Genomic information for outlier strains of Pseudomonas aeruginosa is exiguous when compared with classical strains. We sequenced and constructed the complete genome of an environmental strain CR1 of P. aeruginosa and performed the comparative genomic analysis. It clustered with the outlier group, hence we scaled up the analyses to understand the differences in environmental and clinical outlier strains. We identified eight new regions of genomic plasticity and a plasmid pCR1 with a VirB/D4 complex followed by trimeric auto-transporter that can induce virulence phenotype in the genome of strain CR1. Virulence genotype analysis revealed that strain CR1 lacked hemolytic phospholipase C and D, three genes for LPS biosynthesis and had reduced antibiotic resistance genes when compared with clinical strains. Genes belonging to proteases, bacterial exporters and DNA stabilization were found to be under strong positive selection, thus facilitating pathogenicity and survival of the outliers. The outliers had the complete operon for the production of vibrioferrin, a siderophore present in plant growth promoting bacteria. The competence to acquire multidrug resistance and new virulence factors makes these strains a potential threat. However, we identified major regulatory hubs that can be used as drug targets against both the classical and outlier groups.

As the SARS-CoV-2 virus race around the world across the different population, there needs to be a consolidated effort to understand the divergence of demographically distributed strains. The emerging trends in SARS-CoV-2 genome data show specific mutation and genetic diversity, which could provide the basis to develop a cocktail of vaccine and may also be used to develop the region-specific diagnostic tool, thus decreasing the chances of testing failures in fields. Since the transmission of SARS-CoV-2 is subject to the extent of human interaction, the insights from the correlation of genetic diversity with epidemiological parameter would give paramount information to tackle this transmission. Previously, studies have also correlated the epidemiological data with gut microbiome and its role in immunomodulation for maintaining health status, and such information could be generated from recovered individuals from different demographic regions. It will help in designing a probiotic-based diet for modulation of the gut microbiome, and that could be another plausible prophylactic treatment option. The genomics data suggest that a specific variant of SARS-CoV-2 gets enriched with the specific demographic region. Overall, demographic data suggests that host influences mutation and expression of the virus. Hence, the experiences from the clinical intervention for that region should be considered in control and treatment strategies.

This study highlights the significant role of the genetic repertoire of a microorganism in the similarity between Novosphingobium strains. The results suggest that the phylogenetic relationships were mostly influenced by metabolic trait enrichment, which is possibly governed by the microenvironment of each microbe’s respective niche. Using core genome analysis, the enrichment of a certain set of genes specific to a particular habitat was determined, which provided insights on the influence of habitat on the distribution of metabolic traits for Novosphingobium strains. We also identified habitat-specific protein hubs, which suggested delineation of Novosphingobium strains based on their habitat. Examining the available genomes of ecologically diverse bacterial species and analyzing the habitat-specific genes are useful for understanding the distribution and evolution of functional and phylogenetic diversity in the genus Novosphingobium.

The current prokaryotic taxonomy classifies phenotypically and genotypically diverse microorganisms using a polyphasic approach. With advances in the next-generation sequencing technologies and computational tools for analysis of genomes, the traditional polyphasic method is complemented with genomic data to delineate and classify bacterial genera and species as an alternative to cumbersome and error-prone laboratory tests. This review discusses the applications of sequence-based tools and techniques for bacterial classification and provides a scheme for more robust and reproducible bacterial classification based on genomic data. The present review highlights promising tools and techniques such as ortho-Average Nucleotide Identity, Genome to Genome Distance Calculator and Multi Locus Sequence Analysis, which can be validly employed for characterizing novel microorganisms and assessing phylogenetic relationships. In addition, the review discusses the possibility of employing metagenomic data to assess the phylogenetic associations of uncultured microorganisms. Through this article, we present a review of genomic approaches that can be included in the scheme of taxonomy of bacteria and archaea based on computational and in silico advances to boost the credibility of taxonomic classification in this genomic era.