Analysis of Differentially Expressed Proteins in<i> Mycobacterium avium</i>-Infected Macrophages Comparing with<i> Mycobacterium tuberculosis</i>-Infected Macrophages

Yang, Dongjun; Fu, Xin; He, Shiyi; Ning, Xueping; Ling, Min

doi:10.1155/2017/5103803

Cited by 6 publications

(4 citation statements)

References 36 publications

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“…TUBB2A encodes

-tubulin, a protein that plays an important role in cell division, migration and intracellular transport [ 34 ]. This gene could act in active macrophage, preventing mature phagolysosome formation and provide comfortable conditions for pathogen survival [ 35 ].…”

Section: Resultsmentioning

confidence: 99%

Can miRNA Indicate Risk of Illness after Continuous Exposure to M. tuberculosis?

Silva

Gonçalves

Pinto

et al. 2021

IJMS

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The role of regulatory elements such as small ncRNAs and their mechanisms are poorly understood in infectious diseases. Tuberculosis is one of the oldest infectious diseases of humans and it is still a challenge to prevent and treat. Control of the infection, as well as its diagnosis, are still complex and current treatments used are linked to several side effects. This study aimed to identify possible biomarkers for tuberculosis by applying NGS techniques to obtain global miRNA expression profiles from 22 blood samples of infected patients with tuberculosis (n = 9), their respective healthy physicians (n = 6) and external healthy individuals as controls (n = 7). Samples were run through a pipeline consisting of differential expression, target genes, gene set enrichment and miRNA–gene network analyses. We observed 153 altered miRNAs, among which only three DEmiRNAs (hsa-let-7g-5p, hsa-miR-486-3p and hsa-miR-4732-5p) were found between the investigated patients and their respective physicians. These DEmiRNAs are suggested to play an important role in granuloma regulation and their immune physiopathology. Our results indicate that miRNAs may be involved in immune modulation by regulating gene expression in cells of the immune system. Our findings encourage the application of miRNAs as potential biomarkers for tuberculosis.

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“…TUBB2A encodes

Section: Resultsmentioning

confidence: 99%

Can miRNA Indicate Risk of Illness after Continuous Exposure to M. tuberculosis?

Silva

Gonçalves

Pinto

et al. 2021

IJMS

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“…In addiSon to widening the scope of the assay, accuracy may be improved by including addiSonal informaSve markers. The current panel was suggested by a limited literature review and included target pathways known to be impacted by Johne's disease, including PI3KT, oestrogen, ErbB and FoxO signalling (31,32). The panel could be expanded by including data from addiSonal mycobacterial species, examining miRNAs known to target addiSonal MAP-affected pathways or by performing a hypothesis-generaSng study using miRNASeq.…”

Section: Discussionmentioning

confidence: 99%

A microRNA-based Johne’s disease diagnostic predictive system: preliminary results

Capewell

Lowe

Athanasiadou

et al. 2023

Preprint

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Background: Johne's disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic enteritis impacting welfare and productivity in cattle. Screening and animal removal are common for disease management, but efforts are hindered by low diagnostic sensitivity. Expression levels of small non-coding RNA molecules involved in gene regulation (microRNAs) altered during mycobacterial infection may present an alternative diagnostic method. Methods: Levels of 24 microRNAs affected by mycobacterial infection were measured in sera from MAP-positive (n=66) and MAP-negative samples (n=65). They were used to train a collection of statistical and machine learning models to identify an optimal classifier for diagnosis. Results: The best-performing model provided 72% accuracy, 78% AUC, 73% sensitivity and 71% specificity on average. Limitations: Although control samples were collected from farms nominally MAP-free, low sensitivity in current diagnostics means animals may be misclassified. Conclusion: MicroRNA profiling combined with advanced predictive modelling techniques accurately diagnosed Johne's disease in cattle.

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“…Other hub-central gene of the brown module, including CSF1 ( Chatterjee et al, 2021 ), PLAUR ( McLoughlin et al, 2021b ), ITGB1 ( Yang et al, 2017 ), CCND1 ( Koo et al, 2012 ; Looney et al, 2021 ), CSF2 ( Marsay et al, 2013 ; Shukla et al, 2017 ; Abdelaal et al, 2022 ), CTLA4 ( Zhang et al, 2021 ), FLNA ( Xu et al, 2015 ), CCND2 ( Lavalett et al, 2017 ), WEE1 ( Jayaswal et al, 2010 ), MMP9 ( Blanco et al, 2012 ; McLoughlin et al, 2014 ), CDC25A ( Shapira et al, 2020 ), CSF2RB ( Benmerzoug et al, 2018 ), TIMP1 ( Sun et al, 2020 ), CD69 ( Li et al, 2011 ; Chen et al, 2020 ), PTPN22 ( Boechat et al, 2013 ), CD38 ( Silveira-Mattos et al, 2019 ), IL7R ( Jenum et al, 2016 ; Alsulaimany et al, 2022 ), IL1RN ( Alcaraz-López et al, 2020 ), and IDO1 ( Weiner et al, 2012 ; Gautam et al, 2018 ) were also involved in host-pathogen interactions as well as suppression of host immune response. For example, the CTLA4 hub-central gene encodes an inhibitor of T cell-mediated response ( Schneider et al, 2006 ), and the upregulation of this gene in response to M. bovis infection may reflect a mechanism of immunomodulation used by M. bovis to subvert a host T-cell response ( Killick et al, 2011 ).…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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ObjectiveBovine 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.MethodsRNA-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).ResultsAs 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.ConclusionThe 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.

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Analysis of Differentially Expressed Proteins in Mycobacterium avium-Infected Macrophages Comparing with Mycobacterium tuberculosis-Infected Macrophages

Cited by 6 publications

References 36 publications

Can miRNA Indicate Risk of Illness after Continuous Exposure to M. tuberculosis?

Can miRNA Indicate Risk of Illness after Continuous Exposure to M. tuberculosis?

A microRNA-based Johne’s disease diagnostic predictive system: preliminary results

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

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