Proteome constraints reveal targets for improving microbial fitness in nutrient-rich environments
Artikel i vetenskaplig tidskrift, 2021

Cells adapt to different conditions via gene expression that tunes metabolism for maximal fitness. Constraints on cellular proteome may limit such expression strategies and introduce trade-offs. Resource allocation under proteome constraints has explained regulatory strategies in bacteria. It is unclear, however, to what extent these constraints can predict evolutionary changes, especially for microorganisms that evolved under nutrient-rich conditions, i.e., multiple available nitrogen sources, such as Lactococcus lactis. Here, we present a proteome-constrained genome-scale metabolic model of L. lactis (pcLactis) to interpret growth on multiple nutrients. Through integration of proteomics and flux data, in glucose-limited chemostats, the model predicted glucose and arginine uptake as dominant constraints at low growth rates. Indeed, glucose and arginine catabolism were found upregulated in evolved mutants. At high growth rates, pcLactis correctly predicted the observed shutdown of arginine catabolism because limited proteome availability favored lactate for ATP production. Thus, our model-based analysis is able to identify and explain the proteome constraints that limit growth rate in nutrient-rich environments and thus form targets of fitness improvement.

ccpA

laboratory evolution

Lactococcus lactis

metabolic modeling

proteome constraint

Författare

Yu Chen

Novo Nordisk Foundation Center for Biosustainability

Chalmers, Biologi och bioteknik, Systembiologi

Eunice van Pelt-KleinJan

Top Institute Food and Nutrition (TIFN)

Vrije Universiteit Amsterdam

Berdien van Olst

Vrije Universiteit Amsterdam

Wageningen University and Research

Sieze Douwenga

Wageningen University and Research

Vrije Universiteit Amsterdam

Sjef Boeren

Wageningen University and Research

Top Institute Food and Nutrition (TIFN)

Herwig Bachmann

Vrije Universiteit Amsterdam

Top Institute Food and Nutrition (TIFN)

NIZO food research

Douwe Molenaar

Top Institute Food and Nutrition (TIFN)

Vrije Universiteit Amsterdam

Jens B Nielsen

Chalmers, Biologi och bioteknik, Systembiologi

Danmarks Tekniske Universitet (DTU)

Novo Nordisk Foundation Center for Biosustainability

BioInnovation Institute

B. Teusink

Top Institute Food and Nutrition (TIFN)

Vrije Universiteit Amsterdam

Molecular Systems Biology

1744-4292 (ISSN)

Vol. 17 4 e10093

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Bioinformatik och systembiologi

DOI

10.15252/msb.202010093

PubMed

33821549

Mer information

Senast uppdaterat

2021-05-03