Metabolite secretion in microorganisms: the theory of metabolic overflow put to the test

• Published in: Metabolomics Vol. 14; no. 4; p. 43
• Main Authors: Pinu, Farhana R., Granucci, Ninna, Daniell, James, Han, Ting-Li, Carneiro, Sónia, Rocha, I., Nielsen, Jens, Villas-Boas, Silas G.
• Format: Journal Article
• Language: English
• Published: New York Springer Nature 01.04.2018; Springer US; Springer Nature B.V
• Subjects: Active efflux; Aspergillus niger - metabolism; Biochemistry; Biomedical and Life Sciences; Biomedicine; Cell Biology; Corynebacterium glutamicum - metabolism; Developmental Biology; Escherichia coli - metabolism; Intermediates; Intracellular; Life Sciences; Metabolic engineering; Metabolic modeling; Metabolic modelling; Metabolism; Metabolites; Metabolomics; Microbial metabolism; Microorganisms; Models, Biological; Molecular Medicine; Review Article; Science & Technology; Secretion; Systems biology; Microorganisms; Metabolic modeling; Secretion; Systems biology; Microbial metabolism; Metabolic engineering; Active efflux
• ISSN: 1573-3882; 1573-3890; 1573-3882; 1573-3890
• DOI: 10.1007/s11306-018-1339-7

Introduction Microbial cells secrete many metabolites during growth, including important intermediates of the central carbon metabolism. This has not been taken into account by researchers when modeling microbial metabolism for metabolic engineering and systems biology studies. Materials and Methods The uptake of metabolites by microorganisms is well studied, but our knowledge of how and why they secrete different intracellular compounds is poor. The secretion of metabolites by microbial cells has traditionally been regarded as a consequence of intracellular metabolic overflow. Conclusions Here, we provide evidence based on time-series metabolomics data that microbial cells eliminate some metabolites in response to environmental cues, independent of metabolic overflow. Moreover, we review the different mechanisms of metabolite secretion and explore how this knowledge can benefit metabolic modeling and engineering. The authors are thankful to Mia Jullig for assistance with Fig. 2. Callaghan Innovation and Bioresource Processing Alliance provided PhD stipends for James Daniell and Ninna Granucci respectively.