Mapping high-growth phenotypes in the flux space of microbial metabolism

TL;DR

This paper introduces a comprehensive framework for analyzing microbial metabolism by mapping the entire feasible flux phenotype space, revealing high-growth states and behaviors beyond traditional optimality assumptions, with implications for biotech and medicine.

Contribution

It presents a novel approach to explore all feasible metabolic flux phenotypes, not just optimal states, uncovering new metabolic behaviors and providing a benchmark for experimental validation.

Findings

Feasible flux phenotype maps reveal high-growth states.

Aerobic fermentation occurs under nutrient excess conditions.

Full flux space analysis uncovers behaviors unreachable by optimality models.

Abstract

Experimental and empirical observations on cell metabolism cannot be understood as a whole without their integration into a consistent systematic framework. However, the characterization of metabolic flux phenotypes is typically reduced to the study of a single optimal state, like maximum biomass yield that is by far the most common assumption. Here we confront optimal growth solutions to the whole set of feasible flux phenotypes (FFP), which provides a benchmark to assess the likelihood of optimal and high-growth states and their agreement with experimental results. In addition, FFP maps are able to uncover metabolic behaviors, such as aerobic fermentation accompanying exponential growth on sugars at nutrient excess conditions, that are unreachable using standard models based on optimality principles. The information content of the full FFP space provides us with a map to explore and evaluate metabolic behavior and capabilities, and so it opens new avenues for biotechnological and biomedical applications.