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Hilbert, L.* ; Gadzekpo, A.* ; Vecchio, S.L.* ; Wellhäusser, M.* ; Tschurikow, X.* ; Prizak, R.* ; Becker, B.* ; Burghart, S.* ; Oprzeska-Zingrebe, E.A.*

Chromatin-associated condensates as an inspiration for the system architecture of future DNA computers.

Ann. NY Acad. Sci., DOI: 10.1111/nyas.15415 (2025)
Verlagsversion DOI
Open Access Hybrid
The genome stores and processes approximately 1.5 gigabytes of encoded information. In this article, we propose that the eukaryotic genome and its adaptable three-dimensional packing in the form of chromatin offer a valuable template for the system architecture of DNA-based digital computers. We examine embryonic and stem cells, which exhibit distinct chromatin-associated condensates enriched in transcription machinery. These dynamic biomolecular condensates facilitate the spatial association of genes, genomic control elements, and molecular machinery responsible for reading the genomic code. Drawing a compelling analogy to the von Neumann computer architecture—which integrates storage, processing, and memory in most electronic computers—we reflect on how the operational principles of these condensates could inspire the design of a similar architecture for future DNA computers. In particular, we describe how one could recreate such an architecture by exploiting the process of surface condensation, which underlies the formation of chromatin-associated condensates. We conclude by reviewing our initial steps of constructing synthetic DNA nanostructures that follow the same operational principles and enable programmable surface condensation. Finally, we outline how computational methods from accelerated materials design could further advance the development of DNA computer system architectures.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter 3d Genome Organization ; Architecture Of The Cell Nucleus ; Biological Phase Separation ; Dna Nanotechnology ; Synthetic Biology
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 0077-8923
e-ISSN 1749-6632
Zeitschrift Annals of the New York Academy of Sciences
Verlag New York Academy of Sciences
Begutachtungsstatus Peer reviewed
Institut(e) Helmholtz AI - KIT (HAI - KIT)
DOI 10.1111/nyas.15415
Scopus ID 105015405003
Erfassungsdatum 2025-09-21
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