A Differential Phosphoproteomic Analysis of Retinoic Acid-Treated P19 Cells

Mass Spectrometry-Based Analysis of Time-Resolved Proteome Quantification

The aspect of time is essential in biological processes and thus it is important to be able to monitor signaling molecules through time. Proteins are key players in cellular signaling and they respond to many stimuli and change their expression in many time-dependent processes. Mass spectrometry (MS) is an important tool for studying proteins, including their posttranslational modifications and their interaction partners-both in qualitative and quantitative ways. In order to distinguish the different trends over time, proteins, modification sites, and interacting proteins must be compared between different time points, and therefore relative quantification is preferred. In this review, the progress and challenges for MS-based analysis of time-resolved proteome dynamics are discussed. Further, aspects on model systems, technologies, sampling frequencies, and presentation of the dynamic data are discussed.

ZRF1: a novel epigenetic regulator of stem cell identity and cancer

The Zuotin-related factor 1, ZRF1, has recently been identified as an epigenetic regulator of gene transcription in stem cells and cancer. During differentiation of human teratocarcinoma cells, ZRF1 promotes transcriptional induction of developmental genes that are repressed by Polycomb complexes. Importantly, ZRF1 has recently been shown to be required for both neural differentiation of embryonic stem cells (ESCs) and for maintenance of neural progenitor cell (NPC) identity. Moreover, a dual role has now emerged for ZRF1 in cancer: on the one hand, ZRF1 plays a crucial role in oncogene-induced senescence (OIS) by activating the INK4/ARF locus, thus working as a tumor suppressor; on the other hand, ZRF1 promotes leukemogenesis in acute myeloid leukemia (AML) in a Polycomb-independent fashion. Therefore, increasing evidence points to ZRF1 as a novel target for therapy of neurodegenerative diseases and cancer.

ZRF1 controls the retinoic acid pathway and regulates leukemogenic potential in acute myeloid leukemia

Acute myeloid leukemia (AML) is frequently linked to epigenetic abnormalities and deregulation of gene transcription, which lead to aberrant cell proliferation and accumulation of undifferentiated precursors. ZRF1, a recently characterized epigenetic factor involved in transcriptional regulation, is highly overexpressed in human AML, but it is not known whether it plays a role in leukemia progression. Here, we demonstrate that ZRF1 depletion decreases cell proliferation, induces apoptosis and enhances cell differentiation in human AML cells. Treatment with retinoic acid (RA), a differentiating agent currently used to treat certain AMLs, leads to a functional switch of ZRF1 from a negative regulator to an activator of differentiation. At the molecular level, ZRF1 controls the RA-regulated gene network through its interaction with the RA receptor α (RARα) and its binding to RA target genes. Our genome-wide expression study reveals that ZRF1 regulates the transcription of nearly half of RA target genes. Consistent with our in vitro observations that ZRF1 regulates proliferation, apoptosis, and differentiation, ZRF1 depletion strongly inhibits leukemia progression in a xenograft mouse model. Finally, ZRF1 knockdown cooperates with RA treatment in leukemia suppression in vivo. Taken together, our data reveal that ZRF1 is a key transcriptional regulator in leukemia progression and suggest that ZRF1 inhibition could be a novel strategy to be explored for AML treatment.

Zrf1 is required to establish and maintain neural progenitor identity

The molecular mechanisms underlying specification from embryonic stem cells (ESCs) and maintenance of neural progenitor cells (NPCs) are largely unknown. Recently, we reported that the Zuotin-related factor 1 (Zrf1) is necessary for chromatin displacement of the Polycomb-repressive complex 1 (PRC1). We found that Zrf1 is required for NPC specification from ESCs and that it promotes the expression of NPC markers, including the key regulator Pax6. Moreover, Zrf1 is essential to establish and maintain Wnt ligand expression levels, which are necessary for NPC self-renewal. Reactivation of proper Wnt signaling in Zrf1-depleted NPCs restores Pax6 expression and the self-renewal capacity. ESC-derived NPCs in vitro resemble most of the characteristics of the self-renewing NPCs located in the developing embryonic cortex, which are termed radial glial cells (RGCs). Depletion of Zrf1 in vivo impairs the expression of key self-renewal regulators and Wnt ligand genes in RGCs. Thus, we demonstrate that Zrf1 plays an essential role in NPC generation and maintenance.

Fabrication of a novel magnetic yolk–shell Fe3O4@mTiO2@mSiO2 nanocomposite for selective enrichment of endogenous phosphopeptides from a complex sample

A novel magnetic yolk–shell Fe₃O₄@mTiO₂@mSiO₂ demonstrated the excellent enrichment efficacy and selectivity of endogenous phosphopeptides from human serum.

ZRF1 controls oncogene-induced senescence through the INK4-ARF locus

The reactivation of the INK4-ARF locus, which is epigenetically repressed by Polycomb proteins in healthy cells, is a hallmark of senescence. One mechanism of reactivating Polycomb-silenced genes is mediated by the epigenetic factor ZRF1, which associates with ubiquitinated histone H2A. We show that cells undergoing senescence following oncogenic Ras expression have increased ZRF1 levels, and that this binds to the p15INK4b, ARF and p16INK4a promoters. Furthermore, ZRF1 depletion in oncogenic Ras-expressing cells restores proliferation by preventing Arf and p16Ink4a expression, consequently bypassing senescence. Thus, ZRF1 regulates the INK4-ARF locus during cellular proliferation and senescence, and alterations in ZRF1 may contribute to tumorigenesis.

A bird's-eye view of post-translational modifications in the spliceosome and their roles in spliceosome dynamics

Pre-mRNA splicing, the removal of noncoding intron sequences from the pre-mRNA, is a critical reaction in eukaryotic gene expression. Pre-mRNA splicing is carried out by a remarkable macromolecular machine, the spliceosome, which undergoes dynamic rearrangements of its RNA and protein components to assemble its catalytic center. While significant progress has been made in describing the "moving parts" of this machine, the mechanisms by which spliceosomal proteins mediate the ordered rearrangements within the spliceosome remain elusive. Here we explore recent evidence from proteomics studies revealing extensive post-translational modification of splicing factors. While the functional significance of most of these modifications remains to be characterized, we describe recent studies in which the roles of specific post-translational modifications of splicing factors have been characterized. These examples illustrate the importance of post-translational modifications in spliceosome dynamics.

Strategies for quantitation of phosphoproteomic data

Recent developments in phosphoproteomic sample-preparation techniques and sensitive mass spectrometry instrumentation have led to large-scale identifications of phosphoproteins and phosphorylation sites from highly complex samples. This has facilitated the implementation of different quantitation strategies in order to study the biological role of protein phosphorylation during disease progression, differentiation or during external stimulation of a cellular system. In this article, a brief summary of the most popular strategies for phosphoproteomic studies is given; however, the main focus will be on different quantitation strategies. Methods for metabolic labeling, chemical modification and label-free quantitation and their applicability or inapplicability in phosphoproteomic studies are discussed.

Prophossi: automating expert validation of phosphopeptide-spectrum matches from tandem mass spectrometry

Motivation: Complex patterns of protein phosphorylation mediate many cellular processes. Tandem mass spectrometry (MS/MS) is a powerful tool for identifying these post-translational modifications. In high-throughput experiments, mass spectrometry database search engines, such as MASCOT provide a ranked list of peptide identifications based on hundreds of thousands of MS/MS spectra obtained in a mass spectrometry experiment. These search results are not in themselves sufficient for confident assignment of phosphorylation sites as identification of characteristic mass differences requires time-consuming manual assessment of the spectra by an experienced analyst. The time required for manual assessment has previously rendered high-throughput confident assignment of phosphorylation sites challenging.

Results: We have developed a knowledge base of criteria, which replicate expert assessment, allowing more than half of cases to be automatically validated and site assignments verified with a high degree of confidence. This was assessed by comparing automated spectral interpretation with careful manual examination of the assignments for 501 peptides above the 1% false discovery rate (FDR) threshold corresponding to 259 putative phosphorylation sites in 74 proteins of the Trypanosoma brucei proteome. Despite this stringent approach, we are able to validate 80 of the 91 phosphorylation sites (88%) positively identified by manual examination of the spectra used for the MASCOT searches with a FDR < 15%.

Conclusions:High-throughput computational analysis can provide a viable second stage validation of primary mass spectrometry database search results. Such validation gives rapid access to a systems level overview of protein phosphorylation in the experiment under investigation.

Availability: A GPL licensed software implementation in Perl for analysis and spectrum annotation is available in the supplementary material and a web server can be assessed online at http://www.compbio.dundee.ac.uk/prophossi

Contact:d.m.a.martin@dundee.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Understanding protein phosphorylation on a systems level

Protein kinase phosphorylation is central to the regulation and control of protein and cellular function. Over the past decade, the development of many high-throughput approaches has revolutionized the understanding of protein phosphorylation and allowed rapid and unbiased surveys of phosphoproteins and phosphorylation events. In addition to this technological advancement, there have also been computational improvements; recent studies on network models of protein phosphorylation have provided many insights into the cellular processes and pathways regulated by phosphorylation. This article gives an overview of experimental and computational techniques for identifying and analyzing protein phosphorylation on a systems level.

Identification and characterization of molecular targets of natural products by mass spectrometry

Natural products, and their derivatives and mimics, have contributed to the development of important therapeutics to combat diseases such as infections and cancers over the past decades. The value of natural products to modern drug discovery is still considerable. However, its development is hampered by a lack of a mechanistic understanding of their molecular action, as opposed to the emerging molecule-targeted therapeutics that are tailored to a specific protein target(s). Recent advances in the mass spectrometry-based proteomic approaches have the potential to offer unprecedented insights into the molecular action of natural products. Chemical proteomics is established as an invaluable tool for the identification of protein targets of natural products. Small-molecule affinity selection combined with mass spectrometry is a successful strategy to "fish" cellular targets from the entire proteome. Mass spectrometry-based profiling of protein expression is also routinely employed to elucidate molecular pathways involved in the therapeutic and possible toxicological responses upon treatment with natural products. In addition, mass spectrometry is increasingly utilized to probe structural aspects of natural products-protein interactions. Limited proteolysis, photoaffinity labeling, and hydrogen/deuterium exchange in conjunction with mass spectrometry are sensitive and high-throughput strategies that provide low-resolution structural information of non-covalent natural product-protein complexes. In this review, we provide an overview on the applications of mass spectrometry-based techniques in the identification and characterization of natural product-protein interactions, and we describe how these applications might revolutionize natural product-based drug discovery.

Chemical tagging strategies for mass spectrometry-based phospho-proteomics

The study of protein phosphorylation in combination with chemical methods may serve several purposes. The removal of the phosphate group from phosphoserine and -threonine residues by beta-elimination has been employed to improve sensitivity for mass spectrometric detection and to attach affinity tags for phosphopeptide enrichment. More recently, phosphoramidate chemistry has been shown to be another promising tool for enriching phosphorylated peptides, and other phosphate-directed reactions may also be applicable to the study of the phosphoproteome in the future. In recent years, the combination of large-scale phospho-proteomics studies with stable isotope labeling for quantification purposes has become of growing importance, frequently involving the introduction of chemical tags such as iTRAQ. In this chapter, we will highlight several key strategies that involve chemical tagging reactions.

Predicting protein post-translational modifications using meta-analysis of proteome scale data sets

Protein post-translational modifications are an important biological regulatory mechanism, and the rate of their discovery using high throughput techniques is rapidly increasingly. To make use of this wealth of sequence data, we introduce a new general strategy designed to predict a variety of post-translational modifications in several organisms. We used the motif-x program to determine phosphorylation motifs in yeast, fly, mouse, and man and lysine acetylation motifs in man. These motifs were then scanned against proteomic sequence data using a newly developed tool called scan-x to globally predict other potential modification sites within these organisms. 10-fold cross-validation was used to determine the sensitivity and minimum specificity for each set of predictions, all of which showed improvement over other available tools for phosphoprediction. New motif discovery is a byproduct of this approach, and the phosphorylation motif analyses provide strong evidence of evolutionary conservation of both known and novel kinase motifs.

A comparative study of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) versus SCX-IMAC-based methods for phosphopeptide isolation/enrichment

Electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) has been introduced recently for phosphopeptide enrichment. Here we compared ERLIC with the well-established SCX-IMAC for identifying phosphopeptides in EGF-treated A431 cells. The ERLIC approach detected a higher number of phosphopeptides (17 311) than SCX-IMAC (4850), but it only detected 926 unique phosphopeptides compared to 1315 in SCX-IMAC. Only 12% unique phosphopeptides were common to both approaches, suggesting that more comprehensive phosphoproteomes could be generated by complementing SCX-IMAC with ERLIC.

Quantitative proteomic signature of liver cancer cells: tissue transglutaminase 2 could be a novel protein candidate of human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common diseases worldwide, with extremely poor prognosis due to failure in diagnosing it early. Alpha-fetoprotein (AFP) is the only available biomarker for HCC diagnosis; however, its use in the early detection of HCC is limited, especially because about one-third of patients afflicted with HCC have normal levels of serum AFP. Thus, identifying additional biomarkers that may be used in combination with AFP to improve early detection of HCC is greatly needed. A quantitative proteomic analysis approach using stable isotope labeling with amino acids in cell culture (SILAC) combined with LTQ-FT-MS/MS identification was used to explore differentially expressed protein profiles between normal (HL-7702) and cancer (HepG2 and SK-HEP-1) cells. A total of 116 proteins were recognized as potential markers that could distinguish between HCC and normal liver cells. Certain proteins, such as AFP, intercellular adhesion molecule-1 (ICAM-1), IQ motif containing GTPase activating protein 2 (IQGAP2), claudin-1 (CLDN1) and tissue transglutaminase 2 (TGM2), were validated both in multiple cell lines and in 61 specimens of clinical HCC cases. TGM2 was overexpressed in some of the AFP-deficient HCC cells (SK-HEP-1 and Bel-7402) and in about half of the tumor tissues with low levels of serum AFP (17/32, AFP-negative HCC). Trace amounts of TGM2 were found to be expressed in the samples with high serum AFP (26/29, AFP-positive HCC). Moreover, TGM2 expression in liver tissues showed an inverse correlation with the level of serum AFP in HCC patients. Notably, TGM2 existed in the supernatant of the AFP-deficient SK-HEP-1, SMMC-7721 and HLE cells, and it was found to be induced in AFP-producing cells (HepG2) by specific siRNA silence assay. Serum TGM2 levels of 109 HCC patients and 42 healthy controls were further measured by an established ELISA assay; the levels were significantly higher in HCC patients, and they correlated with the histological grade and tumor size. These data suggest that TGM2 may serve as a novel histological/serologic candidate involved in HCC, especially for the individuals with normal serum AFP. These novel findings may provide important clues to identify new biomarkers of HCC and indirectly improve early detection of the disease.

Recent developments in mass spectrometry-based quantitative phosphoproteomicsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process

Protein phosphorylation is a reversible post-translational modification that is involved in virtually all eukaryotic cellular processes and has been studied in great detail in recent years. Many developments in mass spectrometry (MS)-based proteomics have been successfully applied to study protein phosphorylation in highly complicated samples. Furthermore, the emergence of a variety of enrichment strategies has allowed some of the challenges associated with low phosphorylation stoichiometry and phosphopeptide copy number to be overcome. The dynamic nature of protein phosphorylation complicates its analysis; however, a number of methods have been developed to successfully quantitate phosphorylation changes in a variety of cellular systems. The following review details some of the most recent breakthroughs in the study of protein phosphorylation, or phosphoproteomics, using MS-based approaches. The majority of the focus is placed on detailing strategies that are currently used to conduct MS-based quantitative phosphoproteomics.

Systematic determination of ion score cutoffs based on calculated false positive rates: application for identifying ubiquitinated proteins by tandem mass spectrometry

We report a simple approach for determining ion score cutoffs that permit the confident identification of ubiquitinated proteins by tandem mass spectrometry (MS/MS). Initial experiments involving the analysis of gel bands containing multi-Ubiquitin chains with quadrupole time-of-flight and quadrupole ion trap mass spectrometers revealed that standard ion score cutoffs used for database searching were not sufficiently stringent. We also found that false positive and false negative rates (FPR and FNR) varied significantly depending on the cutoff scores used and that appropriate cutoffs could only be determined following a systematic evaluation of false positive rates. When standard cutoff scores were used for the analysis of complex mixtures of ubiquitinated proteins, unacceptably high FPR were observed. Finally, we found that FPR for ubiquitinated proteins are affected by the size of the protein database that is searched. These observations may be applicable for the study of other post-translational modifications.