Almond Consumption for 8 Weeks Altered Host and Microbial Metabolism in Comparison to a Control Snack in Young Adults

References

• Rezzi S, Ramadan Z, Fay LB, Kochhar S. Nutritional metabonomics: applications and perspectives. J Proteome Res. 2007;6(2):513–25. doi:10.1021/pr060522z.
   Web of Science ®Google Scholar
• Grapov D, Adams SH, Pedersen TL, Garvey WT, Newman JW. Type 2 diabetes associated changes in the plasma non-esterified fatty acids, oxylipins and endocannabinoids. PLoS One. 2012;7(11):e48852. doi:10.1371/journal.pone.0048852.
   PubMed Web of Science ®Google Scholar
• Adams SH, Hoppel CL, Lok KH, Zhao L, Wong SW, Minkler PE, Hwang DH, Newman JW, Garvey WT. Plasma acylcarnitine profiles suggest incomplete long-chain fatty acid beta-oxidation and altered tricarboxylic acid cycle activity in type 2 diabetic African-American women. J Nutr. 2009;139(6):1073–81. doi:10.3945/jn.108.103754.
   PubMed Web of Science ®Google Scholar
• Fiehn O, Garvey WT, Newman JW, Lok KH, Hoppel CL, Adams SH. Plasma metabolomic profiles reflective of glucose homeostasis in non-diabetic and type 2 diabetic obese African-American women. PLoS One. 2010;5(12):e15234. [Database] doi:10.1371/journal.pone.0015234.
   PubMed Web of Science ®Google Scholar
• Gibbons H, O’Gorman A, Brennan L. Metabolomics as a tool in nutritional research. Curr Opin Lipidol. 2015;26(1):30–4. doi:10.1097/MOL.0000000000000140.
   PubMed Web of Science ®Google Scholar
• Cross AJ, Major JM, Sinha R. Urinary biomarkers of meat consumption. Cancer Epidemiol Biomarkers Prev. 2011;20(6):1107–11. doi:10.1158/1055-9965.EPI-11-0048.
   Web of Science ®Google Scholar
• Rothwell JA, Fillâtre Y, Martin J-F, Lyan B, Pujos-Guillot E, Fezeu L, Hercberg S, Comte B, Galan P, Touvier M, et al. New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects. PLoS One. 2014;9(4):e93474. doi:10.1371/journal.pone.0093474.
   PubMed Web of Science ®Google Scholar
• Heinzmann SS, Brown IJ, Chan Q, Bictash M, Dumas M-E, Kochhar S, Stamler J, Holmes E, Elliott P, Nicholson JK. Metabolic profiling strategy for discovery of nutritional biomarkers: proline betaine as a marker of citrus consumption. Am J Clin Nutr. 2010;92(2):436–43. doi:10.3945/ajcn.2010.29672.
   Web of Science ®Google Scholar
• Edmands WMB, Beckonert OP, Stella C, Campbell A, Lake BG, Lindon JC, Holmes E, Gooderham NJ. Identification of human urinary biomarkers of cruciferous vegetable consumption by metabonomic profiling. J Proteome Res. 2011;10(10):4513–21. doi:10.1021/pr200326k.
   PubMed Web of Science ®Google Scholar
• Dhillon J, Ferreira CR, Sobreira TJP, Mattes RD. Multiple reaction monitoring profiling to assess compliance with an almond consumption intervention. Curr Dev Nutr. 2017;1(9):e001545. doi:10.3945/cdn.117.001545.
   Google Scholar
• Andersen M-BS, Kristensen M, Manach C, Pujos-Guillot E, Poulsen SK, Larsen TM, Astrup A, Dragsted L. Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics. Anal Bioanal Chem. 2014;406(7):1829–44. doi:10.1007/s00216-013-7498-5.
   PubMed Web of Science ®Google Scholar
• Goodacre R. Metabolomics of a superorganism. J Nutr. 2007;137(1 Suppl):259S–66S. doi:10.1093/jn/137.1.259S.
   Web of Science ®Google Scholar
• Marcobal A, Kashyap PC, Nelson TA, Aronov PA, Donia MS, Spormann A, Fischbach MA, Sonnenburg JL. A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice. ISME J. 2013;7(10):1933–43. doi:10.1038/ismej.2013.89.
   PubMed Web of Science ®Google Scholar
• Kim Y, Keogh J, Clifton PM. Nuts and cardio-metabolic disease: a review of meta-analyses. Nutrients. 2018:10(12).
   Web of Science ®Google Scholar
• Garcia-Aloy M, Llorach R, Urpi-Sarda M, Tulipani S, Estruch R, Martínez-González MA, Corella D, Fitó M, Ros E, Salas-Salvadó J, et al. Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the predimed study. J Proteome Res. 2014;13(7):3476–83. doi:10.1021/pr500425r.
   PubMed Web of Science ®Google Scholar
• Hernández-Alonso P, Cañueto D, Giardina S, Salas-Salvadó J, Cañellas N, Correig X, Bulló M. Effect of pistachio consumption on the modulation of urinary gut microbiota-related metabolites in prediabetic subjects. J Nutr Biochem. 2017;45:48–53. doi:10.1016/j.jnutbio.2017.04.002.
   Web of Science ®Google Scholar
• Tulipani S, Llorach R, Jáuregui O, López-Uriarte P, Garcia-Aloy M, Bullo M, Salas-Salvadó J, Andrés-Lacueva C. Metabolomics unveils urinary changes in subjects with metabolic syndrome following 12-week nut consumption. J Proteome Res. 2011;10(11):5047–58. doi:10.1021/pr200514h.
   PubMed Web of Science ®Google Scholar
• Mora-Cubillos X, Tulipani S, Garcia-Aloy M, Bulló M, Tinahones FJ, Andres-Lacueva C. Plasma metabolomic biomarkers of mixed nuts exposure inversely correlate with severity of metabolic syndrome. Mol Nutr Food Res. 2015;59(12):2480–90. doi:10.1002/mnfr.201500549.
   Web of Science ®Google Scholar
• Dhillon J, Thorwald M, De La Cruz N, Vu E, Asghar SA, Kuse QD, Rios LK, Ortiz RM. Glucoregulatory and cardiometabolic profiles of almond vs. cracker snacking for 8 weeks in young adults: a randomized controlled trial. Nutrients. 2018;10(8):960. doi:10.3390/nu10080960.
   PubMed Web of Science ®Google Scholar
• Dhillon J, Li Z, Ortiz RM. Almond snacking for 8 weeks increases alpha-diversity of the gastrointestinal microbiome and decreases bacteroides fragilis abundance compared to an isocaloric snack in college freshmen. Curr Dev Nutr. 2019;3(8).
   Google Scholar
• Fiehn O, Wohlgemuth G, Scholz M, Kind T, Lee DY, Lu Y, Moon S, Nikolau B. Quality control for plant metabolomics: reporting MSI-compliant studies. Plant J Cell Mol Biol. 2008;53(4):691–704. doi:10.1111/j.1365-313X.2007.03387.x.
   PubMed Web of Science ®Google Scholar
• Kind T, Tolstikov V, Fiehn O, Weiss RH. A comprehensive urinary metabolomic approach for identifying kidney cancerr. Anal Biochem. 2007;363(2):185–95. doi:10.1016/j.ab.2007.01.028.
   Web of Science ®Google Scholar
• Fiehn O. Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry. Trends Anal Chem TRAC. 2008;27(3):261–9. doi:10.1016/j.trac.2008.01.007.
   Web of Science ®Google Scholar
• Fiehn O, Wohlgemuth G, Scholz M. Setup and annotation of metabolomic experiments by integrating biological and mass spectrometric metadata. In: Ludäscher B, Raschid L, editors. Data Integrity in Life Sciences. Berlin, Heidelberg: Springer; 2005. p. 224–39.
   Google Scholar
• Scholz M, Fiehn O. SetupX–a public study design database for metabolomic projects. Pac Symp Biocomput. 2007;12:169–80.
   Google Scholar
• Matyash V, Liebisch G, Kurzchalia TV, Shevchenko A, Schwudke D. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J Lipid Res. 2008;49(5):1137–46. doi:10.1194/jlr.D700041-JLR200.
   PubMed Web of Science ®Google Scholar
• Tsugawa H, Cajka T, Kind T, Ma Y, Higgins B, Ikeda K, Kanazawa M, VanderGheynst J, Fiehn O, Arita M. MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat Methods. 2015;12(6):523–6. doi:10.1038/nmeth.3393.
   PubMed Web of Science ®Google Scholar
• Chongxiu S, Kenan A, Wang Ying I, Foster Greg A, Radecke Christopher E, Kayan T, Edwards Christina M, Facciotti Marc T, Armstrong Ehrin J, Knowlton Anne A, et al. IRF-1 and miRNA126 modulate VCAM-1 expression in response to a high-fat meal. Circ Res. 2012;111:1054–64.
   Web of Science ®Google Scholar
• Smedes F. Determination of total lipid using non-chlorinated solvents. Analyst. 1999;124(11):1711–8. doi:10.1039/a905904k.
   Web of Science ®Google Scholar
• Fan S, Kind T, Cajka T, Hazen SL, Tang WHW, Kaddurah-Daouk R, Irvin MR, Arnett DK, Barupal DK, Fiehn O. Systematic error removal using random forest for normalizing large-scale untargeted lipidomics data. Anal Chem. 2019;91(5):3590–6. doi:10.1021/acs.analchem.8b05592.
   Web of Science ®Google Scholar
• Barupal DK, Fiehn O. Chemical Similarity Enrichment Analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets. Sci Rep. 2017;7(1):1–11. doi:10.1038/s41598-017-15231-w.
   Google Scholar
• Barupal DK, Haldiya PK, Wohlgemuth G, Kind T, Kothari SL, Pinkerton KE, Fiehn O. MetaMapp: mapping and visualizing metabolomic data by integrating information from biochemical pathways and chemical and mass spectral similarity. BMC Bioinform. 2012;13:99. doi:10.1186/1471-2105-13-99.
   PubMed Web of Science ®Google Scholar
• Cao Y, Jiang T, Girke T. A maximum common substructure-based algorithm for searching and predicting drug-like compounds. Bioinformatics. 2008;24(13):i366–i374. doi:10.1093/bioinformatics/btn186.
   Web of Science ®Google Scholar
• Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. [Database] doi:10.1101/gr.1239303.
   PubMed Web of Science ®Google Scholar
• Su G, Kuchinsky A, Morris JH, States DJ, Meng F. GLay: community structure analysis of biological networks. Bioinformatics. 2010;26(24):3135–7. doi:10.1093/bioinformatics/btq596.
   PubMed Web of Science ®Google Scholar
• Ye Y, Doak TG. A parsimony approach to biological pathway reconstruction/inference for genomes and metagenomes. PLoS Comput Biol. 2009;5(8):e1000465. doi:10.1371/journal.pcbi.1000465.
   PubMed Web of Science ®Google Scholar
• Douglas GM, Maffei VJ, Zaneveld JR, Yurgel SN, Brown JR, Taylor CM, Huttenhower C, Langille MGI. PICRUSt2 for prediction of metagenome functions. Nat Biotechnol. 2020;38(6):685–8. doi:10.1038/s41587-020-0548-6.
   PubMed Web of Science ®Google Scholar
• Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47. doi:10.1093/nar/gkv007.
   PubMed Web of Science ®Google Scholar
• Law CW, Chen Y, Shi W, Smyth GK. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014;15(2):R29. doi:10.1186/gb-2014-15-2-r29.
   PubMed Web of Science ®Google Scholar
• Chong J, Liu P, Zhou G, Xia J. Using microbiomeanalyst for comprehensive statistical, functional, and meta-analysis of microbiome data. Nat Protoc. 2020;15(3):799–821. doi:10.1038/s41596-019-0264-1.
   PubMed Web of Science ®Google Scholar
• Shaffer M, Thurimella K, Quinn K, Doenges K, Zhang X, Bokatzian S, Reisdorph N, Lozupone CA. AMON: annotation of metabolite origins via networks to integrate microbiome and metabolome data. BMC Bioinform. 2019;20(1):614. doi:10.1186/s12859-019-3176-8.
   Web of Science ®Google Scholar
• Borenstein Lab. MIMOSA2 [Internet]. 2020. Available from: http://borensteinlab.com/software_MIMOSA2.html.
   Google 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).
   Web of Science ®Google Scholar
• Jambazian PR, Haddad E, Rajaram S, Tanzman J, Sabaté J . Almonds in the diet simultaneously improve plasma alpha-tocopherol concentrations and reduce plasma lipids. J Am Diet Assoc. 2005;105(3):449–54. doi:10.1016/j.jada.2004.12.002.
   Google Scholar
• Brigelius-Flohé R, Kelly FJ, Salonen JT, Neuzil J, Zingg J-M, Azzi A. The European perspective on vitamin E: current knowledge and future research. Am J Clin Nutr. 2002;76(4):703–16. doi:10.1093/ajcn/76.4.703.
   Web of Science ®Google Scholar
• Dimitrov NV, Meyer C, Gilliland D, Ruppenthal M, Chenoweth W, Malone W. Plasma tocopherol concentrations in response to supplemental vitamin E. Am J Clin Nutr. 1991;53(3):723–9. doi:10.1093/ajcn/53.3.723.
   PubMed Web of Science ®Google Scholar
• Reaven PD, Witztum JL. Comparison of supplementation of RRR-alpha-tocopherol and racemic alpha-tocopherol in humans. Effects on lipid levels and lipoprotein susceptibility to oxidation. Arterioscler Thromb. 1993;13(4):601–8. doi:10.1161/01.ATV.13.4.601.
   Google Scholar
• Law S-H, Chan M-L, Marathe GK, Parveen F, Chen C-H, Ke L-Y. An updated review of lysophosphatidylcholine metabolism in human diseases. Int J Mol Sci. 2019;20(5).
   Web of Science ®Google Scholar
• Heimerl S, Fischer M, Baessler A, Liebisch G, Sigruener A, Wallner S, Schmitz G. Alterations of plasma lysophosphatidylcholine species in obesity and weight loss. PLoS ONE. 2014;9(10).
   Web of Science ®Google Scholar
• Wallace M, Morris C, O’Grada CM, Ryan M, Dillon ET, Coleman E, Gibney ER, Gibney MJ, Roche HM, Brennan L. Relationship between the lipidome, inflammatory markers and insulin resistance. Mol Biosyst. 2014;10(6):1586–95. doi:10.1039/c3mb70529c.
   Google Scholar
• Zhang J-M, An J. Cytokines, inflammation, and pain. Int Anesthesiol Clin. 2007;45(2):27–37. doi:10.1097/AIA.0b013e318034194e.
   PubMedGoogle Scholar
• Nishi S, Kendall CWC, Gascoyne A-M, Bazinet RP, Bashyam B, Lapsley KG, Augustin LSA, Sievenpiper JL, Jenkins DJA. Effect of almond consumption on the serum fatty acid profile: a dose-response study. Br J Nutr. 2014;112(7):1137–46. doi:10.1017/S0007114514001640.
   Web of Science ®Google Scholar
• Grundy MM, Lapsley K, Ellis PR. A review of the impact of processing on nutrient bioaccessibility and digestion of almonds. Int J Food Sci Technol. 2016;51(9):1937–46. doi:10.1111/ijfs.13192.
   PubMed Web of Science ®Google Scholar
• Physiological regulation of NEFA availability: lipolysis pathway. Proceedings of the Nutrition Society, Cambridge Core [Internet]. [cited 2021 Apr 28]. Available from: https://www.cambridge.org/core/journals/proceedings-of-the-nutrition-society/article/physiological-regulation-of-nefa-availability-lipolysis-pathway/81DE2F9FCB84C6A38140D2D7EA63C5B7.
   Google Scholar
• Lim J-H, Gerhart-Hines Z, Dominy JE, Lee Y, Kim S, Tabata M, Xiang YK, Puigserver P. Oleic acid stimulates complete oxidation of fatty acids through protein kinase A-dependent activation of SIRT1-PGC1α complex. J Biol Chem. 2013;288(10):7117–26. doi:10.1074/jbc.M112.415729.
   PubMed Web of Science ®Google Scholar
• Yamada K, Mizukoshi E, Seike T, Horii R, Terashima T, Iida N, Kitahara M, Sunagozaka H, Arai K, Yamashita T, et al. Serum C16:1n7/C16:0 ratio as a diagnostic marker for non-alcoholic steatohepatitis. J Gastroenterol Hepatol. 2019;34(10):1829–35. doi:10.1111/jgh.14654.
   Web of Science ®Google Scholar
• Lankinen MA, Stančáková A, Uusitupa M, Ågren J, Pihlajamäki J, Kuusisto J, Schwab U, Laakso M. Plasma fatty acids as predictors of glycaemia and type 2 diabetes. Diabetologia. 2015;58(11):2533–44. doi:10.1007/s00125-015-3730-5.
   PubMed Web of Science ®Google Scholar
• Yuan C, Spiegelman D, Rimm EB, Rosner BA, Stampfer MJ, Barnett JB, Chavarro JE, Subar AF, Sampson LK, Willett WC. Validity of a dietary questionnaire assessed by comparison with multiple weighed dietary records or 24-hour recalls. Am J Epidemiol. 2017;185(7):570–84. doi:10.1093/aje/kww104.
   PubMed Web of Science ®Google Scholar
• Dyall SC. Long-chain omega-3 fatty acids and the brain: a review of the independent and shared effects of EPA, DPA and DHA. Front Aging Neurosci. 2015;7:52.doi: 10.3389/fnagi.2015.00052.
   Web of Science ®Google Scholar
• Berg JM, Tymoczko JL, Stryer L. The citric acid cycle. In Biochemistry. 5th ed. New York: W H Freeman; 2002.
   Google Scholar
• An Y, Xu W, Li H, Lei H, Zhang L, Hao F, Duan Y, Yan X, Zhao Y, Wu J, et al. High-fat diet induces dynamic metabolic alterations in multiple biological matrices of rats. J Proteome Res. 2013;12(8):3755–68. doi:10.1021/pr400398b.
   Web of Science ®Google Scholar
• Guasch-Ferré M, Santos JL, Martínez-González MA, Clish CB, Razquin C, Wang D, Liang L, Li J, Dennis C, Corella D, et al. Glycolysis/gluconeogenesis- and tricarboxylic acid cycle-related metabolites, Mediterranean diet, and type 2 diabetes. Am J Clin Nutr. 2020;111(4):835–44. doi:10.1093/ajcn/nqaa016.
   Web of Science ®Google Scholar
• Randle PJ, Garland PB, Hales CN, Newsholme EA. The glucose fatty-acid cycle. Its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet Lond Engl. 1963;1:785–9.
   PubMed Web of Science ®Google Scholar
• Chen C-M, Liu J-F, Li S-C, Huang C-L, Hsirh A-T, Weng S-F, Chang M-L, Li H-T, Mohn E, Chen C. YO. Almonds ameliorate glycemic control in Chinese patients with better controlled type 2 diabetes: a randomized, crossover, controlled feeding trial. Nutr Metab. 2017;14:51.
   Google Scholar
• Gulati S, Misra A, Pandey R. Effect of almond supplementation on glycemia and cardiovascular risk factors in Asian Indians in North India with type 2 diabetes mellitus: a 24-week study. Metab Syndr Relat Disord. 2017;15(2):98–105. doi:10.1089/met.2016.0066.
   PubMed Web of Science ®Google Scholar
• Josse AR, Kendall CWC, Augustin LSA, Ellis PR, Jenkins DJA. Almonds and postprandial glycemia-a dose-response study. Metabolism. 2007;56(3):400–4. doi:10.1016/j.metabol.2006.10.024.
   PubMed Web of Science ®Google Scholar
• Ren M, Zhang H, Qi J, Hu A, Jiang Q, Hou Y, Feng Q, Ojo O, Wang X. An almond-based low carbohydrate diet improves depression and glycometabolism in patients with type 2 diabetes through modulating gut microbiota and GLP-1: a randomized controlled trial. Nutrients. 2020;12(10):3036. doi:10.3390/nu12103036.
   PubMed Web of Science ®Google Scholar
• Wien M, Bleich D, Raghuwanshi M, Gould-Forgerite S, Gomes J, Monahan-Couch L, Oda K. Almond consumption and cardiovascular risk factors in adults with prediabetes. J Am Coll Nutr. 2010;29(3):189–97. doi:10.1080/07315724.2010.10719833.
   PubMed Web of Science ®Google Scholar
• Stratton SL, Horvath TD, Bogusiewicz A, Matthews NI, Henrich CL, Spencer HJ, Moran JH, Mock DM. Plasma concentration of 3-hydroxyisovaleryl carnitine is an early and sensitive indicator of marginal biotin deficiency in humans. Am J Clin Nutr. 2010;92(6):1399–405. doi:10.3945/ajcn.110.002543.
   PubMed Web of Science ®Google Scholar
• Horvath TD, Stratton SL, Bogusiewicz A, Pack L, Moran J, Mock DM. Quantitative measurement of plasma 3-hydroxyisovaleryl carnitine by LC-MS/MS as a novel biomarker of biotin status in humans. Anal Chem. 2010;82(10):4140–4. doi:10.1021/ac1003213.
   Web of Science ®Google Scholar
• National Institutes of Health. Office of dietary supplements - biotin [Internet]. [cited 2021 Dec 7]. Available from: https://ods.od.nih.gov/factsheets/Biotin-HealthProfessional/.
   Google Scholar
• Almagro-Moreno S, Boyd EF. Bacterial catabolism of nonulosonic (sialic) acid and fitness in the gut. Gut Microbes. 2010;1(1):45–50. doi:10.4161/gmic.1.1.10386.
   PubMed Web of Science ®Google Scholar
• Ottosson F, Brunkwall L, Smith E, Orho-Melander M, Nilsson PM, Fernandez C, Melander O. The gut microbiota-related metabolite phenylacetylglutamine associates with increased risk of incident coronary artery disease. J Hypertens. 2020;38(12):2427–34. doi:10.1097/HJH.0000000000002569.
   PubMedGoogle Scholar
• Li M, Wang B, Zhang M, Rantalainen M, Wang S, Zhou H, Zhang Y, Shen J, Pang X, Zhang M, et al. Symbiotic gut microbes modulate human metabolic phenotypes. Proc Natl Acad Sci U S A. 2008;105(6):2117–22. doi:10.1073/pnas.0712038105.
   PubMed Web of Science ®Google Scholar
• He M. Pipecolic acid in microbes: biosynthetic routes and enzymes. J Ind Microbiol Biotechnol. 2006;33(6):401–7. doi:10.1007/s10295-006-0078-3.
   PubMed Web of Science ®Google Scholar
• Ortiz-Castro R, Díaz-Pérez C, Martínez-Trujillo M, Río Rd, Campos-García J, López-Bucio J. Transkingdom signaling based on bacterial cyclodipeptides with auxin activity in plants. Proc Natl Acad Sci U S A. 2011;108(17):7253–8. doi:10.1073/pnas.1006740108.
   PubMed Web of Science ®Google Scholar
• Holden MT, Ram Chhabra S, de Nys R, Stead P, Bainton NJ, Hill PJ, Manefield M, Kumar N, Labatte M, England D, et al. Quorum-sensing cross talk: isolation and chemical characterization of cyclic dipeptides from Pseudomonas aeruginosa and other gram-negative bacteria. Mol Microbiol. 1999;33(6):1254–66. doi:10.1046/j.1365-2958.1999.01577.x.
   PubMed Web of Science ®Google Scholar
• Edlund A, Garg N, Mohimani H, Gurevich A, He X, Shi W, Dorrestein PC, McLean JS. Metabolic fingerprints from the human oral microbiome reveal a vast knowledge gap of secreted small peptidic molecules. mSystems. 2017;2(4):e00058-17.
   Web of Science ®Google Scholar
• Zhang LS, Davies SS. Microbial metabolism of dietary components to bioactive metabolites: opportunities for new therapeutic interventions. Genome Med. 2016;8(1):46.
   Web of Science ®Google Scholar