Characterization of Citrullination Sites in Neutrophils and Mast Cells Activated by Ionomycin via Integration of Mass Spectrometry and Machine Learning.

Citrullination is an important post-translational modification implicated in many diseases including rheumatoid arthritis (RA), Alzheimer's disease, and cancer. Neutrophil and mast cells have different expression profiles for protein-arginine deiminases (PADs), and ionomycin-induced activation makes them an ideal cellular model to study proteins susceptible to citrullination. We performed high-resolution mass spectrometry and stringent data filtration to identify citrullination sites in neutrophil and mast cells treated with and without ionomycin. We identified a total of 833 validated citrullination sites on 395 proteins. Several of these citrullinated proteins are important components of pathways involved in innate immune responses. Using this benchmark primary sequence data set, we developed machine learning models to predict citrullination in neutrophil and mast cell proteins. We show that our models predict citrullination likelihood with 0.735 and 0.766 AUCs (area under the receiver operating characteristic curves), respectively, on independent validation sets. In summary, this study provides the largest number of validated citrullination sites in neutrophil and mast cell proteins. The use of our novel motif analysis approach to predict citrullination sites will facilitate the discovery of novel protein substrates of protein-arginine deiminases (PADs), which may be key to understanding immunopathologies of various diseases.

Development of a Parallel Reaction Monitoring Mass Spectrometry Assay for the Detection of SARS-CoV-2 Spike Glycoprotein and Nucleoprotein.

There is an urgent need for robust and high-throughput methods for SARS-CoV-2 detection in suspected patient samples to facilitate disease management, surveillance, and control. Although nucleic acid detection methods such as reverse transcription polymerase chain reaction (RT-PCR) are the gold standard, during the current pandemic, the deployment of RT-PCR tests has been extremely slow, and key reagents such as PCR primers and RNA extraction kits are at critical shortages. Rapid point-of-care viral antigen detection methods have been previously employed for the diagnosis of respiratory viruses such as influenza and respiratory syncytial viruses. Therefore, the direct detection of SARS-CoV-2 viral antigens in patient samples could also be used for diagnosis of active infection, and alternative methodologies for specific and sensitive viral protein detection should be explored. Targeted mass spectrometry techniques have enabled the identification and quantitation of a defined subset of proteins/peptides at single amino acid resolution with attomole level sensitivity and high reproducibility. Herein, we report a targeted mass spectrometry assay for the detection of SARS-CoV-2 spike protein and nucleoprotein in a relevant biological matrix. Recombinant full-length spike protein and nucleoprotein were digested and proteotypic peptides were selected for parallel reaction monitoring (PRM) quantitation using a high-resolution Orbitrap instrument. A spectral library, which contained seven proteotypic peptides (four from spike protein and three from nucleoprotein) and the top three to four transitions, was generated and evaluated. From the original spectral library, we selected two best performing peptides for the final PRM assay. The assay was evaluated using mock test samples containing inactivated SARS-CoV-2 virions, added to in vitro derived mucus. The PRM assay provided a limit of detection of ∼200 attomoles and a limit of quantitation of ∼ 390 attomoles. Extrapolating from the test samples, the projected titer of virus particles necessary for the detection of SARS-CoV-2 spike and nucleoprotein detection was approximately 2 × 105 viral particles/mL, making it an attractive alternative to RT-PCR assays. Potentially, mass spectrometry-based methods for viral antigen detection may deliver higher throughput and could serve as a complementary diagnostic tool to RT-PCR. Furthermore, this assay could be used to evaluate the presence of SARS-CoV-2 in archived or recently collected biological fluids, in vitro-derived research materials, and wastewater samples.

A draft map of the human proteome.

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Actomyosin contraction during cellularization is regulated in part by Src64 control of Actin 5C protein levels.

Src64 is required for actomyosin contraction during cellularization of the Drosophila embryonic blastoderm. The mechanism of actomyosin ring constriction is poorly understood even though a number of cytoskeletal regulators have been implicated in the assembly, organization, and contraction of these microfilament rings. How these cytoskeletal processes are regulated during development is even less well understood. To investigate the role of Src64 as an upstream regulator of actomyosin contraction, we conducted a proteomics screen to identify proteins whose expression levels are controlled by src64. Global levels of actin are reduced in src64 mutant embryos. Furthermore, we show that reduction of the actin isoform Actin 5C causes defects in actomyosin contraction during cellularization similar to those caused by src64 mutation, indicating that a relatively high level of Actin 5C is required for normal actomyosin contraction and furrow canal structure. However, reduction of Actin 5C levels only slows down actomyosin ring constriction rather than preventing it, suggesting that src64 acts not only to modulate actin levels, but also to regulate the actomyosin cytoskeleton by other means.

Proteogenomic Annotation of Chinese Hamsters Reveals Extensive Novel Translation Events and Endogenous Retroviral Elements.

A high-quality genome annotation greatly facilitates successful cell line engineering. Standard draft genome annotation pipelines are based largely on de novo gene prediction, homology, and RNA-Seq data. However, draft annotations can suffer from incorrect predictions of translated sequence, inaccurate splice isoforms, and missing genes. Here, we generated a draft annotation for the newly assembled Chinese hamster genome and used RNA-Seq, proteomics, and Ribo-Seq to experimentally annotate the genome. We identified 3529 new proteins compared to the hamster RefSeq protein annotation and 2256 novel translational events (e.g., alternative splices, mutations, and novel splices). Finally, we used this pipeline to identify the source of translated retroviruses contaminating recombinant products from Chinese hamster ovary (CHO) cell lines, including 119 type-C retroviruses, thus enabling future efforts to eliminate retroviruses to reduce the costs incurred with retroviral particle clearance. In summary, the improved annotation provides a more accurate resource for CHO cell line engineering, by facilitating the interpretation of omics data, defining of cellular pathways, and engineering of complex phenotypes.

Quantitative Tyrosine Phosphoproteomics of Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitor-treated Lung Adenocarcinoma Cells Reveals Potential Novel Biomarkers of Therapeutic Response.

Mutations in the Epidermal growth factor receptor (EGFR) kinase domain, such as the L858R missense mutation and deletions spanning the conserved sequence 747LREA750, are sensitive to tyrosine kinase inhibitors (TKIs). The gatekeeper site residue mutation, T790M accounts for around 60% of acquired resistance to EGFR TKIs. The first generation EGFR TKIs, erlotinib and gefitinib, and the second generation inhibitor, afatinib are FDA approved for initial treatment of EGFR mutated lung adenocarcinoma. The predominant biomarker of EGFR TKI responsiveness is the presence of EGFR TKI-sensitizing mutations. However, 30-40% of patients with EGFR mutations exhibit primary resistance to these TKIs, underscoring the unmet need of identifying additional biomarkers of treatment response. Here, we sought to characterize the dynamics of tyrosine phosphorylation upon EGFR TKI treatment of mutant EGFR-driven human lung adenocarcinoma cell lines with varying sensitivity to EGFR TKIs, erlotinib and afatinib. We employed stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative mass spectrometry to identify and quantify tyrosine phosphorylated peptides. The proportion of tyrosine phosphorylated sites that had reduced phosphorylation upon erlotinib or afatinib treatment correlated with the degree of TKI-sensitivity. Afatinib, an irreversible EGFR TKI, more effectively inhibited tyrosine phosphorylation of a majority of the substrates. The phosphosites with phosphorylation SILAC ratios that correlated with the TKI-sensitivity of the cell lines include sites on kinases, such as EGFR-Y1197 and MAPK7-Y221, and adaptor proteins, such as SHC1-Y349/350, ERRFI1-Y394, GAB1-Y689, STAT5A-Y694, DLG3-Y705, and DAPP1-Y139, suggesting these are potential biomarkers of TKI sensitivity. DAPP1, is a novel target of mutant EGFR signaling and Y-139 is the major site of DAPP1 tyrosine phosphorylation. We also uncovered several off-target effects of these TKIs, such as MST1R-Y1238/Y1239 and MET-Y1252/1253. This study provides unique insight into the TKI-mediated modulation of mutant EGFR signaling, which can be applied to the development of biomarkers of EGFR TKI response.

Reverse and Random Decoy Methods for False Discovery Rate Estimation in High Mass Accuracy Peptide Spectral Library Searches.

Spectral library searching (SLS) is an attractive alternative to sequence database searching (SDS) for peptide identification due to its speed, sensitivity, and ability to include any selected mass spectra. While decoy methods for SLS have been developed for low mass accuracy peptide spectral libraries, it is not clear that they are optimal or directly applicable to high mass accuracy spectra. Therefore, we report the development and validation of methods for high mass accuracy decoy libraries. Two types of decoy libraries were found to be suitable for this purpose. The first, referred to as Reverse, constructs spectra by reversing a library's peptide sequences except for the C-terminal residue. The second, termed Random, randomly replaces all non-C-terminal residues and either retains the original C-terminal residue or replaces it based on the amino-acid frequency of the library's C-terminus. In both cases the m/z values of fragment ions are shifted accordingly. Determination of FDR is performed in a manner equivalent to SDS, concatenating a library with its decoy prior to a search. The utility of Reverse and Random libraries for target-decoy SLS in estimating false-positives and FDRs was demonstrated using spectra derived from a recently published synthetic human proteome project (Zolg, D. P.; et al. Nat. Methods 2017, 14, 259-262). For data sets from two large-scale label-free and iTRAQ experiments, these decoy building methods yielded highly similar score thresholds and spectral identifications at 1% FDR. The results were also found to be equivalent to those of using the decoy-free PeptideProphet algorithm. Using these new methods for FDR estimation, MSPepSearch, which is freely available search software, led to 18% more identifications at 1% FDR and 23% more at 0.1% FDR when compared with other widely used SDS engines coupled to postprocessing approaches such as Percolator. An application of these methods for FDR estimation for the recently reported "hybrid" library search (Burke, M. C.; et al. J. Proteome Res. 2017, 16, 1924-1935) method is also made. The application of decoy methods for high mass accuracy SLS permits the merging of these results with those of SDS, thereby increasing the assignment of more peptides, leading to deeper proteome coverage.

Correction to: Quantitative phosphoproteomic analysis reveals reciprocal activation of receptor tyrosine kinases between cancer epithelial cells and stromal fibroblasts.

[This corrects the article DOI: 10.1186/s12014-018-9197-x.].

Quantitative phosphoproteomic analysis reveals reciprocal activation of receptor tyrosine kinases between cancer epithelial cells and stromal fibroblasts.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are one of the most important components of tumor stroma and play a key role in modulating tumor growth. However, a mechanistic understanding of how CAFs communicate with tumor cells to promote their proliferation and invasion is far from complete. A major reason for this is that most current techniques and model systems do not capture the complexity of signal transduction that occurs between CAFs and tumor cells. METHODS: In this study, we employed a stable isotope labeling with amino acids in cell culture (SILAC) strategy to label invasive breast cancer cells, MDA-MB-231, and breast cancer patient-derived CAF this has already been defined above cells. We used an antibody-based phosphotyrosine peptide enrichment method coupled to LC-MS/MS to catalog and quantify tyrosine phosphorylation-mediated signal transduction events induced by the bidirectional communication between patient-derived CAFs and tumor cells. RESULTS: We discovered that distinct signaling events were activated in CAFs and in tumor epithelial cells during the crosstalk between these two cell types. We identified reciprocal activation of a number of receptor tyrosine kinases including EGFR, FGFR1 and EPHA2 induced by this bidirectional communication. CONCLUSIONS: Our study not only provides insights into the mechanisms of the interaction between CAFs and tumor cells, but the model system described here could be used as a prototype for analysis of intercellular communication in many different tumor microenvironments.

Statistical Models for the Analysis of Isobaric Tags Multiplexed Quantitative Proteomics.

Mass spectrometry is being used to identify protein biomarkers that can facilitate development of drug treatment. Mass spectrometry-based labeling proteomic experiments result in complex proteomic data that is hierarchical in nature often with small sample size studies. The generalized linear model (GLM) is the most popular approach in proteomics to compare protein abundances between groups. However, GLM does not address all the complexities of proteomics data such as repeated measures and variance heterogeneity. Linear models for microarray data (LIMMA) and mixed models are two approaches that can address some of these data complexities to provide better statistical estimates. We compared these three statistical models (GLM, LIMMA, and mixed models) under two different normalization approaches (quantile normalization and median sweeping) to demonstrate when each approach is the best for tagged proteins. We evaluated these methods using a spiked-in data set of known protein abundances, a systemic lupus erythematosus (SLE) data set, and simulated data from multiplexed labeling experiments that use tandem mass tags (TMT). Data are available via ProteomeXchange with identifier PXD005486. We found median sweeping to be a preferred approach of data normalization, and with this normalization approach there was overlap with findings across all methods with GLM being a subset of mixed models. The conclusion is that the mixed model had the best type I error with median sweeping, whereas LIMMA had the better overall statistical properties regardless of normalization approaches.

Lessons from the Hamster: Cricetulus griseus Tissue and CHO Cell Line Proteome Comparison.

Chinese hamster ovary cells represent the dominant host for therapeutic recombinant protein production. However, few large-scale data sets have been generated to characterize this host organism and derived CHO cell lines at the proteomics level. Consequently, an extensive label-free quantitative proteomics analysis of two cell lines (CHO-S and CHO DG44) and two Chinese hamster tissues (liver and ovary) was used to identify a total of 11 801 unique proteins containing at least two unique peptides. 9359 unique proteins were identified specifically in the cell lines, representing a 56% increase over previous work. Additionally, 6663 unique proteins were identified across liver and ovary tissues, providing the first Chinese hamster tissue proteome. Protein expression was more conserved within cell lines during both growth phases than across cell lines, suggesting large genetic differences across cell lines. Overall, both gene ontology and KEGG pathway analysis revealed enrichment of cell-cycle activity in cells. In contrast, upregulated molecular functions in tissue include glycosylation and lipid transporter activity. Furthermore, cellular components including Golgi apparatus are upregulated in both tissues. In conclusion, this large-scale proteomics analysis enables us to delineate specific changes between tissues and cells derived from these tissues, which can help explain specific tissue function and the adaptations cells incur for applications in biopharmaceutical productions.

Post-Translational Modifications (PTMs), Identified on Endogenous Huntingtin, Cluster within Proteolytic Domains between HEAT Repeats.

Post-translational modifications (PTMs) of proteins regulate various cellular processes. PTMs of polyglutamine-expanded huntingtin (Htt) protein, which causes Huntington's disease (HD), are likely modulators of HD pathogenesis. Previous studies have identified and characterized several PTMs on exogenously expressed Htt fragments, but none of them were designed to systematically characterize PTMs on the endogenous full-length Htt protein. We found that full-length endogenous Htt, which was immunoprecipitated from HD knock-in mouse and human post-mortem brain, is suitable for detection of PTMs by mass spectrometry. Using label-free and mass tag labeling-based approaches, we identified near 40 PTMs, of which half are novel (data are available via ProteomeXchange with identifier PXD005753). Most PTMs were located in clusters within predicted unstructured domains rather than within the predicted α-helical structured HEAT repeats. Using quantitative mass spectrometry, we detected significant differences in the stoichiometry of several PTMs between HD and WT mouse brain. The mass-spectrometry identification and quantitation were verified using phospho-specific antibodies for selected PTMs. To further validate our findings, we introduced individual PTM alterations within full-length Htt and identified several PTMs that can modulate its subcellular localization in striatal cells. These findings will be instrumental in further assembling the Htt PTM framework and highlight several PTMs as potential therapeutic targets for HD.

Plasma Selenium Protein P Isoform 1 (SEPP1): A Predictor of Selenium Status in Nepalese Children Detected by Plasma Proteomics.

Selenium deficiency or excess may have public health consequences, yet selenium status is infrequently characterized in populations, perhaps due to challenges in methodology. We are seeking to identify plasma proteins, using proteomics discovery and validation approaches, to serve as proxies for micronutrient status, including selenium, which may in the future be more readily assessed by robust, affordable field methods. In a sample of rural Nepalese children 6 - 8 years old (n = 500), the prevalence of selenium deficiency was 13.6 and 60.9 % at plasma selenium concentrations < 0.60 and < 0.89 µmol/L, respectively, assessed by atomic absorption spectroscopy. Relative abundance of selenoprotein P isoform 1 (SEPP1), glutathione reductase-3, and apolipoprotein A2 from discovery-based experiments was correlated with plasma selenium with a false discovery rate < 10 % (i. e., q < 0.10), all with p < 0.001. In linear mixed effects regression models to predict plasma selenium, only SEPP1 was significant (R2 = 0.63), estimating 8.2 % (95 % CI: 3.9 - 12.6) and 65.5(61.4 - 69.7)% of the in-sample population as deficient at each respective cut-off. Targeted quantification of SEPP1 in a preliminary series of specimens (n = 19) as a validation of the discovery approach revealed a high correlation with plasma selenium (r = 0.757, p = 0.0002). Plasma proteomics can identify valid plasma protein indicators of micronutrient status, as shown with selenium, comprising a step toward making population assessment of selenium status in vulnerable groups more accessible.

Quantitative Proteomic Analysis Reveals Similarities between Huntington's Disease (HD) and Huntington's Disease-Like 2 (HDL2) Human Brains.

The pathogenesis of HD and HDL2, similar progressive neurodegenerative disorders caused by expansion mutations, remains incompletely understood. No systematic quantitative proteomics studies, assessing global changes in HD or HDL2 human brain, were reported. To address this deficit, we used a stable isotope labeling-based approach to quantify the changes in protein abundances in the cortex of 12 HD and 12 control cases and, separately, of 6 HDL2 and 6 control cases. The quality of the tissues was assessed to minimize variability due to post mortem autolysis. We applied a robust median sweep algorithm to quantify protein abundance and performed statistical inference using moderated test statistics. 1211 proteins showed statistically significant fold changes between HD and control tissues; the differences in selected proteins were verified by Western blotting. Differentially abundant proteins were enriched in cellular pathways previously implicated in HD, including Rho-mediated, actin cytoskeleton and integrin signaling, mitochondrial dysfunction, endocytosis, axonal guidance, DNA/RNA processing, and protein transport. The abundance of 717 proteins significantly differed between control and HDL2 brain. Comparative analysis of the disease-associated changes in the HD and HDL2 proteomes revealed that similar pathways were altered, suggesting the commonality of pathogenesis between the two disorders.

Communication between the N and C termini is required for copper-stimulated Ser/Thr phosphorylation of Cu(I)-ATPase (ATP7B).

The Wilson disease protein ATP7B exhibits copper-dependent trafficking. In high copper, ATP7B exits the trans-Golgi network and moves to the apical domain of hepatocytes where it facilitates elimination of excess copper through the bile. Copper levels also affect ATP7B phosphorylation. ATP7B is basally phosphorylated in low copper and becomes more phosphorylated ("hyperphosphorylated") in elevated copper. The functional significance of hyperphosphorylation remains unclear. We showed that hyperphosphorylation occurs even when ATP7B is restricted to the trans-Golgi network. We performed comprehensive phosphoproteomics of ATP7B in low versus high copper, which revealed that 24 Ser/Thr residues in ATP7B could be phosphorylated, and only four of these were copper-responsive. Most of the phosphorylated sites were found in the N- and C-terminal cytoplasmic domains. Using truncation and mutagenesis, we showed that inactivation or elimination of all six N-terminal metal binding domains did not block copper-dependent, reversible, apical trafficking but did block hyperphosphorylation in hepatic cells. We showed that nine of 15 Ser/Thr residues in the C-terminal domain were phosphorylated. Inactivation of 13 C-terminal phosphorylation sites reduced basal phosphorylation and eliminated hyperphosphorylation, suggesting that copper binding at the N terminus propagates to the ATP7B C-terminal region. C-terminal mutants with either inactivating or phosphomimetic substitutions showed little effect upon copper-stimulated trafficking, indicating that trafficking does not depend on phosphorylation at these sites. Thus, our studies revealed that copper-dependent conformational changes in the N-terminal region lead to hyperphosphorylation at C-terminal sites, which seem not to affect trafficking and may instead fine-tune copper sequestration.

Annotation of the zebrafish genome through an integrated transcriptomic and proteomic analysis.

Accurate annotation of protein-coding genes is one of the primary tasks upon the completion of whole genome sequencing of any organism. In this study, we used an integrated transcriptomic and proteomic strategy to validate and improve the existing zebrafish genome annotation. We undertook high-resolution mass-spectrometry-based proteomic profiling of 10 adult organs, whole adult fish body, and two developmental stages of zebrafish (SAT line), in addition to transcriptomic profiling of six organs. More than 7,000 proteins were identified from proteomic analyses, and ∼ 69,000 high-confidence transcripts were assembled from the RNA sequencing data. Approximately 15% of the transcripts mapped to intergenic regions, the majority of which are likely long non-coding RNAs. These high-quality transcriptomic and proteomic data were used to manually reannotate the zebrafish genome. We report the identification of 157 novel protein-coding genes. In addition, our data led to modification of existing gene structures including novel exons, changes in exon coordinates, changes in frame of translation, translation in annotated UTRs, and joining of genes. Finally, we discovered four instances of genome assembly errors that were supported by both proteomic and transcriptomic data. Our study shows how an integrative analysis of the transcriptome and the proteome can extend our understanding of even well-annotated genomes.

The NHERF2 sequence adjacent and upstream of the ERM-binding domain affects NHERF2-ezrin binding and dexamethasone stimulated NHE3 activity.

In the brush border of intestinal and kidney epithelial cells, scaffolding proteins ezrin, Na(+)-H(+) exchanger regulatory factor (NHERF)1 and NHERF2 play important roles in linking transmembrane proteins to the cytoskeleton and assembling signalling regulatory complexes. The last 30 carboxyl residues of NHERF1 and NHERF2 form the EBDs [ezrin, radixin and moesin (ERM)-binding domain]. The current study found that NHERF1/2 contain an ERM-binding regulatory sequence (EBRS), which facilitates the interaction between the EBD and ezrin. The EBRSs are located within 24 and 19 residues immediately upstream of EBDs for NHERF1 and NHERF2 respectively. In OK (opossum kidney) epithelial cells, EBRSs are necessary along with the EBD to distribute NHERF1 and NHERF2 exclusively to the apical domain. Furthermore, phosphorylation of Ser(303) located in the EBRS of NHERF2, decreases the binding affinity for ezrin, dislocates apical NHERF2 into the cytosol and increases the NHERF2 microvillar mobility rate. Moreover, increased phosphorylation of Ser(303) was functionally significant preventing acute stimulation of NHE3 (Na(+)-H(+) exchanger 3) activity by dexamethasone.

Identifying novel targets of oncogenic EGF receptor signaling in lung cancer through global phosphoproteomics.

Mutations in the epidermal growth factor receptor (EGFR) kinase domain occur in 10-30% of lung adenocarcinoma and are associated with tyrosine kinase inhibitor (TKI) sensitivity. We sought to identify the immediate direct and indirect phosphorylation targets of mutant EGFRs in lung adenocarcinoma. We undertook SILAC strategy, phosphopeptide enrichment, and quantitative MS to identify dynamic changes of phosphorylation downstream of mutant EGFRs in lung adenocarcinoma cells harboring EGFR(L858R) and EGFR(L858R/T790M) , the TKI-sensitive, and TKI-resistant mutations, respectively. Top canonical pathways that were inhibited upon erlotinib treatment in sensitive cells, but not in the resistant cells include EGFR, insulin receptor, hepatocyte growth factor, mitogen-activated protein kinase, mechanistic target of rapamycin, ribosomal protein S6 kinase beta 1, and Janus kinase/signal transducer and activator of transcription signaling. We identified phosphosites in proteins of the autophagy network, such as ULK1 (S623) that is constitutively phosphorylated in these lung adenocarcinoma cells; phosphorylation is inhibited upon erlotinib treatment in sensitive cells, but not in resistant cells. Finally, kinase-substrate prediction analysis from our data indicated that substrates of basophilic kinases from, AGC and Calcium and calmodulin-dependent kinase groups, as well as STE group kinases were significantly enriched and those of proline-directed kinases from, CMGC and Casein kinase groups were significantly depleted among substrates that exhibited increased phosphorylation upon EGF stimulation and reduced phosphorylation upon TKI inhibition. This is the first study to date to examine global phosphorylation changes upon erlotinib treatment of lung adenocarcinoma cells and results from this study provide new insights into signaling downstream of mutant EGFRs in lung adenocarcinoma. All MS data have been deposited in the ProteomeXchange with identifier PXD001101 (http://proteomecentral.proteomexchange.org/dataset/PXD001101).

Quantitative phosphoproteomics reveals crosstalk between phosphorylation and O-GlcNAc in the DNA damage response pathway.

The modification of intracellular proteins by monosaccharides of O-linked ß-N-acetylglucosamine (O-GlcNAc) is an essential and dynamic PTM of metazoans. The addition and removal of O-GlcNAc is catalyzed by the O-GlcNAc transferase (OGT) and O-GlcNAcase, respectively. One mechanism by which O-GlcNAc is thought to mediate proteins is by regulating phosphorylation. To provide insight into the pathways regulated by O-GlcNAc, we have utilized SILAC-based quantitative proteomics to carry out comparisons of site-specific phosphorylation in OGT wild-type and Null cells. Quantitation of the phosphoproteome demonstrated that of 5529 phosphoserine, phosphothreonine, and phosphotyrosine sites, 232 phosphosites were upregulated and 133 downregulated in the absence of O-GlcNAc. Collectively, these data suggest that deletion of OGT has a profound effect on the phosphorylation of cell cycle and DNA damage response proteins. Key events were confirmed by biochemical analyses and demonstrate an increase in the activating autophosphorylation event on ATM (Ser1987) and on ATM's downstream targets p53, H2AX, and Chk2. Together, these data support widespread changes in the phosphoproteome upon removal of O-GlcNAc, suggesting that O-GlcNAc regulates processes such as the cell cycle, genomic stability, and lysosomal biogenesis. All MS data have been deposited in the ProteomeXchange with identifier PXD001153 (http://proteomecentral.proteomexchange.org/dataset/PXD001153).

Elucidation of the CHO Super-Ome (CHO-SO) by Proteoinformatics.

Chinese hamster ovary (CHO) cells are the preferred host cell line for manufacturing a variety of complex biotherapeutic drugs including monoclonal antibodies. We performed a proteomics and bioinformatics analysis on the spent medium from adherent CHO cells. Supernatant from CHO-K1 culture was collected and subjected to in-solution digestion followed by LC/LC-MS/MS analysis, which allowed the identification of 3281 different host cell proteins (HCPs). To functionally categorize them, we applied multiple bioinformatics tools to the proteins identified in our study including SignalP, TargetP, SecretomeP, TMHMM, WoLF PSORT, and Phobius. This analysis provided information on the presence of signal peptides, transmembrane domains, and cellular localization and showed that both secreted and intracellular proteins were constituents of the supernatant. Identified proteins were shown to be localized to the secretory pathway including ones playing roles in cell growth, proliferation, and folding as well as those involved in protein degradation and removal. After combining proteins predicted to be secreted or having a signal peptide, we identified 1015 proteins, which we termed as CHO supernatant-ome (CHO-SO), or superome. As a part of this effort, we created a publically accessible web-based tool called GO-CHO to functionally categorize proteins found in CHO-SO and identify enriched molecular functions, biological processes, and cellular components. We also used a tool to evaluate the immunogenicity potential of high-abundance HCPs. Among enriched functions were catalytic activity and structural constituents of the cytoskeleton. Various transport related biological processes, such as vesicle mediated transport, were found to be highly enriched. Extracellular space and vesicular exosome associated proteins were found to be the most enriched cellular components. The superome also contained proteins secreted from both classical and nonclassical secretory pathways. The work and database described in our study will enable the CHO community to rapidly identify high-abundance HCPs in their cultures and therefore help assess process and purification methods used in the production of biologic drugs.