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

TY - JOUR

T1 - Principal component analysis of proteomics (PCAP) as a tool to direct metabolic engineering

AU - Alonso-Gutierrez, Jorge

AU - Kim, Eun-Mi

AU - Batth, Tanveer S

AU - Cho, Nathan

AU - Hu, Qijun

AU - Chan, Leanne Jade G

AU - Petzold, Christopher J

AU - Hillson, Nathan J

AU - Adams, Paul D

AU - Keasling, Jay D

AU - Garcia Martin, Hector

AU - Lee, Taek Soon

N1 - Copyright © 2014 International Metabolic Engineering Society. All rights reserved.

PY - 2015/3/1

Y1 - 2015/3/1

N2 - 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.

AB - 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.

KW - Escherichia coli/genetics

KW - Escherichia coli Proteins/biosynthesis

KW - Gene Expression Regulation, Bacterial

KW - Metabolic Engineering/methods

KW - Proteomics

KW - Terpenes/metabolism

U2 - 10.1016/j.ymben.2014.11.011

DO - 10.1016/j.ymben.2014.11.011

M3 - Journal article

C2 - 25554074

SN - 1096-7176

VL - 28

SP - 123

EP - 133

JO - Metabolic Engineering

JF - Metabolic Engineering

ER -