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Ancient biomolecule analyses are proving increasingly useful in the study of evolutionary patterns, including extinct organisms. Proteomic sequencing techniques complement genomic approaches, having the potential to examine lineages further back in time than achievable using ancient DNA, given the less stringent preservation requirements. In this study, we demonstrate the ability to use collagen sequence analyses via proteomics to provide species delimitation as a foundation for informing evolutionary patterns. We uncover biogeographic information of an enigmatic and recently extinct lineage of Nesophontes across their range on the Caribbean islands. First, evolutionary relationships reconstructed from collagen sequences reaffirm the affinity of Nesophontes and Solenodon as sister taxa within Solenodonota. This relationship helps lay the foundation for testing geographical isolation hypotheses across islands within the Greater Antilles, including movement from Cuba towards Hispaniola. Second, our results are consistent with Cuba having just two species of Nesophontes (N. micrus and N. major) that exhibit intrapopulation morphological variation. Finally, analysis of the recently described species from the Cayman Islands (N. hemicingulus) indicates that it is a closer relative to the Cuban species, N. major rather than N. micrus as previously speculated. Our proteomic sequencing improves our understanding of the origin, evolution, and distribution of this extinct mammal lineage, particularly with respect to approximate timing of speciation. Such knowledge is vital for this biodiversity hotspot, where the magnitude of recent extinctions may obscure true estimates of species richness in the past.

There are thousands of known cellular phosphorylation sites, but the paucity of ways to identify kinases for particular phosphorylation events remains a major roadblock for understanding kinase signaling. To address this, we here develop a generally applicable method that exploits the large number of kinase inhibitors that have been profiled on near-kinome-wide panels of protein kinases. The inhibition profile for each kinase provides a fingerprint that allows identification of unknown kinases acting on target phosphosites in cell extracts. We validate the method on diverse known kinase-phosphosite pairs, including histone kinases, EGFR autophosphorylation, and Integrin β1 phosphorylation by Src-family kinases. We also use our approach to identify the previously unknown kinases responsible for phosphorylation of INCENP at a site within a commonly phosphorylated motif in mitosis (a non-canonical target of Cyclin B-Cdk1), and of BCL9L at S915 (PKA). We show that the method has clear advantages over in silico and genetic screening., Identifying kinases responsible for specific phosphorylation events remains challenging. Here, the authors leverage kinase inhibitor profiles for the identification of kinase-substrate site pairs in cell extracts, developing a method that can identify the enzymes responsible for unassigned phosphorylation events.

Two experiments investigated individual and paired use of programs and the effects of constructed and multiple choice responding across four categories of learning. Attitudes were very favorable toward programmed learning, declined significantly with longer exposure, and then leveled off. (Author/LBH)

Program uses peer observers in lieu of videotapes; includes teaching of both peers and actual students. (RT)

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging, in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionisation, and exploitation of the inherent ionisation and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalising peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC-MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability, but demonstrate a non-linear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion co-elution adversely affects detectability and ionisation. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472.

Chronic RV apical pacing can have adverse effects on LV function and up to 10% ofpatients develop Pacemaker-induced Cardiomyopathy. The pathophysiology of thisis incompletely understood, although previous work has shown that alteredventricular activation patterns can cause abnormal calcium handling and apoptosis.The aim of this work was to determine whether physiological-rate RV apical pacingcould cause a cellular heart failure phenotype and if this could be prevented bypacing from the RV outflow tract (RVOT).Adult sheep were paced at physiological heart rates for 3 months from the RV apexor RVOT. Another group underwent rapid ventricular pacing to cause tachycardiainducedheart failure. Cardiomyocytes from the LV free wall were studied usingpatch clamp techniques and confocal microscopy.RV apical pacing caused a cellular phenotype similar to heart failure, withattenuation of the calcium transient, reduction of ICa-L and disruption of T-tubules.These features did not occur with RVOT pacing.Changes appeared prior to clinical or echocardiographic evidence of heart failureand may therefore represent the initial stages of Pacemaker-inducedCardiomyopathy.