Biology subjects

Gerard, M.

Publications and source records attributed to Gerard, M..

10 recordsLinked to original sources

bioRxiv2026

Toolbox for fluorescent labelling of Pseudomonas aeruginosa across scales: from single cells to bacterial communities and host infection models

Fluorescence microscopy is central to the study of bacterial cell biology, multicellular behaviours, and host-pathogen interactions. Bright, robust and photostable labelling is required for bacterial identification, sorting and quantitative analysis, driving continuous development of state-of-the-art labelling tools. Here, we developed a multicolor fluorescent cell labelling toolkit for Gram-negative bacteria carrying the attTn7 site, using the opportunistic human pathogen Pseudomonas aeruginosa as a model. Cell labelling is achieved by constitutive chromosomal expression of genes encoding a choice of four novel fluorescent proteins, mNeonGreen, mJuniper, mLychee and mScarlet-I3, codon-optimised for P. aeruginosa. These reporters provide bright, stable fluorescence with minimal photobleaching and excellent spectral separation during long-term imaging of single cells, macrocolonies and biofilms. Chromosomal expression of mNeonGreen yielded brighter and more homogeneous labelling than expression of the same construct from a plasmid. Importantly, dual-color labelling of macrocolonies uncovered previously unrecognised phenomena of collective motility when two isogenic swarming populations interact. Finally, we demonstrate the applicability of our constructs in biologically relevant host-pathogen contexts by imaging both live and fixed P. aeruginosa-infected human airway epithelial cells. This versatile cell labelling platform enables reliable bacterial identification, segmentation, tracking, and quantitative fluorescence imaging across spatial and temporal scales, and is readily adaptable to most other Gram-negative bacteria as the attTn7 integration site is well conserved.

microbiology↗

bioRxiv2026

MreB is dispensable for viability but critical for rod shape, motility and biofilm fitness in Pseudomonas aeruginosa

Despite growing interest in the MreBCD morphogenetic complex as a potential antimicrobial target, its function in Pseudomonas aeruginosa remains poorly understood. While previous studies using the MreB inhibitor A22 have established its role in cell shape maintenance and pilus regulation, the impact of mreB deletion has not been comprehensively investigated. Using genetic and microscopy-based approaches, we show that deletion of mreB is viable in P. aeruginosa, but results in spherical cells that lose all forms of motility despite retaining flagella. Importantly, we uncover a previously overlooked polar effect of the in-frame mreB deletion on the downstream mreCD genes and show, using CRISPRi-mediated silencing, that mreCD expression is essential for viability.{Delta} mreB mutants also display increased sensitivity to {beta}-lactam antibiotics and enhanced initial surface attachment, yet form more compact biofilms with reduced dispersal. In mixed-culture biofilms, spherical{Delta} mreB cells are outcompeted by rod-shaped wild-type cells and remain confined to the biofilm base. The identification of natural P. aeruginosa isolates carrying truncated mreB alleles further indicates that loss of MreB function can be tolerated in natural populations. Together, our findings reveal important contributions of the MreBCD system to viability, morphogenesis, motility and biofilm development in P. aeruginosa, providing new insights into bacterial adaptation and informing the development of targeted antimicrobial strategies.

microbiology↗

bioRxiv2026

Homology-aware cross-validation strategies for generalization assessment in RNA structure prediction

RNA secondary structure prediction is a fundamental challenge in bioinformatics, essential for understanding the functional roles of non-coding RNAs. Recently, deep learning models have transformed the field with impressive results, leading to critical discussions regarding the validity of current cross-validation strategies. On the one hand, traditional random partitioning yields overoptimistic results due to data leakage from uncontrolled homology. On the other hand, removing from the training set all sequences that exhibit even the slightest resemblance to the testing sequences penalizes learning-based methods by requiring generalization to completely out-of-distribution sequences. While it is very simple to remove sequences and retrain a machine learned model, it is very difficult to remove the experimental data used for parameter tuning and the sequences used for the development of classical thermodynamic methods. Thus, these methods often benefit from an implicit knowledge leakage. In this work we critically review existing cross-validation strategies for RNA secondary structure prediction: random splitting, clustering-based splitting, and leaving one RNA family out for testing. We analyze the advantages and limitations of each strategy, also expanding them towards the future directions to ensure fair comparisons across the full range of sequence similarities, with the same rigor for both classical and learning-based methods. Data and source code are available at https://github.com/sinc-lab/xvalRNAfolding

bioinformatics↗

bioRxiv2025

Evidence for an ancient master sex determination gene in Hymenoptera

The vast majority of Hymenopterans determine sex by haplodiploidy, in which males and females develop from haploid unfertilized and diploid fertilized eggs, respectively. At the molecular level, the majority of Hymenoptera are thought to determine sex by so-called Complementary Sex Determination (CSD). Under CSD, sex is determined by the feminizing effects of one or more allele-rich loci, in which the feminizing function is imparted by the interactions of functionally distinct alleles. Because of high allelic diversity, most diploids are heterozygous and develop as females, whereas haploid individuals develop as males, as do rare homozygous diploids. Despite diverse empirical results suggesting that CSD is widespread in Hymenopterans, and substantial theoretical and empirical study of the consequences of CSD, the molecular biology of CSD has received little attention outside of the honeybee, Apis mellifera. Available evidence provides support for divergent perspectives ranging from a single (nearly) universally-conserved CSD locus or a pattern dominated by evolutionary turnover with different genes serving as the CSD gene(s) in different lineages. Recently, a novel non-coding RNA gene named ANTSR was shown to serve as a CSD gene in different ant lineages, and the authors suggested that ANTSR might serve as a more broadly-conserved CSD gene. To assess the role of ANTSR role in CSD across diverse Hymenoptera, we studied syntenic conservation and polymorphism patterns in the broad ANTSR locus, genome-wide sequence from available male and female diploid Formica ants, and data from a sibling cross for Bombus terrestris. We find evidence that ANTSR is a conserved CSD gene across diverse Aculeata, the largest group of Hymenoptera, and provide preliminary evidence that Formica may have multiple CSD loci including ANTSR.

genetics↗

bioRxiv2025

Association Between Vaginal Community States and Preeclampsia Status in Pregnant Individuals

Preeclampsia (PE) is a severe pregnancy complication affecting 3-8% of pregnancies. Recent evidence suggests the vaginal microbiome may influence PE risk. To investigate this, we reanalyzed publicly available 16S rRNA sequencing data (PRJNA798597) from vaginal samples of pregnant women with (n=10) and without PE (n=10) and assigned vaginal community state types which were previously uncharacterized. Overall microbial diversity did not differ significantly between groups; however, subtype differences in Lactobacillus spp. were observed. D-lactic acid-producing vaginal community state types were less common in PE, suggesting potential value for microbiome-based risk assessment.

microbiology↗

bioRxiv2024

The Arabidopsis RS2Z32 and RS2Z33 proteins are dynamic splicing factors whose RNA recognition motif (RRM) domain contributes to protein-protein and protein-RNA interactions

The Arabidopsis splicing factors arginine/serine-rich zinc knuckle-containing proteins 32 and 33 (RS2Z32 and RS2Z33) are plant-specific members of the SR family whose molecular functions received little attention. Here, we characterized both RS2Z32 and RS2Z33 by examining their expression profile at different stages of development and their spatial cellular distribution, as well as the contribution of their domains in the establishment of protein-protein interactions and RNA binding specificity. We report that the RS2Z32 and RS2Z33 promoters are ubiquitously active during vegetative and reproductive growth, and that both RS2Z splicing factors localize in the nucleus (except the nucleolus). We show that the C-terminal arginine/serine-rich (RS) domain, but not the serine/proline-rich (SP) extension, is a determinant of nuclear localization, which likely requires phosphoresidues putatively phosphorylated by kinases of the SRPK family. We demonstrate that their RNA recognition motif (RRM) domain specifically binds pyrimidine-rich RNA motifs via three residues (Y14, Y46, F48), and is also involved in protein-protein interactions with at least three SR proteins, namely SR45, SCL30, and SR34. Finally, we show that mutations in RNA-binding domains (i.e. RRM and zinc knuckles, ZnKs) affect the nucleocytoplasmic dynamics of both RS2Z proteins. Our findings provide molecular evidence for the involvement of plant-specific SR splicing factors into the regulation of the splicing process. HighlightSpecific domains of the Arabidopsis RS2Z splicing factors contribute to their nuclear localization, nucleocytoplasmic dynamics, and ability to contact protein partners and specific pyrimidine-rich RNA motifs.

plant biology↗

bioRxiv2023

sincFold: end-to-end learning of short- and long-range interactions for RNA folding

MotivationCoding and non-coding RNA molecules participate in many important biological processes. Non-coding RNAs fold into well-defined secondary structures to exert their functions. However, the computational prediction of the secondary structure from a raw RNA sequence is a long-standing unsolved problem, which after decades of almost unchanged performance has now re-emerged thanks to deep learning. Traditional RNA secondary structure prediction algorithms have been mostly based on thermodynamic models and dynamic programming for free energy minimization. More recently deep learning methods have shown competitive performance compared with the classical ones, but still leaving a wide margin for improvement. ResultsIn this work we present sincFold an end-to-end deep learning approach that predicts the nucleotides contact matrix using only the RNA sequence as input. The model is based on 1D and 2D residual neural networks that can learn short- and long-range interaction patterns. We show that structures can be accurately predicted with minimal physical assumptions. Extensive experiments were conducted on several benchmark datasets, considering sequence homology and cross-family validation. sincFold was compared against classical methods and recent deep learning models, showing that it can outperform state-of-the-art methods. AvailabilityThe source code is available at https://github.com/sinc-lab/sincFold (v0.16) and the web access is provided at https://sinc.unl.edu.ar/web-demo/sincFold Contactlbugnon@sinc.unl.edu.ar

bioinformatics↗

bioRxiv2022

Oct4 interacts with subnucleosomal particles generated by Brg1 at enhancers

BRG1, the catalytic subunit of the mammalian SWI/SNF complexes, is essential for chromatin opening at enhancers. However, the nature of the open chromatin remains unclear. Here we show that in addition to producing histone-free DNA, BRG1 generates hemisome-like subnucleosomal particles containing the four core histones associated with 50-80 base pairs of DNA. Our genome-wide analysis indicates that BRG1 makes these particles by targeting and splitting fragile nucleosomes. In mouse embryonic stem cells, these subnucleosomes become an in vivo binding substrate for the master transcription factor OCT4 independently of the presence of OCT4 DNA motifs. At enhancers, the OCT4-subnucleosome interaction increases OCT4 occupancy and amplifies the genomic interval bound by OCT4 by up to one order of magnitude, compared to the region occupied on histone-free DNA. We suggest that BRG1-dependent subnucleosomes orchestrate an epigenetic mechanism that projects OCT4 function in chromatin opening beyond its DNA motifs.

genomics↗

bioRxiv2022

Dimeric G-quadruplex motifs determine a large fraction of strong replication origins in vertebrates

Replication of vertebrate genomes is tightly regulated to ensure accurate duplication, but our understanding of the interplay between genetic and epigenetic factors in this regulation remains incomplete. Here, we investigated the involvement of three elements enriched at gene promoters and replication origins: guanine-rich motifs potentially forming G-quadruplexes (pG4s), nucleosome-free regions (NFRs), and the histone variant H2A.Z, in the firing of origins of replication in vertebrates. We show that two pG4s on the same DNA strand (dimeric pG4s) are sufficient to induce assembly of an efficient minimal replication origin without inducing transcription. Dimeric pG4s in replication origins trigger formation of an NFR next to precisely-positioned nucleosomes enriched in H2A.Z on this minimal origin and genome-wide. Thus, our data suggest a crucial role for dimeric pG4s in the organization and duplication of vertebrate genomes. It supports the hypothesis that a nucleosome close to an NFR is a shared signal for the formation of replication origins in eukaryotes.

genomics↗

bioRxiv2018

Leaf economics guides slow-fast adaptation across the geographic range of A. thaliana

The slow-fast continuum describes how resource allocation constrains life-history strategies in many organisms. In plants, it is reflected by a trade-off at the leaf level between the rate of carbon assimilation and lifespan, the so-called Leaf Economics Spectrum (LES). However, it is still unclear how the LES is connected to the slow-fast syndrome, and reflects adaptation to climate. Here, we measured growth, morpho-physiological and life-history traits at both leaf and whole-plant levels in 384 natural accessions of Arabidopsis thaliana. We examined the extent to which the LES continuum parallels the slow-fast continuum, and compared trait variation to neutral genetic differentiation between lineages. We found that the LES is tightly linked to variation in whole-plant functioning, relative growth rate and life history. A genetic analysis further suggested that phenotypic differentiation is linked to the evolution of different slow-fast strategies in contrasted climates. Together, our findings shed light on the physiological bases of the slow-fast continuum, and its role for plant adaptation to climate.

ecology↗