Proteomic workflows for deep phenotypic profiling of 3D organotypic liver models

ABSTRACT: Organotypic human tissue models constitute promising systems to facilitate drug discovery and development. They allow to maintain native cellular phenotypes and functions, which enables long-term pharmacokinetic and toxicity studies, as well as phenotypic screening. To trace relevant phenotypic changes back to specific targets or signaling pathways, comprehensive proteomic profiling is the gold-standard. A multitude of proteomic workflows have been applied on 3D tissue models to quantify their molecular phenotypes; however, their impact on analytical results and biological conclusions has not been evaluated. Here, we compared the performance of twelve mass spectrometry-based global proteomic workflows that differed in the amount of cellular input, lysis protocols and quantification methods for the analysis of primary human liver spheroids. We find that the different protocols differ majorly in the total number and subcellular compartment bias of identified proteins, which is particularly relevant for the reliable quantification of transporters and drug metabolizing enzymes. However, using a model of non-alcoholic fatty liver disease, we show that critical disease pathways are robustly identified using a standardized high throughput-compatible workflow based on thermal lysis, even using only individual spheroids (1,500 cells) as input. The results increase the applicability of proteomic profiling to phenotypic screens in organotypic microtissues and provides a scalable platform for deep phenotyping from limited biological material.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Hepatocyte, Liver

SUBMITTER: Akos Vegvari  

LAB HEAD: Akos Vegvari

PROVIDER: PXD047462 | Pride | 2024-04-29

REPOSITORIES: Pride