U.S. patent number RE38,186 [Application Number 09/665,182] was granted by the patent office on 2003-07-15 for method and apparatus for detecting microorganisms.
This patent grant is currently assigned to Osmetech PLC. Invention is credited to Peter Alfred Payne, Krishna Chandra Persaud.
United States Patent |
RE38,186 |
Payne , et al. |
July 15, 2003 |
Method and apparatus for detecting microorganisms
Abstract
A method for identifying a microorganism is described that
includes abstracting gas or vapor associated with the microorganism
from a detection region and flowing the same over an array of
sensors of which an electrical property varies according to
exposure to gases or vapors and observing the response of the
sensors. An apparatus for detecting a microorganism is also
disclosed having a detector means for detecting a gas or vapor
associated with the microorganism which includes an array of
sensors of which an electrical property varies according to
exposure to the gases or vapors.
Inventors: |
Payne; Peter Alfred (Knutsford,
GB), Persaud; Krishna Chandra (Cheadle,
GB) |
Assignee: |
Osmetech PLC
(GB)
|
Family
ID: |
10756425 |
Appl.
No.: |
09/665,182 |
Filed: |
September 15, 2000 |
PCT
Filed: |
June 09, 1995 |
PCT No.: |
PCT/GB95/01347 |
PCT
Pub. No.: |
WO95/33848 |
PCT
Pub. Date: |
December 14, 1995 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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Reissue of: |
750652 |
Feb 28, 1997 |
05807701 |
Sep 15, 1998 |
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Foreign Application Priority Data
Current U.S.
Class: |
435/34; 422/50;
422/83; 422/88; 435/283.1; 435/285.2; 435/286.6; 435/287.1;
435/287.5; 435/300.1; 435/4; 435/807 |
Current CPC
Class: |
C12Q
1/04 (20130101); C12Q 2304/40 (20130101); Y10S
435/807 (20130101) |
Current International
Class: |
C12Q
1/04 (20060101); C12Q 001/04 (); C12Q 001/00 () |
Field of
Search: |
;435/34,4,300.1,807,283.1,287.1,287.5,286.6,285.2
;422/50,83,88 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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124193 |
|
Nov 1984 |
|
EP |
|
158497 |
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Oct 1985 |
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EP |
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286307 |
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Nov 1993 |
|
EP |
|
0597584 |
|
May 1994 |
|
EP |
|
0264221 |
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Apr 1998 |
|
EP |
|
60130398 |
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Jul 1985 |
|
JP |
|
WO9013663 |
|
May 1989 |
|
WO |
|
WO9404705 |
|
Mar 1994 |
|
WO |
|
Other References
Sammon, John W., "A Nonlinear Mapping for Data Structure Analysis,"
May 5, 1969, IEEE Transactions on Computers, vol. 3-18, No. 5, pp.
401-409. .
Greenfield, Philip, "AromaScan Sniffs Out Medical Application,"
Clinica, May 23, 1994, pp. 20-21. .
"Digital Smell of Success," Independent on Sunday, Jun. 5, 1994, 2
pages. .
Winquist, F., et al., "Performance of an Electronic Nose for
Quality Estimation of Ground Meat," Meas. Sci. Technol. vol. 4,
(1993) pp. 1493-1500. .
Schweizer-Berberich, P.M., et al., Characterisation of Food
Freshness with Sensor Arrays, Sensors and Actuators B, 18-19 (1994)
pp. 282-290. .
Persaud, Krishna C., "Odour Detection Using Sensor Arrays,"
Analytical Proceedings, Oct. 1991, vol. 28 pp. 339-341. .
Hartfield, J.V., et al., "Towards an Integrated Electronic Nose
Using Conducting Polymer Sensors," Sensors and Actuators B, Nov.
19, 1993, 11:35:17, pp. 1-8. .
Persaud, Krishna C., "Electronic Gas and Odour Dectectors that
Mimic Chemoreception in Animals," Trends in Analytical Chemistry,
vol. 11, No. 2, 1992. .
Shen-Wu Ho, "Head-Space Gas-Liquid Chromatographic Analysis for
Presumptive Identification of Bacteria in Blood Cultures", Feb.
1986, pp. 18-26.* .
Gardner et al., "A brief history of electronic noses" Sensors and
Actuators B. 18-19 (1994), pp. 211-220.* .
J.L. Berdague et al., "Revue Caracterisation Instrumentale De La
Qualite Des Matieres Premieres Et Des Aliments Par Analyse Des
Composes Volatils", Viandes Prod. Carnes vol. 14, Sep.-Oct. 1993,
pp. 135-138; (with English language summary).* .
M. Sasser, "Identification of Bacteria by Gas Chromatography of
Cellular Fatty Acids", Technical Note #101, MIDI, May 1990, pp.
163-169.* .
M. Sasser, "`Tracking` a Strain Using the Microbial Identification
System", Technical Note #102, MIDI, May 1990, pp. 171-174..
|
Primary Examiner: Leary; Louise N.
Attorney, Agent or Firm: Marger Johnson & McCollom,
P.C.
Claims
We claim:
1. A method for identifying a microorganism, comprising abstracting
gas or vapor associated with the microorganism from a detection
region and flowing the same over an array of sensors of which an
electrical property varies according to exposure to gases or vapors
and observing the response of the sensors.
2. The method according to claim 1, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors.
3. The method according to claim 1 or claim 2, comprising comparing
the response of the sensors against a library of responses to known
microorganisms.
4. The method according to claim 1 or claim 2, comprising inputting
the response to a neural net trained against known
microorganisms.
5. The method according to claim 1 or claim 2, comprising
performing a cluster analysis mapping of the sensor outputs.
6. The method according to claims 1 or 2, in which the detection
region comprises an enclosed space above a Petri dish or other
laboratory culture dish.
7. The method according to claims 1 or 2, in which the array of
sensors is first purged using a purging gas.
8. An apparatus for detecting a microorganism .Iadd.or the state of
a microorganism.Iaddend., comprising.Iadd.:.Iaddend. a detector
means for detecting a gas or vapor associated with the
microorganism, said detector means comprising an array of sensors
of which an electrical property varies according to exposure to the
gases or vapors.Iadd.; and a library of responses to known
microorganisms or known microorganism states.Iaddend..
9. The apparatus according to claim 8, in which the sensors
comprise semi-conducting polymers, the resistance or impedance of
which varies according to exposure to gases or vapors.
10. The apparatus according to claim 8 or claim 9, .Iadd.further
.Iaddend.comprising a .[.store for a library of responses to known
microorganisms and.]. comparison means operable automatically to
compare a given response against the library.
11. The apparatus according to claim 8 or claim 9, comprising a
neural net, the input to which comprises the array of sensors and
which is trained against known microorganisms.
12. The apparatus according to claims 8 or 9, comprising a probe
for sampling a detection region by abstracting gas or vapor from
said region to be passed to said detector means.
13. The apparatus according to claim 12, said probe comprising a
cover for enclosing a Petri or other laboratory dish or an area of
growth medium thereon.
14. The apparatus according to claim 13, said probe comprising a
carrier gas feed and return.
15. The apparatus according to claim 14, comprising a source of
carrier gas.
16. The method according to claim 1, wherein the microorganism is a
bacteria.
17. The method according to claim 16, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors.
18. The method according to claim 16 or claim 17, comprising
comparing the response of the sensors against a library of
responses to known bacteria.
19. The method according to claim 16 or claim 17, comprising
inputting the response to a neural net trained against known
bacteria.
20. The method according to claim 16 or claim 17, comprising
performing a cluster analysis mapping of the sensor outputs.
21. The method according to claim 16 or claim 17, in which the
detection region comprises an enclosed space above a Petri dish or
other laboratory culture dish.
22. The method according to any one of claim 16 or claim 17, in
which the array of sensors is first purged using a purging gas.
23. The apparatus according to claim 8, wherein the microorganism
is a bacteria.
24. The apparatus according to claim 23, in which the sensors
comprise semi-conducting polymers, the resistance or impedance of
which varies according to exposure to gases or vapors.
25. The apparatus according to claim 23 or claim 24, .Iadd.further
.Iaddend.comprising a .[.store for a library of responses to known
bacteria and.]. comparison means operable automatically to compare
a given response against the library.
26. The apparatus according to claim 23 or claim 24, comprising a
neural net, the input to which comprises the array of sensors and
which is trained against known bacteria.
27. The apparatus according to claim 23 or 24, comprising a probe
for sampling a detection region by abstracting gas or vapor from
said region to be passed to said detector means.
28. The apparatus according to claim 27, said probe comprising a
cover for enclosing a Petri or other laboratory culture dish or an
area of growth medium thereon.
29. The apparatus according to claim 28, said probe comprising a
carrier gas feed and return.
30. The apparatus according to claim 29, comprising a source of
carrier gas.
31. The method according to claim 1, wherein the microorganism is a
microfungi.
32. The method according to claim 31, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors.
33. The method according to claim 31 or claim 32, comprising
comparing the response of the sensors against a library of
responses to known microfungi.
34. The method according to claim 31 or claim 32, comprising
inputting the response to a neural net trained against known
microfungi.
35. The method according to claim 31 or claim 32, comprising
performing a cluster analysis mapping of the sensor outputs.
36. The method according to claim 31 or 32, in which the detection
region comprises an enclosed space above a Petri dish or other
laboratory culture dish.
37. The method according to claim 31 or 32, in which the array of
sensors is first purged using a purging gas.
38. The apparatus according to claim 8, wherein the microorganism
is a microfungi.
39. The apparatus according to claim 38, in which the sensors
comprise semi-conducting polymers, the resistance or impedance of
which varies according to exposure to gases or vapors.
40. The apparatus according to claim 38 or claim 39, .Iadd.further
.Iaddend.comprising a .[.store for a library of responses to known
microfungi and.]. comparison means operable automatically to
compare a given response against the library.
41. The apparatus according to claim 38 or claim 39, comprising a
neural net, the input to which comprises the array of sensors and
which is trained against known microfungi.
42. The apparatus according to claim 38 or claim 39, comprising a
probe for sampling a detection region by abstracting gas or vapor
from said region to be passed to said detector means.
43. The apparatus according to claim 42, said probe comprising a
cover for enclosing a Petri or other laboratory culture dish or an
area of growth medium thereon.
44. The apparatus according to claim 43, said probe comprising a
carrier gas feed and return.
45. The apparatus according to claim 44, comprising a source of
carrier gas.
46. The method according to claim 1, comprising detecting gas or
vapor associated with the microorganism species and differentiating
said gas or vapor from gas or vapor associated with other
microorganism species.
47. The method according to claim 1, comprising detecting gas or
vapor associated with a bacterial species and differentiating said
gas or vapor from gas or vapor associated with other bacterial
species.
48. The method according to claim 1, comprising detecting gas or
vapor associated with a microfungi species and differentiating said
gas or vapor from gas or vapor associated with other microfungi
species..Iadd.
49. An apparatus for detecting a microorganism or the state of a
microorganism, comprising: a detector means for detecting a gas or
vapor associated with the microorganism, said detector means
comprising an array of sensors of which an electrical property
varies according to exposure to the gases or vapors; a store for a
library of responses to known microorganisms or known microorganism
states; and comparison means operable automatically to compare a
given response against the library..Iaddend..Iadd.
50. A method for identifying a microorganism comprising:
abstracting gas or vapor associated with the microorganism from a
detection region; flowing the same over an array of sensors of
which an electrical property varies according to exposure to gases
or vapors and observing the response of the sensors; providing a
library of responses to known microorganisms; and comparing the
response of the sensors against the library of responses to known
microorganisms..Iaddend..Iadd.
51. The method according to claim 50, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors..Iaddend..Iadd.
52. The method according to claim 50, further comprising inputting
the response to a neural net trained against known
microorganisms..Iaddend..Iadd.
53. The method according to claim 50, further comprising performing
a cluster analysis mapping of the sensor
outputs..Iaddend..Iadd.
54. The method according to claim 50, wherein the detection region
comprises an enclosed space above a Petri dish or other laboratory
culture dish..Iaddend..Iadd.
55. The method according to claim 50, further comprising purging
the array of sensors with a purging gas..Iaddend..Iadd.
56. The method according to claim 50, wherein the microorganism is
a bacteria..Iaddend..Iadd.
57. The method according to claim 50, wherein the microorganism is
a microfungi..Iaddend..Iadd.
58. The method according to claim 50, further comprising
determining the state of the microorganism..Iaddend..Iadd.
59. A method for identifying a microorganism comprising:
abstracting gas or vapor associated with the microorganism from a
detection region; flowing the same over an array of sensors of
which an electrical property varies according to exposure to gases
or vapors and observing the response of the sensors; and comparing
the response of the sensors against a library of responses to known
microorganisms..Iaddend..Iadd.
60. The method according to claim 59, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors..Iaddend..Iadd.
61. The method according to claim 59, further comprising inputting
the response to a neural net trained against known
microorganisms..Iaddend..Iadd.
62. The method according to claim 59, further comprising performing
a cluster analysis mapping of the sensor
outputs..Iaddend..Iadd.
63. The method according to claim 59, wherein the detection region
comprises and enclosed space above a Petri dish or other laboratory
culture dish..Iaddend..Iadd.
64. The method according to claim 59, further comprising purging
the array of sensors with a purging gas..Iaddend..Iadd.
65. The method according to claim 59, wherein the microorganism is
a bacteria..Iaddend..Iadd.
66. The method according to claim 59, wherein the microorganism is
a microfungi..Iaddend..Iadd.
67. The method according to claim 59, further comprising
determining the state of the microorganism..Iaddend..Iadd.
68. A method for identifying the state of a microorganism
comprising: abstracting gas or vapor associated with the
microorganism from a detection region; flowing the same over an
array of sensors of which an electrical property varies according
to exposure to gases or vapors; observing the response of the
sensors; and identifying the state of the microorganism based on
the observed response..Iaddend..Iadd.
69. The method according to claim 68, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors..Iaddend..Iadd.
70. The method according to claim 68, further comprising inputting
the response to a neural net trained against known microorganism
states..Iaddend..Iadd.
71. The method according to claim 68, further comprising performing
a cluster analysis mapping of the sensor
outputs..Iaddend..Iadd.
72. The method according to claim 68, wherein the detection region
comprises an enclosed space above a Petri dish or other laboratory
culture dish..Iaddend..Iadd.
73. The method according to claim 68, further comprising purging
the array of sensors with a purging gas..Iaddend..Iadd.
74. The method according to claim 68, wherein the microorganism is
a bacteria..Iaddend..Iadd.
75. The method according to claim 68, wherein the microorganism is
a microfungi..Iaddend..Iadd.
76. The method according to claim 68, further comprising: providing
a library of responses to known microorganism states; and comparing
the response of the sensors against the library of responses to
known microorganism states..Iaddend..Iadd.
77. A method for identifying a microorganism comprising:
abstracting gas or vapor associated with the microorganism from a
detection region; flowing the same over an array of sensors of
which an electrical property varies according to exposure to gases
or vapors; observing the response of the sensors; and
differentiating such gas or vapor from gas or vapor known to be
associated with other known microorganisms..Iaddend..Iadd.
78. The method according to claim 77, further comprising: providing
a library of responses to known microorganisms; and comparing the
response of the sensors against the library of responses to known
microorganisms..Iaddend..Iadd.
79. The method according to claim 77, in which the sensors comprise
semi-conducting polymers, the resistance or impedance of which
varies according to exposure to gases or vapors..Iaddend..Iadd.
80. The method according to claim 77, further comprising inputting
the response to a neural net trained against known
microorganisms..Iaddend..Iadd.
81. The method according to claim 77, further comprising performing
a cluster analysis mapping of the sensor
outputs..Iaddend..Iadd.
82. The method according to claim 77, wherein the detection region
comprises an enclosed space above a Petri dish or other laboratory
culture dish..Iaddend..Iadd.
83. The method according to claim 77, further comprising purging
the array of sensors with a purging gas..Iaddend..Iadd.
84. The method according to claim 77, wherein the microorganism is
a bacteria..Iaddend..Iadd.
85. The method according to claim 77, wherein the microorganism is
a microfungi..Iaddend..Iadd.
86. The method according to claim 77, further comprising
determining the state of the microorganism..Iaddend.
Description
This invention relates to detecting bacteria.
Bacteria are identified in a variety of ways. Many have
characteristic forms which can be seen under microscopic
examination, but some are identified, when colonised on a growth
medium, by a characteristic colour and in some cases this is
confirmed by smell. Not all bacteria have any appreciable odour,
but many have a characteristic associated gas or vapour due to
their inherent metabolic activities.
Patent Abstracts of Japan, application number JP-A-60130398,
discloses a detector for detecting the presence of microorganisms
on the basis of evolved gases. WO 94/04705 discloses a method of
detecting E. Coli by monitoring a gaseous product, this gaseous
product being produced by cleavage of a glucuronide conjugate by
.beta.-glucuronidase produced by a certain bacterial species.
GB-A-2176901 describes gas sensors based on the use of
semi-conducting organic polymers, whilst U.S. Pat. No. 4,456,380
discloses an optical bacteria identification system using a
plurality of optical filters.
The invention comprises a method for identifying bacteria
comprising detecting gas or vapour associated with the metabolic
activity of the bacteria and differentiating such gas or vapour
from gas or vapour associated with other bacteria.
The method may comprise abstracting gas or vapour from a detection
region and flowing the same over an array of sensors of which an
electrical property varies according to exposure to gases or
vapours and observing the response of the sensors.
The sensors may comprise semi-conducting polymers the resistance or
impedance of which varies according to exposure to gases or
vapours.
The response of the sensors may be compared against a library of
responses to known bacteria, or the response may be input to a
neural net trained against known bacteria.
The detection region may comprise an enclosed space above a Petri
dish or like laboratory culture dish.
The array of sensors may first be purged using a purging gas.
The invention also comprises apparatus for detecting bacteria
comprising detector means for detecting a gas or vapour associated
with the bacteria.
Said detector means may comprise an array of sensors of which an
electrical property varies according to exposure to gases or
vapours. The sensors may comprise semi-conducting polymers the
resistance or impedance of which varies according to exposure to
gases or vapours.
The apparatus may comprise a store for a library of responses to
known bacteria and comparison means operable automatically to
compare a given response against the library. The apparatus may
also comprise a neural net the input to which comprises the array
of sensors and which is trained against known bacteria.
The apparatus may comprise a probe for sampling a detection region
by abstracting gas or vapour from said region to be passed to said
detector means. Said probe may comprise a cover for enclosing a
Petri or like laboratory culture dish or an area of growth medium
thereon.
Said probe may comprise a carrier gas feed and return and the
apparatus may comprise a source of carrier gas.
Embodiments of apparatus and methods for detecting bacteria
according to the invention will now be described with reference to
the accompanying drawings, in which:
FIG. 1 is a diagrammatic illustration of a first embodiment;
FIG. 2 is a diagrammatic illustration of a second embodiment;
FIG. 3 is a diagrammatic illustration of an arrangement for
detecting bacteria on a culture dish;
FIG. 4 is a diagrammatic illustration of an arrangement for
detecting bacteria in a nutrient broth; and
FIG. 5 is a cluster analysis of vapour associated with three
species of bacteria.
The drawings illustrate methods and apparatus for detecting
bacteria comprising detecting gas or vapour associated with the
bacteria, and, further, methods for identifying bacteria by
differentiating such gas or vapour from gas or vapour associated
with other bacteria.
FIGS. 3 and 4 illustrate abstracting gas or vapour from a detection
region 11 and flowing the same over an array 12 of sensors 13 of
which an electrical property varies according to exposure to gases
or vapours and observing the response of the sensors 13.
The sensors 13 comprise semi-conducting polymers the resistance or
impedance of which varies according to exposure to gases or
vapours.
An array 12 of twenty sensors has been employed to distinguish the
vapours associated with the bacteria Straphylococcus aureus,
Eschericia coli and Group A beta-haemolytic streptococci.
Eight epidermiologically unrelated patient isolates of each species
were recovered from frozen storage. Each bacteria isolate was
cultured overnight in nutrient broth 40 in a glass Duran bottle 42
with a GL-45 screw cap. After overnight incubation at 37.degree. C.
the cap was changed for a cap 44 with inlet and outlet ports. After
a period of equilibration at 37.degree. C. the headspace vapour
above the broth 40 was analysed by pumping same across the 20
sensor array 12 at a flow rate of .about.150 ml min.sup.-1.
The outputs of the sensors 13 were analysed by computing means 46
employing the non-linear cluster analysis mapping technique of
Sammon (Sammon Jr., J. W., IEEE Trans. on computers, Vol. C-18, No.
5, May 1969, pp 401-409). FIG. 5 shows the results of this
analysis, indicating that excellent separation is achieved between
the clusters 50, 52, 54 associated with Straphylococcus aureus,
Eschericia coli and Group A beta-haemolytic streptococci
respectively.
FIG. 1 illustrates comparing the response of the sensors 13 against
a library 14 of responses to known bacteria. FIG. 2 illustrates
inputting the response to a neural net 15 trained against known
bacteria.
FIG. 3 illustrates a further sampling arrangement wherein the
detection region 11 comprises an enclosed space above a Petri dish
16 or like laboratory culture dish. A probe 17 comprises a cover
for enclosing an area of bacterial growth 18 on a growth medium 19
in the dish 16.
The probe 17 comprises a carrier gas feed 21 feeding a carrier gas
such for example as purified air or nitrogen. Prior to taking gas
or vapour from a sample in, say, a Petri dish, the array 12 of
sensors 13 is first purged of any residual substances from a
previous sensing operation by directing over the sensors 13 a
stream of purging gas, which, in this instance, is the same as the
carrier gas. The gas is supplied from a pressure bottle 22.
The sensors 13 can be selected for sensitivity to a broad spectrum
of gases or vapours associated with bacteria and the apparatus may
also be arranged to indicate concentration by measuring the level
of response. A broader spectrum and a greater sensitivity will be
obtained from a given array size by using a.c. technology as taught
in EP-B-0 286 307 than by simply measuring d.c. resistance.
In addition to bacteria, the method may be applied to the detection
of microfungi.
It may be important to specify the state of the microorganism when
making an observation. Gases or vapours associated with growing
bacteria or microfungi may well be different from gases or vapours
associated with the same organism in growth-arrest stage or when it
has been weakened or killed.
However, the library may contain data on the gases or vapours
associated with microorganisms in all possible states, or the
neural net trained to recognise them, so the apparatus may also
identify the state as well as the microorganism.
* * * * *