Chun Tang Feng MS Thes˝Is

Home , Candida zemplinina, Dothioraceae, Grignolino, Pennsylvania wine, Pichia membranifaciens, Saccharomyces uvarum

The Pennsylvania State University

The Graduate School

MICROBIAL AND CHEMICAL ANALYSIS OF WILD YEASTS FROM

CHAMBOURCIN HYBRID GRAPES FOR POTENTIAL USE IN WINEMAKING

A Thesis in

Food Science

Chun Tang Feng

Ó 2020 Chun Tang Feng

Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Science

December 2020

ii The thesis of Chun Tang Feng was reviewed and approved by the following:

Josephine Wee Assistant Professor of Food Science Thesis Advisor

Edward G. Dudley Professor of Food Science

Ryan J. Elias Professor of Food Science

Robert F. Roberts Professor of Food Science Head of the Department of Food Science

iii

ABSTRACT

Native microbial populations present on grape berries in the vineyard and in winery environments can influence final wine quality. Previous studies on wild yeasts isolated from Vitis vinifera grapes have been reported to enhance wine flavor complexity. Although commercial Saccharomyces cerevisiae has been historically used for winemaking due to its efficiency and reliability in alcoholic fermentation, the role of other fungal populations on fermentation and physicochemical properties of final wines are not well characterized.

Chambourcin, a French-American hybrid grape, is the most abundant hybrid grape variety grown in Pennsylvania and is relatively more resistant to cold temperatures and fungal diseases compared to Vitis vinifera grapes. In this study, we isolated and identified wild yeasts from three regional wineries that grow and produce Chambourcin to explore their potential to enhance complexity of final wines. We selected five candidate yeasts,

Hanseniaspora uvarum NV192410, H. opuntiae NV192404, Pichia kluyveri NV192402,

P. kudriavzevii SM192402 and Aureobasidium pullulans SM190002 and characterized their ability to tolerate varying concentrations of sulfite (0~100mg/L sodium metabisulfite, pH=3) and ethanol (0~12%v/v). We further developed a laboratory scale fermentation system that allowed analysis of non-volatile and volatile compounds derived from inoculated fermentations using candidate wild yeasts using Ultra High-Performance Liquid

Chromatography and Gas Chromatography Mass Spectrometry.

One hundred and twenty yeast isolates were obtained from three regional vineyards which comprised of 29 unique yeast species. Two wild yeast strains H. opuntiae NV192404 and P. kudriavzevii SM192402 demonstrate tolerance when grown in 8-10 % ethanol and

iv are able to convert sugars to ethanol at a level comparable with control strain S. cerevisiae

BY4742 (0.5 g ethanol/g sugar). Concentration of wine important non-volatile compounds were conserved among wild yeasts. Of interest in winemaking, H. opuntiae NV192404 was positively correlated to acetoin and linalool (pleasant buttery and flowery odor) and P. kudriavzevii SM192402 had positive correlation with 1-butoxy-1-ethoxyethane and ethyl

2-hexenoate (fruity aroma).

In summary, microbial and chemical analysis of candidate wild yeasts can play a role in fermentation and in wine flavor complexity. Future work will focus on sensory and consumer studies to determine whether the differences of wine flavor can be detected and appreciated.

TABLE OF CONTENTS

LIST OF FIGURES ...... vii

LIST OF TABLES ...... x

ACKNOWLEDGEMENTS ...... xi

Chapter 1

1.1. Statement of Issue ...... 1 1.2. Non-Saccharomyces yeasts on grapes ...... 4 1.3. Characterization of important yeast physiological properties related to winemaking ...... 9 1.4. Core non-volatile and volatile metabolites as the indicators of wine flavor ...... 13

Chapter 2

2.1. Significance ...... 18 2.2. Hypothesis and Objectives ...... 21 2.3. Important considerations to experimental design ...... 22 2.3.1. Combination of early stage fermentation and addition of sulfite are two important aspects to capturing diverse wild yeasts populations ..... 22 2.3.2. Development of a laboratory scale fermentation using sterile Chambourcin juice inoculated with candidate yeast strains for wine chemical profile analysis ...... 26

Chapter 3

3.1. Introduction ...... 30 3.2. Materials and Methods ...... 34 3.2.1. Grape sampling and juice collection ...... 34 3.2.2. Growth media and fungal isolation ...... 35 3.2.3. Molecular identification of fungal isolates ...... 37 3.2.4. Physiological characterization of non-Saccharomyces yeasts ...... 39 3.2.4.1. Tolerance assays ...... 39 3.2.4.2. Laboratory scale fermentation ...... 40

vi 3.2.5. Analysis of flavor compounds of fermented Chambourcin juice ...... 42 3.2.5.1. Optimization of Ultra High-Performance Liquid Chromatography (UHPLC) protocol ...... 42 3.2.5.2. Analysis of non-volatile compounds by UHPLC ...... 44 3.2.5.3. Analysis of volatile compounds by Gas Chromatography Mass Spectrometry ...... 46 3.2.6. Statistical Analysis ...... 48 3.3. Results ...... 48 3.3.1. Isolation and identification of fungal diversity on spontaneous fermentation of Chambourcin grape must ...... 48 3.3.2. Physiological characterization of non-Saccharomyces yeasts ...... 62 3.3.2.1. Candidate Hanseniaspora strains tolerate lower sulfite concentration compared with S. cerevisiae BY4742 ...... 62 3.3.2.2. Variable ethanol tolerance of candidate wild yeast strains ...... 66 3.3.2.3. Fermentation kinetics of candidate wild yeast strains in sterile Chambourcin juice ...... 71 3.3.3. Chemical composition of wines fermented by non-Saccharomyces yeasts ...... 73 3.3.3.1. Core non-volatile compounds as fermentative performance contributed by candidate wild yeast strains ...... 73 3.3.3.2. Distinct volatile profile of inoculated fermentations with yeast strains ...... 83 3.4. Discussion ...... 95 3.4.1. Diverse wild yeast populations in the early stages of fermentation represent unique microbial terroir across three PA vineyards ...... 95 3.4.2. Filamentous fungal populations in grape must could be an indicator of grapevine health and wine quality ...... 99 3.4.3. Characterization of physiological properties in wild yeast provides insights into potential for winemaking ...... 101

Chapter 4

4.1. Major findings and conclusion ...... 107 4.2. Future Study ...... 109

References ...... 110

vii LIST OF FIGURES

Figure 1-1. Importance of selection and timing of adding non-Saccharomyces yeast strains in winemaking to produce wine with increased flavor complexity and microbiological control...... 3 Figure 1-2. Alcoholic fermentation and glycolytic pathways in yeast...... 14 Figure 2-1. Significant decrease in wild yeast diversity was observed after 24 hours of spontaneous fermentation of Isabella grape must...... 23 Figure 2-2. Decrease of yeast colony forming capacity (cells/ml) at different sulfite concentrations depending on time of incubation (min)...... 25 Figure 2-3. Wine associated compounds are categorized into two major groups, non-volatile and volatile metabolites...... 28 Figure 2-4. Analysis of non-volatile and volatile compounds for identifying mouthfeel and flavor profile contributed by non-Saccharomyces yeast species during laboratory scale fermentation...... 29 Figure 3-1. Microbial and chemical analyses used for characterization of wild yeast for potential use in winemaking...... 36 Figure 3-2. Chromatogram of a standard mixture injected through Aminex HPX- 87H (300 x 7.8 mm) columns on (A) Agilent 1100 HPLC and (B) Thermo Vanquish UHPLC system...... 43 Figure 3-3. Sampling of Chambourcin grapes for fungal isolation...... 49 Figure 3-4. Main contributing fungal species during spontaneous fermentation of Chambourcin grape must...... 54 Figure 3-5. Phylogenetic tree constructed with ribosomal internal transcribed spacer (ITS) regions and 5.8S rRNA gene sequences of 120 isolated fungal strains...... 57 Figure 3-6. Phylogenetic subtrees of yeast strains supported with high bootstrap value constructed with ribosomal internal transcribed spacer (ITS) regions and 5.8S rRNA gene sequences...... 60 Figure 3-7. Phylogenetic subtrees of filamentous fungi strains supported with high bootstrap value constructed with ribosomal internal transcribed spacer (ITS) regions and 5.8S rRNA gene sequences...... 61 Figure 3-8. Sulfite tolerance of candidate wild yeast strains and S. cerevisiae BY4742 in neutral YPD media (pH=6.5)...... 62 Figure 3-9. Sulfite tolerance of candidate wild yeast strains and S. cerevisiae BY4742 in acidified YPD media (pH=3.0)...... 64

viii Figure 3-10. Growth curves of H. uvarum NV192410 and H. opuntiae NV192404 at different concentrations of metabisulfite comparing with S. cerevisiae BY4742 control strain...... 65 Figure 3-11. Growth curves of P. kluyveri NV192402 nd P. kudriavzevii SM192402 at different concentrations of metabisulfite comparing with S. cerevisiae BY4742 control strain...... 66 Figure 3-12. Growth curves of A. pullulans SM190002 at different concentrations of metabisulfite comparing with S. cerevisiae BY4742 control strain...... 66 Figure 3-13. Ethanol tolerance of candidate wild yeast strains and S. cerevisiae BY4742...... 68 Figure 3-14. Growth curves of H. uvarum NV192410 and H. opuntiae NV192404 at different concentrations of ethanol comparing with S. cerevisiae BY4742 control strain...... 69 Figure 3-15. Growth curves of P. kluyveri NV192402 and P. kudriavzevii SM192402 at different concentrations of ethanol comparing with S. cerevisiae BY4742 control strain...... 70 Figure 3-16. Growth curves of A. pullulans SM190002 at different concentrations of ethanol comparing with S. cerevisiae BY4742 control strain...... 70 Figure 3-17. Fermentation kinetics of candidate wild yeast strains and S. cerevisiae BY4742 in sterile juice represented by weight reduction (%)...... 72 Figure 3-18. Composition of major sugars (g/L) in sterile juice compared with inoculated fermentations with candidate wild yeast strains with S. cerevisiae BY4742 as control...... 75 Figure 3-19. Non-volatile compounds in sterile juice compared with inoculated fermentations with candidate wild yeast strains with S. cerevisiae BY4742 as control...... 76 Figure 3-20. Total sugars (g/L) and sugar consumed (%) in sterile juice and inoculated fermentations with candidate wild yeast strains and S. cerevisiae BY4742...... 78 Figure 3-21. Ethanol content (g/L) in inoculated fermentations with candidate wild yeast strains and S. cerevisiae BY4742, and ethanol yield (g Ethanol/ g Sugar)...... 79 Figure 3-22. Data obtained from non-volatile chemical analysis were log transformed to remove heteroscedasticity and Pareto scaling was performed to decrease mask effects resulting in a more normal distribution of the data, before normalization (left panel) and after normalization (right panel)...... 81 Figure 3-23. Principal component score plot (A) and biplot (B) of the variables with PC1 and PC2 based on the non-volatile composition of sterile juice

ix (eight spoked asterisk) and inoculated fermentations with candidate yeast strains and S. cerevisiae BY4742...... 83 Figure 3-24. Total 74 volatile compounds detected by GC-MS from sterile juice and inoculated fermentations by candidate wild yeast strains and S. cerevisiae BY4742 were grouped based on chemical structures...... 84 Figure 3-25. Distribution of relative abundance of volatile compounds before (left, skewed) and after (right, more normally distributed) the log transformation and Pareto scaling...... 88 Figure 3-26. Principal component score plot (A and C) and biplot (B and D) of the variables with PC1, PC2 and PC3 based on the volatile composition of sterile juice (eight spoked asterisk) and inoculated fermentations...... 95

x LIST OF TABLES

Table 3-1. Retention time (RT) and the standard curve of the standard compounds...... 45 Table 3-2. Species identified from spontaneously fermenting Chambourcin grapes isolated from three Pennsylvania vineyards at 0 and 24 h combined by number of species and relative abundance (%)...... 51 Table 3-3. Candidate yeasts chosen for tolerance assay and laboratory scale fermentation...... 61 Table 3-4. List of volatiles detected in sterile juice and inoculated fermentations with candidate wild yeast strains and S. cerevisiae BY4742 with mean retention time (RT) and retention indices (RI)...... 85 Table 3-5. All identified volatile compounds showed significant difference (ANOVA, FDR-adjusted p-value<0.05) across sterile juice and inoculated fermentations by candidate wild yeasts and S. cerevisiae BY4742. Data shown here are after normalization...... 89

xi ACKNOWLEDGEMENTS

I would like to thank my advisor, Dr. Josephine Wee, for providing me the opportunity to pursue my Master’s degree in her lab. Her guidance and constant support made me develop into a better researcher. I would like to extend my appreciation to my committee members, Dr. Edward Dudley and Dr. Ryan Elias, for their feedback on this project. They always motivated me to think critically. I would also like to thank Dr. Helene

Hopfer for helping me with GC-MS and Dr. Ashik Sathish from CSL Behring

Fermentation Facility for assisting with developing a protocol for HPLC.

A special thank you to my lab mates, Dr. Xue Du and Hung Li Wang. Their advice helped keep me calm when experiencing difficulties in running experiments. It was an unforgettable journey having numerous brainstorming sessions with them. I am grateful for all the support of my friends in the department. There was lots of fun having classes together and sharing insights into research problems.

I must express my utmost gratitude to my parents and family for encouraging me throughout the years of study. No matter the time difference, I know they are always with me. This accomplishment would not have been possible without them.

This research conducted at Penn State University Park is supported by the USDA

National Institute of Food and Agriculture and Hatch Appropriations under Project

#PEN04699 and Accession #1019351 and the Crouch Endowment for Viticulture,

Enology, and Pomology Research. The findings and conclusions in this study do not necessarily reflect the view of the funding agency.

Chapter 1

Literature Review

1.1. Statement of Issue

Non-Saccharomyces yeasts or wild yeasts are important microorganisms that contribute to grapevine health and wine fermentation, such as grape fungal diseases and wine flavor compounds derived from yeast metabolism. Factors that impact the distribution of microorganisms on grapevines and winery environments include weather, soil, rainfall and human practices. Collectively, these are the factors of ‘terroir’ which describes the unique characteristic of vineyards and final wines (Vaudano et al. 2019). Historically, winemakers have relied on commercial yeasts such as Saccharomyces cerevisiae for winemaking because S. cerevisiae is well-known for its efficient fermentation capacity and reliable performance for fermentation of grape berries to final wine. While commercial S. cerevisiae is still widely used and is the gold standard for winemaking, several studies suggest a decline in complexity of wine flavor which can be improved with proper use of non-Saccharomyces yeast species (Gamero et al. 2016; Lemos Junior et al. 2019).

Previous literature demonstrate several applications of non-Saccharomyces yeast in reduction of alcohol content and enhancement of wine flavor complexity (Romano et al.

2003; Maturano et al. 2019; Lemos Junior et al. 2019). Increased interest in decreasing concentration of alcohol in final wines are related to financial (alcohol tax), health and

1 wine quality considerations. First, financial imposts on higher alcohol concentration have increased cost for both winemakers and consumers. Second, consumer awareness related to health risks of consuming too much alcohol is elevated. Third, the perception of a

‘hotness’ on the palate caused by high concentration of alcohol is considered as a negative impact in some wine styles due to the imbalance between flavor compounds (i.e. acids, tannin, sugars and aroma compounds) (Goold et al. 2017). Therefore, softer alcoholic beverages have seemed to be in accordance to the current market demands in many countries (Pickering 2000). For example, alcohol consumption had been decreased from

9.8 to 6.9 liters of pure alcohol per person annually from 1990 to 2005 in Italy (Allamani,

Voller, and Beccaria 2010). In Australia, low and mid-strength beer (2.8 – 3.5% ethanol) has dominated more than 41% of the national beer market by 1999 and kept increasing according to Associated Brewers of Australia (Stockwell and Crosbie 2001). Additionally, consumers have responded favorably to richer, fruitier and more complex styles of wine

(Goold et al. 2017). Careful selection and timing of addition of non-Saccharomyces yeast strains in winemaking has been considered a strategy to produce wine with increased flavor complexity and better microbiological control. In comparison, pure inoculation of S. cerevisiae could reduce wine flavor complexity, and spontaneous fermentation might cause stuck fermentation or contamination (Padilla, Gil, and Manzanares 2016) (Figure 1-1).

Figure 1-1. Importance of selection and timing of adding non-Saccharomyces yeast strains in winemaking to produce wine with increased flavor complexity and microbiological control.

Spontaneous fermentation only with the involvement of wild yeasts from grapes (mainly non-Saccharomyces) and from winery (mainly Saccharomyces) makes the wines with greater flavor complexity but less microbiological control (a). Whereas, by inoculating the commercial strain of Saccharomyces cerevisiae, the fermentation can be conducted with better microbiological control but the complexity of wine is reduced (c). The use of selected non-Saccharomyces strains allows to obtain wines with greater complexity and better microbiological control of the process (b) (figure reproduced with permission from Padilla,

Gil, and Manzanares 2016).

Pennsylvania (PA) is ranked the fifth largest wine producer (2.1 million gallons annually) in the United States compared to California (684 million gallons). Although total

1.4 billion had been created and contributed to the economic impact in PA from 2017 to

2018, there are many improvements that local winemakers could consider to make PA

Wine industry be more competitive (Pennsylvania Winery Association 2020).

Chambourcin, a French-American hybrid grape, is the most abundant hybrid grapes grown in PA. Therefore, we are expected to contribute most potential benefits to local

Chambourcin wine producers once novel wild yeast strains have been characterized and validated for enhancing wine flavor complexity.

1.2. Non-Saccharomyces yeasts on grapes

The term non-Saccharomyces yeasts is used to describe indigenous, native or wild yeasts present on grape berries originating from the vineyard and at the point of harvest which can present in the grape musts during early stages of winemaking or in the winery environment (Fugelsang and Edwards 2007). Non-Saccharomyces yeasts are the major component of wine grapes microbiome and their influence on shaping sensory characteristics of final wine have been previously described (Pinto et al. 2015; Belda et al.

2017). For example, Hanseniaspora and Metschnikowia spp. were found on grapes in the

Chilean Central Valley including the famous Cabernet Sauvignon vineyards of the Maipo

Valley and were correlated to terpenes, thiols, esters, and higher alcohols (sweet fruity aromas) (Jara et al. 2016). Moreover, H. uvarum and P. guilliermondii found on grapes were correlated to acetophenone and octanoic acid in vineyards of Chardonnay production within Napa County (Bokulich et al. 2016). Although non-Saccharomyces yeasts such as

Hanseniaspora, Schizosaccharomyces and Zygosaccharomyces spp. had been traditionally considered as spoilage yeasts due to excessive production of acetic acid, they are now widely accepted after characterizing the acids production as considerable variability between strains was found (Padilla, Gil, and Manzanares 2016). Thus, the perspective on non-Saccharomyces yeasts has changed from spoilage microorganisms to using yeasts as a biotechnological tool for improving wine flavor complexity during this decade. In the last five years, increasing number of studies focused on characterization of wild yeasts on vineyards and in winemaking and how microbial populations influence wine quality and in shaping terroir.

On the healthy and undamaged Vitis vinifera grape berries, viable populations of non-Saccharomyces yeasts are typically present at a range of 10 to 10 cfu/mL and comprise a group of heterogenous genera such as Hanseniaspora, Pichia, Aureobasidium,

Candida, Cryptococcus, Issatchenkia, Kluyveromyces, Metschnikowia, Rhodotorula,

Wickerhamomyces, Filobasidium and Sporidiobolus (Jolly, Augustyn, and Pretorius 2003;

S. S. Li et al. 2010; Brysch-Herzberg and Seidel 2015). In contrast to non-Saccharomyces yeasts, the presence of indigenous S. cerevisiae is relatively low from the onset of fermentation. In spontaneous fermentation of Tempranillo (V. vinifera), S. cerevisiae was first recovered on day 6 with relative abundance at 4% of the isolates (Bougreau et al.

2019). Many other studies also indicate S. cerevisiae becomes dominant species until middle and final stages of fermentation (Neil P. Jolly, Varela, and Pretorius 2014; Eder,

Conti, and Rosa 2018). Recently, diversity of non-Saccharomyces yeast such as

Hanseniaspora, Pichia, Candida, and Metschnikowia spp. present during early stages of winemaking has been of interest due to their ability to release different volatile metabolites

5 that can enhance flavor complexity and preserve regionality. For example, M. pulcherrima isolated from multiple regions of Italy were found to increase production of higher alcohols, such as �-phenylethyl alcohol corresponding to floral odor (Binati et al. 2020).

Furthermore, co-fermentation with M. pulcherrima and S. cerevisiae resulted in fruitier and fresher white wine indicated by sensory panel due to higher levels of 4-Mercapto-4-methyl-

2-pentanone over the sensory threshold (Ruiz et al. 2018). Thus, studying the diversity of non-Saccharomyces yeast is important to enhance wine quality within the region.

Physiological characteristics of three genera of wild yeasts, Hanseniaspora, Pichia and Aureobasidium were highlighted to provide background knowledge of yeast species as well as summarize relevant findings in winemaking to date.

The genus Hanseniaspora is often found in grape musts before fermentation and dominate in early stages of alcoholic fermentation (Joshi et al. 2017). Common

Hanseniaspora species isolated from grape-associated environment include H. uvarum, H. guilliermondii, H. opuntiae, and H. vineae (Gamero et al. 2016; Raymond Eder et al. 2017;

Luan et al. 2018). Hanseniaspora uvarum has shown the ability to grow at cold temperature

(i.e. 15℃ for white wine fermentation), in anaerobic conditions, and ability to tolerate copper which is a typical anti-fungal treatment used in vineyards (Albertin et al. 2016).

Many H. uvarum strains display β-glucosidase and protease activities which could contribute to aroma formation by hydrolysis of non-volatile glycosidic aroma precursors, and prevention of protein haze by degrading proteins which could become insoluble due to the temperature swings (Hernández et al. 2003; Claus and Mojsov 2018). The presence of

H. uvarum was characterized by high production of acetoin and ethyl acetate, and relatively low production of higher alcohols in Aglianico wines (Romano et al. 2003).

Hanseniaspora guilliermondii was reported to produce significantly higher levels of 2-phenylethyl acetate, 1-propanol, and 3-(methylthio) propionic acid during inoculated fermentation (Moreira et al. 2011). In co-fermentation with S. cerevisiae, improved ester production and reduced amount of ethyl acetate have been identified compared to pure cultures (Ciani et al. 2010). Co-fermentation of H. opuntiae and S. cerevisiae in Cabernet

Sauvignon grape must resulted in higher amounts of higher alcohols (phenylethanol and 3- methyl-butanol) and phenylacetaldehyde which corresponded to intensification of sweet floral attributes of final wine (Luan et al. 2018).

The genus Pichia belongs to the family Saccharomycetaceae and its morphology is described as spherical or elliptical acuminate cells. More than one hundred species of this genus are known. Some Pichia species such as P. membranifaciens and P. kudriavzevii are film-forming yeasts which may form pellicles on the wine surface and produce odor active compounds due to the aerobic nature and fast growth (Moon et al. 2014; Campaniello and

Sinigaglia 2017; Malfeito-Ferreira 2019). During succession of microorganisms during wine fermentation, Pichia spp. usually dominates middle stages of fermentation when ethanol rises to 3-4% (Joshi et al. 2017). In addition, killer toxins produced by P. membranifaciens and P. anomalais are able to inhibit growth of Brettanomyces which is a common cause of fungal spoilage contributing to wine faults (A. Santos et al. 2009; Butzke

2010). Common Pichia species found in grape must include P. kluyveri, P. kudriavzevii, and P. fermentans (S. S. Li et al. 2010; Bezerra-Bussoli et al. 2013; Drumonde-Neves et al. 2017; Luan et al. 2018). Pichia kluyveri, isolated from fermentations of Terrano and

Refosco in Slovenia, was identified as indigenous killer yeast, expressing killer activity against sensitive S. cerevisiae strain which may affect the fermentation capacity of wine

7 starters (Zagorc et al. 2001). In wine fermentation, significant higher amounts of 3- mercaptohexyl acetate (3MHA) in Sauvignon Blanc was found in co-fermentation with commercial Saccharomyces strains and an isolate of P. kluyveri from New Zealand (at a

1:9 starting ratio). 3MHA is one of the dominant aroma compounds in Sauvignon Blanc and exhibits great impact on wine flavor and aroma (Anfang, Brajkovich, and Goddard

2009).

Pichia kudriavzevii has been characterized relative to tolerance to multiple stresses such as ethanol levels up to 12%, glucose concentrations over 40%, temperatures over

45 °C, pH as low as 1.0 (Toivari et al. 2013; C. Li et al. 2018, 2019). A strain of P. kudriavzevii, isolated in Chinese vineyard, demonstrated high β-glucosidase activity and increased production of terpenes, C13-norisoprene, and ethyl esters which contribute positive aroma to Cabernet Sauvignon wine. Moreover, improved sensory evaluation scores were identified from the co-fermentation with this P. kudriavzevii strain and S. cerevisiae (Shi et al. 2019). Pichia fermentans has contribute to the improvement of wine flavor along with S. cerevisiae. For example, increased levels of acetaldehyde, ethyl acetate, 1-propanol, n-butanol, 1-hexanol, ethyl caprylate, and 2,3-butanediol were identified in sequential fermentation of Macabeo with S. cerevisiae (Clemente-Jimenez et al. 2005). In the co-fermentation of Ecolly grapes with S. cerevisiae, the content of phenyl ethyl acetate increased with increasing inoculum volume of P. fermentans (Ma et al. 2017).

Finally, genus Aureobasidium is a cosmopolitan fungus in the family Dothioraceae including 14 species. Aureobasidium pullulans, the yeast-like fungus, is most well-known among all species and frequently found in grape must (Malfeito-Ferreira 2019). It was formerly known as Pullularia pullulans which was named after its ability of synthesizing

8 the extracellular glucan – pullulan (Schmidt 2019). Pullulan (poly-α-1,6-maltotriose biopolymer) has significantly contributed to biotechnological applications in the food and pharmaceutical industries. For the applications in viniculture and viticulture, A. pullulans shows the antagonistic activity against Botrytis cinerea and Alternaria alternata which are associated to plant disease (Bozoudi and Tsaltas 2018; Yalage Don et al. 2020). On the other hand, A. pullulans was found to produce 2-methylbutanoic acid, 3-methyl-1-butanol and ethyl octanoate which are the critical flavor compounds in red wine (Verginer, Leitner, and Berg 2010).

Although some common wild yeast species have been analyzed for the fermentation characteristics and the production of volatile compounds, it is important to acknowledge that physiological properties are strain-dependent for both Saccharomyces and non-

Saccharomyces yeasts which can significantly influence wine quality (Hyma et al. 2011;

López, Mateo, and Maicas 2014; Englezos et al. 2015). Non-Saccharomyces yeast species isolated from varieties of grape cultivars have demonstrated unique contributions to wine quality, however, wild yeast strains on Chambourcin have not been studied. The influence of these wild yeasts on Chambourcin wine would be valuable to investigate.

1.3. Characterization of important yeast physiological properties related to

winemaking

Physiological properties of yeast species related to winemaking include tolerance to high concentration of substrates (e.g. sulfite, glucose, ethanol), killer activity, and production of hydrogen sulfide (H2S) (Zagorc et al. 2001; Englezos et al. 2015). Yeast can produce toxic compounds besides ethanol during fermentation, namely, killer toxins, such

9 as short- and medium-chain fatty acids, sulphite, peptides or glicoproteins (Pérez-Nevado et al. 2006). Secretion of killer toxins by killer strains could induce death of sensitive strains of both Saccharomyces spp. and non-Saccharomyces spp., and thus inhibit the progress of fermentation (Radler and Schmitt 1987; Raymond Eder et al. 2017). Hydrogen sulfide produced by yeasts especially during fermentation of grape musts with nitrogen deficiency is associated to rotten-egg odor which could significantly decrease the sensory quality of wine (Giudici and Kunkee 1994; Franco-Luesma et al. 2016). For the most part, the ability to grow and survive is an important criterion to allow wine yeasts to utilize sugars in the metabolic pathway and contribute to the fermentation process by producing wine- associated metabolites. Therefore, examining tolerance to sulfites and ethanol is critical as these two common stresses to yeast strains in winemaking.

Sulphur dioxide (sulfites, SO2) and its derivatives have been used as antioxidant and antimicrobial agents to preserve and extend the shelf life of foods such as jams, canned vegetables and dried fruits. In the wine industry, sulfites are used to prevent spoilage and preserve the flavor and freshness of wines. SO2 is a weak acid and can form conjugate bases

2- - including potassium or calcium salts of sulfite (SO3 ), bisulfite (HSO3 ), or metabisulfite

2- (S2O5 ) which are commonly used in foods. The anions of these salts have been designated

2- - by IUPAC as sulfites (SO3 ), hydrogen sulfites (HSO3 ), and disulfites, respectively

2- (S2O5 ). When molecular SO2 is dissolved in water, the acidity of solution is significant.

The first dissociation has pKa1 of 1.86 in �� () ⇋ �� + � . When pH level raised

- 2- to range 3 ~ 7, bisulfite (HSO3 ) is predominated; but sulfite (SO3 ) becomes most

abundant when pH above 7. The pKa2 is 7.18 for the second dissociation: �� ⇋ � +

�� . Values of pKa for weak acids increase with increasing ethanol concentration and

10 temperature. Based on the empirically derived correction factors, pKa1 will range between

1.85 to 2.00 at 20℃ in typical wine ethanol content (10-14% v/v). At pH = 3 to 4 which is

- relevant in winemaking, bisulfite (HSO3 ) contribute more than 90% free SO2 species with minor abundance of molecular SO2 form (Damodaran and Parkin 2017). The sum of bisulfite and molecular SO2 is commonly measured in winery settings and called ‘free

2- SO2’, as the concentration of sulfite ion (SO3 ) is negligible at this pH level (Waterhouse,

Sacks, and Jeffery 2016). For the regulatory purposes, wines contain more than 10 mg/l of total sulfites must be labeled, and the maximin legal dosage of total sulfites for all wines is

350 mg/l by Alcohol and Tobacco Tax and Trade Bureau in the United States. Sulfur dioxide is most effective as an antimicrobial agent in acidic conditions due to the effect from the molecular SO2 penetrating the cell wall and disrupting the enzymatic activity of the cell. On the other hand, the antioxidant effect results from the hydrogen sulfites reacting with oxygen.

Certain levels of sulfites, normally 100 mg/l SO2, is added by winemakers to inhibit the growth of spoilage microorganisms and prevent oxidation. Some stages of winemaking are considered to supplement additional sulfites, including beginning of fermentation, aging, and pre-bottling. Sulfites added in early stage of fermentation could ensure the quality of fermentation by avoiding the spoilage microorganisms. Sulfite supplemented after fermentation ensure the stability of aging and storage by preventing overreaction of the residual microorganisms, including S. cerevisiae and Oenococcus oeni which is principally responsible for alcoholic fermentation and malolactic fermentation (Henderson

2009). In addition to the additional sulfites, during alcoholic fermentation, yeast strains could also produce sulphur dioxide as a metabolic intermediate of the sulfate reduction

11 pathway, but most of the commercial wine yeasts are considered as low SO2 producers range from 2mg/l to 20mg/l (Werner et al. 2009). Pathogens and spoilage microorganisms are expected to be disinfected by the additional sulfites for the concerns of food safety.

Thus, wild yeast candidates must have certain level of tolerance to high concentration of sulfites in order to grow and ferment in the winemaking process.

The concertation of ethanol gradually increases while sugars are converted to ethanol by yeasts during fermentation. In average, alcohol content (%, v/v) can range 11-

13% in wine according to The National Consumers League, an American consumer organization. However, ethanol is toxic for yeast cells, because the interaction with cellular membranes causes the damages of membrane integrity, and consequently impacts cellular viability, growth, and fermentation activity (Thomas and Rose 1979; A. Aguilera and

Benítez 1985; M. E. Hong et al. 2010; Schiavone et al. 2016). Non-Saccharomyces yeasts have been reported with mild tolerance at 6% of ethanol, on the other hand, S. cerevisiae has been reported to have tolerate at least at 13% ethanol (Ghareib, Youssef, and Khalil

1988; Pina et al. 2004). Although having lower ethanol tolerance, diverse wild yeast populations in early stage of fermentation produce volatile compounds which contribute wine aroma profile and consequently impact final wine quality (Moreira et al. 2011). Other wild yeast species with comparable ethanol tolerance were inoculated with wine yeasts to enhance flavor complex throughout the fermentation process (Garde-Cerdán and Ancín-

Azpilicueta 2006).

1.4. Core non-volatile and volatile metabolites as the indicators of wine flavor

Wine chemical compounds are derived from (1) the grape, (2) fermentation and (3) aging conditions. Grape composition could be various across varieties and vintages. Aging could be in the bottle or in oak barrels which generally leads to decrease of aroma derived from grapes and fermentation, and forms aromatic characteristic of older wines (Styger,

Prior, and Bauer 2011). Here I will focus on fermentation-derived metabolites. Metabolism is essential to support the growth and survival of microorganisms. During the winemaking process, numerous non-volatile and volatile compounds are produced and can be categorized as primary and secondary metabolites. Primary metabolites are the predominant feature of yeast metabolism during alcoholic fermentation. Secondary metabolites contribute to complex aromatic compounds in wine flavor. Both primary and secondary metabolites are essential for producing a well-balanced wine.

Primary metabolites are universally defined as essential compounds to support normal cells function. In yeast, alcoholic fermentation is the biotransformation of grape sugars into ethanol and carbon dioxide via glycolysis which is part of primary metabolism.

By consuming glucose and fructose, yeast cells subsequently transform sugars to glucose-

6-phosphate and other glycolytic intermediates, and to pyruvate and ethanol (Figure 1-2)

(Rodicio and Heinisch 2017). ATP formation in glycolysis is important for yeast cells as the source of energy. To maintain continuous ATP formation in anaerobic conditions, S.

+ cerevisiae regenerates NAD via the two-step conversion of pyruvate to ethanol and CO2 in order to supplement depleted NAD+, while NAD+ is reduced to NADH during the conversion of glyceraldehyde-3-phosphate to 1,3-biphosphoglycerate during glycolysis

(Querol et al. 2018).

Figure 1-2. Alcoholic fermentation and glycolytic pathways in yeast.

Yeast consumes glucose from grapes and converts to glucose-6-phosphate followed by glycolysis. Ethanol is the end product in yeast sugar metabolism with CO2 as the byproduct (figure reproduced with permission from Querol et al. 2018).

Secondary metabolites are defined as heterogenous low-molecular-weight compounds which do not participate in the central of metabolic processes. The production of many secondary metabolites are defense mechanism against biotic and abiotic stresses, such as oxidative stress and ultraviolet radiation (Siddiqui et al. 2012). For example, eutypinol, a secondary metabolite of the grapevine fungi Eutypa lata could inhibit mitochondrial respiration of S. cerevisiae (J. H. Kim et al. 2004). Yeast peroxiredoxin

Tsa1, an antioxidant, protects cells from oxidative damage to proteins (Sui et al. 2015).

Melanin, a natural pigment in spores or hyphae, provides protection from UV damage to cells (Keller 2019).

During wine fermentation, environmental stresses initiating the production of secondary metabolites include sugar content in grapes inducing high osmolarity, fermentation temperature, ethanol content (Fairbairn et al. 2012). Under these stresses, yeasts produce a wide variety of secondary metabolites, such as glycerol, organic acids, sulfur-containing molecules, fatty acids, higher alcohols, and esters. The interactions between these various chemical compounds primarily contribute to wine aroma and organoleptic quality (Querol et al. 2018). Higher alcohols and esters are the most two important chemical groups within fermentative aroma due to the abundance in wine

(Saerens et al. 2010). The synthesis of higher alcohols in yeast is via the catabolism of amino acids known as the Ehrlich pathway. Three group of amino acidic precursors are: branched-chain aliphatic amino acids (valine, leucine, and isoleucine); aromatic amino acids (phenylalanine, tyrosine, and tryptophan); and sulfur-containing amino acid

(methionine). Lower amounts of higher alcohols present in wine can impart positive contributions to wine flavor and aroma, as it will be regarded as pungent smell when

15 concentration exceeds 400mg/l (Lambrechts and Pretorius 2019). Higher alcohols identified as significant aroma-active metabolites by yeast include propanol (fruity, green grass odor), 2-phenylethanol (floral, rose odor), and isoamyl alcohol and active amyl alcohol (sugar, honey odor). Furthermore, esters are derived from the reaction between acid and alcoholic components. Two main groups of esters produced by S. cerevisiae during fermentation are ethyl esters and acetate esters. Ethyl esters are formed from medium-chain fatty acid and ethanol, such as ethyl butanoate and ethyl decanoate which are associated to fruity and floral odor. On the other hand, acetate esters are formed from the reactions of acetate with ethanol or higher alcohol, such as ethyl acetate (fruity, nail polish odor), isoamyl acetate (banana, fruity odor), and 2-phenylethyl acetate (fruity, rose odor) (Querol et al. 2018).

After completion of grape fermentation, 90 ~ 95% of sugar is theoretically contributed to ethanol yields in S. cerevisiae. The remaining 5 ~ 10% of sugar could be used for biomass biosynthesis or alternative metabolic pathways (König, Unden, and

Fröhlich 2009; Ciani et al. 2016). In comparison, the differences of metabolic flux distribution have been demonstrated between S. cerevisiae and non-Saccharomyces yeasts, which consequently results different ethanol production and by-product formation (Tofalo et al. 2012; Milanovic et al. 2012). For example, Candida stellata has strong fructophilic character, and produces significantly higher amount of glycerol (10.63g/l), but lower amount of ethanol (8.54% v/v), volatile acid (0.79g/l), and acetaldehyde (82.88 mg/l) compared with S. cerevisiae which produce 9.59g/l glycerol, 10.59% ethanol, 1.00g/l volatile acid, and 91.50 mg/l of acetaldehyde (Magyar and Tóth 2011). Therefore, the diversion of alcoholic fermentation and formation of secondary compounds might explain

16 the low ethanol production of non-Saccharomyces yeasts. Interestingly, the link between the production of ethanol and other fermentation compounds were reported. In S. cerevisiae, higher amount of glycerol production is correlated with the production of acetic acid, but this correlation was not identified in H. uvarum (Saerens et al. 2010). In other non-Saccharomyces yeast strains, the relationship between ethanol production and other fermentation metabolites were revealed in previously studies. For example, in Candida stellate, the production of ethanol is positively correlated with glycerol; and in Kloeckera apiculate, the production of ethyl acetate could be explained by positive correlation with ethanol production (Ciani et al. 2016).

In summary, the patterns of alcoholic fermentation and productions of fermentation metabolites are species and strain-specific (Domizio et al. 2011). To differentiate the characteristics of non-Saccharomyces yeasts, liquid chromatography (LC) and gas chromatography (GC) are the analytical tools allowing for the qualification and quantification of non-volatile and volatile metabolites. Equipped chromatography with mass spectrometry, unknown compounds can be identified and analyzed with the nontargeting manner.

Chapter 2

Significance, Hypothesis & Objectives, Rationale

2.1. Significance

Consumers today have responded favorably to richer, fruitier, and more complex styles of wine (Goold et al. 2017). Microbial populations present on grape berries in vineyards and in winery environment can contribute to the winemaking processing through fermentation and is one of the factors that impact final wine flavor (Belda et al. 2017; Liu et al. 2020). According to previous studies, select wild yeast strains isolated from grape- associated environments have been added back into fermentation of grape must to obtain final wine with increased flavor complexity (Padilla, Gil, and Manzanares 2016). However, scientific literature typically focused on Vitis vinifera in viticulture and enology research as it is the most reputable and historic variety used for producing good quality wines globally. Moreover, V. vinefera grapes contain pleasing aroma precursors such as terpenoids and glycosides, which is not commonly found in American grapes or hybrid grapes varieties. In this study, our goal was to investigate whether hybrid grapes

(Chambourcin) inoculated with selected wild yeast strains are able to produce wine important chemical compounds when compared to S. cerevisiae control strain.

Hybrid grapes are defined as interspecific grape varieties that result from the crossing of two or more Vitis species (Alleweldt and Possingham 1988). Examples of

18 hybrid grapes include Cabernet Doré (cross between Cabernet Sauvignon and the Norton),

Seyval Blanc (cross between of Seibel 5656 and Seibel 4986 (Rayon d’Or)), Baco Noir

(cross between V. vinifera (Folle Blanche) and V. riparia), and Chambourcin (cross between Joannès Seyve and Seibel 5455) (Vittek 2020). Between the late nineteenth and twentieth century, crossing of two or more Vitis species to create hybrid lines was conducted to enhance resistance to pathogenic diseases such as downy mildew caused by Plamospara viticola and powdery mildew caused by Erysiphe necator while preserving the potential for production of high quality wines (A. Barata, Malfeito-Ferreira, and

Loureiro 2012; Merdinoglu et al. 2018). In addition to enhanced disease resistance associated with certain hybrid grape varieties, research on hybrid grapes report higher resistance to cold temperature as a result of extreme weather and fluctuations in regional climate (Jones 2012). Chambourcin has been shown to be more resistant to plant diseases

(e.g. grey rot caused by Botrytis cinerrea, black rot, and crown gall) and cold weather (e.g.

-20 ~ -25°C) (A. Barata, Malfeito-Ferreira, and Loureiro 2012; Jones 2012; Pedneault and

Provost 2016). In Pennsylvania, the cold and humid climate is one contributing factor to fluctuating wine quality across vintages caused in part by grapevine diseases or cold injury

(Vernarelli 2018). Therefore, Chambourcin hybrid grapes were chosen to use as a model system in this study with hopes that outcomes from this study would contribute to winemaking by demonstrating that wild yeast isolated from Chambourcin has the potential to produce wine important metabolites that can contribute to final wine quality.

The State of Pennsylvania is ranked as the fifth largest wine producer in the United

States producing 2.1 million gallons annually compared to California (684 million gallons),

Washington (35 million gallons), New York (28 million gallons) and Oregon (10 million

19 gallons) (General Industry Stats 2019; Pennsylvania Winery Association 2020).

Chambourcin is grown in the midwestern states including Missouri, Indiana, Michigan and is one of the most abundant hybrid grape varieties grown in Pennsylvania (Happer and

Kime 2013; Wine-Searcher 2015). The abundance of Chambourcin in PA is a driving factor of this study. We expect that our findings can provide insights into application of a novel yeast strains for use in Chambourcin winemaking to produce unique flavor profile that preserves regionality of PA Chambourcin. Consequently, increase in consumer interest and purchase would directly impact the Pennsylvania wine industry.

One of the objectives of this study was to characterize wild yeasts present on grape berries and used them as single inoculums in laboratory scale fermentation while monitoring non-volatile and volatile compounds produced. Terroir is defined as regional variations in wine quality influenced by climate, landscape, human practices, and other environmental factors. A further extension of this concept is microbial terroir which highlights the contribution of microbial populations present on vineyards and in winery environments that can influence final characteristics and quality of wines (Vaudano et al.

2019). While studies of microbial composition on vineyards and in winery environments have involved V. vinifera varieties, hybrid grapes are less studied. In summary, identification of wild yeast diversity and the correlation to chemical profiling of inoculated fermentations will facilitate understanding of microbial terroir in PA Chambourcin.

2.2. Hypothesis and Objectives

The overall goal of this project is to identify and characterize wild yeast populations on Chambourcin grown in Pennsylvania vineyards, and investigate the ability of select wild yeast strains to produce unique wine-associated metabolites using a laboratory scale fermentation system. To accomplish this goal, following hypothesis and objectives were proposed.

I hypothesize that candidate wild yeasts isolated from Chambourcin grapes can be used for wine fermentation and contribute to production of wine important metabolites indicative of final wine quality. To test this hypothesis, I designed experiments to achieve three objectives:

Aim 1. To use culture-based methods and Sanger sequencing to isolate and identify wild yeasts from spontaneous fermentations of Chambourcin hybrid grapes;

Aim 2. To characterize sulfite and ethanol tolerance of candidate yeast strains as two indicators that support their potential use in winemaking;

Aim 3. To develop a laboratory scale fermentation system using sterile

Chambourcin juice inoculated with candidate yeasts and analyze non-volatile and volatile compounds by Ultra High-Performance Liquid Chromatography (UHPLC) and Gas

Chromatography Mass Spectrometry (GC-MS).

2.3. Important considerations to experimental design

In this section, I describe two important considerations in our experimental design to achieve research objectives in a way that supports industry practices of winemaking.

2.3.1. Combination of early stage fermentation and addition of sulfite are two important

aspects to capturing diverse wild yeasts populations

Spontaneous fermentation allows for growth and development of wild microorganisms in a fermenting system (Fleet 2008; Escribano-Viana et al. 2018). In commercial winemaking, spontaneous fermentation is not usually favored because of difficulties related to the rate of fermentation and reliability of wild microorganisms.

However, in our study, we relied on spontaneous fermentation of Chambourcin grape must for preparation of wild yeasts isolation and identification. High fungal diversity during early stages of isolation would allow for selection of reasonable number of wild yeast candidates for downstream analysis and characterization. While many factors can influence wild yeast composition on Chambourcin, we focused on two important factors that influence diversity and abundance of fungal communities: stage of fermentation (time) and presence of sulfite. In a previous studies by Di Maro, Ercolini, and Coppola (2007) and Raymond Eder et al. (2017), a significant decrease in wild yeast diversity was observed after 24 hours of spontaneous fermentation (Figure 2-1). Fourteen different non-

Saccharomyces yeast species were identified at initial stages (t = 0 ~ 24 h) of spontaneous fermentation. Therefore, in our study, we used spontaneous fermentation of Chambourcin at 0 and 24 h to capture the highest diversity of wild yeast population indicative of vineyard and region-specific microbial terroir.

Figure 2-1. Significant decrease in wild yeast diversity was observed after 24 hours of spontaneous fermentation of Isabella grape must.

(A) Relative contribution (%) of the identified yeast species among 40 selected colonies obtained at the indicated times of fermentation. (B) Yeast species identified among 10 rare colonies isolated from WL-Cm Nutrient agar* at the indicated times of fermentation.

*WL-Cm Nutrient agar: Oxoid WL Nutrient agar medium 7.5% (w/v) and chloramphenicol 10 µg/mL (figure reproduced with permission from Raymond Eder et al.

2017).

The addition of sulfite can significantly reduce the diversity and abundance of fungal communities in wine fermentation. Sulphur dioxide (SO2) is used as an antimicrobial agent to preserve foods and beverages. Current industry practice of winemaking relies heavily on the addition of sulfite to avoid spoilage and to preserve the flavor and freshness of wines (Mitsuhashi, Ikeuchi, and Nojima 2001). However, addition of sulfites in winemaking has been shown to inhibit the growth of yeast and reduce diversity of microorganism including wild yeasts and Saccharomyces cerevisiae (Figure

2-2) (Schimz 1980; Takahashi et al. 2014; Morgan et al. 2019). For the purpose of isolation and identification of wild yeasts, we chose to conduct spontaneous fermentation without addition of sodium metabisulfite to increase the chances of isolating diverse yeast populations using culture-based methods.

Figure 2-2. Decrease of yeast colony forming capacity (cells/ml) at different sulfite concentrations depending on time of incubation (min).

Incubation was conducted at 30℃ in YEPD medium*. Each pattern represents different concentration of sodium sulfite (��): ✕, 10 mM; +, 0.5 mM; ◯, 0.1 mM; ☐, 0.05 mM.

*YEPD medium: Ammonium sulfate 6 g/L, potassium dihydrogen phosphate 6.8 g/L, disodium hydrogen phosphate • 2H2O 8.9 g/L, Bacto Peptone (Difco) 5 g/L, Yeast Extract

(Difco) 25 g/L and D-glucose 20 g/L, calcium chloride • 2H2O 0.214g/L, and magnesium sulfate • 7H2O 0.122 g/L (figure reproduced with permission from Schimz 1980).

2.3.2. Development of a laboratory scale fermentation using sterile Chambourcin juice

inoculated with candidate yeast strains for wine chemical profile analysis

Laboratory scale fermentation has been used previously to study the metabolites of yeast strains and the impact of physiological properties on wine quality and flavor (Capece et al. 2013; Lemos Junior et al. 2019). These studies used synthetic or sterile grape musts as a substrate to enable measurement of specific metabolites produced by single, sequential or co-inoculation. In this study, we chose to use sterile juice inoculated with a single wild yeast strain in the laboratory scale fermentation to monitor fermentation-derived compounds associated with individual wild yeast strain. Grape must was centrifuged and sterile filtered (0.2 μm membrane filter) to obtain sterile juice as sterilization by autoclaving would result in changes to grape juice composition. With the removal of background microorganisms, we believed the chemical profile obtained by single inoculum would be valuable in the initial stages of characterization.

More than hundreds of chemical compounds have been identified in grapes and wines by analytical methods which could contribute to wine taste and aroma (Polášková,

Herszage, and Ebeler 2008). In general, the major components of wine are water, 86%; ethanol, 12%; glycerol, 0.6-1% and other trace elements, 1%; acids, 0.5%; and volatile compounds, 0.5% (Figure 2-3) (Sumby, Grbin, and Jiranek 2010; Nieuwoudt et al. 2017).

These compounds can be categorized into two major groups, non-volatile and volatile compounds. Ethanol, glycerol, sugars, and organic acids are the compounds that are not volatile and are known as core components in wine affecting taste and mouthfeel (Sumby,

Grbin, and Jiranek 2010). Therefore, in our study, we targeted nine non-volatile compounds for analysis using High-Performance Liquid Chromatography (HPLC),

26 including ethanol, glycerol, glucose, fructose, tartaric acid, succinic acid, citric acid, acetic acid and malic acid, as the indicators of yeast strains’ fermentation capability (Figure 2-

4).

On the other hand, volatile compounds including esters, higher alcohols, fatty acids, phenolics, amines and carbonyl compounds (aldehydes and ketones) mainly contribute to aroma of wines. Aroma compounds are important in wine quality wine due to the influence on sensory senses. In addition, profiling of volatile aromatic compounds (VOC) has been used as a useful approach to characterize yeast metabolism during fermentation process

(Mauriello et al. 2009; Ebeler and Thorngate 2009). Therefore, in addition to core non- volatile metabolites, we also analyzed VOC present in inoculated fermentations using non- targeted Gas Chromatography Mass Spectrometry (GC-MS) (Figure 2-4).

Figure 2-3. Wine associated compounds are categorized into two major groups, non- volatile and volatile metabolites.

Values are represented as weight per volume (w/v), and will vary depending on the wine type and the extraction technique (figure reproduced with permission from Sumby, Grbin, and Jiranek 2010).

Ethanol Mouthfeel Glycerol

Sweetness Glucose (sugars) Fructose

Tartaric acid Taste HPLC-RI Succinic acid Sourness Citric acid Flavor (organic acids) Acetic acid

Malic acid

Higher alcohols

Aroma Esters GC-MS

49 (Feng, unpublished) Volatile acids

Figure 2-4. Analysis of non-volatile and volatile compounds for identifying mouthfeel

and flavor profile contributed by non-Saccharomyces yeast species during laboratory

scale fermentation.

Mouthfeel and flavor are two important factors of wine quality. Flavor is defined as a

combination of both taste and aroma. Yellow color represents the sensory perception:

sweetness and sourness. Blue color represents the example compounds analyzed in this

study. Orange color represents the analytical method which HPLC-RI could be used for

analysis of non-volatiles and GC-MS could be used for analysis of volatile compounds.

Abbreviation: HPLC-RI, High-Performance Liquid Chromatography - Refractive Index

Detector; GC-MS, Gas Chromatography Mass Spectrometry.

Chapter 3

Microbial and chemical analysis of wild yeasts from Chambourcin

hybrid grapes for potential use in winemaking

3.1. Introduction

Saccharomyces cerevisiae has been widely applied to many fermentation processes including baking, winemaking and brewing for thousands of years (LEGRAS et al. 2007).

High tolerance of glucose and ethanol, and ability to convert sugars to alcohol in fermentation make S. cerevisiae important for alcoholic beverages (Johnson and Echavarri-

Erasun 2011). In winemaking, commercial strains of S. cerevisiae are selected because of their efficient and reliable fermentation capability especially important in making a final wine that is consistent in taste and aroma. Although commercial yeasts are common in winemaking, there is increasing interest in exploring the potential of wild yeasts, also known as non-Saccharomyces yeasts, in wine fermentation. Previous studies demonstrate that some wild yeast strains are able to influence physiological properties of the resulting wine, such as alcohol content and flavor profile (Contreras et al. 2014; Lemos Junior et al.

2019; Gamero et al. 2016; Escribano-Viana et al. 2018; Chen et al. 2018). For example, Metschnikowia pulcherrima and Torulaspora delbrueckii were able to reduce ethanol content to 0.28 and 0.3 g ethanol/ g sugar compared to S. cerevisiae at 0.46 g ethanol/ g sugar (Contreras et al. 2015). Hanseniaspora uvarum and Starmerella bacillaris

30 were able to enhance aromatic profile by producing higher alcohols that correspond to floral odor (i.e. �-phenylethyl alcohol) (Tristezza et al. 2016; Englezos et al. 2016; Binati et al. 2020). This example compound is one of the important phenolic higher alcohol in wine and consumers have responded favorably to richer, fruitier and more complex styles of wine (Jackson 2014; Goold et al. 2017).

The composition, distribution, and abundance of wild yeasts are affected by many environmental factors such as weather conditions, soil, rainfall, and winemaking practice

(Vaudano et al. 2019). Among the diverse wild yeasts present within vineyards and winery environments, Hanseniaspora spp., Pichia spp., and Candida spp. are the dominant yeast population that have been previously reported to contribute to the initial stages of fermentation and improve the organoleptic characteristics of final wine (Fleet 2008). To isolate and identify wild yeasts, a combination of microbiological culture-based approaches with molecular methods facilitate the identification of yeasts. Dichloran Rose

Bengal Chloramphenicol (DRBC) agar is recommended for the enumeration and selection of yeasts and molds in food products due to the antibacterial effect of chloramphenicol.

After culturing of yeast isolates, internal transcribed spacer (ITS) region consisting the

5.8S rRNA genes has been shown to provide the highest probability of successful identification for the broadest range of fungi (Schoch et al. 2012). Thus, studies to date use a combination of culture-based methods and sequencing to identify fungal populations in complex fermentation systems such as winemaking.

In winemaking, sulfites are added as a preservative to protect wine from spoilage caused by fungi or bacteria. Therefore, one important characteristic of wine yeasts is the ability to tolerate and grow in levels of sulfites during winemaking. Maximum legal limit

31 of total sulfites in wines is regulated at 350 mg/L in the United States. In addition, as concentration of ethanol increases during alcoholic fermentation, tolerance of wine yeasts to increasing concentrations of ethanol is also critical. Generally, red wines contain between 12-14 % of ethanol and commercial strains of S. cerevisiae has been reported to have tolerate and grow in levels of 13 % ethanol (Ghareib, Youssef, and Khalil 1988).

However, depending the type of yeast strain, yeast cell growth and viability can be inhibited by relatively high ethanol concentrations, and thus limit fermentation productivity and ethanol yield (Cray et al. 2013; Brown et al. 1981; F. Aguilera et al. 2006;

Zhang et al. 2015). Heat Shock Proteins (HSP), Hsp104 and Hsp12, encode proteins that function to protect liposomal membrane integrity and have been shown to be induced by ethanol stress and subsequently influence Saccharomyces yeast tolerance to ethanol (Sales et al. 2000; Stanley et al. 2010). Therefore, it is important to investigate physiological properties of yeast strains such as sulfite and ethanol tolerance to support the use of wild yeasts the applications of winemaking.

Flavor is a complex interaction of non-volatile and volatile chemical constituents that make up taste and smell. Certain core compounds such as ethanol, glycerol, organic acids and residual sugars contribute to the primary taste of wine. Sensory panelists perceive those core non-volatile compounds as mouth-waring effect, viscosity, sourness and sweetness. These core compounds are important because they are the fundamental component of wine contributing to organoleptic properties which are the aspects of wine that an individual experiences via sense (Lopez and Gomez 2013). On the other hand, volatile compounds in wine is composed of hundreds of different compounds with concentrations ranging from 10-1 and 10-10 g/kg typically perceived as wine aroma (Rapp

32 and Mandery 1986). Wine associated volatile metabolites are a result of three processes,

(1) metabolism of grape-derived compounds into active aroma compounds, (2) biosynthesis of fermentation-derived metabolites, and (3) post-fermentation practice- derived metabolites (Styger, Prior, and Bauer 2011). In this study, we focus on fermentation-derived metabolites contributed by wild yeasts to investigate the microbial contribution to wine metabolites. Previous literature have found enzymes and metabolites influenced wine flavor, including methoxypyrazines, C13-norisoprenoids, volatile sulfur compounds and terpenes as the major contribution to primary aroma; and volatile fatty acids, higher alcohols, esters and aldehydes having a greater contribution to secondary aroma (Padilla, Gil, and Manzanares 2016; Ebeler and Thorngate 2009). However, the balance and interaction of all of these chemical compounds determine the wine flavor quality. The biosynthesis of these compounds is also depending on species and strains of microorganism present in winemaking. Therefore, in order to isolate and identify novel wild yeast strains for applications in winemaking, it is critical to analyze core volatile and non-volatile metabolites of individual strains.

Chambourcin (cross between Joannès Seyve and Seibel 5455) is a French-

American hybrid grape varietal and is the most abundant hybrid grape grown in

Pennsylvania, USA. Hybrid grape varieties or also known as interspecific varieties have been of recent interest due to their versatile characteristics related to the ability to tolerate extreme cold weathers and disease resistance (Jones 2012). For example, Chambourcin can tolerant cold temperature at -25°C and grey rot caused by Botrytis cinerrea. Another example, Marquette (cross between two other hybrids, MN 1094 and Ravat 262) is resistant to downy mildew and cold temperature at -34°C (Pedneault and Provost 2016). The wine

33 industry in the State of Pennsylvania makes $ 2.5 billion annually in economic impact from

300 wineries across the State. Pennsylvania is ranked fifth for wine production (General

Industry Stats 2019; Pennsylvania Winery Association 2020). The overall objective of this study is to investigate fermentative capacity of isolated wild yeasts on Chambourcin harvested from vineyards in Pennsylvania. This is important because wild yeast isolated from Chambourcin with potential use in winemaking may enhance regional characteristics of Chambourcin wine and potentially increase standards of hybrid wines. To achieve our goal, we used culture-based methods and chemical analysis to characterize five candidate wild yeast isolates for potential use in winemaking. Two wild yeast strains, Hanseniaspora opuntiae NV192404 and Pichia kudriavzevii SM192402 demonstrated relatively high tolerance to ethanol as well as the ability to produce volatile metabolites associated with flowery and fruity aroma. This study provides an exciting first step to incorporate wild yeasts within winemaking of hybrid grapes to enhance regional characteristics and quality of hybrid grapes.

3.2. Materials and Methods

3.2.1. Grape sampling and juice collection

Chambourcin grapes were obtained from three regional vineyards in Pennsylvania,

USA. Grapes were collected and refrigerated at 4℃ until further processing (not more than

72 hours). One hundred and fifty grams of grape berries were crushed to produce must and allowed to ferment in a 1000-mL sterile beaker covered with aluminum foil at 25℃ for 24 hours.

3.2.2. Growth media and fungal isolation

Fungal isolation was conducted as outlined in Raymond Eder et al. (2017) and

Vaudano et al. (2019) with minor modifications related to type of selective agar and sampling timepoint (see Figure 3-1 (A)). To isolate grape-associated fungal populations, appropriate dilutions (10 ~ 10 dilutions) of fermented Chambourcin must at 0 and 24 hours were plated on Dichloran Rose Bengal Chloramphenicol (DRBC) agar based on manufacturer’s instructions (Difco, Sparks, MD). DRBC agar is recommended for the enumeration and selection of yeasts and molds in food and dietary supplements. It contains peptone as a source of carbon and nitrogen, dextrose as a sugar source, and magnesium sulfate to provide trace elements (SMITH and DAWSON 1944). Chloramphenicol is added to inhibit bacterial growth resulting in better recovery of fungal cells, and rose bengal is added to increase the selectivity of wild yeast by suppression of rapidly growing molds such as Neurospora and Rhizopus spp. (Salfinger and Tortorello 2013). Dichloran is added to inhibit the spreading of molds by reducing colony diameters (Henson 1981). Culture plates were incubated at 25℃ for 5 days. Twenty colonies were selected based on unique colony morphology observed from 0 and 24 h samples across all three regional wineries.

Five milliliter enrichments were prepared for individual isolates using liquid YPD medium

(1% yeast extract (Difco, Sparks, MD), 2% peptone (Difco, Sparks, MD) and 2% dextrose

(VWR International, Radnor, PA)), and grown at 25℃ for 24 hours with shaking at 200 rpm (standard laboratory conditions). Yeast Peptone Dextrose (YPD) is a complete medium used for cultivation of a wide range of yeasts, including Saccharomyces cerevisiae

(Frederick M. Ausubel et al. 1990). Four milliliters of enrichment culture (YPD + single colony yeast isolate grown for 24 h) was centrifuged at 3000 x g for 3 minutes, supernatant

35 discarded, and cell pellets were kept frozen at -80 ℃ until further used. Remaining enrichment cultures were stored at -80℃ as a yeast cryo-stock supplemented with 30%

(v/v) glycerol and deposited into our laboratory’s culture collection. Saccharomyces cerevisiae BY4742 [ATCC 4040004, YVC1] was used as a reference strain, grown in liquid YPD medium under standard laboratory conditions, and stored with 30% (v/v) glycerol at -80℃.

(A) Fungal (B) Molecular PCR Cell pellet DNA extraction Isolation Identification amplification

Fresh Chambourcin Sanger NCBI BLAST MUSCLE Phylogenetic grape must sequencing alignment analysis

Spontaneous High-throughput (C) Tolerance Yeast Cell wash Inoculate analysis by fermentation assays culture & dilution to subtracts micro-plate reader

Selective media (D) Lab Scale Yeast Cell wash Lab scale Fermentation culture & dilution fermentation

Culture enrichment (E) Chemical Fermented Analysis of GC-MS system analysis juice non-volatiles

Cryo-stocks Analysis of UHPLC-RI volatiles system

Figure 3-1. Microbial and chemical analyses used for characterization of wild yeast for potential use in winemaking.

Brief procedures of each experiment were framed in the rectangular panel. The arrow indicating the process of protocol. Methods include (A) fungal isolation; (B) molecular

36 identification; (C) tolerance assays; (D) laboratory scale fermentation; and (E) chemical analysis.

3.2.3. Molecular identification of fungal isolates

A total of 120 isolated strains were identified by analysis of the ribosomal internal transcribed spacer (ITS) region (ITS1-5.8S-ITS2) from three regional vineyards (see

Figure 3-1 (B)) (Schoch et al. 2012)). Genomic DNA were extracted from frozen cell pellets using a MasterPure Yeast DNA Purification Kit based on manufacturer’s instructions (Lucigen, Middleton, WI). For isolates which resemble filamentous fungi characterized by aerial mycelium growth, isolates were rinsed with 0.1M MgCl and re- centrifuged to obtain dry cell tissue for cell lysis and precipitation of DNA. Genomic DNA for colonies with yeast-like morphologies were extracted based on manufacturers’ instructions.

The ITS region was amplified by PCR using the universal primers, ITS1 (5’- TCC

GTA GGT GAA CCT GCG G-3’) and ITS4 (5’-TCC TCC GCT TAT TGA TAT GC-3’).

PCR was carried out in a final volume of 25 μL, containing 12.5 μL of PCR Master Mix

5Prime HotMasterMix (Quantabio, Beverly, MA), 1.25 μL of 10 nM forward primer and

1.25 μL of 10 nM reverse primer, and 10 μL of template DNA (10 ng/μL). PCR cycles were as follows: initial denaturation at 93 °C for 3 min and 35 cycles of denaturation at 93

°C for 30 s, annealing at 52 °C for 30 s, extension at 72 °C for 1 min, with a final extension at 72 °C for 10 min. PCR amplicons were separated on 1.5% agarose gel in 1 x TAE buffer, stained with SYBR Safe DNA gel stain (Invitrogen, Thermo Fisher Scientific, MA) and visualized using UV transillumination. PCR products were purified using the QIAquick

PCR purification Kit (Qiagen, Hilden, Germany). Sanger sequencing was performed using

ITS4 primers mentioned above at The Pennsylvania State University’s HUCK Institutes of

Life Sciences (University Park, PA) on an Applied Biosystems 3730XL DNA Analyzer

(Applied Biosystems, Foster City, CA).

ITS sequences obtained from Sanger sequencing were subjected to visual quality assessment on DNA sequencing chromatogram, and then queried using BLAST

(https://blast.ncbi.nlm.nih.gov/Blast.cgi) as outlined in Brysch-Herzberg and Seidel (2015) and Raymond Eder et al. (2017) with minor modifications on criteria of alignment score for molecular identification. The species of reference strain was assigned to an isolate when an identity score of ≥ 99%. Identity scores lower than 99% were assigned a genus. For isolates that had multiple possible genus and species identification from the National

Center for Biotechnology Information (NCBI) database, MycoBank

(http://www.mycobank.org/; Crous et al. 2004) was used for fungal synonyms searching and UNITE (https://unite.ut.ee/) was used for similarity searches against additional fungal databases to increase identification for that particular fungal isolate. Phylogenetic analysis was conducted using the Molecular Evolutionary Genetics Analysis (MEGA) software

(Kumar et al. 2018; Stecher, Tamura, and Kumar 2020). ITS sequences were aligned with

Multiple Sequence Comparison by Log-Expectation (MUSCLE) and phylogenetic tree was constructed using the Maximum Likelihood (ML) method supported by 500 bootstrap replications (Edgar 2004; Buehler et al. 2017).

3.2.4. Physiological characterization of non-Saccharomyces yeasts

3.2.4.1.Tolerance assays

Candidate wild yeasts for downstream characterization experiments were selected based on results obtained from sequencing analysis and the absence of toxin production based on previously published studies. For example, strains with highest statistical confidence based on BLAST results, de novo sequences alignment, and phylogenetic analysis were selected as candidate strains. Wild yeasts Hanseniaspora uvarum

NV192410, H. opuntiae NV192404, Pichia kluyveri NV192402, P. kudriavzevii

SM192402, and Aureobasidium pullulans SM190002 isolated from spontaneously fermenting Chambourcin must were chosen for downstream analysis. Saccharomyces cerevisiae BY4742 was used as a laboratory control.

Candidate wild yeast strains were grown under varying concentrations of sulfite and ethanol using a microplate-based method described by Tofalo et al. (2012) and

Englezos et al. (2015) with minor modifications related to the concentrations of substrate

(see Figure 3-1 (C)). For characterization of sulfite tolerance, yeast strains were grown in liquid YPD media with final concentrations of 0, 40, 60, 80, 100 mg/L sodium metabisulfite (VWR International, Radnor, PA) after adjustment of media to pH=3.0 for measuring sulfite tolerance. For characterization of ethanol tolerance, yeast strains were grown in liquid YPD media containing 0, 8, 10, 12, and 14% (v/v) ethanol (Decon Labs,

King of Prussia, PA). Varying ethanol concentrations were chosen to represent 12-14% ethanol typically present in red wines.

Five candidate strains and one control strain BY4742 were streaked on YPD agar

(1.5% Bacto Agar) (Difco, Sparks, MD) to obtain single colonies which were transferred

39 to 5 mL of liquid YPD media, and allowed to grow for 24 hours at 25℃ with shaking (200 rpm). Cell pellets were collected by centrifugation at 4000 x g for 5 minutes and washed twice with sterile phosphate-buffered saline (PBS) and resuspended in fresh liquid YPD media to obtain a starting optical density (OD) of 0.2 at 600 nm. A starting OD600 of 0.2 is approximately equal to a cell density of 10~10 cfu/mL. The resulting yeast culture (20

μL) was added to 180 μL liquid YPD media supplemented with varying concentrations of sodium metabisulfite or ethanol described above. The microplate-based assay was conducted at 25 ℃ and OD600 was measured every 30 minutes after orbital shaking for 10 seconds using the continuous measurement mode on a microplate reader for 48 hours

(BioTek Instruments, Winooski, VT). To determine ethanol and sulfite tolerance of these isolates, the ratio (%) between growth of the isolate in YPD media with and without sodium metabisulfite or ethanol at the end of incubation time (t = 48 h) was calculated using the following equation:

��ℎ �� (�� ) ��ℎ �� (%) = × 100% ��ℎ �� (��)

Isolates with a percentage growth ratio of larger than 10% were considered tolerant

(Englezos et al. 2015). Each experiment (sulfite and ethanol tolerance) were performed in three biological experiments with triplicate samples for each experimental condition.

3.2.4.2.Laboratory scale fermentation

Fresh Chambourcin grapes were obtained from three regional vineyards as previously described. Grape must was crushed in the lab. Juice was centrifuged and filter-

40 sterilized through a 0.2 μm membrane filter (VWR International, Radnor, PA) and stored at -20℃ until used. For the remaining of this thesis, we use the term “sterile juice” to represent filter sterile Chambourcin juice. Five wild yeast strains and control S. cerevisiae

BY4742 were inoculated into sterile juice (pH=3.26) for laboratory scale fermentation.

Inoculated fermentation of sterile juice has been previous established (Capece et al. 2013;

Lemos Junior et al. 2019). We use the term “inoculated fermentations” to represent filtered sterile juice inoculated with candidate wild yeast strains or control S. cerevisiae. Yeast cultures were prepared from enriched 5 mL of liquid YPD media with a single colony. Cell pellets were washed with PBS resuspended in fresh liquid YPD media to obtain a starting optical density (OD) of 0.2 at 600 nm with same procedure as for the tolerance test.

Laboratory scale fermentations were carried out starting OD600 = 0.2

(10~10 cfu/mL) inoculated to 50 mL sterile juice in 250-mL glass Erlenmeyer flask fitted with an airlock closure to enable carbon dioxide release (see Figure 3-1 (D)).

Inoculated fermentations were performed at 25℃ in static condition, and fermentation was monitored by measuring weight loss due to carbon dioxide release as previously describe

(Capece et al. 2013; Lemos Junior et al. 2019; Maturano et al. 2019). Fermentation was considered complete when weight loss of each sample was lower than 0.05 g in 24 hours as outlined in (Lemos Junior et al. 2019). The resulting fermented juice was collected at the end of fermentation for analysis of volatile and non-volatile compounds (see Figure 3-

1 (E)). All experiments were performed with experimental triplicates and one biological experiments.

3.2.5. Analysis of flavor compounds of fermented Chambourcin juice

3.2.5.1.Optimization of Ultra High-Performance Liquid Chromatography (UHPLC)

protocol

Nine core non-volatile compounds associated with wine were analyzed using Ultra

High-Performance Liquid Chromatography (UHPLC). On the initial trail, the conditions of analysis provided by Bio-Rad Laboratories (Hercules, CA) along with the Aminex HPX-

87H column were tested on Agilent 1100 High Performance Liquid Chromatography

(HPLC) system (Agilent Technologies, Santa Clara, CA): flow 0.6 mL/min, eluent 5mM sulfuric acid and column temperature at 50℃. Under these conditions, the chromatogram showed the unsuccessful separation of malic acid between glucose peak (RT= 12.5 mins) and fructose peak (RT=18.6 mins) and worse separation of citric acid (RT= 11.2 mins) and tartaric acid (RT= 11.9 mins) (Figure 3-2 (A)). Thus, we upgraded to Ultra High-

Performance Liquid Chromatography (UHPLC) system (Vanquish UHPLC Systems,

Thermo Fisher Scientific, Waltham, MA), and also found that by increasing the temperature of column chamber can successfully separate the peak of malic acid and make the shape of the peaks appeared more symmetrically (Figure 3-2 (B)), which was accordant with the result before (Blake, Clarke, and Richards 1987).

3 5

9 2 7 1 6 8

B 3 5

1 9 2 4 7 6 8

FigureFigure 3-2. Chromatogram3-1. Chromatogram of a standard mixtureof a injectedstandard throughmixture Aminexinjected HPX- through Aminex HPX-87H (300 x 7.8 mm) columns on Agilent 87H 1100(300 x HPLC7.8 mm) (A)columnsand onThermo (A) AgilentVanquish 1100 HPLCUHPLC and (B)(B) Thermosystem Vanquish. UHPLC10 µlsystem.of each compound in concentrations typical of a range of wines and grape musts. Conditions: decreased flow rate from 0.6 ml/min 10 μL(A) of eachto 0 .compound5 ml/min in(B) concentrations, increased typicalcolumn of a temperaturerange of wines fromand grape50℃ musts.(A) to 60℃ (B); eluent 5mM sulfuric acid and detection, refractive index. Conditions: decreased flow rate from (A) 0.6 mL/min to (B) 0.5 mL/min, increased column temperaturePeaks :from1, citric(A) 50℃acid to (;B2) ,60tartaric℃; eluentacid 5mM; sulfuric3, glucose acid ;and4, detection,malic acid refractive(not separated); 5, fructose; 6, succinic acid; 7, glycerol; 8, acetic acid; index.and 9, ethanol. X-axis: retention time (min) and Y-axis: RI detector Peaks:response 1, citric acid;(mAU 2, tartaric; RIU) acid;. 3, glucose; 4, malic acid; 5, fructose; 6, succinic acid;

7, glycerol; 8, acetic acid; and 9, ethanol. X-axis: retention time (min) and Y-axis: RI detector response (mAU; RIU).

3.2.5.2.Analysis of non-volatile compounds by UHPLC

To analyze non-volatile compounds, juice and samples of inoculated fermentations were filtered through a 0.2 μm membrane filter. Nine non-volatile compound standards and mobile phase were prepared including glucose (99%, Acros Organics, Thermo Fisher

Scientific, Waltham, MA), fructose (99%, Alfa Aesar, Haverhill, MA), glacial acetic acid

(VWR International, Radnor, PA), tartaric acid (99%, TCI America, Portland, OR), citric acid (99.5%, VWR International, Radnor, PA), malic acid (99%, Acros Organics, Thermo

Fisher Scientific, Waltham, MA), succinic acid (99%, Acros Organics, Thermo Fisher

Scientific, Waltham, MA), glycerol (VWR International, Radnor, PA), ethanol (Decon

Labs, King of Prussia, PA) and sulfuric acid (Sigma-Aldrich, St. Louis, MO) were purchased. Standards and mobile phase were dissolved in deionized water to a desired concentration and filtered through 0.2 μm and 0.45 μm membrane filters, respectively.

Standards were prepared according to previously published concentration of compounds in the juice or wine. Five concentrations of each compound were made by a two-fold serial dilution to construct a standard curve. The highest concentration of each compound was glucose and fructose: 40 g/L; glacial acetic acid: 0.8 g/L, tartaric acid: 8 g/L, citric acid: 2 g/L, malic acid: 6 g/L, succinic acid: 2 g/L, glycerol 6 g/L, and ethanol: 7% (v/v). Serial dilution standards were injected to construct a standards curve and the retention time (RT) of each compound was recorded and validated. Equations of each standard curve had �=1

(Table 3-1).

Chromatographic separations were performed on an Ultra High-Performance

Liquid Chromatography (UHPLC) system (Vanquish UHPLC Systems, Thermo Fisher

Scientific, Waltham, MA) equipped with a refractive index (RI) detector (RefractoMax

521, Thermo Fisher Scientific, Waltham, MA). Targeted compounds were separated and analyzed on an Aminex HPX-87H column (300 x 7.8 mm) (Bio-Rad Laboratories,

Hercules, CA), protected by a Micro-Guard Cation H guard column (30 x 4.6 mm) (Bio-

Rad Laboratories, Hercules, CA) and kept at 60℃. The analytical conditions used were as follows: 10 μL of injection volume, flow 0.5 mL/min, eluent 5mM ��. Temperature set for autosampler and RI detector were 4℃ and 35℃, respectively. A standard curve was prepared using standards to determine the relationship between concentration and the peak area of particular compound eluted. The chromatographic peak corresponding to each compound was identified by comparing the retention time with that of standards. All standards and samples were injected in triplicate.

Table 3-1. Retention time (RT) and the standard curve of the standard compounds.

RT Standard Compounds Standard curve (R-square*) (mins) deviation of RT Citric acid 9.38 0.016 � = 367.191� + 2.121 (� = 1) Tartaric acid 9.90 0.033 � = 140.977� + 5.08 (� = 1) Glucose 10.59 0.011 � = 172.025� + 35.452 (� = 1) Malic acid 11.08 0.014 � = 121.0� + 5.237 (� = 1) Fructose 11.45 0.010 � = 172.951� + 26.779 (� = 1) Succinic acid 13.54 0.005 � = 333.161� + 4.002 (� = 1) Glycerol 15.85 0.004 � = 146.083� + 1.897 (� = 1) Acetic acid 17.77 0.000 � = 79.053� + 0.078 (� = 1) Ethanol 26.40 0.054 � = 530.774� + 17.321 (� = 1) R-square* is the correlation coefficient of response in a regression model.

3.2.5.3.Analysis of volatile compounds by Gas Chromatography Mass Spectrometry

Aromatic compounds were analyzed by gas chromatography-mass spectrometry

(GC-MS) system (7890B System, 5977B MSD, Agilent Technologies, Santa Clara, CA) using the method described by (Pedneault, Dorais, and Angers 2013) with minor modifications. 2-mL of samples were added to 3g sodium chloride (VWR International,

Radnor, PA), 50 μL internal standard ( including 13.7 mg/L 2-octanol and 9.9 mg/L naphthalene-d8 in methanol), and 0.5g D-gluconic acid lactone (Sigma-Aldrich, St. Louis,

MO), which inhibits grape �-glucosidase activity during sample preparation and analysis

(Fenoll et al. 2009). Samples were then vortexed and analyzed immediately. All experiments were performed in triplicate.

Solid-phase microextraction (SPME) mixture comprised heptanal (0.452 g/L), octanal (0.484 g/L), nonanal (0.477 g/L), 1-decanol (0.394 g/L), 1-undecanol (0.392 g/L),

1-dodecanol (0.521 g/L), n-decane (0.451 g/L), n-dodecane (0.481 g/L), n-tetradecane

(0.497 g/L), L-methanol (0.511 g/L), (-)-trans- and (-)-cis-carveol (0.778 g/L), (+)-carvone

(0.584 g/L), a-pinene (0.553 g/L), b-pinene (0.472 g/L), and p-cymene (0.424 g/L) in acetone. 50μL of internal standard as a blank and 10μL of SPME mixture as a quality control were used and placed in the first and last order of each batch of samples, respectively. Performance test of GC-system was carried by the mixture of 5-μL alkane standard solution (� − �, ~40 mg/L each in hexane; Sigma-Aldrich, St. Louis, MO) and

50-μL internal standard.

Samples were incubated at 30 ℃ for 5 minutes under agitation at 250 rpm, and then extracted using a 2 cm Divinylbenzene/Carboxen/Polydimethylsiloxane

(DVB/CAR/PDMS) SPME fiber assembly (Sigma-Aldrich, St. Louis, MO) for 30 minutes.

Separation was carried out with a Rtx-Wax capillary column (25 m × 0.25 mm I.D. × 0.25

μm film thickness; Restek Corporation, Bellefonte, PA) in splitless mode. The transfer line and ion source (70 eV) were maintained at 250 and 230 ℃, respectively. The oven temperature was programmed as follows: hold at 30 ℃ for 1 minute; increase to 250 ℃ at rate of 10 ℃/min and hold for 5 minutes. Helium was used as the carrier gas under constant flow at 1 mL/min. Mass spectra were acquired at a rate of 33 – 350 amu scan.

To identify fermentation associated volatile compounds, chromatograms were stripped of common contaminating ions (147, 148, 149, 207, 221, 267, and 281 m/z) using the Denoising function in OpenChrom followed by the Savitzky-Golay smoothing filter with default settings (width = 15; order = 2) to enhance chromatographic data by reducing noise while maintaining the shape and height of waveform peaks (Bromba and Ziegler

1981; Wenig and Odermatt 2010; Schafer 2011). The PARAFAC2 based Deconvolution and Identification System (PARADISe) computer platform (version 3.9) was used to deconvolute mass spectra with 7,000 iterations and non-negativity constraint settings

(Johnsen et al. 2017). Retention time intervals were manually selected to increase the resolution of peak identification. Identification based on deconvoluted mass spectra were conducted using the National Institute of Standards and Technology (NIST14) mass spectral library with criteria of match factor over 700, and validated with Kovats retention indices referred to NIST14 library, PubChem (https://pubchem.ncbi.nlm.nih.gov/) or literature. Relative concentration of volatile compounds was calculated by dividing the peak area of volatile compounds by the peak area of internal standards (IS) and then subtracted by its relative abundance in the blank.

3.2.6. Statistical Analysis

One-way analysis of variance (ANOVA) was carried out for analysis of optical density (OD600) from the tolerance assays and quantification of non-volatile compounds from UHPLC analysis. Significant differences were established by using the Tukey post- hoc test (p < 0.05) comparing the mean values of control and treatment groups. IBM®

SPSS® Statistic software version 26 (Field 2013) was used for above statistical analysis.

Principal component analysis (PCA) using MetaboAnalyst was carried out for the differentiation of non-volatile and volatile compounds in the samples of inoculated fermentations (Chong, Wishart, and Xia 2019). Input data for PCA was normalized using log transformation and Pareto scaling function for removing heteroskedasticity and making date normally distributed (van den Berg et al. 2006). ANOVA was used to identify significant differences of relative abundance of volatile compounds across laboratory scale fermentation conducted by candidate yeast strains using False Discovery Rate (FDR) adjusted p-value (or q-value) of 0.05.

3.3. Results

3.3.1. Isolation and identification of fungal diversity on spontaneous fermentation of

Chambourcin grape must

One hundred and twenty fungal isolates were identified from spontaneous laboratory scale fermentation of Chambourcin grape collected from three PA wineries during the 2019 vintage (see Figure 3-3 for sampling map). Based on selection criteria characterized by colony morphology (see Materials and Methods), 40 unique isolates were identified from each location by culture-dependent methods and Sanger sequencing. All

(120) isolates belonged to 29 fungal species with Hanseniaspora spp., Pichia spp. being the major genus followed by specific species, including Sporidiobolus pararoseus,

Starmerella bacillaris and Aureobasidium pullulans identified from Chambourcin grape must (Table 3-2). Hanseniaspora species, including H. uvarum, H. meyeri, and H. opuntiae were the most abundant species (i.e., 41.5%). Pichia species, including P. fermentans, P. kluyveri, P. kudriavzevii, and P. terricola, were the second abundant species

(i.e., 10.8%), as well as S. pararoseus. Additionally, S. bacillaris, with 9% of relative abundance, was ranked third of the frequent identified yeast species. Aureobasidium pullulans and Filobasidium floriforme were identified with equal relative abundance (i.e.,

5%). Overall, PAV1 possessed higher diversity of fungal populations belonging to 17 fungal species comparing with PAV2 and PAV3 with 11 and 12 identified fungal species, respectively.

PAV2 PAV3

PAV1

Figure 3-3. Sampling of Chambourcin grapes for fungal isolation. Figure 3-3. Sampling of Chambourcin in local Pennsylvania Fresh Chambourcin(PA) vineyards grapes were collected from 3 vineyards in local Pennsylvania, PAV1, Fresh Chambourcin grapes were collected from 3 vineyards in PAV2 andlocal PAV3,Pennsylvania, showed in thePAV map1, .PAV 2 and PAV3, showed in the map,

Other yeast species isolated and identified from spontaneous fermentation include

Candida spp., Meyerozyma carpophila, Kregervanrija sp. and Papiliotrema sp. Candida species (i.e., 3.2%), including C. californica and C. railenensis. Candida californica was identified only from PAV3. One strain of Kregervanrija sp. and Papiliotrema sp. found in

PAV1 and PAV2, respectively (Table 3-2).

Compared to the abundance of yeast species present on grape berries, filamentous fungi were less dominant and less consistent across vineyards demonstrated by the culture- based methods. Leptosphaerulina chartarum was the only species found across vineyards at PAV1 and PAV2 with 2.5% of relative abundance. Other examples of filamentous fungi identified within individual vineyard at (i.e., 0.8%), include Alternaria alternata,

Cladosporium spp., Epicoccum sorghinum, Fusarium sp., Mucor nidicola,

Neopestalotiopsis clavispora, Penicillium brevicompactum, P. spinulosum and

Pestalotiopsis vismiae (Table 3-2).

Table 3-2. Species identified from spontaneously fermenting Chambourcin grapes isolated from three Pennsylvania vineyards at 0 and 24 h combined by number of species and relative abundance (%).

Number of species and relative abundance (%) Genus Species Total PAV1 PAV2 PAV3

Hanseniaspora Hanseniaspora sp. 0 1 (2.5%) 1 (2.5%) 2 (1.6%)

H. meyeri 7 (17.5%) 0 0 7 (5.8%)

H. opuntiae 2 (5%) 0 0 2 (1.6%)

H. uvarum 5 (12.5%) 14 (35%) 20 (50%) 39 (32.5%)

Pichia Pichia sp. 1 (2.5%) 0 1 (2.5%) 1 (0.8%)

P. fermentans 0 0 1 (2.5%) 1 (0.8%)

P. kluyveri 2 (5%) 0 4 (10%) 6 (5%)

P. kudriavzevii 0 1 (2.5%) 0 1 (0.8%)

P. terricola 4 (10%) 0 0 4 (3.3%) Yeasts Sporidiobolus S. pararoseus 5 (12.5%) 7 (17.5%) 1 (2.5%) 13 (10.8%)

Starmerella S. bacillaris 2 (5%) 4 (10%) 5 (12.5%) 11 (9.2%)

Aureobasidium A. pullulans 0 6 (15%) 0 6 (5%)

Filobasidium F. floriforme 4 (10%) 2 (5%) 0 6 (5%)

Candida C. californica 0 0 2 (5%) 2 (1.6%)

C. railenensis 0 0 2 (5%) 2 (1.6%)

Meyerozyma M. carpophila 1 (2.5%) 0 0 1 (0.8%)

Kregervanrija Kregervanrija sp. 1 (2.5%) 0 0 1 (0.8%)

Papiliotrema Papiliotrema sp. 0 1 (2.5%) 0 1 (0.8%)

Leptosphaerulina L. chartarum 1 (2.5%) 2 (5%) 0 3 (2.5%)

Alternaria A. alternata 1 (2.5%) 0 0 1 (0.8%)

Cladosporium C. angustisporum 1 (2.5%) 0 0 1 (0.8%)

C. cladosporioides 0 0 1 (2.5%) 1 (0.8%)

Epicoccum E. sorghinum 1 (2.5%) 0 0 1 (0.8%)

Fusarium Fusarium sp. 0 1 (2.5%) 0 1 (0.8%)

Mucor M. nidicola 0 1 (2.5%) 0 1 (0.8%) Filamentous Fungi Filamentous Neopestalotiopsis N. clavispora 1 (2.5%) 0 0 1 (0.8%)

Penicillium P. brevicompactum 0 0 1 (2.5%) 1 (0.8%)

P. spinulosum 0 0 1 (2.5%) 1 (0.8%)

Pestalotiopsis P. vismiae 1 (2.5%) 0 0 1 (0.8%)

The differences of fungal distribution in three PA vineyards were shown in Figure

3-4 (A). In PAV1, fungal composition was most diverse highlighted by not only

Hanseniaspora spp. and Pichia spp., but also the filamentous fungi. Six species of filamentous fungi discovered were almost double the number of filamentous fungal species found in the other two vineyards. PAV2 and PAV3 had similar level of fungal diversity.

Hanseniaspora uvarum, S. pararoseus, and A. pullulans were the most dominant in PAV2; and H. uvarum accounted for 50% of isolated strains from PAV3; and Pichia spp., S. bacillaris and Candida spp. were the minor members of the fungal community.

After 24 hours of spontaneous fermentation, decreased fungal diversity in

Chambourcin must was observed and filamentous fungi were not identified in all

vineyards. Hanseniaspora spp. and Pichia spp. became the major species by 24 hours in

PAV1, and Hanseniaspora spp. and S. bacillaris were major species by 24 hours in PAV2

and PAV3 (Figure 3-4 (B)).

(A) 100% Hanseniaspora uvarum

Hanseniaspora meyeri Hanseniaspora uvarum 20 90% Hanseniaspora opuntiae

80% Hanseniaspora sp. Hanseniaspora meyeri 18 Starmerella bacillaris 70% Sporidiobolus pararoseus Hanseniaspora opuntiae 16 60% Pichia kluyveri

Pichia kudriavzevii Hanseniaspora sp.

14 50% Pichia terricola Starmerella bacillaris 40% Pichia fermentans Pichia sp. 12 Sporidiobolus pararoseus 30% Candida railenensis

Candida californica 20% Pichia kluyveri 10 abundance (%) Relative Aureobasidium pullulans

10% Filobasidium floriforme Pichia kudriavzevii Isolated species (count) 8 Meyerozyma carpophila 0% Kregervanrija sp. PAV1 PAV2 PAV3 Pichia terricola Papiliotrema sp. 6 Sampling locations Filamentous Fungi Pichia fermentans Hanseniaspora (B) 20 4 uvarum Pichia sp. 18 Hanseniaspora 2 meyeri 16 CandidaHanseniaspora railenensis opuntiae 0 14 CandidaHanseniaspora californica sp. 0 hr 24 hr 0 hr 24 hr 0 hr 24 hr PAV1 12 PAV1 PAV2 PAV2 PAV3 PAV3 Starmerella Aureobasidiumbacillaris pullulans 10 Sporidiobolus Filobasidiumpararoseus floriforme Fermentation8 time (hour) and Sampling location Pichia kluyveri Meyerozyma carpophila 6 Pichia kudriavzevii

Isolated species (count) 4 KregervanrijaPichia terricola sp. 2 PapiliotremaPichia fermentans sp. 0 0 hr 24 hr 0 hr 24 hr 0 hr 24 hr FilamentousPichia sp. Fungi PAV1 PAV1 PAV2 PAV2 PAV3 PAV3 Candida railenensis Fermentation time (hour) and Sampling location Candida californica 53 Aureobasidium pullulans Figure 3-4. Main contributing fungal speciesFilobasidiumduring spontaneous fermentation of Chambourcin grape mustfloriforme. (A) Relative contribution (%) of the identified fungal species among 40 selected colonies obtained during spontaneous fermentation from each location isolated on DRBC agar plates. (B) Fungal species identified among 20 colonies on DRBC agar plates at the indicated times of fermentation. Decreasing fungal diversity was observed after 24 hours of spontaneous fermentation.

Figure 3-4. Main contributing fungal species during spontaneous fermentation of

Chambourcin grape must.

(A) Relative contribution (%) of the identified fungal species among 40 selected colonies obtained during spontaneous fermentation from each location isolated on DRBC agar plates. (B) Fungal species identified among 20 colonies on DRBC agar plates at the indicated times of fermentation. Decreasing fungal diversity was observed after 24 hours of spontaneous fermentation.

Genetic diversity of 120 isolated strains and S. cerevisiae BY4742 were separated into four main clades according to the alignment of their ITS region by phylogenetic analysis (Figure 3-5). All strains of Hanseniaspora species and S. bacillaris were placed in a cluster with a bootstrap support of 98% and 100%, respectively (Figure 3-6. (A)(B)).

Candida railenensis were clustered with Meyerozyma carpophila (basionym: Candida guilliermondii var. carpophila) supported by 89% bootstrap. All strains of Pichia species were placed in one cluster with a lower bootstrap support of 57% including Candida californica, which belongs to Pichia/Candida clade in taxonomy. The lower bootstrap support most likely indicated the high level of heterogeneity of the ITS region within

Pichia species we isolated. From NCBI BLAST results, isolate HV192401 was assigned to P. fermentans (GenBank: KM402063.1) with 99.01% identity, and to P. kluyveri

(GenBank: KY611839.1) with 98.76% identity; meanwhile, isolate HV190004 was assigned to P. kluyveri (GenBank: MF574304.1 and KY104557.1) and P. fermentans

(GenBank: KM402064.1) with the same statistical value of 100% identity, 717 of Max. and Total score. Even though we observed the limitation of exclusively using ITS

54 barcoding to identify species, strains of P. kluyveri and P. fermentans were clustered with a 94% bootstrap support. Pestalotiopsis vismiae and Neopestalotiopsis clavispora were clustered with a bootstrap support of 99% as Neopestalotiopsis is a novel genus segregated from Pestalotiopsis based on morphological and DNA data (S. S.N. Maharachchikumbura et al. 2014). Multiple strains sharing same genus were clustered with a bootstrap support of 100% including Leptosphaerulina, Aureobasidium, Filobasidium, Sporidiobolus

(Figure 3-6 and 3-7), and Cladosporium, Penicillium.

Candidate yeast strains for physicochemical characterization and downstream laboratory scale fermentation were selected based on information obtained from NCBI

BLAST, phylogenetic analysis, and previous literature (for example, absence of toxin production). Previous literature suggests that Hanseniaspora spp. and Pichia spp. have the capacity to ferment fruit with no evidence of toxin production where as Aureobasidium pullulans is well known for the production of extracellular enzymes such as pectinases

(Manachini, Parini, and Fortina 1988). Based on identity scores obtained from NCBI

BLAST, H. uvarum NV192410, H. opuntiae NV192404, P. kluyveri NV192402, P. kudriavzevii SM192402, and A. pullulans SM190002 were selected for Aims 2 and Aim 3

(Table 3-3).

Hanseniaspora spp.

8E8H8CEE6

1MHFNM88HFC826 0HH8EHA826

Stamerella bacillaris 488HFMH875 76

38BCKMH6

38BCKMH26 38BCKMH26

386

38BCKMH6

38HE8E6 38BCKMH6

3826

38BKH8N41

Candida californica 38HHFC826

38HHFC826 38HHFC826

3826

Leptosphaerulina chartarum

CHE8H88CHE826

FKFHEK26

38CFF826

2F8CFFC8FH826

.K8HK41

C8FFHK8EKFHK26

C8FFHKC8FFHF6

3ECCKEKCFK6 3ECCK9HF8K6

Aureobasidium pullulans

38CFH841

Filobasidium floriforme

1KFHEFC841

Sporidiobolus pararoseus

0.10

Figure 3-5. Phylogenetic tree constructed with ribosomal internal transcribed spacer

(ITS) regions and 5.8S rRNA gene sequences of 120 isolated fungal strains.

Phylogenetic analysis was inferred by using the Maximum Likelihood method and General

Time Reversible model. The bootstrap consensus tree inferred from 500 replicates was taken to represent the evolutionary history of the taxa analyzed. Branches corresponding to partitions reproduced in less than 50% bootstrap replicates were collapsed. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test were shown next to the branches. Evolutionary analyses were conducted in MEGA X.

Hanseniaspora clade was suppressed into black plaid triangle including all Hanseniaspora species clustered with 98% bootstrap support. Subtrees including same species supported by 100% bootstrap value were suppressed and represented as solid black triangle, including

Starmerella bacillaris, Candida californica, Leptosphaerulina chartarum, Aureobasidium pullulans, Filobasidium floriforme, and Sporidiobolus pararoseus strains.

(A) 3703175469692

3703175469692.

3703175469692

3703175469692.

3703175469692

3703175469692.

3703175469692

3703175469692.

37031754675

3703175469692.

3703175469692. 3703175469692. 3703175469692.

3703175469692.

3703175469692

3703175469692.

3703175469692. 37031754620061.

37031754620061.

3703175464593810.

3703175464593810. 37031754620061.

3703175469692.

3703175469692

3703175469692.

37031754675.

3703175469692. 3703175469692.

3703175469692. 3703175469692 3703175469692. 3703175469692.

0.010

(B) 6430402212241

6430402212241

6430402212241 6430402212241

6430402212241

0.0050 (C) 01

0.00000050 (D) 420341443

420341443

0.0010 (E) 015006214042

015006214042

0.0050

(F)

435113327455307

435113327455307 435113327455307

435113327455307

435113327455307 435113327455307

0.020

Figure 3-6. Phylogenetic subtrees of yeast strains supported with high bootstrap value constructed with ribosomal internal transcribed spacer (ITS) regions and 5.8S rRNA gene sequences.

Hanseniaspora species (A) with 98% bootstrap value, and Starmerella bacillaris (B),

Candida californica (C), Aureobasidium pullulans (D), Filobasidium floriforme (E) and

Sporidiobolus pararoseus (F) strains with 100% bootstrap value were the subtrees suppressed in the main phylogenetic tree of 120 isolated strains.

1031

0.010

Figure 3-7. Phylogenetic subtrees of filamentous fungi strains supported with high bootstrap value constructed with ribosomal internal transcribed spacer (ITS) regions and 5.8S rRNA gene sequences.

Leptosphaerulina chartarum strains with 100% bootstrap value were the subtrees suppressed in the main phylogenetic tree of 120 isolated strains.

Table 3-3. Candidate yeasts chosen for tolerance assay and laboratory scale fermentation.

Sample Identity Species GenBank Location ID (%) NV192410 Hanseniaspora uvarum 100 MN556596.1 NV192404 Hanseniaspora opuntiae 100 MN378465.1 PAV1 NV192402 Pichia kluyveri 99.75 KY580407.1 SM192402 Pichia kudriavzevii 99.75 MN710489.1 PAV2 SM190002 Aureobasidium pullulans 100 MT035961.1

3.3.2. Physiological characterization of non-Saccharomyces yeasts

3.3.2.1.Candidate Hanseniaspora strains tolerate lower sulfite concentration compared

with S. cerevisiae BY4742

There is a significant effect of pH level on the concentration of free sulfite. Sulfites are most effective as an antimicrobial agent in acidic conditions due to the effect from the molecular SO2 penetrating the cell wall and disrupting the enzymatic. Therefore, when sulfite tolerance examined in neutral YPD media (pH=6.5), the growth ratio of five candidate strains and S. cerevisiae BY4742 demonstrated the tolerance at 800mg/L sodium metabisulfite (Figure 3-8).

______ns ______ns a __a aab ab a ab__ a ab b b b bcc

__bc c

Figure 3-8. Sulfite tolerance of candidate wild yeast strains and S. cerevisiae BY4742 in neutral YPD media (pH=6.5).

Sulfite tolerance denoted by the height of bar graphs is defined as ratio greater than 10% between growth of a strain with and without a particular supplemented substrate in media.

Dotted line across the y-axis represents the 10% sulfite tolerance cutoff. The different types

62 of yeasts used in this study was represented on the x-axis. Data presented as mean ratio ±

SEM with a common superscript indicating significance (p<0.05). The laboratory strain S. cerevisiae BY4742 was used as a control.

After adjusting culture media to pH = 3, the growth of S. cerevisiae BY4742 was not observed at 200mg/L sodium metabisulfite (data not shown). Therefore, the concentrations of sulfites were decreased for better resolution on sulfite tolerance of candidate wild yeast strains. Except H. opuntiae NV192404, other candidate strains and S. cerevisiae BY4742 had tolerance at 100mg/L sodium metabisulfite. Hanseniaspora uvarum NV192410 and H. opuntiae NV192404 were relatively sensitive to sulfite with significant decreased growth ratio at 80-100mg/L of sodium metabisulfite (Figure 3-9).

Hanseniaspora uvarum NV192410 showed the delay of entering the stationary phase after

12 and 36 hours at 80 and 100mg/L of sodium metabisulfite, respectively. Hanseniaspora opuntiae NV192404 started showing the signs of stationary phase at 80mg/L of sodium metabisulfite after 48 hours and was not able to grow when the concentration increased to

100mg/L (Figure 3-10). The growth of P. kluyveri NV192402 and P. kudriavzevii

SM192402 was not significantly affected by high concentrations of sulfites reaching the stationary phase at similar timepoint and cell density (OD600) (Figure 3-11). Finally, A. pullulans SM190002 were able to grow at 100mg/L of sodium metabisulfite, but had a slow growth rate which is a different growth patter with S. cerevisiae BY4742 (Figure 3-

12). These results illustrated that P. kluyveri NV192402, P. kudriavzevii SM192402 and A. pullulans SM190002 could tolerant higher sulfite concentration during winemaking followed by H. uvarum NV192410 and H. opuntiae NV192404.

______ns ______ns ______ns ______ns ____a ____a ab c b b

Figure 3-9. Sulfite tolerance of candidate wild yeast strains and S. cerevisiae BY4742 in acidified YPD media (pH=3.0).

Sulfite tolerance denoted by the height of bar graphs is defined as ratio greater than 10% between growth of a strain with and without a particular supplemented substrate in media.

Dotted line across the y-axis represents the 10% sulfite tolerance cutoff. The different types of yeasts used in this study was represented on the x-axis. Data presented as mean ratio ±

SEM with a common superscript indicating significance (p<0.05). The laboratory strain S. cerevisiae BY4742 was used as a control.

Figure 3-10. Growth curves of H. uvarum NV192410 and H. opuntiae NV192404 at different concentrations of metabisulfite comparing with S. cerevisiae BY4742 control strain.

Growth curves were measured by OD600 at 25℃ for 48 hours. Each point corresponds to the average of three determinations ± SEM.

Figure 3-11. Growth curves of P. kluyveri NV192402 nd P. kudriavzevii SM192402 at different concentrations of metabisulfite comparing with S. cerevisiae BY4742 control strain.

Growth curves were measured by OD600 at 25℃ for 48 hours. Each point corresponds to the average of three determinations ± SEM.

Figure 3-12. Growth curves of A. pullulans SM190002 at different concentrations of metabisulfite comparing with S. cerevisiae BY4742 control strain.

Growth curves were measured by OD600 at 25℃ for 48 hours. Each point corresponds to the average of three determinations ± SEM.

3.3.2.2.Variable ethanol tolerance of candidate wild yeast strains

Five candidate wild yeasts demonstrated different ethanol tolerance which were generally lower than S. cerevisiae BY4742 control strain. Hanseniaspora uvarum

NV192410, H. opuntiae NV192404 and P. kluyveri NV192402 had tolerance at 8% of 66 ethanol; and A. pullulans SM190002 was not tolerant at any concentration of ethanol tested.

Interestingly, P. kudriavzevii SM192402 was the only wild yeast candidate having comparable tolerance with control S. cerevisiae BY4742 strain grown in 10% ethanol

(Figure 3-13). In general, the delay of entering the stationary phase represented the adaptability of yeast strains in the high ethanol environment. Hanseniaspora uvarum

NV192410 and H. opuntiae NV192404 were showing signs of stationary phase after 12 hours demonstrating the fast growth rate in pure liquid YPD media while 24 hours for S. cerevisiae BY4742. When growing in 8% ethanol, H. opuntiae NV192404 entered the stationary phase after 36 hours similar to S. cerevisiae BY4742 but with significant suppression of cell density (OD600) (Figure 3-14). However, P. kluyveri NV192402 and P. kudriavzevii SM192402 demonstrated the similar growth pattern with S. cerevisiae

BY4742 in pure liquid YPD media, but the signs of stationary phase in the presence of ethanol could not be observed within 48 hours (Figure 3-15). Growth of A. pullulans

SM190002 was suppressed in ethanol concentration above 8% (Figure 3-16). These results illustrated that H. opuntiae NV192404 and P. kudriavzevii SM192402 could adapt the high ethanol environment better than the other candidate wild yeasts during the alcoholic fermentation process.

a ___a _ a a a a b b

c b b __b __c_ b ___c ___c _ __d _____

Figure 3-13. Ethanol tolerance of selected non- Figure 3-13. Ethanol tolerance of candidate wild yeast strains and S. cerevisiae Saccharomyces strains and S. cerevisiae BY4742. BY4742Ethanol. tolerance denoted by the height of bar graphs is defined as ratio greater than 10% between growth of a strain with and Ethanol tolerance is denoted by the height of bar graphs is defined as ratio greater than without supplemented ethanol in media. Dotted line across the 10% ybetween-axis represents growth of a strainthe 10 with% andsulfite withouttolerance a particularcutoff supplemented. The different substrate in types of yeasts used in this study was represented on the x-axis. media. Dotted line across the y-axis represents the 10% sulfite tolerance cutoff. The Data presented as mean ratio ± SEM with a common superscript differentindicating types of yeastssignificance used in this study(p<0 .was05) represented. The laboratory on the x-axis. strainData presentedS. cerevisiae BY4742 was used as a control. as mean ratio ± SEM with a common superscript indicating significance (p<0.05). The laboratory strain S. cerevisiae BY4742 was used as a control.

Figure 3-14. Growth curves of H. uvarum NV192410 and H. opuntiae NV192404 at different concentrations of ethanol comparing with S. cerevisiae BY4742 control strain.

Growth curves were measured by OD600 at 25℃ for 48 hours. Each point corresponds to the average of three determinations ± SEM. Doted reference lines at 12 hours indicated the stationary growth of Hanseniaspora strains in 0% ethanol. Dashed reference lines at 24 and 36 hours indicated the stationary growth of S. cerevisiae BY4742 control strain in 0% and 8% ethanol.

Figure 3-15. Growth curves of P. kluyveri NV192402 and P. kudriavzevii SM192402 at different concentrations of ethanol comparing with S. cerevisiae BY4742 control strain.

Growth curves were measured by OD600 at 25℃ for 48 hours. Each point corresponds to the average of three determinations ± SEM. Reference lines at 24 and 36 hours indicated the stationary growth of S. cerevisiae BY4742 control strain in 0% and 8% ethanol.

Figure 3-16. Growth curves of A. pullulans SM190002 at different concentrations of ethanol comparing with S. cerevisiae BY4742 control strain.

3.3.2.3.Fermentation kinetics of candidate wild yeast strains in sterile Chambourcin juice

In this section of the study, our goal was to measure fermentation kinetics of candidate wild yeast strains in laboratory scale fermentation of sterile Chambourcin grape juice. Fermentation kinetics is defined as time required for completion of the fermentation process measured by weight reduction as a result of CO2 production which is a byproduct of alcoholic fermentation (Figure 3-17). Candidate wild yeasts performed different fermentation kinetics to control strain S. cerevisiae BY4742 which reached the end of fermentation with average 19 days (14 ~ 21 days with pH 3.35). Pichia kluyveri NV192402 completed fermentation faster with average 12 days (9 ~ 15 days) at final pH 3.35, and P. kudriavzevii SM192402 reached the end of fermentation with average 22 days (18 ~ 24 days with pH 3.47). For Hanseniaspora spp., H. uvarum NV192410 reached completion approximately 6 days (5 ~ 6 days with pH 3.40), and H. opuntiae NV192404 finished fermentation with 10 days (8 ~12 days with pH 3.46). Finally, A. pullulans SM190002 which took average 20 days (18 ~ 22 days with pH 3.08) to reach the end of fermentation with relatively slow fermentation kinetics with regard to the daily weight loss comparing to other wild yeast strains. These results showed that P. kudriavzevii SM192402 demonstrated the most similar fermentation kinetics with baseline by S. cerevisiae

BY4742, and thus was expected to convert sugars to ethanol similarly with S. cerevisiae

BY4742.

Figure 3-17. Fermentation kinetics of candidate wild yeast strains and S. cerevisiae

BY4742 in sterile juice represented by weight reduction (%) over time (day).

Weight of the fermentation set was measured every day. The weight reduction (%) indicated the production of gas which is the byproduct of alcoholic fermentation. End of fermentation for each yeast species was represented by the earliest timepoint whichever replicate reached the end of fermentation process. Each point corresponds to the average weight reduction from three technical flasks (mean values ± SEM).

3.3.3. Chemical composition of wines fermented by non-Saccharomyces yeasts

3.3.3.1.Core non-volatile compounds as fermentative performance contributed by

candidate wild yeast strains

Nine non-volatile compounds were measured as the fermentative features of samples inoculated by wild yeasts strains comparing with S. cerevisiae BY4742. Glucose

(i.e. 89.56±0.78g/L) and fructose (i.e. 90.75±0.56g/L) were counted as the major sugars in Chambourcin juice. The proposed hypothesis was that candidate wild yeasts have potential for wine fermentation and to contribute to final wine quality. In support of this, we observed that various wild yeast strains convert sugars into different fermentation by- products. In terms of the amount of residual sugars in the inoculated fermentations, P. kudriazevii SM192402 used similar amounts of glucose and fructose compared to S. cerevisiae BY4742. On the other hand, H. uvarum NV192410 and P. kluyveri NV192402 used similar amount of sugars with each other which were lower than S. cerevisiae BY4742

(Figure 3-18). Ethanol and glycerol are the two major yeast metabolites produced during alcoholic fermentation. The amount of ethanol produced by P. kudriazevii SM192402 (i.e.

9.46±0.90%) was not statistically different with S. cerevisiae BY4742 (i.e. 9.42±0.94%), but was significantly higher than ethanol level produced by H. uvarum NV192410 (i.e.

4.80±0.94%), H. opuntiae NV192404 (i.e. 6.70±0.35%), P. kluyveri NV192402 (i.e.

4.15±0.14%) and A. pullulans SM190002 (i.e. 4.07±0.21%). However, for the production of glycerol, there was no significant difference between S. cerevisiae BY4742, P. kluyveri

NV192402, P. kudriazevii SM192402 and A. pullulans SM190002 (i.e. 5.95~7.54g/L)

(Figure 3-19 (A)). Types and levels of organic acids typically contribute to taste of final wines relative to sourness, bitterness, and tartness (Chidi et al. 2015). Although present at

73 low levels compared to ethanol, five organic acids were chosen for analysis as the major common acids present in laboratory scale fermentation. Specifically, P. kudriazevii

SM192402 produced 1.90±0.69g/L of malic acid and 0.81±0.06g/L of acetic acid having no significant difference with S. cerevisiae BY4742. Concentration of tartaric acid decreased after fermentation by most of the yeast strains (i.e. 0.29~0.54g/L) and had the significant difference with the amount in sterile juice (i.e. 0.69±0.02g/L). Interestingly, S. cerevisiae BY4742 produced highest amount of citric acid (i.e. 0.20±0.003g/L) followed by A. pullulans SM190002 (i.e. 0.17±0.005g/L); and H. opuntiae NV192404 produced

0.17±0.02g/L of succinic acid similar with S. cerevisiae BY4742 which was significantly different with other strains (Figure 3-19 (B)).

Figure 3-18. Composition of major sugars (g/L) in sterile juice compared with Figure 3-20. Composition of major sugars (g/L) in sterile inoculated fermentations with candidate wild yeast strains with S. cerevisiae BY4742 Chambourcin and fermented juice by selected non- asSaccharomyces control. strains and S. cerevisiae BY4742. Glucose and fructose are the major sugars in grape juice and wine. GlucoseThe segmentsand fructosein are thethe majorbar sugarsrepresented in grape juicethe andamount wine. Theof segmentsglucose inor the bar representedfructose theused amountduring of glucosefermentation or fructoseby usedeach duringstrain fermentationcompared by with each strain sterile Chambourcin juice. The different types of yeasts used in this comparedstudy waswith sterilerepresented juice. The differenton the typesx-axis of yeasts. The usedlaboratory in this studystrain was represenS. ted cerevisiae BY4742 was used as a control. on the x-axis. The laboratory strain S. cerevisiae BY4742 was used as a control.

(A)

a a

b b b bc ___c __d_ cd d

d d a a b ab ab a bc bc c ___c bc d d

(B)

a ab

bc abc a ___bc_ ___cde ___b__ b de c cde ade cd c b a c e a b e c c bc c

FigureFigure 3-193-.1 9Non. Non-volatile-volatile compoundscompounds in sterilein sterile juice Chambourcincompared with inoculated and fermented juice inoculated by selected non-Saccharomyces fermentationsstrains and withS. cerevisiae candidateBY wild4742 yeast. strains with S. cerevisiae BY4742 as control. Analyzed non-volatile compounds included sugars (glucose and Analyzed non-volatile compounds included sugars (glucose and fructose), ethanol, fructose), ethanol, glycerol (A) and acids (malic acid, acetic acid, glyceroltartaric (A)acid, and citricacids (malicacid, and acid,succinic acetic acid,acid) tartaric(B). Theacid, differentcitric acid,types and succinic acid) of yeasts used in this study was represented on the x-axis. Data presented as mean ratio ± SEM with a common superscript indicating significance (p<0.05). 76The laboratory strain S. cerevisiae BY4742 was used as a control.

(B). The different types of yeasts used in this study was represented on the x-axis. Data presented as mean ratio ± SEM with a common superscript indicating significance

(p<0.05). The laboratory strain S. cerevisiae BY4742 was used as a control.

The residual sugars (°Brix) is an important measurement not only for winemakers to monitor the progress of fermentation, but also for scientists to investigate the fermentation capacity of yeast strains. During laboratory scale fermentation, S. cerevisiae

BY4742 and P. kudriazevii SM192402 converted about 80% of total sugars (combination of glucose and fructose) followed by H. opuntiae NV192404 and A. pullulans SM190002

(i.e. 60%), and H. uvarum NV192410 and P. kluyveri NV192402 consumed the least with

40% sugars (Figure 3-20). Sugars are typically utilized as part of aerobic fermentation or anaerobic respiration. Next, we compared ethanol concentration between samples. All wild yeast strains produced similar levels of ethanol measured as “g EtOH/g Sugars” except A. pullulans SM190002. Interestingly, H. uvarum NV192410 converted sugars to ethanol at a rate of 0.54 (±0.03) similar with S. cerevisiae BY4742 control strain at 0.51(±0.05)

(Figure 3-21). However, the results of H. uvarum NV192410 and P. kluyveri NV192402 fermenting least sugar but having comparable ethanol yield demonstrated the chance of stuck fermentation. In addition, A. pullulans SM190002 with the low ethanol yield showed the weaker fermentation capacity. In summary, P. kudriazevii SM192402 possessed the comparable fermentation capacity with S. cerevisiae BY4742 to efficiently ferment sugars to ethanol followed by H. opuntiae NV192404.

a A A

B b b BC

C C bc c d d

Figure 3-20. Total sugars (g/L) and sugar consumed (%) in sterile juice and Figure 3-21. Total sugars (g/L) in sterile Chambourcin and inoculatedfermented fermentjuiceationsby withselected candidatenon wild-Saccharomyces yeast strains and S.strains cerevisiaeand BY4742.S. cerevisiae BY4742, and sugar consumed (%) during Total sugars, sum of glucose and fructose, was represented by bars. Circles represent fermentation across strains. percentageEach bar of sugarrepresented consumedthe duringtotal fermentationsugars, sum by eachof glucose yeast strainand comparfructose,ed with in grape juice and wine. The percentage of sugar consumed during sterilefermentation juice. Differentby typeseach of yeastyeasts usedstrain in thiscomparing study was withrepresentedthe sterile on the xjuice-axis. S. cerevisiaewas represented BY4742 waswith used theas a dotcontrol.. The Datadifferent presentedtypes as meanof ratioyeasts ± SEMused within a this study was represented on the x-axis. The laboratory strain S. commoncerevisiae superscriptBY 4742indicatingwas significanceused as (p<0.05).a control . Data presented as mean ratio ± SEM with a common superscript indicating significance (p<0.05).

AB A AB B B a a

C b

bc c c

Figure 3-21. Ethanol content (g/L) in inoculated fermentations with candidate wild yeast strains and S. cerevisiae BY4742, and ethanol yield (g Ethanol/ g Sugar).

EachFigure bar represented3-22. Ethanol the ethanolcontent content(g/L) (g/L) in grapefermented juice andjuice wine. byCirclesselected represent non-Saccharomyces strains and S. cerevisiae BY4742, and ethanol yield after fermentation by strain. Different types of yeasts used in this study was ethanol yield (g Ethanol/ g Sugar) after fermentation. representedEach bar onrepresented the x-axis. The thelaboratoryethanol straincontent S. cerevisiae(g/L) BY4742in grape was usedjuice as a control.and wine. Ethanol yield after fermentation by each yeast strain was Datarepresented presented aswith meanthe ratiodot ± .SEMThe withdifferent a commontypes superscriptof yeasts indicatingused significancein this (p<0.05).study was represented on the x-axis. The laboratory strain S. cerevisiae BY4742 was used as a control. Data presented as mean ratio ± SEM with a common superscript indicating significance (p<0In.05 the). next part of our analysis, we used principal components analysis (PCA) to determine how nine core non-volatile compounds present in inoculated fermentations different by candidate wild yeast strains. Data obtained from non-volatile chemical analysis were log transformed to remove heteroscedasticity and Pareto scaling was performed to decrease mask effects resulting in a more normal distribution of the data (Figure 3-22).

Principal components 1 and 2 (PC1 and PC2, respectively) explained 83% of the experimental variance, while PC1 explained 63.8% and PC2 explained 19.2% (Figure 3-

23). The main compounds separated the samples analyzed in PC1 were glucose (C3) and fructose (C5) (positive loading 0.29 and 0.33, respectively), and malic acid (C4), succinic acid (C6) and ethanol (C9) (negative loading > 0.4). In the case of PC2, tartaric acid (C2) was the major compound responsible for the separation. PC1 and PC2 components separated the samples into two distinctive groups with all the inoculated fermentations clustering together away from the sterile juice with S. cerevisiae BY4742 being the farthest away from sterile juice followed by P. kudriazevii SM192402 and H. opuntiae NV192404.

Figure 3-22. Data obtained from non-volatile chemical analysis were log transformed to remove heteroscedasticity and Pareto scaling was performed to decrease mask effects resulting in a more normal distribution of the data, before normalization (left panel) and after normalization (right panel).

(A)

(B)

Figure 3-24. Principal component82 score plot (A) and biplot (B) of the variables with PC1 and PC2 based on the non-volatile composition of juice (eight spoked asterisk) and ferments (star – S. cerevisiae; square – H. uvarum; squared times – H. opuntiae; circle – P. kudriavzevii; circled plus – P. kluyveri; plus – A. pullulans). C1: Citric acid; C2: Tartaric acid; C3: Glucose; C4: Malic acid; C5: Fructose; C6: Succinic acid; C7: Glycerol; C8: Acetic acid; and C9: Ethanol. 95% confidence region was displayed.

Figure 3-23. Principal component score plot (A) and biplot (B) of the variables with

PC1 and PC2 based on the non-volatile composition of sterile juice (eight spoked asterisk) and inoculated fermentations with candidate yeast strains and S. cerevisiae

BY4742.

Each symbol represented a yeast strain including star – S. cerevisiae BY4742; square – H. uvarum NV192410; squared times – H. opuntiae NV192404; circle – P. kudriavzevii

NV192402; circled plus – P. kluyveri SM192402; plus – A. pullulans SM190002.

C1: Citric acid; C2: Tartaric acid; C3: Glucose; C4: Malic acid; C5: Fructose; C6: Succinic acid; C7: Glycerol; C8: Acetic acid; and C9: Ethanol. 95% confidence region was displayed.

3.3.3.2.Distinct volatile profile of inoculated fermentations with yeast strains

One aspect of wine quality is the contribution of fermentation-derived volatile compounds which can enhance sensory characteristics of final wine. Using GC-MS, we identified 74 volatiles in sterile juice and inoculated fermentations that were assigned to 11 classes based on their chemical structure. The most represented classes with respect to the number of validated compounds were esters, alcohols and ketones (Figure 3-24). Since this study focuses on the differences of volatile profile by candidate wild yeast strains, all identified compounds were validated and included for further analysis even though some compounds were not present in the inoculated fermentations by one or two candidate strains (Table 3-4).

Alcohols 17 Esters 19 Ketones 9 Acids 6 Terpenes 4 Benzenoids 6 Aldehydes 1 Acetals 3 Phenols 1 Diols 3 Others 5 0 5 10 15 20

Figure 3-24. Total 74 volatile compounds detected by GC-MS from sterile juice and inoculated fermentations by candidate wild yeast strains and S. cerevisiae BY4742 were grouped based on chemical structures.

Table 3-4. List of volatiles detected in sterile juice and inoculated fermentations with

candidate wild yeast strains and S. cerevisiae BY4742 with mean retention time (RT)

and retention indices (RI).

Compound RT RI Compound RT RI

Alcohols Ketones

V1 1-Propanol 4.07 1020 V37 2,3-Pentanedione 4.26 1035

V2 1-Propanol, 2-methyl- 4.81 1074 V38 Acetyl valeryl 5.48 1121

V3 1-Butanol 5.43 1117 V39 2-Heptanone 5.95 1154

V4 1-Butanol, 2-methyl- 6.35 1180 V40 Acetoin 7.25 1244

V5 1-Butanol, 3-methyl- 6.37 1181 V41 2-Octanone 7.40 1254

V6 2-Buten-1-ol, 3-methyl-, 6.92 1219 V42 Ionone 10.65 1496 acetate

V7 1-Pentanol, 4-methyl- 7.78 1280 V43 4-Cyclopentene-1,3-dione 11.70 1584

V8 Prenol 7.82 1283 V44 2-Buten-1-one, 1-(2,6,6- 13.95 1787 trimethyl-1,3- cyclohexadien-1-yl)-, (E)-

V9 2-Heptanol 7.90 1288 V45 2-Buten-1-one, 1-(2,6,6- 13.95 1787 trimethyl-1,3- cyclohexadien-1-yl)-

V10 (S)-(+)-3-Methyl-1- 7.95 1291 Acids pentanol

V11 1-Hexanol 8.33 1320 V46 Acetic acid 9.32 1392

V12 1-Propanol, 3-ethoxy- 8.57 1338 V47 Propanoic acid, 2-methyl- 10.89 1517

V13 3-Hexen-1-ol, (Z)- 8.64 1343 V48 Butanoic acid 11.60 1576

V14 2-Hexen-1-ol, (E)- 9.05 1374 V49 Butanoic acid, 3-methyl- 12.11 1620

V15 1-Heptanol 9.65 1418 V50 Butanoic acid, 2-methyl- 12.13 1621

V16 1-Hexanol, 2-ethyl- 10.10 1454 V51 Hexanoic acid 14.07 1798

V17 1-Octanol 10.94 1521 Terpenes

V52 2H-Pyran, 3,6-dihydro-4- 9.86 1435 Esters methyl-2-(2-methyl-1- propenyl)-

V18 Butanoic acid, methyl ester 3.44 968 V53 Linalool 10.81 1509

V19 Butanoic acid, 2-methyl-, 3.70 991 V54 L-à-Terpineol 12.56 1660 methyl ester

V20 Isobutyl acetate 3.76 996 V55 2,6-Octadien-1-ol, 3,7- 14.20 1810 dimethyl-

V21 Acetic acid, butyl ester 4.46 1050 Benzenoids

V22 1-Butanol, 3-methyl-, 5.18 1098 V56 p-Xylene 5.72 1137 acetate

V23 Hexanoic acid, methyl ester 6.00 1157 V57 Styrene 6.90 1218

V24 Hexanoic acid, ethyl ester 6.73 1205 V58 p-Cymene 7.17 1238

V25 Propanoic acid, 2-oxo-, 7.07 1230 V59 Benzaldehyde 10.36 1474 ethyl ester

V26 Acetic acid, hexyl ester 7.26 1244 V60 Benzaldehyde, 3-methyl- 11.88 1598

V27 3-Hexen-1-ol, acetate, (Z)- 7.71 1275 V61 Benzaldehyde, 4-methyl- 11.88 1599

V28 2-Hexen-1-ol, acetate, (Z)- 7.80 1282 Aldehydes

V29 ETHYL (S)-(-)-LACTATE 8.09 1300 V62 Octanal 7.45 1258

V30 Heptanoic acid, ethyl ester 8.13 1304 Others

V31 2-Hexenoic acid, ethyl ester 8.22 1311 V66 1,3-Dioxolane, 2,4,5- 3.43 967 trimethyl-

V32 Octanoic acid, ethyl ester 9.50 1406 V67 3(2H)-Thiophenone, 10.44 1480 dihydro-2-methyl-

V33 3-(Methylthio)propyl 11.71 1585 V68 2,3-Butanediol 10.60 1493 acetate

V34 Decanoic acid, ethyl ester 12.03 1612 V69 2,3-Butanediol, [R- 10.60 1492 (R*,R*)]-

V35 Ethyl 9-decenoate 12.59 1662 V70 2,3-Butanediol, [S- 10.62 1494 (R*,R*)]-

V36 Dodecanoic acid, ethyl 14.34 1823 V71 Acetamide, N-ethyl- 11.77 1590 ester

Acetals V72 1-Propanol, 3-(methylthio)- 12.68 1670

V63 Butane, 1-(1- 3.68 989 V73 1,2-Cyclopentanedione 13.20 1716 ethoxyethoxy)-

V64 Butane, 1,1-diethoxy-3- 4.61 1060 V74 Phenylethyl Alcohol 14.78 1864 methyl-

V65 Pentane, 1-(1- 5.01 1087 ethoxyethoxy)-

Same with non-volatile chemical analysis, data obtained from volatile chemical

analysis were log transformed to remove heteroscedasticity and Pareto scaling was

performed to decrease mask effects resulting in a more normal distribution of the data

(Figure 3-25). Analysis of variance (ANOVA) was used to test the differences of volatile

compounds in the samples. The relative abundance of volatile compounds was significantly

different across inoculated fermentations and sterile juice with FDR-adjusted p-value (q-

value) less than 0.05 (Table 3-5).

Figure 3-25. Distribution of relative abundance of volatile compounds before (left, skewed) and after (right, more normally distributed) the log transformation and

Pareto scaling.

Table 3-5. All identified volatile compounds showed significant difference (ANOVA,

FDR-adjusted p-value<0.05) across sterile juice and inoculated fermentations by candidate wild yeasts and S. cerevisiae BY4742. Data shown here are after normalization.

FDR- Compound p-value adjusted p-value Alcohols V1 1-Propanol 2.54E-43 1.44E-42 V2 1-Propanol, 2-methyl- 4.21E-18 5.20E-18 V3 1-Butanol 1.21E-25 2.08E-25 V4 1-Butanol, 2-methyl- 3.67E-71 9.05E-70 V5 1-Butanol, 3-methyl- 9.21E-38 3.59E-37 V6 2-Buten-1-ol, 3-methyl-, acetate 1.14E-19 1.48E-19 V7 1-Pentanol, 4-methyl- 3.30E-48 2.72E-47 V8 Prenol 5.04E-27 1.01E-26 V9 2-Heptanol 2.13E-41 9.84E-41 V10 (S)-(+)-3-Methyl-1-pentanol 1.87E-43 1.15E-42 V11 1-Hexanol 8.24E-21 1.09E-20 V12 1-Propanol, 3-ethoxy- 6.54E-36 2.31E-35 V13 3-Hexen-1-ol, (Z)- 7.09E-38 2.91E-37 V14 2-Hexen-1-ol, (E)- 3.21E-75 1.19E-73 V15 1-Heptanol 5.81E-34 1.65E-33 V16 1-Hexanol, 2-ethyl- 2.86E-25 4.70E-25 V17 1-Octanol 7.95E-49 7.35E-48 Esters V18 Butanoic acid, methyl ester 1.66E-31 4.11E-31 V19 Butanoic acid, 2-methyl-, methyl ester 2.56E-77 1.89E-75 V20 Isobutyl acetate 6.76E-31 1.56E-30 V21 Acetic acid, butyl ester 5.59E-29 1.22E-28 V22 1-Butanol, 3-methyl-, acetate 4.62E-11 4.96E-11 V23 Hexanoic acid, methyl ester 9.82E-09 9.82E-09 V24 Hexanoic acid, ethyl ester 6.81E-13 7.52E-13 V25 Propanoic acid, 2-oxo-, ethyl ester 1.88E-27 3.87E-27 V26 Acetic acid, hexyl ester 1.99E-26 3.68E-26 V27 3-Hexen-1-ol, acetate, (Z)- 3.68E-26 6.63E-26

V28 2-Hexen-1-ol, acetate, (Z)- 2.03E-22 2.83E-22 V29 Ethyl (S)-(-)-Lactate 6.45E-18 7.82E-18 V30 Heptanoic acid, ethyl ester 6.97E-25 1.10E-24 V31 2-Hexenoic acid, ethyl ester 8.64E-15 9.83E-15 V32 Octanoic acid, ethyl ester 1.22E-15 1.41E-15 V33 3-(Methylthio) propyl acetate 8.62E-24 1.30E-23 V34 Decanoic acid, ethyl ester 1.49E-10 1.55E-10 V35 Ethyl 9-decenoate 2.59E-16 3.04E-16 V36 Dodecanoic acid, ethyl ester 1.95E-21 2.63E-21 Ketones V37 2,3-Pentanedione 2.81E-33 7.69E-33 V38 Acetyl valeryl 2.39E-19 3.05E-19 V39 2-Heptanone 2.21E-34 6.81E-34 V40 Acetoin 5.20E-24 8.02E-24 V41 2-Octanone 3.90E-33 1.03E-32 V42 Ionone 2.83E-23 4.11E-23 V43 4-Cyclopentene-1,3-dione 4.84E-09 4.90E-09 2-Buten-1-one, 1-(2,6,6-trimethyl-1,3-cyclohexadien-1- V44 4.07E-34 1.21E-33 yl)-, (E)- 2-Buten-1-one, 1-(2,6,6-trimethyl-1,3-cyclohexadien-1- V45 3.06E-38 1.33E-37 yl)- Acids V46 Acetic acid 4.65E-50 4.92E-49 V47 Propanoic acid, 2-methyl- 1.32E-22 1.87E-22 V48 Butanoic acid 3.74E-35 1.20E-34 V49 Butanoic acid, 3-methyl- 1.00E-54 1.48E-53 V50 Butanoic acid, 2-methyl- 2.08E-30 4.67E-30 V51 Hexanoic acid 9.76E-27 1.90E-26 Terpenes 2H-Pyran, 3,6-dihydro-4-methyl-2-(2-methyl-1- V52 8.91E-24 1.32E-23 propenyl)- V53 Linalool 1.34E-25 2.25E-25 V54 L-à-Terpineol 1.07E-26 2.03E-26 V55 2,6-Octadien-1-ol, 3,7-dimethyl- 1.41E-35 4.75E-35 Benzenoids V56 p-Xylene 5.90E-44 3.97E-43 V57 Styrene 2.64E-31 6.29E-31 V58 p-Cymene 3.59E-53 4.43E-52 V59 Benzaldehyde 2.30E-32 5.86E-32

V60 Benzaldehyde, 3-methyl- 3.81E-43 2.01E-42 V61 Benzaldehyde, 4-methyl- 1.44E-64 2.67E-63 Aldehydes V62 Octanal 4.22E-44 3.13E-43 Acetals V63 Butane, 1-(1-ethoxyethoxy)- 8.33E-17 9.94E-17 V64 Butane, 1,1-diethoxy-3-methyl- 3.58E-25 5.75E-25 V65 Pentane, 1-(1-ethoxyethoxy)- 2.55E-22 3.50E-22 Others V66 1,3-Dioxolane, 2,4,5-trimethyl- 1.86E-14 2.09E-14 V67 3(2H)-Thiophenone, dihydro-2-methyl- 4.45E-19 5.58E-19 V68 2,3-Butanediol 6.29E-43 3.10E-42 V69 2,3-Butanediol, [R-(R*,R*)]- 2.32E-28 4.91E-28 V70 2,3-Butanediol, [S-(R*,R*)]- 1.94E-36 7.17E-36 V71 Acetamide, N-ethyl- 5.09E-11 5.38E-11 V72 1-Propanol, 3-(methylthio)- 4.57E-26 8.06E-26 V73 1,2-Cyclopentanedione 2.97E-11 3.23E-11 V74 Phenylethyl Alcohol 6.74E-10 6.92E-10

The correlation between volatile profiles and yeast strains were analyzed by PCA based on the identified volatile compounds. Total 58.1% of the experimental variance was explained by the first three principal components, while PC1, PC2 and PC3 accounted for

22.7%, 19.0%, and 16.4%, respectively (Figure 3-26). These principal components separated the inoculated fermentations into distinctive groups by same yeast strain centering around the juice. The inoculated fermentation involving P. kudriazevii

SM192402 were separated in the negative side of PC1 with higher amounts of heptanoic acid ethyl ester (ethyl heptanoate; V30), 2-hexenoic acid ethyl ester (ethyl 2-hexenoate;

V31), butyric acid (V48), p-xylene (V56) and butane 1-(1-ethoxyethoxy)- (1-butoxy-1- ethoxyethane; V63). PC2 distinguished the inoculated fermentation involving P. kluyveri

NV192402 by higher amount of methyl hexanoate (V23) and 1-propanol 3-(methylthio)-

(methionol; V72) with the negative loading. In contrast, the inoculated fermentation involving S. cerevisiae BY4742 were separated to the other direction in the case of PC2 by higher amount of 1-butanol (V3), 1-propanol 3-ethoxy- (3-ethoxy-1-propanol; V12), and ethyl 9-decenoate (V35) (Figure 3-26(A)(B)). Additionally, the inoculated fermentation involving S. cerevisiae BY4742 were distinguished by higher amount of 1-butanol 2- methyl- (2-methyl-1-butanol; V4), butanoic acid methyl ester (methyl butyrate; V18), isobutyl acetate (V20), and acetic acid (V46); and the inoculated fermentation involving P. kluyveri NV192402 had positive correlation with acetic acid hexyl ester (hexyl acetate;

V26) demonstrated on PC3. The inoculated fermentation involving H. opuntiae NV192404 with higher amount of acetoin (V40) and linalool (V53) were separated in the positive side of PC3 (Figure 3-26(C)(D)). These results showed that the individual candidate wild yeast strain had different correlation with the volatile compositions, and the volatile profile was very different with S. cerevisiae BY4742 that could potentially be associated with wine aroma profile.

(A)

(B)

(C)

(D)

Figure 3-26. Principal component score plot (A and C) and biplot (B and D) of the variables with PC1, PC2 and PC3 based on the volatile composition of sterile juice

(eight spoked asterisk) and inoculated fermentations.

Each symbol represents a yeast strain including star – S. cerevisiae BY4742; square – H. uvarum NV192410; squared times – H. opuntiae NV192404; circle – P. kudriavzevii

NV192402; circled plus – P. kluyveri SM192402; plus – A. pullulans SM190002.

Confidence region was displayed at 95% confidence level.

3.4. Discussion

3.4.1. Diverse wild yeast populations in the early stages of fermentation represent unique

microbial terroir across three PA vineyards

Terroir is an expression in viticulture used to describe the unique contribution of regional features such as cultivar, vintage, and climate, that define wine sensory characteristics and product identity in a particular region. In this work, 29 species were identified from 120 isolates obtained across three PA vineyards (Figure 3-4). Diverse wild yeast populations observed in samples collected from early stages of spontaneous fermentation (0 and 24 h) conducted on grapes from three Chambourcin-growing vineyards support previous studies that highlight unique microbial terroir even within a small geographic area (radius about 90 km). Distinct microbial profile from environmental samples such as soil, plant, must, and across fermentation stages from 15 vineyards in southern Australia with distances ranging from 5 km to 400 km suggests that microbial profile is an important factor affecting terroir (Liu et al. 2020). Previous studies also demonstrated the impact of microbial terroir on wine quality (Barata, Malfeito-Ferreira,

95 and Loureiro 2012). For example, wild yeast strains such as Starmerella bacillaris and

Metschnikowia pulcherrima isolated from multiple regions of Italy were found to increase production of higher alcohols, such as �-phenylethyl alcohol corresponding to floral odor

(Binati et al. 2020). Kazachstania aerobia and K. servazzii in Shiraz grape must from southern Australia were found to increase production of esters, such as phenylethyl acetate and isoamyl acetate associated to rose and fruity aroma (Lin et al. 2020). These examples illustrate microbial terroir in PA vineyard can shape the regional Chambourcin wine characteristics.

Hanseniaspora spp. and Pichia spp. are the most dominant species identified during spontaneous fermentation of Chambourcin with relative abundances of 42% and

11% of total isolates, respectively (Table 3-2). Previous studies have reported the dominance of Hanseniaspora and Pichia species on various grape varieties (i.e. V. vinifera, V. labrusca and hybrid grapes), in grape must, and at the early stages of fermentation (Baffi et al. 2011; Bezerra-Bussoli et al. 2013; Brysch-Herzberg and Seidel

2015; Raymond Eder et al. 2017; Eder, Conti, and Rosa 2018). The abundance of

Hanseniaspora spp. and Pichia spp. appear to be make up the core native non-

Saccharomyces population on wine grapes and could be related to nutrient availability of mature grape berries which supports fast growth of these species while suppressing other microorganisms (A. Barata, Malfeito-Ferreira, and Loureiro 2012). In early stages of spontaneous fermentation, high abundance of H. uvarum and Pichia spp. were found on V. vinifera (Malbec), Vitis labrusca (Isabel and Bordeaux), and hybrid grapes (Zweigelt, cross between St. Laurent and Blaufränkisch), and different identified Pichia species included

P. klyuveri, P. novergenisis, P. guilliermondii (Bezerra-Bussoli et al. 2013; Lopandic et al.

2008; Eder, Conti, and Rosa 2018). Therefore, our findings on the dominance of

Hanseniaspora spp. and Pichia spp. further suggest these two species are the conserve components in microbial terroir of the hybrid grapes.

Our results demonstrate that most diverse fungal profile was obtained from PAV1

(17 unique species) compared with PAV2 (11 species) and PAV3 (12 species) (Figure 3-

4 (A)). One explanation for the higher diversity observed in PAV1 could be demographic and regional climate. PAV1 is located close to Lehigh Valley a designated American

Viticultural Area located in South East Pennsylvania. In Lehigh County, regional climate

(wet springs, hot summers, and occasionally wet falls) and proximity to the mountains could be considered factors that influence terroir including conditions that favors growth of diverse indigenous microorganisms (Weathered Vineyards & Winery 2013). Detectable differences between PAV1 and PAV3 relative to the abundance of H. meyeri, H. opuntiae,

P. terricola, Filobasidium floriforme, Candida spp., Meyerozyma carpophila, and

Kregervanrija sp. could be explained by increased distance between sampling sites which are 180 km apart (110 km between PAV1 and PAV2; 90 km between PAV2 and PAV3)

(Bokulich et al. 2014; Miura et al. 2017). Of interest, we only found A. pullulans in PAV2, and Penicillium brevicompactum and P. spinulosum in PAV3. Although these differences could be due to limitations of culture-based methods, future studies should further investigate the role of these species in viticulture and enology. Aureobasidium pullulans is well known for the production of extracellular enzymes such as pectinases (Manachini,

Parini, and Fortina 1988). Pectinases can be added prior to pressing to facilitate color and juice extraction, or used for wine clarification (Dawson Raspuzzi 2020). On the other hand,

P. brevicompactum could be associated with wine spoilage and as well as production of

97 mycotoxins in wines (Pitt et al. 1997; Patiño et al. 2007). The antifungal activity of BP protein from P. brevicompactum was previously reported which could be the possible reason that fungal profile in PAV3 was relatively less diverse compared to the other sampling sites (Garrigues et al. 2018). Diverse fungal community in three Chambourcin sampling sites highlight the uniqueness of microbial terroir associated to individual vineyard.

Wine fermentation is a complex and dynamic process which involves interactions of various species of microorganisms. By 24 hours of spontaneous fermentation, decrease fungal diversity was observed across all three vineyards where H. uvarum and S. bacillaris were the major wild yeast species (Figure 3-4 (B)). Hanseniaspora uvarum represents 15% of the strains isolated at 0 h, increasing to 50% by 24 h; and S. bacillaris represents 10% of the strains isolated at 0 h, increasing to 26% by 24 h. Winemakers typically avoid spontaneous fermentation and instead rely on commercial S. cerevisiae for the conversion of sugars, however, our observations suggests that wild yeast strains such as H. uvarum and S. bacillaris could utilize glucose and fructose from the environment as demonstrated by the increase in relative abundance by 24 h (Ciani and Comitini 2019). On the other hand, we observed decreased relative abundance of non-fermentative species Sporobolomyces pararoseus from 18% at 0 h to 3% by 24 h of spontaneous fermenting Chambourcin must.

The production of an extracellular β-glucosidase by S. pararoseus strain was previously characterized. The enzymatic activity could significantly increase the amount of free terpenes by the hydrolysis of glycosidic terpenes which may be potentially applied in wine aroma improvement (Milla A. Baffi et al. 2011). Therefore, it might be of interest to further explore the role of S. pararoseus in influence on wine flavor compounds.

3.4.2. Filamentous fungal populations in grape must could be an indicator of grapevine

health and wine quality

Filamentous fungi in vineyards and wineries are typically associated with postharvest losses or can cause grapevine disease. Before spontaneous fermentation (t = 0 hr) of Chambourcin, we identified several filamentous fungal strains such as Alternaria alternata, Neopestalotiopsis clavispora, Pestalotiopsis vismiae, Cladosporium angustisporum from PAV1; Fusarium sp. and Mucor nidicola from PAV2; and

Cladosporium cladosporioides and Penicillium brevicompactum and P. spinulosum from

PAV3. Only Leptosphaerulina chartarum was identified across vineyards PAV1 and

PAV2. Alternaria alternata has been previously reported to cause Alternaria rot on grapes resulting in fruit damage and economic losses (Caretta et al. 1999; Romanazzi et al. 2012;

Tournas and Katsoudas 2005; Lorenzini and Zapparoli 2015). Neopestalotiopsis clavispora and Pestalotiopsis spp. have been reported to cause leaf spot and plant diseases such as cane canker and trunk disease on grapevines (Caretta et al. 1999; Sergeeva, Priest, and Nair

2005; Úrbez-Torres et al. 2009; Malacrinò et al. 2015; Sajeewa S.N. Maharachchikumbura et al. 2016; C. C. Santos et al. 2019). In addition, C. angustisporum and C. cladosporioides can cause Cladosporium rot which not only significantly reduces the yield of grapes, but also reduces wine color, aroma and flavor reported in Cabernet Sauvignon wines

(Kantarcioǧlu, Yücel, and De Hoog 2002; Tournas and Katsoudas 2005; Briceño, Latorre, and Bordeu 2009). Fusarium sp. is a potential mycotoxigenic fungi, and F. solani was found to associate to the delayed development of phylloxera (grapevine pest) (Idris and

Arabi 2014; Bolton, Brannen, and Glenn 2016). Mucor nidicola has a cosmopolitan distribution and L. chartarum was previously identified in grape must, but their role in

99 viticulture is less studied (Madden et al. 2012; Pinto et al. 2015). Thus, monitoring the presence of filamentous fungi at crush could be an important step to control wine quality and prevent wine faults (Steel, Blackman, and Schmidtke 2013). Although not the focus of this study, it would be interesting to study the distribution and abundance of filamentous fungi during early stages of fermentation as an indicator of grapevine and wine quality.

Diverse filamentous fungi present in grape must before the start of fermentation was identified in this study on culture-based isolation and in the parallel study on microbiome of Chambourcin (H. L. Wang 2020). Microbiome analysis identified genus

Alternaria and Neopestalotiopsis with significant abundance in grape must which supports the identification of A. alternate and N. clavispora in culture-based methods. Because species having higher abundance in microbiome analysis represent higher chances of being isolated if not limited by culturability. In addition, the majority of identified filamentous fungi in microbiome analysis had significantly higher abundance at crush compared to later stages. This supports the identification of diverse filamentous fungi at t = 0 h compared to the undetectability at t = 24 h in culture-based methods. However, limitations of culture- based methods do exist as fungal species usually grow more slowly in general culture media, and it is rarely that one medium is satisfactory for all fungal species for the purposes of enumeration, detection and isolation (Beuchat 1993; Nagano et al. 2008; André Barata et al. 2008).

Identifying filamentous fungal populations on grape berries and during winemaking could investigate the role of filamentous fungi in microbial terroir. Microbial terroir is dependent on various environmental factors that could influence the conditions for microbial growth and distribution. Other than controlling filamentous fungal

100 populations for wine quality and prevention of wine faults, identification and characterization of indigenous fungal populations for use as biocontrol strains could be a potential application to preserve a particular microbial fingerprint that is favorable to the vineyard. For example, Lemos et al. (2016) showed an interesting application for S. bacillaris as a biocontrol strain for preventing Botrytis cinerea infection which is often associated with overripe grapes and is a challenge to grapevine in temperate climates. In addition, A. pullulans, the species found with relative abundances of 15% in PAV2, has been shown to have effective biocontrol activity for reducing sour rot infection caused by

Botrytis cinerea, Rhizopus stolonifer, and Aspergillus carbonarius on postharvest fruits

(Lima et al. 1997; Schena et al. 2003; Dimakopoulou et al. 2008). Although our study did not characterize wild yeast isolates for potential use in biocontrol, the indigenous biocontrol strains could be more efficacious to combat regional pathogens due to the advantage of growing in the region (X. Wang et al. 2019). Thus, it will be interesting to investigate the microbial interactions between filamentous fungi and wild yeasts isolated in PA vineyards for the applications in grapevine and wine quality control.

3.4.3. Characterization of physiological properties in wild yeast provides insights into

potential for winemaking

Ethanol tolerance is an important parameter related to fermentation kinetics and is a criterion for characterization of wild yeast strains for winemaking. Of interest, H. uvarum

NV192410 can tolerate up to 8% (v/v) ethanol contradictory to previous studies that reported tolerance of H. uvarum at 2.5% (v/v) ethanol (Eder, Conti, and Rosa 2018).

Several studies have indicated increased ethanol tolerance of up to 6% ethanol in some

101 non-Saccharomyces yeasts (Pina et al. 2004). For example, H. opuntiae NV192404 and P. kudriavzevii SM192402 have ethanol tolerance to 8% and 10%, respectively. The ability to tolerate higher levels of ethanol could link to the higher expression of heat shock genes in the yeast strains. Although very less relevant studies on H. uvarum, the elevated expression level of heat shock genes has been thought to play an important role in conferring ethanol tolerance in S. cerevisiae, H. opuntiae and P. kudriavzevii, but the mechanism of specific gene directly related to stresses tolerance in wild yeast species is remained unclear (Martins et al. 2017; Chamnipa et al. 2018). Increased ethanol tolerance in S. cerevisiae has been positively linked to the improvement of fermentation capacity and production of wine important flavor compounds. Ethanol tolerant S. cerevisiae KNU5377 strain showed the increases in alcohol yield and growth kinetics during fermentation in YG medium (20% (w/v) glucose and 1% (w/v) yeast extract) while upregulating the heat shock gene expressions (I. S. Kim et al. 2013). Other ethanol tolerant S. cerevisiae strain demonstrated improvement of flavor contributors with odor activity values (OAVs>1) to

Chinese rice wine (Yang et al. 2018). Thus, H. uvarum NV192410, H. opuntiae NV192404 and P. kudriavzevii SM192402 having higher ethanol tolerance are expected to have potential in improvement of flavor profile in wine fermentation.

Another important characteristic of wild yeast strains in winemaking in addition to ethanol tolerance is the ability to produce wine-associated metabolites. Analysis of non- volatile metabolites from inoculated fermentations is an approach to characterize the role of wild yeast strains in wine taste. Non-volatile metabolites correlated to candidate wild yeasts and control strain appear to be core conserved metabolites that define the most easily perceived sensory balance in wine such as sweetness, sourness and mouthfeel (Figure 3-

102

23). Among five measured organic acids, tartaric and citric acid are primarily derived from grapes, and succinic and acetic acid are mainly formed during fermentation, and malic could derived from both sources (Shiraishi, Fujishima, and Chijiwa 2010; Chidi et al.

2015). In our study, malic acid present in Chambourcin juice at significantly low level and were produced by candidate strains during fermentation (Figure 3-19). Carboxylation of pyruvate followed by reduction of oxaloacetate to malate (salts and esters of malic acid) is the most promising pathway related to malic acid production from glucose by S. cerevisiae during fermentation, but this pathway has not been testified in non-Saccharomyces species

(Zelle et al. 2008). Amount of malic acid produced by candidate strains should be measured again to decrease the large error bars and may consequently assess whether candidate wild yeasts proceed similar pathway with S. cerevisiae based on the production of malic acid.

Moreover, previous study reported no more than 25% of tartaric acid degraded by S. cerevisiae and non-Saccharomyces species (Kloeckera, Candida, Schizosaccharomyces and Hansenula spp.) which corresponds to our results except H. uvarum NV192410 (Gao and Fleet 1995). Although association between H. uvarum and degradation of tartaric acid was not identified previously, it could be possible that yeast strain utilize tartaric acid with the similar manner for malic acid which is used as the carbon and energy source regardless of the presence of assimilable sugar (S. K. Hong et al. 2010). Next, significant high citric acid produced by control strain could be associated to the higher efficiency of utilizing glucose and higher production of glycerol which are the two carbon sources for citric acid production compared with candidate wild yeasts (Hamissa, Abou-Zeid, and Redwan 1981).

H. opuntiae NV192404 producing higher concentration of succinic acid with no significant difference with control strain may indicate that NV192404 strain utilized larger proportion

103 of fermented sugar for the production of succinic acid (Nghiem, Kleff, and Schwegmann

2017). The trend of acetic acid production by candidate strains was similar to their glycerol production with control strain being the highest followed by P. kudriavzevii SM192402, as the production of these two compounds has been linked with each other. Acetic acid is form via the NAD+-dependent enzymatic reactions converting NAD+ back to NADH to balance the NADH:NAD+ ratio caused by increased formation of glycerol which relies on

NADH+-dependent enzymatic reactions (Erasmus, Cliff, and Van Vuuren 2004).

According to these results, although non-volatile profiles by candidate strains are clustered with control strain on PCA plot, different productions of non-volatile compounds indicate that wild yeast strains utilized fermented sugar differently in the metabolic pathway compared with control strain.

On the other hand, analysis of volatile metabolites from inoculated fermentations was conducted to characterize the role of wild yeast strains in wine aroma. Notable differences in volatile metabolites between candidate wild yeasts and control strain were demonstrated by PC analysis and were centered around the sterile juice (Figure 3-26). This represents the diverse volatile wine-associated metabolites were contributed by yeast strains during the fermentation process. Previous studies have highlighted the metabolomic variability depending on yeast species and demonstrated the production of aromatic compounds as “secondary metabolism” are very sensitive to fermentation conditions

(Erasmus, Cliff, and Van Vuuren 2004; Alves et al. 2015; Carrau, Boido, and Dellacassa

2017). Although, P. kudriavzevii SM192402 and H. opuntiae NV192404 demonstrate comparable ethanol yield with the control strain BY4742 (i.e. 0.5 g ethanol/ g sugars), different volatiles were correlated to the strains. Ethyl 2-hexenoate and ethyl heptanoate

104 which are associated to fruity odor were positively correlated to P. kudriavzevii SM192402 whereas H. opuntiae NV192404 is correlated with higher level of linalool (flowery and lavender odor) (Franco and Janzantti 2005; Englezos et al. 2016). Ethyl heptanoate was identified as P. kudriavzevii produced volatiles derived from the fatty acids biosynthesis and degradation pathway when growing on YPD agar (Mozūraitis et al. 2020).

Linalool was identified as one of the main odor-active compounds in orange wine fermented by H. opuntiae, but also found in Muscat grape juice fermented by H. uvarum

(Ferreira, Clímaco, and Faia 2001; Hu et al. 2018). Therefore, the correlation of yeast strains and volatile metabolites could be used for characterization and differentiation between wild yeast species.

The fermentation capacity and production of wine-associated metabolites are the combined factors to consider whether an individual strain could be a wine starter, but the unique metabolic profile by yeast strains with weaker fermentation capacity could be valuable to increase wine flavor when co-fermentation with other wine strains. Pichia kluyveri NV192402 does not appear to efficiently convert sugars to ethanol as more than

50% of sugars is still present at the end of fermentation. Although the high residual sugars and low amount of ethanol production poses a risk for stuck fermentation, P. kluyveri

NV192402 is positively correlated with methyl hexanoate and hexyl acetate (fruity sweet odor) and methionol (cabbage and cooked-potatoes aroma) (Moreira et al. 2011; Englezos et al. 2016). Methyl hexanoate is one of the important volatile compound that contributes to the aroma in strawberries (S. Y. Wang and Bunce 2004). One approach that avoids sluggish fermentation caused by P. kluyveri NV192402 is to conduct sequential or co- inoculation with S. cerevisiae to increase complexity of wine-important volatiles (Paul

105

Henschke 1997; Maisonnave et al. 2013; Querol et al. 2018). Furthermore, sensory analysis of co-fermentation with non-Saccharomyces species and S. cerevisiae could further reveal the preferences of novel wines by panelists. Fermentative characteristics correlated to

Metschnikowia pulcherrima in the co-fermentation of mango wine positively influenced the sensory qualities and preferences by considering the attributes of taste, flavor, mouthfeel and color (Sadineni, Kondapalli, and Reddy Obulam 2012). Therefore, improved wine flavor profile might be observed in the co-inoculation of P. kluyveri

NV192402 with S. cerevisiae comparing with the single inoculation of NV192402 strain.

106

Chapter 4

Conclusion and Future Study

4.1. Major findings and conclusion

One hundred and twenty isolates from 29 fungal species were identified at early stages in spontaneous fermentation of Chambourcin grape must (t = 0 and 24 h) from three

PA vineyards by culture-based methods and Sanger sequencing. Hanseniaspora spp., and

Pichia spp. are dominant genus identified from Chambourcin. PAV1 had the most diverse fungal profile with 17 unique species compared with PAV2 (11 species) and PAV3 (12 species). By 24 hours of spontaneous fermentation, fungal diversity was decreased across three PA vineyards where H. uvarum and S. bacillaris were the major wild yeast species.

Characterization of candidate wild yeast strains relative to ethanol tolerance demonstrate that P. kudriavzevii SM192402 can tolerate 10% v/v ethanol compared to control strain S. cerevisiae BY4742 (10%), followed by H. uvarum NV192410 (8%), H. opuntiae NV192404 (8%), and P. kluyveri NV192402 (8%). Sulfite tolerance assays demonstrate that most wild yeast strains were able to tolerant up to 100mg/L metabisulfite except H. opuntiae NV192404 (tolerant up to 80mg/L metabisulfite) at pH 3.0.

Pichia kudriavzevii SM192402 utilized 80% of sugars and H. opuntiae NV192404 was able to utilize 60% of sugars. Two strains converted sugar to ethanol at rate of 0.5 g

EtOH/ g Sugar similar with S. cerevisiae BY4742 control strain in laboratory scale fermentation.

107

Principal components analysis (PCA) revealed the similarity between candidate wild yeast strains and control strain by the cluster of inoculated fermentations based on the non-volatile profile analyzed by UHPLC-RI.

Furthermore, volatile metabolites in the inoculated fermentations were analyzed by

GC-MS with esters and alcohols being the most abundant chemical groups. Based on the volatile profile, five candidate strains were differentiated with each other and S. cerevisiae

BY4742 on PCA plot centered around the sterile juice. Saccharomyces cerevisiae BY4742 were distinguished by higher levels of 1-butanol, 3-ethoxy-1-propanol, and ethyl 9- decenoate.

Compared with S. cerevisiae BY4742, H. opuntiae NV192404 positively correlates with linalool and acetoin. Moreover, P. kudriavzevii SM192402 was distinguished by higher levels of 1-butoxy-1-ethoxyethane, ethyl 2-hexenoate, ethyl heptanoate, and p- xylene. Pichia kluyveri NV192402 had positive correlation with methionol, methyl hexanoate, and hexyl acetate.

In this study, our investigations on candidate strains isolated from local PA vineyards suggest the potential of wild yeasts in winemaking based on the unique fermentation characteristics. Other isolated strains in our collection constitutes a valuable source for more microbiological, evolutionary and ecological studies to provide more beneficial knowledge to Pennsylvania Wine Industry, and fortify the interest in the novel wild yeasts as the wine starters.

108

4.2. Future Study

Future work could focus on several modifications of experimental approaches and incorporation of extended analysis to further confirm the applications of candidate wild yeast strains in winemaking. Modifications to overcome limitations in culture-based methods and Sanger sequencing are increase of sampling size of isolates to capture more comprehensive fungal community, and conduction of metagenomic approaches by next- generation sequencing to obtain detailed bioinformation on microbial richness and evenness. Modification to tolerance assay is increase of concentration above 100mg/L metabisulfite to investigate the maximum sulfite tolerance of candidate wild yeasts. In the laboratory scale fermentation, single inoculation was conducted for characterization of individual candidate strain. However, further understating of microbial interactions could be analyzed from sequential or co-inoculation with optimized inoculum volume which may result better fermentation kinetics and chemical profile. Quantification of volatile compounds with chemical standards will allow the comparison with perception threshold.

Other wine attributes, such as color, polyphenol contents, and sensory characteristics associated to candidate yeast strains remain unclear. Sensory analysis could be conducted to understand whether different volatile profile by candidate strains is significant to consumers acceptance and preference. Consequently, PA winemakers could apply candidate yeast strains in fermentation to improve wine quality and enhance regional characteristics of wine flavor.

109

References

Aguilera, Andrés, and Tahía Benítez. 1985. “Role of Mitochondria in Ethanol Tolerance

of Saccharomyces Cerevisiae.” Archives of Microbiology 142 (4): 389–92.

https://doi.org/10.1007/BF00491909.

Aguilera, F., R. A. Peinado, C. Millán, J. M. Ortega, and J. C. Mauricio. 2006.

“Relationship between Ethanol Tolerance, H+-ATPase Activity and the Lipid

Composition of the Plasma Membrane in Different Wine Yeast Strains.” International

Journal of Food Microbiology 110 (1): 34–42.

https://doi.org/10.1016/j.ijfoodmicro.2006.02.002.

Albertin, Warren, Mathabatha E. Setati, Cécile Miot-Sertier, Talitha T. Mostert, Benoit

Colonna-Ceccaldi, Joana Coulon, Patrick Girard, et al. 2016. “Hanseniaspora Uvarum

from Winemaking Environments Show Spatial and Temporal Genetic Clustering.”

Frontiers in Microbiology 6 (JAN): 1569. https://doi.org/10.3389/fmicb.2015.01569.

Allamani, Allaman, Fabio Voller, and Franca Beccaria. 2010. “The Puzzle of Italian

Drinking.” NAD Nordic Studies on Alcohol and Drugs 27 (5): 465–78.

https://doi.org/10.1177/145507251002700504.

Alleweldt, G., and J. V. Possingham. 1988. “Progress in Grapevine Breeding.” Theoretical

and Applied Genetics. https://doi.org/10.1007/BF00265585.

Alves, Zélia, André Melo, Ana Raquel Figueiredo, Manuel A. Coimbra, Ana C. Gomes,

and Sílvia M. Rocha. 2015. “Exploring the Saccharomyces Cerevisiae Volatile

Metabolome: Indigenous versus Commercial Strains.” PLoS ONE.

110

https://doi.org/10.1371/journal.pone.0143641.

Anfang, N., M. Brajkovich, and M. R. Goddard. 2009. “Co-Fermentation with Pichia

Kluyveri Increases Varietal Thiol Concentrations in Sauvignon Blanc.” Australian

Journal of Grape and Wine Research. https://doi.org/10.1111/j.1755-

0238.2008.00031.x.

Aplin, Jesse J., Kimberly P. White, and Charles G. Edwards. 2019. “Growth and

Metabolism of Non-Saccharomyces Yeasts Isolated from Washington State

Vineyards in Media and High Sugar Grape Musts.” Food Microbiology 77 (May

2018): 158–65. https://doi.org/10.1016/j.fm.2018.09.004.

Baffi, Milla A., Thaise Tobal, João Henrique, G. Lago, Rodrigo S.R. Leite, Maurício

Boscolo, Eleni Gomes, and Roberto Da-Silva. 2011. “A Novel β-Glucosidase

FromSporidiobolus Pararoseus: Characterization and Application in Winemaking.”

Journal of Food Science. https://doi.org/10.1111/j.1750-3841.2011.02293.x.

Baffi, Milla Alves, Carolina Dos Santos Bezerra, María Arévalo-Villena, Ana Isabel

Briones-Pérez, Eleni Gomes, and Roberto Da Silva. 2011. “Isolation and Molecular

Identification of Wine Yeasts from a Brazilian Vineyard.” Annals of Microbiology 61

(1): 75–78. https://doi.org/10.1007/s13213-010-0099-z.

Barata, A., M. Malfeito-Ferreira, and V. Loureiro. 2012. “The Microbial Ecology of Wine

Grape Berries.” International Journal of Food Microbiology. Elsevier.

https://doi.org/10.1016/j.ijfoodmicro.2011.11.025.

Barata, André, Sara González, Manuel Malfeito-Ferreira, Amparo Querol, and Virgílio

Loureiro. 2008. “Sour Rot-Damaged Grapes Are Sources of Wine Spoilage Yeasts.”

In FEMS Yeast Research, 8:1008–17. Blackwell Publishing Ltd.

111

https://doi.org/10.1111/j.1567-1364.2008.00399.x.

Belda, Ignacio, Javier Ruiz, Adelaida Esteban-Fernández, Eva Navascués, Domingo

Marquina, Antonio Santos, and M. Victoria Moreno-Arribas. 2017. “Microbial

Contribution to Wine Aroma and Its Intended Use for Wine Quality Improvement.”

Molecules. MDPI AG. https://doi.org/10.3390/molecules22020189.

Berg, Robert A. van den, Huub C.J. Hoefsloot, Johan A. Westerhuis, Age K. Smilde, and

Mariët J. van der Werf. 2006. “Centering, Scaling, and Transformations: Improving

the Biological Information Content of Metabolomics Data.” BMC Genomics 7 (1): 1–

15. https://doi.org/10.1186/1471-2164-7-142.

Beuchat, Larry R. 1993. “Selective Media for Detecting and Enumerating Foodborne

Yeasts.” International Journal of Food Microbiology 19 (1): 1–14.

https://doi.org/10.1016/0168-1605(93)90119-2.

Bezerra-Bussoli, Carolina, Milla Alves Baffi, Eleni Gomes, and Roberto Da-Silva. 2013.

“Yeast Diversity Isolated from Grape Musts during Spontaneous Fermentation from

a Brazilian Winery.” Current Microbiology 67 (3): 356–61.

https://doi.org/10.1007/s00284-013-0375-9.

Binati, Renato L., Wilson J.F. Lemos Junior, Giovanni Luzzini, Davide Slaghenaufi,

Maurizio Ugliano, and Sandra Torriani. 2020. “Contribution of Non-Saccharomyces

Yeasts to Wine Volatile and Sensory Diversity: A Study on Lachancea

Thermotolerans, Metschnikowia Spp. and Starmerella Bacillaris Strains Isolated in

Italy.” International Journal of Food Microbiology 318 (April): 108470.

https://doi.org/10.1016/j.ijfoodmicro.2019.108470.

Blake, J. D., M. L. Clarke, and G. N. Richards. 1987. “Determination of Organic Acids in

112

Sugar Cane Process Juice by High-Performance Liquid Chromatography: Improved

Resolution Using Dual Aminex HPX-87H Cation-Exchange Columns Equilibrated to

Different Temperatures.” Journal of Chromatography A 398 (C): 265–77.

https://doi.org/10.1016/S0021-9673(01)96512-4.

Bokulich, Nicholas A., Thomas S. Collins, Chad Masarweh, Greg Allen, Hildegarde

Heymann, Susan E. Ebeler, and David A. Millsa. 2016. “Associations among Wine

Grape Microbiome, Metabolome, and Fermentation Behavior Suggest Microbial

Contribution to Regional Wine Characteristics.” MBio 7 (3): 631–47.

https://doi.org/10.1128/mBio.00631-16.

Bokulich, Nicholas A., John H. Thorngate, Paul M. Richardson, and David A. Mills. 2014.

“Microbial Biogeography of Wine Grapes Is Conditioned by Cultivar, Vintage, and

Climate.” Proceedings of the National Academy of Sciences of the United States of

America 111 (1): E139–48. https://doi.org/10.1073/pnas.1317377110.

Bolton, Stephanie L., Phillip M. Brannen, and Anthony E. Glenn. 2016. “A Novel

Population of Fusarium Fujikuroi Isolated from Southeastern U.S. Winegrapes

Reveals the Need to Re-Evaluate the Species’ Fumonisin Production.” Toxins.

https://doi.org/10.3390/toxins8090254.

Bougreau, Matthias, Kenia Ascencio, Marie Bugarel, Kendra Nightingale, and Guy

Loneragan. 2019. “Yeast Species Isolated from Texas High Plains Vineyards and

Dynamics during Spontaneous Fermentations of Tempranillo Grapes.” PLoS ONE 14

(5). https://doi.org/10.1371/journal.pone.0216246.

Bozoudi, Despina, and Dimitrios Tsaltas. 2018. “The Multiple and Versatile Roles of

Aureobasidium Pullulans in the Vitivinicultural Sector.” Fermentation.

113

https://doi.org/10.3390/fermentation4040085.

Briceño, E.X., B.A. Latorre, and E. Bordeu. 2009. “Effect of Cladosporium Rot on the

Composition and Aromatic Compounds of Red Wine.” Spanish Journal of

Agricultural Research 7 (1): 119. https://doi.org/10.5424/sjar/2009071-404.

Bromba, Manfred U A, and Horst Ziegler. 1981. “Application Hints for Savitzky-Holay

Digital Smoothing Filters and ß = 35/(4(21V-5)(2N-3)(21V-1)(2N + 1)(2N + 3)(21V

+ 5)(2N + 7)). PROPERTIES The Properties of Savitzky-Golay Smoothing Filters

May Be Summarized as Follows: (1) Let Püif+i Be an Arbitrary .” Anal. Chem. Vol.

53. https://pubs.acs.org/sharingguidelines.

Brown, S. W., S. G. Oliver, D. E.F. Harrison, and R. C. Righelato. 1981. “Ethanol

Inhibition of Yeast Growth and Fermentation: Differences in the Magnitude and

Complexity of the Effect.” European Journal of Applied Microbiology and

Biotechnology 11 (3): 151–55. https://doi.org/10.1007/BF00511253.

Brysch-Herzberg, Michael, and Martin Seidel. 2015. “Yeast Diversity on Grapes in Two

German Wine Growing Regions.” International Journal of Food Microbiology 214

(December): 137–44. https://doi.org/10.1016/J.IJFOODMICRO.2015.07.034.

Buehler, A.J., R.L. Evanowski, N.H. Martin, K.J. Boor, and M. Wiedmann. 2017. “Internal

Transcribed Spacer (ITS) Sequencing Reveals Considerable Fungal Diversity in

Dairy Products.” Journal of Dairy Science 100 (11): 8814–25.

https://doi.org/10.3168/jds.2017-12635.

Butzke, Christian. 2010. Winemaking Problems Solved. Winemaking Problems Solved.

https://doi.org/10.1533/9781845690188.

Campaniello, Daniela, and Milena Sinigaglia. 2017. “Wine Spoiling Phenomena.” In The

114

Microbiological Quality of Food: Foodborne Spoilers. https://doi.org/10.1016/B978-

0-08-100502-6.00013-3.

Capece, A., G. Siesto, R. Romaniello, V.M. Lagreca, R. Pietrafesa, A. Calabretti, and P.

Romano. 2013. “Assessment of Competition in Wine Fermentation among Wild

Saccharomyces Cerevisiae Strains Isolated from Sangiovese Grapes in Tuscany

Region.” LWT - Food Science and Technology 54 (2): 485–92.

https://doi.org/10.1016/J.LWT.2013.07.001.

Caretta, Giuseppe, Edoardo Piontelli, Anna Maria Picco, and Giuseppe Del Frate. 1999.

“Some Filamentous Fungi on Grassland Vegetation from Kenya.” Mycopathologia

145 (3): 155–69. https://doi.org/10.1023/A:1007038112075.

Carrau, Francisco, Eduardo Boido, and Eduardo Dellacassa. 2017. “Yeast Diversity and

Flavor Compounds.” In Fungal Metabolites. https://doi.org/10.1007/978-3-319-

25001-4_32.

Chamnipa, Nuttaporn, Sudarat Thanonkeo, Preekamol Klanrit, and Pornthap Thanonkeo.

2018. “The Potential of the Newly Isolated Thermotolerant Yeast Pichia Kudriavzevii

RZ8-1 for High-Temperature Ethanol Production.” Brazilian Journal of Microbiology

49 (2): 378–91. https://doi.org/10.1016/j.bjm.2017.09.002.

Chen, Kai, Carlos Escott, Iris Loira, Juan Manuel del Fresno, Antonio Morata, Wendu

Tesfaye, Fernando Calderon, Jose Antonio Suárez-Lepe, Shunyu Han, and Santiago

Benito. 2018. “Use of Non-Saccharomyces Yeasts and Oenological Tannin in Red

Winemaking: Influence on Colour, Aroma and Sensorial Properties of Young Wines.”

Food Microbiology. https://doi.org/10.1016/j.fm.2017.07.018.

Chidi, Boredi S., Debra Rossouw, Astrid S. Buica, and Florian F. Bauer. 2015.

115

“Determining the Impact of Industrial Wine Yeast Strains on Organic Acid Production

under White and Red Wine-like Fermentation Conditions.” South African Journal of

Enology and Viticulture 36 (3): 316–27. https://doi.org/10.21548/36-3-965.

Chong, Jasmine, David S. Wishart, and Jianguo Xia. 2019. “Using MetaboAnalyst 4.0 for

Comprehensive and Integrative Metabolomics Data Analysis.” Current Protocols in

Bioinformatics 68 (1). https://doi.org/10.1002/cpbi.86.

Ciani, Maurizio, and Francesca Comitini. 2019. “Use of Non-Saccharomyces Yeasts in

Red Winemaking.” In Red Wine Technology, 51–68. Academic Press.

https://doi.org/10.1016/b978-0-12-814399-5.00004-9.

Ciani, Maurizio, Francesca Comitini, Ilaria Mannazzu, and Paola Domizio. 2010.

“Controlled Mixed Culture Fermentation: A New Perspective on the Use of Non-

Saccharomyces Yeasts in Winemaking.” FEMS Yeast Research.

https://doi.org/10.1111/j.1567-1364.2009.00579.x.

Ciani, Maurizio, Pilar Morales, Francesca Comitini, Jordi Tronchoni, Laura Canonico, José

A. Curiel, Lucia Oro, Alda J. Rodrigues, and Ramon Gonzalez. 2016. “Non-

Conventional Yeast Species for Lowering Ethanol Content of Wines.” Frontiers in

Microbiology. https://doi.org/10.3389/fmicb.2016.00642.

Claus, Harald, and Kiro Mojsov. 2018. “Enzymes for Wine Fermentation: Current and

Perspective Applications.” Fermentation.

https://doi.org/10.3390/fermentation4030052.

Clemente-Jimenez, J. M., L. Mingorance-Cazorla, S. Martínez-Rodríguez, F. J. Las Heras-

Vázquez, and F. Rodríguez-Vico. 2005. “Influence of Sequential Yeast Mixtures on

Wine Fermentation.” International Journal of Food Microbiology.

116

https://doi.org/10.1016/j.ijfoodmicro.2004.06.007.

Contreras, A., C. Hidalgo, S. Schmidt, P. A. Henschke, C. Curtin, and C. Varela. 2015.

“The Application of Non-Saccharomyces Yeast in Fermentations with Limited

Aeration as a Strategy for the Production of Wine with Reduced Alcohol Content.”

International Journal of Food Microbiology 205 (July): 7–15.

https://doi.org/10.1016/j.ijfoodmicro.2015.03.027.

Contreras, A, C Hidalgo, P A Henschke, P J Chambers, C Curtin, and C Varela. 2014.

“Evaluation of Non-Saccharomyces Yeasts for the Reduction of Alcohol Content in

Wine.” Applied and Environmental Microbiology 80 (5): 1670–78.

https://doi.org/10.1128/AEM.03780-13.

Cray, Jonathan A., Andrew N.W. Bell, Prashanth Bhaganna, Allen Y. Mswaka, David J.

Timson, and John E. Hallsworth. 2013. “The Biology of Habitat Dominance; Can

Microbes Behave as Weeds?” Microbial Biotechnology. Wiley-Blackwell.

https://doi.org/10.1111/1751-7915.12027.

Crous, Pedro W, Walter Gams, Joost A Stalpers, Vincent Robert, and Gerrit Stegehuis.

2004. “MycoBank: An Online Initiative to Launch Mycology into the 21st Century.”

In Studies in Mycology, 50:19–22. www.indexfungorum.org.

Damodaran, Srinivasan, and Kirk L. Parkin. 2017. Fennema’s Food Chemistry, Fifth

Edition. Fennema’s Food Chemistry, Fifth Edition.

https://doi.org/10.1201/9781315372914.

Dawson Raspuzzi. 2020. “Using Pectic Enzymes - WineMakerMag.Com.” 2020.

https://winemakermag.com/article/using-pectic-enzymes.

Dimakopoulou, Myrto, Sotirios E. Tjamos, Polymnia P. Antoniou, Amedeo Pietri, Paola

117

Battilani, Nikolaos Avramidis, Emmanouil A. Markakis, and Eleftherios C. Tjamos.

2008. “Phyllosphere Grapevine Yeast Aureobasidium Pullulans Reduces Aspergillus

Carbonarius (Sour Rot) Incidence in Wine-Producing Vineyards in Greece.”

Biological Control 46 (2): 158–65. https://doi.org/10.1016/j.biocontrol.2008.04.015.

Domizio, Paola, Cristina Romani, Livio Lencioni, Francesca Comitini, Mirko Gobbi, Ilaria

Mannazzu, and Maurizio Ciani. 2011. “Outlining a Future for Non-Saccharomyces

Yeasts: Selection of Putative Spoilage Wine Strains to Be Used in Association with

Saccharomyces Cerevisiae for Grape Juice Fermentation.” International Journal of

Food Microbiology. https://doi.org/10.1016/j.ijfoodmicro.2011.03.020.

Drumonde-Neves, Joaõ, Ricardo Franco-Duarte, Teresa Lima, Dorit Schuller, and Celia

Pais. 2017. “Association between Grape Yeast Communities and the Vineyard

Ecosystems.” PLoS ONE 12 (1). https://doi.org/10.1371/journal.pone.0169883.

Ebeler, Susan E., and John H. Thorngate. 2009. “Wine Chemistry and Flavor: Looking into

the Crystal Glass.” Journal of Agricultural and Food Chemistry 57 (18): 8098–8108.

https://doi.org/10.1021/jf9000555.

Eder, María L.Raymond, Francisco Conti, and Alberto L Rosa. 2018. “Differences between

Indigenous Yeast Populations in Spontaneously Fermenting Musts from V. Vinifera

L. and V. Labrusca L. Grapes Harvested in the Same Geographic Location.” Frontiers

in Microbiology 9 (JUN). https://doi.org/10.3389/fmicb.2018.01320.

Edgar, Robert C. 2004. “MUSCLE: Multiple Sequence Alignment with High Accuracy

and High Throughput.” Nucleic Acids Research. https://doi.org/10.1093/nar/gkh340.

Englezos, Vasileios, Kalliopi Rantsiou, Fabrizio Torchio, Luca Rolle, Vincenzo Gerbi, and

Luca Cocolin. 2015. “Exploitation of the Non-Saccharomyces Yeast Starmerella

118

Bacillaris (Synonym Candida Zemplinina) in Wine Fermentation: Physiological and

Molecular Characterizations.” International Journal of Food Microbiology 199

(April): 33–40. https://doi.org/10.1016/j.ijfoodmicro.2015.01.009.

Englezos, Vasileios, Fabrizio Torchio, Francesco Cravero, Fabio Marengo, Simone

Giacosa, Vincenzo Gerbi, Kalliopi Rantsiou, Luca Rolle, and Luca Cocolin. 2016.

“Aroma Profile and Composition of Barbera Wines Obtained by Mixed Fermentations

of Starmerella Bacillaris (Synonym Candida Zemplinina) and Saccharomyces

Cerevisiae.” LWT - Food Science and Technology 73 (November): 567–75.

https://doi.org/10.1016/j.lwt.2016.06.063.

Erasmus, Daniel J., Margaret Cliff, and Hennie J.J. Van Vuuren. 2004. “Impact of Yeast

Strain on the Production of Acetic Acid, Glycerol, and the Sensory Attributes of

Icewine.” American Journal of Enology and Viticulture.

Escribano-Viana, Rocío, Lucía González-Arenzana, Javier Portu, Patrocinio Garijo, Isabel

López-Alfaro, Rosa López, Pilar Santamaría, and Ana Rosa Gutiérrez. 2018. “Wine

Aroma Evolution throughout Alcoholic Fermentation Sequentially Inoculated with

Non- Saccharomyces/Saccharomyces Yeasts.” Food Research International 112

(June): 17–24. https://doi.org/10.1016/j.foodres.2018.06.018.

Fairbairn, Samantha, Jian Lin, Bin Jia, Shou Shui Shan, Shi ai Xu, Lee Shee Yen, Krzysztof

Kucharczyk, et al. 2012. “Stress, Fermentation Performance and Aroma Production

by Yeast.” Journal of the Institute of Brewing.

https://doi.org/10.1080/03610470.1976.12006198.

Fenoll, José, Angela Manso, Pilar Hellín, Leonor Ruiz, and Pilar Flores. 2009. “Changes

in the Aromatic Composition of the Vitis Vinifera Grape Muscat Hamburg during

119

Ripening.” Food Chemistry 114 (2): 420–28.

https://doi.org/10.1016/j.foodchem.2008.09.060.

Ferreira, A. M., M. C. Clímaco, and A. M. Faia. 2001. “The Role of Non-Saccharomyces

Species in Releasing Glycosidic Bound Fraction of Grape Aroma Components - A

Preliminary Study.” Journal of Applied Microbiology. https://doi.org/10.1046/j.1365-

2672.2001.01348.x.

Field, Andy. 2013. “Andy Field - Discovering Statistics Using IBM SPSS Statistics.”

Lavoisier.Fr. https://doi.org/10.1111/j.1365-2648.2007.04270_1.x.

Fleet, Graham H. 2008. “Wine Yeasts for the Future.” In FEMS Yeast Research, 8:979–95.

Oxford Academic. https://doi.org/10.1111/j.1567-1364.2008.00427.x.

Franco-Luesma, Ernesto, María Pilar Sáenz-Navajas, Dominique Valentin, Jordi Ballester,

Heber Rodrigues, and Vicente Ferreira. 2016. “Study of the Effect of H2S, MeSH and

DMS on the Sensory Profile of Wine Model Solutions by Rate-All-That-Apply

(RATA).” Food Research International.

https://doi.org/10.1016/j.foodres.2016.07.004.

Franco, M. R. B., and N. S. Janzantti. 2005. “Aroma of Minor Tropical Fruits.” Flavour

and Fragrance Journal 20 (4): 358–71. https://doi.org/10.1002/ffj.1515.

Frederick M. Ausubel, Roger Brent, Robert E. Kingston, David D. Moore, J. G. Seidman,

John A. Smith, Kevin Struhl. 1990. “Short Protocols in Molecular Biology. A

Compendium of Methods from Current Protocols in Molecular Biology.” Gene.

https://doi.org/10.1016/0378-1119(90)90070-8.

Fugelsang, C. Kenneth, and G. Charles Edwards. 2007. Wine Mirobiology.

https://link.springer.com/content/pdf/10.1007%2F978-0-387-33349-6.pdf.

120

Gamero, Amparo, Raquel Quintilla, Marizeth Groenewald, Wynand Alkema, Teun

Boekhout, and Lucie Hazelwood. 2016. “High-Throughput Screening of a Large

Collection of Non-Conventional Yeasts Reveals Their Potential for Aroma Formation

in Food Fermentation.” Food Microbiology 60 (December): 147–59.

https://doi.org/10.1016/j.fm.2016.07.006.

Gao, C., and G. H. Fleet. 1995. “Degradation of Malic and Tartaric Acids by High Density

Cell Suspensions of Wine Yeasts.” Food Microbiology.

https://doi.org/10.1016/S0740-0020(95)80080-8.

Garde-Cerdán, Teresa, and Carmen Ancín-Azpilicueta. 2006. “Contribution of Wild

Yeasts to the Formation of Volatile Compounds in Inoculated Wine Fermentations.”

European Food Research and Technology 222 (1–2): 15–25.

https://doi.org/10.1007/s00217-005-0029-7.

Garrigues, Sandra, Mónica Gandía, Laia Castillo, María Coca, Florentine Marx, Jose F.

Marcos, and Paloma Manzanares. 2018. “Three Antifungal Proteins from Penicillium

Expansum: Different Patterns of Production and Antifungal Activity.” Frontiers in

Microbiology. https://doi.org/10.3389/fmicb.2018.02370.

General Industry Stats. 2019. “United States Wine and Grape Industry FAQS |

WineAmerica.” The National Association of American Wineries. 2019.

https://wineamerica.org/policy/by-the-numbers/.

Ghareib, M., K. A. Youssef, and A. A. Khalil. 1988. “Ethanol Tolerance of Saccharomyces

Cerevisiae and Its Relationship to Lipid Content and Composition.” Folia

Microbiologica 33 (6): 447–52. https://doi.org/10.1007/BF02925769.

Giudici, P., and R. E. Kunkee. 1994. “The Effect of Nitrogen Deficiency and Sulfur-

121

Containing Amino Acids on the Reduction of Sulfate to Hydrogen Sulfide by Wine

Yeasts.” American Journal of Enology and Viticulture.

Goold, Hugh D., Heinrich Kroukamp, Thomas C. Williams, Ian T. Paulsen, Cristian Varela,

and Isak S. Pretorius. 2017. “Yeast’s Balancing Act between Ethanol and Glycerol

Production in Low-Alcohol Wines.” Microbial Biotechnology. John Wiley and Sons

Ltd. https://doi.org/10.1111/1751-7915.12488.

Hamissa, Farouk A., Abou Zeid A. Abou-Zeid, and Ahmed A. Redwan. 1981.

“Fermentative Production of Citric Acid by Yeasts.” Agricultural Wastes.

https://doi.org/10.1016/0141-4607(81)90004-4.

Happer, Jayson K., and Lynn Kime. 2013. “Wine Grape Production.” PennState Extension.

https://extension.psu.edu/wine-grape-production.

Henderson, Pat. 2009. “Sulfur Dioxide : Science behind This Anti-Microbial , Anti-

Oxidant , Wine a ... Sulfur Dioxide : Science behind This Anti-Microbial , Anti-

Oxidant , Wine A ...” Practical Winery and Vineyard, no. Jan/Feb: 1–8.

http://www.practicalwinery.com/janfeb09/page1.htm.

Henson, O Eldon. 1981. “Dichloran as an Inhibitor of Mold Spreading in Fungal Plating

Media: Effects on Colony Diameter and Enumeration.” Applied and Environmental

Microbiology 42 (4): 656–60.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC244078/pdf/aem00191-0102.pdf.

Hernández, L. F., J. C. Espinosa, M. Fernández-González, and A. Briones. 2003. “β-

Glucosidase Activity in a Saccharomyces Cerevisiae Wine Strain.” International

Journal of Food Microbiology. https://doi.org/10.1016/S0168-1605(02)00149-6.

Hong, Min Eui, Ki Sung Lee, Byung Jo Yu, Young Je Sung, Sung Min Park, Hyun Min

122

Koo, Dae Hyuk Kweon, Jae Chan Park, and Yong Su Jin. 2010. “Identification of

Gene Targets Eliciting Improved Alcohol Tolerance in Saccharomyces Cerevisiae

through Inverse Metabolic Engineering.” Journal of Biotechnology 149 (1–2): 52–59.

https://doi.org/10.1016/j.jbiotec.2010.06.006.

Hong, S. K., H. J. Lee, H. J. Park, Y. A. Hong, I. K. Rhee, W. H. Lee, S. W. Choi, O. S.

Lee, and H. D. Park. 2010. “Degradation of Malic Acid in Wine by Immobilized

Issatchenkia Orientalis Cells with Oriental Oak Charcoal and Alginate.” Letters in

Applied Microbiology. https://doi.org/10.1111/j.1472-765X.2010.02833.x.

Hu, Lanlan, Jia Wang, Xueao Ji, Rui Liu, Fusheng Chen, and Xiuyan Zhang. 2018.

“Selection of Non-Saccharomyces Yeasts for Orange Wine Fermentation Based on

Their Enological Traits and Volatile Compounds Formation.” Journal of Food

Science and Technology. https://doi.org/10.1007/s13197-018-3325-5.

Hyma, Katie E, Sofie M Saerens, Kevin J Verstrepen, and Justin C Fay. 2011. “Divergence

in Wine Characteristics Produced by Wild and Domesticated Strains of

Saccharomyces Cerevisiae.” FEMS Yeast Research 11 (7): 540–51.

https://doi.org/10.1111/j.1567-1364.2011.00746.x.

Idris, I., and M. I.E. Arabi. 2014. “The Relationship between Grape Phylloxera and

Fusarium Root Infection.” Advances in Horticultural Science.

https://doi.org/10.13128/ahs-22750.

Jackson, Ronald S. 2014. “Chemical Constituents of Grapes and Wine.” In Wine Science,

347–426. Elsevier. https://doi.org/10.1016/b978-0-12-381468-5.00006-3.

Jara, Carla, V. Felipe Laurie, Albert Mas, and Jaime Romero. 2016. “Microbial Terroir in

Chilean Valleys: Diversity of Non-Conventional Yeast.” Frontiers in Microbiology.

123

https://doi.org/10.3389/fmicb.2016.00663.

Johnsen, Lea G., Peter B. Skou, Bekzod Khakimov, and Rasmus Bro. 2017. “Gas

Chromatography – Mass Spectrometry Data Processing Made Easy.” Journal of

Chromatography A 1503 (June): 57–64.

https://doi.org/10.1016/j.chroma.2017.04.052.

Johnson, Eric A., and Carlos Echavarri-Erasun. 2011. “Yeast Biotechnology.” In The

Yeasts, 1:21–44. Elsevier. https://doi.org/10.1016/B978-0-444-52149-1.00003-3.

Jolly, N.P., O.P.H. Augustyn, and I.S. Pretorius. 2003. “The Occurrence of Non-

Saccharomyces Cerevisiae Yeast Species Over Three Vintages in Four Vineyards and

Grape Musts From Four Production Regions of the Western Cape, South Africa.”

South African Journal of Enology and Viticulture 24 (2). https://doi.org/10.21548/24-

2-2640.

Jolly, Neil P., Cristian Varela, and Isak S. Pretorius. 2014. “Not Your Ordinary Yeast: Non-

Saccharomyces Yeasts in Wine Production Uncovered.” FEMS Yeast Research.

Blackwell Publishing Ltd. https://doi.org/10.1111/1567-1364.12111.

Jones, Norman K. 2012. “The Influence of Recent Climate Change on Wine Regions in

Quebec, Canada.” Journal of Wine Research 23 (2): 103–13.

https://doi.org/10.1080/09571264.2012.678933.

Joshi, V. K., P. S. Panesar, V. S. Rana, and S. Kaur. 2017. “Science and Technology of

Fruit Wines: An Overview.” In Science and Technology of Fruit Wine Production.

https://doi.org/10.1016/B978-0-12-800850-8.00001-6.

Kantarcioǧlu, A. Serda, A. Yücel, and G. S. De Hoog. 2002. “Case Report. Isolation of

Cladosporium Cladosporioides from Cerebrospinal Fluid.” Mycoses 45 (11–12): 500–

124

503. https://doi.org/10.1046/j.1439-0507.2002.00811.x.

Keller, Nancy P. 2019. “Fungal Secondary Metabolism: Regulation, Function and Drug

Discovery.” Nature Reviews Microbiology. https://doi.org/10.1038/s41579-018-

0121-1.

Kim, Il Sup, Young Saeng Kim, Hyun Kim, Ingnyol Jin, and Ho Sung Yoon. 2013.

“Saccharomyces Cerevisiae KNU5377 Stress Response during High-Temperature

Ethanol Fermentation.” Molecules and Cells. https://doi.org/10.1007/s10059-013-

2258-0.

Kim, Jong H., Noreen Mahoney, Kathleen L. Chan, Russell J. Molyneux, and Bruce C.

Campbell. 2004. “Secondary Metabolites of the Grapevine Pathogen Eutypa Lata

Inhibit Mitochondrial Respiration, Based on a Model Bioassay Using the Yeast

Saccharomyces Cerevisiae.” Current Microbiology. https://doi.org/10.1007/s00284-

004-4349-9.

König, Helmut, Gottfried Unden, and Jürgen Fröhlich. 2009. Biology of Microorganisms

on Grapes, in Must and in Wine. Biology of Microorganisms on Grapes, in Must and

in Wine. https://doi.org/10.1007/978-3-540-85463-0.

Kumar, Sudhir, Glen Stecher, Michael Li, Christina Knyaz, and Koichiro Tamura. 2018.

“MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.”

Edited by Fabia Ursula Battistuzzi. Molecular Biology and Evolution 35 (6): 1547–

49. https://doi.org/10.1093/molbev/msy096.

Lambrechts, M.G., and I.S. Pretorius. 2019. “Yeast and Its Importance to Wine Aroma - A

Review.” South African Journal of Enology & Viticulture.

https://doi.org/10.21548/21-1-3560.

125

LEGRAS, JEAN-LUC, DIDIER MERDINOGLU, JEAN-MARIE CORNUET, and

FRANCIS KARST. 2007. “Bread, Beer and Wine: Saccharomyces Cerevisiae

Diversity Reflects Human History.” Molecular Ecology 16 (10): 2091–2102.

https://doi.org/10.1111/j.1365-294X.2007.03266.x.

Lemos Junior, Wilson José Fernandes, Chiara Nadai, Ludmyla Tamara Crepalde, Vanessa

Sales de Oliveira, Amanda Dupas de Matos, Alessio Giacomini, and Viviana Corich.

2019. “Potential Use of Starmerella Bacillaris as Fermentation Starter for the

Production of Low-Alcohol Beverages Obtained from Unripe Grapes.” International

Journal of Food Microbiology 303 (August): 1–8.

https://doi.org/10.1016/j.ijfoodmicro.2019.05.006.

Lemos, Wilson J., Barbara Bovo, Chiara Nadai, Giulia Crosato, Milena Carlot, Francesco

Favaron, Alessio Giacomini, and Viviana Corich. 2016. “Biocontrol Ability and

Action Mechanism of Starmerella Bacillaris (Synonym Candida Zemplinina) Isolated

from Wine Musts against Gray Mold Disease Agent Botrytis Cinerea on Grape and

Their Effects on Alcoholic Fermentation.” Frontiers in Microbiology.

https://doi.org/10.3389/fmicb.2016.01249.

Li, Chunsheng, Laihao Li, Xianqing Yang, Yanyan Wu, Yongqiang Zhao, and Yueqi

Wang. 2018. “Effect of Inorganic Salt Stress on the Thermotolerance and Ethanol

Production at High Temperature of Pichia Kudriavzevii.” Annals of Microbiology 68

(5): 305–12. https://doi.org/10.1007/s13213-018-1339-x.

Li, Chunsheng, Ying Xu, Laihao Li, Xianqing Yang, and Yueqi Wang. 2019. “Acid Stress

Induces Cross-Protection for Cadmium Tolerance of Multi-Stress-Tolerant Pichia

Kudriavzevii by Regulating Cadmium Transport and Antioxidant Defense System.”

126

Journal of Hazardous Materials 366 (March): 151–59.

https://doi.org/10.1016/j.jhazmat.2018.11.101.

Li, Shuang Shi, Chao Cheng, Zheng Li, Jing Yu Chen, Bin Yan, Bei Zhong Han, and

Malcolm Reeves. 2010. “Yeast Species Associated with Wine Grapes in China.”

International Journal of Food Microbiology 138 (1–2): 85–90.

https://doi.org/10.1016/j.ijfoodmicro.2010.01.009.

Lima, Giuseppe, Antonio Ippolito, Franco Nigro, and Mario Salerno. 1997. “Effectiveness

of Aureobasidium Pullulans and Candida Oleophila against Postharvest Strawberry

Rots.” Postharvest Biology and Technology 10 (2): 169–78.

https://doi.org/10.1016/S0925-5214(96)01302-6.

Lin, Mandy Man Hsi, Paul K. Boss, Michelle E. Walker, Krista M. Sumby, Paul R. Grbin,

and Vladimir Jiranek. 2020. “Evaluation of Indigenous Non-Saccharomyces Yeasts

Isolated from a South Australian Vineyard for Their Potential as Wine Starter

Cultures.” International Journal of Food Microbiology 312 (January): 108373.

https://doi.org/10.1016/j.ijfoodmicro.2019.108373.

Liu, Di, Qinglin Chen, Pangzhen Zhang, Deli Chen, and Kate S. Howell. 2020. “The

Fungal Microbiome Is an Important Component of Vineyard Ecosystems and

Correlates with Regional Distinctiveness of Wine.” MSphere 5 (4).

https://doi.org/10.1128/msphere.00534-20.

Lopandic, Ksenija, Wolfgang Tiefenbrunner, Helmut Gangl, Karin Mandl, Susanne Berger,

Gerhard Leitner, Gamalat A. Abd-Ellah, et al. 2008. “Molecular Profiling of Yeasts

Isolated during Spontaneous Fermentations of Austrian Wines.” FEMS Yeast

Research 8 (7): 1063–75. https://doi.org/10.1111/j.1567-1364.2008.00385.x.

127

Lopez, E. F., and E. F. Gomez. 2013. “Simultaneous Determination of the Major Organic

Acids, Sugars, Glycerol, and Ethanol by HPLC in Grape Musts and White Wines.”

Journal of Chromatographic Science 34 (5): 254–57.

https://doi.org/10.1093/chromsci/34.5.254.

López, S., J. J. Mateo, and S. Maicas. 2014. “Characterisation of Hanseniaspora Isolates

with Potential Aromaenhancing Properties in Muscat Wines.” South African Journal

of Enology and Viticulture. https://doi.org/10.21548/35-2-1018.

Lorenzini, Marilinda, and Giacomo Zapparoli. 2015. “Occurrence and Infection of

Cladosporium, Fusarium, Epicoccum and Aureobasidium in Withered Rotten Grapes

during Post-Harvest Dehydration.” Antonie van Leeuwenhoek, International Journal

of General and Molecular Microbiology 108 (5): 1171–80.

https://doi.org/10.1007/s10482-015-0570-8.

Luan, Yu, Bo Qin Zhang, Chang Qing Duan, and Guo Liang Yan. 2018. “Effects of

Different Pre-Fermentation Cold Maceration Time on Aroma Compounds of

Saccharomyces Cerevisiae Co-Fermentation with Hanseniaspora Opuntiae or Pichia

Kudriavzevii.” LWT - Food Science and Technology 92 (June): 177–86.

https://doi.org/10.1016/j.lwt.2018.02.004.

Ma, Decao, Xia Yan, Qianqian Wang, Yanan Zhang, and Yongsheng Tao. 2017.

“Performance of Selected P. Fermentans and Its Excellular Enzyme in Co-Inoculation

with S. Cerevisiae for Wine Aroma Enhancement.” LWT.

https://doi.org/10.1016/j.lwt.2017.08.018.

Madden, A. A., A. M. Stchigel, J. Guarro, D. Sutton, and P. T. Starks. 2012. “Mucor

Nidicola Sp. Nov., a Fungal Species Isolated from an Invasive Paper Wasp Nest.”

128

International Journal of Systematic and Evolutionary Microbiology 62 (7): 1710–14.

https://doi.org/10.1099/ijs.0.033050-0.

Magyar, Ildikó, and Tamás Tóth. 2011. “Comparative Evaluation of Some Oenological

Properties in Wine Strains of Candida Stellata, Candida Zemplinina, Saccharomyces

Uvarum and Saccharomyces Cerevisiae.” Food Microbiology.

https://doi.org/10.1016/j.fm.2010.08.011.

Maharachchikumbura, S. S.N., K. D. Hyde, J. Z. Groenewald, J. Xu, and P. W. Crous.

2014. “Pestalotiopsis Revisited.” Studies in Mycology 79 (1): 121–86.

https://doi.org/10.1016/j.simyco.2014.09.005.

Maharachchikumbura, Sajeewa S.N., Philippe Larignon, Kevin D. Hyde, Abdullah M. Al-

Sadi, and Zuo Yi Liu. 2016. “Characterization of Neopestalotiopsis, Pestalotiopsis

and Truncatella Species Associated with Grapevine Trunk Diseases in France.”

Phytopathologia Mediterranea 55 (3): 380–90.

https://doi.org/10.14601/Phytopathol_Mediterr-18298.

Maisonnave, Pierre, Isabelle Sanchez, Virginie Moine, Sylvie Dequin, and Virginie

Galeote. 2013. “Stuck Fermentation: Development of a Synthetic Stuck Wine and

Study of a Restart Procedure.” International Journal of Food Microbiology 163 (2–

3): 239–47. https://doi.org/10.1016/j.ijfoodmicro.2013.03.004.

Malacrinò, Antonino, Leonardo Schena, Orlando Campolo, Francesca Laudani, and

Vincenzo Palmeri. 2015. “Molecular Analysis of the Fungal Microbiome Associated

with the Olive Fruit Fly Bactrocera Oleae.” Fungal Ecology 18 (December): 67–74.

https://doi.org/10.1016/j.funeco.2015.08.006.

Malfeito-Ferreira, Manuel. 2019. “Spoilage Yeasts in Red Wines.” In Red Wine

129

Technology. https://doi.org/10.1016/b978-0-12-814399-5.00015-3.

Manachini, Pier L., Carlo Parini, and Maria G. Fortina. 1988. “Pectic Enzymes from

Aureobasidium Pullulans LV 10.” Enzyme and Microbial Technology 10 (11): 682–

85. https://doi.org/10.1016/0141-0229(88)90060-9.

Maro, Elena Di, Danilo Ercolini, and Salvatore Coppola. 2007. “Yeast Dynamics during

Spontaneous Wine Fermentation of the Catalanesca Grape.” International Journal of

Food Microbiology 117 (2): 201–10.

https://doi.org/https://doi.org/10.1016/j.ijfoodmicro.2007.04.007.

Martins, Flavia, Maria Eugênia De Oliveira Mamede, Antônio Ferreira Da Silva, Jéssica

Guerreiro, and Suzana Telles Da Cunha Lima. 2017. “Ultraestrutura Celular e

Expressão de Proteínas de Leveduras Hanseniaspora Sob Efeito Do Estresse

Etanólico.” Brazilian Journal of Food Technology. https://doi.org/10.1590/1981-

6723.6516.

Maturano, Y. Paola, M. Victoria Mestre, Benjamín Kuchen, M. Eugenia Toro, Laura A.

Mercado, Fabio Vazquez, and Mariana Combina. 2019. “Optimization of

Fermentation-Relevant Factors: A Strategy to Reduce Ethanol in Red Wine by

Sequential Culture of Native Yeasts.” International Journal of Food Microbiology

289 (January): 40–48. https://doi.org/10.1016/j.ijfoodmicro.2018.08.016.

Mauriello, Giacomo, Angela Capece, Maurizio D’Auria, Teresa Garde-Cerdán, and

Patrizia Romano. 2009. “SPME-GC Method as a Tool to Differentiate VOC Profiles

in Saccharomyces Cerevisiae Wine Yeasts.” Food Microbiology 26 (3): 246–52.

https://doi.org/10.1016/j.fm.2009.01.003.

Merdinoglu, D., C. Schneider, E. Prado, S. Wiedemann-Merdinoglu, and P. Mestre. 2018.

130

“Breeding for Durable Resistance to Downy and Powdery Mildew in Grapevine.”

Oeno One 52 (3): 189–95. https://doi.org/10.20870/oeno-one.2018.52.3.2116.

Milanovic, Vesna, Maurizio Ciani, Lucia Oro, and Francesca Comitini. 2012. “Starmerella

Bombicola Influences the Metabolism of Saccharomyces Cerevisiae at Pyruvate

Decarboxylase and Alcohol Dehydrogenase Level during Mixed Wine Fermentation.”

Microbial Cell Factories. https://doi.org/10.1186/1475-2859-11-18.

Mitsuhashi, H., H. Ikeuchi, and Y. Nojima. 2001. “Is Sulfite an Antiatherogenic Compound

in Wine? [3].” Clinical Chemistry. American Association for Clinical Chemistry Inc.

https://doi.org/10.1093/clinchem/47.10.1872.

Miura, Toshiko, Roland Sánchez, Luis E. Castañeda, Karina Godoy, and Olga Barbosa.

2017. “Is Microbial Terroir Related to Geographic Distance between Vineyards?”

Environmental Microbiology Reports 9 (6): 742–49. https://doi.org/10.1111/1758-

2229.12589.

Moon, Song Hee, Mi Chang, Hae Young Kim, and Hae Choon Chang. 2014. “Pichia

Kudriavzevii Is the Major Yeast Involved in Film-Formation, off-Odor Production,

and Texture-Softening in over-Ripened Kimchi.” Food Science and Biotechnology.

https://doi.org/10.1007/s10068-014-0067-7.

Moreira, N., C. Pina, F. Mendes, J. A. Couto, T. Hogg, and I. Vasconcelos. 2011. “Volatile

Compounds Contribution of Hanseniaspora Guilliermondii and Hanseniaspora

Uvarum during Red Wine Vinifications.” Food Control 22 (5): 662–67.

https://doi.org/10.1016/j.foodcont.2010.07.025.

Morgan, Sydney C, Garrett C Mccarthy, Brittany S Watters, Mansak Tantikachornkiat,

Ieva Zigg, Margaret A Cliff, and Daniel M Durall. 2019. “Effect of Sulfite Addition

131

and Pied de Cuve Inoculation on the Microbial Communities and Sensory Profiles of

Chardonnay Wines: Dominance of Indigenous Saccharomyces Uvarum at a

Commercial Winery.” FEMS Yeast Research 19 (5): 49.

https://doi.org/10.1093/femsyr/foz049.

Mozūraitis, Raimondas, Dominykas Aleknavičius, Iglė Vepštaitė-Monstavičė, Ramunė

Stanevičienė, Seyedeh Noushin Emami, Violeta Apšegaitė, Sandra Radžiutė, Laima

Blažytė-Čereškienė, Elena Servienė, and Vincas Būda. 2020. “Hippophae

Rhamnoides Berry Related Pichia Kudriavzevii Yeast Volatiles Modify Behaviour of

Rhagoletis Batava Flies.” Journal of Advanced Research.

https://doi.org/10.1016/j.jare.2019.08.001.

Nagano, Yuriko, B. Cherie Millar, Colin E. Goldsmith, James M. Walker, J. Stuart Elborn,

Jackie Rendall, and John E. Moore. 2008. “Development of Selective Media for the

Isolation of Yeasts and Filamentous Fungi from the Sputum of Adult Patients with

Cystic Fibrosis (CF).” Journal of Cystic Fibrosis 7 (6): 566–72.

https://doi.org/10.1016/j.jcf.2008.06.007.

Nghiem, Nhuan P., Susanne Kleff, and Stefan Schwegmann. 2017. “Succinic Acid:

Technology Development and Commercialization.” Fermentation.

https://doi.org/10.3390/fermentation3020026.

Nieuwoudt, H.H., B.A. Prior, L.S. Pretorius, and F.F. Bauer. 2017. “Glycerol in South

African Table Wines: An Assessment of Its Relationship to Wine Quality.” South

African Journal of Enology & Viticulture 23 (1). https://doi.org/10.21548/23-1-2151.

Padilla, Beatriz, José V. Gil, and Paloma Manzanares. 2016. “Past and Future of Non-

Saccharomyces Yeasts: From Spoilage Microorganisms to Biotechnological Tools for

132

Improving Wine Aroma Complexity.” Frontiers in Microbiology. Frontiers Research

Foundation. https://doi.org/10.3389/fmicb.2016.00411.

Patiño, B, Á Medina, M Doménech, M T González-Jaén, M Jiménez, and C Vázquez. 2007.

“Polymerase Chain Reaction (PCR) Identification of Penicillium Brevicompactum, a

Grape Contaminant and Mycophenolic Acid Producer.” Food Additives and

Contaminants 24 (2): 165–72. https://doi.org/10.1080/02652030600967222.

Paul Henschke. 1997. “Stuck Fermentation: Causes, Prevention and Cure.” Advances in

Juice Clarification and Yeast Inoculation, 30–41.

Pedneault, Karine, Martine Dorais, and Paul Angers. 2013. “Flavor of Cold-Hardy Grapes:

Impact of Berry Maturity and Environmental Conditions.” Journal of Agricultural

and Food Chemistry 61 (44): 10418–38. https://doi.org/10.1021/jf402473u.

Pedneault, Karine, and Caroline Provost. 2016. “Fungus Resistant Grape Varieties as a

Suitable Alternative for Organic Wine Production: Benefits, Limits, and Challenges.”

Scientia Horticulturae. Elsevier. https://doi.org/10.1016/j.scienta.2016.03.016.

Pennsylvania Winery Association. 2020. “About Pennsylvania Wines - Pennsylvania

Wines.” 2020. https://pennsylvaniawine.com/about/.

Pérez-Nevado, F., H. Albergaria, T. Hogg, and F. Girio. 2006. “Cellular Death of Two

Non-Saccharomyces Wine-Related Yeasts during Mixed Fermentations with

Saccharomyces Cerevisiae.” International Journal of Food Microbiology.

https://doi.org/10.1016/j.ijfoodmicro.2005.12.012.

Pickering, Gary J. 2000. “Low- and Reduced-Alcohol Wine: A Review.” International

Journal of Phytoremediation. https://doi.org/10.1080/09571260020001575.

Pina, Cristina, Cristina Santos, José António Couto, and Tim Hogg. 2004. “Ethanol

133

Tolerance of Five Non-Saccharomyces Wine Yeasts in Comparison with a Strain of

Saccharomyces Cerevisiae - Influence of Different Culture Conditions.” Food

Microbiology 21 (4): 439–47. https://doi.org/10.1016/j.fm.2003.10.009.

Pinto, Cátia, Diogo Pinho, Remy Cardoso, Valéria Custódio, Joana Fernandes, Susana

Sousa, Miguel Pinheiro, Conceição Egas, and Ana C. Gomes. 2015. “Wine

Fermentation Microbiome: A Landscape from Different Portuguese Wine

Appellations.” Frontiers in Microbiology 6 (SEP): 905.

https://doi.org/10.3389/fmicb.2015.00905.

Pitt, J. I., A. D. Hocking, J. I. Pitt, and A. D. Hocking. 1997. “Penicillium and Related

Genera.” In Fungi and Food Spoilage, 203–338. Springer US.

https://doi.org/10.1007/978-1-4615-6391-4_7.

Polášková, Pavla, Julian Herszage, and Susan E. Ebeler. 2008. “Wine Flavor: Chemistry

in a Glass.” Chemical Society Reviews 37 (11): 2478–89.

https://doi.org/10.1039/b714455p.

Querol, Amparo, Roberto Pérez-Torrado, Javier Alonso-del-Real, Romain Minebois, Jiri

Stribny, Bruno M. Oliveira, and Eladio Barrio. 2018. “New Trends in the Uses of

Yeasts in Oenology.” In Advances in Food and Nutrition Research, 85:177–210.

Academic Press. https://doi.org/10.1016/bs.afnr.2018.03.002.

Radler, F., and M. Schmitt. 1987. “Killer Toxins of Yeasts: Inhibitors of Fermentation and

Their Adsorption.” Journal of Food Protection. https://doi.org/10.4315/0362-028X-

50.3.234.

Rapp, A., and H. Mandery. 1986. “Wine Aroma.” Experientia 42 (8): 873–84.

https://doi.org/10.1007/BF01941764.

134

Raymond Eder, María L., Cristina Reynoso, Santiago C. Lauret, and Alberto L. Rosa. 2017.

“Isolation and Identification of the Indigenous Yeast Population during Spontaneous

Fermentation of Isabella (Vitis Labrusca L.) Grape Must.” Frontiers in Microbiology

8 (MAR): 1–8. https://doi.org/10.3389/fmicb.2017.00532.

Rodicio, Rosaura, and Jürgen J. Heinisch. 2017. “Carbohydrate Metabolism in Wine

Yeasts.” In Biology of Microorganisms on Grapes, in Must and in Wine.

https://doi.org/10.1007/978-3-319-60021-5_8.

Romanazzi, Gianfranco, Amnon Lichter, Franka Mlikota Gabler, and Joseph L. Smilanick.

2012. “Recent Advances on the Use of Natural and Safe Alternatives to Conventional

Methods to Control Postharvest Gray Mold of Table Grapes.” Postharvest Biology

and Technology. Elsevier. https://doi.org/10.1016/j.postharvbio.2011.06.013.

Romano, P., C. Fiore, M. Paraggio, M. Caruso, and A. Capece. 2003. “Function of Yeast

Species and Strains in Wine Flavour.” International Journal of Food Microbiology

86 (1–2): 169–80. https://doi.org/10.1016/S0168-1605(03)00290-3.

Ruiz, Javier, Ignacio Belda, Beata Beisert, Eva Navascués, Domingo Marquina, Fernando

Calderón, Doris Rauhut, Antonio Santos, and Santiago Benito. 2018. “Analytical

Impact of Metschnikowia Pulcherrima in the Volatile Profile of Verdejo White Wines.”

Applied Microbiology and Biotechnology. https://doi.org/10.1007/s00253-018-9255-

Sadineni, Varakumar, Naresh Kondapalli, and Vijaya Sarathi Reddy Obulam. 2012.

“Effect of Co-Fermentation with Saccharomyces Cerevisiae and Torulaspora

Delbrueckii or Metschnikowia Pulcherrima on the Aroma and Sensory Properties of

Mango Wine.” Annals of Microbiology. https://doi.org/10.1007/s13213-011-0383-6.

135

Saerens, Sofie M.G., Freddy R. Delvaux, Kevin J. Verstrepen, and Johan M. Thevelein.

2010. “Production and Biological Function of Volatile Esters in Saccharomyces

Cerevisiae.” Microbial Biotechnology. https://doi.org/10.1111/j.1751-

7915.2009.00106.x.

Sales, Kurt, Wolf Brandt, Elaine Rumbak, and George Lindsey. 2000. “The LEA-like

Protein HSP 12 in Saccharomyces Cerevisiae Has a Plasma Membrane Location and

Protects Membranes against Desiccation and Ethanol-Induced Stress.” Biochimica et

Biophysica Acta - Biomembranes 1463 (2): 267–78. https://doi.org/10.1016/S0005-

2736(99)00215-1.

Salfinger, Yvonne, and Mary Lou Tortorello. 2013. Compendium of Methods for the

Microbiological Examination of Foods. American Public Health Association.

https://doi.org/doi:10.2105/MBEF.0222.

Santos, A., M. San Mauro, E. Bravo, and Dom Marquina. 2009. “PMKT2, a New Killer

Toxin from Pichia Membranifaciens, and Its Promising Biotechnological Properties

for Control of the Spoilage Yeast Brettanomyces Bruxellensis.” Microbiology 155 (2):

624–34. https://doi.org/10.1099/mic.0.023663-0.

Santos, C. C., J. L. Domingues, R. F. Santos, M. B. Spósito, A. Santos, and Q. S. Novaes.

2019. “First Report of Neopestalotiopsis Clavispora Causing Leaf Spot on

Macadamia in Brazil.” Plant Disease 103 (7): 1790. https://doi.org/10.1094/PDIS-01-

19-0108-PDN.

Schafer, Ronald W. 2011. “What Is a Savitzky-Golay Filter?” IEEE Signal Processing

Magazine 28 (4): 111–17. https://doi.org/10.1109/MSP.2011.941097.

Schena, Leonardo, Franco Nigro, Isabella Pentimone, Angela Ligorio, and Antonio

136

Ippolito. 2003. “Control of Postharvest Rots of Sweet Cherries and Table Grapes with

Endophytic Isolates of Aureobasidium Pullulans.” Postharvest Biology and

Technology 30 (3): 209–20. https://doi.org/10.1016/S0925-5214(03)00111-X.

Schiavone, Marion, Cécile Formosa-Dague, Carolina Elsztein, Marie Ange Teste, Helene

Martin-Yken, Marcos A. De Morais, Etienne Dague, and Jean M. François. 2016.

“Evidence for a Role for the Plasma Membrane in the Nanomechanical Properties of

the Cell Wall as Revealed by an Atomic Force Microscopy Study of the Response of

Saccharomyces Cerevisiae to Ethanol Stress.” Applied and Environmental

Microbiology 82 (15): 4789–4801. https://doi.org/10.1128/AEM.01213-16.

Schimz, Karl Ludwig. 1980. “The Effect of Sulfite on the Yeast Saccharomyces

Cerevisiae.” Archives of Microbiology 125 (1–2): 89–95.

https://doi.org/10.1007/BF00403203.

Schmidt, Thomas M. 2019. Encyclopedia of Microbiology. Encyclopedia of Microbiology.

https://doi.org/10.1016/B978-0-12-811736-1.09976.

Schoch, Conrad L., Keith A. Seifert, Sabine Huhndorf, Vincent Robert, John L. Spouge,

C. André Levesque, Wen Chen, and Fungal Barcoding Consortium. 2012. “Nuclear

Ribosomal Internal Transcribed Spacer (ITS) Region as a Universal DNA Barcode

Marker for Fungi.” Proceedings of the National Academy of Sciences 109 (16): 6241–

46. https://doi.org/10.1073/PNAS.1117018109.

Sergeeva, V., M. Priest, and N. G. Nair. 2005. “Species of Pestalotiopsis and Related

Genera Occurring on Grapevines in Australia.” Australasian Plant Pathology 34 (2):

255–58. https://doi.org/10.1071/AP05009.

Shi, Wen Ke, Jia Wang, Fu Sheng Chen, and Xiu Yan Zhang. 2019. “Effect of Issatchenkia

137

Terricola and Pichia Kudriavzevii on Wine Flavor and Quality through Simultaneous

and Sequential Co-Fermentation with Saccharomyces Cerevisiae.” LWT.

https://doi.org/10.1016/j.lwt.2019.108477.

Shiraishi, Mikio, Hiroyuki Fujishima, and Hiroyuki Chijiwa. 2010. “Evaluation of Table

Grape Genetic Resources for Sugar, Organic Acid, and Amino Acid Composition of

Berries.” Euphytica. https://doi.org/10.1007/s10681-009-0084-4.

Siddiqui, Michael S., Kate Thodey, Isis Trenchard, and Christina D. Smolke. 2012.

“Advancing Secondary Metabolite Biosynthesis in Yeast with Synthetic Biology

Tools.” FEMS Yeast Research. https://doi.org/10.1111/j.1567-1364.2011.00774.x.

SMITH, NATHAN R., and VIRGINIA T. DAWSON. 1944. “THE BACTERIOSTATIC

ACTION OF ROSE BENGAL IN MEDIA USED FOR PLATE COUNTS OF SOIL

FUNGI.” Soil Science. https://doi.org/10.1097/00010694-194412000-00006.

Stanley, D., A. Bandara, S. Fraser, P.J. Chambers, and G.A. Stanley. 2010. “The Ethanol

Stress Response and Ethanol Tolerance of Saccharomyces Cerevisiae.” Journal of

Applied Microbiology 109 (1): 13–24. https://doi.org/10.1111/j.1365-

2672.2009.04657.x.

Stecher, Glen, Koichiro Tamura, and Sudhir Kumar. 2020. “Molecular Evolutionary

Genetics Analysis (MEGA) for MacOS.” Edited by Claudia Russo. Molecular

Biology and Evolution, January. https://doi.org/10.1093/molbev/msz312.

Steel, Christopher C., John W. Blackman, and Leigh M. Schmidtke. 2013. “Grapevine

Bunch Rots: Impacts on Wine Composition, Quality, and Potential Procedures for the

Removal of Wine Faults.” Journal of Agricultural and Food Chemistry. American

Chemical Society. https://doi.org/10.1021/jf400641r.

138

Stockwell, Tim, and David Crosbie. 2001. “Supply and Demand for Alcohol in Australia:

Relationships between Industry Structures, Regulation and the Marketplace.”

International Journal of Drug Policy 12 (2): 139–52. https://doi.org/10.1016/S0955-

3959(01)00079-2.

Styger, Gustav, Bernard Prior, and Florian F. Bauer. 2011. “Wine Flavor and Aroma.”

Journal of Industrial Microbiology and Biotechnology.

https://doi.org/10.1007/s10295-011-1018-4.

Sui, Yuan, Michael Wisniewski, Samir Droby, and Jia Liu. 2015. “Responses of Yeast

Biocontrol Agents to Environmental Stress.” Applied and Environmental

Microbiology. https://doi.org/10.1128/AEM.04203-14.

Sumby, Krista M., Paul R. Grbin, and Vladimir Jiranek. 2010. “Microbial Modulation of

Aromatic Esters in Wine: Current Knowledge and Future Prospects.” Food Chemistry.

Elsevier. https://doi.org/10.1016/j.foodchem.2009.12.004.

Takahashi, Masayuki, Tami Ohta, Kazuo Masaki, Akihiro Mizuno, and Nami Goto-

Yamamoto. 2014. “Evaluation of Microbial Diversity in Sulfite-Added and Sulfite-

Free Wine by Culture-Dependent and -Independent Methods.” Journal of Bioscience

and Bioengineering 117 (5): 569–75. https://doi.org/10.1016/j.jbiosc.2013.10.012.

Thomas, D. Susan, and A. H. Rose. 1979. “Inhibitory Effect of Ethanol on Growth and

Solute Accumulation by Saccharomyces Cerevisiae as Affected by Plasma-

Membrane Lipid Composition.” Archives of Microbiology 122 (1): 49–55.

https://doi.org/10.1007/BF00408045.

Tofalo, Rosanna, Maria Schirone, Sandra Torriani, Kalliopi Rantsiou, Luca Cocolin,

Giorgia Perpetuini, and Giovanna Suzzi. 2012. “Diversity of Candida Zemplinina

139

Strains from Grapes and Italian Wines.” Food Microbiology 29 (1): 18–26.

https://doi.org/10.1016/j.fm.2011.08.014.

Toivari, Mervi, Maija Leena Vehkomäki, Yvonne Nygård, Merja Penttilä, Laura

Ruohonen, and Marilyn G. Wiebe. 2013. “Low PH D-Xylonate Production with

Pichia Kudriavzevii.” Bioresource Technology 133 (April): 555–62.

https://doi.org/10.1016/j.biortech.2013.01.157.

Tournas, V. H., and Eugenia Katsoudas. 2005. “Mould and Yeast Flora in Fresh Berries,

Grapes and Citrus Fruits.” International Journal of Food Microbiology 105 (1): 11–

17. https://doi.org/10.1016/j.ijfoodmicro.2005.05.002.

Tristezza, Mariana, Maria Tufariello, Vittorio Capozzi, Giuseppe Spano, Giovanni Mita,

and Francesco Grieco. 2016. “The Oenological Potential of Hanseniaspora Uvarum

in Simultaneous and Sequential Co-Fermentation with Saccharomyces Cerevisiae for

Industrial Wine Production.” Frontiers in Microbiology 7 (MAY): 670.

https://doi.org/10.3389/fmicb.2016.00670.

Úrbez-Torres, José Ramón, Penny Adams, Jim Kamas, and Walter Douglas Gubler. 2009.

“Identification, Incidence, and Pathogenicity of Fungal Species Associated with

Grapevine Dieback in Texas.” American Journal of Enology and Viticulture.

Vaudano, Enrico, Giorgia Quinterno, Antonella Costantini, Laura Pulcini, Enrica Pessione,

and Emilia Garcia-Moruno. 2019. “Yeast Distribution in Grignolino Grapes Growing

in a New Vineyard in Piedmont and the Technological Characterization of Indigenous

Saccharomyces Spp. Strains.” International Journal of Food Microbiology 289

(January): 154–61. https://doi.org/10.1016/J.IJFOODMICRO.2018.09.016.

Verginer, Markus, Erich Leitner, and Gabriele Berg. 2010. “Production of Volatile

140

Metabolites by Grape-Associated Microorganisms.” Journal of Agricultural and

Food Chemistry 58 (14): 8344–50. https://doi.org/10.1021/jf100393w.

Vernarelli, Laurel A. 2018. “Novel Vinification Techniques to Improve Pennsylvania

Wine Quality.”

Vittek, Shelby. 2020. “A Beginner’s Guide to Hybrid Grapes | Wine Enthusiast.” Wine

Enthusiast. 2020. https://www.winemag.com/2020/05/21/hybrid-wine-grapes-guide/.

Wang, Hung Li. 2020. “Characterization of Microbial Dynamics and Volatile Metabolome

Changes during Fermentation of Chambourcin Grapes in Two Pennsylvania Regions.”

Wang, S. Y., and J. A. Bunce. 2004. “Elevated Carbon Dioxide Affects Fruit Flavor in

Field-Grown Strawberries (Fragaria x Ananassa Duch).” Journal of the Science of

Food and Agriculture. https://doi.org/10.1002/jsfa.1824.

Wang, Xiaohui, Qian Li, Junkang Sui, Jiamiao Zhang, Zhaoyang Liu, Jianfeng Du, Ruiping

Xu, Yanyan Zhou, and Xunli Liu. 2019. “Isolation and Characterization of

Antagonistic Bacteria Paenibacillus Jamilae HS-26 and Their Effects on Plant

Growth.” BioMed Research International. https://doi.org/10.1155/2019/3638926.

Waterhouse, Andrew L., Gavin L. Sacks, and David W. Jeffery. 2016. Understanding Wine

Chemistry. Understanding Wine Chemistry. https://doi.org/10.1002/9781118730720.

Weathered Vineyards & Winery. 2013. “About | Weathered Vineyards & Winery| New

Tripoli, PA.” 2013. https://www.weatheredvineyards.com/about.

Wenig, Philip, and Juergen Odermatt. 2010. “OpenChrom: A Cross-Platform Open Source

Software for the Mass Spectrometric Analysis of Chromatographic Data.”

https://doi.org/10.1186/1471-2105-11-405.

Werner et al. 2009. “Yeasts and Natural Production of Sulphites.” Journal of Enology and

141

Viticulture.

Wine-Searcher. 2015. “Chambourcin Wine.” November 30, 2015. https://www.wine-

searcher.com/grape-95-chambourcin.

Yalage Don, S. M., L. M. Schmidtke, J. M. Gambetta, and C. C. Steel. 2020.

“Aureobasidium Pullulans Volatilome Identified by a Novel, Quantitative Approach

Employing SPME-GC-MS, Suppressed Botrytis Cinerea and Alternaria Alternata in

Vitro.” Scientific Reports. https://doi.org/10.1038/s41598-020-61471-8.

Yang, Yijin, Yongjun Xia, Xiangna Lin, Guangqiang Wang, Hui Zhang, Zhiqiang Xiong,

Haiyan Yu, Jianshen Yu, and Lianzhong Ai. 2018. “Improvement of Flavor Profiles

in Chinese Rice Wine by Creating Fermenting Yeast with Superior Ethanol Tolerance

and Fermentation Activity.” Food Research International.

https://doi.org/10.1016/j.foodres.2018.03.036.

Zagorc, T., A. Maráz, N. Cadez, K. Povhe Jemec, G. Péter, M. Resnik, J. Nemanič, and P.

Raspor. 2001. “Indigenous Wine Killer Yeasts and Their Application as a Starter

Culture in Wine Fermentation.” Food Microbiology 18 (4): 441–51.

https://doi.org/10.1006/fmic.2001.0422.

Zelle, Rintze M., Erik De Hulster, Wouter A. Van Winden, Pieter De Waard, Cor Dijkema,

Aaron A. Winkler, Jan Maarten A. Geertman, Johannes P. Van Dijken, Jack T. Pronk,

and Antonius J.A. Van Maris. 2008. “Malic Acid Production by Saccharomyces

Cerevisiae: Engineering of Pyruvate Carboxylation, Oxaloacetate Reduction, and

Malate Export.” Applied and Environmental Microbiology.

https://doi.org/10.1128/AEM.02591-07.

Zhang, Qi, Deyi Wu, Yan Lin, Xinze Wang, Hainan Kong, and Shuzo Tanaka. 2015.

142

“Substrate and Product Inhibition on Yeast Performance in Ethanol Fermentation.”

Energy and Fuels 29 (2): 1019–27. https://doi.org/10.1021/ef502349v.

143