Biology subjects

Yassour, M.

Publications and source records attributed to Yassour, M..

10 recordsLinked to original sources

bioRxiv2026

IBD stress impacts gut microbiome intra-species diversity

Intra-species genomic variation results from diversity-generating processes and supplies the raw material for subsequent natural selection. Environmental stress can be regarded as the ultimate accelerator of these processes, especially for microorganisms, which can alter their DNA if presented with nutrient limitation, toxins, or pathogen attack. Chronic intestinal inflammation, as in inflammatory bowel diseases (IBD), may be regarded as prolonged environmental stress for gut commensal bacteria, bringing many enteric species down to undetectable levels. However, it remains unclear how the microbes that survive the IBD gut environment actually respond to IBD stress, and whether their stress response may leave a transient or permanent signature in their genomes. To investigate whether IBD stress induces and selects for certain genetic diversity, we performed metagenomic analyses on gut species in IBD patients and Controls. We focused on strain diversity within single individuals, which might be the result of more recent diversification processes under stress. We found measurable differences at the genome level between IBD and Controls, yet this was species-dependent. We then investigated gene-level diversity and found that certain functions were more likely to be enriched with either neutral divergence, functional divergence, or both. Functions that were enriched in IBD with both kinds of diversity were associated with motility and iron-scavenging, among others. These results may point towards functions that are under selection in the context of IBD stress, and could inform future mechanistic work, exploring previously unknown routes of bacterial diversification and adaptation to stress in the gut microbiome.

microbiology↗

bioRxiv2026

An Observational Study of the Impact of Systemic B-cell Depletion on Cervicovaginal Mucosal Environment

ImportanceEmerging data show that B-cell depleting chemotherapies, which are increasingly used to treat autoimmune disorders and multiple sclerosis, can be associated with mucosal side effects such as inflammatory vaginitis. ObjectiveEvaluate the impact of rituximab treatment on vaginal mucosal immune markers, endocervical immune cell populations and vaginal microbiome. DesignCross-sectional observational study conducted between 2022 - 2024. SettingAcademic medical center, Boston Massachusetts. ParticipantsWe enrolled women aged >18 years who were either 1) receiving rituximab for autoimmune renal disease or were 2) healthy controls ExposureTreatment with rituximab, an anti CD20 monoclonal antibody. Main outcome and measureWe compared endocervical immune cell populations, vaginal fluid immune markers, vaginal fluid immunoglobulins and vaginal microbiome composition between individuals being treated with rituximab and healthy controls. ResultsWe enrolled 26 women treated with rituximab for autoimmune renal disease and 26 healthy controls. Median circulating and endocervical B-cell and plasma cell proportions were significantly lower in treated participants compared to controls. Median vaginal fluid IgA concentrations were significantly lower in participants treated with rituximab, while ILE, IgM, IgG1, IgG2, IgG3 and IgG4 were not different between groups. Total T cell frequencies were similar between groups, but the proportion of activated T cells (CD4+CD38+HLADR+) was significantly lower in people treated with rituximab. Concentrations of IL10, IL13, IL17, IL21, IL23, IL4, ITAC and TNFa were elevated in vaginal fluid from the rituximab group, while IL-8 was lower. A CST-IV-C, low-Lactobacillus pattern of vaginal microbiota was more common in the rituximab group. Conclusions and RelevanceSystemic B-cell depletion is associated with reduced vaginal fluid IgA, a more diverse microbiome composition, and increases in many vaginal fluid immune markers compared to healthy controls. The reduction in vaginal fluid IgA may provide opportunities for vaginal bacteria to induce inflammation. Key pointsO_ST_ABSQuestionC_ST_ABSHow does circulating B-cell depletion impact the vaginal microenvironment? FindingsIn this cross-sectional study of 52 women, B cell and plasma cell proportions were significantly lower in both blood and vaginal mucosa among rituximab-treated participants compared to healthy controls. Vaginal IgA concentrations, but not other immunoglobulins, were significantly lower in rituximab treated participants. In treated participants, vaginal cytokine concentrations were elevated, and microbiome composition shifted toward non-Lactobacillus-dominant communities. In six people with inflammatory vaginitis, both circulating and endocervical B cells were lowest in people with the most severe symptoms. MeaningSystemic B cell depletion is associated with alterations in vaginal mucosal immune markers and microbiome composition which increase local inflammation.

immunology↗

bioRxiv2026

Prophages of infant-derived Bifidobacterium longum subspecies employ antagonistic and synergistic strategies to persist in their host

Early colonisation by bifidobacteria is crucial for infant health, with Bifidobacterium longum subspecies (BL.) dominating the early gut microbiome. However, the interactions between these bacteria and their viruses remain poorly characterised. Here, we applied genomics-based approaches to examine BL. prophage composition and dynamics in infants, as well as their antagonistic and mutualistic evolutionary strategies. Across 213 metagenome-assembled genomes recovered from 139 infant faecal samples in the Dutch Lifelines NEXT cohort, 286 previously undescribed prophages were identified and analysed. Comparative genomics revealed extensive viral diversity, evidence of historical recombination, and widespread counter-defence, with [~]80% of prophages encoding anti-CRISPR or CRISPR-evasion proteins. Approximately half of prophages encoded metabolism altering genes. Notably, prophages and host CRISPR spacer arrays were highly stable across longitudinal samples, indicating stable phage-host associations during early life. Together, these findings show that BL. prophages employ antagonistic and synergistic strategies to maintain infectivity and long-term persistence in the infant gut.

microbiology↗

bioRxiv2025

Bifidobacterium longum subsp. nexus nov., a novel subspecies isolated from infant stool

Bifidobacterium longum is a foundational, genetically diverse member of the infant gut microbiome, yet resolving its subspecies in metagenomic data remains challenging. Here, we performed a deep phylogenetic characterization of the B. longum species utilizing 4,577 fecal metagenomes from the LLNEXT mother-infant cohort alongside a global dataset of 1,220 genomes and metagenome-assembled genomes (MAGs). We identified a novel, geographically widespread lineage: Bifidobacterium longum subsp. nexti. Using a polyphasic taxonomic analysis, including average nucleotide identity and digital DNA-DNA hybridization, confirms subspecies-level divergence. Distinct from other members of the B. longum species, BL. nexti harbors -amylopullulanase and grows on soluble starch and often pullulan, consistent with -glucan utilization. Within the LLNEXT cohort, BL. nexti is enriched in formula-fed infants and shows evidence consistent with vertical transmission. Globally, while BL. nexti is geographically widespread, it usually persists at low relative abundance across diverse populations. By resolving a major fraction of previously unclassified B. longum diversity, this study provides new insights into the specialized lineages and ecological dynamics driving the assembly of the developing infant microbiome.

microbiology↗

bioRxiv2025

Development of the preterm infant gut and gastric residuals microbiome

Prematurity, defined as birth before 37 completed weeks of gestation, is the leading cause of mortality in children under five and affects approximately 11% of live births globally--around 15 million infants each year. Despite advances in neonatal care, preterm infants remain at an increased risk for a range of complications. One widely used clinical practice in neonatal intensive care units (NICUs) is the monitoring of gastric residuals (GRs) to assess feeding tolerance and guide enteral nutrition. While the clinical significance of GRs is debated, their microbial composition has not been extensively studied. In this study, we performed metagenomic sequencing of 199 stool and 69 GR samples from 39 preterm infants during hospitalization to characterize their gut and stomach microbiomes. To our knowledge, this is the first study to describe the microbial landscape of GR in preterm infants. We identified 11 distinct GR clusters, often dominated by Staphylococcus, Streptococcus, and Klebsiella, with microbial diversity correlating with GR aspiration frequency. Longitudinal analysis revealed temporal colonization patterns, with early dominance of Staphylococcus epidermidis and Bradyrhizobium, and later emergence of Escherichia coli, Staphylococcus hominis, and Streptococcus thermophilus. In stool samples, 8 microbial clusters were found, frequently enriched with Enterobacteriaceae. Early samples rich in S. epidermidis were associated with higher gestational age and lower microbial richness, while Bifidobacterium breve, a beneficial gut commensal, appeared later in hospitalization. Comparative analysis showed overlap between gut and gastric microbiota, though stomach samples were more dynamic and exhibited less intra-subject similarity. Strain-level resolution revealed both subject-specific (e.g., E. coli, K. pneumoniae) and widely shared (e.g., S. epidermidis) taxa. We also identified a pathogenic Klebsiella aerogenes strain associated with bacteremia with distinct genomic features a week ahead of its first clinical isolation. These findings provide novel insights into the dynamic and niche-specific microbial colonization of preterm infants.

microbiology↗

bioRxiv2025

PHLAME: A benchmark for continuous evaluation of host phenotype prediction from shotgun metagenomic data

Predicting host phenotypes from shotgun metagenomic data is essential for translating microbiome research into clinical practice)Despite the development of numerous computational tools for this task, researchers often default to traditional machine learning methods such as Random Forest)This hesitancy to adopt newer methods stems from their complexity as well as the lack of standardized evaluations, as most tools are assessed on different datasets and compared against a limited set of methods)Here, we introduce LAMPP, a standardized benchmark for evaluating methods for predicting host phenotypes from gut metagenomic data)LAMPP features a diverse range of prediction tasks and enables consistent, comparative assessments across prediction tools)Our systematic evaluation of existing tools shows that classic machine learning methods (e.g., Random Forest) perform competitively, offering both ease of use and state-of-the-art results)At the same time, it demonstrates that microbiome-based phenotype prediction remains a challenging problem)By providing a consistent platform for ongoing evaluation and access to raw sequencing data, LAMPP motivates the development of novel prediction pipelines from raw sequencing data to phenotype prediction, including novel sample representation and data augmentation strategies)LAMPP is publicly available for ongoing benchmarking at https://lampp.yassourlab.com/.

bioinformatics↗

bioRxiv2023

Longitudinal Variability of Bifidobacterium Species in the Infant Gut is Independent of Maternal Milk HMO Composition

The development of the infant gut microbiome is primarily influenced by the infant feeding type, with breast milk serving as the optimal source of nutrition. Breast milk contains human milk oligosaccharides (HMOs) that act as nourishment for the developing gut microbiome, potentially conferring advantages to specific bacterial species. Previous studies have demonstrated the ability of certain Bifidobacterium species to utilize individual HMOs, however a longitudinal study examining the evolving microbial community at a high resolution in the context of mothers milk HMO composition is lacking. Here, we explored the relationship between the HMO composition in mothers milk and the abundance of Bifidobacterium species in the infant gut throughout the course of early life. To enable subspecies taxonomic classification, we developed a high-throughput method for quantifying the abundance of Bifidobacterium longum subsp. infantis (BL. infantis; the best known HMO-utilizer) from metagenomic sequencing. We applied this method to a longitudinal cohort consisting of 21 mother-infant dyads, from whom we collected matched breast milk and infant stool samples at multiple time points during the first year of life. We observed substantial changes in the infant gut microbiome over the course of several months, while the HMO composition in mothers milk remained relatively stable. Bifidobacterium species were a prominent factor contributing to the variation observed among samples; however, no significant associations were found between specific HMOs in mothers milk and the abundance of Bifidobacterium species. Finally, the longitudinal nature of our cohort enabled us to characterize the dynamic colonization of BL. infantis in the infant gut, which surprisingly began late in the breastfeeding period. Applying our BL. infantis quantification method to additional datasets from various geographical locations, we found similar, late-colonization by BL. infantis, highlighting the importance of quantifying BL. infantis in the infant gut.

microbiology↗

bioRxiv2023

GENI: a web server to identify gene set enrichments in tumor samples

The Cancer Genome Atlas (TCGA) and other projects provide informative tumor-associated genomic data for the broad research community. Hence, several useful web-based tools have been generated to ease non-expert users with the analysis and characterization of a specific gene behavior in selected tumors. However, none of the existing tools offer the user the means to evaluate the expression profile of a given gene in the context of the whole transcriptome. Currently, such analyses require prior bioinformatic knowledge and expertise. Therefore, we developed GENI (Gene ENrichment Identifier) as a fast, user-friendly tool to analyze the TCGA expression data for gene set enrichments. GENI analyzes large-scale tumor-associated gene expression datasets and evaluates biological relevance, thus offering researchers a simplified means to analyze cancer patient-derived data. Availability and implementationGENI is a freely available fast web-based tool developed using the R programming language. It is accessible via the URL: https://yoavshaul-lab.shinyapps.io/gsea-geni/. The complete script can be found at https://github.com/ArataHayashi/GENI-Gene-ENrichment-Identifier.

bioinformatics↗

bioRxiv2021

A comprehensive fitness landscape model reveals the evolutionary history and future evolvability of eukaryotic cis-regulatory DNA sequences

Mutations in non-coding cis-regulatory DNA sequences can alter gene expression, organismal phenotype, and fitness. Fitness landscapes, which map DNA sequence to organismal fitness, are a long-standing goal in biology, but have remained elusive because it is challenging to generalize accurately to the vast space of possible sequences using models built on measurements from a limited number of endogenous regulatory sequences. Here, we construct a sequence-to-expression model for such a landscape and use it to decipher principles of cis-regulatory evolution. Using tens of millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Sacccharomyces cerevisiae, we construct a deep transformer neural network model that generalizes with exceptional accuracy, and enables sequence design for gene expression engineering. Using our model, we predict and experimentally validate expression divergence under random genetic drift and strong selection weak mutation regimes, show that conflicting expression objectives in different environments constrain expression adaptation, and find that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for detecting selective constraint on gene expression using our model and natural sequence variation, and validate it using observed cis-regulatory diversity across 1,011 yeast strains, cross-species RNA-seq from three different clades, and measured expression-to-fitness curves. Finally, we develop a characterization of regulatory evolvability, use it to visualize fitness landscapes in two dimensions, discover evolvability archetypes, quantify the mutational robustness of individual sequences and highlight the mutational robustness of extant natural regulatory sequence populations. Our work provides a general framework that addresses key questions in the evolution of cis-regulatory sequences.

genomics↗

bioRxiv2020

Delivery mode impacts newborn gut colonization efficiency

Delivery mode is the variable with the greatest influence on the infant gut microbiome composition in the first few months of life. Children born by Cesarean section (C-section) lack species from the Bacteroides genus in their gut microbial community, and this difference can be detectable until 6-18 months of age. One hypothesis is that these differences stem from lack of exposure to the maternal vaginal microbiome, as children born by C-section do not pass through the birth canal; however, Bacteroides species are not common members of the vaginal microbiome, thus this explanation seems inadequate. Here, we set out to re-evaluate this hypothesis by collecting rectal and vaginal samples before delivery from 73 mothers with paired stool from their infants in the first two weeks of life. We compared microbial profiles of infants born by planned, pre-labor C-section to those born by emergent, post-labor surgery (where the child was in the birth canal, but eventually delivered through an abdominal incision), and found no significant differences in the microbiome between these two groups. Both groups showed the characteristic signature lack of Bacteroides species, despite their difference in exposure to the birth canal. Surprisingly, this signature was only evident in samples from week two of life, but not in the first week. Children born by C-section often had high abundance of Bacteroides in their first few days of life, but these were not stable colonizers of the infant gut, as they were not detectable by week two. Finally, we used metagenomic sequencing to compare microbial strains in maternal vaginal and rectal samples and samples from their infants; we found evidence for mother-to-child transmission of rectal rather than vaginal strains. These results challenge birth canal exposure as the dominant factor in infant gut microbiome establishment and implicate colonization efficiency rather than exposure as a dictating factor of the newborn gut microbiome composition.

microbiology↗