Methods of detecting mycobacterium avium subsp. paratuberculosis

Abstract

The present invention relates in part to methods of detecting Mycobacterium avium subsp. paratuberculosis in ruminant animals and markers for use in such methods.

Description

Methods of detecting Mycobacterium avium subsp. paratuberculosisTechnical Field

[0001] The present invention relates in part to methods of detecting Mycobacterium avium subsp. paratuberculosis in ruminant animals and markers for use in such methods.Background of Invention

[0002] Mycobacterium avium subsp. paratuberculosis (Map) is the causative agent of Johne's Disease (JD), a debilitating disease-causing chronic enteritis in domestic and wild ruminants. The disease is spread worldwide, causing significant economic loss to the dairy industry due to reduced milk production, culling of animals and reduced slaughter value. There is no cure for Johne's disease and control is complicated due to the progression and presentation of the disease. Infected animals slowly advance through four stages of the disease. In stage one (silent infection) there is no observable or detectable effects of the disease. There are also generally no observable effects in stage two, but some animals may start shedding low numbers of bacteria intermittently, and there is some evidence of cellular and humoral response. Stages three and four are characterized by the onset and progression of clinical disease, which can start from two years of age and up to 10 years after infection

[0003] Control and detection of JD is particularly challenging during the first couple of years when animals are not shedding the bacteria. Current diagnostic tests such as culture, ELISA and PCR have limitations for detecting the disease in the early stages and lack sensitivity due to low or non-existent antibody titres and faecal shedding and therefore these tests have the potential to provide false negatives in subclinical animals.

[0004] Currently, the most common method for detection of Map is culture directly from faeces, however due to the long replication time of the bacteria this method can take up to three months for a definitive result. Test and cull programs for control of JD on farm are the most widely deployed response but they are largely ineffective as they cannot control the spread of disease due to the poor sensitivities of the current testing methods. For successful control of disease, there remains a need for diagnostic methods to detect early infection.Summary of Invention

[0005] In one aspect, the present invention provides a method for determining the presence of Mycobacterium avium subsp. paratuberculosis in a subject, the method comprising the steps of: (a) determining the level of one or more volatile organic compounds in a sample from the subject; (b) comparing the level of said one or more volatile organic compounds in the sample with the level of said one or more volatile organic compounds in a negative control sample and / or a positive control sample to determine whether Mycobacterium avium subsp. paratuberculosis is present in the subject; wherein the one or more volatile organic compounds are selected from the group consisting of pentanal, 3- pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2- butanone, 2-butanol, 3-carene, p-cymene, D-limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

[0006] In one embodiment, the present invention provides a method as described herein, wherein the subject is a ruminant animal.

[0007] In another embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from ruminant faeces, the one or more volatile organic compounds are selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2- octanone.

[0008] In a further embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from ruminant faeces, the one or more volatile organic compounds are selected from the group consisting of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol.

[0009] In another embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from cattle faeces, and the one or more volatile organic compounds are selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one(Z)- and 2-octanone. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of pentanal, hexanal, and l-octen-3-ol, and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control sample indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

[0010] In another embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from sheep faeces, and the one or more volatile organic compounds are selected from the group consisting of dimethylamine, pentanal, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, hexanal, 6-octen-2-one (Z)-, and 2-octanone. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 6- octen-2-one (Z)-, and 2-octanone, and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of pentanal and hexanal, and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control sample indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

[0011] In another embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a cattle faecal sample, andthe one or more volatile organic compounds are selected from the group consisting of methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p- cymene, D-limonene, and phenol 3-methyl. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of acetone, 2-butanone, 2-butanol, and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control sample indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

[0012] In another embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a sheep faecal sample, and the one or more volatile organic compounds are selected from the group consisting of methanthiol, dimethyl sulfide, ethanthiol, disulfide dimethyl, 1-butanol 3-methyl, dimethyl trisulfide, phenol and phenol 3-methyl. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of methanthiol, disulfide dimethyl, 1-butanol 3-methyl, dimethyl trisulfide, and phenol and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject. In another embodiment, the present invention provides a method as described herein, wherein the one or more volatile organic compounds are selected from the group consisting of dimethyl sulfide, ethanthiol, and phenol 3-methyl and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

[0013] In another embodiment, the present invention provides a method as described herein, wherein the sample from a culture prepared from ruminant faeces is headspace gas obtained from the culture, or the sample from ruminant faeces is headspace gas obtained from the ruminant faeces.

[0014] In another embodiment, the present invention provides a method as described herein, wherein the step of (a) determining the level of one or more volatile organic compounds in a sample from the subject comprises Solid Phase Micro Extraction (SPME) of headspace gas obtained from the sample.

[0015] In another embodiment, the present invention provides a method as described herein, wherein the step of (a) determining the level of one or more volatile organic compounds in a sample from the subject comprises using gas chromatography-mass spectrometry.

[0016] In another aspect, the present invention provides a method for detecting, by means of an electronic nose, Mycobacterium avium subsp. paratuberculosis in sample, comprising the steps of a) providing a sample from a ruminant animal; b) contacting a sensor array of said electronic nose to a portion of a gaseous sample released from said sample, and processing a plurality of sensor array output signals emitted by the sensor array; c) obtaining an olfactory signature which characterizes said sample, and d) comparing the olfactory signature which characterises the sample with one or more olfactory signatures which characterise a Mycobacterium avium subsp. paratuberculosis -positive control sample and / or a Mycobacterium avium subsp. paratuberculosis negative control sample.

[0017] In another aspect, the present invention provides a method for detecting as described herein, wherein the control sample is a gaseous sample released from a sample not comprising Mycobacterium avium subsp. paratuberculosis.

[0018] In another aspect, the present invention provides a method for detecting as described herein, wherein the control sample is a gaseous sample released from a sample comprising Mycobacterium avium subsp. paratuberculosis.

[0019] In another aspect, the present invention provides a method for detecting as described herein, wherein the Mycobacterium avium subsp. paratuberculosis positive control sample and / or a Mycobacterium avium subsp. paratuberculosis negative control sample comprise one or more volatile organic compound selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, D-limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

[0020] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of methanthiol, dimethyl sulfide, ethanthiol, 3- carene, p-cymene, D-limonene, and phenol 3-methyl relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

[0021] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more of acetone, 2-butanone, and 2-butanol relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

[0022] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

[0023] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the Mycobacterium avium subsp. paratuberculosis negative control samplecomprises increased levels of one or more of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

[0024] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of 3-pentanone, 1-butanol 3-methyl, 6- octen-2-one (Z)- and 2-octanone relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

[0025] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more of pentanal, hexanal, and l-octen-3-ol relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

[0026] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the ruminant animal is headspace gas from a culture of sheep faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

[0027] In another aspect, the present invention provides a method for detecting as described herein, wherein when the sample from the subject is headspace gas from a culture of sheep faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more of pentanal and hexanal relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.Brief Description of Drawings

[0028] Figure 1: Illustration of the eNose apparatus for sampling faeces in 200 mL plastic containers.

[0029] Figure 2: (A) 2D Principal component analysis (PCA) scores plot of the volatile organic compounds (VOCs) collected from the headspace of Map positive (green square) and Map negative (blue triangle) cattle cultures at four weeks of culture showing grouping pattern of samples according to the first two principal components, (B) Contribution of individual VOCs to principal component 1 is shown in the loadings plot for the cattle cultures at four weeks of culture with seven putative biomarkers, influencing separation on PCI (UK23, UK24, UK30, UK40, UK59, UK60, UK61).

[0030] Figure 3: (A) 2D PCA scores plot of the VOCs collected from the headspace of Map positive (green square) and Map negative (blue triangle) sheep faecal cultures at six weeks of culture showing the clustering pattern of samples according to the first two principal components, (B) Contribution of individual VOCs to principal component 1 is shown in the loadings plot for sheep cultures at six weeks of culture showing eight putative biomarkers, responsible for separation on PCI (UK3, UK23, UK24, UK30, UK38, UK40, UK60, UK61).

[0031] Figure 4: (A) Partial least squares discriminant analysis (PLS-DA) plot of the VOCs collected from the headspace of cattle faeces showing grouping pattern of Map positive (green square) and Map negative (blue triangle) cattle faeces according to the first two latent variables (LV), (B) Contribution of individual VOCs to LV1 of cattle faeces showing ten putative biomarkers, important for separation on LV1 (UK2, UK5, UK6, UK7, UK15, UK16, UK49, UK64, UK65 and UK72).

[0032] Figure 5: (A) PLS-DA plot showing of the VOCs collected from the headspace of sheep faeces showing grouping pattern of Map positive (green square) and Map negative (blue triangle) sheep faeces according to the first two latent variables (LV1 and LV2), (B, C) Contribution of individual VOCs to LV1 and LV2 of sheep faeces showing eight putative biomarkers, important for separation on LV1 (UK2, UK6, UK7, UK26, UK30, UK57, UK70, UK72).

[0033] Figure 6: (A) 2D PCA scores plot of the Map-infected and non-infected cattle faeces used in the training set as determined by the eNose software. Red represents positive Map faecal samples 1-10 (right hand cluster) and blue represents negative Map faecal samples 1- 10 (left hand cluster), (B) 2D Principal component analysis (PCA) scores plot of the Map- infected (red, right hand cluster) and non-infected (blue, left hand cluster) sheep faeces used in the training set as determined by the eNose software. The software displays three principal components (factors), Fl, F2 and F3.

[0034] Figure 7: (A) PLS-DA predicted model plot showing test sample prediction, Map positive (green square) and Map negative (red diamond) cattle faeces (eNose data analysed using Matlab and PLSToolbox) (B) PLS-DA predicted model plot showing test sample prediction, Map positive (green square) and Map negative (red diamond) sheep faeces (eNose data analysed using Matlab and PLSToolbox).Detailed Description

[0035] Currently the gold standard for detection of Mycobacterium avium subsp. paratuberculosis (Map) is culture, which has high specificity but a lower sensitivity due to the intermittent shedding of the organism, formation of clumps and the decontamination process required for culture. Diagnosis of Johne's disease (JD, caused by Map) is also time consuming as culture of Map can take from two to eight months to grow, prolonging the time to diagnosis and then presence or absence of JD is determined by PCR. More rapid techniques like direct faecal qPCR are used but performance is limited, mainly based on the efficacy of the nucleic acid extraction procedure due to inhibition in matrices like faeces. PCR can also detect dead bacteria and so may detect transient infection giving rise to false positive results. Without wishing to be bound by theory, the present inventors propose that the methods of detection of "smellprints" of more than one volatile organic compound described herein do not have these drawbacks, as they are analysing volatile organic compounds that are being emitted at the time of sampling.

[0036] The present inventors have identified volatile organic compounds (VOCs) in the headspace gas of faecal cultures and directly from faeces from cattle and sheep with Map infection. Importantly, the present inventors have demonstrated the VOCs identified can be used to differentiate between Map positive samples from animals and Map negative samples from animals.

[0037] Importantly, the data presented herein represents the first investigation of detecting VOC profiles as potential biomarkers for detection of Map in sheep faeces. It is also the first time that a portable electronic nose has been trained for detection of Map in cattle and sheep.

[0038] Accordingly, in one embodiment, the present invention provides a method for determining the presence of Mycobacterium avium subsp. paratuberculosis in a subject, the method comprising the steps of: (a) determining the level of one or more volatile organic compounds in a sample from the subject; (b) comparing the level of said one or more volatile organic compounds in the sample with the level of said one or more volatile organic compounds in a negative control sample and / or a positive control sample to determine whether Mycobacterium avium subsp. paratuberculosis is present in the subject; wherein the one or more volatile organic compounds are selected from the group consisting of the 22 compounds in Table 2, namely: pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 1-octen- 3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, D- limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

[0039] In another embodiment, the method comprises determining the level of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 of the volatile organic compounds of Table 2.

[0040] As used herein "Mycobacterium avium subsp. paratuberculosis” refers to the obligate pathogenic bacterium in the genus Mycobacterium also abbreviated as Map, M. paratuberculosis or M. avium ssp. paratuberculosis. It is the causative agent of Johne's disease (also referred to as paratuberculosis), which primarily affects ruminants, but which can alsoinfect nonruminant species such as rabbits, foxes, and birds. Horses, dogs, and nonhuman primates can also be infected.

[0041] As used herein the term "subject" refers to an animal at risk of Map infection. As discussed above, Map causes paratuberculosis, a chronic disease which primarily affects ruminants, although cases have also been described in a variety of other animals including, for example, rabbits, foxes, and birds. Horses, dogs, and nonhuman primates can also be infected. Accordingly, in one aspect the subject is an animal.

[0042] In a preferred embodiment, the animal is a ruminant animal. As used herein "ruminant animal" refers to herbivorous grazing or browsing artiodactyls belonging to the suborder Ruminanti orTylopoda. Ruminant animals include cattle, sheep, goats, giraffes, yaks, deer, antelope, camels, buffalo, elk, bison, moose, alpacas, llamas, gazelles, pronghorns, okapis and chevrotains.

[0043] In a preferred embodiment, the ruminant animal is a domesticated livestock such as cattle, goats, sheep, deer, alpacas and llamas.

[0044] As used herein, "determining the level of a volatile organic compound" refers to measuring the level of a VOC in a sample using any suitable means including those described herein. Determining a level can include methods of statistical analysis of data, such as mass spectrometry data, including Principal Components Analysis (PCA) and partial least squares- discriminant analysis (PLS-DA), as described in the Examples.

[0045] For example, in the Examples gas chromatography-mass spectrometry with solid phase micro extraction (SPME-GC-MS) has been used to identify VOCs in the headspace of faecal cultures and directly from faeces from both cattle and sheep. These VOCs were used in PLS-DA models to determine if they could be used to differentiate between Map positive and Map negative samples.

[0046] Methods of determining levels of VOCs in a sample are known in the art. For example, a level of a VOC may be determined using mass spectrometry, for example high resolution mass spectrometry (HR-MS), gas chromatography time-of-flight mass spectrometry(GC-MS), flow infusion electrospray high resolution mass spectrometry (FIE-HRMS) or liquid chromatography-electrospray mass spectrometry (LC-MS).

[0047] GC-MS involves linking a gas chromatograph with a mass spectrometer. The gas chromatograph utilizes a capillary column where the chemical properties between the sampled chemicals in a mixture and their relative affinity for the stationary phase of the column will result in their separation along the column. This provides "retention time", information. The chemicals then enter the mass spectrometer which will show mass-to-charge ratios.

[0048] LC-MS links liquid chromatography (LC or High Performance LC [HPLC]) with a mass spectrometer. The LC part physically separates chemicals between a liquid mixture of two immiscible phases, i.e., stationary and mobile. The chemicals then enter the mass spectrometer which will show mass-to-charge ratios.

[0049] In flow infusion, samples are injected directly into a solvent (usually methanolwater) line leading to a mass spectrometer.

[0050] Alternatively, the level of a VOC may be determined using NMR, enzymatic assays (e.g. enzymatic reaction followed by colorimetric detection) or immunoassays (i.e. antibody binding based assays), where available.

[0051] The way the level of increase is determined will depend on the method of determining the level of the VOC. In one embodiment, the level of increase is a statistically significant increase above the level of the control.

[0052] The present inventors have demonstrated herein that faecal samples can be cultured, and samples prepared from the cultures on different days post inoculation. For example, in the Examples, samples were prepared two, four, six, eight, ten, and twelve weeks post inoculation.

[0053] Accordingly, in one embodiment, the sample is prepared 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, and / or 14 days or more post inoculation, or 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and / or 12 weeks post inoculation of a culture.

[0054] The present inventors have also demonstrated herein that faecal samples can be tested directly, e.g. without the need for culturing bacteria from the faeces.

[0055] Accordingly, in one embodiment, the sample is prepared directly from faeces.

[0056] The term "level of volatile organic compound" as used herein refers to the amount of a VOC present in a sample. The amount of VOC can be compared with a control standard (e.g. an internal control level of VOC), or compared with a control sample of known characteristics (e.g. a sample confirmed to not contain Map, or a sample confirmed to not contain Map).

[0057] As described herein the present inventors have characterised the presence of 72 VOCs in samples from faeces or from cultures prepared from faeces. Accordingly, in one embodiment, the present invention provides a method as described herein, wherein the method comprises determining the level of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine or at least ten or more VOCs in a sample from the subject.

[0058] In one embodiment, the VOCs to be detected are selected from the group consisting of the 22 compounds in Table 2, namely: pentanal, 3-pentanone, 1-butanol 3- methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2- methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, D-limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

[0059] In another embodiment, the method comprises determining the level of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 of the volatile organic compounds of Table 2.

[0060] Importantly, the present inventors have demonstrated that the level of a number of these VOCs are increased relative to a negative control when the sample tested is from a subject with Map, and that the level of a number of these volatile organic compounds are increased in negative control samples relative to a sample from a subject with Map.

[0061] For example, the present inventors have demonstrated in the Examples that cultures prepared from ruminant faeces from subjects infected with Map have an altered level of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone.

[0062] Importantly, it was possible that VOCs in faeces may originate from Map itself, from intestinal inflammation and the local immune response as well as the intestinal content itself (e.g. digested food, other intestinal bacteria). To determine if a culture technique could be used with VOC detection to validate the methods described herein and also predict positives with reduced times, VOC analysis was performed on the headspace of cultures from faeces at two-week intervals, starting from two weeks and finishing at 12 weeks which is the normal time period for routine Map culture. Sheep and cattle samples were analysed separately so that variations specific to the sample type could be detected. Through PCA and loading plots, seven main biomarkers were identified in cattle cultures (pentanal, hexanal, 1- octan-3-ol, 6-octen-2-one (Z), 2-octanone, 1-butanol 3-methyl, and 3-pentanone). Four of the compounds were upregulated in the positive cattle cultures and three were upregulated in the negative cattle cultures and could be used to discriminate between positive and negative cultures. Eight biomarkers were identified in the sheep cultures (dimethylamine, pentanal, hexanal, 6-octen-2-one (Z)-, 2-octanone, 1-butanol 3-methyl, 1-butanol 2-methyl and 3- pentanone). Six compounds were upregulated in the positive sheep cultures and two were upregulated in the negative sheep cultures. These eight putative biomarkers could be used to differentiate between positive and negative sheep cultures. Three compounds (dimethylamine, 1-butanol 2-methyl, and l-octen-3-ol) were only identified in eitherthe cattle or sheep and could be used to differentiate between Type S (sheep) and Type C (cattle) Map in culture samples. The data presented herein is the first time that 6-octen-2-one, (Z)- has been detected in sheep faecal cultures.

[0063] The time to detection of the VOCs was also much less than the time required for culture followed by PCR; for cattle cultures VOC was able to discriminate between positive and negative Map at four weeks and in sheep at six weeks of incubation.

[0064] The present inventors have also demonstrated in the Examples that cultures prepared from ruminant faeces from subjects infected with Map have an altered level of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol.

[0065] PLS-DA score plots were used to evaluate both the cattle and sheep faecal data.

[0066] PLS-DA is a supervised dimensionality reduction method that includes class labels(e.g. positive vs negative) in the analysis. PLS-DA identifies components that maximise the separation between the classes and can determine the biomarkers that can differentiate between positive and negative samples more effectively and predict the effectiveness of the test in a diagnostic situation. PLS-DA and loading plots identified 10 biomarkers in the cattle faeces (acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, D- limonene, methanthiol and phenol 3-methyl). Six of these compounds were upregulated in the positive cattle and three were upregulated in the negative cattle samples.

[0067] PLS-DA evaluation of the test method for identifying biomarkers to differentiate between Map positive and Map negative cattle faeces resulted in a high sensitivity and specificity of 92.3% and 98.1% respectively. These results along with the low class error of 4.8% indicate that VOC analysis of headspace in cattle faeces has a higher discriminatory power than current diagnostic tests such as indirect ELISA that are known to have sensitivities ranging from 16% to 34.9% (Begg DJ, Whittington R. Paratuberculosis in Sheep. In: Behr MA, Collins DM, editors. Paratuberculosis: Organism, Disease, Control: CAB International, Wallington, United Kingdom. 2010. p. 157-68.). Traditional culture is said to be almost 100% specific, but lacks sensitivity due to a number of factors: intermittent shedding of Map, formation of clumps and the decontamination process during culture preparation. The present inventors propose that VOC analysis does not have these drawbacks and therefore even with a slightly lower specificity than culture it may have a higher and more accurate detection rate within a herd.

[0068] PLS-DA and loading plots identified eight biomarkers that could be used to discriminate between positive and negative sheep faeces (dimethyl sulfide, ethanthiol, disulfide dimethyl, phenol 3-methyl, 1-butanol 3-methyl, methanethiol, dimethyl trisulfide and phenol). Six of the compounds were elevated in the positive sheep faeces and three were up regulated in the negative faeces, as is discussed in more detail below.

[0069] PLS-DA evaluation of the test method for identifying biomarkers to differentiate between Map positive and Map negative sheep faeces resulted in 100% sensitivity and specificity, with no class error. This suggests that this method has a very high discriminatory power for detection of Map in sheep faeces that may be better than all other current diagnostic tests including the gold standard culture.

[0070] Without wishing to be bound by theory, the present inventors propose that by determining the level of one or more VOCs in sample and comparing those levels with the levels in a control sample (e.g. a negative control and / or a positive control), the sensitivity and / or specificity of the determination of whether the subject has Map may be increased.

[0071] The VOCs described herein can be considered markers for the presence or absence of Map. A specific combination of marker volatile organic compounds are referred to herein as a "panel" of markers. For example, in one embodiment, the methods described herein include determining the levels of a panel of VOCs. Panels of volatile organic compounds to be detected are discussed in more detail below.

[0072] As used herein a "sample" from a subject refers to a biological sample from a subject, and includes faeces, blood and blood components (e.g. serum), mucus, saliva, urine, vomit, sweat, semen, vaginal secretion, tears, pus, milk or colostrum. The term includes samples derived from a sample from a subject, such as a culture of a sample of from a subject. Such samples include cultures from faeces, and sample from such samples, such as headspace gas from faeces, from a culture from faeces, or a liquid sample from faeces or a culture of faeces.

[0073] In a one preferred embodiment the sample is from faeces from an animal.

[0074] In another preferred embodiment, the sample is from a culture of faeces from an animal.

[0075] As discussed briefly above, comparing the level of one or more VOCs with the level of said one or more VOCs in a control sample to determine whether Map is present in the subject (or absent) can be performed using a control sample such as a control standard, or a sample of known characteristics. Without wishing to be bound by theory, once the levels ofone or more VOCs are known to be increased or decreased in samples from subjects with Map, the level of the one or more VOCs can be compared to reference level (e.g. a threshold level of the one or more VOCs), or a control standard comprising known levels of the one or more VOCs. In some embodiments the control standard is an internal control or an external control.

[0076] Exemplary standards are also used in the Examples.

[0077] As used herein, the term "negative control" includes a sample taken from a subject not infected with Map, and / or a sample confirmed to not contain Map. The term includes samples from faeces of a subject not infected with Map, including from cultures from faeces from a subject not infected with Map.

[0078] As used herein, the term "positive control" includes a sample taken from a subject infected with Map, and / or a sample confirmed to contain Map. The term includes samples from faeces of a subject infected with Map, including from cultures from faeces from a subject infected with Map.

[0079] As will be appreciated by the skilled person, the nature of the control sample will depend upon the particular subject being tested, and the nature of the method of detecting.

[0080] For example, as will be discussed in more detail below, the control sample may be used to train device, such as an eNose, to distinguish between samples confirmed to not contain Map (a negative control) and samples confirmed to contain Map (a positive control).

[0081] Accordingly, in one embodiment, samples confirmed to not contain Map and samples confirmed to contain Map are used.

[0082] In one embodiment, the control sample is confirmed to not contain Map by PCR and / or by culture.

[0083] In another embodiment, the control sample is a positive control sample confirmed to contain Map.

[0084] For example, in one embodiment, the control is a sample taken from a subject infected with Map, and / or a sample confirmed to contain Map by PCR and / or by culture.

[0085] The present inventors have demonstrated that the levels of VOCs in samples taken over a period of time can be used, as well as at single timepoints, including directly from faeces.

[0086] For example, when the sample from the subject is a sample from Map positive ruminant faeces, the one or more VOCs that are altered include methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol, as is shown in the Examples.

[0087] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein the one or more VOCs are selected from the group consisting of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol. In another embodiment, the method comprises determining the level of two or more of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol. In a further embodiment, the method comprises determining the level of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol.

[0088] In another embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from ruminant faeces, the one or more VOCs are selected from the group consisting of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol. In another embodiment, the method comprises determining the level of two or more of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol. In a further embodiment, the method comprises determining the level of methanthiol, dimethyl sulfide, phenol 3-methyland ethanthiol.

[0089] The present inventors have also demonstrated that when the sample from the subject is from a culture prepared from Map positive ruminant faeces, the one or more VOCs that are altered include pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone.

[0090] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein the one or more VOCs are selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone. In another embodiment, the method comprises determining the level of two, three, four, or five of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone. Ina further embodiment, the method comprises determining the level of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone.

[0091] In one embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a culture from ruminant faeces, the one or more VOCs are selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone. In another embodiment, the method comprises determining the level of two, three, four, five, or six of pentanal, 3-pentanone, 1-butanol 3- methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone. In a further embodiment, the method comprises determining the level of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6- octen-2-one (Z)- and 2-octanone.

[0092] The present inventors have demonstrated that when the sample is from Map positive cattle faeces, the one or more VOCs that are altered include methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl.

[0093] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is from cattle faeces, the one or more VOCs are selected from the group consisting of methanthiol, acetone, dimethyl sulfide, ethanthiol, 2- butanone, 2-butanol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl. In another embodiment, the method comprises determining the level of two, three, four, five, six, seven, eight or nine of methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3- carene, p-cymene, D-limonene, and phenol 3-methyl. In a further embodiment, the method comprises determining the level of methanthiol, acetone, dimethyl sulfide, ethanthiol, 2- butanone, 2-butanol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl.

[0094] The present inventors have also demonstrated that when the sample is from Map positive cattle faeces, the one or more VOCs that are increased in a sample from the subject relative to the level of the one or more VOCs in the negative control sample include methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3- methyl.

[0095] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is from cattle faeces, the one or more VOCs are selected from the group consisting of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p- cymene, D-limonene, and phenol 3-methyl, wherein an increased level of the one or more the VOCs in the sample from the subject relative to the level of the one or more VOCs in the negative control sample indicates Map is present in the subject. In another embodiment, the method comprises determining the level of two, three, four, five or six of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl. In a further embodiment, the method comprises determining the level of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl.

[0096] The present inventors have also demonstrated that when the sample is from Map positive cattle faeces, the one or more VOCs that are increased in a negative control sample relative to the level of the one or more VOCs in the sample from the subject include acetone, 2-butanone, and 2-butanol.

[0097] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is from cattle faeces, the one or more VOCs are selected from the group consisting of acetone, 2-butanone, and 2-butanol, wherein an increased level of the one or more VOCs in the sample from the subject relative to the level of the one or more VOCs in the positive control sample indicates Map is not present in the subject. In another embodiment, the method comprises determining the level of two or more of acetone, 2-butanone, and 2-butanol. In a further embodiment, the method comprises determining the level of acetone, 2-butanone, and 2-butanol.

[0098] The present inventors have demonstrated that when the sample is from Map positive sheep faeces, the one or more VOCs that are altered include methanthiol, dimethyl sulfide, ethanthiol, disulfide dimethyl, 1-butanol 3-methyl, dimethyl trisulfide, phenol, and phenol 3-methyl.

[0099] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is from sheep faeces, the one or more VOCs are selected from the group consisting of methanthiol, dimethyl sulfide, ethanthiol, disulfidedimethyl, 1-butanol 3-methyl, dimethyl trisulfide, phenol, and phenol 3-methyl. In another embodiment, the method comprises determining the level of two, three, four, five, six or seven of methanthiol, dimethyl sulfide, ethanthiol, disulfide dimethyl, 1-butanol 3-methyl, dimethyl trisulfide, phenol, and phenol 3-methyl. In a further embodiment, the method comprises determining the level of methanthiol, dimethyl sulfide, ethanthiol, disulfide dimethyl, 1- butanol 3-methyl, dimethyl trisulfide, and phenol, phenol 3-methyl.

[0100] The present inventors have demonstrated that when the sample is from Map positive sheep faeces, the one or more VOCs that are increased in a sample from the subject relative to the level of the one or more VOCs in the negative control sample include methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl.

[0101] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is from sheep faeces, the one or more VOCs are selected from the group consisting of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl , wherein an increased level of the one or more the VOCs in the sample from the subject relative to the level of the one or more VOCs in the negative control sample indicates Map is present in the subject. In another embodiment, the method comprises determining the level of two, three, or four of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl. In a further embodiment, the method comprises determining the level of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl.

[0102] The present inventors have also demonstrated that when the sample is from Map positive sheep faeces, the one or more VOCs that are increased in a negative control sample relative to the level of the one or more volatile organic compounds in the sample from the subject include dimethyl sulfide, ethanthiol, and phenol 3-methyl.

[0103] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is from sheep faeces, the one or more VOCs are selected from the group consisting of dimethyl sulfide, ethanthiol, and phenol 3-methyl, wherein an increased level of the one or more VOCs in the sample from the subject relative to the level of the one or more VOCs in positive control indicates Map is not present in thesubject. In another embodiment, the method comprises determining the level of two of dimethyl sulfide, ethanthiol, and phenol 3-methyl. In another embodiment, the method comprises determining the level of dimethyl sulfide, ethanthiol, and phenol 3-methyl.

[0104] The present inventors have also demonstrated that when the sample from the subject is a sample from a culture prepared from Map positive sheep faeces, the one or more VOCs that are altered include dimethylamine, pentanal, 3-pentanone, 1-butanol 3-methyl, 1- butanol 2-methyl, hexanal, 6-octen-2-one (Z)-, and 2-octanone.

[0105] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from sheep faeces, the one or more VOCs are selected from the group consisting of dimethylamine, pentanal, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, hexanal, 6- octen-2-one (Z)-, and 2-octanone. In another embodiment, the method comprises determining the level of two, three, four, or five of dimethylamine, pentanal, 3-pentanone, 1-butanol 3- methyl, 1-butanol 2-methyl, hexanal, 6-octen-2-one (Z)-, and 2-octanone. In a further embodiment, the method comprises determining the level of dimethylamine, pentanal, 3- pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, hexanal, 6-octen-2-one (Z)-, and 2- octanone.

[0106] The present inventors have also demonstrated that when the sample is from a culture prepared from Map positive sheep faeces, the one or more VOCs that are increased in a sample from the subject relative to the level of the one or more VOCs in the negative control sample include dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6- octen-2-one (Z)-, and 2-octanone.

[0107] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from sheep faeces, the one or more VOCs are selected from the group consisting of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone wherein an increased level of the one or more the VOCs in the sample from the subject relative to the level of the one or more VOCs in the negative control sample indicates Map is present in the subject. In another embodiment, the method comprises determining thelevel of two, three, four or five of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone. In a further embodiment, the method comprises determining the level of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2- methyl, 6-octen-2-one (Z)-, and 2-octanone.

[0108] The present inventors have also demonstrated that when the sample from a subject is a sample from a culture prepared from Map positive sheep faeces, the one or more VOCs that are increased in the negative control sample relative to the level of the one or more VOCs in the sample from the subject include pentanal and hexanal.

[0109] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is a sample from a culture prepared from sheep faeces, the one or more VOCs are selected from the group consisting of pentanal and hexanal, wherein an increased level of the one or more VOCs in the sample from the subject relative to the level of the one or more VOCs in the positive control indicates Map is not present in the subject. In another embodiment, the method comprises determining the level of pentanal and hexanal.

[0110] The present inventors have also demonstrated that when the sample from the subject is a sample from a culture prepared from Map positive cattle faeces, the one or more VOCs that are altered include pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, l-octen-3- ol, 6-octen-2-one (Z)- and 2-octanone.

[0111] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from cattle faeces, the one or more VOCs are selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)- and 2- octanone). In another embodiment, the method comprises determining the level of two, three, four, five, or six of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen- 2-one (Z)- and 2-octanone. In a further embodiment, the method comprises determining the level of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)- and 2-octanone.

[0112] The present inventors have also demonstrated that when the sample a sample from a culture prepared from Map positive cattle faeces, the one or more VOCs that are increased in a sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample include 3-pentanone, 1-butanol 3-methyl, 6-octen- 2-one (Z)- and 2-octanone.

[0113] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample from the subject is a sample from a culture prepared from cattle faeces, the one or more volatile organic compounds are selected from the group consisting of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone, wherein an increased level of the one or more the VOCs in the sample from the subject relative to the level of the one or more VOCs in the negative control sample indicates Map is present in the subject. In another embodiment, the method comprises determining the level of two, or three of3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone. In a further embodiment, the method comprises determining the level of 3-pentanone, 1-butanol 3- methyl, 6-octen-2-one (Z)- and 2-octanone.

[0114] The present inventors have demonstrated that when the sample from a subject is a sample from a culture prepared from Map positive cattle faeces, the one or more VOCs that are increased in the negative control sample relative to the sample from the subject includes pentanal, hexanal, and l-octen-3-ol.

[0115] Accordingly, in one embodiment, the present invention provides a method as described herein, wherein when the sample is a sample from a culture prepared from cattle faeces, the one or more VOCs are selected from the group consisting of pentanal, hexanal, and l-octen-3-ol, wherein an increased level of the one or more VOCs in the sample from the subject relative to the level of the one or more VOCs in the positive control sample indicates Map is not present in the subject. In another embodiment, the method comprises determining the level of two of pentanal, hexanal, and l-octen-3-ol. In a further embodiment, the method comprises determining the level of pentanal, hexanal, and l-octen-3-ol.

[0116] Point-of-care testing is becoming increasingly essential for the rapid detection of diseases near to the subject enabling better disease diagnosis and management. This isparticularly important with a disease like Johne's Disease that is spread rapidly on a farm and has no treatment or cure.

[0117] An electronic nose (eNose) was evaluated to determine if this technology could be used as a point of care tool to detect Map in faeces from both cattle and sheep.

[0118] A point-of-care-gas sensing system, electronic nose or eNose device mimic olfactory receptors in the human nose to differentiate objects according to odour or volatile compounds. It consists of a gas sensor array having global selectivity and chemometric modelbased signal analysis. eNoses are advantageous in that they require only simple sample preparation that does not require extraction or reagents, and are easy and inexpensive to operate.

[0119] An eNose comprises an array of metal oxide semiconductor (MOS) gas sensors, in one example, 32 different MOS gas sensors, communicatively coupled to a gas sampling unit, a data acquisition unit, and a pattern recognition system. The sensor array generates a plurality of output signals in response to the detected odour, which output signals constitute input to a pattern recognition system to analyze data and identify and classify the chemicals contained in the gas exposed to the sensor array. The pattern recognition system uses olfactory reference data which is learned and stored electronically for comparison with sensor array output signals to identify and quantitatively measure detected chemicals. The system can be used as a portable chemical analysis system to identify chemicals present at a location and provide a quantitative measurement in real time.

[0120] The pattern recognition system can include various systems and methods including advanced pattern recognition algorithms to detect and recognize the chemical vapor or mixture of interest via its headspace composition or smell. Statistical methods such as principal component analysis (PCA), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA including linear discriminant analysis (LDA) and canonical discriminant analysis (CDA), and / or supervised learning classifiers such as the non-parametric, supervised learning classifier KNN, enable rapid detection and identification of substances based on their chemical profile.

[0121] In brief, in Example 6, PCA and canonical discriminate analysis were used to develop a model that could differentiate between infected and non-infected cattle and sheep faecal samples. Faecal samples such as those described herein were used in Example 6 to train the eNose. As is shown in Example 6, CDA analysis indicated that there was enough VOCs present in the samples to allow for discrimination between Map positive and Map negative faeces. Further validation of the models demonstrated that the eNose can discriminate between Map infected and non-infected sheep and cattle faeces. The specificity of the eNose was high for both sheep and cattle, being 88.9% and 100% respectively. In sheep and cattle, the sensitivity of the eNose was 100%. The eNose used only allows for 20 samples to be used for training (10 negative and 10 positive) and therefore with this limited number the PCA may have overfitted the data, however the PLSDA plots show that good models can be obtained.

[0122] Accordingly, in one embodiment the present invention provides a method for detecting, by means of an electronic nose, Mycobacterium avium subsp. paratuberculosis in sample, comprising the steps of a) providing a sample from a ruminant animal; b) contacting a sensor array of said electronic nose to a portion of a gaseous sample released from said sample, and processing a plurality of sensor array output signals emitted by the sensor array; c) obtaining an olfactory signature which characterizes said sample, and d) comparing the olfactory signature which characterises the sample with one or more olfactory signatures which characterise a map-positive control sample and / or a mapnegative control sample.

[0123] In one embodiment, the map-positive control sample and / or the map-negative control sample comprise one or more VOC selected from the group consisting of the 22 compounds in Table 2, namely: pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 1-octen- 3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, D- limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, phenol.

[0124] In another embodiment, the method comprises determining the level of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 of the volatile organic compounds of Table 2.

[0125] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the Map-positive control sample comprises increased levels of one or more of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl relative to headspace gas from the Map-negative control sample.

[0126] In another embodiment, the Map-positive control sample comprises increased levels of two, three, four, five, or six of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p- cymene, D-limonene, and phenol 3-methyl relative to headspace gas from the Map-negative control sample.

[0127] In a further embodiment, Map-positive control sample comprises increased levels of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3- methyl relative to headspace gas from the Map-negative control sample.

[0128] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the Map-negative control sample comprises increased levels of one or more of acetone, 2-butanone, and 2-butanol relative to headspace gas from the Mappositive control sample.

[0129] In another embodiment, the Map-negative control sample comprises increased levels of two of acetone, 2-butanone, and 2-butanol relative to headspace gas from the Mappositive control sample.

[0130] In a further embodiment, Map-negative control sample comprises increased levels of acetone, 2-butanone, and 2-butanol relative to headspace gas from the Map-positive control sample.

[0131] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the Map-positive control sample comprises increased levelsof one or more of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to headspace gas from the Map-negative control sample.

[0132] In another embodiment, the Map-positive control sample comprises increased levels of two, three, of four of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to headspace gas from the Map-negative control sample.

[0133] In a further embodiment, Map-positive control sample comprises increased levels of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to headspace gas from the Map-negative control sample.

[0134] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the Map-negative control sample comprises increased levels of one or more of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to headspace gas from the Map-positive control sample.

[0135] In another embodiment, the Map-negative control sample comprises increased levels of two of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to headspace gas from the Map-positive control sample.

[0136] In a further embodiment, Map-negative control sample comprises increased levels of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to headspace gas from the Mappositive control sample.

[0137] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the Map-positive control sample comprises increased levels of one or more of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2- octanone relative to headspace gas from the Map-negative control sample.

[0138] In another embodiment, the Map-positive control sample comprises increased levels of two or three of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone relative to headspace gas from the Map-negative control sample.

[0139] In a further embodiment, Map-positive control sample comprises increased levels of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone relative to headspace gas from the Map-negative control sample.

[0140] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the Map-negative control sample comprises increased levels of one or more of pentanal, hexanal, and l-octen-3-ol relative to headspace gas from the Map-positive control sample.

[0141] In another embodiment, the Map-negative control sample comprises increased levels of two of pentanal, hexanal, and l-octen-3-ol relative to headspace gas from the Mappositive control sample.

[0142] In a further embodiment, Map-negative control sample comprises increased levels of pentanal, hexanal, and l-octen-3-ol relative to headspace gas from the Map-positive control sample.

[0143] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from a culture of sheep faeces, the Map-positive control sample comprises increased levels of one or more of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1- butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone relative to headspace gas from the Mapnegative control sample.

[0144] In another embodiment, the Map-positive control sample comprises increased levels of two, three, four, or five of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1- butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone relative to headspace gas from the Mapnegative control sample.

[0145] In a further embodiment, Map-positive control sample comprises increased levels of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone relative to headspace gas from the Map-negative control sample.

[0146] In another embodiment, wherein when the sample from the subject is headspace gas from a culture of sheep faeces, the Map-negative control sample comprises increasedlevels of one or more of pentanal and hexanal relative to headspace gas from the Map-positive control sample.

[0147] In a further embodiment, Map-negative control sample comprises increased levels of pentanal and hexanal relative to headspace gas from the Map-positive control sample.

[0148] In another aspect, the present invention provides a device for performing a method as described herein. In one embodiment, the device is an electronic nose.

[0149] In one embodiment the present invention provides a method for detecting, by means of an electronic nose, Mycobacterium avium subsp. paratuberculosis in sample, comprising the steps of a) providing a sample from a ruminant animal; b) contacting a sensor array of said electronic nose to a portion of a gaseous sample released from said sample, and processing a plurality of sensor array output signals emitted by the sensor array; c) obtaining an olfactory signature which characterizes said sample, and d) comparing the olfactory signature which characterises the sample with one or more olfactory signatures which characterise a Map-positive control sample and / or a Map-negative control sample, wherein the sensor array comprises gas sensors capable of detecting one or more volatile organic compounds selected from the group consisting of pentanal, 3- pentanone, 1-butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2- butanone, 2-butanol, 3-carene, p-cymene, D-limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

[0150] In another embodiment, the sensor array comprises gas sensors capable of detecting of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 or 22 of the volatile organic compounds of Table 2.

[0151] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the olfactory signature which characterises the Map-positive control sample comprises increased levels of one or more of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl relative to the olfactory signature which characterises the Map-negative control sample.

[0152] In another embodiment, the olfactory signature which characterises the Mappositive control sample comprises increased levels of two, three, four, five, or six of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3- methyl relative to the olfactory signature which characterises the Map-negative control sample.

[0153] In a further embodiment, the olfactory signature which characterises the Mappositive control sample comprises increased levels of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl relative to the olfactory signature which characterises the Map-negative control sample.

[0154] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of one or more of acetone, 2-butanone, and 2-butanol relative to the olfactory signature which characterises the Map-positive control sample.

[0155] In another embodiment, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of two of acetone, 2-butanone, and 2- butanol relative to the olfactory signature which characterises the Map-positive control sample.

[0156] In a further embodiment, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of acetone, 2-butanone, and 2-butanol relative to the olfactory signature which characterises the Map-positive control sample.

[0157] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the olfactory signature which characterises the Map-positive control sample comprises increased levels of one or more of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to the olfactory signature which characterises the Map-negative control sample.

[0158] In another embodiment, the olfactory signature which characterises the Mappositive control sample comprises increased levels of two, three, of four of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to the olfactory signature which characterises the Map-negative control sample.

[0159] In a further embodiment, the olfactory signature which characterises the Mappositive control sample comprises increased levels of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to the olfactory signature which characterises the Map-negative control sample.

[0160] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of one or more of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to the olfactory signature which characterises the Map-positive control sample.

[0161] In another embodiment, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of two of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to the olfactory signature which characterisesthe Map-positive control sample.

[0162] In a further embodiment, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to the olfactory signature which characterises the Map-positive control sample.

[0163] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the olfactory signature which characterises the Map-positive control sample comprises increased levels of one or more of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone relative to the olfactory signature which characterises the Map-negative control sample.

[0164] In another embodiment, the olfactory signature which characterises the Mappositive control sample comprises increased levels of two or three of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone relative to the olfactory signature which characterises the Map-negative control sample.

[0165] In a further embodiment, olfactory signature which characterises the Map-positive control sample comprises increased levels of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone relative to the olfactory signature which characterises the Map-negative control sample.

[0166] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the olfactory signature which characterises the Map-negative control sample comprises increased levels of one or more of pentanal, hexanal, and l-octen-3-ol relative to the olfactory signature which characterises the Map-positive control sample.

[0167] In another embodiment, the olfactory signature which characterises the Mapnegative control sample comprises increased levels of two of pentanal, hexanal, and 1-octen- 3-ol relative to the olfactory signature which characterises the Map-positive control sample.

[0168] In a further embodiment, olfactory signature which characterises the Mapnegative control sample comprises increased levels of pentanal, hexanal, and l-octen-3-ol relative to the olfactory signature which characterises the Map-positive control sample.

[0169] In another embodiment, wherein when the sample from the ruminant animal is headspace gas from a culture of sheep faeces, the olfactory signature which characterises the Map-positive control sample comprises increased levels of one or more of dimethylamine, 3- pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone relative to the olfactory signature which characterises the Map-negative control sample.

[0170] In another embodiment, the olfactory signature which characterises the Mappositive control sample comprises increased levels of two, three, four, or five of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, 6-octen-2-one (Z)-, and 2-octanone relative to the olfactory signature which characterises the Map-negative control sample.

[0171] In another aspect, the present invention provides a method of reducing the incidence of Johne's disease in a herd of ruminant livestock, comprising determining the presence of Mycobacterium avium subsp. paratuberculosis in one or more subjects according to a method as described herein or a device as described herein, said method further comprising separating subjects with Mycobacterium avium subsp. paratuberculosis from subjects without Mycobacterium avium subsp. paratuberculosis.

[0172] In another aspect, the present invention provides a method of reducing the transmission of Mycobacterium avium subsp. paratuberculosis in a herd of ruminant livestock, comprising determining the presence of Mycobacterium avium subsp. paratuberculosis in one or more subjects according to a method as described herein or using a device as described herein, said method further comprising separating subjects with Mycobacterium avium subsp. paratuberculosis from subjects without Mycobacterium avium subsp. paratuberculosis.EXAMPLESExample 1: Materials and MethodsPanel of samples, culture and PCR preparation

[0173] Faecal samples were obtained from the sample collection of the National Johne's Disease Reference Laboratory (NJDRL). Cattle and sheep faeces originated from different animals and herds / flocks from Victoria, Australia that were part of a diagnostic field study. The sample collection for the study was approved by the Animal Ethics Committee in Victoria (permit number 2022-05). The presence or absence of Map was initially determined at the time of the study by cultural isolation (previously described; Hodgeman et al. Molecularcharacterisation of Mycobacterium avium subsp. paratuberculosis in Australia. BMC Microbiology. 2021, 21, 101.) and a Map specific qPCR as previously described in Hodgeman et al 2024 (Development and evaluation of genomics informed real-time PCR assays for the detection and strain typing of Mycobacterium avium subsp. paratuberculosis. Journal of Applied Microbiology, 2024. 135(5)). The strain type of all the isolates was also determined by the IS1311 PCR and REA as previously described (Hodgeman et al. 2021). After initial processing, if the samples could not be tested immediately, they were stored at -80°C until preparation for this study. See Table 3 for a complete description of the faecal samples used in this study.Sample PreparationCultures

[0174] For initial method development 12 faecal samples that consisted of nine cattle (8 confirmed culture positive and one confirmed culture negative) and three sheep (two confirmed culture positive and one confirmed culture negative) were prepared for culture as previously described (Hodgeman et al. 2021), with the exception they were cultured in 20 mL headspace vials. Each faecal sample was cultured in triplicate and cultures were prepared on different days to be analysed by SPME-GC-MS after two, four, six, eight, ten, and twelve weeks post inoculation. For each culture and time point Map status was confirmed by the IS900 PCR as previously described (Hodgeman et al. 2021).Faeces

[0175] For direct faecal analysis, 48 Type C Map negative and 28 Type C Map positive faeces and 30 Type S Map negative and 4 Type S Map positive faeces (Table 3) were prepared in triplicate for direct SPME-GC-MS analysis by weighing 3 g of faeces directly into 20 mL clear headspace vials with magnetic screw top lids and polytetrafluoroethylene (PTFE) septa. Only faecal samples that had tested positive by both culture and PCR and negative by culture and PCR were used as part of the validation panel to ensure there were no discrepancies between results. Peak areas from this data were exported to excel and used as input to Matlab to produce PLS-DA score plots to determine if this method could be used as a diagnostic test.VOC Analysis

[0176] Solid Phase Micro Extraction (SPME) was used to sample the headspace of both the cultures and faeces. A carbon WR / PDMS SPME Arrow (Gerstel GmbH & Co. KG, Germany), 1.1mm diameter, 20mm phase length and 120pm phase thickness, was used for all measurements. Before SPME Arrows were used for the first time, they were conditioned at 270°C for 30 min (according to the manufacturer's instructions). Every day before measurements were taken a blank run of the arrow was performed to ensure the SPME coating was clean and there was no uncontrolled bleeding. Map cultures and faeces were conditioned at 37°C for 5 min and then extraction was performed for 2 min at 37°C. The Arrow was reconditioned at 270°C for 5 min before each sample, and for 2 min directly after injection. SPME fibres were thermally desorbed in the GC-injector for 60 seconds at an injector temperature of 270°C and a 40:1 split. The inlet liner was a 2mm ID straight HS-type liner (Agilent, Mulgrave, Australia). The column was an Agilent DB-624 30 m length, 0.25 internal diameter and 1.4 pm film thickness. The carrier gas was helium at a constant flow rate of 1.2 ml / min. The temperature program was 40°C for 5 min, then a ramp of 3°C / min to 100°C, then 10°C / min to 150°C, then 100°C / min to 240°C held for 5 min. The detector is an Agilent 7250 Q- TOF operated in MSI mode acquiring a mass range of 45-350 amu at 5 spectra / s in centroid. The El source was held at 200°C, emission was fixed at lp Amp and 70 eV.Data

[0177] Volatiles were characterized by interrogating raw data in Mass Hunter Qualitative v.10.0. by their m / z and retention time and labelled according to elution time (UK1-UK76). Mass Hunter Quantitative v.10.0 was used for relative quantification of these VOCs. Peak areas were exported to excel and used as input to PLS Toolbox (ver 9.2.1 Eignevector) Matlab (ver 2023b, Mathworks) for principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Compound intensities were pre-processed using autoscale or mean centring prior to analysis. For PLSDA the data was split into test and validation using the KernardStone approach, with 75% of the data retained for development of the model. The PLSDA model used cross validation with Venetian blinds (with 10 splits and a blind thickness of 1).

[0178] To determine the specificity and sensitivity of the test based on PLS-DA predictive modelling the following calculations were used:„ TN TN+FPTPSe = - TP+FN where, TN = true ne ogative, ’ FP = false positive, TP = true positive, FN = false negative

[0179] Based on these calculations the predicted sensitivity of the test is 97.8% and the predicted specificity is 90.5%.

[0180] The class error was calculated as follows:Class Err. = average of false positive rate and false negative rate for class,= 1 - (sensitivity+specificity) / 2.Identification of putative biomarkers

[0181] Putative biomarkers were identified by spectral matching (NIST 2205 Gatesburg, PA, USA) and, where possible, verified by comparison to GC retention times and mass spectra of pure reference standards. Thirteen such standards (pentanal, hexanal, l-octen-3-ol, 2- octanone, ethanthiol, 3-carene, p-cymene, phenol, acetone, 2-butanol, D-limonene, 1-butanol 3-methyl, 1-butanol 2 methyl, Sigma Aldrich) were prepared by diluting approximately 50 mg of each reference standard in 20 mL and 10 mL of isopropanol (supplier, and grade) and 1 pL of these dilutions were added to a headspace vial. The headspace was measured as previously described.Validation of GC-MS based models for faeces eNose Data Collection and Model Training

[0182] The Cyranose ® 320 eNose® is a portable olfactory system that is a combination of a gas sampling unit and a sensory array. It consists of 32 different thick film metal oxide sensors and has two pumps, one for pulling samples through the sensor array and one for transferringfiltered air into the sensor array. The filtered air is also used as a baseline and to remove residual volatile compounds, and the sensor response from the sample gas is measured in comparison to the filtered air. In this study the Cyranose® 320 eNose® was trained to distinguish between Map positive faeces and Map negative faeces in both cattle and sheep. For training the eNose in the laboratory, 100g of confirmed MAP positive or negative faeces was weighed into a 200 mL plastic container with lid and incubated at 37°C for one hour. Two holes of approximately 3 mm diameter were punched into the lid of the container at opposite ends and the snout was inserted 15mm above the surface of the faeces through one of the holes (Figure 1). For establishing the internal prediction model, the eNose was presented with 10 individual faeces for each class using the 'Training' mode. The method was set up according to the manufacturer's instructions, and a steady readout and baseline purge time was determined empirically (Table 1). The eNose was also trained in the field using the same method as above except the faeces were not incubated at 37°C for one hour. The faeces were taken directly from the animal into large 500 mL collection pots, and from where approximately 100 mL were decanted into 200 mL pots and incubated at air temperature for 10-15 minutes to establish the headspace before analysis. Once training of the eNose was completed a preliminary evaluation of the model is performed by performing an internal cross- validation to determine discrimination ability of the eNose. There were two pattern recognition algorithms that came with the eNose software: KNN (non-parametric, supervised learning classifier) and Canonical discriminant analysis (a special case of linear discriminant analysis, also a supervised learning classifier). The CDA method was chosen to analyse this data as it allowed clear separation of the classes.

[0183] A limitation of the eNose software was that only 10 positive and 10 negative samples could be used to develop the training model. To allow comparison to the GCMS method the sensor data (initial 20 training samples and subsequent test samples) was also exported and analysed using PLSToolbox to create PLSDA models. Pre-processing was either mean centering or autoscaling with the data split into a training (75%) and test set (25%) using the Kennard-Stone algorithm. Premutation testing was performed (n=50) to test model robustness.

[0184] Table 1: Method settings for eNose for laboratory and field samplesValidation of eNose

[0185] For the validation of the eNose for cattle, the original 20 samples used for training were included with an additional 22 Type C Map negative and 12 Type C Map positive faeces. For sheep, the original 10 samples used for training were included with an additional 13 Type S negative and 8 Type S positive faeces and the sheep training samples (Table 3). To validate the eNose capability for identifying samples the eNose is used in 'Identify' mode instead of the 'Training' mode. Only faecal samples that had tested positive by both culture and PCR and negative by culture and PCR were used as part of the validation panel to ensure there were no discrepancies between results. This sensor data was also analysed via PLS-DA models as described earlier.Example 2: Culture and qPCR

[0186] Cattle faeces (n = 95) and sheep faeces (n = 60) were tested by culture and qPCR to determine the presence / absence of Map prior to VOC analysis. Of the 95 cattle faeces 36 were culture and PCR positive and 59 were negative and of the 60 sheep faeces 14 were culture and PCR positive and 46 were negative (Table 3). The 12 cultures that were set up for VOC analysis for testing at 2, 4, 6, 8, 10 and 12 weeks were also subjected to PCR at the same time points. Two of the cattle cultures were detected by PCR at week 8, a further one at week 10 and all cultures were positive at week 12 (Table 4).Example 3: identification of volatile organic compounds that can differentiate between Map positive and negative cultures

[0187] VOC analysis resulted in the identification of 72 compounds in the headspace of the vials. Evaluation of the PCA plot of the cattle culture data from week two to week 12 showed that Map could be detected at four weeks of culture (Figure 2A) with clear separation of the positive and negative samples on PCI. The loadings plot (Figure 2B) revealed that there were seven main VOCs responsible for this separation. They were identified as (UK 23 - pentanal, UK 24 - 3-pentanone, UK 30 - 1-butanol 3-methyl, UK 40 - hexanal, UK 59 - 1-octen- 3-ol, UK 60 - 6-octen-2-one (Z)- and UK61 - 2-octanone) (Table 2). UK 23, 40 and 59 were upregulated in the negative samples and UK 24, 30, 60 and 61 were all upregulated in the positive samples.

[0188] Evaluation of the PCA plot of the sheep cultures from week two to week 12 showed that Map could be detected at six weeks of culture (Figure 3A). The loadings plot (Figure 3B) revealed eight VOCs had a significant effect on this separation (UK3 - dimethylamine, UK23 - pentanal, UK24 - 3-pentanone, UK30 - 1-butanol 3-methyl, UK38 - 1-butanol 2-methyl, UK40 - hexanal, UK60 - 6-octen-2-one (Z)-, UK61 - 2-octanone) in the sheep cultures (Table 2). UK3, 24, 30, 38, 60 and 61 were upregulated in the positive sheep cultures and UK23 and 40 were upregulated in the negative cultures. Six of the compounds (pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone) were present in both the cattle and sheep cultures.Example 4: Identification of volatile organic compounds that can differentiate between Map positive and negative cattle faeces

[0189] VOC emissions from faecal samples were analysed by comparing measurements of Map negative cattle faeces and Map positive cattle faeces. Map status of faeces was firstly determined by culture and qPCR (Table 3). As previously mentioned, only faeces whose results were the same for both culture and qPCR were included in the VOC analysis to ensure there was no ambiguity between a true positive and a true negative result. For diagnostic purposes, test accuracy and validity are extremely important when developing a new test method. Therefore, PLS-DA was used as a statistical method that allows training of the model and then validation against other samples to determine if the model could be used for diagnostic purposes. PLS-DA plot of the cattle faeces (Figure 4A) indicated that Map positive and Map negative faeces could be differentiated. This PLS-DA model used cross validation with Venetian blinds (with 10 splits and a blind thickness of 1). The classification errors for the calibration, cross validation, and the prediction (ie. The 25% withheld from the original model) were 6.3%, 8.3% and 4.8% respectively. The predicted sensitivity of this test model is 92.3% and the predicted specificity is 98.1%. Permutation testing (n=50) returned p-values less than 0.01 suggesting that the model was not overfitted.

[0190] Out of the 72 detectable VOCs the loading plot (Figure 4B) revealed 10 compounds that could differentiate between Map positive and Map negative cattle faeces (Table 2), biomarkers (UK2 - methanthiol, UK5 - acetone, UK6 - dimethyl sulfide, UK7 - ethanthiol, UK15 - 2-butanone, UK16- 2-butanol, UK49 - 3-carene, UK64 - p-cymene, UK65 - D-limonene, LIK72 - phenol 3-methyl. UK2, 6, 7, 64, 65 and 72 were upregulated in the cattle positive samples and UK5, 15 and 16 upregulated in the negative cattle faecal samples.Example 5: Identification of volatile organic compounds that can differentiate between Map positive and negative sheep faeces

[0191] VOC emissions for sheep faecal samples were determined by comparing measurements of Map negative sheep faeces and Map positive sheep faeces and using PLS-DA score plots as was done for the cattle faecal analysis. The PLS-DA plot of the sheep faeces (Figure 5A) showed a clear separation between Map positive and Map negative sheep faeces.Out of the 72 detectable VOCs the loading plot for the sheep faeces (Figure 5B and 5C) revealed eight compounds that could be used to differentiate between Map positive and Map negative sheep faeces (Table 2) (biomarkers UK2 - methanthiol, UK 6 - dimethyl sulfide, UK7 - ethanthiol, UK26 - disulfide dimethyl, UK30 - 1-butanol 3-methyl, UK57 - dimethyl trisulfide, UK70 - phenol, UK72 - phenol 3-methyl). UK2, 26, 57, 70, and 30 were upregulated in the sheep positive samples and UK6, 7 and 72 were upregulated in the negative samples.

[0192] Table 2: Significant compounds identified in cattle, their base peak ions (m / z), retention times (RT), Match, RMatch and probability as identified in the NIST spectral library, identified from (CC: cattle culture, SC: sheep culture, CF: cattle faeces, SF: sheep faeces) and identification status (LM: based on library match, confirmed: matches spectrum and RT of authentic standard.Table 2

[0193] Table 3: Map isolates used for the development and validation of the GC-MS analysis and eNose including the PCR and culture resultsIsolate Host Year Strain Type Map Specific Culture Result qPCR Result511.2Cattle 2022 C Positive Positive491.2Cattle 2022 C Positive Positive341,2Cattle 2022 C Positive Positive221,2Cattle 2022 C Positive Positive181.2Cattle 2022 C Positive Positive431.2Cattle 2022 C Positive PositiveIO1,2Cattle 2022 C Positive PositiveI1,2Cattle 2022 C Positive PositiveCNeg1,2Cattle 2024 C Negative NegativeS251,2'4Sheep 2023 S Positive PositiveS261,2'4Sheep 2023 S Positive PositiveSNeg1,2Sheep 2024 S Negative Negative3322-11'3'5Sheep 2023 S Negative Negative3322-21,3'5Sheep 2023 S Negative Negative3322-31,3'5Sheep 2023 S Negative Negative3322-41,3'5Sheep 2023 S Negative Negative3322-51'3'5Sheep 2023 S Negative Negative3322-61,3'5Sheep 2023 S Negative Negative3322-71,3'5Sheep 2023 S Negative Negative3322-81,3'5Sheep 2023 S Negative Negative3322-91,3-5Sheep 2023 S Negative Negative3322-101,3'5Sheep 2023 S Negative Negative232-31,4Sheep 2023 S Positive Positive2534-201,4Sheep 2023 S Positive Positive38331Sheep 2023 S Negative Negative760-13,4'5Cattle 2024 C Positive Positive760-23,4'5Cattle 2024 C Positive Positive760-33,4'5Cattle 2024 C Positive Positive760-43,4'5Cattle 2024 C Positive Positive760-53'4'5Cattle 2024 C Positive Positive760-73,4'5Cattle 2024 C Positive Positive760-103,4'5Cattle 2024 C Positive Positive760-113'4'5Cattle 2024 C Positive Positive760-133,4'5Cattle 2024 C Positive Positive760-163,4'5Cattle 2024 C Positive Positive487-13,5Cattle 2024 C Negative Negative487-23,5Cattle 2024 C Negative Negative487-33,5Cattle 2024 C Negative Negative487-43,5Cattle 2024 C Negative Negative487-53,5Cattle 2024 C Negative Negative487-63,5Cattle 2024 C Negative Negative487-73,5Cattle 2024 C Negative Negative487-83Cattle 2024 C Negative Negative487-93,5Cattle 2024 C Negative Negative487-103,5Cattle 2024 C Negative NegativeSAI3,5Sheep 2024 S Positive PositiveSA23'5Sheep 2024 S Positive PositiveSA33'5Sheep 2024 S Positive PositiveSA43'5Sheep 2024 S Positive PositiveSA53'5Sheep 2024 S Positive PositiveSA63'5Sheep 2024 S Positive PositiveSA73'5Sheep 2024 S Positive PositiveSA83'5Sheep 2024 S Positive PositiveSA93'5Sheep 2024 S Positive PositiveSAIO3,5Sheep 2024 S Positive PositiveSA115Sheep 2024 S Positive PositiveSA125Sheep 2024 S Positive PositiveSA135Sheep 2024 S Positive PositiveSA145Sheep 2024 S Positive PositiveSA155Sheep 2024 S Positive PositiveSA165Sheep 2024 S Positive PositiveSA175Sheep 2024 S Positive PositiveSA185Sheep 2024 S Positive Positive760-84,5Cattle 2024 C Positive Positive760-94,5Cattle 2024 C Positive Positive760-134,5Cattle 2024 C Positive Positive760-174,5Cattle 2024 C Positive Positive760-184,5Cattle 2024 C Positive Positive760-194,5Cattle 2024 C Positive Positive760-204,5Cattle 2024 C Positive Positive760-214,5Cattle 2024 C Positive Positive760-224,5Cattle 2024 C Positive Positive760-234,5Cattle 2024 C Positive Positive760-254,5Cattle 2024 C Positive Positive760-264,5Cattle 2024 C Positive Positive760-274Cattle 2024 C Positive Positive760-294Cattle 2024 C Positive Positive760-304Cattle 2024 C Positive Positive760-314Cattle 2024 C Positive Positive760-324Cattle 2024 C Positive Positive760-334Cattle 2024 C Positive Positive1486-14,5Cattle 2024 C Negative Negative1486-24,5Cattle 2024 C Negative Negative1486-34,5Cattle 2024 C Negative Negative1486-44,5Cattle 2024 C Negative Negative1486-54,5Cattle 2024 C Negative Negative1486-64,5Cattle 2024 C Negative Negative1486-74,5Cattle 2024 C Negative Negative1486-94,5Cattle 2024 C Negative Negative1486-104,5Cattle 2024 C Negative Negative1486-114'5Cattle 2024 C Negative Negative1486-124,5Cattle 2024 C Negative Negative1486-134,5Cattle 2024 C Negative Negative1486-144,5Cattle 2024 C Negative Negative1486-154,5Cattle 2024 C Negative Negative1486-164,5Cattle 2024 C Negative Negative1486-174,5Cattle 2024 C Negative Negative1486-184,5Cattle 2024 C Negative Negative1486-194,5Cattle 2024 C Negative Negative1486-204,5Cattle 2024 C Negative Negative1486-214,5Cattle 2024 C Negative Negative1486-224,5Cattle 2024 C Negative Negative1486-234,5Cattle 2024 C Negative Negative1486-244Cattle 2024 C Negative Negative1486-254Cattle 2024 C Negative Negative1486-264Cattle 2024 C Negative Negative1486-274Cattle 2024 C Negative Negative1486-284Cattle 2024 C Negative Negative1486-294Cattle 2024 C Negative Negative1486-304Cattle 2024 C Negative Negative1486-314Cattle 2024 C Negative Negative1486-324Cattle 2024 C Negative Negative1486-334Cattle 2024 C Negative Negative1486-344Cattle 2024 C Negative Negative1486-354Cattle 2024 C Negative Negative1486-364Cattle 2024 C Negative Negative1486-374Cattle 2024 C Negative Negative1486-384Cattle 2024 C Negative Negative1486-394Cattle 2024 C Negative Negative1486-404Cattle 2024 C Negative Negative1486-414Cattle 2024 C Negative Negative1486-424Cattle 2024 C Negative Negative1486-434Cattle 2024 C Negative Negative1486-444Cattle 2024 C Negative Negative1486-454Cattle 2024 C Negative Negative1486-464Cattle 2024 C Negative Negative1486-474Cattle 2024 C Negative Negative1486-484Cattle 2024 C Negative Negative1486-494Cattle 2024 C Negative Negative3322-114,5Sheep 2023 S Negative Negative3322-124,5Sheep 2023 S Negative Negative3322-134,5Sheep 2023 S Negative Negative3322-144,5Sheep 2023 S Negative Negative3322-154,5Sheep 2023 S Negative Negative3322-164’ Sheep 2023 S Negative Negative3322-174'5Sheep 2023 S Negative Negative3322-184,5Sheep 2023 S Negative Negative3322-194,5Sheep 2023 S Negative Negative3322-204,5Sheep 2023 S Negative Negative3322-214,5Sheep 2023 S Negative Negative3322-224,5Sheep 2023 S Negative Negative3322-234,5Sheep 2023 S Negative Negative3322-244Sheep 2023 S Negative Negative3322-254Sheep 2023 S Negative Negative3322-264Sheep 2023 S Negative Negative3322-274Sheep 2023 S Negative Negative3322-284Sheep 2023 S Negative Negative3322-294Sheep 2023 S Negative Negative3322-304Sheep 2023 S Negative Negative3322-314Sheep 2023 S Negative Negative3322-324Sheep 2023 S Negative Negative3322-334Sheep 2023 S Negative Negative3322-344Sheep 2023 S Negative Negative3322-354Sheep 2023 S Negative Negative3322-364Sheep 2023 S Negative Negative3322-374Sheep 2023 S Negative Negative3322-384Sheep 2023 S Negative Negative3322-394Sheep 2023 S Negative Negative3322-404Sheep 2023 S Negative Negative1I sol ates used for GC-MS method development on direct faeces, isolates used for GC-MS method development on cultures, isolates used for training of the Cyranose® 320 eNose®, isolates used for validation of the GC-MS method isolates used for the validation of the Cyranose® 320 eNose®

[0194] Table 4: IS900 PCR results for cultures at each time point, W2, W4, W6, W8,W10, W12Isolate Strain Week 2 Week 4 Week 6 Week 8 Week 10 Week 12TypeS25 S - - - - - +S26 S - - - - - +SNeg S - - - - - +CNeg C - - - - - +51 C - - - - - +49 C - - - + + +34 C - - - - - +22 C - - - - - +18 C - - + + +43 C - - - - + +10 C - - - - - +1 C - - - - - +

[0195] The predicted specificity, sensitivity and class error for the sheep faecal analysis was calculated as per the cattle faecal data. Based on the calculations the predicted sensitivity of the test is 100% and the predicted specificity is 100%. The predicted class errorforthe model is 0%. Four of the compounds were present in both the cattle and sheep faeces. There were four compounds present in the headspace of both cattle and sheep, methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol. There were six compounds present in the cattle faeces that were not present in the sheep faeces, acetone, 2-butanone, 2-butanol, 3-carene, p- cymene and D-limonene and there were four compounds present in the sheep faeces that were not present in the cattle faeces, disulfide dimethyl, dimethyl trisulfide, phenol and 1- butanol 3-methyl. There was only one compound, 1-butanol 3-methyl that was present in both sheep culture samples and sheep faecal samples.Example 6: Validation of an eNose that can differentiate between Map positive and negative cattle faeces

[0196] The eNose was firstly trained with 10 Map positive and 10 Map negative cattle faeces both in the laboratory to determine whether the eNose could discriminate between infected and non-infected cattle. Figure 6A shows the PCA analysis of the raw data from cattle faeces obtained with the eNose. Based on the PCA, a discrimination model was built. Internal cross validation of the model then resulted in 100% successful discrimination between the two classes, with an interclass M-distance of 7.822. The eNose was also trained with 10 Map positive and 10 Map negative sheep faeces in the laboratory. Figure 6B shows the PCA analysis of the data from sheep faeces obtained with the eNose. Internal cross validation of this model also resulted in 100% successful discrimination between the two classes, with an interclass M- distance of 6.149.

[0197] As the models passed the internal cross-validation as determined by the eNose software the eNose was further validated in the laboratory to ensure robustness and confidence in the ability of the eNose to identify samples. For the validation of the eNose in sheep 31 sheep faecal samples were used consisting of 18 confirmed Map negative and 13 confirmed Map positive faeces. The sensor data was exported to excel and analysed using Matlab. Data was analysed using autoscaling or mean centering with data split using Kennard- Stone algorithm with Euclidean distance to retain 75% of the samples for training. The best model obtained was with mean centering preprocessing and the PLS-DA plot (Figure 7A) showed good separation between positive and negative sheep faeces, resulting in the eNose having a predicted sensitivity of 100% and a specificity of 88.9% and a class error of 5.5%.

[0198] For validation of the eNose in cattle 44 cattle faecal samples were used consisting of 27 confirmed Map negative and 17 confirmed Map positive faeces. The eNose sensor data was also exported to excel and analysed using Metlab. Data was analysed using autoscaling, mean centred and mean centred with data split using Kennard-Stone algorithm with Euclidean distance and retained 75% of the training samples. The mean centred with data split produced the best model (Figure 7B). Using this model the predicted sensitivity and specificity of the eNose for detecting Map in cattle faeces is 100% with a class error of 0%.

[0199] This PLSDA model used cross validation with Venetian blinds (with 10 splits and a blind thickness of 1). The classification errors for the calibration, cross validation, and the prediction (ie. The 25% withheld from the original model) were 14.5%, 22.1% and 0.0% respectively. The predicted sensitivity of this test model is 100% and the predicted specificity is 100%. Permutation testing (n=50) returned p-values less than 0.05 (Wilcoxon test) suggesting that the model was not overfitted.

Claims

1. The claims defining the invention are as follows1. A method for determining the presence of Mycobacterium avium subsp. paratuberculosis in a subject, the method comprising the steps of:(a) determining the level of one or more volatile organic compounds in a sample from the subject; and(b) comparing the level of said one or more volatile organic compounds in the sample with the level of said one or more volatile organic compounds in a negative control sample and / or a positive control sample to determine whether Mycobacterium avium subsp. paratuberculosis is present in the subject; wherein the one or more volatile organic compounds are selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3-methyl, hexanal, 1-octen- 3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1-butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3- carene, p-cymene, D-limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

2. A method according to claim 1, wherein the subject is a ruminant animal.

3. A method according to claim 1, wherein when the sample from the subject is a sample from a culture prepared from ruminant faeces, the one or more volatile organic compounds are selected from the group consisting of pentanal, 3-pentanone, 1- butanol 3-methyl, hexanal, 6-octen-2-one (Z)- and 2-octanone.

4. A method according to claim 1, wherein when the sample from the subject is a sample from ruminant faeces, the one or more volatile organic compounds are selected from the group consisting of methanthiol, dimethyl sulfide, phenol 3-methyl and ethanthiol.

5. A method according to claim 1, wherein when the sample from the subject is a sample from a culture prepared from cattle faeces, and the one or more volatile organiccompounds are selected from the group consisting of pentanal, 3-pentanone, 1- butanol 3-methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)- and 2-octanone.

6. A method according to claim 5, wherein the one or more volatile organic compounds are selected from the group consisting of 3-pentanone, 1-butanol 3-methyl, 6-octen-2- one (Z)- and 2-octanone and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject.

7. A method according to claim 5, wherein the one or more volatile organic compounds are selected from the group consisting of pentanal, hexanal, and l-octen-3-ol, and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control sample indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

8. A method according to claim 1, wherein when the sample from the subject is a sample from a culture prepared from sheep faeces, and the one or more volatile organic compounds are selected from the group consisting of dimethylamine, pentanal, 3- pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl, hexanal, 6-octen-2-one (Z)-, and 2-octanone.

9. A method according to claim 8, wherein the one or more volatile organic compounds are selected from the group consisting of dimethylamine 3-pentanone, 1-butanol 3- methyl, 6-octen-2-one (Z)-, and 2-octanone, and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject.

10. A method according to claim 8, wherein the one or more volatile organic compounds are selected from the group consisting of pentanal and hexanal, and an increased level of the one or more volatile organic compounds in the sample relative to the level of theone or more volatile organic compounds in the positive control sample indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

11. A method according to claim 1, wherein when the sample from the subject is a sample from a cattle faecal sample, and the one or more volatile organic compounds are selected from the group consisting of methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2-butanol, 3-carene, p-cymene, and D-limonene, and phenol 3-methyl.

12. A method according to claim 11, wherein the one or more volatile organic compounds are selected from the group consisting of methanthiol, dimethyl sulfide, ethanthiol, 3- carene, p-cymene, and D-limonene, and phenol 3-methyl and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of the one or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject.

13. A method according to claim 11, wherein the one or more volatile organic compounds are selected from the group consisting of acetone, 2-butanone, 2-butanol, and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control sample indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

14. A method according to claim 1, wherein when the sample from the subject is a sample from a sheep faecal sample, and the one or more volatile organic compounds are selected from the group consisting of methanthiol, dimethyl sulfide, ethanthiol, disulfide dimethyl, 1-butanol 3-methyl, dimethyl trisulfide, phenol and phenol 3- methyl.

15. A method according to claim 14, wherein the one or more volatile organic compounds are selected from the group consisting of methanthiol, disulfide dimethyl, 1-butanol 3- methyl, dimethyl trisulfide, and phenol and an increased level of the one or more the volatile organic compounds in the sample from the subject relative to the level of theone or more volatile organic compounds in the negative control sample indicates Mycobacterium avium subsp. paratuberculosis is present in the subject.

16. A method according to claim 14, wherein the one or more volatile organic compounds are selected from the group consisting of dimethyl sulfide, ethanthiol, and phenol 3- methyl and an increased level of the one or more volatile organic compounds in the sample relative to the level of the one or more volatile organic compounds in the positive control indicates Mycobacterium avium subsp. paratuberculosis is not present in the subject.

17. A method according to any one of claims 1 to 16, wherein the sample from a culture prepared from ruminant faeces is headspace gas obtained from the culture, or the sample from ruminant faeces is headspace gas obtained from the ruminant faeces.

18. A method according to any one of claims 1 to 17, wherein the step of (a) determining the level of one or more volatile organic compounds in a sample from the subject comprises Solid Phase Micro Extraction (SPME) of headspace gas obtained from the sample.

19. A method according to any one of claims 1 to 17, wherein the step of (a) determining the level of one or more volatile organic compounds in a sample from the subject comprises using gas chromatography-mass spectrometry.

20. A method for detecting, by means of an electronic nose, Mycobacterium avium subsp. paratuberculosis in sample, comprising the steps of a) providing a sample from a ruminant animal; b) contacting a sensor array of said electronic nose to a portion of a gaseous sample released from said sample, and processing a plurality of sensor array output signals emitted by the sensor array; c) obtaining an olfactory signature which characterizes said sample, andd) comparing the olfactory signature which characterises the sample with one or more olfactory signatures which characterise a Mycobacterium avium subsp. paratuberculosis -positive control sample and / or a Mycobacterium avium subsp. paratuberculosis negative control sample.

21. A method for detecting according to claim 20, wherein the control sample is a gaseous sample released from a sample not comprising Mycobacterium avium subsp. paratuberculosis.

22. A method for detecting according to claim 20, wherein the control sample is a gaseous sample released from a sample comprising Mycobacterium avium subsp. paratuberculosis.

23. A method according to claim 20, wherein the Mycobacterium avium subsp. paratuberculosis positive control sample and / or a Mycobacterium avium subsp. paratuberculosis negative control sample comprise one or more volatile organic compound selected from the group consisting of pentanal, 3-pentanone, 1-butanol 3- methyl, hexanal, l-octen-3-ol, 6-octen-2-one (Z)-, 2— octanone, dimethylamine, 1- butanol 2-methyl, methanthiol, acetone, dimethyl sulfide, ethanthiol, 2-butanone, 2- butanol, 3-carene, p-cymene, D-limonene, phenol 3-methyl, disulfide dimethyl, dimethyl trisulfide, and phenol.

24. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of methanthiol, dimethyl sulfide, ethanthiol, 3-carene, p-cymene, D-limonene, and phenol 3-methyl relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

25. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from cattle faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more ofacetone, 2-butanone, and 2-butanol relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

26. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of methanthiol, disulfide dimethyl, dimethyl trisulfide, phenol, and 1-butanol 3-methyl relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

27. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from sheep faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more of dimethyl sulfide, ethanthiol, and phenol 3-methyl relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

28. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of 3-pentanone, 1-butanol 3-methyl, 6-octen-2-one (Z)- and 2-octanone relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

29. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from a culture of cattle faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more of pentanal, hexanal, and l-octen-3-ol relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

30. A method for detecting according to claim 20, wherein when the sample from the ruminant animal is headspace gas from a culture of sheep faeces, the Mycobacterium avium subsp. paratuberculosis positive control sample comprises increased levels of one or more of dimethylamine, 3-pentanone, 1-butanol 3-methyl, 1-butanol 2-methyl,6-octen-2-one (Z)-, and 2-octanone relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis negative control sample.

31. A method for detecting according to claim 20, wherein when the sample from the subject is headspace gas from a culture of sheep faeces, the Mycobacterium avium subsp. paratuberculosis negative control sample comprises increased levels of one or more of pentanal and hexanal relative to headspace gas from the Mycobacterium avium subsp. paratuberculosis positive control sample.

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