Analysis of a comprehensive dataset of diversity generating retroelements generated by the program DiGReF

BACKGROUND: Diversity Generating Retroelements (DGRs) are genetic cassettes that can introduce tremendous diversity into a short, defined region of the genome. They achieve hypermutation through replacement of the variable region with a strongly mutated cDNA copy generated by the element-encoded reverse transcriptase. In contrast to “selfish” retroelements such as group II introns and retrotransposons, DGRs impart an advantage to their host by increasing its adaptive potential. DGRs were discovered in a bacteriophage, but since then additional examples have been identified in some bacterial genomes. RESULTS: Here we present the program DiGReF that allowed us to comprehensively screen available databases for DGRs. We identified 155 DGRs which are found in all major classes of bacteria, though exhibiting sporadic distribution across species. Phylogenetic analysis and sequence comparison showed that DGRs move between genomes by associating with various mobile elements such as phages, transposons and plasmids. The DGR cassettes exhibit high flexibility in the arrangement of their components and easily acquire additional paralogous target genes. Surprisingly, the genomic data alone provide new insights into the molecular mechanism of DGRs. Most notably, our data suggest that the template RNA is transcribed separately from the rest of the element. CONCLUSIONS: DiGReF is a valuable tool to detect DGRs in genome data. Its output allows comprehensive analysis of various aspects of DGR biology, thus deepening our understanding of the role DGRs play in prokaryotic genome plasticity, from the global down to the molecular level

Od sekvencije DNA do kemijske strukture – pretraživanje mikrobnih genomskih i metagenomskih skupova podataka radi pronalaženja novih prirodnih spojeva

Rapid mining of large genomic and metagenomic data sets for modular polyketide synthases, non-ribosomal peptide synthetases and hybrid polyketide synthase/non-ribosomal peptide synthetase biosynthetic gene clusters has been achieved using the generic computer program packages ClustScan and CompGen. These program packages perform the annotation with the hierarchical structuring into polypeptides, modules and domains, as well as storage and graphical presentations of the data. This aims to achieve the most accurate predictions of the activities and specificities of catalytically active domains that can be made with present knowledge, leading to a prediction of the most likely chemical structures produced by these enzymes. The program packages also allow generation of novel clusters by homologous recombination of the annotated genes in silico. ClustScan and CompGen were used to construct a custom database of known compounds (CSDB) and of predicted entirely novel recombinant products (r-CSDB) that can be used for in silico screening with computer aided drug design technology. The use of these programs has been exemplified by analysing genomic sequences from terrestrial prokaryotes and eukaryotic microorganisms, a marine metagenomic data set and a newly discovered example of a \u27shared metabolic pathway\u27 in marine-microbial endosymbiosis.Brzo pretraživanje genomskih i metagenomskih skupova podataka, modularnih biosintetskih genskih nakupina poliketid sintaza i sintetaza neribosomalno sintetiziranih peptida, postignuto je primjenom generičkih računalnih programskih paketa ClustScan i CompGen. Ti programski paketi provode anotaciju hijerarhijskim strukturiranjem podataka na polipeptide, module i domene, te pohranu i grafičku prezentaciju tih podataka. Na temelju dosadašnjih spoznaja, nastoji se postići najtočnije moguće predviđanje aktivnosti i specifičnosti katalitički aktivnih domena, što vodi prema predviđanju najvjerojatnijih kemijskih struktura koje ti enzimi mogu sintetizirati. Programski paketi ClustScan i CompGen omogućuju generiranje novih genskih nakupina homolognom rekombinacijom anotiranih gena u uvjetima in silico, a upotrijebljeni su i za konstrukciju vlastitih baza podataka poznatih poliketidnih i peptidnih supstancija (CSDB) te potpuno novih poliketidnih i peptidnih supstancija produkata rekombinacije (r-CSDB). Ti će se produkti rekombinacije moći upotrijebiti za izbor supstancija s potencijalnom biološkom aktivnošću pomoću računalom vođenog dizajna lijekova u uvjetima in silico. Primjenjivost programskih paketa ClustScan i CompGen dokazana je u analizi genomskih sekvencija prokariotskih i eukariotskih mikroorganizama što žive u tlu, analizi metagenomske skupine podataka u uzorku iz morske vode, a i na nedavno opisanom primjeru \u27zajedničkog metaboličkoga puta\u27 u mikrobnog endosimbionta morske životinje

From DNA sequences to chemical structures – methods for mining microbial genomic and metagenomic data sets for new natural products

Rapid mining of large genomic and metagenomic data sets for modular polyketide synthases, non-ribosomal peptide synthetases and hybrid polyketide synthase/non-ribosomal peptide synthetase biosynthetic gene clusters has been achieved using the generic computer program packages ClustScan and CompGen. These program packages perform the annotation with the hierarchical structuring into polypeptides, modules and domains, as well as storage and graphical presentations of the data. This aims to achieve the most accurate predictions of the activities and specificities of catalytically active domains that can be made with present knowledge, leading to a prediction of the most likely chemical structures produced by these enzymes. The program packages also allow generation of novel clusters by homologous recombination of the annotated genes in silico. ClustScan and CompGen were used to construct a custom database of known compounds (CSDB) and of predicted entirely novel recombinant products (r-CSDB) that can be used for in silico screening with computer-aided drug design technology. The use of these programs has been exemplified by analysing genomic sequences from terrestrial prokaryotes and eukaryotic microorganisms, a marine metagenomic data set and a newly discovered example of a 'shared metabolic pathway' in marine-microbial endosymbiosis

Evolutionary concepts in natural products discovery:what actinomycetes have taught us

Abstract Actinomycetes are a very important source of natural products for the pharmaceutical industry and other applications. Most of the strains belong to Streptomyces or related genera, partly because they are particularly amenable to growth in the laboratory and industrial fermenters. It is unlikely that chemical synthesis can fulfil the needs of the pharmaceutical industry for novel compounds so there is a continuing need to find novel natural products. An evolutionary perspective can help this process in several ways. Genome mining attempts to identify secondary metabolite biosynthetic clusters in DNA sequences, which are likely to produce interesting chemical entities. There are often technical problems in assembling the DNA sequences of large modular clusters in genome and metagenome projects, which can be overcome partially using information about the evolution of the domain sequences. Understanding the evolutionary mechanisms of modular clusters should allow simulation of evolutionary pathways in the laboratory to generate novel compounds.</jats:p