Benchmarking three simple DNA staining-based image metrics for live-cell tracking of chromatin organization

Quantifying chromatin-state dynamics in living cells remains challenging, in part because most methods require fixation or cell lysis. Here, we introduce two simple DNA image-derived metrics - Diffuse Signal Index (DSI)and 1-Gini - and benchmark them against the coefficient of variation (CV) as fixation-free readouts of chromatin reorganization. Leveraging the pronounced compact-to-decompact chromatin transition of NETosis, we show that all three metrics track progressive chromatin reorganization, with DSI providing the strongest trajectory-level discrimination between NETing and non-NETing cells. All three metrics also correlate with ATAC-see-based chromatin accessibility measurement in fixed cells, supporting their biological interpretability. In dividing cells, the metrics capture mitotic chromatin compaction and post-mitotic decompaction, demonstrating applicability in diverse biological processes. Together, these results provide a practical framework for extracting readouts of chromatin reorganization from routine live-cell DNA staining. We also provide NucMetrics, an open-source ImageJ/Fiji macro toolset for easily computing CV, DSI and 1-Gini.

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Publication Details

Journal
Nucleus
Published
2026-09-12
DOI
https://doi.org/10.1080/19491034.2026.2721777
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Benchmarking three simple DNA staining-based image metrics for live-cell tracking of chromatin organization

Manasi Sawant, Hawa Racine Thiam, Minwoo Kang, Aidan Tomas Cabral
Nucleus
Genomics and Chromatin Dynamics
article

Benchmarking three simple DNA staining-based image metrics for live-cell tracking of chromatin organization

Manasi Sawant, Hawa Racine Thiam, Minwoo Kang, Aidan Tomas Cabral
article en

Abstract

Quantifying chromatin-state dynamics in living cells remains challenging, in part because most methods require fixation or cell lysis. Here, we introduce two simple DNA image-derived metrics - Diffuse Signal Index (DSI)and 1-Gini - and benchmark them against the coefficient of variation (CV) as fixation-free readouts of chromatin reorganization. Leveraging the pronounced compact-to-decompact chromatin transition of NETosis, we show that all three metrics track progressive chromatin reorganization, with DSI providing the strongest trajectory-level discrimination between NETing and non-NETing cells. All three metrics also correlate with ATAC-see-based chromatin accessibility measurement in fixed cells, supporting their biological interpretability. In dividing cells, the metrics capture mitotic chromatin compaction and post-mitotic decompaction, demonstrating applicability in diverse biological processes. Together, these results provide a practical framework for extracting readouts of chromatin reorganization from routine live-cell DNA staining. We also provide NucMetrics, an open-source ImageJ/Fiji macro toolset for easily computing CV, DSI and 1-Gini.

NucleusVol. 17(1)
Chan Zuckerberg Biohub San Francisco (US), Stanford University (US)
David and Lucile Packard Foundation, Koret Foundation, School of Medicine, Stanford University, Stanford Bio-X
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 18%
Genomics and Chromatin Dynamics
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Benchmarking three simple DNA staining-based image metrics for live-cell tracking of chromatin organization — Manasi Sawant, Hawa Racine Thiam, et al. · Nucleus (2026) | TGRS Research Map | TGRS