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Characterization of 150 Wheat Cultivars by LC-MS-Based Label-Free Quantitative Proteomics Unravels Possibilities to Design Wheat Better for Baking Quality and Human Health.

ABSTRACT: Wheat (Triticum aestivum ssp. aestivum) contributes to 20% of the human protein supply, delivers essential amino acids and is of fundamental importance for bread and pasta quality. Wheat proteins are also involved in adverse human reactions like celiac disease (CD), wheat allergy (WA) and non-celiac wheat sensitivity (NCWS). Using liquid chromatography-mass spectrometry (LC-MS)-based label-free quantitative (LFQ) proteomics of aqueous flour extracts, we determined 756 proteins across 150 wheat cultivars grown in three environments. However, only 303 proteins were stably expressed across all environments in at least one cultivar and only 89 proteins thereof across all 150 cultivars. This underlines the large influence of environmental conditions on the expression of many proteins. Wheat cultivars varied largely in their protein profile, shown by high coefficients of variation across different cultivars. Heritability (h²) ranged from 0-1, with 114 proteins having h² > 0.6, including important proteins for baking quality and human health. The expression of these 114 proteins should be amenable to targeted manipulation across the wheat supply chain by varietal choice and breeding for designing healthier wheat with better quality. Further technical development is urgently required to assign functions to identifiable proteins labeled yet uncharacterized in databases and speeding up detection methods to routinely use proteomics in wheat supply chains.

SUBMITTER: Afzal M

PROVIDER: S-EPMC7996164 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Highly specialized cells are fundamental for proper functioning of complex organs. Variations in cell-type specific gene expression and protein composition have been linked to a variety of diseases. Although single cell technologies have emerged as valuable tools to address this cellular heterogeneity, a majority of these workflows lack sufficient in situ resolution for functional classification of cells and are associated with extremely long analysis time, especially when it comes to in situ proteomics. In addition, lack of understanding of single cell dynamics within their native environment limits our ability to explore the altered physiology in disease development. This limitation is particularly relevant in the mammalian brain, where different cell types perform unique functions and exhibit varying sensitivities to insults. The hippocampus, a brain region crucial for learning and memory, is of particular interest due to its obvious involvement in various neurological disorders. Here, we present a combination of experimental and data integration approaches for investigation of cellular heterogeneity and functional disposition within the mouse brain hippocampus using MALDI Imaging mass spectrometry (MALDI-IMS) and shotgun proteomics (LC-MS/MS) coupled with laser-capture microdissection (LCM) along with spatial transcriptomics. Within the dentate gyrus granule cells we identified two proteomically distinct cellular subpopulations that are characterized by a substantial number of discriminative proteins. These cellular clusters contribute to the overall functionality of the dentate gyrus by regulating redox homeostasis, mitochondrial organization, RNA processing, and microtubule organization. Importantly, most of the identified proteins matched their transcripts, verifying the in situ protein identification and supporting their functional analyses. By combining high-throughput spatial proteomics with transcriptomics, our approach enables reliable near-single-cell scale identification of proteins and profiling of inter-cellular heterogeneity within similar cell-types in tissues. This methodology has the potential to be applied to different biological conditions and tissues, providing a deeper understanding of cellular subpopulations in situ.

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Characterization of 150 Wheat Cultivars by LC-MS-Based Label-Free Quantitative Proteomics Unravels Possibilities to Design Wheat Better for Baking Quality and Human Health.

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