Biology subjects

Hernandez, B. J.

Publications and source records attributed to Hernandez, B. J..

3 recordsLinked to original sources

bioRxiv2026

Hyperosmolar stress promotes the release of small extracellular vesicles containing metabolic proteins from corneal epithelial cells

PurposeHyperosmolar stress (HOS) is a major contributor to corneal epithelial cell damage in dry eye disease. We have previously shown that HOS damages mitochondria and impairs cell metabolism in corneal epithelial cells. Small extracellular vesicles (sEVs) are cell-derived lipid envelopes that are present in all body fluids, including tears. Prior studies suggest that sEV release and composition may be linked with changes in cell metabolism. In this study, we tested the effects of HOS on sEV release and composition, and found that sEV cargo may reflect early, underlying changes in dry eye disease. MethodsTelomerase-immortalized human corneal epithelial (hTCEpi) cells were treated with 450 mOsm NaCl for five days to induce chronic HOS. sEVs were isolated using differential centrifugation followed by iodixanol density gradient flotation. Particle number was determined using Nanoparticle Tracking Analysis (NTA). Mass spectrometry was used to assess the sEV proteome, and selected proteins were validated by immunoblot. Proteome pathways were analyzed using KEGG and CORUM. ResultsPathway analysis revealed an increase in metabolic proteins and proteasome components in sEV cargo released from hTCEpi cells exposed to HOS. These proteins were increased more than fourfold in HOS-sEVs. Examination of proteins involved in the endosomal pathway and NTA further confirmed an increase in HOS-sEV release. ConclusionOur findings suggest a potential mechanism whereby corneal epithelial cells exposed to HOS retain proteins involved in maintaining tissue integrity, while simultaneously releasing unneeded proteins involved in cell metabolism. The presence of metabolic proteins in sEVs may serve as early indicators of dry eye disease.

cell biology↗

bioRxiv2021

Intermediary role of lung alveolar type 1 cells in epithelial repair upon Sendai virus infection

The lung epithelium forms the first barrier against respiratory pathogens and noxious chemicals; however, little is known about how >90% of this barrier - made of alveolar type 1 (AT1) cells - responds to injury, in contrast to our accumulating knowledge of epithelial progenitor and stem cells whose importance lies in their ability to restore the barrier. Using Sendai virus to model natural infection in mice, we combine 3D imaging, lineage-tracing, and single-cell genomics to show that AT1 cells have an intermediary role by persisting in areas depleted of alveolar type 2 (AT2) cells, mounting an interferon response, and receding from invading airway cells. Sendai virus infection mobilizes airway cells to form alveolar SOX2+ clusters without differentiating into AT1 or AT2 cells, as shown in influenza models. Intriguingly, large AT2-cell-depleted areas remain covered by AT1 cells, which we name "AT2-less regions", and are replaced by SOX2+ clusters spreading both basally and luminally around AT1 cell extensions. AT2 cell proliferation and differentiation are largely confined to topologically distal regions - the end of airspace that could be in the periphery or middle of the lung - and form de novo alveolar surface, with limited contribution to in situ repair of AT2-less regions. Time course single-cell RNA-seq and AT1-cell interactome analyses suggest enhanced recognition of AT1 cells by immune cells and altered growth signals. Our comprehensive spatiotemporal and genome-wide study highlights the hitherto unappreciated role of AT1 cells during Sendai virus infection and possibly other injury-repair processes.

developmental biology↗

bioRxiv2020

Quantitative single-cell interactomes in normal and virus-infected mouse lungs

Mammalian organs consist of diverse, intermixed cell types that signal to each other via ligand-receptor interactions - an interactome - to ensure development, homeostasis, and injury-repair. Dissecting such intercellular interactions is facilitated by rapidly growing single-cell RNA-seq (scRNA-seq) data; however, existing computational methods are often not sufficiently quantitative nor readily adaptable by bench scientists without advanced programming skills. Here we describe a quantitative intuitive algorithm, coupled with an optimized experimental protocol, to construct and compare interactomes in control and Sendai virus-infected mouse lungs. A minimum of 90 cells per cell type compensates for the known gene dropout issue in scRNA-seq and achieves comparable sensitivity to bulk RNA-seq. Cell lineage normalization after cell sorting allows cost-efficient representation of cell types of interest. A numeric representation of ligand-receptor interactions identifies, as outliers, known and potentially new interactions as well as changes upon viral infection. Our experimental and computational approaches can be generalized to other organs and human samples. Summary statementAn intuitive method to construct quantitative ligand-receptor interactomes using single-cell RNA-seq data and its application to normal and Sendai virus-infected mouse lungs.

bioinformatics↗