Biology subjects

Xavier, R.

Publications and source records attributed to Xavier, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Multi-modal foundation model with whole-slide attention enables transferrable digital pathology at single-cell resolution

Paired histopathology and spatial transcriptomics data are advancing our understanding of tissue biology and disease, but modeling both modalities at single-cell resolution while mapping local and distal cell-cell interdependencies remains computationally prohibitive. Here we introduce TissueFormer, a framework for pretraining foundation models with linear rather than quadratic computational complexity, overcoming a long-standing barrier to modeling long-range dependencies at scale. Trained on over 17 million image-expression pairs from 1.2K tissue slides, TissueFormer excels at predicting spatial gene expression from histology images at cellular resolution and scales to diagnostic tasks at the cell, region, and slide levels. Additionally, by identifying both long and short-range cell-cell interdependencies, our model enables the generation of testable hypotheses about disease mechanisms and staging, as demonstrated in lung fibrosis and breast cancer.

bioinformatics↗

bioRxiv2026

A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions

The interaction between T cell receptors (TCRs), peptides, and human leukocyte antigens (HLAs) underlies antigen-specific T cell immunity. Despite substantial advances in peptide- HLA presentation prediction, accurate modeling of coupled TCR-peptide-HLA recognition remains underdeveloped, limiting applications such as TCR and neoepitope prioritization in cancer and antigen identification in autoimmunity. Here we present StriMap, a unified framework for predicting TCR-peptide-HLA interactions by integrating physicochemical, sequence-context, and structural features at recognition interfaces. StriMap achieves state-of-the-art performance with improved generalizability and enables applications in both cancer and autoimmunity. As a case study in ankylosing spondylitis (AS), we screened 13 million peptides derived from 43,241 bacterial proteins and identified candidate molecular mimics that were experimentally validated to activate T cells expressing an AS-associated TCR. Notably, a top validated peptide was enriched in patients with inflammatory bowel disease (IBD), suggesting potential shared microbial triggers between AS and IBD. Overall, StriMap provides a generalizable framework for rational immunotherapy design and for dissecting antigenic drivers of autoimmunity.

bioinformatics↗

bioRxiv2026

Cartilaginous fish inform the lineage-specific evolution and MHC association of the TLR family

Chondrichthyans (sharks, rays and chimaeras) diverged from other vertebrate lineages over 400 million years ago and possess fully functional innate and adaptive immune systems. They comprise over 1,200 species occupying diverse aquatic habitats, from fresh to marine waters and from shallow to deep seas. Exposure to diverse pathogens through time, together with contemporary ocean warming and habitat degradation driven by climate change, has likely shaped unique immune mechanisms in these species. Toll-like receptors (TLRs) are central components of innate immunity, recognizing conserved pathogen-associated molecular patterns and initiating immune responses, yet their diversity remains poorly characterized in Chondrichthyans. Here, we characterize the TLR gene repertoire in elasmobranchs (sharks and rays) using genomic and transcriptomic data. We identify orthologs spanning all known vertebrate TLR families, including genes shared with agnathans as well as gnathostome-specific genes, and detect lineage-specific patterns of TLR duplication and loss, particularly in squaliform sharks and rays. Molecular evolution analyses indicate that most elasmobranch TLRs are under strong purifying selection, with positively selected sites in all genes, consistent with ongoing adaptation to pathogen-and environment-driven pressures. Several TLRs co-localize with genomic regions enriched in immune genes, including MHC paralogous regions, suggesting an ancestral genomic hotspot for vertebrate immunity.

evolutionary biology↗

bioRxiv2026

Hidden immune memory niches in inflammatory skin diseases

Disease-associated histopathological features are widely used to identify tissue microenvironments or niches for diagnostics and treatment response in clinical practice. However, despite its widespread use, histopathology does not reveal the full cellular and molecular composition of known pathological niches. Furthermore, the existence of pathological niches that may not be histologically discernible remains unknown. In this study, we generated a spatially-resolved multi-modal molecular atlas of [~]5 million human skin cells (including 113 skin sections profiled using Xenium-5k) and applied deep learning to unbiasedly decode 26 skin niches in health and disease. Several disease-associated niches corresponded to known histopathological features, and we defined their cellular and molecular features, co-localisations, and interactions. Additionally, we discovered an immunologically active role for skin appendageal structures in disease mechanisms, potentially contributing to inflammatory memory, that was not identifiable using standard histopathological analysis. These include a resident memory T cell-rich niche in the sebaceous gland and a plasma cell-rich niche in the sweat gland, analogous to the gland-associated immune niche in lung. Finally, we illustrate how our atlas can be used to generate high-resolution representations using transfer learning, resolving rare T cell and sebocyte subsets not possible in the original studies, validating niche identification, and the spatial enrichment of candidate genes linked to disease-associated genetic variants. Overall, our study links histopathology and atlas-scale genomics to reveal novel insights into inflammatory disease pathogenesis, chronicity, and potentially curative therapeutic avenues, using skin as an exemplar tissue for this approach.

immunology↗

bioRxiv2025

Neonatal BCG Vaccination Engages the Vasculature to Elicit γδ T Cell-Mediated Protection against Tuberculosis

The Bacillus Calmette-Guerin (BCG) vaccine remains the only approved vaccine against tuber-culosis (TB). Although its efficacy against pulmonary TB in adults is limited, BCG provides re-markable protection against miliary TB when administered during infancy. Despite more than 100 million infants worldwide receiving BCG annually, the mechanisms underlying its neonatal protective effects remain poorly defined. Here, we demonstrate that subcutaneous neonatal BCG vaccination (BCG-sc) induces a marked expansion of {gamma}{delta} T cells producing IL-17 and IL-22, which mediated protection against subsequent Mycobacterium tuberculosis (Mtb) experimental infection. A similar expansion of {gamma}{delta} T cells was observed in a longitudinal cohort of infants, from birth to three months of infants followed after intradermal BCG vaccination. Mechanistical-ly, BCG-mediated protection in neonates was linked to its early vascular dissemination through the distinct structure of neonatal skin, resembling the protective effects of intravenous BCG in adults. Moreover, neonatal BCG-sc vaccination generated a distinct BCG-induced microbiome signature, characterized by enrichment of Prevotellaceae, Tannerellaceae, and Bifidobacteriaceae, which was associated with protection. Together, these findings identify {gamma}{delta} T cells as key mediators of early-life BCG-induced immunity and highlight the role of the gut-lung axis in long-term protection against TB from infancy into adulthood.

immunology↗

bioRxiv2025

Reovirus recombination is highly selective, and its profiles are primarily dictated by viral gene segment identity

Recombination facilitates the generation of defective viral genomes (DVGs), truncated derivatives of the parental genome that require a helper virus to replicate. Recombination mechanisms are poorly understood for viruses with double-stranded RNA genomes. Two strains of the double-stranded RNA virus reovirus differ in the pattern of packaged DVGs during serial passage. To determine whether the polymerase complex or gene segment sequence contributes to these differences, we exchanged polymerase complexes between the two reovirus strains. We identified DVG patterns using RT-PCR and recombination junction profiles using ClickSeq. Reoviruses synthesized DVGs that maintained the 5' and 3' termini and contained large central deletions. The polymerase complex did not detectably affect DVG pattern following reovirus serial passage or viral recombination junction profiles. Instead, recombination junction profiles correlated with the identity of viral RNA gene segments, even in the presence of a non-native polymerase complex or virus background. Reovirus recombination junction start and stop sites often occur in regions of sequence microhomology. While we observed many instances of short stretches of identical nucleotides within a viral gene segment, only a select few positions were incorporated into recombination junctions. Overall, these data suggest that recombination events that can mediate reovirus DVG formation are highly selective, and properties of viral gene segments primarily dictate where recombination occurs. These observations suggest a model for double-stranded RNA virus recombination in which the polymerase pauses RNA synthesis and re-initiates further along the same template at a specific junction stop site that has sequence homology to the junction start site. IMPORTANCEViral infection gives rise to defective viral genomes, which cannot complete a full replication cycle. Recombination facilitates defective viral genome generation but is understudied for RNA viruses with double-stranded genomes. We found that for a double-stranded RNA virus, reovirus, recombination occurs preferentially at specific sites in the genome that correspond with the identity of the gene segment. Recombination tends to initiate and terminate at sites sharing identical sequences. However, even if these short nucleotide sequences appear multiple times in a gene segment, only specific sites are used for recombination. Our results indicate that reovirus recombination is a highly orchestrated event in which individual gene segments contain the characteristics that drive recombination. These findings suggest that RNA properties, such as sequence and structure, drive recombination for double-stranded RNA viruses, likely through reinitiation after re-hybridization of the newly formed RNA product with the same RNA template molecule at a different location.

microbiology↗

bioRxiv2025

Convergent genomic responses of human gut bacteria to variations in industrialization

To what extent gut bacteria respond to the distinct ecological pressures imposed by human lifestyle remains unclear. Here, we investigate how genomic adaptation in gut bacteria differ between industrialized and non-industrialized human populations. We generated a broad collection of isolate genomes spanning diverse host geographies, lifestyles, species, and strains. We first found that compared to MAGs, paired isolate genomes recover more functional elements and signals of horizontal gene transfers (HGTs). Leveraging isolate genomes from multiple species, we find that strains from industrialized hosts experience an expansion of proteome size and harbor greater pangenome fluidity, driven by recent events of HGTs. Gene- and variant-level analyses reveal convergent patterns of lifestyle-specific adaptation in functions that are critical for ecological adaptation, such as stress response, cell envelope remodeling and central metabolism. Our results demonstrate that industrialization imprints evolutionary signatures on gut bacterial genomes, illuminating the effects of rapidly changing environments on human biology.

evolutionary biology↗

bioRxiv2025

Adherence to Lifes Essential 8 Enhances Gut Microbiota Diversity and Cognitive Performance

Emerging evidence suggests a complex interplay among cardiovascular health, gut microbiome composition, and cognitive function. Lifes Essential 8 (LE8), developed by the American Heart Association, includes vital metrics of cardiovascular health, such as diet, physical activity, nicotine exposure, sleep health, body mass index (BMI), blood glucose, blood lipids, and blood pressure. In this study, we analyzed data from 781 participants in the Framingham Heart Study (FHS) to explore the relationship between LE8 adherence, gut microbiota, and cognitive performance. Participants with greater adherence to LE8 demonstrated significantly increased gut microbial diversity (-diversity: Chao1, p = 0.0014; Shannon, p = 0.0071) and distinct microbial compositions ({beta}-diversity: PERMANOVA p = 1e-4). Higher adherence to LE8 was related to an increased abundance of genera Barnesiella and Ruminococcus, while a reduced abundance of Clostridium was associated with higher LE8 adherence. Greater gut microbial diversity (-diversity: Chao1, p = 0.0012; Shannon, p = 0.0066), and beneficial genera like Oscillospira correlated with better global cognitive scores (GCS). Taxonomic overlap analyses revealed microbial taxa that simultaneously influence both LE8 adherence and cognitive outcomes. Mediation analyses indicated that specific taxa, including Barnesiella and Lentisphaerae, mediated the link between LE8 adherence and cognitive performance. These taxa may serve as key modulators in the gut-brain axis, connecting cardiovascular and brain health. Conversely, higher Clostridium abundance was associated with poorer cognitive performance. This study highlights the significance of comprehensive cardiovascular health metrics in shaping gut microbiota and enhancing cognitive resilience. Our findings underscore the therapeutic potential of targeting gut microbiota to mitigate cognitive decline, warranting further exploration through longitudinal and metagenomic studies.

neuroscience↗

bioRxiv2025

From ashes to adaptation: the impact of wildfires on the diet of Podarcis lusitanicus revealed by DNA metabarcoding

Fire has long been recognized as an important ecological and evolutionary force in plant communities, but its influence on animals, particularly regarding predator-prey interactions, remains understudied. This study focuses on the impact of wildfires on the diet of Podarcis lusitanicus, a lizard species inhabiting a fire-prone region in the Iberian Peninsula. Faecal samples were collected from 12 distinct locations in Northern Portugal, at sites that burned in two distinct years (2016 and 2022), and in sites unburned since at least 2016. Podarcis lusitanicus is a generalist arthropod predator with dietary flexibility. Given the turnover of arthropod species after fire, it is expected to find variations in diet caused by different fire histories, especially between unburnt and recently burnt sites. Using DNA metabarcoding approach, employing high-throughput sequencing, the study revealed that while prey richness remained unaffected by wildfire regime, significant shifts occurred in diet composition between more recently burned and unburned areas, demonstrating a likely influence on prey availability after a more recent fire. Specifically, we found that differences in diet composition between these two fire regimes were due to the presence of Tapinoma ants and jumping spiders (Salticus scenicus) in unburned areas, while these were absent in areas burned in 2022. Interestingly, diets in unburned areas and areas burned in 2016 showed no significant differences, highlighting the lizards adaptability and the habitats resilience over time. Talitroides topitotum was found in dominance in both burnt areas, suggesting that this species may be fire tolerant. In addition, families such as Cicadellidae and Noctuidae were found to be more associated with more recently burned areas. The use of DNA metabarcoding in this study was essential to provide a more detailed and accurate view of predator-prey interactions in ecosystems susceptible to fire, providing a better understanding of changes in prey consumption in these environments.

ecology↗

bioRxiv2024

An integrated microfluidic and fluorescence platform for probing in vivo neuropharmacology

Neurotechnologies and genetic tools for dissecting neural circuit functions have advanced rapidly over the past decade, although the development of complementary pharmacological method-ologies has comparatively lagged. Understanding the precise pharmacological mechanisms of neuroactive compounds is critical for advancing basic neurobiology and neuropharmacology, as well as for developing more effective treatments for neurological and neuropsychiatric disorders. However, integrating modern tools for assessing neural activity in large-scale neural networks with spatially localized drug delivery remains a major challenge. Here, we present a dual microfluidic-photometry platform that enables simultaneous intracranial drug delivery with neural dynamics monitoring in the rodent brain. The integrated platform combines a wireless, battery-free, miniaturized fluidic microsystem with optical probes, allowing for spatially and temporally specific drug delivery while recording activity-dependent fluorescence using genetically encoded calcium indicators (GECIs), neurotransmitter sensors GRABNE and GRABDA, and neuropeptide sensors. We demonstrate the performance this platform for investigating neuropharmacological mechanisms in vivo and characterize its efficacy in probing precise mechanistic actions of neuroactive compounds across several rapidly evolving neuroscience domains.

neuroscience↗

bioRxiv2024

Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.

genomics↗

bioRxiv2024

Chemical tools to expand the ligandable proteome: diversity-oriented synthesis-based photoreactive stereoprobes

Chemical proteomics enables the global assessment of small molecule-protein interactions in native biological systems and has emerged as a versatile approach for ligand discovery. The range of small molecules explored by chemical proteomics has, however, been limited. Here, we describe a diversity-oriented synthesis (DOS)-inspired library of stereochemically-defined compounds bearing diazirine and alkyne units for UV light-induced covalent modification and click chemistry enrichment of interacting proteins, respectively. We find that these photo-stereoprobes interact in a stereoselective manner with hundreds of proteins from various structural and functional classes in human cells and demonstrate that these interactions can form the basis for high-throughput screening-compatible nanoBRET assays. Integrated phenotypic analysis and chemical proteomics identified photo-stereoprobes that modulate autophagy by engaging the mitochondrial serine protease CLPP. Our findings show the utility of photo-stereoprobes for expanding the ligandable proteome, furnishing target engagement assays, and discovering and characterizing bioactive small molecules by cell-based screening.

biochemistry↗

bioRxiv2024

Spatial transcriptomics of healthy and fibrotic human liver at single-cell resolution

Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of cell types and their heterogeneity within the human liver, but the spatial organization at single-cell resolution has not yet been described. Here we apply multiplexed error robust fluorescent in situ hybridization (MERFISH) to map the zonal distribution of hepatocytes, resolve subsets of macrophage and mesenchymal populations, and investigate the relationship between hepatocyte ploidy and gene expression within the healthy human liver. We next integrated spatial information from MERFISH with the more complete transcriptome produced by single-nucleus RNA sequencing (snRNA-seq), revealing zonally enriched receptor-ligand interactions. Finally, analysis of fibrotic liver samples identified two hepatocyte populations that are not restricted to zonal distribution and expand with injury. Together these spatial maps of the healthy and fibrotic liver provide a deeper understanding of the cellular and spatial remodeling that drives disease which, in turn, could provide new avenues for intervention and further study.

genomics↗

bioRxiv2022

RF4Del: A Random Forest approach for accurate deletion detection

Efficiently detecting genomic structural variants (SVs) is a key step to grasp the "missing heritability" underlying complex traits involved in major evolutionary processes such as speciation, phenotypic plasticity, and adaptive responses. Yet, the SV-based genotype/trait association studies are still largely overlooked mainly due to the lack of reliable detection methods. Here, we present a random forest (RF) method for accurate deletion identification: RF4Del. By relying on the analysis of the mapping profiles, data already available in most sequencing projects, RF4Del can easily and quickly call deletions. Several classic and ensemble learning strategies were carefully evaluated using proper benchmark data. RF4Del was trained and tested on simulated data from the model species Drosophila melanogaster to detect deletions. The model consists of 13 features extracted from a mapping file. We show that RF4Del outperforms established SV callers (DELLY, Pindel) with higher overall performance (F1-score > 0.75; 6x-12x sequence coverage) and is less affected by low sequencing coverage and deletion size variations. RF4Del could learn from a compilation of sequence patterns linked to a given SV. Such models can then be combined to form a learning system able to detect all types of SVs in a given genome, beyond the one used in our study. https://github.com/alvesrcoo/eletric-scheep

bioinformatics↗

bioRxiv2021

Raman2RNA: Live-cell label-free prediction of single-cell RNA expression profiles by Raman microscopy

Single cell RNA-Seq (scRNA-seq) and other profiling assays have opened new windows into understanding the properties, regulation, dynamics, and function of cells at unprecedented resolution and scale. However, these assays are inherently destructive, precluding us from tracking the temporal dynamics of live cells, in cell culture or whole organisms. Raman microscopy offers a unique opportunity to comprehensively report on the vibrational energy levels of molecules in a label-free and non-destructive manner at a subcellular spatial resolution, but it lacks in genetic and molecular interpretability. Here, we developed Raman2RNA (R2R), an experimental and computational framework to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and multi-modal data integration and domain translation. We used spatially resolved single-molecule RNA-FISH (smFISH) data as anchors to link scRNA-seq profiles to the paired spatial hyperspectral Raman images, and trained machine learning models to infer expression profiles from Raman spectra at the single-cell level. In reprogramming of mouse fibroblasts into induced pluripotent stem cells (iPSCs), R2R accurately (r>0.96) inferred from Raman images the expression profiles of various cell states and fates, including iPSCs, mesenchymal-epithelial transition (MET) cells, stromal cells, epithelial cells, and fibroblasts. R2R outperformed inference from brightfield images, showing the importance of spectroscopic content afforded by Raman microscopy. Raman2RNA lays a foundation for future investigations into exploring single-cell genome-wide molecular dynamics through imaging data, in vitro and in vivo.

genomics↗

bioRxiv2021

Functional screen of Inflammatory Bowel Disease genes reveals key epithelial functions

BackgroundGenetic studies have been tremendously successful in identifying genomic regions associated with a wide variety of phenotypes, although the success of these studies in identifying causal genes, their variants, and their functional impacts have been more limited. MethodsWe identified 145 genes from IBD-associated genomic loci having endogenous expression within the intestinal epithelial cell compartment. We evaluated the impact of lentiviral transfer of the open reading frame (ORF) of these IBD genes into the HT-29 intestinal epithelial cell line via transcriptomic analyses. Comparing the genes whose expression was modulated by each ORF, as well as the functions enriched within these gene lists, identified ORFs with shared impacts and their putative disease-relevant biological functions. ResultsAnalysis of the transcriptomic data for cell lines expressing the ORFs for known causal genes such as HNF4a, IFIH1 and SMAD3 identified functions consistent for what is known for these genes. These analyses also identified two major cluster of genes: Cluster 1 contained the known IBD causal genes IFIH1, SBNO2, NFKB1 and NOD2, as well as genes from other IBD loci (ZFP36L1, IRF1, GIGYF1, OTUD3, AIRE and PITX1), whereas Cluster 2 contained the known causal gene KSR1 and implicated DUSP16 from another IBD locus. Our analyses highlight how multiple IBD gene candidates impact on epithelial structure and function, including the protection of the mucosa from intestinal microbiota, and demonstrate that DUSP16, acts a regulator of MAPK activity and contributes to mucosal defense, in part via its regulation of the polymeric immunoglobulin receptor, involved in the protection of the intestinal mucosa from enteric microbiota. ConclusionsThis functional screen, based on expressing IBD genes within an appropriate cellular context, in this instance intestinal epithelial cells, resulted in changes to the cells transcriptome that are relevant to their endogenous biological function(s). This not only helped in identifying likely causal genes within genetic loci but also provided insight into their biological functions. Furthermore, this work has highlighted the central role of intestinal epithelial cells in IBD pathophysiology, providing a scientific rationale for a drug development strategy that targets epithelial functions in addition to the current therapies targeting immune functions.

genetics↗

bioRxiv2020

Functional modulation of T follicular cells in vivo enhances antigen-specific humoral immunity

Generation of high-affinity IgG is essential for defense against infections and cancer, is the intended consequence of many vaccines, but can cause autoimmune and inflammatory diseases when inappropriately directed against self (Wang et al., 2018, Ludwig et al., 2017, Chinen et al., 2010). The interplay and balance of T follicular helper cells (TFH) and T follicular regulatory cells (TFR) is critical for production of high-affinity IgG (Wing et al., 2018). Here, we empowered TFH cells and improve antigen-specific IgG responses with two interventions intended to transiently diminish TFR influence. First, adult mice were administered an antibiotic cocktail (ABX) for an extended period to deplete the immunoregulatory intestinal microbiota (Belkaid and Harrison, 2017, Thaiss et al., 2016, Rooks and Garrett, 2016, Honda and Littman, 2016, Perruzza et al., 2017, Teng et al., 2016, Block et al., 2016, Proietti et al., 2014, Slack et al., 2014). This treatment skewed T follicular cell ratios, with increased TFH and reduced TFR numbers. TNP-KLH immunization resulted in higher affinity TNP-specific IgG in ABX mice compared to controls. In a model of IgG-driven inflammatory nephritis, ABX mice had significantly worse nephritis accompanied by higher affinity antigen-specific IgG, and enriched TFH cells compared to controls. Second, we sought to functionally manipulate TFH and TFH cells, which both express the checkpoint inhibitory molecule, PD-1 (Sage et al., 2013), by administration of -PD-1 during immunization. This intervention enhanced the affinity of antigen-specific IgG and increased in TFH following TNP-KLH immunization and nephritis induction. These results suggest that altering TFH and TFR ratio during immunization is an appealing strategy to qualitatively improve IgG responses.

immunology↗

bioRxiv2020

Population Structure Discovery in Meta-Analyzed Microbial Communities and Inflammatory Bowel Disease

Microbial community studies in general, and of the human microbiome in inflammatory bowel disease (IBD) in particular, have now achieved a scale at which it is practical to associate features of the microbiome with environmental exposures and health outcomes across multiple large-scale populations. This permits the development of rigorous meta-analysis methods, of particular importance in IBD as a means by which the heterogeneity of disease etiology and treatment response might be explained. We have thus developed MMUPHin (Meta-analysis Methods with a Uniform Pipeline for Heterogeneity in microbiome studies) for joint normalization, meta-analysis, and population structure discovery using microbial community taxonomic and functional profiles. Applying this method to ten IBD cohorts (5,151 total samples), we identified a single consistent axis of microbial associations among studies, including newly associated taxa such as Acinetobacter and Turicibacter detected due to the sensitivity of meta-analysis. Linear random effects models further revealed associations with medications, disease location, and interaction effects consistent within and between studies. Finally, multiple unsupervised clustering metrics and dissimilarity measures agreed on a lack of discrete microbiome "types" in the IBD gut microbiome. These results thus provide a benchmark for consistent characterization of the IBD gut microbiome and a general framework applicable to meta-analysis of any microbial community types.

genomics↗