Article Cite This: J. Agric. Food Chem. XXXX, XXX, XXX−XXX
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Single Nucleotide Polymorphisms and Biochemical Markers As Complementary Tools To Characterize Hops (Humulus lupulus L.) in Brewing Practice Ann Van Holle,*,†,‡ Hilde Muylle,§ Tom Ruttink,§ Anita Van Landschoot,|| Geert Haesaert,† Dirk Naudts,‡ Denis De Keukeleire,⊥ and Isabel Roldán-Ruiz§,# †
Faculty of Bioengineering Sciences, Department of Plants and Crops, Ghent University, Coupure Links 653, 9000 Ghent, Belgium De Proefbrouwerij, Doornzelestraat 20, 9080 Lochristi, Belgium § Flanders Research Institute for Agriculture, Fisheries and Food (ILVO), Caritasstraat 39, 9090 Melle, Belgium || Faculty of Bioengineering Sciences, Department of Biotechnology, Ghent University, Valentin Vaerwyckweg 1, 9000 Ghent, Belgium ⊥ Faculty of Pharmaceutical Sciences, Ghent University, c/o Gontrode Heirweg 115, 9090 Melle, Belgium # Faculty of Sciences, Department of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark Zwijnaarde 71, 9052 Zwijnaarde, Belgium
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‡
S Supporting Information *
ABSTRACT: In brewing practice, the use of the appropriate hop variety is essential to produce consistent and high-quality beers. Yet, hop batches of the same variety cultivated in different geographical regions can display significant biochemical differences, resulting in specific taste- and aroma-related characteristics in beer. In this study, we illustrate the complementarity of genetic and biochemical fingerprinting methods to fully characterize hop batches. Using genotyping-by-sequencing (GBS), a set of 1 830 polymorphic single nucleotide polymorphism (SNP) markers generated 48 unique genetic fingerprints for a collection of 56 commercial hop varieties. Three groups of varieties, consisting of somaclonal variants, could not be further differentiated using this set of markers. Biochemical marker information offered added value to characterize hop samples from a given variety grown at different geographical locations. We demonstrate the power of combining genetic and biochemical fingerprints for quality control of hop batches in the brewing industry. KEYWORDS: Humulus lupulus L., growth location, genotyping, biochemical fingerprinting, quality
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INTRODUCTION
pests and diseases, improved aroma characteristics are among the main targets of hop breeding.4−8 Hop is a labor-intensive crop for growers and a relatively expensive raw material for brewers. The specific taste and aroma profiles of beers depend on the hop variety or combination of varieties used and the character of the addition during the brewing process.9−12 Therefore, quality control of a given hop batch supplied to the brewer is essential, especially on varietal origin.13,14 Distinction between varieties can be based on plant morphological characteristics and the distinctive profile of biochemical components such as hop bitter acids, essential oils, or polyphenols.15−20 However, the varietal origin of processed hop products used in brewing practice can hardly be determined unequivocally by observation of their external appearance, and in current brewing practice, determination of varietal origin of hop batches is mostly based on biochemical markers such as the content of hop bitter acids and essential oils.15,17,20 This is, however, not straightforward because the biochemical profile of hop batches
The hop plant (Humulus lupulus L.), of which the female inflorescences or “hop cones” are used by brewers to provide bitterness, aroma, and flavor to beer, is an herbaceous perennial classified in the family of the Cannabaceae.1,2 Few hundreds of distinct hop varieties are cultivated in different parts of the world including Australia, Europe, New Zealand, North and South America, and South Africa.3 Historically, hop varieties were locally developed as growers’ selections of superior plants in hop yards and were commonly named after a specific region or by a distinctive feature.4,5 In addition to local selection, new varieties also arose through somaclonal variation or by selection of an interesting phenotype coming from the unintended multiplication of a seedling. Several selections are still known by their original cultivation area, such as the ‘Hallertau’ or ‘Tettnang’ regions in Germany and the ‘Saaz’ region in the Czech Republic, or were named after the growers who recognized their potential, like ‘Fuggle’ or ‘Goldings’.4,5 Consequently, several old hop varieties are closely related, yet their exact origins or pedigrees remain unknown. Current breeding efforts still rely on crosses and clonal selections, which give rise to an increasing panel of commercial hop varieties.4,5 Next to traits related to yield and resistance to © XXXX American Chemical Society
Received: February 5, 2019 Revised: March 11, 2019 Accepted: March 13, 2019
A
DOI: 10.1021/acs.jafc.9b00816 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
might already indicate the varietal origin of the hop batch, excluding mislabeling or impurities. The main aim of this study was to investigate the potential complementarity of genetic and biochemical fingerprinting methods to fully characterize hop batches, in order to assign biochemical divergences to either varietal and/or environmental differences. First, the power and limitations of using GBS to differentiate relevant hop varieties were determined. To this end, a reference collection comprising plant material of 56 hop varieties selected among the commercially most relevant genotypes was assembled including varieties of Australian, European, Japanese, New Zealand, North American, and South African origin. The genetic analysis allowed us (i) to investigate the discriminative power of the SNP polymorphisms identified, (ii) to check whether this set of SNPs was able to reveal known pedigree relationships, and (iii) to check whether samples of the same variety from different growth locations displayed identical molecular fingerprints. Next, genetic marker data was combined with biochemical data of hop samples from different growth locations to evaluate and illustrate the added value of combining both sources of information. Relevant hop samples taken from brewing practice including dried cones and pellets were used. Of the 56 hop varieties included in this work, 15 varieties had not been genotyped before using SNP markers,32−34 and 28 of our 78 samples were dried cones or pellets. This allows a realistic evaluation of the research approach suggested for industrial applications.
can vary by function of growth location and processing and storage conditions. Several research groups have reported on the potential of molecular markers for identification and authenticity control of hop batches, as these are independent of environmental, processing, or storage conditions. Different types of molecular markers have been investigated such as random amplified polymorphic DNA (RAPD),21,22 amplified fragment length polymorphism (AFLP),22−25 microsatellites or simple sequence repeats (SSR),13,22,24,26−28 sequence-tagged site (STS) markers,22,29 and diversity array technology (DArT) markers.30 Nowadays, single nucleotide polymorphisms (SNPs) are the most commonly used molecular markers to assess genetic variation in plants. SNPs are widely distributed throughout the genome in both coding and noncoding regions and may display a very high discriminatory power to differentiate genotypes.31 In 2013, Matthews et al.32 were the first to use next-generation sequencing to identify a large number of SNP markers in hops. Using genotyping-bysequencing (GBS), they identified a set of 17 128 SNPs in a collection of 178 hop genotypes and demonstrated that a subset of 3 068 SNPs was sufficient to distinguish all the genotypes investigated. Henning et al.33 identified 7 highly discriminative SNPs as a minimum set of markers that could effectively differentiate a selection of 116 hop genotypes, some of which could not be adequately differentiated using older marker technologies. Yamauchi et al.34 successfully differentiated 21 hop genotypes through the combination of polymorphisms in four SNP-rich regions. Interestingly, hop pellets and dried cones were included in that study, for which contaminations above a 5% admixture level in a mixture of two hop varieties were detected based on electropherogram analysis. Recently, Jiang et al.35 also reported on the use of SNP analysis to discriminate pellet samples of 16 hop varieties. This is relevant as we consider that DNA fragmentation can occur during hop processing and storage. Molecular methods that are useful for dried hop cones or pellets that are commonly used in beer brewing practice are thus needed. Unfortunately, available studies on SNPs in hops are limited to a number of varieties, in some cases of limited commercial value, and included experimental germplasm.32−34 It is therefore not known whether the DNA polymorphisms identified in previous studies are suitable for discrimination and unequivocal identification of commercial hop batches in the brewing industry. In current brewing practice, the differentiation between hop varieties is mostly based on biochemical markers.15,17,20 This is appropriate, as the final determination of the “brewing value” of a hop batch mainly depends on its biochemical properties. Nevertheless, interpretation of these results is not trivial as brewers need to deal with large variations in the quality of the purchased hop batches also due to different growing, processing, and storage conditions.36,37 Consequently, hop pellets of the same variety grown in different geographical regions can display significant biochemical differences, as clearly established in a recent study of our research group.38 In brewing practice it is therefore not obvious to determine whether biochemical differences between hop batches, which are supposed to be of the same variety, are due to mislabeling, presence of impurities, or differences originating from divergent conditions during cultivation, processing, or storage. Complementation of biochemical characterization with a robust molecular fingerprinting method based on SNPs
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MATERIALS AND METHODS
Origin of Plant Materials. Materials of 56 of the commercially most relevant hop varieties were selected including so-called top hops used by craft brewers39 such as Amarillo, Cascade, Centennial, Chinook, Citra, Hallertauer Mittelfrüh, Simcoe, Mosaic, and Zeus (Table 1). Unlike other studies reporting on molecular fingerprinting of hops,23,25,30,33 no wild hops, male breeding lines, experimental germplasm, or other Humulus species were included in this work, as the main purpose was to identify SNPs allowing for discrimination of commercial hop varieties in brewing practice. A total of 78 samples from these 56 varieties was genotyped (Table 1). For each variety we tried to obtain living plant material from reliable sources. Most living plant material used for genotyping was obtained from the National Clonal Germplasm Repository of the United States Department of Agriculture−Agricultural Research Service (USDA-ARS NCGR, Corvallis, OR). If varieties were not available in this collection, Belgian and American hop growers were contacted. However, for 10 hop varieties we were not able to obtain living plant material (Amarillo, Bobek, Citra, Ekuanot, Galaxy, Mosaic, Nelson Sauvin, Simcoe, Spalter, and Zeus). In these cases, only dried hop cones or pellets T90 were used for DNA extraction. Biochemical analysis was performed for a subset of 11 varieties (Amarillo, Cascade, Fuggle, Cobbs Golding, Eastwell Golding, Mathon Golding, Hallertauer Mittelfrüh, Saazer, Styrian Golding, Tettnanger, and Spalter) as dried cones (n = 10) or pellets (n = 7), indicated by their sample code in Table 1. For these 17 samples, genetic and biochemical analysis were performed on the same samples. GBS Library Preparation and SNP Calling. DNA was extracted from 30−50 mg of ground fresh leaf material or 20 mg of ground dry hop cones or pellets T90 using the NucleoSpin Plant II mini kit (Macherey-Nagel, Hoerdt, France). A double-enzyme GBS protocol adapted from Poland et al.40 was followed. One hundred ng of genomic DNA was digested with EcoRI and ApeKI (New England Biolabs, Ipswich, MA), and barcoded adapters were ligated with T4 ligase (New England Biolabs, Ipswich, MA) in a final volume of 50 μL. Ligation products were purified with 1.6×MagNA magnetic beads B
DOI: 10.1021/acs.jafc.9b00816 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry
Table 1. Description of the 78 Hop Samples (from 56 Hop Varieties) Used in This Study, with Their Genetic Origin (the Region in Which They Were Originally Selected)a sample number
variety
genetic origin
material used
harvest year
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59
Amarillo Amarillo Amarillo Amarillo Amarillo Amarillo Bobek Brewer’s Gold Canadian Red Vine Cascade Cascade Cascade Cascade Cascade Cascade Celeia Centennial Challenger Chinook Citra Cobbs Golding Cobbs Golding Columbus Eastwell Golding Eastwell Golding Eastwell Golding Ekuanot Elsasser Eroica Fuggle Fuggle Fuggle H Galaxy Hallertauer Gold Hallertauer Magnum Hallertauer Mittelfrüh Hallertauer Mittelfrüh Hallertauer Mittelfrüh Hallertauer Tradition Mathon Golding Mathon Golding Merkur Mosaic Mt. Hood Nelson Sauvin New Zealand Hallertauer Northern Brewer Nugget Pacific Gem Perle Phoenix Pride of Ringwood Saazer Saazer Saazer-38 Saphir Shinshuwase Simcoe Smaragd
USA, Washington USA, Washington USA, Washington USA, Washington USA, Washington USA, Washington Slovenia England Canada USA, Washington USA, Washington USA, Washington USA, Washington USA, Washington USA, Washington Slovenia USA, Washington England USA, Washington USA, Washington England England USA, Oregon England England England USA, Washington France USA, Idaho England England USA, Oregon Australia Germany, Hallertau Germany, Hallertau Germany, Hallertau Germany, Hallertau Germany, Hallertau Germany, Hallertau England England Germany, Hallertau USA, Washington USA, Oregon New Zealand New Zealand England USA, Oregon New Zealand Germany, Hallertau England Australia Czech Republic, Saaz Czech Republic, Saaz Czech Republic, Saaz Germany, Hallertau Japan USA, Washington Germany, Hallertau
pellets pellets pellets pellets dried cones dried cones pellets plantb plantb plantb plantc plantd dried cones dried cones dried cones plantb plantd plantc plantb dried cones plantc dried cones plantd plantb plantc dried cones pellets plantb plantb plantc dried cones plantb pellets plantb plantb plantc dried cones dried cones plantc plantc dried cones plantc dried cones plantb pellets plantb plantb plantb plantb plantb plantc plantb plantc dried cones plantb plantc plantb dried cones plantc
2013 2013 2014 2014 2015 2015 2012
USA, Idaho USA, Washington USA, Idaho USA, Washington USA, Idaho USA, Washington Slovenia, Ž alec
2015 2015 2015
Australia, Tasmania Germany, Hallertau USA, Washington
C
growth location
2015
USA, Washington
2015
Belgium, Poperinge
biochemical characterization Amarillo_2013_USA(ID) Amarillo_2013_USA(WA) Amarillo_2014_USA(ID) Amarillo_2014_USA(WA) Amarillo_2015_USA(ID) Amarillo_2015_USA(WA)
ref
x x x x x
Cascade_2015_USA x x x x x x CobbsGolding_2015_BEL x x
2015 2015
Belgium, Poperinge USA, Washington
EastwellGolding_2015_BEL
2015
USA, Oregon
Fuggle_2015_USA
2015
Australia, Tasmania
2015 2015
Germany, Hallertau USA, Washington
x x x x x x x x x HallertauerMF_2015_DEU x x
2015
Belgium, Poperinge
2016
USA, Washington
2016
New Zealand, Nelson
2015
Czech Republic, Saaz
2015
USA, Washington
MathonGolding_2015_BEL x x x x x x x x x x x x Saaz_2015_CZE x x x x x DOI: 10.1021/acs.jafc.9b00816 J. Agric. Food Chem. XXXX, XXX, XXX−XXX
Article
Journal of Agricultural and Food Chemistry Table 1. continued sample number 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78
variety Sorachi Ace Southern Brewer Southern Cross Spalter Spalter Select Styrian Golding Styrian Golding Styrian Golding Swiss Tettnanger Tardif de Bourgogne Target Tettnanger Tettnanger Tettnanger Ultra Whitbread’s Golding Willamette Yeoman Zeus
genetic origin Japan South Africa New Zealand Germany, Spalt Germany, Hallertau Slovenia Slovenia Slovenia Switzerland France England Germany, Tettnang Germany, Tettnang Germany, Tettnang USA, Oregon England USA, Oregon England USA, Washington
material used plantb plantb plantb pellets plantc plantb pellets pellets plantb plantb plantb plantb plantc dried cones plantb plantb plantb plantb dried cones
harvest year
growth location
biochemical characterization
2016
Germany, Spalt
Spalter_2016_DEU
2014 2016
Slovenia, Ž alec Slovenia, Ž alec
StyrianGolding_2014_SVN StyrianGolding_2016_SVN
ref x x x x x x
x x x x 2015
2015
Germany, Tettnang
USA, Washington
Tettnanger_2015_DEU x x x x x
If dried cones or pellets were used, also the harvest year and growth location from where the sample was collected are given (see column “growth location”). All samples were genotyped using GBS. A subset of samples, for which the corresponding sample codes are listed under “biochemical characterization”, was additionally characterized biochemically. “ref” indicates the samples that were used as reference for a given variety during genetic analysis (one sample per variety). bPlant material obtained from USDA-ARS NCGR. cPlant material obtained from hop grower in Belgium. d Plant material obtained from hop grower in United States. a
Analysis of Hop Acids. Spectrophotometric measurements of αacids and β-acids were carried out according to the American Society of Brewing Chemists (ASBC) method Hops−6A.53 Extraction of Hop Essential Oil. The hop oil content was determined according to the European Brewery Convention (EBC) method 7.10 using steam distillation.54 Hop samples (20 g) were ground and mixed with 750 mL of deionized water in a 1 L roundbottom flask. After 3 h of distillation, the total volume of hop oil collected was measured. HS-SPME-GC-MS Profiling of Hop Oil Volatiles. The aroma profiling was carried out as previously described.38 In short, 0.1 g of ground hops was weighed into a headspace extraction vial. Headspace solid-phase microextractions (HS-SPME) were automated using a CombiPal autosampler (CTC Analytics, Zwingen, Switzerland). The hop oil volatiles were extracted on a 100 μm PDMS fiber (polydimethylsiloxane; Supelco, Bellefonte, PA) at 50 °C for 45 min. Helium was used as a carrier gas at a flow rate of 1.0 mL/min, and SPME fibers were injected in the split mode (split ratio 1:10, 250 °C, 3 min) in an Ultra Trace gas chromatograph (Thermo Fisher Scientific, Austin, TX). Separation was performed on a Rtx-1 capillary column (40 m × 0.18 mm i.d. × 0.20 μm film thickness). The oven temperature program was as follows: 3 min at 40 °C, followed by a temperature increase of 2 °C/min to 170 °C, followed by an increase of 15 °C/min to a final temperature of 250 °C for 10 min. Detection of hop oil volatiles was achieved by a single-quadrupole mass spectrometer (Thermo Fisher Scientific, Austin, TX) in electron ionization mode at 70 eV, and analysis was performed in the full-scan operating mode (m/z = 40−250). The detected hop oil compounds were identified by mass spectral comparison via Xcalibur software (Thermo Xcalibur 2.2 SP 1.48; Thermo Fisher Scientific, Austin, TX) using the NIST mass spectral library (NIST 2.0, Interscience, Louvain-la-Neuve, Belgium). Processing of the chromatographic data was performed by the Xcalibur data system (Thermo Xcalibur 2.2 SP1.48; Thermo Fisher Scientific, Austin, TX). Data Analysis. To analyze genetic relationships, filtered VCF data were imported in the R 3.5.1 software (R Foundation for Statistical Computing, Vienna, Austria). Only fully informative SNPs (no missing data) were used for analysis, except to study the genetic relationships between the 56 varieties. In this case, loci with
