Evidence map›Paper›PMID 29859036›Full record

ArticleBMC genomics2018

Comparative genomics reveals phylogenetic distribution patterns of secondary metabolites in Amycolatopsis species.

Martina Adamek, Mohammad Alanjary, Helena Sales-Ortells, Michael Goodfellow, Alan T Bull, Anika Winkler, Daniel Wibberg, Jörn Kalinowski, Nadine Ziemert

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed
11.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 133 citations in OpenAlex.

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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 2 countries.

Martina AdamekInterfaculty Institute of Microbiology and Infection Medicine Tübingen, Microbiology/Biotechnology, University of Tübingen, Tübingen, Germany.
Mohammad AlanjaryInterfaculty Institute of Microbiology and Infection Medicine Tübingen, Microbiology/Biotechnology, University of Tübingen, Tübingen, Germany.
Helena Sales-OrtellsInterfaculty Institute of Microbiology and Infection Medicine Tübingen, Microbiology/Biotechnology, University of Tübingen, Tübingen, Germany.
Michael GoodfellowSchool of Biology, Newcastle University, Ridley Building 2, Newcastle upon Tyne, NE1 7RU, UK.
Alan T BullSchool of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK.
Anika WinklerUniversität Bielefeld, Center for Biotechnology (CeBiTec), Bielefeld, Germany.
Daniel WibbergUniversität Bielefeld, Center for Biotechnology (CeBiTec), Bielefeld, Germany.
Jörn KalinowskiUniversität Bielefeld, Center for Biotechnology (CeBiTec), Bielefeld, Germany.
Nadine ZiemertInterfaculty Institute of Microbiology and Infection Medicine Tübingen, Microbiology/Biotechnology, University of Tübingen, Tübingen, Germany. nadine.ziemert@uni-tuebingen.de.ORCID http://orcid.org/0000-0002-7264-1857
German Center for Infection Research · DEBielefeld University · DENewcastle University · GBUniversity of Kent · GB

Funding

Bielefeld-Gießen Center for Microbial Bioinformatics 031A533Deutsches Zentrum für Infektionsforschung TTU 9.704Leverhulme Trust Emeritus Fellowship
6 · The paper itself

Abstract

backgroundGenome mining tools have enabled us to predict biosynthetic gene clusters that might encode compounds with valuable functions for industrial and medical applications. With the continuously increasing number of genomes sequenced, we are confronted with an overwhelming number of predicted clusters. In order to guide the effective prioritization of biosynthetic gene clusters towards finding the most promising compounds, knowledge about diversity, phylogenetic relationships and distribution patterns of biosynthetic gene clusters is necessary.

resultsHere, we provide a comprehensive analysis of the model actinobacterial genus Amycolatopsis and its potential for the production of secondary metabolites. A phylogenetic characterization, together with a pan-genome analysis showed that within this highly diverse genus, four major lineages could be distinguished which differed in their potential to produce secondary metabolites. Furthermore, we were able to distinguish gene cluster families whose distribution correlated with phylogeny, indicating that vertical gene transfer plays a major role in the evolution of secondary metabolite gene clusters. Still, the vast majority of the diverse biosynthetic gene clusters were derived from clusters unique to the genus, and also unique in comparison to a database of known compounds. Our study on the locations of biosynthetic gene clusters in the genomes of Amycolatopsis' strains showed that clusters acquired by horizontal gene transfer tend to be incorporated into non-conserved regions of the genome thereby allowing us to distinguish core and hypervariable regions in Amycolatopsis genomes.

conclusionsUsing a comparative genomics approach, it was possible to determine the potential of the genus Amycolatopsis to produce a huge diversity of secondary metabolites. Furthermore, the analysis demonstrates that horizontal and vertical gene transfer play an important role in the acquisition and maintenance of valuable secondary metabolites. Our results cast light on the interconnections between secondary metabolite gene clusters and provide a way to prioritize biosynthetic pathways in the search and discovery of novel compounds.

Indexed as

GenomicsPhylogenyActinomycetalesGenome, BacterialMultigene FamilySecondary MetabolismAmycolatopsisBiosynthetic gene clusterComparative genomicsEvolutionGene cluster familyGenome miningNatural productsPhylogenySecondary metabolite diversity

Identifiers

PMID29859036
PMCPMC5984834
OpenAlexW2805599849

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.