Single Cell Energy Metabolism Profiling Service
Creative Biolabs provides a comprehensive range of customized, high-quality services in single cell energy metabolism profiling service to help researchers study metabolic responses in multiple cell types and study energetic metabolism reprogramming in cancer and immune responses.
Energy Metabolism
Energetic metabolism comprises a series of interconnected biochemical pathways capable of using energy-rich molecules to produce ATP (Argüello, 2020). ATP can be produced by oxidative phosphorylation (OXPHOS) or glycolysis in cells. Aerobic glycolysis promotes cell proliferation, and in hypoxic conditions, it can help cells survive. Immune cells can migrate into peripheral tissues and adapt to changes in the microenvironment. Their energy metabolic profile is linked to microanatomical localization, activation, proliferation, and functional status (Argüello, 2020). The study of energy metabolism can help researchers to evaluate biological function in both health and disease.
Single Cell Energy Metabolism Profiling Method
The protein synthesis (PS) machinery immediately consumes almost half of the total energy that mammalian cells create by degrading glucose, amino acids, and/or lipids. The high energy cost of this important metabolic process provides a methodological opportunity to use PS levels as a measure of global metabolic activity. SCENITH (single cell energetic metabolism by profiling translation inhibition): a flow cytometry-based method to functionally profile energy metabolism with single-cell resolution. We paired a novel antipuro monoclonal antibody with the drug puromycin(puro), whose incorporation is a reliable readout for assessing PS levels in vitro and in vivo, to establish a simple method for complicated metabolic profiling with single-cell resolution based on PS levels as the readout. The profile reveals the metabolic capacities and dependencies of the cells and high glycolytic capacity profile.
Fig.1. Description of SCENITH procedure. (Argüello, 2020)
Cell sorting and incubation with cell culture can affect the metabolic activity of the cells, so metabolic profiles of heterogenous and scarce living cell populations derived from human blood samples or biopsies, ex vivo cannot be established. SCENITH: a method for determining metabolic capacities and dependencies of cells regardless of their phenotype. Here is a comparative table of methods for profile metabolism.
Fig.2. Comparative Table of Methods to Profile Metabolism. (Argüello,2020)
Our Single Cell Energy Metabolism Profiling Service
We offer scientific and meticulous design for sample preparation and divide it, then treat each with the inhibitors (e.g., DG, O, DG+O, H) and puro. After staining and flow cytometry, the profile of response of the different cell subsets is analyzed. The profile reveals the metabolic capacities and dependencies of the cells and high glycolytic capacity profile.
Fig.3 Our Single Cell Energy Metabolism Profiling Service. (Creative Biolabs)
Published Data
SCENITH assesses the impact of metabolic inhibitors on protein synthesis. The use of specific inhibitors provides the estimation of glucose dependence, mitochondrial dependence, glycolytic capacity and fatty acid and amino acid oxidation (FaaO) capacity.
Fig.4. SCENITH methodology for analysis of cell metabolism. (Lopes, 2021)
Applications
SCENITH technology can determine the energy state of each immune cell or cancer cell in a tumor, as well as their energy source and metabolic pathways. We hope that researchers can use this new technology to conduct relevant clinical trials and learn more about how it might be used to predict patient response to therapy.
Professional consultation provides guidance before, during and after the project. please contact us for your tailored solution about single cell energy metabolism profiling.
References
- Seydel C. Single-cell metabolomics hits its stride. Nature Methods. 2021, 18(12).
- Rafael J. Argüello.; et al. SCENITH: A Flow Cytometry-Based Method to Functionally Profile Energy Metabolism with Single-Cell Resolution. Cell Metabolism. 2020, 32(6).
- Lopes N.; et al. Distinct metabolic programs control the effector fate of γδ T cell subsets and their activities in the tumor microenvironment. Nature Immunology. 2021. 22(2): 179-192.
- Bosc C.; et al. Mitochondrial inhibitors circumvent adaptive resistance to venetoclax and cytarabine combination therapy in acute myeloid leukemia. Nature Cancer. 2021. 1204-1223.
