A novel hardness-related and starch granule-associated protein marker in wheat: LMW-GS-‘S’

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Abstract

Starch granule (SG)-associated proteins are involved in starch synthesis and the interaction between SGs and the endosperm protein matrix. In this study, SG proteins were sequentially extracted with the chaotropic reagent, urea from 1 M to 4 M, and then profiled using an integrated proteomic approach including one- and two-dimensional electrophoresis, mass spectrometry and antibody-based enzyme-linked immunosorbent assay (ELISA). The results demonstrated that the SG-associated proteins were dominated by granule-bound starch synthase (GBSS), gliadin, low molecular weight glutenin subunits (LMW-GS), serine protease inhibitors, α-amylase inhibitors and puroindolines. A protein with an apparent molecular mass of 50 kDa, expressed in cultivar hard wheat Kukri but not in soft wheat Triller was identified as a novel member of the ‘S’ group of LMW-GS, designated as LMW-GS-‘S’. Further characterization using a broad wheat population revealed that LMW-GS-‘S’ was selectively expressed in hard wheat cultivars while deleted in all soft wheats tested. Its relationship with hardness was confirmed by its expression in tetraploid durum wheats, which are among the hardest wheats around the world. Monoclonal antibody (MAb) F8-14E6 against LMW-GS-‘S’ was developed and used in an ELISA to screen 90 Glu allele-defined doubled haploid Janz/Kukri wheat lines. The allele that encodes LMW-GS-‘S’ was mapped to GluB3h (p < 0.001).

Highlights

► Starch granule-associated proteins were profiled by proteomics. ► LMW-GS-‘S’ was associated with hard wheat. ► LMW-GS-‘S’ was encoded by GluB3h.

Introduction

Wheat (Triticum aestivum L.) starch along with storage proteins are major determinants of end-use suitability of flour for making wheat-based foods such as bread, biscuit or noodles (Payne, 1987, Shewry and Halford, 2002, Shewry et al., 1992, Zhao and Sharp, 1998). While the unique visco-elastic property of storage proteins is critical to bread-making, starch properties such as swelling, pasting, viscosity and gelatinization, and interaction between SGs and endosperm protein matrix are also important for flour functionality. Variation in the composition and content of SG-associated proteins leads to different grain texture and hence varying flour functionality.

Two groups of SG-associated proteins have been described in previous studies, namely the starch synthetic enzymes which mainly resided inside SG, and other proteins such as puroindolines located on the granule surface. Considerable attention has been focused on starch enzymes (Ball and Morell, 2003, Rahman et al., 1995). The polymorphism of these proteins among wheat varieties has made a large contribution to wheat breeding and agronomics (Udall et al., 1999, Zhao and Sharp, 1996, Zhao and Sharp, 1998, Zhao et al., 1998). In contrast, the SG surface proteins have not been well-studied. One reason for this is the experimental condition employed by most previous studies on SG proteins in which SDS- or DTT- washed SGs and gelatinized starch were used. SDS and DTT treatment results in loss of the proteins bound to the SG surface and is only suitable for investigating the proteins entrapped inside the starch matrix such as starch synthetic enzymes. Thus far, only one family of SG surface proteins, the 15 kDa puroindolines, has been well-studied, which serves as a hardness trait under significant genetic control at the hardness locus, Ha on the short arm of chromosome 5D (Morris, 2002). Furthermore, the discovery of puroindolines demonstrated the importance of SG surface proteins. SG surface proteins are at the interface between the SGs and the endosperm protein matrix, and they are on the frontline to processes such as granule hydration and chemical modifying agents during bread or noodle making.

With the development of proteomics technology, arrays of protein biomarkers have been discovered in medicine and plants in the last ten years (Chen et al., 2005, Macarthur and Jacques, 2003, Mak et al., 2006). The aims of this study were to explore the nature of SG-associated proteins, especially the surface-associated ones, through the application of proteomic technology coupled with appropriate protein fractionation techniques with a view to developing a new protein biomarker to assist wheat breeders and end users to characterize wheat varieties.

Section snippets

Wheat varieties

Grain samples of Australian hexaploid wheats were provided by the South Australian Research and Development Institute, Adelaide, Australia. Fifty-one Australian hexaploid wheat varieties were examined including 29 hard wheats (Amery, Blade, BT-Schomburgk, Camm, Cascades, Cranbrook, Diamondbird, Dollarbird, Excalibur, Frame, H45, Hartog, Goldmark, Kalannie, Kukri, Janz, Krichauff, Machete, Mawson, Perinjori, Perouse, Sunbri, Sunco, Sunelg, Sunland, Sunstate, Sunvale, Trident and Worrakatta) and

Profiles of SG-associated proteins under varying stringency

The starch granule preparation was first carried out under a range of washing conditions with cultivars Triller and Kukri, which represented both soft (Triller) and hard (Kukri) wheats. As shown in Fig. 1, compared with water and ethanol wash, extra washing with salt and detergent had no affect on the protein profiles. The prominent protein band with apparent molecular weight 50 kDa was present in Kukri (lanes 2 and 4) but absent in Triller (lanes 1 and 3). Stringent washes by high-salt and

Discussion

The discovery of LMW-GS-‘S’ and the mapping of its encoding allele – GluB3h resulted from the integrated proteomic approach used in the current study, which included 1- and 2-dimensional electrophoresis, mass spectrometry, and monoclonal antibody-based immunoassay. Proteomics is widely used for protein identification and characterization in species from prokaryote to eukaryote. For wheat in particular, it has been employed in studies on foam-forming soluble proteins in dough (Salt et al., 2005

Acknowledgments

We thank Value Added Wheat CRC for funding this study. We are grateful to Dr Idris Barchia at the Department of Primary Industry, NSW Australia for statistical analysis of the Janz/Kukri doubled-haploid allele-mapping data, Mrs Clare Johnson at Value Added Wheat CRC for her great support, and Dr Diana Oakes at the University of Sydney for proofreading this manuscript.

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