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1.  Proteomic characterization of Her2/neu-overexpressing breast cancer cells 
Proteomics  2010;10(21):3800-3810.
The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with tandem mass spectrometry, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in MMTV-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin beta 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray datasets revealed a 23-gene signature which can be used to predict the probability of metastasis-free survival in breast cancer patients.
PMCID: PMC4327899  PMID: 20960451
Cancer biomarker; Her2; quantitative proteomics and SILAC
2.  Quantitative analysis of SILAC data sets using spectral counting 
Proteomics  2010;10(7):1408-1415.
We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, method relies on MS2 spectra rather than ion chromatograms for quantitation and therefore does not require the use of high mass accuracy mass spectrometers. The inclusion of a stable isotope label allows the samples to be combined before sample preparation and analysis, thus avoiding many of the sources of variability that can plague spectral counting. To validate the SPeCtRA method, we have analyzed samples constructed with known ratios of protein abundance. Finally, we used SPeCtRA to compare endothelial cell protein abundances between high (20 mM) and low (11 mM) glucose culture conditions. Our results demonstrate that SPeCtRA is a protein quantification technique that is accurate and sensitive as well as easy to automate and apply to high-throughput analysis of complex biological samples.
PMCID: PMC4326228  PMID: 20104619
3.  Quantitative Proteomic Analysis of LPS-induced Differential Immune Response Associated with TLR4 Polymorphisms by Multiplex Amino Acid Coded Mass-tagging 
Proteomics  2008;8(15):3061-3070.
Polymorphisms at Toll-like receptor 4 (TLR4) gene have been found to be associated with immune disorders. A murine macrophage cell line GG2EE derived from C3H/HeJ mice with a polymorphism site at TLR4 is hyposensitive to lipopolysacchride (LPS). To study the molecular base of diverse TLR4-mediated immune responses, the proteomic changes in both TLR4-deficient and –wild-type cell lines in response to the same LPS challenge were quantitatively compared by using multiplex amino acid coded mass-tagging (AACT)/SILAC-assisted mass spectrometry (MS). This strategy allows encoding of two distinct cell populations with different stable isotope-tagged lysine residues as the ‘in-spectra’ quantitative markers. In MS analysis of tryptic peptides derived from the equally mixed three cell populations, the lysine-containing peptides originated from two LPS stimulated cell populations can be clearly distinguished by their different mass shifts from the un-stimulated and unlabeled counterpart. The LPS-induced differential protein expression in TLR4 –deficient and –wild-type proteomes were obtained by comparing the intensities of isotopically encoded peptides. Among the more than 900 proteins identified, 35 were found to be deregulated at different levels in these two cell lines stimulated by LPS. This multiplex mass-tagging methodology can be readily extended to other comparative proteomic quantitation of different cell populations.
PMCID: PMC4302329  PMID: 18654986
4.  Global analysis of the rat and human platelet proteome – the molecular blueprint for illustrating multi-functional platelets and cross-species function evolution 
Proteomics  2010;10(13):2444-2457.
Emerging evidences indicate that blood platelets function in multiple biological processes including immune response, bone metastasis and liver regeneration in addition to their known roles in hemostasis and thrombosis. Global elucidation of platelet proteome will provide the molecular base of these platelet functions. Here, we set up a high throughput platform for maximum exploration of the rat/human platelet proteome using integrated proteomics technologies, and then applied to identify the largest number of the proteins expressed in both rat and human platelets. After stringent statistical filtration, a total of 837 unique proteins matched with at least two unique peptides were precisely identified, making it the first comprehensive protein database so far for rat platelets. Meanwhile, quantitative analyses of the thrombin-stimulated platelets offered great insights into the biological functions of platelet proteins and therefore confirmed our global profiling data. A comparative proteomic analysis between rat and human platelets was also conducted, which revealed not only a significant similarity, but also an across-species evolutionary link that the orthologous proteins representing ‘core proteome’, and the ‘evolutionary proteome’ is actually a relatively static proteome.
PMCID: PMC4302335  PMID: 20443191
Blood platelets; multidimensional separation; mass spectrometry; global profiling; cross-species comparison
5.  Biotin tagging coupled with amino acid-coded mass tagging (BioCAT) for efficient and precise screening of interaction proteome in mammalian cells 
Proteomics  2009;9(24):5414-5424.
In mammalian cells, when tandem affinity purification (TAP) approach is employed, the existence of untagged endogenous target protein and repetitive washing steps together result in overall low yield of purified/stable complexes and the loss of weakly and transiently interacting partners of biological significance. To avoid the trade-offs involving in methodological sensitivity, precision, and throughput here we introduce an integrated method, biotin tagging coupled with amino acid-coded mass tagging (BioCAT) for highly sensitive and accurate screening of mammalian protein-protein interactions (PPIs). Without the need of establishing a stable cell line, using a short peptide tag which could be specifically biotinylated in vivo, the biotin-tagged target/bait protein was then isolated along with its associates efficiently by streptavidin magnetic microbeads in a single step. In a pulled-down complex amino acid-coded mass tagging (AACT) serves as ‘in-spectra’ quantitative markers to distinguish those bait-specific interactors from non-specific background proteins under stringent criteria. Applying this BioCAT approach, we first biotin-tagged in vivo a multi-functional protein family member, 14-3-3ε, which was expressed at close to endogenous level. Starting with approximately 20 millions of 293T cells which were significantly less than what needed for a TAP run, 266 specific interactors of 14-3-3ε were identified in high confidence.
PMCID: PMC4302342  PMID: 19834888
Affinity purification; Amino acid-coded mass tagging; Biotin tagging; Protein-protein interaction; 14-3-3ε
6.  Facile removal of high mannose structures prior to extracting complex type N-glycans from de-N-glycosylated peptides retained by C18 solid phase to allow more efficient glycomic mapping 
Proteomics  2013;14(1):87-92.
The relative amount of high mannose structures within an N-glycomic pool differs from one source to another but quite often it predominates over the larger size complex type structures carrying biologically important glyco-epitopes. An efficient method to separate these two classes of N-glycans would significantly aid in detecting the lower abundant components by mass spectrometry. Capitalizing on an initial observation that only high mannose type structures were recovered in the flow through fraction when PNGase F digested peptides were passed through a C18 cartridge in 0.1% formic acid, we demonstrated here that native complex type N-glycans can be retained by C18 cartridge and to be efficiently separated from both the smaller high mannose type structures, as well as de-N-glycosylated peptides by stepwise elution with increasing acetonitrile concentration. The weak retention of the largely hydrophilic N-glycans on C18 resin is dependent not only on size but also increased by the presence of α6-fucosylation. This was shown by comparing the resulting N-glycomic profiles of the washed and low acetonitrile eluted fractions derived from both a human cancer cell line and an insect cell line.
PMCID: PMC3926941  PMID: 24174266
N-glycan fractionation; C18 RP SPE; Glycomics; Mass spectrometry
Proteomics  2013;14(1):42-50.
Proteolytic signaling, or regulated proteolysis, is an essential part of many important pathways such as Notch, Wnt, and Hedgehog. How the structure of the cleaved substrate regions influences the efficacy of proteolytic processing remains underexplored. Here, we analyzed the relative importance in proteolysis of various structural features derived from substrate sequences using a dataset of more than five thousand experimentally verified proteolytic events captured in CutDB. Accessibility to the solvent was recognized as an essential property of a proteolytically processed polypeptide chain. Proteolytic events were found nearly uniformly distributed among three types of secondary structure, although with some enrichment in loops. Cleavages in α-helices were found to be relatively abundant in regions apparently prone to unfolding, while cleavages in β-structures tended to be located at the periphery of β-sheets. Application of the same statistical procedures to proteolytic events divided into separate sets according to the catalytic classes of proteases proved consistency of the results and confirmed that the structural mechanisms of proteolysis are universal. The estimated prediction power of sequence-derived structural features, which turned out to be sufficiently high, presents a rationale for their use in bioinformatic prediction of proteolytic events.
PMCID: PMC3926948  PMID: 24227478
8.  Subproteome analysis of the neutrophil cytoskeleton 
Proteomics  2009;9(7):2037-2049.
Neutrophils play a key role in the early host-defense mechanisms due to their capacity to migrate into inflamed tissues and phagocytose microorganisms. The cytoskeleton has an essential role in these neutrophil functions, however, its composition is still poorly understood. We separately analyzed different cytoskeletal compartments: cytosolic skeleton, phagosome membrane skeleton, and plasma membrane skeleton. Using a proteomic approach, 138 nonredundant proteins were identified. Proteins not previously known to associate with the skeleton were: n-acetylglucosamine kinase, phosphoglycerate mutase 1, prohibitin, ficolin-1, phosphogluconate dehydrogenase, glucosidase, transketolase, major vault protein, valosin-containing protein, aldehyde dehydrogenase, and lung cancer-related protein-8 (LCRP8). The majority of these proteins can be classified as energy metabolism enzymes. Such a finding was interesting because neutrophil energy metabolism is unusual, mainly relying on glycolysis. The enrichment of phosphoglycerate mutase in cytosolic skeleton was additionally indicated by the use of Western blotting. This is the broadest subcellular investigation to date of the neutrophil cytoskeletal proteome and the first proteomic analysis in any cell type of the phagosome skeleton. The association of metabolic enzymes with cytoskeleton is suggestive of the importance of their localized enrichment and macromolecular organization in neutrophils.
PMCID: PMC4261606  PMID: 19294702
Cytoskeleton; Glycolysis; Neutrophil; Phagosome; Plasma membrane
9.  High-throughput analysis of peptide binding modules 
Proteomics  2012;12(10):1527-1546.
Modular protein interaction domains that recognize linear peptide motifs are found in hundreds of proteins within the human genome. Some protein interaction domains such as SH2, 14-3-3, Chromo and Bromo domains serve to recognize post-translational modification of amino acids (such as phosphorylation, acetylation, methylation etc.) and translate these into discrete cellular responses. Other modules such as SH3 and PDZ domains recognize linear peptide epitopes and serve to organize protein complexes based on localization and regions of elevated concentration. In both cases, the ability to nucleate specific signaling complexes is in large part dependent on the selectivity of a given protein module for its cognate peptide ligand. High throughput analysis of peptide-binding domains by peptide or protein arrays, phage display, mass spectrometry or other HTP techniques provides new insight into the potential protein-protein interactions prescribed by individual or even whole families of modules. Systems level analyses have also promoted a deeper understanding of the underlying principles that govern selective protein-protein interactions and how selectivity evolves. Lastly, there is a growing appreciation for the limitations and potential pitfalls of high-throughput analysis of protein-peptide interactomes. This review will examine some of the common approaches utilized for large-scale studies of protein interaction domains and suggest a set of standards for the analysis and validation of datasets from large-scale studies of peptide-binding modules. We will also highlight how data from large-scale studies of modular interaction domain families can provide insight into systems level properties such as the linguistics of selective interactions.
PMCID: PMC4255589  PMID: 22610655
10.  Proteogenomic strategies for identification of aberrant cancer peptides using large-scale Next Generation Sequencing data 
Proteomics  2014;14(0):2719-2730.
Cancer is driven by the acquisition of somatic DNA lesions. Distinguishing the early driver mutations from subsequent passenger mutations is key to molecular sub-typing of cancers, understanding cancer progression, and the discovery of novel biomarkers. The advances of genomics technologies (whole-genome exome, and transcript sequencing, collectively referred to as NGS(Next Gengeration Sequencing)) have fueled recent studies on somatic mutation discovery. However, the vision is challenged by the complexity, redundancy, and errors in genomic data, and the difficulty of investigating the proteome translated portion of aberrant genes using only genomic approaches. Combination of proteomic and genomic technologies are increasingly being employed.
Various strategies have been employed to allow the usage of large scale NGS data for conventional MS/MS searches. This paper provides a discussion of applying different strategies relating to large database search, and FDR(False Discovery Rate) based error control, and their implication to cancer proteogenomics. Moreover, it extends and develops the idea of a unified genomic variant database that can be searched by any mass spectrometry sample. A total of 879 BAM files downloaded from TCGA repository were used to create a 4.34 GB unified FASTA database which contained 2, 787, 062 novel splice junctions, 38, 464 deletions, 1, 105 insertions, and 182, 302 substitutions. Proteomic data from a single ovarian carcinoma sample (439, 858 spectra) was searched against the database. By applying the most conservative FDR measure, we have identified 524 novel peptides and 65, 578 known peptides at 1% FDR threshold. The novel peptides include interesting examples of doubly mutated peptides, frame-shifts, and non-sample-recruited mutations, which emphasize the strength of our approach.
PMCID: PMC4256132  PMID: 25263569
11.  Identification and Characterization of Cryptococcus neoformans Protein Fractions that Induce Protective Immune Responses 
Proteomics  2013;13(0):3429-3441.
Cryptococcus neoformans , the main causative agent of cryptococcosis, is a fungal pathogen that causes life-threatening meningoencephalitis in immunocompromised patients. To date, there is no vaccine or immunotherapy approved to treat cryptococcosis. Cell- and antibody-mediated immune responses collaborate to mediate optimal protection against C. neoformans infections. Accordingly, we identified cryptococcal protein fractions capable of stimulating cell- and antibody-mediated immune responses and determined their efficacy to elicit protection against cryptococcosis. Proteins were extracted from C. neoformans and fractionated based on molecular mass. The fractions were then evaluated by immunoblot analysis for reactivity to serum extracted from protectively immunized mice and in cytokine recall assays for their efficacy to induce pro-inflammatory and Th1-type cytokine responses associated with protection. Mass spectrometry analysis revealed a number of proteins with roles in stress response, signal transduction, carbohydrate metabolism, amino acid synthesis, and protein synthesis. Immunization with select protein fractions containing immunodominant antigens induced significantly prolonged survival against experimental pulmonary cryptococcosis. Our studies support using the combination of immunological and proteomic approaches to identify proteins that elicit antigen-specific antibody and Th1-type cytokine responses. The immunodominant antigens that were discovered represent attractive candidates for the development of novel subunit vaccines for treatment and/or prevention of cryptococcosis.
PMCID: PMC3916089  PMID: 24170628
Cryptococcus neoformans; Cryptococcosis; ImmunoProteomics; Surface proteins; Cytoplasmic proteins; Vaccination
12.  Label-free profiling of skeletal muscle using high-definition mass spectrometry 
Proteomics  2014;14(20):2339-2344.
We report automated and time efficient (2 h per sample) profiling of muscle using ultra-performance liquid chromatography (LC) coupled directly with high-definition mass spectrometry (HDMSE). Soluble proteins extracted from rat gastrocnemius (n=10) were digested with trypsin and analysed in duplicate using a 90 min RPLC gradient. Protein identification and label-free quantitation were performed from HDMSE spectra analysed using TransOmics Informatics for Proteomics software. In total 1,514 proteins were identified. Of these, 811 had at least 3 unique peptides and were subsequently used to assess the dynamic range and precision of LC-HDMSE label-free profiling. Proteins analysed by LC-HDMSE encompass the entire complement of glycolytic, beta-oxidation and tricarboxylic acid enzymes. In addition, numerous components of the electron transport chain and protein kinases involved in skeletal muscle regulation were detected. The dynamic range of protein abundances spanned 4 orders of magnitude. The correlation between technical replicates of the 10 biological samples was R2 = 0.9961 ± 0.0036 (95 % CI = 0.9940 – 0.9992) and the technical coefficient of variation averaged 7.3 ± 6.7 % (95 % CI = 6.87 – 7.79 %). This represents the most sophisticated label-free profiling of skeletal muscle to date.
PMCID: PMC4237019  PMID: 25065561
data-independent acquisition; ion mobility; LC-MS
13.  Identification, prioritization and evaluation of glycoproteins for aggressive prostate cancer using quantitative glycoproteomics and antibody-based assays on tissue specimens 
Proteomics  2013;13(15):2268-2277.
Prostate cancer is highly heterogeneous in nature; while the majority of cases are clinically insignificant, some cases are lethal. Currently, there are no reliable screening methods for aggressive prostate cancer. Since most established serum and urine biomarkers are glycoproteins secreted or leaked from the diseased tissue, the current study seeks to identify glycoprotein markers specific to aggressive prostate cancer using tissue specimens. With LC-MS/MS glycoproteomic analysis, we identified 350 glycopeptides with 17 being altered in aggressive prostate cancer. ELISA assays were developed/purchased to evaluate 4 candidates, i.e. cartilage oligomeric matrix protein (COMP), periostin, membrane primary amine oxidase (VAP-1) and cathepsin L, in independent tissue sets. In agreement with the proteomic analysis, we found that COMP and periostin expressions were significantly increased in aggressive prostate tumors while VAP-1 expression was significantly decreased in aggressive tumor. In addition, the expression of these proteins in prostate metastases also follows the same pattern observed in the proteomic analysis. This study provides a workflow for biomarker discovery, prioritization and evaluation of aggressive prostate cancer markers using tissue specimens. Our data suggest increase in COMP and periostin and decrease in VAP-1 expression in the prostate may be associated with aggressive prostate cancer.
PMCID: PMC4235679  PMID: 23716368
aggressive; prostate cancer; biomarker; glycoproteomics; OCT
14.  jmzTab: A Java interface to the mzTab data standard 
Proteomics  2014;14(11):1328-1332.
mzTab is the most recent standard format developed by the Proteomics Standards Initiative. mzTab is a flexible tab-delimited file that can capture identification and quantification results coming from MS-based proteomics and metabolomics approaches. We here present an open-source Java application programming interface for mzTab called jmzTab. The software allows the efficient processing of mzTab files, providing read and write capabilities, and is designed to be embedded in other software packages. The second key feature of the jmzTab model is that it provides a flexible framework to maintain the logical integrity between the metadata and the table-based sections in the mzTab files. In this article, as two example implementations, we also describe two stand-alone tools that can be used to validate mzTab files and to convert PRIDE XML files to mzTab. The library is freely available at
PMCID: PMC4230411  PMID: 24659499
Bioinformatics; Data standard; Java application programming interface; Proteomics Standards Initiative
15.  High Throughput Screening of Disulfide-Containing Proteins in a Complex Mixture 
Proteomics  2013;13(22):3256-3260.
The formation of disulfide bonds between cysteine residues is crucial for the stabilization of native protein structures and, thus, determination of disulfide linkages is an important facet of protein structural characterization. Nonetheless, the identification of disulfide bond linkages remains a significant analytical challenge, particularly in large proteins with complex disulfide patterns. Herein, we have developed a new liquid chromatography mass spectrometric (LC/MS) strategy for rapid screening of disulfides in an intact protein mixture after a straightforward reduction step with tris(2-carboxyethyl)phosphine. LC/MS analysis of reduced and non-reduced protein mixtures quickly revealed disulfide-containing proteins owing to a 2 Da mass increase per disulfide reduction and, subsequently, the total number of disulfide bonds in the intact proteins could be determined. We have demonstrated the effectiveness of this method in a protein mixture composed of both disulfide-containing and disulfide-free proteins. Our method is simple (no need for proteolytic digestion, alkylation, or the removal of reducing agents prior to MS analysis), high throughput (fast on-line LC/MS analysis) and reliable (no S-S scrambling), underscoring its potential as a rapid disulfide screening method for proteomics applications.
PMCID: PMC3914208  PMID: 24030959
Disulfide; Intact Proteins; Proteomics; Liquid Chromatography; TCEP; Mass Spectrometry
16.  Finding the Missing Link: Disulfide-containing proteins via a high-throughput proteomics approach 
Proteomics  2013;13(22):3245-3246.
Top-down proteomics have recently started to gain attention as a novel method to provide insight into the structure of proteins in their native state, specifically the number and location of disulfide bridges. However, previous techniques still relied on complex and time-consuming protein purification and reduction reactions to yield useful information. In this issue of Proteomics, Zhao et al. (High throughput Screening of Disulfide-Containing Proteins in a Complex Mixture, Proteomics 2013) devise a clever and rapid method for high-throughput determination of disulfides in proteins via reduction by tris(2-carboxyethyl)phosphine. Their work provides the foundation necessary to undertake more complex experiments in biological samples.
PMCID: PMC3923460  PMID: 24150840
Disulfide; Glutathionylation; Mass spectrometry; Post-translational Modification; Redox Proteomics; Redox Modifications
17.  Characterization of Multiple Myeloma Vesicles by Label-Free Relative Quantitation 
Proteomics  2013;13(20):10.1002/pmic.201300142.
Multiple myeloma (MM) is a hematological malignancy caused by a microenviromentally aided persistence of plasma cells in the bone marrow. The role that extracellular vesicles, microvesicles and exosomes, released by MM cells have in cell-to-cell communication and signaling in the bone marrow is currently unknown. This paper describes the proteomic content of extracellular vesicles derived from MM.1S and U266 MM cell lines. First, we compared the protein identifications between the vesicles and cellular lysates of each cell line finding a large overlap in protein identifications. Next, we applied label-free spectral count quantitation to determine proteins with differential abundance between the groups. Finally, we used bioinformatics to categorize proteins with significantly different abundances into functional groups. The results illustrate the first use of label-free spectral counting applied to determine relative protein abundances in extracellular vesicles.
PMCID: PMC3835174  PMID: 23983189
Extracellular vesicles; Microvesicles; Exosomes; Proteomics; Label-Free; LC-MS/MS
18.  Quantifying proteins by mass spectrometry: The selectivity of SRM is only part of the problem 
Proteomics  2009;9(5):1124-1127.
Precise and accurate protein quantification is critical to many areas of proteomics. Antibody-based approaches are costly and time-consuming to develop, consequently, there is considerable interest in alternative quantitative methods that are versatile and can be implemented without the considerable delays associated with antibody development and characterization. Approaches based on MS have therefore attracted considerable attention and are now frequently touted as the most practical and powerful of all options. Nevertheless, there are serious limitations associated with quantifying a protein based on tandem mass analysis of one or two peptides generated by either chemical or enzymatic cleavage. In an accompanying Viewpoint article, Molloy and coworkers point out that selectivity is not necessarily guaranteed despite the power of SRM. Here we address an additional concern that can also compromise specificity. In complex mammalian systems, multiple proteins can serve as precursors of a single peptide and consequently, depending on the peptide(s) selected, protein levels may be significantly under- or overestimated.
PMCID: PMC4166569  PMID: 19253279
Mass spectrometry; Protein quantification; Selected reaction monitoring
19.  Quantitative analysis of the secretome of TGF-β signaling-deficient mammary fibroblasts 
Proteomics  2010;10(13):2458-2470.
Transforming growth factor β (TGF-β) is a master regulator of autocrine and paracrine signaling pathways between a tumor and its microenvironment. Decreased expression of TGF-β type II receptor (TβRII) in stromal cells is associated with increased tumor metastasis and shorter patient survival. In this study, SILAC quantitative proteomics was used to identify differentially externalized proteins in the conditioned media from the mammary fibroblasts with or without intact TβRII. Over 1000 proteins were identified and their relative differential levels were quantified. Immunoassays were used to further validate identification and quantification of the proteomic results. Differential expression was detected for various extracellular proteins, including proteases and their inhibitors, growth factors, cytokines, and extracellular matrix proteins. CXCL10, a cytokine found to be up-regulated in the TβRII knockout mammary fibroblasts, is shown to directly stimulate breast tumor cell proliferation and migration. Overall, this study revealed hundreds of specific extracellular protein changes modulated by deletion of TβRII in mammary fibroblasts, which may play important roles in the tumor microenvironment. These results warrant further investigation into the effects of inhibiting the TGF-β signaling pathway in fibroblasts because systemic inhibition of TGF-β signaling pathways is being considered as a potential cancer therapy.
PMCID: PMC4156855  PMID: 20405477
Cell biology; Fibroblasts; Secretome; Stable isotope labeling with amino acids in cell culture; TGF-β type II receptor
20.  Histone H4 lysine 16 acetylated isoform synthesis opens new route to biophysical studies 
Proteomics  2013;13(0):1546-1547.
Histone H4 lysine acetylation regulated by MOF (males absent on the first) was initially discovered as a dosage compensation epigenetic mark. Recent studies have revealed, however, that the epigenetic mark has a critical role in cellular function both during oogenesis as well as oncogenesis. Detailed molecular analysis of H4K16 isoforms and other posttranslational modified histones has been limited by the lack of means to prepare sufficient material for in vitro study. This paper describes an improved method to prepare acetylated H4K16 as well as other covalently modified histone H4 isoform for biophysical studies.
PMCID: PMC4151460  PMID: 23595999
Cancer; DNA damage response; H4K16ac; Transcription
21.  Ultra-High Pressure Fast Size Exclusion Chromatography for Top-Down Proteomics 
Proteomics  2013;13(17):10.1002/pmic.201200594.
Top-down mass spectrometry (MS)-based proteomics has gained a solid growth over the past few years but still faces significant challenges in the liquid chromatographic separation of intact proteins. In top-down proteomics, it is essential to separate the high mass proteins from the low mass species due to the exponential decay in S/N as a function of increasing molecular mass. Size exclusion chromatography (SEC) is a favored liquid chromatography method for size-based separation of proteins but suffers from notoriously low resolution and detrimental dilution. Herein we reported the use of ultra-high pressure (UHP) SEC for rapid and high-resolution separation of intact proteins for top-down proteomics. Fast separation of intact proteins (6 – 669 kDa) was achieved in less than 7 min with high-resolution and high efficiency. More importantly, we have shown that this UHP-SEC provides high-resolution separation of intact proteins using a MS-friendly volatile solvent system, allowing the direct top-down MS analysis of SEC eluted proteins without an additional desalting step. Taken together, we have demonstrated that UHP-SEC is an attractive LC strategy for the size-separation of proteins with great potential for top-down proteomics.
PMCID: PMC3839113  PMID: 23794208
Protein separation; liquid chromatography; mass spectrometry; UPLC; post-translational modifications
22.  Bottom-up proteome analysis of E. coli using capillary zone electrophoresis-tandem mass spectrometry with an electrokinetic sheath-flow electrospray interface 
Proteomics  2013;13(17):2546-2551.
The E. coli proteome was digested with trypsin and fractionated using solid phase extraction on a C18 SPE column. Seven fractions were collected and analyzed by capillary zone electrophoresis (CZE)-electrospray ionization tandem mass spectrometry (ESI-MS/MS). The separation was performed in a 60 cm long linear polyacrylamide-coated capillary with a 0.1% (v/v) formic acid separation buffer. An electrokinetic sheath-flow electrospray interface was used to couple the separation capillary with an Orbitrap Velos operating in higher-energy collisional dissociation mode. Each CZE-ESI-MS/MS run lasted 50 minutes and total MS time was 350 minutes. A total of 23,706 peptide spectra matches, 4,902 peptide IDs, and 871 protein group IDs were generated using MASCOT with false discovery rate less than 1% on the peptide level. The total mass spectrometer analysis time was less than six hours, the sample identification rate (145 proteins/hour) was more than two times higher than previous studies of the E. coli proteome, and the amount of sample consumed (<1 μg) was roughly four-fold less than previous studies. These results demonstrate that CZE is a useful tool for the bottom-up analysis of prokaryote proteomes.
PMCID: PMC4121376  PMID: 23798545
23.  Oncogene Induced Cellular Senescence Elicits an Anti-Warburg Effect 
Proteomics  2013;13(17):10.1002/pmic.201200298.
Cellular senescence, an irreversible cell cycle arrest induced by a diversity of stimuli, has been considered as an innate tumor suppressing mechanism with implications and applications in cancer therapy. Using a targeted proteomics approach we show that fibroblasts induced into senescence by expression of oncogenic Ras exhibit a decrease of global acetylation on all core histones, consistent with formation of senescence-associated heterochromatic foci. We also detected clear increases in repressive markers (e.g., >50% elevation of H3K27me2/3) along with decreases in histone marks associated with increased transcriptional expression/elongation (e.g., H3K36me2/3). Despite the increases in repressive marks of chromatin, 179 loci (of 2206 total) were found to be upregulated by global quantitative proteomics. The changes in the cytosolic proteome indicated an upregulation of mitochondrial proteins and downregulation of proteins involved in glycolysis. These alterations in primary metabolism are opposite of the well-known Warburg effect observed in cancer cells. This study significantly improves our understanding of stress-induced senescence and provides a potential application for triggering it in anti-proliferative strategies that target the primary metabolism in cancer cells.
PMCID: PMC3867201  PMID: 23798001
histones; mass spectrometry; metabolism; oxidative phosphorylation; proteomics; senescence
24.  Analysis of phagosomal proteomes: From latex-bead to bacterial phagosomes 
Proteomics  2010;10(22):4098-4116.
Phagosomal proteome characterization has contributed significantly to the understanding of host–pathogen interaction and the mechanism of infectious diseases caused by intracellular bacteria. The latex bead-containing phagosome has been widely used as a model system to study phagosomal proteomes at a global level. In contrast, the study of bacteria-containing phagosomes at a similar level has just begun. A number of intracellular microbial species are studied for their proteomes during the invasion of a host, providing insight into their metabolic adaptation in host cells and interaction with host-cell antimicrobial environments. In this review, we attempt to summarize the most recent advancements in the proteomic study of microbial phagosomes, especially those originating from mouse or human cells. We also briefly describe the proteomics of latex bead-containing phagosomes because they are often used as model phagosomes for study. We provide descriptions on major biological and technological components in phagosomal proteome studies. We also discuss the role of phagosomal proteome study in the broader horizon of systems biology and the technological challenges in phagosomal proteome characterization.
PMCID: PMC4131734  PMID: 21080496
Bacteria; Interaction; Microbiology; Phagosome
25.  A Proteomic Snapshot of Breast Cancer Cell Cycle: The G1/S Transition Point 
Proteomics  2013;13(1):48-60.
The biological processes that unfold during the G1-phase of the cell cycle are dependent on extracellular mitogenic factors which signal the cell to enter a state of quiescence, or commit to a cell cycle round by passing the restriction point (R-point) and enter the S-phase. Unlike normal cells, cancer cells evolved the ability to evade the R-point and continue through the cell cycle even in the presence of extensive DNA damage or absence of mitogenic signals. The purpose of this study was to perform a quantitative proteomic evaluation of the biological processes that are responsible for driving MCF-7 breast cancer cells into division even when molecular checkpoints such as the G1/S R-point are in place. Nuclear and cytoplasmic fractions of the G1 and S cell cycle phases were analyzed by LC-MS/MS to result in the confident identification of >2700 proteins. Statistical evaluation of the normalized data resulted in the selection of proteins that displayed ≥2-fold change in spectral counts in each cell state. Pathway mapping, functional annotation clustering and protein interaction network analysis revealed that the top-scoring clusters that could play a role in overriding the G1/S transition point included DNA damage response, chromatin remodeling, transcription/translation regulation and signaling proteins.
PMCID: PMC4123745  PMID: 23152136
proteomics; mass spectrometry; cell cycle; breast cancer

Results 1-25 (371)