An optogenetic-phosphoproteomic study reveals dynamic Akt1 signaling profiles in endothelial cells.

The serine/threonine kinase AKT is a central node in cell signaling. While aberrant AKT activation underlies the development of a variety of human diseases, how different patterns of AKT-dependent phosphorylation dictate downstream signaling and phenotypic outcomes remains largely enigmatic. Herein, we perform a systems-level analysis that integrates methodological advances in optogenetics, mass spectrometry-based phosphoproteomics, and bioinformatics to elucidate how different intensity, duration, and pattern of Akt1 stimulation lead to distinct temporal phosphorylation profiles in vascular endothelial cells. Through the analysis of ~35,000 phosphorylation sites across multiple conditions precisely controlled by light stimulation, we identify a series of signaling circuits activated downstream of Akt1 and interrogate how Akt1 signaling integrates with growth factor signaling in endothelial cells. Furthermore, our results categorize kinase substrates that are preferably activated by oscillating, transient, and sustained Akt1 signals. We validate a list of phosphorylation sites that covaried with Akt1 phosphorylation across experimental conditions as potential Akt1 substrates. Our resulting dataset provides a rich resource for future studies on AKT signaling and dynamics.

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum.

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Cancer cell seeding density as a mechanism of chemotherapy resistance: a novel cancer cell density index based on IC50-Seeding Density Slope (ISDS) to assess chemosensitivity.

Although the 50% inhibitory concentration (IC50) is a commonly used measurement of chemosensitivity in cancer cells, it has been known to vary with the density of the treated cells (in that more densely seeded cells are more resistant to chemotherapeutic agents). Indeed, density-dependent chemoresistance may be a significant independent mechanism of therapy resistance. We examine the nature of cell density-dependent chemoresistance and explore possible underlying mechanisms. CellTiter-Glo assays and ethidium homodimer staining revealed that response to chemotherapy is density-dependent in all cancer cell lines tested. Our results prompted us to develop a novel cancer cell seeding density index of chemosensitivity, the ISDS (IC50-Seeding Density Slope), which we propose can serve as an improved method of analyzing how cancer cells respond to chemotherapeutic treatment compared to the widely-used IC50. Furthermore, western blot analysis suggests that levels of autophagy and apoptotic markers are modulated by cancer cell density. Cell viability experiments using the autophagy inhibitor chloroquine showed that chloroquine's efficacy was reduced at higher cell densities and that chloroquine and cisplatin exhibited synergy at both higher and lower cell densities in TOV-21G cells. We discuss alternative mechanisms of density-dependent chemoresistance and in vivo/clinical applications, including challenges of adjuvant chemotherapy and minimal residual disease. Taken together, our findings show that cell density is a significant contributor in shaping cancer chemosensitivity, that the ISDS (aka the Ujwal Punyamurtula/Wafik El-Deiry or Ujwal-WAF Index) can be used to effectively assess cell viability and that this phenomenon of density-dependent chemoresistance may be leveraged for a variety of biologic and cancer therapeutic applications.

Mass spectrometry-based proteomic platforms for better understanding of SARS-CoV-2 induced pathogenesis and potential diagnostic approaches.

While protein-protein interaction is the first step of the SARS-CoV-2 infection, recent comparative proteomic profiling enabled the identification of over 11,000 protein dynamics, thus providing a comprehensive reflection of the molecular mechanisms underlying the cellular system in response to viral infection. Here we summarize and rationalize the results obtained by various mass spectrometry (MS)-based proteomic approaches applied to the functional characterization of proteins and pathways associated with SARS-CoV-2-mediated infections in humans. Comparative analysis of cell-lines versus tissue samples indicates that our knowledge in proteome profile alternation in response to SARS-CoV-2 infection is still incomplete and the tissue-specific response to SARS-CoV-2 infection can probably not be recapitulated efficiently by in vitro experiments. However, regardless of the viral infection period, sample types, and experimental strategies, a thorough cross-comparison of the recently published proteome, phosphoproteome, and interactome datasets led to the identification of a common set of proteins and kinases associated with PI3K-Akt, EGFR, MAPK, Rap1, and AMPK signaling pathways. Ephrin receptor A2 (EPHA2) was identified by 11 studies including all proteomic platforms, suggesting it as a potential future target for SARS-CoV-2 infection mechanisms and the development of new therapeutic strategies. We further discuss the potentials of future proteomics strategies for identifying prognostic SARS-CoV-2 responsive age-, gender-dependent, tissue-specific protein targets.