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Evaluating single cell proteomics as a tool for understanding hepatotoxicity

ABSTRACT: Bulk and single human primary hepatocytes were obtained from a commercial source from a single human donor. Cells were grown according to vendor protocols and treated with DMSO control or acetaminophen at the IC50 dose previously determined by R. Bruderer et al., 2015. Single cells were isolated using a Tecan UNO system using vendor protocols. 400 nanogram of bulk cell lysates from each condition were analyzed using diaPASEF using a TIMSTOF Flex system coupled to an EvoSep One system and using a 44 minute total gradient (30SPD). Single isolated cells were ran with a method with a compable run to run time and diaPASEF method using an EasyNLC 1200 system coupled to a TIMSTOF SCP system. In the case of the latter, cells were separated on a PepSep C-18 75 um column operating at 200 nL/min. Bulk cell lysates were used to create a library in SpectroNaut 18 from which was used for the analysis of all single cells.

INSTRUMENT(S): timsTOF SCP

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Benjamin C Orsburn

PROVIDER: MSV000094572 | MassIVE | Fri Apr 19 17:50:00 BST 2024

SECONDARY ACCESSION(S): PXD051595

REPOSITORIES: MassIVE

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Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies. Figure 4c, obtained from the simulation of human colitis model is highlighted here. This model is described in the article: Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9 Abstract: Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease. This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.

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Evaluating single cell proteomics as a tool for understanding hepatotoxicity

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