Dr. Sharmila Mande received her PhD in Physics from Indian Institute of Science, Bangalore, India, in 1991. She had her post-doctoral training at University of Groningen, The Netherlands and University of Washington, Seattle, USA.
- Genome Informatics
- Next Generation Sequencing
- Algorithms for Biological Data
- Disease Informatics
- Systems Biology
List of Publications (PDF, 302 KB)
In silico analysis of antibiotic resistance genes in the gut microflora of individuals from diverse geographies and age-groups.
PLoS ONE 8(12): e83823 (2013)
Authors: Tarini Shankar Ghosh, Sourav Sen Gupta, G Balkrish Nair and Sharmila S Mande
The spread of antibiotic resistance, originating from the rampant and unrestrictive use of antibiotics in humans and livestock over the past few decades has emerged as a global health problem. This problem has been further compounded by recent reports implicating the gut microbial communities to act as reservoirs of antibiotic resistance. We have profiled the presence of probable antibiotic resistance genes in the gut flora of 275 individuals from eight different nationalities. For this purpose, available metagenomic data sets corresponding to 275 gut microbiomes were analyzed. Sequence similarity searches of the genomic fragments constituting each of these metagenomes were performed against genes conferring resistance to around 240 antibiotics. Potential antibiotic resistance genes conferring resistance against 53 different antibiotics were detected in the human gut microflora analysed in this study.
Understanding the sequential activation of Type III and Type VI Secretion Systems in Salmonella typhimurium using Boolean modeling
Gut Pathogens, 5:28. DOI: 10.1186/1757-4749-5-28 (2013)
Authors:Chandrani Das, Anirban Dutta, Hannah Rajasingh and Sharmila S Mande
Three pathogenicity islands, viz. SPI-1 (Salmonella pathogenicity island 1), SPI-2 (Salmonella pathogenicity island 2) and T6SS (Type VI Secretion System), present in the genome of Salmonella typhimurium have been implicated in the virulence of the pathogen. While the regulation of SPI-1 and SPI-2 (both encoding components of the Type III Secretion System - T3SS) are well understood, T6SS regulation is comparatively less studied. Interestingly, inter-connections among the regulatory elements of these three virulence determinants have also been suggested to be essential for successful infection. However, till date, an integrated view of gene regulation involving the regulators of these three secretion systems and their cross-talk is not available.
A platform for visualizing and comparing microbial community structure across microbiomes
Community-Analyzer: Genomics, Aug 24. pii: S0888-7543(13)00176-6. doi: 10.1016/j.ygeno.2013.08.004 (2013)
Authors: Kuntal Kumar Bhusan, Tarini Shankar Ghosh and Sharmila S Mande
A key goal in comparative metagenomics is to identify microbial group(s) which are responsible for conferring specific characteristics to a given environment. These characteristics are the result of the inter-microbial interactions between the resident microbial groups. We present a new GUI-based comparative metagenomic analysis application called Community-Analyzer which implements a correlation-based graph layout algorithm that not only facilitates a quick visualization of the differences in the analyzed microbial communities (in terms of their taxonomic composition), but also provides insights into the inherent inter-microbial interactions occurring therein. Notably, this layout algorithm also enables grouping of the metagenomes based on the probable inter-microbial interaction patterns rather than simply comparing abundance values of various taxonomic groups. In addition, the tool implements several interactive GUI-based functionalities that enable users to perform standard comparative analyses across microbiomes
I-rDNA and C16S: Identification and Classification of Ribosomal RNA Gene Fragments
Nelson K. (Ed.) Encyclopedia of Metagenomics: 10.1007/SpringerReference_312262 (2013)
Authors:Sharmila S Mande, Tarini Shankar Ghosh, Monzoorul Haque Mohammed
Recent advances in high-throughput sequencing technologies have enabled life-science researchers to rapidly sequence and characterize the entire genomic content of microbial communities residing in diverse ecological niches. A key advantage of characterizing microbial communities in this fashion is that it enables the concomitant characterization of several microbes (constituting the community), most of which cannot be studied using traditional culture-based genomic ...
Classification of Metagenomic Sequences: Methods and Challenges
Briefings in Bioinformatics. September 8, PMID: 22962338 (2012)
Authors:Sharmila S Mande, Monzoorul Haque Mohammed, Tarini Shankar Ghosh
Characterizing the taxonomic diversity of microbial communities is one of the primary objectives of metagenomic studies. Taxonomic analysis of microbial communities, a process referred to as binning, is challenging for the following reasons. Primarily, query sequences originating from the genomes of most microbes in an environmental sample lack taxonomically related sequences in existing reference databases. This absence of a taxonomic context makes binning a very challenging task. Limitations of current sequencing platforms, with respect to short read lengths and sequencing errors/artifacts, are also key factors that determine the overall binning efficiency. Furthermore, the sheer volume of metagenomic datasets also demands highly efficient algorithms that can operate within reasonable requirements of compute power. This review discusses the premise, methodologies, advantages, limitations and challenges of various methods available for binning of metagenomic datasets obtained using the shotgun sequencing approach. Various parameters as well as strategies used for evaluating binning efficiency are then reviewed.