Biology subjects

Conte, M.

Publications and source records attributed to Conte, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Scaling of structural variability of ecDNA polymer condensates with copy number boosts and stabilises oncogene regulatory contacts

Extrachromosomal DNAs (ecDNAs) form highly heterogeneous condensates in cancer cells that drive oncogene overexpression, yet how structural variability coexists with stable gene regulation remains unclear. Here, we develop a minimal polymer physics model of MYC-harbouring COLO320-DM ecDNAs, where BRD4-like complexes bind and bridge cognate sites along ecDNA rings. Above a critical binder concentration, ecDNAs phase separate into condensates exhibiting diverse conformations because of their thermodynamic folding degeneracy. Despite this variability, condensates retain conserved interaction scaffolds that give rise to reproducible contact patterns, including in-trans associated domains (I-TADs), genomic regions enriched in intermolecular regulatory contacts between distinct ecDNAs. We find that condensate 3D architecture follows universal scaling relations with ecDNA copy number, n, remaining robust to model parameter changes. Regulatory contacts within I TADs increase linearly with n, yet they are one order of magnitude stronger than in size matched control regions outside I TADs, whereas their relative fluctuations are markedly suppressed as n increases. This scaling produces enhanced, low-noise regulatory environments for oncogenes embedded within I-TADs, such as PVT1-MYC fusions, whereas the canonical MYC copy, located outside, is less amplified as experimentally observed. Our findings reveal universal polymer physics principles underlying ecDNA condensate organization, offering a mechanistic basis for selective oncogene amplification and potential advantages in cancer progression.

biophysics↗

bioRxiv2026

LARP1-DM15/Sgt is a reader for cap-adjacent 2`-O-ribose methylation in TOP ribosomal protein mRNAs required for localization to synapses

The most prominent mRNA modification in animals and many of their parasites is 2`-O-ribose methylation of cap-adjacent nucleotides (cOMe) introduced by cap-methyl transferases (CMTrs). How these modifications impact on gene expression and are decoded by reader proteins, however, remains uncertain. Through analysis of transcriptional start-site usage, we discovered a bias in ribosomal protein mRNAs starting with the Terminal Oligo Pyrimidine (TOP) motif, but not other TOP mRNAs in the absence of cOMe. cOMe stabilizes TOP mRNAs, enhances binding of the LARP1-DM15 domain to the TOP mRNA 5` end and is assisted by the tetratricopeptide domain-containing protein Sgt/SGTA/B. This conserved complex is required for localization of TOP ribosomal protein mRNAs to Drosophila synapses. Our study reveals an mRNA methylation-mediated mechanism to maintain local protein synthesis remote from the nucleus for sustained synaptic functions.

molecular biology↗

bioRxiv2026

Ultrahigh-throughput screening for sialic acid-active enzymes in the microbial genetic diversity

Sialic acids (Sias) and related nonulosonic acids are critical components of glycoconjugates involved in host-pathogen interactions, immune regulation, and cell signalling. Despite their biotechnological relevance, the diversity of enzymes involved in Sia biosynthesis remains largely underexplored due to limitations in culture-dependent methods and the lack of (ultra)high-throughput screening strategies. Here, we report the development of a highly sensitive droplet-based microfluidic screening platform enabling the functional discovery of sialic acid aldolases in environmental metagenomes. The method integrates a fluorescence-coupled enzymatic cascade compatible with fluorescence-activated droplet sorting (FADS), allowing the screening of >10 droplets per experiment, as well as a downstream validation strategy for the selected hits. Although some limitations were identified, the system demonstrated high sensitivity and was utilised for the screening of a metagenomic library from garden soil. During this campaign, a potential new sialic acid aldolase enzyme was identified. This work establishes a generalizable framework for measuring complex, multi-step enzymatic functions at ultrahigh throughput using coupled cascades in droplets

microbiology↗

bioRxiv2026

SaVanache: indexing and visualizing pangenome variation graphs

With the rapid increase in genome sequencing and the growing availability of genomic resources, genomics is shifting toward pangenome representations that capture intra- and inter-specific diversity by integrating multiple genomes into a single entity. These pangenomes are increasingly modeled as graphs, encoding complex genomic variations in structures such as de Bruijn or variation graphs. However, while genome browsers provide standard and effective solutions for visualizing single or limited numbers of genomes, equivalent interactive tools for graph-based pangenomes remain limited, particularly for variation graph models. We developed SaVanache, a multi-resolution visualization interface designed to explore pangenome variation graphs at various depths. SaVanache enables the exploration of both global diversity and structural variations (SVs) across genomes relative to a user-defined linear pivot genome. Unlike synteny viewers, SaVanache emphasizes variations by representing SV types through a dedicated set of glyphs, facilitating intuitive one-to-many comparisons. To support smooth exploration, SaVanache preprocesses a Graphical Fragment Assembly (GFA) pangenome file into optimized index and data structures, enabling fast, real-time queries on large pangenome graphs. By combining advanced visualization techniques with efficient data handling, SaVanache provides a robust tool for scientists to analyze and visualize genetic variation within genomes and pangenomes, facilitating the identification of genetic determinants associated with phenotypes of interest and fully exploiting current genomic resources. Author summaryWe introduce SaVanache, an innovative tool that transforms the way we explore genomic resources. SaVanache allows visualization and analysis of pangenome variation graphs (PVGs), which capture genomic diversity by integrating structural variants (SV) and single nucleotide polymorphisms (SNPs) across multiple genomes. Unlike traditional genome browsers limited to a few genomes, SaVanache offers a multi-level, user-friendly interface that allows users to explore from whole pangenomes down to individual structural variants, enabling multidimensional research and development. Using a linear pivot genome as a visual reference, SaVanache simplifies complex PVG structures into intuitive comparisons. It efficiently handles large datasets and speeds up data retrieval through internal parsing. The front-end, built with modern JavaScript frameworks, provides interactive and responsive visualization, while the Python/Django backend supports real-time data updates. Users can detect and classify SVs by comparing syntenic segments between genomes, visualized through a novel glyph-based system that uses shapes and colors to represent complex rearrangements. SaVanache supports seamless zooming from chromosome-wide to nucleotide-level views, interactive diversity scatterplots, dynamic pivot genome switching, and grouping genomes by metadata to explore genotype-phenotype links. In addition, export functions bridge visualization with downstream bioinformatics. Developed with user feedback, SaVanache balances biological relevance and computational efficiency, overcoming PVG complexity to empower users with unprecedented insight into genomic diversity and SVs.

bioinformatics↗

bioRxiv2026

Autosomal dominant CDC45 deficiency with allelic expression bias causes a novel genetic disease of the immune system

Here we describe a damaging heterozygous variant in CDC45 in an individual with common variable immunodeficiency (CVID) and recurrent viral infections. This individual has variably decreased number of circulating NK cells, disruption in the ratio of CD56bright to CD56dim cells, and consistently decreased NK cell function. Interestingly, the inherited CDC45 variant is also present in a sibling with less severe clinical manifestations; we determined that allelic bias of the damaging allele accounts for this differential expressivity. As previously reported for other helicase variants that cause inborn errors of immunity (IEI), we found cell cycle defects in immune cells from the proband that lead to reduced survival of NK cells. Together, these findings link another member of the core replicative helicase complex to inborn errors of immunity and highlight the sensitivity of NK cells to these variants. They also define another case of allelic bias contributing to variable expressivity of an IEI gene.

immunology↗

bioRxiv2025

Functional architecture of cardiac TF regulatory landscapes in control of mammalian heart development

Congenital heart disease (CHD), the most common human birth defect, often results from disruptions in gene regulatory networks (GRNs) that control cardiac lineage specification and cell type identity during heart development. A conserved core set of cardiac transcription factors (TFs) orchestrates these processes through combinatorial interactions that are cell type-specific and tightly regulated across space and time. However, the genomic enhancer architecture that integrates upstream effectors to establish precise cardiac TF dosage and downstream transcriptional output remains largely unresolved. Here, we assessed the functional necessity of five developmental heart enhancer modules previously linked to the regulation of Gata4 and Hand2, core cardiac TFs exhibiting overlapping roles in myocardial and endocardial development. While individual enhancer deletions in mouse embryonic hearts revealed a surprising degree of transcriptional resilience, a subset of Gata4 enhancers proved indispensable for embryonic progression in a genetically compromised background. To achieve higher precision in cardiac cell type-specific enhancer prediction, we applied single-nucleus multiome profiling, enabling the delineation of cardiac cistromes underlying heart morphogenesis. By integrating this resource with deep learning applications, site-directed transgenesis, and chromatin conformation modeling, we mapped the cardiac enhancer repertoire and regulatory signatures that orchestrate Hand2 dynamics across distinct cardiac compartments and lineages. Genome editing further revealed an essential role for the Hand2-upstream regulatory interval (H2-URI) in transcriptional control of endocardial lineage effectors and, consequently, trabecular network formation and cardiac cushion patterning. Together our findings highlight substantial resilience in the cis-regulatory architectures governing cardiac TF dynamics and demonstrate that combinatorial integration of upstream lineage identities across modular enhancer landscapes establishes the cardiac cell type-specific programs driving heart morphogenesis. These results advance the reconstruction of cardiac GRNs and enhance the functional interpretation of CHD-associated variants.

developmental biology↗

bioRxiv2025

Identification of first-in-class small molecule potential inhibitor of GDF15

BackgroundGrowth Differentiation Factor 15 (GDF15), a mitokine implicated in stress response, has been associated with numerous diseases, particularly cancer cachexia. Many approaches, including monoclonal antibodies and peptide antagonists, have been implemented to inhibit GDF15 activity. It is currently unknown whether it is possible to inhibit GDF15 using small organic molecules (SOMs). MethodsA structure-based in silico screening workflow of a curated compound library was implemented to identify SOMs capable of binding to the monomeric or dimeric form of GDF15. The three top-ranking SOMs of each group were then tested in vitro on normal and cancer cells. ResultsAmong all tested SOMs, dioxoimidazolidin derivative named SOM D resulted capable of inhibiting GDF15 dimer formation and decreasing binding to GFRAL. Furthermore, it was found to be devoid of acute cytotoxicity both in normal cells (dermal fibroblasts, DFs) and tumor cells (OV90), to significantly slow proliferation and modify the expression of genes involved in GDF15 signaling or in cell cycle and senescence in OV90, but not in DFs. Interestingly, simultaneous treatment with SOMs and doxorubicin (doxo) failed in arresting the cell cycle compared to doxo alone. ConclusionsThe in silico screening has proven effective in identifying SOMs putatively capable of inhibiting GDF15, among which SOM D appears the most promising. Further characterizations will be necessary to better understand the exact mechanisms of action. Furthermore, the observation that SOMs have an opposite effect on proliferation in cancer versus normal cellular context suggests a dual role in cell-cycle control in presence of cancer aberration.

molecular biology↗

bioRxiv2025

Physical principles of phase-separation action on chromatin looping associated to pathogenic gene activation

Phase-separation of chimeric proteins resulting from genetic mutations has been shown to trigger aberrant chromatin looping, contributing to disease development, including cancer. However, the physical mechanisms regulating these processes are not yet fully understood. In this study, we employ polymer physics models of chromatin and numerical simulations to investigate the relationship between phase-separation of proteins and chromatin structure. We demonstrate that a simple model, including only protein-protein and protein-chromatin interactions, effectively explains the aberrant looping observed around oncogenes, such as PBX3, in cells expressing the NUP98-HOXA9 chimeric protein, which is associated with leukemia. In this scenario, looping occurs through a switch-like mechanism controlled by the concentration of the chimera and its affinity with chromatin. Moreover, when incorporating the presence of extruding factors in a more complex model, similar results are observed, indicating a mild dependence of this looping mechanism on loop-extrusion activity. Finally, leveraging our numerical simulations, we propose potential strategies to inhibit the formation of enhancer-gene loops by directly targeting the chimeric protein with interfering molecules.

biophysics↗

bioRxiv2025

CAR T-cell and oncolytic virus dynamics and determinants of combination therapy success for glioblastoma

Glioblastoma is a highly aggressive and treatment-resistant primary brain cancer. While chimeric antigen receptor (CAR) T-cell therapy has demonstrated promising results in targeting these tumors, it has not yet been curative. An innovative approach to improve CAR T-cell efficacy is to combine them with other immune modulating therapies. In this study, we investigate in vitro combination of IL-13R2 targeted CAR T-cells with an oncolytic virus (OV) and study the complex interplay between tumor cells, CAR T-cells, and OV dynamics with a novel mathematical model. We fit the model to data collected from experiments with each therapy individually and in combination to reveal determinants of therapy synergy and improved efficacy. Our analysis reveals that the virus bursting size is a critical parameter in determining the net tumor infection rate and overall combination treatment efficacy. Moreover, the model predicts that administering the oncolytic virus simultaneously with, or prior to, CAR T-cells could maximize therapeutic efficacy.

immunology↗

bioRxiv2024

Polymer physics models reveal structural folding features of single-molecule gene chromatin conformations

Here, we employ polymer physics models of chromatin to investigate the 3D folding of a 2Mb wide genomic region encompassing the human LTN1 gene, a crucial DNA locus involved in key cellular functions. Through extensive Molecular Dynamics simulations, we reconstruct in-silico the ensemble of single-molecule LTN1 3D structures, which we benchmark against recent in-situ Hi-C 2.0 data. The model-derived single molecules are then used to predict structural folding features at the single-cell level, providing testable predictions for super-resolution microscopy experiments.

molecular biology↗

bioRxiv2024

Antigenic cartography using hamster sera identifies SARS-CoV-2 JN.1 evasion seen in human XBB.1.5 booster sera

Antigenic assessments of SARS-CoV-2 variants inform decisions to update COVID-19 vaccines. Primary infection sera are often used for assessments, but such sera are rare due to population immunity from SARS-CoV-2 infections and COVID-19 vaccinations. Here, we show that neutralization titers and breadth of matched human and hamster pre-Omicron variant primary infection sera correlate well and generate similar antigenic maps. The hamster antigenic map shows modest antigenic drift among XBB sub-lineage variants, with JN.1 and BA.4/BA.5 variants within the XBB cluster, but with five to six-fold antigenic differences between these variants and XBB.1.5. Compared to sera following only ancestral or bivalent COVID-19 vaccinations, or with post-vaccination infections, XBB.1.5 booster sera had the broadest neutralization against XBB sub-lineage variants, although a five-fold titer difference was still observed between JN.1 and XBB.1.5 variants. These findings suggest that antibody coverage of antigenically divergent JN.1 could be improved with a matched vaccine antigen.

microbiology↗

bioRxiv2023

Structural and practical identifiability of contrast transport models for DCE-MRI

Compartment models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.

systems biology↗

bioRxiv2023

Multiscale modelling of chromatin 4D organization in SARS-CoV-2 infected cells

SARS-CoV-2 is able to re-structure chromatin organization and alters the epigenomic landscape of the host genome, though the mechanisms that produce such changes are still poorly understood. Here, we investigate with polymer physics chromatin re-organization of the host genome, in space and time upon SARS-CoV-2 viral infection. We show that re-structuring of A/B compartments is well explained by a re-modulation of intra-compartment homotypic affinities, which leads to the weakening of A-A interactions and enhances A-B mixing. At TAD level, re-arrangements are physically described by a general reduction of the loop extrusion activity coupled with an alteration of chromatin phase-separation properties, resulting in more intermingling between different TADs and spread in space of TADs themselves. In addition, the architecture of loci relevant to the antiviral interferon (IFN) response, such as DDX58 or IFIT, results more variable within the 3D single-molecule population of the infected model, suggesting that viral infection leads to a loss of chromatin structural specificity. Analysis of time trajectories of pairwise gene-enhancer and higher-order contacts reveals that such variability derives from a more fluctuating dynamics in infected case, suggesting that SARS-CoV-2 alters gene regulation by impacting the stability of the contact network in time. Overall, our study provides the first polymer-physics based 4D reconstruction of SARS-CoV-2 infected genome with mechanistic insights on the consequent gene mis-regulation.

biophysics↗

bioRxiv2023

Phase separation of ecDNA aggregates establishes in-trans contact domains boosting selective MYC regulatory interactions

Extrachromosomal DNAs (ecDNAs) are found in the nucleus of an array of human cancer cells where they can form clusters that were associated to oncogene overexpression, as they carry genes and cis-regulatory elements. Yet, the mechanisms of aggregation and gene amplification beyond copy-number effects remain mostly unclear. Here, we investigate, at the single molecule level, MYC-harboring ecDNAs of COLO320-DM colorectal cancer cells by use of a minimal polymer model of the interactions of ecDNA BRD4 binding sites and BRD4 molecules. We find that BRD4 induces ecDNAs phase separation, resulting in the self-assembly of clusters whose predicted structure is validated against HiChIP data (Hung et al., 2021). Clusters establish in-trans associated contact domains (I-TADs) enriched, beyond copy number, in regulatory contacts among specific ecDNA regions, encompassing its PVT1-MYC fusions but not its other canonical MYC copy. That explains why the fusions originate most of ecDNA MYC transcripts (Hung et al., 2021), and shows that ecDNA clustering per se is important but not sufficient to amplify oncogene expression beyond copy-number, reconciling opposite views on the role of clusters (Hung et al., 2021; Zhu et al., 2021; Purshouse et al. 2022). Regulatory contacts become strongly enriched as soon as half a dozen ecDNAs aggregate, then saturate because of steric hindrance, highlighting that even cells with few ecDNAs can experience pathogenic MYC upregulations. To help drug design and therapeutic applications, with the model we dissect the effects of JQ1, a BET inhibitor. We find that JQ1 reverses ecDNA phase separation hence abolishing I-TADs and extra regulatory contacts, explaining how in COLO320-DM cells it reduces MYC transcription (Hung et al., 2021).

molecular biology↗

bioRxiv2021

Loop-extrusion and polymer phase-separation can co-exist at the single-molecule level to shape chromatin folding

Loop-extrusion and phase-separation have been proposed as mechanisms that shape chromosome large-scale spatial organization. It is unclear, however, how they perform relative to each other in explaining chromatin architecture data and whether they compete or co-exist at the single-molecule level. Here, we compare models of polymer physics based on loop-extrusion and phase-separation, as well as models where both mechanisms act simultaneously in a single molecule, against multiplexed FISH data available in human loci in IMR90 and HCT116 cells. We find that the different models recapitulate bulk Hi-C and average microscopy data. Single-molecule chromatin conformations are also well captured, especially by phase-separation based models that better reflect the experimentally reported segregation in globules of the considered genomic loci and their cell-to-cell structural variability. Such a variability is consistent with two main concurrent causes: single-cell epigenetic heterogeneity and an intrinsic thermodynamic conformational degeneracy of folding. Overall, the model combining loop-extrusion and polymer phase-separation provides a very good description of the data, particularly higher-order contacts, showing that the two mechanisms can co-exist in shaping chromatin architecture in single cells.

molecular biology↗

bioRxiv2021

Polymer physics and machine learning reveal a combinatorial code linking chromatin 3D architecture to 1D epigenetics

The mammalian genome has a complex 3D organization, serving vital functional purposes, yet it remains largely unknown how the multitude of specific DNA contacts, e.g., between transcribed and regulatory regions, is orchestrated by chromatin organizers, such as Transcription Factors. Here, we implement a method combining machine learning and polymer physics to infer from only Hi-C data the genomic 1D arrangement of the minimal set of binding sites sufficient to recapitulate, through only physics, 3D contact patterns genome-wide in human and mouse cells. The inferred binding sites are validated by their predictions on how chromatin refolds in a set of duplications at the Sox9 locus against available independent cHi-C data, showing that their different phenotypes originate from distinct enhancer hijackings in their 3D structure. Albeit derived from only Hi-C, our binding sites fall in epigenetic classes that well match chromatin states from epigenetic segmentation studies, such as active, poised and repressed states. However, the inferred binding domains have an overlapping, combinatorial organization along chromosomes, missing in epigenetic segmentations, which is required to explain Hi-C contact specificity with high accuracy. In a reverse approach, the epigenetic profile of binding domains provides a code to derive from only epigenetic marks the DNA binding sites and, hence, the 3D architecture, as validated by successful predictions of Hi-C matrices in an independent set of chromosomes. Overall, our results shed light on how complex 3D architectural information is encrypted in 1D epigenetics via the related, combinatorial arrangement of specific binding sites along the genome.

molecular biology↗

bioRxiv2020

Modeling invasion patterns in the glioblastoma battlefield

Glioblastoma is the most aggressive tumor of the central nervous system, due to its great infiltration capacity. Understanding the mechanisms that regulate the Glioblastoma invasion front is a major challenge with preeminent potential clinical relevance. In the in1ltration front, the key features of its dynamics relate to biochemical and biomechanical aspects, which result in extended cellular protrusions, known as tumor microtubes. The coordination of metalloproteinase expression, extracellular matrix degradation, and integrin activity emerges as leading mechanism that facilitates Glioblastoma expansion and in1ltration in uncontaminated brain regions. We propose a novel multidisciplinary approach, based on in vivo experiments in Drosophila and mathematical models, for the proteins dynamics at the front of Glioblastoma, with a predictive value of the tumor progression.

cancer biology↗

bioRxiv2020

Chromatin folding variability across single-cells results from state degeneracy in phase-separation

Chromosome spatial organization controls functional interactions between genes and regulators, yet the molecular and physical mechanisms underlying folding at the single DNA molecule level remain to be understood. Here we employ models of polymer physics to investigate the conformations of two 2Mb-wide DNA loci in human HCT116 and IMR90 wild-type and cohesin depleted cells. Model predictions on the 3D structure of single-molecules are consistently validated against super-resolution single-cell imaging data, providing evidence that the architecture of the studied loci is controlled by a thermodynamics mechanism of polymer phase separation whereby chromatin self-assembles in segregated globules. The process is driven by interactions between distinct types of cognate binding sites, correlating each with a different combination of chromatin factors, including CTCF, cohesin and histone marks. The intrinsic thermodynamics degeneracy of conformations results in a broad structural and time variability of single-molecules, reflected in their varying TAD-like contact patterns. Globules breathe in time, inducing stochastic unspecific interactions, yet they produce stable, compact environments where specific contacts become highly favored between regions enriched for cognate binding sites, albeit characterized by weak biochemical affinities. Cohesin depletion tends to reverse globule phase separation into a coil, randomly folded state, resulting in much more variable contacts across single-molecules, hence erasing population-averaged patterns. Overall, globule phase separation appears to be a robust, reversible mechanism of chromatin organization, where stochasticity and specificity coexist.

molecular biology↗