Comparative Biochemical and Proteomic Analyses of Soybean Seed

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Journal of Agricultural and Food Chemistry

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Comparative Biochemical and Proteomic Analyses of Soybean Seed

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Cultivars Differing in Protein and Oil Content

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Chul Woo Min1, Ravi Gupta1, So Wun Kim1, So Eui Lee1, Yong Chul Kim1, Dong Won Bae2,

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Won Young Han3, Byong Won Lee3, Jong Min Ko3, Ganesh Kumar Agrawal4,5, Randeep

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Rakwal4,5,6, Sun Tae Kim1*

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Author’s affiliations:

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Department of Plant Bioscience, Life and Industry Convergence Research Institute, Pusan National University, Miryang, 627-706, South Korea

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Center for Research Facilities, Gyeongsang National University, Jinju, 660-701, South Korea

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Department of Functional Crops, NICS, RDA, Miryang, 627-803, South Korea

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Research Laboratory for Biotechnology and Biochemistry (RLABB), GPO 13265, Kathmandu, Nepal

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GRADE (Global Research Arch for Developing Education) Academy Pvt. Ltd, Adarsh Nagar13, Birgunj, Nepal

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Faculty of Health and Sport Sciences & Tsukuba International Academy for Sport Studies (TIAS), University of Tsukuba, 1-1-1 Tennoudai, Tsukuba 305-8574, Ibaraki, Japan

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*Correspondence: Prof. Sun Tae Kim, Department of Plant Bioscience, Pusan National University, Miryang, 627-706, South Korea.

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E-mail: [email protected]

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Fax: +82-55-350-5509

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ACS Paragon Plus Environment


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Abstract

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This study develops differential protein profiles of soybean (Glycine max) seeds (cv. Saedanbaek

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and Daewon) varying in protein (47.9% and 39.2%) and oil (16.3% and 19.7%) contents, using

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protamine sulfate (PS) precipitation method coupled with two-dimensional gel electrophoresis

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(2-DGE) approach. Of 71 detected differential spots between Daewon and Saedanbaek, 48 were

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successfully identified by MALDI-TOF/TOF. Gene ontology analysis revealed that up-regulated

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proteins in Saedanbaek were largely associated with nutrient reservoir activity (42.6%), which

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included mainly SSPs (subunits of glycinin and β-conglycinin). Similar results were also

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obtained in two cultivars of wild soybean (G. soja) cv. WS22 and WS15 differing in protein

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content. Western blots confirmed higher accumulation of SSPs in the protein-rich Saedanbaek.

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Findings presented and discussed in this study highlight a possible involvement of the urea cycle

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for increased accumulation of SSPs and hence the higher protein content in soybean seeds.

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Keywords: Glycine max, Glycine soja, Two-dimensional gel electrophoresis, MALDI-TOF/TOF,

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Seed storage proteins, Protamine sulfate precipitation method

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1 Introduction

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Soybean seeds are an important source of proteins and oils. These seeds are used worldwide for

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human consumption and feeding domestic livestock and poultry. Commercial seeds of soybean

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contain 36–50% proteins and 18–22 % oils on dry weight basis.1 Most of the seed proteins are

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heat stable and therefore not denatured during processing of soybean to produce food items like

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“tofu”, “soy milk”, etc. Soybean proteins offer a “complete protein profile”, and are healthier

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than the animal derived foods as the later are rich in fats also.2

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A number of proteomic studies have been performed in soybean seeds to investigate protein

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composition, nutritional value, and allergens.1,

3-5

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proteome of soybean seeds using high-throughput 2-DGE and MudPIT approaches showed that

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approximately 42-61 % of the total soybean proteins are involved in metabolism, energy, protein

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destination, and storage.6, 7 However, there are very few studies comparing soybean seeds that

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differ in their protein and oil contents. Recently, Xu and co-workers evaluated the protein

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profiles of high oil and high proteins accessions of soybean, which led to the identification of 40

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differentially-expressed proteins associated with oil synthesis, redox/stress, hydrolysis, and

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storage-related proteins.8 Similarly, a comparative analysis of the whole proteome of four

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conventional soybean seeds led to the identification of a total of 46 differentially expressed

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proteins, the majority of which were associated with the storage and lipid metabolism.9 However,

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it remains largely unclear that what are the major differences in the protein profiles of soybean

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cultivars differing in protein and oil contents. Previous efforts made in this direction have

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provided limited information as the regulatory/signaling-related proteins are masked by the high-

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abundance proteins (HAPs).

Large scale analysis of the seed filling



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Soybean seeds are rich in two major seed storage proteins (SSPs), β-conglycinin and

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glycinin, accounting for approximately 70-80% of the total protein content.10 Due to the presence

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of these two HAPs, mass spectrometry (MS)-based identification of soybean seed proteins

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resulted in the repeated identification of different variants or 2-DGES (2-DGE protein spots

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produced either from a single gene or from paralogous genes are referred as 2-DGES as per the

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classification given previously11) of β-conglycinin and glycinin proteins.12 In addition to their

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high abundance in seed, recent proteomic studies revealed their presence in soybean seed coat.13,

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14

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calcium16, and protamine sulfate (PS).17 However, these methods have not been fully utilized for

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the comparative soybean proteome analysis to get a better insight into the nutritional values of

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the seeds.

Methods have been developed to deplete these major soybean SSPs using isopropanol,15

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As soybean seeds are rich source of proteins and oils, one of the major goals of plant

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breeders worldwide is to enhance the nutritional properties of soybean seeds either by increasing

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their oil or protein content. However, for successful breeding programs, it is highly essential to

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understand the biochemical pathways underlying the accumulation of proteins and oils in

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soybean seeds. In this direction, we have carried out a comparative biochemical and proteomic

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profiling of protein- versus oil-rich seed cultivars of G. max and G. soja. In this study, a

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combination of the PS and 2-DGE methods was used to establish the proteomes of two cultivars

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each of G. max (Daewon and Saedanbaek) and G. soja (WS15 and WS22), differing in protein

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and oil reserve contents in order to get a better understanding on why soybean seeds differ in

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their protein and oil contents.

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2 Materials & Methods

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Plant Materials Seeds of G. max (Daewon and Saedanbaek) and G. soja (WS22 and WS15)

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cultivars were grown in the silt loam soil in the experimental fields of National Institute of Crop

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Science, Rural Development Administration (RDA) at Miryang, South Korea in the month of

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June. The soil was supplemented with a standard RDA N-P-K fertilizer (N-P-K=3-3-3.3 kg/10

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acre). Seeds were harvested in October (average temperature 23.5±3.5ºC, average day length 12

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h 17 min).13

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Analysis of Total Protein and Amino acid Contents Total protein content in the soybean seeds

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was measured using a protein analyzer (rapid N cube, Hanau, Germany). Using a high speed

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vibrating sample mill (CMT T1-100, CMT Company Ltd., Tokyo, Japan), seeds were powdered

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and 50 mg of each sample was then wrapped in nitrogen free paper and pressed to pellets. All the

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parameters were set to default. Glutamic acid (9.52% N) was used as test standard and a protein

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factor of 6.25 was used. Each sample was analyzed in duplicates.

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Amino acids were analyzed using an amino acid analyzer (Biochrom 30, Biochrom Ltd.,

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Cambridge, UK). Briefly, the samples were hydrolyzed with 6 N HCl in sealed glass tubes filled

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with nitrogen at 110ºC for 24 h. The HCl was removed from the hydrolyzed sample on a rotary

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evaporator brought to 10 mL with 0.2 M sodium citrated buffer, pH 2.2. Amino acids were

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analyzed by Biochrom 30 amino acid analyzer using nihydrin as color reactant and on a cation

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exchange resin column. Obtained data were analyzed using Ezchrom E software and the quantity

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of amino acids was calculated by comparison with a known concentration of amino acid standard.

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14



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Fatty Acid Composition Analysis Fatty acid analysis was carried out as described previously.18

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Fatty acid methyl esters (FAMEs) were prepared by soxhlet extraction, saponification, acid-

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catalyzed transesterification, and finally, extraction of FAMEs in hexane. FAMEs were

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subsequently analyzed by capillary gas chromatography (column: 30 m × 0.25 µm I.D., 0.5 µm;

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flame ionization detected temperature at 210ºC; carrier gas N2 at 1.0 ml/min; injector temperature

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at 210 ºC; oven temperature programmed from 180 to 210 ºC) using an Agilent 1100 capillary gas

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chromatograph. Quantitative data were calculated using the peak area ratio (% total fatty acids).

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Protein Extraction and Enrichment of Low-Abundance Proteins Total seed proteins were

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extracted as described previously.17 Briefly, soybean seeds (cv. Daewon, Saedanbaek, WS22 and

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WS15) were powdered in liquid nitrogen using pestle and mortar. Powdered samples (1 g) were

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homogenized in 10 mL Mg/NP-40 protein extraction buffer [0.5 M Tris-HCl (pH 8.3), 2% (v/v)

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NP-40, 20 mM MgCl2) followed by centrifugation at 12,000 g for 10 min at 4 ºC. Supernatant,

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thus obtained, was incubated with 0.1% PS in ice for 30 min after which the extract was again

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centrifuged at 12,000 g for 10 min at 4 ºC to separate the PS-supernatant (PSS) and PS-pellet

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(PSP) fractions, as described earlier.17 PSP fraction was dissolved in the equal volume of

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Mg/NP40 buffer and then proteins were extracted from the PSS and PSP fractions using

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TCA/acetone precipitation method. At the final step, proteins were stored in 80% acetone until

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analysis.

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Two-Dimensional Gel Electrophoresis 2-DGE was performed as described previously.17

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Briefly, proteins from the 80% acetone were precipitated by centrifugation at 12000 g for 5 min

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and the pellet obtained was dissolved in the rehydration buffer containing 7 M urea, 2 M thiourea,


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4% v/v CHAPS, 2 M DTT, and 0.5% v/v IPG buffer pH 4–7 (GE Healthcare, Waukesha, WI,

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USA). Protein concentrations in each fraction were determined by 2D-Quant kit (GE Healthcare).

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Proteins (600 µg) of each sample were loaded on 24 cm IPG strips (pH 4–7) by rehydration

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loading overnight at 20ºC and iso-electric focusing was carried out using following protocol: 50

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V for 4 h, 100 V for 1 h, 500 V for 1 h, 1000 V for 1 h, 2000 V for 1 h, 4000 V for 2 h, 8000 V

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for 5 h, 8000 V for 9 h, and 50 V for 6 h on the IPGphor II platform (GE Healthcare). The

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second dimensional separation was carried out on 12% SDS-PAGE, after sequential equilibration

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of the strips in in equilibration buffer [6 M urea, 30% v/v glycerol, 2% v/v SDS, 50 mM Tris-

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HCl (pH 6.8), and 0.1 mg/mL bromophenol blue] containing 100 mM DTT and 55 mM

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iodoacetamide. Gels were stained with colloidal Coomassie Brilliant Blue (CBB). A total of

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three biological replicates were performed for each data set.

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Image Acquisition and Data Analysis Images of all the CBB stained gels were acquired using

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transmissive scanner (PowerLook 1129, UMAX) at 32 bit pixel depth, 300 dpi resolution, and

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saved as TIFF file. The gel spots were detected using ImageMaster2DPlatinum software 6.0 (GE

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Healthcare). For analyzing the differential expression of proteins, spot volumes were normalized

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in the percentage volume mode and spots showing ≥1.5 fold change in spot volume were

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considered as differentially expressed spots. Student’s t-test (p< 0.05) was performed to check

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the significance of differential expression.

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Mass Spectrometry

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Differentially expressed spots were excised from the gel, destained and subjected to in gel

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digestion.19 In brief, first spots were subjected to in gel reduction using 10 mM DTT in 100 mM



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ammonium bicarbonate at 56ºC for 30 min and then alkylated using 50 mM iodoacetamide in

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100 mM ammonium bicarbonate for 30 min in the dark. Gel pieces were washed with 1:1

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ammonium bicarbonate and acetonitrile (ACN) solution and dehydrated using 100% ACN for 5

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min. Gel pieces were digested with 5 µL of trypsin solution (20 ng/µL, Gold mass spectroscopy

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grade, Promega, Madison, USA) in 50 mM ammonium bicarbonate pH 7.8 for 16 h at 37 ºC .

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Tryptic digested peptides were extracted twice with 0.1% trifluroacetic acid (TFA). Each sample

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was mixed with same volume of matrix (10 mg/mL α-Cynohydroxycinnamic acid, 0.1% TFA,

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50% ACN), loaded on a MALDI target plate and allowed to dry at 25ºC. Prepared samples of

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tryptic peptides were subjected to MALDI-TOF/TOF MS analysis using ABI 4800 Plus TOF-

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TOF Mass Spectrometer (Applied Biosystems, Framingham, MA, USA).14 Spectra were

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calibrated with the peptide calibration standard (Mass Standard Kit for the 4700 Proteomics

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Analyzer; calibration Mixture 1), prepared in the same way. The ten most and least intense ions

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per MALDI spot with signal/noise ratios >25 were selected for subsequent MS/MS analysis in 1

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kV mode using 800–1000 consecutive laser shots.13, 17 MS/MS spectra were searched against the

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Uniprot/Swiss-Prot database (14,926,175 sequences; 5,299,740,401 residues) and soybean

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peptide database obtained from the soybean genome database (Phytozome ver. 8.0,

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http://www.phytozome.net/soybean) by Protein Pilot v.3.0 software (AB Sciex, Framingham,

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MA, USA) using MASCOT as search engine (ver. 2.3.0, Matrix Science, London, UK). The

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search parameters used for the protein identification were as follows: fixed modifications-

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carbamidomethylation of cysteine, variable modification-methionine oxidation, peptide, and

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fragment ion mass tolerances-50 ppm, maximum trypsin missed cleavage-1 and instrument type-

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MALDI-TOF/TOF. Only high confidence identifications with statistically significant search

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scores (greater than 95% confidence, p < 0.05), were used for further analyses.


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Data Processing and Statistical Analysis Functional categories and statistical analyses were

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performed on differential protein spots. Gene ontology (GO) terms analysis was performed using

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an UFO web server (http://ufo.gobics.de/). Spot volumes of all the differentially expressed

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proteins were subsequently log2 transformed to equalize the scale of expression. The log2

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transformed values of each spot was then used for hierarchical clustering analysis (HCL) using

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multi-experimental viewer (MeV) software to generate the heat-map. Principal component

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analysis (PCA) of the differentially expressed protein spots was carried out using the statistical

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tool of the Microsoft Excel program (XLSTAT).

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Tofu Production For production of tofu a previously published protocol based on MgSO4

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precipitation was used.20, 21 In brief, seeds were soaked in water and incubated at 4 ºC for 24 h.

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After incubation, soaked seeds were ground with water for 5 min at high speed in a blender

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(Koco-4800, Koco Silver Co., Incheon, Korea). Soybean slurry, thus obtained, was filtered using

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a cheese cloth and squeezed manually to obtain the filtrate. The residue was mixed with water

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and the slurry was filtered again to obtain the soymilk. After adding 3% MgSO4, the soymilk was

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boiled in a tofu maker. The bean curd thus obtained was pressed smoothly. After pressing, the

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tofu was stored at 4 ºC until analysis.

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Antibody Generation and Western Blot Analysis For production of antibodies, spots

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corresponding to the different subunits of SSPs were excised from the 2-D gels and the proteins

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were identified by MS/MS. Protein sequences thus obtained were used for designing the primers,

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and the genes for respective proteins were cloned in a pQE30 expression vector. Recombinant



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proteins were purified according to the manufacturer’s protocol (Qiagen, Valencia, CA, USA)

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and used for generation of polyclonal antibodies by immunizing the rabbits. Antibodies were

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then purified from rabbit’s blood as described previously.22 For immunoblotting experiments, the

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total, PSS, PSP, tofu and whey protein samples (25 µg) were resolved on SDS-PAGE and

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transferred to a PVDF membrane.17 Transfer of proteins to the membrane was confirmed by

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Ponceau-S staining. Membrane was incubated in blocking solution for 2 h in 5% nonfat dry milk

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in TTBs (50 mM Tris-HCl, pH 8.2, 0.1% (v/v) Tween-20 and 150 mM NaCl), after which the

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membrane was incubated with the SSPs (β-conglycinin α subunit, α’ subunit, β subunit, Glycinin

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acidic chain) antibodies (1:10000) for overnight. After three washings of the membrane in TTBS

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for 15 min, it was incubated with secondary anti-rabbit IgG-antibody (1:6500) conjugated with

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horseradish peroxidase. Finally, the immuno-blot signals were detected using SuperSignal West

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pico Chemiluminescent Substrate Kit (Thermo Scientific, Waltham, MA, USA).

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3. Results

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Protein, Oil and Fatty Acid Analysis The protein content in seeds of Daewon, Saedanbaek,

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WS22 and WS15, was 39.2%, 47.9%, 46.9%, and 56.5%, respectively, whereas the oil content

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was 19.7%, 16.3%, 10.9%, and 6.9%, respectively (Figure S1A). Out of the total 17 amino acids

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analyzed, only glutamate and arginine showed significant differences between Daewon and

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Saedanbaek (Table S1).

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A total of five FA contents were analyzed in seed cultivars of G. max and G. soja

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including palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2),

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and linolenic acid (C18:3). The content of linoleic acid was highest among all FAs analyzed

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constituting 50.3%, 57.9%, 56.7%, and 56.6% in Saedanbaek, Daewon, WS22, and WS15,


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respectively (Figure S1B). Content of palmitic acid and stearic acid was almost similar in G.

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max and G. soja. In case of the G. max seeds, significant differences in content of oleic acid and

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linolenic acid were observed while G. soja seeds contained an almost similar concentration of

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these two FAs. The content of oleic acid and linolenic acid was 24.6% and 10.6% in Saedanbaek,

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respectively, while it was 18.7% and 9.3% in Daewon. In case of G. soja cultivars, these were

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10.5%, 10.4% and 18.1%, 18.5%, in WS22 and WS15, respectively (Figure S1B).

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SDS-PAGE Analysis of Daewon and Saedanbaek Seed Proteins Following the observation

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that there are significant differences in the protein and oil contents, total seed proteins were

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isolated from Daewon and Saedanbaek and resolved on SDS-PAGE. In each cultivar,

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approximately, 30 bands were observed ranging from 12–130 kDa of which two polypeptides of

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~19 kDa and 35 kDa were the most abundant, which represent the major SSPs in soybean.

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Addition of 0.1% PS precipitated major SSPs in the pellet fractions, thus allowing the

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enrichment of rare or low-abundance proteins (LAPs) in the PSS fraction (Lane 3 and 6, Figure

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S2A).17

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Comparative

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ImageMaster2DPlatinum software, a total of 1045±48.8 (CV 5%) and 1144 ± 24.4 (CV 2%)

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spots were detected in the 2-D gels of Daewon and Saedanbaek, respectively (Figure 1A, Figure

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S3). Of these spots, a total of 71 differential spots were identified where 39 and 32 spots showed

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increased and decreased abundance in Saedanbaek compared to Daewon (Figure 1A). MALDI-

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TOF/TOF MS analysis of the 71 differential spots resulted in confident assignment of 48 spots

2-DGE

Proteome

Analysis

of

Two


G.

max

Cultivars

Using


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(Table S2 and S3). Gene ontology analysis of the differentially expressed protein spots showed

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that up-regulated proteins in protein-rich Saedanbaek were associated with the nutrient reservoir

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activity and majorly included SSPs (53%, spots 8, 12, 14, 15, 16, 18, 19, 21, 22, 24, 29, 30, 31,

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32, 42, 43, 44), seed maturation proteins (spots 33, 36, 45 and 51), and trypsin inhibitors (spots

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41, 47 and 48). Out of the total 53% nutrient-related proteins, nine were identified as different 2-

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DGES of glycinin and 3 as β-conglycinin. Except for α’ subunit of β-conglycinin (spot 1) and

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glycinin G2 (spot 26), rest of the 2-DGES of β-conglycinin and glycinin were increased in

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abundance in Saedanbaek. GO functional annotation of the identified proteins showed two major

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categories: nutrient- (42.6%) and metabolism- (14.8%) related proteins in Saedanbaek. In

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contrast, the up-regulated proteins in oil-rich Daewon were mainly associated with the

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proteasome core complex and ubiquitin-dependent protein catabolic processes such as

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proteasome subunit alpha type (spot 27), and UDP-glucose pyrophosphorylase 2 (spot 9) (Figure

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1B, Table S3).

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Validation of the Results in Two G. soja Cultivars In order to validate the above findings in G.

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max cultivars, the same approach was applied to G. soja cultivars; WS22 and WS15. SDS-PAGE

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of WS22 and WS15 proteins showed significant depletion of SSPs in the pellet fractions (Lane 4

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and 7, Figure S2B). 2-DGE analysis of the PSS fractions of WS22 and WS15 revealed a total of

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989 ± 69.3 (CV 7%) and 1074 ± 108.1 (CV 10%) protein spots, respectively (Figure 2A, Figure

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S3). A comparison of the 2-D gels of WS22 and WS15 proteins identified a total of 53

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differentially expressed spots, where 38 and 15 had increased and decreased abundance,

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respectively, in WS15 compared to WS22 (Figure 2A). Protein assignment by MALDI-

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TOF/TOF MS and their GO annotation revealed a similar trend as observed in the G. max


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cultivars (Table S4 and S5). Protein spots showing increased abundance in protein-rich WS15

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cultivar were mainly SSPs with nutrient reservoir activity (spots 3, 4, 5, 9, 10, 11, 12, 13, 14, 26),

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beta-amylase activity (spot 7) and urease activity (spot 2), whereas in oil-rich WS22 cultivar,

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proteins having increased abundance were mainly involved in the sugar binding activity (spots

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20, 21, 22, 23, 24, 25) (Figure 2B, Table S5).

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Hierarchical Clustering and PCA Analysis To analyze the expression pattern of differential

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protein spots in protein- versus oil-rich cultivars of G. max and G. soja, normalized spot volumes

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of identified differentially expressed spots were calculated using the ImageMaster software. The

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obtained values for each spot were subsequently transformed to its base 2 logarithm and finally

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the obtained log2 values of spots were used for hierarchical clustering using MeV software (ver.

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4.9.0). A total of four and two clusters were formed based on the similar expression pattern in G.

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max and G. soja, respectively (Figure 3A and 3C). Functional groups, associated with the up-

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and down-regulated proteins in G. max and G. soja are depicted Figure 3B and 3D, respectively.

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In order to identify the protein groups responsible for correlated variations, the differential data

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set was subjected to PCA. Two principal components PC1 and PC2 contained 55.6 and 44.4%

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cumulative variance in G. max (Figure 4A) and 74.69% and 25.31% in G. soja, respectively

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(Figure 4B). The distribution of spots in two PCs was highly pronounced, suggesting significant

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differences in the spot volumes of the differential protein spots between protein- versus oil-rich

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soybean seed cultivars.

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Western blots confirmed differential regulation of SSPs in protein- versus oil-rich seed

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cultivars Western blotting was performed to confirm the differential modulation of SSPs in

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Daewon and Saedanbaek seeds using antibodies against β-conglycinin α-subunit, β-conglycinin

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α’-subunit, β-conglycinin β–subunit, and glycinin acidic chain. As expected, a very strong signal

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of β-conglycinin α-subunit, β-conglycinin α’-subunit, and glycinin acidic chain was seen in the

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total and PSP fractions and no differences could be observed, which might be due to the

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saturation of the signal, even though only 25 µg of proteins were loaded into each lane (Figure

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S4). Even in the PSS fraction, no significant modulation of SSPs was observed in Daewon and

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Saedanbaek (Figure 5A). At first, use of a high concentration of primary antibody might be

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expected as one of the possible cause of these strong signals observed in the Western blots.

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Therefore, to check the effect of primary antibodies, different dilutions of primary antibodies

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ranging from 1:10000 – 1:80000, were tried, however, even in the lowest concentration used

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(1:80000), no differential expression of these SSPs were observed in the Western blots of total,

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PSS and PSP fractions (Figure S5). Therefore, to further detect the differential expression,

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soybean proteins were fractionated as tofu and whey fractions. Surprisingly, even in the tofu

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fraction, no differences in the expression pattern of the glycinin and β-conglycinin were observed

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(Figure 5B). However, when the whey fraction of Daewon and Saedanbaek seeds was analyzed,

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differences in all the subunits of β-conglycinin were observed (Figure 5C). All the subunits of β-

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conglycinin including α-subunit, α’-subunit, and β–subunit showed higher expression in the

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Saedanbaek in comparison with Daewon (Figure 5C). The fold change of expression between

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Daewon and Saedanbaek was highest for α’-subunit of β-conglycinin and least for β-subunit of

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β-conglycinin (Figure 5C). In case of the glycinin acidic chain, no differences were observed


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even in the whey fraction, suggesting that it does not contribute to the increased protein content

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in soybean cultivars.

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4. Discussion

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The commercial importance of soybean seeds is primarily because of its high protein and oil

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contents. Therefore, our first study objective was to investigate the total protein and oil content

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in the seed cultivars of G. max (cv. Daewon and Saedanbaek) and G. soja (cv. WS22 and WS15).

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Our results showed that of G. max cultivars, Saedanbaek is rich in protein, while Daewon is rich

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in oil content. In case of G. soja, WS15 contained higher protein than WS22. These results

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suggested that the selected cultivars of G. max and G. soja differ in the total protein and oil

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content significantly and hence can be used for analyzing their proteome as high protein and high

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oil cultivars. FAs are important constituents of the oil determining the quality of the oil for

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human consumption. The commercial application of the soybean oil is due to its unique FAs

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composition. Linoleic acid and linolenic acids are polyunsaturated FAs (PUFA) and both are

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essential fatty acids as human beings are not able to synthesize these FAs.

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PS-Precipitation Leads to Enrichment of LAPs in the PSS Fraction Soybean seeds are rich in

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SSPs including different subunits of glycinin and β-conglycinin.1 These SSPs are major HAPs of

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the seeds which inhibit the detection and identification of LAPs. It has been shown that without

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incorporation of any depletion method, this identification of SSPs can reach upto 80%, resulting

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in loss of time, efforts, and resources. As LAPs are crucial components of the signaling and

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regulation machinery in cells, their identification might provide a better picture of the seed

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physiology. In the past few years, several methods have been developed to reduce or completely



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deplete these HAPs from the total seed proteins with an aim to enhance the detection and

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identification of LAPs.15-17 These methods are based on the specific depletion of SSPs using 40%

338

isopropanol,15 10 mM calcium16, or 0.1% PS.17 Here, we used the PS-method for the depletion of

339

SSPs and concurrently enrichment of the LAPs. Proteins after PS treatment were resolved on

340

high-resolution 2-DGE to enhance the detection of LAPs. Coefficient of variation percentages

341

(%CV) for different replicates of 2-DGE of each sample was calculated as 5% and 2%,

342

respectively, for Daewon and Saedanbaek, representing high reproducibility of the used PS

343

method. 2-DGE followed by MS identification of PSS fractions of G. max and G. soja showed

344

that out of the total 79 identified proteins (48 from G. max and 31 from G. soja), only 30% (24

345

spots) were identified as SSPs (different 2-DGES/subunits of glycinin and β-conglycinin),

346

validating the efficacy of PS-precipitation method in the enrichment of LAPs. Enrichment of

347

LAPs by isopropanol or calcium based depletion methods, has also been shown previously.

348

Using 10 mM calcium, 541 LAPs were detected of which 197 showed more than 2.5 fold

349

enrichment after isopropanol treatment.15 In this study, identified LAPs in G. max and G. soja

350

included different 2-DGES of sucrose binding proteins, trypsin inhibitors, seed maturation

351

proteins, seed biotin containing proteins, seed biotinylated proteins, urease, beta-amylase,

352

glutamine synthetase, phosphoglycerate kinase, superoxide dismutase, proteasome subunit beta

353

type, stress-induced protein SAM22, and lectins (Table S3 and S5). In addition to these proteins,

354

15 spots were identified as uncharacterized proteins. As the annotation suggest, these proteins

355

are not yet characterized, most probably due to their masking by HAPs which hinders their

356

identification and characterization. Moreover, a few novel proteins including Ran-binding

357

protein 1 homolog a (spot 25, G. max), and tau class glutathione S-transferase (spot 29, G. soja)

358

were also identified, and these have not been reported previously in the matured seed proteome.


Page 17 of 36


359

A more comprehensive identification of PSS proteins in the future study is likely to identify

360

many more novel proteins, which can increase our understanding of the seed physiology.

361 362

Up-Regulated Proteins in High Protein Cultivars were Mainly SSPs 2-DGE analysis

363

followed by MS identification of the differentially expressed proteins showed a similar trend on

364

accumulation of SSPs in the high-protein cultivars of G. max and G. soja. Although a similar

365

trend of SSPs accumulation was observed in the high-protein cultivars, a contrasting pattern of

366

accumulation of SSPs was observed in WS15 and Saedanbaek. In G. soja, only different subunits

367

of β-conglycinin were identified with no identification of glycinin subunits, while in the case of

368

G. max, the total number of glycinin subunits was three times higher than of β-conglycinin. It has

369

been shown that the ratio of glycinin and β-conglycinin is important for the texture of the tofu.23

370

Similar results were also observed in a comparative study of G. max and G. soja seed where

371

lesser 2-DGES of glycinin were observed in G. soja.11 In G. max, 32 2-DGES of glycinin were

372

observed while in G. soja, only 23 2-DGES could be detected. These results suggest that protein-

373

rich Saedanbaek cultivar accumulates higher amount of SSPs as compared to oil-rich Daewon

374

seeds. This finding is in line with a previous observation that the amount of either β-conglycinin

375

or/and glycinin is associated with protein-rich seeds.24

376

Recently, Xu and coworkers compared the protein profiles of four soybean cultivars.8 A

377

comparison of the results of this study with their study showed 15 common proteins which were

378

identified in both the studies, with 25 and 39 unique proteins in the previous and current study,

379

respectively (Figure S6). Common proteins were divergent in nature and included glycinin

380

A1aBx subunit, dehydrin, sucrose-binding protein-like, glycinin G4 allergen Gly m Bd 28 K, and



381

beta-conglycinin alpha subunit. Unique proteins identified in this study were mainly stress

382

related, while the unique proteins identified in the previous study were associated with the sugar

383

metabolism. These differences might be cultivar specific and were probably due to the use of

384

different cultivars in this and the previous study. In this study, we used Saedanbaek and Daewon

385

cultivars while Jiyu-73 and Zhonghuang-13 cultivars were used in the previous study.8

Page 18 of 36

386 387

Western Blotting Confirmed the Association of SSPs with the Enhanced Protein Amount

388

Our findings showed significant changes in the abundance of glycinin and β-conglycinin

389

between high- and low-protein cultivars of G. max and G. soja. A previous proteomic study also

390

found higher accumulation of SSPs in the protein-rich cultivars. However, as there is high

391

variability in MS results, it is always advisable to have some confirmatory experiments.

392

Therefore, here we used Western blotting to confirm the association of SSPs with enhanced

393

protein amount. Although the PS-precipitation led to significant depletion of the SSPs from the

394

PSS fraction, we could not visualize any differential expression of these SSPs in the PSS fraction

395

of Daewon and Saedanbaek using Western blotting approach (Figure 5A). Therefore, to further

396

analyze the differential modulation of the SSPs, a novel approach was employed. Soybean seeds

397

are being largely used for the production of tofu. The precipitated proteins are used for tofu

398

production while rest of the proteins is washed away as whey. Therefore, we used both Daewon

399

and Saedanbaek seeds for the production of tofu and both tofu and whey protein samples were

400

analyzed by Western blotting. Even though the total protein and SSPs amount were higher in the

401

Saedanbaek as compared with Daewon, no differences in the amount of SSPs in the tofu

402

fractions were observed. One of the possible explanations of this could lie in the tofu making

403

procedure. Tofu production involves precipitation of proteins using MgSO4, and since the same


Page 19 of 36


404

amount of MgSO4 (3%, unsaturated concentrations) was used for precipitation of seed proteins,

405

it is expected that equal amount of seed proteins are precipitated from both Daewon and

406

Saedanbaek seeds, thus the rest of the proteins comes out in whey fraction. Using this

407

methodology, we found the differential expression of the SSPs, suggesting the efficacy of the

408

used approach. Taken together, our results confirm that the high protein content in the some of

409

the soybean cultivars is due to the accumulation of SSPs.

410 411

Established differential Protein Profiles Provides a Possible Explanation for Soybean

412

Cultivars Differing in Protein versus Oil Rich Seeds Urease enzymes are involved in the

413

degradation of urea to form ammonia and carbon dioxide.25, 26 The ammonia thus formed is

414

converted into glutamine by the action of glutamine synthetase.25 Surprisingly, both urease and

415

glutamine synthetase proteins showed increased abundance in seeds of the protein rich cultivars–

416

Saedanbaek and WS15 (Table S3 and S5) including one urease activating protein, namely, Ni-

417

binding urease accessory protein UreG found in Saedanbaek. Urease accessory proteins are

418

involved in the activation of urease by incorporating the nickel ions to the active site of urease

419

which is critical for urease activity.26 Up-regulation of glutamine synthetase in high protein

420

cultivar of soybean was also observed previously.8 Taken together, increased accumulation of

421

these proteins indicates the production of higher amount of glutamine in the protein-rich

422

cultivars (Saedanbaek and WS15) in comparison with the Daewon and WS22. Interestingly,

423

soybean SSPs, which governs the total protein content of soybean seeds, are rich (8–11%) in

424

glutamine amino acid, while the glutamine content of other proteins are less than 2–5%. Based

425

on these results, it could be proposed that the glutamine content is likely to be one of the factors

426

involved in determining the total amount of SSPs accumulation in soybean seeds. Since SSPs



427

amount is directly associated with the increased protein amount, restriction in the glutamine

428

concentration could be one of the limiting factor determining the amount of protein accumulation

429

in seeds. Moreover, analysis of amino acid contents in the Daewon and Saedanbaek seeds also

430

revealed higher concentrations of glutamate and arginine in Saedanbaek. Since both of these

431

amino acids are the precursors of urea and glutamine, their higher concentrations in Saedanbaek

432

further suggest the increased production of urea and thus glutamine in high-protein cultivar-

433

Saedanbaek (Figure 6). Overall, it can be speculated the high protein content in the protein-rich

434

cultivars is potentially because of higher amount of glutamine which is the result of the higher

435

activities of urease, its accessory proteins, and glutamine synthetase.

Page 20 of 36

436

In case of the high-oil cultivar Daewon, increased accumulation of many biotinylated

437

proteins (spots 5, 6, 7) including seed biotin-containing protein SBP65 and seed biotinylated

438

protein 68 kDa isoform, was observed. The exact role/functions of these SBPs remain largely

439

unclear in plants; however majority of the biotinylated enzymes of plants like acetyl-CoA

440

carboxylase, 3-methylcrotonoyl-CoA carboxylase, propionyl CoA carboxylase and pyruvate

441

carboxylase are involved in the fatty acid biosynthesis, suggesting the similar functions of SBPs

442

in plants.27,

443

cultivars may partially explain high accumulation of oil in Daewon and WS22 seeds in

444

comparison with Saedanbaek and WS15.

28

Observed increased abundance of these biotinylated proteins in the oil-rich

445

Taken together, our results confirmed that the protein-rich cultivars Saedanbaek and

446

WS15 accumulate higher amounts of SSPs including various subunits of glycinin and β-

447

conglycinin. Moreover, our results also indicate that the levels of glutamine might be one of the

448

potential factors for the SSPs synthesis, which determines the total protein content in soybean

449

seeds.


Page 21 of 36


450

Abbreviations used

451

2-DGE, two dimensional gel electrophoresis; FA, fatty acid; HAP, high-abundant protein; LAP,

452

low abundant protein; PS, Protamine sulfate; PSP, protamine sulfate pellet; PSS, protamine

453

sulfate supernatant; SSP, seed storage protein

454

455

Acknowledgements

456

This work was supported by a grant from the Next-Generation Bio Green 21 Program (No.

457

PJ011070032015) and National Agenda Programs for Agricultural R&D of Rural Development

458

Administration (PJ01002002), Republic of Korea.

459 460

Supporting Information

461

Figure S1: Biochemical analysis of G. max (Daewon and Saedanbaek) and G. soja (WS22 and

462

WS15) seeds. Comparative analysis of protein, oil (A), and fatty acids (B). Figure S2: SDS-

463

PAGE analysis of Daewon and Saedanbaek (A), WS22 and WS15 (B) seed proteins.

464

Abbreviations: Total (T), PS-supernatant (S) and precipitated fraction (P). Figure S3: Biological

465

replicates of 2-D gels of PSS fraction proteins of G. max (A) and G. soja (B) seeds. Figure S4:

466

Immunoblotting of the total and PSP fractions using SSPs antibodies. Figure S5: Immunoblotting

467

of the β-conglycinin α subunit with different dilution of the antibodies used (1/10,000 to

468

1/80,000). Abbreviations: Total (T), PS-supernatant (S) and precipitated fraction (P). Figure S6:

469

Venn diagram showing a comparative analysis of the identified proteins in this study with the



Page 22 of 36

470

previous published study (Xu et al.8). Table S1: Amino acid profiling of Daewon and

471

Saedanbaek seeds. Table S2: Percentage volumes of differentially expressed spots from the three

472

biological replicates of Daewon and Saedanbaek seeds. Table S3: Identification of differentially

473

expressed G. max proteins by MALDI-TOF/TOF and MS/MS. Table S4: Percentage volumes of

474

differentially expressed spots from the three biological replicates of WS22 and WS15. Table S5:

475

Identification of differentially expressed G. soja proteins by MALDI-TOF/TOF and MS/MS.

476

This material is available free of charge via the Internet at http://pubs.acs.org."

477

478

479

480

481

482

483

484

485

486

487


Page 23 of 36


488

References

489

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Genomics Proteomics 2014, 5, 1. 2. Xiao, C. W. Health effects of soy protein and isoflavones in humans. J. Nutr. 2008, 138, 1244-1249.

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J. I.; Kim, M. C. Proteomic analysis of seed storage proteins in low allergenic soybean

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accession. J. Korean Soc. Appl. Biol. Chem. 2011, 54, 332– 339.

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4. Rajjou, L.; Duval, M.; Gallardo, K.; Catusse, J.; Bally, J.; Job, C.; Job, D. Seed germination and vigor. Annu. Rev. Plant. Biol. 2012, 63, 507-533.

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5. Miernyk, J. A.; Hajduch M. Seed proteomics. J. Proteomics 2011, 74, 389-400.

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6. Hajduch, M.; Ganapathy, A.; Stein, J. W.; Thelen, J. J. A Systematic Proteomic Study of

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Seed Filling in Soybean. Establishment of high-resolution two-dimensional reference maps,

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expression profiles, and an interactive proteome database. Plant Physiol. 2005, 137, 1397-

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proteomics of high-oil and high protein soybean seeds. Food Chem. 2015, 172, 105-116.

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9. Gomes, L. S.; Senna, R.; Sandim, V.; Sliva-Neto, M. A. C.; Perales, J. E. A.; Zingali, R. B.;

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Soares, M. R.; Fialho, E. Four conventional soybean [Glycine max (L.) Merrill] seeds



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2013, 62, 1283-1293.

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10. Wilson, K. A.; Rightmire, B. R.; Chen, J. C.; Tan-Wilson, A. L. Differential proteolysis of

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glycinin and β-conglycinin polypeptide during soybean germination and seedling growth.

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Plant Physiol. 1986, 82, 71-76.

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11. Agrawal, G. K.; Jwa, N.S.; Lebrun, M. H.; Job, D.; Rakwal, R. Plant secretome: unlocking secreted proteins. Proteomics 2010, 10, 799-827.

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12. Natarajan, S. S.; Xu, C.; Bae, H.; Caperna, T. J.; Garrett, W. M. Characterization of storage

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proteins in wild (Glycine soja) and cultivated (Glycine max) soybean seeds using proteomic

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analysis. J. Agric. Food Chem. 2006, 54, 3114-3120.

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13. Kim, Y. J.; Lee, S. J.; Lee, H. M.; Lee, B. W.; Ha, T. J.; Bae, D. W.; Son, B. Y.; Kim, Y. H.;

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Baek, S. B.; Kim, Y. C.; Kim, S. G.; Kim, S. T. Comparative proteomics analysis of seed

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coat from two black colored soybean cultivars during seed development. Plant Omics 2013,

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14. Gupta, R.; Min, C. W.; Kim, S. W.; Wang, Y.; Agrawal, G. K.; Rakwal, R.; Kim, S. G.; Lee,

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B. W.; Ko, J. M.; Baek, I. Y.; Bae, D. W.; Kim, S. T. Comparative investigation of seed

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coats of brown-versus yellow-colored soybean seeds using an integrated proteomics and

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metabolomics approach. Proteomics 2015, 15, 1706-1716.

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15. Natarajan, S. S.; Krishnan, H. B.; Lakshman, S.; Garrett, W. M. An efficient extraction

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method to enhance analysis of low abundant proteins from soybean seed. Anal. Biochem.

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16. Krishnan, H. B.; Oehrle, N. W.; Natarajan, S. S. A rapid and simple procedure for the

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depletion of abundant storage proteins from legume seeds to advance proteome analysis: A

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case study using Glycine max. Proteomics. 2009, 9, 3174–3188.

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17. Kim, Y. J.; Wang, Y.; Gupta, R.; Kim, S. W.; Min, C. W.; Kim, Y. C.; Park, K. H.; Agrawal,

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G. K.; Rakwal, R.; Choung, M. G.; Kang, K. Y.; Kim. S. T. Protamine sulfate precipitation

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method depletes abundant plant seed-storage proteins: A case study on legume plants.

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Proteomics 2015, 15, 1760-1764.

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18. Christie, W. W. Preparation of ester derivatives of fatty acids for chromatographic analysis.

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In Advances in Lipid Methodology-Two; Christie, W. W., Eds.; Oily Press: Dundee,

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Scotland, 1993; pp 69−111.

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19. Kim, S. G.; Wang, Y.; Lee, C. H.; Mun, B. G.; Kim, P. J.; Lee, S. Y.; Kim, Y. C.; Kang, K.

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Y.; Rakwal, R.; Agrawal, G. K.; Kim, S. T. A comparative proteomics survey of proteins

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responsive to phosphorous starvation in roots of hydroponically-grown rive seedlings. J.

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Korean Soc. Appl. Biol. Chem. 2011, 54, 667-677.

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20. Cai, T. D.; Chang, K. C.; Shih, M. C.; Hou, H. J.; Ji, M. Comparison of bench and

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production scale methods for making soymilk and tofu from 13 soybean varieties. Food. Res.

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Int. 1998, 30, 659-668.

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21. Mullin, W. J.; Fregeau-Reid, J. A.; Butler, M.; Poysa, V.; Woodrow, L.; Jessop, D. B.;

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Raymond, D. An interlaboratory test of a procedure to assess soybean quality for soymilk

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and tofu production. Food. Res. Int. 2001, 34, 669-677.

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22. Kim, S. T.; Cho, K. S.; Yu, S.; Kim, S. G.; Hong, J. C.; Han, C. D.; Bae, D. W.; Nam, M. H.;

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Kang, K. Y. Proteomic analysis of differentially expressed proteins induced by rice blast

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23. Saio, K.; Kamiya, M.; Watanabe, T. Food processing characteristics of soybean 11S and 7S proteins. Agric. Biol. Chem. 1969, 33, 1301-1308.

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24. Krishnan, H. B.; Natarajan, S. S.; Mahmoud, A. A.; Nelson, R. L. Identification of glycinin

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and β-conglycinin subunits that contribute to increased protein content of high-protein

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soybean lines. J. Agric. Food Chem. 2007, 55, 1839-1845.

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25. Sirko, A.; Brodzik, R. Plant ureases: Roles and regulation. Acta. Biochim. Pol. 2000, 47, 1189-1195.

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26. Witte, C. P. Urea metabolism in plants. Plant Sci. 2011, 180, 431-438.

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27. Natarajan, S. S.; Krishnan, H. B.; Khan, F.; Chen, X.; Garrett, W. M.; Lakshman, D.

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Analysis of soybean embryonic axis proteins by two-dimensional gel electrophoresis and

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mass spectrometry. J. Basic Appl. Sci. 2013, 9, 309-332.

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28. Charles, D. J.; Cherry, J. H. Purification and characterization of acetyl-coa carboxylase from developing soybean seeds. Phytochemistry. 1986, 25, 1067-1071.

567 568 569

570

571

572

573


Page 26 of 36

Page 27 of 36


574

Figure captions

575

Figure 1. (A) Representative 2-D gels of PSS fractions of Daewon and Saedanbaek cultivars of

576

G. max. First dimension separation was carried out on 24 cm IPG strips, pH 4–7 and second

577

dimension separation was carried out on 12% SDS-PAGE. Gels were stained with colloidal

578

CBB stain. Differentially expressed spots in supernatant fractions are marked by arrows. (B)

579

Enlarged view of 2-D gel areas showing differentially expressed protein spots in PSS

580

fractions of Daewon and Saedanbaek.

581 582

Figure 2. (A) Representative 2-D gels of PSS fractions of WS22 and WS15. (B) Enlarged view of the differentially expressed protein spots.

583

Figure 3. (A) Hierarchical clustering (HCL) analysis of the differentially expressed proteins of

584

Daewon and Saedanbaek. For HCL, percentage spot volumes for each spot were calculated

585

using ImageMaster 2D Platinum software and subsequently log transformed to base 2.

586

Clustering was performed using Mega experiment Viewer (MeV) software. (B) GO

587

enrichment analysis of the identified differentially expressed proteins.

588

Figure 4. Principal component analysis of the differentially expressed proteins of Daewon and

589

Saedanbaek (A) and WS22 and WS15. Two principal components formed accounted for 100%

590

cumulative variance in both the datasets.

591

Figure 5. Immunoblotting of the Daewon and Saedanbaek proteins in different protein fractions

592

using β-conglycinin and glycinin antibodies. A total of 25 µg of protein was loaded in each

593

lane of 14% SDS-PAGE and then proteins were transferred to a PVDF membrane. After

594

blocking in 5% skim milk, membrane was incubated first with 1:10,000 dilutions of primary



595

antibody and 1:10,000 secondary antibody. Blot was developed using Super signal Westpico

596

chemiluminescent substrate kit (Thermo Scientific).

Page 28 of 36

597

Figure 6. A hypothetical model explaining why some soybean seeds are rich in proteins. Up-

598

regulation of urease, Ni-binding urease accessory protein and glutamine synthetase suggest

599

higher production of urea and thus glutamine in the high-protein cultivar. This was further

600

confirmed by the amino acid analysis which showed the higher concentration of glutamate

601

and arginine, precursors of urea and glutamine, in high protein cultivars. Glutamine thus

602

formed is used for the synthesis of SSPs which are rich in glutamine (8-11%). Based on

603

these results, it can be concluded that glutamine concentration can be the determining factor

604

of total protein contents in soybean seeds.

605 606 607 608 609 610 611

612 613


Page 29 of 36



(A)

Journal of Agricultural and Food Chemistry 7 4

pI

4 1

Daewon 8 22

11 9

24

25 26 35

234

27

10 28 29

45

42

30 32

-70-

21 19 18 37 40

51

54

52

8 22 25 26

-35-

35

10

9

24 27

28

-25-

41 42

45

12

29 30

32 31

16 17 1415 33

19 18 34 36

43 44

21

37 40

50 51

46

56 7

234

11

47 -15-

1045±48.8, CV 5%

1

Saedanbaek

-55-40-

50 48 53

7

kDa

7

17

1415 33 34 36

43 44

47 46

16

12

31 41

5 6

Page 30 of 36

pI

48 53 54

52

1144±24.4, CV 2%

(B)


Figure 1 Min et al.

Page 31 of 36

(A)


pI

4

WS22

4 5

6

7

9

16 20 23 25 21 24 27 22 26 30

28

-130 -100 -70 -

2

1

3

8 10

11 13 14 12 18 17 19

15

pI

4

7

WS15 4 5

7

8 10 11

9

13 12 17

20 23 25 21 24 27 22

-25 -

29

6

2

16

-35 -

26 30

31

1

3

-55 -40 -

7

28

14 18

15

19

29

31

-15 -

989±69.3, CV 7%

1074±108.1, CV 10%

(B)


Figure 2 Min et al.


(A)

G. max

(C)

(B)

Page 32 of 36

G. soja

(D)

Up-regulated protein (32) Down-regulated protein (16)

Up-regulated protein (19) Down-regulated protein (12)


Figure 3 Min et al.

Page 33 of 36


(A)

(B) Biplot (axes PC1 and PC2: 100.00 %)

Biplot (axes PC1 and PC2: 100.00 %) 2.5

2.5

11

10 2

Saedanbaek

Daewon

17

WS15

25

1.5

WS22 10

1.5

6 1

19

44

29

1

36 28

0.5

18

40

33

24

32

-0.5

53

52

47

50 45 0

1

51

43 16

30 21

8

26

34

31

-1

12

-1.5

4

37

35

42 14 15

7

11 -3

-2.5

-2

-0.5

31

0

0.5

1

2

2

4

18

15

29

16

21

22

23 1

19

25 24

28

-1.5

2 1.5

12

5

9 30

20

8

14

-1

6 9

-1

3

13

0

5

41 -1.5

0.5

27

3

27 54

17 26

7

-0.5

46

22

-2

PC2 (25.31 %)

48

PC2 (44.40 %)

2

-2 2.5

3

-3

-2.5

PC1(55.60 %)

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

PC1 (74.69 %)

G. max (Daewon and Saedanbaek)

G. soja (WS22 and WS15)


Figure 4 Min et al.


Page 34 of 36


Figure 5 Min et al.

Page 35 of 36


Ni·binding Urease Accessory Protein

Arginine

Urease

High glutamine contents (8-11%)

NH3 + CO2

Urea

Pi

Urea cycle

Ornithine

Glutamate

Protein synthesis

Glutamine Glutamine synthetase

β-conglycinin

SSPs Glycinin


Figure 6 Min et al.


Graphics for table of content (TOC)


Page 36 of 36

Comparative Biochemical and Proteomic Analyses of Soybean Seed

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