Native purification of protein and RNA-protein complexes using a novel affinity procedure

Genetic studies in invertebrate model organisms such as Drosophila melanogaster have been a fundament of cell and developmental biology for more than one century. It is mainly the lack of an efficient purification strategy which has hampered biochemical and proteomic analyses of gene products. We describe a novel affinity-tag, termed TagIt-epitope specifically designed for affinity-purifications of multiprotein complexes from Drosophila. TagIt-fusion proteins can be efficiently purified using a monoclonal antibody and eluted under native conditions by competition with synthetic peptide encompassing the epitope. We demonstrate that this tag is suitable for the purification of proteinaceous assemblies such as the PRMT5-complex and RNA-protein complexes such as snoRNPs from Drosophila Schneider2 cells. Furthermore, we describe a novel approach by which this tag can be used to affinity-purify RNA-binding proteins from cell extracts. Therefore, the TagIt-technique or modifications thereof will be of great value in analyzing macromolecular complexes in Drosophila and also other invertebrates by biochemical means. In addition, RNA-peptide hybrid molecules may become a novel tool to purify RNA binding proteins.     

Quantitative proteomic profiling of pancreatic cancer juice

Pancreatic juice is an exceptionally rich source of cancer-specific proteins shed from cancerous ductal cells into the pancreatic juice. Quantitative proteomic analysis of the proteins specific to pancreatic cancer juice has not previously been reported. We used isotope-code affinity tag (ICAT) technology and MS/MS to perform quantitative protein profiling of pancreatic juice from pancreatic cancer patients and normal controls. ICAT technology coupled with MS/MS allows the systematic study of the proteome and measures the protein abundance in pancreatic juice with the potential for development of biomarkers. A total of 105 proteins were identified and quantified in the pancreatic juice from a pancreatic cancer patient, of which 30 proteins showed abundance changes of at least twofold in pancreatic cancer juice compared to normal controls. Many of these proteins have been externally validated. This is the first comprehensive study of the pancreatic juice proteome by quantitative global protein profiling, and the study reveals numerous proteins that are shown for the first time to be associated with pancreatic cancer, providing candidates for diagnostic biomarkers. One of the identified proteins, insulin-like growth factor binding protein-2 was further validated by Western blotting to be elevated in pancreatic cancer juice and overexpressed in pancreatic cancer tissue.     

Identification of novel citrullinated autoantigens of synovium in rheumatoid arthritis using a proteomic approach

Recently, autoantibodies to some citrullinated autoantigens have been reported to be specific for rheumatoid arthritis (RA). However, an entire profile of and autoimmunity of the citrullinated proteins have been poorly understood. To understand the profile, we examined citrullinated autoantigens by a proteomic approach and further investigated the significance of citrullination in antigenicity of one of the autoantigens. Specifically, we detected citrullinated autoantigens in synovial tissue of a patient with RA by two-dimensional electrophoresis and Western blotting by using pooled sera from five patients with RA and anti-citrulline antibodies. After identifying the detected autoantigens by mass spectrometry, we investigated the contribution of citrullination to autoantigenicity by using a recombinant protein with or without citrullination on one of the identified novel citrullinated autoantigens. As a result, we found 51 citrullinated protein spots. Thirty (58.8%) of these spots were autoantigenic. We identified 13 out of the 30 detected citrullinated autoantigenic proteins. They contained three fibrinogen derivatives and several novel citrullinated autoantigens (for example, asporin and F-actin capping protein α-1 subunit [CapZα-1]). We further analyzed the contribution of citrullination to autoantigenicity in one of the detected citrullinated autoantigens, CapZα-1. As a result, frequencies of autoantibodies to non-citrullinated CapZα-1 were 36.7% in the RA group tested, 10.7% in the osteoarthritis (OA) group, and 6.5% in healthy donors. On the other hand, those to citrullinated CapZα-1 were 53.3% in the RA group, 7.1% in the OA group, and 6.5% in the healthy donors. This shows that autoantigenicity of citrullinated or non-citrullinated CapZα-1 is relevant to RA. The antibody titers to the citrullinated CapZα-1 were significantly higher than those to the non-citrullinated CapZα-1 in 36.7% of patients; however, the other patients showed almost equal antibody titers to both citrullinated and non-citrullinated CapZα-1. Therefore, the autoantibodies would target citrulline-related and/or citrulline-unrelated epitope(s) of CapZα-1. In conclusion, we report a profile of citrullinated autoantigens for the first time. Even though citrullination is closely related to autoantigenicity, citrullination would not always produce autoantigenicity in RA. Citrullinated and non-citrullinated autoantigens/autoepitopes would have different pathological roles in RA.     

Identification of novel citrullinated autoantigens of synovium in rheumatoid arthritis using a proteomic approach

Recently, autoantibodies to some citrullinated autoantigens have been reported to be specific for rheumatoid arthritis (RA). However, an entire profile of and autoimmunity of the citrullinated proteins have been poorly understood. To understand the profile, we examined citrullinated autoantigens by a proteomic approach and further investigated the significance of citrullination in antigenicity of one of the autoantigens. Specifically, we detected citrullinated autoantigens in synovial tissue of a patient with RA by two-dimensional electrophoresis and Western blotting by using pooled sera from five patients with RA and anti-citrulline antibodies. After identifying the detected autoantigens by mass spectrometry, we investigated the contribution of citrullination to autoantigenicity by using a recombinant protein with or without citrullination on one of the identified novel citrullinated autoantigens. As a result, we found 51 citrullinated protein spots. Thirty (58.8%) of these spots were autoantigenic. We identified 13 out of the 30 detected citrullinated autoantigenic proteins. They contained three fibrinogen derivatives and several novel citrullinated autoantigens (for example, asporin and F-actin capping protein alpha-1 subunit [CapZalpha-1]). We further analyzed the contribution of citrullination to autoantigenicity in one of the detected citrullinated autoantigens, CapZalpha-1. As a result, frequencies of autoantibodies to non-citrullinated CapZalpha-1 were 36.7% in the RA group tested, 10.7% in the osteoarthritis (OA) group, and 6.5% in healthy donors. On the other hand, those to citrullinated CapZalpha-1 were 53.3% in the RA group, 7.1% in the OA group, and 6.5% in the healthy donors. This shows that autoantigenicity of citrullinated or non-citrullinated CapZalpha-1 is relevant to RA. The antibody titers to the citrullinated CapZalpha-1 were significantly higher than those to the non-citrullinated CapZalpha-1 in 36.7% of patients; however, the other patients showed almost equal antibody titers to both citrullinated and non-citrullinated CapZalpha-1. Therefore, the autoantibodies would target citrulline-related and/or citrulline-unrelated epitope(s) of CapZalpha-1. In conclusion, we report a profile of citrullinated autoantigens for the first time. Even though citrullination is closely related to autoantigenicity, citrullination would not always produce autoantigenicity in RA. Citrullinated and non-citrullinated autoantigens/autoepitopes would have different pathological roles in RA.     

Evaluation of an integrated strategy for proteomic profiling of skeletal muscle

Proteomic analysis of skeletal muscle presents particular challenges when trying to identify valid biomarkers of phenotypic change in small biopsies from genetically diverse human subjects. Currently, two-dimensional (2-D) gel electrophoresis and mass spectrometry are the chosen analytical strategies but 2-D gels are not appropriate for analyzing proteins less than 11 kDa, they can suffer from problems of reproducibility and in routine use are not a viable high-throughput technique. We have evaluated an integrated proteomic strategy employing Ciphergen ProteinChip arrays, one-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Protein fingerprints characteristic of fast and slow contracting muscles from normal and kyphoscoliosis (ky) mutant mice were obtained from Ciphergen protein arrays. Eight statistically validated protein biomarkers have so far been identified capable of discriminating fast from slow muscle. Five of these showed further differential expression in ky versus normal BDL soleus muscles. Several biomarkers have been formally identified, and were myosin light chain isoforms shown previously to be expressed differentially by fast versus slow skeletal muscles. This integrated experimental approach using a model mouse muscle system shows the potential of Ciphergen protein array technology for proteomic analysis of small proteins in small muscle samples and its applicability for phenotypic characterization of skeletal muscle in general.     

Quantitative proteomic profiling of hepatocellular carcinoma at different serum alpha-fetoprotein level

PurposeHepatocellular carcinoma (HCC) is characterized by a poor long-term prognosis and high mortality rate. Serum alpha-fetoprotein (AFP) levels show great prognostic value in patients undergoing hepatectomy. This study aims to explore proteomic profiling in HCC samples based on AFP subgroups and identify potential key targets involved in HCC progression.MethodsTwelve paired tumor and adjacent noncancerous tissue samples were collected from patients with HCC who underwent primary curative resection from January 2012 to December 2013. Clinical information was curated from four tissue microarrays to conduct survival analysis based on serum AFP levels. TMT-based quantitative proteomic analyses and bioinformatics analyses were performed to comprehensively profile molecular features. Immunohistochemistry was carried out to validate protein expression of identified targets. Kaplan-Meier survival analysis was performed to assess the overall survival and recurrence-free survival based on protein expressions.ResultsAFP (400 ng/mL) was a turning point in prognosis, metabolic- and invasion-associated pathways. The mass spectrometry analysis yielded a total of 5573 identified proteins. Annotations of 151 differentially expressed proteins in tumors and 95 proteins in paracancerous tissues (1.2-fold) showed similarities in biological processes, cellular components, molecular functions. Furthermore, differentially expressed hub proteins with five innovatively nominated druggable targets (C1QBP, HSPE1, GLUD2 for tumors and CHDH, ITGAL for paracancerous tissues), of which four (C1QBP, HSPE1, CHDH, ITGAL) targets were associated with poor overall survival (all Log-rank P < 0.05).ConclusionsOur quantitative proteomics analyses identified four key prognostic biomarkers in HCC and provide opportunities for translational medicine and new treatment.     

Multivariate proteomic profiling identifies novel accessory proteins of coated vesicles

Despite recent advances in mass spectrometry, proteomic characterization of transport vesicles remains challenging. Here, we describe a multivariate proteomics approach to analyzing clathrin-coated vesicles (CCVs) from HeLa cells. siRNA knockdown of coat components and different fractionation protocols were used to obtain modified coated vesicle-enriched fractions, which were compared by stable isotope labeling of amino acids in cell culture (SILAC)-based quantitative mass spectrometry. 10 datasets were combined through principal component analysis into a "profiling" cluster analysis. Overall, 136 CCV-associated proteins were predicted, including 36 new proteins. The method identified >93% of established CCV coat proteins and assigned >91% correctly to intracellular or endocytic CCVs. Furthermore, the profiling analysis extends to less well characterized types of coated vesicles, and we identify and characterize the first AP-4 accessory protein, which we have named tepsin. Finally, our data explain how sequestration of TACC3 in cytosolic clathrin cages causes the severe mitotic defects observed in auxilin-depleted cells. The profiling approach can be adapted to address related cell and systems biological questions.     

Evaluation of clinical colon carcinoma using activity-based proteomic profiling

The evaluation of clinical tumor tissues is a valuable approach to discovering novel drug targets because of the direct relevance of human samples. We used activity-based proteomic profiling (ABPP) to study the differences in serine hydrolase activities from 12 matched pairs of clinical normal and tumor colon tissues. Unlike traditional proteomics or measures of mRNA abundance, ABPP actually quantifies enzymatic activities, a characteristic crucial for drug targeting. Several serine hydrolases were differentially active in tumor vs normal tissues, despite a lack of obvious corresponding alterations in protein expression. We identified one tumor-specific activity by mass spectrometry to be fibroblast activation protein (FAP), an integral membrane serine protease that has been reported to be present only in tumor stroma or during wound healing and absent in normal tissues. FAP activity was further found to be approximately twofold higher in stage III relative to stage II colon cancer, suggestive of a role in tumor progression. We were also able to identify other proteins, some of which had not been previously linked to cancer, which had higher activity in tumors. Our results demonstrate the applicability of ABPP for the efficient identification of multiple clinical disease targets.     

High throughput proteomic and metabolic profiling identified target correction of metabolic abnormalities as a novel therapeutic approach in head and neck paraganglioma

Head and neck paragangliomas (HNPGLs) are rare neoplasms that represent difficult treatment paradigms in neurotology. Germline mutations in genes encoding succinate dehydrogenase (SDH) are the cause of nearly all familial HNPGLs. However, the molecular mechanisms underlying tumorigenesis remain unclear. Mutational analysis identified 6 out of 14 HNPGLs harboring clinicopathologic SDH gene mutations. The SDHB gene was most frequently mutated in these patients, and western blot showed loss of SDHB protein in tumors with SDHB mutations. The paraganglioma cell line (PGL-626) was established from a sample that harbored a missense SDHB mutation (c.649C > T). Spectrometric analysis using tandem mass tags identified 151 proteins significantly differentially expressed in HNPGLs compared with normal nerves. Bioinformatics analyses confirmed the high level of enrichment of oxidative phosphorylation and metabolism pathways in HNPGLs. The mitochondrial complex subunits NDUFA2, NDUFA10, and NDUFA4, showed the most significantly increased expression and were localized predominantly in the cytoplasm of PGL-626 cells. The mitochondrial complex I inhibitor metformin exerted dose-dependent inhibitory effects on PGL-626 cells via cooperative down-regulation of NDUFA2, 4, and 10, with a significant decrease in the levels of reactive oxygen species and mitochondrial membrane potential. Further metabolomic analysis of PGL-626 cells showed that metabolites involved in central carbon metabolism in cancer and sphingolipid signaling pathways, pantothenate and CoA biosynthesis, and tryptophan and carbon metabolism were significantly altered after metformin treatment. Thus, this study provides insights into the molecular mechanisms underlying HNPGL tumorigenesis and identifies target correction of metabolic abnormalities as a novel therapeutic approach for this disease.     

Dynamics of photosystem II: a proteomic approach to thylakoid protein complexes

Oxygenic photosynthesis produces various radicals and activeoxygen species with harmful effects on photosystem II (PSII).Such photodamage occurs at all light intensities. Damaged PSIIcentres, however, do not usually accumulate in the thylakoidmembrane due to a rapid and efficient repair mechanism. Theexcellent design of PSII gives protection to most of the proteincomponents and the damage is most often targeted only to thereaction centre D1 protein. Repair of PSII via turnover of thedamaged protein subunits is a complex process involving (i)highly regulated reversible phosphorylation of several PSIIcore subunits, (ii) monomerization and migration of the PSIIcore from the grana to the stroma lamellae, (iii) partial disassemblyof the PSII core monomer, (iv) highly specific proteolysis ofthe damaged proteins, and finally (v) a multi-step replacementof the damaged proteins with de novo synthesized copies followedby (vi) the reassembly, dimerization, and photoactivation ofthe PSII complexes. These processes will shortly be reviewedpaying particular attention to the damage, turnover, and assemblyof the PSII complex in grana and stroma thylakoids during thephotoinhibition–repair cycle of PSII. Moreover, a two-dimensionalBlue-native gel map of thylakoid membrane protein complexes,and their modification in the grana and stroma lamellae duringa high-light treatment, is presented. Key words: Arabidopsis thylakoid membrane proteome, assembly of photosystem II, D1 protein, light stress, photosystem II photoinhibition, repair of photosystem II     

Quantitative proteomic profiling identifies global protein network dynamics in murine embryonic heart development

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The endless subtleties of RNA-protein complexes

New NMR structures of complexes between double-strand RNA binding domains and their RNA hairpin substrates reported by Wang et?al. in this issue of Structure reveal striking adaptations in both the protein recognition element and in the RNA.     

Characterisation of host defence proteins in milk using a proteomic approach

Besides providing nutrition to the newborn, milk also protects the neonate and the mammary gland against infection. As well as the six major proteins, bovine milk contains minor proteins, not all of which have been characterized. In this study, we have subjected bovine skim milk, whey, and milk fat globule membrane (MFGM) fractions to both direct liquid chromatography-tandem mass spectrometry (LC-MS/MS), and two-dimensional electrophoresis (2-DE) followed by matrix assisted laser desorption ionization-time-of-flight (MALDI-TOF) mass spectrometry (MS) of individual protein spots to better characterize the repertoire of minor milk proteins, particularly those involved with host defense. Milk from peak lactation as well as during the period of colostrum formation and during mastitis were analyzed to gain a more complete sampling of the milk proteome. In total, 2903 peptides were detected by LC-MS and 2770 protein spots by 2-DE. From these, 95 distinct gene products were identified, comprising 53 identified through direct LC-MS/MS and 57 through 2-DE-MS. The latter were derived from a total of 363 spots analyzed with 181 being successfully identified. At least 15 proteins were identified that are involved in host defense. These results demonstrate that the proteome of milk is more complex than has previously been reported and a significant fraction of minor milk proteins are involved in protection against infection.     

Detection of bladder cancer using proteomic profiling of urine sediments

We used protein expression profiles to develop a classification rule for the detection and prognostic assessment of bladder cancer in voided urine samples. Using the Ciphergen PBS II ProteinChip Reader, we analyzed the protein profiles of 18 pairs of samples of bladder tumor and adjacent urothelium tissue, a training set of 85 voided urine samples (32 controls and 53 bladder cancer), and a blinded testing set of 68 voided urine samples (33 controls and 35 bladder cancer). Using t-tests, we identified 473 peaks showing significant differential expression across different categories of paired bladder tumor and adjacent urothelial samples compared to normal urothelium. Then the intensities of those 473 peaks were examined in a training set of voided urine samples. Using this approach, we identified 41 protein peaks that were differentially expressed in both sets of samples. The expression pattern of the 41 protein peaks was used to classify the voided urine samples as malignant or benign. This approach yielded a sensitivity and specificity of 59% and 90%, respectively, on the training set and 80% and 100%, respectively, on the testing set. The proteomic classification rule performed with similar accuracy in low- and high-grade bladder carcinomas. In addition, we used hierarchical clustering with all 473 protein peaks on 65 benign voided urine samples, 88 samples from patients with clinically evident bladder cancer, and 127 samples from patients with a history of bladder cancer to classify the samples into Cluster A or B. The tumors in Cluster B were characterized by clinically aggressive behavior with significantly shorter metastasis-free and disease-specific survival.     

Quantitative protein profiling using antibody arrays

Traditional approaches to microarrays rely on direct binding assays where the extent of hybridisation and the signal detected are a measure of the analyte concentration in the experimental sample. This approach, directly imported from the nucleic acid field, may fail if applied to antibody-antigen interactions due to the shortage of characterised antibodies, the significant heterogeneity of antibody affinities, their dependence on the extent of protein modification during labelling and the inherent antibody cross-reactivity. These problems can potentially limit the multiplexing capabilities of protein affinity assays and in many cases rule out quantitative protein profiling using antibody microarrays. A number of approaches aimed at achieving quantitative protein profiling in a multiplex format have been reported recently. Of those reported, the three most promising routes include signal amplification, multicolour detection and competitive displacement approaches to multiplex affinity assays. One in particular, competitive displacement, also overcomes the problems associated with quantitation of affinity interactions and provides the most generic approach to highly parallel affinity assays, including antibody arrays.