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barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection
BACKGROUND: Tracking dispersal of microbial populations in the environment requires specific detection methods that discriminate between the target strain and all potential natural and artificial interferents, including previously utilized tester strains. Recent work has shown that genomic insertion...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919090/ https://www.ncbi.nlm.nih.gov/pubmed/33648451 http://dx.doi.org/10.1186/s12859-021-04019-5 |
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author | Bernhards, Casey B. Lux, Matthew W. Katoski, Sarah E. Goralski, Tyler D. P. Liem, Alvin T. Gibbons, Henry S. |
author_facet | Bernhards, Casey B. Lux, Matthew W. Katoski, Sarah E. Goralski, Tyler D. P. Liem, Alvin T. Gibbons, Henry S. |
author_sort | Bernhards, Casey B. |
collection | PubMed |
description | BACKGROUND: Tracking dispersal of microbial populations in the environment requires specific detection methods that discriminate between the target strain and all potential natural and artificial interferents, including previously utilized tester strains. Recent work has shown that genomic insertion of short identification tags, called “barcodes” here, allows detection of chromosomally tagged strains by real-time PCR. Manual design of these barcodes is feasible for small sets, but expansion of the technique to larger pools of distinct and well-functioning assays would be significantly aided by software-guided design. RESULTS: Here we introduce barCoder, a bioinformatics tool that facilitates the process of creating sets of uniquely identifiable barcoded strains. barCoder utilizes the genomic sequence of the target strain and a set of user-specified PCR parameters to generate a list of suggested barcode “modules” that consist of binding sites for primers and probes, and appropriate spacer sequences. Each module is designed to yield optimal PCR amplification and unique identification. Optimal amplification includes metrics such as ideal melting temperature and G+C content, appropriate spacing, and minimal stem-loop formation; unique identification includes low BLAST hits against the target organism, previously generated barcode modules, and databases (such as NCBI). We tested the ability of our algorithm to suggest appropriate barcodes by generating 12 modules for Bacillus thuringiensis serovar kurstaki—a simulant for the potential biowarfare agent Bacillus anthracis—and three each for other potential target organisms with variable G+C content. Real-time PCR detection assays directed at barcodes were specific and yielded minimal cross-reactivity with a panel of near-neighbor and potential contaminant materials. CONCLUSIONS: The barCoder algorithm facilitates the generation of synthetically barcoded biological simulants by (a) eliminating the task of creating modules by hand, (b) minimizing optimization of PCR assays, and (c) reducing effort wasted on non-unique barcode modules. |
format | Online Article Text |
id | pubmed-7919090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79190902021-03-02 barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection Bernhards, Casey B. Lux, Matthew W. Katoski, Sarah E. Goralski, Tyler D. P. Liem, Alvin T. Gibbons, Henry S. BMC Bioinformatics Methodology Article BACKGROUND: Tracking dispersal of microbial populations in the environment requires specific detection methods that discriminate between the target strain and all potential natural and artificial interferents, including previously utilized tester strains. Recent work has shown that genomic insertion of short identification tags, called “barcodes” here, allows detection of chromosomally tagged strains by real-time PCR. Manual design of these barcodes is feasible for small sets, but expansion of the technique to larger pools of distinct and well-functioning assays would be significantly aided by software-guided design. RESULTS: Here we introduce barCoder, a bioinformatics tool that facilitates the process of creating sets of uniquely identifiable barcoded strains. barCoder utilizes the genomic sequence of the target strain and a set of user-specified PCR parameters to generate a list of suggested barcode “modules” that consist of binding sites for primers and probes, and appropriate spacer sequences. Each module is designed to yield optimal PCR amplification and unique identification. Optimal amplification includes metrics such as ideal melting temperature and G+C content, appropriate spacing, and minimal stem-loop formation; unique identification includes low BLAST hits against the target organism, previously generated barcode modules, and databases (such as NCBI). We tested the ability of our algorithm to suggest appropriate barcodes by generating 12 modules for Bacillus thuringiensis serovar kurstaki—a simulant for the potential biowarfare agent Bacillus anthracis—and three each for other potential target organisms with variable G+C content. Real-time PCR detection assays directed at barcodes were specific and yielded minimal cross-reactivity with a panel of near-neighbor and potential contaminant materials. CONCLUSIONS: The barCoder algorithm facilitates the generation of synthetically barcoded biological simulants by (a) eliminating the task of creating modules by hand, (b) minimizing optimization of PCR assays, and (c) reducing effort wasted on non-unique barcode modules. BioMed Central 2021-03-01 /pmc/articles/PMC7919090/ /pubmed/33648451 http://dx.doi.org/10.1186/s12859-021-04019-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Bernhards, Casey B. Lux, Matthew W. Katoski, Sarah E. Goralski, Tyler D. P. Liem, Alvin T. Gibbons, Henry S. barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection |
title | barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection |
title_full | barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection |
title_fullStr | barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection |
title_full_unstemmed | barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection |
title_short | barCoder: a tool to generate unique, orthogonal genetic tags for qPCR detection |
title_sort | barcoder: a tool to generate unique, orthogonal genetic tags for qpcr detection |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919090/ https://www.ncbi.nlm.nih.gov/pubmed/33648451 http://dx.doi.org/10.1186/s12859-021-04019-5 |
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