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Composition of low-molecular-weight glutenin subunits in common wheat (Triticum aestivum L.) and their effects on the rheological properties of dough

  • Sławomir Franaszek EMAIL logo and Bolesław Salmanowicz
Published/Copyright: June 24, 2021
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Open Life Sciences
From the journal Open Life Sciences Volume 16 Issue 1

Abstract

The main purpose of this research was the identification and characterization of low-molecular-weight glutenin subunit (LMW-GS) composition in common wheat and the determination of the effect of these proteins on the rheological properties of dough. The use of capillary zone electrophoresis and reverse-phase high-performance liquid chromatography has made it possible to identify four alleles in the Glu-A3 and Glu-D3 loci and seven alleles in the Glu-B3 locus, encoding LMW-GSs in 70 varieties and breeding lines of wheat tested. To determine the technological quality of dough, analyses were performed at the microscale using a TA.XT Plus Texture Analyzer. Wheat varieties containing the Glu-3 loci scheme (Glu-A3b, Glu-A3f at the Glu-A3 locus; Glu-B3a, Glu-B3b, Glu-B3d, Glu-B3h at the Glu-B3 locus; Glu-D3a, Glu-D3c at the Glu-D3 locus) determined the most beneficial quality parameters.

Keywords: low-molecular-weight glutenin subunits; dough rheology; wheat; capillary zone electrophoresis; reverse-phase high-performance liquid chromatography

1 Introduction

Wheat (Triticum aestivum L.) is a cereal species belonging to the family of Poaceae. Owing to its very good nutritional values (a rich source of starch, proteins, vitamins, minerals) and technological properties essential in the food industry, wheat is of great economic importance and is one of the most commonly grown cereals worldwide [1]. Analyses of the qualitative–quantitative composition of wheat storage proteins are a rich source of information regarding the technological properties of flour and are also used to select varieties in terms of desirable traits. The gluten complex, consisting of gliadins and glutenins, plays an important role during plant development and determines the technological use of wheat [2]. Glutenins are polymeric proteins that are divided into high-molecular-weight (HMW) glutenins with a molecular mass of 75–120 kDa and low-molecular-weight (LMW) glutenins with a mass of 20–55 kDa [3]. HMW glutenin subunits (HMW-GSs) account for nearly 10% of gluten proteins and determine 50–70% of the technological quality of the wheat grain, while LMW glutenin subunits (LMW-GSs) account for about 50% of gluten proteins and determine 30% of the technological quality [3]. With the separation of glutenin proteins on a polyacrylamide gel, it is possible to distinguish four regions of protein bands: A, B, C, and D [4]. The region A consists of HMW-GSs, while the LMW-GSs are located in regions B, C, and D. Additionally, in the C and D regions, there are α-, γ-, and ω-gliadins. The synthesis of proteins belonging to the LMW-GS group is mainly controlled by Glu-3 loci located on the short arms of the first group of chromosomes, in the vicinity of the Gli-1 loci complex responsible for coding of both γ- and ω-gliadins [3]. In recent years, based on the qualitative analysis, increased protein content in grains of wheat, which resulted in the presence of certain allelic variants encoding LMW-GSs, was observed [5]. In addition, biochemical and rheological analyses enabled the demonstration of both positive and negative effects of individual LMW subunit encoded by the Glu-3 loci on the technological parameters of wheat flour, dough, and finished bread [5,6,7]. It was also shown that the presence of LMW-GSs encoded by the Glu-A3 loci positively affects the viscoelastic properties, while the subunits encoded by the Glu-B3 loci are important in the creation of mechanical parameters of dough (sodium dodecyl sulfate [SDS] sedimentation index, dough mixing time, dough resistance, and the ratio of dough work to resistance) [8,9]. So far, capillary zone electrophoresis (CZE) and reverse-phase high-performance liquid chromatography (RP-HPLC) methods were used to identify LMW-GSs in a very limited range. In previous studies, scientists only distinguished a group of proteins without detailed identification or identified individual LMW-GS [10,11,12,13,14].

The objective of this study was to identify HMW-GSs using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and LMW-GSs in common wheat (Triticum aestivum L.) using CZE and RP-HPLC and to investigate their effect on the technological properties of wheat dough. The compositions of HMW-GSs and LMW-GSs were characterized in the analyzed plant material. Moreover, the technological quality of wheat and rheological analyses using a TA.XT Plus Texture Analyzer with Kieffer Rig (Stable MicroSystem) was determined at the microscale.

2 Materials and methods

2.1 Plant material

The plant material consisted of 57 varieties and 13 breeding lines of winter wheat (Triticum aestivum L.). The experimental material was cultivated at Smolice Plant Breeding Station in the years 2010–2012. In the first year, plant material was tested for the identification of HMW-GSs and LMW-GSs. In the last year, plant material was tested for technological quality. Plants were grown on 10 m2 in two replications, each on podzolic soil with clayey soil class IIIa. Peas were used as forecrop, and the fertilization dose was, respectively, 110 N, 60 P, and 90 K (kg ha−1) each year. Standard plant protection products against fungal diseases and pests were used during the experiment. The material was harvested to avoid inaccuracies.

Additionally, 22 reference varieties were used in this study (Table 1). This material was obtained from the Australia Winter Cereals Collection and is recommended as a standard for LMW-GSs [15]. These varieties were homozygous, with a strictly defined composition of LMW-GSs.

Table 1

List of the 22 foreign reference varieties with a strictly defined composition of LMW-GSs

Varieties Alleles Country of origin
Glu-A3 Glu-B3 Glu-D3
Alva a d a Portugal
Arcane c c a France
Bastian a i a France
Chara b b b Australia
Cheyenne c e f USA
Chinese Spring a a a China
Democrat a h a France
Gabo b b b Australia
Gluclub e d a Australia
Insygnia f c c Australia
Isis e f a Australia
Jufy-1 e i d Belgium
Kharkov e g a Russia
Kukri d h b Australia
Newbury c c c UK
Norin-61 d i c Japan
Norstar c b b Canada
Orca d d e France
Pato Argentino d i e Argentina
Radja e f b France
Rescue f h a Canada
Thatcher e h e Canada

2.2 Extraction of HMW glutenins and SDS-PAGE separation

The characterization of HMW-GSs was performed according to the methods of Tohver [16]. Material for protein extraction was wheat flour obtained from milling a single grain. HMW-GSs were extracted according to the procedure described by Salmanowicz [17] and Dai et al. [18]. The supernatants were transferred to clean microcentrifuge tubes (1.5 mL) and stored at 4°C until separation. A total of 7 µL of the supernatants were loaded onto stacking gel, including 4.5% (w/v) acrylamide, and HMW-GS proteins were separated on resolving gel containing 11.5% (w/v) acrylamide. SDS-PAGE was carried out using Protean II xi gel apparatus (Bio-Rad, Hercules, CA, USA) at 240 V for 4.5 h. Gels were stained overnight with Coomassie Brilliant Blue G-250.

2.3 Extraction of LMW glutenins and separation

LMW-GS proteins were extracted and analyzed using CZE and RP-HPLC techniques as three replicates. Material for protein extraction was obtained from flour that was obtained from milling a single grain. The LMW-GS fraction for the CZE analyses was extracted according to the method described by Salmanowicz et al. [19]. To carry out analyses with RP-HPLC, the LMW-GSs were extracted according to Salmanowicz [20] with some modifications [21]. Capillary electrophoretic separations of LMW-GSs were carried out on the P/ACE apparatus with the Beckman Coulter MDQ system. Silica capillaries with an internal diameter of 50 μm and a total length of 30.2 cm were used for the separation of proteins (the detector length was 21 cm). A Beckman Coulter absorbance UV detector was used for detection. For camera operation, parameter control, and initial analysis of results, the computer software GOLD System version 8.11 (Beckman Coulter) was used. The separation was run at a constant temperature of 38°C and 10 kV. The duration of the separation was 18 min. Detection of proteins occurred at a wavelength of 200 nm, in accordance with Di Luccia et al. [10]. Before each injection, the capillary was washed with 0.1 N hydrochloric acid (0.3 MPa for 4 min) and water (0.3 MPa for 1 min). The buffers and solutions used for the analyses were filtered through membranes and then sonicated. A buffer consisting of 20% acetonitrile (AcN), 0.2% polyvinylpyrrolidone (PVP-360), 0.05% hydroxypropyl methylcellulose, 0.05 M iminodiacetic acid, and lauryl sulfobetaine (SB-12) was used to fill the capillary. For the partition buffer, a mixture of 20% AcN, 0.15% poly(ethylene oxide), 0.05% IDA, and 26 mM SB-12 was used. Testing was carried out at the anode end of the capillary, for 3 s at 0.5 psi (3.447 × 10−3 MPa).

The chromatographic separation was carried out according to Li Vigni et al. [22] with some modifications [13]. Chromatographic separations of proteins isolated from glutenin extracts were carried out using a Beckman Coulter RP-HPLC apparatus equipped with two pumps (126 solvent module) and a UV spectral detector. For the separation of LMW-GSs, a chromatographic Phenomenex 250 C18 column (size 4.6 × 250 mm) was used. All solvents and reagents were filtered through a 0.5 µm Millipore (Bedford, MA, USA) membrane filter and sonicated before each analysis. A gradient of two solvents was used to separate the proteins on the chromatographic column: solvent (A) – ultrapure water with TFA (trifluoroacetic acid) (99.9/0.1%, v/v) and solvent (B) – ultrapure AcN by the addition of TFA (99.9/0.1%, v/v). Extracts were separated with increasing concentration of solvent B from 20 to 60% for 50 min and then to 80% for 5 min. Each time, prior to the analysis, the chromatography column was purged for 3 min under an increased flow of 80% AcN. Camera operation, parameter control, and initial analysis of the results were carried out using the GOLD Nouveau Chromatography Workstation version 1.7 software (Beckman Coulter).

2.4 Preparing the flour for rheological analysis

At the first step of the experiment, an initial assessment and determination of the basic physicochemical parameters of wheat grain were made using the standard near-infrared (NIR) technique [23]. The percentages of protein (%) and moisture (%) were determined for each wheat grain simple. About 300 g of grain samples was adjusted to 14% moisture content with water and stored for 72 h at 18oC prior to milling with a quad-roller mill (Quadrumat Junior). A drum sieve with a mesh size of 250 μm was used to separate the flour from the bran. The milling capacity was 300 g in 4 min, while the maximum extract was about 70%. The obtained flour was packed in paper bags, sealed, and stored for 14 days at 18oC. After that time, the percentages of protein and moisture of wheat flour were made using the standard NIR technique.

2.5 Rheological analysis

At the later step of the experiment, analyses were performed at the microscale using a TA.XT Plus Texture Analyzer. About 10 g flour and 2% brine were added into the mixer chamber. The required volume of brine for each sample was calculated by the Remix 32 program, by the following equation: water absorption (%, 14%mb) = protein (14%mb) × 1.5 × 43.6, based on previously determined protein content. The dough was prepared by mixing for 10 min. The dough obtained was formed into balls, covered tightly with foil, and rested in a heat chamber at 30°C for 30 min. After that time, the dough ball was placed in a mold with five grooves (53 mm × 5 mm × 3 mm). The mold was placed in a clamp, squeezed, excess dough was removed, and kept in a heat chamber for another 10 min. After that time, the formed dough strips were analyzed in extension at a crosshead speed of 3.3 mm s−1 and a trigger force of 5 g [24]. Parameters obtained from the Kieffer force–distance curves were maximum resistance (R max, in grams), maximum extensibility (L max, in millimeters), and area under the force versus distance curve (P max, in grams × millimeters). Each sample was analyzed in triplicate, of which the average was calculated. Due to the small sample amounts available, reference varieties were not used in the rheological analyses.

  1. Ethical approval: The conducted research is not related to either human or animal use.

3 Results

3.1 Identification of HMW-GS

The use of the SDS-PAGE method allowed the identification of 10 HMW subunits that occurred in the plant material. Based on the analyses of the obtained images separated by electrophoresis of the subunits, eight HMW-GS schemas were distinguished. Figure 1 presents examples of electrophoretic images obtained for selected wheat. The electrophoretic mobility of individual subunits was referenced to the reference variety Tonacja containing Ax2*/Bx7+By9/Dx2+Dy12 subunits. HMW-GS patterns identified in the studied plant material are listed in Table 2. The HMW-GS scheme N/7+9/5+10 was the most frequent, occurring in 19 samples, constituting 27.14% of the analyzed plant material. Schemes 2*/7+9/5+10 and 1/6+8/5+10 were, jointly, the least common, with each occurring in only three samples (4.29%).

Figure 1 Electrophoretic images of dissociated HMW wheat glutenin subunits separated by SDS-PAGE. Lines: 1. Tonacja (2*/7+9/2+12), 2. Bamberka (N/7+9/5+10), 3. Ludwig (N/6+8/5+10), 4. Figura (1/7+9/5+10), 5. BZ 210801 (N/7+9/2+12), 6. Look (1/6+8/5+10), 7. Opus (1/7+9/2+12), 8. Batuta (N/6+8/5+10), 9. SZD 96 (N/7+9/5+10), 10. SMH 8063 (2*/7+9/5+10), 11. Discus (N/6+8/5+10), 12. Akteur (1/7+9/5+10), 13. Skagen (N/7+9/2+12), 14. KWS Ozon (1/7+9/5+10), 15. Bagou (N/6+8/2+12).
Figure 1

Electrophoretic images of dissociated HMW wheat glutenin subunits separated by SDS-PAGE. Lines: 1. Tonacja (2*/7+9/2+12), 2. Bamberka (N/7+9/5+10), 3. Ludwig (N/6+8/5+10), 4. Figura (1/7+9/5+10), 5. BZ 210801 (N/7+9/2+12), 6. Look (1/6+8/5+10), 7. Opus (1/7+9/2+12), 8. Batuta (N/6+8/5+10), 9. SZD 96 (N/7+9/5+10), 10. SMH 8063 (2*/7+9/5+10), 11. Discus (N/6+8/5+10), 12. Akteur (1/7+9/5+10), 13. Skagen (N/7+9/2+12), 14. KWS Ozon (1/7+9/5+10), 15. Bagou (N/6+8/2+12).

Table 2

Percentage of HMW-GS patterns in 70 tested varieties and lines of wheat

HMW-GS scheme Number of varieties Percentage
Glu-A1 Glu-B1 Glu-D1
N 7+9 5+10 19 27.14
N 7+9 2+12 11 15.71
1 7+9 5+10 9 12.86
1 7+9 2+12 4 5.71
2* 7+9 5+10 3 4.29
N 6+8 5+10 11 15.71
N 6+8 2+12 10 14.29
1 6+8 5+10 3 4.29

3.2 Identification of LMW-GSs

Reference varieties of wheat representing the LMW subunit encoding alleles were used to determine the migration times for 52 major protein peaks via CZE analyses. The migration times of all protein peaks encoded by the Glu-A3, Glu-B3, and Glu-D3 loci that were identified in the reference material are listed in Table 3. These results served to identify the LMW-GS alleles in the tested varieties.

Table 3

Migration time of protein peaks juxtaposed in blocks for the Glu-3 alleles determined based on CZE profiles of wheat reference varieties

Genome A Genome B Genome D
Allele Migration time (min) Allele Migration time (min) Allele Migration time (min) Allele Migration time (min)
Glu-A3a 9.10 Glu-B3a 10.50 Glu-B3e 9.70 Glu-D3a 9.71
12.14 10.70 10.45 13.38
11.45 11.15 Glu-D3b 9.61
11.78 11.60 13.57
Glu-A3b 9.44 Glu-B3b 10.47 Glu-B3f 10.41 Glu-D3c 9.64
14.79 10.73 10.64 13.39
11.39 11.36
Glu-A3c 14.53 Glu-B3c 10.22 Glu-B3g 10.28 Glu-D3d 9.40
10.49 11.23 13.50
10.69 12.13
11.31 Glu-B3h 10.35 Glu-D3e 9.70
Glu-A3d 10.16 Glu-B3d 9.35 10.69 13.43
13.24 10.38 11.40
14.85 11.33 Glu-B3i 9.93 Glu-D3f 9.85
Glu-A3e — 11.65 10.37 13.87
Glu-A3f 12.83 11.33

Figure 2 presents the identification of LMW-GS samples using capillary electrophoresis in reference wheat Gabo (Glu-A3b, Glu-B3b, Glu-D3b) and previously uncharacterized wheat variety Jantarka (Glu-A3f, Glu-B3b, Glu-D3a).

Figure 2 Identification of LMW-GSs using capillary electrophoresis in (a) Gabo and (b) Jantarka.
Figure 2

Identification of LMW-GSs using capillary electrophoresis in (a) Gabo and (b) Jantarka.

Sixteen allelic combinations of the Glu-3 loci, based on separation visualized on CZE electropherograms, were distinguished in the 70 tested kinds of wheat. The exact distribution of plant material according to HMW-GSs and LMW-GSs is presented in Appendix Table 1 (Table A1). Four alleles were detected for the Glu-A3 and Glu-D3 loci (Glu-A3b, Glu-A3d, Glu-A3e, Glu-A3f and Glu-D3a, Glu-D3b, Glu-D3c, Glu-D3e, respectively), whereas for the Glu-B3 locus, seven alleles were identified (Glu-B3a, Glu-B3b, Glu-B3c, Glu-B3d, Glu-B3e, Glu-B3h, and Glu-B3i). Across the studied plant material, the most common allele was Glu-D3c present in 52 samples, followed by Glu-A3e and Glu-A3f which were found in 33 samples, and Glu-B3b present in 27 samples. Infrequent variants included Glu-B3i present only in Bogatka, SZD 96, and SZD 205, and Glu-B3a was found in Banderola, Brilliant, Look, and Turkis; while the Glu-A3d allele was found only in Bystra, and the Glu-D3b allele only in line SZD 205.

Verification of the identified LMW-GS schemes in the studied plant material was achieved by chromatographic analyses. First, 22 reference varieties were scored against the LMW-GS fraction (Table 1). As a result, for the Glu-A3 locus (Glu-A3a-d and Glu-A3f), three to five protein peaks were observed on the chromatograms of the reference samples, which elute from 39.53 to 44.97 min. No peaks were observed for the Glu-A3e allele due to the lack of expression of this allele. For the reference varieties containing the Glu-B3h allele, four peaks were observed that eluted from 41.22 to 48.92 min. For the Glu-B3 locus (Glu-3a – Glu-B3g and Glu-B3i), five protein peaks were observed on the chromatograms, which eluted from 40.69 to 48.92 min. Sets of LMW-GS protein peaks encoded by the Glu-D3 locus alleles consisted of three peaks with retention times ranging from 40.51 to 50.46 min. The elution times of all protein peaks encoded by the Glu-A3, Glu-B3, and Glu-D3 loci that were identified in the reference material are listed in Table 4.

Table 4

Elution time of protein peaks juxtaposed in blocks for the Glu-3 alleles determined based on RP-HPLC profiles of wheat reference varieties

Genome A Genome B Genome D
Allele Elution time (min) Allele Elution time (min) Allele Elution time (min) Allele Elution time (min)
Glu-A3a 40.55 Glu-B3a 41.57 Glu-B3e 41.77 Glu-D3a 43.07
41.56 42.60 42.15 46.55
45.05 42.67 50.33
Glu-D3b 42.85
Glu-A3b 39.53 48.27 45.00 46.64
43.28 48.92 48.05 50.27
Glu-B3b 40.96 Glu-B3f 40.69 Glu-D3c 43.20
41.82 41.63 46.69
42.35 42.63 50.29
45.08 45.15
Glu-A3c 40.69 48.33 48.24
Glu-B3c 41.72 Glu-B3g 41.37 Glu-D3d 41.92
42.57 41.95 46.62
Glu-A3d 39.89 43.73 42.55 50.32
40.41 45.14 45.18
43.16 48.22 48.05
Glu-B3h 41.22 Glu-D3e 42.81
Glu-B3d 40.88 42.27 46.58
45.22 50.19
Glu-A3e — 41.20 48.15
41.63 Glu-B3i 41.44 Glu-D3f 40.51
45.20 42.27 46.75
Glu-A3f 44.97 48.70 43.55 50.46
45.08
48.09

The use of RP-HPLC made it possible to identify the same amount of LMW-GSs, both in the reference material and in the studied plant material, as in the case of applied CE. As was the case for capillary electrophoresis, alleles of the Glu-3 loci constituting 16 allelic variants were found in the examined material.

3.3 Rheological analysis of wheat dough

The average values of dough parameters determined by the Kieffer method for allelic variations of the Glu-3 loci are presented in Table 6, and an example of a graph obtained using the Kieffer texture analyzer is shown in Figure 3.

Figure 3 Graph obtained on the texture analyzer for variant containing Glu-A3f, Glu-B3b, and Glu-D3e (R max – resistance, L max – extension).
Figure 3

Graph obtained on the texture analyzer for variant containing Glu-A3f, Glu-B3b, and Glu-D3e (R max – resistance, L max – extension).

The results obtained were subjected to an analysis of variance to determine the effect of the LMW-GS variant on the rheological features of the dough (Table 5).

Table 5

Analysis of variance for the qualitative determinants of the dough of the tested wheat varieties and breeding lines

Parameter Sources of variation D. F. Mean square F statistics F 0.05 F 0.01
R max Variant LMW 15 0.3313 2.747 1.72 2.13
L max Variant LMW 15 0.7014 3.091 1.72 2.13
P max Variant LMW 15 0.1308 3.765 1.72 2.13

Analyzing the tested samples in terms of average resistance values (R max), significant differences were found between the allelic variants of LMW-GSs (P < 0.01). With an average dough resistance value of R max = 25.89 g for the first group (number1 in Table 6) (variants: Glu-A3f, Glu-B3b, and Glu-D3e; Glu-A3f, Glu-B3e, and Glu-D3e; Glu-A3f, Glu-B3b, and Glu-D3a; Glu-A3f, Glu-B3c, and Glu-D3c; and Glu-A3e, Glu-B3h, and Glu-D3e) and an average resistance of R max = 34.71 g for the second group (number2 in Table 6). Similarly, two groups of allelic combinations were discriminated with respect to the mean values of elongation (L max). The first group (number3 in Table 6) with an average extension of 17.89 mm was wheat doughs characterized by the alleles: Glu-A3f, Glu-B3b, and Glu-D3e; Glu-A3d, Glu-B3b, and Glu-D3c; Glu-A3e, Glu-B3a, and Glu-D3c; Glu-A3f, Glu-B3c, and Glu-D3c; Glu-A3f, Glu-B3b, and Glu-D3a; Glu-A3e, Glu-B3d, and Glu-D3c; Glu-A3e, Glu-B3i, and Glu-D3c; and Glu-A3e, Glu-B3b, and Glu-D3c. The second group (number4 in Table 6) with an average extension of 21.71 mm was the remaining eight variants of the Glu-3 loci. In the case of surface area, P max significant differences were found between the allelic variants of LMW-GSs (P < 0.01). Two groups were distinguished, the first (number5 in Table 6) with P max = 335,86 g mm and variants: Glu-A3f, Glu-B3b, and Glu-D3e; Glu-A3f, Glu-B3b, and Glu-D3a; Glu-A3f, Glu-B3c, and Glu-D3c; Glu-A3d, Glu-B3b, and Glu-D3c; Glu-A3e, Glu-B3a, and Glu-D3c; and the second (number6 in Table 6) with an average P max = 505.92 g mm for the 11 remaining analyzed variants.

Table 6

Average values of rheological parameters determined by the Kieffer method for allelic variations of the Glu-3 loci

Glu-A3 Glu-B3 Glu-D3 R max (g) L max (mm) P max (g mm)
b h c 35.452 22.404 544.736
d b c 34.862 16.903 389.595
e a c 33.142 17.323 401.475
e b c 32.682 19.353 462.946
e d c 34.312 18.833 449.256
e h c 36.972 21.954 583.986
e h e 29.291 22.154 463.716
e i a 38.392 20.734 536.356
e i b 36.202 23.034 578.986
e i c 35.142 18.853 443.266
f b a 27.601 17.703 348.425
f b e 18.651 14.563 221.985
f c c 28.651 17.333 361.335
f d c 36.782 20.954 532.966
f e c 35.392 21.224 533.426
f e e 25.091 24.194 450.766

Note: In the table, 1–6 are groups of allelic combinations of LMW-GS which were discriminated with respect to mean values of resistance (R max), elongation (L max) and surface area (P max).

The smallest total mean resistance (R max = 18.65 g) came from a wheat dough with the allelic variant Glu-A3f, Glu-B3b, and Glu-D3e. In turn, the highest total average resistance, and thus the greatest resistance (R max = 38.39 g), was in a dough with an allelic variant of Glu-A3e, Glu-B3i, and Glu-D3a. The weakest dough in terms of extensibility (L max = 14.56 mm) was observed for allelic variants: Glu-A3f, Glu-B3b, and Glu-D3e. The most flexible and stretchable (L max = 24.19 mm) was from dough with the allele variant Glu-A3f, Glu-B3e, and Glu-D3e. Taking into account the area of P max, the smallest cumulative mean values (221.98 g mm) were for the Glu-A3f, Glu-B3b, and Glu-D3e variants, while the largest total mean values (583.98 g mm) were wheat doughs characterized by the allele variant Glu-A3e, Glu-B3a, and Glu-D3c.

4 Discussion

Literature reports show that the technological properties of wheat are largely determined by the composition and the amount of gluten, which includes glutenins and gliadins. A thorough understanding of the polymorphism of glutenin proteins makes it possible to determine the extent to which the rheological properties of wheat dough are determined by a complex of gluten proteins formed by both high- and low-molecular subunits [25,26]. HMW-GSs account for up to 10% of gluten proteins, and it has been shown that they determine up to 70% of the quality characteristics of wheat grain. Otherwise, the impact of LMW-GSs on rheological parameters is still poorly characterized. It seems that the specific rheological properties of wheat dough can also be significantly affected by LMW-GSs, which account for up to 50% of gluten and generate up to 30% variation in technological features of wheat [1,4].

Protein electrophoresis in polyacrylamide gel with the addition of sodium dodecyl sulfate (SDS-PAGE) is a commonly used method for assessing the variability of the qualitative composition of wheat storage proteins. The comparative analyses of protein profiles obtained on SDS-electropherograms allowed us to distinguish 11 HMW-GSs in the examined plant material, coded by the allelic variants of the genes in the Glu-1 locus: Glu-A1-1a (Ax1), Glu-A1-1b (Ax2*), Glu-A1-1c (Null variant), Glu-B1-1a (Bx7), Glu-B1-1d (Bx6), Glu-B1-2a (By8), Glu-B1-2d (By9), Glu-D1-1a (Dx5), Glu-D1-2a (Dx2), Glu-D1-1d (Dy5), and Glu-D1-2b (Dy12). Featured HMW subunits are usually identified in wheat technological studies [27,28].

In the presented work, the identification of the LMW-GS qualitative composition in the tested material was carried out using electrophoretic (CZE) and chromatographic (RP-HPLC) methods. In recent years, CZE has been used to perform qualitative and quantitative determinations of the majority of distinguished classes of wheat storage proteins [17,19,29]. The literature data show that LMW-GSs migrate in the silica capillaries in the time range similar to the HMW-GS fraction, which requires prior accurate separation of these fractions prior to conducting the separation [30]. Li et al. [11], based on identified protein peaks, distinguished two alleles at the Glu-A3 locus, four alleles at the Glu-B3 locus, and three alleles at the Glu-D3 locus. In the presented study, a wide range of migration times (9.10–14.85 min) was found for individual LMW subunits, which enabled their full identification in the tested genotypes. In contrast to the studies of Li et al. [11], we observed one to four protein peaks corresponding to LMW-GSs based on the CZE electropherograms with the exception of the Glu-A3e allele, which was not expressed. Multiple migration times of the individual LMW-GSs result from the presence of multiple genes at a particular locus [11].

At the same time, the RP-HPLC method was used to determine the qualitative composition of LMW-GSs in tested wheat varieties with the previously determined HMW-GS composition. LMW subunits have so far been characterized using this method by several research teams, but the subject of research has been a very small number of trials in individual studies [12,31]. For the separation of LMW subunits, researchers applied various fillings in the chromatographic columns, which makes it more difficult to compare the retention times of protein peaks on the presented chromatograms. The main disadvantage of this method when compared with free capillary electrophoresis is a long time of separation of individual samples (up to 60 min) and high costs of columns and solvents used for protein separation. The LMW subunit separation carried out as part of this study, refining the methodology and using the most modern columns, enabled full identification of all (from one to five) subunits encoded by particular Glu-3 loci. The reports presented previously revealed the presence of only a few subunits but confirm that multiple elution times of LMW-GS proteins are due to the presence of multiple genes at a particular locus [12,31]. In our study, full concordance was obtained in the number of subunits in separation performed using the CZE and RP-HPLC methods. In recent years, along with the refinement of the RP-HPLC method, i.e., the use of ultra-dry liquid chromatography (UPLC), the use of columns with smaller fillings has provided a comparable resolution of proteins for a number of chemical compounds with three times shorter subunit separation time. Yu et al. [13] using the UPLC method to separate the LMW subunits shortened the time of separation (up to 18 min) but did not obtain such a good resolution for individual subunits (only 1–2 subunits were distinguished) as in the case of the methodology used in the presented study.

To determine the performance traits of common wheat, technological research studies on grain or flour are carried out [32,33,34,35]. In recent years, the impact of LMW-GSs on rheological parameters has mainly been determined using a texture analyzer with the Kieffer method [36]. The rheological analyses carried out in this research confirmed the increase in dough resistance in the LMW-GS containing samples encoded by the Glu-A3d, Glu-B3d, Glu-B3h, Glu-B3i, Glu-D3a, and Glu-D3b alleles. The lowest dough resistance was linked with the presence of Glu-A3e and Glu-A3f alleles. The increase in dough resistance in wheat genotypes containing LMW-GSs encoded by the Glu-B3i allele has not previously been reported in the literature. Based on previous studies by the teams of Branlard et al. [37] and Eagles et al. [38], it can be concluded that the increased extensibility and elongation of dough also depends on the presence of LMW subunits coded at the Glu-A3 locus (Glu-A3a, Glu-A3d), the Glu-B3 locus (Glu-B3b and Glu-B3d), and the Glu-D3 locus (Glu-D3b, Glu-D3c). Rai et al. [32] showed that LMW-GSs coded at the Glu-A3 locus (Glu-A3b, Glu-A3c) and the Glu-B3 (Glu-B3b) locus are responsible for the low rheological values. In subsequent studies, the beneficial effects of Glu-A3d, Glu-B3d, Glu-B3b, Glu-B3f alleles, and Glu-D3c [39] on the elongation of dough were demonstrated. Maucher et al. [40] found that the improvement of the dough elongation parameter is influenced by the presence of the Glu-A3b, Glu-B3d, Glu-D3d allelic combination. Oury et al. [41] have shown that LMW-GSs encoded by the Glu-A3a, Glu-B3g, Glu-D3a, and Glu-D3b alleles increase the extensibility of the dough. Park’s team [42] demonstrated the positive effects of the Glu-A3b, Glu-A3d, Glu-B3b, Glu-B3d, GluD3b, and Glu-D3a alleles on the dough extensibility. The rheological data obtained in this study indicated that particularly beneficial effects on the extensionality of the dough came from the Glu-B3b, Glu-D3b, Glu-D3c alleles, which confirms the results obtained by other researchers [38,39,41]. The presence of the Glu-A3b, Glu-A3f, Glu-B3h, and Glu-B3e alleles in samples also had a significant influence on the shaping of this parameter. In-depth studies on the area under the force versus distance curve (P max) were conducted by Maucher’s team [40]. They arranged the LMW-GS coding alleles favorably affecting this parameter in the following order: Glu-A3d > Glu-A3c > Glu-A3b > Glu-A3e at the Glu-A3 locus; Glu-B3d > Glu-B3g > Glu-B3h > Glu-B3f > Glu-B3i at the Glu-B3 locus and Glu-D3d > Glu-D3b > Glu-D3a > Glu-D3c at the Glu-D3 locus. Oury et al. [41] observed an increase in tear resistance in LMW-GS-tested samples encoded by the Glu-A3d, Glu-B3b’, Glu-B3g and Glu-D3b alleles. In a recent study, Zhang’s team [43] ranked the Glu-3 loci alleles contribution to the increase in tear dough resistance within the Glu-A3 locus as Glu-A3c > Glu-A3d > Glu-A3f > Glu-A3b > Glu-A3e; within the Glu-B3 locus as Glu-B3i > Glu-B3b = Glu-B3a > Glu-B3f = Glu-B3g > Glu-B3h > Glu-B3c > Glu-B3d; and within the Glu-D3 locus as GluD3a = Glu-D3b = Glu-D3c > Glu-D3d > Glu-D3f. Based on comparative analyses carried out in this work, it was shown that the presence of Glu-A3f, Glu-A3e, Glu-B3a, Glu-B3e, Glu-B3h, Glu-D3a, Glu-D3b, and Glu-D3c alleles in the tested samples has a significant effect on increasing the breaking strength of the dough. The data obtained on the beneficial effects of LMW-GSs encoded by the Glu-B3h, Glu-D3a and Glu-D3b alleles on breaking strength are in agreement with the literature data [40,43]. In the case of the remaining alleles of Glu-3 loci in the tested samples, the presence of which significantly enhanced the tear strength of the dough, discrepancies were found with the literature data, which may be due to the smaller number of samples tested by other authors.

5 Conclusion

The use of modern analytical methods such as capillary electrophoresis and RP-HPLC enabled the full identification of LMW-GSs encoded by the Glu-3 loci alleles. Our research clearly showed that LMW-GSs play an important role in creating the rheological quality of wheat. Obtained results enabled the selection of wheat varieties containing the Glu-3 loci scheme (Glu-A3b, Glu-A3f at the Glu-A3 locus; Glu-B3a, Glu-B3b, Glu-B3d, Glu-B3h at the Glu-B3 locus; Glu-D3a, Glu-D3c at the Glu-D3 locus) determining the most beneficial quality parameters, namely, Operetka, Smaragd, SMH 90, Ludwig, Brilliant, Natula, Akteur, and Bamberka. These varieties may be used in wheat breeding for crossing and developing new plants with favorable technological parameters. This research can be integrated with a molecular marker approach in an expansion of the knowledge about the genetic background of wheat quality giving an effective marker-assisted selection in the future.

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Acknowledgments

The authors thank the Plant Breeding Smolice, which raised and collected the basic research material in the form of 70 wheat varieties and lines, and the Australia Winter Cereals Collection for providing 22 reference wheat varieties.

  1. Funding information: The authors state no funding involved.

  2. Author contributions: Conceptualization, S.F. and B.S.; methodology, B.S. and S.F.; validation, B.S.; formal analysis, S.F.; investigation, S.F.; resources, B.S.; data curation, S.F.; writing – original draft preparation, S.F.; writing – review and editing, S.F. and B. S.; supervision, B.S.; project administration, B.S.; funding acquisition, B.S. All authors have read and agreed to the published version of the manuscript.

  3. Conflict of interest: The authors state no conflict of interest.

  4. Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Appendix

Table A1

List of wheat genotypes according to HMW-GS and LMW-GS schemes

Sample number Genotypes HMW-GS scheme LMW-GS scheme
Glu-A3 Glu-B3 Glu-D3
1 AREZZO N/7+9/5+10 f e c
2 BALETKA e h c
3 BAMBERKA e d c
4 BOCKRIS e b c
5 BOGATKA e i c
6 BRILLIANT e a c
7 CUBUS e b c
8 DOROTA f d c
9 KOHELIA e h e
10 KRANICH f e c
11 PAMIER f c c
12 SKAGEN f e c
13 SMARAGD f d c
14 SZD 205 e i b
15 SZD 87 e d c
16 SZD 96 e i a
17 TORAS f e c
18 TORRILD f e c
19 TURKIS e a c
20 ANTHUS N/7+9/2+12 f e e
21 BB 742206 DH e b c
22 BZ 210801 f c c
23 FIDELIUS e b c
24 GARANTUS e d c
25 KREDO e b c
26 POB 779 05 e h e
27 RUMBA e h c
28 RYSA e h c
29 SMH 8134 e h c
30 VISCOUNT e b c
31 ATTLAS N/6+8/5+10 f b a
32 BUTEO f c c
33 BYSTRA d b c
34 DISCUS f b e
35 GALVANO b h c
36 GECKO f b a
37 JANTARKA f b a
38 LP 227 1 03 f b a
39 LUDWIG b h c
40 PREMIO f c c
41 ACONEL N/6+8/2+12 e b c
42 ADONIS f e c
43 AND 3509 e b c
44 AUGUSTUS f e c
45 BAGOU f b e
46 BISCAY f b e
47 CENTENAIR e b c
48 HENRIK f b a
49 KATART f b e
50 MULAN e d c
51 AKTEUR 1/7+9/5+10 e h c
52 ARISTOS e b c
53 BANDEROLA e a c
54 FIGURA f e c
55 KWS OZON e b c
56 NATULA e h c
57 QUEBON f e c
58 SMH 92 e b c
59 STETANUS e b c
60 KEPLER 1/7+9/2+12 f b e
61 OPERETKA f d c
62 OPUS f b a
63 TUAREG f b a
64 LOOK 1/6+8/5+10 e a c
65 POTENTIAL f e c
66 SZD 11 e d c
67 SMH 8063 2*/7+9/5+10 f c c
68 SMH 90 b h c
69 SMUGA 2*/7+9/2+12 f c c
70 GLOBAL 2*/6+8/5+10 f b a

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Received: 2020-12-03
Revised: 2021-04-07
Accepted: 2021-04-24
Published Online: 2021-06-24

© 2021 Sławomir Franaszek and Bolesław Salmanowicz, published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  38. Gamma irradiation-mediated inactivation of enveloped viruses with conservation of genome integrity: Potential application for SARS-CoV-2 inactivated vaccine development
  39. ADHFE1 is a correlative factor of patient survival in cancer
  40. The association of transcription factor Prox1 with the proliferation, migration, and invasion of lung cancer
  41. Is there a relationship between the prevalence of autoimmune thyroid disease and diabetic kidney disease?
  42. Immunoregulatory function of Dictyophora echinovolvata spore polysaccharides in immunocompromised mice induced by cyclophosphamide
  43. T cell epitopes of SARS-CoV-2 spike protein and conserved surface protein of Plasmodium malariae share sequence homology
  44. Anti-obesity effect and mechanism of mesenchymal stem cells influence on obese mice
  45. Long noncoding RNA HULC contributes to paclitaxel resistance in ovarian cancer via miR-137/ITGB8 axis
  46. Glucocorticoids protect HEI-OC1 cells from tunicamycin-induced cell damage via inhibiting endoplasmic reticulum stress
  47. Prognostic value of the neutrophil-to-lymphocyte ratio in acute organophosphorus pesticide poisoning
  48. Gastroprotective effects of diosgenin against HCl/ethanol-induced gastric mucosal injury through suppression of NF-κβ and myeloperoxidase activities
  49. Silencing of LINC00707 suppresses cell proliferation, migration, and invasion of osteosarcoma cells by modulating miR-338-3p/AHSA1 axis
  50. Successful extracorporeal membrane oxygenation resuscitation of patient with cardiogenic shock induced by phaeochromocytoma crisis mimicking hyperthyroidism: A case report
  51. Effects of miR-185-5p on replication of hepatitis C virus
  52. Lidocaine has antitumor effect on hepatocellular carcinoma via the circ_DYNC1H1/miR-520a-3p/USP14 axis
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  54. Multimodal magnetic resonance imaging analysis in the characteristics of Wilson’s disease: A case report and literature review
  55. Therapeutic potential of anticoagulant therapy in association with cytokine storm inhibition in severe cases of COVID-19: A case report
  56. Neoadjuvant immunotherapy combined with chemotherapy for locally advanced squamous cell lung carcinoma: A case report and literature review
  57. Rufinamide (RUF) suppresses inflammation and maintains the integrity of the blood–brain barrier during kainic acid-induced brain damage
  58. Inhibition of ADAM10 ameliorates doxorubicin-induced cardiac remodeling by suppressing N-cadherin cleavage
  59. Invasive ductal carcinoma and small lymphocytic lymphoma/chronic lymphocytic leukemia manifesting as a collision breast tumor: A case report and literature review
  60. Clonal diversity of the B cell receptor repertoire in patients with coronary in-stent restenosis and type 2 diabetes
  61. CTLA-4 promotes lymphoma progression through tumor stem cell enrichment and immunosuppression
  62. WDR74 promotes proliferation and metastasis in colorectal cancer cells through regulating the Wnt/β-catenin signaling pathway
  63. Down-regulation of IGHG1 enhances Protoporphyrin IX accumulation and inhibits hemin biosynthesis in colorectal cancer by suppressing the MEK-FECH axis
  64. Curcumin suppresses the progression of gastric cancer by regulating circ_0056618/miR-194-5p axis
  65. Scutellarin-induced A549 cell apoptosis depends on activation of the transforming growth factor-β1/smad2/ROS/caspase-3 pathway
  66. lncRNA NEAT1 regulates CYP1A2 and influences steroid-induced necrosis
  67. A two-microRNA signature predicts the progression of male thyroid cancer
  68. Isolation of microglia from retinas of chronic ocular hypertensive rats
  69. Changes of immune cells in patients with hepatocellular carcinoma treated by radiofrequency ablation and hepatectomy, a pilot study
  70. Calcineurin Aβ gene knockdown inhibits transient outward potassium current ion channel remodeling in hypertrophic ventricular myocyte
  71. Aberrant expression of PI3K/AKT signaling is involved in apoptosis resistance of hepatocellular carcinoma
  72. Clinical significance of activated Wnt/β-catenin signaling in apoptosis inhibition of oral cancer
  73. circ_CHFR regulates ox-LDL-mediated cell proliferation, apoptosis, and EndoMT by miR-15a-5p/EGFR axis in human brain microvessel endothelial cells
  74. Resveratrol pretreatment mitigates LPS-induced acute lung injury by regulating conventional dendritic cells’ maturation and function
  75. Ubiquitin-conjugating enzyme E2T promotes tumor stem cell characteristics and migration of cervical cancer cells by regulating the GRP78/FAK pathway
  76. Carriage of HLA-DRB1*11 and 1*12 alleles and risk factors in patients with breast cancer in Burkina Faso
  77. Protective effect of Lactobacillus-containing probiotics on intestinal mucosa of rats experiencing traumatic hemorrhagic shock
  78. Glucocorticoids induce osteonecrosis of the femoral head through the Hippo signaling pathway
  79. Endothelial cell-derived SSAO can increase MLC20 phosphorylation in VSMCs
  80. Downregulation of STOX1 is a novel prognostic biomarker for glioma patients
  81. miR-378a-3p regulates glioma cell chemosensitivity to cisplatin through IGF1R
  82. The molecular mechanisms underlying arecoline-induced cardiac fibrosis in rats
  83. TGF-β1-overexpressing mesenchymal stem cells reciprocally regulate Th17/Treg cells by regulating the expression of IFN-γ
  84. The influence of MTHFR genetic polymorphisms on methotrexate therapy in pediatric acute lymphoblastic leukemia
  85. Red blood cell distribution width-standard deviation but not red blood cell distribution width-coefficient of variation as a potential index for the diagnosis of iron-deficiency anemia in mid-pregnancy women
  86. Small cell neuroendocrine carcinoma expressing alpha fetoprotein in the endometrium
  87. Superoxide dismutase and the sigma1 receptor as key elements of the antioxidant system in human gastrointestinal tract cancers
  88. Molecular characterization and phylogenetic studies of Echinococcus granulosus and Taenia multiceps coenurus cysts in slaughtered sheep in Saudi Arabia
  89. ITGB5 mutation discovered in a Chinese family with blepharophimosis-ptosis-epicanthus inversus syndrome
  90. ACTB and GAPDH appear at multiple SDS-PAGE positions, thus not suitable as reference genes for determining protein loading in techniques like Western blotting
  91. Facilitation of mouse skin-derived precursor growth and yield by optimizing plating density
  92. 3,4-Dihydroxyphenylethanol ameliorates lipopolysaccharide-induced septic cardiac injury in a murine model
  93. Downregulation of PITX2 inhibits the proliferation and migration of liver cancer cells and induces cell apoptosis
  94. Expression of CDK9 in endometrial cancer tissues and its effect on the proliferation of HEC-1B
  95. Novel predictor of the occurrence of DKA in T1DM patients without infection: A combination of neutrophil/lymphocyte ratio and white blood cells
  96. Investigation of molecular regulation mechanism under the pathophysiology of subarachnoid hemorrhage
  97. miR-25-3p protects renal tubular epithelial cells from apoptosis induced by renal IRI by targeting DKK3
  98. Bioengineering and Biotechnology
  99. Green fabrication of Co and Co3O4 nanoparticles and their biomedical applications: A review
  100. Agriculture
  101. Effects of inorganic and organic selenium sources on the growth performance of broilers in China: A meta-analysis
  102. Crop-livestock integration practices, knowledge, and attitudes among smallholder farmers: Hedging against climate change-induced shocks in semi-arid Zimbabwe
  103. Food Science and Nutrition
  104. Effect of food processing on the antioxidant activity of flavones from Polygonatum odoratum (Mill.) Druce
  105. Vitamin D and iodine status was associated with the risk and complication of type 2 diabetes mellitus in China
  106. Diversity of microbiota in Slovak summer ewes’ cheese “Bryndza”
  107. Comparison between voltammetric detection methods for abalone-flavoring liquid
  108. Composition of low-molecular-weight glutenin subunits in common wheat (Triticum aestivum L.) and their effects on the rheological properties of dough
  109. Application of culture, PCR, and PacBio sequencing for determination of microbial composition of milk from subclinical mastitis dairy cows of smallholder farms
  110. Investigating microplastics and potentially toxic elements contamination in canned Tuna, Salmon, and Sardine fishes from Taif markets, KSA
  111. From bench to bar side: Evaluating the red wine storage lesion
  112. Establishment of an iodine model for prevention of iodine-excess-induced thyroid dysfunction in pregnant women
  113. Plant Sciences
  114. Characterization of GMPP from Dendrobium huoshanense yielding GDP-D-mannose
  115. Comparative analysis of the SPL gene family in five Rosaceae species: Fragaria vesca, Malus domestica, Prunus persica, Rubus occidentalis, and Pyrus pyrifolia
  116. Identification of leaf rust resistance genes Lr34 and Lr46 in common wheat (Triticum aestivum L. ssp. aestivum) lines of different origin using multiplex PCR
  117. Investigation of bioactivities of Taxus chinensis, Taxus cuspidata, and Taxus × media by gas chromatography-mass spectrometry
  118. Morphological structures and histochemistry of roots and shoots in Myricaria laxiflora (Tamaricaceae)
  119. Transcriptome analysis of resistance mechanism to potato wart disease
  120. In silico analysis of glycosyltransferase 2 family genes in duckweed (Spirodela polyrhiza) and its role in salt stress tolerance
  121. Comparative study on growth traits and ions regulation of zoysiagrasses under varied salinity treatments
  122. Role of MS1 homolog Ntms1 gene of tobacco infertility
  123. Biological characteristics and fungicide sensitivity of Pyricularia variabilis
  124. In silico/computational analysis of mevalonate pyrophosphate decarboxylase gene families in Campanulids
  125. Identification of novel drought-responsive miRNA regulatory network of drought stress response in common vetch (Vicia sativa)
  126. How photoautotrophy, photomixotrophy, and ventilation affect the stomata and fluorescence emission of pistachios rootstock?
  127. Apoplastic histochemical features of plant root walls that may facilitate ion uptake and retention
  128. Ecology and Environmental Sciences
  129. The impact of sewage sludge on the fungal communities in the rhizosphere and roots of barley and on barley yield
  130. Domestication of wild animals may provide a springboard for rapid variation of coronavirus
  131. Response of benthic invertebrate assemblages to seasonal and habitat condition in the Wewe River, Ashanti region (Ghana)
  132. Molecular record for the first authentication of Isaria cicadae from Vietnam
  133. Twig biomass allocation of Betula platyphylla in different habitats in Wudalianchi Volcano, northeast China
  134. Animal Sciences
  135. Supplementation of probiotics in water beneficial growth performance, carcass traits, immune function, and antioxidant capacity in broiler chickens
  136. Predators of the giant pine scale, Marchalina hellenica (Gennadius 1883; Hemiptera: Marchalinidae), out of its natural range in Turkey
  137. Honey in wound healing: An updated review
  138. NONMMUT140591.1 may serve as a ceRNA to regulate Gata5 in UT-B knockout-induced cardiac conduction block
  139. Radiotherapy for the treatment of pulmonary hydatidosis in sheep
  140. Retraction
  141. Retraction of “Long non-coding RNA TUG1 knockdown hinders the tumorigenesis of multiple myeloma by regulating microRNA-34a-5p/NOTCH1 signaling pathway”
  142. Special Issue on Reuse of Agro-Industrial By-Products
  143. An effect of positional isomerism of benzoic acid derivatives on antibacterial activity against Escherichia coli
  144. Special Issue on Computing and Artificial Techniques for Life Science Applications - Part II
  145. Relationship of Gensini score with retinal vessel diameter and arteriovenous ratio in senile CHD
  146. Effects of different enantiomers of amlodipine on lipid profiles and vasomotor factors in atherosclerotic rabbits
  147. Establishment of the New Zealand white rabbit animal model of fatty keratopathy associated with corneal neovascularization
  148. lncRNA MALAT1/miR-143 axis is a potential biomarker for in-stent restenosis and is involved in the multiplication of vascular smooth muscle cells
https://doi.org/10.1515/biol-2021-0059
Keywords for this article
low-molecular-weight glutenin subunits; dough rheology; wheat; capillary zone electrophoresis; reverse-phase high-performance liquid chromatography
Creative Commons
BY 4.0

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  40. The association of transcription factor Prox1 with the proliferation, migration, and invasion of lung cancer
  41. Is there a relationship between the prevalence of autoimmune thyroid disease and diabetic kidney disease?
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  43. T cell epitopes of SARS-CoV-2 spike protein and conserved surface protein of Plasmodium malariae share sequence homology
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  49. Silencing of LINC00707 suppresses cell proliferation, migration, and invasion of osteosarcoma cells by modulating miR-338-3p/AHSA1 axis
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  70. Calcineurin Aβ gene knockdown inhibits transient outward potassium current ion channel remodeling in hypertrophic ventricular myocyte
  71. Aberrant expression of PI3K/AKT signaling is involved in apoptosis resistance of hepatocellular carcinoma
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  80. Downregulation of STOX1 is a novel prognostic biomarker for glioma patients
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  82. The molecular mechanisms underlying arecoline-induced cardiac fibrosis in rats
  83. TGF-β1-overexpressing mesenchymal stem cells reciprocally regulate Th17/Treg cells by regulating the expression of IFN-γ
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  85. Red blood cell distribution width-standard deviation but not red blood cell distribution width-coefficient of variation as a potential index for the diagnosis of iron-deficiency anemia in mid-pregnancy women
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  94. Expression of CDK9 in endometrial cancer tissues and its effect on the proliferation of HEC-1B
  95. Novel predictor of the occurrence of DKA in T1DM patients without infection: A combination of neutrophil/lymphocyte ratio and white blood cells
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  97. miR-25-3p protects renal tubular epithelial cells from apoptosis induced by renal IRI by targeting DKK3
  98. Bioengineering and Biotechnology
  99. Green fabrication of Co and Co3O4 nanoparticles and their biomedical applications: A review
  100. Agriculture
  101. Effects of inorganic and organic selenium sources on the growth performance of broilers in China: A meta-analysis
  102. Crop-livestock integration practices, knowledge, and attitudes among smallholder farmers: Hedging against climate change-induced shocks in semi-arid Zimbabwe
  103. Food Science and Nutrition
  104. Effect of food processing on the antioxidant activity of flavones from Polygonatum odoratum (Mill.) Druce
  105. Vitamin D and iodine status was associated with the risk and complication of type 2 diabetes mellitus in China
  106. Diversity of microbiota in Slovak summer ewes’ cheese “Bryndza”
  107. Comparison between voltammetric detection methods for abalone-flavoring liquid
  108. Composition of low-molecular-weight glutenin subunits in common wheat (Triticum aestivum L.) and their effects on the rheological properties of dough
  109. Application of culture, PCR, and PacBio sequencing for determination of microbial composition of milk from subclinical mastitis dairy cows of smallholder farms
  110. Investigating microplastics and potentially toxic elements contamination in canned Tuna, Salmon, and Sardine fishes from Taif markets, KSA
  111. From bench to bar side: Evaluating the red wine storage lesion
  112. Establishment of an iodine model for prevention of iodine-excess-induced thyroid dysfunction in pregnant women
  113. Plant Sciences
  114. Characterization of GMPP from Dendrobium huoshanense yielding GDP-D-mannose
  115. Comparative analysis of the SPL gene family in five Rosaceae species: Fragaria vesca, Malus domestica, Prunus persica, Rubus occidentalis, and Pyrus pyrifolia
  116. Identification of leaf rust resistance genes Lr34 and Lr46 in common wheat (Triticum aestivum L. ssp. aestivum) lines of different origin using multiplex PCR
  117. Investigation of bioactivities of Taxus chinensis, Taxus cuspidata, and Taxus × media by gas chromatography-mass spectrometry
  118. Morphological structures and histochemistry of roots and shoots in Myricaria laxiflora (Tamaricaceae)
  119. Transcriptome analysis of resistance mechanism to potato wart disease
  120. In silico analysis of glycosyltransferase 2 family genes in duckweed (Spirodela polyrhiza) and its role in salt stress tolerance
  121. Comparative study on growth traits and ions regulation of zoysiagrasses under varied salinity treatments
  122. Role of MS1 homolog Ntms1 gene of tobacco infertility
  123. Biological characteristics and fungicide sensitivity of Pyricularia variabilis
  124. In silico/computational analysis of mevalonate pyrophosphate decarboxylase gene families in Campanulids
  125. Identification of novel drought-responsive miRNA regulatory network of drought stress response in common vetch (Vicia sativa)
  126. How photoautotrophy, photomixotrophy, and ventilation affect the stomata and fluorescence emission of pistachios rootstock?
  127. Apoplastic histochemical features of plant root walls that may facilitate ion uptake and retention
  128. Ecology and Environmental Sciences
  129. The impact of sewage sludge on the fungal communities in the rhizosphere and roots of barley and on barley yield
  130. Domestication of wild animals may provide a springboard for rapid variation of coronavirus
  131. Response of benthic invertebrate assemblages to seasonal and habitat condition in the Wewe River, Ashanti region (Ghana)
  132. Molecular record for the first authentication of Isaria cicadae from Vietnam
  133. Twig biomass allocation of Betula platyphylla in different habitats in Wudalianchi Volcano, northeast China
  134. Animal Sciences
  135. Supplementation of probiotics in water beneficial growth performance, carcass traits, immune function, and antioxidant capacity in broiler chickens
  136. Predators of the giant pine scale, Marchalina hellenica (Gennadius 1883; Hemiptera: Marchalinidae), out of its natural range in Turkey
  137. Honey in wound healing: An updated review
  138. NONMMUT140591.1 may serve as a ceRNA to regulate Gata5 in UT-B knockout-induced cardiac conduction block
  139. Radiotherapy for the treatment of pulmonary hydatidosis in sheep
  140. Retraction
  141. Retraction of “Long non-coding RNA TUG1 knockdown hinders the tumorigenesis of multiple myeloma by regulating microRNA-34a-5p/NOTCH1 signaling pathway”
  142. Special Issue on Reuse of Agro-Industrial By-Products
  143. An effect of positional isomerism of benzoic acid derivatives on antibacterial activity against Escherichia coli
  144. Special Issue on Computing and Artificial Techniques for Life Science Applications - Part II
  145. Relationship of Gensini score with retinal vessel diameter and arteriovenous ratio in senile CHD
  146. Effects of different enantiomers of amlodipine on lipid profiles and vasomotor factors in atherosclerotic rabbits
  147. Establishment of the New Zealand white rabbit animal model of fatty keratopathy associated with corneal neovascularization
  148. lncRNA MALAT1/miR-143 axis is a potential biomarker for in-stent restenosis and is involved in the multiplication of vascular smooth muscle cells
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