Omics assisted N-terminal proteoform and protein expression profiling on methionine aminopeptidase 1 (MetAP1) deletion

Excision of the N-terminal initiator methionine (iMet) residue from nascent peptide chains is an essential and omnipresent protein modification carried out by methionine aminopeptidases (MetAPs) that accounts for a major source of N-terminal proteoform diversity. Although MetAP2 is known to be implicated in processes such as angiogenesis and proliferation in mammals, the physiological role of MetAP1 is much less clear. In this report we studied the omics-wide effects of human MetAP1 deletion and general MetAP inhibition. The levels of iMet retention are inversely correlated with cellular proliferation rates. Further, despite the increased MetAP2 expression on MetAP1 deletion, MetAP2 was unable to restore processing of Met-Ser-, Met-Pro-, and Met-Ala- starting N termini as inferred from the iMet retention profiles observed, indicating a higher activity of MetAP1 over these N termini. Proteome and transcriptome expression profiling point to differential expression of proteins implicated in lipid metabolism, cytoskeleton organization, cell proliferation and protein synthesis upon perturbation of MetAP activity

LC-MS proteomics analysis of the iInsulin/IGF-1-deficient Caenorhabditis elegans daf-2(e1370) mutant reveals extensive restructuring of intermediary metabolism

The insulin/IGF-1 receptor is a major known determinant of dauer formation, stress resistance, longevity, and metabolism in Caenorhabditis elegans. In the past, whole-genome transcript profiling was used extensively to study differential gene expression in response to reduced insulin/IGF-1 signaling, including the expression levels of metabolism-associated genes. Taking advantage of the recent developments in quantitative liquid chromatography mass spectrometry (LC-MS)-based proteomics, we profiled the proteomic changes that occur in response to activation of the DAF-16 transcription factor in the germline-less glp-4(bn2);daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile suggests extensive reorganization of intermediary metabolism, characterized by the upregulation of many core intermediary metabolic pathways. These include glycolysis/gluconeogenesis, glycogenesis, pentose phosphate cycle, citric acid cycle, glyoxylate shunt, fatty acid beta-oxidation, one-carbon metabolism, propionate and tyrosine catabolism, and complexes I, II, III, and V of the electron transport chain. Interestingly, we found simultaneous activation of reciprocally regulated metabolic pathways, which is indicative of spatiotemporal coordination of energy metabolism and/or extensive post-translational regulation of these enzymes. This restructuring of daf-2 metabolism is reminiscent to that of hypometabolic dauers, allowing the efficient and economical utilization of internal nutrient reserves and possibly also shunting metabolites through alternative energy-generating pathways to sustain longevity

DART-ID increases single-cell proteome coverage.

Analysis by liquid chromatography and tandem mass spectrometry (LC-MS/MS) can identify and quantify thousands of proteins in microgram-level samples, such as those comprised of thousands of cells. This process, however, remains challenging for smaller samples, such as the proteomes of single mammalian cells, because reduced protein levels reduce the number of confidently sequenced peptides. To alleviate this reduction, we developed Data-driven Alignment of Retention Times for IDentification (DART-ID). DART-ID implements principled Bayesian frameworks for global retention time (RT) alignment and for incorporating RT estimates towards improved confidence estimates of peptide-spectrum-matches. When applied to bulk or to single-cell samples, DART-ID increased the number of data points by 30-50% at 1% FDR, and thus decreased missing data. Benchmarks indicate excellent quantification of peptides upgraded by DART-ID and support their utility for quantitative analysis, such as identifying cell types and cell-type specific proteins. The additional datapoints provided by DART-ID boost the statistical power and double the number of proteins identified as differentially abundant in monocytes and T-cells. DART-ID can be applied to diverse experimental designs and is freely available at http://dart-id.slavovlab.net

Unexpected transformation of dissolved phenols to toxic dicarbonyls by hydroxyl radicals and UV light.

Water treatment systems frequently use strong oxidants or UV light to degrade chemicals that pose human health risks. Unfortunately, these treatments can result in the unintended transformation of organic contaminants into toxic products. We report an unexpected reaction through which exposure of phenolic compounds to hydroxyl radicals (•OH) or UV light results in the formation of toxic α,β-unsaturated enedials and oxoenals. We show that these transformation products damage proteins by reacting with lysine and cysteine moieties. We demonstrate that phenolic compounds react with •OH produced by the increasingly popular UV/hydrogen peroxide (H2O2) water treatment process or UV light to form toxic enedials and oxoenals. In addition to raising concerns about potential health risks of oxidative water treatment, our findings suggest the potential for formation of these toxic compounds in sunlit surface waters, atmospheric water, and living cells. For the latter, our findings may be particularly relevant to efforts to understand cellular damage caused by in vivo production of reactive oxygen species. In particular, we demonstrate that exposure of the amino acid tyrosine to •OH yields an electrophilic enedial product that undergoes cross-linking reaction with both lysine and cysteine residues

Addressing the needs of traumatic brain injury with clinical proteomics.

BackgroundNeurotrauma or injuries to the central nervous system (CNS) are a serious public health problem worldwide. Approximately 75% of all traumatic brain injuries (TBIs) are concussions or other mild TBI (mTBI) forms. Evaluation of concussion injury today is limited to an assessment of behavioral symptoms, often with delay and subject to motivation. Hence, there is an urgent need for an accurate chemical measure in biofluids to serve as a diagnostic tool for invisible brain wounds, to monitor severe patient trajectories, and to predict survival chances. Although a number of neurotrauma marker candidates have been reported, the broad spectrum of TBI limits the significance of small cohort studies. Specificity and sensitivity issues compound the development of a conclusive diagnostic assay, especially for concussion patients. Thus, the neurotrauma field currently has no diagnostic biofluid test in clinical use.ContentWe discuss the challenges of discovering new and validating identified neurotrauma marker candidates using proteomics-based strategies, including targeting, selection strategies and the application of mass spectrometry (MS) technologies and their potential impact to the neurotrauma field.SummaryMany studies use TBI marker candidates based on literature reports, yet progress in genomics and proteomics have started to provide neurotrauma protein profiles. Choosing meaningful marker candidates from such 'long lists' is still pending, as only few can be taken through the process of preclinical verification and large scale translational validation. Quantitative mass spectrometry targeting specific molecules rather than random sampling of the whole proteome, e.g., multiple reaction monitoring (MRM), offers an efficient and effective means to multiplex the measurement of several candidates in patient samples, thereby omitting the need for antibodies prior to clinical assay design. Sample preparation challenges specific to TBI are addressed. A tailored selection strategy combined with a multiplex screening approach is helping to arrive at diagnostically suitable candidates for clinical assay development. A surrogate marker test will be instrumental for critical decisions of TBI patient care and protection of concussion victims from repeated exposures that could result in lasting neurological deficits

Networks of motifs from sequences of symbols

We introduce a method to convert an ensemble of sequences of symbols into a weighted directed network whose nodes are motifs, while the directed links and their weights are defined from statistically significant co-occurences of two motifs in the same sequence. The analysis of communities of networks of motifs is shown to be able to correlate sequences with functions in the human proteome database, to detect hot topics from online social dialogs, to characterize trajectories of dynamical systems, and might find other useful applications to process large amount of data in various fields.Comment: Accepted for publication in Phys. Rev. Lett. Main article 4 pages, 2 figure; supplementary material 4 pages, 1 figur