Identification, Quantification, and Sensory Characterization of Steviol Glycosides from Differently Processed <i>Stevia rebaudiana</i> Commercial Extracts

Espinoza, María Inés; Vincken, Jean‐Paul; Sanders, Mark; Castro, C. C.; Stieger, Markus; Agosín, Eduardo

doi:10.1021/jf502878k

Cited by 49 publications

(35 citation statements)

References 30 publications

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“…More than 35 different steviol glycosides have been identified in S. rebaudiana [5, 12]. In S. rebaudiana, the glucosylation reactions are catalyzed by the action of four UDPG-dependent glucosyltransferases (UGTs): UGT85C2 glucosylates the steviol backbone at the C 13 -hydroxyl position forming a β- d -glucoside whereas UGT74G1 glucosylates the C 19 -carboxylic acid functional group giving rise to the formation of an ester (Fig.…”

Section: Introductionmentioning

confidence: 99%

Microbial production of next-generation stevia sweeteners

et al. 2016

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BackgroundThe glucosyltransferase UGT76G1 from Stevia rebaudiana is a chameleon enzyme in the targeted biosynthesis of the next-generation premium stevia sweeteners, rebaudioside D (Reb D) and rebaudioside M (Reb M). These steviol glucosides carry five and six glucose units, respectively, and have low sweetness thresholds, high maximum sweet intensities and exhibit a greatly reduced lingering bitter taste compared to stevioside and rebaudioside A, the most abundant steviol glucosides in the leaves of Stevia rebaudiana.ResultsIn the metabolic glycosylation grid leading to production of Reb D and Reb M, UGT76G1 was found to catalyze eight different reactions all involving 1,3-glucosylation of steviol C 13- and C 19-bound glucoses. Four of these reactions lead to Reb D and Reb M while the other four result in formation of side-products unwanted for production. In this work, side-product formation was reduced by targeted optimization of UGT76G1 towards 1,3 glucosylation of steviol glucosides that are already 1,2-diglucosylated. The optimization of UGT76G1 was based on homology modelling, which enabled identification of key target amino acids present in the substrate-binding pocket. These residues were then subjected to site-saturation mutagenesis and a mutant library containing a total of 1748 UGT76G1 variants was screened for increased accumulation of Reb D or M, as well as for decreased accumulation of side-products. This screen was performed in a Saccharomyces cerevisiae strain expressing all enzymes in the rebaudioside biosynthesis pathway except for UGT76G1.ConclusionsScreening of the mutant library identified mutations with positive impact on the accumulation of Reb D and Reb M. The effect of the introduced mutations on other reactions in the metabolic grid was characterized. This screen made it possible to identify variants, such as UGT76G1Thr146Gly and UGT76G1His155Leu, which diminished accumulation of unwanted side-products and gave increased specific accumulation of the desired Reb D or Reb M sweeteners. This improvement in a key enzyme of the Stevia sweetener biosynthesis pathway represents a significant step towards the commercial production of next-generation stevia sweeteners.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-016-0609-1) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Microbial production of next-generation stevia sweeteners

et al. 2016

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“…The full-length transcriptome dataset may also provide useful candidate genes for the elucidation of the mechanism of steviol glucosides biosynthesis. In S. rebaudiana, more than thirty-five steviol glycosides have been successfully identified [4,5]. Of these glycosides, the standards of steviolbioside, Reb B, ST, Reb F, Reb A, Reb D and Reb M were easy to purchase; furthermore, their concentrations were relatively higher than those of other glycosides.…”

Section: Resultsmentioning

confidence: 99%

“…After analysis, a total of six SSR types can be detected, including mononucleotide, dinucleotide, trinucleotide, tetranucleotide, pentanucleotide, and hexanucleotide SSRs. In addition, the repeat times were divided into 5,6,7,8,9,10,11, and > 11 times.…”

Section: Simple Sequence Repeat (Ssr) Analysismentioning

confidence: 99%

Characterizing glycosyltransferases by a combination of sequencing platforms applied to the leaf tissues of Stevia rebaudian

Zhang

Liu

Lyu

et al. 2020

Preprint

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Background: Stevia rebaudiana (Bertoni) is considered one of the most valuable plants because of the steviol glycosides (SGs) that can be extracted from its leaves. Glycosyltransferases (GTs), which can transfer sugar moieties from activated sugar donors onto saccharide and nonsaccharide acceptors, are widely distributed in the genome of S. rebaudiana and play important roles in the synthesis of steviol glycosides.Results: Six stevia genotypes with significantly different concentrations of SGs were obtained by induction through various mutagenic methods, and the contents of seven glycosides (stevioboside, Reb B, ST, Reb A, Reb F, Reb D and Reb M) in their leaves were considerably different. Then, NGS and single-molecule real-time (SMRT) sequencing were combined to analyse leaf tissue from these six different genotypes to generate a more complete and correct full-length transcriptome of S. rebaudiana. Two phylogenetic trees of glycosyltransferases (SrUGTs) were constructed by the neighbour-joining method and successfully predicted the functions of SrUGTs involved in SG biosynthesis. With further insight into glycosyltransferases (SrUGTs) involved in SG biosynthesis, the weighted gene co-expression network analysis (WGCNA) method was used to characterize the relationships between SrUGTs and SGs, and forty-four potential SrUGTs were finally obtained. Of these potential SrUGTs, twenty-seven have complete ORFs and have not been verified to date, and enzyme assays were subsequently performed, but none of them had activity towards SGs. In addition, SrUGT (SrUGT88B1-1) could utilize UDP-glucose as a sugar donor to glycosylate isoquercetin to form three products containing one, two, and three glucoses, respectively. Conclusion:Combined with the results obtained by previous studies and those of this work, we systematically characterized glycosyltransferases in S. rebaudiana and confirmed that four enzymes (SrUGT85C2, SrUGT74G1, SrUGT76G1 and SrUGT91D2) are primarily involved in the glycosylation of steviol glucosides. Moreover, the complete and correct full-length transcriptome obtained in this study will provide valuable support for further research investigating S. rebaudiana.(S. rebaudiana and S. phlebophylla) in this genus to produce steviol glycosides (SGs), compounds that appeal to people looking for more natural plant-based ingredients in their diet because of their natural-origin, plant-based and zero-calorie sustainable sweeteners [1,2]. Indeed, finding nonnutritive sweeteners to reduce sugar intake is one valuable path to solve some serious health problems at present, especially for those with obesity or diabetes. Therefore, making stevia a leaf crop with significant economic value and the food industry has a very positive outlook regarding the opportunities for SGs. Consequently, the value of the SG market is expected to exceed $1 billion USD by 2021 [3]. To date, more than thirty-five SGs have been isolated and identified from S. rebaudiana, including steviolbioside, rebaudioside A-Q (Reb A-Q), 1,2-stevioside (...

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“…FCM has been used during training and calibration of sensory panels in a wide range of products (Acevedo et al, 2018;Bavay et al, 2013;Chang & Dando, 2018;Espinoza et al, 2014;Fisher, King, Castura, & Findlay, 2016;Mahan, Morrow, & Hayes, 2011;Martin et al, 2016;Obst et al, 2013;Pietrasik, Wang, & Janz, 2013;Richards, De Kock, & Buys, 2014). However, only papers by the developers of the method have investigated the implications of using FCM.…”

Section: Introduction To the Feedback Calibration Methodsmentioning

confidence: 99%

Performance of beer sensory panels: A comparison of experience level, product knowledge, and responsiveness to feedback calibration

Elgaard

Jensen²,

Mielby

et al. 2019

Journal of Sensory Studies

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This study investigated the effect of level of sensory experience and type of product knowledge on panel performance during a descriptive analysis. Additionally, the applicability of the feedback calibration method (FCM) was investigated for use with different types of panels. A well‐established expert panel (professional product specific knowledge) was compared to (a) a newly trained product‐specific panel (interest based product specific knowledge) and (b) a well‐established general panel (general product knowledge). Results showed that the overall product sensory profiles generated by the three panels were similar. However, analysis of the panels' repeatability, discriminability, attribute understanding, and use of scale displayed that the product‐specific panel performed more similar to the professional beer panel and was therefore superior compared to the general panel. The applicability of FCM was most effective for the newly trained panel, compared to the more extensively trained panel. Practical applications Sensory descriptive analysis is one of the basic tools in the field of sensory science. However, recent focus in research has been to investigate faster and more cost‐efficient methods, resulting in a decrease in research on the methodology of classical sensory descriptive analysis. The methodology of descriptive analysis still has many unanswered questions regarding panel selection and training. The results of the current study indicate that product specificity is more important than sensory experience when studying complex foods like beer. More attention should therefore be applied to type of panel, when conducting descriptive analysis of complex products. Furthermore, the results show that the feedback calibration method (FCM) is more advantageous for training of panels with less sensory experience, though beneficial for all types of panels. The general guideline is therefore to include FCM as part of the training procedure for all type of panels.

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Identification, Quantification, and Sensory Characterization of Steviol Glycosides from Differently Processed Stevia rebaudiana Commercial Extracts

Cited by 49 publications

References 30 publications

Microbial production of next-generation stevia sweeteners

Microbial production of next-generation stevia sweeteners

Characterizing glycosyltransferases by a combination of sequencing platforms applied to the leaf tissues of Stevia rebaudian

Performance of beer sensory panels: A comparison of experience level, product knowledge, and responsiveness to feedback calibration

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