Evidence map›Paper›PMID 36840589›Full record

ArticleJournal of clinical microbiology2023

Multicenter Preparedness Exercise Enables Rapid Development of Cluster-Specific PCR-Based Screening Assays from Bacterial Genomic Data.

Janina Treffon, Karola Prior, Johannes Dreesman, Richard Egelkamp, Antje Flieger, Barbara Middendorf-Bauchart, Michaela Projahn, Anne Richter, Elisabeth Schuh, Dag Harmsen and 1 more

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Journal of clinical microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 43% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 country.

Janina TreffonInstitute of Hygiene, University Hospital Münster, Münster, Germany.
Karola PriorDepartment of Periodontology and Operative Dentistry, University Hospital Münster, Münster, Germany.
Johannes DreesmanDepartment of Microbiology, Infection Protection, Hospital Hygiene, and Infection Epidemiology, Public Health Agency of Lower Saxony, Hannover, Germany.
Richard EgelkampDepartment of Microbiology, Infection Protection, Hospital Hygiene, and Infection Epidemiology, Public Health Agency of Lower Saxony, Hannover, Germany.
Antje FliegerDepartment of Enteropathogenic Bacteria and Legionella, National Reference Center for Salmonella and other Bacterial Enteric Pathogens, Robert Koch Institute, Wernigerode, Germany.ORCID 0000-0003-3819-2979
Barbara Middendorf-BauchartInstitute of Hygiene, University Hospital Münster, Münster, Germany.
Michaela ProjahnDepartment of Biological Safety, National Reference Laboratory for Escherichia coli Including VTEC, German Federal Institute for Risk Assessment, Berlin, Germany.ORCID 0000-0002-3896-3561
Anne RichterDepartment of Enteropathogenic Bacteria and Legionella, National Reference Center for Salmonella and other Bacterial Enteric Pathogens, Robert Koch Institute, Wernigerode, Germany.
Elisabeth SchuhDepartment of Biological Safety, National Reference Laboratory for Escherichia coli Including VTEC, German Federal Institute for Risk Assessment, Berlin, Germany.
Dag Harmsen *Department of Periodontology and Operative Dentistry, University Hospital Münster, Münster, Germany.
Alexander Mellmann *Institute of Hygiene, University Hospital Münster, Münster, Germany.ORCID 0000-0002-0649-5185
University Hospital Münster · DEFederal Institute for Risk Assessment · DERobert Koch Institute · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PCR-based screening assays targeting strain-specific genetic markers allow the timely detection and specific differentiation of bacterial strains. Especially in situations where an infection cluster occurs, fast assay development is crucial for supporting targeted control measures. However, the turnaround times (TATs) for assay setup may be high due to insufficient knowledge about screening assay methods, workflows, and software tools. Here, two blind-coded and quality-controlled ring trials were performed in which five German laboratories established PCR-based screening assays from genomic data that specifically target selected bacterial clusters within two bacterial monospecies sample panels. While the first ring trial was conducted without a time limit to train the participants and assess assay feasibility, in the second ring trial, a challenging time limit of 2 weeks was set to force fast assay development as soon as genomic data were available. During both ring trials, we detected high interlaboratory variability regarding the screening assay methods and targets, the TATs for assay setup, and the number of screening assays. The participants designed between one and four assays per cluster that targeted cluster-specific unique genetic sequences, genes, or single nucleotide variants using conventional PCRs, high-resolution melting assays, or TaqMan PCRs. Assays were established within the 2-week time limit, with TATs ranging from 4 to 13 days. TaqMan probe delivery times strongly influenced TATs. In summary, we demonstrate that a specific exercise improved the preparedness to develop functional cluster-specific PCR-based screening assays from bacterial genomic data. Furthermore, the parallel development of several assays enhances assay availability.

Indexed as

BacteriaGenome, BacterialGenomicsHumansPolymerase Chain Reactionbacterial clusterPCRring trialscreening assaywhole-genome sequencing

Identifiers

PMID36840589
PMCPMC10035311
OpenAlexW4321493425

What OpenQuestion holds

Textmetadata
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.