Biology subjects

Soubeyrand, S.

Publications and source records attributed to Soubeyrand, S..

12 recordsLinked to original sources

bioRxiv2026

Exon Resolved Dissection of Shared, Unique, and Antagonistic Functions of ZFAS1 Isoforms

The long noncoding RNA ZFAS1 plays a role in cell proliferation and has been linked to cancer development and prognosis. However, the ZFAS1 locus is predicted to encode over 40 ZFAS1 splice variants, which remain largely uncharacterized. To shed light on the role of ZFAS1 in hepatocyte models, we examined the transcriptome-wide effects of separately targeting three exons present in representative ZFAS1 variants with gapmer antisense oligonucleotides. Evidence of cross-exon compensatory regulation was obtained by qRT-PCR. Although targeting resulted in a subset of concerted transcript perturbations-indicating specificity and shared functionalities-the overall effects were predominantly non-redundant. Overrepresentation analyses revealed that proximal exon and distal exon targeting affected cell cycle and transcription regulation, respectively. Strikingly, interrogation of the entire transcriptome with gene set enrichment analysis identified a shared subset of pathways related to cell-cycle control and translation, which were affected antagonistically in an exon-dependent manner. Whereas targeting the proximal exon was predicted to broadly compromise cell-cycle and translational functions, targeting distal exons produced contrasting effects on these processes. Together, these findings demonstrate that the arrangement of ZFAS1 exons can markedly modulate its function.

cell biology↗

bioRxiv2026

Inferring the multi-host fitness landscape of endive necrotic mosaic virus from cross-inoculation experiments

Fitness landscapes offer a compact representation of adaptation, yet are rarely inferred from sparse multi-environment data. We present a Bayesian approach to infer an effective multi-host phenotypic fitness landscape from cross-inoculation assays by linking successful infection probabilities to Fishers geometrical model and to an explicit decomposition of establishment routes. The model estimates (i) the distance matrix among host-specific phenotypic optima, (ii) target-host permissiveness through the widths of fitness peaks, (iii) target-specific differences in the efficiency with which phenotypic suitability translates into successful infection, and (iv) the conditional probabilities that successful infections are attributed to direct establishment, rescue from standing variation in the source inoculum, or de novo rescue in the target host. We apply the approach to an experimental evolution dataset for endive necrotic mosaic virus evolved on five Asteraceae hosts and challenged in a full cross-inoculation design. The inferred landscape can be visualized as a phenotypic map of the host community, revealing pronounced heterogeneity in target-host permissiveness and a geometry broadly concordant with host phylogeny. By grounding assay-derived distances in an explicit mechanistic model, the approach provides a parsimonious representation of multi-host constraints that can be used to discuss establishment barriers and potential springboard hosts in heterogeneous communities. More broadly, it offers a general method for inferring effective fitness landscapes from sparse multi-environment data.

evolutionary biology↗

bioRxiv2025

Deciphering the role of the lncRNA TRIBAL in hepatocyte models

We recently reported that the long non-coding RNA TRIBAL/TRIB1AL was required to sustain key hepatocyte functions. Here, we identify HepaRG cells as a model for studying TRIBAL and provide additional validation and functional insights. In contrast to HepG2 and HuH-7 cells, differentiated HepaRG cells showed similarities to primary hepatocytes in response to TRIBAL suppression. TRIBAL suppression was associated with reduced HNF4A and MLXIPL abundance in hepatocytes and HepaRG cells. TRIBAL targeting using a panel of targeting ASOs confirmed specificity. Comparing TRIBAL-suppressed hepatocyte and HepaRG transcriptomics identified extensive functional overlap. Biological ontologies associated with key hepatic metabolic functions were predicted to be inhibited in both models. Comparative analyses with TRIB1-suppressed HepaRG cells, a major metabolic regulator vicinal to TRIBAL, also revealed extensive functional congruence with TRIBAL. Interestingly, TRIBAL transduction failed to restore function in TRIBAL-suppressed cells, which may be linked to structural differences, as supported by contrasting RNAseR sensitivities between the endogenous and transduced forms. In summary, these findings support the use of HepaRG cells as an experimental model to study TRIBAL and underscore its importance in regulating key hepatocyte genes essential for metabolic function.

cell biology↗

bioRxiv2024

Climatic fluctuations modulate eco-evolutionary processes associated with pathogen dynamics and continue to fuel bacterial spot epidemics in tomato

Recurring outbreaks caused by endemic pathogens continue to pose problems in managing plant, wildlife, livestock and human health. Understanding how these outbreaks unfold and what drives the variability in disease epidemics across space and time is less understood, especially in the agricultural settings. In this study, we investigated the contribution of pathogen genetic diversity, climatic variation and their interaction towards disease dynamics, with an integrative approach grounded on multitype, high resolution sequencing data and analysis techniques. This investigation was carried out for bacterial spot disease epidemic by surveying tomato fields for bacterial pathogen (Xanthomonas perforans) across southeastern US over a span of three years. The strength of epidemic severity varied across space and time in the agricultural fields. Disease severity was positively associated with strain diversity, and was linked to environmental fluctuations, specifically, large variation and extreme changes in certain climatic factors. Strain-resolved metagenomics approach revealed that co-existence of multiple pathogen lineages was common in the individual fields, although accompanied by differential lineage dynamics. The co-occurring lineages displayed environmentally dependent fitness contributions. By tracing allelic frequencies in pathogen populations across temporal scales, we find evidence for asynchronous allele cycling across seasons, hinting at the presence of adaptive single-nucleotide polymorphisms (SNPs) being polymorphic in space in response to seasonality. Despite this pathogen heterogeneity, we identified positively selected loci under parallel evolution, which may explain the nature of selection pressures experienced by the pathogen. While single pathogen lineage is assumed to dominate the host in the agricultural settings, our findings challenge this notion by demonstrating genetic diversity in the pathogen population observed within a single field and linking it to the disease dynamics. Our results explain the role of pathogen genetic diversity, climate-dependent compositional dynamics, and differential fitness contributions in dictating the variability of disease epidemics in the agricultural settings. Such findings will be invaluable for building predictive models in disease epidemiology. Our high-resolution combinatorial approach exploiting high- resolution sequence data, metadata types and analysis tools, is general enough to finely investigate disease epidemics at large scales in diverse case-studies concerning plant, animal and human health.

microbiology↗

bioRxiv2024

Constitutive Photomorphogenesis Protein 1 homolog (COP1) sustains nuclear factor-4 alpha function in human hepatocyte models

Constitutive Photomorphogenesis Protein 1 homolog (COP1) is a conserved E3 ligase with key roles in several biological systems. Prior work in hepatocyte derived tumors categorized COP1 as an oncogene but its role in untransformed hepatocytes remains largely unexplored. Here we have investigated the role of COP1 in primary human hepatocytes as well as in two transformed hepatocyte models, HepG2 and HuH-7 cells. Contrary to a previous report, COP1 suppression via siRNA had no noticeable impact on HepG2 and HuH-7 proliferation and was associated with contrasting rather than congruent transcriptome changes. Clustering analyses identified patterns indicative of perturbed metabolism in primary hepatocytes and HepG2 cells whereas patterns pointed to cell proliferation impacts in HuH-7 cells. In HepG2 and primary hepatocytes, COP1 suppression reduced the expression important hepatic regulators and markers, which could be restored by the introduction of a siRNA resistant COP1 transgene. COP1 downregulation reduced hepatic nuclear factor-4 alpha (HNF4A) abundance and function, as assessed by lower abundance of key HNF4A targets and reduced APOB secretion. HNF4A restoration partially rescued COP1 silencing in HepG2 cells. This study identifies COP1 as a key regulator of hepatocyte function, in part via HNF4A. COP1 was required to maintain HNF4A abundance and function in primary hepatocytes and in HepG2 cells, but not in HuH-7 cells. Lastly, by demonstrating contrasting roles of COP1 in HuH-7 and HepG2 cells, our findings also challenge previous work linking COP1 to hepatic tumorigenesis.

cancer biology↗

bioRxiv2023

Inferring invasion determinants with mechanistic models and multitype samples

Dispersal, and in particular the frequency of long-distance dispersal (LDD) events, has strong implications for population dynamics with possibly the acceleration of the colonisation front, and for evolution with possibly the conservation of genetic diversity along the colonised domain. However, accurately inferring LDD is challenging as it requires both large-scale data and a methodology that encompasses the redistribution of individuals in time and space. Here, we propose a mechanistic-statistical framework to estimate dispersal from one-dimensional invasions. The mechanistic model takes into account population growth and grasps the diversity in dispersal processes by using either diffusion, leading to a reaction-diffusion (R.D.) formalism, or kernels, leading to an integro-differential (I.D.) formalism. The latter considers different dispersal kernels (e.g. Gaussian, Exponential, and Exponential-power) differing in their frequency of LDD events. The statistical model relies on dedicated observation laws that describe two types of samples, clumped or not. As such, we take into account the variability in both habitat suitability and occupancy perception. We first check the identifiability of the parameters and the confidence in the selection of the dispersal process. We observed good identifiability for all parameters (correlation coefficient > 0.9 between true and fitted values). The dispersal process that is the most confidently identified is Exponential-Power (i.e. fat-tailed) kernel. We then applied our framework to data describing an annual invasion of the poplar rust disease along the Durance River valley over nearly 200 km. This spatio-temporal survey consisted of 12 study sites examined at seven time points. We confidently estimated that the dispersal of poplar rust is best described by an Exponential-power kernel with a mean dispersal distance of 1.94 km and an exponent parameter of 0.24 characterising a fat-tailed kernel with frequent LDD events. By considering the whole range of possible dispersal processes our method forms a robust inference framework. It can be employed for a variety of organisms, provided they are monitored in time and space along a one-dimension invasion.

evolutionary biology↗

bioRxiv2022

Regulation of TRIB1 abundance in hepatoma models

Tribbles related homolog 1 (TRIB1) contributes to lipid and glucose homeostasis by facilitating the degradation of cognate cargos by the proteasome. We previously reported that TRIB1 was unstable in non-hepatic cellular models. Moreover, inclusion of proteasome inhibitors failed to prevent TRIB1 loss, consistent with the involvement of proteasome independent degradative processes. In view of the key role of TRIB1 in liver function, we continue our exploration of TRIB1 regulation pathways in two commonly used human hepatocyte models, HuH-7 and HepG2 cells. Proteasome inhibitors potently upregulated both endogenous and recombinant TRIB1 mRNA and protein levels. Increased transcript abundance was independent of MAPK activation while ER stress was a relatively mild inducer. Despite increasing TRIB1 protein abundance and stabilizing bulk ubiquitination, proteasome inhibition failed to stabilize TRIB1, pointing to the predominance of proteasome independent protein degradation processes controlling TRIB1 protein abundance in hepatomas. Proteasome inhibition via downregulation of its PSMB3 regulatory subunit, in contrast to its chemical inhibition, had minimal impact on TRIB1 levels. Moreover, immunoprecipitation experiments showed no evidence of TRIB1 ubiquitination. Cytoplasmic retained TRIB1 was unstable, indicating that TRIB1 lability is regulated prior to its nuclear import. Substitution of the TRIB1 PEST-like region with a GST helical region or N-terminal deletions failed to fully stabilize TRIB1. Finally, inclusion of protease or autophagy inhibitors in vivo did not rescue TRIB1 stability. This work excludes proteasome-mediated degradation as a significant contributor to TRIB1 instability and identifies transcriptional regulation as a prominent mechanism regulating TRIB1 abundance in liver models in response to proteasome inhibition.

cell biology↗

bioRxiv2021

Dynamics of Aedes albopictus invasion. Insights from a spatio-temporal model

France displays a latitudinal range for the expansion of Aedes albopictus invasive populations that is not yet completely colonized providing a critical opportunity to address key invasion processes. We propose a spatio-temporal model (DISTIGRI) to describe and predict current and future expansion at both intra- and inter-annual scales of A. albopictus. This process-based model integrates mechanistic descriptions of the developmental cycle and the dispersal process of A. albopictus within a reaction-diffusion framework, depending on climatic suitability and photoperiod with a high spatio-temporal resolution. Using this model coupled with a climatic database, we propose several maps describing the current intra-annual distribution of A. albopictus, including the date of first emergence and the length of the period with significant adult presence. We also compute its future distribution over the next 10 years under several climatic scenarios, which shows a range expansion with a strong dependence on the climatic scenario. The outputs of the model may constitute a valuable asset for designing control and avoidance strategies, and to anticipate the biting nuisance with a high spatio-temporal resolution. These outputs also emphasize the importance of taking both dispersal and life cycle into account to obtain accurate descriptions of out-of-equilibrium processes such as ongoing invasions.

ecology↗

bioRxiv2021

A common polymorphism that protects from cardiovascular disease increases fibronectin processing and secretion

BackgroundFibronectin (FN1) is an essential regulator of homodynamic processes and tissue remodeling which has been proposed to contribute to atherosclerosis. Moreover, recent large scale genome wide association studies have linked common genetic variants within the FN1 gene to coronary artery disease (CAD) risk. MethodsPublic databases were analyzed by two-Sample Mendelian Randomization. Expression constructs encoding short FN1 reporter constructs and full-length plasma FN1, differing in the polymorphism, were designed and introduced in various cell models. Secreted and cellular levels were then analyzed and quantified by SDS-PAGE and fluorescence approaches. Mass spectrometry and glycosylation analyses were performed to probe possible post-transcriptional differences. ResultsHigher FN1 protein levels in plasma associates with a reduced risk of cardiovascular disease. Moreover, common CAD risk SNPs in the FN1 locus associate with circulating levels of FN1. This region is shown to encompass a L15Q polymorphism within the FN1 signal peptide. The presence of the minor allele that predisposes to CAD, corresponding to the Q15 variant, alters glycosylation and reduces FN1 secretion in a direction consistent with the bioinformatic analyses. ConclusionIn addition to providing novel functional evidence implicating FN1 as a protective force in cardiovascular disease, these findings demonstrate that a common variant within a secretion signal peptide regulates protein function.

biochemistry↗

bioRxiv2020

Emerging strains of watermelon mosaic virus in Southeastern France: model-based estimation of the dates and places of introduction

Where and when alien organisms are successfully introduced are central questions to elucidate biotic and abiotic conditions favorable to the introduction, establishment and spread of invasive species. We propose a modelling framework to analyze multiple introductions by several invasive genotypes or genetic variants, in competition with a resident population, when observations provide knowledge on the relative proportions of each variant at some dates and places. This framework is based on a mechanistic-statistical model coupling a reaction-diffusion model with a probabilistic observation model. We apply it to a spatio-temporal dataset reporting the relative proportions of five genetic variants of watermelon mosaic virus (WMV, genus Potyvirus, family Potyviridae) in infections of commercial cucurbit fields. Despite the parsimonious nature of the model, it succeeds in fitting the data well and provides an estimation of the dates and places of successful introduction of each emerging variant as well as a reconstruction of the dynamics of each variant since its introduction.

ecology↗

bioRxiv2018

Heuristic optimisation of the management strategy of a plant epidemic using sequential sensitivity analyses

O_LIOptimisation of management strategies of epidemics is often limited by constraints on experiments at large spatiotemporal scales. A promising approach consists in modelling the biological epidemic process and human interventions, which both impact disease spread. However, few methods enable the simultaneous optimisation of the numerous parameters of sophisticated control strategies. To do so, we propose a heuristic approach based on sequential use of sensitivity analysis. This work is motivated by sharka (caused by Plum pox virus), a vector-borne disease of prunus trees (especially apricot, peach and plum), and its management in orchards, mainly based on surveillance and tree removal.\nC_LIO_LIOur approach is based on three sensitivity analyses which respectively aim to: i) identify the key parameters of a spatiotemporal model simulating disease spread and control; ii) approach optimal values for the key parameters; iii) refine the optimisation.\nC_LIO_LIWe highlight the importance of carefully designing the removal procedure, and propose improved strategies with regard to an economic criterion accounting for both the cost of the different control measures and the benefit generated by productive trees.\nC_LIO_LIWe expect that our general approach will help policymakers to design sustainable and cost-effective strategies for the management of infectious diseases.\nC_LI

epidemiology↗

bioRxiv2017

Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease, and from the computationally intractable number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a fragmented landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years over 600 orchards, we obtain the first estimate of the distribution of the flight distances of infectious aphids at the landscape scale. Most infectious aphids leaving a tree land beyond the bounds of a 1-ha orchard (50% of flights terminate within about 90 m). Moreover, long-distance flights are not rare (10% of flights exceed 1 km). By their impact on our quantitative understanding of winged aphids dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.\n\nAuthor SummaryIn spatial epidemiology, dispersal kernels quantify how the probability of pathogen dissemination varies with distance. Spatial models of pathogen spread are sensitive to kernel parameters; yet these parameters have rarely been estimated using field data gathered at relevant scales. Robust estimation is rendered difficult by practical constraints limiting the number of surveyed individuals, and uncertainties concerning their disease status. Here, we present a framework that overcomes these barriers and permits inference for a between-patch transmission model. Extensive simulations show that dispersal kernels can be estimated from epidemiological surveillance data. When applied to such data collected from more than 600 orchards during 15 years of a plant virus epidemic our approach enables the estimation of the dispersal kernel of infectious winged aphids. This kernel is long-tailed, as 50% of the infectious aphids leaving a tree terminate their infectious flight within 90 m and 10% beyond 1 km. This first estimate of flight distances at the landscape scale for aphids-a group of vectors transmitting numerous viruses-is crucial for the science-based design of control strategies targeting plant virus epidemics.

epidemiology↗