Transcriptional Profiling of Early and Late Phases of Bovine Tuberculosis

In-silico analysis of cattle blood transcriptome to identify lncRNAs and their role during bovine tuberculosis

Long noncoding RNAs (lncRNAs) are RNA molecules with a length greater than 200 nucleotides that do not code for functional proteins. Although, genes play a vital role in immune response against a disease, it is less known that lncRNAs also contribute through gene regulation. Bovine tuberculosis is a significant zoonotic disease caused by Mycobacterium bovis (M. bovis) in cattle. Here, we report the in-silico analysis of the publicly available transcriptomic data of calves infected with M. bovis. A total of 51,812 lncRNAs were extracted across all the samples. A total of 216 genes and 260 lncRNAs were found to be differentially expressed across all the 4 conditions-infected vs uninfected at 8- and 20-week post-infection (WPI), 8 vs 20-WPI of both infected and uninfected. Gene Ontology and Functional annotation showed that 8 DEGs were annotated with immune system GOs and 2 DEGs with REACTOME immune system pathways. Co-expression analysis of DElncRNAs with DEGs revealed the involvement of lncRNAs with the genes annotated with Immune related GOs and pathways. Overall, our study sheds light on the dynamic transcriptomic changes in response to M. bovis infection, particularly highlighting the involvement of lncRNAs with immune-related genes. The identified immune pathways and gene-lncRNA interactions offer valuable insights for further research in understanding host-pathogen interactions and potential avenues for genetic improvement strategies in cattle.

Proteome overview of exosome derived from plasma of cows infected with Mycobacterium bovis

Bovine tuberculosis (bTB), primarily caused by Mycobacterium bovis (M. bovis), is a globally zoonotic disease with significant economic impacts. Plasma exosomes have been extensively used for investigating disease processes and exploring biomarkers. While mass spectrometry (MS)-based proteomic analysis of plasma exosomes has been employed for human tuberculosis (TB) studies, it has not yet been applied to bTB. Therefore, a comprehensive proteomic overview of plasma exosomes from M. bovis-infected cows is essential. In this study, we presented an extensive proteomic analysis of plasma exosomes from 89 M. bovis-infected cows across three farms, using data dependent acquisition (DDA) mode. Our analysis encompasses 239,894 spectra, 6,011 peptides and 835 proteins. The proteomic overview revealed both consistencies and differences among individual cows, supplements 595 proteins to the bovine exosome library, and enriches tuberculosis and related pathways. Additionally, six pathways were validated as immune response pathways, and three proteins (CATHL1, H1-1, and LCN2) were identified as potential indicators of bTB. This study is the first to investigate the exosome proteome of plasma from cows infected with M. bovis, providing a valuable dataset for exploring candidate bTB markers and understanding the mechanisms of host defense against M. bovis.

Screening of mRNA markers in early bovine tuberculosis blood samples

Bovine tuberculosis (bTB) is a chronic zoonotic disease caused by Mycobacterium bovis. A large number of cattle are infected with bTB every year, resulting in huge economic losses. How to control bTB is an important issue in the current global livestock economy. In this study, the original transcriptome sequences related to this study were obtained from the dataset GSE192537 by searching the Gene Expression Omnibus (GEO) database. Our differential gene analysis showed that there were obvious biological activities related to immune activation and immune regulation in the early stage of bTB. Immune-related biological processes were more active in the early stage of bTB than in the late. There were obvious immune activation and immune cell recruitment in the early stage of bTB. Regulations in immune receptors are associated with pathophysiological processes of the early stage of bTB. A gene module consisting of 236 genes significantly related to the early stage of bTB was obtained by weighted gene co-expression network analysis, and 18 hub genes were further identified as potential biomarkers or therapeutic targets. Finally, by random forest algorithm and logistic regression modeling, FCRL1 was identified as a representative mRNA marker in early bTB blood. FCRL1 has the potential to be a diagnostic biomarker in early bTB.

In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlying Mycobacterium bovis infection

OBJECTIVE

Bovine tuberculosis (bTB) is a chronic respiratory infectious disease of domestic livestock caused by intracellular Mycobacterium bovis infection, which causes ~$3 billion in annual losses to global agriculture. Providing novel tools for bTB managements requires a comprehensive understanding of the molecular regulatory mechanisms underlying the M. bovis infection. Nevertheless, a combination of different bioinformatics and systems biology methods was used in this study in order to clearly understand the molecular regulatory mechanisms of bTB, especially the immunomodulatory mechanisms of M. bovis infection.

METHODS

RNA-seq data were retrieved and processed from 78 (39 non-infected control vs. 39 M. bovis-infected samples) bovine alveolar macrophages (bAMs). Next, weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression modules in non-infected control bAMs as reference set. The WGCNA module preservation approach was then used to identify non-preserved modules between non-infected controls and M. bovis-infected samples (test set). Additionally, functional enrichment analysis was used to investigate the biological behavior of the non-preserved modules and to identify bTB-specific non-preserved modules. Co-expressed hub genes were identified based on module membership (MM) criteria of WGCNA in the non-preserved modules and then integrated with protein-protein interaction (PPI) networks to identify co-expressed hub genes/transcription factors (TFs) with the highest maximal clique centrality (MCC) score (hub-central genes).

RESULTS

As result, WGCNA analysis led to the identification of 21 modules in the non-infected control bAMs (reference set), among which the topological properties of 14 modules were altered in the M. bovis-infected bAMs (test set). Interestingly, 7 of the 14 non-preserved modules were directly related to the molecular mechanisms underlying the host immune response, immunosuppressive mechanisms of M. bovis, and bTB development. Moreover, among the co-expressed hub genes and TFs of the bTB-specific non-preserved modules, 260 genes/TFs had double centrality in both co-expression and PPI networks and played a crucial role in bAMs-M. bovis interactions. Some of these hub-central genes/TFs, including PSMC4, SRC, BCL2L1, VPS11, MDM2, IRF1, CDKN1A, NLRP3, TLR2, MMP9, ZAP70, LCK, TNF, CCL4, MMP1, CTLA4, ITK, IL6, IL1A, IL1B, CCL20, CD3E, NFKB1, EDN1, STAT1, TIMP1, PTGS2, TNFAIP3, BIRC3, MAPK8, VEGFA, VPS18, ICAM1, TBK1, CTSS, IL10, ACAA1, VPS33B, and HIF1A, had potential targets for inducing immunomodulatory mechanisms by M. bovis to evade the host defense response.

CONCLUSION

The present study provides an in-depth insight into the molecular regulatory mechanisms behind M. bovis infection through biological investigation of the candidate non-preserved modules directly related to bTB development. Furthermore, several hub-central genes/TFs were identified that were significant in determining the fate of M. bovis infection and could be promising targets for developing novel anti-bTB therapies and diagnosis strategies.