Generating information-dense promoter sequences with optimal string packing.

Autor: Andreani V; Biomedical Engineering Department, Boston University, Boston, Massachusetts, United States of America.; Biological Design Center, Boston University, Boston, Massachusetts, United States of America., South EJ; Biological Design Center, Boston University, Boston, Massachusetts, United States of America.; Molecular Biology, Cell Biology & Biochemistry Program, Boston University, Boston, Massachusetts, United States of America., Dunlop MJ; Biomedical Engineering Department, Boston University, Boston, Massachusetts, United States of America.; Biological Design Center, Boston University, Boston, Massachusetts, United States of America.; Molecular Biology, Cell Biology & Biochemistry Program, Boston University, Boston, Massachusetts, United States of America.
Jazyk: angličtina
Zdroj: PLoS computational biology [PLoS Comput Biol] 2024 Jul 24; Vol. 20 (7), pp. e1012276. Date of Electronic Publication: 2024 Jul 24 (Print Publication: 2024).
DOI: 10.1371/journal.pcbi.1012276
Abstrakt: Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation. Despite the prevalence of overlapping binding sites in nature, rapid design of nucleotide sequences with many overlapping sites remains a challenge. Here, we show that this is an NP-hard problem, coined here as the nucleotide String Packing Problem (SPP). We then introduce a computational technique that efficiently assembles sets of DNA-protein binding sites into dense, contiguous stretches of double-stranded DNA. For the efficient design of nucleotide sequences spanning hundreds of base pairs, we reduce the SPP to an Orienteering Problem with integer distances, and then leverage modern integer linear programming solvers. Our method optimally packs sets of 20-100 binding sites into dense nucleotide arrays of 50-300 base pairs in 0.05-10 seconds. Unlike approximation algorithms or meta-heuristics, our approach finds provably optimal solutions. We demonstrate how our method can generate large sets of diverse sequences suitable for library generation, where the frequency of binding site usage across the returned sequences can be controlled by modulating the objective function. As an example, we then show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The nucleotide string packing approach we present can accelerate the design of sequences with complex DNA-protein interactions. When used in combination with synthesis and high-throughput screening, this design strategy could help interrogate how complex binding site arrangements impact either gene expression or biomolecular mechanisms in varied cellular contexts.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2024 Andreani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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