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From a Natural Product to Its Biosynthetic Gene Cluster: A Demonstration Using Polyketomycin from Streptomyces diastatochromogenes Tü6028

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

Marnix H Medema¹, Peter Cimermancic², Andrej Sali³

¹Department 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.

Plos Computational Biology

|December 5, 2014

Summary

Nature invents new molecules through bacterial biosynthetic gene clusters (BGCs) by merging sub-clusters and concerted evolution of enzymes. Understanding these evolutionary constraints aids synthetic biology for pathway engineering.

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Area of Science:

Microbiology
Biochemistry
Bioinformatics

Background:

Bacterial secondary metabolites are crucial for medicine and industry.
Engineering biosynthetic gene clusters (BGCs) is challenging due to enzyme complexity.

Purpose of the Study:

To computationally analyze BGC evolution to understand natural product discovery.
To identify evolutionary constraints and successful invention strategies.

Main Methods:

Systematic computational analysis of bacterial biosynthetic gene cluster evolution.
Examining evolutionary patterns of polyketide synthases and nonribosomal peptide synthetases.

Main Results:

BGCs evolve via sub-cluster mergers and concerted evolution of enzyme domains.
Sequence-homogenized domains show functional interoperability.
BGC families exhibit distinct evolutionary trajectories.

Conclusions:

Evolutionary constraints shape BGC innovation.
Family-specific constraints must guide synthetic biology strategies.
Findings enable rational engineering of biosynthetic pathways for novel metabolite production.