Biology subjects

Lahiri, R.

Publications and source records attributed to Lahiri, R..

4 recordsLinked to original sources

bioRxiv2019

GSMN-ML- a genome scale metabolic network reconstruction of the obligate human pathogen Mycobacterium leprae

Leprosy, caused by Mycobacterium leprae, has plagued humanity for thousands of years and continues to cause morbidity, disability and stigmatization in two to three million people today. Although effective treatment is available, the disease incidence has remained approximately constant for decades so new approaches, such as vaccine or new drugs, are urgently needed for control. Research is however hampered by the pathogens obligate intracellular lifestyle and the fact that it has never been grown in vitro. Consequently, despite the availability of its complete genome sequence, fundamental questions regarding the biology of the pathogen, such as its metabolism, remain largely unexplored. In order to explore the metabolism of the leprosy bacillus with a long-term aim of developing a medium to grow the pathogen in vitro, we reconstructed an in silico genome scale metabolic model of the bacillus, GSMN-ML. The model was used to explore the growth and biomass production capabilities of the pathogen with a range of nutrient sources, such as amino acids, glucose, glycerol and metabolic intermediates. We also used the model to analyze RNA-seq data from M. leprae grown in mouse foot pads, and performed Differential Producibility Analysis (DPA) to identify metabolic pathways that appear to be active during intracellular growth of the pathogen, which included pathways for central carbon metabolism, co-factor, lipids, amino acids, nucleotides and cell wall synthesis. The GSMN-ML model is thereby a useful in silico tool that can be used to explore the metabolism of the leprosy bacillus, analyze functional genomic experimental data, generate predictions of nutrients required for growth of the bacillus in vitro and identify novel drug targets.\n\nAuthor SummaryMycobacterium leprae, the obligate human pathogen is uncultivable in axenic growth medium, and this hinders research on this pathogen, and the pathogenesis of leprosy. The development of novel therapeutics relies on the understanding of growth, survival and metabolism of this bacterium in the host, the knowledge of which is currently very limited. Here we reconstructed a metabolic network of M. leprae-GSMN-ML, a powerful in silico tool to study growth and metabolism of the leprosy bacillus. We demonstrate the application of GSMN-ML to identify the metabolic pathways, and metabolite classes that M. leprae utilizes during intracellular growth.

microbiology↗

bioRxiv2019

Fragment-based discovery of a new class of inhibitors targeting mycobacterial tRNA modification

Translational frameshift errors are often deleterious to the synthesis of functional proteins as they lead to the production of truncated or inactive proteins. TrmD (tRNA-(N(1)G37) methyltransferase) is an essential tRNA modification enzyme in bacteria that prevents +1 errors in the reading frame during protein translation and has been identified as a therapeutic target for several bacterial infections. Here we validate TrmD as a target in Mycobacterium abscessus and describe the application of a structure-guided fragment-based drug discovery approach for the design of a new class of inhibitors against this enzyme. A fragment library screening followed by structure-guided chemical elaboration of hits led to the development of compounds with potent in vitro TrmD inhibitory activity. Several of these compounds exhibit activity against planktonic M. abscessus and Mycobacterium tuberculosis. The compounds were further active in macrophage infection models against Mycobacterium leprae and M. abscessus suggesting the potential for novel broad-spectrum mycobacterial drugs.

biochemistry↗

bioRxiv2019

Pleiotropic effects for Parkin and LRRK2 in leprosy type-1 reactions and Parkinson’s disease

Type-1 reactions (T1Rs) are pathological inflammatory episodes and main contributors to nerve damage in leprosy. Here, we evaluate the gene-wise enrichment of rare protein altering variants in seven genes where common variants were previously associated with T1R. We selected 474 Vietnamese leprosy-patients of which 237 were T1R-affected and 237 were T1R-free matched controls. Gene-wise enrichment of nonsynonymous variants was tested with both kernel based (SKAT) and burden methods. Of the seven genes tested two showed statistical evidence of association with T1R. For the LRRK2 gene an enrichment of nonsynonymous variants was observed in T1R-free controls (p O_SCPCAPSKAT-OC_SCPCAP= 1.6x10-4). This gene-wise association was driven almost entirely by the gain of function variant R1628P (p = 0.004; OR = 0.29). The second gene-wise association was found for the Parkin coding gene PRKN (formerly PARK2) where seven rare variants were enriched in T1R-affected cases (p O_SCPCAPSKAT-OC_SCPCAP = 7.4x10-5). Mutations in both PRKN and LRRK2 are known causes of Parkinsons Disease (PD). Hence, we evaluated to what extent such rare amino acid changes observed in T1R are shared with PD. We observed that nonsynonymous T1R-risk mutations in Parkin were enriched for amino acid mutations implicated in PD (p = 1.5x10-4). Hence, neuro-inflammation in PD and peripheral nerve damage due to inflammation in T1R share overlapping mechanisms of pathogenicity.

genetics↗

bioRxiv2018

Dual RNAseq of human leprosy lesions identifies bacterial determinants linked to host immune response

To understand how the interaction between an intracellular bacterium and the host immune system contributes to outcome at the site of infection, we studied leprosy, a disease that forms a clinical spectrum, in which progressive infection by the intracellular bacterium Mycobacterium leprae is characterized by the production of type | IFNs and antibody production. We performed dual RNAseq on patient lesions, identifying a continuum of distinct bacterial states that are linked to the host immune response. The bacterial burden, represented by the fraction of bacterial transcripts, correlates with a host type | IFN gene signature, known to inhibit antimicrobial responses. Second, the bacterial transcriptional activity, defined by the bacterial mRNA/rRNA ratio, links bacterial heat shock proteins with the BAFF-BCMA host antibody response pathway. Our findings provide a platform for interrogation of host and pathogen transcriptomes at the site of infection, allowing insight into mechanisms of inflammation in human disease.

microbiology↗