A highly multiplexed quantitative phosphosite assay for biology and preclinical studies.

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.

A CRISPR Screen Reveals Resistance Mechanisms to CD3-Bispecific Antibody Therapy.

CD3-bispecific antibodies represent an important therapeutic strategy in oncology. These molecules work by redirecting cytotoxic T cells to antigen-bearing tumor cells. Although CD3-bispecific antibodies have been developed for several clinical indications, cases of cancer-derived resistance are an emerging limitation to the more generalized application of these molecules. Here, we devised whole-genome CRISPR screens to identify cancer resistance mechanisms to CD3-bispecific antibodies across multiple targets and cancer types. By validating the screen hits, we found that deficiency in IFNγ signaling has a prominent role in cancer resistance. IFNγ functioned by stimulating the expression of T-cell killing-related molecules in a cell type-specific manner. By assessing resistance to the clinical CD3-bispecific antibody flotetuzumab, we identified core fucosylation as a critical pathway to regulate flotetuzumab binding to the CD123 antigen. Disruption of this pathway resulted in significant resistance to flotetuzumab treatment. Proper fucosylation of CD123 was required for its normal biological functions. In order to treat the resistance associated with fucosylation loss, flotetuzumab in combination with an alternative targeting CD3-bispecific antibody demonstrated superior efficacy. Together, our study reveals multiple mechanisms that can be targeted to enhance the clinical potential of current and future T-cell-engaging CD3-bispecific antibody therapies.

Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

TRPS1 Is a Lineage-Specific Transcriptional Dependency in Breast Cancer.

Perturbed epigenomic programs play key roles in tumorigenesis, and chromatin modulators are candidate therapeutic targets in various human cancer types. To define singular and shared dependencies on DNA and histone modifiers and transcription factors in poorly differentiated adult and pediatric cancers, we conducted a targeted shRNA screen across 59 cell lines of 6 cancer types. Here, we describe the TRPS1 transcription factor as a strong breast cancer-specific hit, owing largely to lineage-restricted expression. Knockdown of TRPS1 resulted in perturbed mitosis, apoptosis, and reduced tumor growth. Integrated analysis of TRPS1 transcriptional targets, chromatin binding, and protein interactions revealed that TRPS1 is associated with the NuRD repressor complex. These findings uncover a transcriptional network that is essential for breast cancer cell survival and propagation.

Integrated microscale analysis system for targeted liquid chromatography mass spectrometry proteomics on limited amounts of enriched cell populations.

Limited samples, such as those that are in vivo sourced via biopsy, are closely representative of biological systems and contain valuable information for drug discovery. However, these precious samples are often heterogeneous and require cellular prefractionation prior to proteomic analysis to isolate specific subpopulations of interest. Enriched cells from in vivo samples are often very limited (<10(4) cells) and pose a significant challenge to proteomic nanoliquid chromatography mass spectrometry (nanoLCMS) sample preparation. To enable the streamlined analysis of these limited samples, we have developed an online cell enrichment, microscale sample preparation, nanoLCMS proteomics workflow by integrating fluorescence activated cell sorting (FACS), focused ultrasonication, microfluidics, immobilized trypsin digestion, and nanoLCMS. To assess the performance of the online FACS-Chip-LCMS workflow, 5000 fluorescent labeled cells were enriched from a 5% heterogeneous cell population and processed for LCMS proteomics in less than 2 h. Within these 5000 enriched cells, 30 peptides corresponding to 17 proteins spanning more than 4 orders of magnitude of cellular abundance were quantified using a QExactive MS. The results from the online FACS-Chip-LCMS workflow starting from 5000 enriched cells were directly compared to results from a traditional macroscale sample preparation workflow starting from 2.0 × 10(6) cells. The microscale FACS-Chip-LCMS workflow demonstrated high cellular enrichment efficiency and high peptide recovery across the wide dynamic range of targeted peptides. Overall the microscale FACS-Chip-LCMS workflow has shown effectiveness in efficiently preparing limited amounts of FACS enriched cells in an online manner for proteomic LCMS.

Human folliculin delays cell cycle progression through late S and G2/M-phases: effect of phosphorylation and tumor associated mutations.

The Birt-Hogg-Dube disease occurs as a result of germline mutations in the human Folliculin gene (FLCN), and is characterized by clinical features including fibrofolliculomas, lung cysts and multifocal renal neoplasia. Clinical and genetic evidence suggest that FLCN acts as a tumor suppressor gene. The human cell line UOK257, derived from the renal cell carcinoma of a patient with a germline mutation in the FLCN gene, harbors a truncated version of the FLCN protein. Reconstitution of the wild type FLCN protein into UOK257 cells delays cell cycle progression, due to a slower progression through the late S and G2/M-phases. Similarly, Flcn (-/-) mouse embryonic fibroblasts progress more rapidly through the cell cycle than wild type controls (Flcn (flox/flox)). The reintroduction of tumor-associated FLCN mutants (FLCN ΔF157, FLCN 1-469 or FLCN K508R) fails to delay cell cycle progression in UOK257 cells. Additionally, FLCN phosphorylation (on Serines 62 and 73) fluctuates throughout the cell cycle and peaks during the G2/M phase in cells treated with nocodazole. In keeping with this observation, the reintroduction of a FLCN phosphomimetic mutant into the UOK257 cell line results in faster progression through the cell cycle compared to those expressing the wild type FLCN protein. These findings suggest that the tumor suppression function of FLCN may be linked to its impact on the cell cycle and that FLCN phosphorylation is important for this activity. Additionally, these observations describe a novel in vitro assay for testing the functional significance of FLCN mutations and/or genetic polymorphisms.

Integrated proteomic, transcriptomic, and biological network analysis of breast carcinoma reveals molecular features of tumorigenesis and clinical relapse.

Gene and protein expression changes observed with tumorigenesis are often interpreted independently of each other and out of context of biological networks. To address these limitations, this study examined several approaches to integrate transcriptomic and proteomic data with known protein-protein and signaling interactions in estrogen receptor positive (ER+) breast cancer tumors. An approach that built networks from differentially expressed proteins and identified among them networks enriched in differentially expressed genes yielded the greatest success. This method identified a set of genes and proteins linking pathways of cellular stress response, cancer metabolism, and tumor microenvironment. The proposed network underscores several biologically intriguing events not previously studied in the context of ER+ breast cancer, including the overexpression of p38 mitogen-activated protein kinase and the overexpression of poly(ADP-ribose) polymerase 1. A gene-based expression signature biomarker built from this network was significantly predictive of clinical relapse in multiple independent cohorts of ER+ breast cancer patients, even after correcting for standard clinicopathological variables. The results of this study demonstrate the utility and power of an integrated quantitative proteomic, transcriptomic, and network analysis approach to discover robust and clinically meaningful molecular changes in tumors.

Microproteomic analysis of 10,000 laser captured microdissected breast tumor cells using short-range sodium dodecyl sulfate-polyacrylamide gel electrophoresis and porous layer open tubular liquid chromatography tandem mass spectrometry.

Precise proteomic profiling of limited levels of disease tissue represents an extremely challenging task. Here, we present an effective and reproducible microproteomic workflow for sample sizes of only 10,000 cells that integrates selective sample procurement via laser capture microdissection (LCM), sample clean-up and protein level fractionation using short-range SDS-PAGE, followed by ultrasensitive LC-MS/MS analysis using a 10 µm i.d. porous layer open tubular (PLOT) column. With 10,000 LCM captured mouse hepatocytes for method development and performance assessment, only 10% of the in-gel digest, equivalent to ∼1000 cells, was needed per LC-MS/MS analysis. The optimized workflow was applied to the differential proteomic analysis of 10,000 LCM collected primary and metastatic breast cancer cells from the same patient. More than 1100 proteins were identified from each injection with >1700 proteins identified from three LCM samples of 10,000 cells from the same patient (1123 with at least two unique peptides). Label free quantitation (spectral counting) was performed to identify differential protein expression between the primary and metastatic cell populations. Informatics analysis of the resulting data indicated that vesicular transport and extracellular remodeling processes were significantly altered between the two cell types. The ability to extract meaningful biological information from limited, but highly informative cell populations demonstrates the significant benefits of the described microproteomic workflow.

Ultrasensitive characterization of site-specific glycosylation of affinity-purified haptoglobin from lung cancer patient plasma using 10 µm i.d. porous layer open tubular liquid chromatography-linear ion trap collision-induced dissociation/electron transfer dissociation mass spectrometry.

Site-specific analysis of protein glycosylation is important for biochemical and clinical research efforts. Glycopeptide analysis using liquid chromatography-collision-induced dissociation/electron transfer dissociation mass spectrometry (LC-CID/ETD-MS) allows simultaneous characterization of the glycan structure and attached peptide site. However, due to the low ionization efficiency of glycopeptides during electrospray ionization, 200-500 fmol of sample per injection is needed for a single LC-MS run, which makes it challenging for the analysis of limited amounts of glycoprotein purified from biological matrixes. To improve the sensitivity of LC-MS analysis for glycopeptides, an ultranarrow porous layer open tubular (PLOT) LC column (2.5 m × 10 µm i.d.) was coupled to a linear ion trap (LTQ) collision-induced dissociation/electron transfer dissociation mass spectrometer to provide sensitive analysis of N-linked protein glycosylation heterogeneity. The potential of the developed method is demonstrated by the characterization of site-specific glycosylation using haptoglobin (Hpt) as a model protein. To limit the amount of haptoglobin to low picomole amounts of protein, we affinity purified it from 1 µL of pooled lung cancer patient plasma. A total of 26 glycoforms/glycan compositions on three Hpt tryptic glycopeptides were identified and quantified from 10 LC-MS runs with a consumption of 100 fmol of Hpt digest (13 ng of protein, 10 fmol per injection). Included in this analysis was the determination of the glycan occupancy level. At this sample consumption level, the high sensitivity of the PLOT LC-LTQ-CID/ETD-MS system allowed glycopeptide identification and structure determination, along with relative quantitation of glycans presented on the same peptide backbone, even for low abundant glycopeptides at the ∼100 amol level. The PLOT LC-MS system is shown to have sufficient sensitivity to allow characterization of site-specific protein glycosylation from trace levels of glycosylated proteins.

Substrates of the Arabidopsis thaliana protein isoaspartyl methyltransferase 1 identified using phage display and biopanning.

The role of protein isoaspartyl methyltransferase (PIMT) in repairing a wide assortment of damaged proteins in a host of organisms has been inferred from the affinity of the enzyme for isoaspartyl residues in a plethora of amino acid contexts. The identification of PIMT target proteins in plant seeds, where the enzyme is highly active and proteome long-lived, has been hindered by large amounts of isoaspartate-containing storage proteins. Mature seed phage display libraries circumvented this problem. Inclusion of the PIMT co-substrate, S-adenosylmethionine (AdoMet), during panning permitted PIMT to retain aged phage in greater numbers than controls lacking co-substrate or when PIMT protein binding was poisoned with S-adenosyl homocysteine. After four rounds, phage titer plateaued in AdoMet-containing pans, whereas titer declined in both controls. This strategy identified 17 in-frame PIMT target proteins, including a cupin-family protein similar to those identified previously using on-blot methylation. All recovered phage had at least one susceptible Asp or Asn residue. Five targets were recovered independently. Two in-frame targets were produced in Escherichia coli as recombinant proteins and shown by on-blot methylation to acquire isoAsp, becoming a PIMT target. Both gained isoAsp rapidly in solution upon thermal insult. Mutant analysis of plants deficient in any of three in-frame PIMT targets resulted in demonstrable phenotypes. An over-representation of clones encoding proteins involved in protein production suggests that the translational apparatus comprises a subgroup for which PIMT-mediated repair is vital for orthodox seed longevity. Impaired PIMT activity would hinder protein function in these targets, possibly resulting in poor seed performance.

In situ proteomic analysis of human breast cancer epithelial cells using laser capture microdissection: annotation by protein set enrichment analysis and gene ontology.

Identification of molecular signatures that allow detection of the transition from normal breast epithelial cells to malignant invasive cells is a critical component in the development of diagnostic, therapeutic, and preventative strategies for human breast cancer. Substantial efforts have been devoted to deciphering breast cancer etiology at the genome level, but only a limited number of studies have appeared at the proteome level. In this work, we compared individual in situ proteome profiles of nonpatient matched nine noncancerous, normal breast epithelial (NBE) samples with nine estrogen receptor (ER)-positive (luminal subtype), invasive malignant breast epithelial (MBE) samples by combining laser capture microdissection (LCM) and quantitative shotgun proteomics. A total of 12,970 unique peptides were identified from the 18 samples, and 1623 proteins were selected for quantitative analysis using spectral index (SpI) as a measure of protein abundance. A total of 298 proteins were differentially expressed between NBE and MBE at 95% confidence level, and this differential expression correlated well with immunohistochemistry (IHC) results reported in the Human Protein Atlas (HPA) database. To assess pathway level patterns in the observed expression changes, we developed protein set enrichment analysis (PSEA), a modification of a well-known approach in gene expression analysis, Gene Set Enrichment Analysis (GSEA). Unlike single gene-based functional term enrichment analyses that only examines pathway overrepresentation of proteins above a given significance threshold, PSEA applies a weighted running sum statistic to the entire expression data to discover significantly enriched protein groups. Application of PSEA to the expression data in this study revealed not only well-known ER-dependent and cellular morphology-dependent protein abundance changes, but also significant alterations of downstream targets for multiple transcription factors (TFs), suggesting a role for specific gene regulatory pathways in breast tumorigenesis. A parallel GOMiner analysis revealed both confirmatory and complementary data to PSEA. The combination of the two annotation approaches yielded extensive biological feature mapping for in depth analysis of the quantitative proteomic data.

Shotgun proteomic analysis of yeast-elicited California poppy (Eschscholzia californica) suspension cultures producing enhanced levels of benzophenanthridine alkaloids.

The California poppy, Eschscholzia californica, produces benzophenanthridine alkaloids (BPAs), an important class of biologically active compounds. Cell cultures of E. californica were investigated as an alternative and scalable method for producing these valuable compounds; treatment with yeast extract increased production from low levels to 23 mg/g dry weight (DW) of BPAs. A shotgun proteomic analysis of E. californica cell cultures was undertaken to explore changes in metabolism associated with enhanced BPA production. We implemented differential centrifugation and then shotgun proteomics based on nanoliquid chromatography/mass spectrometry (nano-LC-MS/MS) for peptide separation and analysis. A unigene database available for E. californica was translated and utilized for protein identification. Approximately 646 proteins (3% false discovery rate at the protein level) were identified. Differentially abundant proteins observed with elicitation included enzymes involved in (S)-adenosyl methionine (SAM) biosynthesis and BPA biosynthesis. These results demonstrate (1) the identification of proteins from a medicinal plant using shotgun proteomics combined with a well-annotated, translated unigene database and (2) the potential utility of proteomics for exploring changes in metabolism associated with enhanced secondary metabolite production.

Desulfurization of cysteine-containing peptides resulting from sample preparation for protein characterization by mass spectrometry.

In this study, we have examined two cysteine modifications resulting from sample preparation for protein characterization by mass spectrometry (MS): (1) a previously observed conversion of cysteine into dehydroalanine, now found in the case of disulfide mapping and (2) a novel modification corresponding to conversion of cysteine into alanine. Using model peptides, the conversion of cysteine into dehydroalanine via beta-elimination of a disulfide bond was seen to result from the conditions of typical tryptic digestion (37 degrees C, pH 7.0-9.0) without disulfide reduction and alkylation. Furthermore, the surprising conversion of cysteine into alanine was shown to occur by heating cysteine-containing peptides in the presence of a phosphine (tris(2-carboxyethyl)phosphine hydrochloride (TCEP)). The formation of alanine from cysteine, investigated by performing experiments in H(2)O or D(2)O, suggested a radical-based desulfurization mechanism unrelated to beta-elimination. Importantly, an understanding of the mechanism and conditions favorable for cysteine desulfurization provides insight for the establishment of improved sample preparation procedures of protein analysis.

Profiling the glycoforms of the intact alpha subunit of recombinant human chorionic gonadotropin by high-resolution capillary electrophoresis-mass spectrometry.

With the rapid growth of complex heterogeneous biological molecules, effective techniques that are capable of rapid characterization of biologics are essential to ensure the desired product characteristics. To address this need, we have developed a method for analysis of intact glycoproteins based on high-resolution capillary electrophoretic separation coupled to an LTQ-FT mass spectrometer. We evaluated the performance of this method on the alpha subunit of mouse cell line-derived recombinant human chorionic gonadotrophin (r-alpha hCG), a protein that is glycosylated at two sites and is part of the clinically relevant gonadotrophin family. Analysis of r-alpha hCG, using capillary electrophoresis (CE) with a separation time under 20 min, resulted in the identification of over 60 different glycoforms with up to nine sialic acids. High-resolution CE-Fourier transform mass spectrometry (FT-MS) allowed separation and analysis of not only intact glycoforms with different numbers of sialic acids but also intact glycoforms that differed by the number and extent of neutral monosaccharides. The high mass resolution of the FT-MS enabled a limited mass range to be targeted for the examination of the protein glycoforms, simplifying the analysis without sacrificing accuracy. In addition, the limited mass range resulted in a fast scan speed that enhanced the reproducibility of the relative quantitation of individual glycoforms. The intact glycoprotein analysis was complemented with the analysis of the tryptic glycopeptides and glycans of r-alpha hCG to enable the assignment of glycan structures to individual sites, resulting in a detailed characterization of the protein. Samples of r-alpha hCG obtained from a CHO cell line were also analyzed and briefly shown to be significantly different from the murine cell line product. Taken together, the results suggest that the CE coupled to high-resolution FT-MS can be one of the effective tools for in-process monitoring as well as for final product characterization.

CLUE-TIPS, clustering methods for pattern analysis of LC-MS data.

Liquid Chromatography Mass Spectrometry (LC-MS) based proteomics is an important tool in detecting changes in peptide/protein abundances in samples potentially leading to the discovery of disease biomarker candidates. We present CLUE-TIPS (Clustering Using Euclidean distance in Tanimoto Inter-Point Space), an approach that compares complex proteomic samples for similarity/dissimilarity analysis. In CLUE-TIPS, an intersample distance feature map is generated from filtered, aligned and binarized raw LC-MS data by applying the Tanimoto distance metric to obtain normalized similarity scores between all sample pairs for each m/z value. We developed clustering and visualization methods for the intersample distance map to analyze various samples for differences at the sample level as well as the individual m/z level. An approach to query for specific m/z values that are associated with similarity/dissimilarity patterns in a set of samples was also briefly described. CLUE-TIPS can also be used as a tool in assessing the quality of LC-MS runs. The presented approach does not rely on tandem mass-spectrometry (MS/MS), isotopic labels or gels and also does not rely on feature extraction methods. CLUE-TIPS suite was applied to LC-MS data obtained from plasma samples collected at various time points and treatment conditions from immunosuppressed mice implanted with MCF-7 human breast cancer cells. The generated raw LC-MS data was used for pattern analysis and similarity/dissimilarity detection. CLUE-TIPS successfully detected the differences/similarities in samples at various time points taken during the progression of tumor, and also recognized differences/similarities in samples representing various treatment conditions.

SeMoP: a new computational strategy for the unrestricted search for modified peptides using LC-MS/MS data.

A novel computational approach, termed Search for Modified Peptides (SeMoP), for the unrestricted discovery and verification of peptide modifications in shotgun proteomic experiments using low resolution ion trap MS/MS spectra is presented. Various peptide modifications, including post-translational modifications, sequence polymorphisms, as well as sample handling-induced changes, can be identified using this approach. SeMoP utilizes a three-step strategy: (1) a standard database search to identify proteins in a sample; (2) an unrestricted search for modifications using a newly developed algorithm; and (3) a second standard database search targeted to specific modifications found using the unrestricted search. This targeted approach provides verification of discovered modifications and, due to increased sensitivity, a general increase in the number of peptides with the specific modification. The feasibility of the overall strategy has been first demonstrated in the analysis of 65 plasma proteins. Various sample handling induced modifications, such as beta-elimination of disulfide bridges and pyrocarbamidomethylation, as well as biologically induced modifications, such as phosphorylation and methylation, have been detected. A subsequent targeted Sequest search has been used to verify selected modifications, and a 4-fold increase in the number of modified peptides was obtained. In a second application, 1367 proteins of a cervical cancer cell line were processed, leading to detection of several novel amino acid substitutions. By conducting the search against a database of peptides derived from proteins with decoy sequences, a false discovery rate of less than 5% for the unrestricted search resulted. SeMoP is shown to be an effective and easily implemented approach for the discovery and verification of peptide modifications.

Two-dimensional strong cation exchange/porous layer open tubular/mass spectrometry for ultratrace proteomic analysis using a 10 microm id poly(styrene- divinylbenzene) porous layer open tubular column with an on-line triphasic trapping column.

This study expands the capabilities for ultratrace proteomic analysis of our previous work by incorporating on-line sample desalting using a triphasic (RP/strong cation exchange (SCX)/micro-SPE) trapping column connected to a 3.2 m x 10 microm id poly(styrene-divinylbenzene) (PS-DVB) porous layer open tubular (PLOT) column. To minimize extra sample handling steps, C18 RP packing was incorporated in the capillary tubing upstream of the SCX column for the on-line desalting. For the micro-SPE column, a 50 microm id PS-DVB monolithic column was positioned downstream of the SCX column. High-performance separation was achieved on the PLOT column at a mobile phase flow rate of 20 nL/min. The sensitivity and high resolution capability of the new multidimensional platform was evaluated using an in-gel tryptic digested sample of a cervical cancer (SiHa) cell line. For the injected amount of 1200 cells ( approximately 500 ng), over 2700 peptides covering greater than 850 unique proteins were identified from the triphasic SCX/PLOT/MS analysis of a single SDS gel section (>40 kDa). The 2-D LC/MS platform demonstrated good separation performance, such that more than 85% of the identified peptides were detected from only one salt fraction. In a triplicate analysis of the above >40 kDa gel section, 4497 peptides and 1209 unique proteins were identified when applying stringent filtering criteria, with a false-positive rate of 2.4%. When all three SDS-PAGE gel sections of the lysed SiHa cells were analyzed, 5047 peptides and 1857 unique proteins (false-positive rate 1.8%), including cancer-related proteins such as MAP kinases, were identified.

N-Glycan structure annotation of glycopeptides using a linearized glycan structure database (GlyDB).

While glycoproteins are abundant in nature, and changes in glycosylation occur in cancer and other diseases, glycoprotein characterization remains a challenge due to the structural complexity of the biopolymers. This paper presents a general strategy, termed GlyDB, for glycan structure annotation of N-linked glycopeptides from tandem mass spectra in the LC-MS analysis of proteolytic digests of glycoproteins. The GlyDB approach takes advantage of low-energy collision-induced dissociation of N-linked glycopeptides that preferentially cleaves the glycosidic bonds while the peptide backbone remains intact. A theoretical glycan structure database derived from biosynthetic rules for N-linked glycans was constructed employing a novel representation of branched glycan structures consisting of multiple linear sequences. The commonly used peptide identification program, Sequest, could then be utilized to assign experimental tandem mass spectra to individual glycoforms. Analysis of synthetic glycopeptides and well-characterized glycoproteins demonstrate that the GlyDB approach can be a useful tool for annotation of glycan structures and for selection of a limited number of potential glycan structure candidates for targeted validation.

A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.

Quantitative proteomic and microarray analysis of the archaeon Methanosarcina acetivorans grown with acetate versus methanol.

Methanosarcina acetivorans strain C2A is an acetate- and methanol-utilizing methane-producing organism for which the genome, the largest yet sequenced among the Archaea, reveals extensive physiological diversity. LC linear ion trap-FTICR mass spectrometry was employed to analyze acetate- vs methanol-grown cells metabolically labeled with 14N vs 15N, respectively, to obtain quantitative protein abundance ratios. DNA microarray analyses of acetate- vs methanol-grown cells was also performed to determine gene expression ratios. The combined approaches were highly complementary, extending the physiological understanding of growth and methanogenesis. Of the 1081 proteins detected, 255 were > or =3-fold differentially abundant. DNA microarray analysis revealed 410 genes that were > or =2.5-fold differentially expressed of 1972 genes with detected expression. The ratios of differentially abundant proteins were in good agreement with expression ratios of the encoding genes. Taken together, the results suggest several novel roles for electron transport components specific to acetate-grown cells, including two flavodoxins each specific for growth on acetate or methanol. Protein abundance ratios indicated that duplicate CO dehydrogenase/acetyl-CoA complexes function in the conversion of acetate to methane. Surprisingly, the protein abundance and gene expression ratios indicated a general stress response in acetate- vs methanol-grown cells that included enzymes specific for polyphosphate accumulation and oxidative stress. The microarray analysis identified transcripts of several genes encoding regulatory proteins with identity to the PhoU, MarR, GlnK, and TetR families commonly found in the Bacteria domain. An analysis of neighboring genes suggested roles in controlling phosphate metabolism (PhoU), ammonia assimilation (GlnK), and molybdopterin cofactor biosynthesis (TetR). Finally, the proteomic and microarray results suggested roles for two-component regulatory systems specific for each growth substrate.