Dynamic Proteome Alteration and Functional Modulation of Human

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Chemistry and Biology of Aroma and Taste

Dynamic Proteome Alteration and Functional Modulation of Human Saliva Induced by Dietary Chemosensory Stimuli Matthias Bader, Andreas Dunkel, Mareike Wenning, Bernd Kohler, Guillaume Medard, Estela del Castillo, Amin Gholami, Bernhard Kuster, Siegfried Scherer, and Thomas Hofmann J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b02092 • Publication Date (Web): 22 May 2018 Downloaded from http://pubs.acs.org on May 23, 2018

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Journal of Agricultural and Food Chemistry

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Dynamic Proteome Alteration and Functional Modulation of

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Human Saliva Induced by Dietary Chemosensory Stimuli

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Matthias Bader1, Andreas Dunkel1, Mareike Wenning2, Bernd Kohler2, Guillaume

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Medard3, Estela del Castillo3, Amin Gholami3, Bernhard Kuster3, Siegfried Scherer2,4,

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and Thomas Hofmann1,2,5*

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Chair of Food Chemistry and Molecular Sensory Science, Technische Universität

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München, Lise-Meitner Str. 34, D-85354 Freising, Germany, 2

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ZIEL Institute for Food and Health, Technische Universität München, D-85350

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Freising, Germany, 3

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Chair of Proteomics and Bioanalytics, Technische Universität München, Emil-

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Erlenmeyer-Forum 5, D-85354 Freising, Germany, 4

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Chair of Microbial Ecology, Department of Biosciences, WZW, Technische

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Universität München, 85354 Freising, Germany, 5

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Leibniz-Institute for Food Systems Biology at the Technical University of Munich,

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Lise-Meitner Str. 34, D-85354 Freising, Germany.

18 19 20 21

*

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PHONE

+49-8161/71-2902

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FAX

+49-8161/71-2949

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E-MAIL

[email protected]

To whom correspondence should be addressed

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ACS Paragon Plus Environment


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ABSTRACT

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Saliva flow measurements and SDS-PAGE separation of human whole saliva freshly

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collected after oral stimulation with citric acid (sour), aspartame (sweet), iso-α-acids

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(bitter), mono sodium L-glutamate (umami), NaCl (salty), 6-gingerol (pungent),

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hydroxy-α-sanshool (tingling), and hydroxy-β-sanshool (numbing), followed by tryptic

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digestion, nano-HPLC-MS/MS, and label-free protein quantitation demonstrated a

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stimulus- and time-dependent influence of the dietary chemosensates on salivation

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and the salivary proteome composition. Gene ontology enrichment analysis showed

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evidence for stimulus-induced alterations of the saliva proteome to boot an efficient

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molecular defense network of the oral cavity, e.g. 6-gingerol increased salivary

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lactoperoxidase activity, catalyzing the oxidation of thiocyanate to produce the

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antimicrobial and antifungal hypothiocyanate, from 0.37±0.02 to 0.91±0.05 mU/mL 45

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sec after stimulation. In comparison, oral citric acid stimulation induced an increase

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of

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antimicrobial hypochloride in saliva, from 0.24±0.04 to 0.70±0.1 mU/mL as well as an

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increase of salivary levels of lysozyme, exhibiting antimicrobial activity on Gram-

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positive bacteria, from 6.0 – 10 to 100 – 150 µg/mL. Finally, microbial growth

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experiments clearly demonstrated for the first time that the increase of the salivary

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lysozyme abundance upon oral citric acid stimulation translates into an enhanced

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biological function, that is an almost complete growth inhibition of the two lysozyme-

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sensitive Gram-positive bacteria tested.

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Key words: saliva, taste, saliva enzymes, proteomics, lysozyme

myeloperoxidase activity, catalyzing the chloride oxidation to generate


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INTRODUCTION

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Human saliva consists of a heterogeneous aqueous mixture of electrolytes, small

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organic molecules, oligopeptides and proteins, desquamated mucosal and immune

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cells, oral microorganisms, as well as food debris 1, 2. The quantitative composition of

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the secretions of the major submandibular, sublingual and parotid glands as well as

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the multiple minor salivary glands shows considerable variations depending on the

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type of salivary stimulation and is affected by age, gender, day time, health status,

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diet, and the use of pharmacologicals, respectively

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developments in standardizing saliva sample collection and handling procedures as

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well as in cutting-edge proteomics technologies 3-5, a total of 1.166 proteins has been

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reported in whole human saliva

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saliva secretions 3, 15, respectively. Very recently, mass-spectrometry-based mapping

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of the human proteome revealed the existence of more than 2000

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even more than 7400 proteins in saliva

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of human saliva.

6-14

, glandular parotid

1,

2

. Enabled by recent

3, 6, 14, 15

and submandibular

16

, 3700

17

and

18

, thus confirming the enormous complexity

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Saliva constituents play an important role in acquired pellicle formation, which

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is a thin layer of several calcium hydroxide-binding salivary proteins such as, e.g.

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mucins, on tooth surfaces19-21. The acquired pellicle has a crucial function in crystal

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growth homeostasis of the teeth, in protection of the teeth from acid-induced

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demineralization processes2, and in bacterial adhesion and colonization on tooth

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surfaces22, 23. Moreover, saliva has been shown to play an important role in physico-

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chemical and immune defense of the oral mucosal structure via both direct

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antimicrobial action and agglutination or surface exclusion of microbes20, 21.

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Next to supporting food bolus formation and the swallowing process by

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lubrication, saliva supports the maintenance of the structures of taste-sensing cells



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and the fine-tuning of the gustatory system1,

22, 24-27

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composition of saliva seem to affect taste sensitivity during the initial processes of

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taste stimulation. First, chemosensory stimuli must pass through the salivary fluid

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layer to reach the taste receptor sites, and this may include solubilisation and

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chemical interactions of the tastants with salivary components. Some salivary

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constituents are known to chemically interact with taste molecules, e.g. histatins and

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some proline-rich proteins (PRPs) have been shown to complex and precipitate

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astringent tasting plant polyphenols27-31, thus diminishing the aversive orosensation

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induced by these phytochemicals and combating gastrointestinal irritation by tannin-

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rich food at a very early stage of food ingestion27, 28, 32. The major salivary enzyme α-

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amylase induces early polysaccharide digestion in the mouth, e.g. translating into an

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increased saltiness perception in starch-based food products33. Furthermore, lipases

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released from the von Ebner glands and their ability to generate free fatty acids from

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dietary triglycerides to activate fatty acid responsive G-protein coupled receptors in

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taste buds has been correlated to orosensory fat sensitivity34-38. Finally, the perceived

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intensity of sour taste stimuli is modulated by the buffering action of salivary

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bicarbonate39, 40, e.g. electrophysiological studies revealed decreased oral responses

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to hydrochloric acid in rodents when the tongue was conditioned with saliva and

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NaHCO3 when compared to water and NaCl, respectively41.

. Changes in the quantity and

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Moreover, the salivary proteome has been proposed to be an indicator of taste

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disorders, e.g. taste-impaired patients show a significantly decreased abundance of

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Zn-alpha-2 glycoprotein, prolactin-inducible protein, cystatin SN, as well as carbonic

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anhydrase VI in whole saliva42. The latter, carbonic anhydrase VI, reversibly

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catalyzing the conversion of carbon dioxide to hydrogen carbonate and free protons,

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has been related to taste perception due to its proposed implication in the paracrine

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modulation of taste function and taste receptor cell apoptosis43, 44. ACS Paragon Plus Environment

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The rather dynamic changes in saliva composition raised the question as to

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whether dietary taste stimuli themselves are able to induce changes in the

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abundance of selected saliva proteins. 2D-Electrophoresis and mass spectrometric

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analysis of saliva samples collected from volunteers after stimulation with taste

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compounds such as, e.g. glucose, mono sodium L-glutamate, and calcium nitrate,

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respectively, revealed a stimulus-specific modulation of the abundance of some

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saliva proteins including annexin A1 and calgranulin A

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with a complex ginger extract induced elevated levels of the lung and nasal

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epithelium carcinoma-associated protein 2 (SPLUNC2), zinc-alpha-2-glycoproteins

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(Zn-alpha-GP), and carbonic anhydrase VI (CAVI)47.

45, 46

, while oral stimulation

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To gain a more systematic understanding of the dynamic changes of the

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salivary proteome and function of the oral defense system in response to individual

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dietary chemosensory stimuli, the objectives of the present study were to

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quantitatively measure saliva flow induced by dietary taste (sweet, sour, salty,

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umami, bitter) and trigeminal stimuli (pungent, tingling, numbing), to investigate the

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time-resolved changes in the whole salivary proteome by means of a label-free,

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quantitative nano-LC-MS/MS approach, and to investigate whether and, if so, how

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such proteome alterations translate into a functional modulation of saliva.

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MATERIALS AND METHODS

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Chemicals. The following materials were obtained commercially: Coomassie

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Plus (Bradford) Assay Kit (Thermo Fischer Scientific, Rockford, IL, USA);

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SIGMAFAST™ protease inhibitor, 1,4-dithiothreitol (DTT), iodoacetamide (IAA),

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colloidal coomassie blue, formic acid (FA), acetic acid, SIGMAFAST™ protease

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inhibitor, triethylammonium bicarbonate (TEAB), lysozyme (recombinant, expressed



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in rice), myeloperoxidase (Sigma, Steinheim, Germany); acetone, methanol (MeOH),

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ethanol (EtOH) (VWR International, Darmstadt, Germany); trypsin (Promega,

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Fitchburg, WI, USA); acetonitrile (ACN, Rathburn Chemicals, Walkerburn, UK);

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precision plus unstained standards (Biorad, Munich, Germany); 4x NuPAGE® LDS

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Sample Buffer, NuPAGE® MOPS SDS Running Buffer (Invitrogen, Darmstadt,

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Germany).

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For sensory analysis, the following dietary taste compounds were used:

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aspartame, citric acid, 6-gingerol, sodium chloride (Sigma, Steinheim, Germany),

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mono sodium L-glutamate (MSG) (Merck, Darmstadt, Germany), hop iso-α-extract

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(Hallertauer Hopfenveredelungsgesellschaft mbH, Mainburg, Germany). Hydroxy-α-

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sanshool and hydroxy-β-sanshool (purity >98%, each) were obtained from

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Zanthoxylum piperitum as reported recently48.

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Human Saliva Experiments. Eleven healthy volunteers (6 male and 5 female,

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ages 24 – 31), giving informed written consent to the experimental plan, were

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recruited from the Technische Universität München, Germany, without any exclusion

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parameters besides being in good health, non-smoking, and not under medication.

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The saliva collection procedure and protocols for the oral stimulation experiments

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were approved by the ethics committee of the Technical University of Munich. The

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methods were carried out in accordance with the relevant guidelines and regulations.

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The individuals were asked to brush their teeth and rinse their mouth with water (100

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mL) after breakfast and, with the exception of water, not to consume any food

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products and smoking articles, respectively, for 2 h prior to the experiment.

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Saliva Flow Measurement. Following a literature procedure47 with some

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modifications, non-stimulated and stimulated whole saliva samples of eight subjects

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(4 male, 4 female) were collected in a sensory room at 23°C as follows: to collect

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non-stimulated saliva (control), the volunteers were asked to rinse their oral cavity ACS Paragon Plus Environment

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with water (8 mL) for 60 s and, then, to spit out. After waiting for 60 s and swallowing,

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an aliquot (2 mL) of water was taken into the mouth and, after performing chewing

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motions for 30 s, the subjects were asked to expectorate in pre-weighed petri dishes

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(pre-stimulus sample, t0). For the sampling of stimulated saliva, the subjects were

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asked to rinse their mouth with water (8 mL) and, then, to spit out. After waiting for 60

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s and swallowing, an aliquot (2 mL) of water (control) or an aqueous stimulus solution

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of citric acid (stimulus S1; 156 mmol/L), aspartame (stimulus S2; 3.4 mmol/L), iso-α-

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acids (stimulus S3; 0.3 mmol/L), mono sodium L-glutamate (stimulus S4; 30 mmol/L),

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sodium chloride (stimulus S5; 513 mmol/L), 6-gingerol (stimulus S6; 1.7 mmol/L),

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hydroxy-α-sanshool (stimulus S7; 4 mmol/L), and hydroxy-β-sanshool (stimulus S8; 4

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mmol/L), respectively, was taken up in the mouth and, after performing chewing

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motions for 15 s, the subjects were asked to expectorate in pre-weighed petri dishes

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(stimulus sample t15). Thereafter, the subjects were asked not to swallow and to take

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a sample of bottled water (2 mL) into the mouth and to chew for 30 s and then to

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expectorate again (post-stimulus sample t45). Without swallowing in between, the

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later part of this experiment was repeated once to afford a second post-stimulus

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sample (t75). To minimize protease-induced artifact formation, SIGMAFAST™

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protease inhibitor (1 µL/mL saliva) was added immediately after sample collection.

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The corresponding samples (t0-t75) collected for each stimulus from all eight different

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subjects at three independent days were pooled and stored at -20°C until use. The

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amount of saliva was calculated from the weight difference of the expectorated

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saliva/water mixture and the aliquot (2 g) of the aqueous stimulus solution used to

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collect the stimulus sample and the aliquot (2 g) of water used to obtain the pre-

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stimulus sample (t0), the stimulus sample (t15), as well as the post-stimulus samples

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(t45, t75). Saliva samples were divided into 2.0 mL aliquots and stored at -80°C until

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use. For the enzymatic assays and microbial growth experiments saliva samples ACS Paragon Plus Environment


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were collected in additional sampling sessions as described above. For peroxidase

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related assays, the saliva of 4 subjects (4 male, 4 female), for quantitation of

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lysozyme 11 subjects (6 male, 5 female) and for microbial growth experiments saliva

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of 6 subjects (3 male, 3 female) were collected.

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Quantitation of Salivary Protein Content. The protein concentration in

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pooled saliva samples was determined by using the Coomassie (Bradford) Assay Kit

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following the supplier´s instructions (Thermo Fisher Scientific, Rockford, IL, USA).

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After centrifugation (12’000 rpm, 4°C, 10 min) of the saliva samples, aliquots (5 µL) of

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the supernatant were mixed with the Bradford reagent solution (250 µL) and, after 10

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min of incubation at room temperature, were photometrically analyzed at 595 nm with

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a reference wavelength of 690 nm. The values recorded at the measurement

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wavelength were divided by those received at the reference wavelength. A standard

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curve, recorded by plotting the absorbance measured for standard solutions of

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bovine serum albumin (0, 25, 125, 250, 500, 1000, 1500 and 2000 µg/mL) against

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the quantity of protein, showed excellent linearity (y = 0.0005x + 0.0725; R2 = 0.9933)

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within the range of 0-1000 µg/mL protein.

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Protein Clean-Up and Electrophoresis. Aliquots of saliva samples (350 µg

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protein) were mixed with ice-cold acetone in a 1:9 ratio and incubated for 90 min at -

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20°C, followed by centrifugation (4’500 rpm, 4°C, 10 min). After separating the

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supernatant, the protein pellets were washed twice with ice-cold acetone (200 µL).

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The acetone was removed under a stream of nitrogen, the protein pellets were re-

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suspended in 4× NuPAGE® LDS buffer (65 µL) containing 50 mM DTT and, after

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incubation at 95°C for 10 min, the sample was treated with IAA (550 mM, 5 µL) for 30

200

min in the dark. The reduced and alkylated samples were stored at -20°C until further

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use.


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Portions (150 µg) of the pre-treated protein pellet (350 µg) isolated from saliva

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samples (t0, t15, t45, t75) were loaded on a 4-12% NuPAGE® gel (Invitrogen,

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Darmstadt, Germany) in a XCell Sure Lock™ electrophoresis cell (Invitrogen,

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Darmstadt, Germany) operated at 200V for 45 min. To determine the molecular

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weight of the salivary proteins, precision plus unstained standards (Bio-Rad,

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München, Germany) were used as references. The protein bands were fixed by

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slowly shaking the gels in 40% aqueous MeOH containing 2% acetic acid for 60 min.

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Thereafter, the fixing solution was removed and the protein bands were stained by

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keeping the gels in a solution (20 mL) containing 16% colloidal coomassie, 64%

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ELGA water (ELGA Labwater, Celle, Germany), and 20% MeOH with agitation for 2

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h at room temperature. After partial de-staining of the gel by washing with 5% acetic

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acid in 25% MeOH, followed by washing in 25% EtOH, the gel was kept in 1% acetic

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acid until use for in-gel digestion.

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In-Gel Digestion and Nano-LC-MS/MS. Prior to digestion, twelve proteins

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bands from each gel were manually excised to accommodate the whole range of

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molecular weight using a scalpel and subjected to tryptic in-gel digestion following

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standard procedures. The gel bands were de-stained twice with 5 mM TEAB in 50%

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EtOH at 55°C, dehydrated with EtOH, and washed with 5 mM TEAB. After additional

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dehydration with EtOH, trypsin (250 ng) in 5 mM TEAB digestion buffer were added

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at 4°C and then incubated at 37°C for 4 h. Digestion was stopped by the addition of

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5% aqueous formic acid, the peptides were extracted with 1% aqueous formic acid

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(20 µL, 2 times), followed by 0.1% formic acid in 60% acetonitrile (20 µL). At the end,

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50 µL of acetonitrile were added. The peptides were then dried in a Univapo 150

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ECH vacuum concentrator (Uniequip, Planegg, Germany), re-suspended in 0.1%

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aqueous formic acid (20 µL), followed by nano-LC-MS/MS analysis on an amaZon

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ETD mass spectrometer (Bruker Daltonik, Bremen, Germany) coupled to a nanoLCACS Paragon Plus Environment


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Ultra 1D+ (Eksigent, Dublin, CA). Peptides were delivered to a 20 mm x 100 µm

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ReproSil-PUR C18-AQ, 5 µm, trap column (Dr. Maisch, Ammerbuch, Germany) at a

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flow rate of 5 µL/min in 100% buffer A (0.1% FA in HPLC grade water). After 10

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minutes, the flow rate was reduced to 300 nL/min, and the peptides were transferred

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to a 20 cm x 75 µm ReproSil-PUR C18-AQ, 3 µm, analytical column (Dr. Maisch).

233

Separation was performed within 110 min using the following gradient: 2 to 10% B

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(0.1% FA in ACN) in 2 min, ramp to 35% B over 98 min followed by 8 minutes at 80%

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B and 2 minutes to re-equilibrate at 2% B. Peptides eluted from the column were

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sprayed via emitter tips (PicoTip, New Objective, MA) using a nano-electrospray ion

237

source (Bruker Daltonik, Bremen, Germany). Intact masses of eluting peptides were

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determined in enhanced resolution scan mode and the ten most intense peaks were

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selected for further fragmentation by collision-induced dissociation (CID) and

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acquisition of fragment spectra in ultra scan mode. Singly charged ions as well as

241

ions with unknown charge state were discarded. After MS analyses, raw tandem

242

mass spectra were converted into Mascot generic file format (mgf) by using Bruker

243

Compass DataAnalysis Software 4.0 (Bruker Daltonik, Bremen, Germany). Protein

244

identification was performed using the Mascot search engine version 2.3.01 (Matrix

245

Science, London, UK) with carbamidomethyl cysteine, oxidized methionine,

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phosphorylation of serine, threonine and tyrosine and pyro-Glu/Gln N-termini as

247

variable modifications. Trypsin was specified as the proteolytic enzyme and up to two

248

missed cleavages were allowed. The mass tolerance of the precursor ion was set to

249

0.3 Da and that of fragment ions was set to 0.5 Da. MS/MS spectra were searched

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against a decoyed human IPI database (ipi.HUMAN.v3.58.fasta, containing 79794

251

entries). Protein identification from individual search engine results were combined

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using probabilistic protein identification algorithms implemented in Scaffold software

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3.0 (Proteome Software, Portland, OR). Proteins having at least two independent ACS Paragon Plus Environment

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peptide identifications (probability > 0.95) were considered to be present in the

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sample.

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Label-Free Protein Quantitation and Statistical Analysis. Proteins, for which

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at least two suitable peptides could be reliably identified and at least four spectral

258

counts for at least one biological replicate in a group could be detected, were

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considered for protein quantification in non-stimulated (t0) and stimulated saliva

260

samples (t15 – t75). Protein abundances were estimated using normalized spectral

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abundance factor (NSAF) values calculated from the spectral counts of each

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individual identified protein49. Briefly, in order to account for the fact that the larger

263

proteins tend to contribute more peptides or spectra, spectral counts were divided by

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protein length to provide a spectral abundance factor (SAF). SAF values were then

265

normalized against the sum of all SAF values in the corresponding run, allowing the

266

comparison of protein levels across different runs. The NSAF dataset was imported

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into the R programming environment for statistical computing50 and the "Power Law

268

Global Error Model" was fitted. It has been shown that the use of PLGEM-based

269

standard deviations to calculate signal-to-noise (STN) ratios in a NSAF dataset

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improves determination of protein expression changes since it is more conservative

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with proteins of low abundance than proteins with high abundance. The null

272

hypothesis was accepted or rejected on the basis of p-values at a specified

273

significance level. For multiple testing adjustments, the false discover rate was

274

calculated using the algorithm of Benjamini and Hochberg51. With appropriate

275

multiple testing adjustment to control the false discovery rate at 5%, p-values allowed

276

to identify differentially expressed proteins. The good fit of the model to the NSAF

277

data and the relevant algorithmic details of the PLGEM method are reported earlier52,

278

53

.



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Gene-Ontology Term Enrichment Analysis. Uniprot IDs of proteins showing

280

significantly different expression to control were converted to Entrez GeneID´s using

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the Uniprot ID mapping tool (http://www.uniprot.org/uploadlists/), the background

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gene set containing all proteins (2564 proteins) detected in human saliva was

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obtained from ProteomicsDB (https://www.proteomicsdb.org/). GO term enrichment

284

was calculated using the over-representation test implemented in the clusterProfiler

285

package (version 3.6.0) within the R programming environment54,

286

following parameters: org.Hs.eg.db (version 3.5.0)56 as organism database,

287

“biological process” as subontology, p-value cut-off of 0.01, p-value adjustment

288

method by Benjamini and Hochberg51, three as minimal size of genes annotated by

289

Ontology term for testing.

290

From the enrichment results, 50 GO-terms with the lowest adjusted p-values per

291

stimulus were selected and filtered for offsprings of GO:0050896 (response to

292

stimulus) using the GOBPOFFSPRING function of the R package GO.db (version

293

3.5.0)57. The list of 44 remaining GO-terms was analyzed for semantic similarities by

294

application of functions included in the GOSemSim package (version 2.4.0)58 and

295

subsequently clustered using the Ward.D2 clustering method within R. Visualization

296

of p-values for individual stimuli and GO-terms grouped by function based on

297

semantic similarity was performed by means of the R-packages ggplot2 (version

298

2.2.1)59 and dendextend (version 1.6.0)60. For assignment of individual proteins to the

299

antimicrobial activity of citric acid induced saliva, proteins from the respective dataset

300

that are annotated for the GO terms GO:0051707 (response to other organism),

301

GO:0009617 (response to bacterium), GO:0043207 (response to external biotic

302

stimulus), GO:0019730 (antimicrobial humoral response), GO:0042742 (defense

303

response to bacterium), or GO:0051873 (killing by host of symbiont cells) were

304

extracted

yielding

22

proteins,

namely

ANXA3_HUMAN,


55

based on the

CAP7_HUMAN,

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305

BPIA1_HUMAN, BPIB1_HUMAN, CAMP_HUMAN, CD14_HUMAN, CATG_HUMAN,

306

ELNE_HUMAN, ENOA_HUMAN, FIBB_HUMAN, G3P_HUMAN, GSTP1_HUMAN,

307

HPT_HUMAN, HSPB1_HUMAN, IGJ_HUMAN, NGAL_HUMAN, LYSC_HUMAN,

308

PERM_HUMAN,

309

SLPI_HUMAN. Similarily, proteins annotated for the GO terms GO:0000302

310

(response to reactive oxygen species), GO:0042542 (response to hydrogen

311

peroxide), GO:0000305 (response to oxygen radical), GO:0000303 (response to

312

superoxide), GO:0006979 (response to oxidative stress), GO:0000303 (response to

313

superoxide), GO:0071450 (cellular response to oxygen radical), GO:0034614

314

(cellular response to reactive oxygen species), or GO:0019430 (removal of

315

superoxide radicals) being responsible for the salivary antioxidative activity after 6-

316

gingerol

317

CATA_HUMAN, CYTC_HUMAN, GSTP1_HUMAN, HBA_HUMAN, HBB_HUMAN,

318

NGAL_HUMAN,

319

PRDX2_HUMAN, S10A7_HUMAN, SODC_HUMAN, and THIO_HUMAN. Mean

320

values for each protein per sample collection time as well as individual time profiles

321

of replicates were visualized using the R programming environment.

322

PRTN3_HUMAN,

stimulation

Enzymatic

lead

to

the

ECP_HUMAN,

following

PERL_HUMAN,

Assays.

Peroxidase

14

S10AC_HUMAN,

proteins:

PERM_HUMAN,

activity

was

and

ANXA1_HUMAN,

PRDX1_HUMAN,

determined

using

the

323

commercially available Amplex Red Hydrogen Peroxide/Peroxidase Assay Kit

324

(Invitrogen, Darmstadt, Germany) following the instructions of the manufacturer.

325

Saliva samples, freshly collected from four volunteers (2 female, 2 male) before (t0)

326

and after stimulation (t45) with 6-gingerol and citric acid, respectively, were pooled to

327

give a pooled pre-stimulus (t0) and a pooled post-stimulus sample (t45). After

328

centrifugation (13’200 rpm, 10 min, 4°C) and 1+1 dilution with the kit reaction buffer,

329

the samples (50 µL) were mixed with a working solution (50 µL) containing H2O2 and

330

the Amplex Red reagent, incubated for 30 min at room temperature and, then, ACS Paragon Plus Environment


331

fluorescence was measured using an excitation wavelength of 544 nm and an

332

emission wavelength of 590 nm. Using a standard curve measured for horseradish

333

peroxidase (0, 0.02, 0.05, 0.1, 0.2, 0.25, 0.5, 1 and 2 mU/mL), the peroxidase activity

334

[mU/mL] was plotted against the fluorescence measured for the saliva samples.

335

The chloride oxidation activity of saliva was determined using the EnzCheck

336

Myeloperoxidase (MPO) Activity Assay Kit (Invitrogen, Darmstadt, Germany)

337

following the manufacturer’s instructions. Aliquots of saliva samples (50 µL),

338

collected and pooled from four volunteers (2 female, 2 male) before (t0) and after

339

citric acid stimulation (t45) were centrifuged (13’200 rpm, 10 min, 4°C), mixed 1+1

340

with the kit’s working solution (50 µL) containing H2O2 and 3’-(p-aminophenyl)

341

fluorescein (APF), incubated for 30 min at room temperature, and, then, the

342

fluorescence was measured using an excitation wavelength of 485 nm and an

343

emission wavelength of 530 nm. Using a standard curve measured for human

344

myeloperoxidase (0, 0.1, 0.2, 1, 2 and 5 mU/mL), the myeloperoxidase activity

345

[mU/mL] was plotted against the fluorescence measured for the saliva samples.

346

Lysozyme quantitation in saliva was performed by means of the EnzChek

347

Lysozyme Assay Kit (life technologies, Darmstadt, Germany) according to the

348

manual, however, using recombinant human lysozyme instead of the provided

349

standard. For assay calibration, a standard curve was recorded using defined

350

lysozyme concentrations (0.01, 0.005, 0.001, 0.0005, 0.0001 and 0 µg/µL). As the

351

calibration showed excellent linearity (y = 305447.58x + 67.21; R2 = 0.99), the non-

352

stimulated (t0) as well as the stimulated saliva (t45) had to be diluted to match the

353

calibration. After centrifugation (13’200 rpm, 10 min, 4°C) aliquots (100 µL) of the

354

non-stimulated saliva (t0) were 1+4 and 1+9 diluted with PBS buffer, aliquots (100 µL)

355

of stimulated saliva (t45) were 1+29 and 1+49 diluted with PBS buffer, and aliquots

356

(100 µL) of non-stimulated saliva (t0) spiked with lysozyme were 1+39 and 1+69 ACS Paragon Plus Environment

Page 14 of 51

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357

diluted with PBS buffer, respectively. Finally, aliquots (50 µL) of the respective

358

samples were mixed with the DQ lysozyme substrate working suspension (50 µL) in

359

a solid black 96-well-plate (round bottom; Corning®, Sigma Aldrich), and incubated

360

for 30 min at 37°C inside a FLUOstar OPTIMA (BMG Labtech) reader. The

361

fluorescence was recorded using the excitation at 485 nm and emission at 520 nm.

362

Using triplicate analysis in both dilutions, lysozyme concentration was calculated

363

from the average of the data determined in individual non-stimulated (t0) and

364

stimulated saliva samples (t45) collected from eleven volunteers. The lysozyme

365

concentrations determined in saliva samples at the same day time (10:00 am) on

366

three consecutive days were used to study interday variation, and those found at

367

10:00 am, 1:00 pm and 16:00 pm to investigate the intraday variation of the stimulus-

368

induced rise in salivary lysozyme levels. The same assay was used to quantitate the

369

lysozyme concentrations in saliva samples used for the microbial growth

370

experiments.

371

Molecular Weight Separation of Human Saliva. Stimulated saliva was

372

separated into a low molecular weight fraction (LMW, 3 kDa) using a Vivaspin Turbo 4 (Sartorius, Göttingen,

374

Germany) spinning tube following the manufacturer´s instructions. To achieve this,

375

the ultrafiltration tube (MW cutoff: 3 kDa) was centrifuged (7’500 rpm, 30 min, 4°C)

376

twice with water (4 mL) to wash the filtration membrane, then an aliquot (2 mL) of the

377

stimulated saliva (t45) was centrifuged (13’200 rpm, 10 min, 4°C) and the filtrate

378

(< 3 kDa) and the residue (> 3 kDa) was made up with PBS buffer to a final volume

379

of 2 mL to perform microbial growth experiments.

380

Microbial Growth Experiments. Aliquots (12 mL) of non-stimulated (t0) and

381

post-stimulus saliva samples (t45), each collected and pooled from six volunteers,

382

were centrifuged (13’200 rpm, 10 min, 4 °C) and after filtration using a syringe filter ACS Paragon Plus Environment


Page 16 of 51

383

(0.22 µm, Millex GP, Merck Millipore, Darmstadt, Germany), the supernatants were

384

used for growth experiments with Gram-positive and lysozyme sensitive species

385

Microbacterium oxydans (G4266) and Kocuria palustris (G4058) as well as

386

Staphylococcus aureus (G4508) as a lysozyme resistant control using an automated

387

plate

388

Finland). To perform the growth experiments, pre-cultures were prepared from a

389

single colony in tryptic soy broth (TSB, Roth, Karlsruhe, Germany) incubated at 30°C

390

for 22 h. Each strain pre-culture was inoculated 1:1000 with the double concentrated

391

TSB medium. An aliquot (100 µL) of inoculated medium was dispensed into each

392

well of a microplate and aliquots (100 µL) of the saliva samples were added. PBS

393

was used instead of saliva as a control. Analyses were performed at 30°C for 48

394

hours by shaking at medium intensity in the Bioscreen C™ instrument and measuring

395

the OD600 every 30 minutes. Every sample was measured in triplicate and four

396

independent experiments were carried out. Prior to the Bioscreen C™ experiments,

397

the lysozyme content of all samples was quantified by using the lysozyme assay.

reader

(BioScreen

C;

Oy

Growth

curves

Ab

Ltd,

Helsinki

398 399

RESULTS AND DISCUSSION

400

In order to study the impact of chemosensory stimuli on human saliva flow and

401

salivary proteome alterations, healthy volunteers were orally challenged with a

402

stimulus-free control vehicle (water) and aqueous hyperthreshold solutions of the

403

sour tasting citric acid (stimulus S1; 156 mmol/L), the high-potency sweetener

404

aspartame (stimulus S2; 3.4 mmol/L), the beer’s bitter principle iso-α-acids (stimulus

405

S3; 0.3 mmol/L), the umami tasting monosodium L-glutamate (MSG, stimulus S4; 30

406

mmol/L), the salty tasting sodium chloride (NaCl, stimulus S5; 513 mmol/L), the

407

ginger’s pungent principle 6-gingerol (stimulus S6; 1.7 mmol/L), and Szechuan ACS Paragon Plus Environment

Page 17 of 51


408

pepper’s chemosensates hydroxy-α-sanshool (tingling, stimulus S7; 4 mmol/L) and

409

hydroxy-β-sanshool (numbing, stimulus S8; 4 mmol/L), respectively.

410

Influence of chemosensory stimuli on saliva flow. After cleansing the oral

411

cavity for 60 s with water, the healthy volunteers were asked to take stimulus-free

412

water (control, w/o) into the oral cavity, to perform chewing motions for 30 s and,

413

then, to expectorate into pre-weighed petri-dishes to give the pre-stimulus sample

414

(t0). Defined aliquots of the aqueous stimulus solutions (S1 – S8) were then taken

415

into the mouth and, after performing chewing motions for 15 s, the panellists were

416

asked to expectorate into pre-weighed petri-dishes to deliver the corresponding

417

stimulus sample (t15). The subjects were then requested to take up an aliquot of

418

water and, after performing chewing motions for 30 s, to expectorate to afford the first

419

post-stimulus saliva sample (t45), followed by another repetition of this last assay step

420

to give a second post-stimulus sample (t75). After addition of a protease inhibitor, the

421

saliva samples (t0 – t75) collected from eight different subjects at three independent

422

days were pooled and the amount of saliva was calculated from the weight difference

423

of the expectorated saliva/water mixture and the aliquot of the aqueous solutions

424

used to collect the saliva sample.

425

When compared to the control (water), which did not significantly affect salivation

426

from t0 to t75, citric acid (S1) showed the highest salivation inducing activity with a

427

saliva flow increase running through a maximum of ~110% at t45, followed by the

428

tingling hydroxy-α-sanshool (S7) and the pungent 6-gingerol (S6), both showing a

429

maximum saliva flow increase of ~60% at t45 (Figure 1). This confirms previous

430

reports on the salivation inducing activity of sour, tingling, and pungent taste stimuli46,

431

48, 61-66

432

by the configuration of a double bond, stimulation with equimolar concentrations of

433

the numbing hydroxy-β-sanshool (S8) showed a comparatively small saliva flow

. Although differing from the chemical structure of hydroxy-α-sanshool (S7) just



434

increase of 25% only (Figure 1). The salty stimulus (S5) induced a weaker but more

435

rapid saliva flow increase of about 30% at t15, whereas the sweet, bitter, and umami

436

stimuli S2-S4 affected saliva flow only to a marginal extend reaching a maximum of

437

~20% at t45 (Figure 1).

438

Salivary proteome alterations induced by chemosensory stimuli. In order

439

to investigate the influence of the dietary taste stimuli (S1 – S8) on the human saliva

440

proteome, proteins were precipitated from the collected saliva samples (t0, t15, t45,

441

t75), separated by SDS-PAGE and, after tryptic in-gel digestion, the cleaved peptides

442

were analyzed by means of nano-LC-MS/MS. A total number of 344 proteins were

443

identified by searching MS/MS spectra against a decoyed human IPI database and

444

using probabilistic protein identification algorithms with a threshold of at least two

445

independent peptide identifications (probability > 0.95). Only proteins with at least

446

two reliably identified peptides and at least four spectral counts for at least one

447

biological replicate in a group were considered for label-free protein quantification

448

using normalized spectral abundance factor (NSAF) values calculated from the

449

spectral counts of each individual identified protein49, 50.

450

Plotting the number of identified proteins for each of the eight taste stimuli

451

revealed, independent of the stimulus, a high number of identified proteins ranging

452

between 174 (S4) and 227 (S3) (Figure 2a). Among the 344 proteins identified in

453

total, a subset of 108 proteins were found in all eight datasets independent of the

454

stimulus and 15-39 proteins were found to be shared by two up to seven stimuli. In

455

comparison, 77 proteins were identified in saliva samples stimulated by only a single

456

stimulus, thus indicating the proteome alteration to be highly specific to the chemical

457

structure of the stimulus (Figure 2b).

458

To further narrow down the data set to the interesting target proteins, only

459

those proteins, which were significantly affected in abundance upon salivary ACS Paragon Plus Environment

Page 18 of 51

Page 19 of 51


460

stimulation, were taken into further consideration. The highest number of 131

461

proteins was found to be modulated after stimulation with citric acid (S1), followed by

462

NaCl (S5), 6-gingerol (S6), and hydroxy-α-sanshool (S7) with 90, 81, and 66

463

significantly modulated proteins detected, respectively (Figure 2c). The saliva

464

samples collected after stimulation with the other tastants revealed a lower number of

465

significantly affected proteins ranging between 36 (S8) and 54 proteins (S2),

466

respectively. While not even a single protein was significantly modulated by each of

467

the eight stimuli and less than 20 out of the total number of proteins were found to be

468

affected by four to seven chemosensory stimuli, intriguingly, 105 proteins were found

469

to be significantly modulated upon stimulation with a single tastant (Figure 2d).

470

These data clearly demonstrate a stimulus-specific, rather than a generic impact of

471

chemosensates on saliva proteome composition.

472

PCA score plotting of log scaled protein abundances revealed a clear

473

separation of the eight stimuli with the largest proportion of the variance in the first

474

two principal components covered by longitudinal changes during stimulation with

475

citric acid (S1) and sodium chloride (S5), respectively (Figure 3). Visualization of

476

trajectories connecting the mean scores for the individual time intervals (t0 → t75) of

477

each stimulus showed protein pattern shifts in different directions, again indicating

478

stimulus-specific effects. For example, time-resolved analysis of proteome changes

479

induced by citric acid (S1) revealed a major impact immediately after stimulation (t15),

480

followed by smaller changes on the way back to the control sample (t0), thus

481

demonstrating the instantaneous salivary response to that stimulus (Figure 3).

482

Gene ontology term enrichment analysis. In order to investigate whether the

483

observed stimuli-dependent proteome alterations may translate into a modulation of

484

saliva’s biological activities and to visualize functional inter-relationships, a gene

485

ontology (GO) enrichment analysis was performed67-69. To identify biological ACS Paragon Plus Environment


486

functions associated with significantly enriched proteins upon a chemosensory

487

stimulation, enrichment of GO-terms of the subontology “biological process”,

488

representing molecular events with a defined beginning and end, pertinent to the

489

functioning of integrated living units such as cells, tissues, and organisms, was

490

calculated using Fisher´s exact test and the ensemble of proteins detected in human

491

saliva as the background proteome18. Using a p-value of 0.01 as cut-off after

492

adjusting for multiple tests51, a total of 460 enriched GO-terms for the set of eight

493

stimuli was obtained ranging from 247 for citric acid (S1), 197 for sodium chloride

494

(S5), and 155 for 6-gingerol (S6) to lower numbers of 108 for hydroxy-α-sanshool

495

(S7), 96 for iso-α-acids (S3), 85 for mono sodium L-glutamate (S4), 80 for aspartame

496

(S2), and 49 for hydroxy-β-sanshool (S8), respectively. To highlight GO-terms

497

associated with the chemosensory stimulation, the enrichment result was filtered for

498

terms that are offspring of the term compiling “response to stimulus” functions

499

(GO:0050896) including processes that result in a change in state or activity of a cell

500

or organism as a result of a stimulus and lead to functions such as enzyme

501

production, gene expression, secretion, or chemotaxis, respectively. The remaining

502

GO-terms were subsequently analyzed for semantic similarities applying a graph-

503

based method70, which determines the semantic similarity of two GO-terms based on

504

both the locations of these terms in the GO-graphs and their relations with their

505

ancestor terms (Figure 4)58. Cluster analysis using the semantic similarities as

506

distance matrix lead to a grouping of enriched GO terms with closely related

507

biological functions, which were subsequently compared for group by the individual

508

chemosensory stimuli S1 – S8 (Figure 4).

509

Whereas stimulation with iso-α-acids (S3) and mono sodium L-glutamate (S4)

510

delivered only minor GO term enrichments, GO-terms related to immune response

511

and to response to bacteria were enriched highly significantly in the saliva collected ACS Paragon Plus Environment

Page 20 of 51

Page 21 of 51


512

after simulation of citric acid (S1), e.g. the enriched GO-terms “response to other

513

organism” (GO:0051707; p-value: 3.8×10-5), “response to bacterium” (GO:0009617;

514

p-value: 2.5×10-5), “response to external biotic stimulus” (GO:0043207; p-value:

515

3.8×10-5), “antimicrobial humoral response” (GO:0019730; p-value: 1.1×10-7), and

516

“defense response to bacterium” (GO:0042742; p-value: 5.4×10-6) show evidence for

517

the citric acid induced alterations of the saliva proteome to boot a molecular defense

518

network against microorganisms.

519

In comparison, the NaCl as well as the 6-gingerol challenge led to a strong

520

enrichment of GO terms related to detoxification and immune response, while GO-

521

terms related to oxidative stress were solely enriched after 6-gingerol stimulation.

522

The GO-terms “response to reactive oxygen species” (GO:0000302; p-value: 2.9×10-

523

8

524

oxygen radical” (GO:0000305; p-value: 7.9×10-5), or “cellular response to oxygen

525

radical” (GO:0071450; p-value: 7.9×10-5) respectively, were highly enriched after 6-

526

gingerol activation when compared to the background proteome (Figure 4,

527

supporting information).

), “response to hydrogen peroxide” (GO:0042542; p-value: 1.4×10-5), “response to

528

Chemosensory modulation of biological saliva functions. In order to

529

identify those significantly modulated proteins showing the highest contribution to the

530

highly significant enrichment of oxidative stress related GO-terms in the 6-gingerol

531

dataset, those proteins contributing most to the enriched GO-terms were extracted.

532

Among the 14 proteins extracted (Figure 5), cystatin C (CYTC_HUMAN) and

533

lactoperoxidase (PERL_HUMAN) showed the strongest increase in abundance upon

534

6-gingerol stimulation, whereas the other 12 proteins were affected only to a minor

535

extent. While cystatin C has been reported to show proteinase inhibitory71,

536

antimicrobial activity in saliva73, salivary lactoperoxidase plays a crucial role in the

537

peroxidase innate defense system74. The latter enzyme is reported to catalyze the ACS Paragon Plus Environment

72

and


Page 22 of 51

538

oxidation of thiocyanate (0.5 – 2 mmol/L in saliva) by hydrogen peroxide (8 – 14

539

µmol/L in saliva) to produce hypothiocyanate, an antimicrobial agent that inhibits the

540

growth of a wide range of microorganism including oral pathogens like Streptococcus

541

species, Porphyromonas gingivalis, and Aggregatibacter actinomycetemcomitans74-

542

76

.

543

The 14 target proteins were also searched among the significantly modulated

544

proteins in the datasets of the other seven stimuli (supplementary information).

545

Interestingly, lactoperoxidase was also found to be modulated to some extent after

546

stimulation with hydroxy-α-sanshool (S7), whereas stimulation with citric acid (S1)

547

translated

548

myeloperoxidase (supplementary information). In the other datasets, no peroxidases

549

were found to be significantly increased in abundance upon stimulation.

into

an

increasing

abundance

of

another

peroxidase,

namely

550

To investigate whether the increased abundance in lactoperoxidase in gingerol-

551

stimulated saliva translates into an increased enzymatic activity, the lactoperoxidase

552

activity was measured in saliva collected before (t0) and 45 s after 6-gingerol

553

stimulation (t45) by means of a fluorescence assay (Figure 6a). The peroxidase

554

activity in saliva showed a significant 2.5-fold increase from 0.37±0.02 (t0) to

555

0.91±0.05 mU/mL (t45), thus confirming that the increased abundance of the protein

556

observed upon 6-gingerol stimulation leads to an increased peroxidase activity of

557

saliva.

558

In contrast to 6-gingerol (S6), the salivary stimulation with citric acid (S2)

559

induced an increase of salivary abundance of myeloperoxidase (Fig. 6b), which is

560

known to catalyze the oxidation of chloride ions (10 – 56 mmol/L in resting saliva) by

561

hydrogen peroxide to generate hypochloride ions acting as a strong antimicrobial

562

agent in saliva74. To study whether the increased concentration of this protein is

563

translated into a higher enzymatic activity in saliva, the peroxidase activity as well as ACS Paragon Plus Environment

Page 23 of 51


564

the activity to oxidize chloride to hypochlorite were measured before (t0) and after

565

stimulation (t45) with citric acid (Figure 6b). Myeloperoxidase activity increased from

566

0.24±0.04 (t0) to 0.70±0.1 mU/mL (t45). Whereas the saliva sample t0 did not show

567

any significant amounts of hypochlorite, the activated saliva (t45) generated elevated

568

levels of OCl- (Figure 6b), thus indicating that the citric acid stimulation induces a

569

significant raise in myeloperoxidase abundance, followed by a significant increase in

570

the antimicrobial agent hypochlorite.

571

In comparison, a total of 22 significantly modulated proteins showed the highest

572

contribution to the significant enrichment of “response to bacteria” related GO-terms

573

in the citric acid dataset (Figure 7). Among the proteins extracted, lysozyme

574

(LYSC_HUMAN) showed by far the strongest increase in abundance upon citric acid

575

stimulation, whereas the other 21 proteins were affected to a much lower extent

576

(supplementary information).

577

To validate the strong increase of lysozyme abundance, the concentration of

578

lysozyme was enzymatically determined in resting saliva (t0) and citric acid stimulated

579

saliva (t45) collected from eleven individuals. To investigate intra-day and inter-day

580

variation of citric acid induced lysozyme stimulation, saliva samples were collected at

581

three time slots at the same day (10:00 am, 1:00 and 4:00 pm) and at the same time

582

(10:00 pm) on three consecutive days (Figure 8). While non-stimulated saliva (t0)

583

contained lysozyme in low levels of 0.006 - 0.01 µg/µL, citric acid stimulation induced

584

a more than 10-fold increased lysozyme secretion to reach concentrations of 0.10 –

585

0.14 (intraday; Figure 8a) and 0.11 – 0.15 µg/µL (interday; Figure 8b) in activated

586

saliva (t45), without showing major inter-individual differences.

587

Inhibition of bacterial growth. To investigate as to whether the citric acid

588

induced increase of lysozyme levels translates into an enhanced antimicrobial activity

589

of saliva on Gram-positive bacteria, growth experiments were carried out using the ACS Paragon Plus Environment


590

lysozyme-sensitive species Microbacterium oxydans and Kocuria palustris, as well as

591

Staphylococcus aureus as a lysozyme resistant control, each incubated in TSB in the

592

absence or presence of non-stimulated saliva (t0), stimulated saliva (t45), and non-

593

stimulated saliva (t0) spiked with lysozyme to adjust the concentration to the levels

594

determined in stimulated saliva, respectively. For each growth inhibition experiment

595

four biological replicates and three analytical replicates were performed and

596

averaged into one growth curve (Figure 9). The growth of the control strain S. aureus

597

was neither inhibited by stimulated saliva (t45), nor by non-stimulated saliva (t0)

598

spiked with lysozyme to adjust the concentration to the level of 0.152±0.045 µg/µL

599

determined in stimulated saliva (Fig. 9a), confirming the well-known resistance of S.

600

aureus against lysozyme77. In contrast, the growth of M. oxydans and K. palustris

601

was strongly affected or even completely inhibited in the presence of stimulated

602

saliva (Fig. 9b,c), thus confirming a direct inhibitory effect of stimulated saliva (t45) on

603

the growth of these lysozyme-sensitive bacteria.

604

To investigate whether, next to high-molecular weight (HMW) biopolymers like

605

lysozyme, also low-molecular weight (LMW) metabolites account for the growth

606

inhibitory activity of stimulated saliva, activated (t45) saliva samples were fractionated

607

by means of ultrafiltration using a 3 kDa cut-off and both molecular weight fractions

608

were again tested for their anti-growth potential. Growth curves recorded in the

609

presence of the LMW fraction (< 3 kDa), where all proteins including lysozyme had

610

been removed, perfectly matched the control curves using PBS (Figure 9b, c). In

611

comparison, the presence of the HMW fraction (> 3 kDa) containing 0.15±0.03 µg/µL

612

lysozyme induced growth inhibition resembling the data recorded for stimulated t45

613

saliva (Figure 9b, c). These data clearly demonstrate the observed growth inhibitory

614

activity of citric acid stimulated saliva to be primarily caused by lysozyme.


Page 24 of 51

Page 25 of 51


615

In summary, saliva flow measurements, SDS-PAGE separation of human

616

saliva, followed by tryptic digestion, nano-HPLC-MS/MS, and label-free quantitation

617

demonstrated a stimulus- and time-dependent influence of dietary taste compounds

618

on salivation and the salivary proteome alteration. Gene ontology enrichment

619

analysis showed evidence for the tastant-induced alterations of the saliva proteome

620

to trigger innate protective mechanisms and an enhanced level of antimicrobial

621

defense. An oral challenge with 6-gingerol increased the abundance of cystatin C,

622

showing proteinase inhibitory71,

623

lactoperoxidase, which plays a key role in the peroxidase innate defense system74,

624

catalyzes

625

hypothiocyanate (OSCN-), and has been reported to inhibit the growth of a wide

626

range of microorganism74-76. In comparison, citric acid stimulation induced an

627

increase of myeloperoxidase, reported to catalyze the oxidation of chloride ions to

628

generate antimicrobial hypochloride ions (OCl-) in saliva74 and lysozyme, well-known

629

to exhibit antimicrobial activity on gram-positive bacteria21, 73, 77.

the

oxidative

72

and antimicrobial activity in saliva73, and

conversion

of

thiocyanate

into

the

antimicrobial

630

Functional analysis of these target enzyme activities confirmed the increase of

631

the salivary lactoperoxidase activity from 0.37±0.02 (t0) to 0.91±0.05 mU/mL (t45)

632

after oral 6-gingerol stimulation, while citric acid induced the increase of

633

myeloperoxidase activity from 0.24±0.04 (t0) to 0.70±0.1 mU/mL (t45) and salivary

634

lysozyme levels from 0.006 – 0.01 µg/µL (t0) to 0.10 – 0.15 (t45). As the stimulus-

635

induced salivary proteome response was observed instantaneously upon stimulation,

636

any proteome modulation is very likely to result from the release of proteins from

637

preformed vesicles and not from de novo synthesis which in exocrine cells were

638

shown to take about 30 min to pass from the rough endoplasmatic reticulum to the

639

condensing vacuoles79. As lactoperoxidase is released from the salivary glands and

640

myeloperoxidase is produced by neutrophil granulocytes entering the oral cavity and ACS Paragon Plus Environment


641

is also present in the gingival crevicular fluid73, the stimulus-specific release of these

642

enzymes indicates rather specific and different sites of action of 6-gingerol and citric

643

acid.

644

The data indicate that oral stimulation with 6-gingerol and citric acid,

645

respectively, may activate the innate defense and enhanced antimicrobial function of

646

saliva through the increased generation of the antimicrobial agents OSCN-

647

(lactoperoxidase) and OCl- (myeloperoxidase) catalyzed by salivary peroxidases as

648

well as the enhanced release of lysozyme. This latter enzyme, produced primarily

649

from the sublingual saliva glands80 and also by neutrophil granulocytes entering the

650

mouth78, induces lysis of gram-positive bacteria by its muramidase activity

651

hydrolysing the β-1,4-glycosidic bonds between N-acetylmuramic acid and N-acetyl-

652

D-glucosamine

653

positive bacteria Microbacterium oxydans and Kocuria palustris in the presence of

654

non-stimulated and stimulated saliva samples clearly demonstrated for the first time

655

that the increase of the salivary lysozyme abundance upon oral chemosensory

656

stimulation translates into an enhanced biological function, that is an almost complete

657

growth inhibition of the gram-positive microorganisms tested. The effects of the

658

various antimicrobial agents may also be additive or synergistic, resulting in the

659

activation of an efficient molecular defense network of the oral cavity through

660

chemosensory stimulation upon food ingestion.

of the cell wall peptidoglycan78. Growth experiments with gram-

661

The depth and relatively straightforward nature of the developed analytical

662

workflow should make it a powerful tool enabling a better understanding of stimulus-

663

triggered alterations of the oral proteome and, in consequence, of saliva’s biological

664

functions. Such approaches will help to better understand the mechanisms triggering

665

the molecular defense network and open new avenues for innovative oral care

666

applications triggering innate defense mechanisms in the mouth. ACS Paragon Plus Environment

Page 26 of 51

Page 27 of 51


667 668

SUPPORTING INFORMATION AVAILABLE

669

Data on identified proteins, Uniprot identifier, and NSAF data before and after

670

chemosensory stimulation are available free of charge via the Internet at

671

http://pubs.acs.org.

672 673 674 675



676

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FIGURE LEGENDS

940 Figure 1.

Time course of saliva flow affected by chemosensory stimuli. Saliva samples were collected from eight individuals before stimulation (t0), after a 15 sec chemosensory stimulation (t15), and 30 (t45) and 60 sec after stimulation (t75) with the following aqueous stimuli solutions: (a) stimulus-free vehicle (water; control), (b) citric acid (stimulus S1; 156 mmol/L), (c) aspartame (stimulus S2; 3.4 mmol/L), (d) iso-α-acids (stimulus S3; 0.3 mmol/L), (e) mono sodium L-glutamate (stimulus S4; 30 mmol/L), (f) NaCl (stimulus S5; 513 mmol/L), (g) 6-gingerol (stimulus S6; 1,7 mmol/L), (h) hydroxy-α-sanshool (stimulus S7; 4 mmol/L), and (i) hydroxy-βsanshool (stimulus S8; 4 mmol/L), respectively. The thin lines indicate the individual replicates, the bold line indicates the mean value, and the colored area surrounding the mean curve indicates the simple standard deviation.


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Figure 2.

Number of proteins identified in human saliva after chemosensory stimulation. Stimuli used were citric acid (S1; 156 mmol/L), aspartame (S2; 3.4 mmol/L), iso-α-acids (S3; 0.3 mmol/L), mono sodium L-glutamate (S4; 30 mmol/L), NaCl (S5; 513 mmol/L); 6gingerol (S6; 1,7 mmol/L), hydroxy-α-sanshool (S7; 4 mmol/L), and hydroxy-β-sanshool (S8; 4 mmol/L), respectively. (a) Total number of proteins identified per stimuli (S1-S8). (b) Number of proteins shared by single or multiple (two to eight) stimuli. (c) Number of significantly modulated proteins per stimulus. (d) Number of significantly modulated proteins shared by single or multiple (two to eight) stimuli.

Figure 3.

PCA score plot of log-scaled protein abundances in control (t0), stimulated saliva (t15), and post-stimulation saliva samples (t45, t75). Stimuli used were citric acid (S1; 156.0 mmol/L), aspartame (S2; 3.4 mmol/L), iso-α-acids (S3; 0.3 mmol/L), mono sodium Lglutamate (S4; 30.0 mmol/L), NaCl (S5; 513.0 mmol/L); 6-gingerol (S6; 1,7 mmol/L), hydroxy-α-sanshool (S7; 4.0 mmol/L), and hydroxy-β-sanshool (S8; 4.0 mmol/L). Trajectories connecting the mean scores for the individual time intervals (t0 → t75) of each stimulus are shown as arrows.



Figure 4.

Page 40 of 51

GO enrichment analysis after chemosensory stimulation with citric acid (S1; 156.0 mmol/L), aspartame (S2; 3.4 mmol/L), iso-α-acids (S3; 0.3 mmol/L), mono sodium L-glutamate (S4; 30.0 mmol/L), NaCl (S5; 513 mmol/L); 6-gingerol (S6; 1.7 mmol/L), hydroxy-αsanshool (S7; 4 mmol/L), and hydroxy-β-sanshool (S8; 4.0 mmol/L), respectively.

Figure 5.

Time course of significantly modulated salivary proteins with highest contribution to the significant enrichment of oxidative stress related GO-terms in the 6-gingerol dataset (Cluster B; Figure 4). Saliva samples were collected before stimulation (t0), after a 15 sec stimulation with 6-gingerol (S6; 1.7 mmol/L) (t15), and 30 (t45) and 60 sec after stimulation (t75). The thin lines indicate the individual replicates, the bold line indicates the mean value.

Figure 6.

Time course and enzymatic activity of lactoperoxidase upon 6-

gingerol

stimulation

and

myeloperoxidase

upon

citric

acid

stimulation. (a) Lactoperoxidase abundance (left) and peroxidase activity (right) in saliva samples collected before stimulation (t0), after a 15 sec stimulation with 6-gingerol (S6; 1.7 mmol/L) (t15), and 30 (t45) and 60 sec after stimulation (t75). (b) Myeloperoxidase abundance (left), enzymatic activity (middle), and chlorination activity (right) in saliva samples collected before stimulation (t0), after a 15 sec stimulation with citric acid (S1; 156 mmol/L) (t15), and 30 (t45) and 60 sec after stimulation (t75).


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Figure 7.

Time course of significantly modulated salivary proteins with highest contribution to the significant enrichment of response to bacterium related GO-terms upon citric acid stimulation (Cluster A; Figure 4). Saliva samples were collected before stimulation (t0), after a 15 sec stimulation with citric acid (S1; 156 mmol/L) (t15), and 30 (t45) and 60 sec after stimulation (t75). The thin lines indicate the individual replicates, the bold line indicates the mean value.

Figure 8.

Box plots of salivary lysozyme concentrations before (t0) and after stimulation (t45) with citric acid (S1). (a) Interday variation (n=11). (b) intraday variation (n=11).

Figure 9.

Growth curves of selected microorganisms in the presence of saliva samples. (a) Staphylococcus aureus, (b) Microbacterium oxydans, (c) and Kocuria palustris.

941



942

Figure 1

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945 946 947 948 949 950 951 952 953 954 955 956


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Figure 2

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959 960 961 962 963



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Figure 3

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Figure 4

974 975 976 977

978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 ACS Paragon Plus Environment


994

Figure 5

995 996

997 998 999 1000 1001 ACS Paragon Plus Environment

Page 46 of 51

Page 47 of 51

1002


Figure 6

1003

1004 1005 1006 1007



1008

Figure 7

1009

1010 1011 1012


Page 48 of 51

Page 49 of 51

1013


Figure 8

1014

1015 1016 1017 1018 1019 1020 1021 1022 1023 1024



1025

Figure 9

1026

1027 1028 1029


Page 50 of 51

Page 51 of 51


TOC Graphic 176x115mm (150 x 150 DPI)


Dynamic Proteome Alteration and Functional Modulation of Human

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