Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins

New Function Annotation of PROSER2 in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to the absence of diagnostic markers and molecular targets. Here, we took an unconventional approach to identify new molecular targets for pancreatic cancer. We chose uncharacterized protein evidence level 1 without function annotation from extensive proteomic research on pancreatic cancer and focused on proline and serine-rich 2 (PROSER2), which ranked high in the cell membrane and cytoplasm. In our study using cell lines and patient-derived orthotopic xenograft cells, PROSER2 exhibited a higher expression in cells derived from primary tumors than in those from metastatic tissues. PROSER2 was localized in the cell membrane and cytosol by immunocytochemistry. PROSER2 overexpression significantly reduced the metastatic ability of cancer cells, whereas its suppression had the opposite effect. Proteomic analysis revealed that PROSER2 interacts with STK25 and PDCD10, and their binding was confirmed by immunoprecipitation and immunocytochemistry. STK25 knockdown enhanced metastasis by decreasing p-AMPK levels, whereas PROSER2-overexpressing cells increased the level of p-AMPK, indicating that PROSER2 suppresses invasion via the AMPK pathway by interacting with STK25. This is the first demonstration of the novel role of PROSER2 in antagonizing tumor progression via the STK25-AMPK pathway in PDAC. LC-MS/MS data are available at MassIVE (MSV000092953) and ProteomeXchange (PXD045646).

Identifying drug targets with thermal proteome profiling using IBT-16plex

RATIONALE

Thermal proteome profiling (TPP) has been widely used for the identification of drug targets for several years, and TMTpro-16plex has recently been evaluated for TPP of vehicle- and drug-treated samples in a single labeling process to reduce missing values and save instrument time. A novel isobaric labeling reagent, IBT-16plex, was developed with slightly better performance in protein identification and quantification than the commercially available TMTpro-16plex.

METHODS

In this study, we applied the newly developed IBT-16plex for target identification of methotrexate and panobinostat using TPP.

RESULTS

The known targets of these two drugs were successfully identified with elevated melting temperatures, and some known off-targets and potential new off-targets were also identified.

CONCLUSIONS

IBT-16plex can be a cost-effective replacement for TMTpro-16plex for TPP applications.

Ultra-High-Resolution IonStar Strategy Enhancing Accuracy and Precision of MS1-Based Proteomics and an Extensive Comparison with State-of-the-Art SWATH-MS in Large-Cohort Quantification

Quantitative proteomics in large cohorts is highly valuable for clinical/pharmaceutical investigations but often suffers from severely compromised reliability, accuracy, and reproducibility. Here, we describe an ultra-high-resolution IonStar method achieving reproducible protein measurement in large cohorts while minimizing the ratio compression problem, by taking advantage of the exceptional selectivity of ultra-high-resolution (UHR)-MS1 detection (240k_FWHM@m/z = 200). Using mixed-proteome benchmark sets reflecting large-cohort analysis with technical or biological replicates (N = 56), we comprehensively compared the quantitative performances of UHR-IonStar vs a state-of-the-art SWATH-MS method, each with their own optimal analytical platforms. We confirmed a cutting-edge micro-liquid chromatography (LC)/Triple-TOF with Spectronaut outperforms nano-LC/Orbitrap for SWATH-MS, which was then meticulously developed/optimized to maximize sensitivity, reproducibility, and proteome coverage. While the two methods with distinct principles (i.e., MS1- vs MS2-based) showed similar depth-of-analysis (∼6700-7000 missing-data-free proteins quantified, 1% protein-false discovery rate (FDR) for entire set, 2 unique peptides/protein) and good accuracy/precision in quantifying high-abundance proteins, UHR-IonStar achieved substantially superior quantitative accuracy, precision, and reproducibility for lower-abundance proteins (a category that includes most regulatory proteins), as well as much-improved sensitivity/selectivity for discovering significantly altered proteins. Furthermore, compared to SWATH-MS, UHR-IonStar showed markedly higher accuracy for a single analysis of each sample across a large set, which is an inadequately investigated albeit critical parameter for large-cohort analysis. Finally, we compared UHR-IonStar vs SWATH-MS in measuring the time courses of altered proteins in paclitaxel-treated cells (N = 36), where dysregulated biological pathways have been very well established. UHR-IonStar discovered substantially more well-recognized biological processes/pathways induced by paclitaxel. Additionally, UHR-IonStar showed markedly superior ability than SWATH-MS in accurately depicting the time courses of well known to be paclitaxel-induced biomarkers. In summary, UHR-IonStar represents a reliable, robust, and cost-effective solution for large-cohort proteomic quantification with excellent accuracy and precision.

A translational program that suppresses metabolism to shield the genome

Translatome reprogramming is a primary determinant of protein levels during stimuli adaptation. This raises the question: what are the translatome remodelers that reprogram protein output to activate biochemical adaptations. Here, we identify a translational pathway that represses metabolism to safeguard genome integrity. A system-wide MATRIX survey identified the ancient eIF5A as a pH-regulated translation factor that responds to fermentation-induced acidosis. TMT-pulse-SILAC analysis identified several pH-dependent proteins, including the mTORC1 suppressor Tsc2 and the longevity regulator Sirt1. Sirt1 operates as a pH-sensor that deacetylates nuclear eIF5A during anaerobiosis, enabling the cytoplasmic export of eIF5A/Tsc2 mRNA complexes for translational engagement. Tsc2 induction inhibits mTORC1 to suppress cellular metabolism and prevent acidosis-induced DNA damage. Depletion of eIF5A or Tsc2 leads to metabolic re-initiation and proliferation, but at the expense of incurring substantial DNA damage. We suggest that eIF5A operates as a translatome remodeler that suppresses metabolism to shield the genome.

Regulation of Cell Uptake and Cytotoxicity by Nanoparticle Core under the Controlled Shape, Size, and Surface Chemistries

Nanoparticle structural parameters, such as size, surface chemistry, and shape, are well-recognized parameters that affect biological activities of nanoparticles. However, whether the core material of a nanoparticle also plays a role remains unknown. To answer this long-standing question, we synthesized and investigated a comprehensive library of 36 nanoparticles with all combinations of three types of core materials (Au, Pt, and Pd), two sizes (6 and 26 nm), and each conjugated with one of six surface ligands of different hydrophobicity. Using this systematic approach, we were able to identify cellular perturbation specifically attributed to core, size, or surface ligand. We discovered that core materials exhibited a comparable regulatory ability as surface ligand on cellular ROS generation and cytotoxicity. Pt nanoparticles were much more hydrophilic and showed much less cell uptake compared to Au and Pd nanoparticles with identical size, shape, and surface ligands. Furthermore, diverse core materials also regulated levels of cellular redox activities, resulting in different cytotoxicity. Specifically, Pd nanoparticles significantly reduced cellular H₂O₂ and promoted cell survival, while Au nanoparticles with identical size, shape, and surface ligand induced higher cellular oxidative stress and cytotoxicity. Our results demonstrate that nanoparticle core material is as important as other structural parameters in nanoparticle-cell interactions, making it also a necessary consideration when designing nanomedicines.