Monday, June 2, 7:00-8:15 AM

A Confident Start: Reliable Sample Prep for Robust Proteomic Data in Discovery Research 

An AFA-assisted workflow for mass-spectrometry-based proteomics analysis of low input FFPE samples 

Presented by Anu Jain
Postdoctoral Fellow, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN

Studying the spatial proteome is crucial for understanding of physiological or pathological processes as it provides a deeper insight into proteins function within their specific locations in cells and tissues. With significant advancements in microscopy and mass spectrometry, it has become feasible to explore the cellular proteome at low number of cells or even single cells. However, spatial proteomics is an evolving field with scope for newer sample preparation and data analysis techniques. Our objective was to develop a sample preparation workflow for analyzing proteome from limited cells obtained from formalin fixed paraffin embedded (FFPE) tissue. 

Accurate assessment of endogenous protein from human colon FFPE tissues by LC-MS/MS bioanalysis  

Presented by Soumya Kandi
Senior Scientist, Quantitative Translational ADME Sciences, Abbvie, North Chicago, IL

Formalin-Fixed Paraffin Embedding (FFPE) is widely used for tissue preservation in clinical settings; protein expression is primarily assessed with immunohistochemistry. Proteomics from FFPE tissues can only identify proteins with large quantitative changes and require multiple technical steps that introduce error and batch effects. Proteomics data are hypothesis generating at best due to the breadth of coverage, making the dataset prone to statistical challenges for proteins with subtle expression differences. In this presentation, Soumya will talk about the use of LC-MS/MS targeted protein quantification for measuring more subtle protein changes due to the ability to carefully assess relative precision and preparation robustness.  

Tuesday, June 3, 7:00-8:15 AM

Proteomics and Beyond: Addressing Sample Preparation Challenges for Proteomics and Metabolomics   

An optimized workflow for metabolite and lipid extraction using Covaris cryoPREP® and AFA technology for 4D-LC-timsTOF-MS analysis of cancer tissue 

 
Presented by Denis Ispan 
Core Facility Manager, University of Tübingen, Tübingen, Germany 

Metabolomics and lipidomics provide crucial insights into metabolic alterations in disease models or human samples. Reliable extraction of metabolites from complex samples such as tissue, organoids, or cells with robust membranes is essential for accurate detection and analysis. To achieve high-quality extraction from a preclinical brain cancer mouse model, we first employed cryogenic sample pulverization with the Covaris cryoPREP, ensuring precise and reproducible tissue disruption. This was followed by treatment with Adaptive Focused Acoustics (AFA) on the Covaris LE220 Focused-ultrasonicator, which enables efficient, contact-free, high-throughput and reproducible extraction of metabolites and lipids. The resulting extracts were analyzed using four dimensional (4D) LC-timsTOF-MS/MS workflows, incorporating both RP and HILIC chromatography in dual polarities with collision cross section (CCS) values for unprecedented metabolome and lipidome coverage. This optimized workflow facilitated the robust identification of metabolite and lipid variations across different tumor treatment groups, establishing a robust, reproducible, and scalable platform for metabolomics and lipidomics studies of cancer tissue samples. 

Simplified homogenization workflow to maximize protein extraction and minimize variance across sample types using Adaptive Focused Acoustics (AFA) technology

Presented by Juan Wang, Ph.D.
Senior Scientist, Proteomics, AstraZeneca, Waltham, MA

Proteomic analysis of tissue samples by mass spectrometry is critical for the drug development pipeline. Efficient and reproducible pre-analytical sample preparation, such as homogenization and protein extraction, is a prerequisite for high quality data and results reflecting the underlying biology of the system. Presently, bead beating is the primary technique, but it presents multiple issues that risk the quality of the data. We have optimized two workflows for automated homogenization of tissue samples from 2mg up to 50mg in weight without or with dry pulverization and Adaptive Focused Acoustics (AFA) technology to mitigate the challenges of bead beating. The optimized workflows were demonstrated to be broadly applicable to tissues of varying types. The new high throughput workflow decreased the fraction of time of active engagement by approximately 45%, achieving the target improvement.

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