Evidence map›Paper›PMID 25474254›Full record

ArticlePLoS computational biology2014

A systematic computational analysis of biosynthetic gene cluster evolution: lessons for engineering biosynthesis.

Marnix H Medema, Peter Cimermancic, Andrej Sali, Eriko Takano, Michael A Fischbach

Erratum issuedAbstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 124 papers.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed
–field-weighted citation impact
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

124 citing papers in PubMed.

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  15. Chromosome-level genome assembly ofHorticulture research · 2026
    Article
  16. Review
  17. Article
  18. Evolutionary Tree in Chemical Space of Natural Products.bioRxiv : the preprint server for biology · 2025
    Article
  19. Article
  20. Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Marnix H MedemaDepartment of Microbial Physiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands; Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands.
Peter CimermancicDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America; California Institute for Quantitative Biosciences, San Francisco, California, United States of America.
Andrej SaliDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America; California Institute for Quantitative Biosciences, San Francisco, California, United States of America; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California, United States of America.
Eriko TakanoManchester Institute of Biotechnology, Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom.
Michael A FischbachDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America; California Institute for Quantitative Biosciences, San Francisco, California, United States of America.

Funding

Rewiring Therapeutic Cells: User-Controlled T Cells and Stem CellsP50GM081879 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIM, WENDELL A · 2010 to 2017
$19.0M
Antibiotics from nose and throat commensals that impact pathogen colonizationR01AI101018 · NIAID · BAYLOR COLLEGE OF MEDICINE · PI FISCHBACH, MICHAEL ANDREW, LEMON, KATHERINE PAIGE · 2012 to 2021
$4.4M
Identifying and characterizing small molecules from the human microbiomeDP2OD007290 · OD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FISCHBACH, MICHAEL ANDREW · 2010 to 2010
$2.3M
Natural products from a human-asssociated fungal pathogenR21AI101722 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FISCHBACH, MICHAEL ANDREW, SIL, ANITA · 2012 to 2013
$419k
Howard Hughes Medical InstituteNIAID NIH HHS AI101018NIAID NIH HHS AI101722NIAID NIH HHS HHSN272200900018CNIAID NIH HHS R01 AI101018NIAID NIH HHS R21 AI101722NIGMS NIH HHS GM081879NIGMS NIH HHS P50 GM081879NIH HHS DP2 OD007290NIH HHS OD007290PHS HHS HHSN272200900018C
6 · The paper itself

Abstract

Bacterial secondary metabolites are widely used as antibiotics, anticancer drugs, insecticides and food additives. Attempts to engineer their biosynthetic gene clusters (BGCs) to produce unnatural metabolites with improved properties are often frustrated by the unpredictability and complexity of the enzymes that synthesize these molecules, suggesting that genetic changes within BGCs are limited by specific constraints. Here, by performing a systematic computational analysis of BGC evolution, we derive evidence for three findings that shed light on the ways in which, despite these constraints, nature successfully invents new molecules: 1) BGCs for complex molecules often evolve through the successive merger of smaller sub-clusters, which function as independent evolutionary entities. 2) An important subset of polyketide synthases and nonribosomal peptide synthetases evolve by concerted evolution, which generates sets of sequence-homogenized domains that may hold promise for engineering efforts since they exhibit a high degree of functional interoperability, 3) Individual BGC families evolve in distinct ways, suggesting that design strategies should take into account family-specific functional constraints. These findings suggest novel strategies for using synthetic biology to rationally engineer biosynthetic pathways.

Indexed as

Evolution, MolecularModels, GeneticBioengineeringComputational BiologyMultigene Family

Identifiers

PMID25474254
PMCPMC4256081

What OpenQuestion holds

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Registered trials

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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.