Biology subjects

Six, A.

Publications and source records attributed to Six, A..

14 recordsLinked to original sources

bioRxiv2026

A regulatory T cell signature provides a shared molecular basis for the therapeutic window of opportunity in rheumatic disease

Rheumatic diseases, including rheumatoid arthritis (RA), spondyloarthritis (SpA) and osteoarthritis (OA), show distinct phenotypes yet respond to overlapping therapies, implicating shared immune mechanisms. In the Transimmunom cohort, we profiled peripheral blood from 240 individuals (47 healthy, 44 OA, 91 RA, 58 SpA) across deep immunophenotyping, immunoproteomics and Treg-Teff transcriptomics. Single-layer analyses revealed broader Treg than Teff remodeling, along with a shared pattern of reduced activated Tregs and expanded Helios+ Tregs across all diseases, alongside a decrease in functional Treg subpopulations, including CTLA4+ and CD45RA- Tregs. In RA specifically, LAG3+ Tregs were also expanded. Combining omics layers outperformed single-layer approaches for disease classification. Among individual layers, Treg transcriptomes were most discriminative, and integration uncovered disease-specific programs. Unsupervised clustering identified a cross-disease cluster independent of activity, treatment and age, mapping to early disease (<= years) and dominated by a Treg dysfunction-associated program. These results provide a biological rationale for the therapeutic "window of opportunity" concept and duration-stratified Treg-directed trials.

immunology↗

bioRxiv2025

Transcriptomic module fingerprint reveals heterogeneity of whole blood transcriptome in type 1 diabetic patients

BackgroundType 1 diabetes (T1D) is a complex autoimmune disease resulting from {beta}-cell destruction in the pancreas. Yet, no gene signature derived from whole blood samples has been established to differentiate T1D patients from healthy donors, likely because of the high heterogeneity of the underlying pathophysiological mechanisms. MethodsWe analysed whole blood transcriptomic profiles from 39 patients and 43 healthy donors, collected as part of our observational clinical trial, using a multi-step multivariate statistical analysis. This approach combined classical differential analysis, random forest and support vector machine classifications, gene set functional enrichment analysis to construct the most stable and reliable gene signature. ResultsClassical differential analysis did not separate clearly samples into healthy and T1D clusters, but rather spread samples into three clusters. On the contrary, we show that our approach, which combined molecular signatures independently constructed, adds robustness to the analysis without compromising the specificity. This efficiency was demonstrated by the clear separation of the samples according to their diagnosis group. Also, the functional annotation of the gene modules that we obtained was more associated with T1D-related pathways compared to the classical statistical analysis. ImpactsThese results emphasize that single differential analyses are not able to capture immune continuums involved in such a complex pathophysiological process. We hypothesize that T1D patients can have different molecular pathways involved in their pathology or/and can display unsynchronized -omics profiles. These findings call for further investigations to identify the molecular pathways involved in T1D patients, and for revising the nosology of autoimmune diseases.

bioinformatics↗

bioRxiv2025

Thymic selection of the T cell receptor repertoire is biased toward autoimmunity in females

Women represent about 80% of patients with autoimmune diseases. This may partly result from sex-based differences in T cell receptor (TCR) selection during thymocyte development, potentially influenced by hormones and the lower expression of the Autoimmune Regulator (AIRE) transcription factor in females. To investigate this, we analyzed sex-specific differences in TCR generation and selection. We examined TCR repertoires in double-positive thymocytes and single-positive thymic cells, including CD8 and CD4 effector T cells and regulatory T cells (Tregs), derived from male and female organ donors. Minimal sex-based differences were observed in V and J gene usage, and there were no notable differences in TCR repertoire diversity, complementarity-determining region 3 (CDR3) length, amino acid composition, or network structure. No TCR sequences were exclusive to either sex. However, female effector T cells exhibited a significantly higher prevalence of TCRs specific to self-antigens implicated in autoimmunity compared to males, while female Tregs showed a reduced frequency of such TCRs. These differences were not observed for TCRs targeting self-antigens unrelated to autoimmunity or antigens associated with cancer or viruses. Our findings identify a sex-specific imbalance in thymic selection of TCRs with autoimmunity-associated specificities, providing mechanistic insight into the increased susceptibility of women to autoimmune diseases.

systems biology↗

bioRxiv2024

Immunological Profiling in Knee Osteoarthritis: Treg Dysfunction as Key Driver of Pain

Pain is the hallmark symptom of osteoarthritis (OA) and its biological drivers remain poorly understood. While the role of innate immunity in OA has been extensively studied, the involvement of adaptive immunity, in particular regulatory T cells (Tregs), is not well understood. Using a comprehensive multi-omic approach on the peripheral blood from 46 knee OA patients with similar radiographic stage, including deep immunophenotyping, cytokine profiling, transcriptomic and T-cell receptor analysis on sorted CD4 Tregs and effector T cells (Teff), we identified an immunological signature associated with OA-related pain. Cytokines promoting Treg expansion and activation (with increases of sIL2-RA, sTNFR1, sTNFR2) were correlated with the Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain subscore, suggesting a potential Treg dysfunction. Nineteen T cell subsets were correlated with WOMAC pain. Notably, we found a negative correlation of cell subsets associated with Treg expansion and activation (FoxP3+CTLA4+, CD4+CD57+, Treg CD95+, CD4 Treg CD45RA-). Differential gene expression analysis between patients with low and high WOMAC pain intensity (threshold [≥] 40/100) revealed an upregulation of inflammasome-related genes such as IL1RL1, IL31RA, IFITM3, NLRP3, IFNG in Tregs. Functional enrichment analysis highlighted an overrepresentation of innate immune response, IL-8, and interferon activation pathways suggesting a pro-inflammatory state in Tregs of patients with high pain intensity. Collectively, our systems immunology approach highlights multiple associations between Treg dysfunctionality and OA-related pain, providing new insights into the adaptive immune systems contribution to OA-related pain.

immunology↗

bioRxiv2024

AnalyzAIRR: A user-friendly guided workflow for AIRR data analysis

The analysis of bulk adaptive immune receptor repertoires (AIRR) enables the understanding of immune responses in both normal and pathological conditions. However, the complexity of AIRR calls for advanced, specialized methods to extract meaningful biological insights. These sophisticated approaches often present challenges for researchers with limited bioinformatics expertise, hindering access to comprehensive immune system analysis. To address this challenge, we developed AnalyzAIRR, an AIRR-compliant R package enabling advanced bulk AIRR sequencing data. The tool integrates state-of-the-art statistical and visualization methods applicable at various levels of granularity. It offers a platform for general data exploration, filtering and manipulation, and in-depth cross-comparisons of AIRR datasets, aimed at answering specific biological questions. We illustrate AnalyzAIRR functionalities using of a published murine dataset of 18 T-cell receptor repertoires from three diferrent T cell subsets. We first detected and removed a major contaminant in a group of samples, before proceeding with to the comparative analysis. Subsequent cross-sample analysis revealed differences in repertoire diversity that aligned with the respective cell phenotypes, and in repertoire convergence among the studied subsets. AnalyzAIRRs set of analytical metrics is integrated into a Shiny web application and complemented with a tutorial to help users in their analytical strategy, making it user-friendly for biologists with little or no background in bioinformatics.

bioinformatics↗

bioRxiv2024

From raw microalgae to bioplastics: conversion of Chlorella vulgaris starch granules into thermoplastic starch

Microalgae are emerging as a promising feedstock for bioplastics, with Chlorella vulgaris yielding significant amounts of starch. This polysaccharide is convertible into thermoplastic starch (TPS), a biodegradable plastic of industrial relevance. In this study, we developed a pilot-scale protocol for extracting and purifying starch from starch-enriched Chlorella vulgaris biomass. From 430.3 {+/-} 0.5 g (dry weight - DW) of microalgae biomass containing 42.2 {+/-} 3.4 % of starch, we successfully extracted 205.8 {+/-} 1.2 gDW of purified starch extract containing 86.9 {+/-} 3.0 % of starch, resulting in a final recovery yield of 98.5%. We have characterized this extracted starch and processed it into TPS using twin-screw extrusion and injection molding. Microalgal starch showed similar properties to those of native plant starch, but with smaller granules. We compared the mechanical properties of microalgal TPS with two controls, namely a commercial TPS and a TPS prepared from commercial potato starch granules. TPS prepared from microalgal starch showed a softer and more ductile behavior compared to the reference materials. This study demonstrates the feasibility of recovering high-purity microalgal starch on a pilot scale with high yields, and highlights the potential of microalgal starch for the production of TPS using industrially relevant processes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/589749v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@f2f7fcorg.highwire.dtl.DTLVardef@176dc8corg.highwire.dtl.DTLVardef@8989d3org.highwire.dtl.DTLVardef@1b7b978_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

bioRxiv2022

OntoContext, a new python package for gene contextualization based on the annotation of biomedical texts

MotivationThe automatic mining for bibliography exploitation in given contexts is a challenge according to the increasing number of scientific publications and new concepts. Several indexing systems were developed for biomedical literature. However, such systems have failed to produce contextualised research of genes and proteins and automatically group texts according to shared concepts. In this paper, we present OntoContext, a contextualization system crossing the use of biomedical ontologies to annotate texts containing terms related to cell populations, anatomical locations and diseases and to extract gene, RNA or protein names in these contexts. ResultsOntoContext, a new python package contains two modules. The "annot" module for "annotation" function, is based on combination of morphosyntactic labelling and exact matching and on dictionaries derived from the Cell Ontology, the UBERON Ontology (anatomical context), the Human Disease Ontology and geniatagger, (which contains particular tags for gene-related names). The "annot" output is used as input for the second module "crisscross" generating lists of gene-related names obtained by crossing annotations from the three mentioned ontologies. OntoContext showed better performances than NCBO Annotator after evaluation on two text corpuses. OntoContext is freely available in the pypi. Availabilityhttps://pypi.python.org/pypi/OntoContext and https://github.com/walidbedhiafi/OntoContext1. Contactadrien.six@sorbonne-universite.fr

bioinformatics↗

bioRxiv2020

Human thymopoiesis selects unconventional CD8+ α/β T cells that respond to multiple viruses.

T cell receptors (TCRs) are formed by stochastic gene rearrangements, theoretically generating >1019 sequences. They are selected during thymopoiesis, which releases a repertoire of about 108 unique TCRs per individual. How evolution shaped a process that produces TCRs that can effectively handle a countless and evolving set of infectious agents is a central question of immunology. The paradigm is that a diverse enough repertoire of TCRs should always provide a proper, though rare, specificity for any given need. Expansion of such rare T cells would provide enough fighters for an effective immune response and enough antigen-experienced cells for memory. We show here that human thymopoiesis releases a large population of CD8+ T cells harboring /{beta} paired TCRs that (i) have high generation probabilities and (ii) a preferential usage of some V and J genes, (iii) are shared between individuals and (iv) can each recognize and be activated by multiple unrelated viral peptides, notably from EBV, CMV and influenza. These polyspecific T cells may represent a first line of defense that is mobilized in response to infections before a more specific response subsequently ensures viral elimination. Our results support an evolutionary selection of polyspecific /{beta} TCRs for broad antiviral responses and heterologous immunity.

immunology↗

bioRxiv2020

Pyocin efficacy in a murine model of Pseudomonas aeruginosa sepsis

SynopsisO_ST_ABSBackgroundC_ST_ABSBloodstream infections with antibiotic resistant Pseudomonas aeruginosa are common and increasingly difficult to treat. Pyocins are naturally occurring protein antibiotics produced by P. aeruginosa that have potential for human use. ObjectivesTo determine if pyocin treatment is effective in a murine model of sepsis with P. aeruginosa. MethodsRecombinant pyocins S5 and AP41 were purified tested for efficacy in a Galleria mellonella infection model and a murine model of P. aeruginosa sepsis. ResultsBoth pyocins produced no adverse effects when injected alone into mice and showed good in vitro antipseudomonal activity. In an invertebrate model of sepsis using Galleria mellonella, both pyocins significantly prolonged survival. Following injection into mice, both showed extensive distribution into different organs. When administered 5 hours after infection, both pyocins reduced mortality, with pyocin S5 being more effective than AP41. ConclusionsPyocins S5 and AP41 show in vivo biological activity and can improve survival in a murine model of P. aeruginosa infection. They hold promise as novel antimicrobial agents for treatment of multi-drug resistant infections with this microbe.

microbiology↗

bioRxiv2018

Galleria mellonella as an infection model for the multi-host pathogen Streptococcus agalactiae reflects hypervirulence of ST283

Streptococcus agalactiae, or group B streptococcus (GBS), infects diverse hosts including humans, economically important livestock and fishes. In the context of human health, GBS is a major cause of neonatal infections and an emerging cause of invasive disease in adults. Here we show that GBS is able to establish a systemic infection in G. mellonella larvae that is associated with extensive bacterial replication and dose dependent larval survival. This infection model is suitable for use with GBS isolates from both homeothermic and poikilothermic hosts and a hypervirulent sequence type (ST) associated with invasive human disease, ST283, shows increased virulence in this model, indicating it may be useful in studying GBS virulence determinants. In addition, we demonstrate that larval survival can be afforded by antibiotic treatment and so the model may also be useful in the development of novel anti-GBS strategies. The use of G. mellonella in GBS research has the potential to provide a low cost infection model that could reduce the number of vertebrates used in the study of GBS infection.

microbiology↗

bioRxiv2018

Genomic inversion drives small colony variant formation and increased virulence in P. aeruginosa

Phenotypic change is a hallmark of bacterial adaptation during chronic infection. In the case of chronic Pseudomonas aeruginosa lung infection in patients with cystic fibrosis, well-characterised phenotypic variants include mucoid and small colony variants (SCVs). It has previously been shown that SCVs can be reproducibly isolated from the murine lung following the establishment of chronic infection with mucoid P. aeruginosa strain NH57388A. Here we show, using a combination of singlemolecule real-time (PacBio) and Illumina sequencing that the genetic switch for conversion to the SCV phenotype is a large genomic inversion through recombination between homologous regions of two rRNA operons. This phenotypic conversion is associated with large-scale transcriptional changes distributed throughout the genome. This global rewiring of the cellular transcriptomic output results in changes to normally differentially regulated genes that modulate resistance to oxidative stress, central metabolism and virulence. These changes are of clinical relevance since the appearance of SCVs during chronic infection is associated with declining lung function.

microbiology↗

bioRxiv2018

Clinical data specification and coding for cross-analyses with omics data in autoimmune disease trials

ObjectivesAutoimmune and inflammatory diseases (AIDs) form a continuum of autoimmune and inflammatory diseases, yet AIDs nosology is based on syndromic classification. The TRANSIMMUNOM trial (NCT02466217) was designed to re-evaluate AIDs nosology through clinic-biological and multi-omics investigations of patients with one of 19 selected AIDs. To allow cross-analyses of clinic-biological data together with omics data, we needed to integrate clinical data in a harmonized database.\n\nMaterials and MethodsWe assembled a clinical expert consortium (CEC) to select relevant clinic-biological features to be collected for all patients and a cohort management team comprising biologists, clinicians and computer scientists to design an electronic case report form (eCRF). The eCRF design and implementation has been done on OpenClinica, an open-source CFR-part 11 compliant electronic data capture system.\n\nResultsThe CEC selected 865 clinical and biological parameters. The CMT selected coded the items using CDISC standards into 5835 coded values organized in 28 structured eCRFs. Examples of such coding are check boxes for clinical investigation, numerical values with units, disease scores as a result of an automated calculations, and coding of possible treatment formulas, doses and dosage regimens per disease.\n\nDiscussion21 CRFs were designed using OpenClinica v3.14 capturing the 5835 coded values per patients. Technical adjustment have been implemented to allow data entry and extraction of this amount of data, rarely achieved in classical eCRFs designs.\n\nConclusionsA multidisciplinary endeavour offers complete and harmonized CRFs for AID clinical investigations that are used in TRANSIMMUNOM and will benefit translational research team.

clinical trials↗

bioRxiv2018

Representativeness and robustness of TCR repertoire diversity assessment by high-throughput sequencing

High-throughput sequencing (HTS) has the potential to decipher the diversity of T cell repertoires and their dynamics during immune responses. Applied to T cell subsets such as T effector and T regulatory cells, it should help identify novel biomarkers of diseases. However, given the extreme diversity of TCR repertoires, understanding how the sequencing conditions, including cell numbers, biological and technical sampling and sequencing depth, impact the experimental outcome is critical to properly use of these data. Here we assessed the representativeness and robustness of TCR repertoire diversity assessment according to experimental conditions. By comparative analyses of experimental datasets and computer simulations, we found that (i) for small samples, the number of clonotypes recovered is often higher than the number of cells per sample, even after removing the singletons; (ii) high sequencing depth for small samples alters the clonotype distributions, which can be corrected by filtering the datasets using Shannon entropy as a threshold; (iii) a single sequencing run at high depth does not ensure a good coverage of the clonotype richness in highly polyclonal populations, which can be better covered using multiple sequencing. Altogether, our results warrant better understanding and awareness of the limitation of TCR diversity analyses by HTS and justify the development of novel computational tools for improved modelling of the highly complex nature of TCR repertoires.

immunology↗

bioRxiv2017

High-resolution repertoire analysis of Tfr and Tfh cells reveals unexpectedly high diversities indicating a bystander activation of follicular T cells

T follicular helper (Tfh) and regulatory (Tfr) cells regulate B cell activation and ultimately antibody production. While concordant results show that Tfh cells are specific for the immunizing antigens, limited and even controversial results have been reported regarding the specificity of Tfr cells. Here we used high-throughput T cell receptor (TCR) sequencing to address this issue. We observed that although the Tfh- and Tfr-cell repertoires are less diverse than those of effector (Teff) and regulatory T (Treg) cells, they still represent thousands of clonotypes after immunization with a single antigen. T-cell receptor beta variable (TRBV) gene usage distinguishes both follicular T cells (Tfol) from non-Tfol cells, as well as helper (Teff and Tfh) vs. regulatory (Treg and Tfr) cells. Analysis of the sharing of clonotypes between samples revealed that a specific response to the immunizing antigen can only be detected in Tfh cells immunized with a non-self-antigen and Tfr cells immunized with a self-antigen. Finally, the Tfr TCR repertoire is more similar to that of Tregs than to that of Tfh or Teff cells. Altogether, our results highlight a bystander Tfol-cell activation during antigenic response in the germinal centres and support the Treg cell origin of Tfr cells.\n\nSignificance StatementFollicular helper T (Tfh) cells promote high-affinity antibody production by B cells while follicular regulatory T (Tfr) cells represses it. The question of the specificity of follicular T (Tfol) cells is of utmost importance in the understanding of the antibody response specificity and our work is the first to analysed the global Tfol TCR repertoire in wild type mice. This allowed us not only to portray the overall global structure of these repertoires, but also to substantiate the fact that Tfr cells respond to self-antigen while Tfh cells respond to non self-antigen, a still controversial issue. Importantly, our work revealed an unexpected bystander activation of Tfol cells. We think and discuss that it has a general significance in immune responses and possibly immunopathologies.

immunology↗