Activation of the transcription factor NF-E2-related factor-2 (Nrf2) through modification of Kelch-like ECH-associated protein 1 (Keap1) cysteines, leading to up-regulation of the antioxidant response element (ARE), is an important mechanism of cellular defense against reactive oxygen species and xenobiotic electrophiles. Sulforaphane, occurring in cruciferous vegetables such as broccoli, is a potent natural ARE activator that functions by modifying Keap1 cysteine residues, but there are conflicting in vitro and in vivo data regarding which of these cysteine residues react. Although most biological data indicate that modification of C151 is essential for sulforaphane action, some recent studies using mass spectrometry have failed to identify C151 as a site of Keap1 sulforaphane reaction. We have reconciled these conflicting data using mass spectrometry with a revised sample preparation protocol and confirmed that C151 is indeed among the most readily modified cysteines of Keap1 by sulforaphane. Previous mass spectrometry-based studies used iodoacetamide during sample preparation to derivatize free cysteine sulfhydryl groups causing loss of sulforaphane from highly reactive and reversible cysteine residues on Keap1 including C151. By omitting iodoacetamide from the protocol and reducing sample preparation time, our mass spectrometry-based studies now confirm previous cell-based studies which showed that sulforaphane reacts with at least four cysteine residues of Keap1 including C151.

Mesoscale convective systems (MCSs) are important components of tropical weather systems and the climate system. Longterm data of MCS are of great significance in weather and climate research. Using long-term (1985-2008) global satellite infrared (IR) data, we developed a novel objective automatic tracking algorithm, which combines a Kalman filter (KF) with the conventional area-overlapping method, to generate a comprehensive MCS dataset. The new algorithm can effectively track small and fast-moving MCSs and thus obtain more realistic and complete tracking results than previous studies. A few examples are provided to illustrate the potential application of the dataset with a focus on the diurnal variations of MCSs over land and ocean regions. We find that the MCSs occurring over land tend to initiate in the afternoon with greater intensity, but the oceanic MCSs are more likely to initiate in the early morning with weaker intensity. A double peak in the maximum spatial coverage is noted over the western Pacific, especially over the southwestern Pacific during the austral summer. Oceanic MCSs also persist for approximately 1 h longer than their continental counterparts.

The presence of missing values (MVs) in label-free quantitative proteomics greatly reduces the completeness of data. Imputation has been widely utilized to handle MVs, and selection of the proper method is critical for the accuracy and reliability of imputation. Here we present a comparative study that evaluates the performance of seven popular imputation methods with a large-scale benchmark dataset and an immune cell dataset. Simulated MVs were incorporated into the complete part of each dataset with different combinations of MV rates and missing not at random (MNAR) rates. Normalized root mean square error (NRMSE) was applied to evaluate the accuracy of protein abundances and intergroup protein ratios after imputation. Detection of true positives (TPs) and false altered-protein discovery rate (FADR) between groups were also compared using the benchmark dataset. Furthermore, the accuracy of handling real MVs was assessed by comparing enriched pathways and signature genes of cell activation after imputing the immune cell dataset. We observed that the accuracy of imputation is primarily affected by the MNAR rate rather than the MV rate, and downstream analysis can be largely impacted by the selection of imputation methods. A random forest-based imputation method consistently outperformed other popular methods by achieving the lowest NRMSE, high amount of TPs with the average FADR < 5%, and the best detection of relevant pathways and signature genes, highlighting it as the most suitable method for label-free proteomics.

For quantitative proteomics, efficient, robust, and reproducible sample preparation with high throughput is critical yet challenging, especially when large cohorts are involved, as is often required by clinical/pharmaceutical studies. We describe a rapid and straightforward surfactant cocktail-aided extraction/precipitation/on-pellet digestion (SEPOD) strategy to address this need. Prior to organic solvent precipitation and on-pellet digestion, SEPOD treats samples with a surfactant cocktail (SC) containing multiple nonionic/anionic surfactants, which achieves (i) exhaustive/reproducible protein extraction, including membrane-bound proteins; (ii) effective removal of detrimental nonprotein matrix components (e.g., >94% of phospholipids); (iii) rapid/efficient proteolytic digestion owing to dual (surfactants + precipitation) denaturation. The optimal SC composition and concentrations were determined by Orthogonal-Array-Design investigation of their collective/individuals effects on protein extraction/denaturation. Key parameters for cleanup and digestion were experimentally identified as well. The optimized SEPOD procedures allowed a rapid 6 h digestion providing a clean digest with high peptide yields and excellent quantitative reproducibility (especially low-abundance proteins). Compared with filter-assisted sample preparation (FASP) and in-solution digestion, SEPOD showed superior performance by recovering substantially more peptide/proteins (including integral membrane proteins), yielding significantly higher peptide intensities and improving quantification for peptides with extreme physicochemical properties. SEPOD was further applied in a large-cohort temporal investigation of 44 IAV-infected mouse lungs, providing efficient and reproducible peptide yields (77.9 ± 4.6%) across all samples. With the IonStar pipeline, >6 400 unique protein groups were quantified (≥2 peptide/protein, peptide-FDR < 0.05%), ∼99% without missing data in any sample with <7% technical median-intragroup CV. Altered proteome patterns revealed interesting novel insights into pathophysiological changes by IAV infection. In summary, SEPOD offers a feasible solution for rapid, efficient, and reproducible preparation of biological samples, facilitating high-quality proteomic quantification of large sample cohorts.