Unravelling metabolic cross‐feeding in a yeast–bacteria community using 13C‐based proteomics

Author:

Gabrielli Natalia1ORCID,Maga‐Nteve Christoniki1,Kafkia Eleni12,Rettel Mandy1,Loeffler Jakob1,Kamrad Stephan2,Typas Athanasios1,Patil Kiran Raosaheb12ORCID

Affiliation:

1. European Molecular Biology Laboratory Heidelberg Germany

2. Medical Research Council Toxicology Unit University of Cambridge Cambridge UK

Abstract

AbstractCross‐feeding is fundamental to the diversity and function of microbial communities. However, identification of cross‐fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13C isotope tracing in peptides to elucidate cross‐fed metabolites in co‐cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13C. Data analysis allowing for the possible mass‐shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross‐fed metabolites was further supported by metabolite labelling in the co‐culture supernatant, and by diminished fitness of a galactose‐negative yeast mutant in the community. Together, our results demonstrate the utility of 13C‐based proteomics for uncovering microbial interactions.

Funder

H2020 European Research Council

European Research Council

H2020 Marie Skłodowska-Curie Actions

Medical Research Council

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Information Systems

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