bioRxiv Science⌕ Search

Biology subjects

Maillot, A.

Publications and source records attributed to Maillot, A..

2 recordsLinked to original sources

Fluid transport properties dominate blastocyst expansion over mechanics

Lumens populate most of our organs and their size, which dynamically changes throughout the day and lifetime, can influence their function. During mammalian development, the first lumen appears in the blastocyst. Surface epithelial cells pump ions to build an osmotic gradient that draws water, which inflates the embryo and stretches the epithelium as well as the zona pellucida, an elastic shell protecting the embryo. Blastocyst expansion is not steady and instead undergoes cycles of expansion interrupted by collapses during which the lumen leaks out. Early studies identified the critical role of osmotic pressure difference in regulating the expansion of the blastocyst whereas recent studies proposed that mechanical stresses would set the size of the embryo. However, the relative contributions of osmotic and mechanical stresses to lumen expansion dynamics remain unclear. Here, we investigate this using microfluidics, biophysics, machine learning and modelling on mouse embryos. Breaking down the expansion dynamics of mouse embryos, we discovered that fluid pumping rate accelerates, compensating for the increased frequency of collapses interrupting episodes of expansion. We reasoned that fluid transport could be rate limited by osmotic pumping, water permeability and/or mechanical constraints. Removing the mechanical constraint from the zona pellucida only marginally affected these expansion dynamics. Forcing fluid exchange with osmotic shocks we measured that water permeability is large enough not to restrict fluid accumulation rates. Finally, we estimate ion pumping for mouse blastocysts and interfere with it using inhibitors to measure how it quantitatively sets blastocyst expansion rates. Together, we propose that osmotic pressure differences, regulated by fluid transport properties, dominate over mechanical stresses in controlling blastocyst expansion dynamics.

developmental biology↗

Transcriptomic analysis of chronic chikungunya in the Reunionese CHIKGene cohort uncovers a shift in gene expression more than 10 years after infection

AimIn 2005-2006, a chikungunya epidemic of unprecedented magnitude hit Reunion Island, which raised a public health concern through the substantial proportions of long-lasting manifestations. To understand the pathophysiology underlying chronic chikungunya (CC), we designed the CHIKGene cohort study and collected blood samples from 133 subjects diagnosed with CC and from 86 control individuals that had recovered within 3 months, 12-to-15 years after exposure. MethodsWe conducted bulk RNAseq analysis on peripheral blood mononuclear cells to find differentially expressed genes (DEGs), gene set enrichment analysis (GSEA) and gene ontologies to uncover top-level enriched terms associated with DEGs, and weighted gene correlation network analysis (WGCNA) to elucidate underlying cellular processes. ResultsAmong 1549 DEGs, gene expression analysis identified 10 top genes including NR4A2 and TRIM58 (upregulated in CC), IGHG3 and IGHV3-49 (downregulated in CC) linked to immune regulation, OSBP2 (upregulated in CC) and SEMA6B (downregulated in CC) linked to neuronal homeostasis and axon guidance, respectively. GSEA and WGCNA unveiled cellular processes such as "Metabolism of RNA" and "Cell Cycle". ConclusionsThis study uncovers a shift in gene expression of CC subjects. IGHG3 and IGHV3-49 gene shut-offs spotlight the importance of neutralizing antibodies against chikungunya virus in the progression to chronic disease. Human diseases associations highlight connections to rheumatoid arthritis, nervous and cardiac systems. GSEA and WGCNA bounce the hypotheses of a persistent viral reservoir or an increased susceptibility to RNA viral pathogens with new onset infections. Together, our findings might offer potential targets for therapeutic options aimed at alleviating chronic chikungunya.

bioinformatics↗