Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Modelling chromosome-wide target search
Umeå University, Faculty of Science and Technology, Department of Physics. Integrated Science Lab, Umeå University, Sweden.ORCID iD: 0000-0002-3315-0633
Umeå University, Faculty of Science and Technology, Department of Physics. Integrated Science Lab, Umeå University, Sweden.ORCID iD: 0000-0003-3174-8145
2023 (English)In: New Journal of Physics, E-ISSN 1367-2630, Vol. 25, no 3, article id 033024Article in journal (Refereed) Published
Abstract [en]

The most common gene regulation mechanism is when a transcription factor (TF) protein binds to a regulatory sequence to increase or decrease RNA transcription. However, TFs face two main challenges when searching for these sequences. First, the sequences are vanishingly short relative to the genome length. Second, there are many nearly identical sequences scattered across the genome, causing proteins to suspend the search. But as pointed out in a computational study of LacI regulation in Escherichia coli, such almost-targets may lower search times if considering DNA looping. In this paper, we explore if this also occurs over chromosome-wide distances. To this end, we developed a cross-scale computational framework that combines established facilitated-diffusion models for basepair-level search and a network model capturing chromosome-wide leaps. To make our model realistic, we used Hi-C data sets as a proxy for 3D proximity between long-ranged DNA segments and binding profiles for more than 100 TFs. Using our cross-scale model, we found that median search times to individual targets critically depend on a network metric combining node strength (sum of link weights) and local dissociation rates. Also, by randomizing these rates, we found that some actual 3D target configurations stand out as considerably faster or slower than their random counterparts. This finding hints that chromosomes’ 3D structure funnels essential TFs to relevant DNA regions.

Place, publisher, year, edition, pages
Institute of Physics (IOP), 2023. Vol. 25, no 3, article id 033024
Keywords [en]
chromosome 3D folding, diffusion on networks, DNA target-search, gene regulation, Hi-C data, stochastic simulations
National Category
Bioinformatics and Computational Biology
Identifiers
URN: urn:nbn:se:umu:diva-206375DOI: 10.1088/1367-2630/acc127ISI: 000951783900001Scopus ID: 2-s2.0-85150899174OAI: oai:DiVA.org:umu-206375DiVA, id: diva2:1748730
Funder
Swedish Research Council, 2017-03848Swedish Research Council, 2018-05973Available from: 2023-04-04 Created: 2023-04-04 Last updated: 2025-02-07Bibliographically approved
In thesis
1. Finding a target on DNA: interplay between the genomic sequence and 3D structure
Open this publication in new window or tab >>Finding a target on DNA: interplay between the genomic sequence and 3D structure
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Att hitta ett mål på DNA : samspelet mellan den genomiska sekvensen och 3D-strukturen
Abstract [en]

Cells are complex systems of interconnected machinery that maintain, repairs and furthers the growth of themselves. In the centre lies the instructions that coordinate it all — the DNA. This meter-long string of code carries the instructions that coordinate cell life, from basic maintenance to the specific function of the cell in the body.

These instructions are constantly used by different protein complexes, but the mechanisms behind several details of these processes are still not understood. For example — the size of a specific set of instructions on the DNA is a mere fraction of the whole genome — how can these instructions be quickly found, and how can the complexes know it found the right set of instructions? Is this search problem related to how DNA is folded and stored in our cell nucleus? These questions are further complicated by the fact that different cell types only use specific instructions, which can change as the cell is affected by, for example, external forces. How can the DNA control which instruction set is available, and how does this affect the other questions we just asked?

These are some questions this thesis tackles. To take a step towards a better mechanistic understanding, this thesis combines data from biology and methods from physics to formulate computational and analytic models to understand the mechanical principles of DNA folding, as well as protein search and binding. This entails finding new hierarchical clusters in DNA, proposing explanations for discrepancies in DNA regulation, connecting sequence specificity with DNA folding and investigating how multiple cooperating parts complicate the DNA search problem.

We find that we can improve our tools to better understand the data we base our models on, and that sequence specificity and folding connects in intricate ways, giving us a more complete view of cellular function.

Abstract [sv]

Celler består av sammanflätade maskinerier som underhåller, reparerar och främjar tillväxten av sig själva. Centralt ligger instruktionerna som samordnar allt — DNA. Denna meterlånga kodsträng är instruktionerna som samordnar cellens liv, allt från enkelt underhåll till cellens specifika funktion i kroppen.

Dessa instruktioner används ständigt av olika proteinkomplex, men vi saknar fortfarande detaljerad förståelse om flera mekanismer bakom dessa processer. Till exempel så är längden av en specifik uppsättning instruktioner på DNA:t endast en bråkdel av hela genomet — hur kan dessa instruktioner hittas snabbt, och hur vet komplexen att de har hittat rätt instruktioner? Är detta sökproblem relaterat till hur DNA veckas och lagras i vår cellkärna? Dessa frågor kompliceras ytterligare av att olika celltyper bara använder vissa instruktioner, som kan ändras när cellen påverkas av till exempel externa påfrestningar. Hur kan DNA:t bestämma vilken uppsättning instruktioner som används, och hur påverkar det de andra frågorna vi ställde tidigare?

Detta är några av de frågor denna avhandling fokuserar på. För att uppnå en bättre mekanistisk förståelse kombinerar denna avhandling data från biologin och metoder från fysik för att formulera beräknings- och analysmodeller för att förstå de mekanistiska principerna bakom DNA-veckning samt proteinsökning och bindning. Detta innefattar att hitta nya hierarkiska kluster i DNA, föreslå alternativa förklaringar till avvikelser i DNA-reglering, koppla samman sekvenskänslighet med DNA-veckning och undersöka hur samverkande komponenter komplicerar DNA-sökningsproblemet.

Vi finner att vi kan förbättra våra verktyg för att bättre förstå det data som vi baserar våra modeller på, samt att sekvensspecificitet och veckning bör kombineras för att bättre förstå mekanismerna i cellen.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2024. p. 69
Keywords
search processes, stochastic simulations, DNA, network science, gene regulation, target-finding problems
National Category
Physical Sciences Biophysics
Research subject
Physical Biology; Physics
Identifiers
urn:nbn:se:umu:diva-231571 (URN)978-91-8070-518-9 (ISBN)978-91-8070-517-2 (ISBN)
Public defence
2024-12-06, NAT.D.450, Naturvetarhuset, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2024-11-15 Created: 2024-11-11 Last updated: 2025-02-20Bibliographically approved

Open Access in DiVA

fulltext(2146 kB)229 downloads
File information
File name FULLTEXT01.pdfFile size 2146 kBChecksum SHA-512
7ea7be81b0049287ea41b6b2feee3deee6075f81ed763bf18eacb76fe9ad84441cc4dabc27d4454a7f53daa23800af99c6be401bce6db2b82a2143ebc462f542
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Hedström, LucasLizana, Ludvig

Search in DiVA

By author/editor
Hedström, LucasLizana, Ludvig
By organisation
Department of Physics
In the same journal
New Journal of Physics
Bioinformatics and Computational Biology

Search outside of DiVA

GoogleGoogle Scholar
Total: 229 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 357 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf