MMINP: A computational framework of microbe-metabolite interactions-based metabolic profiles predictor based on the O2-PLS algorithm

References

• Lloyd-Price J, Arze C, Ananthakrishnan AN, Schirmer M, Avila-Pacheco J, Poon TW, Andrews E, Ajami NJ, Bonham KS, Brislawn CJ, et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature. 2019;569(7758):655–14. doi:10.1038/s41586-019-1237-9.
   PubMed Web of Science ®Google Scholar
• Hsiao EY, McBride SW, Hsien S, Sharon G, Hyde ER, McCue T, Codelli J, Chow J, Reisman S, Petrosino J, et al. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cell. 2013;155(7):1451–1463. doi:10.1016/j.cell.2013.11.024.
   PubMed Web of Science ®Google Scholar
• Wong SH, Yu J. Gut microbiota in colorectal cancer: mechanisms of action and clinical applications. Nat Rev Gastroenterol Hepatol. 2019;16(11):690–704. doi:10.1038/s41575-019-0209-8.
   PubMed Web of Science ®Google Scholar
• Krautkramer KA, Fan J, Bäckhed F. Gut microbial metabolites as multi-kingdom intermediates. Nat Rev Microbiol. 2021;19(2):77–94. doi:10.1038/s41579-020-0438-4.
   PubMed Web of Science ®Google Scholar
• Quinn RA, Melnik AV, Vrbanac A, Fu T, Patras KA, Christy MP, Bodai Z, Belda-Ferre P, Tripathi A, Chung LK, et al. Global chemical effects of the microbiome include new bile-acid conjugations. Nature. 2020;579(7797):123–129. doi:10.1038/s41586-020-2047-9.
   PubMed Web of Science ®Google Scholar
• de Vos WM, Tilg H, Van Hul M, Cani PD, de Vos WM. Gut microbiome and health: mechanistic insights. Gut. 2022;71(5):1020–1032. doi:10.1136/gutjnl-2021-326789.
   PubMed Web of Science ®Google Scholar
• Bauermeister A, Mannochio-Russo H, Costa-Lotufo LV, Jarmusch AK, Dorrestein PC. Mass spectrometry-based metabolomics in microbiome investigations. Nat Rev Microbiol. 2022;20(3):143–160. doi:10.1038/s41579-021-00621-9.
   PubMed Web of Science ®Google Scholar
• Integrative HMP (iHMP) Research Network Consortium. The integrative human microbiome project. Nature. 2019;569:641–648. doi:10.1038/s41586-019-1238-8.
   PubMed Web of Science ®Google Scholar
• Pasolli E, Asnicar F, Manara S, Zolfo M, Karcher N, Armanini F, Beghini F, Manghi P, Tett A, Ghensi P, et al. Extensive unexplored human microbiome diversity revealed by over 150,000 genomes from metagenomes spanning age, geography, and lifestyle. Cell. 2019;176(3):649–662.e20. doi:10.1016/j.cell.2019.01.001.
   PubMed Web of Science ®Google Scholar
• Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30. doi:10.1093/nar/28.1.27.
   PubMed Web of Science ®Google Scholar
• Larsen PE, Collart FR, Field D, Meyer F, Keegan KP, Henry CS, McGrath J, Quinn J, Gilbert JA. Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset. Microb Informatics Exp. 2011;1(1):4. doi:10.1186/2042-5783-1-4.
   PubMedGoogle Scholar
• Noecker C, Eng A, Srinivasan S, Theriot CM, Young VB, Jansson JK, Fredricks DN, Borenstein E. Metabolic model-based integration of microbiome taxonomic and metabolomic profiles elucidates mechanistic links between ecological and metabolic variation. mSystems. 2016;1(1):e00013–15. doi:10.1128/mSystems.00013-15.
   PubMed Web of Science ®Google Scholar
• Mallick H, Franzosa EA, Mclver LJ, Banerjee S, Sirota-Madi A, Kostic AD, Clish CB, Vlamakis H, Xavier RJ, Huttenhower C, et al. Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences. Nat Commun. 2019;10(1):3136. doi:10.1038/s41467-019-10927-1.
   PubMedGoogle Scholar
• Xie J, Cho H, Lin BM, Pillai M, Heimisdottir LH, Bandyopadhyay D, Zou F, Roach J, Divaris K, Wu D, et al. Improved metabolite prediction using microbiome data-based elastic net models. Front Cell Infect Microbiol. 2021;11:734416. doi:10.3389/fcimb.2021.734416.
   PubMed Web of Science ®Google Scholar
• Trygg J, Wold S. O2-PLS, a two-block (X–Y) latent variable regression (LVR) method with an integral OSC filter. J Chemom. 2003;17(1):53–64. doi:10.1002/cem.775.
   Web of Science ®Google Scholar
• Trygg J. O2-PLS for qualitative and quantitative analysis in multivariate calibration. J Chemom. 2002;16(6):283–293. doi:10.1002/cem.724.
   Web of Science ®Google Scholar
• Wold S, Trygg J, Berglund A, Antti H. Some recent developments in PLS modeling. Chemometr Intell Lab Sys. 2001;58(2):131–150. doi:10.1016/S0169-7439(01)00156-3.
   Web of Science ®Google Scholar
• Wold S, Antti H, Lindgren F, Öhman J. Orthogonal signal correction of near-infrared spectra. Chemometr Intell Lab Sys. 1998;44(1–2):175–185. doi:10.1016/S0169-7439(98)00109-9.
   Web of Science ®Google Scholar
• Chu SH, Huang M, Kelly RS, Benedetti E, Siddiqui JK, Zeleznik OA, Pereira A, Herrington D, Wheelock C, Krumsiek J, et al. Integration of metabolomic and other omics data in population-based study designs: an epidemiological perspective. Metabolites. 2019;9(6):117. doi:10.3390/metabo9060117.
   PubMed Web of Science ®Google Scholar
• Louca S, Polz MF, Mazel F, Albright MBN, Huber JA, O’Connor MI, Ackermann M, Hahn AS, Srivastava DS, Crowe SA, et al. Function and functional redundancy in microbial systems. Nat Ecol Evol. 2018;2(6):936–943. doi:10.1038/s41559-018-0519-1.
   PubMed Web of Science ®Google Scholar
• van den Berg RA, Hoefsloot HC, Westerhuis JA, Smilde AK, van der Werf MJ, van den Berg RA. Centering, scaling, and transformations: improving the biological information content of metabolomics data. Bmc Genom. 2006;7(1):142. doi:10.1186/1471-2164-7-142.
   PubMedGoogle Scholar
• Franzosa EA, Sirota-Madi A, Avila-Pacheco J, Fornelos N, Haiser HJ, Reinker S, Vatanen T, Hall AB, Mallick H, McIver LJ, et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat microbiol. 2019;4(2):293–305. doi:10.1038/s41564-018-0306-4.
   PubMed Web of Science ®Google Scholar
• Bouhaddani SE, Uh H-W, Jongbloed G, Hayward C, Klarić L, Kiełbasa SM, Houwing-Duistermaat J. Integrating omics datasets with the OmicsPLS package. BMC Bioinform. 2018;19(1):371. doi:10.1186/s12859-018-2371-3.
   PubMedGoogle Scholar
• Zhou Y, Hu G, Wang MC. Host and microbiota metabolic signals in aging and longevity. Nat Chem Biol. 2021;17(10):1027–1036. doi:10.1038/s41589-021-00837-z.
   PubMed Web of Science ®Google Scholar
• Lien EC, Westermark AM, Zhang Y, Yuan C, Li Z, Lau AN, Sapp KM, Wolpin BM, Vander Heiden MG. Low glycaemic diets alter lipid metabolism to influence tumour growth. Nature. 2021;599(7884):302–307. doi:10.1038/s41586-021-04049-2.
   PubMed Web of Science ®Google Scholar
• Liu J, Lahousse L, Nivard MG, Bot M, Chen L, van Klinken JB, Thesing CS, Beekman M, van den Akker EB, Slieker RC, et al. Integration of epidemiologic, pharmacologic, genetic and gut microbiome data in a drug–metabolite atlas. Nat Med. 2020;26(1):110–117. doi:10.1038/s41591-019-0722-x.
   PubMed Web of Science ®Google Scholar
• Statistical power analysis for the behavioral sciences. Routledge; 2013
   Google Scholar
• Schirmer M, Garner A, Vlamakis H, Xavier RJ. Microbial genes and pathways in inflammatory bowel disease. Nat Rev Microbiol. 2019;17(8):497–511. doi:10.1038/s41579-019-0213-6.
   PubMed Web of Science ®Google Scholar
• Xiang MSW, Tan JK, Macia L. Fatty acids, gut bacteria, and immune cell function. In: The molecular nutrition of fats. Elsevier; 2019. p. 151–164.
   Google Scholar
• Heimerl S, Moehle C, Zahn A, Boettcher A, Stremmel W, Langmann T, Schmitz G. Alterations in intestinal fatty acid metabolism in inflammatory bowel disease. Biochim Biophys Acta. 2006;1762(3):341–350. doi:10.1016/j.bbadis.2005.12.006.
   PubMed Web of Science ®Google Scholar
• Hosomi K, Kiyono H, Kunisawa J. Fatty acid metabolism in the host and commensal bacteria for the control of intestinal immune responses and diseases. Gut Microbes. 2020;11(3):276–284. doi:10.1080/19490976.2019.1612662.
   PubMed Web of Science ®Google Scholar
• Asanuma N. Effect of dietary ceramide and glucosylceramide on the alleviation of experimental inflammatory bowel disease in mice. J Oleo Sci. 2022;71(9):1397–1402. doi:10.5650/jos.ess22169.
   PubMed Web of Science ®Google Scholar
• Bouhaddani SE, Houwing-Duistermaat J, Salo P, Perola M, Jongbloed G, Uh H-W. Evaluation of O2PLS in Omics data integration. BMC Bioinform. 2016;17:S11. doi:10.1186/s12859-015-0854-z.
   PubMed Web of Science ®Google Scholar
• Andersen CM, Bro R. Variable selection in regression-a tutorial. J Chemom. 2010;24(11–12):728–737. doi:10.1002/cem.1360.
   Web of Science ®Google Scholar
• Galindo-Prieto B, Trygg J, Geladi P. A new approach for variable influence on projection (VIP) in O2PLS models. Chemometr Intell Lab Sys. 2017;160:110–124. doi:10.1016/j.chemolab.2016.11.005.
   Web of Science ®Google Scholar
• Muller E, Algavi YM, Borenstein E. A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations. Microbiome. 2021;9(1):203. doi:10.1186/s40168-021-01149-z.
   PubMed Web of Science ®Google Scholar
• Yu G, Smith DK, Zhu H, Guan Y, Lam T-Y, McInerny G. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol Evol. 2017;8(1):28–36. doi:10.1111/2041-210X.12628.
   Web of Science ®Google Scholar
• Xu S, Dai Z, Guo P, Fu X, Liu S, Zhou L, Tang W, Feng T, Chen M, Zhan L, et al. ggtreeExtra: compact visualization of richly annotated phylogenetic data. Mol Biol Evol. 2021;38(9):4039–4042. doi:10.1093/molbev/msab166.
   PubMed Web of Science ®Google Scholar
• Wu T, Hu E, Xu S, Chen M, Guo P, Dai Z, Feng T, Zhou L, Tang W, Zhan L, et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation (Camb). 2021;2(3):100141. doi:10.1016/j.xinn.2021.100141.
   PubMedGoogle Scholar