Technical versus biological variability in a synthetic human gut community.

Synthetic communities grown in well-controlled conditions are an important tool to decipher the mechanisms driving community dynamics. However, replicate time series of synthetic human gut communities in chemostats are rare, and it is thus still an open question to what extent stochasticity impacts gut community dynamics. Here, we address this question with a synthetic human gut bacterial community using an automated fermentation system that allows for a larger number of biological replicates. We collected six biological replicates for a community initially consisting of five common gut bacterial species that fill different metabolic niches. After an initial 12 hours in batch mode, we switched to chemostat mode and observed the community to stabilize after 2-3 days. Community profiling with 16S rRNA resulted in high variability across replicate vessels and high technical variability, while the variability across replicates was significantly lower for flow cytometric data. Both techniques agree on the decrease in the abundance of Bacteroides thetaiotaomicron, accompanied by an initial increase in Blautia hydrogenotrophica. These changes occurred together with reproducible metabolic shifts, namely a fast depletion of glucose and trehalose concentration in batch followed by a decrease in formic acid and pyruvic acid concentrations within the first 12 hours after the switch to chemostat mode. In conclusion, the observed variability in the synthetic bacterial human gut community, as assessed with 16S rRNA gene sequencing, is largely due to technical variability. The low variability seen in HPLC and flow cytometry data suggests a highly deterministic system.

Fast quantification of gut bacterial species in cocultures using flow cytometry and supervised classification.

A bottleneck for microbial community experiments with many samples and/or replicates is the fast quantification of individual taxon abundances, which is commonly achieved through sequencing marker genes such as the 16S rRNA gene. Here, we propose a new approach for high-throughput and high-quality enumeration of human gut bacteria in a defined community, combining flow cytometry and supervised classification to identify and quantify species mixed in silico and in defined communities in vitro. We identified species in a 5-species in silico community with an F1 score of 71%. In addition, we demonstrate in vitro that our method performs equally well or better than 16S rRNA gene sequencing in two-species cocultures and agrees with 16S rRNA gene sequencing data on the most abundant species in a four-species community. We found that shape and size differences alone are insufficient to distinguish species, and that it is thus necessary to exploit the multivariate nature of flow cytometry data. Finally, we observed that variability of flow cytometry data across replicates differs between gut bacterial species. In conclusion, the performance of supervised classification of gut species in flow cytometry data is species-dependent, but is for some combinations accurate enough to serve as a faster alternative to 16S rRNA gene sequencing.

Growth promotion and inhibition induced by interactions of groundwater bacteria.

Microorganisms can produce a plethora of secondary metabolites, some acting as signaling compounds and others as suppressing agents. As yet, the potential of groundwater microbes to produce antimicrobial compounds to increase their competitiveness against other bacteria has not been examined. In this study, we developed an AlamarBlue® based high-throughput screening method that allowed for a fast and highly standardized evaluation of both growth-inhibiting and -promoting metabolites. With this technique, 149 screened bacterial isolates were grown in monocultures and in 1402 co-cultures. Co-cultivation did not increase the frequency of growth inhibition against the two tested model organisms (Staphylococcus aureus 533R4 and Escherichia coli WA321) compared to monocultures. Mainly co-cultivation of Proteobacteria induced growth inhibition of both model organisms. Only slightly increased growth promotion of S. aureus 533R4 was observed. Growth-promoting effects on E. coli WA321 were observed by supernatants from co-cultures between Bacteroidetes and Firmicutes. With the standardized screening for both growth-inhibiting and -promoting effects, this method will enable further studies to elaborate and better understand complex inter-specific interactions and networks in aquatic communities as well as in other environments.