Macrowine 2021
IVES 9 IVES Conference Series 9 Optimised extraction and preliminary characterisation of mannoproteins from non-Saccharomyces wine yeasts

Optimised extraction and preliminary characterisation of mannoproteins from non-Saccharomyces wine yeasts

Abstract

The use of non-Saccharomyces yeast species for the improvement of wine technological and oenological properties is a topic that has gained much interest in recent years [1]. Their application as co-starter cultures sequential to the inoculation of Saccharomyces cerevisiae and in aging on the lees has been shown to improve aspects such as protein stability and mouthfeel [2]. These contributions have frequently been associated with higher levels of polysaccharides, specifically the cell wall-derived mannoprotein [3]. Furthermore, mannoprotein structure and composition has been shown to vary between yeast strains, which in turn may influence their behaviour in the wine matrix [4-6]. However, non-Saccharomyces yeasts are typically weak fermentors and are frequently out-competed in the fermentation medium. An alternative strategy to their use as co-starter cultures is the isolation of the compound of interest for exogenous application to wine [7]. Indeed, the addition of exogenous mannoprotein-containing products derived from the cell wall of the wine yeast S. cerevisiae is a fairly common winemaking practice [8]. Nevertheless, the extraction of mannoproteins from non-Saccharomyces yeasts has not yet been well described. AIM: This study aimed to optimise the extraction of mannoproteins from four non-Saccharomyces strains, and to perform a preliminary investigation into the compositional differences of the mannoproteins obtained from the different species.

METHODS: Four non-Saccharomyces wine strains, Saccharomyces cerevisiaeSaccharomyces boulardiiMetschnikowia fructicola and Torulaspora delbrueckii, were exposed to combined methods with varied parameters of ultrasound and enzymatic extraction with β-glucanase to optimise mannoprotein yield. Colorimetric assays were used to quantify protein and carbohydrate concentrations in the extracts.

RESULTS: Yeast cells subjected to 4 min of ultrasound treatment applied at 80% of the maximum amplitude with a 50% duty cycle, followed by an enzymatic treatment of 4000 U lyticase per g dry cells weight, showed the highest yield of mannoproteins from all species. Furthermore, preliminary evaluation of the obtained extracts revealed differences in carbohydrate/protein ratios between species and with increased enzyme incubation time, as demonstrated by the higher ratios obtained for T. Delbrueckii and S. cerevisiae after almost all treatments, in comparison to M. fructicola and S. boulardii.

CONCLUSIONS: The results obtained in this study form an important step towards further characterisation of extraction treatment impact and yeast species effect on the extracted mannoproteins. Their impact on the carbohydrate/protein ratio in particular is an important factor to consider for applications such as wine protein haze reduction and tartrate stabilisation, and requires more in-depth investigation of isolated mannoproteins.

DOI:

Publication date: September 3, 2021

Issue: Macrowine 2021

Type: Article

Authors

Carla Snyman, Benoit DIVOL, Matteo MARANGON, Julie MEKOUE NGUELA, Nathalie SCIECZKOWSKI

South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Private Bag X1, Matieland 7602, South Africa, South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Private Bag X1, Matieland 7602, South Africa, Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale Dell’Università, 16, 35020, Legnaro, Padova, Italy, Lallemand SAS, 19 rue des briquetiers, BP 59, 31702 Blagnac, France, Lallemand SAS, 19 rue des briquetiers, BP 59, 31702 Blagnac, France

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Keywords

mannoprotein; yeast; non-saccharomyces; extraction; wine; ultrasound; β-glucanase

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Macrowine 2021
IVES 9 IVES Conference Series 9 Optimised extraction and preliminary characterisation of mannoproteins from non-Saccharomyces wine yeasts

Optimised extraction and preliminary characterisation of mannoproteins from non-Saccharomyces wine yeasts

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The development of new generations of multispectral satellites such as Sentinel-2 opens possibilities as to vine water status assessment (Cohen et al., 2019). Based on a three years field campaign, a model of Stem Water Potential (SWP) estimation on vine using four satellite bands in Red, Red-Edge, NIR and SWIR domains was developed (Laroche-Pinel et al., 2021). The model relies on SWP field measures done using a pressure chamber (Scholander et al., 1965), which is a common, robust and precise method to assess vine water status (Acevedo-Opazo et al., 2008). The model was mainly developed from from SWP measures on Syrah N (Laroche Pinel E., 2021).

A large scale monitoring was organized in different vineyards in the Mediterranean region in 2021. 10 varieties amongst the most represented in this area were monitored (Cabernet sauvignon N, Chardonnay B, Cinsault N, Grenache N, Merlot N, Mourvèdre N, Sauvignon B, Syrah N, Vermentino B, Viognier B). The model was used to produce water status maps from Sentinel-2 images, starting from the beginning of June (fruit set) up to September (harvest). The average estimated SWP for each vine was compared to actual field SWP measures done by wine growers or technicians during usual monitoring of irrigation programs. The correlations between mean estimated SWP and mean measured SWP were at the same level than expected by the model. (Laroche Pinel, 2021) The general SWP kinetics were comparable. The estimated SWP would have led to same irrigation decisions concerning the date of first irrigation in comparison with measured SWP.

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Cohen, Y., Gogumalla, P., Bahat, I., Netzer, Y., Ben-Gal, A., Lenski, I., … Helman, D. (2019). Can time series of multispectral satellite images be used to estimate stem water potential in vineyards? In Precision agriculture ’19, The Netherlands: Wageningen Academic Publishers, pp. 445–451.
Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837.
Laroche-Pinel,E. (2021). Suivi du statut hydrique de la vigne par télédétection hyper et multispectrale. Thèse INP Toulouse, France.
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