Biology subjects

Montis, G.

Publications and source records attributed to Montis, G..

2 recordsLinked to original sources

bioRxiv2025

Decoding Cellular Stress States for Toxicology Using Single-Cell Transcriptomics

We applied the TempO-LINC(R) platform to generate single-cell transcriptomic (SCTr) profiles of [~]40,000 HepaRG cells exposed to etoposide, brefeldin A, cycloheximide, rotenone, tBHQ, troglitazone, and tunicamycin at three concentrations for 24 hours. SCTr enabled a detailed analysis of adaptive stress response pathways (SRPs), including the unfolded protein response (UPR), oxidative stress response (OSR), heat shock response (HSR), and DNA damage response (DDR). Troglitazone upregulated lipid metabolism genes (PLIN2, ACOX1) along with HSR and UPR activation, with co-expression of DNAJA1, HSP90AA1, and DDIT3 in subsets of cells. Brefeldin A and tunicamycin strongly induced UPR markers (HSPA5, SYVN1, LMF2, PDIA4) in subsets of cells, with some also expressing apoptotic (DDIT3, CASP8) and autophagic (SQSTM1) genes, indicating diverse stress responses. Rotenone activated GDF15, TRIB3, and DDIT3 in a fraction of cells, accompanied by PLIN2 and mild UPR induction, reflecting heterogeneous mitochondrial stress responses. We scored individual cells using literature-derived SRP gene signatures to characterize overall stress phenotypes and clustered them using a generalized Jaccard metric. The clustering revealed five phenotypic groups spanning cell states associated with homeostasis, adaptive responses, terminal outcomes, autophagy, and apoptosis. By systematically analyzing the distributions of cells in different states across treatments, we visualized dynamic shifts in cellular subpopulations responding to chemicals, revealing early stress responses and potential transitions to cell death. Our findings suggest the utility of SCTr in decoding stress states that could provide possible insights into transitions between cellular adaptive and terminal transitions involved in toxicity.

pharmacology and toxicology↗

bioRxiv2024

High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution

We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial-indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000+ cells per run. The TempO-LINC approach is easily scalable based on the number of barcodes and rounds of barcoding performed; however, for the experiments reported in this study, the assay utilized over 5.3 million unique barcodes. TempO-LINC has a robust protocol for fixing and banking cells and displays high-sensitivity gene detection from multiple diverse sample types. We show that TempO-LINC has an observed multiplet rate of less than 1.1% and a cell capture rate of [~]50%. Although the assay can accurately profile the whole transcriptome (19,683 human or 21,400 mouse genes), it can be targeted to measure only actionable/informative genes and molecular pathways of interest - thereby reducing sequencing requirements. In this study, we applied TempO-LINC to profile the transcriptomes of 89,722 cells across multiple sample types, including nuclei from mouse lung, kidney and brain tissues. The data demonstrated the ability to identify and annotate at least 50 unique cell populations and positively correlate expression of cell type-specific molecular markers within them. TempO-LINC is a robust new single-cell technology that is ideal for large-scale applications/studies across thousands of samples with high data quality.

genomics↗