Evidence map›Paper›PMID 31138090›Full record

ArticleJournal of the Royal Society, Interface2019

A mathematical model for a biphasic DNA amplification reaction.

Danielle Ciesielski, Burcu Özay, Stephanie McCalla, Tomas Gedeon

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Danielle Ciesielski1 Department of Mathematical Sciences, Montana State University , Bozeman, MT 59715 , USA.
Burcu Özay2 Department of Chemical and Biological Engineering, Montana State University , Bozeman, MT 59715 , USA.
Stephanie McCalla2 Department of Chemical and Biological Engineering, Montana State University , Bozeman, MT 59715 , USA.
Tomas Gedeon1 Department of Mathematical Sciences, Montana State University , Bozeman, MT 59715 , USA.

Funding

Needle in a haystack: effective search for dynamics across the space of networksR01GM126555 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI MISCHAIKOW, KONSTANTIN · 2017 to 2021
$1.8M
NIGMS NIH HHS R01 GM126555
6 · The paper itself

Abstract

Isothermal DNA amplification reactions are a prevalent tool with many applications, ranging from analyte detection to DNA circuits. Exponential amplification reaction (EXPAR) is a popular isothermal DNA amplification method that exponentially amplifies short DNA oligonucleotides. A recent modification of this technique using an energetically stable looped template with palindromic binding regions demonstrated unexpected biphasic amplification and much higher DNA yield than EXPAR. This ultrasensitive DNA amplification reaction (UDAR) shows high-gain, switch-like DNA output from low concentrations of DNA input. Here we present the first mathematical model of UDAR based on four reaction mechanisms and show the model can reproduce the experimentally observed biphasic behaviour. Furthermore, we show that three of these mechanisms are necessary to reproduce biphasic experimental results. The reaction mechanisms are (i) positively cooperative multistep binding spurred by two trigger binding sites on the template; (ii) gradual template deactivation; (iii) recycling of deactivated templates into active templates; and (iv) polymerase sequestration. These mechanisms can potentially illuminate the behaviour of EXPAR as well as other nucleic acid amplification reactions.

Indexed as

Models, ChemicalNucleic Acid Amplification TechniquesDNADNAbiochemical networkbiphasicDNA amplificationkinetic model

Identifiers

PMID31138090
PMCPMC6544893

What OpenQuestion holds

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Registered trials

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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.