Evidence map›Paper›PMID 30043772›Full record

ArticleThe Analyst2018

Pathogen-specific DNA sensing with engineered zinc finger proteins immobilized on a polymer chip.

Dat Thinh Ha, Sthitodhi Ghosh, Chong H Ahn, David J Segal, Moon-Soo Kim

Abstract read
In one paragraph

Article in The Analyst, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

3 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
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

5 authors at 3 institutions in 1 country.

Dat Thinh HaDepartment of Chemistry, Western Kentucky University, Bowling Green, Kentucky 42101, USA. moon-soo.kim@wku.edu.
Sthitodhi Ghosh
Chong H Ahn
David J Segal
Moon-Soo Kim
Bowling Green State University · USOracle (United States) · USUniversity of California System · US

Funding

WKU Lead Faculty AwardP20GM103436 · NIGMS · UNIVERSITY OF LOUISVILLE · PI ERIC C ROUCHKA · 2012 to 2026
$60.1M
NIGMS NIH HHS P20 GM103436
6 · The paper itself

Abstract

A specific double-stranded DNA sensing system is of great interest for diagnostic and other biomedical applications. Zinc finger domains, which recognize double-stranded DNA, can be engineered to form custom DNA-binding proteins for the recognition of specific DNA sequences. As a proof of concept, a sequence-enabled reassembly of a TEM-1 β-lactamase system (SEER-LAC) was previously demonstrated to develop zinc finger protein (ZFP) arrays for the detection of a double-stranded bacterial DNA sequence. Here, we implemented the SEER-LAC system to demonstrate the direct detection of pathogen-specific DNA sequences present in E. coli O157:H7 on a lab-on-a-chip. ZFPs custom-designed to detect Shiga toxin in E. coli O157:H7 were immobilized on a cyclic olefin copolymer (COC) chip, which can function as a non-PCR based molecular diagnostic device. Pathogen-specific double-stranded DNA was directly detected by using engineered ZFPs immobilized on the COC chip with high specificity, providing a detection limit of 10 fmol of target DNA in a colorimetric assay. Therefore, in this study, we demonstrated the great potential of ZFP arrays on the COC chip for further development of a simple and novel lab-on-a-chip technology for the detection of pathogens.

Indexed as

Zinc FingersDNA, BacterialDNA-Binding ProteinsEscherichia coli O157Immobilized ProteinsLab-On-A-Chip DevicesPolymersProtein EngineeringSensitivity and SpecificityDNA, BacterialDNA-Binding ProteinsImmobilized ProteinsPolymers

Identifiers

PMID30043772
PMCPMC6239418
OpenAlexW2832688453

What OpenQuestion holds

Textmetadata
LicenceTDM
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.