Optimizing scheduling in dual-pulse nucleoside labeling experiments for cell cycle analysis
File(s)
Published version
Author(s)
Phelan, Alastar
Pospori, Constandina
Lo Celso, Cristina
Lee, Chiu Fan
Type
Journal Article
Abstract
All eukaryotic cells go though a universal sequence of phases during their division cycle, where the phase
timings vary according to cell type and state. Dual-pulse nucleoside labeling (DPNL) is a standard, widely applicable
experimental DNA base substituting technique to probe cell cycle kinetics at the population level, including in living organisms. In such an experimental protocol, a key scheduling parameter is the choice of waiting time between the two labeling pulses. Here, we model population cell cycle dynamics as a three-stage Poisson process with an idealized S-phase labeling step, and use a simulation-based look-up procedure to demonstrate that the inter-pulse waiting time can be optimized to maximize the signal-to-noise ratio of inferred cycle parameters — an issue that is especially critical in DPNL experiments with limited cell numbers and replicates. An optimal choice of pulse scheduling typically improves S phase time inference by 50% compared to a random choice. We further discuss the procedure to perform such a task in an experimentally relevant
setting.
timings vary according to cell type and state. Dual-pulse nucleoside labeling (DPNL) is a standard, widely applicable
experimental DNA base substituting technique to probe cell cycle kinetics at the population level, including in living organisms. In such an experimental protocol, a key scheduling parameter is the choice of waiting time between the two labeling pulses. Here, we model population cell cycle dynamics as a three-stage Poisson process with an idealized S-phase labeling step, and use a simulation-based look-up procedure to demonstrate that the inter-pulse waiting time can be optimized to maximize the signal-to-noise ratio of inferred cycle parameters — an issue that is especially critical in DPNL experiments with limited cell numbers and replicates. An optimal choice of pulse scheduling typically improves S phase time inference by 50% compared to a random choice. We further discuss the procedure to perform such a task in an experimentally relevant
setting.
Date Issued
2026-05-05
Date Acceptance
2026-03-02
Citation
Biophysical Journal, 2026, 125 (9), pp.2115-2121
ISSN
0006-3495
Publisher
Cell Press
Start Page
2115
End Page
2121
Journal / Book Title
Biophysical Journal
Volume
125
Issue
9
Copyright Statement
© 2026 Published by Elsevier Inc. on behalf of Biophysical Society. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
License URL
Identifier
10.1016/j.bpj.2026.03.049
Publication Status
Published
Date Publish Online
2026-03-27