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Genome Mining in Prokaryotes: Glossary

Key Points

Introduction to Genome Mining	Natural products are encoded in Biosynthetic Gene Clusters (BGCs) Genome mining describes the exploitation of genomic information with specialized algorithms intended to discover and study BGCs
Secondary metabolite biosynthetic gene cluster identification	antiSMASH is a bioinformatic tool capable of identifying, annotating and analysing secondary metabolite BGC antiSMASH can be used as a web-based tool or as stand-alone command-line tool The file extensions accepted by antiSMASH are GenBank, FASTA and EMBL
Genome Mining Databases	MIBiG provides BGCs that have been experimentally tested antiSMASH database comprises predicted BGCs of each organism
BGC Similarity Networks	BGC similarity is measured by BiG-SCAPE according to protein domain content, adjacency and sequence identity. The `gbks` of the regions identified by antiSMASH are the input for BiG-SCAPE. BiG-SCAPE delivers BGCs similarity networks with which it delimits Gene Cluster Families and creates a phylogeny of the BGCs in each GCF.
Homologous BGC Clusterization	`BiG-SLiCE` and `BiG-FAM` are softwares that are useful to compare the metabolic diversity of bacterial lineages between each other and against a big database An input-folder containing the BGCs from antiSMASH and the taxonomic information of each genome is needed to run `BiG-SLiCE` The results from the antiSMASH web-tool are needed to run `BiG-FAM` Gene Cluster Families can help us to compare the metabolic capabilities of a set of bacterial lineages We can use `BiG-FAM` to compare a BGC against the whole database and predict its Gene Cluster Family
Finding Variation on Genomic Vicinities	CORASON is a command-line tool that finds BGC-families Genomic vicinity variation is organized phylogenetically according to the conserved genes in the BGC-family
Evolutionary Genome Mining	EvoMining is a command-line tool that performs evolutionary genome mining over gene families EvoMining hits can belong to new BGC MicroReact is an interactive genomic visualizer compatible with EvoMining output
GATOR-GC: Genomic Assessment Tool for Orthologous Regions and Gene Clusters	GATOR-GC is an innovative tool that uses an enzyme-aware scoring system and evolutionary principles to explore BGC diversity. Unlike traditional methods, GATOR-GC offers flexibility in defining the taxonomic scope and prioritizes the identification of novel biosynthetic pathways. GATOR-GC can be customized to search for essential and optional enzymes, making it a powerful tool for targeted exploration. Dynamic gene cluster diagrams and GATOR neighborhood visualizations provide clear insights into gene conservation and genomic relationships.
Metabolomics workshop	Data is generated using Liquid Chromatography coupled to a tandem mass spectrometer (LC-MS/MS or MS2). Dereplication is the process of identifying previously known compounds. Molecular networking is a computational method that organizes MS2 data based on spectral similarity, allowing us to infer relationships between chemical structures Feature-Based Molecular Networking (FBMN) enhances classical molecular networking by integrating relative quantitative data, enabling more robust metabolomics statistical analysis.
Other Resources	First key point. Brief Answer to questions. (FIXME)

Glossary

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