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arxiv: 2606.10779 · v1 · pith:TSO4423Wnew · submitted 2026-06-09 · ❄️ cond-mat.soft · physics.bio-ph

NANOG assembles into self-limiting aging micelles that drive a sol-gel transition and modulate DNA dynamics

Amandine Hong-Minh , Yair Augusto Gutierrez Fosado , Abbie Guild , Nicholas Mullin , Laura Spagnolo , Ian Chambers , Davide Michieletto This is my paper

Pith reviewed 2026-06-27 11:36 UTC · model grok-4.3

classification ❄️ cond-mat.soft physics.bio-ph
keywords NANOGself-limiting micellesaging gelsDNA entanglementsintrinsically disordered domainsol-gel transitionstem cell pluripotencyDNA dynamics
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The pith

NANOG forms self-limiting micelles with exposed DNA-binding domains that stabilize DNA entanglements and drive aging gel formation at high concentrations.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes that the transcription factor NANOG, which maintains embryonic stem cell pluripotency, assembles into self-limiting micelles instead of the unbounded condensates typical of many disordered proteins. These micelles keep DNA-binding domains accessible on their surface, allowing them to stabilize DNA entanglements and alter DNA movement. At higher concentrations NANOG produces macroscopic gels whose formation and aging depend on its intrinsically disordered domain. If correct, this mechanism offers a route by which NANOG could create local mechanical environments that restrict genome dynamics and embed memory in gene regulation.

Core claim

NANOG forms self-limiting micelles that expose DNA-binding domains, in contrast to unbounded condensates formed by other intrinsically disordered proteins. These micelles stabilize DNA entanglements and thereby modulate DNA dynamics. At high concentrations NANOG assembles into macroscopic aging gels whose properties depend on its intrinsically disordered domain, leading to the conjecture that NANOG may regulate gene expression by generating local gel-like environments that restrict genome dynamics and that its aging may ingrain mechanical memory in gene regulatory networks.

What carries the argument

Self-limiting micelles assembled by NANOG that keep DNA-binding domains exposed while capping further growth.

If this is right

  • The micelles stabilize DNA entanglements and slow or alter DNA dynamics.
  • High NANOG concentrations produce macroscopic aging gels whose formation requires the intrinsically disordered domain.
  • Local gel-like environments created by the micelles can restrict genome dynamics.
  • Aging of the gels may embed mechanical memory within gene regulatory networks.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the micelle-to-gel transition occurs in nuclei, it could provide a concentration-dependent switch for controlling how easily transcription factors reach their targets.
  • Mutating the disordered domain to block gelation while preserving micelle formation would test whether aging is required for the proposed memory effect.
  • Similar self-limiting assemblies might exist in other transcription factors that contain both ordered DNA-binding and disordered regions.

Load-bearing premise

Observations of micelle formation, self-limitation, and gelation made in purified solutions and simulations apply directly to how NANOG functions inside living embryonic stem cells.

What would settle it

Direct imaging or rheological measurements inside stem cells showing that NANOG neither forms micelles nor produces local gel-like constraints on DNA motion would falsify the functional link.

read the original abstract

Proteins and nucleic acids form non-Newtonian liquids with complex rheological properties that contribute to their function in vivo. Here we investigate the rheology of the transcription factor NANOG, a key protein to maintain embryonic stem cell pluripotency. We find that at high concentrations, NANOG forms macroscopic aging gels that are dependent on its intrinsically disordered domain. By combining molecular dynamics simulations, mass photometry and Cryo-EM, we also discover that -- in contrast with unbounded condensates formed by other intrinsically disordered proteins -- NANOG forms self-limiting micelles with exposed DNA-binding domains. We show that these micelles can stabilize DNA entanglements and in turn modulate DNA dynamics. Based on our findings, we conjecture that NANOG may contribute to regulate gene expression by creating local gel-like environments that restrict genome dynamics and that its aging may ingrain mechanical memory in gene regulatory networks.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript reports that the transcription factor NANOG assembles into self-limiting micelles with exposed DNA-binding domains, as evidenced by molecular dynamics simulations, mass photometry, and Cryo-EM. At high concentrations, NANOG forms aging gels dependent on its intrinsically disordered region, which can stabilize DNA entanglements and modulate DNA dynamics. The authors conjecture that this assembly may regulate gene expression in embryonic stem cells by creating local gel-like environments that restrict genome dynamics.

Significance. If the in vitro micelle formation, self-limitation, and gelation observations hold and extend to cellular conditions, this would offer a novel physical mechanism linking transcription factor self-assembly to mechanical regulation of the genome and pluripotency maintenance. The multi-method approach (MD, mass photometry, Cryo-EM, rheology) is a strength for characterizing the assemblies.

major comments (2)
  1. [Abstract] Abstract: the functional claim that micelles 'modulate DNA dynamics' and 'may contribute to regulate gene expression' by creating gel-like environments in embryonic stem cells is load-bearing for the paper's significance but rests on in vitro observations at high concentrations; no cellular NANOG concentration measurements, live-cell imaging of assemblies, or perturbation experiments linking micelles/gels to gene expression changes are reported.
  2. [Abstract] Abstract: gelation is explicitly qualified as occurring 'at high concentrations' and the regulatory role labeled a 'conjecture'; without data on whether self-limiting micelles form at physiological NANOG levels, the extrapolation from purified-protein rheology to genome dynamics in cells remains unsupported.
minor comments (1)
  1. The abstract and discussion would benefit from more explicit separation between the supported in vitro observations (micelle structure, gelation) and the conjectured in vivo implications.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for their careful reading and for emphasizing the distinction between our in vitro biophysical observations and potential cellular implications. We address the two abstract-related comments below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the functional claim that micelles 'modulate DNA dynamics' and 'may contribute to regulate gene expression' by creating gel-like environments in embryonic stem cells is load-bearing for the paper's significance but rests on in vitro observations at high concentrations; no cellular NANOG concentration measurements, live-cell imaging of assemblies, or perturbation experiments linking micelles/gels to gene expression changes are reported.

    Authors: We agree that the manuscript reports exclusively in vitro data and contains no cellular NANOG concentration measurements, live-cell imaging, or gene-expression perturbation experiments. The abstract already qualifies the gelation as occurring 'at high concentrations' and labels the proposed regulatory role a 'conjecture.' The in vitro evidence (MD, mass photometry, Cryo-EM, and rheology) demonstrates that NANOG micelles can stabilize DNA entanglements and modulate DNA dynamics under the conditions tested; this provides the biophysical foundation for the stated conjecture without claiming direct cellular validation. revision: no

  2. Referee: [Abstract] Abstract: gelation is explicitly qualified as occurring 'at high concentrations' and the regulatory role labeled a 'conjecture'; without data on whether self-limiting micelles form at physiological NANOG levels, the extrapolation from purified-protein rheology to genome dynamics in cells remains unsupported.

    Authors: The manuscript already qualifies both the concentration dependence and the conjectural nature of the cellular extrapolation, as the referee notes. Our work characterizes the self-limiting micellar assembly and its rheological consequences in purified systems; we do not claim that micelles form at physiological levels or directly regulate gene expression in cells. The multi-method in vitro data establish a plausible physical mechanism that could operate locally if similar assemblies occur in the nucleus, thereby motivating future cellular studies. revision: no

standing simulated objections not resolved
  • Absence of cellular NANOG concentration measurements, live-cell imaging of assemblies, or perturbation experiments linking micelles/gels to gene expression changes

Circularity Check

0 steps flagged

No circularity: experimental observations with no derivations or self-referential reductions

full rationale

The manuscript reports direct experimental and simulation results on NANOG micelle formation (MD, mass photometry, Cryo-EM) and gelation (rheology) without any mathematical derivation chain, fitted parameters renamed as predictions, or load-bearing self-citations. Claims are presented as observations qualified by 'conjecture' for cellular relevance, with no equations, uniqueness theorems, or ansatzes that reduce to inputs by construction. The work is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

No mathematical model or free parameters are described in the abstract; the work is experimental with standard biophysical assumptions.

pith-pipeline@v0.9.1-grok · 5703 in / 1122 out tokens · 17303 ms · 2026-06-27T11:36:10.012696+00:00 · methodology

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Works this paper leans on

41 extracted references · 1 canonical work pages

  1. [1]

    Alberts, R

    B. Alberts, R. Heald, A. Johnson, D. Morgan, M. Raff, K. Roberts, and P. Walter,Molecular Biology of the Cell, 7th ed. (W. W. Norton & Company, 2022)

    2022

  2. [2]

    Niwa, J.-i

    H. Niwa, J.-i. Miyazaki, and A. G. Smith, Nature Genet- ics24, 372 (2000)

    2000

  3. [3]

    Chambers, D

    I. Chambers, D. Colby, M. Robertson, J. Nichols, S. Lee, S. Tweedie, and A. Smith, Cell113, 643 (2003)

    2003

  4. [4]

    Masui, Y

    S. Masui, Y. Nakatake, Y. Toyooka, D. Shimosato, R. Yagi, K. Takahashi, H. Okochi, A. Okuda, R. Ma- toba, A. A. Sharov, M. S. H. Ko, and H. Niwa, Nature Cell Biology9, 625 (2007)

    2007

  5. [5]

    Mitsui and et al., Cell113, 631 (2003)

    K. Mitsui and et al., Cell113, 631 (2003). 6

    2003

  6. [6]

    Karwacki-Neisius, J

    V. Karwacki-Neisius, J. G¨ oke, R. Osorno, F. Halbritter, J. H. Ng, A. Y. Weiße, F. C. K. Wong, A. Gagliardi, N. P. Mullin, N. Festuccia, D. Colby, S. R. Tomlinson, H.-H. Ng, and I. Chambers, Cell Stem Cell12, 531 (2013)

    2013

  7. [7]

    Chambers, J

    I. Chambers, J. Silva, D. Colby, J. Nichols, B. Nijmeijer, M. Robertson, J. Vrana, K. Jones, L. Grotewold, and A. Smith, Nature450, 1230 (2007)

    2007

  8. [8]

    K.-J. Choi, M. D. Quan, C. Qi, J.-H. Lee, P. S. Tsoi, M. Zahabiyon, A. Bajic, L. Hu, B. V. V. Prasad, S.-C. J. Liao, W. Li, A. C. M. Ferreon, and J. C. Ferreon, Nature Cell Biology24, 737 (2022)

    2022

  9. [9]

    Boija, I

    A. Boija, I. A. Klein, B. R. Sabari, A. Dall’Agnese, E. L. Coffey, A. V. Zamudio, C. H. Li, K. Shrinivas, J. C. Man- teiga, N. M. Hannett, B. J. Abraham, L. K. Afeyan, Y. E. Guo, J. K. Rimel, C. B. Fant, J. Schuijers, T. I. Lee, D. J. Taatjes, and R. A. Young, Cell175, 1842 (2018)

    2018

  10. [10]

    D. T. McSwiggen, M. Mir, X. Darzacq, and R. Tjian, Genes & development33, 1619 (2019)

    2019

  11. [11]

    Gagliardi, N

    A. Gagliardi, N. P. Mullin, Z. Ying Tan, D. Colby, A. I. Kousa, F. Halbritter, J. T. Weiss, A. Felker, K. Bezs- tarosti, R. Favaro, J. Demmers, S. K. Nicolis, S. R. Tom- linson, R. A. Poot, and I. Chambers, The EMBO Journal 32, 2231 (2013)

    2013

  12. [12]

    Mullin, A

    N. Mullin, A. Yates, A. Rowe, B. Nijmeijer, D. Colby, P. Barlow, M. Walkinshaw, and I. Chambers, Biochemi- cal Journal411, 227 (2008)

    2008

  13. [13]

    J. Wang, D. N. Levasseur, and S. H. Orkin, Proceedings of the National Academy of Sciences of the United States of America105, 6326 (2008)

    2008

  14. [14]

    N. P. Mullin, A. Gagliardi, L. T. P. Khoa, D. Colby, E. Hall-Ponsele, A. J. Rowe, and I. Chambers, Journal of Molecular Biology429, 1544 (2017)

    2017

  15. [15]

    Lopes Novo, C

    C. Lopes Novo, C. Tang, K. Ahmed, U. Djuric, E. Fuss- ner, N. P. Mullin, N. P. Morgan, J. Hayre, A. R. Sienerth, S. Elderkin, R. Nishinakamura, I. Chambers, J. Ellis, D. P. Bazett-Jones, and P. J. Rugg-Gunn, Genes & De- velopment30, 1101 (2016)

    2016

  16. [16]

    Lopes Novo, B.-M

    C. Lopes Novo, B.-M. Javierre, J. Cairns, A. Segonds- Pichon, S. W. Wingett, P. Freire-Pritchett, M. Furlan- Magaril, S. Schoenfelder, P. Fraser, and P. J. Rugg-Gunn, Cell Reports22, 2615 (2018)

    2018

  17. [17]

    de Wit, B

    E. de Wit, B. A. M. Bouwman, Y. Zhu, P. Klous, E. Splinter, M. J. A. M. Verstegen, P. H. L. Krijger, N. Festuccia, E. P. Nora, M. Welling, E. Heard, N. Gei- jsen, R. A. Poot, I. Chambers, and W. de Laat, Nature 501, 227 (2013)

    2013

  18. [18]

    Jawerth, E

    L. Jawerth, E. Fischer-Friedrich, S. Saha, J. Wang, T. Franzmann, X. Zhang, J. Sachweh, M. Ruer, M. Ijavi, S. Saha, J. Mahamid, A. A. Hyman, and F. J¨ ulicher, Science370, 1317 (2020)

    2020

  19. [19]

    Pulupa, N

    J. Pulupa, N. G. McArthur, O. Stathi, M. Wang, M. Za- zhytska, I. D. Pirozzolo, A. Nayar, L. Shapiro, and S. Lomvardas, Nature643, 820 (2025)

    2025

  20. [20]

    Michieletto and M

    D. Michieletto and M. Marenda, JACS Au2, 1506 (2022)

    2022

  21. [21]

    Muzzopappa, M

    F. Muzzopappa, M. Hertzog, and F. Erdel, Biophysical Journal120, 1288 (2021)

    2021

  22. [22]

    Navarro, N

    P. Navarro, N. Festuccia, D. Colby, A. Gagliardi, N. P. Mullin, W. Zhang, V. Karwacki-Neisius, R. Osorno, D. Kelly, M. Robertson, and I. Chambers, The EMBO Journal31, 4547 (2012)

    2012

  23. [23]

    Jauch, C

    R. Jauch, C. K. L. Ng, K. S. Saikatendu, R. C. Stevens, and P. R. Kolatkar, Journal of Molecular Biology376, 758 (2008)

    2008

  24. [24]

    T. G. Mason and D. A. Weitz, Physical Review Letters 74, 1250 (1995)

    1995

  25. [25]

    T. G. Mason, K. Ganesan, J. H. van Zanten, D. Wirtz, and S. C. Kuo, Physical Review Letters79, 3282 (1997)

    1997

  26. [26]

    T. G. Mason, Rheologica Acta39, 371 (2000)

    2000

  27. [27]

    Cicuta and A

    P. Cicuta and A. M. Donald, Soft Matter3, 1449 (2007)

    2007

  28. [28]

    Where the MSD was not scaling linearly with time, we approximated the diffusion coefficient with its upper bound based on the measured MSD

    We tracked trajectories independently in the x and y di- rections and averaged them, so that the MSD is expected to be proportional to 2Dtfor 1D free diffusion. Where the MSD was not scaling linearly with time, we approximated the diffusion coefficient with its upper bound based on the measured MSD

  29. [29]

    See Supplemental Material at [URL] for additional details on simulations and experiments

  30. [30]

    Brizioli, M

    M. Brizioli, M. A. Escobedo-S’anchez, P. M. McCall, Y. Roichman, C. Beck Adiels, G. Volpe, and R. Cerbino, Soft Matter21, 1234 (2025)

    2025

  31. [31]

    J. A. Joseph, A. Reinhardt, A. Aguirre, P. Y. Chew, K. O. Russell, J. R. Espinosa, A. Garaizar, and R. Collepardo-Guevara, Nature Computational Science 1, 732 (2021)

    2021

  32. [32]

    A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolin- tineanu, W. M. Brown, P. S. Crozier, P. J. in ’t Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimp- ton, Comp. Phys. Comm.271, 108171 (2022)

    2022

  33. [33]

    Mizutani, C

    A. Mizutani, C. Tan, Y. Sugita, and S. Takada, PLoS computational biology19, e1011321 (2023)

    2023

  34. [34]

    I. W. Hamley,Introduction to Soft Matter: Synthetic and Biological Self-Assembling Materials, 2nd ed. (John Wi- ley & Sons, 2007)

    2007

  35. [35]

    A. Burt, B. Toader, R. Warshamanage, A. von K¨ ugelgen, E. Pyle, J. Zivanov, D. Kimanius, T. A. M. Bharat, and S. H. W. Scheres, FEBS Open Bio14, 1788 (2024)

    2024

  36. [36]

    X. Zhu, B. Kundukad, and J. R. Van Der Maarel, J. Chem. Phys.129, 1 (2008)

    2008

  37. [37]

    Y. A. G. Fosado, J. Howard, S. Weir, A. Noy, M. C. Leake, and D. Michieletto, Physical Review Letters130, 058203 (2023)

    2023

  38. [38]

    Shin and C

    Y. Shin and C. P. Brangwynne, Science357, eaaf4382 (2017)

    2017

  39. [39]

    Mizutani, C

    A. Mizutani, C. Tan, Y. Sugita, and S. Takada, Biophys- ical journal124, 1587 (2025)

    2025

  40. [40]

    Marenda, D

    M. Marenda, D. Michieletto, R. Czapiewski, J. Stocks, S. M. Winterbourne, J. Miles, O. C. A. Flemming, E. Lazarova, M. Chiang, S. Aitken, G. R. Grimes, H. Becher, A. Cook, D. Marenduzzo, R.-S. Nozawa, and N. Gilbert, bioRxiv 10.1101/2024.06.16.599208 (2024)

    work page doi:10.1101/2024.06.16.599208 2024

  41. [41]

    H. Li, J. L. Dalgleish, G. Lister, M. J. Maristany, J. Huer- tas, A. M. Dopico-Fernandez, J. C. Hamley, N. Denny, G. Bloye, W. Zhang, L. Hentges, R. Doll, Y. Wei, M. Maresca, E. Dimitrova, L. Pytowski, E. A. Tunna- cliffe, M. Kassouf, D. Higgs, E. de Wit, R. J. Klose, C. Schermelleh, R. Collepardo-Guevara, T. A. Milne, and J. O. Davies, Cell186, 4735 (2025)

    2025