Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota
Background: Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliabilit...
| Autores: | , , , , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad de Barcelona |
| Repositorio: | Dipòsit Digital de la UB |
| OAI Identifier: | oai:diposit.ub.edu:2445/215281 |
| Acceso en línea: | https://hdl.handle.net/2445/215281 |
| Access Level: | acceso abierto |
| Palabra clave: | Microbiota intestinal Càncer colorectal Gastrointestinal microbiome Colorectal cancer |
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Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiotaBars Cortina, DavidRamon, EliesRius Sansalvador, BlancaGuinó, ElisabetGarcia Serrano, AinhoaMach, NúriaKhannous Ileiffe, OlfatSaus, EsterGabaldón, ToniIbáñez Sanz, GemmaRodríguez Alonso, LorenaMata, AlfredoGarcía Rodríguez, AnaObón Santacana, MireiaMoreno Aguado, VíctorMicrobiota intestinalCàncer colorectalGastrointestinal microbiomeColorectal cancerBackground: Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models. Results: As expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra. Conclusions: Shotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims.Springer Science and Business Media LLC2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/215281Articles publicats en revistes (Ciències Clíniques)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1186/s12864-024-10621-7BMC Genomics, 2024, vol. 25, num. 1https://doi.org/10.1186/s12864-024-10621-7cc by (c) Bars Cortina, David et al., 2024http://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/2152812026-05-27T06:46:51Z |
| dc.title.none.fl_str_mv |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| title |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| spellingShingle |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota Bars Cortina, David Microbiota intestinal Càncer colorectal Gastrointestinal microbiome Colorectal cancer |
| title_short |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| title_full |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| title_fullStr |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| title_full_unstemmed |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| title_sort |
Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota |
| dc.creator.none.fl_str_mv |
Bars Cortina, David Ramon, Elies Rius Sansalvador, Blanca Guinó, Elisabet Garcia Serrano, Ainhoa Mach, Núria Khannous Ileiffe, Olfat Saus, Ester Gabaldón, Toni Ibáñez Sanz, Gemma Rodríguez Alonso, Lorena Mata, Alfredo García Rodríguez, Ana Obón Santacana, Mireia Moreno Aguado, Víctor |
| author |
Bars Cortina, David |
| author_facet |
Bars Cortina, David Ramon, Elies Rius Sansalvador, Blanca Guinó, Elisabet Garcia Serrano, Ainhoa Mach, Núria Khannous Ileiffe, Olfat Saus, Ester Gabaldón, Toni Ibáñez Sanz, Gemma Rodríguez Alonso, Lorena Mata, Alfredo García Rodríguez, Ana Obón Santacana, Mireia Moreno Aguado, Víctor |
| author_role |
author |
| author2 |
Ramon, Elies Rius Sansalvador, Blanca Guinó, Elisabet Garcia Serrano, Ainhoa Mach, Núria Khannous Ileiffe, Olfat Saus, Ester Gabaldón, Toni Ibáñez Sanz, Gemma Rodríguez Alonso, Lorena Mata, Alfredo García Rodríguez, Ana Obón Santacana, Mireia Moreno Aguado, Víctor |
| author2_role |
author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Microbiota intestinal Càncer colorectal Gastrointestinal microbiome Colorectal cancer |
| topic |
Microbiota intestinal Càncer colorectal Gastrointestinal microbiome Colorectal cancer |
| description |
Background: Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models. Results: As expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra. Conclusions: Shotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims. |
| publishDate |
2024 |
| dc.date.none.fl_str_mv |
2024 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
| dc.identifier.none.fl_str_mv |
https://hdl.handle.net/2445/215281 |
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https://hdl.handle.net/2445/215281 |
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Inglés |
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Inglés |
| dc.relation.none.fl_str_mv |
Reproducció del document publicat a: https://doi.org/10.1186/s12864-024-10621-7 BMC Genomics, 2024, vol. 25, num. 1 https://doi.org/10.1186/s12864-024-10621-7 |
| dc.rights.none.fl_str_mv |
cc by (c) Bars Cortina, David et al., 2024 http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess |
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cc by (c) Bars Cortina, David et al., 2024 http://creativecommons.org/licenses/by/3.0/es/ |
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openAccess |
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application/pdf |
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Springer Science and Business Media LLC |
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Springer Science and Business Media LLC |
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Articles publicats en revistes (Ciències Clíniques) reponame:Dipòsit Digital de la UB instname:Universidad de Barcelona |
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Universidad de Barcelona |
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Dipòsit Digital de la UB |
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