Sharmila S. Mande

Identification and Functional Characterization of Gene Components of Type VI Secretion System in Bacterial Genomes

A new secretion system, called the Type VI Secretion system (T6SS), was recently reported in Vibrio cholerae, Pseudomonas aeruginosa and Burkholderia mallei. A total of 18 genes have been identified to be belonging to this secretion system in V. cholerae. Here we attempt to identify presence of T6SS in other bacterial genomes. This includes identification of orthologous sequences, conserved motifs, domains, families, 3D folds, genomic islands containing T6SS components, phylogenetic profiles and protein-protein association of these components. Our analysis indicates presence of T6SS in 42 bacteria and its absence in most of their non-pathogenic species, suggesting the role of T6SS in imparting pathogenicity to an organism. Analysis of genomic regions containing T6SS components, phylogenetic profiles and protein-protein association of T6SS components indicate few additional genes which could be involved in this secretion system. Based on our studies, functional annotations were assigned to most of the components. Except one of the genes, we could group all the other genes of T6SS into those belonging to the puncturing device, and those located in the outer membrane, transmembrane and inner membrane. Based on our analysis, we have proposed a model of T6SS and have compared the same with the other bacterial secretion systems.

Classification of metagenomic sequences: methods and challenges

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.

Metagenome of the gut of a malnourished child

BackgroundMalnutrition, a major health problem, affects a significant proportion of preschool children in developing countries. The devastating consequences of malnutrition include diarrhoea, malabsorption, increased intestinal permeability, suboptimal immune response, etc. Nutritional interventions and dietary solutions have not been effective for treatment of malnutrition till date. Metagenomic procedures allow one to access the complex cross-talk between the gut and its microbial flora and understand how a different community composition affects various states of human health. In this study, a metagenomic approach was employed for analysing the differences between gut microbial communities obtained from a malnourished and an apparently healthy child.ResultsOur results indicate that the malnourished child gut has an abundance of enteric pathogens which are known to cause intestinal inflammation resulting in malabsorption of nutrients. We also identified a few functional sub-systems from these pathogens, which probably impact the overall metabolic capabilities of the malnourished child gut.ConclusionThe present study comprehensively characterizes the microbial community resident in the gut of a malnourished child. This study has attempted to extend the understanding of the basis of malnutrition beyond nutrition deprivation.

Identification of compositionally distinct regions in genomes using the centroid method

MOTIVATION It is known that most genomic regions of special interest, e.g. horizontally acquired sequences, genomic islands, etc. have distinct word (m-mer) compositions. Most of the earlier work along this direction, addressed di- and tri-nucleotide compositions. We present an approach that can be applied to analyze compositions of any given word size. The method, called the centroid approach, can reveal compositionally distinct regions in genomic sequences for any given word size. RESULTS We applied our method to 50 bacterial genomes and demonstrated its ability to identify embedded sequences of varying lengths from distantly related organisms. We also investigated the genetic makeup of the regions identified as compositionally distinct by our method, for four organisms from our dataset. Pathogenicity island (PAI) components and genes encoding strain-specific proteins are all frequently seen to be constituents of these regions. AVAILABILITY Program is available on request from the authors. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Gut bacterial diversity of the tribes of India and comparison with the worldwide data

The gut bacteria exert phenotypic traits to the host but the factors which determine the gut bacterial profile (GBP) is poorly understood. This study aimed to understand the effect of ethnicity and geography on GBP of Mongoloid and Proto-Australoid tribes of India. Fecal bacterial diversity was studied in fifteen tribal populations representing four geographic regions (Assam, Telangana, Manipur and Sikkim) by DGGE followed by NGS analysis on Illumina MiSeq platform. Geography and diet had significant effect on GBP of the Indian tribes which was dominated by Prevotella. The effects were more prominent with lower taxonomic levels, indicating probable functional redundancy of the core GBP. A comparison with the worldwide data revealed that GBP of the Indian population was similar to the Mongolian population (Mongolia). The bacterial genera Faecalibacterium, Eubacterium, Clostridium, Blautia, Ruminococcus and Roseburia were found to be core genera in the representative populations of the world.

Computational analysis of the ESX-1 region of Mycobacterium tuberculosis: insights into the mechanism of type VII secretion system.

Type VII secretion system (T7SS) is a recent discovery in bacterial secretion systems. First identified in Mycobacterium tuberculosis, this secretion system has later been reported in organisms belonging to the Actinomycetales order and even to distant phyla like Firmicutes. The genome of M. tuberculosis H37Rv contains five gene clusters that have evolved through gene duplication events and include components of the T7SS secretion machinery. These clusters are called ESAT-6 secretion system (ESX) 1 through 5. Out of these, ESX-1 has been the most widely studied region because of its pathological importance. In spite of this, the overall mechanism of protein translocation through ESX-1 secretion machinery is not clearly understood. Specifically, the structural components contributing to the translocation through the mycomembrane have not been characterized yet. In this study, we have carried out a comprehensive in silico analysis of the genes known to be involved in ESX-1 secretion pathway and identified putative proteins having high probability to be associated with this particular pathway. Our study includes analysis of phylogenetic profiles, identification of domains, transmembrane helices, 3D folds, signal peptides and prediction of protein-protein associations. Based on our analysis, we could assign probable novel functions to a few of the ESX-1 components. Additionally, we have identified a few proteins with probable role in the initial activation and formation of mycomembrane translocon of ESX-1 secretion machinery. We also propose a probable working model of T7SS involving ESX-1 secretion pathway.

In Silico Analysis of Antibiotic Resistance Genes in the Gut Microflora of Individuals from Diverse Geographies and Age-Groups

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. In addition to several geography/country-specific patterns, four distinct clusters of gut microbiomes, referred to as ‘Resistotypes’, exhibiting similarities in their antibiotic resistance profiles, were identified. Groups of antibiotics having similarities in their resistance patterns within each of these clusters were also detected. Apart from this, mobile multi-drug resistance gene operons were detected in certain gut microbiomes. The study highlighted an alarmingly high abundance of antibiotic resistance genes in two infant gut microbiomes. The results obtained in the present study presents a holistic ‘big picture’ on the spectra of antibiotic resistance within our gut microbiota across different geographies. Such insights may help in implementation of new regulations and stringency on the existing ones.

DELIMINATE—a fast and efficient method for loss-less compression of genomic sequences

SUMMARY An unprecedented quantity of genome sequence data is currently being generated using next-generation sequencing platforms. This has necessitated the development of novel bioinformatics approaches and algorithms that not only facilitate a meaningful analysis of these data but also aid in efficient compression, storage, retrieval and transmission of huge volumes of the generated data. We present a novel compression algorithm (DELIMINATE) that can rapidly compress genomic sequence data in a loss-less fashion. Validation results indicate relatively higher compression efficiency of DELIMINATE when compared with popular general purpose compression algorithms, namely, gzip, bzip2 and lzma. AVAILABILITY AND IMPLEMENTATION Linux, Windows and Mac implementations (both 32 and 64-bit) of DELIMINATE are freely available for download at: http://metagenomics.atc.tcs.com/compression/DELIMINATE. CONTACT sharmila@atc.tcs.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

INDeGenIUS, a new method for high-throughput identification of specialized functional islands in completely sequenced organisms

Genomic islands (GIs) are regions in the genome which are believed to have been acquired via horizontal gene transfer events and are thus likely to be compositionally distinct from the rest of the genome. Majority of the genes located in a GI encode a particular function. Depending on the genes they encode, GIs can be classified into various categories, such as ‘metabolic islands’, ‘symbiotic islands’, ‘resistance islands’, ‘pathogenicity islands’, etc. The computational process for GI detection is known and many algorithms for the same are available. We present a new method termed as Improved N-mer based Detection of Genomic Islands Using Sequence-clustering (INDeGenIUS) for the identification of GIs. This method was applied to 400 completely sequenced species belonging to proteobacteria. Based on the genes encoded in the identified GIs, the GIs were grouped into 6 categories: metabolic islands, symbiotic islands, resistance islands, secretion islands, pathogenicity islands and motility islands. Several new islands of interest which had previously been missed out by earlier algorithms were picked up as GIs by INDeGenIUS. The present algorithm has potential application in the identification of functionally relevant GIs in the large number of genomes that are being sequenced. Investigation of the predicted GIs in pathogens may lead to identification of potential drug/vaccine candidates.

Microbial community profiling shows dysbiosis in the lesional skin of Vitiligo subjects

Healthy human skin harbours a diverse array of microbes that comprise the skin microbiome. Commensal bacteria constitute an important component of resident microbiome and are intricately linked to skin health. Recent studies describe an association between altered skin microbial community and epidemiology of diseases, like psoriasis, atopic dermatitis etc. In this study, we compare the differences in bacterial community of lesional and non-lesional skin of vitiligo subjects. Our study reveals dysbiosis in the diversity of microbial community structure in lesional skin of vitiligo subjects. Although individual specific signature is dominant over the vitiligo-specific microbiota, a clear decrease in taxonomic richness and evenness can be noted in lesional patches. Investigation of community specific correlation networks reveals distinctive pattern of interactions between resident bacterial populations of the two sites (lesional and non-lesional). While Actinobacterial species constitute the central regulatory nodes (w.r.t. degree of interaction) in non-lesional skin, species belonging to Firmicutes dominate on lesional sites. We propose that the changes in taxonomic characteristics of vitiligo lesions, as revealed by our study, could play a crucial role in altering the maintenance and severity of disease. Future studies would elucidate mechanistic relevance of these microbial dynamics that can provide new avenues for therapeutic interventions.