Biology subjects

Marchand, M.

Publications and source records attributed to Marchand, M..

10 recordsLinked to original sources

bioRxiv2026

Insights into the genetic architecture of resistance to viral haemorrhagic septicaemia virus in rainbow trout from a genome-wide association study to in vitro CRISPR-Cas9 functional evaluation

Viral haemorrhagic septicaemia (VHS) is a severe disease affecting rainbow trout (Oncorhynchus mykiss) and a wide range of wild freshwater and marine fish species. VHSV threatens rainbow trout aquaculture, as it may cause 100% mortality in fry. Previous studies identified a quantitative trait locus (QTL) on chromosome 3 associated with resistance to VHSV waterborne challenge and reduced viral replication in fin explants, although these findings were obtained using limited genetic diversity. The objective of this study was to validate and extend the identification of genomic regions associated with resistance to VHSV in the genetically diverse rainbow trout line designated "synthetic." A genome-wide association study (GWAS) was conducted using whole-genome sequences from parents of progeny classified as resistant or susceptible to a VHSV waterborne challenge. While the QTL on chromosome 3 was not validated in the synthetic line, four novel suggestive SNPs associated with survival following VHSV waterborne challenge were identified on chromosomes 6, 8, 17, and 32. Notably, one SNP on chromosome 17 was located within a gene potentially involved in antiviral defence, a paralog of lrp1 (low-density lipoprotein receptor-related protein 1). To further investigate its role, lrp1 function was analysed in vitro using CRISPR-Cas9 genome editing. Three independent lrp1-/- CHSE-EC cell lines were generated and challenged with VHSV. The results showed that lrp1 is not essential for viral entry but may modulate the inflammatory response during VHSV infection in epithelial cell lines.

genetics↗

bioRxiv2025

Ultrafast tyrosine-based cell membrane modification via diazonium salts: a new frontier for biomedical applications

In this study, we present an ultrafast, efficient, and broadly applicable strategy for cell membrane modification via tyrosine bioconjugation using diazonium salt derivatives. This chemical approach enables both one-step and two-step functionalization of adherent, suspension, and primary cells with diverse ligands, including imaging probes, carbohydrates, biotin, and proteins, without inducing cytotoxicity or immune activation. Membrane engineering through bioconjugation is emerging as a valuable tool in biomedical research, given the cell membranes central role in signaling, transport, and cell-cell interactions. Compared to traditional glyco-engineering methods that often require multiday incubations and can cause cellular stress, our approach achieves precise and high-density grafting in less than one hour, with improved reproducibility and biological compatibility. Importantly, we demonstrate that this strategy can be applied to a variety of cell types, encompassing both immortalized cell lines and primary cells, notably Peripheral Blood Mononuclear Cells (PBMCs) and human effector cells such as natural killer (NK) cells, to enhance their cytotoxic function against EGFR-positive cancer cells via surface-conjugated Nanofitin. Moreover, we show that the bioconjugated signal diminishes over time due to cell division, offering a self-limiting alternative to permanent genetic modifications such as CAR-T, thereby mitigating risks associated with overly prolonged immune activation. Finally, the feasibility of storing pre-functionalized cells at -80 {degrees}C expands the practicality of this platform for future ready-to-use applications. Together, these features make our method a compelling alternative to current technologies for applications in targeted therapy, diagnostics, and cell-based immunotherapy.

bioengineering↗

bioRxiv2025

Scaffolded hiPSC liver organoids recapitulating bile duct tubulogenesis and periportal architecture.

Recapitulating the liver periportal area in vitro remains a major challenge due to its complex cellular composition and the coordinated development of both ductal and endothelial networks. Most existing bile duct organoid models fail to reproduce tubular extension and multicellular organization. We present a 3D ECM micro-rods system biofunctionalized with grafted growth factors mimicking fetal liver paracrine signaling to initiate and to coordinate the development of bile ducts, parenchymal cells, and vascular structures. Our system recapitulates key developmental stages, from the formation of the ductal plate to the emergence of elongated tubular ducts. The ECM rod alone provides the biophysical cues initiating the elongation of the bile ducts and the spatial structuration of the cellular organization, while the biofunctionalization with growth factors enhance the organization and maturation of the biliary and vascular systems. We further demonstrate that this approach is scalable and amenable to quantitative analysis through label-free Optical Coherence Tomography combined with AI-driven 3D segmentation.

cell biology↗

bioRxiv2025

Strategic Conservation Prioritization Through Creating and Updating the Regional Species of Greatest Conservation Need (RSGCN) List in the Northeastern U.S.

Through the end of the century, biodiversity is expected to markedly decline around the world due to climate change, habitat loss, and other factors. Because of this, there is an increasing need for more efficient, effective, and collaborative conservation efforts worldwide. While many global and national threat assessment databases exist, they may only have limited utility at regional and local scales where on-the-ground conservation is best implemented. To better identify species risk at a more regional scale, the 14 state fish and wildlife agencies in the northeastern United States worked with taxonomic experts across the Northeast to create the most recent (2023) list of Regional Species of Greatest Conservation Need (RSGCN). We compared a preliminary list compiled from global and national datasets to the finalized list after the process documented here. We found that the global and national datasets only identified [~]55% of the 806 species statuses accurately for the region, demonstrating the importance of current local and regional expertise and data. The process of identifying RSGCN for the northeastern U.S. has resulted in specific actionable information leading to beneficial outcomes, such as dedicated funding for regional initiatives, data-sharing, and coordination among regional, state, and local conservation organizations - enabling beneficial conservation outcomes across the region for many of the species and habitats of the region. The methods described may serve as a framework for other regions to help identify conservation targets using the best available and more localized landscape- and watershed-scale information.

ecology↗

bioRxiv2024

Recent climate change strongly impacted the population dynamic of a North American insect pest species

Climate change is redefining the dynamics of forest ecosystems globally, particularly through its impact on forest pest populations such as the spruce budworm (SBW, Choristoneura fumiferana [Clem.]), a major defoliator in North American boreal forests. This study investigates the shifts in the population dynamics of spruce budworm across its range in response to recent climate change. We used a process-based, temperature-dependent ecophysiological model combined with the ERA5 reanalysis to assess changes in SBW phenology, reproduction rate, winter survival and population growth rates from 1950 to 2022 across North America. Our findings demonstrate a pronounced northward expansion of suitable climate conditions for SBW, accompanied by earlier phenological events and increased reproduction rates in northern regions. Conversely, the southern parts of its range are experiencing increased winter mortality due to warmer temperatures. This study highlights the significant impact of elevated temperatures, particularly during critical developmental windows such as spring and summer, which are pivotal for spruce budworm survival and reproduction. Additionally, our results reveal that the observed shifts in pest dynamics are more strongly driven by climate change than by changes in landscape composition and structure. We estimated that suitable growth rates have shifted northward by over 68 km on average, but this shift reached more than 200 km in the easternmost portions of its range. Climate-induced shift in suitable conditions for SBW underscores the need for adaptive forest management strategies that consider the rapid ecological changes and the potential for increased forest vulnerability due to climatic and biotic stressors. This study provides vital insights that can inform adaptive management ensuring the sustainability of forest ecosystems in the face of ongoing climate change.

ecology↗

bioRxiv2024

Advancing Liver Gene Therapy: Enhanced Transduction with GalNAc-Bioconjugated rAAV Capsids

This study investigates novel approaches to improve targeted gene delivery to the liver, a crucial organ for metabolic processes that faces vulnerabilities from various pathologies. Adeno-associated virus (AAV)-based gene therapy has emerged as a promising approach for liver targeting, with numerous investigational avenues. However, administration of high doses of AAV vectors present safety concerns, often requiring the use of corticosteroids and immunosuppression to mitigate immune adverse events. To address this, substantial efforts are underway to engineer optimized capsids to enhance the efficiency and specificity of recombinant AAV (rAAV) targeting hepatocytes, aiming to reduce required dosages. In this study, we employed bioconjugation chemistry to target the Asialoglycoprotein receptor (ASGPR), a C-type lectin abundantly expressed at the surface of hepatocyte membranes. We demonstrated that covalently attaching carbohydrates derived from GalNAc (a known ASGPR ligand) to lysine amino-acids on the rAAV2 capsid significantly enhanced in vivo liver transduction efficiency in mice. These optimized vectors present a promising avenue for the treatment of a spectrum of liver diseases, providing an alternative solution within the framework of liver gene therapy.

bioengineering↗

bioRxiv2023

High carbohydrate to protein ratio promotes changes in intestinal microbiota and host metabolism in rainbow trout (Oncorhynchus mykiss) fed plant-based diet.

To ensure the sustainability of aquaculture, it is necessary to change the "menu" of carnivorous fish such as rainbow trout from a fish-based diet to one with plant-based ingredients. However, there is a major problem with the growth performance decrease of fish fed with a 100% plant-based diet due to the reduction in feed intake and feed efficiency. For the first time, we incorporated high levels of digestible carbohydrates (high-starch diet) in a 100% plant-based diet during a 12-week feeding trial in order to improve protein utilization for growth (protein sparing effect) and reduce nitrogen waste. We measured the changes in the intestinal microbiota, Short-Chain Fatty Acid (SCFA) levels and metabolic responses in liver. Dietary carbohydrates had a strong effect on alpha and beta diversity and abundance of 12 genera, including Ralstonia and Bacillus in digesta associated microbiota whereas mucosa associated microbiota was less affected. The change in microbial diversity might be linked to the change observed in SCFA production. High levels of Mycoplasma were observed in the intestinal mucosa. Overall, hepatic gene expression was significantly altered by the CHO/protein ratio. Up-regulation of genes involved in glucose metabolism (gcka, gckb, g6pcb2a), down-regulation of genes involved in lipid metabolism (hadh, acox3, srebp2a, and cyp51a) were associated with higher enzymatic activities (such as glucokinase or pyruvate kinase) and higher glycogen levels in the liver, suggesting adequate adaptation to diet. Interestingly, strong correlations were observed between abundances of certain bacterial OTUs and gene expression in the liver. The inclusion of digestible carbohydrates in combination with a 100% plant-based diet, could be a promising way to improve and reduce the use of plant proteins in rainbow trout. In addition, the relationship between intestinal microbiota and host metabolism needs further investigation to better understand fish nutrition.

molecular biology↗

bioRxiv2022

Ants dynamically adjust liquid foraging strategies in response to biophysical constraints

Ant foragers need to provide food to the rest of the colony, which often requires transport over long distances. Foraging for liquid is especially challenging because it is difficult to transport and share. Many social insects store liquid food inside the crop to transport it to the nest, and then regurgitate this fluid to distribute it to nestmates through a behaviour called trophallaxis. Some ants instead transport fluids with a riskier behaviour called pseudotrophallaxis - holding a drop of liquid between the mandibles through surface tension. Ants can then share this droplet with nestmates without ingestion or regurgitation. Here, we hypothesised that ants optimise their liquid-collection approach depending on viscosity. Working with a ponerine ant that uses both trophallaxis and pseudotrophallaxis, we investigated why each liquid-collection behaviour might be favoured under different conditions by measuring biophysical properties, collection time, and reaction to food quality for typical and viscosity-altered sucrose solutions. We found that ants can collect more liquid food per unit time by mandibular grabbing than by drinking. At high viscosities, which in nature correspond to high sugar concentrations, ants switched their liquid collection method to mandibular grabbing in response to viscosity, and not to sweetness. Our results demonstrate that ants change their transport and sharing methods according to viscosity - a proxy for sugar concentration in nature - increasing the mass of sugar returned to the nest per trip.

animal behavior and cognition↗

bioRxiv2018

Interpretable genotype-to-phenotype classifiers with performance guarantees

Understanding the relationship between the genome of a cell and its phenotype is a central problem in precision medicine. Nonetheless, genotype-to-phenotype prediction comes with great challenges for machine learning algorithms that limit their use in this setting. The high dimensionality of the data tends to hinder generalization and challenges the scalability of most learning algorithms. Additionally, most algorithms produce models that are complex and difficult to interpret. We alleviate these limitations by proposing strong performance guarantees, based on sample compression theory, for rule-based learning algorithms that produce highly interpretable models. We show that these guarantees can be leveraged to accelerate learning and improve model interpretability. Our approach is validated through an application to the genomic prediction of antimicrobial resistance, an important public health concern. Highly accurate models were obtained for 12 species and 56 antibiotics, and their interpretation revealed known resistance mechanisms, as well as some potentially new ones. An open-source disk-based implementation that is both memory and computationally efficient is provided with this work. The implementation is turnkey, requires no prior knowledge of machine learning, and is complemented by comprehensive tutorials.

genomics↗

bioRxiv2018

Mass Spectra alignment using virtual lock-masses

Mass spectrometry is a valued method to evaluate the metabolomics content of a biological sample. The recent advent of rapid ionization technologies such as Laser Diode Thermal Desorption (LDTD) and Direct Analysis in Real Time (DART) has rendered high-throughput mass spectrometry possible. It is used for large-scale comparative analysis of populations of samples. In practice, many factors resulting from the environment, the protocol, and even the instrument itself, can lead to minor discrepancies between spectra, rendering automated comparative analysis difficult. In this work, a sequence/pipeline of algorithms to correct variations between spectra is proposed. The algorithms correct multiple spectra by identifying peaks that are common to all and, from those, computes a spectrum-specific correction. We show that these algorithms increase comparability within large datasets of spectra, facilitating comparative analysis, such as machine learning.

bioinformatics↗