Automated systems to accelerate large-scale phosphoproteomics studies

James Burgess¹, Hannah Huckstep¹, Lina Le¹, Sean J. Humphrey¹

¹Functional Phosphoproteomics, Murdoch Children"s Research Institute, Royal Children"s Hospital, Melbourne, Victoria 3052, Australia

Protein phosphorylation is involved in almost all cellular processes. The ability to study phosphorylation in a global and unbiased manner using mass spectrometry (MS-based phosphoproteomics) is transforming our understanding of cell biology. Advances in mass spectrometry instrumentation together with streamlined and efficient workflows for performing phosphopeptide enrichment now make it feasible to process hundreds of phosphoproteome samples in parallel. However, workflows for upstream sample generation present a bottleneck, limiting the throughput of large-scale phosphoproteomic studies. Here we describe an automated platform for mass spectrometry-based phosphoproteomics, enhancing reproducibility and throughput through three key innovations: automated and semi-automated human-in-the-loop experimental manipulation, multi-instrument control by programming of a robotic arm with high degrees of freedom, and sustained high-throughput operation.

1) Automated Experimental Manipulation: Advanced liquid handling instruments by vendors like Tecan and Opentrons enable standardisation of sample preparation process, including the application of compounds or ligands, cell lysis, and protein digestion. Automating sample handling using these instruments minimises human error, ensuring consistent and precise manipulation and facilitating large batch processing.

2) Robotic Arm Programming: Open-source libraries for motion planning, collision aware inverse kinematics and environmental simulations enable programming of collaborative robotic arms to perform complex sample transfers in tandem with liquid handling and cell incubators, ensuring precise, timely movements between machines and reducing the risk of cross-contamination.

3) Sustained High-Throughput Operation: Our platform is designed to achieve sustained throughput in phosphoproteomics studies. This sustained operation will facilitate comprehensive phosphoproteome characterisation, greatly increasing the quantity and quality of data gathered as compared to manual operations in a similar timeframe at a fraction of the cost.

Conclusion: Our platform improves existing phosphoproteomics workflows by providing an economical, reliable and high-throughput solution for the generation and handling of biological samples. By integrating liquid handling machines and incubators using robotic arm programming, we enable studies otherwise out of reach. We will first apply our platform to study the impact of a library of small molecules on the phosphoproteome. We plan to subsequently use this data to elucidate novel pathways and effector proteins specifically responsible for observed cellular phenotypic effects of the compounds in a disease context.