Dataset Information

LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis.

ABSTRACT: Detecting bovine tuberculosis (bTB) primarily relies on the tuberculin skin test, requiring two separate animal handling events with a period of incubation time (normally 3 days) between them. Here, we present the use of liquid atmospheric pressure (LAP)-MALDI for the identification of bTB infection, employing a three-class prediction model that was obtained by supervised linear discriminant analysis (LDA) and tested with bovine mastitis samples as disease-positive controls. Noninvasive collection of nasal swabs was used to collect samples, which were subsequently subjected to a short (<4 h) sample preparation method. Cross-validation of the three-class LDA model from the processed nasal swabs provided a sensitivity of 75.0% and specificity of 90.1%, with an overall classification accuracy of 85.7%. These values are comparable to those for the skin test, showing that LAP-MALDI MS has the potential to provide an alternative single-visit diagnostic platform that can detect bTB within the same day of sampling.

SUBMITTER: Lellman SE

PROVIDER: S-EPMC10515614 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis.

Lellman Sophie E SE Reynolds Christopher K CK Jones A K Barney AKB Taylor Nick N Cramer Rainer R

Journal of agricultural and food chemistry 20230907 37

Detecting bovine tuberculosis (bTB) primarily relies on the tuberculin skin test, requiring two separate animal handling events with a period of incubation time (normally 3 days) between them. Here, we present the use of liquid atmospheric pressure (LAP)-MALDI for the identification of bTB infection, employing a three-class prediction model that was obtained by supervised linear discriminant analysis (LDA) and tested with bovine mastitis samples as disease-positive controls. Noninvasive collecti ...[more]

PMID: 37677086

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Project description:The definition of biomarkers correlating with disease progression could have impact on the rational design of novel diagnostic approaches for bovine tuberculosis in cattle. We have used the advantages of the murine model to identify promising candidates in the host transcriptome post-infection. RNA from BALB/c splenocytes and lung cells after aerogenic Mycobacterium bovis infection were with high-density microarrays to defining biomarkers of disease progression. In antigen-stimulated splenocytes we found statically significant modulation of 1109 genes early after infection and 1134 at later time-point post-infection. 618 of these genes were modulated at both time points. In the lung 282 genes were significantly modulated post-infection. Amongst the most strongly up-regulated genes were granzyme A in spleen, and cxcl9, granzyme B, interleukin-22, interluekin-17A receptor, and ccr6 in lungs. The expression of 20 of the most up-regulated genes identified in the murine studies were evaluated using PBMC from uninfected and naturally infected cattle. We could show that the expression of cxcl9, granzyme A and interleukin-22 following in vitro stimulation with PPD was significantly increased in infected cows compared to naïve animals. Thus, we have demonstrated that murine transcriptome analysis can be used to predict responses in cattle. In addition, we have prioritised CXCL9, GnzA and IL-22 as potential additional readout systems for the ante-mortem diagnosis of bovine tuberculosis. Two groups of 5 BALB/c mice each were infecetd with approx 600 CFU M. bovis via the intranasal route. At days 3 and 14 post challenge five mice per group were euthanized and spleens and lungs harvested. One group of 5 mice were used as a control. Their splenocytes and lung cells were stimulated in vitro for 3 days with M7 protein pool. Antigen cell culture stimulations in mice were performed using an equal pool of seven secreted, immunogenic recombinant mycobacterial proteins (Rv1886c, Rv3019c, Rv3763, Rv3804c, Rv0251, Rv0287 and Rv0288) common to M. bovis and BCG, referred here as M7 protein cocktail. Each protein was used at final concentration of 2μg/ml in 3-day culture.

Project description:MALDI mass-spectrometry imaging (MALDI-MSI) is a technique capable of the label-free identification and visualization of analytes in tissue sections. We have previously applied MALDI-MSI to the study of the spatial distribution of tuberculosis (TB) drugs in necrotic lung granulomas characteristic of pulmonary TB disease, revealing heterogeneous and often suboptimal drug distributions. To investigate the impact of differential drug distributions at sites of infection, we sought to image mycobacterial biomarkers to coregister drugs and bacteria in lesion sections. The traditional method of visualizing Mycobacterium tuberculosis inside lesions is acid-fast staining and microscopy. Directly analyzing and visualizing mycobacteria-specific lipid markers by MALDI-MSI provides detailed molecular information on bacterial distributions within granulomas, complementary to high-spatial-resolution staining and microscopy approaches. Moreover, spatial monitoring of molecular changes occurring in bacteria during granuloma development can potentially contribute to a greater understanding of pulmonary-TB pathogenesis. In this study, we developed a MALDI-MSI method to detect and visualize specific glycolipids of mycobacteria within TB lesions. The biomarker signal correlated well with the bacteria visualized by IHC and acid-fast staining. This observation was seen in samples collected from multiple animal models. Although individual bacteria could not be visualized because of the limit of spatial resolution (50 μm), bacterial clusters were clearly detected and heterogeneously distributed throughout lesions. The ability to visualize drugs, metabolites, and bacterial biomarkers by MALDI-MSI enabled direct colocalization of drugs with specific bacterial target populations (identifiable by distinct metabolic markers). Future applications include assessing drug activity in lesions by visualizing drug-mediated lipid changes and other drug-induced mycobacterial metabolic responses.

Project description:Emergence of extensively drug resistant tuberculosis (XDR-TB) is the consequence of the failure of second line TB treatment. Aminoglycosides are the important second line anti-TB drugs used to treat the multi drug resistant tuberculosis (MDR-TB). Main known mechanism of action of aminoglycosides is to inhibit the protein synthesis by inhibiting the normal functioning of ribosome. Primary target of aminoglycosides are the ribosomal RNA and its associated proteins. Various mechanisms have been proposed for aminoglycosides resistance but still some are unsolved. As proteins are involved in most of the biological processes, these act as a potential diagnostic markers and drug targets. In the present study we analyzed the purely cytosolic proteome of amikacin (AK) and kanamycin (KM) resistant Mycobacterium tuberculosis isolates by proteomic and bioinformatic approaches. Twenty protein spots were found to have over expressed in resistant isolates and were identified. Among these Rv3208A, Rv2623, Rv1360, Rv2140c, Rv1636, and Rv2185c are six proteins with unknown functions or undefined role. Docking results showed that AK and KM binds to the conserved domain (DUF, USP-A, Luciferase, PEBP and Polyketidecyclase/dehydrase domain) of these hypothetical proteins and over expression of these proteins might neutralize/modulate the effect of drug molecules. TBPred and GPS-PUP predicted cytoplasmic nature and potential pupylation sites within these identified proteins, respectively. String analysis also suggested that over expressed proteins along with their interactive partners might be involved in aminoglycosides resistance. Cumulative effect of these over expressed proteins could be involved in AK and KM resistance by mitigating the toxicity, repression of drug target and neutralizing affect. These findings need further exploitation for the expansion of newer therapeutics or diagnostic markers against AK and KM resistance so that an extreme condition like XDR-TB can be prevented.

Dataset Information

LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis.

Publications

LAP-MALDI MS Profiling and Identification of Potential Biomarkers for the Detection of Bovine Tuberculosis.

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