Journal article
spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes
Nucleic acids research, Vol.51(17), e92
09/22/2023
DOI: 10.1093/nar/gkad682
PMCID: PMC10516669
PMID: 37602419
Abstract
Stochastic simulation models have played an important role in efforts to understand the mechanistic basis of prokaryotic transcription and translation. Despite the fundamental linkage of these processes in bacterial cells, however, most simulation models have been limited to representations of either transcription or translation. In addition, the available simulation models typically either attempt to recapitulate data from single-molecule experiments without considering cellular-scale high-throughput sequencing data or, conversely, seek to reproduce cellular-scale data without paying close attention to many of the mechanistic details. To address these limitations, we here present spotter (Simulation of Prokaryotic Operon Transcription & Translation Elongation Reactions), a flexible, user-friendly simulation model that offers highly-detailed combined representations of prokaryotic transcription, translation, and DNA supercoiling. In incorporating nascent transcript and ribosomal profiling sequencing data, spotter provides a critical bridge between data collected in single-molecule experiments and data collected at the cellular scale. Importantly, in addition to rapidly generating output that can be aggregated for comparison with next-generation sequencing and proteomics data, spotter produces residue-level positional information that can be used to visualize individual simulation trajectories in detail. We anticipate that spotter will be a useful tool in exploring the interplay of processes that are crucially linked in prokaryotes.
Details
- Title: Subtitle
- spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes
- Creators
- William C Hacker - University of IowaAdrian H Elcock - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Nucleic acids research, Vol.51(17), e92
- DOI
- 10.1093/nar/gkad682
- PMID
- 37602419
- PMCID
- PMC10516669
- eISSN
- 1362-4962
- Grant note
- DOI: 10.13039/100000002, name: National Institutes of Health, award: R35 GM122466
- Language
- English
- Electronic publication date
- 08/21/2023
- Date published
- 09/22/2023
- Academic Unit
- Physics and Astronomy; Biochemistry and Molecular Biology
- Record Identifier
- 9984456077702771
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