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Dynamics of protein turnover, a missing dimension in proteomics.

Functional genomic experiments frequently involve a comparison of the levels of gene expression between two or more genetic, developmental, or physiological states. Such comparisons can be carried out at either the RNA (transcriptome) or protein (proteome) level, but there is often a lack of congruence between parallel analyses using these two approaches. To fully interpret protein abundance data from proteomic experiments, it is necessary to understand the contributions made by the opposing processes of synthesis and degradation to the transition between the states compared. Thus, there is a need for reliable methods to determine the rates of turnover of individual proteins at amounts comparable to those obtained in proteomic experiments. Here, we show that stable isotope-labeled amino acids can be used to define the rate of breakdown of individual proteins by inspection of mass shifts in tryptic fragments. The approach has been applied to an analysis of abundant proteins in glucose-limited yeast cells grown in aerobic chemostat culture at steady state. The average rate of degradation of 50 proteins was 2.2%/h, although some proteins were turned over at imperceptible rates, and others had degradation rates of almost 10%/h. This range of values suggests that protein turnover is a significant missing dimension in proteomic experiments and needs to be considered when assessing protein abundance data and comparing it to the relative abundance of cognate mRNA species.

Amino Acids↗

Genomics and clinical medicine: rationale for creating and effectively evaluating animal models.

Because resolving human complex diseases is difficult, appropriate biomedical models must be developed and validated. In the past, researchers have studied diseases either by characterizing a human clinical disease and choosing the most appropriate animal model, or by characterizing a naturally occurring or induced mutant animal and identifying which human disease it best resembled. Although there has been a great deal of progress through the use of these methods, such models have intrinsic faults that limit their relevance to clinical medicine. The recent advent of techniques in molecular biology, genomics, transgenesis, and cloning furnishes investigators with the ability to study vertebrates (e.g., pigs, cows, chickens, dogs) with greater precision and utilize them as model organisms. Comparative and functional genomics and proteomics provide effective approaches for identifying the genetic and environmental factors responsible for complex diseases and in the development of prevention and treatment strategies and therapeutics. By identifying and studying homologous genes across species, researchers are able to accurately translate and apply experimental data from animal experiments to humans. This review supports the hypothesis that associated enabling technologies can be used to create, de novo, appropriate animal models that recapitulate the human clinical manifestation. Comparative and functional genomic and proteomic techniques can then be used to identify gene and protein functions and the interactions responsible for disease phenotypes, which aids in the development of prevention and treatment strategies.

Animals↗

Proteomic profiling of the aqueous extract from the antennal gland of the Pacific white shrimp, Litopenaeus vannamei.

The antennal gland (AnG) of decapod crustaceans has been proposed as a potential source of bioactive molecules involved in chemical communication; however, its protein composition remains largely unexplored. Here, we present the first reference proteomic map of the aqueous extract from the antennal gland of the Pacific white shrimp Litopenaeus vannamei. Protein extracts from immature and mature females were analyzed using an integrated workflow combining one-dimensional SDS-PAGE, reverse-phase high-performance liquid chromatography (RP-HPLC), and nanoLC-tandem mass spectrometry. Electrophoretic and chromatographic analyses revealed a high degree of qualitative similarity between reproductive stages. SDS-PAGE resolved six major protein bands (∼227, 166, 77, 42, 35, and 17 kDa), most comprising multiple co-migrating proteins as revealed by LC-MS/MS. Hemocyanin was identified as the predominant protein and was detected across several electrophoretic bands. Additional proteins were associated with innate immunity, including β-1,3-glucan-binding protein and coagulable hemolymph protein; reproductive processes, including vitellogenin, spermatogonial stem-cell renewal factor, farnesoic acid O-methyltransferase, estrogen sulfotransferase, and prostaglandin reductase 1; as well as energy metabolism, protein homeostasis, cytoskeletal organization, and intracellular trafficking. Because several identified proteins are widely distributed or known hemolymph components, their detection cannot be assumed to reflect AnG-specific expression or function. Collectively, these findings establish a molecular reference for the L. vannamei AnG and reveal protein components associated with multiple physiological processes. This dataset provides a proteomic framework for future comparative and functional studies aimed at elucidating antennal gland physiology and experimentally evaluating the potential involvement of proteinaceous or peptide-based molecules in chemical communication in decapod crustaceans.

Animals↗

A protein evolution model with independent sites that reproduces site-specific amino acid distributions from the Protein Data Bank.

BACKGROUND: Since thermodynamic stability is a global property of proteins that has to be conserved during evolution, the selective pressure at a given site of a protein sequence depends on the amino acids present at other sites. However, models of molecular evolution that aim at reconstructing the evolutionary history of macromolecules become computationally intractable if such correlations between sites are explicitly taken into account. RESULTS: We introduce an evolutionary model with sites evolving independently under a global constraint on the conservation of structural stability. This model consists of a selection process, which depends on two hydrophobicity parameters that can be computed from protein sequences without any fit, and a mutation process for which we consider various models. It reproduces quantitatively the results of Structurally Constrained Neutral (SCN) simulations of protein evolution in which the stability of the native state is explicitly computed and conserved. We then compare the predicted site-specific amino acid distributions with those sampled from the Protein Data Bank (PDB). The parameters of the mutation model, whose number varies between zero and five, are fitted from the data. The mean correlation coefficient between predicted and observed site-specific amino acid distributions is larger than = 0.70 for a mutation model with no free parameters and no genetic code. In contrast, considering only the mutation process with no selection yields a mean correlation coefficient of = 0.56 with three fitted parameters. The mutation model that best fits the data takes into account increased mutation rate at CpG dinucleotides, yielding = 0.90 with five parameters. CONCLUSION: The effective selection process that we propose reproduces well amino acid distributions as observed in the protein sequences in the PDB. Its simplicity makes it very promising for likelihood calculations in phylogenetic studies. Interestingly, in this approach the mutation process influences the effective selection process, i.e. selection and mutation must be entangled in order to obtain effectively independent sites. This interdependence between mutation and selection reflects the deep influence that mutation has on the evolutionary process: The bias in the mutation influences the thermodynamic properties of the evolving proteins, in agreement with comparative studies of bacterial proteomes, and it also influences the rate of accepted mutations.

Algorithms↗

Analysis of curated and predicted plastid subproteomes of Arabidopsis. Subcellular compartmentalization leads to distinctive proteome properties.

Carefully curated proteomes of the inner envelope membrane, the thylakoid membrane, and the thylakoid lumen of chloroplasts from Arabidopsis were assembled based on published, well-documented localizations. These curated proteomes were evaluated for distribution of physical-chemical parameters, with the goal of extracting parameters for improved subcellular prediction and subsequent identification of additional (low abundant) components of each membrane system. The assembly of rigorously curated subcellular proteomes is in itself also important as a parts list for plant and systems biology. Transmembrane and subcellular prediction strategies were evaluated using the curated data sets. The three curated proteomes differ strongly in average isoelectric point and protein size, as well as transmembrane distribution. Removal of the cleavable, N-terminal transit peptide sequences greatly affected isoelectric point and size distribution. Unexpectedly, the Cys content was much lower for the thylakoid proteomes than for the inner envelope. This likely relates to the role of the thylakoid membrane in light-driven electron transport and helps to avoid unwanted oxidation-reduction reactions. A rule of thumb for discriminating between the predicted integral inner envelope membrane and integral thylakoid membrane proteins is suggested. Using a combination of predictors and experimentally derived parameters, four plastid subproteomes were predicted from the fully annotated Arabidopsis genome. These predicted subproteomes were analyzed for their properties and compared to the curated proteomes. The sensitivity and accuracy of the prediction strategies are discussed. Data can be extracted from the new plastid proteome database (http://ppdb.tc.cornell.edu).

Arabidopsis↗

An integrated approach to identifying chemically induced posttranslational modifications using comparative MALDI-MS and targeted HPLC-ESI-MS/MS.

Identification of multiple and novel posttranslational modifications remains a major challenge in proteomics. The present approach uses comparative analysis by matrix-assisted laser/desorption ionization (MALDI) MS of proteolytic digests from control and treated proteins to target differences due to modifications, without initial assumption as to type or residue localization. Differences between modified and unmodified digest MS spectra highlight peptides of interest for subsequent tandem mass spectrometry (MS/MS) analysis. Targeted HPLC-electrospray ionization (ESI)-MS/MS is then used to fragment peptides, and manual de novo sequencing is used to determine the amino acid sequence and type of modification. This strategy for identifying posttranslational modifications in an unbiased manner is particularly useful for finding modifications produced by exogenous chemicals. Successful characterization of chemically induced posttranslational modifications and novel chemical adducts is given as an example of the use of this strategy. Histone H4 from butyrate-treated LLC-PK1 cells is separated on a gel into bands representing different overall charge state. Bands are analyzed by comparative MALDI-MS and LC-MS/MS to identify the sites of methylation and acetylation. Previous attempts to identify chemically adducted proteins in vivo have been unsuccessful in part due to a lack of understanding of the final adduct form. Cytochrome c is adducted in vitro with benzoquinone, an electrophilic metabolite of benzene capable of interacting with nucleophilic sites within proteins. De novo sequencing identifies a novel cyclized diquinone adduct species as the major reaction product, targeting Lys and His residues at two specific locations on the protein surface. This unpredicted reaction product is characterized using our unbiased methods for detection and demonstrates the important influence of protein structure on chemical adduction.

Acetylation↗

A proteomic study on human osteoblastic cells proliferation and differentiation.

Changes in expression profiles for 17 proteins were ascertained in human mature osteoblasts compared to pre-osteoblasts (differentiation markers). A differential approach was used to highlight proteomic changes between human osteosarcoma cells and mature osteoblasts, showing a relative over-expression of 8 proteins (proliferation and tumor indicators), as well as under-expression of proteins also found down-regulated in pre-osteoblasts (specific markers of osteoblast differentiation). Our findings confirmed the differences between cell lines and primary human cell cultures and suggested caution on the use of osteosarcoma to study anti-osteoporotic drugs in humans.

Adult↗

Proteomic analysis of rat soleus muscle undergoing hindlimb suspension-induced atrophy and reweighting hypertrophy.

A proteomic analysis was performed comparing normal rat soleus muscle to soleus muscle that had undergone either 0.5, 1, 2, 4, 7, 10 and 14 days of hindlimb suspension-induced atrophy or hindlimb suspension-induced atrophied soleus muscle that had undergone 1 hour, 8 hour, 1 day, 2 day, 4 day and 7 days of reweighting-induced hypertrophy. Muscle mass measurements demonstrated continual loss of soleus mass occurred throughout the 21 days of hindlimb suspension; following reweighting, atrophied soleus muscle mass increased dramatically between 8 hours and 1 day post reweighting. Proteomic analysis of normal and atrophied soleus muscle demonstrated statistically significant changes in the relative levels of 29 soleus proteins. Reweighting following atrophy demonstrated statistically significant changes in the relative levels of 15 soleus proteins. Protein identification using mass spectrometry was attempted for all differentially regulated proteins from both atrophied and hypertrophied soleus muscle. Five differentially regulated proteins from the hindlimb suspended atrophied soleus muscle were identified while five proteins were identified in the reweighting-induced hypertrophied soleus muscles. The identified proteins could be generally grouped together as metabolic proteins, chaperone proteins and contractile apparatus proteins. Together these data demonstrate that coordinated temporally regulated changes in the skeletal muscle proteome occur during disuse-induced soleus muscle atrophy and reweighting hypertrophy.

Amino Acid Sequence↗

Changes in the rat heart proteome induced by exercise training: Increased abundance of heat shock protein hsp20.

Chronic exercise training elicits adaptations in the heart that improve pump function and confer cardioprotection. To identify molecular mechanisms by which exercise training stimulates this favorable phenotype, a proteomic approach was employed to detect rat cardiac proteins that were differentially expressed or modified after exercise training. Exercise-trained rats underwent six weeks of progressive treadmill training five days/week, 0% grade, using an interval training protocol. Sedentary control rats were age- and weight-matched to the exercise-trained rats. Hearts were harvested at various times (0-72 h) after the last bout of exercise and were used to generate 2-D electrophoretic proteome maps and immunoblots. Compared with hearts of sedentary rats, 26 protein spot intensities were significantly altered in hypertrophied hearts of exercise-trained rats (p <0.05), and 12 spots appeared exclusively on gels from hearts of exercise-trained rats. Immunoblotting confirmed that chronic exercise training, but not a single bout of exercise, elicited a 2.5-fold increase in the abundance of one of the candidate proteins in the heart, a 20 kDa heat shock protein (hsp20) that persisted for at least 72 h of detraining. Thus, exercise training alters the cardiac proteome of the rat heart; the changes include a marked increase in the expression of hsp20.

Animals↗

Characterization of mouse spleen cells by subtractive proteomics.

Major analytical challenges encountered by shotgun proteome analysis include both the diversity and dynamic range of protein expression. Often new instrumentation can provide breakthroughs in areas where other analytical improvements have not been successful. In the current study, we utilized new instrumentation (LTQ FT) to characterize complex protein samples by shotgun proteomics. Proteomic analyses were performed on murine spleen tissue separated by magnetic beads into distinct CD45- and CD45+ cell populations. Using shotgun protein analysis we identified approximately 2,000 proteins per cell group by over 12,000 peptides with mass deviations of less than 4.5 ppm. Datasets obtained by LTQ FT analysis provided a significant increase in the number of proteins identified and greater confidence in those identifications and improved reproducibility in replicate analyses. Because CD45- and not CD45+ cells are able to regenerate functional pancreatic islet cells in a mouse model of type I diabetes, protein expression was further compared by a subtractive proteomic approach in search of an exclusive protein expression profile in CD45- cells. Characterization of the proteins exclusively identified in CD45- cells was performed using gene ontology terms via the Javascript GoMiner. The CD45- cell subset readily revealed proteins involved in development, suggesting the persistence of a fetal stem cell in an adult animal.

Animals↗

Analysis of polyubiquitin conjugates reveals that the Rpn10 substrate receptor contributes to the turnover of multiple proteasome targets.

The polyubiquitin receptor Rpn10 targets ubiquitylated Sic1 to the 26S proteasome for degradation. In contrast, turnover of at least one ubiquitin-proteasome system (UPS) substrate, CPY*, is impervious to deletion of RPN10. To distinguish whether RPN10 is involved in the turnover of only a small set of cell cycle regulators that includes Sic1 or plays a more general role in the UPS, we sought to develop a general method that would allow us to survey the spectrum of ubiquitylated proteins that selectively accumulate in rpn10Delta cells. Polyubiquitin conjugates from yeast cells that express hexahistidine-tagged ubiquitin (H6-ubiquitin) were first enriched on a polyubiquitin binding protein affinity resin. This material was then denatured and subjected to IMAC to retrieve H6-ubiquitin and proteins to which it may be covalently linked. Using this approach, we identified 127 proteins that are candidate substrates for the 26S proteasome. We then sequenced ubiquitin conjugates from cells lacking Rpn10 (rpn10Delta) and identified 54 proteins that were uniquely recovered from rpn10Delta cells. These include two known targets of the UPS, the cell cycle regulator Sic1 and the transcriptional activator Gcn4. Our approach of comparing the ubiquitin conjugate proteome in wild-type and mutant cells has the resolving power to identify even an extremely in abundant transcriptional regulatory protein and should be generally applicable to mapping enzyme substrate networks in the UPS.

Carrier Proteins↗

Proteome of amyloplasts isolated from developing wheat endosperm presents evidence of broad metabolic capability.

By contrast to chloroplasts, our knowledge of amyloplasts--organelles that synthesize and store starch in heterotrophic plant tissues--is in a formative stage. While our understanding of what is considered their primary function, i.e. the biosynthesis and degradation of starch, has increased dramatically in recent years, relatively little is known about other biochemical processes taking place in these organelles. To help fill this gap, a proteomic analysis of amyloplasts isolated from the starchy endosperm of wheat seeds (10 d post-anthesis) has been conducted. The study has led to the identification of 289 proteins that function in a range of processes, including carbohydrate metabolism, cytoskeleton/plastid division, energetics, nitrogen and sulphur metabolism, nucleic acid-related reactions, synthesis of various building blocks, protein-related reactions, transport, signalling, stress, and a variety of other activities grouped under 'miscellaneous'. The function of 12% of the proteins was unknown. The results highlight the role of the amyloplast as a starch-storing organelle that fulfills a spectrum of biosynthetic needs of the parent tissue. When compared with a recent proteomic analysis of whole endosperm, the current study demonstrates the advantage of using isolated organelles in proteomic studies.

Carbohydrate Metabolism↗

An approach to the proteomic analysis of a breast cancer cell line (SKBR-3).

This report describes the profiling of proteins in a sample prepared by laser capture microdissection (LCM) from a breast cancer cell line (SKBR-3). This experimental approach serves as a model system for proteomic studies on selected tissue samples and for studies of specific cell types. The captured cells were isolated in a dehydrated and reduced state and solubilized with a denaturing buffer. After dilution the protein mixture was digested with trypsin and the resulting peptide mixture was fractionated by reversed phase HPLC (RPLC) and analyzed on an ion trap mass spectrometer. A key part of this study is the combination of the LCM process with an extraction/digestion procedure that allowed effective solubilization of a significant part of the cellular sample in a single step. The identity of the peptides was determined by tandem mass spectrometry measurements in which the resulting spectra were compared with genomic and proteomic databases and protein identifications were made. While only peptides with a high probability assignment were used, the interpretation of mass spectral fragmentation patterns were also confirmed by manual interpretation of the spectra. Also, for the more abundant proteins the initial protein assignment from the best match peptide was strengthened by the observation of additional confirmatory peptide identifications. Another selection criteria was correlation of the mass spectrometric studies with clinical and genomic studies of potential cancer markers in tumor samples. This proteomic study allowed identification of the following proteins: human receptor protein kinase HER-2 or ERBB-2 and related kinases HER-3 and HER-4, the gene products from breast cancer type I and II susceptibility genes and cytoskeletal components such as cytokeratins 8, 18 and 19. Other proteins include fibroblast growth factor receptor variants (FGFR-2&4) and T-lymphoma invasion and metastasis inducing protein 1 (TIAM1). In addition several nonreceptor protein kinases YES, FAK and JAK-1 and 3 were identified. Since the study was performed on a limited number of cells (approximately 10,000) it raises the possibility of such studies being performed on individual patient samples prepared by needle biopsy.

Biomarkers, Tumor↗

Immunoproteomic analysis of capsulate and non-capsulate strains of Lactococcus garvieae.

A comparative immunoproteomic study was carried out to investigate the immunogenicity of capsulate (KG9408) and non-capsulate (NSS9310) strains of Lactococcus garvieae. Immunoblot assays, following two-dimensional gel electrophoresis (2-DE) for L. garvieae strains, revealed a significant difference between anti-capsulate and anti-non-capsulate rabbit sera with respect to the number and antigenicity of antigenic spots. Anti-capsulate and anti-non-capsulate rabbit sera reacted with an average of 72 and 127 antigenic spots, respectively. The strong reaction of anti-non-capsulate sera with elongation factor (EF)-G and -Tu, and GMP synthase, of the L. garvieae strains identifies these as specific major antigens. This study clearly demonstrates the differences in 2-DE immunoblot profiles between the capsulate and non-capsulate strains of L. garvieae. These differences may be the reason for variations in immunogenicity between capsulate and non-capsulate strains. Glyceraldehyde-3-phosphate dehydrogenase, phosphoglycerate kinase, arginine deaminase and ornithine carbamoyltransferase were identified from the 2-DE immunoblot profiles of both strains. Therefore, these common antigens are potential markers for the development of vaccines against L. garvieae, irrespective of strain. Immunoproteomics, a powerful tool for studying antigens at the proteomic level, allowed a comparative investigation of the immunogenicity of capsulate and non-capsulate strains of L. garvieae for vaccine development.

Animals↗

Enzyme activity profiles of the secreted and membrane proteome that depict cancer cell invasiveness.

By primarily measuring changes in transcript and protein abundance, conventional genomics and proteomics methods may fail to detect significant posttranslational events that regulate protein activity and, ultimately, cell behavior. To address these limitations, activity-based proteomic technologies that measure dynamics in protein function on a global scale would be of particular value. Here, we describe the application of a chemical proteomics strategy to quantitatively compare enzyme activities across a panel of human breast and melanoma cancer cell lines. A global analysis of the activity, subcellular distribution, and glycosylation state for the serine hydrolase superfamily resulted in the identification of a cluster of proteases, lipases, and esterases that distinguished cancer lines based on tissue of origin. Strikingly, nearly all of these enzyme activities were down-regulated in the most invasive cancer lines examined, which instead up-regulated a distinct set of secreted and membrane-associated enzyme activities. These invasiveness-associated enzymes included urokinase, a secreted serine protease with a recognized role in tumor progression, and a membrane-associated hydrolase KIAA1363, for which no previous link to cancer had been made. Collectively, these results suggest that invasive cancer cells share discrete proteomic signatures that are more reflective of their biological phenotype than cellular heritage, highlighting that a common set of enzymes may support the progression of tumors from a variety of origins and thus represent attractive targets for the diagnosis and treatment of cancer.

Biomarkers, Tumor↗

A proteome analysis of the yeast response to the herbicide 2,4-dichlorophenoxyacetic acid.

The intensive use of herbicides may give rise to a number of toxicological problems in non-target organisms and has led to the emergence of resistant weeds. To gain insights into the mechanisms of adaptation to the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D), we have identified variations in protein expression level in the eukaryotic experimental model Saccharomyces cerevisiae exposed to herbicide aggression, based on two-dimensional gel electrophoresis. We show results suggesting that during the adaptation period preceding the resumption of inhibited exponential growth under herbicide stress, the antioxidant enzyme Ahp1p and the heat shock proteins Hsp12p and Ssb2p (or Ssb1p) are present in higher amounts. The increased level of other enzymes involved in protein (Cdc48p) and mRNA (Dcp1p) degradation, in carbohydrate metabolism (Eno1p, Eno2p and Glk1p) and in vacuolar H(+)-ATPase (V-ATPase) function (Vma1p and Vma2p, two subunits of the peripheral catalytic sector) was also registered. V-ATPase is involved in the homeostasis of intracellular pH and in the compartmentalization of amino acids and other metabolites in the vacuole. The increased expression of amino acid biosynthetic enzymes (Arg1p, Aro3p, Aro8p, Gdh1p, His4p, Ilv3p and Met6p), also suggested by comparative analysis of the proteome, was correlated with the reduction of amino acid concentration registered in both the vacuole and the cytosol of 2,4-D-stressed cells, possibly due to the disturbance of vacuolar and plasma membrane functions by the lipophilic acid herbicide.

2,4-Dichlorophenoxyacetic Acid↗

The role of emerging genomics and proteomics technologies in cancer drug target discovery.

Cancer drugs have traditionally been identified in screens designed to produce broad biological end points such as cell death. A serious undesired outcome of drugs discovered in these screens is that the mechanism of drug action is unknown and such drugs often have adverse side effects. Designing cancer drugs that act on specific targets offer the advantage that the mechanism of drug action can be understood and accurately monitored in clinical trials leading to development of better drugs. The pharmacological industry has recently shifted to a target directed drug discovery model. However, until recently potential cancer drug targets comprised of only a small fraction of the human genome. The human genome project and high-throughput structural and functional genomics have dramatically increased the number of cancer drug targets. Deciphering cancer drug targets requires the understanding of biochemical pathways that are affected in the cancer genome. It has been suggested that utilization of Single-nucleotide polymorphisms (SNPs) will aid in identifying individuals at high risk of developing certain cancers, and will also help in development of tailored medication or identify genetic profiles of specific drug action and toxicity. Achieving successful new cancer drug development schemes will require a merger of research disciplines that include pharmacology, genomics, comparative genomics, functional genomics, proteomics and bioinformatics. In this review the significance and challenges of these rapidly evolving technologies in cancer drug target discovery are discussed.

Animals↗

Simultaneous qualitative and quantitative analysis of the Escherichia coli proteome: a sweet tale.

We describe a novel LCMS approach to the relative quantitation and simultaneous identification of proteins within the complex milieu of unfractionated Escherichia coli. This label-free, LCMS acquisition method observes all detectable, eluting peptides and their corresponding fragment ions. Postacquisition data analysis methods extract both the chromatographic and the mass spectrometric information on the tryptic peptides to provide time-resolved, accurate mass measurements, which are subsequently used for quantitation and identification of constituent proteins. The response of E. coli to carbon source variation is well understood, and it is thus commonly used as a model biological system when validating an analytical method. Using this LCMS approach, we characterized proteins isolated from E. coli grown in glucose, lactose, and acetate. The change in relative abundance of the corresponding proteins was measured from peptides common to both conditions. Protein identities were also determined for those peptides that were unique to each condition, and these identities were found to be consistent with the underlying biochemical restrictions imposed by the growth conditions. The relative change in abundance of the characterized proteins ranged from 0.1- to 90-fold among the three binary comparisons. The overall coverage of the characterized proteins ranged from 10 to 80%, consisting of one to 34 peptides per protein. The quantitative results obtained from our study were comparable to other existing proteomic and transcriptional profiling approaches. This study illustrates the robustness of this novel LCMS approach for the simultaneous quantitative and comprehensive qualitative analysis of proteins in complex mixtures.

Chromatography, High Pressure Liquid↗