The colonization process of the infant gut microbiome has been called chaotic, but this view could reflect insufficient documentation of the factors affecting the microbiome. We performed a 2.5-y case study of the assembly of the human infant gut microbiome, to relate life events to microbiome composition and function. Sixty fecal samples were collected from a healthy infant along with a diary of diet and health status. Analysis of >300,000 16S rRNA genes indicated that the phylogenetic diversity of the microbiome increased gradually over time and that changes in community composition conformed to a smooth temporal gradient. In contrast, major taxonomic groups showed abrupt shifts in abundance corresponding to changes in diet or health. Community assembly was nonrandom: we observed discrete steps of bacterial succession punctuated by life events. Furthermore, analysis of ≈500,000 DNA metagenomic reads from 12 fecal samples revealed that the earliest microbiome was enriched in genes facilitating lactate utilization, and that functional genes involved in plant polysaccharide metabolism were present before the introduction of solid food, priming the infant gut for an adult diet. However, ingestion of table foods caused a sustained increase in the abundance of Bacteroidetes, elevated fecal short chain fatty acid levels, enrichment of genes associated with carbohydrate utilization, vitamin biosynthesis, and xenobiotic degradation, and a more stable community composition, all of which are characteristic of the adult microbiome. This study revealed that seemingly chaotic shifts in the microbiome are associated with life events; however, additional experiments ought to be conducted to assess how different infants respond to similar life events.

Anaerobic digestion is the most successful bioenergy technology worldwide with, at its core, undefined microbial communities that have poorly understood dynamics. Here, we investigated the relationships of bacterial community structure (>400,000 16S rRNA gene sequences for 112 samples) with function (i.e., bioreactor performance) and environment (i.e., operating conditions) in a yearlong monthly time series of nine full-scale bioreactor facilities treating brewery wastewater (>20,000 measurements). Each of the nine facilities had a unique community structure with an unprecedented level of stability. Using machine learning, we identified a small subset of operational taxonomic units (OTUs; 145 out of 4,962), which predicted the location of the facility of origin for almost every sample (96.4% accuracy). Of these 145 OTUs, syntrophic bacteria were systematically overrepresented, demonstrating that syntrophs rebounded following disturbances. This indicates that resilience, rather than dynamic competition, played an important role in maintaining the necessary syntrophic populations. In addition, we explained the observed phylogenetic differences between all samples on the basis of a subset of environmental gradients (using constrained ordination) and found stronger relationships between community structure and its function rather than its environment. These relationships were strongest for two performance variables-methanogenic activity and substrate removal efficiency-both of which were also affected by microbial ecology because these variables were correlated with community evenness (at any given time) and variability in phylogenetic structure (over time), respectively. Thus, we quantified relationships between community structure and function, which opens the door to engineer communities with superior functions.T he production of bioenergy from wastes is an essential component in the global development of sustainable energy sources (1). Anaerobic digestion, which is the most prominent bioenergy technology worldwide, uses undefined microbial cultures to produce methane from organic substrates (2). Methanogenic bioreactors are maintained on the basis of decades of observed relationships between performance and operating parameters. However, differences underlying bioreactors that perform well and bioreactors that perform inadequately are often poorly understood (3). This has led to a general perception that methanogenic bioreactors are unreliable or unstable, inhibiting their wider adoption for bioenergy production (2). A deeper analysis of the structure and dynamics of bioreactor microbial communities as a function of performance and operating conditions has the potential to reveal important and unappreciated structure-function relationships.The efficient and stable operation of methanogenic bioreactors relies on syntrophic relationships among a community of microbes, including fermenting bacteria, specialized acidogenic and acetogenic syntrophs, and methanogenic archaea (4), with diverse and parallel pathways for...

The microbial communities from three upflow anaerobic bioreactors treating purified terephthalic acid (PTA) wastewater were characterized with 16S ribosomal RNA gene sequencing surveys. Universal bacterial and archaeal primers were used to compare the bioreactor communities to each other. A total of 1,733 bacterial sequences and 383 archaeal sequences were characterized. The high number of Syntrophus spp. and Pelotomaculum spp. found within these reactors indicates efficient removal of benzoate and terephthalate. Under anaerobic conditions benzoate can be degraded through syntrophic associations between these bacteria and hydrogen-scavenging microbes, such as Desulfovibrio spp. and hydrogenotrophic methanogens, which remove H(2) to force the thermodynamically unfavourable reactions to take place. The authors did not observe a relatively high percentage of hydrogenotrophic methanogens with the archaeal gene survey because of a high acetate flux (acetate is a main component in PTA wastewater and is the main degradation product of terephthalate/benzoate fermentation), and because of the presence of Desulfovibrio spp. (a sulfate reducer that scavenges hydrogen). The high acetate flux also explains the high percentage of acetoclastic methanogens from the genus Methanosaeta among the archaeal sequences. A group of uncultured bacteria (OD1) may be involved in the degradation of p-toluate (4-methyl benzoate), which is a component of PTA wastewater.

Bacterioplankton assemblages play crucial ecosystem roles in diverse aquatic habitats. Areas in which 2 distinct aquatic bodies converge provide insight into how bacterial communities respond to dramatic environmental change and assemblage confluence. The tolerance and success of combined assemblage components to mixed conditions, however, is unclear. To address this, freshwater (FW) and seawater (SW) were combined in ratios of entirely SW, 1:10, 1:1, 10:1 and entirely FW in experimental mesocosms on Appledore Island, Gulf of Maine (Shoals Marine Laboratory), to examine the response of microbial abundance and composition to habitat convergence. The relative proportion of operational taxonomic units (OTUs) that increased in each incubation demonstrated that SW OTUs were more capable of success in FW habitats than FW OTUs in SW habitats. Most OTUs from each source that grew under confluent conditions were initially rare (<1% of the total fingerprint amplified fluorescence) in the incubations. These data demonstrate that rarer OTUs may be more responsive to environmental change than abundant OTUs. These data ultimately indicate that habitat confluence imparts changes in microbial assemblages and that mixing zones within areas of habitat confluence (e.g. estuaries and intertidal rock pools) select for new assemblages composed of OTUs that may be adapted to mixed conditions and that are at low abundance in source populations.