Diversity and granularity in immunometabolism: combining SCENITH with spectral flow on the ID7000™ Spectral Cell Analyzer
Scientists have increasingly recognized that the metabolic profile of an immune cell is closely linked to its function, in contexts ranging from infection and cancer to autoimmunity and aging. Given the complexity of the human immune system, our understanding of immunometabolism is unevenly distributed, with smaller cell populations and those which fare poorly in culture insufficiently studied.
In this webinar, we use recent advancements—spectral flow cytometry and SCENITH™ technology—to combine high-resolution profiling of cellular heterogeneity with granular measurement of glycolytic and mitochondrial activity. We also show how sample size and cell number are key technical requirements for reliable measurement and demonstrate the strengths of the ID7000™ Spectral Cell Analyzer in the implementation of barcoding and autofluorescence measurement. With this knowledge, researchers can establish best practices in flow cytometry for assaying immunometabolism in highly heterogeneous samples.
Key Learning Objectives:
- Learn how SCENITH and spectral flow cytometry can be combined to gather new insights into immunometabolism
- Understand how the ID7000 can be used to effectively measure autofluorescence
- Discover how sample barcoding improves accuracy in high-throughput sample acquisition
Who should attend
Researchers who are interested in combining spectral flow cytometry with SCENITH to enhance their studies of immunometabolism will benefit from this webinar.
Speaker
Ee Lyn Lim, PhD
Senior Scientist, BioMed X
As a Senior Scientist at BioMed X, Lyn’s work focuses on the links between immune-mediated inflammation and metabolic dysfunction in autoimmunity. She completed her PhD at the University of Cambridge and has conducted research on broad areas of immunology at Osaka University and the Max Planck Institute for Infection Biology. Her current interest involves single-cell functional characterization within highly heterogeneous primary cell populations using high-dimensional flow cytometry.