A cross-sectional study on the nasopharyngeal microbiota of individuals with SARS-CoV-2 infection across three COVID-19 waves in India.

Background: Multiple variants of the SARS-CoV-2 virus have plagued the world through successive waves of infection over the past three years. Independent research groups across geographies have shown that the microbiome composition in COVID-19 positive patients (CP) differs from that of COVID-19 negative individuals (CN). However, these observations were based on limited-sized sample-sets collected primarily from the early days of the pandemic.

Exploring the human microbiome - A step forward for precision medicine in breast cancer.

Background: The second most frequent cancer in the world and the most common malignancy in women is breast cancer. Breast cancer is a significant health concern in India with a high mortality-to-incidence ratio and presentation at a younger age.

Recent Findings: Recent studies have identified gut microbiota as a significant factor that can have an influence on the development, treatment, and prognosis of breast cancer.

Structural aspects of lesional and non-lesional skin microbiota reveal key community changes in leprosy patients from India.

Although skin is the primary affected organ in Leprosy, the role of the skin microbiome in its pathogenesis is not well understood. Recent reports have shown that skin of leprosy patients (LP) harbours perturbed microbiota which grants inflammation and disease progression. Herein, we present the results of nested Polymerase Chain Reaction-Denaturing Gradient Gel Electrophoresis (PCR-DGGE) which was initially performed for investigating the diversity of bacterial communities from lesional skin (LS) and non-lesional skin (NLS) sites of LP (n = 11).

Crosstalk Between Female Gonadal Hormones and Vaginal Microbiota Across Various Phases of Women's Gynecological Lifecycle.

Functional equilibrium between vaginal microbiota and the host is important for maintaining gynecological and reproductive health. Apart from host genetics, infections, changes in diet, life-style and hygiene status are known to affect this delicate state of equilibrium. More importantly, the gonadal hormones strongly influence the overall structure and function of vaginal microbiota.

Lifestyle-Induced Microbial Gradients: An Indian Perspective.

Urbanization is a globally pervasive trend. Although urban settings provide better access to infrastructure and opportunities, urban lifestyles have certain negative consequences on human health. A number of recent studies have found interesting associations between the structure of human gut microbiota and the prevalence of metabolic conditions characterizing urban populations.

Decoding the microbiome for the development of translational applications: Overview, challenges and pitfalls.

Recent studies have highlighted the potential of 'translational' microbiome research in addressing real-world challenges pertaining to human health, nutrition and disease. Additionally, outcomes of microbiome research have also positively impacted various aspects pertaining to agricultural productivity, fuel or energy requirements, and stability/preservation of various ecological habitats. Microbiome data is multi-dimensional with various types of data comprising nucleic and protein sequences, metabolites as well as various metadata related to host and or environment.

16S rDNA based skin microbiome data of healthy individuals and leprosy patients from India.

Leprosy is an infectious disease that has predilection in skin and peripheral nerves. Skin has its own microbiome, however it is not extensively studied in Indian leprosy patients. Here, by using next-generation 16S rDNA sequencing, we have attempted to assess the skin associated microbial diversity pertaining to affected and unaffected skin of Indian leprosy patients.

Can Targeting Non-Contiguous V-Regions With Paired-End Sequencing Improve 16S rRNA-Based Taxonomic Resolution of Microbiomes?: An Evaluation.

Next-generation sequencing (NGS) technologies have enabled probing of microbial diversity in different environmental niches with unprecedented sequencing depth. However, due to read-length limitations of popular NGS technologies, 16S amplicon sequencing-based microbiome studies rely on targeting short stretches of the 16S rRNA gene encompassing a selection of variable (V) regions. In most cases, such a short stretch constitutes a single V-region or a couple of V-regions placed adjacent to each other on the 16S rRNA gene.

A prospective randomized, double-blind, placebo-controlled, dose-response relationship study to investigate efficacy of fructo-oligosaccharides (FOS) on human gut microflora.

Fructo-oligosaccharides (FOS), a prebiotic supplement, is known for its Bifidogenic capabilities. However, aspects such as effect of variable quantities of FOS intake on gut microbiota, and temporal dynamics of gut microbiota (transitioning through basal, dosage, and follow-up phases) has not been studied in detail. This study investigated these aspects through a randomized, double-blind, placebo-controlled, dose-response relationship study.

iVikodak-A Platform and Standard Workflow for Inferring, Analyzing, Comparing, and Visualizing the Functional Potential of Microbial Communities.

The objectives of any metagenomic study typically include identification of resident microbes and their relative proportions (taxonomic analysis), profiling functional diversity (functional analysis), and comparing the identified microbes and functions with available metadata (comparative metagenomics). Given the advantage of cost-effectiveness and convenient data-size, amplicon-based sequencing has remained the technology of choice for exploring phylogenetic diversity of an environment. A recent school of thought, employing the existing genome annotation information for inferring functional capacity of an identified microbiome community, has given a promising alternative to Whole Genome Shotgun sequencing for functional analysis.

A snapshot of gut microbiota of an adult urban population from Western region of India.

The human gut microbiome contributes to a broad range of biochemical and metabolic functions that directly or indirectly affect human physiology. Several recent studies have indicated that factors like age, geographical location, genetic makeup, and individual health status significantly influence the diversity, stability, and resilience of the gut microbiome. Of the mentioned factors, geographical location (and related dietary/socio-economic context) appears to explain a significant portion of microbiome variation observed in various previously conducted base-line studies on human gut microbiome.

First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk.

Preterm birth is a leading cause of global neonate mortality. Hospitalization costs associated with preterm deliveries present a huge economic burden. Existing physical/biochemical markers for predicting preterm birth risk are mostly suited for application at mid/late pregnancy stages, thereby leaving very short time (between diagnosis and delivery) for adopting appropriate intervention strategies.

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g.

Vikodak--A Modular Framework for Inferring Functional Potential of Microbial Communities from 16S Metagenomic Datasets.

Background: The overall metabolic/functional potential of any given environmental niche is a function of the sum total of genes/proteins/enzymes that are encoded and expressed by various interacting microbes residing in that niche. Consequently, prior (collated) information pertaining to genes, enzymes encoded by the resident microbes can aid in indirectly (re)constructing/ inferring the metabolic/ functional potential of a given microbial community (given its taxonomic abundance profile). In this study, we present Vikodak--a multi-modular package that is based on the above assumption and automates inferring and/ or comparing the functional characteristics of an environment using taxonomic abundance generated from one or more environmental sample datasets.

COGNIZER: A Framework for Functional Annotation of Metagenomic Datasets.

Background: Recent advances in sequencing technologies have resulted in an unprecedented increase in the number of metagenomes that are being sequenced world-wide. Given their volume, functional annotation of metagenomic sequence datasets requires specialized computational tools/techniques. In spite of having high accuracy, existing stand-alone functional annotation tools necessitate end-users to perform compute-intensive homology searches of metagenomic datasets against "multiple" databases prior to functional analysis.

CS-SCORE: Rapid identification and removal of human genome contaminants from metagenomic datasets.

Unlabelled: Metagenomic sequencing data, obtained from host-associated microbial communities, are usually contaminated with host genome sequence fragments. Prior to performing any downstream analyses, it is necessary to identify and remove such contaminating sequence fragments. The time and memory requirements of available host-contamination detection techniques are enormous.

FQC: A novel approach for efficient compression, archival, and dissemination of fastq datasets.

Sequence data repositories archive and disseminate fastq data in compressed format. In spite of having relatively lower compression efficiency, data repositories continue to prefer GZIP over available specialized fastq compression algorithms. Ease of deployment, high processing speed and portability are the reasons for this preference.

MetaCAA: A clustering-aided methodology for efficient assembly of metagenomic datasets.

A key challenge in analyzing metagenomics data pertains to assembly of sequenced DNA fragments (i.e. reads) originating from various microbes in a given environmental sample.

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.

BIND - an algorithm for loss-less compression of nucleotide sequence data.

Recent advances in DNA sequencing technologies have enabled the current generation of life science researchers to probe deeper into the genomic blueprint. The amount of data generated by these technologies has been increasing exponentially since the last decade. Storage, archival and dissemination of such huge data sets require efficient solutions, both from the hardware as well as software perspective.

DELIMINATE--a fast and efficient method for loss-less compression of genomic sequences: sequence analysis.

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.

TWARIT: an extremely rapid and efficient approach for phylogenetic classification of metagenomic sequences.

Phylogenetic assignment of individual sequence reads to their respective taxa, referred to as 'taxonomic binning', constitutes a key step of metagenomic analysis. Existing binning methods have limitations either with respect to time or accuracy/specificity of binning. Given these limitations, development of a method that can bin vast amounts of metagenomic sequence data in a rapid, efficient and computationally inexpensive manner can profoundly influence metagenomic analysis in computational resource poor settings.

HabiSign: a novel approach for comparison of metagenomes and rapid identification of habitat-specific sequences.

Background: One of the primary goals of comparative metagenomic projects is to study the differences in the microbial communities residing in diverse environments. Besides providing valuable insights into the inherent structure of the microbial populations, these studies have potential applications in several important areas of medical research like disease diagnostics, detection of pathogenic contamination and identification of hitherto unknown pathogens. Here we present a novel and rapid, alignment-free method called HabiSign, which utilizes patterns of tetra-nucleotide usage in microbial genomes to bring out the differences in the composition of both diverse and related microbial communities.

i-rDNA: alignment-free algorithm for rapid in silico detection of ribosomal gene fragments from metagenomic sequence data sets.

Background: Obtaining accurate estimates of microbial diversity using rDNA profiling is the first step in most metagenomics projects. Consequently, most metagenomic projects spend considerable amounts of time, money and manpower for experimentally cloning, amplifying and sequencing the rDNA content in a metagenomic sample. In the second step, the entire genomic content of the metagenome is extracted, sequenced and analyzed.

INDUS - a composition-based approach for rapid and accurate taxonomic classification of metagenomic sequences.

Background: Taxonomic classification of metagenomic sequences is the first step in metagenomic analysis. Existing taxonomic classification approaches are of two types, similarity-based and composition-based. Similarity-based approaches, though accurate and specific, are extremely slow.