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CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification
Cryptosporidium is a protozoan parasite that is transmitted to both humans and animals through zoonotic or anthroponotic means. When a host is infected with this parasite, it causes a gastrointestinal disease known as cryptosporidiosis. To understand the transmission dynamics of Cryptosporidium, the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966988/ https://www.ncbi.nlm.nih.gov/pubmed/33748443 http://dx.doi.org/10.1016/j.fawpar.2021.e00115 |
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author | Yanta, Christine A. Bessonov, Kyrylo Robinson, Guy Troell, Karin Guy, Rebecca A. |
author_facet | Yanta, Christine A. Bessonov, Kyrylo Robinson, Guy Troell, Karin Guy, Rebecca A. |
author_sort | Yanta, Christine A. |
collection | PubMed |
description | Cryptosporidium is a protozoan parasite that is transmitted to both humans and animals through zoonotic or anthroponotic means. When a host is infected with this parasite, it causes a gastrointestinal disease known as cryptosporidiosis. To understand the transmission dynamics of Cryptosporidium, the small subunit (SSU or 18S) rRNA and gp60 genes are commonly studied through PCR analysis and conventional Sanger sequencing. However, analyzing sequence chromatograms manually is both time consuming and prone to human error, especially in the presence of poorly resolved, heterozygous peaks and the absence of a validated database. For this study, we developed a Cryptosporidium genotyping tool, called CryptoGenotyper, which has the capability to read raw Sanger sequencing data for the two common Cryptosporidium gene targets (SSU rRNA and gp60) and classify the sequence data into standard nomenclature. The CryptoGenotyper has the capacity to perform quality control and properly classify sequences using a high quality, manually curated reference database, saving users' time and removing bias during data analysis. The incorporated heterozygous base calling algorithms for the SSU rRNA gene target resolves double peaks, therefore recovering data previously classified as inconclusive. The CryptoGenotyper successfully genotyped 99.3% (428/431) and 95.1% (154/162) of SSU rRNA chromatograms containing single and mixed sequences, respectively, and correctly subtyped 95.6% (947/991) of gp60 chromatograms without manual intervention. This new, user-friendly tool can provide both fast and reproducible analyses of Sanger sequencing data for the two most common Cryptosporidium gene targets. |
format | Online Article Text |
id | pubmed-7966988 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-79669882021-03-19 CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification Yanta, Christine A. Bessonov, Kyrylo Robinson, Guy Troell, Karin Guy, Rebecca A. Food Waterborne Parasitol Special issue: Protozoa molecular tool Cryptosporidium is a protozoan parasite that is transmitted to both humans and animals through zoonotic or anthroponotic means. When a host is infected with this parasite, it causes a gastrointestinal disease known as cryptosporidiosis. To understand the transmission dynamics of Cryptosporidium, the small subunit (SSU or 18S) rRNA and gp60 genes are commonly studied through PCR analysis and conventional Sanger sequencing. However, analyzing sequence chromatograms manually is both time consuming and prone to human error, especially in the presence of poorly resolved, heterozygous peaks and the absence of a validated database. For this study, we developed a Cryptosporidium genotyping tool, called CryptoGenotyper, which has the capability to read raw Sanger sequencing data for the two common Cryptosporidium gene targets (SSU rRNA and gp60) and classify the sequence data into standard nomenclature. The CryptoGenotyper has the capacity to perform quality control and properly classify sequences using a high quality, manually curated reference database, saving users' time and removing bias during data analysis. The incorporated heterozygous base calling algorithms for the SSU rRNA gene target resolves double peaks, therefore recovering data previously classified as inconclusive. The CryptoGenotyper successfully genotyped 99.3% (428/431) and 95.1% (154/162) of SSU rRNA chromatograms containing single and mixed sequences, respectively, and correctly subtyped 95.6% (947/991) of gp60 chromatograms without manual intervention. This new, user-friendly tool can provide both fast and reproducible analyses of Sanger sequencing data for the two most common Cryptosporidium gene targets. Elsevier 2021-02-26 /pmc/articles/PMC7966988/ /pubmed/33748443 http://dx.doi.org/10.1016/j.fawpar.2021.e00115 Text en Crown Copyright © 2021 Published by Elsevier Inc. on behalf of International Association of Food and Waterborne Parasitology. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Special issue: Protozoa molecular tool Yanta, Christine A. Bessonov, Kyrylo Robinson, Guy Troell, Karin Guy, Rebecca A. CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification |
title | CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification |
title_full | CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification |
title_fullStr | CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification |
title_full_unstemmed | CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification |
title_short | CryptoGenotyper: A new bioinformatics tool for rapid Cryptosporidium identification |
title_sort | cryptogenotyper: a new bioinformatics tool for rapid cryptosporidium identification |
topic | Special issue: Protozoa molecular tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966988/ https://www.ncbi.nlm.nih.gov/pubmed/33748443 http://dx.doi.org/10.1016/j.fawpar.2021.e00115 |
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