Biology subjects

Mizrahi, I.

Publications and source records attributed to Mizrahi, I..

At least 19 recordsLinked to original sources

bioRxiv2026

An AI-assisted platform for quantitative histopathological analysis in interstitial lung disease

Interstitial lung diseases (ILDs) are heterogeneous pulmonary disorders characterized by chronic inflammation and/or fibrosis. 30-40% of ILD patients develop fibrotic disease that is associated with progressive respiratory decline and poor prognosis, particularly in idiopathic pulmonary fibrosis. Current antifibrotic therapies slow disease progression but do not reverse fibrosis, highlighting the need for improved therapeutic strategies. Robust histopathological evaluation in preclinical models is essential for drug development; however, conventional scoring systems are semi-quantitative, labor-intensive, subject to inter-observer variability, and rely on limited field sampling. Here, we introduce FibroSight, a standalone platform for compartment-resolved quantification of lung remodeling in Sirius Red-stained sections. By integrating deep learning- based structural segmentation with color-based feature extraction, FibroSight enables highly automated whole-lobe analysis without requiring complex computational setup. The platform quantifies complementary remodeling parameters, including parenchymal collagen fraction, parenchymal tissue density, nuclear area fraction, parenchymal airspace fraction, and airway- and vascular-associated remodeling. Validated in the bleomycin-induced fibrosis model, FibroSight-derived metrics strongly correlated with expert Ashcroft scoring and showed stronger associations with histological severity than corresponding outputs from a semi-automated ImageJ-based workflow. The platform further distinguished inflammatory from fibrotic remodeling in influenza-induced lung injury and demonstrated translational proof-of-concept applicability in human ILD biopsy specimens. By enabling scalable, reproducible, and multi-compartment histological quantification, FibroSight provides a practical framework for objective assessment of lung remodeling. This approach expands conventional fibrosis evaluation by integrating fibrotic, inflammatory, airway, and vascular-associated readouts, supporting more precise analysis of disease mechanisms and therapeutic responses in preclinical and translational ILD research.

pathology↗

bioRxiv2026

Dihydropyrimidines sustain aggressive cancer states by stabilizing DPYSL2

Cancer cell states are governed by coordinated signaling and metabolic networks, yet the mechanisms coupling metabolic activity to oncogenic signaling remain poorly understood. Here, we identify dihydropyrimidines (DHPs), metabolites generated during pyrimidine catabolism, as "signaling metabolites" that sustain aggressive cancer cell states. Depletion of DHPs, either by knockout of the pyrimidine catabolic enzyme DPYD or by expression of the DHP-degrading enzyme DPYS, suppressed STAT3 signaling and attenuated mesenchymal and inflammatory transcriptional programs. Mechanistically, DHPs stabilized DPYSL2, a JAK1-interacting adaptor protein required for efficient STAT3 activation. Structural modeling and thermal stability analyses further support a direct interaction between DHPs and DPYSL2. Accordingly, high DPYD expression was associated with EMT, inflammatory signaling, and poor-prognosis breast cancer subtypes across patient cohorts. Ultimately, our findings establish pyrimidine catabolism as a direct regulator of signaling competence and identify DHPs as signaling-active metabolites that couple cellular metabolic state to oncogenic transcriptional programs and mesenchymal identity.

cancer biology↗

bioRxiv2026

Ruminosignatures associated with methane emissions and feed efficiency across geographies and cattle breeds

The cattle rumen microbiota represents a highly complex and dynamic ecosystem, whose organization and connection to host phenotypes are of the highest importance to food security and the environment. In this study, we analyzed the rumen microbiota, from 2,492 cattle belonging to five different breeds and production systems across five countries, categorizing them into microbial co-abundance groups referred to as Ruminosignatures. We identified twelve distinct Ruminosignatures, including two that were consistently observed across all populations and were dominated by the genus Prevotella and UBA2810. Additional Ruminosignatures showed breed-and diet-specific patterns and collectively explained 96-99% of the variance in rumen microbial composition. The abundances of several Ruminosignatures were associated with methane emissions and feed efficiency, and were influenced by host genetics, with heritability estimates ranging from 0.09 to 0.51. The Ruminosignature dominated by UAB2810 was negatively associated with methane emissions across all datasets and positively linked to feed efficiency in Holstein from Italy and crossbred from Ireland. Additionally, the type of production system affects both the occurrence of Ruminosignatures and their impact on host phenotypes, emphasizing the need for context-specific approaches to modulate the rumen microbiome. Overall, our results offer new perspectives on the assembly of ruminal microbes and underscore the potential of the Ruminosignatures framework for microbiome-informed precision agriculture and breeding initiatives aimed at enhancing feed efficiency and minimizing the environmental impact of cattle farming.

microbiology↗

bioRxiv2025

Mucinolysome in gut microbiomes of farm animals and humans

Mucins are glycoproteins that create a protective barrier protecting host tissues from microbial pathogens and are instrumental for host health. Here, we provide evidence that mucin glycan degradation in the gut can be mediated by mucinolysomes, defined as extracellular multi-enzyme complexes specializing in mucin glycan degradation. We computationally predicted the presence of mucinolysomes across 63 metagenome-assembled genomes (MAGs) and two isolated genomes of anaerobic Limousia bacteria, including seven MAGs from human samples of six countries. All 65 genomes were found to display core mucinolysome components, consisting of 3[~]6 scaffoldins (containing up to 12 cohesin modules) and up to 22 dockerin-containing mucin glycan-degrading CAZymes (carbohydrate active enzymes). The organization of mucinolysomes allows the assembly of up to 24 CAZymes in the same complex. We validated that a cultivated Limousia strain ET540 from chicken cecum can support growth on mucins as its sole carbon source, triggering the expression of most mucinolysome-related genes, including both scaffoldins and CAZymes. We also modeled the assembly of proteins into a multi-enzyme complex by predicting the cohesin-dockerin interactions among most of the mucinolysome proteins using AlphaFold3. While mucinolysosome-encoding Limousia have low abundance in different animal hosts, their abundance and prevalence are higher in farm animals than in humans, highlighting a potentially important role in livestock gut ecosystems. Our findings reveal a novel mechanism of mucin glycan degradation and provide a framework to explore microbial contributions to gut health and host-microbe interactions across species.

bioinformatics↗

bioRxiv2025

Systematic discovery of bacterial symbionts in rumen ciliate protozoa

Microbial interactions are fundamental to global ecological and evolutionary processes, exemplified by endosymbiosis between prokaryotes and single-cell eukaryotes that gave rise to organelles. While such associations remain widespread and ecologically important, the diversity and evolutionary dynamics of intracellular symbioses in many microbial ecosystems remain poorly understood. Here, we uncover a hidden layer of microbial complexity in the rumen ecosystem by identifying multiple endosymbiotic associations between ciliate protozoa and bacteria. Using genome-resolved metagenomics on protozoa enriched rumen fractions, we reveal diverse bacterial genomes exhibiting hallmarks of an obligate intracellular lifestyle. These candidate symbionts span several bacterial phyla and include close relatives of known endosymbionts and parasites of protists as well as previously unclassified or presumed free-living bacterial lineages that likely represent overlooked symbiont specialists. Our findings therefore expand the known distribution of bacterial endosymbiosis, establish the rumen - a key site of global carbon and nitrogen cycling - as a promising model for symbiosis research, and demonstrate the power of our approach to uncover hidden symbiotic associations across complex microbial communities. Overall, our results highlight the ubiquity and evolutionary significance of intracellular symbiosis as a shaping force in microbial ecosystems.

microbiology↗

bioRxiv2025

Spatial constraints drive amylosome-mediated resistant starch degradation by Ruminococcus bromii in the human colon

Degradation of complex dietary fiber by gut microbes is essential for colonic fermentation, short-chain fatty acid production, and microbiome function. Ruminococcus bromii is the primary resistant starch (RS) degrader in humans, which relies on the amylosome, a specialized cell-bound enzymatic complex. To unravel its architecture, function, and the interplay among its components, we applied an holistic multilayered approach and found that amylosome composition RS degradation, and enzymatic synergy are regulated at two levels: structural constraints enforcing enzyme proximity and expression-driven shifts in enzyme proportions. Cryo-electron tomography revealed that the amylosome comprises a constitutive extracellular layer extending toward the RS. However, proteomics demonstrated its remodeling across different growth conditions, with Amy4 and Amy16 comprising 60% of the amylosome in response to RS. Structural and biochemical analyses revealed complementarity and synergistic RS degradation by these enzymes, which allow R. bromii to fine-tune its adaptation to dietary fiber and shape colonic metabolism.

microbiology↗

bioRxiv2024

Understanding the Dynamics of Biomass Deconstruction by the Cellulolytic Anaerobe C. thermocellum

Clostridium thermocellum is one of the most efficient microorganisms for the deconstruction of cellulosic biomass. To achieve this high level of cellulolytic activity, C. thermocellum uses large multienzyme complexes known as cellulosomes to break down complex polysaccharides, notably cellulose, found in plant cell walls. The attachment of bacterial cells to the nearby substrate via the cellulosome has been hypothesized to be the reason for this high efficiency. The region lying between the cell and the substrate has shown great variation and dynamics that are affected by the growth stage of cells and the biomass used for growth. Here, we utilized both photoactivation localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) in combination with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to study the distribution of C. thermocellum cellulosomes at different stages of growth when actively growing on soluble and insoluble substrates, providing a clearer picture of the dynamics of cellulosome populations at the enzyme microbe substrate interface. This research demonstrates the promising application of novel optical methodologies in tandem with targeted mutations within C. thermocellum to test the prevailing theories regarding the mechanisms of cellulosomes and their potential to shuttle onto the biomass for the attachment of C. thermocellum to improve biomass deconstruction.

microbiology↗

bioRxiv2022

Multilayer Networks of Plasmid Genetic Similarity Reveal Potential Pathways of Gene Transmission

Antimicrobial resistance (AMR) is a major threat to public health. Plasmids are principal vectors of antimicrobial resistance genes, greatly contributing to their spread and mobility across hosts. Nevertheless little is known about the dynamics of plasmid genetic exchange across animal hosts. The cow rumen ecosystem is an excellent model system because it hosts diverse plasmid communities which interact and exchange genes. Here, we use theory and methodology from network and disease ecology to investigate the potential of gene transmission between plasmids using a data-set of 21 plasmidomes from a single dairy cow population. We constructed a multilayer network based on pairwise genetic similarity between plasmids serving as a signature for past genetic exchange to identify potential routes and mechanisms of gene transmission within and between cows. The transmission network was dominated by links between cows. Modularity analysis unraveled a major cross-cow transmission pathway with additional small pathways. Plasmid functions influenced network structure: plasmids containing mobility genes were more connected; those with the same AMR genes formed their own modules. We find signatures of gene superspreading in which a few plasmids and cows are responsible for most gene exchange. An agent-based transmission model showed that a new gene invading the cow population is likely to reach all cows. Finally, we showed that link weights contain a non-random signature for the mechanisms of gene transmission allowing us to differentiate between dispersal and genetic exchange. These results provide insights into the mechanisms by which genes, including those providing AMR, spread across animal hosts.

ecology↗

bioRxiv2022

A link between genotype and cellular architecture in microbiome members as revealed by cryo-EM

Microbial taxonomy is not yet sufficient to describe microbe functionality and ecology. Since function is often linked to structure, we sought here to use cryo-electron microscopy and tomography to analyze microbial cellular architecture and correlate it to specific phylogenies and genomes. We cultured and imaged a large collection of microbiota covering 90% of the richness of the core rumen microbiome at the family level, which we selected as a model for our analyses. Based on measurements of several parameters, we found that the structural similarity of microbiota is significantly related to their taxonomic distance, i.e., closely related microbes have similar cellular architectures. However, above the Family level, these similarities end: the structural diversity stops increasing with phylogenetic distance. Our results highlight that cellular architectures could serve as an important parameter in microbial ecology and microbial ecosystems.

microbiology↗

bioRxiv2022

A human DNA methylation atlas reveals principles of cell type-specific methylation and identifies thousands of cell type-specific regulatory elements

DNA methylation is a fundamental epigenetic mark that governs chromatin organization, cell identity, and gene expression. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 207 healthy tissue samples. Replicates of the same cell-type are >99.5% identical, demonstrating robustness of cell identity programs to genetic variation and environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny, and identifies methylation patterns retained since gastrulation. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hyper-methylated loci are rare and are enriched for CpG islands, polycomb targets, and CTCF binding sites, suggesting a novel role in shaping cell type-specific chromatin looping. The atlas provides an essential resource for interpretation of disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies. Summary paragraphDNA methylation, a fundamental epigenetic mark, governs chromatin organization and gene expression1, thus defining the molecular identity of cells and providing a window into developmental processes with wide-ranging physiologic and clinical ramifications. Current DNA methylation datasets have limitations, typically including only a fraction of methylation sites, many from cell lines that underwent massive changes in culture or from tissues containing unspecified mixtures of cells2-6. We present a human methylome atlas based on deep whole-genome bisulfite sequencing of 39 sorted, primary cell types and use this dataset to address fundamental questions in developmental biology, physiology and pathology. Biological replicates are >99.5% identical, demonstrating unappreciated robustness to genetic variation and environmental perturbations. Clustering recapitulates key elements of tissue ontogeny, identifying methylation patterns retained since gastrulation. Loci uniquely unmethylated in individual cell types identify novel transcriptional enhancers and are enriched for tissue-specific transcription factors binding motifs. In contrast, loci uniquely hyper-methylated in specific cell types are rare, enriched for CpG islands and polycomb targets, and overlap CTCF binding sites, suggesting a novel role in shaping cell-type-specific chromatin looping. Finally, the atlas facilitates fragment-level deconvolution of tissue and plasma methylomes across thousands of cell-type specific regions to quantify their individual components at unprecedented resolution. The human cell-type-specific methylation atlas provides an essential resource for studying gene regulation by defining cell-type-specific distal enhancers and regulators of 3D organization, for identifying pathological changes in DNA methylation, and for the interpretation of methylation-based liquid biopsies. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY O_LIA deep methylation atlas of 39 human cell types, sorted from healthy samples C_LIO_LIMethylomes record developmental history of cells C_LIO_LIThousands of novel cell type-specific methylation markers C_LIO_LIHypo-methylation uncovers cell type-specific regulatory map of distal enhancers C_LIO_LIHyper-methylation across CTCF sites C_LIO_LICell type-specific biomarkers facilitate fragment-level deconvolution of tissues and cfDNA C_LI

genomics↗

bioRxiv2021

Asgard ESCRT-III and VPS4 reveal evolutionary conserved chromatin binding properties of the ESCRT machinery

The ESCRT machinery drive membrane remodeling in numerous processes in eukaryotes. Genes encoding for ESCRT proteins have been identified in Asgard archaea, a newly discovered superphylum, currently recognized as the ancestor of all eukaryotes. This begs the question of the functional evolutionary origin of this machinery and its conservation across lineages. Here, we find that Asgard-ESCRTs exhibit conserved DNA-binding properties, which is derived from recruitment of specific members. We show that Asgard-ESCRT-III/VPS4 homologs interact with one another inside mammalian cells, associate with chromatin, and recruit their counterparts to organize in discrete foci in the mammalian nucleus. This is congruent with human-ESCRT-III homologs. We find that human- and Asgard-ESCRT-IIIs associate with chromatin via the same N terminal domain, and that human-ESCRT-III can recruit Asgard-VPS4 to the nucleus to form foci. Therefore, ESCRTs possess chromatin binding properties that were preserved through the billion years of evolution that separate Asgard and human cells.

cell biology↗

bioRxiv2021

Generation of lineage-resolved complete metagenome-assembled genomes by precision phasing

Microbial communities in many environments include distinct lineages of closely related organisms which have proved challenging to separate in metagenomic assembly, preventing generation of complete metagenome-assembled genomes (MAGs). The advent of long and accurate HiFi reads presents a possible means to address this challenge by generating complete MAGs for nearly all sufficiently abundant bacterial genomes in a microbial community. We present a metagenomic HiFi assembly of a complex microbial community from sheep fecal material that resulted in 428 high-quality MAGs from a single sample, the highest resolution achieved with metagenomic deconvolution to date. We applied a computational approach to separate distinct haplotype lineages and identified haplotypes of hundreds of variants across hundreds of kilobases of genomic sequence. Analysis of these haplotypes revealed 220 lineage-resolved complete MAGs, including 44 in single circular contigs, and demonstrated improvement in overall assembly compared to error-prone long reads. We report the characterization of multiple, closely-related microbes within a sample with potential to improve precision in assigning mobile genetic elements to host genomes within complex microbial communities.

microbiology↗

bioRxiv2021

GNPS Dashboard: Collaborative Analysis of Mass Spectrometry Data in the Web Browser

Access to web-based platforms has enabled scientists to perform research remotely. A critical aspect of mass spectrometry data analysis is the inspection, analysis, and visualization of the raw data to validate data quality and confirm statistical observations. We developed the GNPS Dashboard, a web-based data visualization tool, to facilitate synchronous collaborative inspection, visualization, and analysis of private and public mass spectrometry data remotely.

bioinformatics↗

bioRxiv2021

Nanoscale resolution of microbial fiber degradation in action

Deconstruction of plant cell walls is imperative to global carbon cycling and sustainability efforts. Selected microbes degrade plant fibers using extremely efficient multi-enzymatic cellulosomes assemblies. Organization of cellulosomes on the bacterial cell surface and their ecological regulation remain elusive. By combining structural methodologies with molecular and biochemical approaches on the canonical Clostridium thermocellum system, we provide an unprecedented view into the in-situ structure and distribution of cellulosomal enzymes while interacting with their cellulosic substrate during fiber degradation. Structural exploration of growing cultures revealed isogenic phenotypic heterogeneity of cellulosome organization on single cells across the bacterial population, suggesting a division-of labor strategy driven by product-dependent dynamics. This study demonstrates how structural biology under near-physiological conditions can be employed to develop ecological hypotheses to understand microbial plant-fiber degradation at the single-cell nanoscale level. One Sentence SummaryThis study contributes critical insights into the in-situ organization of cellulosomes and their cellulosic substrates and provides evidence for phenotypic heterogeneity, with dynamic, growth phase-dependent organization of the fiber-degrading machinery.

microbiology↗

bioRxiv2020

SCAPP: An algorithm for improved plasmid assembly in metagenomes

BackgroundMetagenomic sequencing has led to the identification and assembly of many new bacterial genome sequences. These bacteria often contain plasmids: usually small, circular double-stranded DNA molecules that may transfer across bacterial species and confer antibiotic resistance. These plasmids are generally less studied and understood than their bacterial hosts. Part of the reason for this is insufficient computational tools enabling the analysis of plasmids in metagenomic samples. ResultsWe developed SCAPP (Sequence Contents-Aware Plasmid Peeler) - an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. SCAPP builds on some key ideas from the Recycler algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids. We compared the performance of SCAPP to Recycler and metaplasmidSPAdes on simulated metagenomes, real human gut microbiome samples, and a human gut plasmidome dataset that we generated. We also created plasmidome and metagenome data from the same cow rumen sample and used the parallel sequencing data to create a novel assessment procedure. Overall, SCAPP outperformed Recycler and metaplasmidSPAdes across this wide range of datasets. ConclusionsSCAPP is an easy to use Python package that enables the assembly of full plasmid sequences from metagenomic samples. It outperformed existing metagenomic plasmid assemblers in most cases, and assembled novel and clinically relevant plasmids in samples we generated such as a human gut plasmidome. SCAPP is open-source software available from: https://github.com/Shamir-Lab/SCAPP.

bioinformatics↗

bioRxiv2020

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a "balance score" that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

bioinformatics↗

bioRxiv2019

PlasClass improves plasmid sequence classification

BackgroundMany bacteria contain plasmids, but separating between contigs that originate on the plasmid and those that are part of the bacterial genome can be difficult. This is especially true in metagenomic assembly, which yields many contigs of unknown origin. Existing tools for classifying sequences of plasmid origin give less reliable results for shorter sequences, are trained using a fraction of the known plasmids, and can be difficult to use in practice. ResultsWe present PlasClass, a new plasmid classifier. It uses a set of standard classifiers trained on the most current set of known plasmid sequences for different sequence lengths. PlasClass outperforms the state-of-the-art plasmid classification tool on shorter sequences, which constitute the majority of assembly contigs, while using less time and memory. ConclusionsPlasClass can be used to easily classify plasmid and bacterial genome sequences in metagenomic or isolate assemblies. It is available from: https://github.com/Shamir-Lab/PlasClass

bioinformatics↗

bioRxiv2019

Context-dependent dynamics lead to the assembly of functionally distinct pitcher-plant microbiomes

Niche construction through interspecific interactions can condition future community states on past ones. However, the extent to which such history dependency can steer communities towards functionally different states remains a subject of active debate. Using bacterial communities collected from wild pitchers of the carnivorous pitcher plant, Sarracenia purpurea, we tested the effects of history on composition and function across communities assembled in synthetic pitcher plant microcosms. We found that the diversity of assembled communities was determined by the diversity of the system at early, pre-assembly stages. Species composition was also contingent on early community states, not only because of differences in the species pool, but also because the same species had different dynamics in different community contexts. Importantly, compositional differences were proportional to differences in function, as profiles of resource use were strongly correlated with composition, despite convergence in respiration rates. Early differences in community structure can thus propagate to mature communities, conditioning their functional repertoire.

ecology↗