Biology subjects

Marquet, P.

Publications and source records attributed to Marquet, P..

17 recordsLinked to original sources

bioRxiv2026

Graph-based characterization of in vitro neuronal network maturation using machine learning and digital holographic microscopy

SignificanceDigital Holographic Microscopy (DHM) provides label-free quantitative phase images (QPIs) of living cells and has become a powerful tool for studying cellular morphology and dynamics. While most DHM studies have focused on cell-level analysis, the quantitative characterization of neuronal network organization and maturation from DHM images remains largely unexplored, highlighting the need for dedicated computational approaches. AimWe aimed to develop an automated framework combining deep-learning-based image analysis and graph theory to quantitatively characterize the organization, connectivity, and maturation of neuronal networks in primary rat cortical cultures imaged by DHM. ApproachTwo U-Net convolutional neural networks were trained on manually annotated DHM phase images to segment neuronal cell bodies and neurites. The resulting segmentation maps were used to infer putative morphological connections between neurons and generate graph representations of neuronal networks, referred to as graph fingerprints. A panel of 18 connectomics-inspired graph features was then computed to characterize local and global properties of network organization across four stages of culture maturation. ResultsThe mean area under the receiver operating characteristic curves was 0.98 for cell-body and 0.91 for neurite segmentation, indicating near-perfect identification. Graph-theoretical analysis revealed reproducible topological changes during network maturation in vitro, including increased density, reduced modularity, and progressive network integration. Correlation analysis showed that the 18 graph features grouped into two highly correlated families. A Random Forest classifier identified density and modularity as the most informative descriptors, achieving an accuracy of 87% in classifying maturation stages of neuronal cultures. ConclusionsOur results demonstrate that combining DHM, deep-learning-based segmentation, and graphtheoretical analysis enables quantitative characterization of neuronal network organization and maturation from label-free phase images. This framework provides a foundation for future studies of pharmacological experiments, neuronal network phenotyping, and human induced pluripotent stem cell (hiPSC)-derived neuronal cultures, where quantitative assessment of network organization remains a major challenge.

neuroscience↗

bioRxiv2026

Integrating social-ecological dimensions of fisheries non-compliance in a stochastic framework

Non-compliance with regulations threatens the sustainability of fisheries worldwide. Understanding the interconnected feedbacks of this complex social-ecological problem is key for sustainability but rarely integrated into fisheries management. We provide an adaptive stochastic modelling framework that integrates economic, social behavior, and ecological aspects of the Chilean kelp fishery, which plays a critical economic and ecological role in coastal social-ecological ecosystem. High levels of non-compliance is threatening sustainability, fishers well-being, and ecosystem health. Our model considers inherent environmental uncertainties and enables the assessment of different harvesting and compliance scenarios and the role of market-based economic incentives in reducing non-compliance. Results show that, unlike the sustainability obtained under an idealized full-compliance scenario, under dynamic compliance the social, economic, and ecological feedbacks leads to system collapse. Importantly, price premiums can promote compliance and sustainability, but the probability of collapse, albeit small, still exist. Our generalizable stochastic modeling framework evidenced that accounting for inherent uncertainty in natural resource management is key to designing interventions for sustainability.

ecology↗

bioRxiv2025

A database of biological thermal performances

We built a database of thermal performance curves that includes different variables --mostly population growth rates --for species in representative groups across major domains, including viruses, bacteria, archaea, unicellular eukaryotes (such as fungi), and multicellular eukaryotes (including plants and both invertebrates and vertebrates). To build the database, we integrated previous databases and compiled additional data from individual studies, all of which were normalized to the same units when corresponding. Our database contains data for 1300 curves across 1125 different species and 38 variable types. The database consists of four (.csv) tables and an R code that can be explored through an R package or a Shiny app. Applications of our dataset include providing a resource to studies in thermal ecology and integration with other types of data, such as geographic temperatures. This would allow us to make further predictions, such as potential species distributions based on their thermal tolerances and their changes with climate warming.

bioinformatics↗

bioRxiv2025

Scaling laws in biological thermal performances

Understanding the extent to which genetic correlations change in response to environmental factors, such as temperature, is a poorly explored question, despite the importance of understanding how different processes will change with climate warming. Despite correlations between thermal performance traits having been reported in the literature for a few taxa and performance tasks, such as population growth rate, a comprehensive global analysis of the entire tree of life and multiple performance tasks remains an open challenge. To advance in this open question, we compile a database of 1,300 thermal response curves, encompassing 38 variable types related to individuals performance (including per capita population growth rate, photosynthetic rate, among others) and 1,125 different species, ranging from viruses to mammals, encompassing all major lineages of the tree of life. Our analysis reveals that among all possible relationships between traits and optimal performance, four traits form a line with a high goodness-of-fit, while the remaining traits exhibit a polygonal pattern, either a triangle or a tetrahedron. We derive a thermodynamic framework that explains the relationships described by a curve or line (as opposed to a surface or polygon), highlighting the linear relationship between maximum and minimum temperatures, as well as between maximum and optimum temperatures. We also discuss other generic trait evolution models, which could account for the other significant sublinear relationships, as well as the more general model, Pareto optimality theory, which could account for relationships in the form of lines or polygons. Our theoretical framework and empirical evidence suggest that, based on a single data point (e.g., minimum temperature), all critical temperature limits and maximum performance boundaries can be predicted using the estimated parameter from this study. Our results reveal universal scaling relationships in thermal performance, which could be useful for predicting changes in performance under scenarios of climate warming.

biophysics↗

bioRxiv2025

A general model for genomic traits evolution

A large body of data indicates that genomic elements, including gene families and entire genomes, exhibit diverse types of evolutionary dynamics. Several models have been developed to describe the dynamics of, for example, genome size; however, a simple deterministic model with interpretable parameters that could be useful for fitting a variety of data remains an open problem. Here, we show that (a continuous form of) the Breeders equation for the evolution of quantitative traits/characters leads to a general model that explains the dynamics of genomic elements generated by indel mutations (duplications, insertions, and deletions) and selection. Our framework consists of a general exponential-linear model that predicts at least six different types of dynamical behaviors, including exponential growth and decay. The equations fit data, such as evolution experiments across generations, field observational data of genome sizes across time, and data from phylogenetic reconstructions of ancestral states of genome size across millions of years of a variety of taxa, including viruses, bacteria, fungi, unicellular eukaryotes, plants, and animals, at both intra- and interspecific levels. To test the universality of the dynamics, we derived a dimensionless equation that enables the (re)scaling and subsequent collapse of all data for growth or decay onto a single universal curve. Thus, our model provides a general basis not only for explaining the dynamics in the size of gene families or whole genomes of populations across taxonomic and environmental scales, but also other traits, providing a foundation for further theoretical developments.

evolutionary biology↗

bioRxiv2025

On the energetic boundaries of trophic systems

Energy is the fundamental currency of life. Every organism requires a minimum intake to meet maintenance needs, and every trophic transfer dissipates part of the energy flow as heat. Classical theory has emphasized lower bounds on supply--the minimum resource level required for consumers to persist--yet the possible upper bounds and their role in limiting food-chain length remain unclear. We develop a thermodynamically grounded framework that reveals a triad of boundaries: (i) consumer thresholds, (ii) a basal protection limit that reframes the paradox of enrichment as a thermodynamic constraint, and (iii) environmental or physiological supply caps. We show that the intersection of these three boundaries determines the exact range of conditions under which a given ecosystem structure can occur, and that within this range trophic configurations arise as the unique solution that maximizes energy flow. As chain length increases, consumer thresholds rise while the basal protection limit falls, causing this range to contract and eventually disappear. Whether this limit is reached depends on the relative position of these two boundaries and the external supply cap. Their crossing defines an energetic ceiling: a thermodynamic bound on food-chain length beyond which no further level can be sustained. Our results show that feasibility conditions are directly shaped by thermodynamic laws, providing a mechanistic explanation for the emergence and limits of trophic systems.

ecology↗

bioRxiv2025

Metabolic ecology, microbial community structure, and gene-centric metagenomics

Metabolic ecology includes predictions for biological rates from molecules to ecosystems, but despite the broad range of its scope, its applicability to metagenomes remains an open question. Here, we integrate metabolic ecology with principles of DNA shotgun sequencing to generate specific testable predictions for the metagenomic structure of microbial communities. We start by predicting a scaling relationship between population and assemblage abundance with genome size. This allows us to simplify DNA shotgun sequencing equations for the reads of a population and a gene. Then we derive the temperature dependence of population and assemblage abundance using the volume-temperature and abundance-volume rules and integrate them with simplified DNA sequencing equations to show that these predictions are compatible with a metagenomic framework. In addition, we derive predictions for the temperature dependence of the structure (abundance and richness) of genes and groups of related genes (e.g., metabolic pathways). To test our model, we provide some example data from human, aquatic, and terrestrial microbiomes from recent global projects. All predictions were supported by the observed data. Our model, derived from the integration of first principles, provides a mechanistic basis for variation in the structure of microbial community genomes in environmental and host-associated ecosystems.

ecology↗

bioRxiv2025

Global patterns of taxonomic and functional diversity in hot springs microbiomes

A reformulation of the metabolic theory of ecology has been proposed based on a derivation of the Eyring-Polanyi equation, leading to a reduced model with the form of a power-law with exponential cut-off (PLECO). Moreover, the recent integration of this new model and metagenomic DNA sequencing theory has led to the hypothesis that, given that temperature affects cell size and assemblage abundance, it should also affect the number of genes, metabolisms, and populations in a microbial community. In particular, for microbial communities, the model predicts that the diversity of taxa, their genes, and metabolisms should respond to temperature according to the PLECO model, and after scaling the data using the estimated parameters, all data should collapse into a single curve. To test these predictions, we use global hot springs microbial communities; geothermally heated environments that include aquatic and terrestrial habitats with large temperature gradients. We analyzed a global database (five continents) of 19 hot springs metagenomes covering a wide gradient of temperature (32-90{degrees}C). We found that the alpha diversity of taxa, genes, and their metabolisms decreases with temperature, in agreement with the predictions of the PLECO model. Further, after non-dimensionalization of the model, we derive a single nondimensional curve for taxa and functions. Finally, using general linear models, we analyzed the effects of pH, latitude, and substrate (soil, water, or both), in addition to temperature, to explain the observed diversity pattern. We find that they explain a lower proportion of the variance, but pH can explain up to half of the variance in global diversity in these ecosystems, indicating the need to include pH in the theory. Our study supports the hypothesis that temperature regulates the structure of community genomes.

ecology↗

bioRxiv2025

Fine-scale spatial patterns in hot springs mat bacterial communities

Some of the most widely recognized spatial scaling relationships in ecology include the species-area, the abundance-occupancy, and the community compositional similarity-geographic distance relationships. These patterns have been shown to emerge from common mechanisms, such as habitat heterogeneity and colonization-extinction dynamics, and are predicted by various ecological models and theories, including Island Biogeography, Metapopulation theory, and Neutral Theory of Biodiversity and Biogeography. These patterns have been studied in microbial communities at large-scale, but studies at fine grain and small extent are rare, despite at a fine-scale, emerging patterns can be tested with a higher resolution. In this study, we explored these macroecological patterns in bacterial communities inhabiting hot springs mats, which have been shown to exhibit fine-scale spatial heterogeneity in fundamental environmental parameters such as temperature. In three different localities, we sampled a grid with a heterogeneous temperature at a fine-scale, a small extent (approximately 150 cm2), and fine grain (each containing 30 cells spaced about 1 or 2 cm apart). Our findings revealed sublinear scaling for the species-area relationship, with similar parameters across localities, indicating a low rate of spatial species turnover. For the abundance-occupancy relationship, we observed increasing trends, meaning that species that occupied more patches were, on average, more abundant. Additionally, we identified a decay in community compositional similarity with distance in two of the localities, though with low parameter values, indicating minimal geographic isolation at this scale. These results are consistent with different models that predict that spatial ecological patterns arise from spatial heterogeneity, as different species can partition their niches in space and constitute an example of predictable spatial patterns at a fine scale.

ecology↗

bioRxiv2024

Proximal Tubule-on-Chip for Predicting Cation Transport: Dynamic Insights into Drug Transporter Expression and Function

Deciphering the sources of variability in drug responses requires to understand the processes modulating drug pharmacokinetics. However, pharmacological research suffers from poor reproducibility across clinical, animal, and experimental models. Predictivity can be improved by using Organs-on-Chips, which are more physiological, human-oriented, micro-engineered devices that include microfluidics. OoC are particularly relevant at the fundamental and preclinical stages of drug development by providing more accurate assessment of key pharmacokinetic events. We have developed a proximal tubule-on-a-chip model combining commercial microfluidic and chip technologies. Using the RPTEC/TERT1 cell line, we set up a dual-flow system with antiparallel flows to mimic the dynamics of blood and urine. We assessed transporters mRNA expression using RT-qPCR, cellular polarization and protein expression via immunofluorescence and confocal microscopy, and monitored the transcellular transport of a list of prototypic xenobiotics by determining their efflux ratios with LC-MS/MS. Our results show that flow exposure significantly modulate mRNA expression of drug membrane transporters compared to static conditions. Dynamic conditions also enhance cell polarization, as evidenced by preferential basal and apical expressions of Na+/K+-ATPase, P-gp, OCT2, and MATE1, as well as the cellular secretory profile. We demonstrated unidirectional transcellular transport of a cationic substrate (metformin) with a higher efflux than influx ratio, inhibited with a specific OCT2 inhibitor, thus confirming the relevance of our proximal tubule- on-a-chip set up for cation transport investigations. Our proximal tubule-on-a-chip can also be used to explore the interactions between transporters, xenobiotics, and endogenous metabolites, possibly involved in the variability of individual drug responses. This study provides additional evidence that OoC can bridge the gaps between systemic and local pharmacokinetics, i.e., drug concentration close to its target, at the fundamental and preclinical stages. HighlightsO_LICell exposure to flow shear stress modulate mRNA drug membrane transporters and cell polarization of proximal tubule C_LIO_LIProximal tubule-on-chip relying on RPTEC/TERT1 cell line is a suitable platform for assessing transcellular cationic transport C_LIO_LIOCT2 and MATE are involved in potential drug-endogenous metabolite interactions C_LIO_LICell exposure to xenobiotics and endogenous metabolites modulate the drug transporters expression. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/617976v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@7562b7org.highwire.dtl.DTLVardef@a409c0org.highwire.dtl.DTLVardef@17c1d9aorg.highwire.dtl.DTLVardef@17b9a6f_HPS_FORMAT_FIGEXP M_FIG C_FIG Data StatementOriginal microscopy pictures, raw data for metabolomics and other data are available upon reasonable request.

pharmacology and toxicology↗

bioRxiv2023

Linking metabolic scaling and coexistence theories

Metabolic scaling theory has been pivotal in formalizing the expected energy expenditures across populations as a function of body size. Coexistence theory has provided a mathematization of the environmental conditions compatible with multispecies coexistence. Yet, it has been challenging to explain how observed community-wide patterns, such as the inverse relationship between population abundance density and body size, can be unified under both theories. Here, we provide the foundation for a tractable, scalable, and extendable framework to study the coexistence of resource-mediated competing populations as a function of their body size. For a given thermal domain and response, this integration reveals that the metabolically predicted 1/4 power dependence of carrying capacity of biomass density on body size can be understood as the average distribution of carrying capacities across feasible environmental conditions, especially for large communities. In line with empirical observations, our integration predicts that such average distribution leads to communities in which population biomass densities at equilibrium are independent from body size, and consequently, population abundance densities are inversely related to body size. This integration opens new opportunities to increase our understanding of how metabolic scaling relationships at the population level can shape processes at the community level under changing environments.

ecology↗

bioRxiv2022

Substrate binding and lipid-mediated allostery in the human organic anion transporter 1 at the atomic-scale

The Organic Anion Transporter 1 is a membrane transporter known for its central role in drug elimination by the kidney. hOAT1 is an antiporter translocating substrate in exchange for -ketoglutarate. The understanding of hOAT1 structure and function remains limited due to the absence of resolved structure of hOAT1. Benefiting from conserved structural and functional patterns shared with other Major Facilitator Superfamily transporters, the present study intended to investigate fragments of hOAT1 transport function and modulation of its activity in order to make a step forward the understanding of its transport cycle. s-long molecular dynamics simulation of hOAT1 were carried out suggesting two plausible binding sites for a typical substrate, adefovir, in line with experimental observations. The well-known B-like motif binding site was observed in line with previous studies. However, we here propose a new inner binding cavity which is expected to be involved in substrate translocation event. Binding modes of hOAT1 co-substrate -ketoglutarate were also investigated suggesting that it may binds to highly conserved intracellular motifs. We here hypothesize that -ketoglutarate may disrupt the pseudo-symmetrical intracellular charge-relay system which in turn may participate to the destabilisation of OF conformation. Investigations regarding allosteric communications along hOAT1 also suggest that substrate binding event might modulate the dynamics of intracellular charge relay system, assisted by surrounding lipids as active partners. We here proposed a structural rationalisation of transport impairments observed for two single nucleotide polymorphisms, p.Arg50His and p.Arg454Gln suggesting that the present model may be used to transport dysfunctions arising from hOAT1 mutations. HighlightsO_LIAdefovir has at least two binding pockets on hOAT1 in the outward-facing conformation. C_LIO_LIThe highly conserved B-motif within MFS is strongly involved in substrate binding. C_LIO_LI-Ketoglutarate binds to the intracellular domain of hOAT1 and destabilizes its OF conformation. C_LIO_LIThe lipid membrane bilayer plays an active role in the allosteric communication between intracellular and extracellular domains of hOAT1. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/500056v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@18d092corg.highwire.dtl.DTLVardef@5538e9org.highwire.dtl.DTLVardef@10b62cforg.highwire.dtl.DTLVardef@84421e_HPS_FORMAT_FIGEXP M_FIG The present work (from left): (i) reveals binding modes of adefovir (top) and -ketoglutarate (bottom) to hOAT1; (ii) maps Single Nucleotide Polymorphisms on outward-facing (top) and inward-facing (bottom) conformation of hOAT1; (iii) asses the allosteric effect of lipidic environment and presence of substrates. C_FIG

pharmacology and toxicology↗

bioRxiv2022

Insights into the structure and function of the human organic anion transporter 1 in lipid bilayer membranes

The human SLC22A6/OAT1 plays an important role in the elimination of a broad range of endogenous substances and xenobiotics thus attracting attention from the pharmacological community. Furthermore, OAT1 is also involved in key physiological events such as the remote inter-organ communication. Despite its significance, the knowledge about hOAT1 structure and the transport mechanism at the atomic level remains fragmented owing to the lack of resolved structures. By means of protein-threading modeling refined by s-scaled Molecular Dynamics simulations, the present study provides the first robust model of hOAT1 in outward-facing conformation. Taking advantage of the AlphaFold 2 predicted structure of hOAT1 in inward-facing conformation, we here provide the essential structural and functional features comparing both states. The intracellular motifs conserved among Major Facilitator Superfamily members create a so-called "charge-relay system" that works as molecular switches modulating the conformation. The principal element of the event points at interactions of charged residues that appear crucial for the transporter dynamics and function. Moreover, hOAT1 model was embedded in different lipid bilayer membranes highlighting the crucial structural dependence on lipid-protein interactions. MD simulations supported the pivotal role of phosphatidylethanolamine components to the protein conformation stability. The present model is made available to decipher the impact of any observed polymorphism and mutation on drug transport as well as to understand substrate binding modes.

pharmacology and toxicology↗

bioRxiv2021

A general model for temperature-dependence in biology

At present, there is no simple, complete, and first principles-based model for quantitatively describing the full range of observed biological temperature responses. Here, we derive a theory exhibiting these features based on the Eyring-Evans-Polanyi theory governing chemical reaction rates, and which is applicable across all scales from the micro to the macro. Assuming only that the conformational entropy of molecules changes with temperature, we derive a theory for the temperature dependence which takes the form of an exponential function modified by a power-law. Our framework leads to six deductions applicable to any biological trait that depends on temperature, and elucidates novel aspects of universal temperature responses across the tree of life, from quantum to classical scales. All predictions are well supported by data for a wide variety of biological rates and steady states, from molecular to ecological scales and across multiple taxonomic groups. In addition, we provide novel explanations of several empirical relationships including optimal values in temperature response curves. One-Sentence SummaryWe derive a simple and universal formulae to characterize temperature responses of biological processes across the tree of life.

ecology↗

bioRxiv2020

Areas of global importance for terrestrial biodiversity, carbon, and water

Summary paragraphTo meet the ambitious objectives of biodiversity and climate conventions, countries and the international community require clarity on how these objectives can be operationalized spatially, and multiple targets be pursued concurrently1. To support governments and political conventions, spatial guidance is needed to identify which areas should be managed for conservation to generate the greatest synergies between biodiversity and natures contribution to people (NCP). Here we present results from a joint optimization that maximizes improvements in species conservation status, carbon retention and water provisioning and rank terrestrial conservation priorities globally. We found that, selecting the top-ranked 30% (respectively 50%) of areas would conserve 62.4% (86.8%) of the estimated total carbon stock and 67.8% (90.7%) of all clean water provisioning, in addition to improving the conservation status for 69.7% (83.8%) of all species considered. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to improve the conservation status of 86.3% of plant and vertebrate species on Earth. Our results provide a global baseline on where land could be managed for conservation. We discuss how such a spatial prioritisation framework can support the implementation of the biodiversity and climate conventions.

ecology↗

bioRxiv2019

Strategies based on sum of peak intensities may better reflect protein expression than peak area integration in iTRAQ protein expression measurement by LC-MS/MS using a TripleTOF 5600+ platform

In the field of quantitative proteomics, the Isobaric Tags for Relative & Absolute Quantitation (iTRAQ) technology has demonstrated efficacy for proteome monitoring despite its lack of a consensus for data handling. In this study, after peptide and protein identification, we compared the widespread quantitation method based on the calculation of MS/MS reporter ion peaks areas ratios (ProteinPilot) to the alternative method based on the calculation of ratios of the sum of peak intensities (jTRAQx (Quant)) and we processed output data with the in-house Customizable iTRAQ Ratios Calculator (CiR-C) algorithm. Quantitation based on peak area ratios displayed no significant linear correlation with Western blot quantitation. In contrast, quantitation based on the sum of peak intensities displayed a significant linear association with Western blot quantitation (non-zero slope; Pearson correlation coefficient test, r = 0.2962, p = 0.0099 **) with an average bias of 0.08747 {+/-} 0.5004 and 95% Limits of Agreement from - 0.8932 to 1.068. We proposed the Mascot-jTRAQx-CiR-C strategy as a simple yet powerful data processing adjunct to the iTRAQ technology.

cell biology↗

bioRxiv2018

Cyclosporine A inhibits MRTF-SRF signalling through Na+/K+ ATPase inhibition & Actin remodelling

Calcineurin Inhibitors (CNI) are the pillars of immunosuppression in transplantation. However, they display a potent nephrotoxicity whose mechanisms remained widely unsolved. We used an untargeted quantitative proteomic approach (iTRAQ technology) to highlight new targets of CNI in renal proximal tubular cells (RPTCs). CNI-treated RPTCs proteome displayed an over-representation of Actin-binding proteins with a CNI-specific expression profile. Cyclosporine A (CsA) induced F-Actin remodelling and depolymerisation, decreased F-Actin-stabilizing, polymerization-promoting Cofilin (CFL) oligomers and inhibited the G-Actin-regulated serum responsive factor (SRF) pathway. Inhibition of CFL canonical phosphorylation pathway reproduced CsA effects; however, Ser3, an analogue of the phosphorylation site of CFL prevented the effects of CsA which suggests that CsA acted independently from the canonical CFL regulation. CFL is known to be regulated by the Na+/K+-ATPase. Molecular docking calculations evidenced 2 inhibiting sites of CsA on Na+/K+-ATPase and a 23% decrease in Na+/K+-ATPase activity of RPTCs was observed with CsA. Ouabain, a specific inhibitor of Na+/K+-ATPase also reproduced CsA effects on Actin organization and SRF activity. Altogether, these results described a new original pathway explaining CsA nephrotoxicity.

cell biology↗