Evidence map›Paper›PMID 28438642›Full record

ArticleJournal of microbiological methods2017

Diagnostic microarray for 14 water and foodborne pathogens using a flatbed scanner.

Vidya Srinivasan, Robert D Stedtfeld, Dieter M Tourlousse, Samuel W Baushke, Yu Xin, Sarah M Miller, Trinh Pham, Jean-Marie Rouillard, Erdogan Gulari, James M Tiedje and 1 more

Open access · greenAbstract readValidation Study
In one paragraph

Article in Journal of microbiological methods, 2017. 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
0.3field-weighted citation impact, top 41% 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, 7 citations in OpenAlex.

  1. Article
  2. Disposable microfluidic micromixers for effective capture ofJournal of biological engineering · 2018
    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

11 authors at 3 institutions in 2 countries.

Vidya SrinivasanDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Robert D StedtfeldDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Dieter M TourlousseDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Samuel W BaushkeDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Yu XinDepartment of Environmental Engineering, Nanjing University, China.
Sarah M MillerDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Trinh PhamDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, United States.
Jean-Marie RouillardDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, United States.
Erdogan GulariDepartment of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, United States.
James M TiedjeDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States.
Syed A HashshamDepartment of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, United States. Electronic address: hashsham@egr.msu.edu.
Michigan State University · USUniversity of Michigan–Ann Arbor · USNanjing University · CN

Funding

Flexible Biochip for Highly Parallel Microbial DetectionR01RR018625 · NCRR · MICHIGAN STATE UNIVERSITY · PI HASHSHAM, SYED A. · 2003 to 2005
$1.4M
NCRR NIH HHS R01 RR018625
6 · The paper itself

Abstract

Parallel detection approaches are of interest to many researchers interested in identifying multiple water and foodborne pathogens simultaneously. Availability and cost-effectiveness are two key factors determining the usefulness of such approaches for laboratories with limited resources. In this study, we developed and validated a high-density microarray for simultaneous screening of 14 bacterial pathogens using an approach that employs gold labeling with silver enhancement (GLS) protocol. In total, 8887 probes (50-mer) were designed using an in-house database of virulence and marker genes (VMGs), and synthesized in quadruplicate on glass slides using an in-situ synthesis technology. Target VMG amplicons were obtained using multiplex polymerase chain reaction (PCR), labeled with biotin, and hybridized to the microarray. The signals generated after gold deposition and silver enhancement, were quantified using a flatbed scanner having 2-μm resolution. Data analysis indicated that reliable presence/absence calls could be made, if: i) over four probes were used per gene, ii) the signal-to-noise ratio (SNR) cutoff was greater than or equal to two, and iii) the positive fraction (PF), i.e., number of probes with SNR≥2 for a given VMG was greater than 0.75. Hybridization of the array with blind samples resulted in 100% correct calls, and no false positive. Because amplicons were obtained by multiplex PCR, sensitivity of this method is similar to PCR. This assay is an inexpensive and reliable technique for high throughput screening of multiple pathogens.

Indexed as

Food MicrobiologyOligonucleotide Array Sequence AnalysisWater MicrobiologyBacteriaGoldImage Processing, Computer-AssistedMultiplex Polymerase Chain ReactionNucleic Acid HybridizationOligonucleotide ProbesSalmonellaShigellaSilverYersiniaGoldOligonucleotide ProbesSilverGold labeling and silver enhancementLow cost microarrayVirulence and marker genesWaterborne pathogens

Identifiers

PMID28438642
PMCPMC5491306
OpenAlexW2606097644

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.