Interactions In Yeast Research Articles

The Networked Partial Correlation and Its Application to the Analysis of Genetic Interactions

SummaryGenetic interactions confer robustness on cells in response to genetic perturbations. This often occurs through molecular buffering mechanisms that can be predicted by using, among other features, the degree of coexpression between genes, which is commonly estimated through marginal measures of association such as Pearson or Spearman correlation coefficients. However, marginal correlations are sensitive to indirect effects and often partial correlations are used instead. Yet, partial correlations convey no information about the (linear) influence of the coexpressed genes on the entire multivariate system, which may be crucial to discriminate functional associations from genetic interactions. To address these two shortcomings, here we propose to use the edge weight derived from the covariance decomposition over the paths of the associated gene network. We call this new quantity the networked partial correlation and use it to analyse genetic interactions in yeast.

Improving analytical methods for protein-protein interaction through implementation of chemically inducible dimerization.

When investigating interactions between two proteins with complementary reporter tags in yeast two-hybrid or split GFP assays, it remains troublesome to discriminate true- from false-negative results and challenging to compare the level of interaction across experiments. This leads to decreased sensitivity and renders analysis of weak or transient interactions difficult to perform. In this work, we describe the development of reporters that can be chemically induced to dimerize independently of the investigated interactions and thus alleviate these issues. We incorporated our reporters into the widely used split ubiquitin-, bimolecular fluorescence complementation (BiFC)- and Förster resonance energy transfer (FRET)- based methods and investigated different protein-protein interactions in yeast and plants. We demonstrate the functionality of this concept by the analysis of weakly interacting proteins from specialized metabolism in the model plant Arabidopsis thaliana. Our results illustrate that chemically induced dimerization can function as a built-in control for split-based systems that is easily implemented and allows for direct evaluation of functionality.

Yeast Interactions in Inoculated Wine Fermentation.

The use of selected starter culture is widely diffused in winemaking. In pure fermentation, the ability of inoculated Saccharomyces cerevisiae to suppress the wild microflora is one of the most important feature determining the starter ability to dominate the process. Since the wine is the result of the interaction of several yeast species and strains, many studies are available on the effect of mixed cultures on the final wine quality. In mixed fermentation the interactions between the different yeasts composing the starter culture can led the stability of the final product and the analytical and aromatic profile. In the present review, we will discuss the recent developments regarding yeast interactions in pure and in mixed fermentation, focusing on the influence of interactions on growth and dominance in the process.

Novel Interactions of Yeast Glycerol‐3‐Phosphate Acyltransferases

Glycerol‐3‐phosphate acyltransferases (GPATs) catalyze the first committed and rate limiting step in the de novo synthesis of glycerophospholipids and neutral triacylglycerols. GPATs transfer an acyl group from acyl‐coenzyme A to the sn‐1 position of glycerol‐3‐phosphate to produce 1‐acyl glycerol‐3‐phosphate (lysophosphatidic acid). Lysophosphatidic acid can then be further acylated by a second acyltransferase to produce phosphatidic acid, a signalling lipid and key intermediate in lipid biosynthesis. In the model organism yeast Saccharomyces cerevisiae two GPATs, Gpt2 and Sct1, have been identified. Both are integral membrane proteins located to the endoplasmic reticulum (ER), differentially enriched in ER domains. Interestingly, we have shown that Gpt2 (but not Sct1) is responsible for channeling oleate (C18:1) into triacylglycerol that is eventually stored in lipid droplets. Furthermore, our studies on oleate metabolism unveiled novel ER structures that surround lipid droplets and are differentially enriched in Gpt2 while devoid of Sct1. In addition, we also uncovered a dynamic post‐translational regulation of Gpt2 and Sct1 through phosphorylation that responds to growth phase, carbon source and cellular GPAT imbalance. The aim of this work was to understand how GPAT interactions with other proteins contribute to their spatial distribution in the ER and to lipid synthesis partitioning. In order to identify potential protein interactors, Gpt2 and Sct1 were overproduced in cells deleted for endogenous GPATs and then isolated from lysates and microsomes using co‐immuno‐affinity and Ni‐NTA affinity chromatography purification techniques. Potential interactors co‐purifying with Gpt2 or Sct1 were identified through liquid chromatography‐tandem mass spectrometry (LC‐MS/MS). Our results suggest that Gpt2 and Sct1 differentially associate with ER sites where inter‐organelle transport of lipids occurs. Of importance are the contact sites between ER‐mitochondria, ER‐lipid droplets and the nuclear‐vacuolar junction.Support or Funding InformationThis work was supported by an operating grant from the Natural Sciences and Engineering Research Council of Canada to VZ.

Interactions between the Powdery Mildew Effector BEC1054 and Barley Proteins Identify Candidate Host Targets.

There are over 500 candidate secreted effector proteins (CSEPs) or Blumeria effector candidates (BECs) specific to the barley powdery mildew pathogen Blumeria graminis f.sp. hordei. The CSEP/BEC proteins are expressed and predicted to be secreted by biotrophic feeding structures called haustoria. Eight BECs are required for the formation of functional haustoria. These include the RNase-like effector BEC1054 (synonym CSEP0064). In order to identify host proteins targeted by BEC1054, recombinant BEC1054 was expressed in E. coli, solubilized, and used in pull-down assays from barley protein extracts. Many putative interactors were identified by LC-MS/MS after subtraction of unspecific binders in negative controls. Therefore, a directed yeast-2-hybrid assay, developed to measure the effectiveness of the interactions in yeast, was used to validate putative interactors. We conclude that BEC1054 may target several host proteins, including a glutathione-S-transferase, a malate dehydrogenase, and a pathogen-related-5 protein isoform, indicating a possible role for BEC1054 in compromising well-known key players of defense and response to pathogens. In addition, BEC1054 interacts with an elongation factor 1 gamma. This study already suggests that BEC1054 plays a central role in barley powdery mildew virulence by acting at several levels.

Predicting physiologically relevant SH3 domain mediated protein-protein interactions in yeast.

Motivation: Many intracellular signaling processes are mediated by interactions involving peptide recognition modules such as SH3 domains. These domains bind to small, linear protein sequence motifs which can be identified using high-throughput experimental screens such as phage display. Binding motif patterns can then be used to computationally predict protein interactions mediated by these domains. While many protein–protein interaction prediction methods exist, most do not work with peptide recognition module mediated interactions or do not consider many of the known constraints governing physiologically relevant interactions between two proteins.Results: A novel method for predicting physiologically relevant SH3 domain-peptide mediated protein–protein interactions in S. cerevisae using phage display data is presented. Like some previous similar methods, this method uses position weight matrix models of protein linear motif preference for individual SH3 domains to scan the proteome for potential hits and then filters these hits using a range of evidence sources related to sequence-based and cellular constraints on protein interactions. The novelty of this approach is the large number of evidence sources used and the method of combination of sequence based and protein pair based evidence sources. By combining different peptide and protein features using multiple Bayesian models we are able to predict high confidence interactions with an overall accuracy of 0.97.Availability and implementation: Domain-Motif Mediated Interaction Prediction (DoMo-Pred) command line tool and all relevant datasets are available under GNU LGPL license for download from http://www.baderlab.org/Software/DoMo-Pred. The DoMo-Pred command line tool is implemented using Python 2.7 and C ++.Contact: gary.bader@utoronto.caSupplementary information: Supplementary data are available at Bioinformatics online.

Uranium bioprecipitation mediated by yeasts utilizing organic phosphorus substrates.

In this research, we have demonstrated the ability of several yeast species to mediate U(VI) biomineralization through uranium phosphate biomineral formation when utilizing an organic source of phosphorus (glycerol 2-phosphate disodium salt hydrate (C3H7Na2O6P·xH2O (G2P)) or phytic acid sodium salt hydrate (C6H18O24P6·xNa(+)·yH2O (PyA))) in the presence of soluble UO2(NO3)2. The formation of meta-ankoleite (K2(UO2)2(PO4)2·6(H2O)), chernikovite ((H3O)2(UO2)2(PO4)2·6(H2O)), bassetite (Fe(++)(UO2)2(PO4)2·8(H2O)), and uramphite ((NH4)(UO2)(PO4)·3(H2O)) on cell surfaces was confirmed by X-ray diffraction in yeasts grown in a defined liquid medium amended with uranium and an organic phosphorus source, as well as in yeasts pre-grown in organic phosphorus-containing media and then subsequently exposed to UO2(NO3)2. The resulting minerals depended on the yeast species as well as physico-chemical conditions. The results obtained in this study demonstrate that phosphatase-mediated uranium biomineralization can occur in yeasts supplied with an organic phosphate substrate as sole source of phosphorus. Further understanding of yeast interactions with uranium may be relevant to development of potential treatment methods for uranium waste and utilization of organic phosphate sources and for prediction of microbial impacts on the fate of uranium in the environment.

BioGRID: A Resource for Studying Biological Interactions in Yeast.

The Biological General Repository for Interaction Datasets (BioGRID) is a freely available public database that provides the biological and biomedical research communities with curated protein and genetic interaction data. Structured experimental evidence codes, an intuitive search interface, and visualization tools enable the discovery of individual gene, protein, or biological network function. BioGRID houses interaction data for the major model organism species--including yeast, nematode, fly, zebrafish, mouse, and human--with particular emphasis on the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe as pioneer eukaryotic models for network biology. BioGRID has achieved comprehensive curation coverage of the entire literature for these two major yeast models, which is actively maintained through monthly curation updates. As of September 2015, BioGRID houses approximately 335,400 biological interactions for budding yeast and approximately 67,800 interactions for fission yeast. BioGRID also supports an integrated posttranslational modification (PTM) viewer that incorporates more than 20,100 yeast phosphorylation sites curated through its sister database, the PhosphoGRID.

Torulaspora delbrueckii in the brewing process: A new approach to enhance bioflavour and to reduce ethanol content

Nowadays, consumers require fermented alcoholic beverages with particular and enhanced flavour profiles while avoiding the health concerns due to high ethanol content. Here, the use of Torulaspora delbrueckii was evaluated for beer production, in both pure and in mixed cultures with a Saccharomyces cerevisiae starter strain (US-05). The yeast interactions were also evaluated. In mixed fermentations with S. cerevisiae, the main analytical characters from T. delbrueckii were comparable with those of the S. cerevisiae starter strain, but the beers were characterized by a distinctive overall analytical and aromatic profile. Indeed, there were interactions between S. cerevisiae and T. delbrueckii, with enhanced ethyl hexanoate (0.048 mg l−1) and ethyl octaonate (0.014 mg l−1) levels at the 1:20 and 1:10 inoculation ratios, respectively; while phenyl ethyl acetate increased in all mix combinations. The presence of T. delbrueckii resulted in reduced β-phenyl ethanol and isoamyl acetate levels, which are responsible for floral and fruity aromas, respectively. Beer produced with T. delbrueckii pure cultures had a low alcohol content (2.66%; v/v), while also showing a particularly analytical and aromatic profile.

Biochemical Changes in Orange Fruit Due to Plant – <i>Penicillium italicum</i> – Antagonism Interactions

One of the most important orange fruit diseases is blue mold which cause by Penicillium italicum that is responsible for important economic losses. This study investigated biochemical changes in exo-mesocarp layers of orange fruits related to host- pathogen- yeast interactions. Initial result showed that among eight strains isolated, the most effective antagonist were belonged to two species of Pichia kluyveri (M45) and Rhodotorula mucilaginosa (M61). These isolates were selected for biochemical evaluation. In order to assessment of biochemical changes, the orange fruits were inoculated with 40 µl of yeast cell suspension and after 24 h, the wounds were inoculated with 20 µl of conidial suspension of P. italicum. The analysis of variance showed that all of the measured biochemical characterises were significant in both layers by treatments (yeast isolates; pathogen; yeast isolates + pathogen and control) (P ≤ 0.01), including POD, CAT and β-1, 3-glucanase activities and total phenolic compounds. Also result showed that when the yeast isolates (M45 or M54) were inoculated into wounds with the pathogen, it stimulated the orange to increase produce of total phenol and enzymes activity (POD, CAT and β-1, 3-glucanase) and these changes were related to incubation time. The result showed that understanding biochemical mechanism derived from plant-pathogen-antagonist interactions is essential for investigating the dynamics of infectious processes.

Biochemical Changes in Orange Fruit Due to Plant – <i>Penicillium italicum</i> – Antagonism Interactions

One of the most important orange fruit diseases is blue mold which cause by Penicillium italicum that is responsible for important economic losses. This study investigated biochemical changes in exo-mesocarp layers of orange fruits related to host - pathogen - yeast interactions. Initial result showed that among eight strains isolated, the most effective antagonist were belonged to two species of Pichia kluyveri (M45) and Rhodotorula mucilaginosa (M61). These isolates were selected for biochemical evaluation. In order to assessment of biochemical changes, the orange fruits were inoculated with 40 µl of yeast cell suspension and after 24 h, the wounds were inoculated with 20 µl of conidial suspension of P. italicum. The analysis of variance showed that all of the measured biochemical characterises were significant in both layers by treatments (yeast isolates; pathogen; yeast isolates + pathogen and control) (P ≤ 0.01), including POD, CAT and β-1, 3-glucanase activities and total phenolic compounds. Also result showed that when the yeast isolates (M45 or M54) were inoculated into wounds with the pathogen, it stimulated the orange to increase produce of total phenol and enzymes activity (POD, CAT and β-1, 3-glucanase) and these changes were related to incubation time. The result showed that understanding biochemical mechanism derived from plant-pathogen-antagonist interactions is essential for investigating the dynamics of infectious processes.

Systematic identification and correction of annotation errors in the genetic interaction map of Saccharomyces cerevisiae.

The yeast mutant collections are a fundamental tool in deciphering genomic organization and function. Over the last decade, they have been used for the systematic exploration of ∼6 000 000 double gene mutants, identifying and cataloging genetic interactions among them. Here we studied the extent to which these data are prone to neighboring gene effects (NGEs), a phenomenon by which the deletion of a gene affects the expression of adjacent genes along the genome. Analyzing ∼90,000 negative genetic interactions observed to date, we found that more than 10% of them are incorrectly annotated due to NGEs. We developed a novel algorithm, GINGER, to identify and correct erroneous interaction annotations. We validated the algorithm using a comparative analysis of interactions from Schizosaccharomyces pombe. We further showed that our predictions are significantly more concordant with diverse biological data compared to their mis-annotated counterparts. Our work uncovered about 9500 new genetic interactions in yeast.

Bayesian hierarchical modelling for inferring genetic interactions in yeast.

SummaryQuantitative fitness analysis (QFA) is a high throughput experimental and computational methodology for measuring the growth of microbial populations. QFA screens can be used to compare the health of cell populations with and without a mutation in a query gene to infer genetic interaction strengths genomewide, examining thousands of separate genotypes. We introduce Bayesian hierarchical models of population growth rates and genetic interactions that better reflect QFA experimental design than current approaches. Our new approach models population dynamics and genetic interaction simultaneously, thereby avoiding passing information between models via a univariate fitness summary. Matching experimental structure more closely, Bayesian hierarchical approaches use data more efficiently and find new evidence for genes which interact with yeast telomeres within a published data set.

Development of sourdough fermented date seed for improving the quality and shelf life of flat bread: study with univariate and multivariate analyses.

The aim of this work was to study the effects of a novel sourdough system prepared by wheat flour supplemented by combination of pulverized date seed, Lactobacillus plantarum, and/or Lactobacillus brevis as well as Saccharomyces cerevisiae on the sourdough characteristics, quality, sensory, texture, shelf life and image properties of Barbari flat bread. The highest sourdough acidity and bread specific volume was obtained with co-culture of Lb. plantarum+Lb. brevis+S. cerevisiae. The results suggest that fermentation is a potential bioprocessing technology for improving sensory aspects of bread supplemented with pulverized date seed, as a dietary fiber resource. Texture analysis of bread samples during 7days of storage indicated that the presence of pulverized date seed in sourdough was able to diminish bread staling. The interaction of baker's yeast and lactic acid bacteria (LAB) has led to increase the particle average size of bread crumb and decrease the area fraction than the LAB samples. It was observed that all treatments of sourdough Barbari breads had higher cell wall thickness than the control Barbari bread. Avrami non-linear regression equation was chosen as useful mathematical model to properly study bread hardening kinetics. In addition, principal component analysis (PCA) allowed discriminating among sourdough and bread specialties. Partial least squares regression (PLSR) models were applied to determine the relationships between sensory and instrumental data.

Structural basis of pathogen recognition by an integrated HMA domain in a plant NLR immune receptor.

Plants have evolved intracellular immune receptors to detect pathogen proteins known as effectors. How these immune receptors detect effectors remains poorly understood. Here we describe the structural basis for direct recognition of AVR-Pik, an effector from the rice blast pathogen, by the rice intracellular NLR immune receptor Pik. AVR-PikD binds a dimer of the Pikp-1 HMA integrated domain with nanomolar affinity. The crystal structure of the Pikp-HMA/AVR-PikD complex enabled design of mutations to alter protein interaction in yeast and in vitro, and perturb effector-mediated response both in a rice cultivar containing Pikp and upon expression of AVR-PikD and Pikp in the model plant Nicotiana benthamiana. These data reveal the molecular details of a recognition event, mediated by a novel integrated domain in an NLR, which initiates a plant immune response and resistance to rice blast disease. Such studies underpin novel opportunities for engineering disease resistance to plant pathogens in staple food crops.

Influence of vintage and selected starter on Torulaspora delbrueckii/Saccharomyces cerevisiae sequential fermentation

The practice of sequential fermentation of grape juice with a Saccharomyces cerevisiae starter strain coupled with a selected culture of a non-Saccharomyces yeast is used to improve the sensory profile and add complexity of wines. In this study, the effect of Torulaspora delbrueckii/S. cerevisiae sequential fermentation on Verdicchio wine under winery conditions was investigated, evaluating grape juices of three different vintages and two S. cerevisiae starter strains. In the 3 years of examination, some of oenological characters of the final wines were influenced by grape juices coming from different vintages. However, in all cases, T. delbrueckii/S. cerevisiae sequential fermentation influenced the analytical profiles of the Verdicchio wines according to the S. cerevisiae starter strain used. Indeed, different behaviours were found for the same T. delbrueckii strain together with the autochthonous Sc151 or the commercial VIN13 S. cerevisiae yeast, indicting that the yeast–yeast interaction plays an important role in analytical profile of wines. On the other hand, specific contributions were seen with T. delbrueckii, which is inoculated in sequential fermentation for three consecutive vintages using different starters.

Solution structure of the PsIAA4 oligomerization domain reveals interaction modes for transcription factors in early auxin response

The plant hormone auxin activates primary response genes by facilitating proteolytic removal of auxin/indole-3-acetic acid (AUX/IAA)-inducible repressors, which directly bind to transcriptional auxin response factors (ARF). Most AUX/IAA and ARF proteins share highly conserved C-termini mediating homotypic and heterotypic interactions within and between both protein families. The high-resolution NMR structure of C-terminal domains III and IV of the AUX/IAA protein PsIAA4 from pea (Pisum sativum) revealed a globular ubiquitin-like β-grasp fold with homologies to the Phox and Bem1p (PB1) domain. The PB1 domain of wild-type PsIAA4 features two distinct surface patches of oppositely charged amino acid residues, mediating front-to-back multimerization via electrostatic interactions. Mutations of conserved basic or acidic residues on either face suppressed PsIAA4 PB1 homo-oligomerization in vitro and confirmed directional interaction of full-length PsIAA4 in vivo (yeast two-hybrid system). Mixing of oppositely mutated PsIAA4 PB1 monomers enabled NMR mapping of the negatively charged interface of the reconstituted PsIAA4 PB1 homodimer variant, whose stoichiometry (1:1) and equilibrium binding constant (KD ∼ 6.4 μM) were determined by isothermal titration calorimetry. In silico protein-protein docking studies based on NMR and yeast interaction data derived a model of the PsIAA4 PB1 homodimer, which is comparable with other PB1 domain dimers, but indicated considerable differences between the homodimeric interfaces of AUX/IAA and ARF PB1 domains. Our study provides an impetus for elucidating the molecular determinants that confer specificity to complex protein-protein interaction circuits between members of the two central families of transcription factors important to the regulation of auxin-responsive gene expression.

Evolutionary and functional analysis of the invariant SWIM domain in the conserved Shu2/SWS1 protein family from Saccharomyces cerevisiae to Homo sapiens.

The Saccharomyces cerevisiae Shu2 protein is an important regulator of Rad51, which promotes homologous recombination (HR). Shu2 functions in the Shu complex with Shu1 and the Rad51 paralogs Csm2 and Psy3. Shu2 belongs to the SWS1 protein family, which is characterized by its SWIM domain (CXC...Xn...CXH), a zinc-binding motif. In humans, SWS1 interacts with the Rad51 paralog SWSAP1. Using genetic and evolutionary analyses, we examined the role of the Shu complex in mitotic and meiotic processes across eukaryotic lineages. We provide evidence that the SWS1 protein family contains orthologous genes in early-branching eukaryote lineages (e.g., Giardia lamblia), as well as in multicellular eukaryotes including Caenorhabditis elegans and Drosophila melanogaster. Using sequence analysis, we expanded the SWIM domain to include an invariant alanine three residues after the terminal CXH motif (CXC…Xn…CXHXXA). We found that the SWIM domain is conserved in all eukaryotic orthologs, and accordingly, in vivo disruption of the invariant residues within the canonical SWIM domain inhibits DNA damage tolerance in yeast and protein-protein interactions in yeast and humans. Furthermore, using evolutionary analyses, we found that yeast and Drosophila Shu2 exhibit strong coevolutionary signatures with meiotic proteins, and in yeast, its disruption leads to decreased meiotic progeny. Together our data indicate that the SWS1 family is an ancient and highly conserved eukaryotic regulator of meiotic and mitotic HR.

Identification of putative interactions between swine and human influenza A virus nucleoprotein and human host proteins

BackgroundInfluenza A viruses (IAVs) are important pathogens that affect the health of humans and many additional animal species. IAVs are enveloped, negative single-stranded RNA viruses whose genome encodes at least ten proteins. The IAV nucleoprotein (NP) is a structural protein that associates with the viral RNA and is essential for virus replication. Understanding how IAVs interact with host proteins is essential for elucidating all of the required processes for viral replication, restrictions in species host range, and potential targets for antiviral therapies.MethodsIn this study, the NP from a swine IAV was cloned into a yeast two-hybrid “bait” vector for expression of a yeast Gal4 binding domain (BD)-NP fusion protein. This “bait” was used to screen a Y2H human HeLa cell “prey” library which consisted of human proteins fused to the Gal4 protein’s activation domain (AD). The interaction of “bait” and “prey” proteins resulted in activation of reporter genes.ResultsSeventeen positive bait-prey interactions were isolated in yeast. All of the “prey” isolated also interact in yeast with a NP “bait” cloned from a human IAV strain. Isolation and sequence analysis of the cDNAs encoding the human prey proteins revealed ten different human proteins. These host proteins are involved in various host cell processes and structures, including purine biosynthesis (PAICS), metabolism (ACOT13), proteasome (PA28B), DNA-binding (MSANTD3), cytoskeleton (CKAP5), potassium channel formation (KCTD9), zinc transporter function (SLC30A9), Na+/K+ ATPase function (ATP1B1), and RNA splicing (TRA2B).ConclusionsTen human proteins were identified as interacting with IAV NP in a Y2H screen. Some of these human proteins were reported in previous screens aimed at elucidating host proteins relevant to specific viral life cycle processes such as replication. This study extends previous findings by suggesting a mechanism by which these host proteins associate with the IAV, i.e., physical interaction with NP. Furthermore, this study revealed novel host protein-NP interactions in yeast.

Yeast population dynamics reveal a potential 'collaboration' between Metschnikowia pulcherrima and Saccharomyces uvarum for the production of reduced alcohol wines during Shiraz fermentation.

The wine sector is actively seeking strategies and technologies that facilitate the production of wines with lower alcohol content. One of the simplest approaches to achieve this aim would be the use of wine yeast strains which are less efficient at transforming grape sugars into ethanol; however, commercial wine yeasts have very similar ethanol yields. We recently demonstrated that Metschnikowia pulcherrima AWRI1149 was able to produce wine with reduced alcohol concentration when used in sequential inoculation with a wine strain of Saccharomyces cerevisiae. Here, different inoculation regimes were explored to study the effect of yeast population dynamics and potential yeast interactions on the metabolism of M. pulcherrima AWRI1149 during fermentation of non-sterile Shiraz must. Of all inoculation regimes tested, only ferments inoculated with M. pulcherrima AWRI1149 showed reduced ethanol concentration. Population dynamics revealed the presence of several indigenous yeast species and one of these, Saccharomyces uvarum (AWRI 2846), was able to produce wine with reduced ethanol concentration in sterile conditions. Both strains however, were inhibited when a combination of three non-Saccharomyces strains, Hanseniaspora uvarum AWRI863, Pichia kluyveri AWRI1896 and Torulaspora delbrueckii AWRI2845 were inoculated into must, indicating that the microbial community composition might impact on the growth of M. pulcherrima AWRI1149 and S. uvarum AWRI 2846. Our results indicate that mixed cultures of M. pulcherrima AWRI1149 and S. uvarum AWRI2846 enable an additional reduction of wine ethanol concentration compared to the same must fermented with either strain alone. This work thus provides a foundation to develop inoculation regimes for the successful application of non-cerevisiae yeast to the production of wines with reduced alcohol.