Genome Mining Tools for Secondary Metabolites in Bacteria

As products of billions of years of evolution, secondary metabolites perform a wide range of activities ensuring the survival of organisms in competitive envi- ronments. These natural products synthesized by diverse living beings through- out the tree of life have been a valuable resource for many industrial applica- tions. Specifically, in pharmaceutical ventures, natural products are used pro- foundly against cancer, pests and microorganisms. Peaked in the golden era of antibiotics, drug discovery against infectious diseases was mainly centered around natural products from fungi and bacteria. Consequently however, mi- crobes have made impressive and frightening progress in gaining resistance against antimicrobials fueled by their improper usage. Coupled with the stag- nation in discovery rates of novel natural products, antimicrobial resistance has become a destructive phenomenon damaging humanity financially and health- wise. To fight off such resistant microbes, it is of paramount importance that we find and produce novel secondary metabolites with antimicrobial features. With the vast improvements in sequencing technologies and analysis algorithms, we possess repositories swarming with “multiomics”-based data, ready to be mined. Now, a crucial thing to do is to enable the prioritization of such data for the sub- sequent processes in wet-lab applications. In this thesis, I have built command line tools as well as web-based databases and pipelines to I) detect genes conferring antibiotic resistance in order to find promising biosynthetic gene clusters that might encode for novel antibiotics and II) prioritize target genes for genetic manipulation that could be used to increase the production of secondary metabolites

Developing genome mining tools for the discovery of bioactive secondary metabolites

With the rise of Multi-resistant strains of previously treatable pathogenic microorganisms, some of which immune to all known antibiotics, we face a public health crisis that threatens the lives of anyone prone to infection. This challenge needs to be faced on many fronts and an important step to finding a solution is to replenish our antibiotic arsenals with new drugs that evade current antibiotic resistance strategies. The majority of these compounds have traditionally been sourced from, or inspired by, natural products – compounds produced by living things. This continues to be a valuable resource as the millennia of development through natural selection has made for precisely adapted molecules with desired antibiotic properties. Unfortunately natural products research has experienced stagnation due to high rates of rediscovery and low returns on research investment. Fortunately the widespread use of cheap sequencing technologies, influx of complete whole genomes, and tools used to process them have simultaneously been on the rise. These “genome mining” tools have only begun to highlight chemical potential that has been hidden from traditional approaches from a diverse set of genera. As the detection of various classes of Biosynthetic Gene Clusters (BGCs), areas of the genome responsible for production of these compounds, has matured there are now more leads generated than can be experimentally verified. The problem now is to prioritize these leads for those that have the highest potential for downstream experiments. Common prioritization schemes include: using comparative genomics to highlight unique or shared BGCs, focusing on novel genera besides the traditional prolific producing organisms, and highlighting BGCs that imply antibiotic activity via antibiotic resistance determinates. This research is focused on providing automated and accessible tools to preform these analyses in high-throughput. In addition to the prioritization and de-replication of potential BGCs, applications to enrich for novel leads via resistance determinant and target screening are also presented. As the number of genomes from different taxa begins to rise, shifting from a single genome analysis to a comparative pan-genome approach also shows promise to reinvigorate natural products research. The tools in this research that leverage these approaches will be continually maintained on free public servers for the furthered research and discovery of new antibiotic and anti-infective compounds to ensure the threat of antibiotic resistance is controlled

Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters

Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies

<em>Rhodococcus indonesiensis</em> sp. nov. a new member of the <em>Rhodococcus ruber</em> lineage isolated from sediment of a neutral hot spring and reclassification of <em>Rhodococcus electrodiphilus</em> (Ramaprasad et al. 2018) as a later heterotypic synonym of <em>Rhodococcus ruber </em>(Kruse 1896) Goodfellow and Alderson 1977 (Approved Lists 1980)

\ua9 2024 The Authors.A polyphasic study was designed to determine the taxonomic status of isolate CSLK01-03T, which was recovered from an Indonesian neutral hot spring and provisionally assigned to the genus Rhodococcus. The isolate was found to have chemo-taxonomic, cultural and morphological properties typical of rhodococci. It has a rod–coccus lifecycle and grows from 10 to 39 \ub0C, from pH 6.5 to 8.0 and in the presence of 0–10% (w/v) sodium chloride. Whole-organism hydrolysates contain meso-diaminopimelic acid, arabinose and galactose, the predominant menaquinone is MK-8 (H2), the polar lipid pattern consists of diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol mannosides, phosphatidylmethylethanolamine and two unidentified components, it produces mycolic acids, and C16:0 is the major fatty acid. Whole-genome analyses show that the isolate and Rhodococcus electrodiphilus LMG 29881T (GenBank accession: JAULCK000000000) have genome sizes of 5.5 and 5.1 Mbp, respectively. These strains and Rhodococcus aetherivorans DSM 44752T and Rhodococcus ruber DSM 43338T form well-supported lineages in 16S rRNA and whole-genome trees that are close to sister lineages composed of the type strains of Rhodococcus rhodochrous and related Rhodococcus species. The isolate can be distinguished from its closest evolutionary neighbours using combinations of cultural and phenotypic features, and by low DNA–DNA hybridization values. Based on these data it is proposed that isolate CSLK01-03T (=CCMM B1310T=ICEBB-06T=NCIMB 15214T) be classified in the genus Rhodococcus as Rhodococcus indonesiensis sp. nov. The genomes of the isolate and its closest phylogenomic relatives are rich in biosynthetic gene clusters with the potential to synthesize new natural products, notably antibiotics. In addition, whole-genome-based taxonomy revealed that Rhodococ-cus electrodiphilus LMG 29881T and Rhodococcus ruber DSM 43338T belong to a single species. It is, therefore, proposed that R. electrodiphilus be recognized as a heterotypic synonym of R. ruber

Advances in actinomycete research: an ActinoBase review of 2019

The actinomycetes are Gram-positive bacteria belonging to the order Actinomycetales within the phylum Actinobacteria. They include members with significant economic and medical importance, for example filamentous actinomycetes such as Streptomyces species, which have a propensity to produce a plethora of bioactive secondary metabolites and form symbioses with higher organisms, such as plants and insects. Studying these bacteria is challenging, but also fascinating and very rewarding. As a Microbiology Society initiative, members of the actinomycete research community have been developing a Wikipedia-style resource, called ActinoBase, the purpose of which is to aid in the study of these filamentous bacteria. This review will highlight 10 publications from 2019 that have been of special interest to the ActinoBase community, covering 4 major components of actinomycete research: (i) development and regulation; (ii) specialized metabolites; (iii) ecology and host interactions; and (iv) technology and methodology

Diverse secondary metabolites are expressed in particle-associated and free-living microorganisms of the permanently anoxic Cariaco Basin

Secondary metabolites play essential roles in ecological interactions and nutrient acquisition, and are of interest for their potential uses in medicine and biotechnology. Genome mining for biosynthetic gene clusters (BGCs) can be used for the discovery of new compounds. Here, we use metagenomics and metatranscriptomics to analyze BGCs in free-living and particle-associated microbial communities through the stratified water column of the Cariaco Basin, Venezuela. We recovered 565 bacterial and archaeal metagenome-assembled genomes (MAGs) and identified 1154 diverse BGCs. We show that differences in water redox potential and microbial lifestyle (particle-associated vs. free-living) are associated with variations in the predicted composition and production of secondary metabolites. Our results indicate that microbes, including understudied clades such as Planctomycetota, potentially produce a wide range of secondary metabolites in these anoxic/euxinic waters

antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline

Secondary metabolites produced by bacteria and fungi are an important source of antimicrobials and other bioactive compounds. In recent years, genome mining has seen broad applications in identifying and characterizing new compounds as well as in metabolic engineering. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' (https://antismash.secondarymetabolites.org) has assisted researchers in this, both as a web server and a standalone tool. It has established itself as the most widely used tool for identifying and analysing biosynthetic gene clusters (BGCs) in bacterial and fungal genome sequences. Here, we present an entirely redesigned and extended version 5 of antiSMASH. antiSMASH 5 adds detection rules for clusters encoding the biosynthesis of acyl-amino acids, β-lactones, fungal RiPPs, RaS-RiPPs, polybrominated diphenyl ethers, C-nucleosides, PPY-like ketones and lipolanthines. For type II polyketide synthase-encoding gene clusters, antiSMASH 5 now offers more detailed predictions. The HTML output visualization has been redesigned to improve the navigation and visual representation of annotations. We have again improved the runtime of analysis steps, making it possible to deliver comprehensive annotations for bacterial genomes within a few minutes. A new output file in the standard JavaScript object notation (JSON) format is aimed at downstream tools that process antiSMASH results programmatically.</p

Exploration and exploitation of the environment for novel specialized metabolites

Microorganisms are Nature's little engineers of a remarkable array of bioactive small molecules that represent most of our new drugs. The wealth of genomic and metagenomic sequence data generated in the last decade has shown that the majority of novel biosynthetic gene clusters (BGCs) is identified from cultivation-independent studies, which has led to a strong expansion of the number of microbial taxa known to harbour BGCs. The large size and repeat sequences of BGCs remain a bioinformatic challenge, but newly developed software tools have been created to overcome these issues and are paramount to identify and select the most promising BGCs for further research and exploitation. Although heterologous expression of BGCs has been the greatest challenge until now, a growing number of polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS)-encoding gene clusters have been cloned and expressed in bacteria and fungi based on techniques that mostly rely on homologous recombination. Finally, combining ecological insights with state-of-the-art computation and molecular methodologies will allow for further comprehension and exploitation of microbial specialized metabolites