Biology subjects

Navarro-Munoz, J.

Publications and source records attributed to Navarro-Munoz, J..

2 recordsLinked to original sources

bioRxiv2023

Association of secondary metabolite gene clusters with host specialization in the cereal blast fungus Pyricularia oryzae

Fungal plant pathogens constantly evolve and deploy novel peptide and metabolite effectors to break down plant resistance and adapt to new host plants. The blast fungal pathogen Pyricularia oryzae is a single species subdivided into multiple host-specific lineages that have evolved through gain and/or loss of virulence and/or effector related genes through chromosomal rearrangement. Here, we mined 68 genomes of P. oryzae, belonging to six host-specific lineages, to identify secondary metabolite (SM) biosynthetic gene clusters (BGCs) likely associated with potential metabolite effectors involved in host specialization. A similarity network analysis grouped a total of 4501 BGCs into 283 gene cluster families (GCFs), based on the content and architecture of the BGCs. While most of the GCFs were present in all the P. oryzae lineages, two (BGC-O1 and BGC-O2) were found specifically in the Oryza lineage and one (BGC-TLE) was found in the lineage specific to Triticum, Lolium and Eleusine hosts. Further analysis of the phylogenetic relationships between core biosynthetic genes confirmed that BGC-O1, which comprises a reducing polyketide synthase gene (MGG_08236) and four putative tailoring genes, was present only in the Oryza lineage. Importantly, most genes, including MGG_08236, from the BGC-O1 were expressed specifically during pathogenesis. We propose that the Oryza lineage-specific BGC-O1 produces a metabolite effector likely involved in specialization of P. oryzae to the rice host. In addition, we identified five SM genes under positive or balancing selection only in the Oryza lineage, suggesting a role in the interaction with rice specifically. Our findings highlight the importance of further mining novel metabolite effectors in specialization and virulence of the blast fungus to different cereal hosts.

genomics↗

bioRxiv2018

A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data

Genome mining has become a key technology to explore and exploit natural product diversity through the identification and analysis of biosynthetic gene clusters (BGCs). Initially, this was performed on a single-genome basis; currently, the process is being scaled up to large-scale mining of pan-genomes of entire genera, complete strain collections and metagenomic datasets from which thousands of bacterial genomes can be extracted at once. However, no bioinformatic framework is currently available for the effective analysis of datasets of this size and complexity. Here, we provide a streamlined computational workflow, tightly integrated with antiSMASH and MIBiG, that consists of two new software tools, BiG-SCAPE and CORASON. BiG-SCAPE facilitates rapid calculation and interactive visual exploration of BGC sequence similarity networks, grouping gene clusters at multiple hierarchical levels, and includes a glocal alignment mode that accurately groups both complete and fragmented BGCs. CORASON employs a phylogenomic approach to elucidate the detailed evolutionary relationships between gene clusters by computing high-resolution multi-locus phylogenies of all BGCs within and across gene cluster families (GCFs), and allows researchers to comprehensively identify all genomic contexts in which particular biosynthetic gene cassettes are found. We validate BiG-SCAPE by correlating its GCF output to metabolomic data across 403 actinobacterial strains. Furthermore, we demonstrate the discovery potential of the platform by using CORASON to comprehensively map the phylogenetic diversity of the large detoxin/rimosamide gene cluster clan, prioritizing three new detoxin families for subsequent characterization of six new analogs using isotopic labeling and analysis of tandem mass spectrometric data.

bioinformatics↗