Investigation of the impact of black chokeberry polyphenols in different matrices on the human gut microbiota using the in vitro model of the large intestine (TIM-2)

Abstract

BACKGROUND:

Despite the great range of health-beneficial activities associated with dietary polyphenols, their influence on gut ecology remains poorly understood. Only a few studies have examined the impact of black chokeberry polyphenols present in different matrices on human gut microbiota, and in fact none have examined encapsulated black chokeberry polyphenols.

OBJECTIVE:

The objective of this study was to evaluate the effect of black chokeberry polyphenols in pulp, extract and encapsulate (in a maltodextrin:gum Arabic polymer system) on human gut microbiota and fecal short-chain and branched-chain fatty acids (SCFA and BCFA, respectively).

METHODS:

The effect of black chokeberry polyphenols on gut microbiota was tested in a validated, dynamic in vitro model of the colon (TIM-2) for 24 h by applying five different interventions (Pulp, Extract, Encapsulate, Encapsulate control, SIEM) to the standardized microbiota from five healthy donors.

RESULTS:

We observed that the fermentation of black chokeberry polyphenols in the in vitro colon model resulted in shifts in the standardized microbiota and differentiation in the extent of the production of SCFA and BCFAs. Synergy between maltodextrin+gum Arabic+polyphenols resulted in an increase in the relative abundances of some health-promoting taxa and decrease in the disease related taxa Alistipes. Encapsulation increased the SCFA production and decreased the BCFA production in the lumen.

CONCLUSIONS:

Although encapsulation of polyphenols may provide a robust way for their protection during their transit along the upper gastrointestinal tract, their effect on the gut microbiota should be further investigated both by using different coating materials and with in vivo studies.

Keywords

Colonic fermentation dynamic model short-chain fatty acids branched-chain fatty acids microencapsulation

1 Introduction

Epidemiological studies have suggested that adopting a diet rich in fruits and vegetables has been associated with a reduced risk of noncommunicable diseases, such as cardiovascular diseases, neurodegenerative diseases, type II diabetes and cancer [1]. The presence of bioactive substances such as polyphenols has been linked to these potentially health promoting benefits [2]. However, polyphenols are processed as xenobiotics by the human body after consumption, and hence the bioavailability of native substances is rather low. Only 5–10%of the total dietary polyphenols, mostly those with monomeric and dimeric structures, is estimated to be directly absorbed in the small intestine [3]. The remaining polyphenols pass to the colon, where they are metabolized by the enzymatic activity of colonic bacteria to molecules with varied physiological significance. These phenolics generated by the microbial catabolism are more absorbable than the original molecules present in foods and may have higher health benefits. Additionally, dietary polyphenols reaching the colon can act as prebiotics and they may modulate the gut microbiota by promoting the growth of beneficial bacteria and/or hindering the proliferation of harmful bacteria [4]. In general, decreased level of Firmicutes:Bacteroidetes ratio is believed to be associated with healthier gut [5]. For example, 1000 mg/day pomegranate extract consumption decreased the Firmicutes abundance. Moreover, the abundance of beneficial bacteria Lactobacillus spp. and/or Bifidobacterium spp. was increased with the enocianin and malvidin-3-glucoside [6], flavanols and hydroxycinnamic acids [7, 8], green tea [9], red wine [10].

Among the fruits, black chokeberries (Aronia melanocarpa) are one of the richest plant sources of bioactive polyphenols, especially anthocyanins. A systematic review which meta-analyzed randomized controlled trials demonstrated that black chokeberry intake enhanced vascular function, increased high density lipoprotein (HDL) levels and downregulated oxidative stress markers [11]. However, despite their beneficial nature, their sour and astringent taste limits their consumption in the diet. Therefore, these berries are generally processed into juices, jams, etc., in which they are generally blended with other fruits [12]. However, a considerable amount of polyphenolic compounds still remains in the pulp that is obtained from the juice processing [13, 14] and this pulp can thus be considered as a good candidate for by-product valorization.

The objective of the present study was to investigate the effect of black chokeberry polyphenols on the human gut microbiota in a sophisticated, computer-controlled dynamic colonic fermentation model. TIM-2 is a validated in vitro model that simulates the human proximal large intestine with human-origin microbiota and it allows determination of the polyphenolic metabolites generated as a result of gut microbial catabolism as well as determining the modulation in the gut microbiome composition [15, 16]. Therefore, we hypothesized that gut microbiota composition and gut SCFA and BCFA levels would be differently affected when the black chokeberry polyphenols were administered into the system in different matrices. For this purpose, black chokeberry pulp (BCP), anthocyanin-rich extract obtained from black chokeberry pulp (BCE), and an encapsulate of the extract in maltodextrin-gum Arabic system (BCEn) were examined in terms of their differential effects on above-mentioned parameters. Although there are a few studies examining the interaction of black chokeberry polyphenols and human gut microbiota in dynamic in vitro colonic systems [17, 18], only black chokeberry juice was used as the polyphenol source in these studies. Therefore, to have a better understanding on the interactions between black chokeberry polyphenols and the gut microbiota, the effect of black chokeberry polyphenols in different matrices (pulp, extract and microencapsulated extract) on human gut microbiota was examined by using a validated, in vitro large intestinal model using a standardized microbiota.

2 Materials and methods

2.1 Plant material and sample preparation

Black chokeberries (grown in Demirkoy, Kirklareli, Türkiye and harvested at the end of August 2018, at ripened stage) were supplied from Balkan Orman ve Tarim Urunleri Industry and Trade Ltd. Co. (Istanbul, Turkey). Gum Arabic (Senegal) and Maltodextrin (dextrose equivalent 18–20) were kindly donated by Aromsa Industry and Trade Inc. (Istanbul, Turkey) and Cargill Inc. (Istanbul, Turkey), respectively. Sample preparation, extraction of polyphenols and microencapsulation by spray drying were carried out as described in a previous study [19]. Briefly, BCP was obtained after processing the berries into juice in a home type juicer (Tefal Frutelia Plus Juicer). Then, the polyphenols were extracted by mixing 1 : 5 (w/v) BCP and 75%(v/v) aqueous ethanol containing 0.1%(v/v) HCOOH and sonicating the mixture for 15 min in a cooled ultrasonic water bath. Subsequently, the extracted polyphenols were separated by centrifuging the ultrasonicated mixture for 10 min at 4 °C and 2700 g. The supernatant was transferred to a volumetric flask and the pellet was extracted one more time with the same procedure. Both of the collected supernatants were pooled and completed to 10 mL with 75%aqueous ethanol [20]. Finally, black chokeberry extract was concentrated in a rotary evaporator at 40 °C under vacuum to obtain concentrated black chokeberry extract which was kept at in –80 °C until further processing.

Microencapsulation was achieved by coating the BCE polyphenols with a polymer (MDGA) consisting of MD (maltodextrin) and GA (gum Arabic) in a ratio of 3 : 1 (w/w). Firstly, BCE stock solution (25 %in 10 mM acetate buffer, pH 3.5±0.1) and MDGA stock solution (40 %in 10 mM acetate buffer, pH 3.5±0.1) were mixed in a ratio of 1 : 1 (v/v) to obtain a feed solution with a final dry matter content of 21 %. This was homogenized by a magnetic stirrer for one hour [21]. After that, the homogenized feed solution was pumped into the spray drier (Mini Spray Dryer B-290, BÜCHI Labortechnik AG, Switzerland) with a feed flow rate of 4.5 mL/min, air flow rate of 357 L/h, inlet temperature of 150 °C, outlet temperature of 90 °C, and an aspirator capacity of 100 %. A feed solution prepared by replacing BCE solution with sodium acetate buffer solution at the same volume was used as control treatment (EnC). The microencapsulated samples (further denoted as encapsulate) were collected, transferred into a zipper storage bag and kept at 4 °C until further use.

2.2 Collection and processing of stool samples for standardized microbiota preparation

Fresh stool samples were donated by five healthy individuals (3 males and 2 females, 26–53 years old) who declared that they did not have any gastrointestinal disorders or did not use any antibiotics at least three months prior to donation. The volunteers placed the fresh fecal samples in a gastight bag containing an anaerobic strip (AnaeroGen^™, Cambridge, UK) and put it in a plastic box with a tight lid. The samples were transported to the laboratory within 2 hours and kept at 4°C until they were transferred to the anaerobic chamber (Sheldon Lab –Bactron IV, Cornelius, OR, USA) for standardization. The standardized microbiota stock was prepared as described by Aguirre et al. [22]. Briefly, approximately equal portion of feces from the participating individuals was weighed and mixed with equal volume of pre-reduced dialysate (2.5 g/L K₂HPO₄·3H₂O, 4.5 g/L NaCl, 0.005 g/L FeSO₄·7H₂O, 0.5 g/L MgSO₄·H₂O, 0.45 g/L CaCl₂·2H₂O, 0.05 g/L ox bile, 0.4 g/L cysteine·HCl; pH was adjusted to 5.8) with 1 mL of vitamin mixture (1 mg/L menadion, 2 mg/L D-biotin, 0.5 mg/L vitamin B12, 10 mg/L pantothenate, 5 mg/L nicotinamide, 5 mg/L p-aminobenzoic acid and 4 mg/L thiamin). After adding 15 %glycerol (w/w) as a cryoprotectant agent, a total of 500 g of fecal slurry was obtained. It was portioned (35 mL) into sterile centrifuge tubes, snap-frozen in liquid nitrogen and kept at –80°C until further use.

2.3 Simulated ileal efflux medium (SIEM)

A standard growth medium, in other words simulated ileal efflux medium (SIEM), was used for feeding the microbiota during the analysis. This media mimics the components that reach the colon from the terminal ileum through the ileocecal valve and it comprises some undigested complex carbohydrates, some protein, some residual bile, and some minerals and vitamins. The recipe of SIEM is as follows [23]: 100 g carbohydrate medium (12 g/L citrus pectin, 12 g/L xylan, 12 g/L arabinogalactan, 12 g/L amylopectin, 100 g/L starch), 25 g TBCO mixture [6.25-fold concentrated] (270 g/L Tween80, 375 g/L Bactopepton, 375 g/L Casein, 6.25 g/L Ox bile), 2 g MgSO₄ (50 g/L), 2 g cysteine (20 g/L), 0.2 mL vitamin mixture (as given above), 4 mL salts solution (4.7 g/L K₂HPO₄·3H₂O, 8.4 g/L NaCl, 0.8 g CaCl₂·2H₂O, 0.009 g/L FeSO₄·7H₂O, 0.02 g/L haemin) and antifoam B emulsion (Sigma-Aldrich, Munich, Germany). The pH was adjusted to 5.8.

2.4 Experimental procedure for the in vitro colonic fermentation in TIM-2

TIM-2 (Fig. 1) has been described in detail before [24]. The systems consist of 4 identical units that can be run in parallel. The system was turned into anaerobic state by flushing for 3 hours with a continuous gaseous N₂ stream. Before being inoculated into the system, the frozen fecal suspension was thawed in a water bath at 37°C for one hour. Afterwards, it was diluted with pre-reduced dialysate in a ratio of 1 : 1 (v/v) in the anaerobic chamber, transferred into a sterile plastic syringe and used as a standardized inoculum for each individual TIM-2 unit. The standardized microbiota was allowed to adapt for 16 hours. At the end of the adaptation period, T₀ samples of lumen and dialysate were collected from each unit. Then a 24-hour experimental period was initiated by connecting the feeding syringes of each intervention to the system along with injecting the samples into sampling port of lumen as single shots. The interventions with or without chokeberry polyphenols were as follows: i) SIEM, ii) Extract (BCE), iii) Pulp (BCP), iv) Encapsulate (BCEn), v) Encapsulate-control without BCE (EnC). Except for the experiment with SIEM, the feeding syringes of each intervention contained the recipe of SIEM, but without carbohydrates, mixed with BCE, BCP, BCEn or EnC. The single-shot injection samples were prepared by mixing each sample with 25 mL pre-reduced dialysate. The dose of polyphenols that administered into the system was set as 300 mg cyanidin-3-glucoside equivalent of total anthocyanins in each intervention since the anthocyanins were the abundant polyphenols in black chokeberries [19]. The total anthocyanin content of BCE, BCP and BCEn was 491±29.7 mg cya-3-glu per 100 mL, 313±19.0 mg cya-3-glu per 100 g dry matter and 296±2.52 mg cya-3-glu per 100 g powder, respectively. All the experiments were conducted in duplicate on different days, and in different compartments. At the end of the 24-hour experimental period, T₂₄ samples from lumen and dialysate were collected (Fig. 1). Both T₀ and T₂₄ samples were immediately snap-frozen in liquid nitrogen and stored at –80°C until further analyses.

Fig. 1

Schematic of TIM-2 and experimental procedure for the in vitro colonic fermentation.

2.5 Analytical procedures

BCFAs (iso-butyrate and iso-valerate), and SCFAs (acetate, propionate and butyrate) and lactate were measured as previously described [25]. External calibration curves prepared from the standards of the related compounds were used in the quantification of these compounds.

2.6 DNA isolation and PCR amplification of the 16 S rRNA gene V3-V4 region

Genomic DNA from the luminal samples was extracted using a QIAmp^® DNA Mini Kit (QIAGEN, Venlo, the Netherlands) following the manufacturer’s instructions. The sequencing and sequence conversion into FASTQ files were carried out by using Illumina MiSeq and BCL2FASTQ pipeline version 1.8.3. (both Illumina, Eindhoven, The Netherlands), respectively [23]. The QIIME2 (Quantitative Insights Into Microbial Ecology) software package was employed for taking sequencing data from raw sequences to interpretation for the microbiota analyses [26]. Classification of the sequences into amplicon sequence variants (ASVs) was performed using the Silva database (version 132 (available online: https://www.arb-silva.de/documentation/release-132/ accessed on 27 October 2021)) as a reference 16 S rRNA database.

2.7 Statistical analyses

The software package R (version 4.1.3, R Foundation for Statistical Computing, Vienna, Austria (R Core Team, 2013; https://cran.r-project.org/bin/windows/base/old/4.1.3; accessed on 27 October 2021)) was used for statistical analyses in RStudio. To determine changes in the microbial community composition, various indexes were calculated and the abundances of microbial species in the total microbial community were calculated and shown as relative abundance (RA). Kruskal–Wallis analysis was performed to determine differences in species abundance between the treatment conditions. The correlation of RA of ASVs and microbial metabolites were calculated with Spearman’s correlation. Adjustment for multiple comparisons was done with the Benjamini–Hochberg false discovery rate, and q-values (FDR-corrected p-values) were considered significant at q < 0.25.

3 Results and discussion

The validated, dynamic in vitro model of the colon, TIM-2, has been used for numerous studies when investigating the changes of microbiota composition and activity after dietary interventions, including for polyphenols [15 , 28]. The unique dialysis system of the model ensures a highly active microbiota of physiological density in the proximal colon. To study the effect of intake of back chokeberry polyphenols, a 24-hour experiment was performed and changes in microbiota composition and activity were analyzed.

3.1 Alpha- and beta-diversity

After the adaptation period (Fig. 1), all T₀ samples clustered together, as expected, because a standardized microbiota was used. Figure 2 show the beta-diversity in a principal coordinate analysis (PCoA) plot of Bray-Curtis dissimilarity.

Fig. 2

Beta-diversity of the samples, PCoA plot of Bray-Curtis dissimilarity. Rings: time point T₀; spheres: time point T₂₄; red: BCEn; blue: EnC; green: BCP; orange: BCE, purple: SIEM.

Figure 2 also shows that the different intervention led to differences in the beta-diversity, with samples containing BCEn and EnC separated from the other samples, and also a small separation between the SIEM and BCP and BCE. It seems that the MD and GA in the encapsulates led to some shifts in the microbiota in addition to the polyphenols. The overall separation between groups at T₂₄ is significant when tested by PERMANOVA (p = 0.02), but no longer significant in pairwise comparisons, due to the small sample size. Only for the alpha-diversity metric evenness there was a difference between interventions at T₂₄ (Fig. 3). Shannon-diversity, Faith’s phylogenetic diversity and number of ASVs observed were not significantly different.

Fig. 3

Kruskal-Wallis analysis of differences in evenness of the samples at time point T₂₄. BCEn vs. EnC; BCEn vs. BCP; EnC vs. BCE; EnC vs. SIEM; BCE vs. BCP; BCP vs. SIEM, q = 0.20.

3.2 Shifts in microbiota composition

Most experiments were performed using TIM-2 feed the dietary components over a 3-day period. This allows for the observation of changes in the gut microbiota composition, since in that time-frame part of the content of the model is removed simulating passage of stool. Here, the major goal was to study metabolism of the polyphenols from black chokeberries (data not shown). It was also studied whether there were any changes in the microbiota composition induced by the polyphenols. Several taxa were shown to be modulated using the Kruskal-Wallis method. Since the starting microbiota at time point T₀ was very similar (see the clustering in the PCoA plot in Fig. 2), the differences in microbiota composition at time point 24 were investigated. Figure 4 illustrates the percentage relative abundances of the taxa at T₂₄ at genus level. Bifidobacteria are one of the most prevalent groups of known health-promoting or probiotic microorganisms, and several bifidobacterial species are often employed as a probiotic ingredient in many functional food formulations [29]. In this study, the increase in the relative abundance of Bifidobacterium was promoted by EnC treatment in which only the blend of MD and GA was administered to the system. In other studies, fermentation of GA by the human gut microbiota in both batch culture model [30] and randomized, double-blinded, double-controlled human trial [31] also resulted in an increase in the abundance of the Bifidobacterium spp. Additionally, the methane-producing microorganism Methanobrevibacter was also increased by the EnC and BCE. However, interestingly, the combination of MDGA and polyphenols (BCEn) reduced the relative abundance of this genus. On the other hand, MDGA and polyphenols had synergistic effect on some other genera, such as Dorea, Blautia, Collinsella, Faecalibacterium, Christensenellaceae R7 group, Anaerostipes and Prevotella 9. Among these, Dorea is associated with increased intestinal permeability [32], food sensitization and food allergy [33], colorectal cancer [34], and irritable bowel syndrome [35]. Blautia is a genus of bacteria in the Lachnospiraceae family which is a prominent taxonomic category of the human gut microbiota, where they breakdown complex polysaccharides to SCFAs such as acetate, butyrate, and propionate, that can be used by the host for energy [36]. Faecalibacterium and Anaerostipes are also butyrate producers and considered as one of the most common species in the gut microbiome of healthy individuals [37, 38]. Collinsella is regarded as a pro-inflammatory genus which previously linked to total cholesterol [39], obesity [40] and atheroschlerosis [41]. The family Christensenellaceae has been connected to leanness with a negative correlation of visceral fat mass [42]. Prevotella is known for its capability to digest complex carbohydrates and mostly associated with a diet rich in vegetables [43]. It is also noteworthy to mention that Prevotella 7 and Prevotella 9 were almost affected inversely by the five different interventions. Besides, BCEn or EnC showed an antagonistic effect on the relative abundance of Lachnospiraceae D5_uncultured, which is an uncharacterized taxon of Lachnospiraceae, and Ruminococcaceae NK4A214 group, which positively correlate with quinone and quinol metabolism, glycolysis, sulfur metabolism and peptidoglycan biosynthesis, while BCE and BCP promoted the increase of relative abundance of these bacteria. A similar trend was also observed for Ruminococcaceae UCG 002, Ruminococcaceae UCG 010 and Ruminococcaceae UCG 013. Slackia was determined as a genus specifically modulated by extract, as only the BCE intervention increased its relative abundance. This genus is known for its isoflavone metabolizing capability (e.g. daidzein and genistein are converted into equol and 5-hydroxy-equol, respectively) [44, 45]. Also, the growth of Akkermansia, a health beneficial genus and an indicator of healthy gut [46, 47], was induced when the system was fed with BCEn, EnC or BCE whereas the growth of Alistipes, a gut bacteria highly relevant in disease and dysbiosis, was limited with the application of BCEn and EnC. Similar results were also reported by Liu et al. [48] where they assessed the effect of black chokeberry polyphenols from berry extract, whole berry and extractable polyphenol depleted berries in a mouse model. The relative abundance of Lachnospiraceae was remarkably high in the following order: whole berry > extractable polyphenol depleted berries > berry extract. Ruminococcaceae was found in whole berries and polyphenol depleted berries interventions whereas Blautia was abundantly found after extract supplementation. In another study, black chokeberry juice treatment in the SHIME^® model (Simulator of Human Intestinal Microbial Ecosystem) led to an increase in the Lachnospiraceae and Ruminococcaceae genera [17]. Furthermore, supplementing anthocyanin rich black chokeberry extract or grape pomace resulted in an increase in the dominance of Akkermansia and Prevotella [49, 50], whereas blueberry extract caused a decrease in Prevotella and an increase in Bifidobacterium [51] in in vivo mice studies.

Fig. 4

Boxplots of relative abundances (%) of the taxa shown to be modulated by different treatments. The boxplots in each graph represent BCEn, EnC, BCE, BCP and SIEM from left to right, respectively.

3.3 Production of short-chain and branched-chain fatty acids

SCFA content was differentially affected by the different black chokeberry polyphenol interventions. SCFA production was highest for the interventions with the encapsulates (BCEn and EnC), due to the presence of the MD and GA (Fig. 5). For the pulp, the amount (Fig. 5) and ratio of the individual SCFA (ratio acetate:propionate:butyrate = 47 : 26 : 27) was very similar to SIEM (acetate:propionate:butyrate = 41 : 31 : 28). For the BCE it was slightly lower, with a higher ratio of acetate and a lower ratio of butyrate (acetate:propionate:butyrate = 53 : 26 : 20). The encapsulates led to highest acetate ratio for the EnC, lowest propionate ratio and highest butyrate for the BCEn (acetate:propionate:butyrate = 49 : 20 : 32, and 67 : 8:25, respectively for encapsulates with and without chokeberry extract). Compared to SIEM, the acetate content was increased in EnC 2.8-fold and in BCEn 1.7-fold, which was most likely depending on the MD and GA. According to Gerasimidis et al. [52], MD led to a significant increase in total SCFA, acetate, caproate and propionate in a batch culture of human feces. Acetate has the lowest acid logarithmic dissociation constant (pKa) of the three primary SCFAs, thus a larger concentration of acetate is expected to give a higher suppression of pathogenic bacteria [25].

Fig. 5

Cumulative SCFA production due to the different interventions. Production was artificially set to zero at time point zero.

Apart from the major SCFA, valerate and caproate and the BCFAs iso-butyrate and iso-valerate, the latter stemming from fermentation of the branched-chain amino acids were also measured. In the interventions where the encapsulate with chokeberry extract was present, the production of these fatty acids was negative, possibly indicating that molecules that were present at the moment of addition of the BCEn were incorporated by the bacteria into biomass, rather than that they accumulated and were dialyzed out of the lumen (Fig. 6). Also, MD may have an adverse effect on the BCFA production which was also previously shown by Gerasimidis et al. [52]. According to their study, valerate and iso-valerate concentrations were negatively affected by the MD treatment. On the other hand, the production of valerate was negative in BCE while it was positive and closer to the SIEM and BCP. The higher valerate content might be linked to the fiber content of BCP and potential negative effect of the polyphenols or other compounds present in black chokeberries.

Fig. 6

Cumulative BCFA and valerate and caproate production due to the different interventions. Production was artificially set to zero at time point zero.

None of the measured metabolites correlated with one of the interventions of with the different taxa. Since there is enormous functional overlap in the microbiota with respect to functional capacity, this may not be surprising, although it is unknown which taxa are capable of metabolizing the polyphenols.

4 Conclusions

The results of this work revealed that the fermentation of black chokeberry polyphenols in the in vitro colon model (TIM-2) resulted in shifts of the standardized microbiota obtained from five healthy individuals. Based on the beta-diversity, all T₀ samples clustered together in the PCoA chart showing that the microbiota was standardized and initial conditions for all treatments were the same. The relative abundance of some genera in T₂₄ samples was differentially affected by the different treatments. Relative abundances of some beneficial microbes namely, Anaerostipes, Blautia, Christensenellaceae R7 group, Prevotella 9 were increased as a result of synergism of MDGA+polyphenols. Furthermore, encapsulation also led to increase of beneficial taxa or limited the growth of disease related taxa (decreased relative abundance in Alistipes). Also, BCP and/or BCE promoted the relative abundances of some beneficial bacteria (Akkermensia, Lachnospiraceae, Ruminococcaceae, and Slackia). Metabolically, the acetate levels significantly increased depending on the presence of MDGA in the fermentation media. Moreover, BCFA content, considered a marker for protein fermentation that is believed to lead to production of detrimental metabolites, was decreased by the encapsulation process. Nevertheless, none of the metabolites could be correlated with the identified operational taxonomic units.

To conclude, although encapsulation of polyphenols may provide a robust way for their protection during upper gastrointestinal transit, their effect on the gut microbiota should be further investigated both by using different coating materials and with in vivo studies.

Footnotes

Acknowledgments

The authors would like to thank Jessica Verhooven, Rob van Dinter and Evy Maas for their assistance in this study.

Funding

This research was supported by the Council of Higher Education of Türkiye with YÖK-YUDAB Scholarship and the Scientific Research Projects (BAP) Unit of Istanbul Technical University (Project IDs: 41928 and 43993). The study was also partly funded by the Centre for Healthy Eating & Food Innovation (HEFI) of Maastricht University –campus Venlo, the Netherlands. This research has been made possible with the support of the Dutch Province of Limburg with a grant to HEFI.

Conflict of interest

Esra Capanoglu is an Editorial Board Member of this journal, but was not involved in the peer-review process nor had access to any information regarding its peer-review.

CRediT author contribution statement

Gizem Catalkaya: Conceptualization, Resources, Investigation, Writing-original draft; Esra Capanoglu: Conceptualization, Supervision, Writing –review & editing; Koen Venema: Methodology, Resources, Formal analysis, Visualization, Writing –original draft.

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