysis using the procedures
described in Examples 1-8. PCR primers were selected from those
listed in Tables 4 and 5.
[0659] Sequence Information: 330,413 sequence reads were obtained
for the given sample. The longest 268 sequences were analyzed and
compared to all available prokaryotic species.
[0660] Results Confidence Profile (355): At the provided quality
control cut-off it is estimated that >95% of the sequence reads
correctly list the genus, while >95% of the sequence reads
correctly list the species.
[0661] The identified species are shown in Table 10 and in FIG.
6.
TABLE-US-00013 TABLE 10 Species identified by computer-based
genomics analysis Number of Species Sequences % Actinomyces
naeslundii 198 74% Neisseria lactamica 10 4% Streptococcus gordonii
10 4% Streptococcus mutans 9 3% Granulicatella adiacens 6 2%
Streptococcus infantis 6 2% Streptococcus oralis 6 2%
[0662] The antibiotic susceptibility was determined and reported
based on the genera identified with the computer-based genomic
analysis. The results are shown below and in Table 11.
TABLE-US-00014 TABLE 11 Antibiotic susceptibilities Description
Genus Antibiotics Noted Resistance Actinomyces Penicillin,
amoxicillin, Metronidazole, TMP-SMX, naeslundii doxycycline,
erythromycin, and ceftazidime, aminoglycosides, clindamycin. Other
agents having oxacillin, and fluoroquinolones. limited date
include: clarithromycin, azithromycin, imipenem, cefotaxime, and
ceftiaxone. Neisseria Cefotaxime and ceftriaxone. Penicillin
lactamica Streptococcus Penicillin, amoxicillin, Penicillin,
B-lactams, and gordonii intramuscular benzathine macrolides.
pencicillin G, erythromycin, clindamycin, cephalosporins,
cephalexin, cefuroxime axetil, and cefdinir. Streptococcus Refer to
Streptococcus mutans Refer to Streptococcus mutans mutans
Granulicatella Penicillin and ceftriaxone, Penicillin, cefotaxime,
and adiacens vancomycin. ampicillin, azithromycin. Resistance to
beta- ampicillin-sulbactam, lactam and macrolide antibiotics
amoxicillin-clavulanate, has been described. cefazolin,
cefinetazole, or meropenem. Streptococcus Refer to Streptococcus
mutans Refer to Streptococcus mutans infantis
Actinomyces Species:
[0663] Antibiotics: Active antibiotics for treatment of Actinomyces
include penicillin, amoxicillin, doxycycline, erythromycin, and
clindamycin. Other agents having limited date include:
clarithromycin, azithromycin, imipenem, cefotaxime, and ceftiaxone.
Resistance: Antibiotic resistance for Actinomyces include
metronidazole, TMP-SMX, ceftazidime, aminoglycosides, oxacillin,
and fluoroquinolones.
References:
[0664] Smith A J et al: Antimicrobial susceptibility testing of
Actinomyces species with 12 antimicrobial agents. J Antimicrob
Chemother 56:407, 2005.
Neisseria Species:
[0665] Antibiotics: Active antibiotics for Neisseria include
third-generation cephalosporin antibiotics such as cefotaxime and
ceftriaxone. Resistance: Some species have been shown to be
resistant to the penicillin family of antibiotics.
References:
[0666] Tunkel A R, Hartman B J, Kaplan S L, Kaufman B A, Roos K L,
Scheld W M, Whitley R J (November 2004). "Practice guidelines for
the management of bacterial meningitis". Clin Infect Dis 39 (9):
1267-84. "UK doctors advised gonorrhoea has turned drug resistant
BBC News. 10 Oct. 2011.
Streptococcus Species:
[0667] Antibiotics: Active antibiotics for Streptococcus include:
penicillin, amoxicillin, intramuscular benzathine pencicillin G,
erythromycin, clindamycin, cephalosporins, cephalexin, cefuroxime
axetil, and cefdinir. Resistance: Penicillin has been reported to
be ineffective in some cases. B-lactams and macrolides have been
reported as an inactive antibiotics.
References:
[0668] Hooton T M. A comparison of azithromycin and penicillin V
for the treatment of streptococcal pharyngitis. Am J. Med. 1991
Sep. 12; 91(3A):23S-26S.PubMed [0669] Cohen R, Reinert P, De La
Rocque F, Levy C, Boucherat M, Robert M, Navel M, Brahimi N,
Deforche D, Palestro B, Bingen E. Comparison of two dosages of
azithromycin for three days versus penicillin V for ten days in
acute group A streptococcal tonsillopharyngitis. Pediatr Infect Dis
J. 2002 April; 21(4):297-303. [0670] Casey J R, Pichichero M E.
Meta-analysis of cephalosporin versus penicillin treatment of group
A streptococcal tonsillopharyngitis in children. Pediatrics. 2004
April; 113(4):866-82. [0671] Scholz H. Streptococcal-A
tonsillopharyngitis: a 5-day course of cefuroxime axetil versus a
10-day course of penicillin V. results depending on the children's
age. Chemotherapy. [0672] Baltimore R S (February 2010).
"Re-evaluation of antibiotic treatment of streptococcal
pharyngitis". Curr. Opin. Pediatr. 22 (1): 77-82. [0673] Shulman, S
T; Bisno, A L; Clegg, H W; Gerber, M A; Kaplan, E L; Lee, G;
Martin, J M; Van Beneden, C (2012 Sep. 9). "Clinical Practice
Guideline for the Diagnosis and Management of Group A Streptococcal
Pharyngitis: 2012 Update by the Infectious Diseases Society of
America.". Clinical infectious diseases: an official publication of
the Infectious Diseases Society of America. [0674] Choby B A (March
2009). "Diagnosis and treatment of streptococcal pharyngitis". Am
Fam Physician 79 (5): 383-90. [0675] Albrich, W; Monnet, D L;
Harbarth, S (2004). "Antibiotic selection pressure and resistance
in Streptococcus pneumoniae and Streptococcus pyogenes". Emerging
Infect. Dis. 10 (3): 514-7. PMC 3322805. PMID 15109426.
Granulicatella Species:
[0676] Antibiotics: Active antibiotics against Granulicatella
species include: penicillin and ceftriaxone, vancomycin.
ampicillin, ampicillin-sulbactam, amoxicillin-clavulanate,
cefazolin, cefmetazole, or meropenem. Resistance: Inactive
antibiotics: penicillin, cefotaxime, and azithromycin. Resistance
to beta-lactam and macrolide antibiotics has been described.
References:
[0677] Sheng Kai Tung and Tsung Chain Chang, Molecular Detection of
Human Bacterial Pathogens, Edited by Dongyou Liu CRC Press 2011,
Pages 249-255. Levin, Yana D. MD; Petronaci, Carol-Lynn M D.
Isolation of Abiotrophia/Granulicatella Species from a Brain
Abscess in an Adult Patient Without Prior History of Neurosurgical
Instrumentation Southern Medical Journal: April 2010-Volume
103-Issue 4-pp 386-387. [0678] Chung-Hsin Liao, Lee-Jene Teng,
Po-Ren Hsuch, Yu-Chi Chen, Li-Min Huang, Shan-Chwen Chang, and
Shen-Wu Ho. Nutritionally Variant Streptococcal Infections at a
University Hospital in Taiwan: Disease Emergence and High
Prevalence of .beta.-Lactam and Macrolide Resistance. Oxford
Journals, Medicine Clinical Infectious Diseases, Volume 38, Issue
3Pp. 452-455. [0679] Jason C. Gardenier, Tjasa Hranjec, Robert G.
Sawyer, and Hugo Bonatti, Granulicatella adiacens Bacteremia in an
Elderly Trauma Patient. Surgical Infections Volume 12, Number 3,
2011.
Example 12
Analysis of 16S rRNA Variable Regions
[0680] The oligonucleotides tested were fusion oligonucleotides as
described herein. The oligonucleotides had primer sequences that
anneal to the indicated regions on the 16S gene, but they also
contain the adapter sequences to make them compatible with
sequencing.
[0681] An objective of this analysis was to identify important
factors for identification of bacteria via 16S sequencing. An equal
distribution across four 16S rRNA variable regions (V1/2, V3/2,
V3/4, and V5/4) was used to derive this data. The designation
"V1/2" indicates that the oligonucleotide allows for sequencing of
V1 in the direction of V2, the designation "V3/2" indicates that
the oligonucleotide allows for sequencing of V3 in the direction of
V2, etc. The fraction of the time that Ralstonia solanacearum was
correctly identified was plotted based on the length of the
obtained reads.
[0682] As can be seen in FIG. 7A, the longer reads resulted in more
accurate identification of the bacterial species. This analysis was
repeated with several other species and similar results were
obtained (data not shown). At read lengths of about 250 bp, the
accuracy of species identification approached 100% correct
identification. Thus, the length of the reads is one of the most
important factors to correctly identify a bacterial species. Future
selection processes were directly focused on obtaining the longest
reads and analyzing the longest reads available.
[0683] Also, as expected the number of sequences obtained at longer
sizes drop as well. FIG. 7B presents a compilation of cutoffs and
the percentage of the sequences in that category from seven
different runs.
[0684] Having identified the length of the reads as an important
factor for accurate identification of bacterial species based on
16S rRNA sequencing, the next objective of the analysis was to
determine which 16S variable region resulted in the longest read
lengths. As can be seen in Table 12, consistently regions V1/2 and
V5/4 produced the longest reads even when the total number of
sequences across two different barcodes varied by over double the
amount (85574 and 269817, respectively). Ultimately, the extra
basepairs translate into longer reads and more accurate
identifications.
TABLE-US-00015 TABLE 12 Average Read Length Obtained with
Oligonucleotides Targeting Specific 16S rRNA Variable Regions Total
Number Bar Code V1/2 V3/2 V3/4 V5/4 of Sequences BC005 155.23
144.86 137.70 162.94 85574 BC006 157.70 136.69 145.72 151.81
269817
[0685] These regions were also tested to see if the resulting
number of sequences skewed in any particular manner. It was found
that for many bacterial species regions V1/2 and V5/4 naturally
produced more useable sequences. Table 13 presents an example of
one of these analyses.
TABLE-US-00016 TABLE 13 Summary of the number of sequences 150 bp
or longer obtained from a sample of Bordatella persussis with the
Oligonucleotides Targeting Specific 16S rRNA Variable Regions
Library Bar Code V1/2 V3/2 V3/4 V5/4 Unknown Sum L6 BC003 32566
1631 74 66858 1808 102937 L6 BC004 46781 23247 337 45510 1791
117666 Library Bar Code V1/2 V3/2 V3/4 V5/4 Unknown L6 BC003 31.6%
1.6% 0.1% 65.0% 1.8% L6 BC004 39.8% 19.8% 0.3% 38.7% 1.5%
[0686] rRNA variable regions V1/2 and V5/4 were selected for
further analysis. Quite a few identification runs were performed
using these regions to confirm that they consistently provided
longer reads and more accurate genus and species identifications.
From this additional experimentation, it was determined that the
use of both regions (i.e., V1/2 and V5/4) is preferable because the
various bacteria were identified more accurately to the Genus and
Species level when both variable regions were sequenced and
analyzed (see Table 14). This effect can be seen amongst not only
the species tested but with the barcodes selected as well. Using
these parameters for bacterial identifications in the samples,
generally the genus was accurately identified greater than 95% of
the time and the species was accurately identified greater than 30%
of the time.
TABLE-US-00017 TABLE 14 Identification of bacterial genus and
species in control samples using oligonucleotides targeting the
V1/2 and V5/4 variable regions of the 16S rRNA. The percentages
shown indicate the level of accuracy achieved in correctly
identifying the bacterial genus and species in the sample. Genus
Level Species Level Region Region Region Region Barcode Control ID
% ID 1/2 5/4 % ID 1/2 5/4 011 Mycoplasma 98.94% 94.89% 5.11% 98.94%
94.89% 5.11% pneumoniae 010 Ralstonia 99.38% 75.70% 24.30% 75.22%
100.00% 0.00% solanacearum 005 Ralstonia 99.60% 69.17% 30.83%
68.82% 100.00% 0.00% solanacearum 005 Ralstonia 99.62% 77.45%
22.55% 77.15% 100.00% 0.00% solanacearum 007 Acholeplasma 99.74%
71.41% 28.59% 97.86% 72.78% 27.22% laidlawii 012 Ralstonia 99.36%
72.02% 27.98% 71.55% 100.00% 0.00% solanacearum 006 Mycoplasma
99.84% 0.43% 99.57% 99.84% 0.43% 99.57% arthritidis 007 Mycoplasma
99.86% 97.05% 2.95% 99.86% 97.05% 2.95% fermentans 012 Ralstonia
99.50% 45.38% 54.62% 45.13% 99.97% 0.03% solanacearum 012 Ralstonia
99.64% 76.18% 23.82% 75.91% 99.98% 0.02% solanacearum 012 Ralstonia
98.90% 42.44% 57.56% 41.93% 100.00% 0.00% solanacearum 012
Ralstonia 99.65% 68.87% 31.13% 68.62% 100.00% 0.00% solanacearum
012 Ralstonia 99.65% 68.89% 31.11% 68.62% 99.99% 0.01%
solanacearum
[0687] It was also discovered that the number of reads representing
any given organism from region V1/2 and V5/4 start to even out
given increasingly long read lengths as seen in FIG. 8. Also as the
number of >100 bp sequences over various cutoffs were examined
it became apparent that there is a consistent result obtained when
looking at the two selected regions (see FIGS. 9A, 9B, 10A, and
10B).
[0688] Thus, the analysis revealed the surprising result that
sequencing the 16S variable regions of V1, V2, V4, and V5 produced
the most accurate bacterial identifications. In particular,
sequencing from V1 into V2 and from V5 into V4 proved to generate
the longest reads and the most accurate identifications of
bacterial genera and species.
Example 13
Further Analysis of 16S rRNA Variable Regions
[0689] Additional analysis was performed to confirm that 16S rRNA
hypervariable regions 1/2 and 5/4 produce superior results over
other hypervariable regions. This analysis revealed that regions
1/2 and 5/4 gave total average lengths (before any size filtering)
of 156.3 and 171.4 respectively, while regions 3/2 and 3/4 resulted
in 120.5 and 140.8, respectively (see Table 15). This length
difference was also accompanied by a staggering difference in
sequence read number with regions 1/2 and 5/4 resulting in a
respective 106151.5 and 90913.7 sequences (on average), while 3/2
and 3/4 resulted in a meager 4942.7 and 433.0 average sequences,
respectively (see Table 16).
TABLE-US-00018 TABLE 15 Average lengths of sequencing reads using
oligonucleotides targeting 16S rRNA variable regions V1/2, V3/2,
V3/4, and V5/4. Run/Barcodes Regions L6BC003 L6BC004 L7BC003
L7BC004 L9BC007 L9BC008 Average 1/2 134.2 166.7 163.7 165.5 154.6
153.0 156.3 3/2 133.1 108.6 119.5 118.3 118.4 125.4 120.5 3/4 130.7
132.6 141.7 140.9 148.9 149.9 140.8 5/4 171.3 168.3 172.8 177.6
169.2 169.0 171.4
TABLE-US-00019 TABLE 16 Average sequence read numbers using
oligonucleotides targeting 16S rRNA variable regions V1/2, V3/2,
V3/4, and V5/4. Run/Barcodes Regions L6BC003 L6BC004 L7BC003
L7BC004 L9BC007 L9BC008 Average 1/2 32957 47370 159605 163316
131133 102528 106151.5 3/2 1641 23420 2159 1486 651 299 4942.7 3/4
81 356 569 533 545 514 433.0 5/4 68107 46325 96003 210504 81332
43211 90913.7
[0690] All of this taken together resulted in higher identification
rates from regions 1/2 and 5/4 over 3/2 and 3/4. This is shown in
looking at the correct identification rates to the genus level with
1/2 identifying 52.2% of the sequences correctly, 5/4 identifying
44.3%, 3/2 only identifying 2.4%, and 3/4 identifying 0.2% (see
Tables 17 and 18). This result was not expected based on previous
results and could be due to inherent bias or aspects of the
sequencing set up.
[0691] It was found that using both of V1/2 and V5/4
oligonucleotides for sequencing was preferable because they had
slightly different effectiveness identifying various bacterial
genera and species. Increasing the detection depth was useful by
including both and allowed verification of some of the sequenced
organisms by having independent sequence confirmation from two
regions (see Table 19).
TABLE-US-00020 TABLE 17 Percentage of sequence counts that
correctly identified the genus of control samples containing known
bacterial microorganisms using oligonucleotides targeting 16S rRNA
variable regions V1/2, V3/2, V3/4, and V5/4. Identification Regions
Correct Incorrect Region Total 1/2 52.2% 0.2% 52.4% 3/2 2.4% 0.1%
2.4% 3/4 0.2% 0.0% 0.2% 5/4 44.3% 0.6% 44.9%
TABLE-US-00021 TABLE 18 Total sequence read numbers resulting in
correct identification of the bacterial genus of control samples
using oligonucleotides targeting 16S rRNA variable regions V1/2,
V3/2, V3/4, and V5/4. Identification Regions Correct Incorrect
Region Total 1/2 634646 2263 636909 3/2 28836 820 29656 3/4 2335
263 2598 5/4 537587 7895 545482 Total 1214645
TABLE-US-00022 TABLE 19 Percentages of correctly identified
bacterial genera using oligonucleotides targeting 16S rRNA variable
regions V1/2, V3/2, V3/4, and V5/4 Region 1/2 Reads % Identified
Borrelia 13876 42.1% Bordatella 18707 56.8% Off Target 374 1.1%
Total 32957 100.0% Region 1/2 Reads % Identified Mycoplasma 67152
42.1% Bordatella 92142 57.7% Off Target 311 0.2% Total 159605
100.0% Region 1/2 Reads % Identified Borrelia 41133 31.4%
Bordatella 89428 68.2% Off Target 572 0.4% Total 131133 100.0%
Region 3/2 Reads % Identified Borrelia 543 33.1% Bordatella 970
59.1% Off Target 128 7.8% Total 1641 100.0% Region 3/2 Reads %
Identified Mycoplasma 345 16.0% Bordatella 1682 77.9% Off Target
132 6.1% Total 2159 100.0% Region 3/2 Reads % Identified Borrelia
146 22.4% Bordatella 381 58.5% Off Target 124 19.0% Total 651
100.0% Region 3/4 Reads % Identified Borrelia 30 37.0% Bordatella
37 45.7% Off Target 14 17.3% Total 81 100.0% Region 3/4 Reads %
Identified Mycoplasma 62 10.9% Bordatella 470 82.6% Off Target 37
6.5% Total 569 100.0% Region 3/4 Reads % Identified Borrelia 104
19.1% Bordatella 382 70.1% Off Target 59 10.8% Total 545 100.0%
Region 5/4 Reads % Identified Borrelia 44599 65.5% Bordatella 22984
33.7% Off Target 524 0.8% Total 68107 100.0% Region 5/4 Reads %
Identified Mycoplasma 18177 18.9% Bordatella 76160 79.3% Off Target
1666 1.7% Total 96003 100.0% Region 5/4 Reads % Identified Borrelia
36411 44.8% Bordatella 43794 53.8% Off Target 1127 1.4% Total 81332
100.0% Region 1/2 Reads % Identified Bartonella 30974 65.4%
Borrelia 7689 16.2% Bordatella 8414 17.8% Off Target 293 0.6% Total
47370 100.0% Region 1/2 Reads % Identified Mycoplasma 74691 45.7%
Bordatella 88239 54.0% Off Target 386 0.2% Total 163316 100.0%
Region 1/2 Reads % Identified Borrelia 36449 35.6% Bordatella 65752
64.1% Off Target 327 0.3% Total 102528 100.0% Region 3/2 Reads %
Identified Bartonella 22513 96.1% Borrelia 0 0.0% Bordatella 604
2.6% Off Target 303 1.3% Total 23420 100.0% Region 3/2 Reads %
Identified Mycoplasma 203 13.7% Bordatella 1183 79.6% Off Target
100 6.7% Total 1486 100.0% Region 3/2 Reads % Identified Borrelia
67 22.4% Bordatella 199 66.6% Off Target 33 11.0% Total 299 100.0%
Region 3/4 Reads % Identified Bartonella 241 67.7% Borrelia 0 0.0%
Bordatella 42 11.8% Off Target 73 20.5% Total 356 100.0% Region 3/4
Reads % Identified Mycoplasma 46 8.6% Bordatella 453 85.0% Off
Target 34 6.4% Total 533 100.0% Region 3/4 Reads % Identified
Borrelia 72 14.0% Bordatella 396 77.0% Off Target 46 8.9% Total 514
100.0% Region 5/4 Reads % Identified Bartonella 32806 70.8%
Borrelia 68 0.1% Bordatella 12588 27.2% Off Target 863 1.9% Total
46325 100.0% Region 5/4 Reads % Identified Mycoplasma 49079 23.3%
Bordatella 158274 75.2% Off Target 3151 1.5% Total 210504 100.0%
Region 5/4 Reads % Identified Borrelia 17302 40.0% Bordatella 25345
58.7% Off Target 564 1.3% Total 43211 100.0%
Example 14
Pan-Bacterial Metagenomics Analysis No. 4
[0692] A blood sample from a patient was processed to extract the
nucleic acids, prepare an ion amplicon library, purify the ion
amplicon library, sequence the 16S rRNA in the library, and
identify the species of microorganisms present in the biological
sample with a computer-based genomic analysis using the procedures
described in Examples 1-8. PCR primers were selected from those
listed in Tables 4 and 5.
[0693] Sequence Information: 703297 sequence reads were obtained
for DNA extracted from a blood sample. The longest 332,906
sequences were analyzed and compared to all available prokaryotic
species.
[0694] Results Confidence Profile: At the provided quality control
cut-off it is estimated that >95% of the sequence reads
correctly list the genus, while >30% of the sequence reads
correctly list the species.
[0695] The identified species are shown in FIG. 11.
[0696] Further examples include using the systems, methods and/or
kits as described herein to characterize other microorganisms, such
as protozoa, viruses, and fungi. FIGS. 18-20 illustrate reports
generated from a method that detected protozoa. A PCR procedure
suitable for amplification of protozoa is disclosed in application
Ser. No. 13/834,441, entitled SEMI-PAN-PROTOZOAL BY QUANTITATIVE
PCR, filed on Mar. 15, 2013, the contents of which are hereby
incorporated herein by reference, to the extend such contents do
not conflict with the present disclosure. FIG. 21 illustrates a
report generated from a method that detected fungi. Further, by way
of specific example, Adenovirus type 2 was detected using a method
as described herein.
[0697] Additional nonlimiting examples of the disclosure
include:
[0698] 1. A method of characterizing one or more microorganisms,
the method comprising the steps of:
[0699] preparing an amplicon library with a polymerase chain
reaction (PCR) of nucleic acids;
[0700] sequencing a characteristic gene sequence in the amplicon
library to obtain a gene sequence; and
[0701] characterizing the one or more microorganisms based on the
gene sequence using a computer-based genomic analysis of the gene
sequence.
[0702] 2. The method of example 1, wherein the amplicon library
comprises an ion amplicon library.
[0703] 3. The method of any of examples 1-2, further comprising a
step of extracting nucleic acids from a biological sample of a
subject.
[0704] 4. The method of any of examples 1-3, further comprising a
step of purifying the amplicon library from the PCR reaction.
[0705] 5. The method of any of examples 1-4, wherein the one or
more microorganisms comprise bacteria and the characteristic gene
comprises 16S ribosomal RNA (16S rRNA).
[0706] 6. The method of any of examples 1-5, wherein the one or
more microorganisms comprise protozoa.
[0707] 7. The method of any of examples 1-6, wherein the one or
more microorganisms comprise fungi.
[0708] 8. The method of any of examples 1-7, wherein the one or
more microorganisms comprise viruses.
[0709] 9. The method of any of examples 1-8, wherein the step of
sequencing comprises using an ion semiconductor sequencing platform
or a platform based on stepwise addition of reversible terminator
nucleotides.
[0710] 10. The method of any of examples 1-9, further comprising a
step of identifying the one or more microorganisms using a
computer-based genomic analysis of the gene sequence.
[0711] 11. The method of any of examples 1-10, further comprising a
step of determining a nearest characterized microorganism.
[0712] 12. The method of any of examples 1-11, wherein the PCR
reaction uses at least one forward primer.
[0713] 13. The method of example 12, wherein the forward primer
comprises a target sequence that comprises a sequence from the
characteristic gene.
[0714] 14. The method of example 13, wherein the target sequence
comprises a sequence from a 16S rRNA gene selected from a
hypervariable region selected from the group consisting of V1, V2,
V4, and V5.
[0715] 15. The method of any of examples 13-14, wherein the target
sequence comprises a sequence from the 16S rRNA gene selected from
the group consisting of (i) a sequence beginning in V1 and
extending towards V2, (ii) a sequence beginning in V5 and extending
towards V4, (iii) a sequence beginning in V2 and extending towards
V1, and (iv) a sequence beginning in V4 and extending towards
V5.
[0716] 16. The method of any of examples 13-15, wherein the target
sequence from the 16S rRNA comprises SEQ ID NO: 18 or SEQ ID NO:
19.
[0717] 17. The example of any of examples 1-16, wherein the PCR
reaction uses at least a first forward primer and a second forward
primer, each comprising a barcode, a barcode adapter, and a target
sequence;
[0718] wherein a target sequence of the first forward primer
comprises a sequence from a 16S rRNA gene beginning in V1 and
extending towards V2 and a target sequence of the second forward
primer comprises a sequence beginning in V5 and extending towards
V4.
[0719] 18. The method of any of examples 13-17, wherein the target
sequence comprises a sequence from a 16S rRNA gene selected from
the group consisting of SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO:
20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ
ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO:
29, and SEQ ID NO: 30.
[0720] 19. The method of any of examples 12-18, wherein the forward
primer comprises a sequence from a 16S rRNA gene selected from the
group consisting of SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37,
SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID
NO: 42, SEQ ID NO: 43, SEQ ID NO: 44, SEQ ID NO: 45, SEQ ID NO: 46,
SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, and SEQ ID NO: 50.
[0721] 20. The method of any of examples 1-19, wherein the PCR
reaction uses a reverse primer comprising SEQ ID NO: 33.
[0722] 21. The method of any of examples 12-20, wherein the forward
primer comprises a sequence from a 16S rRNA gene selected from the
group consisting of SEQ ID NO: 51, SEQ ID NO: 52, SEQ ID NO: 53,
SEQ ID NO: 54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID
NO: 58, SEQ ID NO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62,
SEQ ID NO: 63, SEQ ID NO: 64, SEQ ID NO: 65, and SEQ ID NO: 66.
[0723] 22. The method of any of examples 1-21, wherein the PCR
reaction uses a reverse primer comprising SEQ ID NO: 34.
[0724] 23. The method of any of examples 3-22, wherein the
biological sample comprises material selected from a urine sample,
a blood sample, a joint sample, a dental sample, a bronchioalveolar
lavage, a nasal swab, cerebrospinal fluid, synovial fluid, brain
tissue, cardiac tissue, bone, skin, and a lymph node tissue.
[0725] 24. The method of any of examples 3-23, wherein the
biological sample comprises a dental sample and the one or more
microorganisms comprises a microorganism from a genus selected from
the group consisting of Bacteroides, Tannerella, Prevotella,
Peptostreptococcus, Streptococcus, Staphylococcus, Porphyromonas,
Fusobacterium, Clostridium, Treponema, Atopobium, Cryptobacterium,
Eubacterium, Mogibacterium, Filifactor, Dialister, Centipeda,
Selenomonas, Granulicatella, and Kingella.
[0726] 25. The method of any of examples 3-24, wherein the
biological sample comprises a joint sample and the one or more
microorganisms comprises a microorganism from a genus selected from
the group consisting of Staphylococcus, Streptococcus, Kingella,
Aeromonas, Mycobacterium, Actinomyces, Fusobacterium, Salmonella,
Haemophilus, Borrelia, Neisseria, Escherichia, Brucella,
Pseudomonas, Mycoplasma, Salmonella, Propionibacterium,
Acinetobacter, Treponema, and Erysipelothrix.
[0727] 26. The method of any of examples 3-25, wherein the
biological sample comprises a blood sample and the one or more
microorganisms comprises a microorganism from a genus selected from
the group consisting of Capnocytophaga, Rickettsia, Staphylococcus,
Streptococcus, Neisseria, Mycobacterium, Klebsiella, Haemophilus,
Fusobacterium, Chlamydia, Enterococcus, Escherichia, Enterobacter,
Proteus, Legionella, Pseudomonas, Clostridium, Listeria, Serratia,
and Salmonella.
[0728] 27. The method of any of examples 1-26, wherein the one or
more microorganisms comprises at least one nonculturable
pathogen.
[0729] 28. The method of any of examples 1-27, further comprising a
step of generating a report with a one or more of a genera and
species of the one or more microorganisms.
[0730] 29. The method of example 28, wherein the report includes a
relative measure of the one or more of genera and species
contribution and diversity in the biological sample and
antimicrobial resistance and susceptibility information for each
genus and/or species.
[0731] 30. The method of any of examples 1-29, further comprising
treating the subject with a treatment identified in the report.
[0732] 31. The method of any of examples 1-30, wherein the
computer-based genomic analysis comprises application of a
procedural algorithm to sequencing data.
[0733] 32. The method of example 31, wherein the procedural
algorithm excludes sequences that are present less than five times
or constitute less than one percent of the sequencing data.
[0734] 33. A kit for characterizing at least one microorganism, the
kit comprising:
[0735] a) at least one forward primer comprising an adapter
sequence and a priming sequence, for a target sequence, wherein the
target sequence comprises a sequence from a characteristic gene
sequence; and
[0736] b) at least one reverse primer.
[0737] 34. The kit of example 33, wherein the target sequence
comprises a sequence from a hypervariable region from a 16S rRNA
gene selected from the group consisting of V1, V2, V4, and V5.
[0738] 35. The kit of any of examples 33-34, wherein the forward
primer comprises a barcode and a barcode adapter.
[0739] 36. The kit of any of examples 33-35, wherein the target
sequence comprises a 16S rRNA gene sequence selected from the group
consisting of (i) a sequence beginning in V1 and extending towards
V2, (ii) a sequence beginning in V5 and extending towards V4, (iii)
a sequence beginning in V2 and extending towards V1, and (iv) a
sequence beginning in V4 and extending towards V5.
[0740] 37. The kit of any of examples 33-36, wherein the at least
one forward primer comprises a sequence selected from the group
consisting of SEQ ID NO: 18 and SEQ ID NO: 19.
[0741] 38. The kit of any of examples 33-37, wherein the at least
one forward primer comprises a first forward primer and a second
forward primer, each comprising a barcode, a barcode adapter, and a
target sequence;
[0742] wherein the target sequence of the first forward primer
comprises a sequence beginning in V1 and extending towards V2 and
the target sequence of the second forward primer comprises a
sequence beginning in V5 and extending towards V4.
[0743] 39. The kit of any of examples 33-38, wherein the first
forward primer comprises SEQ ID NO: 18 and a second forward primer
comprises SEQ ID NO: 19.
[0744] 40. The kit of any of examples 33-39, wherein the at least
one reverse primer comprises a sequence selected from the group
consisting of SEQ ID NO: 33 and SEQ ID NO: 34.
[0745] 41. The kit of any of examples 33-40, wherein the target
sequence is selected from the group consisting of SEQ ID NO: 18,
SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID
NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27,
SEQ ID NO: 28, SEQ ID NO: 29, and SEQ ID NO: 30.
[0746] 42. The kit of any of examples 33-38, wherein the target
sequence is about 10 nucleotides in length to about 30 nucleotides
in length.
[0747] 43. A method of characterizing one or more microorganisms in
a biological sample, the method comprising the steps of:
[0748] providing at least one forward primer comprising an adapter
sequence and a primer sequence for a target sequence, wherein the
target sequence comprises a sequence from a hypervariable region
from a 16S rRNA gene selected from the group consisting of V1, V2,
V4, and V5;
[0749] providing at least one reverse primer;
[0750] providing a biological sample comprising nucleic acids;
[0751] preparing an amplicon library with a polymerase chain
reaction (PCR) of the nucleic acids;
[0752] purifying the amplicon library from the PCR reaction;
[0753] sequencing a 16S ribosomal RNA (16S rRNA) gene in the ion
amplicon library to obtain a gene sequence; and
[0754] characterizing the one or more microorganisms based on the
gene sequence using a computer-based genomic analysis of the 16S
rRNA gene sequence.
[0755] Although any methods and materials, similar or equivalent to
those described herein, can be used in the practice or testing of
the present invention, the preferred methods and materials are
described herein. All publications, patents, and patent
publications cited are incorporated by reference herein in their
entirety for all purposes, to the extent such references do not
conflict with the present disclosure.
[0756] It is understood that the disclosed invention is not limited
to the particular methodology, protocols and materials described as
these can vary. It is also understood that the terminology used
herein is for the purposes of describing particular embodiments
only and is not intended to limit the scope of the present
invention that will be limited only by the appended claims.
[0757] Those skilled in the art will recognize, or be able to
ascertain using no more than routine experimentation, many
equivalents to the specific embodiments of the invention described
herein. Such equivalents are intended to be encompassed by the
following claims.
Sequence CWU 1
1
74110DNAArtificial sequencePrimer 1ctaaggtaac 10210DNAArtificial
sequencePrimer 2taaggagaac 10310DNAArtificial sequencePrimer
3aagaggattc 10410DNAArtificial sequencePrimer 4taccaagatc
10510DNAArtificial sequencePrimer 5cagaaggaac 10610DNAArtificial
sequencePrimer 6ctgcaagttc 10710DNAArtificial sequencePrimer
7ttcgtgattc 10810DNAArtificial sequencePrimer 8ttccgataac
10910DNAArtificial sequencePrimer 9tgagcggaac 101010DNAArtificial
sequencePrimer 10ctgaccgaac 101110DNAArtificial sequencePrimer
11tcctcgaatc 101210DNAArtificial sequencePrimer 12taggtggttc
101310DNAArtificial sequencePrimer 13tctaacggac 101410DNAArtificial
sequencePrimer 14ttggagtgtc 101510DNAArtificial sequencePrimer
15tctagaggtc 101610DNAArtificial sequencePrimer 16tctggatgac
10173DNAArtificial sequencePrimer 17gat 31820DNAArtificial
sequencePrimer 18agagtttgat cctggctcag 201920DNAArtificial
sequencePrimer 19ccgtcaattn ntttnagttt 202019DNAArtificial
sequencePrimer 20ggttaccttg ttacgactt 192123DNAArtificial
sequencePrimer 21taaaactnaa angaattgac ggg 232223DNAArtificial
sequencePrimer 22actgctgcnn cccgtaggag tct 232315DNAArtificial
sequencePrimer 23naacgagcgc aaccc 152415DNAArtificial
sequencePrimer 24gggttgcgct cgttg 152521DNAArtificial
sequencePrimer 25gactcctacg ggaggcngca g 212620DNAArtificial
sequencePrimer 26ccgtcaattc ctttnagttt 202718DNAArtificial
sequencePrimer 27ggattagata ccctggta 182820DNAArtificial
sequencePrimer 28gactaccagg gtatctaatc 202919DNAArtificial
sequencePrimer 29gtgccagcng ccgcggtaa 193019DNAArtificial
sequencePrimer 30gtattaccgc ggctgctgg 193130DNAArtificial
sequencePrimer 31ccatctcatc cctgcgtgtc tccgactcag
303223DNAArtificial sequencePrimer 32cctctctatg ggcagtcggt gat
233338DNAArtificial sequencePrimer 33cctctctatg ggcagtcggt
gatctgctgc ctnccgta 383438DNAArtificial sequencePrimer 34cctctctatg
ggcagtcggt gatantgggn ntaaagng 383563DNAArtificial sequencePrimer
35ccatctcatc cctgcgtgtc tccgactcag ctaaggtaac gatagagttt gatcctggct
60cag 633663DNAArtificial sequencePrimer 36ccatctcatc cctgcgtgtc
tccgactcag taaggagaac gatagagttt gatcctggct 60cag
633763DNAArtificial sequencePrimer 37ccatctcatc cctgcgtgtc
tccgactcag aagaggattc gatagagttt gatcctggct 60cag
633863DNAArtificial sequencePrimer 38ccatctcatc cctgcgtgtc
tccgactcag taccaagatc gatagagttt gatcctggct 60cag
633963DNAArtificial sequencePrimer 39ccatctcatc cctgcgtgtc
tccgactcag cagaaggaac gatagagttt gatcctggct 60cag
634063DNAArtificial sequencePrimer 40ccatctcatc cctgcgtgtc
tccgactcag ctgcaagttc gatagagttt gatcctggct 60cag
634163DNAArtificial sequencePrimer 41ccatctcatc cctgcgtgtc
tccgactcag ttcgtgattc gatagagttt gatcctggct 60cag
634263DNAArtificial sequencePrimer 42ccatctcatc cctgcgtgtc
tccgactcag ttccgataac gatagagttt gatcctggct 60cag
634363DNAArtificial sequencePrimer 43ccatctcatc cctgcgtgtc
tccgactcag tgagcggaac gatagagttt gatcctggct 60cag
634463DNAArtificial sequencePrimer 44ccatctcatc cctgcgtgtc
tccgactcag ctgaccgaac gatagagttt gatcctggct 60cag
634563DNAArtificial sequencePrimer 45ccatctcatc cctgcgtgtc
tccgactcag tcctcgaatc gatagagttt gatcctggct 60cag
634663DNAArtificial sequencePrimer 46ccatctcatc cctgcgtgtc
tccgactcag taggtggttc gatagagttt gatcctggct 60cag
634763DNAArtificial sequencePrimer 47ccatctcatc cctgcgtgtc
tccgactcag tctaacggac gatagagttt gatcctggct 60cag
634863DNAArtificial sequencePrimer 48ccatctcatc cctgcgtgtc
tccgactcag ttggagtgtc gatagagttt gatcctggct 60cag
634963DNAArtificial sequencePrimer 49ccatctcatc cctgcgtgtc
tccgactcag tctagaggtc gatagagttt gatcctggct 60cag
635063DNAArtificial sequencePrimer 50ccatctcatc cctgcgtgtc
tccgactcag tctggatgac gatagagttt gatcctggct 60cag
635163DNAArtificial sequencePrimer 51ccatctcatc cctgcgtgtc
tccgactcag ctaaggtaac gatccgtcaa ttnntttnag 60ttt
635263DNAArtificial sequencePrimer 52ccatctcatc cctgcgtgtc
tccgactcag taaggagaac gatccgtcaa ttnntttnag 60ttt
635363DNAArtificial sequencePrimer 53ccatctcatc cctgcgtgtc
tccgactcag aagaggattc gatccgtcaa ttnntttnag 60ttt
635463DNAArtificial sequencePrimer 54ccatctcatc cctgcgtgtc
tccgactcag taccaagatc gatccgtcaa ttnntttnag 60ttt
635563DNAArtificial sequencePrimer 55ccatctcatc cctgcgtgtc
tccgactcag cagaaggaac gatccgtcaa ttnntttnag 60ttt
635663DNAArtificial sequencePrimer 56ccatctcatc cctgcgtgtc
tccgactcag ctgcaagttc gatccgtcaa ttnntttnag 60ttt
635763DNAArtificial sequencePrimer 57ccatctcatc cctgcgtgtc
tccgactcag ttcgtgattc gatccgtcaa ttnntttnag 60ttt
635863DNAArtificial sequencePrimer 58ccatctcatc cctgcgtgtc
tccgactcag ttccgataac gatccgtcaa ttnntttnag 60ttt
635963DNAArtificial sequencePrimer 59ccatctcatc cctgcgtgtc
tccgactcag tgagcggaac gatccgtcaa ttnntttnag 60ttt
636063DNAArtificial sequencePrimer 60ccatctcatc cctgcgtgtc
tccgactcag ctgaccgaac gatccgtcaa ttnntttnag 60ttt
636163DNAArtificial sequencePrimer 61ccatctcatc cctgcgtgtc
tccgactcag tcctcgaatc gatccgtcaa ttnntttnag 60ttt
636263DNAArtificial sequencePrimer 62ccatctcatc cctgcgtgtc
tccgactcag taggtggttc gatccgtcaa ttnntttnag 60ttt
636363DNAArtificial sequencePrimer 63ccatctcatc cctgcgtgtc
tccgactcag tctaacggac gatccgtcaa ttnntttnag 60ttt
636463DNAArtificial sequencePrimer 64ccatctcatc cctgcgtgtc
tccgactcag ttggagtgtc gatccgtcaa ttnntttnag 60ttt
636563DNAArtificial sequencePrimer 65ccatctcatc cctgcgtgtc
tccgactcag tctagaggtc gatccgtcaa ttnntttnag 60ttt
636663DNAArtificial sequencePrimer 66ccatctcatc cctgcgtgtc
tccgactcag tctggatgac gatccgtcaa ttnntttnag 60ttt
636750DNAArtificial sequencePrimer 67ccatctcatc cctgcgtgtc
tccgactcag nnnnnnnnnn nnnnnnnnnn 506843DNAArtificial sequencePrimer
68cctctctatg ggcagtcggt gatnnnnnnn nnnnnnnnnn nnn
436944DNAArtificial sequencePrimer 69cctctctatg ggcagtcggt
gatcactggt tcaaggttct ggag 447041DNAArtificial sequencePrimer
70cctctctatg ggcagtcggt gatcatttca cccgcagcct a 417151DNAArtificial
sequencePrimer 71ccatctcatc cctgcgtgtc tccgactcag cactggttca
aggttctgga g 517248DNAArtificial sequencePrimer 72ccatctcatc
cctgcgtgtc tccgactcag catttcaccc gcagccta 487390DNAArtificial
sequenceTarget amplicon 73cactggttca aggttctgga gttctccatg
aaacttgggt taattttgct cagagtatcc 60ngagttagcc actaggctgc gggtgaaatg
907490DNAArtificial sequenceTarget amplicon 74catttcaccc gcagcctagt
ggctaactcn ggatactctg agcaaaatta acccaagttt 60catggagaac tccagaacct
tgaaccagtg 90
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