Evidence map›Paper›PMID 41814656›Full record

ArticleBiophysical journal2026

A tunable, ultrasensitive threshold in enzymatic activity governs the DNA methylation landscape.

Kwadwo A Bonsu, Nandor Laszik, Annie Trinh, Timothy L Downing, Elizabeth L Read

Abstract read
In one paragraph

Article in Biophysical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kwadwo A BonsuDepartment of Chemical & Biomolecular Engineering, University of California, Irvine, Irvine, California; The NSF Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine California.
Nandor LaszikDepartment of Biomedical Engineering, University of California, Irvine, Irvine, California.
Annie TrinhDepartment of Microbiology & Molecular Genetics, University of California, Irvine, Irvine, California; The NSF Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine California.
Timothy L DowningDepartment of Biomedical Engineering, University of California, Irvine, Irvine, California; Department of Microbiology & Molecular Genetics, University of California, Irvine, Irvine, California; The NSF Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine California.
Elizabeth L ReadDepartment of Chemical & Biomolecular Engineering, University of California, Irvine, Irvine, California; The NSF Simons Center for Multiscale Cell Fate Research, University of California, Irvine, Irvine California. Electronic address: elread@uci.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation is a widely studied epigenetic mark, affecting gene expression and cellular function at multiple levels. DNA methylation in the mammalian genome occurs primarily at cytosine-phosphate-guanine (CpG) dinucleotides, and patterning of the methylation landscape (i.e., the presence or absence of CpG methylation at a given genomic location) exhibits a generally bimodal distribution. Although much is known about the enzymatic writers and erasers of CpG methylation, it is not fully understood how these enzymes, along with genetic, chromatin, and regulatory factors, control the genome-wide methylation landscape. In this study, methylation is analyzed at annotated CpG islands (CGIs) and independent CpGs as a function of their proximity to other CpG substrates. Analysis is aided by a computationally efficient stochastic mathematical model of methylation dynamics, enabling parameterization from data. We find that methylation exhibits a switch-like dependence on local CpG density with a threshold of 7-8 CpGs per 100 bp and a Hill coefficient of 4-5. The threshold and steepness of the switch is modified in cell lines in which key enzymes are knocked out. Modeling further elucidates how enzymatic parameters, including catalytic rates and lengthscales of inter-CpG interaction, tune the properties of the switch. Together, the results support a model in which competition between opposing TET1-3 demethylating enzymes and DNA methyltransferases (DNMT3A/B) results in an ultrasensitive switch, analogous to the protein phosphorylation switch (termed "zero-order ultrasensitivity"). Our study provides insight to the mechanisms underlying establishment and maintenance of bimodal DNA methylation landscapes, and further provides a flexible pipeline for gleaning molecular insights to the cellular methylation machinery across cell-specific, epigenomic data sets.

Indexed as

DNA MethylationAnimalsCpG IslandsDNA (Cytosine-5-)-MethyltransferasesHumansStochastic ProcessesDNA (Cytosine-5-)-Methyltransferases

Identifiers

PMID41814656
PMCPMC13351868

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.