Stanford Scientists Use MIBI Technology to Study Single-Cell Metabolic Profiles in Colorectal Carcinoma

Dec 23, 2020

Single-cell, metabolic regulome profiling

Scientists at Stanford University, Vrije University Amsterdam, and the California Institute of Technology reported this year on compelling new work to characterize cellular metabolic profiles at the single-cell level. For a more comprehensive view including spatial resolution, they combined their novel method with Ionpath’s multiplexed ion beam imaging (MIBI™) technology. The results were published in Nature Biotechnology. In the paper, lead author Felix Hartmann, senior author Sean Bendall, and collaborators in California and Amsterdam describe the development of a method they call scMEP (short for single-cell metabolic regulome profiling) designed to quantify proteins associated with regulating the activity of metabolic pathways. One important goal was to improve the metabolomic resolution to help characterize immune cells.
Hartmann, et al. cover

The challenge of studying context-dependent metabolic activity of immune cells

“Immune cells dynamically execute highly context-dependent functions, including migration into affected tissues, exponential expansion and secretion of effector molecules,” the scientists note in the paper. “All of these diverse capacities are enabled and coordinated by dynamic changes in cellular metabolism.” Unfortunately, though, “current metabolic approaches lack single-cell resolution and simultaneous characterization of cellular phenotype,” they add. To address that limitation, Hartmann et al. created scMEP to quantify metabolic features in single cells using proteomic platforms based on antibody capture. They assessed and validated more than 100 antibodies for a broad range of metabolomic targets, selecting about 40 to demonstrate that the antibodies make it possible to infer immune cell identity in heterogeneous populations based on metabolomic regulome profiles. There was overlap between closely related T cells, for instance, but for an average of 94% of the cells studied, metabolic features accurately predicted cell identity.
scMEP - Figure 5d

Pairing scMEP with MIBI technology enabled spatial interrogation of metabolic profiles along the tumor-immune boundary

By pairing scMEP with our MIBI technology, the team generated an excellent view of the spatial organization of cellular metabolism in tissue samples. Each 400 μm × 400 μm image included 36 antibody dimensions, allowing the scientists to identify cell lineage, activation status, and more. A detailed analysis of the images revealed site-specific enzyme enrichment associated with a particular metabolic pathway, including respiratory, glycolysis, and amino acid pathways.
scMEP - single-cell metabolic profiling FOV 23 and 38
scMEP - Figure 5f

The scMEP/MIBI combination allowed the scientists to take a close look at the tumor–immune boundary, an area where the immune cell metabolism is altered by competition from the tumor. The team compared the metabolic regulatory profiles of immune cells on the tumor–immune border to those from far-away cells. They found significant evidence of “metabolic polarization of immune cells toward the tumor, which was dominated by increased expression of CD98 and ASCT2 and which could not be explained by variations in immune cell lineage,” the authors report. Interestingly, these markers have been associated with prognosis in cancer patients, and the scientists speculate that incorporating their expression with tissue features or other metabolic proteins could increase their diagnostic utility.

“These spatial analyses revealed specific exclusion of metabolic immune cell subsets from the tumor–immune boundary, demonstrating the influence of tissue architecture on metabolic regulation,” the scientists conclude. “Incorporating this new lens of single-cell metabolism into translational research promises better control of cellular alterations and dysfunction in human disease.”

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