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The gut microbiome is at the center of inflammatory bowel disease (IBD) pathogenesis and disease activity. While this has mainly been studied in the context of the bacterial microbiome, recent advances have provided tools for the study of host genetics and metagenomics of host-fungal interaction. Through these tools, strong evidence has emerged linking certain fungal taxa, such as Candida and Malassezia, with cellular and molecular pathways of IBD disease biology. Mouse models and human fecal microbial transplant also suggest that some disease-participatory bacteria and fungi may act not via the host directly, but via their fungal-bacterial ecologic interactions. We hope that these insights, and the study design and multi-omics strategies used to develop them, will facilitate the inclusion of the fungal community in basic and translational IBD research.

In a cohort of BNT162b2 (Pfizer–BioNTech) mRNA vaccine recipients ( n  = 1,090), we observed that spike-specific IgG antibody levels and ACE2 antibody binding inhibition responses elicited by a single vaccine dose in individuals with prior SARS-CoV-2 infection ( n  = 35) were similar to those seen after two doses of vaccine in individuals without prior infection ( n  = 228). Post-vaccine symptoms were more prominent for those with prior infection after the first dose, but symptomology was similar between groups after the second dose. Virus-specific antibody levels after a single dose of the BNT162b2 vaccine in individuals previously infected with SARS-CoV-2 are similar to levels after two doses of the vaccine in infection-naive individuals.

Inflammatory bowel diseases, which include Crohn’s disease and ulcerative colitis, affect several million individuals worldwide. Crohn’s disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study’s infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi’omics Database ( http://ibdmdb.org ), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases. The Inflammatory Bowel Disease Multi’omics Database includes longitudinal data encompassing a multitude of analyses of stool, blood and biopsies of more than 100 individuals, and provides a comprehensive description of host and microbial activities in inflammatory bowel diseases.

The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community. Microbial communities are commonly studied using culture-independent methods, such as 16S rRNA gene sequencing. However, one challenge in accurately characterizing microbial communities is exogenous bacterial DNA contamination, particularly in low-microbial-biomass niches. Computational approaches to identify contaminant sequences have been proposed, but their performance has not been independently evaluated. To identify the impact of decreasing microbial biomass on polymicrobial 16S rRNA gene sequencing experiments, we created a mock microbial community dilution series. We evaluated four computational approaches to identify and remove contaminants, as follows: (i) filtering sequences present in a negative control, (ii) filtering sequences based on relative abundance, (iii) identifying sequences that have an inverse correlation with DNA concentration implemented in Decontam, and (iv) predicting the sequence proportion arising from defined contaminant sources implemented in SourceTracker. As expected, the proportion of contaminant bacterial DNA increased with decreasing starting microbial biomass, with 80.1% of the most diluted sample arising from contaminant sequences. Inclusion of contaminant sequences led to overinflated diversity estimates and distorted microbiome composition. All methods for contaminant identification successfully identified some contaminant sequences, which varied depending on the method parameters used and contaminant prevalence. Notably, removing sequences present in a negative control erroneously removed >20% of expected sequences. SourceTracker successfully removed over 98% of contaminants when the experimental environments were well defined. However, SourceTracker misclassified expected sequences and performed poorly when the experimental environment was unknown, failing to remove >97% of contaminants. In contrast, the Decontam frequency method did not remove expected sequences and successfully removed 70 to 90% of the contaminants. IMPORTANCE The relative scarcity of microbes in low-microbial-biomass environments makes accurate determination of community composition challenging. Identifying and controlling for contaminant bacterial DNA are critical steps in understanding microbial communities from these low-biomass environments. Our study introduces the use of a mock community dilution series as a positive control and evaluates four computational strategies that can identify contaminants in 16S rRNA gene sequencing experiments in order to remove them from downstream analyses. The appropriate computational approach for removing contaminant sequences from an experiment depends on prior knowledge about the microbial environment under investigation and can be evaluated with a dilution series of a mock microbial community.

Plasmacytoid dendritic cells (pDC) are a specialized sensor of viral and bacterial nucleic acids and a major producer of IFN-α that promotes host defense by priming both innate and acquired immune responses. Although synthetic Toll-like receptor (TLR) ligands, pathogenic bacteria and viruses activate pDC, there is limited investigation of non-pathogenic microbiota that are in wide industrial dietary use, such as lactic acid bacteria (LAB). In this study, we screened for LAB strains, which induce pDC activation and IFN-α production using murine bone marrow (BM)-derived Flt-3L induced dendritic cell culture. Microbial strains with such activity on pDC were absent in a diversity of bacillary strains, but were observed in certain spherical species (Lactococcus, Leuconostoc, Streptococcus and Pediococcus), which was correlated with their capacity for uptake by pDC. Detailed study of Lactococcus lactis subsp. lactis JCM5805 and JCM20101 revealed that the major type I and type III interferons were induced (IFN-α, -β, and λ). IFN-α induction was TLR9 and MyD88-dependent; a slight impairment was also observed in TLR4(-/-) cells. While these responses occurred with purified pDC, IFN-α production was synergistic upon co-culture with myeloid dendritic cells (mDC), an interaction that required direct mDC-pDC contact. L. lactis strains also stimulated expression of immunoregulatory receptors on pDC (ICOS-L and PD-L1), and accordingly augmented pDC induction of CD4(+)CD25(+)FoxP3(+) Treg compared to the Lactobacillus strain. Oral administration of L. lactis JCM5805 induced significant activation of pDC resident in the intestinal draining mesenteric lymph nodes, but not in a remote lymphoid site (spleen). Taken together, certain non-pathogenic spherical LAB in wide dietary use has potent and diverse immunomodulatory effects on pDC potentially relevant to anti-viral immunity and chronic inflammatory disease.

Inflammatory bowel disease (IBD) is a group of chronic diseases of the digestive tract that affects millions of people worldwide. Genetic, environmental and microbial factors have been implicated in the onset and exacerbation of IBD. However, the mechanisms associating gut microbial dysbioses and aberrant immune responses remain largely unknown. The integrative Human Microbiome Project seeks to close these gaps by examining the dynamics of microbiome functionality in disease by profiling the gut microbiomes of >100 individuals sampled over a 1-year period. Here, we present the first results based on 78 paired faecal metagenomes and metatranscriptomes, and 222 additional metagenomes from 59 patients with Crohn’s disease, 34 with ulcerative colitis and 24 non-IBD control patients. We demonstrate several cases in which measures of microbial gene expression in the inflamed gut can be informative relative to metagenomic profiles of functional potential. First, although many microbial organisms exhibited concordant DNA and RNA abundances, we also detected species-specific biases in transcriptional activity, revealing predominant transcription of pathways by individual microorganisms per host (for example, by Faecalibacterium prausnitzii ). Thus, a loss of these organisms in disease may have more far-reaching consequences than suggested by their genomic abundances. Furthermore, we identified organisms that were metagenomically abundant but inactive or dormant in the gut with little or no expression (for example, Dialister invisus ). Last, certain disease-specific microbial characteristics were more pronounced or only detectable at the transcript level, such as pathways that were predominantly expressed by different organisms in patients with IBD (for example, Bacteroides vulgatus and Alistipes putredinis ). This provides potential insights into gut microbial pathway transcription that can vary over time, inducing phenotypical changes that are complementary to those linked to metagenomic abundances. The study’s results highlight the strength of analysing both the activity and the presence of gut microorganisms to provide insight into the role of the microbiome in IBD. Analysis of paired metagenomes and metatranscriptomes associated with patients with inflammatory bowel disease (IBD) and non-IBD controls over time provides some insights into microbial community variation and potential pathways influencing IBD symptoms.

Background Pronounced sex differences in the susceptibility and response to SARS-CoV-2 infection remain poorly understood. Emerging evidence has highlighted the potential importance of autoimmune activation in modulating the acute response and recovery trajectories following SARS-CoV-2 exposure. Given that immune-inflammatory activity can be sex-biased in the setting of severe COVID-19 illness, the aim of the study was to examine sex-specific autoimmune reactivity to SARS-CoV-2 in the absence of extreme clinical disease. Methods In this study, we assessed autoantibody (AAB) reactivity to 91 autoantigens previously linked to a range of classic autoimmune diseases in a cohort of 177 participants (65% women, 35% men, mean age of 35) with confirmed evidence of prior SARS-CoV-2 infection based on presence of antibody to the nucleocapsid protein of SARS-CoV-2. Data were compared to 53 pre-pandemic healthy controls (49% women, 51% men). For each participant, socio-demographic data, serological analyses, SARS-CoV-2 infection status and COVID-19 related symptoms were collected by  an electronic survey of questions. The symptoms burden score was constructed based on the total number of reported symptoms (N = 21) experienced within 6 months prior to the blood draw, wherein a greater number of symptoms corresponded to a higher score and assigned as more severe burden. Results In multivariable analyses, we observed sex-specific patterns of autoreactivity associated with the presence or absence (as well as timing and clustering of symptoms) associated with prior COVID-19 illness. Whereas the overall AAB response was more prominent in women following asymptomatic infection, the breadth and extent of AAB reactivity was more prominent in men following at least mildly symptomatic infection. Notably, the observed reactivity included distinct antigens with molecular homology with SARS-CoV-2. Conclusion Our results reveal that prior SARS-CoV-2 infection, even in the absence of severe clinical disease, can lead to a broad AAB response that exhibits sex-specific patterns of prevalence and antigen selectivity. Further understanding of the nature of triggered AAB activation among men and women exposed to SARS-CoV-2 will be essential for developing effective interventions against immune-mediated sequelae of COVID-19.

Abnormalities of the intestinal microbiota are implicated in the pathogenesis of Crohn's disease (CD) and ulcerative colitis (UC), two spectra of inflammatory bowel disease (IBD). However, the high complexity and low inter-individual overlap of intestinal microbial composition are formidable barriers to identifying microbial taxa representing this dysbiosis. These difficulties might be overcome by an ecologic analytic strategy to identify modules of interacting bacteria (rather than individual bacteria) as quantitative reproducible features of microbial composition in normal and IBD mucosa. We sequenced 16S ribosomal RNA genes from 179 endoscopic lavage samples from different intestinal regions in 64 subjects (32 controls, 16 CD and 16 UC patients in clinical remission). CD and UC patients showed a reduction in phylogenetic diversity and shifts in microbial composition, comparable to previous studies using conventional mucosal biopsies. Analysis of weighted co-occurrence network revealed 5 microbial modules. These modules were unprecedented, as they were detectable in all individuals, and their composition and abundance was recapitulated in an independent, biopsy-based mucosal dataset 2 modules were associated with healthy, CD, or UC disease states. Imputed metagenome analysis indicated that these modules displayed distinct metabolic functionality, specifically the enrichment of oxidative response and glycan metabolism pathways relevant to host-pathogen interaction in the disease-associated modules. The highly preserved microbial modules accurately classified IBD status of individual patients during disease quiescence, suggesting that microbial dysbiosis in IBD may be an underlying disorder independent of disease activity. Microbial modules thus provide an integrative view of microbial ecology relevant to IBD.

Metagenomic sequencing has greatly enhanced the discovery of viral genomic sequences; however, it remains challenging to identify the host(s) of these new viruses. We developed VirHostMatcher-Net, a flexible, network-based, Markov random field framework for predicting virus–prokaryote interactions using multiple, integrated features: CRISPR sequences and alignment-free similarity measures ($s_2^*$ and WIsH). Evaluation of this method on a benchmark set of 1462 known virus–prokaryote pairs yielded host prediction accuracy of 59% and 86% at the genus and phylum levels, representing 16–27% and 6–10% improvement, respectively, over previous single-feature prediction approaches. We applied our host prediction tool to crAssphage, a human gut phage, and two metagenomic virus datasets: marine viruses and viral contigs recovered from globally distributed, diverse habitats. Host predictions were frequently consistent with those of previous studies, but more importantly, this new tool made many more confident predictions than previous tools, up to nearly 3-fold more (n > 27 000), greatly expanding the diversity of known virus–host interactions.

Mucin-type O-linked oligosaccharides (O-glycans) are primary components of the intestinal mucins that form the mucus gel layer overlying the gut epithelium. Impaired expression of intestinal O-glycans has been observed in patients with ulcerative colitis (UC), but its role in the etiology of this disease is unknown. Here, we report that mice with intestinal epithelial cell-specific deficiency of core 1-derived O-glycans, the predominant form of O-glycans, developed spontaneous colitis that resembled human UC, including massive myeloid infiltrates and crypt abscesses. The colitis manifested in these mice was also characterized by TNF-producing myeloid infiltrates in colon mucosa in the absence of lymphocytes, supporting an essential role for myeloid cells in colitis initiation. Furthermore, induced deletion of intestinal core 1-derived O-glycans caused spontaneous colitis in adult mice. These data indicate a causal role for the loss of core 1-derived O-glycans in colitis. Finally, we detected a biosynthetic intermediate typically exposed in the absence of core 1 O-glycan, Tn antigen, in the colon epithelium of a subset of UC patients. Somatic mutations in the X-linked gene that encodes core 1 β1,3-galactosyltransferase-specific chaperone 1 (C1GALT1C1, also known as Cosmc), which is essential for core 1 O-glycosylation, were found in Tn-positive epithelia. These data suggest what we believe to be a new molecular mechanism for the pathogenesis of UC.