Mukul Sharma

Bio: Mukul Sharma is an academic researcher from Indian Council of Medical Research. The author has contributed to research in topics: Mycobacterium leprae & Mycobacterium lepromatosis. The author has an hindex of 1, co-authored 4 publications receiving 3 citations.

Use of Artificial Intelligence in Research and Clinical Decision Making for Combating Mycobacterial Diseases

Abstract: Tuberculosis (TB) and leprosy (caused by mycobacterial pathogens) are two age-old infections, which we are facing even today. India is a major contributor to the global burden of leprosy and tuberculosis, which adversely affects the diverse communities as well as having a prevalence in different parts of the country. Timely diagnostics and effective treatment are very challenging, and the emergence of drug resistance has further complicated the management of these mycobacterial diseases. Various lineages of these mycobacterial pathogens show varying phenotypes in terms of clinical presentations and treatment outcomes. Altogether these factors make it further difficult to understand the full genetic diversity and pathogenicity of these pathogens using the conventional genomic and proteomic approaches. However, thanks to the recent technological advances in the genomics and proteomics field, many of these constraints have been suitably addressed. While it is relatively simpler to produce the omics data in a high-throughput manner, the bottleneck now is the pace to assimilate this large data into some useful information to reach a relevant, meaningful conclusion in a timely manner to assist the clinician in making a judgment.

Mycobacterium lepromatosis MLPM_5000 is a potential heme chaperone protein HemW and mis-annotation of its orthologues in mycobacteria.

Abstract: The genome of a newly identified leprosy causing bacillus Mycobacterium lepromatosis was sequenced in 2015 wherein a gene MLPM_5000 was detected whose corresponding sequences are missing in its close relative Mycobacterium leprae, the well-known causal agent of leprosy. Thus MLPM_5000 is considered to be a specific genomic locus for differentiating M. lepromatosis from M. leprae. The locus was annotated as HemN (Coproporphyrinogen III oxidase) based on the available annotations in other mycobacterial species. However, we noticed that the MLPM_5000 and its orthologues in different mycobacterial species show a much higher degree of similarity with Escherichia coli HemW (378 aa) in comparison to the E. coli HemN (457 aa). Additionally, the fourth cysteine of the characteristic CX3CX2CXC motif of the E. coli HemN is replaced by a phenylalanine in the M. lepromatosis MLPM_5000 and its mycobacterial orthologues, which is a hallmark of heme chaperone protein HemW in E. coli and other species. Phylogenetic analysis of MLPM_5000 and its mycobacterial orthologues also showed that these proteins form a divergent phylogenetic clade with the HemW proteins of other species such as Escherichia coli and Lactococcus lactis. Further, Molecular Dynamics simulation studies also predicted that the residues of conserved HNXXYW motif of the MLPM_5000 may have a role in binding to heme part of the host hemoglobin, thereby suggesting it to be a HemW instead of HemN. Altogether, this work shows that MLPM_5000 and its mycobacterial orthologues are highly unlikely to be HemN. Therefore, the current annotations of mycobacterial HemN sequences should be corrected to heme chaperone 'HemW' in various protein databases. The study not only corrects the mis-annotation but also provides a new perspective in the context of evolutionary history of M. leprae and M. lepromatosis such as lack of HemW in M. leprae may explain some of the variations in the virulence between the two pathogens.

Simultaneous detection and differentiation between Mycobacterium leprae and Mycobacterium lepromatosis using novel polymerase chain reaction primers.

Abstract: We have developed a polymerase chain reaction-based method to detect and distinguish Mycobacterium leprae and Mycobacterium lepromatosis using a single set of primers based on a 45-bp difference in the amplicon size of their rpoT gene. This method can also help in detecting the cases of co-infection in a single experiment.

Linguistic Hedges Fuzzy Feature Selection for Differential Diagnosis of Erythemato-Squamous Diseases.

Abstract: The differential diagnosis of erythemato-squamous diseases is a real challenge in dermatology. In diagnosing of these diseases, a biopsy is vital. However, unfortunately these diseases share many histopathological features, as well. Another difficulty for the differential diagnosis is that one disease may show the features of another disease at the beginning stage and may have the characteristic features at the following stages. In this paper, a new Feature Selection based on Linguistic Hedges Neural-Fuzzy classifier is presented for the diagnosis of erythemato-squamous diseases. The performance evaluation of this system is estimated by using four training-test partition models: 50–50%, 60–40%, 70–30% and 80–20%. The highest classification accuracy of 95.7746% was achieved for 80–20% training-test partition using 3 clusters and 18 fuzzy rules, 93.820% for 50–50% training-test partition using 3 clusters and 18 fuzzy rules, 92.5234% for 70–30% training-test partition using 5 clusters and 30 fuzzy rules, and 91.6084% for 60–40% training-test partition using 6 clusters and 36 fuzzy rules. Therefore, 80–20% training-test partition using 3 clusters and 18 fuzzy rules are the best classification accuracy with RMSE of 6.5139e-013. This research demonstrated that the proposed method can be used for reducing the dimension of feature space and can be used to obtain fast automatic diagnostic systems for other diseases.

Machine Learning for Medicine

Abstract: Machine Learning in Medicine In this view of the future of medicine, patient–provider interactions are informed and supported by massive amounts of data from interactions with similar patients. The...

Functional Diversity of HemN-like Proteins

Abstract: HemN is a radical S-adenosylmethionine (SAM) enzyme that catalyzes the anaerobic oxidative decarboxylation of coproporphyrinogen III to produce protoporphyrinogen IX, a key intermediate in heme biosynthesis. Proteins homologous to HemN (HemN-like proteins) are widespread in both prokaryotes and eukaryotes. Although these proteins are in most cases annotated as anaerobic coproporphyrinogen III oxidases (CPOs) in the public database, many of them are actually not CPOs but have diverse functions such as methyltransferases, cyclopropanases, heme chaperones, to name a few. This Perspective discusses the recent advances in the understanding of HemN-like proteins, and particular focus is placed on the diverse chemistries and functions of this growing protein family.

Construction and Analysis of the Complete Genome Sequence of Leprosy Agent Mycobacterium lepromatosis

Abstract: Leprosy is a dreaded infection that still affects millions of people worldwide. Mycobacterium lepromatosis is a recently recognized cause in addition to the well-known Mycobacterium leprae. M. lepromatosis is likely specific for diffuse lepromatous leprosy, a severe form of the infection and endemic in Mexico. This study constructed and annotated the complete genome sequence of M. lepromatosis FJ924 and performed comparative genomic analyses with related mycobacteria. ABSTRACT Leprosy is caused by Mycobacterium leprae and Mycobacterium lepromatosis. We report construction and analyses of the complete genome sequence of M. lepromatosis FJ924. The genome contained 3,271,694 nucleotides to encode 1,789 functional genes and 1,564 pseudogenes. It shared 1,420 genes and 885 pseudogenes (71.4%) with M. leprae but differed in 1,281 genes and pseudogenes (28.6%). In phylogeny, the leprosy bacilli started from a most recent common ancestor (MRCA) that diverged ~30 million years ago (Mya) from environmental organism Mycobacterium haemophilum. The MRCA then underwent reductive evolution with pseudogenization, gene loss, and chromosomal rearrangements. Analysis of the shared pseudogenes estimated the pseudogenization event ~14 Mya, shortly before species bifurcation. Afterwards, genomic changes occurred to lesser extent in each species. Like M. leprae, four major types of highly repetitive sequences were detected in M. lepromatosis, contributing to chromosomal rearrangements within and after MRCA. Variations in genes and copy numbers were noted, such as three copies of the gene encoding bifunctional diguanylate cyclase/phosphodiesterase in M. lepromatosis, but single copy in M. leprae; 6 genes encoding the TetR family transcriptional regulators in M. lepromatosis, but 11 such genes in M. leprae; presence of hemW gene in M. lepromatosis, but absence in M. leprae; and others. These variations likely aid unique pathogenesis, such as diffuse lepromatous leprosy associated with M. lepromatosis, while the shared genomic features should explain the common pathogenesis of dermatitis and neuritis in leprosy. Together, these findings and the genomic data of M. lepromatosis may facilitate future research and care for leprosy. IMPORTANCE Leprosy is a dreaded infection that still affects millions of people worldwide. Mycobacterium lepromatosis is a recently recognized cause in addition to the well-known Mycobacterium leprae. M. lepromatosis is likely specific for diffuse lepromatous leprosy, a severe form of the infection and endemic in Mexico. This study constructed and annotated the complete genome sequence of M. lepromatosis FJ924 and performed comparative genomic analyses with related mycobacteria. The results afford new and refined insights into the genome size, gene repertoire, pseudogenes, phylogenomic relationship, genome organization and plasticity, process and timing of reductive evolution, and genetic and proteomic basis for pathogenesis. The availability of the complete M. lepromatosis genome may prove to be useful for future research and care for the infection.

Discovery and validation of biomarkers for Zhongning goji berries using liquid chromatography mass spectrometry

Abstract: Daodi medicinal material (DMM), which is traditional Chinese herbal medicine that has been used for long periods and have gained credibility in clinical practice, is part of the Chinese culture. However, Zhongning Goji berries (ZNG), a DMM, are illegally adulterated in the market by adding non Zhongning goji berries (NZNG). Consequently, the development of biomarker(s) is necessary for proper identification of ZNG and NZNG. In this study, a nontargeted metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was used to find the differential composition between ZNG and NZNG. Using a combination of single-factor and multivariate statistical analyses, seven compounds with significant differences were discovered and identified, one of which was an unreported compound (a glycoside of pyrrolidine alkaloid). These compounds could be used as single biomarkers for receiver operating characteristic (ROC) analysis. In particular, the binary logistic regression result showed that two sets of combinative biomarkers to distinguish ZNG from NZNG with good sensitivity and specificity. Moreover, there was a significant positive correlation between the two combinative biomarkers and the glycoside of pyrrolidine alkaloid. The results of this study provide new ideas on the developments of ZNG identification, authenticity control and against adulteration in the Chinese circulation market.