USRE38186EExpiredUtility

Method and apparatus for detecting microorganisms

Assignee: OSMETECH PLCPriority: Jun 9, 1994Filed: Jun 9, 1995Granted: Jul 15, 2003

Est. expiryJun 9, 2014(expired)· nominal 20-yr term from priority

Inventors:Peter Alfred Payne Krishna Chandra Persaud

C12Q 2304/40C12Q 1/04Y10S435/807

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Claims

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.

Claims

exact text as granted — not AI-modified

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 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; and

a library of responses to known microorganisms or known microorganism states.

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 , further 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 , further 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 , further 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.

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.

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.

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.

52. The method according to claim 50 , further comprising inputting the response to a neural net trained against known microorganisms.

53. The method according to claim 50 , further comprising performing a cluster analysis mapping of the sensor outputs.

54. The method according to claim 50 , wherein the detection region comprises an enclosed space above a Petri dish or other laboratory culture dish.

55. The method according to claim 50 , further comprising purging the array of sensors with a purging gas.

56. The method according to claim 50 , wherein the microorganism is a bacteria.

57. The method according to claim 50 , wherein the microorganism is a microfungi.

58. The method according to claim 50 , further comprising determining the state of the microorganism.

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.

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.

61. The method according to claim 59 , further comprising inputting the response to a neural net trained against known microorganisms.

62. The method according to claim 59 , further comprising performing a cluster analysis mapping of the sensor outputs.

63. The method according to claim 59 , wherein the detection region comprises and enclosed space above a Petri dish or other laboratory culture dish.

64. The method according to claim 59 , further comprising purging the array of sensors with a purging gas.

65. The method according to claim 59 , wherein the microorganism is a bacteria.

66. The method according to claim 59 , wherein the microorganism is a microfungi.

67. The method according to claim 59 , further comprising determining the state of the microorganism.

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.

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.

70. The method according to claim 68 , further comprising inputting the response to a neural net trained against known microorganism states.

71. The method according to claim 68 , further comprising performing a cluster analysis mapping of the sensor outputs.

72. The method according to claim 68 , wherein the detection region comprises an enclosed space above a Petri dish or other laboratory culture dish.

73. The method according to claim 68 , further comprising purging the array of sensors with a purging gas.

74. The method according to claim 68 , wherein the microorganism is a bacteria.

75. The method according to claim 68 , wherein the microorganism is a microfungi.

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.

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.

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.

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.

80. The method according to claim 77 , further comprising inputting the response to a neural net trained against known microorganisms.

81. The method according to claim 77 , further comprising performing a cluster analysis mapping of the sensor outputs.

82. The method according to claim 77 , wherein the detection region comprises an enclosed space above a Petri dish or other laboratory culture dish.

83. The method according to claim 77 , further comprising purging the array of sensors with a purging gas.

84. The method according to claim 77 , wherein the microorganism is a bacteria.

85. The method according to claim 77 , wherein the microorganism is a microfungi.

86. The method according to claim 77 , further comprising determining the state of the microorganism.

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