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Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/. The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community.

Recent studies have provided an unprecedented view of the microbial communities colonizing captive mice; yet the host and environmental factors that shape the rodent gut microbiota in their natural habitat remain largely unexplored. Here, we present results from a 2-year 16 S ribosomal RNA gene sequencing-based survey of wild wood mice (Apodemus sylvaticus) in two nearby woodlands. Similar to other mammals, wild mice were colonized by 10 bacterial phyla and dominated by the Firmicutes, Bacteroidetes and Proteobacteria. Within the Firmicutes, the Lactobacillus genus was most abundant. Putative bacterial pathogens were widespread and often abundant members of the wild mouse gut microbiota. Among a suite of extrinsic (environmental) and intrinsic (host-related) factors examined, seasonal changes dominated in driving qualitative and quantitative differences in the gut microbiota. In both years examined, we observed a strong seasonal shift in gut microbial community structure, potentially due to the transition from an insect- to a seed-based diet. This involved decreased levels of Lactobacillus, and increased levels of Alistipes (Bacteroidetes phylum) and Helicobacter. We also detected more subtle but statistically significant associations between the gut microbiota and biogeography, sex, reproductive status and co-colonization with enteric nematodes. These results suggest that environmental factors have a major role in shaping temporal variations in microbial community structure within natural populations.

Systemic infection induces conserved physiological responses that include both resistance and 'tolerance of infection' mechanisms. Temporary anorexia associated with an infection is often beneficial, reallocating energy from food foraging towards resistance to infection or depriving pathogens of nutrients. However, it imposes a stress on intestinal commensals, as they also experience reduced substrate availability; this affects host fitness owing to the loss of caloric intake and colonization resistance (protection from additional infections). We hypothesized that the host might utilize internal resources to support the gut microbiota during the acute phase of the disease. Here we show that systemic exposure to Toll-like receptor (TLR) ligands causes rapid α(1,2)-fucosylation of small intestine epithelial cells (IECs) in mice, which requires the sensing of TLR agonists, as well as the production of interleukin (IL)-23 by dendritic cells, activation of innate lymphoid cells and expression of fucosyltransferase 2 (Fut2) by IL-22-stimulated IECs. Fucosylated proteins are shed into the lumen and fucose is liberated and metabolized by the gut microbiota, as shown by reporter bacteria and community-wide analysis of microbial gene expression. Fucose affects the expression of microbial metabolic pathways and reduces the expression of bacterial virulence genes. It also improves host tolerance of the mild pathogen Citrobacter rodentium. Thus, rapid IEC fucosylation appears to be a protective mechanism that utilizes the host's resources to maintain host-microbial interactions during pathogen-induced stress.

Long-term dietary intake influences the structure and activity of the trillions of microorganisms residing in the human gut, but it remains unclear how rapidly and reproducibly the human gut microbiome responds to short-term macronutrient change. Here we show that the short-term consumption of diets composed entirely of animal or plant products alters microbial community structure and overwhelms inter-individual differences in microbial gene expression. The animal-based diet increased the abundance of bile-tolerant microorganisms (Alistipes, Bilophila and Bacteroides) and decreased the levels of Firmicutes that metabolize dietary plant polysaccharides (Roseburia, Eubacterium rectale and Ruminococcus bromii). Microbial activity mirrored differences between herbivorous and carnivorous mammals, reflecting trade-offs between carbohydrate and protein fermentation. Foodborne microbes from both diets transiently colonized the gut, including bacteria, fungi and even viruses. Finally, increases in the abundance and activity of Bilophila wadsworthia on the animal-based diet support a link between dietary fat, bile acids and the outgrowth of microorganisms capable of triggering inflammatory bowel disease. In concert, these results demonstrate that the gut microbiome can rapidly respond to altered diet, potentially facilitating the diversity of human dietary lifestyles.

Humans are home to complex microbial communities, whose aggregate genomes and their encoded metabolic activities are referred to as the human microbiome. Recently, researchers have begun to appreciate that different human body habitats and the activities of their resident microorganisms can be better understood in ecological terms, as a range of spatial scales encompassing single cells, guilds of microorganisms responsive to a similar substrate, microbial communities, body habitats, and host populations. However, the bulk of the work to date has focused on studies of culturable microorganisms in isolation or on DNA sequencing-based surveys of microbial diversity in small-to-moderate-sized cohorts of individuals. Here, we discuss recent work that highlights the potential for assessing the human microbiome at a range of spatial scales, and for developing novel techniques that bridge multiple levels: for example, through the combination of single-cell methods and metagenomic sequencing. These studies promise to not only provide a much-needed epidemiological and ecological context for mechanistic studies of culturable and genetically tractable microorganisms, but may also lead to the discovery of fundamental rules that govern the assembly and function of host-associated microbial communities.

Individuals who are minoritized as a result of race, sexual identity, gender, or socioeconomic status experience a higher prevalence of many diseases. Understanding the biological processes that cause and maintain these socially driven health inequities is essential for addressing them. The gut microbiome is strongly shaped by host environments and affects host metabolic, immune, and neuroendocrine functions, making it an important pathway by which differences in experiences caused by social, political, and economic forces could contribute to health inequities. Nevertheless, few studies have directly integrated the gut microbiome into investigations of health inequities. Here, we argue that accounting for host-gut microbe interactions will improve understanding and management of health inequities, and that health policy must begin to consider the microbiome as an important pathway linking environments to population health. [ABSTRACT FROM AUTHOR]

The first error is a duplication of the Mitomycin C and Norfloxacin panels, which took place during the figure layout process in Power Point. In this case, the Ampicillin plot is correct, but the Mitomycin C and Norfloxacin are duplications of the Ampicillin treatment. The published Mitomycin C column is the correct one, whereas the published Norfloxacin column was a duplicated version of Mitomycin C. The second mistake is also a duplication concerning the Normalized read coverage profiles for prophage 2 in the Mitomycin C, Norfloxacin, and Ampicillin treatments. [Extracted from the article]