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  • P-III-1045

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

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Human Health Insights (Neurobiology, Cardiovascular, Liver, Kidney etc.)

Poster

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

Thema

  • Human Health Insights (Neurobiology, Cardiovascular, Liver, Kidney etc.)

Mitwirkende

Stefania Koutsilieri (Solna / SE), Evgeniya Mickols (Solna / SE; Uppsala / SE), Ákos Végvári (Solna / SE), Volker M. Lauschke (Solna / SE; Stuttgart / DE; Tuebingen / DE)

Abstract

Our publication addresses the pressing need for reliable and efficient methods in drug discovery and development by focusing on organotypic human tissue models. These models hold immense potential for advancing pharmacokinetic and toxicity studies, as well as phenotypic screening, due to their ability to maintain native cellular phenotypes and functions over extended periods.

While proteomic profiling is recognized as the gold standard for tracing phenotypic changes in these tissue models, the impact of various proteomic workflows on analytical results and biological conclusions remains largely unexplored. Our study addresses this gap by comparing the performance of twelve mass spectrometry-based proteomic workflows on primary human liver spheroids. We investigated differences in the total number and subcellular compartment bias of identified proteins, crucial for accurate quantification of transporters and drug metabolizing enzymes.

Our findings reveal significant variations between protocols, highlighting the importance of selecting an appropriate workflow for proteomic analysis in organotypic tissue models. Notably, we demonstrate that a standardized, high-throughput-compatible workflow based on thermal lysis yields robust results, even with minimal cellular input. This was exemplified in a model of metabolic dysfunction-associated steatotic liver disease, where critical disease pathways were reliably identified using individual spheroids as input.

Our study significantly advances the field by increasing the applicability of proteomic profiling to phenotypic screens in organotypic microtissues. Furthermore, we provide a scalable platform for deep phenotyping from limited biological material, thus enhancing the efficiency and effectiveness of drug discovery and development processes.

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