Rhodococcus comparative genomics reveals a phylogenomic-dependent non-ribosomal peptide synthetase distribution: insights into biosynthetic gene cluster connection to an orphan metabolite.
Agustina Undabarrena,Ricardo Valencia,Ricardo Valencia,Andrés Cumsille,Leonardo Zamora-Leiva,Eduardo Castro-Nallar,Francisco Barona-Gómez,Beatriz Cámara +7 more
- Vol. 7, Iss: 7
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The article was published on 2021-07-01 and is currently open access. It has received 9 citations till now. The article focuses on the topics: Gene cluster & Comparative genomics.read more
Citations
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The confluence of big data and evolutionary genome mining for the discovery of natural products.
Marc G. Chevrette,Athina Gavrilidou,Shrikant Mantri,Nelly Selem-Mojica,Nadine Ziemert,Francisco Barona-Gómez +5 more
TL;DR: This review covers literature between 2003-2021 and highlights examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes.
Journal ArticleDOI
Role is in the eye of the beholder—the multiple functions of the antibacterial compound tropodithietic acid produced by marine Rhodobacteraceae
Nathalie N. S. E. Henriksen,L. L. Lindqvist,Mario Wibowo,Eva C. Sonnenschein,Mikkel Bentzon-Tilia,Lone Gram +5 more
TL;DR: The current understanding of the chemical ecology of T DA, including the environmental niches of TDA-producing bacteria, and the molecular mechanisms governing the function and regulation of Tda are summarized.
Journal ArticleDOI
OUP accepted manuscript
TL;DR: The tropone derivative tropodithietic acid (TDA) is a broad spectrum antimicrobial compound produced by several members of the Rhodobacteraceae family, a major marine bacterial lineage, within the genera Phaeobacter, Tritonibacter, and Pseudovibrio as mentioned in this paper .
Posted ContentDOI
A global survey of specialized metabolic diversity encoded in bacterial genomes
Athina Gavriilidou,Satria A. Kautsar,Nestor Zaburannyi,Daniel Krug,Rolf Mueller,Marnix H. Medema,Nadine Ziemert +6 more
TL;DR: In this article, the authors surveyed around 170,000 bacterial genomes as well as several thousands of Metagenome Assembled Genomes (MAGs) for their diversity in Biosynthetic Gene Clusters (BGCs) known to encode the biosynthetic machinery for producing secondary metabolites.
Journal ArticleDOI
Rhodococcus strains as a good biotool for neutralizing pharmaceutical pollutants and obtaining therapeutically valuable products: Through the past into the future
TL;DR: The review presents the latest knowledge and current trends regarding the use of Rhodococcus spp.
References
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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Kazutaka Katoh,Daron M. Standley +1 more
TL;DR: This version of MAFFT has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update.
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MrBayes 3: Bayesian phylogenetic inference under mixed models
TL;DR: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models to analyze heterogeneous data sets and explore a wide variety of structured models mixing partition-unique and shared parameters.
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MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.
TL;DR: The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine and has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses.
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MRBAYES: Bayesian inference of phylogenetic trees
TL;DR: The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo, and an executable is available at http://brahms.rochester.edu/software.html.
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IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies
TL;DR: It is shown that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented and found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space.
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