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Dystonia is a movement disorder in which patients have involuntary abnormal movements or postures. Non-motor symptoms, such as psychiatric symptoms, sleep problems and fatigue, are common. We hypothesise that the gut microbiome might play a role in the pathophysiology of the (non-)motor symptoms in dystonia via the gut–brain axis. This exploratory study investigates the composition of the gut microbiome in dystonia patients compared to healthy controls. Furthermore, the abundance of neuro-active metabolic pathways, which might be implicated in the (non-)motor symptoms, was investigated. We performed both metagenomic and 16S rRNA sequencing on the stool samples of three subtypes of dystonia (27 cervical dystonia, 20 dopa-responsive dystonia and 24 myoclonus-dystonia patients) and 25 controls. While microbiome alpha and beta diversity was not different between dystonia patients and controls, dystonia patients had higher abundances of Ruminococcus torques and Dorea formicigenerans, and a lower abundance of Butyrivibrio crossotus compared to controls. For those with dystonia, non-motor symptoms and the levels of neurotransmitters in plasma explained the variance in the gut microbiome composition. Several neuro-active metabolic pathways, especially tryptophan degradation, were less abundant in the dystonia patients compared to controls. This suggest that the gut–brain axis might be involved in the pathophysiology of dystonia. Further studies are necessary to confirm our preliminary findings.

Baboons inform on human gut microbiota Commensal bacteria are found throughout an organism, but it is not known whether associations between gut bacteria and their host are heritable. Grieneisen et al. examined changes in the microbiomes of 585 wild baboons from fecal samples collected over 14 years (see the Perspective by Cortes-Ortiz and Amato). Almost all microbiome traits tested demonstrated some level of statistically significant heritability. Most heritability values were low but varied over time correlating with the age of the host. Baboons live in an environment similar to that postulated for early humans and have a microbiome similar to that of humans. Thus, this heritability of the microbiome may reflect similar genetic determinants in humans, for which similar datasets are not available. Science , aba5483, this issue p. 181 ; see also abj5287, p. 159

Organ transplantation is a life-saving treatment for patients with end-stage disease, but survival rates after transplantation vary considerably. There is now increasing evidence that the gut microbiome is linked to the survival of patients undergoing hematopoietic cell transplant, yet little is known about the role of the gut microbiome in solid organ transplantation. We analyzed 1370 fecal samples from 415 liver and 672 renal transplant recipients using shotgun metagenomic sequencing to assess microbial taxonomy, metabolic pathways, antibiotic resistance genes, and virulence factors. To quantify taxonomic and metabolic dysbiosis, we also analyzed 1183 age-, sex-, and body mass index–matched controls from the same population. In addition, a subset of 78 renal transplant recipients was followed longitudinally from pretransplantation to 24 months after transplantation. Our data showed that both liver and kidney transplant recipients suffered from gut dysbiosis, including lower microbial diversity, increased abundance of unhealthy microbial species, decreased abundance of important metabolic pathways, and increased prevalence and diversity of antibiotic resistance genes and virulence factors. These changes were found to persist up to 20 years after transplantation. Last, we demonstrated that the use of immunosuppressive drugs was associated with the observed dysbiosis and that the extent of dysbiosis was associated with increased mortality after transplantation. This study represents a step toward potential microbiome-targeted interventions that might influence the outcomes of recipients of solid organ transplantation.

ImportanceImmune checkpoint blockade (ICB) has improved the survival of patients with advanced melanoma. Durable responses are observed for 40% to 60% of patients, depending on treatment regimens. However, there is still large variability in the response to treatment with ICB, and patients experience a range of immune-related adverse events of differing severity. Nutrition, through its association with the immune system and gut microbiome, is a poorly explored but appealing target with potential to improve the efficacy and tolerability of ICB.ObjectiveTo investigate the association between habitual diet and response to treatment with ICB.Design, Setting, and ParticipantsThis multicenter cohort study (the PRIMM study) was conducted in cancer centers in the Netherlands and UK and included 91 ICB-naive patients with advanced melanoma who were receiving ICB between 2018 and 2021.ExposuresPatients were treated with anti–programmed cell death 1 and anti–cytotoxic T lymphocyte–associated antigen 4 monotherapy or combination therapy. Dietary intake was assessed through food frequency questionnaires before treatment.Main Outcomes and MeasuresClinical end points were defined as overall response rate (ORR), progression-free survival at 12 months (PFS-12), and immune-related adverse events that were grade 2 or higher.ResultsThere were a total of 44 Dutch participants (mean [SD] age, 59.43 [12.74] years; 22 women [50%]) and 47 British participants (mean [SD] age, 66.21 [16.63] years; 15 women [32%]). Dietary and clinical data were prospectively collected from 91 patients receiving ICB between 2018 and 2021 for advanced melanoma in the UK and the Netherlands. Logistic generalized additive models revealed positive linear associations between a Mediterranean dietary pattern that was high in whole grains, fish, nuts, fruit, and vegetables and the probability of ORR and PFS-12 (probability of 0.77 for ORR; P = .02; false discovery rate, 0.032; effective degrees of freedom, 0.83; probability of 0.74 for PFS-12; P = .01; false discovery rate, 0.021; effective degrees of freedom, 1.54).Conclusions and RelevanceThis cohort study found a positive association between a Mediterranean diet, a widely recommended model of healthy eating, and response to treatment with ICB. Large prospective studies from different geographies are needed to confirm the findings and further elucidate the role of diet in the context of ICB.

Dysregulation of gut mucosal host–microbe interactions is a central feature of inflammatory bowel disease (IBD). To study tissue-specific interactions, we performed transcriptomic (RNA-seq) and microbial (16S-rRNA-seq) profiling of 696 intestinal biopsies derived from 353 patients with IBD and controls. Analysis of transcript-bacteria interactions identified six distinct groups of inflammation-related pathways that were associated with intestinal microbiota, findings we could partially validate in an independent cohort. An increased abundance of Bifidobacterium was associated with higher expression of genes involved in fatty acid metabolism, while Bacteroides was associated with increased metallothionein signaling. In fibrostenotic Crohn’s disease, a transcriptional network dominated by immunoregulatory genes associated with Lachnoclostridium bacteria in non-stenotic tissue. In patients using TNF-α-antagonists, a transcriptional network dominated by fatty acid metabolism genes associated with Ruminococcaceae. Mucosal microbiota composition was associated with enrichment of specific intestinal cell types. Overall, we identify multiple host–microbe interactions that may guide microbiota-directed precision medicine.

The composition of the gut microbiome has been associated with clinical responses to immune checkpoint inhibitor (ICI) treatment, but there is limited consensus on the specific microbiome characteristics linked to the clinical benefits of ICIs. We performed shotgun metagenomic sequencing of stool samples collected before ICI initiation from five observational cohorts recruiting ICI-naive patients with advanced cutaneous melanoma (n = 165). Integrating the dataset with 147 metagenomic samples from previously published studies, we found that the gut microbiome has a relevant, but cohort-dependent, association with the response to ICIs. A machine learning analysis confirmed the link between the microbiome and overall response rates (ORRs) and progression-free survival (PFS) with ICIs but also revealed limited reproducibility of microbiome-based signatures across cohorts. Accordingly, a panel of species, including Bifidobacterium pseudocatenulatum, Roseburia spp. and Akkermansia muciniphila, associated with responders was identified, but no single species could be regarded as a fully consistent biomarker across studies. Overall, the role of the human gut microbiome in ICI response appears more complex than previously thought, extending beyond differing microbial species simply present or absent in responders and nonresponders. Future studies should adopt larger sample sizes and take into account the complex interplay of clinical factors with the gut microbiome over the treatment course.

Human gut microbial dynamics are highly individualized, making it challenging to link microbiota to health and to design universal microbiome therapies. This individuality is typically attributed to variation in host genetics, diets, environments and medications but it could also emerge from fundamental ecological forces that shape microbiota more generally. Here, we leverage extensive gut microbial time series from wild baboons-hosts who experience little interindividual dietary and environmental heterogeneity-to test whether gut microbial dynamics are synchronized across hosts or largely idiosyncratic. Despite their shared lifestyles, baboon microbiota were only weakly synchronized. The strongest synchrony occurred among baboons living in the same social group, probably because group members range over the same habitat and simultaneously encounter the same sources of food and water. However, this synchrony was modest compared to each host's personalized dynamics. In support, host-specific factors, especially host identity, explained, on average, more than three times the deviance in longitudinal dynamics compared to factors shared with social group members and ten times the deviance of factors shared across the host population. These results contribute to mounting evidence that highly idiosyncratic gut microbiomes are not an artefact of modern human environments and that synchronizing forces in the gut microbiome (for example, shared environments, diets and microbial dispersal) are not strong enough to overwhelm key drivers of microbiome personalization, such as host genetics, priority effects, horizontal gene transfer and functional redundancy.

Organ transplantation is a life-saving treatment for patients with end-stage disease, but survival post-transplantation varies considerably. There is now increasing evidence that the gut microbiome is linked to the survival of hematopoietic cell transplant patients, yet little is known about the role of the gut microbiome in solid organ transplantation. We analyzed 1,370 fecal samples from liver and renal transplant recipients using shotgun metagenomic sequencing to assess microbial taxonomy, metabolic pathways, antibiotic resistance genes and virulence factors. To quantify taxonomic and metabolic dysbiosis, we analyzed 1,183 age-, sex- and BMI-matched subjects from the same population. A subset of patients were also followed longitudinally from pre- to post-transplantation. Our data show that transplant recipients suffer from gut dysbiosis—including lower microbial diversity, increased abundance of unhealthy microbial species, decreased abundance of important metabolic pathways, and increased prevalence and diversity of antibiotic resistant genes and virulence factors—that persist up to 20 years post-transplantation. Finally, we demonstrate that the use of immunosuppressive drugs is significantly associated with the observed dysbiosis and that the extent of dysbiosis is associated with increased post-transplant mortality.

The gut microbiome is associated with diverse diseases, but the universal signature of an (un)healthy microbiome remains elusive and there is a need to understand how genetics, exposome, lifestyle and diet shape the microbiome in health and disease. To fill this gap, we profiled bacterial composition, function, antibiotic resistance and virulence factors in the gut microbiomes of 8,208 Dutch individuals from a three-generational cohort comprising 2,756 families. We then correlated this to 241 host and environmental factors, including physical and mental health, medication use, diet, socioeconomic factors and childhood and current exposome. We identify that the microbiome is primarily shaped by environment and cohousing. Only ~13% of taxa are heritable, which are enriched with highly prevalent and health-associated bacteria. By identifying 2,856 associations between microbiome and health, we find that seemingly unrelated diseases share a common signature that is independent of comorbidities. Furthermore, we identify 7,519 associations between microbiome features and diet, socioeconomics and early life and current exposome, of which numerous early-life and current factors are particularly linked to the microbiome. Overall, this study provides a comprehensive overview of gut microbiome and the underlying impact of heritability and exposures that will facilitate future development of microbiome-targeted therapies.

To date, most insights into the processes shaping vertebrate gut microbiomes have emerged from studies with cross-sectional designs. While this approach has been valuable, emerging time series analyses on vertebrate gut microbiomes show that gut microbial composition can change rapidly from one day to the next, with consequences for host physical functioning, health, and fitness. Hence, the next frontier of microbiome research will require longitudinal perspectives. Here we argue that primatologists, with their traditional focus on tracking the lives of individual animals and familiarity with longitudinal fecal sampling, are well positioned to conduct research at the forefront of gut microbiome dynamics. We begin by reviewing some of the most important ecological processes governing microbiome change over time, and briefly summarizing statistical challenges and approaches to microbiome time series analysis. We then introduce five questions of general interest to microbiome science where we think field-based primate studies are especially well-positioned to fill major gaps: (1) Do early life events shape gut microbiome composition in adulthood? (2) Do shifting social landscapes cause gut microbial change? (3) Are gut microbiome phenotypes heritable across variable environments? (4) Does the gut microbiome show signs of host aging? And (5) do gut microbiome composition and dynamics predict host health and fitness? For all of these questions, we high-light areas where primatologists are uniquely positioned to make substantial contributions. We review preliminary evidence, discuss possible study designs, and suggest future directions.

Background Primary sclerosing cholangitis (PSC) is an inflammatory disorder of the bile ducts. The etiology of PSC is unknown, but it is hypothesized that intestinal barrier dysfunction, as seen in inflammatory bowel disease (IBD), plays a role. Roughly 75% of PSC patients have concomitant IBD (PSC-IBD). PSC-IBD is phenotypically different from ulcerative colitis (UC) with predominantly right-sided disease and a higher risk for colorectal cancer. In this study we aim aim to find probable distinct pathomechanisms for PSC-IBD, by comparing gut mucosal biopsies between PSC-IBD and UC using single-cell RNA sequencing. Methods 47 gut mucosal samples from the colon of subjects with either PSC-IBD (n=24), UC (n=18) or non-IBD control (n=5) were collected, from which 28 were paired inflamed and non-inflamed. Whole biopsies were cryopreserved and dissociated into single cells using collagenase digestion. Library preparation was done using the 10x Genomics system and subsequent sequencing was performed on an MGI2000 sequencer. The ‘Seurat’ R package was used for analysis. Results A total of 75.078 high quality cells identified 38 distinct cell types. No differences in cell type composition were observed between PSC-IBD and UC. We did see different cell type composition and gene expression between inflamed and non-inflamed samples. For example, in PSC-IBD specifically, an enterocyte subtype defined by DUOX2-expression showed inflammatory pathways upon inflammation. UC inflammation, on the other hand, was characterized by involvement of BEST4+ enterocytes and inflammatory fibroblasts. In addition, activated B cells and IgA plasma cells expressed stress-related genes in PSC, but not in UC inflammation. Conclusion We show that intestinal inflammation in PSC-IBD is characterized by distinct, cell-specific gene expression patterns as compared to UC. This highlights differential cell types mediating inflammation between these IBDs. Our study provides insight in cellular mechanisms underlying intestinal disease in PSC, and may serve as a starting point for further studies, for example on the functions of DUOX2+ enterocytes.

Background The pathogenesis of inflammatory bowel diseases is characterized by gastrointestinal dysbiosis. Small molecules -or metabolites- present in feces can improve our understanding of host and microbes’ interactions. By exploring the relationship between host genetics, gut microbiota, and fecal metabolites composition from 500 patients with IBD and 255 population controls, we aimed to identify potential new biomarkers for the disease and to reveal host-microbiota interactions while considering factors like life-style and clinical history. Methods In short, we used shotgun sequencing to profile the microbiota composition, and an untargeted metabolomics platform (Metabolon INC., USA) was used to identify the levels of 1684 fecal metabolites. Whole exome sequencing and GSA Illumina chip were used to characterize host’s genetics. Multi-omics penalized regressions were used to explore the relationship between metabolite levels and the use of 44 types of medication, 144 long-term dietary patterns, and multiple patient characteristics. Random forest models were used to determine the discriminative power of metabolites. Results The levels of 597 fecal metabolites were altered in Crohn’s disease and 209 in patients with ulcerative colitis compared to population controls. Disease heterogeneity was reflected in the fecal metabolite profile; for example, disease location had a large impact on fecal bile-acid profile. Interestingly, metabolomics data could discriminate IBD samples from non-IBD samples (Random Forest AUC= 0.81). Genetic polymorphisms in the NAT2 gene were associated with the levels of multiple coffee metabolites. In both cohorts, IBD and non-IBD individuals, the increase in the abundance of several pathobionts was related to changes in the tryptophan, fatty-acids, and bilirubin metabolism. For example, the increase in abundance of R.gnavus was correlated with higher tryptamine levels, and the presence of bacterial starch degradation enzymes with increased concentrations of butyrate (FDR Conclusion Patients with IBD present a different fecal metabolite profile that can be used to distinguish IBD from non-IBD individuals. Metabolite patterns are strongly related to microbial composition, diet, and patient’s clinical characteristics. Overall, these results can help to understand the disease’s complexity considering host-microbiota interaction and point to new therapeutical directions.

International audience; In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure and therefore cannot explicitly account for the effect of the host in struc-turing the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates such as diet and collection site, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including (a) model-based ordination to visualize and quantify the main patterns in the data; (b) variance partitioning to assess how influential the included host-specific factors are in structuring the microbiota; and (c) co-occurrence networks to visualize microbe-to-microbe associations. K E Y W O R D S Bayesian inference, generalized linear mixed models, host-associated, joint species distribution models, microbiome, microbiota

In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure, and therefore cannot explicitly account for the effect of the host in structuring the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates like diet and collection sites, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including: (i) model-based ordination to visualize and quantify the main patterns in the data; (ii) variance partitioning to asses how influential the included host-specific factors are in structuring the microbiota; and (iii) co-occurrence networks to visualize microbe-to-microbe associations.

The long-term stability of microbiomes is crucial as the persistent occurrence of beneficial microbes and their associated functions ensure host health and well-being. Microbiomes are highly diverse and dynamic, making them challenging to understand. Because many natural systems work as temporal networks, we present an approach that allows identifying meaningful ecological patterns within complex microbiomes: the dynamic core microbiome. On the basis of six marine sponge species sampled monthly over three years, we study the structure, dynamics and stability of their microbiomes. What emerge for each microbiome is a negative relationship between temporal variability and mean abundance. The notion of the dynamic core microbiome allowed us to determine a relevant functional attribute of the microbiome: temporal stability is not determined by the diversity of a host’s microbial assemblages, but rather by the density of those microbes that conform its core microbiome. The core microbial interaction network consisted of complementary members interacting weakly with dominance of comensal and amensal interactions that suggests self-regulation as a key determinant of the temporal stability of the microbiome. These interactions have likely coevolved to maintain host functionality and fitness over ecological, and even evolutionary time scales.

Thomas, Torsten ... et al.-- 12 pages, 10 figures, additional information https://dx.doi.org/10.1038/ncomms11870, Sponges (phylum Porifera) are early-diverging metazoa renowned for establishing complex microbial symbioses. Here we present a global Porifera microbiome survey, set out to establish the ecological and evolutionary drivers of these host–microbe interactions. We show that sponges are a reservoir of exceptional microbial diversity and major contributors to the total microbial diversity of the world’s oceans. Little commonality in species composition or structure is evident across the phylum, although symbiont communities are characterized by specialists and generalists rather than opportunists. Core sponge microbiomes are stable and characterized by generalist symbionts exhibiting amensal and/or commensal interactions. Symbionts that are phylogenetically unique to sponges do not disproportionally contribute to the core microbiome, and host phylogeny impacts complexity rather than composition of the symbiont community. Our findings support a model of independent assembly and evolution in symbiont communities across the entire host phylum, with convergent forces resulting in analogous community organization and interactions, T.T. and N.S.W. were funded through Australian Research Council Future Fellowships FT140100197 and FT120100480, respectively. S.L.L. and P.M.E. were funded by the Spanish Government project MARSYMBIOMICS CTM2013-43287-P. R.C. was funded by the Portuguese Foundation for Science and Technology through the Investigator Grant IF/01076/2014 and the project UID/Multi/04326/2013. C.G.E. and R.W.T. were supported by grants from the US National Science Foundation (DEB-0829986 and DEB-1208340). A.C.-F. was supported by the UNESCO L’Oréal Fellowship for Young Women in Science. U.H. and L.M.S. received funding from the EU- FP7 Program (KBBE.2012.3.2-01; grant no. 311932; SeaBioTech). J.M.M. was supported by the French Laboratory of Excellence Project ‘TULIP’ (ANR-10-LABX-41; ANR-11-IDEX-002-02) and by a Region Midi-Pyrénées Project (CNRS 121090)