Peptide Labeling with Isobaric Tags Yields Higher Identification Rates Using iTRAQ 4-Plex Compared to TMT 6-Plex and iTRAQ 8-Plex on LTQ Orbitrap

Peptide labeling with isobaric tags has become a popular technique in quantitative shotgun proteomics. Using two different samples viz. a protein mixture and HeLa extracts, we show that three commercially available isobaric tags differ with regard to peptide identification rates: The number of identified proteins and peptides was largest with iTRAQ 4-plex, followed by TMT 6-plex, and smallest with iTRAQ 8-plex. In all experiments, we employed a previously described method where two scans were acquired for each precursor on an LTQ Orbitrap: A CID scan under standard settings for identification, and a HCD scan for quantification. The observed differences in identification rates were similar when data was searched with either Mascot or Sequest. We consider these findings to be the result of a combination of several factors, most notably prominent ions in CID spectra as a consequence of loss of fragments of the label tag from precursor ions. These fragment ions cannot be explained by current search engines and were observed to have a negative impact on peptide scores

A Mouse to Human Search for Plasma Proteome Changes Associated with Pancreatic Tumor Development

Background: The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. Methods and Findings: Plasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer. Conclusions: Our findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection

Unlimited multistability in multisite phosphorylation systems

Reversible phosphorylation on serine, threonine and tyrosine is the most widely studied posttranslational modification of proteins (1, 2). The number of phosphorylated sites on a protein (n) shows a significant increase from prokaryotes, with n less than or equal to 7 sites, to eukaryotes, with examples having n greater than or equal to 150 sites (3). Multisite phosphorylation has many roles (4, 5) and site conservation indicates that increasing numbers of sites cannot be due merely to promiscuous phosphorylation. A substrate with n sites has an exponential number (2^n) of phospho-forms and individual phospho-forms may have distinct biological effects (6, 7). The distribution of these phospho-forms and how this distribution is regulated have remained unknown. Here we show that, when kinase and phosphatase act in opposition on a multisite substrate, the system can exhibit distinct stable phospho-form distributions at steady state and that the maximum number of such distributions increases with n. Whereas some stable distributions are focused on a single phospho-form, others are more diffuse, giving the phospho-proteome the potential to behave as a fluid regulatory network able to encode information and flexibly respond to varying demands. Such plasticity may underlie complex information processing in eukaryotic cells (8) and suggests a functional advantage in having many sites. Our results follow from the unusual geometry of the steady-state phospho-form concentrations, which we show to constitute a rational algebraic curve, irrespective of n. We thereby reduce the complexity of calculating steady states from simulating 3 times 2^n differential equations to solving two algebraic equations, while treating parameters symbolically. We anticipate that these methods can be extended to systems with multiple substrates and multiple enzymes catalysing different modifications, as found in posttranslational modification 'codes' (9) such as the histone code (10, 11). Whereas simulations struggle with exponentially increasing molecular complexity, mathematical methods of the kind developed here can provide a new language in which to articulate the principles of cellular information processing (12)

Identification of Combinatorial Patterns of Post-Translational Modifications on Individual Histones in the Mouse Brain

Post-translational modifications (PTMs) of proteins are biochemical processes required for cellular functions and signalling that occur in every sub-cellular compartment. Multiple protein PTMs exist, and are established by specific enzymes that can act in basal conditions and upon cellular activity. In the nucleus, histone proteins are subjected to numerous PTMs that together form a histone code that contributes to regulate transcriptional activity and gene expression. Despite their importance however, histone PTMs have remained poorly characterised in most tissues, in particular the brain where they are thought to be required for complex functions such as learning and memory formation. Here, we report the comprehensive identification of histone PTMs, of their combinatorial patterns, and of the rules that govern these patterns in the adult mouse brain. Based on liquid chromatography, electron transfer, and collision-induced dissociation mass spectrometry, we generated a dataset containing a total of 10,646 peptides from H1, H2A, H2B, H3, H4, and variants in the adult brain. 1475 of these peptides carried one or more PTMs, including 141 unique sites and a total of 58 novel sites not described before. We observed that these PTMs are not only classical modifications such as serine/threonine (Ser/Thr) phosphorylation, lysine (Lys) acetylation, and Lys/arginine (Arg) methylation, but also include several atypical modifications such as Ser/Thr acetylation, and Lys butyrylation, crotonylation, and propionylation. Using synthetic peptides, we validated the presence of these atypical novel PTMs in the mouse brain. The application of data-mining algorithms further revealed that histone PTMs occur in specific combinations with different ratios. Overall, the present data newly identify a specific histone code in the mouse brain and reveal its level of complexity, suggesting its potential relevance for higher-order brain functions

Digital Gene Expression Profiling by 5′-End Sequencing of cDNAs during Reprogramming in the Moss Physcomitrella patens

Stem cells self-renew and repeatedly produce differentiated cells during development and growth. The differentiated cells can be converted into stem cells in some metazoans and land plants with appropriate treatments. After leaves of the moss Physcomitrella patens are excised, leaf cells reenter the cell cycle and commence tip growth, which is characteristic of stem cells called chloronema apical cells. To understand the underlying molecular mechanisms, a digital gene expression profiling method using mRNA 5′-end tags (5′-DGE) was established. The 5′-DGE method produced reproducible data with a dynamic range of four orders that correlated well with qRT-PCR measurements. After the excision of leaves, the expression levels of 11% of the transcripts changed significantly within 6 h. Genes involved in stress responses and proteolysis were induced and those involved in metabolism, including photosynthesis, were reduced. The later processes of reprogramming involved photosynthesis recovery and higher macromolecule biosynthesis, including of RNA and proteins. Auxin and cytokinin signaling pathways, which are activated during stem cell formation via callus in flowering plants, are also activated during reprogramming in P. patens, although no exogenous phytohormone is applied in the moss system, suggesting that an intrinsic phytohormone regulatory system may be used in the moss

Dynamic protein methylation in chromatin biology

Post-translational modification of chromatin is emerging as an increasingly important regulator of chromosomal processes. In particular, histone lysine and arginine methylation play important roles in regulating transcription, maintaining genomic integrity, and contributing to epigenetic memory. Recently, the use of new approaches to analyse histone methylation, the generation of genetic model systems, and the ability to interrogate genome wide histone modification profiles has aided in defining how histone methylation contributes to these processes. Here we focus on the recent advances in our understanding of the histone methylation system and examine how dynamic histone methylation contributes to normal cellular function in mammals

Mechanisms and models of somatic cell reprogramming

Whitehead Institute for Biomedical Research (Jerome and Florence Brill Graduate Student Fellowship)National Institutes of Health (U.S.) (US NIH grant RO1-CA087869)National Institutes of Health (U.S.) (US NIH grant R37-CA084198)National Science Foundation (U.S.) (NSF Graduate Research Fellowship)National Institutes of Health (U.S.) ((NIH) Kirschstein National Research Service Award,1 F32 GM099153-01A1)Vertex Pharmaceuticals Incorporated (Vertex Scholar