Intestinal Blastocystis is linked to healthier diets and more favorable cardiometabolic outcomes in 56,989 individuals from 32 countries.

Diet impacts human health, influencing body adiposity and the risk of developing cardiometabolic diseases. The gut microbiome is a key player in the diet-health axis, but while its bacterial fraction is widely studied, the role of micro-eukaryotes, including Blastocystis, is underexplored. We performed a global-scale analysis on 56,989 metagenomes and showed that human Blastocystis exhibits distinct prevalence patterns linked to geography, lifestyle, and dietary habits. Blastocystis presence defined a specific bacterial signature and was positively associated with more favorable cardiometabolic profiles and negatively with obesity (p < 1e-16) and disorders linked to altered gut ecology (p < 1e-8). In a diet intervention study involving 1,124 individuals, improvements in dietary quality were linked to weight loss and increases in Blastocystis prevalence (p = 0.003) and abundance (p < 1e-7). Our findings suggest a potentially beneficial role for Blastocystis, which may help explain personalized host responses to diet and downstream disease etiopathogenesis.

Discovery of bioactive microbial gene products in inflammatory bowel disease.

Microbial communities and their associated bioactive compounds1-3 are often disrupted in conditions such as the inflammatory bowel diseases (IBD)4. However, even in well-characterized environments (for example, the human gastrointestinal tract), more than one-third of microbial proteins are uncharacterized and often expected to be bioactive5-7. Here we systematically identified more than 340,000 protein families as potentially bioactive with respect to gut inflammation during IBD, about half of which have not to our knowledge been functionally characterized previously on the basis of homology or experiment. To validate prioritized microbial proteins, we used a combination of metagenomics, metatranscriptomics and metaproteomics to provide evidence of bioactivity for a subset of proteins that are involved in host and microbial cell-cell communication in the microbiome; for example, proteins associated with adherence or invasion processes, and extracellular von Willebrand-like factors. Predictions from high-throughput data were validated using targeted experiments that revealed the differential immunogenicity of prioritized Enterobacteriaceae pilins and the contribution of homologues of von Willebrand factors to the formation of Bacteroides biofilms in a manner dependent on mucin levels. This methodology, which we term MetaWIBELE (workflow to identify novel bioactive elements in the microbiome), is generalizable to other environmental communities and human phenotypes. The prioritized results provide thousands of candidate microbial proteins that are likely to interact with the host immune system in IBD, thus expanding our understanding of potentially bioactive gene products in chronic disease states and offering a rational compendium of possible therapeutic compounds and targets.

Metagenomics of the Gut Microbiome in Parkinson's Disease: Prodromal Changes.

OBJECTIVE: Prior studies on the gut microbiome in Parkinson's disease (PD) have yielded conflicting results, and few studies have focused on prodromal (premotor) PD or used shotgun metagenomic profiling to assess microbial functional potential. We conducted a nested case-control study within 2 large epidemiological cohorts to examine the role of the gut microbiome in PD. METHODS: We profiled the fecal metagenomes of 420 participants in the Nurses' Health Study and the Health Professionals Follow-up Study with recent onset PD (N = 75), with features of prodromal PD (N = 101), controls with constipation (N = 113), and healthy controls (N = 131) to identify microbial taxonomic and functional features associated with PD and features suggestive of prodromal PD. Omnibus and feature-wise analyses identified bacterial species and pathways associated with prodromal and recently onset PD. RESULTS: We observed depletion of several strict anaerobes associated with reduced inflammation among participants with PD or features of prodromal PD. A microbiome-based classifier had moderate accuracy (area under the curve [AUC] = 0.76 for species and 0.74 for pathways) to discriminate between recently onset PD cases and controls. These taxonomic shifts corresponded with functional shifts indicative of carbohydrate source preference. Similar, but less marked, changes were observed in participants with features of prodromal PD, in both microbial features and functions. INTERPRETATION: PD and features of prodromal PD were associated with similar changes in the gut microbiome. These findings suggest that changes in the microbiome could represent novel biomarkers for the earliest phases of PD. ANN NEUROL 2023;94:486-501.

High-sensitivity pattern discovery in large, paired multiomic datasets.

MOTIVATION: Modern biological screens yield enormous numbers of measurements, and identifying and interpreting statistically significant associations among features are essential. In experiments featuring multiple high-dimensional datasets collected from the same set of samples, it is useful to identify groups of associated features between the datasets in a way that provides high statistical power and false discovery rate (FDR) control. RESULTS: Here, we present a novel hierarchical framework, HAllA (Hierarchical All-against-All association testing), for structured association discovery between paired high-dimensional datasets. HAllA efficiently integrates hierarchical hypothesis testing with FDR correction to reveal significant linear and non-linear block-wise relationships among continuous and/or categorical data. We optimized and evaluated HAllA using heterogeneous synthetic datasets of known association structure, where HAllA outperformed all-against-all and other block-testing approaches across a range of common similarity measures. We then applied HAllA to a series of real-world multiomics datasets, revealing new associations between gene expression and host immune activity, the microbiome and host transcriptome, metabolomic profiling and human health phenotypes. AVAILABILITY AND IMPLEMENTATION: An open-source implementation of HAllA is freely available at http://huttenhower.sph.harvard.edu/halla along with documentation, demo datasets and a user group. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Higher-order brain regions show shifts in structural covariance in adolescent marmosets.

Substantial progress has been made studying morphological changes in brain regions during adolescence, but less is known of network-level changes in their relationship. Here, we compare covariance networks constructed from the correlation of morphometric volumes across 135 brain regions of marmoset monkeys in early adolescence and adulthood. Substantial shifts are identified in the topology of structural covariance networks in the prefrontal cortex (PFC) and temporal lobe. PFC regions become more structurally differentiated and segregated within their own local network, hypothesized to reflect increased specialization after maturation. In contrast, temporal regions show increased inter-hemispheric covariances that may underlie the establishment of distributed networks. Regionally selective coupling of structural and maturational covariance is revealed, with relatively weak coupling in transmodal association areas. The latter may be a consequence of continued maturation within adulthood, but also environmental factors, for example, family size, affecting brain morphology. Advancing our understanding of how morphological relationships within higher-order brain areas mature in adolescence deepens our knowledge of the developing brain's organizing principles.

Differential Effects of the Inactivation of Anterior and Posterior Orbitofrontal Cortex on Affective Responses to Proximal and Distal Threat, and Reward Anticipation in the Common Marmoset.

Structural and functional abnormalities of the orbitofrontal cortex (OFC) have been implicated in affective disorders that manifest anxiety-related symptoms. However, research into the functions of primate OFC has predominantly focused on reward-oriented rather than threat-oriented responses. To redress this imbalance, the present study performed a comprehensive analysis of the independent role of 2 distinct subregions of the central OFC (anterior area 11; aOFC and posterior area 13; pOFC) in the processing of distal and proximal threat. Temporary inactivation of both aOFC and pOFC heightened responses to distal threat in the form of an unknown human, but not to proximal threat assessed in a discriminative Pavlovian conditioning task. Inactivation of the aOFC, however, did unexpectedly blunt conditioned threat responses, although the effect was not valence-specific, as conditioned appetitive responses were similarly blunted and appeared restricted to a discriminative version of the task (when both CS- and CS+ are present within a session). Inactivation of the pOFC did not affect conditioned responses to either proximal threat or reward and basal cardiovascular activity was unaffected by manipulations of activity in either subregion. The results highlight the contribution of aOFC and pOFC to regulation of responses to more distal uncertain but not proximal, certain threat and reveal their opposing contribution to that of the immediately adjacent medial OFC, area 14.

Ventromedial prefrontal area 14 provides opposing regulation of threat and reward-elicited responses in the common marmoset.

The ventromedial prefrontal cortex (vmPFC) is a key brain structure implicated in mood and anxiety disorders, based primarily on evidence from correlational neuroimaging studies. Composed of a number of brain regions with distinct architecture and connectivity, dissecting its functional heterogeneity will provide key insights into the symptomatology of these disorders. Focusing on area 14, lying on the medial and orbital surfaces of the gyrus rectus, this study addresses a key question of causality. Do changes in area 14 activity induce changes in threat- and reward-elicited responses within the nonhuman primate, the common marmoset, similar to that seen in mood and anxiety disorders? Area 14 overactivation was found to induce heightened responsivity to uncertain, low-imminence threat while blunting cardiovascular and behavioral anticipatory arousal to high-value food reward. Conversely, inactivation enhanced the arousal to high-value reward cues while dampening the acquisition of cardiovascular and behavioral responses to a Pavlovian threat cue. Basal cardiovascular activity, including heart rate variability and sympathovagal balance, which are dysfunctional in mood and anxiety disorders, are insensitive to alterations in area 14 activity as is the extinction of conditioned threat responses. The distinct pattern of dysregulation compared to neighboring region area 25 highlights the heterogeneity of function within vmPFC and reveals how the effects of area 14 overactivation on positive and negative reactivity mirror symptoms of anhedonia and anxiety that are so often comorbid in mood disorders.

Multivariable association discovery in population-scale meta-omics studies.

It is challenging to associate features such as human health outcomes, diet, environmental conditions, or other metadata to microbial community measurements, due in part to their quantitative properties. Microbiome multi-omics are typically noisy, sparse (zero-inflated), high-dimensional, extremely non-normal, and often in the form of count or compositional measurements. Here we introduce an optimized combination of novel and established methodology to assess multivariable association of microbial community features with complex metadata in population-scale observational studies. Our approach, MaAsLin 2 (Microbiome Multivariable Associations with Linear Models), uses generalized linear and mixed models to accommodate a wide variety of modern epidemiological studies, including cross-sectional and longitudinal designs, as well as a variety of data types (e.g., counts and relative abundances) with or without covariates and repeated measurements. To construct this method, we conducted a large-scale evaluation of a broad range of scenarios under which straightforward identification of meta-omics associations can be challenging. These simulation studies reveal that MaAsLin 2's linear model preserves statistical power in the presence of repeated measures and multiple covariates, while accounting for the nuances of meta-omics features and controlling false discovery. We also applied MaAsLin 2 to a microbial multi-omics dataset from the Integrative Human Microbiome (HMP2) project which, in addition to reproducing established results, revealed a unique, integrated landscape of inflammatory bowel diseases (IBD) across multiple time points and omics profiles.

Species-level functional profiling of metagenomes and metatranscriptomes.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types.

bioBakery: a meta'omic analysis environment.

Summary: bioBakery is a meta'omic analysis environment and collection of individual software tools with the capacity to process raw shotgun sequencing data into actionable microbial community feature profiles, summary reports, and publication-ready figures. It includes a collection of pre-configured analysis modules also joined into workflows for reproducibility. Availability and implementation: bioBakery (http://huttenhower.sph.harvard.edu/biobakery) is publicly available for local installation as individual modules and as a virtual machine image. Each individual module has been developed to perform a particular task (e.g. quantitative taxonomic profiling or statistical analysis), and they are provided with source code, tutorials, demonstration data, and validation results; the bioBakery virtual image includes the entire suite of modules and their dependencies pre-installed. Images are available for both Amazon EC2 and Google Compute Engine. All software is open source under the MIT license. bioBakery is actively maintained with a support group at biobakery-users@googlegroups.com and new tools being added upon their release. Contact: chuttenh@hsph.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Divergence of Drosophila melanogaster repeatomes in response to a sharp microclimate contrast in Evolution Canyon, Israel.

Repeat sequences, especially mobile elements, make up large portions of most eukaryotic genomes and provide enormous, albeit commonly underappreciated, evolutionary potential. We analyzed repeatomes of Drosophila melanogaster that have been diverging in response to a microclimate contrast in Evolution Canyon (Mount Carmel, Israel), a natural evolutionary laboratory with two abutting slopes at an average distance of only 200 m, which pose a constant ecological challenge to their local biotas. Flies inhabiting the colder and more humid north-facing slope carried about 6% more transposable elements than those from the hot and dry south-facing slope, in parallel to a suite of other genetic and phenotypic differences between the two populations. Nearly 50% of all mobile element insertions were slope unique, with many of them disrupting coding sequences of genes critical for cognition, olfaction, and thermotolerance, consistent with the observed patterns of thermotolerance differences and assortative mating.

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/.

Large scale comparison of non-human sequences in human sequencing data.

Several studies have demonstrated that unmapped reads in next generation sequencing data could be used to identify infectious agents or structural variants, but there has been no intensive effort to analyze and classify all non-human sequences found in individual large data sets. To identify commonality in non-human sequences by infectious agents and putative contamination events, we analyzed non-human sequences in 150 genomic sequencing data files from the 1000 Genomes Project and observed that 0.13% of reads on average showed similarities to non-human genomes. We compared results among different sample groups divided based on ethnicities, sequencing centers and enrichment methods (whole genome sequencing vs. exome sequencing) and found that sequencing centers had specific signatures of contaminating genomes as 'time stamps'. We also observed many unmapped reads that falsely indicated contamination because of the high similarity of human sequences to sequences in non-human genome assemblies such as mouse and Nicotiana.

Subcallosal area 25: Its responsivity to the stress hormone cortisol and its opposing effects on appetitive motivation in marmosets.

Aberrant activity in caudal subcallosal anterior cingulate cortex (scACC) is implicated in depression and anxiety symptomatology, with its normalisation a putative biomarker of successful treatment response. The function of scACC in emotion processing and mental health is not fully understood despite its known influence on stress-mediated processes through its rich expression of mineralocorticoid and glucocorticoid receptors. Here we examine the causal interaction between area 25 within scACC (scACC-25) and the stress hormone, cortisol, in the context of anhedonia and anxiety-like behaviour. In addition, the overall role of scACC-25 in hedonic capacity and motivation is investigated under transient pharmacological inactivation and overactivation. The results suggest that a local increase of cortisol in scACC-25 shows a rapid induction of anticipatory anhedonia and increased responsiveness to uncertain threat. Separate inactivation and overactivation of scACC-25 increased and decreased motivation and hedonic capacity, respectively, likely through different underlying mechanisms. Together, these data show that area scACC-25 has a causal role in consummatory and motivational behaviour and produces rapid responses to the stress hormone cortisol, that mediates anhedonia and anxiety-like behaviour.

Comprehensive profile of the companion animal gut microbiome integrating reference-based and reference-free methods.

The gut microbiome of companion animals is relatively underexplored, despite its relevance to animal health, pet owner health, and basic microbial community biology. Here, we provide the most comprehensive analysis of the canine and feline gut microbiomes to date, incorporating 2639 stool shotgun metagenomes (2272 dog and 367 cat) spanning 14 publicly available datasets (n = 730) and 8 new study populations (n = 1909). These are compared with 238 and 112 baseline human gut metagenomes from the Human Microbiome Project 1-II and a traditionally living Malagasy cohort, respectively, processed in a manner identical to the animal metagenomes. All microbiomes were characterized using reference-based taxonomic and functional profiling, as well as de novo assembly yielding metagenomic assembled genomes clustered into species-level genome bins. Companion animals shared 184 species-level genome bins not found in humans, whereas 198 were found in all three hosts. We applied novel methodology to distinguish strains of these shared organisms either transferred or unique to host species, with phylogenetic patterns suggesting host-specific adaptation of microbial lineages. This corresponded with functional divergence of these lineages by host (e.g. differences in metabolic and antibiotic resistance genes) likely important to companion animal health. This study provides the largest resource to date of companion animal gut metagenomes and greatly contributes to our understanding of the "One Health" concept of a shared microbial environment among humans and companion animals, affecting infectious diseases, immune response, and specific genetic elements.

Chemogenetics identifies separate area 25 brain circuits involved in anhedonia and anxiety in marmosets.

Poor outcomes are common in individuals with anxiety and depression, and the brain circuits underlying symptoms and treatment responses remain elusive. To elucidate these neural circuits, experimental studies must specifically manipulate them, which is only possible in animals. Here, we used a chemogenetics strategy involving engineered designer receptors exclusively activated by designer drugs (DREADDs) to activate a region of the marmoset brain that is dysfunctional in human patients with major depressive disorder, called the subcallosal anterior cingulate cortex area 25 (scACC-25). Using this DREADDs system, we identified separate scACC-25 neural circuits that underlie specific components of anhedonia and anxiety in marmosets. Activation of the neural pathway connecting the scACC-25 to the nucleus accumbens (NAc) caused blunting of anticipatory arousal (a form of anhedonia) in marmosets in response to a reward-associated conditioned stimulus in an appetitive Pavlovian discrimination test. Separately, activation of the circuit between the scACC-25 and the amygdala increased a measure of anxiety (the threat response score) when marmosets were presented with an uncertain threat (human intruder test). Using the anhedonia data, we then showed that the fast-acting antidepressant ketamine when infused into the NAc of marmosets prevented anhedonia after scACC-25 activation for more than 1 week. These neurobiological findings provide targets that could contribute to the development of new treatment strategies.

A two-cohort study on the association between the gut microbiota and bone density, microarchitecture, and strength.

The gut microbiome affects the inflammatory environment through effects on T-cells, which influence the production of immune mediators and inflammatory cytokines that stimulate osteoclastogenesis and bone loss in mice. However, there are few large human studies of the gut microbiome and skeletal health. We investigated the association between the human gut microbiome and high resolution peripheral quantitative computed tomography (HR-pQCT) scans of the radius and tibia in two large cohorts; Framingham Heart Study (FHS [n=1227, age range: 32 - 89]), and the Osteoporosis in Men Study (MrOS [n=836, age range: 78 - 98]). Stool samples from study participants underwent amplification and sequencing of the V4 hypervariable region of the 16S rRNA gene. The resulting 16S rRNA sequencing data were processed separately for each cohort, with the DADA2 pipeline incorporated in the16S bioBakery workflow. Resulting amplicon sequence variants were assigned taxonomies using the SILVA reference database. Controlling for multiple covariates, we tested for associations between microbial taxa abundances and HR-pQCT measures using general linear models as implemented in microbiome multivariable association with linear model (MaAslin2). Abundance of 37 microbial genera in FHS, and 4 genera in MrOS, were associated with various skeletal measures (false discovery rate [FDR] ≤ 0.1) including the association of DTU089 with bone measures, which was independently replicated in the two cohorts. A meta-analysis of the taxa-bone associations further revealed (FDR ≤ 0.25) that greater abundances of the genera; Akkermansia and DTU089, were associated with lower radius total vBMD, and tibia cortical vBMD respectively. Conversely, higher abundances of the genera; Lachnospiraceae NK4A136 group, and Faecalibacterium were associated with greater tibia cortical vBMD. We also investigated functional capabilities of microbial taxa by testing for associations between predicted (based on 16S rRNA amplicon sequence data) metabolic pathways abundance and bone phenotypes in each cohort. While there were no concordant functional associations observed in both cohorts, a meta-analysis revealed 8 pathways including the super-pathway of histidine, purine, and pyrimidine biosynthesis, associated with bone measures of the tibia cortical compartment. In conclusion, our findings suggest that there is a link between the gut microbiome and skeletal metabolism.

Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4.

Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains.

Metagenomic assessment of gut microbial communities and risk of severe COVID-19.

BACKGROUND: The gut microbiome is a critical modulator of host immunity and is linked to the immune response to respiratory viral infections. However, few studies have gone beyond describing broad compositional alterations in severe COVID-19, defined as acute respiratory or other organ failure. METHODS: We profiled 127 hospitalized patients with COVID-19 (n = 79 with severe COVID-19 and 48 with moderate) who collectively provided 241 stool samples from April 2020 to May 2021 to identify links between COVID-19 severity and gut microbial taxa, their biochemical pathways, and stool metabolites. RESULTS: Forty-eight species were associated with severe disease after accounting for antibiotic use, age, sex, and various comorbidities. These included significant in-hospital depletions of Fusicatenibacter saccharivorans and Roseburia hominis, each previously linked to post-acute COVID syndrome or "long COVID," suggesting these microbes may serve as early biomarkers for the eventual development of long COVID. A random forest classifier achieved excellent performance when tasked with classifying whether stool was obtained from patients with severe vs. moderate COVID-19, a finding that was externally validated in an independent cohort. Dedicated network analyses demonstrated fragile microbial ecology in severe disease, characterized by fracturing of clusters and reduced negative selection. We also observed shifts in predicted stool metabolite pools, implicating perturbed bile acid metabolism in severe disease. CONCLUSIONS: Here, we show that the gut microbiome differentiates individuals with a more severe disease course after infection with COVID-19 and offer several tractable and biologically plausible mechanisms through which gut microbial communities may influence COVID-19 disease course. Further studies are needed to expand upon these observations to better leverage the gut microbiome as a potential biomarker for disease severity and as a target for therapeutic intervention.