HS-SPME-GC-MS approach for the analysis of volatile salivary metabolites and application in a case study for the indirect assessment of gut microbiota

Abstract

In this work, a straightforward analytical approach based on headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry was developed for the analysis of salivary volatile organic compounds without any prior derivatization step. With a sample volume of 500 μL, optimal conditions were achieved by allowing the sample to equilibrate for 10 min at 50 °C and then extracting the samples for 10 min at the same temperature, using a carboxen/polydimethylsiloxane fibre. The method allowed the simultaneous identification and quantification of 20 compounds in sample headspace, including short-chain fatty acids and their derivatives which are commonly analysed after analyte derivatization. The proof of applicability of the methodology was performed with a case study regarding the analysis of the dynamics of volatile metabolites in saliva of a single subject undergoing 5-day treatment with rifaximin antibiotic. Non-stimulated saliva samples were collected over 3 weeks from a nominally healthy volunteer before, during, and after antibiotic treatment. The variations of some metabolites, known to be produced by the microbiota and by bacteria that are susceptible to antibiotics, suggest that the study of the dynamics of salivary metabolites can be an excellent indirect method for analysing the gut microbiota. This approach is novel from an analytical standpoint, and it encourages further studies combining saliva metabolite profiles and gut microbiota dynamics.

Graphical abstract

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. 1.

    Panek M, Paljetak HC, Baresic A, Peric M, Matijasic M, Lojkic I, et al. Methodology challenges in studying human gut microbiota - effects of collection, storage, DNA extraction and next generation sequencing technologies. Sci Rep. 2018;8. https://doi.org/10.1038/s41598-018-23296-4.

  2. 2.

    Alonso A, Marsal S, Julià A. Analytical methods in untargeted metabolomics: state of the art in 2015. Front Bioeng Biotechnol. 2015. https://doi.org/10.3389/fbioe.2015.00023.

  3. 3.

    Lenz EM, Wilson ID. Analytical strategies in metabonomics. J Proteome Res. 2007;6.2:443–58.

    CAS  Article  Google Scholar 

  4. 4.

    Moosmang S, Pitscheider M, Sturm S, Seger C, Tilg H, Halabalaki M, et al. Metabolomic analysis—addressing NMR and LC-MS related problems in human feces sample preparation. Clin Chim Acta. 2017. https://doi.org/10.1016/j.cca.2017.10.029.

    CAS  Article  Google Scholar 

  5. 5.

    Santiago A, Panda S, Mengels G, Martinez X, Azpiroz F, Dore J, et al. Processing faecal samples: a step forward for standards in microbial community analysis. BMC Microbiol. 2014;14:112. https://doi.org/10.1186/1471-2180-14-112.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Lawal O, Muhamadali H, Ahmed WM, White IR, Nijsen TME, Goodacre R, et al. Headspace volatile organic compounds from bacteria implicated in ventilator-associated pneumonia analysed by TD-GC/MS. J Breath Res. 2018;12:26002. https://doi.org/10.1088/1752-7163/aa8efc.

    CAS  Article  Google Scholar 

  7. 7.

    Kamal F, Kumar S, Singanayagam A, Edwards M, Romano A, Veslkov K, et al. Volatile organic compound (VOC) analysis to differentiate between bacterial and viral respiratory infections in COPD. Eur Respir J. 2018;52:PA5301. https://doi.org/10.1183/13993003.congress-2018.PA5301.

    Article  Google Scholar 

  8. 8.

    Amann A, Costello Bde L, Miekisch W, Schubert J, Buszewski B, Pleil J, et al. The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. J Breath Res. 2014;8:34001. https://doi.org/10.1088/1752-7155/8/3/034001.

    CAS  Article  Google Scholar 

  9. 9.

    Smolinska A, Tedjo DI, Blanchet L, Bodelier A, Pierik MJ, Masclee AAM, et al. Volatile metabolites in breath strongly correlate with gut microbiome in CD patients. Anal Chim Acta. 2018. https://doi.org/10.1016/j.aca.2018.03.046.

    CAS  Article  Google Scholar 

  10. 10.

    Michalke B, Rossbach B, Göen T, Schäferhenrich A, Scherer G, Hartwig A. Saliva as a matrix for human biomonitoring in occupational and environmental medicine [Biomonitoring Methods, 2015]. MAK-Collection Occup Heal Saf. 2016. https://doi.org/10.1002/3527600418.bisalivae2115.

  11. 11.

    Biagi S, Ghimenti S, Onor M, Bramanti E. Simultaneous determination of lactate and pyruvate in human sweat using reversed-phase high-performance liquid chromatography: a noninvasive approach. Biomed Chromatogr. 2012:26. https://doi.org/10.1002/bmc.2713.

    CAS  Article  Google Scholar 

  12. 12.

    Bessonneau V, Boyaci E, Maciazek-Jurczyk M, Pawliszyn J. In vivo solid phase microextraction sampling of human saliva for non-invasive and on-site monitoring. Anal Chim Acta. 2015;856:35–45. https://doi.org/10.1016/j.aca.2014.11.029.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Bonne NJ, Wong DTW. Salivary biomarker development using genomic, proteomic and metabolomic approaches. Genome Med. 2012;4. https://doi.org/10.1186/gm383.

    Article  Google Scholar 

  14. 14.

    Lomonaco T, Ghimenti S, Piga I, Biagini D, Onor M, Fuoco R, et al. Influence of sampling on the determination of warfarin and warfarin alcohols in oral fluid. PLoS One. 2014;9. https://doi.org/10.1371/journal.pone.0114430.

    Article  Google Scholar 

  15. 15.

    Lomonaco T, Ghimenti S, Biagini D, Bramanti E, Onor M, Bellagambi FG, et al. The effect of sampling procedures on the urate and lactate concentration in oral fluid. Microchem J. 2018. https://doi.org/10.1016/j.microc.2017.02.032.

    CAS  Article  Google Scholar 

  16. 16.

    Cuevas-Cordoba B, Santiago-Garcia J. Saliva: a fluid of study for OMICS. Omi J Integr Biol. 2014;18:87–97. https://doi.org/10.1089/omi.2013.0064.

    CAS  Article  Google Scholar 

  17. 17.

    Lima DP, Diniz DG, Moimaz SAS, Sumida DH, Okamoto AC. Saliva: reflection of the body. Int J Infect Dis. 2010;14:e184–8. https://doi.org/10.1016/j.ijid.2009.04.022.

    Article  PubMed  Google Scholar 

  18. 18.

    Dame ZT, Aziat F, Mandal R, Krishnamurthy R, Bouatra S, Borzouie S, et al. The human saliva metabolome. Metabolomics. 2015;11:1864–83. https://doi.org/10.1007/s11306-015-0840-5.

    CAS  Article  Google Scholar 

  19. 19.

    Kaczor-Urbanowicz KE, Carreras-Presas CM, Aro K, Tu M, Garcia-Godoy F, Wong DTW. Saliva diagnostics - current views and directions. Exp Biol Med. 2017;242:459–72. https://doi.org/10.1177/1535370216681550.

    CAS  Article  Google Scholar 

  20. 20.

    Relvas M, Tomas I, Casares-De-Cal MD, Velazco C. Evaluation of a new oral health scale of infectious potential based on the salivary microbiota. Clin Oral Investig. 2015;19:717–28. https://doi.org/10.1007/s00784-014-1286-2.

    Article  PubMed  Google Scholar 

  21. 21.

    He JY, Huang WJ, Pan ZW, Cui HH, Qi GG, Zhou XP, et al. Quantitative analysis of microbiota in saliva, supragingival, and subgingival plaque of Chinese adults with chronic periodontitis. Clin Oral Investig. 2012;16:1579–88. https://doi.org/10.1007/s00784-011-0654-4.

    Article  PubMed  Google Scholar 

  22. 22.

    Xu Y, Teng F, Huang S, Lin ZM, Yuan X, Zeng XW, et al. Changes of saliva microbiota in nasopharyngeal carcinoma patients under chemoradiation therapy. Arch Oral Biol. 2014;59:176–86. https://doi.org/10.1016/j.archoralbio.2013.10.011.

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Tasoulas J, Patsouris E, Giaginis C, Theocharis S. Salivaomics for oral diseases biomarkers detection. Expert Rev Mol Diagn. 2016;16:285–95. https://doi.org/10.1586/14737159.2016.1133296.

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Kageyama G, Saegusa J, Tanaka S, Takahashi S, Nishida M, Tsuda K, et al. Salivary metabolomics of primary Sjogren’s syndrome. Ann Rheum Dis. 2014;73:524–5. https://doi.org/10.1136/annrheumdis-2014-eular.1201.

    Article  Google Scholar 

  25. 25.

    Hansen TH, Kern T, Bak EG, Kashani A, Allin KH, Nielsen T, et al. Impact of a vegan diet on the human salivary microbiota. Sci Rep. 2018;8. https://doi.org/10.1038/s41598-018-24207-3.

  26. 26.

    Proctor GB, Andre P, Lopez-Garcia E, Lopez DGC, Neyraud E, Feart C, et al. The SALAMANDER project: SALivAry bioMarkers of mediterraneAN Diet associated with long-tERm protection against type 2 diabetes. Nutr Bull. 2017;42:369–74. https://doi.org/10.1111/nbu.12298.

    Article  Google Scholar 

  27. 27.

    Wang J, Schipper HM, Velly AM, Mohit S, Gornitsky M. Salivary biomarkers of oxidative stress: a critical review. Free Radic Biol Med. 2015;85:95–104. https://doi.org/10.1016/j.freeradbiomed.2015.04.005.

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Abe K, Takahashi A, Fujita M, Hayashi M, Okai K, Ohira H. Dysbiosis of oral microbiota and its association with salivary immunological biomarkers in autoimmune liver disease. Hepatology. 2017;66:189A–90A.

    Google Scholar 

  29. 29.

    Francavilla R, Ercolini D, Piccolo M, Vannini L, Siragusa S, De Filippis F, et al. Salivary microbiota and metabolome associated with celiac disease. Appl Environ Microbiol. 2014;80:3416–25. https://doi.org/10.1128/aem.00362-14.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Francavilla R, Ercolini D, Vannini L, Indrio F, Capriati T, Di Cagno R, et al. Italian-style gluten-free diet changes the salivary microbiota and metabolome of African (Saharawi) celiac children. Dig Liver Dis. 2014;46:E88–9. https://doi.org/10.1016/j.dld.2014.07.063.

    Article  Google Scholar 

  31. 31.

    Iwasawa K, Suda W, Tsunoda T, Oikawa-Kawamoto M, Umetsu S, Takayasu L, et al. Dysbiosis of the salivary microbiota in pediatric-onset primary sclerosing cholangitis and its potential as a biomarker. Sci Rep. 2018;8. https://doi.org/10.1038/s41598-018-23870-w.

  32. 32.

    Said HS, Suda W, Nakagome S, Chinen H, Oshima K, Kim S, et al. Dysbiosis of salivary microbiota in inflammatory bowel disease and its association with oral immunological biomarkers. DNA Res. 2014;21:15–25. https://doi.org/10.1093/dnares/dst037.

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Mishiro T, Oka K, Kuroki Y, Takahashi M, Tatsumi K, Saitoh T, et al. Oral microbiome alterations of healthy volunteers with proton pump inhibitor. J Gastroenterol Hepatol. 2018;33:1059–66. https://doi.org/10.1111/jgh.14040.

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Ponziani FR, Pompili M, Gasbarrini A. Rifaximin re-treatment in patients with irritable bowel syndrome: feels like the first time? Dig Dis Sci. 2017;62:2220–2. https://doi.org/10.1007/s10620-017-4656-1.

    Article  PubMed  Google Scholar 

  35. 35.

    Ponziani FR, Scaldaferri F, Petito V, Sterbini FP, Pecere S, Lopetuso LR, et al. The role of antibiotics in gut microbiota modulation: the eubiotic effects of rifaximin. Dig Dis. 2016;34:269–78. https://doi.org/10.1159/000443361.

    Article  PubMed  Google Scholar 

  36. 36.

    Ponziani FR, Pecere S, Lopetuso L, Scaldaferri F, Cammarota G, Gasbarrini A. Rifaximin for the treatment of irritable bowel syndrome - a drug safety evaluation. Expert Opin Drug Saf. 2016;15:983–91. https://doi.org/10.1080/14740338.2016.1186639.

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    Ponziani FR, Gerardi V, Pecere S, D’Aversa F, Lopetuso L, Zocco MA, et al. Effect of rifaximin on gut microbiota composition in advanced liver disease and its complications. World J Gastroenterol. 2015;21:12322–33. https://doi.org/10.3748/wjg.v21.i43.12322.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Roalfe AK, Roberts LM, Wilson S. Evaluation of the Birmingham IBS symptom questionnaire. BMC Gastroenterol. 2008;8:30. https://doi.org/10.1186/1471-230X-8-30.

    Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Al-Kateb H, de Lacy Costello B, Ratcliffe N. An investigation of volatile organic compounds from the saliva of healthy individuals using headspace-trap/GC-MS. J Breath Res. 2013;7:36004. https://doi.org/10.1088/1752-7155/7/3/036004.

    CAS  Article  Google Scholar 

  40. 40.

    Soini HA, Klouckova I, Wiesler D, Oberzaucher E, Grammer K, Dixon SJ, et al. Analysis of volatile organic compounds in human saliva by a static sorptive extraction method and gas chromatography-mass spectrometry. J Chem Ecol. 2010;36:1035–42. https://doi.org/10.1007/s10886-010-9846-7.

    CAS  Article  PubMed  Google Scholar 

  41. 41.

    Brown SK, Sim MR, Abramson MJ, Gray CN. Concentrations of volatile organic compounds in indoor air – a review. Indoor Air. 1994;4:123–34. https://doi.org/10.1111/j.1600-0668.1994.t01-2-00007.x.

    CAS  Article  Google Scholar 

  42. 42.

    de Lacy CB, Amann A, Al-Kateb H, Flynn C, Filipiak W, Khalid T, et al. A review of the volatiles from the healthy human body. J Breath Res. 2014;8:14001. https://doi.org/10.1088/1752-7155/8/1/014001.

    CAS  Article  Google Scholar 

  43. 43.

    Kwak J, Preti G. Chapter 21 - Challenges in the investigation of volatile disease biomarkers in urine. In: Volatile biomarkers. Boston: Elsevier; 2013. p. 394–404.

    Google Scholar 

  44. 44.

    Buljubasic F, Buchbauer G. The scent of human diseases: a review on specific volatile organic compounds as diagnostic biomarkers. Flavour Fragr J. 2014;30:5–25. https://doi.org/10.1002/ffj.3219.

    CAS  Article  Google Scholar 

  45. 45.

    Dolch ME, Hornuss C, Klocke C, Praun S, Villinger J, Denzer W, et al. Volatile organic compound analysis by ion molecule reaction mass spectrometry for Gram-positive bacteria differentiation. Eur J Clin Microbiol Infect Dis. 2012;31:3007–13. https://doi.org/10.1007/s10096-012-1654-2.

    CAS  Article  PubMed  Google Scholar 

  46. 46.

    Allardyce RA, Langford VS, Hill AL, Murdoch DR. Detection of volatile metabolites produced by bacterial growth in blood culture media by selected ion flow tube mass spectrometry (SIFT-MS). J Microbiol Methods. 2006;65:361–5. https://doi.org/10.1016/j.mimet.2005.09.003.

    CAS  Article  PubMed  Google Scholar 

  47. 47.

    Mal M. Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders. Futur Sci OA. 2016;2. https://doi.org/10.4155/fsoa-2015-0014.

  48. 48.

    Zhang AH, Sun H, Wang XJ. Saliva metabolomics opens door to biomarker discovery, disease diagnosis, and treatment. Appl Biochem Biotechnol. 2012;168:1718–27. https://doi.org/10.1007/s12010-012-9891-5.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    de Oliveira LRP, Martins C, Fidalgo TKS, Freitas-Fernandes LB, Torres RD, Soares AL, et al. Salivary metabolite fingerprint of type 1 diabetes in young children. J Proteome Res. 2016;15:2491–9. https://doi.org/10.1021/acs.jproteome.6b00007.

    CAS  Article  PubMed  Google Scholar 

  50. 50.

    Yilmaz A, Geddes T, Han B, Bahado-Singh RO, Wilson GD, Imam K, et al. Diagnostic biomarkers of Alzheimer’s disease as identified in saliva using H-1 NMR-based metabolomics. J Alzheimers Dis. 2017;58:355–9. https://doi.org/10.3233/jad-161226.

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    De Angelis M, Vannini L, Di Cagno R, Cavallo N, Minervini F, Francavilla R, et al. Salivary and fecal microbiota and metabolome of celiac children under gluten-free diet. Int J Food Microbiol. 2016;239:125–32. https://doi.org/10.1016/j.ijfoodmicro.2016.07.025.

    Article  PubMed  Google Scholar 

  52. 52.

    De Filippis F, Vannini L, La Storia A, Laghi L, Piombino P, Stellato G, et al. The same microbiota and a potentially discriminant metabolome in the saliva of omnivore, ovo-lacto-vegetarian and vegan individuals. PLoS One. 2014;9. https://doi.org/10.1371/journal.pone.0112373.

    Article  Google Scholar 

  53. 53.

    Mueller DC, Piller M, Niessner R, Scherer M, Scherer G. Untargeted metabolomic profiling in saliva of smokers and nonsmokers by a validated GC-TOF-MS method. J Proteome Res. 2014;13:1602–13. https://doi.org/10.1021/pr401099r.

    CAS  Article  PubMed  Google Scholar 

  54. 54.

    Liang Q, Liu H, Zhang TY, Jiang Y, Xing HT, Zhang AH. Metabolomics-based screening of salivary biomarkers for early diagnosis of Alzheimer’s disease. RSC Adv. 2015;5:96074–9. https://doi.org/10.1039/c5ra19094k.

    CAS  Article  Google Scholar 

  55. 55.

    Liang Q, Liu H, Li X, Zhang AH. High-throughput metabolomics analysis discovers salivary biomarkers for predicting mild cognitive impairment and Alzheimer’s disease. RSC Adv. 2016;6:75499–504. https://doi.org/10.1039/c6ra16802g.

    CAS  Article  Google Scholar 

  56. 56.

    Madsen BS, Trebicka J, Thiele M, Israelsen M, Arumugan M, Havelund T, et al. Antifibrotic and molecular aspects of rifaximin in alcoholic liver disease: study protocol for a randomized controlled trial. Trials. 2018:19. https://doi.org/10.1186/s13063-018-2523-9.

  57. 57.

    Bajaj JS. Review article: potential mechanisms of action of rifaximin in the management of hepatic encephalopathy and other complications of cirrhosis. Aliment Pharmacol Ther. 2016;43:11–26. https://doi.org/10.1111/apt.13435.

    CAS  Article  PubMed  Google Scholar 

  58. 58.

    Brigidi P, Swennen E, Rizzello F, Bozzolasco M, Matteuzzi D. Effects of rifaximin administration on the intestinal microbiota in patients with ulcerative colitis. J Chemother. 2002;14:290–5. https://doi.org/10.1179/joc.2002.14.3.290.

    CAS  Article  PubMed  Google Scholar 

  59. 59.

    Cash BD, Pimentel M, Rao SSC, Weinstock L, Chang L, Heimanson Z, et al. Repeat treatment with rifaximin improves irritable bowel syndrome-related quality of life: a secondary analysis of a randomized, double-blind, placebo-controlled trial. Ther Adv Gastroenterol. 2017;10:689–99. https://doi.org/10.1177/1756283x17726087.

    CAS  Article  Google Scholar 

  60. 60.

    Gupta K, Ghuman HS, Handa SV. Review of rifaximin: latest treatment frontier for irritable bowel syndrome mechanism of action and clinical profile. Clin Med Insights-Gastroenterol. 2017;10. https://doi.org/10.1177/1179552217728905.

    Google Scholar 

  61. 61.

    Guslandi M. Rifaximin in the treatment of inflammatory bowel disease. World J Gastroenterol. 2011;17:4643–6. https://doi.org/10.3748/wjg.v17.i42.4643.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Kane JS, Ford AC. Rifaximin for the treatment of diarrhea-predominant irritable bowel syndrome. Expert Rev Gastroenterol Hepatol. 2016;10:431–42. https://doi.org/10.1586/17474124.2016.1140571.

    CAS  Article  PubMed  Google Scholar 

  63. 63.

    Lembo A, Pimentel M, Rao SS, Schoenfeld P, Cash B, Weinstock LB, et al. Repeat treatment with rifaximin is safe and effective in patients with diarrhea-predominant irritable bowel syndrome. Gastroenterology. 2016;151:1113–21. https://doi.org/10.1053/j.gastro.2016.08.003.

    CAS  Article  PubMed  Google Scholar 

  64. 64.

    Cobbold JFL, Atkinson S, Marchesi JR, Smith A, Wai SN, Stove J, et al. Rifaximin in non-alcoholic steatohepatitis: an open-label pilot study. Hepatol Res. 2018;48:69–77. https://doi.org/10.1111/hepr.12904.

    CAS  Article  PubMed  Google Scholar 

  65. 65.

    Gangarapu V, Ince AT, Baysal B, Kayar Y, Kilic U, Gok O, et al. Efficacy of rifaximin on circulating endotoxins and cytokines in patients with nonalcoholic fatty liver disease. Eur J Gastroenterol Hepatol. 2015;27:840–5. https://doi.org/10.1097/meg.0000000000000348.

    CAS  Article  PubMed  Google Scholar 

  66. 66.

    Weber D, Oefner PJ, Dettmer K, Hiergeist A, Koestler J, Gessner A, et al. Rifaximin preserves intestinal microbiota balance in patients undergoing allogeneic stem cell transplantation. Bone Marrow Transplant. 2016;51:1087–92. https://doi.org/10.1038/bmt.2016.66.

    CAS  Article  PubMed  Google Scholar 

  67. 67.

    DuPont HL. Review article: the antimicrobial effects of rifaximin on the gut microbiota. Aliment Pharmacol Ther. 2016;43:3–10. https://doi.org/10.1111/apt.13434.

    CAS  Article  PubMed  Google Scholar 

  68. 68.

    Lopetuso LR, Petito V, Scaldaferri F, Gasbarrini A. Gut microbiota modulation and mucosal immunity: focus on rifaximin. Mini-Rev Med Chem. 2016;16:179–85. https://doi.org/10.2174/138955751603151126121633.

    CAS  Article  Google Scholar 

  69. 69.

    Song Z, Du H, Zhang Y, Xu Y. Unraveling core functional microbiota in traditional solid-state fermentation by high-throughput amplicons and metatranscriptomics sequencing. Front Microbiol. 2017;8:1294. https://doi.org/10.3389/fmicb.2017.01294.

    Article  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Del Chierico F, Nobili V, Vernocchi P, Russo A, Stefanis C, Gnani D, et al. Gut microbiota profiling of pediatric nonalcoholic fatty liver disease and obese patients unveiled by an integrated meta-omics-based approach. Hepatology. 2017;65:451–64. https://doi.org/10.1002/hep.28572.

    CAS  Article  PubMed  Google Scholar 

  71. 71.

    Abdel-Razik A, Mousa N, Shabana W, Refaey M, Elzehery R, Elhelaly R, et al. Rifaximin in nonalcoholic fatty liver disease: hit multiple targets with a single shot. Eur J Gastroenterol Hepatol. 2018;30.10:1237–46.

    CAS  Article  Google Scholar 

  72. 72.

    Anderson JC. Measuring breath acetone for monitoring fat loss: review. Obesity (Silver Spring). 2015;23:2327–34. https://doi.org/10.1002/oby.21242.

    CAS  Article  Google Scholar 

  73. 73.

    Laforest-Lapointe I, Arrieta M-C. Microbial eukaryotes: a missing link in gut microbiome studies. mSystems. 2018;3:e00201–17. https://doi.org/10.1128/mSystems.00201-17.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work is dedicated to Dr Giovanni Battista Gervasi of Laboratori Baldacci, Pisa (Italy), who believed in the reliability of saliva analysis and in its potentialities in drug development.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Emilia Bramanti.

Ethics declarations

The study was conducted under approved Institutional Review protocol in accordance with the Declaration of Helsinki and in accordance with the ethical standards. All the volunteer donors provided written informed consent before study entry.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Campanella, B., Onor, M., Lomonaco, T. et al. HS-SPME-GC-MS approach for the analysis of volatile salivary metabolites and application in a case study for the indirect assessment of gut microbiota. Anal Bioanal Chem 411, 7551–7562 (2019). https://doi.org/10.1007/s00216-019-02158-6

Download citation

Keywords

  • Volatile organic compounds
  • Microbiota
  • HS-SPME-GC-MS method
  • Saliva