Biology subjects

Bou About, G.

Publications and source records attributed to Bou About, G..

3 recordsLinked to original sources

bioRxiv2025

Establishing Comprehensive Transthoracic Echocardiography Reference Ranges for Mouse Models: Insights into the Impact of Anesthesia, Sex, and Age

Mouse models play a critical role in cardiology research, offering valuable insights into the molecular mechanisms, genetics, and potential treatments for cardiovascular diseases. However, the ability to transfer findings in mice between studies is limited by the absence of standardized protocols and valid reference values for the assessment of normal cardiac function in mice. This study aims to establish comprehensive transthoracic echocardiography (TTE) reference ranges for mice, particularly focusing on C57BL/6N wildtype controls. The study, which includes data from over 15,000 mice through the International Mouse Phenotyping Consortium (IMPC), highlights how variables such as sex, age, body weight, and anesthesia affect TTE parameters. The findings showed that anesthesia is the primary predictor of variability in cardiac function. Isoflurane and tribromoethanol anesthetized mice presented with modified cardiac function compared to conscious mice. Additionally, we observed minimal sex differences in cardiac morphology and function, except for small variations influenced by anesthesia. The effects of aging on cardiac function were modest, characterized by a decrease in heart rate and subtle changes in ventricular dimensions without evidence of pathological remodeling, likely attributable to disease-free cardiovascular aging. Validation of the reference ranges across multiple mouse strains showed that these values provide a reliable baseline for experiments involving cardiac function in mice. The data underscore the importance of using anesthesia-specific reference values when interpreting TTE results, ensuring robust comparisons in genetic and pharmacological studies. These reference ranges serve as quality assurance tools for future cardiac studies in mice, offering insights into typical TTE parameter values, supporting the detection of experimental perturbations, and contributing to more effective translation of findings from mouse to human.

genetics↗

bioRxiv2021

Isolation, omics characterization and organotypic culture of alveolar type II pulmonary epithelial cells

The alveolar type II (AT2) epithelial cell fraction includes the stem cells of the pulmonary alveoli, functioning in lung homeostasis and post-injury repair. AT2 cells have been characterized primarily in situ, in transgenic mouse models. We report a new methodology for their isolation, their "omics" characterization and stroma-cell-free organotypic culture. Our multi-omics analysis identified high expression of genes involved in oxidative phosphorylation and of AP-1 components, as well as new phosphorylation sites in AT2 biomarkers. Furthermore, we show that supplementation with KGF, FGF10 & HGF suffices for the in vitro proliferation of AT2 cells and formation of alveolar organoids, suggesting that AT2-based organotypic development depends on ligands of the c-Met and FGFR2 receptors. The reported methodology and in-depth molecular characterization provide new tools for the in vitro and in vivo functional analysis of pulmonary cells and of mouse models of lung disease.

cell biology↗

bioRxiv2019

Soft Windowing Application to Improve Analysis of High-throughput Phenotyping Data

MotivationHigh-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximises analytic power while minimising noise from unspecified environmental factors.\n\nResultsHere we introduce \"soft windowing\", a methodological approach that selects a window of time that includes the most appropriate controls for analysis. Using phenotype data from the International Mouse Phenotyping Consortium (IMPC), adaptive windows were applied such that control data collected proximally to mutants were assigned the maximal weight, while data collected earlier or later had less weight. We applied this method to IMPC data and compared the results with those obtained from a standard non-windowed approach. Validation was performed using a resampling approach in which we demonstrate a 10% reduction of false positives from 2.5 million analyses. We applied the method to our production analysis pipeline that establishes genotype-phenotype associations by comparing mutant versus control data. We report an increase of 30% in significant p-values, as well as linkage to 106 versus 99 disease models via phenotype overlap with the soft windowed and non-windowed approaches, respectively, from a set of 2,082 mutant mouse lines. Our method is generalisable and can benefit large-scale human phenomic projects such as the UK Biobank and the All of Us resources.\n\nAvailability and ImplementationThe method is freely available in the R package SmoothWin, available on CRAN http://CRAN.R-project.org/package=SmoothWin.

bioinformatics↗