IN VITRO METHOD FOR DIAGNOSING SUBJECTS INFECTED WITH MYCOBACTERIUM SPECIES

Abstract

In vitro method for diagnosing subjects infected with Mycobacterium species. The present invention is directed to an in vitro method for the diagnosis of subjects infected with Mycobacterium species, particularly subjects infected with Mycobacterium avium subsp. paratuberculosis (MAP) which is the causative agent of paratuberculosis (PTB).

Claims

1. In vitro method for diagnosing subjects infected with Mycobacterium species which comprises: a) Measuring the concentration of the protein ABCA13 in a biological sample obtained from the subject, and b) Wherein if an increase of the concentration of the protein ABCA13 is identified in the step a) with respect to the concentration of the protein ABCA13 measured in uninfected control subjects, it is an indication that the subject is infected with Mycobacterium species.

2. In vitro method, according to claim 1, for diagnosing subjects infected with Mycobacterium avium subsp. paratuberculosis which comprises: a) Measuring the concentration of the protein ABCA13 in a biological sample obtained from the subject, and b) Wherein if an increase of the concentration of the protein ABCA13 is identified in the step a) with respect to the concentration of the protein ABCA13 measured in uninfected control subjects, it is an indication that the subject is infected with Mycobacterium avium subsp. paratuberculosis.

3. In vitro method, according to any of the previous claims, for the diagnosis of paratuberculosis in a subject which comprises: a) Measuring the concentration of the protein ABCA13 in a biological sample obtained from the subject, and b) Wherein if an increase of the concentration of the protein ABCA13 is identified in the step a) with respect to the concentration of the protein ABCA13 measured in uninfected control subjects, it is an indication that the subject is suffering from paratuberculosis.

4. In vitro method, according to any of the previous claims, which comprises: a) Measuring the concentration of the proteins [ABCA13 and SPARC] in a biological sample obtained from the subject, and b) Wherein if an increase of the concentration of the proteins [ABCA13 and SPARC] is identified in the step a) with respect to the concentration of the proteins [ABCA13 and SPARC] measured in uninfected control subjects, it is an indication that the subject is suffering from paratuberculosis.

5. In vitro method, according to any of the previous claims, which comprises: a) Measuring the concentration of the proteins [ABCA13 and SPARC and MMP8] in a biological sample obtained from the subject, and b) Wherein if an increase of the concentration of the proteins [ABCA13 and SPARC and MMP8] is identified in the step a) with respect to the concentration of the proteins [ABCA13 and SPARC and MMP8] measured in uninfected control subjects, it is an indication that the subject is suffering from paratuberculosis.

6. In vitro method, according to any of the previous claims, which comprises: a) Measuring the concentration of the proteins of any of the claims 1 to 5, in a biological sample obtained from the subject, b) Wherein if the concentration obtained for any of the previously cited proteins is above the established cut-off value, this is indicative that the subject is suffering from paratuberculosis.

7. In vitro method, according to any of the previous claims, for the diagnosis of latent or patent paratuberculosis, preferably latent paratuberculosis.

8. In vitro method, according to any of the previous claims, wherein the biological sample is a body fluid comprising serum, plasma or blood.

9. In vitro method, according to any of the previous claims, wherein the subject is a mammal selected from the group consisting of: cattle, goat, sheep, horse, pig, deer, rabbit, wild boar, bison, llama, alpaca, opossum, badger, elephant or human being; preferably a farm-animal selected from the group consisting of: cow, goat, sheep, horse, pig, deer, llama or alpaca.

10. In vitro use of the protein ABCA13, of the proteins [ABCA13 and SPARC], or of the proteins [ABCA13 and SPARC and MMP8], for diagnosing subjects infected with Mycobacterium species.

11. In vitro use, according to claim 10, for diagnosing subjects infected with Mycobacterium avium subsp. paratuberculosis.

12. In vitro use, according to any of the claim 10 or 11, for the diagnosis of paratuberculosis.

13. In vitro use, according to any of the claims 10 to 12, for the diagnosis of latent or patent paratuberculosis, preferably latent paratuberculosis.

14. Use of a kit which comprises tools or reagents for determining the concentration of the protein ABCA13 for diagnosing subjects infected with Mycobacterium species.

15. Use of a kit, according to claim 14, which comprises tools or reagents for determining the concentration of the proteins [ABCA13 and SPARC] or the proteins [ABCA13 and SPARC and MMP8] for diagnosing subjects infected with Mycobacterium species.

Description

DESCRIPTION OF THE FIGURES

[0042] FIG. 1. Biomarker concentration levels in serum of Holstein Friesian cattle showing different types of histological lesions in the intestinal tissues focal (n=55), multifocal (n=17), and diffuse (n=15). Control animals (n=61) were animals from a PTB-free farm. The number of animals with focal, multifocal, diffuse or with any type of lesions analysed for ABCA13 was 53, 16, 14 and 83, respectively. Biomarkers were detected and quantified in bovine serum by specific ELISAs supplied by MyBioSource, San Diego, Calif., USA. a) FAM84A, bovine family with sequence similarity 84-member A; b) DES, bovine desmin; c) ABCA13, bovine ATP binding cassette subfamily A member 13; d) MMP8, bovine matrix metallopeptidase 8; e) SPARC, bovine secreted protein acidic and cystein rich; f) IDEXX ELISA. The data are represented as scatter plots with each dot representing a single animal. The mean of each histological group is represented by a gross black point and the standard deviation by a vertical line. The asterisks indicate if the differences between each histological group and the control are or not significant (*, p<0.05; **, p>0.01; ***, p<0.001).

[0043] FIG. 2. Receiver operator characteristics curves (ROC curves) of selected biomarkers in Holstein Friesian cows with focal (n=55), multifocal (n=17) or diffuse (n=15) histological lesions in their intestinal tissues versus control animals from a PTB-free farm (n=61). The number of animals with focal, multifocal, diffuse or with any type of lesions analysed for ABCA13 was 53, 16, 14 and 83, respectively. a) FAM84A, bovine family with sequence similarity 84-member A; b) DES, bovine desmin, c) ABCA13, bovine ATP binding cassette subfamily A member 13; d) MMP8, bovine matrix metallopeptidase 8; e) SPARC, bovine secreted protein acidic and cystein rich; f) IDEXX serum ELISA.

DETAILED DESCRIPTION OF THE INVENTION

[0044] The following examples disclose a preferred way of carrying out the invention, without the intention of limiting its scope of protection.

EXAMPLE 1

Methodology.

EXAMPLE 1.1

Animals and Ethical Considerations

[0045] Two groups of animals were included in this field study: Slaughtered group) Ninety-three Holstein Friesian cows (ranging from 0.81 to 12.66 years of age) came from 26 farms located in the Principality of Asturias (Northwest of Spain). In Asturias 25% of the herds and 1.9% of the animals were positive by serum ELISA in 2017 (data taken from the records of the Regional Government). Specifically, fifty-five animals came from a dairy farm with a mean herd size of 105 cows (2016-2019) and a mean prevalence of PTB of 6.30% in the sampling period, based on serum ELISA test (IDEXX laboratories, Hoofddorp, The Netherlands). Another thirty-four animals were chosen randomly from cows slaughtered in the local abattoir (coming from 24 different farms) and the remaining four cows came from SERIDA's Friesian cow farm (3% mean prevalence of PTB in the period 2018-2019). The PTB infection status of these 93 animals at the time of slaughter was determined by histopathology, serum ELISA test, and bacteriological culture and specific real-time PCR of tissues and feces. Information related to the presence of PTB-associated clinical signs such as gradual weight loss, diarrhea and decreased milk production was obtained from the farmers when possible; and PTB-free group) Sixty-one animals (ranging from 0.50 to 10.08 years of age) from a PTB-free faun in Asturias were used as the control group for the study. The PTB-free status of this control farm was verified yearly by IDEXX serum ELISA, the absence of clinical cases in the period 2016-2020 as well as by the absence of positive fecal bacteriological culture and PCR results in 2019.

[0046] Experimental procedures were approved by the SERIDA Animal Ethics Committee and authorised by the Regional Consejeria de Agroganaderia y Recursos Autoctonos del Principado de Asturias. Spain (authorization codes PROAE 29/2015 and PROAE 66/2019). All the procedures were carried out in accordance with the Directive 2012/63/EU of the European Parliament.

EXAMPLE 1.2

Tissues and Fecal Real-Time Polymerase Chain Reaction (PCR)

[0047] Isolation of genomic DNA from tissues and feces was performed using the MagMax Total Nucleic Acid Isolation kit according to the manufacturer's instructions (TeiinoFisher Scientifc, Lissieu, France). For detection of MAP DNA, the LSI VetMax Triplex real-time PCR was used according to the manufacturer's instructions (TermoFisher Scientifc, Lissieu, France). The kit enables real-time PCR detection of Map IS900 and F57 genes in DNA extracted from feces, liquid cultures, and tissues or colonies. Real-time PCR amplifications were performed using the MX3000P Real-Time PCR detection system (Stratagene, San Diego, USA) system with the following conditions: 1 cycle at 50° C. for 2 min, 1 cycle of 95° C. for 10 min, 45 cycles of denaturation at 95° C. for 15 s, and annealing/extension at 60° C. for 60 s.

EXAMPLE 1.3.

Bacteriological Culture of Tissues and Feces

[0048] For bacteriological culture, a pool (2 gr) of ileocecal lymph nodes, distal jejunal lymph node, ileocecal valve (ICV), and distal jejunum were decontaminated with 38 mL of hexa-decyl pyridinium chloride at a final concentration of 0.75% (Sigma, St. Louis, Mo.) and homogenized in a stomacher blender. After 30 min of incubation at room temperature, 15 mL of the suspension was transferred to a new tube and incubated overnight for decontamination and sedimentation. Approximately, 200 μl of the suspension was taken from the layer near the sediment and inoculated into two slants of Herrolds egg yolk medium (HEYM; Becton Dickinson, Sparks, Md.) and into two slants of Lowenstein-Jensen medium (LJ; Difco, Detroit, Mich.), both supplemented with 2 mg/L of Mycobactin J (ID.vet Innovative Diagnostics, Grabels, France). At the time of slaughter, feces were taken from the rectum of each animal, maintained at 4° C. and processed within 48 h after arrival at the laboratory. The fecal samples (2 g each) were decontaminated, blended in a stomacher, and cultured in HEYM and LJ, as previously described for tissue culture.

EXAMPLE 1.4

Histological Classification of Animals

[0049] As mentioned above animals included in this study were classified according to the type of histological lesions present in their intestinal tissues. Tissue sections of distal jejunum, ICV and jejunum and ICV lymph nodes were collected from the 93 slaughtered cows, fixed in 10% neutral buffered formalin, sliced and embedded in paraffin wax using standard procedures. Afterwards, 4 μm sections were assessed by haematoxylin-eosin (HE) and Ziehl-Neelsen (ZN) staining for specific acid-fast bacteria detection. Slices were observed using an Olympus BH-2 light microscope and photographed using an Olympus DP-12 digital camera. The stained sections were examined by light microscopy for detection and classification of pathological lesions and for the presence of acid-fast bacteria (AFB).

EXAMPLE 1.5

Enzyme-Linked Immunosorbent Assays (ELISA) for Detection of the Selected Biomarkers

[0050] Peripheral blood was collected from the tail vein of all the cows included in the study using BD Vacutainer Z serum clot activator Plastic tubes (Vacuette. Kremsmunster. Austria). After clotting, serum was separated by centrifugation for 20 min at 2,500 g at room temperature and stored at −20° C. until use. The concentrations of the selected biomarkers in the serum of each animal were measured using commercially available ELISAs according to the manufacturers' instructions. Quantitative sandwich ELISA kits Bovine Matrix Metalloproteinase 8 (MMP8) (Detection range 3.12-100 ng/mL); Bovine Protein FAM84A ELISA kit (Detection range 62.5-2000 pg/mL), Bovine SPARC ELISA kit (Detection range 0.78-50 ng/mL), and competitive Bovine ATP-binding cassette sub-family A member 13 (ABCA13) ELISA kit (Detection range 0-5000 pg/mL) and Bovine Desmin (DES) ELISA kit (Detection range 0-25 ng/mL) were used for specific detection of MMP8, FAM84A, ABCA13, SPARC and DES, respectively (MyBioSource, San Diego, Calif. USA).

[0051] The assay procedure for the specific detection of biomarker ABCA13 is described in more details as follows: [0052] 1. Add 100 μL of serum samples and the standards to the appropriate well. Add 100 μL of PBS (pH 7.0-7.2) to the blank control well. [0053] 2. Add 50 μL of conjugate to each well (NOT to the blank control well). Mix well. Cover the plate and incubate for 1 hour at 37° C. [0054] 3. Wash the plate five times with diluted 1× wash solution (350-400 μL/well/wash) using an automatic washer. It is recommended that the washer be set for a soaking time of 10 seconds and shaking time of 5 seconds between each wash. [0055] 4. Add 50 μL substrate A and 50 μL substrate B to each well including blank control well. Subsequently, cover and incubate for 15 minutes at 37° C. (avoid sunlight, if after 15 min the color is not dark please prolong the incubation time, but the longest time is 30 min) [0056] 5. Add 50 μL of Stop Solution to each well including blank control well. Mix well. [0057] 6. Determine the Optical Density (O.D.) at 450 nm using a microplate reader immediately.

[0058] A standard curve was used to determine the concentration of biomarkers in the serum samples (average OD of each standard was plotted on the vertical axis against the concentration on the horizontal axis and the best fit drawn to generate a regression curve). Standards and samples were tested in duplicate. The mean value of the blank control was subtracted from mean raw OD values before result interpretation. For optimization various dilutions of the serum were tested (for instance: undiluted, 1:2, 1:4 and 1:8) and the dilution which showed a larger number of samples with measurement values included within the range of the standard curve was considered optimal. In most cases the optimal dilution was 1:2, however, samples with high concentrations of a specific biomarker had to be assayed at higher dilutions.

EXAMPLE 1.6

Statistical Analysis

[0059] The AUC (area under the curve) and optimal cut-off value for each ELISA was determined by Receiver operator characteristic (ROC) curve analysis. The optimal cut off values for sensitivity and specificity were based on maximum Youden Index (J=Se+Sp−1).

[0060] The discriminatory power of each biomarker-based ELISA to differentiate between the different histological groups and the control group was determined according to [Muller, M. P., Tomlinson, G., Marrie, T. J., Tang, P., McGeer, A., Low, D. E., Detsky, A. S., Gold, W. L. (2005). Can routine laboratory tests discriminate between severe acute respiratory syndrome and other causes of community-acquired pneumonia? Clin Infect Dis. 40(8):1079-86. https://doi.org/10.1086/428577][Park H E., Park, H-T., Jung Y H., Yoo, H S. (2017). Establishment a real-time reverse transcription PCR based on host biomarkers for the detection of the sub-clinical cases of Mycobacterium avium subsp. Paratuberculosis. PLoS One. 25; 12(5):e0178336. doi: 10.1371/journal.pone.0178336] as follows: AUC scores≥0.9 were considered to have excellent discriminatory power; 0.8≤AUC <0.9 good discriminatory power; 0.7≤AUC<0.8 fair discriminatory power; and AUC<0.7, poor discriminatory power (Muller et al., 2005). Higher AUC scores were considered as showing better discriminatory powers.

[0061] Multivariate binary logistic regression models (Caret package of R) were used to assess the diagnostic capacity of the simultaneous use of several biomarkers, providing the AUC, and values like sensitivity and specificity for the different biomarker combinations. Comparison of ROC curves to test the statistical significance of the difference between the areas under ROC curves (derived from the same cases) was performed with the method of DeLong et al. (1988) [DeLong E R, DeLong D M, Clarke-Pearson D L (1988): Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837-845] for the biomarkers with fair, good and excellent AUC values (AUC≥0.7). Statistical significance of differences in quantitative variables (for instance: age) between two histological groups were studied using the t Student test (normality) or Wilcoxon test (not normality).

[0062] All the data was analyzed using the pROC, OptimalCutpoints and Caret [Max Kuhn (2020). caret: Classification and Regression Training. R package version 6.0-85. https://CRAN.R-project.org/package=caret] packages of R Statistical environment version 3.6.0 [R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna. Austria. URL https://www.R-projectorg/], with confidence intervals stated at 95%.

EXAMPLE 2

Results.

EXAMPLE 2.1

Histological, Immunological and Microbiological Assessment of MAP Infection Status

[0063] The histological, immunological and microbiological characteristics of all the animals included in this study (slaughtered animals n=93 and control animals from a PTB-free farm n=61) are summarized in Table 2.

[0064] Thus, Table 2 shows the assessment of MAP infection status in 154 Holstein Friesian cows included in the study. Pathological examination of intestinal tissue sections allowed the classification of the animals in four groups: focal (n=55, 59.14%), multifocal (n=17, 18.28%), diffuse (n=15, 16.12%) and no lesions (n=6, 6.45%).

TABLE-US-00002 TABLE 2 MULTI- DIAGNOSTIC FOCAL FOCAL DIFFUSE NL CONTROL METHOD (n = 55) (n = 17) (n = 15) (n = 6) (n = 61) ZN 49.09% 94.11% .sup. 100% 0% UN IDEXX 5.45% 23.52% 73.33% 0% 0% ELISA FECAL 9.09% 29.41% 73.33% 0% 0% PCR FECAL 5.45% 17.64% 20.00% 0% 0% CULTURE TISSUE 27.27% 41.17% 73.33% 0% UN PCR TISSUE 27.27% 41.17% 66.66% 0% UN CULTURE CLINICAL 0.00% 15.38% 64.28% 0% 0.00%   SIGNS AGE 5.72 ± 5.50 ± 4.98 ± 2.41 ± 3.62 ± (years) 2.16 1.85 1.58 1.11 2.41 NL, no lesions; CONTROL; refers to the 61 control animals from a PTB-free farm; UN, undetermined (tissues not available as animals are alive); Age is expressed as the mean value of the group ± standard deviation. The calculation of the % of animals with clinical signs is based on animals with known clinical status (focal n = 28, multifocal n = 13, diffuse n = 14 and control n = 61).

[0065] In the group of animals with focal lesions, 76.36% were positive by one or more diagnostic methods (Ziehl-Neelsen, fecal and tissue real-time PCR, fecal and tissue bacteriological culture and serum ELISA) and the remaining 23.64% were negative by all the tests assayed (n=13). Specifically, 49.09% were positive by Ziehl-Neelsen, 9.09% by fecal real-time PCR, 27.27% by tissue real-time PCR and by tissue bacteriological culture, and 5.45% by fecal bacteriological culture, and serum ELISA. None of the animals in the focal group showed clinical signs associated with PTB, so these animals with focal lesions were considered to be sub-clinically infected.

[0066] In the group of animals with multifocal lesions, 100% of the samples were positive for at least one of the following 6 techniques: Ziehl-Neelsen, fecal and tissue real-time PCR, fecal and tissue bacteriological culture and serum ELISA. In particular, 94.11% of the animals were positive by Ziehl-Neelsen, 23.52% by serum ELISA, 29.41% by fecal real-time PCR, 41.17% by tissue real-time PCR, 17.64% by fecal culture and 41.17% by tissue culture. In this group a higher percentage of animals (15.38%) showed clinical signs, including the youngest animal with clinical signs (2.72 years old). In the diffuse group, 100% of the animals were positive by Ziehl-Neelsen, 73.33% were positive by serum ELISA and by fecal and tissue real-time PCR, 20% by fecal culture and 66.66% by tissue culture. In this group, 64.28% of the animals had PTB-associated clinical signs.

[0067] Only 6 out of the 94 animals analyzed by histopathology did not show histological lesions in their intestinal tissues. These animals were negative by fecal and tissue MAP-specific PCR and bacteriological culture, and by serum ELISA. Given the difficulty to find animals without lesions it was decided to use as control group 61 animals coming from a PTB-free farm in Asturias in order to increase the size of the sample and the statistical significance of the results. The PTB-free status of this control farm had been verified yearly four times by IDEXX serum ELISA and absence of clinical cases in the period 2016-2019, as well as by bacteriological culture and specific real-time PCR of feces in 2019. However, none of them had been examined histologically since this is a post-mortem test and these animals are still alive.

[0068] Significant differences were found between the age of the focal (5.72±2.16 years) and the PTB-free control (3.62±2.41 years) group (p<0.001); and between the age of the multifocal (5.50±1.85 years) and PTB-free control (3.62±2.41 years) group (p=0.009). However, no significant differences were found between the age of the diffuse (4.98±1.58 years) and control (3.62±2.41) groups (p=0.141), focal and diffuse groups (p=0.65), multifocal and diffuse groups (p=0.905), and multifocal and focal groups (0.982).

EXAMPLE 2.2

ROC Analysis of the Selected Biomarker-Based ELISAs

[0069] The diagnostic accuracies of each biomarker-based ELISA to discriminate between the different histological groups and the control group were calculated by ROC analysis (FIGS. 1 and 2). ROC analysis of the data obtained from 4 biomarker-based ELISAs for detection of FAM84A, DES, MMP8 and SPACR was performed using 87 serum samples from 55 animals with focal, 17 with multifocal and 15 with diffuse lesions. ROC analysis of ABCA13-based ELISA was performed using 83 serum samples from 53 animals with focal, 16 with multifocal and 14 with diffuse lesions. As mentioned above, the control group used for this analysis consisted of 61 animals from a PTB-free farm in Asturias. The diagnostic performance of the biomarker-based ELISAs was also compared to that of conventional PTB diagnosis methods such as specific anti-MAP antibody ELISA (IDEXX ELISA). FIG. 1 shows the concentration of each biomarker in the serum of every single Holstein Friesian cattle classified within a specific histological group and FIG. 2 shows the ROC curves of the data obtained with each of the biomarker-based ELISA for each histological group.

EXAMPLE 2.2.1

Detection of Animals with Focal Histological Lesions (Table 3)

[0070] Three ELISAs for the detection of the biomarkers ABCA13, MMP8 and SPARC had good discriminatory power between the focal and control groups (0.8≤AUC<0.9). However, the ABCA13-based ELISA showed the most accurate diagnostic performance (AUC value of 0.866, p<0.001), with a sensitivity of 79.25% and a high specificity of 93.44%. Combination of ABCA13 and SPARC-based ELISAs gave an AUC value slightly higher 0.951, with a sensitivity of 93.44% and a specificity (80.77%). Diagnostic performance of ABCA13-based ELISA for the detection of animals with focal lesions was better than that of the IDEXX ELISA (AUC value of 0.536), which had a sensitivity of 14.50% and a specificity of 100.00%. No significant differences were observed between the ROC curves of the ABCA13, MMP8 and SPARC-based ELISAs (ABCA13 vs MMP8, p=0.386; ABCA13 vs. SPARC, p=0.372 and MMP8 vs. SPARC, p=0.781). Table 3 shows the diagnostic performance of selected biomarker-based ELISAs for diagnosis of cattle with focal histological lesions in the intestinal tissues. The ELISA with the best diagnostic performance is shown in bold face.

TABLE-US-00003 TABLE 3 FOCAL (N = 55) VS. CONTROL (N = 61) BIOMARKER AUC p-value CUT OFF SE (%) SP (%) DV FAM84A 0.522 0.682 1.04 38.2 73.8 0.560 DES 0.622 0.024 23.1 61.8 68.8 0.653 ABCA13 0.866 <0.001 1.74 79.2 93.4 0.863 MMP8 0.802 <0.001 33.31 87.3 68.8 0.780 SPARC 0.816 <0.001 273.15 59.2 88.5 0.738 IDEXX ELISA.sup.a 0.536 0.511 28.39 14.5 100 0.572 IDEXX ELISA.sup.b 55% 5.45 100 0.527 AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); p-value, it is the p-value of the AUC area, indicates whether the discrimination between animals with lesions and controls is significant; DES, bovine desmin; FAM84A, bovine family with sequence similarity 84 member A; ABCA13, bovine ATP binding cassette subfamily A member 13; MMP8, bovine matrix metallopeptidase 8; SPARC, bovine secreted protein acidic and cysteine rich; .sup.athe diagnostic accuracy of the IDEXX ELISA was calculated by ROC curve analysis; .sup.bthe cut off value used to calculate the sensitivity and specificity of the assay was calculated using the cut off value established by the supplier.

EXAMPLE 2.2.2

Detection of Animals with Multifocal Histological Lesions (Table 4)

[0071] In the multifocal group the SPARC-based ELISA showed the most accurate diagnostic performance. The SPARC-based ELISA had good discriminatory power (AUC value of 0.865, p<0.001) between the multifocal and control groups, with a sensitivity of 66.70% and a specificity of 95.10%. Combination of the results using the ABCA13 and SPARC-based ELISAs gave an AUC of 0.900 with a sensitivity of 98.36% and a specificity of 64.71%. The diagnostic performance of the ELISA based on detection of SPARC was also compared to that of the IDEXX ELISA. Diagnostic performance of SPARC-based ELISA for detection of animals with multifocal lesions was better than that of the IDEXX ELISA (AUC value of 0.594), which has a sensitivity of 27.80% and a specificity of 100.00%. There were no significant differences between their ROC curves of the MMP8 and SPARC-based ELISAs (MMP8 vs. SPARC, p=0.771).

[0072] Table 4 shows the diagnostic performance of selected biomarkers-based ELISAs for diagnosis of cattle with multifocal histological lesions in their intestinal tissues. The ELISA with the best diagnostic performance is shown in bold face.

TABLE-US-00004 TABLE 4 MULTIFOCAL (N = 17) VS. CONTROL (N = 61) BIOMARKER AUC p-value CUT OFF SE (%) SP (%) DV FAM84A 0.524 0.766 0.87 50.00 67.20 0.586 DES 0.597 0.213 23.93 61.10 68.80 0.649 ABCA13 0.676 0.028 0.97 70.60 70.50 0.705 MMP8 0.779 <0.001 26.92 94.40 62.30 0.783 SPARC 0.865 <0.001 354.94 66.70 95.10 0.809 IDEXX ELISA.sup.a 0.594 0.229 67.58 27.80 100.00 0.639 IDEXX ELISA.sup.b 55% 27.77 100.00 0.617 AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); p-value, it is the p-value of the AUC area, indicates whether the discrimination between animals with lesions and controls is significant; DES, bovine desmin; FAM84A, bovine family with sequence similarity 84 member A; ABCA13, bovine ATP binding cassette subfamily A member 13; MMP8, bovine matrix metallopeptidase 8; SPARC, bovine secreted protein acidic and cysteine rich; .sup.athe diagnostic accuracy of the IDEXX ELISA was calculated by ROC curve analysis; .sup.bthe cut off value used to calculate the sensitivity and specificity of the assay was calculated using the cut off value established by the supplier.

EXAMPLE 2.2.3

Detection of Animals with Diffuse Histological Lesions (Table 5)

[0073] Two ELISAs for the detection of ABCA13 and MMP8 had good discriminatory power between the diffuse and control groups (0.8≤AUC<0.9). However, MMP8-based ELISA showed the most accurate diagnostic performance (AUC value of 0.866, <0.001) with a sensitivity of 100.00% and a specificity of 77.10%. In this case, combination of biomarkers-based ELISAs does not improve the results obtained individually by the MMP8-based ELISA. The diagnostic performance of the ELISA based on detection of MMP8 was also compared to that of the IDEXX ELISA. The discriminatory power of the IDEXX ELISA between the diffuse and control groups was excellent with an AUC value of 0.917 (p<0.001). The diagnostic performance of the IDEXX ELISA for the detection of animals with diffuse lesions was better than that of the biomarker-based ELISAs, with a sensitivity of 86.70% and a specificity of 96.70%. Comparison of the ROC curves of ABCA13, MMP8 and IDEXX ELISAs showed that there were no significant differences between the three ROC curves (ABCA13 vs MMP8, p=0.843; ABCA13 vs. IDEXX ELISA, p=0.482 and MMP8 vs. IDEXX ELISA, p=0.444).

[0074] Table 5 shows the diagnostic performance of selected biomarkers-based ELISAs for diagnosis of cattle with diffuse histological lesions in their intestinal tissues. The ELISA with the best diagnostic performance is shown in bold face.

TABLE-US-00005 TABLE 5 DIFFUSE (N = 15) VS. CONTROL (N = 61) BIOMARKER AUC p-value CUT OFF SE (%) SP (%) DV FAM84A 0.635 0.108 1.06 66.70 75.40 0.710 DES 0.619 0.159 36.59 46.70 88.50 0.676 ABCA13 0.851 <0.001 1.20 86.70 83.30 0.850 MMP8 0.866 <0.001 40.23 100.00 77.10 0.885 SPARC 0.61 0.192 7.73 100.00 36.10 0.680 IDEXX ELISA.sup.a 0.917 <0.001 19.6 86.70 96.70 0.917 IDEXX ELISA.sup.b 55% 73.33 100 0.866 AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); p-value, it is the p-value of the AUC area, indicates whether the discrimination between animals with diffuse lesions and controls is significant; DES, bovine desmin; FAM84A. bovine family with sequence similarity 84 member A; ABCA13, bovine ATP binding cassette subfamily A member 13; MMP8, bovine matrix metallopeptidase 8; SPARC, bovine secreted protein acidic and cysteine rich; .sup.athe diagnostic accuracy of the IDEXX ELISA was calculated by ROC curve analysis; .sup.bthe cut off value used to calculate the sensitivity and specificity of the assay was calculated using the cut off value established by the supplier of the kit.

EXAMPLE. 2.2.4

Overall Detection of Animals with Any Type of Histological Lesions (Table 6)

[0075] We compared the ability of the biomarker-based ELISAs to discriminate infected cows with any type of histological lesion (focal, multifocal or diffuse) from the control group. It must be taken into account that the three different histological groups are not equally represented (focal n=55, multifocal n=17 and diffuse n=15), however, this is a reflection of the real situation in the farms. The ABCA13 and MMP8-based ELISAs had good discriminatory power (0.8≤AUC<0.9) between the animals with lesions and the control group. However, ABCA13-based ELISA showed the most accurate diagnostic performance (AUC value of 0.825, p<0.001) with a sensitivity of 70.60% and a specificity of 91.80%. The combination of the results obtained with the ABCA13 and SPARC-based ELISAs gave an AUC value slightly higher (0.933) with a sensitivity of 88.52% and a specificity of 79.76%. The diagnostic performance of the ELISA based on detection of ABCA13 was also compared to that of the IDEXX ELISA. Diagnostic performance of ABCA13-based ELISA for detection of infected animals was better than that of the IDEXX ELISA (AUC value of 0.613), which had a sensitivity of 28.40% and a specificity of 100.00%.

[0076] Table 6 shows the diagnostic perfoi nance of selected biomarkers-based ELISAs for diagnosis of cattle with histological lesions in their intestinal tissues. The ELISA with the best diagnostic performance is shown in bold face.

TABLE-US-00006 TABLE 6 ALL LESIONS (N = 93) VS. CONTROL (N = 61) BIOMARKER AUC p-value CUT OFF SE (%) SP (%) DV FAM84A 0.542 0.388 1.06 42.00 75.40 0.587 DES 0.617 0.016 23.1 61.40 68.80 0.651 ABCA13 0.825 <0.001 1.29 70.60 91.80 0.812 MMP8 0.808 <0.001 33.17 87.50 68.80 0.782 SPARC 0.79 <0.001 354.94 47.10 95.10 0.711 IDEXX ELISA.sup.a 0.613 0.020 28.39 28.40 100.00 0.642 IDEXX ELISA.sup.b 55% 32.20 100.00 0.661 AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); p-value, it is the p-value of the AUC area, indicates whether the discrimination between animals with lesions and controls is significant; DES, bovine desmin; FAM84A. bovine family with sequence similarity 84 member A; ABCA13, bovine ATP binding cassette subfamily A member 13; MMP8, bovine matrix metallopeptidase 8; SPARC, bovine secreted protein acidic and cysteine rich; .sup.athe diagnostic accuracy of the IDEXX ELISA was calculated by ROC curve analysis; .sup.bthe cut off value used to calculate the sensitivity and specificity of the assay was calculated using the cut off value established by the supplier.

[0077] A summary of the ELISAs with the best diagnostic performance for each histological group is provided below. ABCA13-based ELISA showed the most accurate diagnostic performance (AUC value of 0.866, p<0.001) for detection of animals with focal lesions. SPARC-based ELISA showed the most accurate diagnostic performance (AUC value of 0.865, p<0.001) for the detection of animals with multifocal lesions. MMP8-based ELISA showed the most accurate diagnostic performance (AUC value of 0.866, p<0.001) for the detection of animals with diffuse lesions, however, the diagnostic performance of the IDEXX ELISA (AUC value of 0.917, p<0.001) was better than that of the biomarker-based ELISAs with a sensitivity of 86.70% and a specificity of 96.70%. Finally, for overall detection of animals with any type of histological lesions ABCA13-based ELISA showed the most accurate diagnostic performance (AUC value of 0.825, p<0.001) with a sensitivity of 70.60% and a specificity of 91.80%. Moreover, the combination of biomarkers for detection of animals with focal, multifocal or any type of lesions could improve the sensitivity of the diagnosis. Taken together our results show that the ABCA13-based ELISA is a very accurate method for the discrimination of animals with focal lesions and for overall detection of animals with any type of histological lesion.

[0078] Table 7 shows the diagnostic performance of the best biomarker-based ELISAs and IDEXX ELISA for the detection of the different histological animal groups. ROC analysis of MMP8 and SPARC-based ELISAs and the IDEXX ELISA was performed using 87 serum samples from 55 animals with focal, 17 with multifocal and 15 with diffuse lesions. ROC analysis of ABCA13-based ELISA was performed using 83 serum samples from 53 animals with focal, 16 with multifocal and 14 with diffuse lesions:

TABLE-US-00007 TABLE 7 GROUP ELISA AUC p-value CUT OFF SE (%) SP (%) DV FOCAL ABCA13 0.866 <0.001 1.74 79.20 93.40 0.863 MULTIFOCAL SPARC 0.676 0.028 0.97 70.60 70.50 0.705 DIFFUSE MMP8 0.851 <0.001 1.20 86.70 83.30 0.850 DIFFUSE IDEXX.sup.a 0.917 <0.001 19.6 86.70 96.70 0.917 ALL LESIONS ABCA13 0.825 <0.001 1.29 70.60 91.80 0.812 GROUP, refers to the different groups of analysis established based on histopathological classification; AUC, area under the curve; p-value, indicates whether the discrimination between animals with lesions and controls is significant; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); ABCA13, bovine ATP binding cassette subfamily A member 13; MMP8, bovine matrix metallopeptidase 8; SPARC, bovine secreted protein acidic and cysteine rich; .sup.athe diagnostic accuracy of the IDEXX ELISA was calculated by ROC curve analysis

EXAMPLE 2.2.5

Comparison of the Diagnostic Performance of the ABCA13-based ELISA with that of Other Conventional Methods for the Diagnostic of Animals with Focal Lesions

[0079] The diagnostic performance of the ELISA based on detection of ABCA13 was also compared to that of conventional PTB diagnosis methods such as specific anti-MAP antibody ELISA (IDEXX ELISA), and specific fecal and tissue real-time PCR and bacteriological culture.

[0080] Table 8 shows the diagnostic performance of conventional and novel biomarker-based diagnostic assays for the detection of animals with focal lesions in their intestinal tissues. ABCA13-based ELISA showed a better diagnostic value than the other diagnostic methods tested for the detection and discrimination of animals with focal lesions. It was able to detect as positive 44 out of 55 animals with focal lesions (80% sensitivity) and as negative 57 out of the 61 controls (93% specificity). The diagnostic value or sensitivities of the other conventional methodologies was lower. Specifically, the IDEXX ELISA was 100% specific but only detected as positive 3 out of 55 animals (5.45% sensitivity) when the cut off used (55%) was the one established by the supplier or 8 out of 55 (14.54%) when we used the cut-off point (28.39%) calculated by ROC analysis.

TABLE-US-00008 TABLE 8 METHOD AUC p-value CUT OFF SE (%) SP (%).sup.d DV ELISA ABCA13.sup.a 0.866 <0.001 1.74 79.20 93.40 0.863 IDEXX ELISA.sup.b 0.536 0.511 28.39% 14.50 100 0.572 IDEXX ELISA.sup.c   55% 5.45 100 0.527 Fecal culture 5.45 100 0.527 Fecal PCR 9.09 100 0.545 Tissue culture 27.27 UN Tissue PCR 27.27 UN AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value; UN, undetermined; p-value, indicates whether the discrimination between animals with focal lesions and controls is significant. ABCA13, bovine ATP binding cassette subfamily A member 13; .sup.aindicate that the number of animals with focal, multifocal, diffuse or with any type of lesions analysed with theABCA13-based ELISA was 53, 16, 14 and 83, respectively; .sup.bthe cut off value used to estimate the sensitivity and specificity of the assay was calculated by ROC analysis; .sup.cthe cut off value used to estimate the sensitivity and specificity of the assay was the one established by the supplier; .sup.dthe control group used to calculate the specificity consisted of 61 animals from a PTB-free farm.

EXAMPLE 2.2.6

A combination of Biomarker-Based ELISAs was Tested to Determine the Diagnostic Value of the ABCA13-based ELISA Using Logistic Regression Analysis5

[0081] Diagnostic models based on the combination of some of the five selected biomarkers slightly improve the diagnostic value of the single biomarker-based ELISAs (see Table 9).

[0082] Table 9 shows the diagnostic performance of models based on the combined use of various biomarkers compared with the performance obtained for single biomarker-based ELISAs for diagnosis of cattle with different histological lesions in the intestinal tissues. This analysis was carried out using 55 focal, 18 multifocal, 15 diffuse animals and 67 control animals

TABLE-US-00009 TABLE 9 SE SP GROUP BIOMARKER AUC P-value (%) (%) DV FOCAL ABCA13 0.837 <0.001 79.25 88.06 0.84 MULTIFOCAL SPARC 0.852 <0.001 66.67 92.54 0.80 DIFFUSE MMP8 0.831 <0.001 100 71.64 0.86 PATENT MMP9 0.781 <0.001 96.97 58.21 0.78 ANY LESION ABCA13 0.793 <0.001 69.41 86.57 0.78 BIOMARKER SE SP GROUP MODELS AUC 95% CI (%) (%) DV FOCAL DES, ABCA13 AND 0.911 0.437-0.646 84.62 86.57 0.86 SPARC MULTIFOCAL DES, FAM84A AND 0.851 0.737-0.964 70.54 89.55 0.80 SPARC DIFFUSE — PATENT DES, ABCA13, 0.82 0.727-0.910 75 85.07 0.80 MMP8 AND SPARC ANY LESION DES, ABCA13, 0.878 0.824-0.932 80.95 85.07 0.83 MMP8 AND SPARC Group, histological group; AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); p-value, it is the p-value of the AUC area, indicates whether the discrimination between animals with focal lesions and Controls is significant; DES, bovine desmin; FAM84A, bovine family with sequence similarity 84 member A; ABCA13, bovine ATP binding cassette subfamily A member 13; MMP8, bovine matrix metallopeptidase 8; SPARC, bovine secreted protein acidic and cystein rich.

EXAMPLE 2.2.7

Large-Scale Validation of ABCA13-based ELISA

[0083] We had shown that the ELISA for the detection of ABCA13 is an accurate method for detection of animals with focal lesions and for overall detection of animals with any type of histological lesion.

[0084] To further confirm these results a large-scale validation of the ABC13-based ELISA (n=661) was performed using 556 serum samples from 445 infected animals with focal, 55 with multifocal and 58 with diffuse lesions. The non-infected control group consisted of 105 animals from two PTB-free farms in Asturias.

[0085] Table 10 shows the diagnostic performance of the ABCA13-based ELISA for diagnosis of cattle with different types of histological lesions in their intestinal tissues. The diagnostic accuracy of the ABCA13-based ELISA was calculated by ROC curve analysis.

TABLE-US-00010 TABLE 10 AUC P value CUTOFF SE % SP % DV Control (n = 105) vs. All-lesion 0.843 <0.0001 >3.66 77.24 84.76 0.81 (n = 556) Control (n = 105) vs. focal 0.883 <0.0001 >3.66 82.02 84.76 0.83 (n = 445) Control (n = 105) vs. multifocal 0.667 0.0032 >3.66 61.82 84.76 0.73 (n = 55) Control (n = 105) vs. diffuse 0.705 <0.0001 >3.1 63.79 77.10 0.70 (n = 58) Control (n = 105) vs. Patent 0.687 <0.0001 >3.66 58.41 84.76 0.72 (n = 113) AUC, area under the curve; SE, sensitivity; SP, specificity; DV, diagnostic value (semi-sum of the sensitivity and specificity); p-value, it is the p-value of the AUC area, indicates whether the discrimination between animals with focal lesions and Controls is significant; ABCA13, bovine ATP binding cassette subfamily A member 13. The patent group consisted of the animals with multifocal and diffuse lesions; The discriminatory power of each biomarker to discern between the different histopathological groups and the Control group was considered as follows: biomarker-based ELISAs with AUC values ≥ 0.9 were considered to have excellent discriminatory power; 0.8 ≤ AUC < 0.9 good discriminatory power; 0.7 ≤ AUC < 0.8 fair discriminatory power; and AUC < 0.7, poor discriminatory.

[0086] The ELISA for detection of ABCA13 has a good discriminatory power between the focal and the control group (AUC value of 0.843, p<0.0001) and between the all-lesion group and the control (AUC value of 0.883, p<0.0001). These results further confirm that the ELISA for the detection of ABCA13 is an accurate diagnostic method for detection of animals with focal lesions and for overall detection of animals with any type of histological lesion.

EXAMPLE 2.2.8

Comparison Between the Results Obtained with ABCA13-based ELISA and IDEXX ELISA (N=661)

[0087] As we have mentioned the IDEXX ELISA is nowadays widely used for the diagnosis of PTB although this method is associated with a high rate of false negative results (low sensitivity). For this reason, we have compared the results obtained with the ABCA13-based ELISA and the IDEXX ELISA for the 661 samples used in the large-scale validation study.

[0088] Table 11 shows the sensitivity, specificity, and diagnostic value of the novel ABCA13-based ELISA and the conventional IDEXX ELISA for the detection of the different histological groups.

[0089] The cut-off value used to estimate the sensitivity and the specificity of the ABCA13-based ELISA and IDEXX ELISA were 3,66 ng/mL and 55% (relative % ODsample/ODpositive control), respectively. The estimation of the sensitivity was based on the analysis of 445 animals with focal lesions, 55 with multifocal, and 58 with diffuse. The control group used to calculate the specificity consisted of 105 animals from two PTB-free farms.

TABLE-US-00011 TABLE 11 Sensitivity (%) LESION TYPE ABCA13-based ELISA IDEX ELISA FOCAL 82.02 3.37 MULTIFOCAL 61.82 32.72 DIFFUSE 63.8 86.2 MULTIFOCAL + DIFFUSE 58.41 60.17 ALL LESION TYPES 77.24 15.09 Specificity (%) ABCA13-based ELISA IDEXX ELISA FOCAL 84.76 100 MULTIFOCAL 84.76 100 DIFFUSE 77.1 100 MULTIFOCAL + DIFFUSE 84.76 100 ALL LESION TYPES 84.76 100 Diagnostic value ABCA13-based ELISA IDEX ELISA FOCAL 0.83 0.52 MULTIFOCAL 0.73 0.66 DIFFUSE 0.70 0.93 MULTIFOCAL + DIFFUSE 0.72 0.80 ALL LESION TYPES 0.81 0.58 ABCA13, bovine ATP binding cassette subfamily A member 13

[0090] These findings support our previous results indicating that the ABCA13-based ELISA is a very accurate method for the discrimination of animals with focal lesions and for overall detection of animals with any type of histological lesion. Specifically, the ABC13-based ELISA has a higher sensitivity for detection of animals with focal lesions representing subclinical infections difficult to detect by conventional diagnostic methods.