A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies.

التفاصيل البيبلوغرافية
العنوان:	A complementary metaproteomic approach to interrogate microbiome cultivated from clinical colon biopsies.
المؤلفون:	Duong VA; The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA., Enkhbayar A; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas, USA., Bhasin N; Department of Medicine, Baylor College of Medicine, Houston, Texas, USA., Senavirathna L; The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA., Preisner EC; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA., Hoffman KL; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA., Shukla R; Department of Medicine, Baylor College of Medicine, Houston, Texas, USA., Jenq RR; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas, USA.; Department of Genomic Medicine, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA., Cheng K; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada., Bronner MP; Department of Pathology, University of Utah, Salt Lake City, USA., Figeys D; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada., Britton RA; Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA., Pan S; The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas, USA.; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas, USA., Chen R; Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
المصدر:	Proteomics [Proteomics] 2024 Jun 02, pp. e2400078. Date of Electronic Publication: 2024 Jun 02.
Publication Model:	Ahead of Print
نوع المنشور:	Journal Article
اللغة:	English
بيانات الدورية:	Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 101092707 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1615-9861 (Electronic) Linking ISSN: 16159853 NLM ISO Abbreviation: Proteomics Subsets: MEDLINE
أسماء مطبوعة:	Original Publication: Weinheim, Germany : Wiley-VCH,
مستخلص:	The human gut microbiome plays a vital role in preserving individual health and is intricately involved in essential functions. Imbalances or dysbiosis within the microbiome can significantly impact human health and are associated with many diseases. Several metaproteomics platforms are currently available to study microbial proteins within complex microbial communities. In this study, we attempted to develop an integrated pipeline to provide deeper insights into both the taxonomic and functional aspects of the cultivated human gut microbiomes derived from clinical colon biopsies. We combined a rapid peptide search by MSFragger against the Unified Human Gastrointestinal Protein database and the taxonomic and functional analyses with Unipept Desktop and MetaLab-MAG. Across seven samples, we identified and matched nearly 36,000 unique peptides to approximately 300 species and 11 phyla. Unipept Desktop provided gene ontology, InterPro entries, and enzyme commission number annotations, facilitating the identification of relevant metabolic pathways. MetaLab-MAG contributed functional annotations through Clusters of Orthologous Genes and Non-supervised Orthologous Groups categories. These results unveiled functional similarities and differences among the samples. This integrated pipeline holds the potential to provide deeper insights into the taxonomy and functions of the human gut microbiome for interrogating the intricate connections between microbiome balance and diseases. (© 2024 Wiley‐VCH GmbH.)
References:	Sender, R., Fuchs, S., & Milo, R., Are We Really Vastly Outnumbered?. Revisiting the ratio of bacterial to host cells in humans. Cell, 164(3), 337–340. Lloyd‐Price, J., Abu‐Ali, G., & Huttenhower, C. (2016). The healthy human microbiome. Genome Med, 8(1), 51. Bidell, M R., Hobbs, A. L. V., & Lodise, T P. (2022). Gut microbiome health and dysbiosis: A clinical primer. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, 42(11), 849–857. Miura, N., & Okuda, S. (2023). Current progress and critical challenges to overcome in the bioinformatics of mass spectrometry‐based metaproteomics. Computational and Structural Biotechnology Journal, 21, 1140–1150. Cullin, N., Azevedo Antunes, C., Straussman, R., Stein‐Thoeringer, C K., & Elinav, E. (2021). Microbiome and cancer. Cancer Cell, 39(10), 1317–1341. Lai, L. A., et al. (2019). Metaproteomics Study of the Gut Microbiome in Functional Proteomics: Methods and Protocols (X. Wang and M. Kuruc, Eds.)g Springer, New York: New York, NY, pp. 123–132. Pan, S., & Chen, R. (2020). Chapter One—Metaproteomic analysis of human gut microbiome in digestive and metabolic diseases in Advances in Clinical Chemistry. G. S., Makowski, Editor., Elsevier, pp. 1–12. Li, L., Wang, T., Ning, Z., Zhang, X., Butcher, J., Serrana, J. M., Simopoulos, C. M. A., Mayne, J., Stintzi, A., Mack, D. R., Liu, Y. Y., & Figeys, D. (2023). Revealing proteome‐level functional redundancy in the human gut microbiome using ultra‐deep metaproteomics. Nature Communications, 14(1), 3428. Zhang, X., Li, L., Butcher, J., Stintzi, A., & Figeys, D. (2019). Advancing functional and translational microbiome research using meta‐omics approaches. Microbiome, 7(1), 154. Sanna, S., Kurilshikov, A., Van Der Graaf, A., Fu, J., & Zhernakova, A. (2022). Challenges and future directions for studying effects of host genetics on the gut microbiome. Nature Genetics, 54(2), 100–106. Salvato, F., Hettich, R L., & Kleiner, M. (2021). Five key aspects of metaproteomics as a tool to understand functional interactions in host‐associated microbiomes. Plos Pathogens, 17(2), e1009245. Huttenhower, C., Gevers, D., Knight, R., Abubucker, S., Badger, J. H., Chinwalla, A. T., Creasy, H. H., Earl, A. M., Fitzgerald, M., Fulton, R. S., Gonzalez, A., & Griggs, A. D. (2012). Structure, function and diversity of the healthy human microbiome. Nature, 486(7402), 207–214. Proctor, L. M., Creasy, H. H., Fettweis, J. M., Lloyd‐Price, J., Mahurkar, A., Zhou, W., Buck, G. A., Snyder, M., Strauss, J. F., Weinstock, G. M., White, O., & Huttenhower, C. (2019). The integrative human microbiome project. Nature, 569(7758), 641–648. Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., Yamada, T., Mende, D. R., Li, J., Xu, J., Li, S., Li, D., Cao, J., Wang, B., Liang, H., Zheng, H., & Wang, J. (2010). A human gut microbial gene catalogue established by metagenomic sequencing. Nature, 464(7285), 59–65. Li, J., Jia, H., Cai, X., Zhong, H., Feng, Q., Sunagawa, S., Arumugam, M., Kultima, J. R., Prifti, E., Nielsen, T., Juncker, A. S., Manichanh, C., Chen, B., Zhang, W., Levenez, F., Wang, J., Xu, X., Xiao, L., Liang, S., & Wang, J. (2014). An integrated catalog of reference genes in the human gut microbiome. Nature Biotechnology, 32(8), 834–841. Almeida, A., Nayfach, S., Boland, M., Strozzi, F., Beracochea, M., Shi, Z. J., Pollard, K S., Sakharova, E., Parks, D H., Hugenholtz, P., Segata, N., Kyrpides, N C., & Finn, R D. (2021). A unified catalog of 204,938 reference genomes from the human gut microbiome. Nature Biotechnology, 39(1), 105–114. Mitchell, A. L., Almeida, A., Beracochea, M., Boland, M., Burgin, J., Cochrane, G., Crusoe, M. R., Kale, V., Potter, S. C., Richardson, L., Lapidus, A., & Finn, R. D. (2019). MGnify: The microbiome analysis resource in 2020. Nucleic Acids Res., 48(D1), D570–D578. Verschaffelt, P., Tanca, A., Abbondio, M., Van Den Bossche, T., Moortele, T. V., Dawyndt, P., Martens, L., & Mesuere, B. (2023). Unipept Desktop 2.0: Construction of targeted reference protein databases for metaproteogenomics analyses. Journal of Proteome Research, 22(8), 2620–2628. Singh, R. G., Tanca, A., Palomba, A., Jeugt, F. V. D., Verschaffelt, P., Uzzau, S., Martens, L., Dawyndt, P., & Mesuere, B. (2019). Unipept 4.0: Functional analysis of metaproteome data. Journal of Proteome Research, 18(2), 606–615. Cheng, K., Ning, Z., Li, L., Zhang, X., Serrana, J M., Mayne, J., & Figeys, D. (2023). MetaLab‐MAG: A metaproteomic data analysis platform for genome‐level characterization of microbiomes from the metagenome‐assembled genomes database. Journal of Proteome Research, 22(2), 387–398. Kong, A. T., Leprevost, F. V., Avtonomov, D. M., Mellacheruvu, D., & Nesvizhskii, A. I. (2017). MSFragger: Ultrafast and comprehensive peptide identification in mass spectrometry–based proteomics. Nature Methods, 14(5), 513–520. Chen, R., Pan, S., Lai, K., Lai, L. A., Crispin, D. A., Bronner, M. P., & Brentnall, T. A. (2014). Up‐regulation of mitochondrial chaperone TRAP1 in ulcerative colitis associated colorectal cancer. World J. Gastroenterol., 20(45), 17037–17048. Auchtung, J M., Robinson, C D., & Britton, R A. (2015). Cultivation of stable, reproducible microbial communities from different fecal donors using minibioreactor arrays (MBRAs). Microbiome, 3(1), 42. Disis, M L., Corulli, L R., Gad, E A., Koehnlein, M R., Cecil, D L., Senter, P D., Gardai, S J., & Okeley, N M. (2020). Therapeutic and prophylactic antitumor activity of an oral inhibitor of fucosylation in spontaneous mammary cancers. Molecular Cancer Therapeutics, 19(5), 1102–1109. Engevik, M. A., Danhof, H. A., Auchtung, J., Endres, B. T., Ruan, W., Bassères, E., Engevik, A. C., Wu, Q., Nicholson, M., Luna, R. A., Garey, K. W., Crawford, S. E., Estes, M. K., Lux, R., Yacyshyn, M. B., Yacyshyn, B., Savidge, T., Britton, R. A., & Versalovic, J. (2021). FusobacteriumnucleatumAdheres to Clostridioides difficilevia the RadD Adhesin to Enhance Biofilm Formation in Intestinal Mucus. Gastroenterology, 160(4), 1301–1314.e8. Mahnic, A., Auchtung, J M., Poklar Ulrih, N., Britton, R A., & Rupnik, M. (2020). Microbiota in vitro modulated with polyphenols shows decreased colonization resistance against Clostridioides difficile but can neutralize cytotoxicity. Scientific Reports, 10(1), 8358. Masi, A. C., Fofanova, T., Lamb, C. A., Auchtung, J. M., Britton, R. A., Estes, M. K., Ramani, S., Cockell, S. J., Coxhead, J., Embleton, N. D., & Stewart, C. J. (2022). Distinct gene expression profiles between human preterm‐derived and adult‐derived intestinal organoids exposed to Enterococcus faecalis: A pilot study. Gut, 71(10), 2141–2143. Auchtung, T A., Fofanova, T Y., Stewart, C J., Nash, A K., Wong, M C., Gesell, J R., Auchtung, J M., Ajami, N J., & Petrosino, J F. (2018). Investigating colonization of the healthy adult gastrointestinal tract by fungi. mSphere., 3(2), . Pan, S., Hullar, M A. J., Lai, L A., Peng, H., May, D H., Noble, W S., Raftery, D., Navarro, S L., Neuhouser, M L., Lampe, P D., Lampe, J W., & Chen, R. (2020). Gut microbial protein expression in response to dietary patterns in a controlled feeding study. A Metaproteomic Approach. Microorganisms, 8(3), 379. Keller, A., Nesvizhskii, A I., Kolker, E., & Aebersold, R. (2002). Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Analytical Chemistry, 74(20), 5383–5392. Nesvizhskii, A I., Keller, A., Kolker, E., & Aebersold, R. (2003). A statistical model for identifying proteins by tandem mass spectrometry. Analytical Chemistry, 75(17), 4646–4658. Perez‐Riverol, Y., Bai, J., Bandla, C., García‐Seisdedos, D., Hewapathirana, S., Kamatchinathan, S., Kundu, D. J., Prakash, A., Frericks‐Zipper, A., Eisenacher, M., Walzer, M., Wang, S., Brazma, A., & Vizcaíno, J. A. (2021). The PRIDE database resources in 2022: A hub for mass spectrometry‐based proteomics evidences. Nucleic Acids Res., 50(D1), D543–D552. Nalpas, N., Hoyles, L., Anselm, V., Ganief, T., Martinez‐Gili, L., Grau, C., Droste‐Borel, I., Davidovic, L., Altafaj, X., Dumas, M. E., & Macek, B. (2021). An integrated workflow for enhanced taxonomic and functional coveragse of the mouse fecal metaproteome. Gut Microbes, 13(1), 1994836. Galperin, M. Y., Wolf, Y. I., Makarova, K. S., VeraAlvarez, R., Landsman, D., & Koonin, E. V. (2021). COG database update: Focus on microbial diversity, model organisms, and widespread pathogens. Nucleic Acids Res., 49(D1), D274–D281. Hernández‐Plaza, A., Szklarczyk, D., Botas, J., Cantalapiedra, C. P., Giner‐Lamia, J., Mende, D. R., Kirsch, R., Rattei, T., Letunic, I., Jensen, L. J., Bork, P., Von Mering, C., & Huerta‐Cepas, J. (2022). eggNOG 6.0: Enabling comparative genomics across 12 535 organisms. Nucleic Acids Res., 51(D1), D389–D394. Schoch, C. L., Ciufo, S., Domrachev, M., Hotton, C. L., Kannan, S., Khovanskaya, R., Leipe, D. D., McVeigh, R., O'Neill, K., Robbertse, B., Turner, S., & Karsch‐Mizrachi, I. (2020). NCBI Taxonomy: A comprehensive update on curation, resources and tools. Database (Oxford), 2020. Bateman, A., Martin, M. J., Orchard, S., Magrane, M., Ahmad, S., Alpi, E., Bowler‐Barnett, E. H., Britto, R., Bye‐A‐Jee, H., Cukura, A., Denny, P., Dogan, T., Ebenezer, T., Fan, J., Garmiri, P., Da Costa Gonzales, L. J., Hatton‐Ellis, E., Hussein, A., Ignatchenko, A., & Zhang, J. (2022). UniProt: The universal protein knowledgebase in 2023. Nucleic Acids Res., 51(D1), D523–D531. Consortium, T. G. O. (2019). The gene ontology resource: 20 years and still GOing strong. Nucleic Acids Res., 47(D1), D330–d338. Paysan‐Lafosse, T., Blum, M., Chuguransky, S., Grego, T., Pinto, B. L., Salazar, G. A., Bileschi, M. L., Bork, P., Bridge, A., Colwell, L., Gough, J., Haft, D. H., Letunić, I., Marchler‐Bauer, A., Mi, H., Natale, D. A., Orengo, C. A., Pandurangan, A. P., Rivoire, C., & Bateman, A. (2022). InterPro in 2022. Nucleic Acids Res., 51(D1), D418–D427. Mcdonald, A G., & Tipton, K F. (2023). Enzyme nomenclature and classification: The state of the art. FEBS J., 290(9), 2214–2231. Spellerberg, I F., & Fedor, P J. (2003). A tribute to Claude Shannon (1916–2001) and a plea for more rigorous use of species richness, species diversity and the ‘Shannon–Wiener’ Index. Glob Ecol Biogeogr, 12(3), 177–179. Wagner, B D., Grunwald, G K., Zerbe, G O., Mikulich‐Gilbertson, S K., Robertson, C E., Zemanick, E T., & Harris, J. K (2018). On the use of diversity measures in longitudinal sequencing studies of microbial communities. Frontiers in Microbiology, 9, . Ternes, D., Tsenkova, M., Pozdeev, V. I., Meyers, M., Koncina, E., Atatri, S., Schmitz, M., Karta, J., Schmoetten, M., Heinken, A., Rodriguez, F., Delbrouck, C., Gaigneaux, A., Ginolhac, A., Nguyen, T. T. D., Grandmougin, L., Frachet‐Bour, A., Martin‐Gallausiaux, C., Pacheco, M., & Letellier, E. (2022). The gut microbial metabolite formate exacerbates colorectal cancer progression. Nat Metab, 4(4), 458–475. Han, Y. W. (2015). Fusobacterium nucleatum: A commensal‐turned pathogen. Curr. Opin. Microbiol., 23, 141–147. Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A. L., Fang, T., Doncheva, N. T., Pyysalo, S., Bork, P., Jensen, L. J., & Von Mering, C. (2023). The STRING database in 2023: Protein‐protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res., 51(D1), D638–d646. Kanehisa, M., Furumichi, M., Sato, Y., Kawashima, M., & & Ishiguro‐Watanabe, M. (2023). KEGG for taxonomy‐based analysis of pathways and genomes. Nucleic Acids Res., 51(D1), D587–d592. Cummings, J. H., Pomare, E. W., Branch, W. J., Naylor, C. P., & Macfarlane, G. T. (1987). Short chain fatty acids in human large intestine, portal, hepatic and venous blood. Gut, 28(10), 1221–1227. Nogal, A., Valdes, A M., & Menni, C. (2021). The role of short‐chain fatty acids in the interplay between gut microbiota and diet in cardio‐metabolic health. Gut Microbes, 13(1), 1–24. Cong, J., Zhou, P., & Zhang, R. (2022). Intestinal microbiota‐derived short chain fatty acids in host health and disease. Nutrients, 14(9), 1977.
معلومات مُعتمدة:	R01 CA211892 United States CA NCI NIH HHS; P30CA125123 United States GF NIH HHS; R01 CA276173 United States CA NCI NIH HHS; R01CA211892 United States GF NIH HHS; P30 CA125123 United States CA NCI NIH HHS; R01CA276173 United States GF NIH HHS
فهرسة مساهمة:	Keywords: data processing and analysis; gut microbiome; mass spectrometry; metaproteomics; proteomics; taxonomy
تواريخ الأحداث:	Date Created: 20240602 Latest Revision: 20240711
رمز التحديث:	20240711
DOI:	10.1002/pmic.202400078
PMID:	38824665
قاعدة البيانات:	MEDLINE

View record at Wiley

Full Text Finder

الوصف
تدمد:	1615-9861
DOI:	10.1002/pmic.202400078