Evidence map›Paper›PMID 36937816›Full record

ArticleMethodsX2023

Development of a robust and quantitative high-throughput screening method for assessing phenotypic variation in large

Robeena Farzand, Megan De Ste Croix, Neelam Dave, Christopher D Bayliss

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Article in MethodsX, 2023. 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.

Robeena FarzandDepartment of Genetics and Genome Biology, University of Leicester, United Kingdom.
Megan De Ste CroixDepartment of Genetics and Genome Biology, University of Leicester, United Kingdom.
Neelam DaveDepartment of Genetics and Genome Biology, University of Leicester, United Kingdom.
Christopher D BaylissDepartment of Genetics and Genome Biology, University of Leicester, United Kingdom.

Funding

Medical Research Council MR/S009264/1
6 · The paper itself

Abstract

Genome-wide association studies are a powerful approach for identifying determinants of disease. For infectious diseases, high throughput assays are required for measuring the variance in multiple virulence-related phenotypes of large bacterial isolate collections and for association of this phenotypic variance with genotype. The primary limiting factors are cost, effectiveness and a standardized inoculum. A method was developed to create an inoculum array of multiple isolates that could be used for a series of high-throughput multi-isolate phenotypic investigations in a laboratory setting. A key starting point was the standardisation of the inoculum by production of identical batches of each isolate from cells grown to mid-log phase. Cultures with pre-determined optical densities were aliquoted in set patterns into multiple multi-well plates containing 50% glycerol and stored at -80 °C. Prior to a specific assay, an inoculum plate was defrosted and subjected to a brief period of incubation. Control strains can be placed on each plate in order to control for intra-assay variability. A high throughput screen is described in detail for quantification of biofilm formation. This example utilised the crystal violet staining method and multi-assay stock plates containing 16 meningococcal isolates.•Multi-assay stock plate of exponentially growing isolates is cost-effective and simple to implement in a laboratory setting.•This method would predict realistic standard deviations for multiple isolates in phenotypic assays and generate data for performance of power calculations for genotyping.•This method has the potential to identify both known and unknown genetic determinants of phenotypic variability for each tested isolate when paired with genetic analysis of whole genome sequencing data.

Indexed as

High-throughputHigh-throughput phenotypic screening method for assessing phenotypic variationMeningococcusMulti-assay stockNeisseria meningitidisPhenotypic screening

Identifiers

PMID36937816
PMCPMC10020651

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read35
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.