Browsing by Subject "Product-quality"

Now showing 1 - 1 of 1

Deciphering the potential of large-scale proteomics to improve product quality and nutritional value in different wheat species
(2022) Afzal, Muhammad; Longin, Friedrich
Wheat (Triticum aestivum) is one of the most important staple crops globally, which provides on average ~20% of the dietary intake of protein, starch and further important ingredients like fiber, minerals, vitamins, and essential amino acids for humans. Besides common wheat, there exist further wheat species with global to only local importance, i.e., durum, spelt, emmer and einkorn. Common wheat and durum are relatively widely cultivated whereas the other three species are cultivated only in specific regions. Apart from other functions, wheat proteins largely influence the end-use quality of products such as bread and pasta quality. Furthermore, wheat proteins can induce inflammatory reactions in humans such as celiac disease, wheat allergy and non-celiac wheat sensitivity. Thus, proteome profiles of different wheat species and cultivars within these species are of high relevance for stakeholders along the wheat supply chain. Proteomic technology has made breakthrough advancements in the recent times capable of quantifying thousands of proteins in 1.5–2 hours. Also, the wheat reference genome has been published and extended recently. These developments are extremely helpful in studying the wheat proteome at a high resolution. However, the modern large-scale proteomics has yet neither been applied to perform comparative investigation of the proteomes of different wheat species nor to study the proteomes of different types of breads and flours nor to study its application in the context of plant breeding. Therefore, we utilized modern large-scale proteomics to fill these gaps within the framework of this PhD work. First of all, an optimized data analysis pipeline was designed to deal with big proteomics data. This was necessary to estimate a multitude of quantitative genetics parameters for each protein and perform a comparative investigation of the proteomes. Optimization included implementation of data filtering based on the quantification of a protein in a given proportion of the samples, cultivars and environments. Different tests such as test for normal distribution of each protein in the context of statistical modelling and test to check the equality of variance between groups to apply the appropriate t-test were incorporated into a semi-automated workflow. In parallel, we adjusted and improved the lab methodology to deal with hundreds of samples within a short time period. We introduced a novel hybrid liquid chromatography-mass spectrometry (LC-MS) approach that combines quantification concatamer (QconCAT) technology with short microflow LC gradients and data-independent acquisition (DIA). The proposed approach measures the proteome by label-free quantification (LFQ) while concurrently providing accurate QconCAT-based absolute quantification of the key amylase/trypsin inhibitors (ATIs). These methods were then applied to compare different wheat species based on dozens of cultivars grown at multiple locations. First, we compared common wheat and spelt and identified 3,050 proteins overall. Of total proteins, 1,555 proteins in spelt and 1,166 in common wheat were only detected in a subset of the field locations. There were 1,495 and 1,604 proteins in spelt and common wheat, respectively, which were consistently expressed across all test locations in at least one cultivar. Finally, there were 84 and 193 unique proteins for spelt and common wheat, respectively, as well as 396 joint proteins, which were significantly differentially expressed between the two species. Using potentially allergenic proteins – annotated as amylase/trypsin inhibitors, serpins, and wheat germ agglutinin – we calculated an equally weighted “allergen index” that largely varied across cultivars ranging from –13.32 to 10.88 indicating the potential to select for cultivars with favorable proteome profiles. Next, we examined the proteomes of six different flours (wholegrain and superfine flours) and 14 different bread types (yeast and sourdough fermented breads and common wheat breads plus/minus bread improver) from common wheat, spelt and rye. Proteins that could cause allergies were functionally classified and comparatively measured by LFQ in flours and breads. Our findings showed that allergenic proteins were more prevalent in common wheat and spelt than rye and were not specifically degraded during bread manufacturing. In terms of abundance of the allergenic proteins, there was almost no difference between spelt and common wheat and the type of grain is likely more important for allergenicity than milling or traditional fermentation techniques. In a further study, we generated the flour reference proteomes for five wheat species, identifying at least 2,540 proteins in each species. More than 50% of the proteins significantly differed between species. Particularly, einkorn expressed 5.4 and 7.2 times less allergens and amylase/trypsin inhibitors than common wheat, respectively, emerging as a potential alternative cereal crop for people with sensitivities to cereal allergens. Lastly, we studied the application of large-scale proteomics for plant breeding. We found a significant impact of the environmental factors on protein expression. Only a fraction of proteins was stably expressed in all environments in at least one cultivar. Environmental influence was observed not only in the form of absolute expression or suppression of a certain protein at one or more environments but also in the form of low heritability (H2). High coefficients of variation across wheat cultivars indicate that the protein profiles of different cultivars vary considerably. Although, heritability was low for many proteins, we were able to identify hundreds of proteins with H²>0.5 – including key proteins for baking quality and human health. It should be possible to specifically manipulate the expression of functionally important proteins with high heritability by selecting and breeding for superior wheat cultivars along the wheat supply chain. Nevertheless, a successful implementation in plant breeding programs needs an improvement in the speed of protein quantification methods and in the validation of protein functions and annotations. In a nutshell, high number of proteins can be quantified in cereal grains utilizing cutting-edge proteomics techniques, opening new avenues for their use in the wheat supply chain. We generated lists of intriguing candidate proteins for further investigations on wheat sensitivity, and proteins with high heritability and important biological functions. Current research work has significant implications for the scientific and business communities across multiple disciplines including breeding, agriculture, cereal technology, nutritional science, health, and medicine. Political decision-makers and stakeholders in the food supply chain can benefit from the findings of this PhD project.