Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases
El microbioma intestinal está involucrado en múltiples procesos de la fisiología del huésped, y las disrupciones en la homeostasis del microbioma se han ligado a enfermedades o infecciones secundarias. Dada su importancia, se introdujo el término biomarcadores, definidos como bacterias correlacionad...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/38282
- Acceso en línea:
- https://doi.org/10.48713/10336_38282
https://repository.urosario.edu.co/handle/10336/38282
- Palabra clave:
- Gut microbiome
Instestinal inflammatory diseases
Differentially abundant bacteria
Beneficial bacteria
Pathogenic bacteria
Gut microbiome
Intestinal inflammatory diseases
Differentially abundant bacteria
Beneficial bacteria
Pathogenic bacteria
- Rights
- License
- Attribution-NonCommercial-ShareAlike 4.0 International
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EDOCUR2 |
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Repositorio EdocUR - U. Rosario |
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| dc.title.none.fl_str_mv |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| dc.title.TranslatedTitle.none.fl_str_mv |
¿Necesitamos cambiar nuestra perspectiva sobre los biomarcadores intestinales? Un análisis de datos públicos para identificar bacterias diferencialmente abundantes en enfermedades inflamatorias intestinales |
| title |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| spellingShingle |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases Gut microbiome Instestinal inflammatory diseases Differentially abundant bacteria Beneficial bacteria Pathogenic bacteria Gut microbiome Intestinal inflammatory diseases Differentially abundant bacteria Beneficial bacteria Pathogenic bacteria |
| title_short |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| title_full |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| title_fullStr |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| title_full_unstemmed |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| title_sort |
Do we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases |
| dc.contributor.advisor.none.fl_str_mv |
Muñoz Díaz, Claudia Marina |
| dc.contributor.gruplac.none.fl_str_mv |
Grupo de Investigaciones Microbiológicas UR (GIMUR) |
| dc.subject.none.fl_str_mv |
Gut microbiome Instestinal inflammatory diseases Differentially abundant bacteria Beneficial bacteria Pathogenic bacteria |
| topic |
Gut microbiome Instestinal inflammatory diseases Differentially abundant bacteria Beneficial bacteria Pathogenic bacteria Gut microbiome Intestinal inflammatory diseases Differentially abundant bacteria Beneficial bacteria Pathogenic bacteria |
| dc.subject.keyword.none.fl_str_mv |
Gut microbiome Intestinal inflammatory diseases Differentially abundant bacteria Beneficial bacteria Pathogenic bacteria |
| description |
El microbioma intestinal está involucrado en múltiples procesos de la fisiología del huésped, y las disrupciones en la homeostasis del microbioma se han ligado a enfermedades o infecciones secundarias. Dada su importancia, se introdujo el término biomarcadores, definidos como bacterias correlacionadas con estados de enfermedad, dietas y el estilo de vida del huésped. Sin embargo, el área de estudio de los biomarcadores intestinales sigue poco explorado dado que las comunidades asociadas a un estado de enfermedad particular aún no han sido exactamente definidas. Así, este estudio tuvo como objetivo identificar bacterias diferencialmente abundantes entre los sujetos con la enfermedad y sus controles. Por lo anterior, se analizaron datos públicos de estudios enfocados en describir la microbiota intestinal de pacientes con alguna enfermedad inflamatoria intestinal (cáncer colorrectal, enfermedad de Crohn, colitis ulcerosa y síndrome de colon irritable), junto con sus respectivos controles. Algunas bacterias frecuentemente reportadas (Fusobacterium, Streptococcus y Escherichia/Shigella) presentaron una abundancia diferencial entre los grupos de estudio, exhibiendo una alta abundancia en pacientes con la enfermedad. Los resultados de las bacterias diferencialmente abundantes contrastan con lo reportado en estudios previos sobre ciertas enfermedades inflamatorias, no obstante, se resalta la importancia de considerar enfoques integrales para redefinir o expandir la definición de biomarcadores. Por ejemplo, la diversidad intra-taxa de una comunidad bacteriana debe ser considerada, así como factores ambientales y genéticos del hospedero, e incluso considerar una validación funcional de estos biomarcadores con experimentos in vivo e in vitro. Por lo anterior, estas comunidades bacterianas claves en la microbiota intestinal pueden tener un potencial como probióticos de siguiente generación o pueden ser funcionales para el diseño de tratamientos específicos para ciertas enfermedades intestinales |
| publishDate |
2023 |
| dc.date.accessioned.none.fl_str_mv |
2023-03-29T19:38:51Z |
| dc.date.available.none.fl_str_mv |
2023-03-29T19:38:51Z |
| dc.date.created.none.fl_str_mv |
2023-02-20 |
| dc.type.none.fl_str_mv |
bachelorThesis |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_7a1f |
| dc.type.document.none.fl_str_mv |
Trabajo de grado |
| dc.type.spa.none.fl_str_mv |
Trabajo de grado |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.48713/10336_38282 |
| dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/38282 |
| url |
https://doi.org/10.48713/10336_38282 https://repository.urosario.edu.co/handle/10336/38282 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.rights.*.fl_str_mv |
Attribution-NonCommercial-ShareAlike 4.0 International |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
| dc.rights.acceso.none.fl_str_mv |
Abierto (Texto Completo) |
| dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-sa/4.0/ |
| rights_invalid_str_mv |
Attribution-NonCommercial-ShareAlike 4.0 International Abierto (Texto Completo) http://creativecommons.org/licenses/by-nc-sa/4.0/ http://purl.org/coar/access_right/c_abf2 |
| dc.format.extent.none.fl_str_mv |
835 pp |
| dc.format.mimetype.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad del Rosario |
| dc.publisher.department.none.fl_str_mv |
Facultad de Ciencias Naturales |
| dc.publisher.program.none.fl_str_mv |
Maestría en Ciencias Naturales |
| publisher.none.fl_str_mv |
Universidad del Rosario |
| institution |
Universidad del Rosario |
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Ai, D., Pan, H., Li, X., Gao, Y., Liu, G., and Xia, L. C. (2019). Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model. Frontiers in Microbiology 10. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2019.00826 [Accessed January 26, 2022]. Alam, M. T., Amos, G. C. A., Murphy, A. R. J., Murch, S., Wellington, E. M. H., and Arasaradnam, R. P. (2020). Microbial imbalance in inflammatory bowel disease patients at different taxonomic levels. Gut Pathogens 12, 1. doi: 10.1186/s13099-019-0341-6. Amitay, E. L., Werner, S., Vital, M., Pieper, D. H., Höfler, D., Gierse, I.-J., et al. (2017). Fusobacterium and colorectal cancer: causal factor or passenger? Results from a large colorectal cancer screening study. Carcinogenesis 38, 781–788. doi: 10.1093/carcin/bgx053. Anderson, M. J., and Walsh, D. C. I. (2013). PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecological Monographs 83, 557–574. doi: 10.1890/12-2010.1. Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Arumugam, M., Raes, J., Pelletier, E., Le Paslier, D., Yamada, T., Mende, D. R., et al. (2011). Enterotypes of the human gut microbiome. nature 473, 174–180. https://doi.org/10.1038/nature09944 Bajer, L., Kverka, M., Kostovcik, M., Macinga, P., Dvorak, J., Stehlikova, Z., et al. (2017). Distinct gut microbiota profiles in patients with primary sclerosing cholangitis and ulcerative colitis. World J Gastroenterol 23, 4548–4558. doi: 10.3748/wjg.v23.i25.4548. Barb, J. J., Oler, A. J., Kim, H.-S., Chalmers, N., Wallen, G. R., Cashion, A., et al. (2016). Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples. PLOS ONE 11, e0148047. doi: 10.1371/journal.pone.0148047. Basak, D., Uddin, M. N., and Hancock, J. (2020). The Role of Oxidative Stress and Its Counteractive Utility in Colorectal Cancer (CRC). Cancers 12, 3336. doi: 10.3390/cancers12113336. Berg, G., Rybakova, D., Fischer, D., Cernava, T., Vergès, M.-C. C., Charles, T., et al. (2020). Microbiome definition re-visited: old concepts and new challenges. Microbiome 8, 103. doi: 10.1186/s40168-020-00875-0. Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., et al. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37, 852–857. doi: 10.1038/s41587-019-0209-9. Bourgonje, A. R., Roo-Brand, G., Lisotto, P., Sadaghian Sadabad, M., Reitsema, R. D., de Goffau, M. C., et al. (2022). Patients With Inflammatory Bowel Disease Show IgG Immune Responses Towards Specific Intestinal Bacterial Genera. Front Immunol 13, 842911. doi: 10.3389/fimmu.2022.842911. Braun, T., Di Segni, A., BenShoshan, M., Neuman, S., Levhar, N., Bubis, M., et al. (2019). Individualized Dynamics in the Gut Microbiota Precede Crohn’s Disease Flares. Official journal of the American College of Gastroenterology | ACG 114, 1142–1151. doi: 10.14309/ajg.0000000000000136. Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., and Holmes, S. P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13, 581–583. doi: 10.1038/nmeth.3869. Chang, C.-J., Lin, T.-L., Tsai, Y.-L., Wu, T.-R., Lai, W.-F., Lu, C.-C., et al. (2019). Next generation probiotics in disease amelioration. Journal of Food and Drug Analysis 27, 615–622. doi: 10.1016/j.jfda.2018.12.011. Chen, Z., Hui, P. C., Hui, M., Yeoh, Y. K., Wong, P. Y., Chan, M. C. W., et al. (2019). Impact of Preservation Method and 16S rRNA Hypervariable Region on Gut Microbiota Profiling. mSystems 4, e00271-18. doi: 10.1128/mSystems.00271-18. Cheng, M., and Ning, K. (2019). Stereotypes About Enterotype: the Old and New Ideas. Genomics, Proteomics & Bioinformatics 17, 4–12. doi: 10.1016/j.gpb.2018.02.004. Cherny, K. E., Muscat, E. B., Reyna, M. E., and Kociolek, L. K. (2021). Clostridium innocuum: Microbiological and clinical characteristics of a potential emerging pathogen. Anaerobe 71, 102418. doi: 10.1016/j.anaerobe.2021.102418. Chia, J.-H., Wu, T.-S., Wu, T.-L., Chen, C.-L., Chuang, C.-H., Su, L.-H., et al. (2018). Clostridium innocuum is a vancomycin-resistant pathogen that may cause antibiotic-associated diarrhoea. Clinical Microbiology and Infection 24, 1195–1199. doi: 10.1016/j.cmi.2018.02.015. Clos-Garcia, M., Garcia, K., Alonso, C., Iruarrizaga-Lejarreta, M., D’Amato, M., Crespo, A., et al. (2020). Integrative Analysis of Fecal Metagenomics and Metabolomics in Colorectal Cancer. Cancers 12, 1142. doi: 10.3390/cancers12051142. Costea, P. I., Hildebrand, F., Arumugam, M., Bäckhed, F., Blaser, M. J., Bushman, F. D., et al. (2018). Enterotypes in the landscape of gut microbial community composition. Nat Microbiol 3, 8–16. doi: 10.1038/s41564-017-0072-8. Dam, B., Misra, A., and Banerjee, S. (2019). “Role of Gut Microbiota in Combating Oxidative Stress,” in Oxidative Stress in Microbial Diseases, eds. S. Chakraborti, T. Chakraborti, D. Chattopadhyay, and C. Shaha (Singapore: Springer), 43–82. doi: 10.1007/978-981-13-8763-0_4. Dao, M. C., Belda, E., Prifti, E., Everard, A., Kayser, B. D., Bouillot, J.-L., et al. (2019). Akkermansia muciniphila abundance is lower in severe obesity, but its increased level after bariatric surgery is not associated with metabolic health improvement. American Journal of Physiology-Endocrinology and Metabolism 317, E446–E459. doi: 10.1152/ajpendo.00140.2019. Dave, M., Higgins, P. D., Middha, S., and Rioux, K. P. (2012). The human gut microbiome: current knowledge, challenges, and future directions. Translational Research 160, 246–257. doi: 10.1016/j.trsl.2012.05.003. Di Pierro, F. (2021). A Possible Perspective about the Compositional Models, Evolution, and Clinical Meaning of Human Enterotypes. Microorganisms 9, 2341. doi: 10.3390/microorganisms9112341. Ding, R., Goh, W.-R., Wu, R., Yue, X., Luo, X., Khine, W. W. T., et al. (2019). Revisit gut microbiota and its impact on human health and disease. Journal of Food and Drug Analysis 27, 623–631. doi: 10.1016/j.jfda.2018.12.012. Du, X., Li, Q., Tang, Z., Yan, L., Zhang, L., Zheng, Q., et al. (2022). Alterations of the Gut Microbiome and Fecal Metabolome in Colorectal Cancer: Implication of Intestinal Metabolism for Tumorigenesis. Front Physiol 13, 854545. doi: 10.3389/fphys.2022.854545. Duan, J., Meng, X., Liu, S., Zhou, P., Zeng, C., Fu, C., et al. (2020). Gut Microbiota Composition Associated With Clostridium difficile-Positive Diarrhea and C. difficile Type in ICU Patients. Frontiers in Cellular and Infection Microbiology 10. Available at: https://www.frontiersin.org/article/10.3389/fcimb.2020.00190 [Accessed January 27, 2022]. Ewels, P., Magnusson, M., Lundin, S., and Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048. doi: 10.1093/bioinformatics/btw354. Feng, Q., Chen, W.-D., and Wang, Y.-D. (2018). Gut Microbiota: An Integral Moderator in Health and Disease. Frontiers in Microbiology 9. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2018.00151 [Accessed January 21, 2022]. Feng, Q., Liang, S., Jia, H., Stadlmayr, A., Tang, L., Lan, Z., et al. (2015). Gut microbiome development along the colorectal adenoma–carcinoma sequence. Nat Commun 6, 6528. doi: 10.1038/ncomms7528. Feng, Z., Long, W., Hao, B., Ding, D., Ma, X., Zhao, L., et al. (2017). A human stool-derived Bilophila wadsworthia strain caused systemic inflammation in specific-pathogen-free mice. Gut Pathogens 9, 59. 1-10. doi: 10.1186/s13099-017-0208-7. Ferreira-Halder, C. V., Faria, A. V. de S., and Andrade, S. S. (2017). Action and function of Faecalibacterium prausnitzii in health and disease. Best Practice & Research Clinical Gastroenterology 31, 643–648. doi: 10.1016/j.bpg.2017.09.011. Forbes, J. D., Chen, C., Knox, N. C., Marrie, R.-A., El-Gabalawy, H., de Kievit, T., et al. (2018). A comparative study of the gut microbiota in immune-mediated inflammatory diseases—does a common dysbiosis exist? Microbiome 6, 1–15. https://doi.org/10.1186/s40168-018-0603-4 Gibson, M. K., Pesesky, M. W., and Dantas, G. (2014). The Yin and Yang of Bacterial Resilience in the Human Gut Microbiota. Journal of Molecular Biology 426, 3866–3876. doi: 10.1016/j.jmb.2014.05.029. Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V., and Egozcue, J. J. (2017). Microbiome Datasets Are Compositional: And This Is Not Optional. Frontiers in Microbiology 8. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2017.02224 [Accessed October 10, 2022]. Gorvitovskaia, A., Holmes, S. P., and Huse, S. M. (2016). Interpreting Prevotella and Bacteroides as biomarkers of diet and lifestyle. Microbiome 4, 15. doi: 10.1186/s40168-016-0160-7. Guo, S., Lu, Y., Xu, B., Wang, W., Xu, J., and Zhang, G. (2019). A Simple Fecal Bacterial Marker Panel for the Diagnosis of Crohn’s Disease. Frontiers in Microbiology 10. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2019.01306 [Accessed January 26, 2022]. Gursoy, O., and Can, M. (2019). Hypervariable Regions in 16S rRNA Genes for the Taxonomic Classification. Southeast Europe Journal of Soft Computing 8. 23-26. doi: 10.21533/scjournal.v8i1.171. Halfvarson, J., Brislawn, C. J., Lamendella, R., Vázquez-Baeza, Y., Walters, W. A., Bramer, L. M., et al. (2017). Dynamics of the human gut microbiome in inflammatory bowel disease. Nat Microbiol 2, 1–7. doi: 10.1038/nmicrobiol.2017.4. Hall, A. B., Yassour, M., Sauk, J., Garner, A., Jiang, X., Arthur, T., et al. (2017). A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients. Genome Medicine 9, 103. doi: 10.1186/s13073-017-0490-5. He, X., Zhao, S., and Li, Y. (2021). Faecalibacterium prausnitzii: A Next-Generation Probiotic in Gut Disease Improvement. Canadian Journal of Infectious Diseases and Medical Microbiology 2021, e6666114. doi: 10.1155/2021/6666114. Jiang, S., Xie, S., Lv, D., Zhang, Y., Deng, J., Zeng, L., et al. (2016). A reduction in the butyrate producing species Roseburia spp. and Faecalibacterium prausnitzii is associated with chronic kidney disease progression. Antonie van Leeuwenhoek 109, 1389–1396. doi: 10.1007/s10482-016-0737-y. Karlsson, F. H., Fåk, F., Nookaew, I., Tremaroli, V., Fagerberg, B., Petranovic, D., et al. (2012). Symptomatic atherosclerosis is associated with an altered gut metagenome. Nat Commun 3, 1245. doi: 10.1038/ncomms2266. Kim, M., Morrison, M., and Yu, Z. (2011). Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes. Journal of Microbiological Methods 84, 81–87. doi: 10.1016/j.mimet.2010.10.020. Knights, D., Ward, T. L., McKinlay, C. E., Miller, H., Gonzalez, A., McDonald, D., et al. (2014). Rethinking “Enterotypes.” Cell Host & Microbe 16, 433–437. doi: 10.1016/j.chom.2014.09.013. Konishi, Y., Okumura, S., Matsumoto, T., Itatani, Y., Nishiyama, T., Okazaki, Y., et al. (2022). Development and evaluation of a colorectal cancer screening method using machine learning‐based gut microbiota analysis. Cancer Med 11, 3194–3206. doi: 10.1002/cam4.4671. Koren, O., Knights, D., Gonzalez, A., Waldron, L., Segata, N., Knight, R., et al. (2013). A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets. PLOS Computational Biology 9, e1002863. doi: 10.1371/journal.pcbi.1002863. Kostic, A. D., Gevers, D., Pedamallu, C. S., Michaud, M., Duke, F., Earl, A. M., et al. (2012). Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. Genome Res. 22, 292–298. doi: 10.1101/gr.126573.111. Kumar, R., Herold, J. L., Taylor, J., Xu, J., and Xu, Y. (2018). Variations among Streptococcus gallolyticus subsp. gallolyticus strains in connection with colorectal cancer. Sci Rep 8, 1514. 1-10. doi: 10.1038/s41598-018-19941-7. Kwong, T. N., Wang, X., Nakatsu, G., Chow, T. C., Tipoe, T., Dai, R. Z., et al. (2018). Association between bacteremia from specific microbes and subsequent diagnosis of colorectal cancer. Gastroenterology 155, 383–390. Le, P.-H., Chiu, C.-T., Yeh, P.-J., Pan, Y.-B., and Chiu, C.-H. (2022). Clostridium innocuum infection in hospitalised patients with inflammatory bowel disease. Journal of Infection 84, 337–342. doi: 10.1016/j.jinf.2021.12.031. Liu, Y.-X., Qin, Y., Chen, T., Lu, M., Qian, X., Guo, X., et al. (2021). A practical guide to amplicon and metagenomic analysis of microbiome data. Protein Cell 12, 315–330. doi: 10.1007/s13238-020-00724-8. Lloyd-Price, J., Arze, C., Ananthakrishnan, A. N., Schirmer, M., Avila-Pacheco, J., Poon, T. W., et al. (2019). Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 569, 655–662. doi: 10.1038/s41586-019-1237-9. Lopez-Siles, M., Enrich-Capó, N., Aldeguer, X., Sabat-Mir, M., Duncan, S. H., Garcia-Gil, L. J., et al. (2018). Alterations in the Abundance and Co-occurrence of Akkermansia muciniphila and Faecalibacterium prausnitzii in the Colonic Mucosa of Inflammatory Bowel Disease Subjects. Frontiers in Cellular and Infection Microbiology 8, 281. doi: 10.3389/fcimb.2018.00281. Lu, Y., Chen, J., Zheng, J., Hu, G., Wang, J., Huang, C., et al. (2016). Mucosal adherent bacterial dysbiosis in patients with colorectal adenomas. Sci Rep 6, 26337. doi: 10.1038/srep26337. Mancabelli, L., Milani, C., Lugli, G. A., Turroni, F., Cocconi, D., van Sinderen, D., et al. (2017). Identification of universal gut microbial biomarkers of common human intestinal diseases by meta-analysis. FEMS Microbiology Ecology 93, fix153. doi: 10.1093/femsec/fix153. Mandal, S., Van Treuren, W., White, R. A., Eggesbø, M., Knight, R., and Peddada, S. D. (2015). Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis 26, 10.3402/mehd.v26.27663. 1651-2235. doi: 10.3402/mehd.v26.27663. Martín, R., Miquel, S., Benevides, L., Bridonneau, C., Robert, V., Hudault, S., et al. (2017). Functional Characterization of Novel Faecalibacterium prausnitzii Strains Isolated from Healthy Volunteers: A Step Forward in the Use of F. prausnitzii as a Next-Generation Probiotic. Frontiers in Microbiology 8, 1226. doi: 10.3389/fmicb.2017.01226. Matsuo, Y., Komiya, S., Yasumizu, Y., Yasuoka, Y., Mizushima, K., Takagi, T., et al. (2021). Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinIONTM nanopore sequencing confers species-level resolution. BMC Microbiology 21, 35. doi: 10.1186/s12866-021-02094-5. McLaren, M. R., and Callahan, B. J. (2021). Silva 138.1 prokaryotic SSU taxonomic training data formatted for DADA2 [Data set]. 10.5281/zenodo.4587955 McMurdie, P. J., and Holmes, S. (2013). phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLOS ONE 8, e61217. doi: 10.1371/journal.pone.0061217. Metwaly, A., Reitmeier, S., and Haller, D. (2022). Microbiome risk profiles as biomarkers for inflammatory and metabolic disorders. Nat Rev Gastroenterol Hepatol, 1–15. doi: 10.1038/s41575-022-00581-2. Muñoz, M., Guerrero-Araya, E., Cortés-Tapia, C., Plaza-Garrido, A., Lawley, T. D., and Paredes-Sabja, D. (2020). Comprehensive genome analyses of Sellimonas intestinalis, a potential biomarker of homeostasis gut recovery. Microb Genom 6, mgen000476. doi: 10.1099/mgen.0.000476. Nearing, J. T., Douglas, G. M., Hayes, M. G., MacDonald, J., Desai, D. K., Allward, N., et al. (2022). Microbiome differential abundance methods produce different results across 38 datasets. Nat Commun 13, 342. doi: 10.1038/s41467-022-28034-z. Osman, M. A., Neoh, H., Ab Mutalib, N.-S., Chin, S.-F., Mazlan, L., Raja Ali, R. A., et al. (2021). Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum and Akkermansia muciniphila as a four-bacteria biomarker panel of colorectal cancer. Sci Rep 11, 2925. doi: 10.1038/s41598-021-82465-0. O’Toole, P. W., Marchesi, J. R., and Hill, C. (2017). Next-generation probiotics: the spectrum from probiotics to live biotherapeutics. Nat Microbiol 2, 1–6. doi: 10.1038/nmicrobiol.2017.57. Pisani, A., Rausch, P., Bang, C., Ellul, S., Tabone, T., Marantidis Cordina, C., et al. (2022). Dysbiosis in the Gut Microbiota in Patients with Inflammatory Bowel Disease during Remission. Microbiology Spectrum 10, e00616-22. doi: 10.1128/spectrum.00616-22. Quraishi, M. N., Acharjee, A., Beggs, A. D., Horniblow, R., Tselepis, C., Gkoutos, G., et al. (2020). A Pilot Integrative Analysis of Colonic Gene Expression, Gut Microbiota, and Immune Infiltration in Primary Sclerosing Cholangitis-Inflammatory Bowel Disease: Association of Disease With Bile Acid Pathways. Journal of Crohn’s and Colitis 14, 935–947. doi: 10.1093/ecco-jcc/jjaa021. Rinninella, E., Raoul, P., Cintoni, M., Franceschi, F., Miggiano, G. A. D., Gasbarrini, A., et al. (2019). What is the Healthy Gut Microbiota Composition? A Changing Ecosystem across Age, Environment, Diet, and Diseases. Microorganisms 7, 14. doi: 10.3390/microorganisms7010014. Rogers, A. E., Hu, Y.-J., Yue, Y., Wissel, E. F., Iii, R. A. P., Jarrett, S., et al. (2021). Shiftwork, functional bowel symptoms, and the microbiome. PeerJ 9, e11406. doi: 10.7717/peerj.11406. Sankarasubramanian, J., Ahmad, R., Avuthu, N., Singh, A. B., and Guda, C. (2020). Gut Microbiota and Metabolic Specificity in Ulcerative Colitis and Crohn’s Disease. Frontiers in Medicine 7. Available at: https://www.frontiersin.org/article/10.3389/fmed.2020.606298 [Accessed March 5, 2022]. Seedorf, H., Kittelmann, S., Henderson, G., and Janssen, P. H. (2014). RIM-DB: a taxonomic framework for community structure analysis of methanogenic archaea from the rumen and other intestinal environments. PeerJ 2, e494. doi: 10.7717/peerj.494. Segata, N. (2018). On the Road to Strain-Resolved Comparative Metagenomics. mSystems 3, e00190-17. doi: 10.1128/mSystems.00190-17. Sekizuka, T., Ogasawara, Y., Ohkusa, T., and Kuroda, M. (2017). Characterization of Fusobacterium varium Fv113-g1 isolated from a patient with ulcerative colitis based on complete genome sequence and transcriptome analysis. PLOS ONE 12, e0189319. doi: 10.1371/journal.pone.0189319. Sheikh, A. F., Masjedi Zadeh, A. R., Saki, M., Khani, P., Hashemi, S. J., Shahin Zadeh, S., et al. (2020). Detection of Streptococcus gallolyticus in colorectal cancer and inflammatory bowel disease patients compared to control group in southwest of Iran. Mol Biol Rep 47, 8361–8365. doi: 10.1007/s11033-020-05807-7. Sokol, H., Pigneur, B., Watterlot, L., Lakhdari, O., Bermúdez-Humarán, L. G., Gratadoux, J.-J., et al. (2008). Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. PNAS 105, 16731–16736. doi: 10.1073/pnas.0804812105. Tremblay, J., Singh, K., Fern, A., Kirton, E., He, S., Woyke, T., et al. (2015). Primer and platform effects on 16S rRNA tag sequencing. Frontiers in Microbiology 6. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2015.00771 [Accessed October 27, 2022]. Uchino, Y., Goto, Y., Konishi, Y., Tanabe, K., Toda, H., Wada, M., et al. (2021). Colorectal Cancer Patients Have Four Specific Bacterial Species in Oral and Gut Microbiota in Common—A Metagenomic Comparison with Healthy Subjects. Cancers 13, 3332. doi: 10.3390/cancers13133332. Vacca, M., Celano, G., Calabrese, F. M., Portincasa, P., Gobbetti, M., and De Angelis, M. (2020). The Controversial Role of Human Gut Lachnospiraceae. Microorganisms 8, 573. doi: 10.3390/microorganisms8040573. Walter, J., and Ley, R. (2011). The human gut microbiome: ecology and recent evolutionary changes. Annual review of microbiology 65, 411–429. https://doi.org/10.1146/annurev-micro-090110-102830 Wang, B., Yao, M., Lv, L., Ling, Z., and Li, L. (2017). The Human Microbiota in Health and Disease. Engineering 3, 71–82. doi: 10.1016/J.ENG.2017.01.008. Wang, B., Zhu, S., Liu, Z., Wei, H., Zhang, L., He, M., et al. (2020). Increased expression of colonic mucosal melatonin in patients with irritable bowel syndrome correlated with gut dysbiosis. Genomics, proteomics & bioinformatics 18, 708–720. https://doi.org/10.1016/j.gpb.2020.06.013 Weng, Y. J., Gan, H. Y., Li, X., Huang, Y., Li, Z. C., Deng, H. M., et al. (2019). Correlation of diet, microbiota and metabolite networks in inflammatory bowel disease. Journal of Digestive Diseases 20, 447–459. doi: 10.1111/1751-2980.12795. Willis, A. D. (2019). Rarefaction, Alpha Diversity, and Statistics. Frontiers in Microbiology 10. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2019.02407 [Accessed October 10, 2022]. Xu, N., Bai, X., Cao, X., Yue, W., Jiang, W., and Yu, Z. (2021). Changes in intestinal microbiota and correlation with TLRs in ulcerative colitis in the coastal area of northern China. Microbial Pathogenesis 150, 104707. doi: 10.1016/j.micpath.2020.104707. Yang, B., Wang, Y., and Qian, P.-Y. (2016). Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis. BMC Bioinformatics 17, 135. doi: 10.1186/s12859-016-0992-y. Yatsunenko, T., Rey, F. E., Manary, M. J., Trehan, I., Dominguez-Bello, M. G., Contreras, M., et al. (2012). Human gut microbiome viewed across age and geography. Nature 486, 222–227. doi: 10.1038/nature11053. Zakerska-Banaszak, O., Tomczak, H., Gabryel, M., Baturo, A., Wolko, L., Michalak, M., et al. (2021). Dysbiosis of gut microbiota in Polish patients with ulcerative colitis: a pilot study. Sci Rep 11, 2166. doi: 10.1038/s41598-021-81628-3. Zhang, M., Lv, Y., Hou, S., Liu, Y., Wang, Y., and Wan, X. (2021). Differential Mucosal Microbiome Profiles across Stages of Human Colorectal Cancer. Life 11, 831. doi: 10.3390/life11080831. Zhou, Y., Xu, Z. Z., He, Y., Yang, Y., Liu, L., Lin, Q., et al. (2018a). Gut Microbiota Offers Universal Biomarkers across Ethnicity in Inflammatory Bowel Disease Diagnosis and Infliximab Response Prediction. mSystems 3(1). e00188-17. doi: 10.1128/mSystems.00188-17. Zhou, Z., Chen, J., Yao, H., and Hu, H. (2018b). Fusobacterium and Colorectal Cancer. Frontiers in Oncology 8. Available at: https://www.frontiersin.org/articles/10.3389/fonc.2018.00371 [Accessed October 10, 2022]. Zhu, S., Liu, S., Li, H., Zhang, Z., Zhang, Q., Chen, L., et al. (2019). Identification of gut microbiota and metabolites signature in patients with irritable bowel syndrome. Frontiers in cellular and infection microbiology 9, 346. https://doi.org/10.3389/fcimb.2019.00346 Zhuang, X., Tian, Z., Li, L., Zeng, Z., Chen, M., and Xiong, L. (2018). Fecal Microbiota Alterations Associated With Diarrhea-Predominant Irritable Bowel Syndrome. Frontiers in Microbiology 9. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2018.01600 [Accessed January 25, 2022]. Zou, Y., Xue, W., Luo, G., Deng, Z., Qin, P., Guo, R., et al. (2019). 1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses. Nat Biotechnol 37, 179–185. doi: 10.1038/s41587-018-0008-8. |
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Muñoz Díaz, Claudia Marinaed1d1be3-30ee-46d3-95f3-0bde7b16b402-1Grupo de Investigaciones Microbiológicas UR (GIMUR)Vega Romero, Laura CamilaMagíster en Ciencias NaturalesMaestríaFull time8c10535b-9657-446c-bd30-73b002ec2b28-12023-03-29T19:38:51Z2023-03-29T19:38:51Z2023-02-20El microbioma intestinal está involucrado en múltiples procesos de la fisiología del huésped, y las disrupciones en la homeostasis del microbioma se han ligado a enfermedades o infecciones secundarias. Dada su importancia, se introdujo el término biomarcadores, definidos como bacterias correlacionadas con estados de enfermedad, dietas y el estilo de vida del huésped. Sin embargo, el área de estudio de los biomarcadores intestinales sigue poco explorado dado que las comunidades asociadas a un estado de enfermedad particular aún no han sido exactamente definidas. Así, este estudio tuvo como objetivo identificar bacterias diferencialmente abundantes entre los sujetos con la enfermedad y sus controles. Por lo anterior, se analizaron datos públicos de estudios enfocados en describir la microbiota intestinal de pacientes con alguna enfermedad inflamatoria intestinal (cáncer colorrectal, enfermedad de Crohn, colitis ulcerosa y síndrome de colon irritable), junto con sus respectivos controles. Algunas bacterias frecuentemente reportadas (Fusobacterium, Streptococcus y Escherichia/Shigella) presentaron una abundancia diferencial entre los grupos de estudio, exhibiendo una alta abundancia en pacientes con la enfermedad. Los resultados de las bacterias diferencialmente abundantes contrastan con lo reportado en estudios previos sobre ciertas enfermedades inflamatorias, no obstante, se resalta la importancia de considerar enfoques integrales para redefinir o expandir la definición de biomarcadores. Por ejemplo, la diversidad intra-taxa de una comunidad bacteriana debe ser considerada, así como factores ambientales y genéticos del hospedero, e incluso considerar una validación funcional de estos biomarcadores con experimentos in vivo e in vitro. Por lo anterior, estas comunidades bacterianas claves en la microbiota intestinal pueden tener un potencial como probióticos de siguiente generación o pueden ser funcionales para el diseño de tratamientos específicos para ciertas enfermedades intestinalesIntroduction: the gut microbiome is involved in multiple processes that influence host physiology, and therefore, disruptions in microbiome homeostasis have been linked to diseases or secondary infections. Given the importance of the microbiome and the communities of microorganisms that compose it (microbiota), the term biomarkers were coined, which are bacteria correlated with disease states, diets, and the lifestyle of the host. However, a large field in the study of intestinal biomarkers remains unexplored because the bacterial communities associated with a given disease state have not been exactly defined yet. Methods: Here, we analyzed public data of studies focused on describing the intestinal microbiota of patients with some intestinal inflammatory diseases together with their respective controls. With these analyses, we aimed to identify differentially abundant bacteria between the subjects with the disease and their controls. Results: We found that frequently reported bacteria such as Fusobacterium, Streptococcus, and Escherichia/Shigella were differentially abundant between the groups, with a higher abundance mostly in patients with the disease in contrast with their controls. On the other hand, we also identified potentially beneficial bacteria such as Faecalibacterium and Phascolarctobacterium, with a higher abundance in control patients. Discussion: Our results of the differentially abundant bacteria contrast with what was already reported in previous studies on certain inflammatory diseases, but we highlight the importance of considering more comprehensive approaches to redefine or expand the definition of biomarkers. For instance, the intra-taxa diversity within a bacterial community must be considered, as well as environmental and genetic factors of the host, and even consider a functional validation of these biomarkers through in vivo and in vitro approaches. With the above, these key bacterial communities in the intestinal microbiota may have potential as next-generation probiotics or may be functional for the design of specific therapies in certain intestinal diseases.835 ppapplication/pdfhttps://doi.org/10.48713/10336_38282 https://repository.urosario.edu.co/handle/10336/38282engUniversidad del RosarioFacultad de Ciencias NaturalesMaestría en Ciencias NaturalesAttribution-NonCommercial-ShareAlike 4.0 InternationalAbierto (Texto Completo)http://creativecommons.org/licenses/by-nc-sa/4.0/http://purl.org/coar/access_right/c_abf2Ai, D., Pan, H., Li, X., Gao, Y., Liu, G., and Xia, L. C. (2019). Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model. Frontiers in Microbiology 10. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2019.00826 [Accessed January 26, 2022].Alam, M. T., Amos, G. C. A., Murphy, A. R. J., Murch, S., Wellington, E. M. H., and Arasaradnam, R. P. (2020). Microbial imbalance in inflammatory bowel disease patients at different taxonomic levels. Gut Pathogens 12, 1. doi: 10.1186/s13099-019-0341-6.Amitay, E. L., Werner, S., Vital, M., Pieper, D. H., Höfler, D., Gierse, I.-J., et al. (2017). Fusobacterium and colorectal cancer: causal factor or passenger? Results from a large colorectal cancer screening study. Carcinogenesis 38, 781–788. doi: 10.1093/carcin/bgx053.Anderson, M. J., and Walsh, D. C. I. (2013). PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecological Monographs 83, 557–574. doi: 10.1890/12-2010.1.Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/.Arumugam, M., Raes, J., Pelletier, E., Le Paslier, D., Yamada, T., Mende, D. R., et al. (2011). Enterotypes of the human gut microbiome. nature 473, 174–180. https://doi.org/10.1038/nature09944Bajer, L., Kverka, M., Kostovcik, M., Macinga, P., Dvorak, J., Stehlikova, Z., et al. (2017). Distinct gut microbiota profiles in patients with primary sclerosing cholangitis and ulcerative colitis. World J Gastroenterol 23, 4548–4558. doi: 10.3748/wjg.v23.i25.4548.Barb, J. J., Oler, A. J., Kim, H.-S., Chalmers, N., Wallen, G. R., Cashion, A., et al. (2016). Development of an Analysis Pipeline Characterizing Multiple Hypervariable Regions of 16S rRNA Using Mock Samples. PLOS ONE 11, e0148047. doi: 10.1371/journal.pone.0148047.Basak, D., Uddin, M. N., and Hancock, J. (2020). The Role of Oxidative Stress and Its Counteractive Utility in Colorectal Cancer (CRC). Cancers 12, 3336. doi: 10.3390/cancers12113336.Berg, G., Rybakova, D., Fischer, D., Cernava, T., Vergès, M.-C. C., Charles, T., et al. (2020). Microbiome definition re-visited: old concepts and new challenges. Microbiome 8, 103. doi: 10.1186/s40168-020-00875-0.Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., et al. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37, 852–857. doi: 10.1038/s41587-019-0209-9.Bourgonje, A. R., Roo-Brand, G., Lisotto, P., Sadaghian Sadabad, M., Reitsema, R. D., de Goffau, M. C., et al. (2022). Patients With Inflammatory Bowel Disease Show IgG Immune Responses Towards Specific Intestinal Bacterial Genera. Front Immunol 13, 842911. doi: 10.3389/fimmu.2022.842911.Braun, T., Di Segni, A., BenShoshan, M., Neuman, S., Levhar, N., Bubis, M., et al. (2019). Individualized Dynamics in the Gut Microbiota Precede Crohn’s Disease Flares. Official journal of the American College of Gastroenterology | ACG 114, 1142–1151. doi: 10.14309/ajg.0000000000000136.Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., and Holmes, S. P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13, 581–583. doi: 10.1038/nmeth.3869.Chang, C.-J., Lin, T.-L., Tsai, Y.-L., Wu, T.-R., Lai, W.-F., Lu, C.-C., et al. (2019). Next generation probiotics in disease amelioration. Journal of Food and Drug Analysis 27, 615–622. doi: 10.1016/j.jfda.2018.12.011.Chen, Z., Hui, P. C., Hui, M., Yeoh, Y. K., Wong, P. Y., Chan, M. C. W., et al. (2019). Impact of Preservation Method and 16S rRNA Hypervariable Region on Gut Microbiota Profiling. mSystems 4, e00271-18. doi: 10.1128/mSystems.00271-18.Cheng, M., and Ning, K. (2019). Stereotypes About Enterotype: the Old and New Ideas. Genomics, Proteomics & Bioinformatics 17, 4–12. doi: 10.1016/j.gpb.2018.02.004.Cherny, K. E., Muscat, E. B., Reyna, M. E., and Kociolek, L. K. (2021). Clostridium innocuum: Microbiological and clinical characteristics of a potential emerging pathogen. Anaerobe 71, 102418. doi: 10.1016/j.anaerobe.2021.102418.Chia, J.-H., Wu, T.-S., Wu, T.-L., Chen, C.-L., Chuang, C.-H., Su, L.-H., et al. (2018). Clostridium innocuum is a vancomycin-resistant pathogen that may cause antibiotic-associated diarrhoea. Clinical Microbiology and Infection 24, 1195–1199. doi: 10.1016/j.cmi.2018.02.015.Clos-Garcia, M., Garcia, K., Alonso, C., Iruarrizaga-Lejarreta, M., D’Amato, M., Crespo, A., et al. (2020). Integrative Analysis of Fecal Metagenomics and Metabolomics in Colorectal Cancer. Cancers 12, 1142. doi: 10.3390/cancers12051142.Costea, P. I., Hildebrand, F., Arumugam, M., Bäckhed, F., Blaser, M. J., Bushman, F. D., et al. (2018). Enterotypes in the landscape of gut microbial community composition. Nat Microbiol 3, 8–16. doi: 10.1038/s41564-017-0072-8.Dam, B., Misra, A., and Banerjee, S. (2019). “Role of Gut Microbiota in Combating Oxidative Stress,” in Oxidative Stress in Microbial Diseases, eds. S. Chakraborti, T. Chakraborti, D. Chattopadhyay, and C. Shaha (Singapore: Springer), 43–82. doi: 10.1007/978-981-13-8763-0_4.Dao, M. C., Belda, E., Prifti, E., Everard, A., Kayser, B. D., Bouillot, J.-L., et al. (2019). Akkermansia muciniphila abundance is lower in severe obesity, but its increased level after bariatric surgery is not associated with metabolic health improvement. American Journal of Physiology-Endocrinology and Metabolism 317, E446–E459. doi: 10.1152/ajpendo.00140.2019.Dave, M., Higgins, P. D., Middha, S., and Rioux, K. P. (2012). The human gut microbiome: current knowledge, challenges, and future directions. Translational Research 160, 246–257. doi: 10.1016/j.trsl.2012.05.003.Di Pierro, F. (2021). A Possible Perspective about the Compositional Models, Evolution, and Clinical Meaning of Human Enterotypes. Microorganisms 9, 2341. doi: 10.3390/microorganisms9112341.Ding, R., Goh, W.-R., Wu, R., Yue, X., Luo, X., Khine, W. W. T., et al. (2019). Revisit gut microbiota and its impact on human health and disease. Journal of Food and Drug Analysis 27, 623–631. doi: 10.1016/j.jfda.2018.12.012.Du, X., Li, Q., Tang, Z., Yan, L., Zhang, L., Zheng, Q., et al. (2022). Alterations of the Gut Microbiome and Fecal Metabolome in Colorectal Cancer: Implication of Intestinal Metabolism for Tumorigenesis. Front Physiol 13, 854545. doi: 10.3389/fphys.2022.854545.Duan, J., Meng, X., Liu, S., Zhou, P., Zeng, C., Fu, C., et al. (2020). Gut Microbiota Composition Associated With Clostridium difficile-Positive Diarrhea and C. difficile Type in ICU Patients. Frontiers in Cellular and Infection Microbiology 10. Available at: https://www.frontiersin.org/article/10.3389/fcimb.2020.00190 [Accessed January 27, 2022].Ewels, P., Magnusson, M., Lundin, S., and Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048. doi: 10.1093/bioinformatics/btw354.Feng, Q., Chen, W.-D., and Wang, Y.-D. (2018). Gut Microbiota: An Integral Moderator in Health and Disease. Frontiers in Microbiology 9. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2018.00151 [Accessed January 21, 2022].Feng, Q., Liang, S., Jia, H., Stadlmayr, A., Tang, L., Lan, Z., et al. (2015). Gut microbiome development along the colorectal adenoma–carcinoma sequence. Nat Commun 6, 6528. doi: 10.1038/ncomms7528.Feng, Z., Long, W., Hao, B., Ding, D., Ma, X., Zhao, L., et al. (2017). A human stool-derived Bilophila wadsworthia strain caused systemic inflammation in specific-pathogen-free mice. Gut Pathogens 9, 59. 1-10. doi: 10.1186/s13099-017-0208-7.Ferreira-Halder, C. V., Faria, A. V. de S., and Andrade, S. S. (2017). Action and function of Faecalibacterium prausnitzii in health and disease. Best Practice & Research Clinical Gastroenterology 31, 643–648. doi: 10.1016/j.bpg.2017.09.011.Forbes, J. D., Chen, C., Knox, N. C., Marrie, R.-A., El-Gabalawy, H., de Kievit, T., et al. (2018). A comparative study of the gut microbiota in immune-mediated inflammatory diseases—does a common dysbiosis exist? Microbiome 6, 1–15. https://doi.org/10.1186/s40168-018-0603-4Gibson, M. K., Pesesky, M. W., and Dantas, G. (2014). The Yin and Yang of Bacterial Resilience in the Human Gut Microbiota. Journal of Molecular Biology 426, 3866–3876. doi: 10.1016/j.jmb.2014.05.029.Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V., and Egozcue, J. J. (2017). Microbiome Datasets Are Compositional: And This Is Not Optional. Frontiers in Microbiology 8. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2017.02224 [Accessed October 10, 2022].Gorvitovskaia, A., Holmes, S. P., and Huse, S. M. (2016). Interpreting Prevotella and Bacteroides as biomarkers of diet and lifestyle. Microbiome 4, 15. doi: 10.1186/s40168-016-0160-7.Guo, S., Lu, Y., Xu, B., Wang, W., Xu, J., and Zhang, G. (2019). A Simple Fecal Bacterial Marker Panel for the Diagnosis of Crohn’s Disease. Frontiers in Microbiology 10. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2019.01306 [Accessed January 26, 2022].Gursoy, O., and Can, M. (2019). Hypervariable Regions in 16S rRNA Genes for the Taxonomic Classification. Southeast Europe Journal of Soft Computing 8. 23-26. doi: 10.21533/scjournal.v8i1.171.Halfvarson, J., Brislawn, C. J., Lamendella, R., Vázquez-Baeza, Y., Walters, W. A., Bramer, L. M., et al. (2017). Dynamics of the human gut microbiome in inflammatory bowel disease. Nat Microbiol 2, 1–7. doi: 10.1038/nmicrobiol.2017.4.Hall, A. B., Yassour, M., Sauk, J., Garner, A., Jiang, X., Arthur, T., et al. (2017). A novel Ruminococcus gnavus clade enriched in inflammatory bowel disease patients. Genome Medicine 9, 103. doi: 10.1186/s13073-017-0490-5.He, X., Zhao, S., and Li, Y. (2021). Faecalibacterium prausnitzii: A Next-Generation Probiotic in Gut Disease Improvement. Canadian Journal of Infectious Diseases and Medical Microbiology 2021, e6666114. doi: 10.1155/2021/6666114.Jiang, S., Xie, S., Lv, D., Zhang, Y., Deng, J., Zeng, L., et al. (2016). A reduction in the butyrate producing species Roseburia spp. and Faecalibacterium prausnitzii is associated with chronic kidney disease progression. Antonie van Leeuwenhoek 109, 1389–1396. doi: 10.1007/s10482-016-0737-y.Karlsson, F. H., Fåk, F., Nookaew, I., Tremaroli, V., Fagerberg, B., Petranovic, D., et al. (2012). Symptomatic atherosclerosis is associated with an altered gut metagenome. Nat Commun 3, 1245. doi: 10.1038/ncomms2266.Kim, M., Morrison, M., and Yu, Z. (2011). Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes. Journal of Microbiological Methods 84, 81–87. doi: 10.1016/j.mimet.2010.10.020.Knights, D., Ward, T. L., McKinlay, C. E., Miller, H., Gonzalez, A., McDonald, D., et al. (2014). Rethinking “Enterotypes.” Cell Host & Microbe 16, 433–437. doi: 10.1016/j.chom.2014.09.013.Konishi, Y., Okumura, S., Matsumoto, T., Itatani, Y., Nishiyama, T., Okazaki, Y., et al. (2022). Development and evaluation of a colorectal cancer screening method using machine learning‐based gut microbiota analysis. Cancer Med 11, 3194–3206. doi: 10.1002/cam4.4671.Koren, O., Knights, D., Gonzalez, A., Waldron, L., Segata, N., Knight, R., et al. (2013). A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets. PLOS Computational Biology 9, e1002863. doi: 10.1371/journal.pcbi.1002863.Kostic, A. D., Gevers, D., Pedamallu, C. S., Michaud, M., Duke, F., Earl, A. M., et al. (2012). Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. Genome Res. 22, 292–298. doi: 10.1101/gr.126573.111.Kumar, R., Herold, J. L., Taylor, J., Xu, J., and Xu, Y. (2018). Variations among Streptococcus gallolyticus subsp. gallolyticus strains in connection with colorectal cancer. Sci Rep 8, 1514. 1-10. doi: 10.1038/s41598-018-19941-7.Kwong, T. N., Wang, X., Nakatsu, G., Chow, T. C., Tipoe, T., Dai, R. Z., et al. (2018). Association between bacteremia from specific microbes and subsequent diagnosis of colorectal cancer. Gastroenterology 155, 383–390.Le, P.-H., Chiu, C.-T., Yeh, P.-J., Pan, Y.-B., and Chiu, C.-H. (2022). Clostridium innocuum infection in hospitalised patients with inflammatory bowel disease. Journal of Infection 84, 337–342. doi: 10.1016/j.jinf.2021.12.031.Liu, Y.-X., Qin, Y., Chen, T., Lu, M., Qian, X., Guo, X., et al. (2021). A practical guide to amplicon and metagenomic analysis of microbiome data. Protein Cell 12, 315–330. doi: 10.1007/s13238-020-00724-8.Lloyd-Price, J., Arze, C., Ananthakrishnan, A. N., Schirmer, M., Avila-Pacheco, J., Poon, T. W., et al. (2019). Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 569, 655–662. doi: 10.1038/s41586-019-1237-9.Lopez-Siles, M., Enrich-Capó, N., Aldeguer, X., Sabat-Mir, M., Duncan, S. H., Garcia-Gil, L. J., et al. (2018). Alterations in the Abundance and Co-occurrence of Akkermansia muciniphila and Faecalibacterium prausnitzii in the Colonic Mucosa of Inflammatory Bowel Disease Subjects. Frontiers in Cellular and Infection Microbiology 8, 281. doi: 10.3389/fcimb.2018.00281.Lu, Y., Chen, J., Zheng, J., Hu, G., Wang, J., Huang, C., et al. (2016). Mucosal adherent bacterial dysbiosis in patients with colorectal adenomas. Sci Rep 6, 26337. doi: 10.1038/srep26337.Mancabelli, L., Milani, C., Lugli, G. A., Turroni, F., Cocconi, D., van Sinderen, D., et al. (2017). Identification of universal gut microbial biomarkers of common human intestinal diseases by meta-analysis. FEMS Microbiology Ecology 93, fix153. doi: 10.1093/femsec/fix153.Mandal, S., Van Treuren, W., White, R. A., Eggesbø, M., Knight, R., and Peddada, S. D. (2015). Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis 26, 10.3402/mehd.v26.27663. 1651-2235. doi: 10.3402/mehd.v26.27663.Martín, R., Miquel, S., Benevides, L., Bridonneau, C., Robert, V., Hudault, S., et al. (2017). Functional Characterization of Novel Faecalibacterium prausnitzii Strains Isolated from Healthy Volunteers: A Step Forward in the Use of F. prausnitzii as a Next-Generation Probiotic. Frontiers in Microbiology 8, 1226. doi: 10.3389/fmicb.2017.01226.Matsuo, Y., Komiya, S., Yasumizu, Y., Yasuoka, Y., Mizushima, K., Takagi, T., et al. (2021). Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinIONTM nanopore sequencing confers species-level resolution. BMC Microbiology 21, 35. doi: 10.1186/s12866-021-02094-5.McLaren, M. R., and Callahan, B. J. (2021). Silva 138.1 prokaryotic SSU taxonomic training data formatted for DADA2 [Data set]. 10.5281/zenodo.4587955McMurdie, P. J., and Holmes, S. (2013). phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLOS ONE 8, e61217. doi: 10.1371/journal.pone.0061217.Metwaly, A., Reitmeier, S., and Haller, D. (2022). Microbiome risk profiles as biomarkers for inflammatory and metabolic disorders. Nat Rev Gastroenterol Hepatol, 1–15. doi: 10.1038/s41575-022-00581-2.Muñoz, M., Guerrero-Araya, E., Cortés-Tapia, C., Plaza-Garrido, A., Lawley, T. D., and Paredes-Sabja, D. (2020). Comprehensive genome analyses of Sellimonas intestinalis, a potential biomarker of homeostasis gut recovery. Microb Genom 6, mgen000476. doi: 10.1099/mgen.0.000476.Nearing, J. T., Douglas, G. M., Hayes, M. G., MacDonald, J., Desai, D. K., Allward, N., et al. (2022). Microbiome differential abundance methods produce different results across 38 datasets. Nat Commun 13, 342. doi: 10.1038/s41467-022-28034-z.Osman, M. A., Neoh, H., Ab Mutalib, N.-S., Chin, S.-F., Mazlan, L., Raja Ali, R. A., et al. (2021). Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum and Akkermansia muciniphila as a four-bacteria biomarker panel of colorectal cancer. Sci Rep 11, 2925. doi: 10.1038/s41598-021-82465-0.O’Toole, P. W., Marchesi, J. R., and Hill, C. (2017). Next-generation probiotics: the spectrum from probiotics to live biotherapeutics. Nat Microbiol 2, 1–6. doi: 10.1038/nmicrobiol.2017.57.Pisani, A., Rausch, P., Bang, C., Ellul, S., Tabone, T., Marantidis Cordina, C., et al. (2022). Dysbiosis in the Gut Microbiota in Patients with Inflammatory Bowel Disease during Remission. Microbiology Spectrum 10, e00616-22. doi: 10.1128/spectrum.00616-22.Quraishi, M. N., Acharjee, A., Beggs, A. D., Horniblow, R., Tselepis, C., Gkoutos, G., et al. (2020). A Pilot Integrative Analysis of Colonic Gene Expression, Gut Microbiota, and Immune Infiltration in Primary Sclerosing Cholangitis-Inflammatory Bowel Disease: Association of Disease With Bile Acid Pathways. Journal of Crohn’s and Colitis 14, 935–947. doi: 10.1093/ecco-jcc/jjaa021.Rinninella, E., Raoul, P., Cintoni, M., Franceschi, F., Miggiano, G. A. D., Gasbarrini, A., et al. (2019). What is the Healthy Gut Microbiota Composition? A Changing Ecosystem across Age, Environment, Diet, and Diseases. Microorganisms 7, 14. doi: 10.3390/microorganisms7010014.Rogers, A. E., Hu, Y.-J., Yue, Y., Wissel, E. F., Iii, R. A. P., Jarrett, S., et al. (2021). Shiftwork, functional bowel symptoms, and the microbiome. PeerJ 9, e11406. doi: 10.7717/peerj.11406.Sankarasubramanian, J., Ahmad, R., Avuthu, N., Singh, A. B., and Guda, C. (2020). Gut Microbiota and Metabolic Specificity in Ulcerative Colitis and Crohn’s Disease. Frontiers in Medicine 7. Available at: https://www.frontiersin.org/article/10.3389/fmed.2020.606298 [Accessed March 5, 2022].Seedorf, H., Kittelmann, S., Henderson, G., and Janssen, P. H. (2014). RIM-DB: a taxonomic framework for community structure analysis of methanogenic archaea from the rumen and other intestinal environments. PeerJ 2, e494. doi: 10.7717/peerj.494.Segata, N. (2018). On the Road to Strain-Resolved Comparative Metagenomics. mSystems 3, e00190-17. doi: 10.1128/mSystems.00190-17.Sekizuka, T., Ogasawara, Y., Ohkusa, T., and Kuroda, M. (2017). Characterization of Fusobacterium varium Fv113-g1 isolated from a patient with ulcerative colitis based on complete genome sequence and transcriptome analysis. PLOS ONE 12, e0189319. doi: 10.1371/journal.pone.0189319.Sheikh, A. F., Masjedi Zadeh, A. R., Saki, M., Khani, P., Hashemi, S. J., Shahin Zadeh, S., et al. (2020). Detection of Streptococcus gallolyticus in colorectal cancer and inflammatory bowel disease patients compared to control group in southwest of Iran. Mol Biol Rep 47, 8361–8365. doi: 10.1007/s11033-020-05807-7.Sokol, H., Pigneur, B., Watterlot, L., Lakhdari, O., Bermúdez-Humarán, L. G., Gratadoux, J.-J., et al. (2008). Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. PNAS 105, 16731–16736. doi: 10.1073/pnas.0804812105.Tremblay, J., Singh, K., Fern, A., Kirton, E., He, S., Woyke, T., et al. (2015). Primer and platform effects on 16S rRNA tag sequencing. Frontiers in Microbiology 6. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2015.00771 [Accessed October 27, 2022].Uchino, Y., Goto, Y., Konishi, Y., Tanabe, K., Toda, H., Wada, M., et al. (2021). Colorectal Cancer Patients Have Four Specific Bacterial Species in Oral and Gut Microbiota in Common—A Metagenomic Comparison with Healthy Subjects. Cancers 13, 3332. doi: 10.3390/cancers13133332.Vacca, M., Celano, G., Calabrese, F. M., Portincasa, P., Gobbetti, M., and De Angelis, M. (2020). The Controversial Role of Human Gut Lachnospiraceae. Microorganisms 8, 573. doi: 10.3390/microorganisms8040573.Walter, J., and Ley, R. (2011). The human gut microbiome: ecology and recent evolutionary changes. Annual review of microbiology 65, 411–429. https://doi.org/10.1146/annurev-micro-090110-102830Wang, B., Yao, M., Lv, L., Ling, Z., and Li, L. (2017). The Human Microbiota in Health and Disease. Engineering 3, 71–82. doi: 10.1016/J.ENG.2017.01.008.Wang, B., Zhu, S., Liu, Z., Wei, H., Zhang, L., He, M., et al. (2020). Increased expression of colonic mucosal melatonin in patients with irritable bowel syndrome correlated with gut dysbiosis. Genomics, proteomics & bioinformatics 18, 708–720. https://doi.org/10.1016/j.gpb.2020.06.013Weng, Y. J., Gan, H. Y., Li, X., Huang, Y., Li, Z. C., Deng, H. M., et al. (2019). Correlation of diet, microbiota and metabolite networks in inflammatory bowel disease. Journal of Digestive Diseases 20, 447–459. doi: 10.1111/1751-2980.12795.Willis, A. D. (2019). Rarefaction, Alpha Diversity, and Statistics. Frontiers in Microbiology 10. Available at: https://www.frontiersin.org/articles/10.3389/fmicb.2019.02407 [Accessed October 10, 2022].Xu, N., Bai, X., Cao, X., Yue, W., Jiang, W., and Yu, Z. (2021). Changes in intestinal microbiota and correlation with TLRs in ulcerative colitis in the coastal area of northern China. Microbial Pathogenesis 150, 104707. doi: 10.1016/j.micpath.2020.104707.Yang, B., Wang, Y., and Qian, P.-Y. (2016). Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis. BMC Bioinformatics 17, 135. doi: 10.1186/s12859-016-0992-y.Yatsunenko, T., Rey, F. E., Manary, M. J., Trehan, I., Dominguez-Bello, M. G., Contreras, M., et al. (2012). Human gut microbiome viewed across age and geography. Nature 486, 222–227. doi: 10.1038/nature11053.Zakerska-Banaszak, O., Tomczak, H., Gabryel, M., Baturo, A., Wolko, L., Michalak, M., et al. (2021). Dysbiosis of gut microbiota in Polish patients with ulcerative colitis: a pilot study. Sci Rep 11, 2166. doi: 10.1038/s41598-021-81628-3.Zhang, M., Lv, Y., Hou, S., Liu, Y., Wang, Y., and Wan, X. (2021). Differential Mucosal Microbiome Profiles across Stages of Human Colorectal Cancer. Life 11, 831. doi: 10.3390/life11080831.Zhou, Y., Xu, Z. Z., He, Y., Yang, Y., Liu, L., Lin, Q., et al. (2018a). Gut Microbiota Offers Universal Biomarkers across Ethnicity in Inflammatory Bowel Disease Diagnosis and Infliximab Response Prediction. mSystems 3(1). e00188-17. doi: 10.1128/mSystems.00188-17.Zhou, Z., Chen, J., Yao, H., and Hu, H. (2018b). Fusobacterium and Colorectal Cancer. Frontiers in Oncology 8. Available at: https://www.frontiersin.org/articles/10.3389/fonc.2018.00371 [Accessed October 10, 2022].Zhu, S., Liu, S., Li, H., Zhang, Z., Zhang, Q., Chen, L., et al. (2019). Identification of gut microbiota and metabolites signature in patients with irritable bowel syndrome. Frontiers in cellular and infection microbiology 9, 346. https://doi.org/10.3389/fcimb.2019.00346Zhuang, X., Tian, Z., Li, L., Zeng, Z., Chen, M., and Xiong, L. (2018). Fecal Microbiota Alterations Associated With Diarrhea-Predominant Irritable Bowel Syndrome. Frontiers in Microbiology 9. Available at: https://www.frontiersin.org/article/10.3389/fmicb.2018.01600 [Accessed January 25, 2022].Zou, Y., Xue, W., Luo, G., Deng, Z., Qin, P., Guo, R., et al. (2019). 1,520 reference genomes from cultivated human gut bacteria enable functional microbiome analyses. Nat Biotechnol 37, 179–185. doi: 10.1038/s41587-018-0008-8.instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURGut microbiomeInstestinal inflammatory diseasesDifferentially abundant bacteriaBeneficial bacteriaPathogenic bacteriaGut microbiomeIntestinal inflammatory diseasesDifferentially abundant bacteriaBeneficial bacteriaPathogenic bacteriaDo we need to change our perspective about gut biomarkers? A public data mining approach to identify differentially abundant bacteria in intestinal inflammatory diseases¿Necesitamos cambiar nuestra perspectiva sobre los biomarcadores intestinales? 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