Biology subjects

Auffray, C.

Publications and source records attributed to Auffray, C..

4 recordsLinked to original sources

bioRxiv2026

User-driven development and evaluation of an agentic framework for analysis of large pathway diagrams

As biomedical knowledge keeps growing, resources storing available information multiply and grow in size and complexity. Such resources can be in the format of molecular interaction maps, which represent cellular and molecular processes under normal or pathological conditions. However, these maps can be complex and hard to navigate, especially to novice users. Large Language Models (LLMs), particularly in the form of agentic frameworks, have emerged as a promising technology to support this exploration. In this article, we describe a user-driven process of prototyping, development, and user testing of Llemy, an LLM-based system for exploring these molecular interaction maps. By involving domain experts from the very first prototyping in the form of a hackathon and collecting both fine-grained and general feedback on more refined versions, we were able to evaluate the perceived utility and quality of the developed system, in particular for summarising maps and pathways, as well as prioritise the development of future features. We recommend continued user-driven development and benchmarking to keep the community engaged. This will also facilitate the transition towards open-weight LLMs to support the needs of the open research environment in an ever-changing technology landscape.

bioinformatics↗

bioRxiv2021

Capsaicin activates TRPV1 in human Langerhans cells and inhibits mucosal HIV-1 transmission via secreted CGRP

Upon its mucosal transmission, human immunodeficiency virus type 1 (HIV-1) rapidly targets resident antigen-presenting Langerhans cells (LCs) in genital epithelia, which subsequently trans-infect CD4+ T-cells. We previously described an inhibitory neuro-immune sensory mucosal crosstalk, whereby peripheral pain-sensing nociceptor neurons, innervating all mucosal epithelia and associating with LCs, secret the neuropeptide calcitonin gene-related peptide (CGRP) that strongly inhibits HIV-1 trans-infection. Moreover, we reported that LCs secret low levels of CGRP that are further increased by CGRP itself via an autocrine/paracrine mechanism. As nociceptors secret CGRP following activation of their Ca2+ ion channel transient receptor potential vanilloid 1 (TRPV1), we investigated whether LCs also express functional TRPV1. We found that human LCs expressed TRPV1 mRNA and protein. TRPV1 in LCs was functional, as the TRPV1 agonists capsaicin (CP) and resiniferatoxin (RTX) induced Ca2+ influx in a dose-dependent manner. Treatment of LCs with CP and the TRPV1 agonist rutaecarpine (Rut) increased CGRP secretion, reaching concentrations close to its IC50 for inhibition of HIV-1 trans-infection. Accordingly, CP significantly inhibited HIV-1 trans-infection, which was abrogated by antagonists of both TRPV1 and the CGRP receptor. Finally, pre-treatment of inner foreskin tissue explants with CP markedly increased CGRP secretion, and upon subsequent polarized exposure to HIV-1, inhibited increase in LC-T-cell conjugate formation and T-cell infection. Together, our results reveal that alike nociceptors, LCs express functional TRPV1, whose activation induces CGRP secretion that inhibits mucosal HIV-1 transmission. Our studies could permit re-positioning of formulations containing TRPV1 agonists, already approved for pain relief, as novel topical microbicides against HIV-1. Significance StatementUpon its sexual transmission, HIV-1 targets different types of mucosal immune cells, such as antigen-presenting Langerhans cells (LCs). In turn, LCs transfer HIV-1 to its principal cellular targets, namely CD4+ T-cells, in a process termed trans-infection. We previously discovered that the mucosal neuropeptide CGRP strongly inhibits trans-infection. CGRP is principally secreted from pain-sensing peripheral neurons termed nociceptors, once activated via their TRPV1 ion channel. Herein, we reveal that LCs also express functional TRPV1, whose activation induces secretion of CGRP that inhibits mucosal HIV-1 transmission. Accordingly, molecules activating TRPV1 and inducing CGRP secretion could be used to prevent mucosal HIV-1 transmission. This approach represents an original neuro-immune strategy to fight HIV-1.

microbiology↗

bioRxiv2020

Informing epidemic (research) responses in a timely fashion by knowledge management - a Zika virus use case

The response of pathophysiological research to emerging epidemics often occurs after the epidemic and, as a consequence, has little to no impact on improving patient outcomes or on developing high-quality evidence to inform clinical management strategies during the epidemic. Rapid and informed guidance of epidemic (research) responses to severe infectious disease outbreaks requires quick compilation and integration of existing pathophysiological knowledge. As a case study we chose the Zika virus (ZIKV) outbreak that started in 2015 to develop a proof-of-concept knowledge repository. To extract data from available sources and build a computationally tractable and comprehensive molecular interaction map we applied generic knowledge management software for literature mining, expert knowledge curation, data integration, reporting and visualisation. A multi-disciplinary team of experts, including clinicians, virologists, bioinformaticians and knowledge management specialists, followed a pre-defined workflow for rapid integration and evaluation of available evidence. While conventional approaches usually require months to comb through the existing literature, the initial ZIKV KnowledgeBase (ZIKA KB) was completed within a few weeks. Recently we updated the ZIKA KB with additional curated data from the large amount of literature published since 2016 and made it publicly available through a web interface together with a step-by-step guide to ensure reproducibility of the described use case (S4). In addition, a detailed online user manual is provided to enable the ZIKV research community to generate hypotheses, share knowledge, identify knowledge gaps, and interactively explore and interpret data (S5). A workflow for rapid response during outbreaks was generated, validated and refined and is also made available. The process described here can be used for timely structuring of pathophysiological knowledge for future threats. The resulting structured biological knowledge is a helpful tool for computational data analysis and generation of predictive models and opens new avenues for infectious disease research. Availabilitywww.zikaknowledgebase.eu FundingEuropean Commissions Seventh Framework Research Programme project PREPARE (FP7-Health n{degrees}602525) and ZIKALLIANCE (MK, H2020; No 734548). Author summaryDuring the recent ZIKV outbreak there was little information about the interactions between Zika virus and the host, however, the massive research response lead to a steep increase in the number of relevant publications within a very short period of time. At the time, there was no structured and comprehensive database available for integrated molecular and physiological data and knowledge about ZIKV infection. Researchers had to manually review the literature (amounting to over 5000 articles on ZIKV during our last update of the ZIKA KB in September 2018) to extract information about host-pathogen interaction and affected molecular, cellular and organ pathways. We explored the use of automated literature analysis and a defined cooperative effort between experts from various scientific, biomedical and information-technology domains to rapidly compile existing pathophysiological knowledge as a potential tool to support investigations during an emergency. This tool is contrasted with conventional approaches that would take months to comb through the massive amount of existing literature. In addition to providing background information for research, scientific publications can be processed to transform textual information into complex networks, which can be integrated with existing knowledge resources to suggest novel hypotheses that potentially contribute to innovative infectious disease research approaches. This study shows that the knowledge extraction and mapping process required to inform clinical and research responses to an emerging epidemic can be efficiently and effectively executed with a dedicated and trained group of experts, a validated process and the necessary tools. Our results further provide an overview of ZIKV biology, allow prediction of drug efficacy and indentify specific host factors and signalling pathways affected by ZIKV.

pathology↗

bioRxiv2019

A Topological Data Analysis Network Model of Asthma Based on Blood Gene Expression Profiles

Stratified medicine requires discretisation of disease populations for targeted treatments. We have developed and applied a discrete Morse theory clustering algorithm to a Topological Data Analysis (TDA) network model of 498 gene expression profiles of peripheral blood from asthma and healthy participants. The Morse clustering algorithm defined nine clusters, BC1-9, representing molecular phenotypes with discrete phenotypes including Type-1, 2 & 17 cytokine inflammatory pathways. The TDA network model and clusters were also characterised by activity of glucocorticoid receptor signalling associated with different expression profiles of glucocorticoid receptor (GR), according to microarray probesets targeted to the start or end of the GR mRNAs 3 UTR; suggesting differential GR mRNA processing as a possible driver of asthma phenotypes including steroid insensitivity.

molecular biology↗