MicroNiche: an R package for assessing microbial niche breadth and overlap from amplicon sequencing data.

Niche is a fundamental concept in ecology. It integrates the sum of biotic and abiotic environmental requirements that determines a taxon's distribution. Microbiologists currently lack quantitative approaches to address niche-related hypotheses. We tested four approaches for the quantification of niche breadth and overlap of taxa in amplicon sequencing datasets, with the goal of determining generalists, specialists and environmental-dependent distributions of community members. We applied these indices to in silico training datasets first, and then to real human gut and desert biological soil crust (biocrust) case studies, assessing the agreement of the indices with previous findings. Implementation of each approach successfully identified a priori conditions within in silico training data, and we found that by including a limit of quantification based on species rank, one could identify taxa falsely classified as specialists because of their low, sparse counts. Analysis of the human gut study offered quantitative support for Bacilli, Gammaproteobacteria and Fusobacteria specialists enriched after bariatric surgery. We could quantitatively characterise differential niche distributions of cyanobacterial taxa with respect to precipitation gradients in biocrusts. We conclude that these approaches, made publicly available as an R package (MicroNiche), represent useful tools to assess microbial environment-taxon and taxon-taxon relationships in a quantitative manner.

Insights into Butyrate Production in a Controlled Fermentation System via Gene Predictions.

Butyrate is a common fatty acid produced in important fermentative systems, such as the human/animal gut and other H2 production systems. Despite its importance, there is little information on the partnerships between butyrate producers and other bacteria. The objective of this work was to uncover butyrate-producing microbial communities and possible metabolic routes in a controlled fermentation system aimed at butyrate production. The butyrogenic reactor was operated at 37°C and pH 5.5 with a hydraulic retention time of 31 h and a low hydrogen partial pressure (PH2). High-throughput sequencing and metagenome functional prediction from 16S rRNA data showed that butyrate production pathways and microbial communities were different during batch (closed) and continuous-mode operation. Lactobacillaceae, Lachnospiraceae, and Enterococcaceae were the most abundant phylotypes in the closed system without PH2 control, whereas Prevotellaceae, Ruminococcaceae, and Actinomycetaceae were the most abundant phylotypes under continuous operation at low PH2. Putative butyrate producers identified in our system were from Prevotellaceae, Clostridiaceae, Ruminococcaceae, and Lactobacillaceae. Metagenome prediction analysis suggests that nonbutyrogenic microorganisms influenced butyrate production by generating butyrate precursors such as acetate, lactate, and succinate. 16S rRNA gene analysis suggested that, in the reactor, a partnership between identified butyrogenic microorganisms and succinate (i.e., Actinomycetaceae), acetate (i.e., Ruminococcaceae and Actinomycetaceae), and lactate producers (i.e., Ruminococcaceae and Lactobacillaceae) took place under continuous-flow operation at low PH2. IMPORTANCE This study demonstrates how bioinformatics tools, such as metagenome functional prediction from 16S rRNA genes, can help understand biological systems and reveal microbial interactions in controlled systems (e.g., bioreactors). Results obtained from controlled systems are easier to interpret than those from human/animal studies because observed changes may be specifically attributed to the design conditions imposed on the system. Bioinformatics analysis allowed us to identify potential butyrogenic phylotypes and associated butyrate metabolism pathways when we systematically varied the PH2 in a carefully controlled fermentation system. Our insights may be adapted to butyrate production studies in biohydrogen systems and gut models, since butyrate is a main product and a crucial fatty acid in human/animal colon health.

Dissipation of atrazine, enrofloxacin, and sulfamethazine in wood chip bioreactors and impact on denitrification.

Wood chip bioreactors are receiving increasing attention as a means of reducing nitrate in subsurface tile drainage systems. Agrochemicals in tile drainage water entering wood chip bioreactors can be retained or degraded and may affect denitrification. The degradation of 5 mg L atrazine, enrofloxacin, and sulfamethazine under denitrifying conditions in wood chips from an in situ reactor was determined. The impact of these chemicals on denitrifying microorganisms was assessed using the denitrification potential assay, most probable number (MPN), and quantitative polymerase chain reaction targeting the gene of the denitrifiers. Initial half-lives for these chemicals in the aqueous phase were 0.98 d for atrazine, 0.17 d for enrofloxacin, and 6.2 d for sulfamethazine. Similar rates of disappearance in autoclaved and nonautoclaved wood chip solutions during the first 48 h suggested sorption was the dominant mechanism. The presence of atrazine did not impair denitrification potential, the MPN, or the copy number. The denitrifier MPN and copy number in sulfamethazine- and enrofloxacin-treated microcosms were less than the control within the first 5 d after chemical addition, whereas the denitrification potentials were not affected. However, after 45 d the denitrification rate, MPN and gene copy numbers for sulfamethazine and enrofloxacin were similar to that of the no-chemical control, indicating that acclimation of the denitrifier population to the antibiotic or reduced bioavailability over time allowed recovery of the denitrifier population.