Biology subjects

Martel, S.

Publications and source records attributed to Martel, S..

5 recordsLinked to original sources

bioRxiv2026

A comprehensive genetic study of the vaginal microbiota composition of Holstein cows

The vaginal microbiota is a potentially important component of the bovine reproductive tract and has been associated with fertility, health, and production-related traits in cattle. However, the impact of host genetics on the bovine vaginal microbiota and its genetic correlations with animal performance remain largely unexplored. To investigate this, we performed a comprehensive genetic study of the vaginal microbiota in Holstein cows. Vaginal swabs from 681 lactating cows across 18 herds in Northern France were collected, along with records of fertility, milk production, and health traits. The microbiota samples were sequenced for the 16S rRNA gene, generating count tables of amplicon sequence variants (ASV). We estimated genetic parameters for vaginal microbiota -diversity (Chao1, Shannon, and Simpson indices) and {beta}-diversity (Bray-Curtis dissimilarity matrix), as well as the centered log-ratio (CLR)-transformed abundances of taxa present in more than 50% of samples. Across the 173 analyzed taxa, heritability estimates ranged from low to moderate (h2 = 0.09 to 0.38) for five genera, three families, eight orders, three classes, and one phylum. Notably, the order Flavobacteriales exhibited the highest heritability estimate. The study also highlighted genetic correlations between heritable microbiota traits and host phenotypes related to fertility, production, and health. Sequence-based genome-wide association studies (GWAS) identified biologically relevant signals, including a quantitative trait locus (QTL) for the genus Alloprevotella on chromosome 6, with lead variants located within the NAF1 gene. Additionally, two signals on chromosome 17 for the Bacteroidales order and the Bacteroida class co-localized with IL15. Our findings show that host genetics contributes to variation in specific components of the bovine vaginal microbiota and suggest that microbiome-related traits may warrant further investigation as potential indicators in dairy cattle breeding and management research.

genetics↗

bioRxiv2025

The RUMIGEN EpiChip: a versatile, medium density DNA methylation Beadchip for large scale population studies in cattle

BackgroundDNA methylation contributes to the elaboration of phenotypes and is hypothesized to account for interindividual variations in farm animals. Currently, methodologies available to investigate DNA methylation in cattle rely on high throughput sequencing, which cannot be applied to large cohorts. To enable large scale DNA methylation analysis, we developed the RUMIGEN EpiChip, the first DNA methylation array specifically designed for cattle. ResultsManufactured by Illumina, the EpiChip contains 43,317 CpG markers allowing analysis of phenotypes of agronomical interest as well as the study of regulatory processes. The assay design drew on data from numerous studies achieved by the scientific community, and includes CpGs where methylation varies with health status, physiological stage, fertility, and environmental challenges, as well as CpGs located in functional genomic elements (promoters, CTCF binding sites, expression quantitative trait loci). The technical performances of the EpiChip were tested on several semen and blood DNA samples and in two laboratories, showing excellent repeatability, accuracy and interoperability. Methylation values were also concordant with those obtained by reduced representation bisulfite sequencing. The EpiChip has demonstrated a good ability to explore biological processes such as genomic imprinting and differences between cell types, opening the possibility of inferring blood cell composition. Finally, analysis of longitudinal ear biopsies allowed accurate age prediction, suggesting the potential of the array to refine epigenetic clocks. ConclusionsThe RUMIGEN EpiChip is a cost-effective and versatile resource that opens new opportunities for the study of regulatory mechanisms underlying phenotypic variation and for large-scale association analyses in cattle.

genomics↗

bioRxiv2023

Characterization of bovine vaginal microbiota and its relationship with host fertility, health, and production

BackgroundBecause of its potential influence on the hosts phenotype, increasing attention is paid to organ-specific microbiota in several animal species, including cattle. However, ecosystems other than those related to the digestive tract remain largely understudied. In particular, little is known about the vaginal microbiota of ruminants despite the importance of the reproductive functions of cows in a livestock context, where fertility disorders represent one of the primary reasons for culling. ResultsIn the present study, we aimed at better characterizing the vaginal microbiota of dairy cows through 16S rRNA sequencing, using a large cohort of Holstein cows from Northern France. Our results allowed to define a core microbiota of the dairy cows vagina, and highlighted that 90% of the sequences belonged to the Firmicutes, the Proteobacteria, and the Bacteroidetes phyla. The core microbiota was composed of four phyla, 16 families, 14 genera and only one amplicon sequence variant (ASV), supporting the idea of the high diversity of vaginal microbiota within the studied population. This variability was partly explained by various environmental factors such as the herd, the sampling season, the lactation rank and the lactation stage. In addition, we investigated potential associations between the diversity and the composition of the vaginal microbiota and several health-, performance-, and fertility-related phenotypes. Our analyses highlighted significant associations between the and {beta}- diversities and several traits including the first insemination outcome, the productive longevity, and the culling. Besides, relevant phenotypes were correlated with the abundance of several genera, some of which, such as Leptotrichia, Streptobacillus, Methylobacterium-Methylorubrum, or Negativibacillus, were linked to multiple traits. ConclusionConsidering the large number of samples, which were collected in commercial farms, and the diversity of the phenotypes considered, this study represents a first step towards a better understanding of the close relationship between the vaginal and the dairy cows phenotypes.

microbiology↗

bioRxiv2022

Toxicology assessment of manganese oxide nanomaterials with enhanced electrochemical properties using human in vitro models representing different exposure routes

In the present study, a comparative human toxicity assessment between newly developed Mn3O4 nanoparticles with enhanced electrochemical properties (GNA35) and their precursor material (Mn3O4) was performed, employing different in vitro cellular models representing alveolar, oral and dermal exposure routes, namely the human alveolar carcinoma epithelial cell line (A549), the human colorectal adenocarcinoma cell line (HT29), and the reconstructed 3D human epidermal model EpiDerm (RhE). The obtained results showed that Mn3O4 and GNA35 harbour similar morphological characteristics, while differences were observed in relation to their thermal stability and electrochemical properties. In regard to their toxicological properties, both nanomaterials induced oxidative stress in the A549 and HT29 cell lines that have demonstrated that manganese oxide nanoparticles reduce the cell viability in A549 cells while they do not produce any negative effect on that of HT29 cells. On the other hand, it was observed that Mn3O4 and GNA35 induce oxidative stress in both cell lines. Finally, it was noticed that none of the nanoparticles caused a reduction of the viability on the skin tissue so that they could not be classified as irritants. Our findings demonstrate that the evaluation of the toxicity of nanoparticles using different models is a critical aspect to increase the knowledge on their potential impact on human health.

cell biology↗

bioRxiv2022

Machine learning-based detection of label-free cancer stem-like cell fate

Most imaging methods rely on labelling biological samples in order to provide specific and easily detectable features. However, label-free imaging is a non-invasive and non-toxic alternative that requires accurate image analysis algorithm based on cell morphology. Such analysis has to deal with a high image variability while fewer features are extractable, so far, fast analysis of label-free brightfield microscopy (LFBM) images remains a challenging task. With the development of microfabricated devices during the last decades, high throughput image generation makes it possible to use machine learning-based algorithms in order to analyse LFBM images. Fast algorithms are also crucially needed to analyze high throughput experiments. In this paper, we provide a data-driven study in order to assess the complexity of LFBM time-lapses monitoring isolated cancer stem-like cells (CSCs) fate in non-adherent conditions. We combined for the first time individual cell fate and cell state temporality analysis in a unique algorithm. Several image analysis algorithms of increasing processing capacities were tested: a classical computer vision algorithm (CCVA), a shallow learning-based algorithm (SLBA) and a deep learning-based algorithm (DLBA). We show that our optimized DLBA has by far the best accuracy compared to CCVA and SLBA, is at least as accurate as other state-of-the-art DLBAs while being faster. With this study, we demonstrate that optimizing our DLBA accordingly to the image analysis problem can overall provide better results than pretrained models. Such a fast and accurate DLBA is therefore compatible with the generation of high throughput data and opens the route for on-the-fly analysis of CSC fate from LFBM time-lapses.

bioinformatics↗