(143c) Measuring Metabolism of Individual Cell Populations in Mixed Microbial Cultures

Microbial communities play an important role in biochemical engineering, medicine, food production, and waste water treatment. The capabilities of multi-microorganism systems are often enhanced by synergistic interactions at different levels. For example, it was recently shown that co-culture systems have unique advantages over mono-culture systems in optimizing product yield resulting from synergistic interactions and optimal division of labor.

Here, we present a novel framework for measuring metabolism of individual cell populations in mixed microbial cultures using ¹³C metabolic flux analysis (¹³C-MFA). We demonstrate for the first time that it is possible to measure metabolic fluxes in multiple species simultaneously in a mixed microbial culture without the need for physical separation of cells or proteins, or overexpression and detection of species-specific products. Instead, metabolic fluxes of each species are estimated directly from isotopic labeling of total biomass obtained using conventional mass spectrometry approaches (GC-MS). In addition to determining metabolic fluxes, this approach estimates relative population size of each species in the mixed culture, and inter-species metabolite exchange. As such, this approach enables detailed studies of microbial communities including species dynamics and interactions between community members. We have applied this methodology to study two model co-culture systems: 1) a co-culture of two E. coli knockout strains, Dzwf (knockout of the first step in the pentose phosphate pathway) and Dpgi (knockout of the first step in glycolysis pathway); and 2) a co-culture of E. coli and yeast. For the first time, we have elucidated how these two model microbes grow and interact with each other when grown simultaneously in a co-culture.

In summary, we have developed a new fluxomic methodology that adds a new dimension to metabolic engineering and significantly extends the scope of ¹³C-MFA studies to a large number of multi-cellular systems that are of significant importance in biotechnology and medicine.