Cynthia Denbow

BACKGROUND: Accurate quantification of soybean storage protein subunits glycinin (11S) and β‐conglycinin (7S), and their ratio (11S/7S), is essential for applications in plant breeding, food processing, and allergen research. Although sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS‐PAGE) is widely used due to its accessibility and cost‐effectiveness, its quantitative reliability is often limited by variability in protein extraction and band resolution. This study presents an improved SDS‐PAGE protocol optimized for quantifying the 11S/7S ratio with improved accuracy, reproducibility, and cost‐effectiveness. RESULTS: Two established extraction protocols were evaluated across three soybean cultivars, and a new protocol was developed by integrating their strengths. The new protocol employs a Tris–HCl‐based buffer containing sucrose, ethylenediaminetetraacetic acid, β‐mercaptoethanol, and phenylmethylsulfonyl fluoride, which improves protein solubility and minimizes degradation. Compared to two prior protocols, the new method achieved clearer band resolution, lower error variance, and higher F ‐values in analysis of variance. Standard curves derived from bovine serum albumin confirmed strong linearity between band intensity and protein quantity ( r ² = 0.993, 0.985), supporting reliable quantitative analysis. Reproducibility tests demonstrated consistent 11S/7S estimation across independent runs. In an application evaluation across 14 breeding lines, the protocol effectively discriminated genotypic variation, with 11S/7S ratio ranging from 1.29 to 2.20 and separation into seven statistically distinct groups, which further validated the protocol's stability and discriminatory power. CONCLUSION: This optimized SDS‐PAGE method provides a reliable, scalable tool for phenotyping 11S/7S ratios in diverse soybean germplasm, offering a practical balance between resolution, affordability, and throughput for both research and applied use. © 2026 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Plant immunity relies on the perception of microbe-associated molecular patterns (MAMPs) from invading microbes to induce defense responses that suppress attempted infections. It has been proposed that MAMP-triggered immunity (MTI) suppresses bacterial infections by suppressing the onset of bacterial virulence. However, the mechanisms by which plants exert this action are poorly understood. Here, we showed that MAMP perception in Arabidopsis (Arabidopsis thaliana) induces the accumulation of free amino acids in a salicylic acid (SA)-dependent manner. When co-infiltrated with Glutamine and Serine, two of the MAMP-induced highly accumulating amino acids, Pseudomonas syringae pv. tomato DC3000 expressed low levels of virulence genes and failed to produce robust infections in otherwise susceptible plants. When applied exogenously, Glutamine and Serine directly suppressed bacterial virulence and growth, bypassing MAMP perception and SA signaling. In addition, an increased level of endogenous Glutamine in the leaf apoplast of a gain-of-function mutant of Glutamine Dumper-1 rescued the partially compromised bacterial virulence- and growth-suppressing phenotype of the SA-induced deficient-2 (sid2) mutant. Our data suggest that MTI suppresses bacterial infections by delaying the onset of virulence with an excess of amino acids at the early stages of infection.

Background Synechocystis sp. PCC6803 is a model cyanobacterium that has been studied widely and is considered for metabolic engineering applications. Here, Raman spectroscopy and Raman chemometrics (Rametrix™) were used to (i) study broad phenotypic changes in response to growth conditions, (ii) identify phenotypic changes associated with its circadian rhythm, and (iii) correlate individual Raman bands with biomolecules and verify these with more accepted analytical methods. Methods Synechocystis cultures were grown under various conditions, exploring dependencies on light and/or external carbon and nitrogen sources. The Rametrix™ LITE Toolbox for MATLAB® was used to process Raman spectra and perform principal component analysis (PCA) and discriminant analysis of principal components (DAPC). The Rametrix™ PRO Toolbox was used to validate these models through leave-one-out routines that classified a Raman spectrum when growth conditions were withheld from the model. Performance was measured by classification accuracy, sensitivity, and specificity. Raman spectra were also subjected to statistical tests (ANOVA and pairwise comparisons) to identify statistically relevant changes in Synechocystis phenotypes. Finally, experimental methods, including widely used analytical and spectroscopic assays were used to quantify the levels of glycogen, fatty acids, amino acids, and chlorophyll a for correlations with Raman data. Results PCA and DAPC models produced distinct clustering of Raman spectra, representing multiple Synechocystis phenotypes, based on (i) growth in the presence of 5 mM glucose, (ii) illumination (dark, light/dark [12 h/12 h], and continuous light at 20 µE), (iii) nitrogen deprivation (0–100% NaNO₃ of native BG-11 medium in continuous light), and (iv) throughout a 24 h light/dark (12 h/12 h) circadian rhythm growth cycle. Rametrix™ PRO was successful in identifying glucose-induced phenotypes with 95.3% accuracy, 93.4% sensitivity, and 96.9% specificity. Prediction accuracy was above random chance values for all other studies. Circadian rhythm analysis showed a return to the initial phenotype after 24 hours for cultures grown in light/dark (12 h/12 h) cycles; this did not occur for cultures grown in the dark. Finally, correlation coefficients (R > 0.7) were found for glycogen, all amino acids, and chlorophyll a when comparing specific Raman bands to other experimental results.