Evidence map›Paper›PMID 18789148›Full record

ArticleBMC bioinformatics2008

Increasing the efficiency of bacterial transcription simulations: when to exclude the genome without loss of accuracy.

Marco A J Iafolla, Guang Qiang Dong, David R McMillen

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Marco A J IafollaDepartment of Chemical and Physical Sciences and Institute for Optical Sciences, University of Toronto Mississauga, 3359 Mississauga Rd N, Mississauga, ON, L5L 1C6, Canada. marco.iafolla@gmail.com
Guang Qiang Dong
David R McMillen
University of Toronto · CACollege of Family Physicians of Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSimulating the major molecular events inside an Escherichia coli cell can lead to a very large number of reactions that compose its overall behaviour. Not only should the model be accurate, but it is imperative for the experimenter to create an efficient model to obtain the results in a timely fashion. Here, we show that for many parameter regimes, the effect of the host cell genome on the transcription of a gene from a plasmid-borne promoter is negligible, allowing one to simulate the system more efficiently by removing the computational load associated with representing the presence of the rest of the genome. The key parameter is the on-rate of RNAP binding to the promoter (k_on), and we compare the total number of transcripts produced from a plasmid vector generated as a function of this rate constant, for two versions of our gene expression model, one incorporating the host cell genome and one excluding it. By sweeping parameters, we identify the k_on range for which the difference between the genome and no-genome models drops below 5%, over a wide range of doubling times, mRNA degradation rates, plasmid copy numbers, and gene lengths.

resultsWe assess the effect of the simulating the presence of the genome over a four-dimensional parameter space, considering: 24 min<or=bacterial doubling time<or=100 min; 10<or=plasmid copy number<or=1000; 2 min<or=mRNA half-life<or=14 min; and 10 bp<or=gene length<or=10000 bp. A simple MATLAB user interface generates an interpolated k_on threshold for any point in this range; this rate can be compared to the ones used in other transcription studies to assess the need for including the genome.

conclusionExclusion of the genome is shown to yield less than 5% difference in transcript numbers over wide ranges of values, and computational speed is improved by two to 24 times by excluding explicit representation of the genome.

Indexed as

AlgorithmsBase SequenceChromosome MappingEscherichia coliGenome, BacterialMolecular Sequence DataReproducibility of ResultsSensitivity and SpecificitySequence Analysis, DNATranscription FactorsTranscription Factors

Identifiers

PMID18789148
PMCPMC2543029
OpenAlexW2000165838

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.