XMAn v2-a database of Homo sapiens mutated peptides.

SUMMARY: The 'Unknown Mutation Analysis (XMAn)' database is a compilation of Homo sapiens mutated peptides in FASTA format, that was constructed for facilitating the identification of protein sequence alterations by tandem mass spectrometry detection. The database comprises 2 539 031 non-redundant mutated entries from 17 599 proteins, of which 2 377 103 are missense and 161 928 are nonsense mutations. It can be used in conjunction with search engines that seek the identification of peptide amino acid sequences by matching experimental tandem mass spectrometry data to theoretical sequences from a database. AVAILABILITY AND IMPLEMENTATION: XMAn v2 can be accessed from github.com/lazarlab/XMAnv2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Streamlined microfluidic analysis of phosphopeptides using stable isotope-labeled synthetic peptides and MRM-MS detection.

Modern high-throughput and high-content biological research is performed with advanced instrumentation and complex and time-consuming protocols, which, as a whole, pose a challenge for routine implementation in a research laboratory. In support of a "bioanalytical toolbox" with potential utility for exploring cellular functions mediated via protein phosphorylation-a post-translational modification (PTM) with essential regulatory roles in a variety of cellular processes-in this work, we describe the development of a simple, integrated microfluidic chip that can perform targeted, quantitative analysis of phosphopeptides involved in cancer-relevant signaling pathways. The microfluidic device comprises microreactors packed with C18 and TiO2 particles for on-chip solid phase extraction (SPE) and phosphopeptide enrichment, and an ESI interface for facilitating multiple reaction monitoring (MRM)-mass spectrometry (MS) detection. The chips are demonstrated for the detection of three phosphopeptides involved in ERBB2/MAPK signaling pathways, selected from the outcome of a proteomic study involving EGF stimulation of SKBR3/HER2+ breast cancer cells. The data demonstrate that the proposed microfluidic strategy can be used for the MS quantification of phosphopeptides in the low nM range from cell lysates without any prior sample pretreatment, fractionation or bioaffinity enrichment, and is generally applicable to the analysis of any phosphopeptide targets.

Partial enzymatic reactions: A missed opportunity in proteomics research.

RATIONALE: Biological studies are conducted at ever-increasing rates by relying on proteomic workflows. Although data acquisition by mass spectrometry is highly automated and rapid, sample preparation continues to be the bottleneck of developing high-throughput workflows. Enzymatic protein processing, in particular, involves time-consuming protocols that can extend from one day to another. To address this gap, we developed and evaluated simple, in-solution tryptic enzymatic reactions that unfold within a few minutes, and demonstrate the utility of the methodology for the rapid analysis of proteins originating from cancer cell extracts. METHODS: Tryptic enzymatic reactions were conducted for 7-60 min, and the results were compared with that of a routine approach conducted for 18 h. No other reaction conditions were changed relative to the 18 h procedure. The reaction products were analyzed by nanospray high-performance liquid chromatography/tandem mass spectrometry (nano-HPLC/MS/MS), and the quality of the products was assessed in terms of peptide/protein identifications, sequence coverage, peptide length, missed-cleavage sites, quality of generated ions, and peptide hydrophilic/hydrophobic properties. RESULTS: The results demonstrate that brief, and therefore incomplete, enzymatic processes lead to a large number of peptide fragments that improve protein sequence and proteome coverage, that the tandem mass spectra produced from these peptides are of high quality for reliable protein identifications, and that the physical properties of peptides are prone to supporting the development of alternative multi-dimensional separations and middle-down proteomics analysis strategies. The reproducibility of generating the same peptides within a few minutes of enzymatic digestion was remarkably close to that obtained from 18 h long reactions, and the combined results of short and long reactions increased proteome coverage by ~40%. CONCLUSIONS: We demonstrate that partial enzymatic reactions conducted on short time-scales represent a valuable asset to proteomic studies, and propose their implementation either as simple, cost-effective, stand-alone protocols for substantially streamlining the analysis of biological samples, or as complementary protocols, for improving protein sequence and proteome coverage.

Recurrent chimeric fusion RNAs in non-cancer tissues and cells.

Gene fusions and their products (RNA and protein) were once thought to be unique features to cancer. However, chimeric RNAs can also be found in normal cells. Here, we performed, curated and analyzed nearly 300 RNA-Seq libraries covering 30 different non-neoplastic human tissues and cells as well as 15 mouse tissues. A large number of fusion transcripts were found. Most fusions were detected only once, while 291 were seen in more than one sample. We focused on the recurrent fusions and performed RNA and protein level validations on a subset. We characterized these fusions based on various features of the fusions, and their parental genes. They tend to be expressed at higher levels relative to their parental genes than the non-recurrent ones. Over half of the recurrent fusions involve neighboring genes transcribing in the same direction. A few sequence motifs were found enriched close to the fusion junction sites. We performed functional analyses on a few widely expressed fusions, and found that silencing them resulted in dramatic reduction in normal cell growth and/or motility. Most chimeras use canonical splicing sites, thus are likely products of 'intergenic splicing'. We also explored the implications of these non-pathological fusions in cancer and in evolution.

Exploring the glycoproteomics landscape with advanced MS technologies.

The advance of glycoproteomic technologies has offered unique insights into the importance of glycosylation in determining the functional roles of a protein within a cell. Biologically active glycoproteins include the categories of enzymes, hormones, proteins involved in cell proliferation, cell membrane proteins involved in cell-cell recognition, and communication events or secreted proteins, just to name a few. The recent progress in analytical instrumentation, methodologies, and computational approaches has enabled a detailed exploration of glycan structure, connectivity, and heterogeneity, underscoring the staggering complexity of the glycome repertoire in a cell. A variety of approaches involving the use of spectroscopy, MS, separation, microfluidic, and microarray technologies have been used alone or in combination to tackle the glycoproteome challenge, the research results of these efforts being captured in an overwhelming number of annual publications. This work is aimed at reviewing the major developments and accomplishments in the field of glycoproteomics, with focus on the most recent advancements (2012-2014) that involve the use of capillary separations and MS detection.

XMAn: a Homo sapiens mutated-peptide database for the MS analysis of cancerous cell states.

To enable the identification of mutated peptide sequences in complex biological samples, in this work, two novel cancer- and disease-related protein databases with mutation information collected from several public resources such as COSMIC, IARC P53, OMIM, and UniProtKB were developed. In-house developed Perl scripts were used to search and process the data and to translate each gene-level mutation into a mutated peptide sequence. The cancer and disease mutation databases comprise a total of 872,125 and 27,148 peptide entries from 25 642 and 2913 proteins, respectively. A description line for each entry provides the parent protein ID and name, the cDNA- and protein-level mutation site and type, the originating database, and the disease or cancer tissue type and corresponding hits. The two databases are FASTA-formatted to enable data retrieval by commonly used tandem MS search engines. While the largest number of mutations were encountered for the amino acids A/D/E/G/L/P/R/S, the global mutation profiles replicate closely the outcome of the 1000 Genomes Project aimed at cataloguing natural mutations in the human population. The affected proteins were primarily involved in transcription regulation, splicing, protein synthesis/folding/binding, redox/energy production, adhesion/motility, and to some extent in DNA damage repair and signaling. The applicability of the database to identifying the presence of mutated peptides was investigated with MCF-7 breast cancer cell extracts.

Endogenous protein "barcode" for data validation and normalization in quantitative MS analysis.

Quantitative proteomic experiments with mass spectrometry detection are typically conducted by using stable isotope labeling and label-free quantitation approaches. Proteins with housekeeping functions and stable expression level such actin, tubulin, and glyceraldehyde-3-phosphate dehydrogenase are frequently used as endogenous controls. Recent studies have shown that the expression level of such common housekeeping proteins is, in fact, dependent on various factors such as cell type, cell cycle, or disease status and can change in response to a biochemical stimulation. The interference of such phenomena can, therefore, substantially compromise their use for data validation, alter the interpretation of results, and lead to erroneous conclusions. In this work, we advance the concept of a protein "barcode" for data normalization and validation in quantitative proteomic experiments. The barcode comprises a novel set of proteins that was generated from cell cycle experiments performed with MCF7, an estrogen receptor positive breast cancer cell line, and MCF10A, a nontumorigenic immortalized breast cell line. The protein set was selected from a list of ~3700 proteins identified in different cellular subfractions and cell cycle stages of MCF7/MCF10A cells, based on the stability of spectral count data generated with an LTQ ion trap mass spectrometer. A total of 11 proteins qualified as endogenous standards for the nuclear and 62 for the cytoplasmic barcode, respectively. The validation of the protein sets was performed with a complementary SKBR3/Her2+ cell line.

Proteomic study reveals a functional network of cancer markers in the G1-Stage of the breast cancer cell cycle.

BACKGROUND: Cancer cells are characterized by a deregulated cell cycle that facilitates abnormal proliferation by allowing cells to by-pass tightly regulated molecular checkpoints such as the G1/S restriction point. To facilitate early diagnosis and the identification of new drug targets, current research efforts focus on studies that could lead to the development of protein panels that collectively can improve the effectiveness of our response to the detection of a life-threatening disease. METHODS: Estrogen-responsive MCF-7 cells were cultured and arrested by serum deprivation in the G1-stage of the cell cycle, and fractionated into nuclear and cytoplasmic fractions. The protein extracts were trypsinized and analyzed by liquid chromatography--mass spectrometry (MS), and the data were interpreted with the Thermo Electron Bioworks software. Biological characterization of the data, selection of cancer markers, and identification of protein interaction networks was accomplished with a combination of bioinformatics tools provided by GoMiner, DAVID and STRING. RESULTS: The objective of this work was to explore via MS proteomic profiling technologies and bioinformatics data mining whether randomly identified cancer markers can be associated with the G1-stage of the cell cycle, i.e., the stage in which cancer cells differ most from normal cells, and whether any functional networks can be identified between these markers and placed in the broader context of cell regulatory pathways. The study enabled the identification of over 2000 proteins and 153 cancer markers, and revealed for the first time that the G1-stage of the cell cycle is not only a rich source of cancer markers, but also a host to an intricate network of functional relationships within the majority of these markers. Three major clusters of interacting proteins emerged: (a) signaling, (b) DNA repair, and (c) oxidative phosphorylation. CONCLUSIONS: The identification of cancer marker regulatory components that act not alone, but within networks, represents an invaluable resource for elucidating the moxlecular mechanisms that govern the uncontrolled proliferation of cancer cells, as well as for catalyzing the development of protein panels with biomarker and drug target potential, screening tests with improved sensitivity and specificity, and novel cancer therapies aimed at pursuing multiple drug targets.

Proteomic insights into breast cancer response to brain cell-secreted factors.

The most devastating feature of cancer cells is their ability to metastasize to distant sites in the body. HER2 + and TN breast cancers frequently metastasize to the brain and stay potentially dormant for years until favorable conditions support their proliferation. The sheltered and delicate nature of the brain prevents, however, early disease detection and effective delivery of therapeutic drugs. Moreover, the challenges associated with the acquisition of brain biopsies add compounding difficulties to exploring the mechanistic aspects of tumor development. To provide insights into the determinants of cancer cell behavior at the brain metastatic site, this study was aimed at exploring the early response of HER2 + breast cancer cells (SKBR3) to factors present in the brain perivascular niche. The neural microenvironment was simulated by using the secretome of a set of brain cells that come first in contact with the cancer cells upon crossing the blood brain barrier, i.e., endothelial cells, astrocytes, and microglia. Cytokine microarrays were used to investigate the secretome mediators of intercellular communication, and proteomic technologies for assessing the changes in the behavior of cancer cells upon exposure to the brain cell-secreted factors. The cytokines detected in the brain secretomes were supportive of inflammatory conditions, while the SKBR3 cells secreted numerous cancer-promoting growth factors that were either absent or present in lower abundance in the brain cell cultures, indicating that upon exposure the SKBR3 cells may have been deprived of favorable conditions for optimal growth. Altogether, the results suggest that the exposure of SKBR3 cells to the brain cell-secreted factors altered their growth potential and drove them toward a state of quiescence, with broader overall outcomes that affected cellular metabolism, adhesion and immune response processes. The findings of this study underscore the key role played by the neural niche in shaping the behavior of metastasized cancer cells, provide insights into the cellular cross-talk that may lead cancer cells into dormancy, and highlight novel opportunities for the development of metastatic breast cancer therapeutic strategies.

Proteomic Assessment of SKBR3/HER2+ Breast Cancer Cellular Response to Lapatinib and Investigational Ipatasertib Kinase Inhibitors.

Modern cancer treatment approaches aim at achieving cancer remission by using targeted and personalized therapies, as well as harnessing the power of the immune system to recognize and eliminate the cancer cells. To overcome a relatively short-lived response due to the development of resistance to the administered drugs, combination therapies have been pursued, as well. To expand the outlook of combination therapies, the objective of this study was to use high-throughput data generation technologies such as mass spectrometry and proteomics to investigate the response of HER2+ breast cancer cells to a mixture of two kinase inhibitors that has not been adopted yet as a standard treatment regime. The broader landscape of biological processes that are affected by inhibiting two major pathways that sustain the growth and survival of cancer cells, i.e., EGFR and PI3K/AKT, was investigated by treating SKBR3/HER2+ breast cancer cells with Lapatinib or a mixture of Lapatinib/Ipatasertib small molecule drugs. Changes in protein expression and/or activity in response to the drug treatments were assessed by using two complementary quantitative proteomic approaches based on peak area and peptide spectrum match measurements. Over 900 proteins matched by three unique peptide sequences (FDR<0.05) were affected by the exposure of cells to the drugs. The work corroborated the anti-proliferative activity of Lapatinib and Ipatasertib, and, in addition to cell cycle and growth arrest processes enabled the identification of several multi-functional proteins with roles in cancer-supportive hallmark processes. Among these, immune response, adhesion and migration emerged as particularly relevant to the ability to effectively suppress the proliferation and dissemination of cancer cells. The supplementation of Lapatinib with Ipatasertib further affected the expression or activity of additional transcription factors and proteins involved in gene expression, trafficking, DNA repair, and development of multidrug resistance. Furthermore, over fifty of the affected proteins represented approved or investigational targets in the DrugBank database, which through their protein-protein interaction networks can inform the selection of effective therapeutic partners. Altogether, our findings exposed a broad plethora of yet untapped opportunities that can be further explored for enhancing the anti-cancer effects of each drug as well as of many other multi-drug therapies that target the EGFR/ERBB2 and PI3K/AKT pathways. The data are available via ProteomeXchange with identifier PXD051094.

Proteomic snapshot of breast cancer cell cycle: G1/S transition point.

The biological processes that unfold during the G1-phase of the cell cycle are dependent on extracellular mitogenic factors that 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 more than 2700 proteins. Statistical evaluation of the normalized data resulted in the selection of proteins that displayed twofold or more 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.

Glycoproteomics on the rise: established methods, advanced techniques, sophisticated biological applications.

Glycosylation is the most complex form of protein PTMs. Affected proteins may carry dozens of glycosylation sites with tens to hundreds of glycan residues attached to every site. Glycosylated proteins have many important functions in biology, from cellular to organismal levels, being involved in cell-cell signaling, cell adhesion, immune response, host-pathogen interactions, and development and growth. Glycosylation, however, expands the biological functional diversity of proteins at the expense of a tremendous increase in structural heterogeneity. Aberrant glycosylation of cell surface proteins, as well as their detectable fingerprint in plasma samples, has been associated with cancer, inflammatory and degenerative diseases, and congenital disorders of glycosylation. Therefore, there are on-going efforts directed toward developing new technologies and approaches for glycan sequencing and high-throughput analysis of glycosylated proteins in complex samples with simultaneous characterization of both the protein and glycan moieties. This work is aimed primarily at pinpointing the challenges associated with the large-scale analysis of glycoproteins and the latest developments in glycoproteomic research, with focus on recent advancements (2011-2012) in microcolumn separations and MS detection.

Anti-inflammatory cytokine stimulation of HMC3 cells: Proteome dataset.

The immunoprotective functions of microglia in the brain are mediated by the inflammatory M1 phenotype. This phenotype is challenged by anti-inflammatory cytokines which polarize the microglia cells to an immunosuppressive M2 phenotype, a trait that is often exploited by cancer cells to evade immune recognition and promote tumor growth. Investigating the molecular determinants of this behavior is crucial for advancing the understanding of the mechanisms that cancer cells use to escape immune attack. In this article, we describe liquid chromatography (LC)-mass spectrometry (MS)/proteomic data acquired with an EASY-nanoLC 1200-Q ExactiveTM OrbitrapTM mass spectrometer that reflect the response of human microglia cells (HMC3) to stimulation with potential cancer-released anti-inflammatory cytokines known to be key players in promoting tumorigenesis in the brain (IL-4, IL-13, IL-10, TGFB and MCP-1). The MS files were processed with the Proteome Discoverer v.2.4 software package. The cell culture conditions, the sample preparation protocols, the MS acquisition parameters, and the data processing approach are described in detail. The RAW and processed MS files associated with this work were deposited in the PRIDE partner repository of the ProteomeXchange Consortium with the dataset identifiers PXD023163 and PXD023166, and the analyzed data in the Mendeley Data cloud-based repository with DOI 10.17632/fvhw2zwt5d.1. The biological interpretation of the data can be accessed in the research article "Systems-Level Proteomics Evaluation of Microglia Response to Tumor-Supportive Anti-inflammatory Cytokines" (Shreya Ahuja and Iulia M. Lazar, Frontiers in Immunology 2021 [1]). The proteome data described in this article will benefit researchers who are either interested in re-processing the data with alternative search engines and filtering criteria, and/or exploring the data in more depth to advance the understanding of cancer progression and the discovery of novel biomarkers or drug targets.

Proteomic Insights into Metastatic Breast Cancer Response to Brain Cell-Secreted Factors.

The most devastating feature of cancer cells is their ability to metastasize to distant sites in the body. HER2+ and triple negative breast cancers frequently metastasize to the brain and stay potentially dormant for years, clinging to the microvasculature, until favorable environmental conditions support their proliferation. The sheltered and delicate nature of the brain prevents, however, early disease detection, diagnosis, and effective delivery of therapeutic drugs. Moreover, the challenges associated with the acquisition of brain tissues and biopsies add compounding difficulties to exploring the mechanistic aspects of tumor development, leading to slow progress in understanding the drivers of disease progression and response to therapy. To provide insights into the determinants of cancer cell behavior at the brain metastatic site, this study was aimed at exploring the growth and initial response of HER2+ breast cancer cells (SKBR3) to factors present in the brain perivascular niche. The neural microenvironment conditions were simulated by using the secretome of a set of brain cells that come first in contact with the cancer cells upon crossing the blood brain barrier, i.e., human endothelial cells (HBEC5i), human astrocytes (NHA) and human microglia (HMC3) cells. Cytokine microarrays were used to investigate the cell secretomes and explore the mediators responsible for cell-cell communication, and proteomic technologies for assessing the changes in the behavior of cancer cells upon exposure to the brain cell-secreted factors. The results of the study suggest that the exposure of SKBR3 cells to the brain secretomes altered their growth potential and drove them towards a state of quiescence. The cytokines, growth factors and enzymes detected in the brain cell-conditioned medium were supportive of mostly inflammatory conditions, indicating a collective functional contribution to cell activation, defense, inflammatory responses, chemotaxis, adhesion, angiogenesis, and ECM organization. The SKBR3 cells, on the other hand, secreted numerous cancer-promoting growth factors that were either absent or present in lower abundance in the brain cell culture media, suggesting that upon exposure the SKBR3 cells were deprived of favorable environmental conditions required for optimal growth. The findings of this study underscore the key role played by the neural niche in shaping the behavior of metastasized cancer cells, providing insights into the cancer-host cell cross-talk that contributes to driving metastasized cancer cells into dormancy and into the opportunities that exist for developing novel therapeutic strategies that target the brain metastases of breast cancer.

The SKBR3 cell-membrane proteome reveals telltales of aberrant cancer cell proliferation and targets for precision medicine applications.

The plasma membrane proteome resides at the interface between the extra- and intra-cellular environment and through its various roles in signal transduction, immune recognition, nutrient transport, and cell-cell/cell-matrix interactions plays an absolutely critical role in determining the fate of a cell. Our work was aimed at exploring the cell-membrane proteome of a HER2+ breast-cancer cell line (SKBR3) to identify triggers responsible for uncontrolled cell proliferation and intrinsic resources that enable detection and therapeutic interventions. To mimic environmental conditions that enable cancer cells to evolve adaptation/survival traits, cell culture was performed under serum-rich and serum-deprived conditions. Proteomic analysis enabled the identification of ~ 2000 cell-membrane proteins. Classification into proteins with receptor/enzymatic activity, CD antigens, transporters, and cell adhesion/junction proteins uncovered overlapping roles in processes that drive cell growth, apoptosis, differentiation, immune response, adhesion and migration, as well as alternate pathways for proliferation. The large number of tumor markers (> 50) and putative drug targets (> 100) exposed a vast potential for yet unexplored detection and targeting opportunities, whereas the presence of 15 antigen immunological markers enabled an assessment of epithelial, mesenchymal or stemness characteristics. Serum-starved cells displayed altered processes related to mitochondrial OXPHOS/ATP synthesis, protein folding and localization, while serum-treated cells exhibited attributes that support tissue invasion and metastasis. Altogether, our findings advance the understanding of the biological triggers that sustain aberrant cancer cell proliferation, survival and development of resistance to therapeutic drugs, and reveal vast innate opportunities for guiding immunological profiling and precision medicine applications aimed at target selection or drug discovery.

Mapping the cell-membrane proteome of the SKBR3/HER2+ cell line to the cancer hallmarks.

The hallmarks of biological processes that underlie the development of cancer have been long recognized, yet, existing therapeutic treatments cannot prevent cancer from continuing to be one of the leading causes of death worldwide. This work was aimed at exploring the extent to which the cell-membrane proteins are implicated in triggering cancer hallmark processes, and assessing the ability to pinpoint tumor-specific therapeutic targets through a combined membrane proteome/cancer hallmark perspective. By using GO annotations, a database of human proteins associated broadly with ten cancer hallmarks was created. Cell-membrane cellular subfractions of SKBR3/HER2+ breast cancer cells, used as a model system, were analyzed by high resolution mass spectrometry, and high-quality proteins (FDR<3%) identified by at least two unique peptides were mapped to the cancer hallmark database. Over 1,400 experimentally detected cell-membrane or cell-membrane associated proteins, representing ~18% of the human cell-membrane proteome, could be matched to the hallmark database. Representative membrane constituents such as receptors, CDs, adhesion and transport proteins were distributed over the entire genome and present in every hallmark category. Sustained proliferative signaling/cell cycle, adhesion/tissue invasion, and evasion of immune destruction emerged as prevalent hallmarks represented by the membrane proteins. Construction of protein-protein interaction networks uncovered a high level of connectivity between the hallmark members, with some receptor (EGFR, ERBB2, FGFR, MTOR, CSF1R), antigen (CD44), and adhesion (MUC1) proteins being implicated in most hallmark categories. An illustrative subset of 138 hallmark proteins that included 42 oncogenes, 24 tumor suppressors, 9 oncogene/tumor suppressor, and 45 approved drug targets was subjected to a more in-depth analysis. The existing drug targets were implicated mainly in signaling processes. Network centrality analysis revealed that nodes with high degree, rather than betweenness, represent a good resource for informing the selection of putative novel drug targets. Through heavy involvement in supporting cancer hallmark processes, we show that the functionally diverse and networked landscape of cancer cell-membrane proteins fosters unique opportunities for guiding the development of novel therapeutic interventions, including multi-agent, immuno-oncology and precision medicine applications.

Impact of peptide modifications on the isobaric tags for relative and absolute quantitation method accuracy.

In this study, the impact of amino acid modifications on the accuracy of the iTRAQ (isobaric tags for relative and absolute quantitation) method was evaluated. MCF-7 breast cancer cells, cultured in the presence of 17ß-estradiol and tamoxifen, were used as a model system. The cells were labeled and analyzed by reversed-phase liquid chromatography and pulsed Q dissociation ion trap tandem mass spectrometry detection. Database searching was performed by using various combinations of amino acid modification allowances, i.e, Lys/Tyr/Cys and amino terminal iTRAQ labeling, Lys methylation, acetylation and carbamylation, and Cys/Met oxidation. Other than the intended Lys/amino terminal iTRAQ labeling, such modifications occur as a result of either enzymatic or sample preparation related reactions and are typically ignored in quantitation analysis to minimize the rate of false-positive peptide identifications. The study revealed that the modifications with the greatest impact on protein identification and quantitation pertain to Lys and Tyr amino acid residues, that by enabling such modifications the number and type of identified proteins will change (by up to 10%), and that the rate of false-positive protein identifications can be maintained below an upper threshold of 5% if appropriate data filtering conditions are used. In addition, the interference of possible posttranslational modifications (i.e., phosphorylation) with iTRAQ quantitation was examined.

Recent advances in the MS analysis of glycoproteins: Theoretical considerations.

Protein glycosylation is involved in a broad range of biological processes that regulate protein function and control cell fate. As aberrant glycosylation has been found to be implicated in numerous diseases, the study and large-scale characterization of protein glycosylation is of great interest not only to the biological and biomedical research community, but also to the pharmaceutical and biotechnology industry. Due to the complex chemical structure and differing chemical properties of the protein/peptide and glycan moieties, the analysis and structural characterization of glycoproteins has been proven to be a difficult task. Large-scale endeavors have been further limited by the dynamic outcome of the glycosylation process itself, and, occasionally, by the low abundance of glycoproteins in biological samples. Recent advances in MS instrumentation and progress in miniaturized technologies for sample handling, enrichment and separation, have resulted in robust and compelling analysis strategies that effectively address the challenges of the glycoproteome. This review summarizes the key steps that are involved in the development of efficient glycoproteomic analysis methods, and the latest innovations that led to successful strategies for the characterization of glycoproteins and their corresponding glycans. As a follow-up to this work, we review innovative capillary and microfluidic-MS workflows for the identification, sequencing and characterization of glycoconjugates.

Recent advances in the MS analysis of glycoproteins: Capillary and microfluidic workflows.

Recent developments in bioanalytical instrumentation, MS detection, and computational data analysis approaches have provided researchers with capabilities for interrogating the complex cellular glycoproteome, to help gain a better insight into the cellular and physiological processes that are associated with a disease and to facilitate the efforts centered on identifying disease-specific biomarkers. This review describes the progress achieved in the characterization of protein glycosylation by using advanced capillary and microfluidic MS technologies. The major steps involved in large-scale glycoproteomic analysis approaches are discussed, with special emphasis given to workflows that have evolved around complex MS detection functions. In addition, quantitative analysis strategies are assessed, and the bioinformatics aspects of glycoproteomic data processing are summarized. The developments in commercial and custom fabricated microfluidic front-end platforms to ESI- and MALDI-MS instrumentation, for addressing major challenges in carbohydrate analysis such as sensitivity, throughput, and ability to perform structural characterization, are further evaluated and illustrated with relevant examples.