Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics, construct co-occurrence networks, and evaluate how well networks reveal the underlying interactions, and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of “hub” species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

The intestinal microbiota is known to regulate host energy homeostasis and can be influenced by high-calorie diets. However, changes affecting the ecosystem at the functional level are still not well characterized. We measured shifts in cecal bacterial communities in mice fed a carbohydrate or high-fat (HF) diet for 12 weeks at the level of the following: (i) diversity and taxa distribution by high-throughput 16S ribosomal RNA gene sequencing; (ii) bulk and single-cell chemical composition by Fourier-transform infrared- (FT-IR) and Raman micro-spectroscopy and (iii) metaproteome and metabolome via high-resolution mass spectrometry. High-fat diet caused shifts in the diversity of dominant gut bacteria and altered the proportion of Ruminococcaceae (decrease) and Rikenellaceae (increase). FT-IR spectroscopy revealed that the impact of the diet on cecal chemical fingerprints is greater than the impact of microbiota composition. Diet-driven changes in biochemical fingerprints of members of the Bacteroidales and Lachnospiraceae were also observed at the level of single cells, indicating that there were distinct differences in cellular composition of dominant phylotypes under different diets. Metaproteome and metabolome analyses based on the occurrence of 1760 bacterial proteins and 86 annotated metabolites revealed distinct HF diet-specific profiles. Alteration of hormonal and anti-microbial networks, bile acid and bilirubin metabolism and shifts towards amino acid and simple sugars metabolism were observed. We conclude that a HF diet markedly affects the gut bacterial ecosystem at the functional level.

“Barcode-tagged” PCR primers used for multiplex amplicon sequencing generate a thus-far-overlooked amplification bias that produces variable terminal restriction fragment length polymorphism (T-RFLP) and pyrosequencing data from the same environmental DNA template. We propose a simple two-step PCR approach that increases reproducibility and consistently recovers higher genetic diversity in pyrosequencing libraries.

Significance: Measuring activity patterns of microbes in their natural environment is essential for understanding ecosystems and the multifaceted interactions of microorganisms with eukaryotes. In this study, we developed a technique that allows fast and nondestructive activity measurements of microbial communities on a single-cell level. Microbial communities were amended with heavy water (D ₂ O), a treatment that does not change the available substrate pool. After incubation, physiologically active cells are rapidly identified with Raman microspectroscopy by measuring cellular D incorporation. Using this approach, we characterized the activity patterns of two dominant microbes in mouse cecum samples amended with different carbohydrates and discovered previously unidentified bacteria stimulated by mucin and/or glucosamine by combining Raman microspectroscopy and optical tweezer-based sorting.

Summary: The composition and function of the mammalian gut microbiota has been the subject of much research in recent years, but the principles underlying the assembly and structure of this complex community remain incompletely understood. Processes that shape the gut microbiota are thought to be mostly niche‐driven, with environmental factors such as the composition of available nutrients largely determining whether or not an organism can establish. The concept that the nutrient landscape dictates which organisms can successfully colonize and persist in the gut was first proposed in Rolf Freter's nutrient niche theory. In a situation where nutrients are perfectly mixed and there is balanced microbial growth, Freter postulated that an organism can only survive if it is able to utilize one or a few limiting nutrients more efficiently than its competitors. Recent experimental work indicates, however, that nutrients in the gut vary in space and time. We propose that in such a scenario, Freter's nutrient niche theory must be expanded to account for the co‐existence of microorganisms utilizing the same nutrients but in distinct sites or at different times, and that metabolic flexibility and mixed‐substrate utilization are common strategies for survival in the face of ever‐present nutrient fluctuations.