TY - JOUR
AU - Roura,, Eugeni
AB - Abstract Starch-related sweet taste perception plays an important role as a part of the dietary nutrient sensing mechanisms in the oral cavity. However, the release of sugars from starchy foods eliciting sweetness has been less studied in humans than in laboratory rodents. Thus, 28 respondents were recruited and evaluated for their starch-related sweet taste perception, salivary alpha-amylase (sAA) activity, oral release of reducing sugars, and salivary leptin. The results demonstrated that a 2-min oral mastication of starchy chewing gum produced an oral concentration of maltose above the sweet taste threshold and revealed that the total amount of maltose equivalent reducing sugars produced was positively correlated with the sAA activity. In addition, respondents who consistently identified the starch-related sweet taste in two sessions (test and retest) generated a higher maltose equivalent reducing sugar concentration compared to respondents who could not detect starch-related sweet taste at all (51.52 ± 2.85 and 29.96 ± 15.58 mM, respectively). In our study, salivary leptin levels were not correlated with starch-related sweet taste perception. The data contribute to the overall understanding of oral nutrient sensing and potentially to the control of food intake in humans. The results provide insight on how starchy foods without added glucose can elicit variable sweet taste perception in humans after mastication as a result of the maltose generated. The data contribute to the overall understanding of oral sensing of simple and complex carbohydrates in humans. leptin, reducing sugar, salivary alpha-amylase, starch, sweet taste Introduction Excess energy intake is a key contributor to the global overweight and obesity epidemic affecting more than 1.9 billion people (Swinburn et al. 2011; WHO 2015). Since starch is the main dietary energy source, it is important to understand the digestive and metabolic mechanisms of starchy foods and their impact on appetite (Ma et al. 2005; Krieger et al. 2006). Starch degradation products such as maltose, maltotriose, and higher oligomers of glucose (Robyt 2009) have the potential to contribute to the cephalic response to nutrients, which consists of the activation of the enteroendocrine system to signal the brain and condition the digestive tract for enzymatic digestion and absorption of foods (Zafra et al. 2006; Behrens et al. 2011; Breslin 2013). Hormones involved in this response include leptin, cholecystokinin, peptide YY, and glucagon-like peptide-1 (GLP-1) (Badman and Flier 2005; Janssen and Depoortere 2013). These hormones are known to regulate energy and glucose homeostasis by modulating the food reward system implicated in hunger and satiety neuronal signals (Berridge and Robinson 1998; Finlayson et al. 2007). In addition, saliva also contains a small quantity of some of the hormones, such as leptin, an anorexigenic hormone, which has been suggested to supress sweet taste perception (Shigemura et al. 2004; Shin et al. 2008; Elson et al. 2010; Martin et al. 2010). Starch hydrolysis starts during the mastication process thanks to salivary alpha-amylase (sAA), the most abundant enzyme in saliva (de Wijk et al. 2004; Ferry et al. 2004; Ferry et al. 2006; Mandel et al. 2010; Woolnough et al. 2010). Despite having only a short contact time with foods in the oral cavity, sAA has the potential to elicit sweet taste by releasing maltose and maltotriose, two known agonists of the sweet taste receptor dimer (consisting of two subunits: T1R2 and T1R3) in humans (Pedersen et al. 2002; Pullicin et al. 2017). In addition, in the context of oral starch hydrolysis products, the T1R2/T1R3-independent sensing of monosaccharides (e.g., glucose and fructose) seems to be related to the system of glucose transporters, sodium-glucose transport protein 1 and brush border enzymes in the oral cavity (Yee et al. 2011; Glendinning et al. 2015; Sukumaran et al. 2016), an analogous system previously described in the small intestine (Cheng et al. 2014; Zhang et al. 2015). Recent literature have reported that the amount of simple sugars released from glucose polymers or starch solutions (mainly maltose) in the absence of chewing was too low to be detected (Lapis et al. 2014; Lapis et al. 2017). In addition, individual differences in sAA may play a significant role in starch-related sweet taste perception (Lapis et al. 2017). However, the impact of a normal mastication on glucose oligomer and polymer release from starch and on starch-related sweet taste perception in humans has not been fully elucidated to date. Thus, in the present study, the potential effect of sAA to elicit starch-related sweet taste during an oral mastication process and how sAA activity changes during oral starch digestion were studied. In addition, we aimed to investigate the relationship between individual sAA activity and starch-related sweet taste intensity in human respondents. Finally, the potential suppressing effect of leptin on sweet taste perception was assessed. Materials and Methods This study was approved by the University of Queensland Research Ethics Committee (certificate #2014001195). Declaration of Helsinki principle was applied in this study, and all the respondents provided informed consent before participation. Respondents Thirty-one respondents were selected from the University of Queensland staff and student populations. However, 2 respondents were not able to complete the study and 1 respondent was excluded from the analysis due to ill health. Thus, the data collected from 28 respondents (15 males and 13 females, mean age 32.57 ± 1.47, mean body mass index [BMI] 23.6 ± 0.74) was used for the final statistical analysis. Before performing the sensory test, respondents were required to complete a general questionnaire with health status, food habits, and age to determine suitability for the project. All selected respondents were non-smokers, had no chronic medication, had no dental injuries, and had no known taste disorders. The respondents were asked to comply with the following restrictions prior to test sessions: no consumption of food or beverages of any kind except water within 1 h and no exercise within 2 h of the test session. All tests carried out by respondents were conducted in duplicate, with the first replicate referred to as “test” and the second replicate as “retest.” In total, respondents were required to perform 10 sessions: 2 sessions per day between 9 AM and 12 PM for 5 non-consecutive days over a 5-week period with a week interval between the test and retest of each taste compound. The respondents attended the 2 sessions (test and retest) at approximately the same time of the day as previously requested. This allowed the assessment of sweet taste sensitivity and sweet ratings as well as a dietary-based starch intervention using chewing gum as an oral delivery model. The tests were conducted in an individual booth of the food sensory laboratory at the University of Queensland. Each day, respondents performed a starch intervention session consisting of using chewing gum as a delivery system in the first session followed by a sweet taste sensitivity and rating study in the second session, except for the last day, in which sweet taste sensitivity and rating was carried out in both sessions. In addition, actual body weight (Sanitas SGS 06) and height (Seca 213) were measured on the last day of experiment and BMI was calculated from these measurements (BMI = weight [kg]/height [m2]). Remuneration was given to respondents completing the study. Best estimate thresholds and supra-threshold ratings Six sessions were performed using the triangular forced-choice ascending concentration series method of limits developed by the American Society for Testing and Materials International (ASTM) to determine the best estimate thresholds (BET) of sweet taste detection threshold (ASTM 2008). Three simple sugars were used: sucrose (Home Brand, Woolworths), maltose monohydrate (Sunmalt, Hayashibara), and glucose monohydrate (Glucodin, ICN Pharmaceutical). It was noted that maltose and glucose concentration were 89% and 100%, respectively. One day prior to the test session, sweet taste compounds were prepared by diluting in spring water and were then stored in the fridge at 4 °C. On the testing day, solutions were provided at room temperature (22 °C ± 2) as 3-mL portions in disposable cups. The respondents were asked to use a nose clip and tested 8 different taste concentrations (Table 1). For each concentration, three samples were provided, of which 2 were spring water and 1 contained the sample tastant. Individual taste detection thresholds were derived from the pattern of correct/incorrect answers. More precisely, BET were measured using the geometric mean of the last missed concentration and the next (adjacent) higher concentration (ASTM 2008). Table 1. Sucrose, maltose, and glucose concentrations used for the BET test Tastants Concentration (mM)* Sucrose 0.99 1.61 2.75 4.55 7.56 12.62 21.03 35.05 Maltose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 Glucose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 Tastants Concentration (mM)* Sucrose 0.99 1.61 2.75 4.55 7.56 12.62 21.03 35.05 Maltose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 Glucose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 *Based on the anhydrous form of the sugars. View Large Table 1. Sucrose, maltose, and glucose concentrations used for the BET test Tastants Concentration (mM)* Sucrose 0.99 1.61 2.75 4.55 7.56 12.62 21.03 35.05 Maltose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 Glucose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 Tastants Concentration (mM)* Sucrose 0.99 1.61 2.75 4.55 7.56 12.62 21.03 35.05 Maltose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 Glucose 2.97 4.83 8.25 13.65 22.68 37.86 63.09 105.15 *Based on the anhydrous form of the sugars. View Large Supra-threshold sweet ratings were performed at the end of the BET test. Based on published material, the diurnal sweet recognition threshold for sucrose and glucose were 23–38 and 95–157 mM, respectively (Nakamura et al. 2008). Thus, to be perceived as sweet, the studied concentrations used required around 3–4 times the published detection thresholds (Fabian and Blum 1943; Mickel et al. 1976; Meyerhof 2013; Newman et al. 2013): 35.05 mM for sucrose, 105.15 mM for glucose, and 105.15 mM for maltose (Table 1). The labeled magnitude scale (LMS) was used in this study, as previously described (Green et al. 1996; Bartoshuk et al. 2003). Respondents were trained to use the scale to familiarize themselves with the category ratings, which were “barely detectable,” “weak,” “moderate,” “strong,” “very strong,” and “strongest imaginable.” The sweet ratings were then derived by measuring the percentage of scale range for each taste. Starch-related sweet taste perception and saliva collection An odorless and tasteless commercial polyethylene chewing gum base (Navia, CAFOSA Gum S.A.) was used as a delivery system for starch. The gum allowed the study of starch-related sweet taste in long mastication processes of foods in the absence of other typical starchy food stimuli (e.g., smell, visual cues). In addition, the use of the chewing gum matrix allowed the substrate (starch) to be easily separated from saliva. Four sessions were conducted to measure the starch-related sweet taste intensity. Gelatinized starch was prepared by mixing normal maize starch (Avon Maize Starch, New Zealand Starch, Ltd.) with deionized water in a sealed tube (50% w/v = 56.3 g of maize starch [moisture content 11%] in 100 mL deionized water), and heating at 90 °C for 20 min with continuous agitation at 200 revolutions per minute in a shaking water bath (Ratek). The starchy chewing gums were prepared by mixing equal weights of gelatinized starch (50% w/w) and plain gum base, for a final concentration of 25% (w/w) of starch in each 2.8-g portion of chewing gum. In detail, plain gum base (50 g) was first melted using microwave for 5 min (Panasonic), and then the gelatinized starch (50 g) was added to the melted gum and mixed manually to form a unified gum between the gelatinized starch and plain gum base. Once melted and mixed, the samples were heated using the same microwave for 1 min reaching a melted stage which was manually mixed again. The second process was repeated again to ensure the complete mixing. The control (no starch) chewing gum consisted of 2.8-g portions of plain gum base. During each session 3 saliva collections were performed: the first collection was 7 minutes before the chewing process, and the 2nd and 3rd collections were immediately or 7 minutes after the chewing process, respectively (Figure 1). Salivette (Sarstedt), a commercial pharmaceutical grade sponge for oral applications, was used to collect the saliva. Respondents were asked to gently roll the sponge inside their mouths while chewing it for 2 min. The first saliva (T1) was collected 5 min after the respondents’ arrival. The session continued with the respondents starting to chew the starchy or control gums at a rate of 1 chew per second as previously instructed during a training session. In the study, the volunteers were asked to chew the samples for 2 min. After chewing, a second saliva sample (T2) was collected followed by a subjective sweet taste rating by asking the respondents to answer the following “yes” or “no” question: “Did you perceive sweet taste? Please answer with a yes or no.” Respondents who answered “yes” were asked to rate the sweet intensity using the LMS to rate the supra-threshold taste experienced from “barely detectable” to “strongest imaginable.” The sweet intensity was derived by measuring its percentage of scale range as previously described by others (Green et al. 1996; Bartoshuk et al. 2003). Lastly, a third saliva sample (T3) was collected 5 min after T2. All saliva samples (embedded in the sponges) were weighed and were immediately cooled in ice prior to centrifugation at 1690 × g at 40 °C for 5 min (Heraeus Megafuge 16R, Thermo Fisher Scientific). After centrifugation, T1 and T2 were divided into 2 aliquots: one of the aliquots for both T1 and T2 was used to measure sAA activity. The second aliquot was used to determine leptin or maltose equivalent reducing sugar for the T1 and T2 samples, respectively. The aliquot for the leptin assay was treated with aprotinin (10 µL) (Sigma Aldrich A6279), a protease inhibitor. The aliquot for reducing-sugar assay was heated at 100 °C for 10 min to inactivate the enzymes. All saliva samples were transferred to microfuge tubes and were kept at −80 °C until being processed for analysis. Salivary α-amylase activity assay Upon thawing, the tubes containing saliva were centrifuged once more at 1690 × g at 4 °C for 5 min to ensure that the saliva aliquot was free of solid particles. A commercial kit (EnzChek UltraAmylase Assay Kit) was used as described by the manufacturer to determine sAA activities using porcine pancreatic α-amylase (powdered, 150 000 U/g, Megazyme) as a standard (Boehm et al. 2014). Samples were analyzed using black, flat-bottom, 96-well plates (Greiner) with a FLUOstar Optima fluorescence plate reader (BMG Labtech), taking measurements every 5 min for 30 min using 480-nm (excitation) and 520-nm (emission) filters. The rate of increase of fluorescence intensity was used to determine sAA from the linear range of a standard curve constructed from known sAA activities from 0.01 to 0.1 U/mL. Maltose equivalent reducing sugar assay The para-hydroxybenzoic acid hydrazide (PHBAH) (H9882, Sigma-Aldrich) reducing sugar assay was applied in this experiment using maltose (M9171, Sigma-Aldrich) as a standard (Lever 1972; Moretti and Thorson 2008). The amounts of maltotriose were not measured. The sample (100 µL) was pipetted into a 1.5-mL microcentrifuge tube. A 1:9 mixture of 5% (w/v) PHBAH dissolved in 0.5-M hydrochloric acid (HCl) (Univar, Ajax Finechem) mixed with 0.5-M sodium hydroxide (NaOH) (Chem-Supply Pty Ltd) was freshly prepared. This PHBAH solution (1 mL) was added to the sample tube and heated for 5 min at 100 °C. After being allowed to cool, 200 µL of the solution was transferred into a transparent microplate (Corning Costar 3596) and its absorbance was measured at 410 nm, using a FLUOstar Optima fluorescence plate reader (BMG Labtech). The concentration of maltose equivalent reducing sugar in the samples was determined from the linear range of a standard curve of maltose from 5 to 900 µM. Leptin assay The T1 saliva samples were analyzed for leptin levels. The first saliva collections from the starch test and retest were thawed at room temperature and leptin concentration was determined using a human leptin commercial ELISA Kit (RayBio). The manufacturer’s instructions for analysis of cell culture supernatants and urine were followed (Thanakun et al. 2013). The absorbance was measured at 450 nm using a FLUOstar Optima fluorescence plate reader (BMG Labtech). The leptin standard used contained 0–400 pg/mL and the concentration of leptin in the samples was derived from the linear range. Statistical analysis Pearson correlations were used to correlate test and retest of sAA activity and sweet taste ratings, as well as sAA activity and maltose equivalent reducing sugar concentrations. Paired t-tests were performed for analyzing test and retest sweet taste BET, as well as changes in sAA activity following a starch based intervention and the difference between sAA activity following starchy and control chewing gums. One way ANOVA also was performed to analyze sAA activity, leptin level, and maltose equivalent reducing sugar content based on the difference among starch-related sweet taste perception for none, either test or retest, and both. In addition, principal component analysis (PCA) was performed to observe the difference between tasters (respondents who could detect starch-related sweet taste in at least one test) and non-tasters (respondents who could not detect starch-related sweet taste) based on several parameters, namely: maltose equivalent reducing sugar concentration, leptin level, sAA activity, sugar-sweet thresholds, and ratings for sucrose, maltose, and glucose. If the data were not normally distributed, Kruskall–Wallis instead of ANOVA and Wilcoxon instead of paired t-test were performed. P-values of <0.05 were considered significant. All results are presented as mean ± standard error of the mean (SEM). Figure 1. View largeDownload slide Experimental procedures followed in each testing session. The chewing process consisted of a chewing gum with or without starch and was followed by a subjective sweet taste rating using an LMS. Saliva samples were collected from each correspondent 5, 14 and 21 minutes after the start of the session. Figure 1. View largeDownload slide Experimental procedures followed in each testing session. The chewing process consisted of a chewing gum with or without starch and was followed by a subjective sweet taste rating using an LMS. Saliva samples were collected from each correspondent 5, 14 and 21 minutes after the start of the session. Results Sweet taste BET were evaluated for sucrose, maltose, and glucose to elucidate the respondents’ sensitivity. Overall, there was a highly significant (r = 0.353, P < 0.01) positive correlation between the test and retest sessions (Figure 2A). The average BET (including test and retest sessions) were 7.42 ± 0.85, 15.87 ± 1.53, and 27.64 ± 2.38 mM for sucrose, maltose, and glucose, respectively (Figure 2B). The mean sweetness supra-threshold ratings were 16.30 ± 1.79, 20.87 ± 2.22, and 14.28 ± 2.04 for sucrose (35.05 mM), maltose, and glucose (the last two at 105.15 mM), respectively. Pearson correlations were performed to detect association between sweet ratings among the tastants. Sucrose rating for sweetness was correlated with glucose and maltose (r = 0.722 and r = 0.756, respectively) (P < 0.01). A significant correlation (r = 0.726) was also observed between maltose and glucose (P < 0.01). Figure 2. View largeDownload slide (A) Overall correlation of the BET for sucrose, maltose, and glucose between test and retest (r = 0.353, P < 0.01) and (B) BET were significantly different for sucrose (7.42 ± 0.85 mM), maltose (15.87 ± 4.43 mM), and glucose (27.64 ± 2.38 mM). Different letters (a, b, c) indicate statistically significant differences (P < 0.05). Figure 2. View largeDownload slide (A) Overall correlation of the BET for sucrose, maltose, and glucose between test and retest (r = 0.353, P < 0.01) and (B) BET were significantly different for sucrose (7.42 ± 0.85 mM), maltose (15.87 ± 4.43 mM), and glucose (27.64 ± 2.38 mM). Different letters (a, b, c) indicate statistically significant differences (P < 0.05). The sAA activity results of the test and retest sessions showed highly significant correlations (P < 0.01) with “r” values ranging between 0.491 and 0.770 depending on the time point and treatment (starch vs. non-starch) (Supplementary Figure 2A2B2C2D2E2F). The mean activity at time 2 (after averaging test and retest) was significantly lower in the starch enriched chewing gum (139.16 ± 12.97 U/mL) than the control (179.35 ± 14.03 U/mL), but there was no significant difference at times 1 and 3 (Figure 3). The amount of saliva collected in the control and starchy chewing gums were not significantly different across treatments (P > 0.05). In addition, the mean salivary maltose equivalent reducing sugar concentration was significantly (P < 0.01) lower in the control compared to the starchy chewing gum treatments (0.26 ± 0.32 and 37.04 ± 3.09 mM, respectively). Figure 3. View largeDownload slide sAA activity (U/mL) in control or starchy chewing gum treatments. The first and third saliva collection showed no significant differences (P > 0.05) between the two treatments. The second saliva collection showed a lower sAA in the starchy compared to the control chewing gum cohorts (139.19 ± 12.97 vs. 179.353 ± 14.03 U/mL, P = 0.001). Figure 3. View largeDownload slide sAA activity (U/mL) in control or starchy chewing gum treatments. The first and third saliva collection showed no significant differences (P > 0.05) between the two treatments. The second saliva collection showed a lower sAA in the starchy compared to the control chewing gum cohorts (139.19 ± 12.97 vs. 179.353 ± 14.03 U/mL, P = 0.001). Eleven of the 28 respondents (21.4%) detected starch-related sweet taste in at least 1 of the 2 tests. However, 17 respondents did not perceive sweetness associated with the starch. We also observed that the 6 respondents who detected starch-related sweet taste in both tests had a higher maltose equivalent reducing sugar concentration compared to respondents who could not detect starch-related sweet taste at all (51.52 ± 2.85 and 29.96 ± 15.58 mM, respectively) (Figure 4). Figure 4. View largeDownload slide Level of salivary leptin in first saliva collection (◆ columns) and maltose equivalent reducing sugars in the second saliva collection (● columns) in the starchy chewing gum treatment, categorized by respondents’ groups reporting starch-related sweet taste perception in both, one, or none of two sensory sessions. Different letters (a, b) indicate statistically significant differences (P < 0.05). Figure 4. View largeDownload slide Level of salivary leptin in first saliva collection (◆ columns) and maltose equivalent reducing sugars in the second saliva collection (● columns) in the starchy chewing gum treatment, categorized by respondents’ groups reporting starch-related sweet taste perception in both, one, or none of two sensory sessions. Different letters (a, b) indicate statistically significant differences (P < 0.05). Furthermore, we found that the sAA activity before the chewing process (T1) was positively correlated with the reducing sugar concentrations (r = 0.447, P < 0.05) (Figure 5). When the three groups of respondents were considered separately, the Pearson coefficient correlations were 0.589 (P = 0.219), 0.831 (P = 0.081), and 0.407 (P = 0.105), for both, one only, and none of starch-related sweet taste perception, respectively. In contrast, starch-related sweet taste perception was not significantly related to salivary leptin levels (P > 0.05) (Figure 4) or sAA activity (P > 0.05; Supplementary Figure 3). Lastly, we also found that there was a positive correlation between leptin level test and retest (r = 0.490, P < 0.01). Figure 5. View largeDownload slide Correlation between the mean values of sAA activity at T1 (first saliva collected 5 min after respondents’ arrival) and the salivary maltose equivalent reducing sugars content from the starchy chewing gum group. The overall Pearson coefficient correlation (represented by the thick line) was 0.447 (P < 0.05). When the 3 groups of respondents were considered separately (represented by the 3 thin lines), the Pearson coefficient correlations were 0.589 (P = 0.219), 0.831 (P = 0.081), and 0.407 (P = 0.105), for both, one only, and none of the starch-related sweet taste perception sessions, respectively. Figure 5. View largeDownload slide Correlation between the mean values of sAA activity at T1 (first saliva collected 5 min after respondents’ arrival) and the salivary maltose equivalent reducing sugars content from the starchy chewing gum group. The overall Pearson coefficient correlation (represented by the thick line) was 0.447 (P < 0.05). When the 3 groups of respondents were considered separately (represented by the 3 thin lines), the Pearson coefficient correlations were 0.589 (P = 0.219), 0.831 (P = 0.081), and 0.407 (P = 0.105), for both, one only, and none of the starch-related sweet taste perception sessions, respectively. Putting together all the parameters, the PCA (Figure 6) showed that more than 55% of the variability in starch-related sweet taste parameters was accounted for by the 2 main components (Principal component 1 (PC1) 32.46%; Principal component 2 (PC2) 23.47%). The results showed that respondents who could perceive sweetness from the starch chewing gum (in at least 1 test) tended to cluster together segregating from the non-tasting respondents. The PCA analysis showed that the most relevant parameters to differentiate between tasters and non-tasters were sweet taste ratings and sugar BET. Figure 6. View largeDownload slide PCA of starch-related sweet tasters (■) and non-tasters (○) based on sAA activity, salivary levels of maltose equivalent reducing sugars and leptin, and sugar-sweet thresholds and ratings for sucrose, maltose, and glucose. Figure 6. View largeDownload slide PCA of starch-related sweet tasters (■) and non-tasters (○) based on sAA activity, salivary levels of maltose equivalent reducing sugars and leptin, and sugar-sweet thresholds and ratings for sucrose, maltose, and glucose. Discussion The lower BET (7.42 ± 0.85 mM) for sucrose compared with maltose (15.87 ± 1.53 mM) and glucose (27.64 ± 2.38 mM) confirmed some of the values reported in the literature (Fabian and Blum 1943; Mickel et al. 1976; Mojet et al. 2001; Chang et al. 2006; Newman and Keast 2013; Webb et al. 2015; Joseph et al. 2016) (Figure 2B). However, for maltose, we estimated a lower threshold than the 38 mM observed by Fabian and Blum. The drop method to determine thresholds used in the previous study may have underestimated the sweetness of maltose (Fabian and Blum 1943). The BET method uses a much higher volume than a drop (0.05 vs. 3 mL for drop and current study, respectively), which results in an improved measurement of taste sensitivity (Brosvic and McLaughlin 1989). In addition, it was observed that the taste activity of sucrose, glucose, and maltose were highly correlated (“r” values all above 0.70; P < 0.01) across respondents. Detection thresholds of other taste types such as sweet, salty, sour, and umami have been previously correlated with “r” values of 0.3–0.4 (Webb et al. 2015). Thus, it is tempting to speculate that the high correlations observed in our results may indicate that these 3 tastants share a common perception mechanism (Figure 2B). Indeed, previous publications have shown that sweet compounds interact with the Venus flytrap domain of the sweet taste receptor subunit T1R2 (Servant et al. 2011). Thus, our data seem to confirm in vitro data using T1R2–T1R3 cell expression systems published by others (Nelson et al. 2001; Li et al. 2002). Our data indicated that a 2-min mastication was sufficient to elicit sweet taste in 11 out of 28 respondents. The main sugars and oligosaccharides released from starch after mastication in the oral cavity are maltose and maltotriose (Hoebler et al. 1998). These sugars/oligosaccharides have the potential to elicit starch-related sweet taste in humans (Lapis et al. 2017; Pullicin et al. 2017). In our study, the average level of maltose equivalent reducing sugars in saliva (mainly maltose or maltotriose) was 37 mM, which was above the measured maltose detection threshold value in our respondents (15.87 mM) (Figure 2A). Interestingly, the average concentration of reducing sugars in saliva was significantly higher in respondents tasting starch-related sweetness in both sessions (n = 6) compared to the non-tasting respondents (n = 17) (51.52 ± 2.85 vs. 29.96 ± 15.58 mM, respectively) (Figure 4). In addition, we observed that the mean sweet intensity rating perceived for sucrose and glucose was significantly lower (P < 0.05) for non-tasters than tasters in both sessions: 13.52 ± 2.32, and 11.02 ± 2.14 versus 23.23 ± 3.83, and 23.42 ± 6.29 mM, respectively (data not presented). On another note, it might be relevant to note that 15 of the 17 non-taster respondents had maltose equivalent reducing sugar levels in saliva (after a 2-min mastication of the starchy chewing gum) above the maltose detection threshold value of the overall group (16 mM) but lower than the BET for the non-taster group (24.69 mM). It has been documented that several metabolic hormones such as leptin (Kawai et al. 2000; Shigemura et al. 2004; Nakamura et al. 2008; Han et al. 2017) and/or T1R2 polymorphisms (Han et al. 2017) were associated with changes in taste sensitivity in rats and humans. However, our data on salivary leptin did not correlate with starch-related sweet taste discrimination (Figure 4). Thus, while the current study did not address genetic polymorphisms, these results warrant further investigation on the involvement of potential taste receptor polymorphisms in the variations on starch-related sweet taste perception in humans. On another note, we found that the sAA activity before the chewing process was positively correlated with the release of reducing sugars (r = 0.447, P < 0.05) (Figure 5). In addition, we observed a significant relationship between starch-related sweet taste perception and the amount of maltose equivalent reducing sugars (Figure 4). These data are in line with in vitro findings that sAA contributes to producing sugars and short oligosaccharides from starch (Prinz and de Wijk 2007; Warren et al. 2015; Lapis et al. 2017). In contrast, we could not find a significant direct relationship between starch-related sweet taste perception and sAA activity (Supplementary Figure 3). Importantly, the starch treatment during chewing significantly decreased the sAA activity in the second saliva collection time point compared to the control group (139.19 ± 12.97 vs. 179.35 ± 14.03 U/mL [P < 0.01]) (Figure 3). The data is consistent with previous findings suggesting that after mastication, sAA remained bound to the starch in the food bolus, possibly through the N-terminal of its active site (Butterworth et al. 2011). However, the contribution of sAA in starch digestion, beyond the oral cavity as part of the food bolus contributing to the release of maltose further down the gastrointestinal tract, is minor (Joubert et al. 2017). One of the limitations of our study is the categorical grouping of the respondents into starch-related sweet tasters or non-tasters which could not be balanced “a priori” since it required the results on sweet taste perception. A second limitation should be pointed in the 3-h timespan (9 AM to 12 PM) of the sensory tests, which corresponds to the lowest point in human diurnal variation in both salivary leptin levels (Randeva et al. 2003; Nakamura et al. 2008) and sAA activity (Nater et al. 2007; Out et al. 2013) and to the period of the greatest rate of change in these biomarkers. Thus, 1–3 h difference in the time of day the tests were performed may have caused large variations and potentially mask differences in some of the parameters studied (particularly salivary leptin levels). In addition, other hormones such as GLP-1 or glucagon were not studied which could warrant further investigation (Shin et al. 2008; Elson et al. 2010). Finally, the PCA analysis indicated that subjective ratings (such as BET) are better predictors of starch-related sweet taste sensitivity than the objective measures related to salivary markers (i.e., sAA activity, reducing sugar released or salivary leptin) (Figure 6). This suggests that in addition to the parameters measured, other physiological factors unaccounted for in our study play a significant role in mediating starch-related sweet taste perception in humans. Conclusion This study focuses on the interaction of sAA with starch in the oral cavity, which may contribute to sweet taste perception and thus play a role in the food reward system. Here, using a novel starch delivery system in the form of a chewing gum containing gelatinized/pasted starch, we have shown that 2-min oral mastication was sufficient to produce an oral concentration of maltose above the sweet detection threshold for 11 of 28 respondents. We also observed that the maltose equivalent reducing sugar produced was positively related to sAA activity. The latter may have metabolic implications relevant to the oral release of starch hydrolysis products and the sensing of simple sugars through T1R2/T1R3 dependent or independent sweet perception. Potential involvement of gene polymorphism warrants further investigation. Overall, our results support the idea that in the absence of preexisting glucose, starchy foods can elicit variable sweet taste responses in people, through releasing sugars (mainly maltose) and small glucose oligomers (such as maltotriose) during starch digestion by sAA. Funding This work was supported by the Australia Awards Scholarship to G.K.A. for his MPhil. References ASTM . 2008 . Standard practice for determining odor and taste thresholds by a forced-choice ascending concentration series method of limits, E-679-04 . Conshocken, (PA) : ASTM International . Badman MK , Flier JS . 2005 . The gut and energy balance: visceral allies in the obesity wars . Science . 307 : 1909 – 1914 . Google Scholar Crossref Search ADS PubMed Bartoshuk LM , Duffy VB , Fast K , Green BG , Prutkin J , Snyder DJ . 2003 . 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TI - Salivary α-Amylase Activity and Starch-Related Sweet Taste Perception in Humans
JF - Chemical Senses
DO - 10.1093/chemse/bjz010
DA - 2019-04-15
UR - https://www.deepdyve.com/lp/oxford-university-press/salivary-amylase-activity-and-starch-related-sweet-taste-perception-in-80AZ2Xw3nT
SP - 249
VL - 44
IS - 4
DP - DeepDyve
ER -