SpeciesPrimer: a bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species.

Bioinformatics pipeline Docker container Primer design Primer validation Quantitative real-time polymerase chain reaction Species specific quantification Species specific sequences qPCR primer

Journal

PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425

Informations de publication

Date de publication:
2020
Historique:
received: 10 07 2019
accepted: 10 01 2020
entrez: 29 2 2020
pubmed: 29 2 2020
medline: 29 2 2020
Statut: epublish

Résumé

Quantitative real-time PCR (qPCR) is a well-established method for detecting and quantifying bacteria, and it is progressively replacing culture-based diagnostic methods in food microbiology. High-throughput qPCR using microfluidics brings further advantages by providing faster results, decreasing the costs per sample and reducing errors due to automatic distribution of samples and reagents. In order to develop a high-throughput qPCR approach for the rapid and cost-efficient quantification of microbial species in complex systems such as fermented foods (for instance, cheese), the preliminary setup of qPCR assays working efficiently under identical PCR conditions is required. Identification of target-specific nucleotide sequences and design of specific primers are the most challenging steps in this process. To date, most available tools for primer design require either laborious manual manipulation or high-performance computing systems. We developed the SpeciesPrimer pipeline for automated high-throughput screening of species-specific target regions and the design of dedicated primers. Using SpeciesPrimer, specific primers were designed for four bacterial species of importance in cheese quality control, namely In this work, we present the SpeciesPrimer pipeline, a tool to design species-specific primers for the detection and quantification of bacterial species. We use SpeciesPrimer to design qPCR assays for four bacterial species and describe a workflow to evaluate the designed primers. SpeciesPrimer facilitates efficient primer design for species-specific quantification, paving the way for a fast and accurate quantitative investigation of microbial communities.

Sections du résumé

BACKGROUND BACKGROUND
Quantitative real-time PCR (qPCR) is a well-established method for detecting and quantifying bacteria, and it is progressively replacing culture-based diagnostic methods in food microbiology. High-throughput qPCR using microfluidics brings further advantages by providing faster results, decreasing the costs per sample and reducing errors due to automatic distribution of samples and reagents. In order to develop a high-throughput qPCR approach for the rapid and cost-efficient quantification of microbial species in complex systems such as fermented foods (for instance, cheese), the preliminary setup of qPCR assays working efficiently under identical PCR conditions is required. Identification of target-specific nucleotide sequences and design of specific primers are the most challenging steps in this process. To date, most available tools for primer design require either laborious manual manipulation or high-performance computing systems.
RESULTS RESULTS
We developed the SpeciesPrimer pipeline for automated high-throughput screening of species-specific target regions and the design of dedicated primers. Using SpeciesPrimer, specific primers were designed for four bacterial species of importance in cheese quality control, namely
CONCLUSION CONCLUSIONS
In this work, we present the SpeciesPrimer pipeline, a tool to design species-specific primers for the detection and quantification of bacterial species. We use SpeciesPrimer to design qPCR assays for four bacterial species and describe a workflow to evaluate the designed primers. SpeciesPrimer facilitates efficient primer design for species-specific quantification, paving the way for a fast and accurate quantitative investigation of microbial communities.

Identifiants

pubmed: 32110486
doi: 10.7717/peerj.8544
pii: 8544
pmc: PMC7034379
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e8544

Informations de copyright

©2020 Dreier et al.

Déclaration de conflit d'intérêts

The authors declare there are no competing interests.

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Auteurs

Matthias Dreier (M)

Agroscope, Bern, Switzerland.
Laboratory of Microbiology, University of Neuchâtel, Neuchâtel, Switzerland.

Hélène Berthoud (H)

Agroscope, Bern, Switzerland.

Noam Shani (N)

Agroscope, Bern, Switzerland.

Daniel Wechsler (D)

Agroscope, Bern, Switzerland.

Pilar Junier (P)

Laboratory of Microbiology, University of Neuchâtel, Neuchâtel, Switzerland.

Classifications MeSH