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Microbiology and Biotechnology Letters

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Fermentation Microbiology  |  Microbial Community

Microbiol. Biotechnol. Lett. 2022; 50(3): 404-413

https://doi.org/10.48022/mbl.2204.04002

Received: April 5, 2022; Revised: June 21, 2022; Accepted: July 11, 2022

A Culture-Independent Comparison of Microbial Communities of Two Maturating Craft Beers Styles

João Costa1, Isabel N. Sierra-Garcia2, and Angela Cunha2*

1Department of Chemistry, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
2CESAM and Department of Biology, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal

Correspondence to :
Angela Cunha,      acunha@ua.pt

Abstract

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The process of manufacturing craft beer involves a wide variety of spontaneous microorganisms, acting in different stages of the brewing process, that contribute to the distinctive characteristics of each style. The objective of this work was to compare the structure of microbial communities associated with two different craft beer styles (Doppelbock and Märzen lagers), at a late maturation stage, and to identify discriminative, or style-specific taxa. Bacterial and fungal microbial communities were analyzed by Illumina sequencing of 16S rRNA gene of prokaryotes and the ITS 2 spacer of fungi (eukaryotes). Fungal communities in maturating beer were dominated by the yeast Dekkera, and by lactic acid (Lactobacillus and Pediococcus) and acetic acid (Acetobacter) bacteria. The Doppelbock barrels presented more rich and diverse fungal communities. The Märzen barrels were more variable in terms of structure and composition of fungal and bacterial communities, with occurrence of exclusive taxa of fungi (Aspergillus sp.) and bacteria (L. kimchicus). Minority bacterial taxa, differently represented in the microbiome of each barrel, may underlie the variability between barrels and ultimately, the distinctive traits of each style. The composition of the microbial communities indicates that in addition to differences related to upstream stages of the brewing process, the contact with the wood barrels may contribute to the definition of style-specific microbiological traits.

Keywords: Acetic acid bacteria, brewing yeasts, Illumina, lactic acid bacteria, microbiomes

Graphical Abstract


Introduction

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Beer is a drink that results from the activity of selected yeasts on a wort, typically prepared from malted barley and water, to which hops are added to provide a bitter-floral taste [1]. Depending on the fermenting processes and on sensory traits, beers are categorized as ales, produced by “top” fermentation, or lagers, produced by “bottom” fermentation” [2]. In ales, the fermentation is carried out by Saccharomyces cerevisiae that tends to concentrate on the surface of the vat [3]. The fermentation of lagers is usually carried out by Saccharomyces pastorianus [4, 5]. Lambic beers differ from ales and lagers, since the fermentation process occurs spontaneously, involving mainly strains of autochthonous yeasts [6, 7]. Artisanal breweries preserved this traditional practice and given the growing interest of consumers in the uniqueness of organoleptic characteristics, of craft beers [8], new malts, hops and additives have been exploited to achieve rich and complex flavors and aromas, that can include notes of coffee, fruits, flowers and spices [9]. In order to further enrich flavor and aroma, some beers are intentionally allowed a long period of maturation, following the initial fermentation by yeasts [10]. For this, the beer is transferred from the brewing vats to oak wood barrels, where a succession of microorganisms will progressively define the chemical and sensorial profile of the final product [11]. The initial phase, corresponds approximately to the first two months of maturation, during which Enterobacteriaceae decline, while small amounts of alcohol are formed and the pH drops due to the production of low concentrations of organic acids, such as acetic, lactic and formic acid [12]. The first fermentative yeast to appear is Hanseniaspora (anamorph Kloeckera), usually two weeks after boiling the wort [12]. Yeasts of the genus Saccharomyces carry out the main fermentation in the following months [13]. In a later phase, the activity of lactic acid bacteria (LAB) and acetic acid bacteria (AAB) leads to an increase in the concentration of lactic acid, acetic acid and the corresponding esters. The marked decrease in pH, causes the progressive inactivation of Saccharomyces [7]. In a final stage, Brettanomyces spp. may become dominant, playing a major role in the development of characteristic flavors and aromas [10].

For the maturation, barrels that had previously contained other drinks are usually preferred [7]. The contact with the new drinks allows the extraction of various compounds, such as phenolics and tannins, involved in the formation of multiple flavors, during maturation. The barrels also represent a seedbank of microorganisms that will contribute to the development of complex microbiomes during maturation and to the development of the particular traits of craft beer [14].

The objective of this work was to compare microbial communities of two craft beer styles, during the maturation in barrels, and to infer on the contribution of stylespecific fungal and bacterial taxa to the development of the particular microbiological traits of each style.

Materials and Methods

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Sampling

For this study, 2 beer styles manufactured by a commercial craft brewery were selected. According to information of the brewery (https://www.cervejavadia.pt/pt/gamas/#gamas), Extra is a Doppelbock Lager (8%) and Rubi is a Märzen Lager (6.3%). A general explanation of the manufacturing process can be found at https:// www.cervejavadia.pt/pt/fabrico/#1. Both beer styles follow the production process of lagers, with some differences in the recipe, namely in terms of hop content. As finished products, Ruby has a lower alcohol content than Extra, and lower Plato (12.1) and IBU (22). It has a cereal and caramel flavor and a distinct hop aftertaste. Extra has higher Plato (18.7) and IBU (25) and the hop is practically undetectable in the final aftertaste. At the moment of sampling, both styles had been fermenting in identical oak wood barrels (225 L) for approximately 7 months. Samples were aseptically collected with a syringe, from 3 barrels of the same lot of Extra (barrels #21, #22 and #25) or Rubi (barrels #9, #11 and #13), transferred to sterile glass bottles and kept at 4℃ until processing.

Fermentation parameters

In order to characterize the degree of maturation of the beer lots, pH, brix and potential alcohol were determined at the moment of sampling from the barrels. pH was measured with a potentiometer (Hanna edge™ Tablet pH Meter Kit). Brix level and alcohol potential were estimated with an electronic refractometer (HI96800 Digital Refractometer).

DNA extraction and sequencing

Cells corresponding to a total volume of 250 ml of beer were concentrated by successive centrifugations of 50-ml aliquots, at 13,000 g, for 15 min (Thermo Scientific Heraeus Megafuge 16). The supernatant was discarded and the pellet was used for DNA extraction with the NZY Soil gDNA Isolation Kit (NZytech), according to the manufacturer’s protocol.

Analysis of bacterial and fungal diversity was based on Illumina sequencing of the hypervariable region V3− V4 of the 16S rRNA genes of prokaryotes and the ITS 2 region between the 5.8S and 28S rRNA genes of fungi (eukaryotes). The DNA was amplified for the hypervariable regions with specific primers and further re-amplified in a limited-cycle PCR reaction to add sequencing adapters and dual indexes. First PCR reactions were performed for each sample using KAPA HiFi HotStart PCR Kit according to manufacturer suggestions and 0.3 μM of PCR primers and 12.5 ng of template DNA in a total volume of 25 μl. The forward primer Bakt_341F 5'-CCTACGGGNGGCWGCAG-3' and the reverse primer Bakt_805R 5'-GACTACHVGGGTATCTAATCC-3' were used for prokaryotes [15, 16] and a pool of forward primers ITS3NGS1_F 5'-CATCGATGAAGAACGCAG-3', ITS3NGS2_F 5'-CAACGATGAAGAACGCAG-3', ITS3NGS3_F 5'-CACCGATGAAGAACGCAG-3', ITS3NGS4_F 5'-CATCGATGAAGAACGTAG-3', ITS3NGS5_F 5'-CATCGATGAAGAACGTGG-3', and ITS3NGS10_F 5'-CATCGATGAAGAACGCTG-3' and reverse primer ITS4NGS001_R 5'-TCCTSCGCTTATTGATATGC-3' was used for fungi [17]. The PCR conditions involved a 3 min denaturation at 95℃, followed by 25 cycles of 98℃ for 20 s, 55℃ (bacterial region) / 60℃ (fungal region) for 30 s and 72℃ for 30 s and a final extension at 72℃ for 5 min. Second PCR reactions added indexes and sequencing adapters to both ends of the amplified target region according to manufacturer’s recommendations (Illumina, 2013). Negative PCR controls were included for all amplification procedures. PCR products were one-step purified and normalized using SequalPrep 96-well plate kit (ThermoFisher Scientific) [18] pooled and pair-end sequenced at Genoinseq (Cantanhede, Portugal) in the Illumina MiSeq® sequencer with the V3 chemistry, following the manufacturer’s instructions (Illumina, USA). Sequences are available from the NCBI under Bioproject number PRJNA725177.

Processing of sequencing data and statistical analyses

Raw reads were extracted from Illumina MiSeq® System in fastq format and quality-filtered with PRINSEQ version 0.20.4 [19] to remove sequencing adapters, reads with less than 100 bases for samples targeting ITS region and 150 for samples targeting 16S rRNA gene, and trim bases with an average quality lower than Q25 in a window of 5 bases. The forward and reverse reads were merged by overlapping paired-end reads with AdapterRemoval version 2.3.0 [20] using default parameters. ITSx version 1.1.2 [21] was used on samples targeting the ITS region to extract the highly variable fungal ITS2 subregion from the merged reads. Sequences containing ITS2 subregions with less than 100 bases were discarded. The QIIME2 package version 2020.2.0 [22] was used for Amplicon Sequence Variant (ASV) generation and taxonomic identification. Chimeric sequences had been identified and removed via the consensus method in DADA2. Taxonomy was assigned to representative ASVs using q2-feature classifier plugin [23] and the pre-trained Naïve Bayes classifier based on SILVA 138 OTUs full-length sequences in the case of 16S rRNA While, UNITE dynamic database v. 8.2 [24] was applied for fungi ITS2 DNA sequences. Downstream analysis were performed on R v4.0 [8] and the Phyloseq [9] and Vegan package [25]. All ASVs not classified at phylum level were removed. The relative abundances of the taxonomic groups in each sample, was calculated as the cumulative abundance of ASVs assigned to each functional group. Plots were visualized using the ggplot2 package [26]. Sequencing coverage was evaluated by rarefaction analysis. Datasets were normalized to the same sequencing depth by random subsampling. Alpha diversity indices (Chao1, Shannon and Simpson) were calculated on rarified dataset to reflect the diversity and richness of the fungal and bacterial communities. Statistical differences in alpha diversity indexes between both Extra and Rubi style were determined by the oneway ANOVA test using the “aov” function in R. In addition, beta diversity analysis of the bacterial and fungal communities normalized by relative abundances was evaluated using principal components analysis (PCoA) based on Jaccard similarity coefficient matrices using the “ordinate” function in the Phyloseq package. Significant different clusters were determined by PERMANOVA analysis using the “adonis” function in Vegan package. Shared and unshared ASVs among the beer samples were shown with a Venn diagram [27] at species and genus level. Microbial taxonomic compositions were expressed as relative abundances at the species levels. The NCBI accession number of the sequences reported in this paper correspond to BioProject PRJNA725177.

Results and Discussion

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Descriptors of fermentation

The values of the parameters related with the fermentation processes, determined at the moment of sampling, are summarized in Table 1.

Table 1 . Values of pH, brix and potential alcohol determined in the barrels at the moment of sampling.

StyleLotBarrelpHBrixPotential alcohol
ExtraB055EX#213.6911.06.1
#223.6811.16.1
#253.7011.06.1
RubiA092SL#93.376.83.7
#113.356.63.6
#133.557.54.1


The ranges of pH were 3.68−3.70 in Extra and 3.35− 3.55 in Rubi. Values of Brix (11.0−11.1) and potential alcohol (6.1) were also slightly higher in Extra. Before being used for the maturation of this lot of beer, barrels #21, #22 and #25 had previously contained muscat wine and barrels #9, #11 and #13 had contained red wine (personal communication). At the moment of sampling, the fermentation parameters were coherent with the distinctive traits of two craft lagers, being Extra characterized by higher Plato degree and alcohol content. The pH and Brix values indicate that Extra is sweeter and less sour than Rubi.

Fungal diversity

A total of 570,250 high quality merged ITS reads were obtained. Filtering, denoising and removal of chimeras resulted in 350,950 high quality sequences. The number of sequences ranged from 72,819 to 142427 (Table S1). A total of 178 fungal ASVs was generated. The number of fungal ASVs ranged from 48 to 93 in Extra, and from 70 to 116 in Rubi datasets (Table 2).

Table 2 . Estimates of species richness and diversity of fungal communities in Extra and Rubi beer barrels.

SampleASVsaChao1bShannoncSimpsond
Extra #2148482.070.83
Extra #226767.52.450.87
Extra #259398.62.530.86
Rubi #117070.51.880.72
Rubi #139090.22.160.77
Rubi #9116117.23.140.92

aASVs: Amplicon Sequence Variant

bChao1: Species richness estimator

cShannon index of biodiversity (>0, higher more diverse)

dSimpson diversity index (0-1; 0 = most simple)

Rarefaction analyses showed that all the samples reached the saturation plateau, indicating that the sequencing effort was sufficient to cover most of fungal diversity in these beer samples (Fig. S1). The number of ASVs as an indicator of species richness was overall higher in Rubi (mean 92 ± 23) in comparison with Extra style (mean 69 ± 23). Shannon and Simpson diversity indices were the highest in Rubi #9 (Shannon 3.14; Simpson 0.92) and the lowest on Rubi #11 (Shannon 1.88; Simpson 0.72). However, ANOVA analysis did not show a significant effect of the style of beer (Extra or Rubi) on the diversity indices such as number of observed ASVs (p = 0.291) or Shannon (p = 0.927), Chao1 (p = 0.241) or Simpson (p = 0.441) estimates.

A total of 63 different ASVs were identified in the two beer styles. Of these, 13 ASVs were found in relative abundance ≥1% (Fig. 1, Table S3). ASVs with a relative abundance ≥1% were assigned to the yeast genera Saccharomyces, Dekkera, Pichia, Zygosaccharomyes and Debaromyces and the molds Cladosporium, Penicillium, Aspergillus and Wallemia (Fig. 1).

Figure 1.Relative abundance of fungal taxa (species level or above) in the beer styles.

As often observed in spontaneously-fermented craft beer, Saccharomyces was not dominant [28, 29]. Dekkera was the most abundant genus in both beer styles (Fig. 1) being represented by the species D. bruxellensis, D. anomala and D. custersiana (Table S3). Dekkera designates the teleomorph state of Brettamomyces that is common in fruits, but considered as a contaminant in wine, cider and industrial beer [30]. The dominance of Dekkera in the yeast community is, however, a common trait of the mature fungal microbiomes of sour beer, indicating that a process of souring is occurring during the maturation [29, 31]. Because of their capacity to produce esters and ferment the cellobiose of wood, their activity is particularly relevant during the maturation phase, contributing to the fruity flavors and to a more complex sensorial profile of the final product [30, 32]. Pichia are highly tolerant to ethanol and can degrade xylose and cellulose, traits that underlie their abundance in the microbiome of wooden-aged beer [11, 28]. Zygosaccharomyces is associated with the development of fruity flavors [33]. Aspergillus, Penicillium and Cladosporium were detected. Molds are present in the cereal grains [34]. In industrial beer, they are associated with spoilage and development of off-flavours [35]. In the particular case of craft beer maturated in wood barrels, lignocellulose and hemicellulose degrading fungi [14] can actually contribute to the saccharification of wood compounds, increasing the alcoholic potential and clarity of beer and providing particular imprints to the final flavor [36]. Wallemia, although less reported in craft beer, was detected in survey of commercial beer in different European countries [35].

Fungal communities betadiversity, based on the Jaccard similarity coefficient, showed that the structure of the fungal species in Extra and Rubi styles were different, as there were separated by the axis 1. However, the PERMANOVA analysis indicated that the beer style did not have a significant effect in the fungal communities (p = 0.1). Despite this, fungal communities from the three Extra barrels (#21, #22 and #25) were closely grouped, confirming a higher degree of similarity among these communities than among the fungal communities of the Rubi barrels (Fig. 2). This is consistent with the taxonomic composition represented in Fig. 1, which also shows a higher variability among Rubi barrels than among Extra barrels. Main differences were related with the higher dominance of Dekkera custersiana in Rubi barrel #11, Dekkera bruxellensis in Rubi barrel #13 and the presence of the molds Cladosporium sphaerosmermum and Penicillium corylophilum in Rubi barrel #9. Considering that the presence of molds may be an effect of the contact with the wood barrels, the results confirm that changes in the structure and composition of the fungal community represent an important biological mechanism by which the well-known impact of the wood barrels on the final characteristics of craft beers, is exerted [37]. In this case, the structure of fungal communities in the Rubi barrels was more variable, possibly as an effect of the lower selective pressure represented by the alcohol content. In fact, it was among Rubi samples that the lowest and highest value for alpha diversity indexes were observed (Table 2).

Figure 2.PCoA analysis of the fungal community structure in the two beer styles using Jaccard distance.

The number of fungal species (ASVs) shared between the beer styles was higher than the amount of species (ASVs) found exclusively in one of the beer styles (Fig. 3). Most of the shared ASVs were found in higher relative abundance than the ASVs particular in each beer style (Fig. 3, Table S3). In accordance to what it was observed previously, the number of ASVs present solely in Rubi barrels was higher (19 ASVs) than in the Extra barrels (7 ASVs), but these species were found in low relative abundances.

Figure 3.Venn diagram of all fungal ASVs in the two of beer styles. The numbers indicate how many ASVs were shared or exclusive in the samples.

Bacterial diversity

Amplicon-based analysis of the V3−V4 region of the 16S rRNA gene generated a total of 484,836 sequences. Filtering, denoising and removal of chimeras resulted in 150,254 high quality merged sequences. The number of bacterial sequences ranged from 15,149 to 38,250 (Table S1). Like for fungal communities, the rarefaction analyses of bacterial species showed that the saturation curves reached a plateau, indicating that the sequencing effort covered the bacterial diversity existent in the beer samples (Fig. S2). A total of 32 ASVs was generated. The number of bacterial ASVs was similar in the two beer styles, ranging from 10 to 18 and from 9 to 17 in Extra and Rubi datasets, respectively (Table 3). Alpha diversity estimates were similar in all beer samples (Table 3). As for fungal communities, the ANOVA analysis failed to demonstrate a significant effect of the style of beer (Extra or Rubi) on indicators of richness and diversity in bacterial communities (ANOVA, p > 0.05).

Table 3 . Estimates of species richness and diversity of bacterial communities in Extra and Rubi beer barrels.

SampleASVsaChao1bShannoncSimpsond
Extra #2110101.450.74
Extra #2210101.860.82
Extra #2518181.880.81
Rubi #11991.720.80
Rubi #1317171.960.83
Rubi #910101.750.81

aASVs: Amplicon Sequence Variant

bChao1: Species richness estimator

cShannon index of biodiversity (>0, higher more diverse)

dSimpson diversity index (0-1; 0 = most simple)

Considering the two beer styles, a total of 14 different genera were identified (Table S4), but only 3 of them with relative abundance ≥1% (Fig. 4). These dominant genera corresponded to Pediococcus (P. damnosus), Lactobacillus (L. acetotolerans)), and Acetobacter (Table S4 and Fig. 4). The distribution of these genera was more variable between Extra samples, than between Ruby samples. Extra barrel #21 was dominated by Pediococcus (99%), while Extra barrel #22 showed the highest proportion of Acetobacter, in all beer samples (22%) and Extra barrel #25 showed the highest abundance of Lactobacillus among Extra samples. On the contrary, the distribution of the bacterial genera was more similar among Rubi barrels.

Figure 4.Relative abundance of bacterial taxa (genera) in the beer styles.

LAB (Firmicutes) and AAB (Proteobacteria) are important players in the process of slight souring, that is often valued as contributing to the development of the beer character [38]. In fact, the species identified in this analysis can be considered as common in different craft sour beers [11]. In general, the contribution of Lactobacilli is mostly the production of lactic acid, with a minor impact in flavor. P. damnosus (formerly P. cerevisiae) is the most common Pediococcus species in sour beers, being more tolerant to hop and low pH than Lactobacilli [10] and very persistent in wood barrels [14]. Pediococci produce diacetyl, that gives an undesirable buttery flavor. However, in craft beer this effect is tolerable because some non-Saccharomyces yeasts degrade diacetyl [33]. ABB of genus Acetobacter, and particularly the species A. pasteurianus, are also characteristic of lambic and sour beer microbiomes [11]. As strict aerobes, they develop at the surface, taking advantage of the air inside the barrels [12]. A. pastorianus is present since early stages of maturation in wooden barrels, but the relative abundance increases as maturation progresses [39].

The proportion between LAB and AAB is critical, as an excessive production of acetic acid and ethyl acetate by the later can lead to an unpleasant flavor [10]. Although the proportion of LAB was much higher that the proportion of AAB, the ratio between these two groups was more stable in Rubi. In Extra, a very high proportion of Acetobacter was found in the community represented in barrel #22, making it structurally dissimilar from the communities represented in the other Extra barrels.

PCoA of bacterial communities based on Jaccard similarity coefficient (Fig. 5) revealed that the structure of bacterial communities was different within and between beer styles. There was no exact match between clusters and beer styles, as confirmed by the PERMANOVA analysis (p = 0.1), indicating that bacterial communities differ between and within styles. For each of the styles, there was one sample that corresponded to a quite different community (#9 for Rubi style and #22 for Extra style). Considering the pattern of clustering observed in the PCoA (Fig. 5) and the representation of dominant genera (Fig. 4), the intra-style variation may be related with Acetobacter as well as with minority taxa (Table S4). In fact, although the 3 dominant genera, each represented with more than 1% relative abundance, were ubiquitously common to all barrels of both beer styles, there are 2 less abundant taxa identified as Uncultured Morganellaceae and Pseudomonas, that were present in both beer styles but not presented in all the barrels of each style (Fig. 6). Furthermore, six other rare genera were found almost exclusively in one barrel of Extra. Sphingobacterium, Flavobacterium, Acinetobacter, Chryseobacterium and Serratia were only detected in Extra #25 while Enterobacter was only detected in Extra #21. On the other hand, Leuconostoc was detected in Rubi barrels #11 and #9, and the taxa Candidatus Cardinium and Enhydrobacter were only detected in Rubi barrel #13 (Fig. 6).

Figure 5.PCoA analysis of the bacterial community structure in the two beer styles using Jaccard distance.

Figure 6.Venn diagram of all bacterial ASVs identified in the two of beer styles. The numbers indicate how many ASVs were shared or exclusive in the samples.

An integrative perspective on the results provides some clues for the organoleptic complexity and diversity of craft beer and for the wide range of factors that may affect the dynamics of microbial communities and ultimately, the distinctive traits of each particular style. Extra, that is stronger in terms of body and alcohol, was characterized by more similar fungal communities. The dominance of Dekkera bruxellensis may contribute to the fruity flavors, characteristic of Doppelbocks. Although in minority, Sacharomyces were also well represented in fungal communities of Extra, and may also contribute to the distinctive traits of this style. The wild species S. paradoxus was well represented in Extra beer, but below the 1% threshold in Rubi. S. paradoxus, like other wild Saccharomyces, is unable to use maltotriose but it has been recently demonstrated that with the adequate handling, it can be used to craft new full-bodied beers, with a clean flavor profile [40]. Rubi, has a lighter character, in terms of body and alcohol. The higher abundance of Wallemia, that can originate from water, the oak barrels, dust or human contact, may point to a higher risk of contamination of Ruby style beers.

There was a significant variation between barrels, in terms of composition of the fungal community. Dekkera was still dominant but Saccharomyces was much less represented. On the other hand, molds were relatively more abundant in the fungal community of Rubi barrels and may contribute to the clarity of the final product. The contact with the wood barrels seems have an important effect on the fungal community, that includes several cellulose and hemi-cellulose degrading species. Bacterial communities of bacteria were dominated by LAB, but AAB were also represented, indicating that a souring process is progressing during maturation. However, the structure of bacterial communities was more variable within each style than fungal communities, indicating that bacterial and fungal communities are responding to different drivers, during the maturation process.

Aknowledgments

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The authors are grateful to Essência D’Alma craft brewery and to master brewer Nicolas Billard for the internship opportunity given to João Costa and for providing the beer samples. We acknowledge financial support to CESAM by FCT/MCTES (UIDP/50017/2020+UIDB/50017/2020+LA/P/0094/2020), through national funds.

References

Go to
  1. De Keukeleire D. 2000. Fundamentals of beer and hop chemistry. Quim. Nova 23: 108-112.
    CrossRef
  2. Salanță LC, Coldea TE, Ignat MV, Pop CR, Tofană M, Mudura E, et al. 2020. Non-alcoholic and craft beer production and challenges. Processes 8: 1382.
    CrossRef
  3. Bokulich NA, Bamforth CW, Mills DA. 2012. Brewhouse-resident microbiota are responsible for multi-stage fermentation of American coolship ale. PLoS One 7: e35507.
    Pubmed KoreaMed CrossRef
  4. Monerawela C, Bond U. 2018. The hybrid genomes of Saccharomyces pastorianus: A current perspective. Yeast 35: 39-50.
    Pubmed CrossRef
  5. Nevoigt E. 2008. Progress in metabolic engineering of Saccharomyces cerevisiae. Microbiol. Mol. Biol. Rev. 72: 379-412.
    Pubmed KoreaMed CrossRef
  6. Walker GM, Stewart GG. 2016. Saccharomyces cerevisiae in the production of fermented beverages. Beverages 2: 30.
    CrossRef
  7. Spitaels F, Wieme AD, Janssens M, Aerts M, Daniel H-M, Van Landschoot A, et al. 2014. The microbial diversity of traditional spontaneously fermented lambic beer. PLoS One 9: e95384.
    Pubmed KoreaMed CrossRef
  8. Aquilani B, Laureti T, Poponi S, Secondi L. 2015. Beer choice and consumption determinants when craft beers are tasted: An exploratory study of consumer preferences. Food Qual. Prefer. 41: 214-224.
    CrossRef
  9. Mastanjević K, Krstanović V, Lukinac J, Jukić M, Lučan M, Mastanjević K. 2019. Craft brewing-is it really about the sensory revolution? Kvasný Průmysl. 65: 13-16.
    CrossRef
  10. Bossaert S, Crauwels S, De Rouck G, Lievens B. 2019. The power of sour-a review: old traditions, new opportunities. Brewingscience 72: 78-88.
  11. Dysvik A, La Rosa SL, De Rouck G, Rukke E-O, Westereng B, Wicklund T. 2020. Microbial dynamics in traditional and modern sour beer production. Appl. Environ. Microbiol. 86: e00566-20.
    Pubmed KoreaMed CrossRef
  12. Bossaert S, Winne V, Van Opstaele F, Buyse J, Verreth C, Herrera-Malaver B, et al. 2020. Description of the temporal dynamics in microbial community composition and beer chemistry in sour beer production via barrel ageing of finished beers. Int. J. Food Microbiol. 339: 109030.
    Pubmed CrossRef
  13. Rodhouse L, Carbonero F. 2019. Overview of craft brewing specificities and potentially associated microbiota. Crit. Rev. Food Sci. Nutr. 59: 462-473.
    Pubmed CrossRef
  14. De Roos J, Van der Veken D, De Vuyst L. 2019. The interior surfaces of wooden barrels are an additional microbial inoculation source for lambic beer production. Appl. Environ. Microbiol. 85: e02226-18.
    Pubmed KoreaMed CrossRef
  15. Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. 2011. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 5: 1571-1579.
    Pubmed KoreaMed CrossRef
  16. Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. 2013. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 41: e1.
    Pubmed KoreaMed CrossRef
  17. Tedersoo L, Bahram M, Põlme S, Kõljalg U, Yorou NS, Wijesundera R, et al. 2014. Global diversity and geography of soil fungi. Science 346: 1256688.
  18. Comeau AM, Douglas GM, Langille MG. 2017. Microbiome helper: a custom and streamlined workflow for microbiome research. mSystems 2: e00127-16.
    Pubmed KoreaMed CrossRef
  19. Schmieder R, Edwards R. 2011. Quality control and preprocessing of metagenomic datasets. Bioinformatics 27: 863-864.
    Pubmed KoreaMed CrossRef
  20. Schubert M, Lindgreen S, Orlando L. 2016. AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Res. Notes 9: 88.
    Pubmed KoreaMed CrossRef
  21. Bengtsson‐Palme J, Ryberg M, Hartmann M, Branco S, Wang Z, Godhe A, et al. 2013. Improved software detection and extraction of ITS1 and ITS 2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods Ecol. Evol. 4: 914-919.
    CrossRef
  22. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37: 852-857.
  23. Bokulich NA, Bergsveinson J, Ziola B, Mills DA. 2015. Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance. Elife 4: e04634.
    Pubmed KoreaMed CrossRef
  24. Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, et al. 2018. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin. Microbiome 6: 90.
    Pubmed KoreaMed CrossRef
  25. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. 2019. Vegan: community ecology package (version 2.5-6). Comprehensive R Arch. Network.
  26. Wickham H. 2016. ggplot2-Elegant Graphics for Data Analysis. Springer International Publishing, Cham, Switzerland.
  27. Bardou F, Ariel F, Simpson CG, Romero-Barrios N, Laporte P, Balzergue S, et al. 2014. Long noncoding RNA modulates alternative splicing regulators in Arabidopsis. Dev. Cell 30: 166-176.
    Pubmed CrossRef
  28. Ver Eecke H, Lambert J, Fetter L, Stout G, Spindler M. 2017. Presented at the 2017 SIMB Annual Meeting and Exhibition.
  29. Shayevitz A, Harrison K, Curtin CD. 2020. Barrel-induced variation in the microbiome and mycobiome of aged sour ale and imperial porter beer. J. Am. Soc. Brew. Chem. 79: 33-40.
    CrossRef
  30. Kochláňová T, Kij D, Kopecká J, Kubizniaková P, Matoulková D. 2016. Non-Saccharomyces yeasts and their importance in the brewing industry Part I - Brettanomyces (Dekkera). Kvasný Průmysl. 62: 198-205.
    CrossRef
  31. Tyakht A, Kopeliovich A, Klimenko N, Efimova D, Dovidchenko N, Odintsova V, et al. 2021. Characteristics of bacterial and yeast microbiomes in spontaneous and mixed-fermentation beer and cider. Food Microbiol. 94: 103658.
    Pubmed CrossRef
  32. Basso RF, Alcarde AR, Portugal CB. 2016. Could non-Saccharomyces yeasts contribute on innovative brewing fermentations? Food Res. Int. 86: 112-120.
    CrossRef
  33. Methner Y, Hutzler M, Matoulková D, Jacob F, Michel M. 2019. Screening for the brewing ability of different non-Saccharomyces yeasts. Fermentation 5: 101.
    CrossRef
  34. Noots I, Delcour JA, Michiels CW. 1999. From field barley to malt: detection and specification of microbial activity for quality aspects. Crit. Rev. Microbiol. 25: 121-153.
    Pubmed CrossRef
  35. Sobel J, Henry L, Rotman N, Rando G. 2017. BeerDeCoded: the open beer metagenome project. F1000Res. 6: 1676.
    Pubmed KoreaMed CrossRef
  36. Nigam D, Asthana M, Kumar A. 2018. Penicillium: a fungus in the wine and beer industries, pp. 187-200. In: New and Future Developments in Microbial Biotechnology and Bioengineering. Ed. Elsevier.
  37. Shayevitz AM. 2018. Do oak barrels contribute to the variability of the microbiome of barrel-aged beers? Oregon State University.
  38. Tenhovirta S. 2019. The effects of lactic acid bacteria species on properties of sour beer. University of Helsinki.
  39. De Roos J, Verce M, Aerts M, Vandamme P, De Vuyst L. 2018. Temporal and spatial distribution of the acetic acid bacterium communities throughout the wooden casks used for the fermentation and maturation of lambic beer underlines their functional role. Appl. Environ. Microbiol. 84: e02846-02817.
    Pubmed KoreaMed CrossRef
  40. Nikulin J, Vidgren V, Krogerus K, Magalhães F, Valkeemäki S, Kangas-Heiska T, et al. 2020. Brewing potential of the wild yeast species Saccharomyces paradoxus. Eur. Food Res. Technol. 246: 2283-2297.
    CrossRef

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