# Modeling extensive cellular variability in glycolytic rates using multiplexed live-cell data

> **NIH CA R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2026 · $648,177

## Abstract

Summary
Glycolysis, the fundamental metabolic process in which glucose is converted to lactate, lies at the
core of diabetes and metabolic dysfunction, as well as cancer and immune function. Regulation
of glycolytic rate by insulin and other endocrine signals is essential for bodily metabolic
homeostasis and also plays important cell-intrinsic roles in regulating cellular proliferation,
apoptosis, and differentiation. While there is a long history of quantitative modeling of glycolysis
in bulk, regulation at the single-cell level has been explored in much less depth. This lack of
understanding makes it impossible to know whether glucose disposal and lactate production are
distributed evenly across tissues or are selectively performed by cellular subpopulations. Our lab
has made significant progress in single-cell metabolism using multiplexed live-cell measurements
for key points of glycolytic flux and regulation, including fructose 1,6-bisphosphate (FBP),
NADH/NAD+, ADP/ATP, and kinase activities of AKT, AMPK, and mTOR. Our preliminary data in
epithelial, muscle, and liver cell lines indicate an extensive degree of glycolytic heterogeneity and
motivate our overall hypothesis that a small number of live-cell measurements can adequately
constrain mathematical models of the glycolytic rate distributions. Specifically, we hypothesize
that dual measurements of FBP and NADH/NAD+ ratio will provide strong modeling constraints
that will enable the distribution of single-cell glucose disposal and lactate production rates. We
further hypothesize that signaling by the AKT/AMPK/mTOR network links glycolysis rates to
protein synthesis rates to create time-dependent variation and metabolic microenvironments that
affect cellular processes including cell death and differentiation. In this project, we will 1) use
multiplexed live-cell measurements to constrain models of single-cell glycolytic distributions and
identify optimal sets of observables; 2) Measure the single-cell linkage 

## Key facts

- **NIH application ID:** 11298868
- **Project number:** 1R01CA301398-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** John G. Albeck
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** CA
- **Fiscal year:** 2026
- **Award amount:** $648,177
- **Award type:** 1
- **Project period:** 2026-04-01T00:00:00 → 2031-02-28T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11298868

## Citation

> US National Institutes of Health, RePORTER application 11298868, Modeling extensive cellular variability in glycolytic rates using multiplexed live-cell data (1R01CA301398-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11298868. Licensed CC0.

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