Biology subjects

Rigal, S.

Publications and source records attributed to Rigal, S..

5 recordsLinked to original sources

bioRxiv2026

An Integrated Analysis of GLP-1R Agonist Mechanisms: Addressing Study Variations in Heterogeneous Cell Systems

Experimental cell systems support the development of pharmacological therapies such as glucagon-like peptide-1 receptor agonists (GLP-1RAs). However, their utility in drug discovery is limited due to study variability, which complicates formation of unified conclusions based on all available data. To address this, we conducted a comprehensive analysis of the GLP-1RA exenatide, incorporating 16 new and five pre-existing mono- or co-culture studies of human liver and pancreatic models. We employed a new pragmatic model-based approach designed to handle the common situation of heterogeneous in vitro datasets with few replicates per condition. All studies are jointly explained (disagreement<{chi}{superscript 2}-limit; 542<732), thereby providing a unified conclusion based on all studies. This work links in vitro biology to clinically relevant mechanisms, such as exenatides effect on glucose-insulin interplay, and predicts previously undescribed inter-study variabilities. Independent validation confirms predictive performance (64<83). Our new integrative approach enhances the utility of experimental cell systems in preclinical drug discovery.

systems biology↗

bioRxiv2025

M4 drug discovery: human drug predictions from integrated pre-clinical insights exemplified with a GLP1-R agonist

A major recent breakthrough in the treatment of type 2 diabetes has been the development of glucagon-like peptide-1 receptor agonists (GLP-1RAs). However, current translational frameworks struggle to predict the clinical outcomes of these drugs from preclinical data. There are several reasons for this struggle, which are generic for many drugs: GLP-1RAs act through multi-timescale mechanisms in which short-term effects propagate into long-term changes; no single preclinical system can capture all their effects in humans; and mechanistic extrapolation requires modelling numerous whole-body biological processes. To address this gap, we present a new extrapolation approach, M4 drug discovery, and retrospectively apply it to the GLP-1RA exenatide in a manner that is generalisable to other drugs. The method integrates: Multi-level data (cellular to whole-body), Multi-timescale data (minutes to months), Multi-species data (e.g., rodents to humans), and Mechanistic knowledge. In this study, we integrate human cell and animal data with drug-free human studies to successfully predict human pharmacokinetics (cost < {chi}2, p=0.05; 64 < 97) and the outcomes of a 30-week clinical trial (36 < 45). We found that integrating information across the four M4 axes improved predictive performance and physiological relevance: multi-species data inform pharmacokinetics, human cell data provide human population- and donor-specific potency estimates, animal data reveal additional drug effects not observable in cell cultures, and the multi-timescale mathematical modelling enables short-term effects of exenatide and meals to inform long-term changes in insulin sensitivity. This work provides new tools for drug extrapolations, supporting the community towards safer and more informed preclinical-to-clinical drug extrapolations.

systems biology↗

bioRxiv2025

Rapid structural network changes in bird communities

As biodiversity is declining, the dynamics of species interactions is a growing conservation concern. However, estimating and monitoring explicit species interactions across large spatial and temporal scales remain challenging. An alternative and yet under-explored approach is to track whether and how the interaction milieu, defined as the background of all realised interactions, is changing in space and time. Here, we assess changes in the interaction milieu of common bird communities in France. We estimate associated species pairs using spatial and temporal information for 109 species monitored across 1,969 sites during 17 years. We validate the ecological significance of associated species pairs by testing the relationship between the propensity to be associated and species functional proximity or shared habitat preference. We reconstruct association networks for these intra-guild bird communities and track temporal changes in network layout in terms of size, density of links, modularity and degree distribution. We show that, beyond changes usually documented based on species numbers and abundances, the interaction milieu is also changing non-randomly. Communities become smaller with a similar relative number of associations that becomes unevenly distributed through time. These structural changes vary among bird communities according to their habitat and may impact community functioning and how communities can cope with global change.

ecology↗

bioRxiv2023

Diseased human pancreas and liver microphysiological system for preclinical diabetes research

Current research on metabolic disorders such as type 2 diabetes relies on animal models because multi-organ diseases cannot be well studied with the standard in vitro assays. Here, we connect models of key metabolism organs, pancreas and liver, on a microfluidic chip to enable diabetes research in a human-based preclinical system. Aided by mechanistic mathematical modelling, we developed a two-organ microphysiological system (MPS) that replicates clinically-relevant phenotypes of diabetic dysregulation both in the liver and pancreas compartments. Exposure to hyperglycemia and high cortisone created a diseased pancreas-liver MPS which displayed beta-cell dysfunction, steatosis, elevated ketone-body secretion, increased glycogen storage, and upregulated gluconeogenic machinery. In turn, normoglycemia and physiological cortisone concentration maintained glucose tolerance and stable liver and beta-cell functions. This method was evaluated for repeatability in two laboratories and was effective in multiple pancreatic islet donors. The model also provides a platform to identify new therapeutic targets as demonstrated with a liver-secreted IL-1R2 protein that induced islet proliferation.

cell biology↗

bioRxiv2020

Linking biotic homogenisation with large-scale changes of species associations

AimThe impact of global change on biodiversity is commonly assessed in terms of changes in species distributions, community richness and community composition. Whether and how much associations between species, i.e. the degree of correlation in their spatial co-occurrence, are also changing is much less documented and mostly limited to local studies of ecological networks. In this study, we quantify changes in large-scale patterns of species associations in bird communities in relation to changes in species composition. LocationFrance. Time period2001-2017. Major taxa studiedCommon breeding birds. MethodsWe use network approaches to build three community-aggregated indices reflecting complementary aspects of species association networks. We characterise the spatio-temporal dynamics of these indices using a large-scale and high-resolution dataset of bird co-abundances of 109 species monitored for 17 years (2001-2017) from 1,969 sites across France. We finally test whether spatial and temporal changes in species association networks are related to species homogenisation estimated as the spatio-temporal dynamics of {beta}-diversity and the proportion of habitat generalists. The consistency of these relationships is tested across three main habitats, namely woodland, grassland and human settlements. ResultsWe document a directional change in association-based indices in response to modifications in {beta}-diversity and in the proportion of generalists in space and time. Weaker associations and sparser networks were related to lower {beta}-diversity and a higher proportion of generalists, suggesting an overlooked aspect of biotic homogenisation affecting species associations. We report that this overall pattern is not constant across habitats, with opposite relationships between biotic homogenisation and change in species association networks in urban versus forest communities suggesting distinct homogenisation processes. Main ConclusionsAlthough species association contain only partial signatures of species interactions, our study highlights that biotic homogenisation translates to finer changes in community structure by affecting the number, strength and type of species associations.

ecology↗