Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

Affiliations

¹ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
² Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA 90095, USA.
³ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; Department of Bioengineering, University of California, Berkeley, CA 94720, USA.
⁴ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; Department of Bioengineering, University of California, Berkeley, CA 94720, USA; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA.
⁵ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. Electronic address: hgmartin@lbl.gov.
⁶ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. Electronic address: tslee@lbl.gov.

PMID: 25554074
DOI: 10.1016/j.ymben.2014.11.011

Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

Jorge Alonso-Gutierrez et al. Metab Eng. 2015 Mar.

. 2015 Mar:28:123-133.

doi: 10.1016/j.ymben.2014.11.011. Epub 2014 Dec 29.

Affiliations

¹ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
² Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA 90095, USA.
³ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; Department of Bioengineering, University of California, Berkeley, CA 94720, USA.
⁴ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; Department of Bioengineering, University of California, Berkeley, CA 94720, USA; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, USA.
⁵ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. Electronic address: hgmartin@lbl.gov.
⁶ Joint BioEnergy Institute, 5885 Hollis Street, Emeryville, CA 94608, USA; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. Electronic address: tslee@lbl.gov.

PMID: 25554074
DOI: 10.1016/j.ymben.2014.11.011

Abstract

Targeted proteomics is a convenient method determining enzyme expression levels, but a quantitative analysis of these proteomic data has not been fully explored yet. Here, we present and demonstrate a computational tool (principal component analysis of proteomics, PCAP) that uses quantitative targeted proteomics data to guide metabolic engineering and achieve higher production of target molecules from heterologous pathways. The method is based on the application of principal component analysis to a collection of proteomics and target molecule production data to pinpoint specific enzymes that need to have their expression level adjusted to maximize production. We illustrated the method on the heterologous mevalonate pathway in Escherichia coli that produces a wide range of isoprenoids and requires balanced pathway gene expression for high yields and titers. PCAP-guided engineering resulted in over a 40% improvement in the production of two valuable terpenes. PCAP could potentially be productively applied to other heterologous pathways as well.

Keywords: Escherichia coli; Heterologous pathway; Metabolic engineering; Mevalonate pathway; Principal component analysis (PCA); Targeted proteomics.

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Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

Affiliations

Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

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