A quantitative lens on anaerobic life: leveraging the state-of-the-art fluxomics approach to explore clostridial metabolism. (August 2020)

• Record Type: Journal Article
• Authors: Wu, Chao; Cano, Melissa; Gao, Xiang; Lo, Jonathan; Maness, PinChing; Xiong, Wei
• Is Part Of: Current opinion in biotechnology. Volume 64(2020)
• Page Start: 47
• Page End: 54
• Publication Date: 2020-08
• Subjects: Biotechnology -- Periodicals; 660.6
• DOI: 10.1016/j.copbio.2019.09.012
• Languages: English
• ISSNs: 0958-1669

Abstract

Highlights: Fluxomics approaches can be tailored to decipher clostridial metabolism strategically. New fluxomic techniques arise such as machine learning-based approach, deuterium labeling, and high-throughput flux analysis. Advanced fluxomics is radically updating our understanding of clostridial metabolism. Abstract : Quantitative understanding of clostridial metabolism is of longstanding interest due to the importance of Clostridia as model anaerobes, biotechnology workhorses, and contributors to evolutionary history and ecosystem. Current computational methods such as flux balance analysis-based construction of clostridial metabolism in genome scale provide a fundamental framework for metabolic analysis. However, this method alone is inadequate to characterize cellular metabolic activity. Experiment-driven approaches including isotope tracer-based fluxomics in association with genetic and biochemical methods are needed to gain a more comprehensive understanding. Here we focus on typical examples where these integrated approaches have contributed to the identification of new metabolic pathways and quantification of metabolic fluxes in Clostridia. We also highlight the opportunities and challenges of cutting-edge fluxomics approaches such as machine learning modeling, deuterium tracer approach, and high throughput flux phenotyping in exploring clostridial metabolism with respect to inorganic carbon utilization, redox cofactor interconversion, and other key metabolic features.