Strategies for drug target identification in Mycobacterium leprae

Acebrón-García-de-Eulate, Marta; Blundell, Tom L.; Vedithi, Sundeep Chaitanya

doi:10.1016/j.drudis.2021.03.026

Cited by 12 publications

(9 citation statements)

References 51 publications

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“…In addition, we noted that 10 virulence genes were significantly over expressed. They are ML0243—Putative acyl-CoA synthetase, ML1014—RNA polymerase sigma factor sigB, ML1076—RNA polymerase sigma factor SigE, ML1128—Diaminopimelate decarboxylase, ML1633—Possible secreted hydrolase, ML1727—O-phosphoserine phosphohydrolase( Acebrón-García-de-Eulate et al, 2021 ), ML1925—Superoxide dismutase [Cu-Zn], ML1954—Pantothenate kinase( Hasan et al, 2004 ), ML2307—Transcriptional regulator and ML2439—Sensory transduction protein RegX3 ( Duthie et al, 2007 ; Sapkota et al, 2010 ; Tang et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Mycobacterium leprae and host immune transcriptomic signatures for reactional states in leprosy

et al. 2023

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BackgroundMycobacterium leprae transcriptomic and human host immune gene expression signatures that demonstrate a plausible association with type I (T1R) and type II reactions (T2R) aid in early diagnosis, prevention of nerve damage and consequent demyelinating neuropathy in leprosy. The aim of the study is to identify M. leprae and host-associated gene-expression signatures that are associated with reactional states in leprosy.MethodsThe differentially expressed genes from the whole transcriptome of M. leprae were determined using genome-wide hybridization arrays with RNA extracted from skin biopsies of 20 T1R, 20 T2R and 20 non reactional controls (NR). Additionally, human immune gene-expressions were profiled using RT2-PCR profiler arrays and real-time qPCRs.ResultsThe RNA quality was optimal in 16 NR, 18 T1R and 19 T2R samples. Whole transcriptome expression array of these samples revealed significant upregulation of the genes that encode integral and intrinsic membrane proteins, hydrolases and oxidoreductases. In T1R lesional skin biopsy specimens, the top 10 significantly upregulated genes are ML2064, ML1271, ML1960, ML1220, ML2498, ML1996, ML2388, ML0429, ML2030 and ML0224 in comparison to NR. In T2R, genes ML2498, ML1526, ML0394, ML1960, ML2388, ML0429, ML0281, ML1847, ML1618 and ML1271 were significantly upregulated. We noted ML2664 was significantly upregulated in T1R and repressed in T2R. Conversely, we have not noted any genes upregulated in T2R and repressed in T1R. In both T1R and T2R, ML2388 was significantly upregulated. This gene encodes a probable membrane protein and epitope prediction using Bepipred-2.0 revealed a distinct B-cell epitope. Overexpression of ML2388 was noted consistently across the reaction samples. From the host immune gene expression profiles, genes for CXCL9, CXCL10, CXCL2, CD40LG, IL17A and CXCL11 were upregulated in T1R when compared to the NR. In T2R, CXCL10, CXCL11, CXCL9, CXCL2 and CD40LG were upregulated when compared to the NR group.ConclusionA gene set signature involving bacterial genes ML2388, ML2664, and host immune genes CXCL10 and IL-17A can be transcriptomic markers for reactional states in leprosy.

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Section: Discussionmentioning

confidence: 99%

Mycobacterium leprae and host immune transcriptomic signatures for reactional states in leprosy

et al. 2023

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“…From the upregulated genes in T2R, we noted that 10 virulence genes were significantly over expressed. They are ML0243 - Putative acyl-CoA synthetase, ML1014–RNA polymerase sigma factor sigB, ML1076 - RNA polymerase sigma factor SigE, ML1128 - Diaminopimelate decarboxylase, ML1633 - Possible secreted hydrolase, ML1727 - O-phosphoserine phosphohydrolase(32), ML1925 - Superoxide dismutase [Cu-Zn], ML1954-Pantothenate kinase(33), ML2307 - Transcriptional regulator and ML2439 - Sensory transduction protein RegX3(34–36).…”

Section: Discussionmentioning

confidence: 99%

Mycobacterium leprae and host immune transcriptomic signatures for reactional states in leprosy

Das

Diana

Horo

et al. 2022

Preprint

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Mycobacterium leprae transcriptomic and human host immune gene expression signatures that demonstrate a plausible association with type I (T1R) and type II reactions (T2R) aid in early diagnosis, prevention of nerve damage and consequent demyelinating neuropathy in leprosy. The aim of the study is to identify M. leprae and host-associated gene-expression signatures that are associated with reactional states in leprosy. Methods: The differentially expressed genes from the whole transcriptome of M. leprae were determined using genome-wide hybridization arrays with RNA extracted from skin biopsies of 20 T1R, 20 T2R and 20 non reactional controls (NR). Additionally, human immune gene-expressions were profiled using RT2- PCR profiler arrays and real-time qPCRs. Results: The RNA quality was optimal in 16 NR, 18 T1R and 19 T2R samples. Whole transcriptome expression array of these samples revealed significant overexpression of the genes that encode integral and intrinsic membrane proteins, hydrolases and oxidoreductases. In T1R lesional skin biopsy specimens, the top 10 over significantly upregulated genes are ML2064, ML1271, ML1960, ML122, ML2498, ML1996, ML2388, ML0429, ML2030 and ML0224 in comparison to NR. In T2R, genes ML2498, ML1526, ML0394, ML1960, ML2388, ML0429, ML0281, ML1847, ML1618 and ML1271 were significantly upregulated. We noted ML2664 was significantly upregulated in T1R and repressed in T2R. In both T1R and T2R, ML2388 was significantly overexpressed. Overexpression of ML2388 was noted consistently across the reaction samples. Conclusion: A gene set signature involving bacterial genes ML2388, ML2664, and host immune genes CXCL10 and IL-17A can be transcriptomic markers for reactional states in leprosy.

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“…We devised a suitable subtractive proteomics strategy [ 48 ] to pinpoint the highly druggable core proteins of mpox virus. We did so by screening out undesirable proteins from the core proteomic dataset of mpox virus by applying a set of rationally chosen parameters in the order listed below.…”

Section: Methodsmentioning

confidence: 99%

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach

Sahu

Gaur

Mahanandia

et al. 2023

Computers in Biology and Medicine

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Strategies for drug target identification in Mycobacterium leprae

Cited by 12 publications

References 51 publications

Mycobacterium leprae and host immune transcriptomic signatures for reactional states in leprosy

Mycobacterium leprae and host immune transcriptomic signatures for reactional states in leprosy

Mycobacterium leprae and host immune transcriptomic signatures for reactional states in leprosy

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach

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