Profiling the 16S-rRNA gene is a common method in microbial ecology to provide estimates of microbial diversity and abundance, but it cannot directly produce information about the functional potential of these taxa. While shotgun sequencing can provide functional information, the cost can be prohibitive for large scale comparative studies. Functional prediction tools have been developed to generate expected gene counts from 16S-rRNA amplicon data and allow for initial exploration of hypotheses prior to shotgun sequencing. PICRUSt2 and Tax4Fun2 are two such prediction tools that are becoming increasingly popular in microbial ecology studies. However, there are only a few benchmarking studies that have tested their performance, and none that focused on soils. The goal of the present study was to compare the performance of both prediction tools with each other and shotgun sequencing. We assessed prediction output from both tools used on the same samples from two sites in Southwest Florida and compared the predicted functional profiles with MG-RAST functional profiles on a shotgun-sequenced subset of samples. Shotgun and amplicon sequencing datasets showed comparable 16S rRNA gene profiles with observed differences likely stemming from PCR bias and taxa-dependent variability of 16S rRNA gene density in shotgun sequences. PICRUSt2 functional profiles represented greater relative abundances of genes in the pathway for oxidative phosphorylation, while Tax4Fun2 detected more genes from specialized metabolic pathways, such as for methane metabolism. PICRUSt2 functional profiles showed somewhat stronger correlations with shotgun-sequenced functional profiles than Tax4Fun2. However, both prediction tools significantly underestimated gene frequencies in many KEGG categories, including genes with biogeochemical significance for soil carbon- and nitrogen cycling.

Using human fecal samples and including sequencing for both bacterial and fungal taxa, this study compared the conventional antibiotics used to treat C. difficile infection (CDI) from the perspective of the microbiome, which is particularly relevant, given the relationship between dysbiotic states and the development of CDI. Sequencing and imputed functional analyses suggest that C. difficile -directed antibiotics are associated with distinct forms of dysbiosis that may be influential in the course of CDI. Further, a role for fungal organisms in the perpetuation of the causal dysbiosis of CDI is discussed, suggesting a previously unappreciated, clinically relevant transkingdom interaction that warrants further study.

Here we characterize and compare the diversity of belowground fungal communities of maples (Sapindaceae: Acer) varying in both nativity and weediness, and interpret our findings in the context of multiple non-exclusive theories on tree invasions and fungal associations. We made our fungal community comparisons based on high-throughput Illumina sequencing of the internal transcribed spacer region of fungal ribosomal DNA of soil samples associated with the roots of different species of maple collected from six sites throughout Central Pennsylvania. In our system, we found that weedy species, regardless of nativity, had the greatest soil fungal richness and that the nonnative invasive Norway maple had the highest abundance of mycorrhizal mutualists. Despite that much of the fungal community variability in our system was attributable to inter-site variability, we found that the core fungal communities associated with nonnative tree species were an inclusively larger set that included nearly all of those associated with native trees in addition to many not found with the natives, and the core communities of non-weedy species were largely a subset of those associated with weedy maples. In addition to confirming the strong influence that site variation has on soil fungal communities, our findings are also largely consistent with positive feedback from native fungal communities, possible co-invasion by fungal associates that are only associated with the nonnative trees, and generally add to the growing number of studies that have observed a greater abundance of mutualists associated with invasive trees that interact with arbuscular mycorrhizal fungi.

This study sought to characterize the bacterial and fungal microbiota changes associated with Clostridium difficile infection (CDI) among inpatients with diarrhea, in order to further explain the pathogenesis of this infection as well as to potentially guide new CDI therapies. Twenty-four inpatients with diarrhea were enrolled, 12 of whom had CDI. Each patient underwent stool testing for CDI prior to being treated with difficile-directed antibiotics, when appropriate. Clinical data was obtained from the medical record, while each stool sample underwent 16S rRNA and ITS sequencing for bacterial and fungal elements. An analysis of microbial community structures distinct to the CDI population was also performed. The results demonstrated no difference between the CDI and non-CDI cohorts with respect to any previously reported CDI risk factors. Butyrogenic bacteria were enriched in both CDI and non-CDI patients. A previously unreported finding of increased numbers of Akkermansia muciniphila in CDI patients was observed, an organism which degrades mucin and which therefore may provide a selective advantage toward CDI. Fungal elements of the genus Penicillium were predominant in CDI; these organisms produce antibacterial chemicals which may resist recovery of healthy microbiota. The most frequent CDI microbial community networks involved Peptostreptococcaceae and Enterococcus, with decreased population density of Bacteroides. These results suggest that the development of CDI is associated with microbiota changes which are consistently associated with CDI in human subjects. These gut taxa contribute to the intestinal dysbiosis associated with C. difficile infection.

Diverticular disease is commonly associated with the older population in the United States. As individual’s age, diverticulae, or herniation of the mucosa through the colonic wall, develop. In 10–25% of individuals, the diverticulae become inflamed, resulting in diverticulitis. The gut ecosystem relies on the interaction of bacteria and fungi to maintain homeostasis. Although bacterial dysbiosis has been implicated in the pathogenesis of diverticulitis, associations between the microbial ecosystem and diverticulitis remain largely unstudied. This study investigated how the cooperative network of bacteria and fungi differ between a diseased area of the sigmoid colon chronically affected by diverticulitis and adjacent non-affected tissue. To identify mucosa-associated microbes, bacterial 16S rRNA and fungal ITS sequencing were performed on chronically diseased sigmoid colon tissue (DT) and adjacent tissue (AT) from the same colonic segment. We found that Pseudomonas and Basidiomycota OTUs were associated with AT while Microbacteriaceae and Ascomycota were enriched in DT. Bipartite co-occurrence networks were constructed for each tissue type. The DT and AT networks were distinct for each tissue type, with no microbial relationships maintained after intersection merge of the groups. Our findings indicate that the microbial ecosystem distinguishes chronically diseased tissue from adjacent tissue.

ABSTRACT Bacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter- and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in which Betaproteobacteria and Gammaproteobacteria decreased in 16S rRNA gene relative abundance, while the relative abundance of members of the Firmicutes increased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains of Legionella , Campylobacter , Arcobacter , and Helicobacter , as well as bacteria of fecal origin (e.g., Bacteroides ), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event. IMPORTANCE In order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study investigated the bacterial communities during and after Superstorm Sandy to provide fine time point resolution of dynamic changes in bacterial composition. This study adds to the current literature by revealing the variation in bacterial community structure during the course of a storm. This study employed high-throughput DNA sequencing, which generated a deep analysis of inter- and intracommunity responses during a significant storm event. This study has highlighted the utility of applying high-throughput sequencing for water quality monitoring purposes, as this approach enabled a more comprehensive investigation of the bacterial community structure. Altogether, these data suggest a drastic restructuring of the stream bacterial community during a storm event and highlight the potential of high-throughput sequencing approaches for assessing the microbiological quality of our environment.