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Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing
The tissue-resident microbiota is an integral component of multiple tumor types, but it remains challenging to characterize its abundance and composition due to its low biomass. Here, we describe an optimized protocol for quantification and profiling of tissue-resident microbiota. The major optimize...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9558047/ https://www.ncbi.nlm.nih.gov/pubmed/36209427 http://dx.doi.org/10.1016/j.xpro.2022.101765 |
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author | Yao, Bingqing Dong, Tingting Fu, Aikun Li, Hang Jiang, Chuhan Li, Nan Cai, Shang |
author_facet | Yao, Bingqing Dong, Tingting Fu, Aikun Li, Hang Jiang, Chuhan Li, Nan Cai, Shang |
author_sort | Yao, Bingqing |
collection | PubMed |
description | The tissue-resident microbiota is an integral component of multiple tumor types, but it remains challenging to characterize its abundance and composition due to its low biomass. Here, we describe an optimized protocol for quantification and profiling of tissue-resident microbiota. The major optimized steps include DNA extraction, qPCR, 16S library construction, and bioinformatics analysis. This protocol enables robust and accurate characterization of the dynamics of normal and tumor tissue-resident microbiota at its physiological abundance from both mouse and human origins. For complete details on the use and execution of this protocol, please refer to Fu et al. (2022). |
format | Online Article Text |
id | pubmed-9558047 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-95580472022-10-14 Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing Yao, Bingqing Dong, Tingting Fu, Aikun Li, Hang Jiang, Chuhan Li, Nan Cai, Shang STAR Protoc Protocol The tissue-resident microbiota is an integral component of multiple tumor types, but it remains challenging to characterize its abundance and composition due to its low biomass. Here, we describe an optimized protocol for quantification and profiling of tissue-resident microbiota. The major optimized steps include DNA extraction, qPCR, 16S library construction, and bioinformatics analysis. This protocol enables robust and accurate characterization of the dynamics of normal and tumor tissue-resident microbiota at its physiological abundance from both mouse and human origins. For complete details on the use and execution of this protocol, please refer to Fu et al. (2022). Elsevier 2022-10-07 /pmc/articles/PMC9558047/ /pubmed/36209427 http://dx.doi.org/10.1016/j.xpro.2022.101765 Text en © 2022 The Author(s) https://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 | Protocol Yao, Bingqing Dong, Tingting Fu, Aikun Li, Hang Jiang, Chuhan Li, Nan Cai, Shang Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing |
title | Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing |
title_full | Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing |
title_fullStr | Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing |
title_full_unstemmed | Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing |
title_short | Quantification and characterization of mouse and human tissue-resident microbiota by qPCR and 16S sequencing |
title_sort | quantification and characterization of mouse and human tissue-resident microbiota by qpcr and 16s sequencing |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9558047/ https://www.ncbi.nlm.nih.gov/pubmed/36209427 http://dx.doi.org/10.1016/j.xpro.2022.101765 |
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