Procedures for the biochemical enrichment and proteomic analysis of the cytoskeletome.

The cell cytoskeleton is composed of microtubules, intermediate filaments, and actin that provide a rigid support structure important for cell shape. However, it is also a dynamic signaling scaffold that receives and transmits complex mechanosensing stimuli that regulate normal physiological and aberrant pathophysiological processes. Studying cytoskeletal functions in the cytoskeleton's native state is inherently difficult due to its rigid and insoluble nature. This has severely limited detailed proteomic analyses of the complex protein networks that regulate the cytoskeleton. Here, we describe a purification method that enriches for the cytoskeleton and its associated proteins in their native state that is also compatible with current mass spectrometry-based protein detection methods. This method can be used for biochemical, fluorescence, and large-scale proteomic analyses of numerous cell types. Using this approach, 2346 proteins were identified in the cytoskeletal fraction of purified mouse embryonic fibroblasts, of which 635 proteins were either known cytoskeleton proteins or cytoskeleton-interacting proteins. Functional annotation and network analyses using the Ingenuity Knowledge Database of the cytoskeletome revealed important nodes of interconnectivity surrounding well-established regulators of the actin cytoskeleton and focal adhesion complexes. This improved cytoskeleton purification method will aid our understanding of how the cytoskeleton controls normal and diseased cell functions.

Systematic analysis of protein phosphorylation networks from phosphoproteomic data.

In eukaryotes, hundreds of protein kinases (PKs) specifically and precisely modify thousands of substrates at specific amino acid residues to faithfully orchestrate numerous biological processes, and reversibly determine the cellular dynamics and plasticity. Although over 100,000 phosphorylation sites (p-sites) have been experimentally identified from phosphoproteomic studies, the regulatory PKs for most of these sites still remain to be characterized. Here, we present a novel software package of iGPS for the prediction of in vivo site-specific kinase-substrate relations mainly from the phosphoproteomic data. By critical evaluations and comparisons, the performance of iGPS is satisfying and better than other existed tools. Based on the prediction results, we modeled protein phosphorylation networks and observed that the eukaryotic phospho-regulation is poorly conserved at the site and substrate levels. With an integrative procedure, we conducted a large-scale phosphorylation analysis of human liver and experimentally identified 9719 p-sites in 2998 proteins. Using iGPS, we predicted a human liver protein phosphorylation networks containing 12,819 potential site-specific kinase-substrate relations among 350 PKs and 962 substrates for 2633 p-sites. Further statistical analysis and comparison revealed that 127 PKs significantly modify more or fewer p-sites in the liver protein phosphorylation networks against the whole human protein phosphorylation network. The largest data set of the human liver phosphoproteome together with computational analyses can be useful for further experimental consideration. This work contributes to the understanding of phosphorylation mechanisms at the systemic level, and provides a powerful methodology for the general analysis of in vivo post-translational modifications regulating sub-proteomes.

Proteome-wide discovery and characterizations of nucleotide-binding proteins with affinity-labeled chemical probes.

Nucleotide-binding proteins play pivotal roles in many cellular processes including cell signaling. However, targeted studies of the subproteome of nucleotide-binding proteins, especially protein kinases and GTP-binding proteins, remain challenging. Here, we report a general strategy in using affinity-labeled chemical probes to enrich, identify, and quantify ATP- and GTP-binding proteins in the entire human proteome. Our results revealed that the ATP/GTP affinity probes facilitated the identification of 100 GTP-binding proteins and 206 kinases with the use of low milligram quantities of lysate of HL-60 cells. In combination with the use of the stable isotope labeling by amino acids in cell culture-based quantitative proteomics method, we assessed the ATP/GTP binding selectivities of nucleotide-binding proteins at the global proteome scale. Our results confirmed known and, more importantly, unveiled new ATP/GTP-binding preferences of hundreds of nucleotide-binding proteins. Additionally, our strategy led to the identification of three and one unique nucleotide-binding motifs for kinases and GTP-binding proteins, respectively, and the characterizations of the nucleotide-binding selectivities of individual motifs. Our strategy for capturing and characterizing ATP/GTP-binding proteins should be generally applicable for those proteins that can interact with other nucleotides.

Spatial phosphoprotein profiling reveals a compartmentalized extracellular signal-regulated kinase switch governing neurite growth and retraction.

Brain development and spinal cord regeneration require neurite sprouting and growth cone navigation in response to extension and collapsing factors present in the extracellular environment. These external guidance cues control neurite growth cone extension and retraction processes through intracellular protein phosphorylation of numerous cytoskeletal, adhesion, and polarity complex signaling proteins. However, the complex kinase/substrate signaling networks that mediate neuritogenesis have not been investigated. Here, we compare the neurite phosphoproteome under growth and retraction conditions using neurite purification methodology combined with mass spectrometry. More than 4000 non-redundant phosphorylation sites from 1883 proteins have been annotated and mapped to signaling pathways that control kinase/phosphatase networks, cytoskeleton remodeling, and axon/dendrite specification. Comprehensive informatics and functional studies revealed a compartmentalized ERK activation/deactivation cytoskeletal switch that governs neurite growth and retraction, respectively. Our findings provide the first system-wide analysis of the phosphoprotein signaling networks that enable neurite growth and retraction and reveal an important molecular switch that governs neuritogenesis.

Enrichment of peptides containing consensus sequence by an enzymatic approach for targeted analysis of proteins.

Multiple residues with consensus sequence, i.e. motif, on proteins are closely related to protein function. However, there is no effective method for targeted analysis of such proteins. The challenge for analysis of these classes of proteins by MS is how to selectively enrich peptides containing consensus sequence from protein digest. Although enrichment of peptides containing one type of amino acid residue was successfully achieved by chemically labeling followed by chromatographic isolation, however, it is almost impossible to label and isolate signature peptides containing multiple residues with consensus sequence by chemical approach. Herein, we developed an enzymatic approach based on the specific recognition between enzyme and its substrates to enrich such peptides. This approach was realized by modification of a residue in the consensus sequence via enzyme that can recognize the sequence followed by the isolation of the modified peptides. cAMP-dependent protein kinase was used to validate this approach and 168 peptides containing consensus motif were identified with selectivity of 67.2%. Those peptides resulted in the identification of 88 proteins with consensus sequence from serum sample. As this motif-oriented peptide enrichment approach allows targeted analysis of a subset of proteins with consensus sequence, it will have broad application in biological studies.

Quantitative proteomic analysis revealed lovastatin-induced perturbation of cellular pathways in HL-60 cells.

Lovastatin, a member of the statin family of drugs, is widely prescribed for treating hypercholesterolemia. The statin family of drugs, however, also shows promise for cancer treatment and prevention. Although lovastatin is known to be an inhibitor for HMG-CoA reductase, the precise mechanisms underlying the drug's antiproliferative activity remain unclearly defined. Here we utilized mass spectrometry, in conjunction with stable isotope labeling by amino acids in cell culture (SILAC), to analyze the perturbation of protein expression in HL-60 cells treated with lovastatin. We were able to quantify ∼3200 proteins with both forward and reverse SILAC labeling experiments, among which ∼120 exhibited significant alterations in expression levels upon lovastatin treatment. Apart from confirming the expected inhibition of the cholesterol biosynthesis pathway, our quantitative proteomic results revealed that lovastatin perturbed the estrogen receptor signaling pathway, which was manifested by the diminished expression of estrogen receptor α, steroid receptor RNA activator 1, and other related proteins. Lovastatin also altered glutamate metabolism through down-regulation of glutamine synthetase and γ-glutamylcysteine synthetase. Moreover, lovastatin treatment led to a marked down-regulation of carbonate dehydratase II (a.k.a. carbonic anhydrase II) and perturbed the protein ubiquitination pathway. Together, the results from the present study underscored several new cellular pathways perturbed by lovastatin.

Perspectives of comprehensive phosphoproteome analysis using shotgun strategy.

Protein phosphorylation is a ubiquitous post-translational modification that regulates almost all cellular processes. The analysis of protein phosphorylation is challenging due to the high dynamic range and low abundance natures of the analyte. Shotgun based proteomics has emerged as a very useful platform to achieve a comprehensive phosphoproteome analysis in considerable depth. In the past few years, significant breakthroughs on the large scale phosphorylation analysis have been witnessed along with the great development of related technologies. The combination of effective enrichment materials, refined analysis workflows, new type of powerful mass spectrometers, and sophisticated bioinformatic tools greatly boost the performance of comprehensive phosphoproteome analysis. In this Perspective, we briefly reviewed recent technological developments on the enrichment materials, prefractionation workflows, and different mass spectrometry fragmentation modes as well as software tools for phosphoproteome identification and quantification. Then, we described the current challenges and potential directions for the future of comprehensive phosphoproteome analysis. We also provide perspectives on how to further improve the performance of related analysis methods and technologies.

The proteome analysis of oleaginous yeast Lipomyces starkeyi.

Oleaginous yeast Lipomyces starkeyi, a species in the Saccharomycetales order, has the capability to accumulate over 70% of its cell biomass as lipid under defined culture conditions. In this study, analysis of L. starkeyi AS 2.1560 proteome samples from different culture stages during a typical lipid production process was performed using an online multidimensional µRPLC/MS/MS method. Data searching against the proteome database of the yeast Saccharomyces cerevisiae led to the identification of 289 protein hits. Further comparative and semi-quantitative analysis under more stringent criteria revealed 81 proteins with significant expression-level changes. Among them, 52 proteins were upregulated and 29 proteins were downregulated. Gene ontology annotation indicated that global responses occurred when cells were exposed to the nitrogen deficiency environment for lipid production. Protein hits were annotated and largely concerned metabolic processes for alternative nitrogen sources usage or lipid accumulation. Many of the downregulated proteins were related to glycolysis, whereas the majority of the upregulated proteins were involved in proteolysis and peptidolysis, carbohydrate metabolism and lipid metabolism. Insights were provided in terms of cellular responses to nutrient availability as well as the basic biochemistry of lipid accumulation. This work presented potentially valuable information for understanding the biochemical events related to microbial oleaginity and rational engineering of oleaginous yeasts.

Quantitative proteomic analysis reveals the perturbation of multiple cellular pathways in jurkat-T cells induced by doxorubicin.

Doxorubicin remains an important part of chemotherapy regimens in the clinic and is considered an effective agent in the treatment of acute lymphoblastic leukemia (ALL). Although the cellular responses induced by doxorubicin treatment have been investigated for years, the precise mechanisms underlying its cytotoxicity and therapeutic activity remain unclear. Here we utilized mass spectrometry, together with stable isotope labeling by amino acids in cell culture (SILAC), to analyze comparatively the protein expression in Jurkat-T cells before and after treatment with a clinically relevant concentration of doxorubicin. We were able to quantify 1066 proteins in Jurkat-T cells with both forward and reverse SILAC measurements, among which 62 were with significantly altered levels of expression induced by doxorubicin treatment. These included the up-regulation of core histones, heterogeneous nuclear ribonucleoproteins, and superoxide dismutase 2 as well as the down-regulation of hydroxymethylglutaryl-CoA synthase and farnesyl diphosphate synthase. The latter two are essential enzymes for cholesterol biosynthesis. We further demonstrated that the doxorubicin-induced growth inhibition of Jurkat-T cells could be rescued by treatment with cholesterol, supporting that doxorubicin exerts its cytotoxic effect, in part, by suppressing the expression of hydroxymethylglutaryl-CoA synthase and farnesyl diphosphate synthase, thereby inhibiting the endogenous production of cholesterol. The results from the present study provide important new knowledge for gaining insights into the molecular mechanisms of action of doxorubicin.

ArMone: a software suite specially designed for processing and analysis of phosphoproteome data.

The development of new phosphoproteomic technologies has led to a rapid increase in the number of phosphoprotein identifications. Managing and extracting valuable information from the phosphoproteome data sets and generating output information in user-friendly formats require special data management and process platform. Even though a few proteome pipelines have been developed, they are mainly designed for processing data set of unmodified peptide/protein identifications. Because of the different characteristics of phosphorylated peptides/proteins, these pipelines are inconvenient, sometimes inappropriate, to process the phosphoproteome data sets. In this study, a software suite named ArMone was specially designed for the management and analysis of phosphoproteome data. It can readily identify phosphopeptides with high reliability and high sensitivity, and can effectively pinpoint the most probable phosphorylation site. A few well-designed postvalidation process tools are also available to extract and export valuable information. ArMone is a stand-alone application with friendly graphic user interface. It can run on different operating systems and can process data sets obtained by most of the commonly used database search engines.

Global proteome quantification for discovering imatinib-induced perturbation of multiple biological pathways in K562 human chronic myeloid leukemia cells.

Imatinib mesylate, currently marketed by Novartis as Gleevec in the U.S., has emerged as the leading compound to treat the chronic phase of chronic myeloid leukemia (CML), through its inhibition of Bcr-Abl tyrosine kinases, and other cancers. However, resistance to imatinib develops frequently, particularly in late-stage disease. To identify new cellular pathways affected by imatinib treatment, we applied mass spectrometry together with stable isotope labeling by amino acids in cell culture (SILAC) for the comparative study of protein expression in K562 cells that were untreated or treated with a clinically relevant concentration of imatinib. Our results revealed that, among the 1344 quantified proteins, 73 had significantly altered levels of expression induced by imatinib and could be quantified in both forward and reverse SILAC labeling experiments. These included the down-regulation of thymidylate synthase, S-adenosylmethionine synthetase, and glycerol-3-phosphate dehydrogenase as well as the up-regulation of poly(ADP-ribose) polymerase 1, hemoglobins, and enzymes involved in heme biosynthesis. We also found, by assessing alteration in the acetylation level in histone H4 upon imatinib treatment, that the imatinib-induced hemoglobinization and erythroid differentiation in K562 cells are associated with global histone H4 hyperacetylation. Overall, these results provided potential biomarkers for monitoring the therapeutic intervention of CML using imatinib and offered important new knowledge for gaining insight into the molecular mechanisms of action of imatinib.

Classification filtering strategy to improve the coverage and sensitivity of phosphoproteome analysis.

Data dependent neutral loss triggered MS3 methodology (NLMS3) is often applied to acquire MS data for the analysis of phosphopeptides. Some phosphopeptides tend to seriously lose the phosphate and result in MS2 spectra with poor fragments and fragment-rich MS3 spectra, while some phosphopeptides do not lose phosphate and result in nice MS2 spectra. Since different phosphopeptides have fragment spectra with different characteristics, filtering all of the phosphopeptide identifications by setting a global filter criteria may be inappropriate and result in low sensitivity. In this study, we developed a classification filtering strategy to improve the phosphopeptide identification and phosphorylation site localization. Phosphopeptide identifications were classified into four classes according to their different characteristics, and then, the identifications from each class of mass spectra were processed and filtered separately using different filtering strategies. It was found that the overlap of phosphopeptide identifications from different classes was low and the classification strategy significantly improved the coverage of the phosphoproteome analysis. Compared with MS2 strategy and multiple stage activation (MSA) strategy, NLMS3 with the classification filtering strategy was demonstrated to have higher sensitivity and higher performance in localizing the phosphorylation to specific sites.

Reversed-phase-reversed-phase liquid chromatography approach with high orthogonality for multidimensional separation of phosphopeptides.

Protein phosphorylation regulates a series of important biological processes in eukaryotes. However, the phosphorylation sites found up to now are far below than that actually exists in proteins due to the extreme complexity of the proteome sample. Here a new reversed-phase-reversed-phase liquid chromatography (RP-RPLC) approach was developed for multidimensional separation of phosphopeptides. In this approach, a large number of fractions were collected from the first dimensional RPLC separation at high pH. And then these fractions were pooled every two fractions with equal time interval, one from the early eluted section and another one from the later eluted section. The pooled fractions were finally submitted to RPLC-tandem mass spectrometry (MS/MS) analysis at low pH. It was found the resulting 2D separation was highly orthogonal and yielded more than 30% phosphopeptide identifications over the conventional RP-RPLC approach. This study provides a powerful approach for efficient separation of phosphopeptides and global phosphorylation analysis, where the orthogonality of 2D separation is greatly improved and the first dimensional separation is of high resolution.

Phosphoproteome analysis of human liver tissue by long-gradient nanoflow LC coupled with multiple stage MS analysis.

Reversible protein phosphorylation plays a critical role in liver development and function. Comprehensively cataloging the phosphoproteins and their phosphorylation sites in human liver tissue will facilitate the understanding of physiological and pathological mechanisms of liver. Owing to lacking of efficient approach to fractionate phosphopeptides, nanoflow-RPLC with long-gradient elution was applied to reduce the complexity of the phosphopeptides in this study. Two approaches were performed to further improve the coverage of phosphoproteome analysis of human liver tissue. In one approach, ten-replicated long-gradient LC-MS/MS runs were performed to analyze the enriched phosphopeptides, which resulted in the localization of 1080 phosphorylation sites from 495 proteins. In another approach, proteins from liver tissue were first fractionated by SDS-PAGE and then long-gradient LC-MS/MS analysis was performed to analyze the phosphopeptides derived from each fraction, which resulted in the localization of 1786 phosphorylation sites from 911 proteins. The two approaches showed the complementation in phosphoproteome analysis of human liver tissue. Combining the results of the two approaches, identification of 2225 nonredundant phosphorylation sites from 1023 proteins was obtained. The confidence of phosphopeptide identifications was strictly controlled with false discovery rate (FDR) < or = 1% by a MS(2)/MS(3) target-decoy database search approach. Among the localized 2225 phosphorylated sites, as many as 70.07% (1559 phosphorylated sites) were also reported by others, which confirmed the high confidence of the sites determined in this study. Considering the data acquired from low accuracy mass spectrometer and processed by a conservative MS(2)/MS(3) target-decoy approach, the number of localized phosphorylation sites obtained for human liver tissue in this study is quite impressive.

Fractionation of phosphopeptides on strong anion-exchange capillary trap column for large-scale phosphoproteome analysis of microgram samples.

It is one of the key issues to develop powerful fractionating method to increase the identification of the low-abundance phosphopeptides. In this study, a semi-online 2-D LC separation strategy based on three-step fractionation of the enriched peptides on strong anion-exchange trap column was developed. It was demonstrated that the sensitivity and phosphoproteome coverage obtained by this fractionating method with strong anion-exchange trap column is much higher than those by the conventional methods based on C18 trap column. In addition, when the same amount of sample was loaded, the number of identified phosphopeptides had increased 108%. Combination of this three-step fractionation method with RPLC-MS/MS analysis by 300 min RP-gradient separation was applied to phosphoproteome analysis of human liver proteins, and 853 unique phosphopeptides was positively identified from 500 microg tryptic digest of human liver proteins. After three cycles' consecutive analyses, 1554 unique phosphopeptides and 1566 phosphorylated sites were totally identified from 735 phosphorylated proteins at a false discovery rate of <1% in about 54 h of analysis time.

Comprehensive and reliable phosphorylation site mapping of individual phosphoproteins by combination of multiple stage mass spectrometric analysis with a target-decoy database search.

Since the emergence of proteomics, much attention has been paid to the development of new technologies for phosphoproteomcis analysis. Compared with large scale phosphorylation analysis at the proteome level, comprehensive and reliable phosphorylation site mapping of individual phosphoprotein is equally important. Here, we present a modified target-decoy database search strategy for confident phosphorylation site analysis of individual phosphoproteins without manual interpretation of spectra. Instead of using all protein sequences in a proteome database of an organism for the construction of a target-decoy database for phosphoproteome analysis, the composite database constructed for phosphorylation site analysis of individual phosphoproteins only included the sequences of the individual target proteins and a decoy version of a small inhomogeneous protein database. It was found that the confidence of phosphopeptide identifications could be effectively controlled when the acquired MS2 and MS3 spectra were searched against the above composite database followed with data processing. Because of the small size of the composite database, the computation time for the database search is very short, which allows the adoption of low-specificity proteases for protein digestion to increase the coverage of phosphorylation site mapping. The sensitivity and comprehensive phosphorylation site mapping of this approach was demonstrated by using two standard phosphoprotein samples of alpha-casein and beta-casein, and this approach was further applied to analyze the phosphorylation of the cyclic AMP-dependent protein kinase (PKA), which resulted in the identification of 17 phosphorylation sites, including five novel sites on four PKA subunits.

Large-scale phosphoproteome analysis of human liver tissue by enrichment and fractionation of phosphopeptides with strong anion exchange chromatography.

The mixture of phosphopeptides enriched from proteome samples are very complex. To reduce the complexity it is necessary to fractionate the phosphopeptides. However, conventional enrichment methods typically only enrich phosphopeptides but not fractionate phosphopeptides. In this study, the application of strong anion exchange (SAX) chromatography for enrichment and fractionation of phosphopeptides was presented. It was found that phosphopeptides were highly enriched by SAX and majority of unmodified peptides did not bind onto SAX. Compared with Fe(3+) immobilized metal affinity chromatography (Fe(3+)-IMAC), almost double phosphopeptides were identified from the same sample when only one fraction was generated by SAX. SAX and Fe(3+)-IMAC showed the complementarity in enrichment and identification of phosphopeptides. It was also demonstrated that SAX have the ability to fractionate phosphopeptides under gradient elution based on their different interaction with SAX adsorbent. SAX was further applied to enrich and fractionate phosphopeptides in tryptic digest of proteins extracted from human liver tissue adjacent to tumorous region for phosphoproteome profiling. This resulted in the highly confident identification of 274 phosphorylation sites from 305 unique phosphopeptides corresponding to 168 proteins at false discovery rate (FDR) of 0.96%.

Improvement of performance in label-free quantitative proteome analysis with monolithic electrospray ionization emitter.

The postcolumn void volume, which is introduced by the connecting tubing and void ESI emitter in the nanoflow LC coupled with MS/MS system (microLC-MS/MS), is harmful for the analysis of peptides in shotgun proteome analysis. A new type of porous C12 monolithic ESI emitter was prepared to eliminate the disruption and mixing effects occurring in the connecting tubing and void emitter. It was demonstrated that the porous hydrophobic monolith inside the emitter played a key role in retaining the good peak profile, and the average peak capacity of the whole separation system increased 12.8% in contrast to commercially available void emitter. Then, the porous C12 monolithic emitter was applied in label-free quantitative proteome analysis of two standard protein mixtures that were spiked into the tryptic digest of mouse livers extract. Compared to commercially available void ESI emitter, the number of proteins with reliable results in quantification increased greatly. And the relative quantities of the four standard proteins were all determined with the relative error < or = 6.8%. However, quantitative information of only three standard proteins could be obtained when void emitter was used.

Facile synthesis of a graphene/nickel-cobalt hydroxide ternary hydrogel for high-performance supercapacitors.

In this paper, a graphene/nickel-cobalt hydroxide ternary hydrogel (G-Ni-Co) with superior electrochemical performances was prepared by a simple hydrothermal method using Ni(NO3)2·6H2O, Co(NO3)2·6H2O, and graphene oxide as the starting materials. The mass fraction and the pH value of the reaction system were optimized. The prepared G-Ni-Co was assembled into a symmetric supercapacitor and its electrochemical performance was estimated. In a symmetric supercapacitor, the specific capacitance of G-Ni-Co is 551.3 F g-1 at the scan rate of 10 mV s-1 and 646.1 F g-1 at the current density of 0.5 A g-1, respectively. The specific capacitance still retains 70.8% after 5000 cycles at the scan rate of 100 mV s-1. The energy density reaches 108.6 W h kg-1 at a power density of 550.0 W kg-1 and remains 72.4 W h kg-1 at 7600.0 W kg-1, respectively.

Optimization of filtering criterion for SEQUEST database searching to improve proteome coverage in shotgun proteomics.

BACKGROUND: In proteomic analysis, MS/MS spectra acquired by mass spectrometer are assigned to peptides by database searching algorithms such as SEQUEST. The assignations of peptides to MS/MS spectra by SEQUEST searching algorithm are defined by several scores including Xcorr, Delta Cn, Sp, Rsp, matched ion count and so on. Filtering criterion using several above scores is used to isolate correct identifications from random assignments. However, the filtering criterion was not favorably optimized up to now. RESULTS: In this study, we implemented a machine learning approach known as predictive genetic algorithm (GA) for the optimization of filtering criteria to maximize the number of identified peptides at fixed false-discovery rate (FDR) for SEQUEST database searching. As the FDR was directly determined by decoy database search scheme, the GA based optimization approach did not require any pre-knowledge on the characteristics of the data set, which represented significant advantages over statistical approaches such as PeptideProphet. Compared with PeptideProphet, the GA based approach can achieve similar performance in distinguishing true from false assignment with only 1/10 of the processing time. Moreover, the GA based approach can be easily extended to process other database search results as it did not rely on any assumption on the data. CONCLUSION: Our results indicated that filtering criteria should be optimized individually for different samples. The new developed software using GA provides a convenient and fast way to create tailored optimal criteria for different proteome samples to improve proteome coverage.