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Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing
BACKGROUND: The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable t...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901789/ https://www.ncbi.nlm.nih.gov/pubmed/24418497 http://dx.doi.org/10.1186/2043-9113-4-1 |
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author | Chiu, Chih-Min Lin, Feng-Mao Chang, Tzu-Hao Huang, Wei-Chih Liang, Chao Yang, Ting Wu, Wei-Yun Yang, Tzu-Ling Weng, Shun-Long Huang, Hsien-Da |
author_facet | Chiu, Chih-Min Lin, Feng-Mao Chang, Tzu-Hao Huang, Wei-Chih Liang, Chao Yang, Ting Wu, Wei-Yun Yang, Tzu-Ling Weng, Shun-Long Huang, Hsien-Da |
author_sort | Chiu, Chih-Min |
collection | PubMed |
description | BACKGROUND: The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species. RESULTS: We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. CONCLUSIONS: The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method. |
format | Online Article Text |
id | pubmed-3901789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-39017892014-02-06 Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing Chiu, Chih-Min Lin, Feng-Mao Chang, Tzu-Hao Huang, Wei-Chih Liang, Chao Yang, Ting Wu, Wei-Yun Yang, Tzu-Ling Weng, Shun-Long Huang, Hsien-Da J Clin Bioinforma Methodology BACKGROUND: The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species. RESULTS: We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. CONCLUSIONS: The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method. BioMed Central 2014-01-13 /pmc/articles/PMC3901789/ /pubmed/24418497 http://dx.doi.org/10.1186/2043-9113-4-1 Text en Copyright © 2014 Chiu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Chiu, Chih-Min Lin, Feng-Mao Chang, Tzu-Hao Huang, Wei-Chih Liang, Chao Yang, Ting Wu, Wei-Yun Yang, Tzu-Ling Weng, Shun-Long Huang, Hsien-Da Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
title | Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
title_full | Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
title_fullStr | Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
title_full_unstemmed | Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
title_short | Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
title_sort | clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901789/ https://www.ncbi.nlm.nih.gov/pubmed/24418497 http://dx.doi.org/10.1186/2043-9113-4-1 |
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