Metabolomics Masterclass: Cutting-Edge Techniques for Single Cell Analysis and Precision Health at Scale
Session 1:
The fundamental unit of a living organism is the single cell. What are the benefits and issues with pushing towards single cell measurements? The overarching goal is to provide an understanding of why discovery based single cell analysis is important and achievable. Several example applications highlight single cell metabolites including amino acids, small bio-active neuropeptides and neurotransmitters. Metabolites in individual cells were characterized using capillary electrophoresis (CE) with MRM MS with the QqQ-MS. The sample preparation steps were performed in vial inserts in the CE system to reduce the solution requirements of the autosampler to ~2 µL. Other changes to the system include a nanointerface and a mechanically tapered capillary tip for optimized detectability. The CE-nanoESI-QqQ MS system demonstrated detection limits at the single attomole level for a range of amino acids and transmitters. We characterize a range of cells including Aplysia californica neurons, rodent neurons, transplant-quality islets, and individual endocrine cells. The combination of nanovial CE-nanoESI-QqQ MS, interface, auto sampler, and fast MRM measurements enables high-throughput, high-sensitivity, and robust metabolite analysis of single cells.
Key learning objectives
- Why single cell assays provide key details
- How to prepare single cells for measurements
- Why CE/MS works well for single cell metabolomics
- Benefits of a targeted QQQ approach
- How to reduce sample volumes
- On going optimization of CEMS interface
- Quantify differences in metabolic levels between cells
- Scientists in the life sciences, with a focus on discovery, or a need for large-scale analyses
Who should attend?
- Discovery groups involved with identifying and quantifying biomarkers. Researchers who are sample limited.
Session 2:
Untargeted metabolomics and lipidomics have traditionally been seen as primarily academic pursuits, often dismissed in clinical research due to perceived challenges in scalability and reproducibility. However, the emergence of precision health, which relies on the concept of digital twins—comprehensive digital representations of the complete molecular content of biological specimens—necessitates the use of untargeted approaches. These methods, in theory, offer the potential to explore an extensive chemical space. But what does it take to implement such analyses on a large scale, aiming both for accuracy in quantification and extensive identification? This presentation will highlight the key lessons learned from the Swiss Personalized Health Initiative.
Key learning objectives
- Why is QTOF technology ideally suited for untargeted analyses, both for metabolites and lipidomics
- What are the critical factors to perform large scale LC-MS (LC, MS, DDA)
- Harmonization of large-scale data
Who should attend?
- Scientists in the life sciences, with a focus on discovery, or a need for large-scale analyses
Certificate of attendance
All webinar participants can request a certificate of attendance, including a learning outcomes summary, for continuing education purposes.
Speakers
Dr. Sweedler’s research interests focus on developing new lipidomics, metabolomics and peptidomics approaches for assaying small volume samples including new sampling approaches, miniaturized separations, and mass spectrometry. He has used these tools to characterize small molecules and peptides in a range of animal models across metazoan life and in samples as small as individual cells and cellular domains. Sweedler has published more than 500 manuscripts and presented more than 600 invited lectures. He has received numerous awards including the Instrumentation Award from the Analytical Division of the ACS, the Pittsburgh Analytical Chemistry Award, and the ACS Award in Analytical Chemistry. He is a fellow of both the American Association for the Advancement of Science and the American Chemical Society. He is currently the Editor-in-Chief for Analytical Chemistry.
Nicola Zamboni’s research pivots on investigating metabolism and its regulation, from cells to humans. The lab relies heavily on mass spectrometry to quantify levels and rates of conversion of metabolites. In parallel, it develops computational approaches to enable large-scale data acquisition and integration. The lab is embedded in the Swiss personalized health initiatives as main provider of metabolomics and lipidomics for clinical research.
Moderator
