Biology subjects

Francois, P.

Publications and source records attributed to Francois, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Cycles upon cycles - Temperature Scaling of Medaka Development

How organisms develop in dynamic environmental conditions is a fundamental question. We asked how day-night temperature cycles impact embryonic axis elongation and segmentation, itself a cyclic process linked to the segmentation clock, using the Japanese rice fish medaka. We developed an unbiased dimensional reduction approach, based on Singular Value Decomposition (SVD), to reliably identify the dynamic modes of segmentation clock oscillations across all temperature conditions. We reveal that the two major dynamic modes show opposite temperature sensitivities: while the temporal oscillation (mode 1) varies strongly with temperature, the spatial phase gradient (mode 2) appears largely temperature invariant. In addition, we found developmental parameters with intermediate, sub-scaled temperature responses, such as axis elongation. We used theoretical modeling to understand how dynamic modes emerge from the underlying local oscillation dynamics and axis elongation. We then exposed embryos to circadian and ultradian temperature cycles to reveal dynamic response patterns of oscillations and axis elongation, and found how these responses are integrated into morphological features. Combined, our theoretical-experimental results support a model in which the dynamic integration of temporal (i.e. segmentation clock related) and spatial (i.e. axis elongation) processes, in particular their sub-scaled temperature response patterns, quantitatively compensate each other to yield a robust, temperature-invariant axis patterning outcome.

developmental biology↗

bioRxiv2025

Division Asymmetry Drives Cell Size Variability in Budding Yeast

Cell size variability within proliferating populations reflects the interdependent regulation of cell growth and division as well as intrinsically stochastic effects. In budding yeast, the G1/S transition exerts strong size control in daughter cells, which manifests as the inverse correlation between how big a cell is when it is born and how much it grows in G1. However, mutations affecting this size control checkpoint only modestly influence population-wide size variability, often altering the coefficient of variation (CV) only by [~]10%. To resolve this paradox, we combine computational modeling and live-cell imaging to identify the principal determinants of cell size variability. Using an experimentally validated stochastic model of the yeast cell cycle, we perform parameter sensitivity analysis and find that division asymmetry between mothers and daughters is the dominant driver of CV, outweighing the effects of G1/S size control. Experimental measurements across genetic perturbations and growth conditions confirm a strong correlation between mother-daughter size asymmetry and population CV. These findings reconcile previous observations and show how asymmetric division operates in concert with G1/S size control to govern cell size heterogeneity.

cell biology↗

bioRxiv2025

Dynamical model and geometric insights in the discontinuity theory of immunity

The immune systems most basic task is to decide what is "self" and "non-self", but a precise definition of self versus non-self remains challenging. According to the discontinuity theory of immunity, effector responses depend on how quickly an antigenic stimulus changes: rapid change triggers an immune response, whereas gradual change fosters tolerance. We present a model of adaptive immune dynamics including T cells, Tregs and cytokines that reproduces the hallmarks of the discontinuity theory. The model allows for sharp discrimination between acute and chronic infections based on the growth rate of the immune challenge, and vaccination-like acute dynamics upon presentation of a bolus of immune challenge. We further show that the model behavior only depends on a handful of testable assumptions that we map to geometric constraints in phase space. This suggests that the model properties are generic and robust across alternative mechanistic details. We also examine the impact of multiple concurrent immune challenges in this model, and demonstrate the occurrence of dynamical antagonism, wherein, in some parameter regimes, slow-growing challenges hinder acute responses to fast-growing ones, with further counter-intuitive behaviors for sequential co-infections. Together, these results place the discontinuity theory on firm mathematical footing and encourage further investigation of interferences of multi-agent immune challenges, from chronic viral co-infections to cancer immunoediting.

systems biology↗

bioRxiv2025

Generative epigenetic landscapes map the topology and topography of cell fates

Epigenetic landscapes were proposed by Waddington as the central concept to describe cell fate dynamics in a locally low-dimensional space. In modern landscape models, attractors represent cell types, and stochastic jumps and bifurcations drive cellular decisions, allowing for quantitative and predictive descriptions. However, given a biological problem of interest, we still lack tools to infer and build possible Waddington landscapes systematically. In this study, we propose a generative model for deriving epigenetic landscapes compatible with data. To build the landscapes, we combine gradient and rotational vector fields composed of locally weighted elements that encode valleys of the Waddington landscape, resulting in interpretable models. We optimize landscapes through computational evolution and illustrate our approach with two developmental examples: metazoan segmentation and neuromesoderm differentiation. In both cases, we obtain ensembles of solutions that reveal both known and novel landscapes in terms of topology and bifurcations. Conversely, topographic features appear strongly constrained by dynamical data, which suggests that our approach can generically derive interpretable and predictive epigenetic landscapes.

developmental biology↗

bioRxiv2025

Manifold learning for olfactory habituation to strongly fluctuating backgrounds

Animals rely on their sense of smell to survive, but important olfactory cues are mixed with confounding background odors that fluctuate due to atmospheric turbulence. It is unclear how the olfactory system habituates to such stochastic backgrounds to detect behaviorally important odors. Here, we explicitly consider the high-dimensional nature of odor coding, the natural statistics of odor fluctuations and the architecture of the early olfactory pathway. We show that their combination favors a manifold learning mechanism for olfactory habituation over alternatives based on predictive filtering. Manifold learning is implemented in our model by a biologically plausible network of inhibitory interneurons in the early olfactory pathway. We demonstrate that plasticity rules based on IBCM or online PCA are effective at implementing this mechanism in turbulent conditions and outperform previous models relying on mean background subtraction. Interneurons with an IBCM plasticity rule acquire selectivity to independently varying odors. This manifold learning mechanism offers a path towards distinguishing plasticity rules in experiments and could be leveraged by other biological circuits facing fluctuating environments.

neuroscience↗

bioRxiv2025

Oscillatory Co-expression of HES1 and HES5 Enables a Hybrid State in a Bistable Transcription Factor Regulatory Motif

Many cell fate decisions in the developing neural tube are directed by cross-repressive transcription factor (TF) motifs that generate bistability, enforcing expression of one dominant TF. However, evidence of hybrid states, where cells co-express opposing fate determinants, challenges this model. We hypothesised that oscillatory expression enables co-existence of cross-repressive TFs within single cells, allowing hybrid states in bistable motifs. To test this, we focused on HES1 and HES5, oscillatory, cross-repressive TFs that regulate neural progenitor maintenance and are expressed in adjacent dorsoventral domains in the developing spinal cord. Using live-cell imaging of fluorescent reporters and computational modelling, we show that HES1 and HES5 co-express and oscillate in-phase within single cells. Differences in protein stability result in distinct free-running periodicity, but co-expression results in entrainment and phase-locking. Modulating cross-repression strength and/or abundance shifts the system towards bistability and dominance of a single TF oscillator. Consistent with this, we observe progressive separation of the HES expression domains in vivo, through a decrease in oscillatory co-expression. Our findings provide a mechanism for hybrid states to emerge in a developmental bistable motif.

developmental biology↗

bioRxiv2025

The Staphylococcus aureus prophage-encoded SSBP attenuates virulence and enhances IL-6-mediated macrophage clearance

Pathogens often manipulate host immune responses to promote infection. Here, we describe a novel mechanism by which a secreted prophage-encoded single-stranded DNA-binding protein (SSBP) attenuates Staphylococcus aureus virulence while enhancing host immune defenses. SSBP, encoded by the ROSA-like prophage in a colonizing, reduced-virulence strain of S. aureus (NSA1385), significantly increases bacterial susceptibility to macrophage-mediated killing in vitro and reduces pathogenicity in a zebrafish infection model. Treatment with purified recombinant SSBP decreases bacterial survival within macrophages and demonstrates therapeutic potential. Notably, SSBP activates macrophages via interleukin-6 (IL-6), a pro-inflammatory cytokine that promotes bacterial clearance and macrophage activation. These findings uncover an unexpected prophage-derived mechanism in a colonizing S. aureus strain that attenuates virulence while stimulating host immunity, offering promising avenues for anti-infective therapies and immunomodulatory strategies.

microbiology↗

bioRxiv2024

The Product neutrality function defining genetic interactions emerges from mechanistic models of cell growth

Genetic analyses, which examine the phenotypic effects of mutations both individually and in combination, have been fundamental to our understanding of cellular functions. Such analyses rely on a neutrality function that predicts the expected phenotype for double mutants based on the phenotypes of the two individual non-interacting mutations. In this study, we examine fitness, the most fundamental cellular phenotype, through an analysis of the extensive colony growth rate data for budding yeast. Our results confirm that the Product neutrality function describes the colony growth rate, or fitness, of a double mutant as the product of the fitnesses of the individual single mutants. This Product neutrality function performs better than additive or minimum neutrality functions, supporting its continued use in genetic interaction studies. Furthermore, we explore the mechanistic origins of this neutrality function by analyzing two theoretical models of cell growth. We perform a computational genetic analysis to show that in both models the product neutrality function naturally emerges due to the interdependence of cellular processes that maximize growth rates. Thus, our findings provide mechanistic insight into how the Product neutrality function arises and affirm its utility in predicting genetic interactions affecting cell growth and proliferation.

systems biology↗

bioRxiv2024

Unveiling novel conserved HIV-1 open reading frames encoding T cell antigens using ribosome profiling.

The development of ribosomal profiling (Riboseq) revealed the immense coding capacity of human and viral genomes. Here, we used Riboseq to delineate the first translatome of HIV-1 in infected CD4+ T cells. In addition to canonical viral protein coding sequences (CDSs), we identify 98 alternative open reading frames (ARFs), corresponding to small Open Reading Frames (sORFs) that are distributed across the HIV genome including the UTR regions. Using a database of HIV genomes, we observed that most ARF amino-acid sequences are likely conserved among clade B and C of HIV-1, with 8 ARF-encoded amino-acid sequences being more conserved than the overlapping CDSs. Using T cell-based assays and mass spectrometry-based immunopeptidomics, we demonstrate that ARFs encode viral polypeptides. In the blood of HIV-infected individuals, ARF-derived peptides elicit potent poly-functional T cell responses mediated by both CD4+ and CD8+ T cells. Our discovery expands the list of conserved viral polypeptides that are targets for vaccination strategies and might reveal the existence of viral microproteins or pseudogenes.

immunology↗

bioRxiv2024

Foci, waves, excitability : self-organization of phase waves in a model of asymmetrically coupled embryonic oscillators

The segmentation clock is an emergent embryonic oscillator that controls the periodic formation of vertebrae precursors (or somites). It relies on the self-organization at the Pre Somitic Mesoderm (PSM) level of multiple coupled cellular oscillators. Dissociation-reaggregation experiments have further revealed that ensembles made of such cellular oscillators self-organize into an oscillatory bidimensional system, showing concentric waves around multiple foci. Here, we systematically study the dynamics of a two dimensional lattice of phase oscillators locally coupled to their nearest neighbors through a biharmonic coupling function, of the form sin{theta} + {Lambda} sin2{theta} . This coupling was inferred from the Phase Response Curve (PRC) of entrainment experiments on cell cultures, leading to the formulation of a minimal Elliptic Radial Isochron Cycle (ERIC) phase model. We show that such ERIC-based coupling parsimoniously explains the emergence of self-organized concentric phase wave patterns around multiple foci, for a range of weak couplings and wide distributions of initial random phases, closely mimicking experimental conditions. We further study extended modalities of this problem to derive an atlas of possible behaviours. In particular, we predict the dominant observation of spirals over target wave patterns for initial phase distributions wider than approximately{pi} . Since PSM cells further display properties of an excitable system, we also introduce excitability into our simple model, and show that it also supports the observation of concentric phase waves for the conditions of the experiment. Our work suggests important modifications that can be made to the simple phase model with Kuramoto coupling, that can provide further layers of complexity and can aid in the explanation of the spatial aspects of self-organization in the segmentation clock.

biophysics↗

bioRxiv2024

The interplay between Mobilome and Resistome in Staphylococcus aureus

Antibiotic resistance genes (ARGs) in Staphylococcus aureus can disseminate vertically through successful clones, but also horizontally through the transfer of genes conveyed by mobile genetic elements (MGEs). The underexplored MGE/ARG associations in S. aureus favor the emergence of multidrug-resistant clones, posing a significant threat to human and animal health. This study investigated the interplay between the mobilome, encompassing MGEs, and the resistome, the collection of ARGs, in more than 10,000 S. aureus genomes from human and animal sources. The analysis revealed a remarkable diversity of MGEs and ARGs, with plasmids and transposons being the main carriers of resistance genes. Numerous MGE/ARG associations were identified, suggesting that MGEs play a critical role in the dissemination of resistance. A high degree of similaritywas observed in MGE/ARG associations between human and animal isolates, highlighting the potential for unrestricted spread of ARGs between hosts. While clonal expansion is a major driver of resistance dissemination in S. aureus, our results showed that MGEs and their associated ARGs can spread across different strain types (STs), favoring the evolution of these clones and their adaptation in selective environments. The high variability of MGE/ARG associations within individual STs and the ir spread across several STs highlight the crucial role of MGEs in shaping the S. aureus resistome. Overall, this study provides valuable insights into the complex interplay between MGEs and ARGs in S. aureus, emphasizing the need to elucidate the mechanisms governing the epidemic success of MGEs, particularly those implicated in ARG transfer. ImportanceThe research presented in this article highlights the crucial importance of understanding the interactions between mobile genetic elements (MGEs) and antibiotic resistance genes (ARGs) carried by Staphylococcus aureus, a versatile bacterium that can be both a harmless commensal and a dangerous pathogen for humans and animals. S. aureus strains represent a major threat due to their ability to rapidly acquire and disseminate ARGs. By analyzing a large dataset of S. aureus genomes, we highlighted the substantial role of MGEs, in particular plasmids and transposons, in the dissemination of ARGs within and between S. aureus populations, bypassing the host barrier. Given that multidrug-resistant S. aureus strains are classified as a high-prioritypathogenby global health organizations, this knowledge is crucial for understanding the complex dynamics of transmission of antibiotic resistance in this species.

microbiology↗

bioRxiv2024

Nonreciprocal synchronization in embryonic oscillator ensembles

Synchronization of coupled oscillators is a universal phenomenon encountered across different scales and contexts e.g., chemical wave patterns, superconductors and the unison applause we witness in concert halls. The existence of common underlying coupling rules define universality classes, revealing a fundamental sameness between seemingly distinct systems. Identifying rules of synchronization in any particular setting is hence of paramount relevance. Here, we address the coupling rules within an embryonic oscillator ensemble linked to vertebrate embryo body axis segmentation. In vertebrates, the periodic segmentation of the body axis involves synchronized signaling oscillations in cells within the presomitic mesoderm (PSM), from which somites, the pre-vertebrae, form. At the molecular level, it is known that intact Notch-signaling and cell-to-cell contact is required for synchronization between PSM cells. However, an understanding of the coupling rules is still lacking. To identify these, we develop a novel experimental assay that enables direct quantification of synchronization dynamics within mixtures of oscillating cell ensembles, for which the initial input frequency and phase distribution are known. Our results reveal a "winner-takes-it-all" synchronization outcome i.e., the emerging collective rhythm matches one of the input rhythms. Using a combination of theory and experimental validation, we develop a new coupling model, the "Rectified Kuramoto" (ReKu) model, characterized by a phase-dependent, non-reciprocal interaction in the coupling of oscillatory cells. Such non-reciprocal synchronization rules reveal fundamental similarities between embryonic oscillators and a class of collective behaviours seen in neurons and fireflies, where higher level computations are performed and linked to non-reciprocal synchronization.

systems biology↗

bioRxiv2023

RlmQ: A Newly Discovered rRNA Modification Enzyme Bridging RNA Modification and Virulence Traits in Staphylococcus aureus

rRNA modifications play crucial roles in fine-tuning the delicate balance between translation speed and accuracy, yet the underlying mechanisms remain elusive. Comparative analysis of the ribosomal RNA modifications in taxonomically distant bacteria could help define their general as well as species-specific roles. In this study, we identified a new methyltransferase, RlmQ, in Staphylococcus aureus responsible for the Gram-positive specific m7G2601, which is not modified in E. coli (G2574). We also demonstrate the absence of methylation on C1989, equivalent to E. coli C1962, which is methylated at position 5 by the Gram-negative specific RlmI methyltransferase, a paralogue of RlmQ. Both modifications (S. aureus m7G2601 and E. coli m5C1962) are situated within the same tRNA accommodation corridor, hinting at a potential shared function in translation. Inactivation of S. aureus rlmQ causes the loss of methylation at G2601 and significantly impacts growth, cytotoxicity, and biofilm formation. These findings unravel the intricate connections between rRNA modifications, translation, and virulence in pathogenic Gram-positive bacteria.

molecular biology↗

bioRxiv2022

Extensive uORF translation from HIV-1 transcripts conditions DDX3 dependency for expression of main ORFs and elicits specific T cell immune responses in infected individuals

Human immunodeficiency virus type-1 (HIV-1) is a complex retrovirus which relies on alternative splicing, translational and post-translational mechanisms to produce more than 15 functional proteins from its single [~]10kb transcriptional unit. Here, we have applied ribosome profiling and nascent protein labeling at different time points during infection of CD4+ T lymphocytes to characterize the translational landscape of cellular and viral transcripts during the course of infection. Our results indicate a strong impact of viral infection on host cellular transcript levels but a modest impact on global translation rates. Analysis of ribosome profiling reads from viral transcripts reveals extensive and productive non-AUG translation of small peptides from multiple upstream open reading-frames (uORFs) located in the 5 long terminal repeat. Remarkably, these uORFs derived peptides elicit specific T cell responses in HIV-infected individuals. uORFs are conserved among other retroviruses and, together with the TAR sequence, condition the dependency on DDX3 for efficient translation of the main viral open-reading frames.

microbiology↗

bioRxiv2022

Evolution of cell size control is canalized towards adders or sizers by cell cycle structure and selective pressures

Cell size is controlled to be within a specific range to support physiological function. To control their size, cells use diverse mechanisms ranging from sizers, in which differences in cell size are compensated for in a single cell division cycle, to adders, in which a constant amount of cell growth occurs in each cell cycle. This diversity raises the question why a particular cell would implement one rather than another mechanism? To address this question, we performed a series of simulations evolving cell size control networks. The size control mechanism that evolved was influenced by both cell cycle structure and specific selection pressures. Moreover, evolved networks recapitulated known size control properties of naturally occurring networks. If the mechanism is based on a G1 size control and an S/G2/M timer, as found for budding yeast and some human cells, adders likely evolve. But, if the G1 phase is significantly longer than the S/G2/M phase, as is often the case in mammalian cells in vivo, sizers become more likely. Sizers also evolve when the cell cycle structure is inverted so that G1 is a timer, while S/G2/M performs size control, as is the case for the fission yeast S. pombe. For some size control networks, cell size consistently decreases in each cycle until a burst of cell cycle inhibitor drives an extended G1 phase much like the cell division cycle of the green algae Chlamydomonas. That these size control networks evolved such self-organized criticality shows how the evolution of complex systems can drive the emergence of critical processes.

systems biology↗

bioRxiv2021

Interest of phenomic prediction as an alternative to genomic prediction in grapevine

Phenomic prediction has been defined as an alternative to genomic prediction by using spectra instead of molecular markers. A reflectance spectrum reflects the biochemical composition within a tissue, under genetic determinism. Thus, a relationship matrix built from spectra could potentially capture genetic signal. This new methodology has been successfully applied in several cereal species but little is known so far about its interest in perennial species. Besides, phenomic prediction has only been tested for a restricted set of traits, mainly related to yield or phenology. This study aims at applying phenomic prediction for the first time in grapevine, using spectra collected on two tissues and over two consecutive years, on two populations and for 15 traits. First, we characterized the genetic signal in spectra and under which condition it could be maximized, then phenomic predictive ability was compared to genomic predictive ability. We found that the co-inertia between spectra and genomic data was stable across tissues or years, but variable across populations, with co-inertia around 0.3 and 0.6 for diversity panel and half-diallel populations, respectively. Differences between populations were also observed for predictive ability of phenomic prediction, with an average of 0.27 for the diversity panel and 0.35 for the half-diallel. For both populations, there was a correlation across traits between predictive ability of genomic and phenomic prediction, with a slope around 1 and an intercept of -0.2, thus suggesting that phenomic prediction could be applied for any trait.

genetics↗

bioRxiv2021

2-Guanidino-quinazoline promotes the readthrough of nonsense mutations underlying human genetic diseases

Premature termination codons (PTCs) account for 10% to 20% of genetic diseases in humans. The gene inactivation resulting from PTC can be counteracted by the use of drugs stimulating PTC readthrough, thereby restoring production of the full-length protein. However, a greater chemical variety of readthrough inducers is required to broaden the medical applications of this therapeutic strategy. In this study, we developed a new reporter cell line and performed high-throughput screening (HTS) to identify potential new readthrough inducers. After three successive assays, we isolated 2-guanidino-quinazoline (TLN468). We assessed the clinical potential of this drug as a potent readthrough inducer on the 40 PTCs most frequently responsible for Duchenne muscular dystrophy. We found that TLN468 was more efficient than gentamicin, and acted on a broader range of sequences, without inducing the readthrough of natural stop codons.

molecular biology↗

bioRxiv2021

Arnold tongue entrainment reveals dynamicalprinciples of the embryonic segmentation clock

Living systems exhibit an unmatched complexity, due to countless, entangled interactions across scales. Here we aim to understand a complex system, i.e. segmentation timing in mouse embryos, without a reference to these detailed interactions. To this end, we develop a coarse-grained approach, in which theory guides the experimental identification of the segmentation clock entrainment responses. We demonstrate period- and phase-locking of the segmentation clock across a wide range of entrainment parameters, including higher-order coupling. These quantifications allow to derive the phase response curve (PRC) and Arnold tongues of the segmentation clock, revealing its essential dynamical properties. Our results indicate that the somite segmentation clock has characteristics reminiscent of a highly non-linear oscillator close to an infinite period bifurcation and suggests the presence of long-term feedbacks. Combined, this coarse-grained theoretical-experimental approach reveals how we can derive simple, essential features of a highly complex dynamical system, providing precise experimental control over the pace and rhythm of the somite segmentation clock.

developmental biology↗