Biology subjects

Nuhamunada, M.

Publications and source records attributed to Nuhamunada, M..

4 recordsLinked to original sources

bioRxiv2025

Unlocking the biosynthetic potential of Paenibacilli through a genus-wide exploration of gene clusters for secondary metabolite production

The genus Paenibacillus is a prolific producer of secondary metabolites with diverse ecological and industrial applications. However, a comprehensive overview of the biosynthetic gene cluster (BGC) diversity and distribution throughout the genus has been limited. Here, we performed large-scale genome mining on 284 high-quality genomes and generated a non-redundant dataset of 126 representative genomes to explore the biosynthetic potential of this genus. A total of 3,273 BGCs were identified from the 284 genomes that clustered into 1,013 gene cluster families (GCFs), with 98.7% classified as unknown, indicating vast potential for novel secondary metabolite discovery in the Paenibacillus genus. Comparative analysis revealed significant phylogenetic and clade-specific distribution patterns of GCFs, with certain clades enriched in unique biosynthetic pathways while others exhibited low similarity to known BGCs, suggesting evolutionary adaptation to diverse ecological niches. This study uncovers the rich and largely untapped biosynthetic potential of the genus Paenibacillus, providing a foundation for future exploration of its natural products and their applications in biotechnology and medicine. IMPORTANCEBacterial secondary metabolites have been instrumental in the development of antibiotics, antifungals, and other bioactive compounds. The genus Paenibacillus is an underexplored source of such metabolites, with significant potential for novel discoveries. By integrating genome mining and phylogenetic analysis, this study systematically characterizes the diversity, distribution, and novelty of biosynthetic gene cluster across the genus. The identification of clade-specific biosynthetic patterns and numerous unknown gene cluster families highlights Paenibacillus as a promising target for uncovering novel compounds with ecological and therapeutic relevance. These findings not only expand our understanding of bacterial secondary metabolite biosynthesis but also offer new opportunities for the development of sustainable biotechnological applications.

microbiology↗

bioRxiv2024

BGC Atlas: A Web Resource for Exploring the Global Chemical Diversity Encoded in Bacterial Genomes

Secondary metabolites are compounds not essential for an organisms development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology, and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35,000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptides (RiPPs) are the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites, and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.

bioinformatics↗

bioRxiv2024

Expanding the genome information on Bacillales for biosynthetic gene cluster discovery

This study showcases 121 new genomes of spore-forming Bacillales from strains collected globally from a variety of habitats, assembled using Oxford Nanopore long-read and MGI short-read sequences. Bacilli are renowned for their capacity to produce diverse secondary metabolites with use in agriculture, biotechnology, and medicine. These secondary metabolites are encoded within biosynthetic gene clusters (smBGCs). smBGCs have significant research interest due to their potential for the discovery of new bioactivate compounds. Our dataset includes 62 complete genomes, 2 at chromosome level, and 57 at contig level, covering a genomic size range from 3.50 Mb to 7.15 Mb. Phylotaxonomic analysis revealed that these genomes span 16 genera, with 69 of them belonging to Bacillus. A total of 1,176 predicted BGCs were identified by in silico genome mining. We anticipate that the open-access data presented here will expand the reported genomic information of spore-forming Bacillales and facilitate a deeper understanding of the genetic basis of Bacillales potential for secondary metabolite production.

microbiology↗

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↗