Biology subjects

Levy, L.

Publications and source records attributed to Levy, L..

9 recordsLinked to original sources

bioRxiv2026

Probiotic formula intervention in infants leads to colonization and competitive strain displacement independent of IgA binding

Early-life microbiota assembly is affected by environmental exposure, diet, and immunity. We performed shotgun metagenomics sequencing of fecal samples (N=401) from a controlled infant intervention trial to evaluate how pre- and probiotic exposure affects bacterial strain dynamics, maternal-to-offspring strain transmissibility, strain persistence, and host immune responses. Species- and strain-level analyses revealed that the early-life intervention with Bifidobacterium longum subsp. infantis (BL subsp. infantis), Bifidobacterium breve, and galacto-oligosaccharides (GOS) replaced main resident strains of these species unlike breast-feeding and exclusive infant formula. BL subsp. infantis low-diversity clusters were representative of several populations and were enriched for genes linked to recombination, mobilization, and antimicrobial activity. lnterestingly, Bifidobacterium bifidum but not Bifidobacterium longum or B. breve was heavily targeted by mucosal lgA, regardless of feeding type. These findings suggest that early-life pro- and prebiotic interventions promote colonization of specific dominant strains, potentially by outcompeting and displacing existing strains, independently of host immune responses.

microbiology↗

bioRxiv2025

Spatial and Single-cell Transcriptomics Reveal Programs Governing Fibroblastic Foci Fibroblasts

RationaleFibroblastic foci (FF) are central for fibrosis propagation in idiopathic pulmonary fibrosis (IPF), yet their resident fibroblast subpopulation remains poorly defined. ObjectiveTo deeply characterize FF-fibroblasts and identify programs governing their differentiation and activation. MethodsGeoMx spatial transcriptomics was applied to IPF lung regions, comparing carefully delineated FF (excluding overlying epithelium) with areas of established fibrosis, to derive an FF-specific signature. This signature was projected onto a large single-cell RNA-sequencing (scRNA-seq) dataset to identify an FF-specific fibroblast cluster, facilitating its deep characterization. Measurements and Main ResultsGeoMx revealed 272 increased genes in FF; this FF-signature was validated against several independent spatial transcriptomics and proteomics datasets. FF-signature genes were highly enriched in a specific cluster of fibroblasts in the IPF scRNA-seq dataset. MMP11 was the most specific gene of the FF-fibroblast cluster, and was validated using in situ RNA hybridization. Furthermore, higher MMP11 bronchoalveolar lavage protein levels were found in progressive pulmonary fibrosis and were associated with worse outcome in Cox regression (HR 4.54, 95% CI 1.24-15.8). Cell-cell interaction analysis with fibroblasts and adjacent aberrant basaloid cells, detected signals that may induce the FF-fibroblast signature, including from TGF-{beta} superfamily ligands. Using trajectory and transcription factor (TF) analysis we show that the trajectory from non-FF to FF-specific fibroblasts is correlated with activation of EMT-associated TFs and deactivation of AP-1 family TFs. ConclusionsWe identified transcriptional programs governing FF-fibroblasts, for which MMP11 serves as a novel highly-specific biomarker with prognostic significance. We highlight potential regulators whose targeting may curb pulmonary fibrosis progression.

genomics↗

bioRxiv2025

Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization.

Absolute bacterial biomass estimation in the human gut is crucial for understanding microbiome dynamics and host-microbe interactions. Current methods for quantifying bacterial biomass in stool, such as flow cytometry, qPCR, or spike-ins (i.e., adding cells or DNA from an organism not normally found in a sample), can be labor-intensive, costly, and confounded by factors like water content, DNA extraction efficiency, PCR inhibitors, and other technical challenges that add bias and noise. We propose a simple, cost-effective approach that circumvents some of these technical challenges: directly estimating bacterial biomass from metagenomes using bacterial-to-host (B:H) read ratios. We compare B:H ratios to the standard methods outlined above, demonstrating that B:H ratios are useful proxies for bacterial biomass in stool and possibly in other host-associated substrates. We show how B:H ratios can be used to track antibiotic treatment response and recovery in both mice and humans, which showed 403-fold and 45-fold reductions in bacterial biomass during antibiotic treatment, respectively. Our results indicate that host and bacterial metagenomic DNA fractions in human stool fluctuate longitudinally around a stable mean in healthy individuals, and the average host read fraction varies across healthy individuals by < 8-9 fold. B:H ratios offer a convenient alternative to other absolute biomass quantification methods, without the need for additional measurements, experimental design considerations, or machine learning algorithms, enabling retrospective absolute biomass estimates from existing stool metagenomic data.

microbiology↗

bioRxiv2024

A long-term ecological research data set from the marine genetic monitoring programme ARMS-MBON 2018-2020

Molecular methods such as DNA/eDNA metabarcoding have emerged as useful tools to document biodiversity of complex communities over large spatio-temporal scales. We established an international Marine Biodiversity Observation Network (ARMS-MBON) combining standardised sampling using autonomous reef monitoring structures (ARMS) with metabarcoding for genetic monitoring of marine hard-bottom benthic communities. Here, we present the data of our first sampling campaign comprising 56 ARMS units deployed in 2018-2019 and retrieved in 2018-2020 across 15 observatories along the coasts of Europe and adjacent regions. We describe the open-access data set (image, genetic, and metadata) and explore the genetic data to show its potential for marine biodiversity monitoring and ecological research. Our analysis shows that ARMS recovered more than 60 eukaryotic phyla capturing diversity of up to [~]5,500 amplicon sequence variants and [~]1,800 operational taxonomic units, and up to [~]250 and [~]50 species per observatory using the cytochrome c oxidase subunit I (COI) and 18S rRNA marker genes, respectively. Further, ARMS detected threatened, vulnerable and non-indigenous species often targeted in biological monitoring. We show that while deployment duration does not drive diversity estimates, sampling effort and sequencing depth across observatories do. We recommend that ARMS should be deployed for at least three to six months during the main growth season to use resources as efficiently as possible and that post-sequencing curation is applied to enable statistical comparison of spatio-temporal entities. We suggest that ARMS should be used in biological monitoring programmes and long-term ecological research and encourage the adoption of our ARMS-MBON protocols.

ecology↗

bioRxiv2023

Emergence of a senescent and inflammatory pulmonary CD4+ T cell population prior to lung allograft failure

Lung transplantation is a life-saving therapy for end-stage pulmonary disease, but its long-term outlook is poor due to a high incidence of chronic lung allograft dysfunction (CLAD). CLAD results from alloimmune-mediated progressive fibrosis and culminates in death or the need for re-transplantation after a median of 6 years. Existing immunosuppression fails to prevent CLAD, suggesting the existence of alloimmune pathways resistant to these drugs. Here, we used mass cytometry to identify cell populations enriched in the bronchoalveolar lavage (BAL) of patients with subsequent allograft dysfunction. We show that CD4+CD57+PD1+ T cells emerge in stable lung transplant recipients in the first year post-transplant, conferring heightened risks for CLAD and death or re-transplantation. CD4+CD57+PD1+ T cells display features of senescence and secrete inflammatory cytokines. Cellular indexing by transcriptomes and epitopes (CITE-Seq) on BAL CD4+ T cells revealed the existence of 2 oligoclonal CD57+ subsets with putative cytotoxic and follicular helper functions. Finally, we observed that CD4+CD57+PD1+ T cells are associated with lung allograft fibrosis in a mouse model and in human explanted CLAD lungs, where they localize near airway epithelium and B cells. Together, our findings reveal the existence of an inflammatory T cell population that predicts future lung allograft dysfunction and may represent a rational therapeutic target in lung transplant recipients.

immunology↗

bioRxiv2023

Microbial community-scale metabolic modeling predicts personalized short-chain-fatty-acid production profiles in the human gut.

Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro, ex vivo, and in vivo data. Next, we show how MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.

systems biology↗

bioRxiv2022

Analysis of Larval Fish Feeding Behavior under Naturalistic Conditions

Modern research efforts concerned with animal behavior rely heavily on image and video analysis. While such data are now quick to obtain, extracting and analyzing complex behaviors under naturalistic conditions is still a major challenge, specifically when the behavior of interest is sporadic and rare. In this study, we present an end-to-end system for capturing, detecting and analyzing larval fish feeding behavior in unconstrained naturalistic environments. We first constructed a specialized system for imaging these tiny, fast-moving creatures and deployed it in large aquaculture rearing pools. We then designed an analysis pipeline using several action classification backbones, and compare their performance. A natural feature of the data was the extremely low prevalence of feeding events, leading to low sample sizes and highly imbalanced datasets despite extensive annotation efforts. Nevertheless, our pipeline successfully detected and classified the sparsely-occurring feeding behavior of fish larvae in a curated experimental setting from videos featuring multiple animals. We introduce three new annotated datasets of underwater videography, in a curated and an uncurated setting. As challenges related to data imbalance and experts annotation are common to the analysis of animal behavior under naturalistic conditions, we believe our findings can contribute to the growing field of computer vision for the study and understanding of animal behavior.

zoology↗

bioRxiv2020

High-throughput organoid screening enables engineering of intestinal epithelial composition

Barrier tissue epithelia play an essential role in maintaining organismal homeostasis, and changes in their cellular composition have been observed in multiple human diseases. Within the small intestinal epithelium, adult stem cells integrate diverse signals to regulate regeneration and differentiation, thereby establishing overall cellularity. Accordingly, directing stem cell differentiation could provide a tractable approach to alter the abundance or quality of specialized cells of the small intestinal epithelium, including the secretory Paneth, goblet, and enteroendocrine populations. Yet, to date, there has been a lack of suitable tools and rigorous approaches to identify biological targets and pharmacological agents that can modify epithelial composition to enable causal testing of disease-associated changes with novel therapeutic candidates. To empower the search for epithelia-modifying agents, we establish a first-of-its-kind high-throughput phenotypic organoid screen. We demonstrate the ability to screen thousands of samples and uncover biological targets and associated small molecule inhibitors which translate to in vivo. This approach is enabled by employing a functional, cell-type specific, scalable assay on an organoid model designed to represent the physiological cues of in vivo Paneth cell differentiation from adult intestinal stem cells. Further, we miniaturize and adapt the organoid culture system to enable automated plating and screening, thereby providing the ability to test thousands of samples. Strikingly, in our screen we identify inhibitors of the nuclear exporter Xpo1 modulate stem cell fate commitment by inducing a pan-epithelial stress response combined with an interruption of mitogen signaling in cycling intestinal progenitors, thereby significantly increasing the abundance of Paneth cells independent of known WNT and Notch differentiation cues. We extend our observation in vivo, demonstrating that oral administration of Xpo1 inhibitor KPT-330 at doses 1,000-fold lower than conventionally used in hematologic malignancies increases Paneth cell abundance. In total, we provide a framework to identify novel biological cues and therapeutic leads to rebalance intestinal stem cell differentiation and modulate epithelial tissue composition via high-throughput phenotypic screening in rationally-designed organoid model of differentiation.

bioengineering↗

bioRxiv2016

Short CT-rich motifs can trigger context-specific silencing of gene expression in bacteria

We use an oligonucleotide library of over 10000 variants together with a synthetic biology approach to identify an insulation mechanism encoded within a subset of {sigma}54 promoters. Insulation manifests itself as dramatically reduced protein expression for a downstream gene that may be expressed by transcriptional read-through. The insulation we observe is strongly associated with the presence of short CT-rich motifs (3-5 bp), positioned within 25 bp upstream of the Shine-Dalgarno (SD) motif of the silenced gene. We hypothesize that insulation is effected by binding of the RBS to the upstream CT-rich motif. We provide evidence to support this hypothesis using mutations to the CT-rich motif and gene expression measurements on multiple sequence variants. Modelling is also consistent with this hypothesis. We show that the strength of the silencing, effected by insulation, depends on the location and number of CT-rich motifs encoded within the promoters. Finally, we show that in E.coli these insulator sequences are preferentially encoded within {sigma}54 promoters as compared to other promoter types, suggesting a regulatory role for these sequences in natural contexts. Our findings suggest that context-related regulatory effects may often be due to sequence-specific interactions encoded sparsely by short motifs that are not easily detected by lower throughput studies. Such short sequence-specific phenomena can be uncovered with a focused OL design that filters out the sequence noise, as exemplified herein.

systems biology↗