Biology subjects

Mohite, O. S.

Publications and source records attributed to Mohite, O. S..

6 recordsLinked to original sources

bioRxiv2024

Understanding flux switching in metabolic networks through an analysis of synthetic lethals

Biological systems are extremely robust and exhibit high levels of redundancy for multiple cellular functions. Some of this redundancy manifests as alternative pathways in metabolism. Synthetic double lethals in metabolic networks comprise pairs of reactions, which, when deleted simultaneously, abrogate cell growth. However, when one reaction from such pairs is removed, the cell reroutes its metabolites through alternative pathways. Very little is known about the set of reactions through which fluxes are rerouted. Analysing this redistribution would help us to uncover the linkage between the reactions in a synthetic double lethal and also understand the complexity underlying the reroutings. Studying synthetic lethality in the context of pathogenic bacteria can offer valuable insights into therapeutic interventions. In this work, we propose a constraint-based approach to unravel these alternate pathways and complex interdependencies within and across metabolic modules. The approach involves a generic optimisation that minimises the extent of rerouting between two reaction deletions, corresponding to synthetic lethal pairs. We also include a systematic analysis of synthetic lethals by identifying the reaction classes that make up these synthetic lethals. We applied our computational workflow to several existing high-quality genome-scale models to show that these rerouted reactions span across metabolic modules, thereby illustrating the complexity and uniqueness of metabolism. Our results provide interesting insights into the organisation of metabolic networks and their redundancy. The algorithm is available at https://github.com/RamanLab/minRerouting. Contact: kraman@iitm.ac.in

systems biology↗

bioRxiv2023

Genomic insights into Lactobacillaceae: Analyzing the Alleleome of core pangenomes for enhanced understanding of strain diversity and revealing Phylogroup-specific unique variants

The Lactobacillaceae familys significance in food and health, combined with available strain-specific genomes, enables genome assessment through pangenome analysis. The Alleleome of the core pangenomes of the Lactobacillaceae family, which identifies natural sequence variations, was reconstructed from the amino acid and nucleotide sequences of the core genes across 2,447 strains of 26 species. It comprised 3.71 million amino acid variants in 29,448 core genes across the family. The alleleome analysis of the Lactobacillaceae family revealed key findings: 1) In the core pangenome, amino acid substitutions prevailed over rare insertions and deletions, 2) Purifying negative selection primarily influenced core gene variations in the family, with diversifying selection noted in L. helveticus. L. plantarums core alleleome was investigated due to its industrial importance. In L. plantarum, the defining characteristics of its core alleleome included: 1) It is highly conserved; 2) Among 235 isolation sources, the primary categories displaying variant prevalence were fermented food, feces, and unidentified sources; 3) It is predominantly characterized by conservative and moderately conservative mutations; and 4) Phylogroup-specific core variant gene analysis identified unique variants (DltX, FabZ1, Pts23B, CspP) in phylogroups I and B which could be used as identifier or validation markers of strain or phylogroup.

genomics↗

bioRxiv2023

BGCFlow: Systematic pangenome workflow for the analysis of biosynthetic gene clusters across large genomic datasets

Genome mining is revolutionizing natural products discovery efforts. The rapid increase in available genomes demands comprehensive computational platforms to effectively extract biosynthetic knowledge encoded across bacterial pangenomes. Here, we present BGCFlow, a novel systematic workflow integrating analytics for large-scale genome mining of bacterial pangenomes. BGCFlow incorporates several genome analytics and mining tools grouped into five common stages of analysis such as; i) data selection, ii) functional annotation, iii) phylogenetic analysis, iv) genome mining, and v) comparative analysis. Furthermore, BGCFlow provides easy configuration of different projects, parallel distribution, scheduled job monitoring, an interactive database to visualize tables, exploratory Jupyter notebooks, and customized reports. Here, we demonstrate the application of BGCFlow by investigating the phylogenetic distribution of various biosynthetic gene clusters detected across 42 genomes of the Saccharopolyspora genus, known to produce industrially important secondary/specialized metabolites. The BGCFlow-guided analysis predicted more accurate dereplication of BGCs and guided the targeted comparative analysis of selected RiPPs. The scalable, interoperable, adaptable, re-entrant, and reproducible nature of the BGCFlow will provide an effective novel way to extract the biosynthetic knowledge in the ever-growing genomic datasets of biotechnologically relevant bacterial species. BGCFlow is available for downloading at https://github.com/NBChub/bgcflow.

bioinformatics↗

bioRxiv2023

Pangenome analysis reveals the genetic basis for taxonomic classification of the Lactobacillaceae family

Lactobacillaceae represent a large family of important microbes that are foundational to the food industry. Many genome sequences of Lactobacillaceae strains are now available, enabling us to conduct a comprehensive pangenome analysis of this family. We collected 3,591 high-quality genomes from public sources and found that: 1) they contained enough genomes for 26 species to perform a pangenomic analysis, 2) the normalized Heaps coefficient {lambda} (a measure of pangenome openness) was found to have an average value of 0.27 (ranging from 0.07-0.37), 3) the pangenome openness was correlated with the abundance and genomic location of transposons and mobilomes, 4) the pangenome for each species was divided into core, accessory, and rare genomes, that highlight the species-specific properties (such as motility and restriction-modification systems), 5) the pangenome of Lactiplantibacillus plantarum (which contained the highest number of genomes found amongst the 26 species studied) contained nine distinct phylogroups, and 6) genome mining revealed a richness of detected biosynthetic gene clusters, with functions ranging from antimicrobial and probiotic to food preservation, but [~]93% were of unknown function. This study provides the first in-depth comparative pangenomics analysis of the Lactobacillaceae family.

systems biology↗

bioRxiv2020

Characterization and Engineering of Streptomyces griseofuscus DSM 40191 as a Potential Host for Heterologous Expression of Biosynthetic Gene Clusters

Streptomyces griseofuscus DSM 40191 is a fast growing Streptomyces strain that remains largely underexplored as a heterologous host. Here, we report the genome mining of S. griseofuscus, followed by the detailed exploration of its phenotype, including production of native secondary metabolites and ability to utilise carbon, nitrogen, sulphur and phosphorus sources. Furthermore, several routes for genetic engineering of S. griseofuscus were explored, including use of GusA-based vectors, CRISPR-Cas9 and CRISPR-cBEST-mediated knockouts. Using CRISPR-BEST technology, core genes of 4 biosynthetic gene clusters (BGCs) that are situated on the chromosome arms were inactivated and the outcomes of the inactivations were tested. Two out of the three native plasmids were cured using CRISPR-Cas9 technology, leading to the generation of strain S. griseofuscus DEL1. DEL1 was further modified by full deletion of a pentamycin BGC and an unknown NRPS BGC, leading to the generation of strain DEL2, lacking approx. 500 kbp of the genome, which corresponds to a 5,19% genome reduction. Sequencing confirmed that DEL2 does not bear any crucial off-target effects or rearrangements in its genome. It can be characterized by faster growth and inability to produce three main native metabolites of S. griseofuscus: lankacidin, lankamycin, pentamycin and their derivatives. To test the ability of DEL2 to heterologously produce secondary metabolites, the actinorhodin BGC was used. We were able to confirm the production of actinorhodin by both S. griseofuscus wild type and DEL2. We believe that this strain will serve as a good chassis for heterologous expression of BGCs. ImportanceThe rise of antibacterial resistance calls on the development of the next generation of antibiotics, majority of which are derived from natural compounds, produced by actinomycetes. The manipulation, refactoring and expression of BGCs coding for such natural products is a promising approach in secondary metabolite discovery. Thus, the development of a versatile panel of heterologous hosts for the expression of BGCs is essential. We believe that first-to-date systematic, detailed characterisation of S. griseofuscus, a highly promising chassis strain, will not only facilitate the further development of this particular strain, but also will set a blueprint for characterisation of other potential hosts.

microbiology↗

bioRxiv2019

Pangenome Analysis of Enterobacteria Reveals Richness of Secondary Metabolite Gene Clusters and their Associated Gene Sets

The growing number of sequenced genomes enables the study of secondary metabolite biosynthetic gene clusters (BGC) in phyla beyond well-studied soil bacteria. We mined 2627 enterobacterial genomes to detect 8604 BGCs, including nonribosomal peptide synthetases, siderophores, polyketide-nonribosomal peptide hybrids, and 60 other BGC types, with an average of around 3.3 BGCs per genome. These BGCs represented 212 distinct BGC families, of which only 20 have associated products in the MIBiG standard database with functions such as siderophores, antibiotics, and genotoxins. Pangenome analysis identified genes associated with a specific BGC encoding for colon cancer-related colibactin. In one example, we associated genes involved in the type VI secretion system with the presence of a colibactin BGC in Escherichia. This richness of BGCs in enterobacteria opens up the possibility to discover novel secondary metabolites, their physiological roles and provides a guide to identify and understand PKS associated gene sets.

systems biology↗