Biology subjects

Lesker, T. R.

Publications and source records attributed to Lesker, T. R..

12 recordsLinked to original sources

bioRxiv2026

The microbiome determines the phenotype in CTLA-4 insufficient mice and men

CTLA-4 (haplo)insufficiency displays incomplete penetrance and phenotypic heterogeneity, indicating the involvement of additional disease modifiers beyond the genetic defect. Microbiome analyses reveal a positive association between disease severity and intestinal dysbiosis, highlighting the microbiome as a critical contributor. To investigate this relationship mechanistically, we generated Ctla4/- wildlings harboring a natural microbiota. Unlike specific pathogen free (SPF) counterparts, which remain healthy, Ctla4/- wildlings spontaneously develop disease phenotypes resembling human CTLA-4 haploinsufficiency. Disease onset is followed by reduced microbial diversity and expansion of pathobionts. Integrative immunophenotyping shows that the natural microbiota synergizes with Ctla4 haploinsufficiency to reshape innate and adaptive immune compartments, generating a sustained pro-inflammatory milieu and reduced CTLA-4 expression in the cecum. Furthermore, microbiota-derived metabolites promote inflammatory cytokine production in both murine and human primary T cells via NF-{kappa}B activation. Collectively, Ctla4/- wildlings constitute an effective model for dissecting microbiome-immune crosstalk in CTLA-4 (haplo)insufficiency and for exploring therapeutic strategies.

immunology↗

bioRxiv2025

Probiotic-conditioned microbiota from preterm infants modulate immune response to pathogen challenge in a humanized mouse model

AbstractEarly-life host-microbe interactions critically shape immune development, lifelong homeostasis, and disease susceptibility. The PRIMAL trial (Priming Immunity at the Beginning of Life) demonstrated that multistrain probiotics shifted the gut microbiota of very preterm infants toward eubiosis without affecting sepsis incidence, yet the immunological consequences remained unresolved. To explore this, we colonized germ-free female mice with fecal samples from probiotic- or placebo-treated preterm infants from the PRIMAL trial. Microbiota composition was vertically transmitted and stable across generations. At steady-state, 3-week-old pups colonized with probiotic-conditioned microbiota exhibited markedly reduced populations of innate immune cells, particularly in the colon, with subtler effects in the small intestine and spleen, while adaptive immune subsets were less affected. Upon enteropathogenic Escherichia coli challenge at day 5, pups harboring probiotic-conditioned microbiota displayed reduced growth and impaired bacterial clearance, correlating with diminished numbers of key innate immune cell populations. These findings demonstrate that probiotic-driven shifts in human-derived microbial communities can attenuate immune cell development in mice and alter early-life infection outcomes. Our study underscores the complex, context-dependent effects of probiotics on the neonatal microbiota-immune axis and provides mechanistic insight into how interventions in preterm infants may influence susceptibility to infection.

immunology↗

bioRxiv2025

Interleukin-17A Mediates Cardiorenal Injury In Oxalate Nephropathy

AimsCardiovascular disease (CVD) is the leading cause of mortality in chronic kidney disease (CKD). While CKD is known to give rise to systemic inflammation, its inciting factors remain poorly defined. Oxalate, long implicated in rare genetic kidney disorders, accumulates with decreased kidney function and has emerged as a driver of inflammation and independent risk factor for CVD. Here, we investigate the immunological mechanisms linking oxalate nephropathy to systemic inflammation, cardiac damage and kidney injury. Methods and ResultsOxalate nephropathy was induced in C57Bl6/N mice via an oxalate-enriched diet. Oxalate induced systemic immune activation, renal fibrosis, and cardiac remodeling, including pulmonary congestion with systolic and diastolic dysfunction. Flow cytometry analysis identified interleukin (IL)-17A as a dominant inflammatory effector, with expansion of Th17 and Th17-like Treg in the kidney, intestine, and spleen. Bulk mRNA sequencing confirmed these findings. Confirming the oxalate-IL-17A relationship, plasma IL-17A was elevated in patients with primary hyperoxaluria. Gut microbiome analysis by 16S amplicon sequencing showed only mild oxalate-induced alterations in mice. However, soluble oxalate directly enhanced Th17 polarization and disrupted mitochondrial respiration in vitro. In vivo, antibody-mediated (clone: 17F3) IL-17A blockade decreased cardiac fibrosis, reduced neutrophil infiltration, and partially restored cardiac function in oxalate-fed mice. ConclusionsOur study identifies oxalate as a systemic immunometabolic stressor and IL-17A as a central mediator of oxalate-induced cardiorenal injury. These findings establish the oxalate-IL-17A axis as a mechanistic link between CKD and CVD and suggest IL-17A inhibition as a potential therapeutic strategy to reduce cardiovascular damage in CKD. Translational PerspectiveThis study advances our understanding of targetable mediators of the cardiovascular risk in chronic kidney disease (CKD). We identify the organic anion oxalate, beyond its traditional role in crystal-induced kidney damage, as a systemic immunometabolic stressor. We demonstrate that oxalate induces IL-17A-mediated inflammation and thereby contributes to maladaptive cardiac remodeling. Therapeutic blockade of IL-17A protects against oxalate-induced cardiorenal injury, highlighting the oxalate-IL-17A axis as a relevant and druggable link between CKD and cardiovascular disease.

immunology↗

bioRxiv2025

Metabolites produced by gut bacteria under anoxic conditions drive the suppression of Acinetobacter baumannii

Multidrug-resistant (MDR) bacteria pose a significant global health threat. Among these, Acinetobacter baumannii, particularly carbapenem-resistant A. baumannii, is a leading cause of healthcare-associated infections. Emerging evidence links gut colonization to systemic infections, highlighting opportunities for new control strategies. We demonstrate that A. baumannii can survive under anaerobic conditions ([≤]1%) and shows limited growth under low oxygen conditions ([≥]1%), underscoring its adaptation to niches in the intestine. However, specific carbohydrates, including maltose, provide the gut bacteria Klebsiella oxytoca with a competitive advantage under anoxic conditions, enabling it to actively suppress A. baumannii through its metabolism. Notably, maltose induces this suppressive capacity in other commensals and complex gut microbiomes as well. Force-feeding experiments in Galleria mellonella larvae corroborate that K. oxytoca in combination with maltose significantly reduces A. baumannii recovery in gut environments. These findings suggest that targeted carbohydrate supplementation could enhance probiotic strategies, creating an environment unfavorable to A. baumannii.

microbiology↗

bioRxiv2025

Gene-centric metagenomic analyses reveal microbiome functional insights into diseases

The microbiome encodes millions of genes; however, understanding their role in human health remains challenging. Here, we developed MetaGEAR, a gene-centric analysis framework for metagenomic data. MetaGEAR constructs cohort-specific databases for efficient retrieval of gene annotations, abundances, and co-localization, while providing enhanced taxonomic resolution by integrating reference- and assembly-based approaches. This is combined with a Metagenomic Assembled Graph (MAGraph) capturing gene neighborhood information. Using MetaGEAR, we built a multi-cohort database comprising >33 million gene families to investigate microbiome functionality across 24 cohorts of inflammatory bowel disease, colorectal cancer, and healthy populations and identified disease signature genes. Furthermore, the MAGraph revealed mobile genetic elements acting as hubs for tetracycline resistance spreading among Enterococcus, Streptococcus, and Veillonella species. Also, a duplicated nitrate reduction operon in Klebsiella pneumoniae was linked to differential gene expression under stress and virulence-inducing conditions. In summary, gene-centric metagenomic analyses reveal important insights into microbiome functionality in diseases.

microbiology↗

bioRxiv2025

Mucosal innate immune activation as the trigger to Prevotella species-induced arthritis in genetically resistant mice

An altered gut microbiota, particularly the expansion of Prevotellaceae members, is increasingly implicated in the pathogenesis of rheumatoid arthritis (RA), yet the mechanisms hind this phenomenon remain unclear. Here, we demonstrate that Palleniella intestinalis, a member of the Prevotellaceae family, induces a 100% arthritis incidence in genetically resistant C57BL/6 mice. Inoculation with P. intestinalis modifies gut microbiota ecology, increases intestinal permeability, and selectively activates colonic CD11bCD11c myeloid cells, facilitating Th17 differentiation and driving joint inflammation. In vitro, outer membrane vesicles (OMV) from P. intestinalis and Segatella copri (formerly known as Prevotella copri) prime bone marrow-derived dendritic cells (BMDCs) to drive Th17 differentiation in an IL-6-dependent manner. Similar changes with increase in innate immune cell activation and IL-6 levels were shown in gut biopsies from new-onset RA patients. The transfer of Prevotellaceae-derived OMVs or Prevotellaeae-primed BMDCs replicates the hightened arthritis incidence in resistant mice, highlighting the critical role of intestinal immune activation in RA. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/643707v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1ce227corg.highwire.dtl.DTLVardef@3a2d0eorg.highwire.dtl.DTLVardef@16404b6org.highwire.dtl.DTLVardef@1717dc1_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIColonization with Paleniella intestinalis bypasses genetic resistance, consistently inducing arthritis incidence in non-susceptible C57BL/6 mice C_LIO_LIP. intestinalis activates colonic CD11b+CD11c+ myeloid cells, driving systemic Th17 cell differentiation C_LIO_LIIn vitro, outer membrane vesicles from P. intestinalis or RA-derived S. copri RPC01 primed DCs that drive Th17 differentiation in an IL-6-dependent manner C_LIO_LITransfer of P. intestinalis-primed DCs or its outer membrane vesicles alone increases arthritis incidence in non-susceptible C57BL/6 mice C_LI

immunology↗

bioRxiv2024

The RNA landscape of the human commensal Segatella copri reveals a small RNA essential for gut colonization

The bacterium Segatella copri is a prevalent member of the human gut microbiota associated with both health and disease states, but intrinsic factors that determine its ability to effectively colonize the gut are not understood. By extensive transcriptome mapping of S. copri and examining human-derived samples, we discover a previously unknown small RNA named here Segatella RNA colonization factor (SrcF). We show that SrcF is essential for S. copri gut colonization in a gnotobiotic mouse model. SrcF regulates genes involved in nutrient acquisition, and its own expression is controlled by complex carbohydrates, particularly fructans. Furthermore, SrcF expression is strongly influenced by human microbiome composition and by the breakdown of fructans by cohabitating commensals, suggesting that the breakdown of complex carbohydrates mediates inter-species signaling among commensals beyond its established function in generating energy. Together, this study highlights the contribution of a small RNA as a key regulator in gut colonization.

microbiology↗

bioRxiv2022

Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in severe COVID-19

The clinical course of the 2019 coronavirus disease (COVID-19) is variable and to a substantial degree still unpredictable, especially in persons who have neither been vaccinated nor recovered from previous infection. We hypothesized that disease progression and inflammatory responses were associated with alterations in the microbiome and metabolome. To test this, we integrated metagenome, metabolome, cytokine, and transcriptome profiles of longitudinally collected samples from hospitalized COVID-19 patients at the beginning of the pandemic (before vaccines or variants of concern) and non-infected controls, and leveraged detailed clinical information and post-hoc confounder analysis to identify robust within- and cross-omics associations. Severe COVID-19 was directly associated with a depletion of potentially beneficial intestinal microbes mainly belonging to Clostridiales, whereas oropharyngeal microbiota disturbance appeared to be mainly driven by antibiotic use. COVID-19 severity was also associated with enhanced plasma concentrations of kynurenine, and reduced levels of various other tryptophan metabolites, lysophosphatidylcholines, and secondary bile acids. Decreased abundance of Clostridiales potentially mediated the observed reduction in 5-hydroxytryptophan levels. Moreover, altered plasma levels of various tryptophan metabolites and lower abundances of Clostridiales explained significant increases in the production of IL-6, IFN{gamma} and/or TNF. Collectively, our study identifies correlated microbiome and metabolome alterations as a potential contributor to inflammatory dysregulation in severe COVID-19. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/518860v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@afc4edorg.highwire.dtl.DTLVardef@1a9ac2aorg.highwire.dtl.DTLVardef@65fb46org.highwire.dtl.DTLVardef@153ee6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2020

Tutorial: Assessing metagenomics software with the CAMI benchmarking toolkit

Computational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices, common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized data sets, procedures, and metrics for evaluation. In this tutorial, we describe emerging standards in computational metaomics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics to assess metagenome assembly, binning, and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI data sets. This tutorial will serve as a reference to the community and facilitate informative and reproducible benchmarking in microbiome research.

bioinformatics↗

bioRxiv2019

An integrated metagenome catalog reveals novel insights into the murine gut microbiome

The vast complexity of host-associated microbial ecosystems requires generation of host-specific gene catalogs to survey the functions and diversity of these communities. We generated a comprehensive resource, the integrated mouse gut metagenome catalog (iMGMC), comprising 4.6 million unique genes and 660 high-quality metagenome-assembled genomes (MAGs) linked to reconstructed full-length 16S rRNA gene sequences. iMGMC enables unprecedented coverage and taxonomic resolution, i.e. more than 89% of the identified taxa are not represented in any other databases. The tool (github.com/tillrobin/iMGMC) allowed characterizing the diversity and functions of prevalent and previously unknown microbial community members along the gastrointestinal tract. Moreover, we show that integration of MAGs and 16S rRNA gene data allows a more accurate prediction of functional profiles of communities than based on 16S rRNA amplicons alone. Integrated gene catalogs such as iMGMC are needed to enhance the resolution of numerous existing and future sequencing-based studies.

microbiology↗

bioRxiv2018

Nucleotide-pair encoding of 16S rRNA sequences for host phenotype and biomarker detection

Identifying combinations of taxa distinctive for microbiome-associated diseases is considered key to the establishment of diagnosis and therapy options in precision medicine and imposes high demands on accuracy of microbiome analysis techniques. We propose subsequence based 16S rRNA data analysis, as a new paradigm for microbiome phenotype classification and biomarker detection. This method and software called DiTaxa substitutes standard OTU-clustering or sequence-level analysis by segmenting 16S rRNA reads into the most frequent variable-length subsequences. These subsequences are then used as data representation for downstream phenotype prediction, biomarker detection and taxonomic analysis. Our proposed sequence segmentation called nucleotide-pair encoding (NPE) is an unsupervised data-driven segmentation inspired by Byte-pair encoding, a data compression algorithm. The identified subsequences represent commonly occurring sequence portions, which we found to be distinctive for taxa at varying evolutionary distances and highly informative for predicting host phenotypes. We compared the performance of DiTaxa to the state-of-the-art methods in disease phenotype prediction and biomarker detection, using human-associated 16S rRNA samples for periodontal disease, rheumatoid arthritis and inflammatory bowel diseases, as well as a synthetic benchmark dataset. DiTaxa identified 17 out of 29 taxa with confirmed links to periodontitis (recall= 0.59), relative to 3 out of 29 taxa (recall= 0.10) by the state-of-the-art method. On synthetic benchmark data, DiTaxa obtained full precision and recall in biomarker detection, compared to 0.91 and 0.90, respectively. In addition, machine-learning classifiers trained to predict host disease phenotypes based on the NPE representation performed competitively to the state-of-the art using OTUs or k-mers. For the rheumatoid arthritis dataset, DiTaxa substantially outperformed OTU features with a macro-F1 score of 0.76 compared to 0.65. Due to the alignment- and reference free nature, DiTaxa can efficiently run on large datasets. The full analysis of a large 16S rRNA dataset of 1359 samples required {approx}1.5 hours on 20 cores, while the standard pipeline needed {approx}6.5 hours in the same setting.\n\nAvailabilityAn implementation of our method called DiTaxa is available under the Apache 2 licence at http://llp.berkeley.edu/ditaxa.

bioinformatics↗

bioRxiv2018

CAMISIM: Simulating metagenomes and microbial communities

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required. Here, we describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series and differential abundance studies, includes real and simulated strain-level diversity, and generates second and third generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT and metaSPAdes, on several thousand small data sets generated with CAMISIM. CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with truth standards for method evaluation. All data sets and the software are freely available at: https://github.com/CAMI-challenge/CAMISIM

bioinformatics↗