Calcium/calmodulin (Ca2+/CaM)-dependent protein kinase II (CaMKII) couples increases in cellular Ca2+ to fundamental responses in excitable cells. CaMKII was identified over 20 years ago by activation dependence on Ca2+/CaM, but recent evidence shows that CaMKII activity is also enhanced by pro-oxidant conditions. Here we show that oxidation of paired regulatory domain methionine residues sustains CaMKII activity in the absence of Ca2+/CaM. CaMKII is activated by angiotensin II (AngII)-induced oxidation, leading to apoptosis in cardiomyocytes both in vitro and in vivo. CaMKII oxidation is reversed by methionine sulfoxide reductase A (MsrA), and MsrA-/- mice show exaggerated CaMKII oxidation and myocardial apoptosis, impaired cardiac function, and increased mortality after myocardial infarction. Our data demonstrate a dynamic mechanism for CaMKII activation by oxidation and highlight the critical importance of oxidation-dependent CaMKII activation to AngII and ischemic myocardial apoptosis.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low µg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.Proteomic technologies based on mass spectrometry (MS) have emerged as preferred components of a strategy for discovery of diagnostic, prognostic and therapeutic protein biomarkers. Because of the stochastic sampling of proteomes in unbiased analyses and the associated high false-discovery rate, tens to hundreds of potential biomarkers are often reported in discovery studies. Those few that will ultimately show sufficient sensitivity and specificity for a given medical condition must thus be culled from lengthy lists of candidates -a particularly challenging aspect of the biomarker-development pipeline and currently its main limiting step. In this context, it is highly desirable to verify, by more targeted quantitative methods, the levels of candidate biomarkers in body fluids, cells, tissues or organs from healthy individuals and affected patients in large enough sample numbers to confirm statistically relevant differences 1, 2. Verification of novel biomarkers has relied primarily on the use of sensitive, specific, high-throughput immunoassays, whose development depends critically on the availability of suitable well-characterized antibodies. However, antibody reagents of sufficient specificity and sensitivity to assay novel protein biomarkers in plasma are generally not available. The high cost and long development time required to generate high-quality immunoassay reagents, as well as technical limitations in multiplexing immunoassays for panels of biomarkers, is strong motivation to develop more straightforward quantitative approaches exploiting the sensitivity and molecular specificity of mass spectrometry.Recently, multiple reaction monitoring (MRM) coupled with stable isotope dilution (SID)-MS for direct quantification of proteins in cell lysates as well as human plasma and serum has been shown to have considerable promise 3- RESULTS Study de...

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and