An FD-LC-MS/MS proteomic strategy for revealing cellular protein networks: a conditional superoxide dismutase 1 knockout cells.
ABSTRACT: Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively.
Project description:Nephrotoxicity severely limits the chemotherapeutic efficacy of cisplatin (CDDP). Oxidative stress is associated with CDDP-induced acute kidney injury (AKI). Methylglyoxal (MG) forms advanced glycation end products that elevate oxidative stress. We aimed to explore the role of MG and its metabolite D-lactate and identify the proteins involved in CDDP-induced AKI. Six-week-old female BALB/c mice were intraperitoneally administered CDDP (5 mg/kg/day) for 3 or 5 days. Blood urea nitrogen (42.6 ± 7.4 vs. 18.3 ± 2.5; p < 0.05) and urinary N-acetyl-?-D-glucosaminide (NAG; 4.89 ± 0.61 vs. 2.43 ± 0.31 U/L; p < 0.05) were significantly elevated in the CDDP 5-day group compared to control mice. Histological analysis confirmed AKI was successfully induced. Confocal microscopy revealed TNF-? was significantly increased in the CDDP 5-day group. Fluorogenic derivatized liquid chromatography-tandem mass spectrometry (FD-LC-MS/MS) showed the kidney MG (36.25 ± 1.68 vs. 18.95 ± 2.24 mg/g protein, p < 0.05) and D-lactate (1.78 ± 0.29 vs. 1.12 ± 0.06 mol/g protein, p < 0.05) contents were significantly higher in the CDDP 5-day group than control group. FD-LC-MS/MS proteomics identified 33 and nine altered peaks in the CDDP 3-day group and CDDP 5-day group (vs. control group); of the 35 proteins identified using the MOSCOT database, 11 were antioxidant-related. Western blotting confirmed that superoxide dismutase 1 (SOD-1) and parkinson disease protein 7 (DJ-1) are upregulated and may participate with MG in CDDP-induced AKI. This study demonstrates TNF-?, MG, SOD-1 and DJ-1 play crucial roles in CDDP-induced AKI.
Project description:Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics provides a wealth of information about proteins present in biological samples. In bottom-up LC-MS/MS-based proteomics, proteins are enzymatically digested into peptides prior to query by LC-MS/MS. Thus, the information directly available from the LC-MS/MS data is at the peptide level. If a protein-level analysis is desired, the peptide-level information must be rolled up into protein-level information. We propose a principal component analysis-based statistical method, ProPCA, for efficiently estimating relative protein abundance from bottom-up label-free LC-MS/MS data that incorporates both spectral count information and LC-MS peptide ion peak attributes, such as peak area, volume, or height. ProPCA may be used effectively with a variety of quantification platforms and is easily implemented. We show that ProPCA outperformed existing quantitative methods for peptide-protein roll-up, including spectral counting methods and other methods for combining LC-MS peptide peak attributes. The performance of ProPCA was validated using a data set derived from the LC-MS/MS analysis of a mixture of protein standards (the UPS2 proteomic dynamic range standard introduced by The Association of Biomolecular Resource Facilities Proteomics Standards Research Group in 2006). Finally, we applied ProPCA to a comparative LC-MS/MS analysis of digested total cell lysates prepared for LC-MS/MS analysis by alternative lysis methods and show that ProPCA identified more differentially abundant proteins than competing methods.
Project description:Proteomic analysis of gastroduodenal fluid offers an alternative strategy to study diseases, such as peptic ulcer disease and gastric cancer. We use in-gel tryptic digestion followed by LC-MS/MS (GeLC-MS/MS) to profile the proteome of gastroduodenal fluid collected during the endoscopic pancreatic function test (ePFT).Gastroduodenal fluid specimens collected during ePFT from six patients with upper abdominal pain were subjected to proteomic analysis. We extracted proteins using three chemical precipitation reagents (acetone, ethanol, and trichloroacetic acid) and analyzed each sample by SDS-PAGE and GeLC-MS/MS for protein identification. Cellular origin and molecular function of the identified proteins were determined via gene ontology analysis.All three precipitation techniques successfully extracted protein from gastroduodenal fluid, with acetone resulting in excellent resolution and minimal protein degradation compared with the other methods. A total of 134 unique proteins were found in our GeLC-MS/MS analysis of ePFT-collected gastroduodenal fluid samples. Sixty-seven proteins were identified in at least two of the three samples. Gene ontology analysis classified these proteins mainly as being peptidases and localized extracellularly.ePFT, followed by acetone precipitation, and coupled with LC-MS/MS, can be used to safely collect gastroduodenal fluid from the upper gastrointestinal tract for MS-based proteomic analysis.
Project description:Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC-MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC-MS/MS using a 1?×?150?mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16?h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16?h. The system identifies >30,000 phosphopeptides in 12?h and protein-protein or protein-drug interaction experiments can be analyzed in 20?min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC-MS/MS is suitable for a broad range of proteomic applications.
Project description:Glioblastoma is a difficult disease to diagnose. Proteomic techniques are commonly applied in biomedical research, and can be useful for early detection, making an accurate diagnosis and reducing mortality. The relevance of mitochondria in brain development and function is well known; therefore, mitochondria may influence the development of glioblastoma. The T98G (with oxidative metabolism) and U87MG (with glycolytic metabolism) cell lines are considered to be useful glioblastoma models for studying these tumors and the role of mitochondria in key aspects of this disease, such as prognosis, metastasis and apoptosis. In the present study, principal component analysis of protein abundance data identified by liquid chromatography coupled to tandem mass spectrometry (LC?MS/MS) and matrix?assisted laser desorption/ionization?time of flight mass spectrometry (MALDI?TOF) from 2D gels indicated that representative mitochondrial proteins were associated with glioblastoma. The selected proteins were organized into T98G? and U87MG?specific protein?protein interaction networks to demonstrate the representativeness of both proteomic techniques. Gene Ontology overrepresentation analysis based on the relevant proteins revealed that mitochondrial processes were associated with metabolic changes, invasion and metastasis in glioblastoma, along with other non?mitochondrial processes, such as DNA translation, chaperone responses and autophagy. Despite the lower resolution of 2D electrophoresis, principal component analysis yielded information of comparable quality to that of LC?MS/MS. The present analysis pipeline described a specific and more complete metabolic status for each cell line, defined a clear mitochondrial performance for distinct glioblastoma tumors, and introduced a useful strategy to understand the heterogeneity of glioblastoma.
Project description:The use of offline liquid chromatography-matrix assisted laser desorption/ionization (LC-MALDI) tandem mass spectrometry (MS/MS) for bottom-up proteomics offers advantages in terms of cost, ease of use, and the time-decoupled nature of the separation step and the mass analysis. A method was developed to improve the capabilities of LC-MALDI-MS/MS in terms of protein identification in a bottom-up proteomic workflow. Enhanced protein identification is achieved by an increase in the MALDI signal intensity of the precursor peptides brought about by coating the MALDI plate with a thin film of graphite powder. Using the Escherichia coli proteome, it is demonstrated that the graphite-modified MALDI plates used in an offline LC-MALDI-MS/MS bottom-up protocol led to a 50-135% increase in the number of peptide identifications, and a concomitant 21%-105% increase in the number of proteins inferred. We identify factors that lead to improvements in peptide sequence identifications and in the number of unique proteins identified when compared to using an unmodified MALDI plate. These improvements are achieved using a low cost approach that it is easy to implement, requires no hardware/protocol modification, it is compatible with LC and adds no additional analysis time.
Project description:An increasingly popular and promising field in functional proteomics is the isolation of proteome subsets based on small molecule-protein interactions. One platform approach in this field are Capture Compounds that contain a small molecule of interest to bind target proteins, a photo-activatable reactivity function to covalently trap bound proteins, and a sorting function to isolate captured protein conjugates from complex biological samples for direct protein identification by liquid chromatography/mass spectrometry (nLC-MS/MS). In this study we used staurosporine as a selectivity group for analysis in HepG2 cells derived from human liver. In the present study, we combined the functional isolation of kinases with different separation workflows of automated split-free nanoflow liquid chromatography prior to mass spectrometric analysis. Two different CCMS setups, CCMS technology combined with 1D LC-MS and 2D LC-MS, were compared regarding the total number of kinase identifications. By extending the chromatographic separation of the tryptic digested captured proteins from 1D LC linear gradients to 2D LC we were able to identify 97 kinases. This result is similar to the 1D LC setup we previously reported but this time 4 times less input material was needed. This makes CCMS of kinases an even more powerful tool for the proteomic profiling of this important protein family.
Project description:The proportionately low abundance of membrane proteins hampers their proteomic analysis, especially for a quantitative LC-MS/MS approach. To overcome this limitation, a method was developed that consists of one cell disruption step in a hypotonic reagent using liquid nitrogen, one isolation step using a low speed centrifugation, and three wash steps using high speed centrifugation. Pellets contained plasma, nuclear, and mitochondrial membranes, including their integral, peripheral, and anchored membrane proteins. The reproducibility of this method was verified by protein assay of four separate experiments with a CV of 7.7%, and by comparative LC-MS/MS label-free quantification of individual proteins between two experiments with 99% of the quantified proteins having a CV ?30%. Western blot and LC-MS/MS results of markers for cytoplasm, nucleus, mitochondria, and their membranes indicated that the enriched membrane fraction was highly pure by the absence of, or presence of trace amounts of, nonmembrane marker proteins. The average yield of membrane proteins was 237 ?g/10 million HT29-MTX cells. LC-MS/MS analysis of the membrane-enriched sample resulted in the identification of 2597 protein groups. In summary, the developed method is reproducible, produces a highly pure membrane fraction, and generates a high yield of membrane proteins.
Project description:A significant consequence of protein phosphorylation is to alter protein-protein interactions, leading to dynamic regulation of the components of protein complexes that direct many core biological processes. Recent proteomic studies have populated databases with extensive compilations of cellular phosphoproteins and phosphorylation sites and a similarly deep coverage of the subunit compositions and interactions in multiprotein complexes. However, considerably less data are available on the dynamics of phosphorylation, composition of multiprotein complexes or that define their interdependence. We describe a method to identify candidate phosphoprotein complexes by combining phosphoprotein affinity chromatography, separation by size, denaturing gel electrophoresis, protein identification by tandem mass spectrometry, and informatics analysis. Toward developing phosphoproteome profiling, we have isolated native phosphoproteins using a phosphoprotein affinity matrix, Pro-Q Diamond resin (Molecular Probes-Invitrogen). This resin quantitatively retains phosphoproteins and associated proteins from cell extracts. Pro-Q Diamond purification of a yeast whole cell extract followed by 1-D PAGE separation, proteolysis and ESI LC-MS/MS, a method we term PA-GeLC-MS/MS, yielded 108 proteins, a majority of which were known phosphoproteins. To identify proteins that were purified as parts of phosphoprotein complexes, the Pro-Q eluate was separated into two fractions by size, <100 kDa and >100 kDa, before analysis by PAGE and ESI LC-MS/MS and the component proteins queried against databases to identify protein-protein interactions. The <100 kDa fraction was enriched in phosphoproteins indicating the presence of monomeric phosphoproteins. The >100 kDa fraction contained 171 proteins of 20-80 kDa, nearly all of which participate in known protein-protein interactions. Of these 171, few are known phosphoproteins, consistent with their purification by participation in protein complexes. By comparing the results of our phosphoprotein profiling with the informational databases on phosphoproteomics, protein-protein interactions and protein complexes, we have developed an approach to examining the correlation between protein interactions and protein phosphorylation.
Project description:Associating changes in protein levels with the onset of cancer has been widely investigated to identify clinically relevant diagnostic biomarkers. In the present study, we analyzed sera from 205 patients recruited in the United States and Egypt for biomarker discovery using label-free proteomic analysis by LC-MS/MS. We performed untargeted proteomic analysis of sera to identify candidate proteins with statistically significant differences between hepatocellular carcinoma (HCC) and patients with liver cirrhosis. We further evaluated the significance of 101 proteins in sera from the same 205 patients through targeted quantitation by MRM on a triple quadrupole mass spectrometer. This led to the identification of 21 candidate protein biomarkers that were significantly altered in both the United States and Egyptian cohorts. Among the 21 candidates, ten were previously reported as HCC-associated proteins (eight exhibiting consistent trends with our observation), whereas 11 are new candidates discovered by this study. Pathway analysis based on the significant proteins reveals upregulation of the complement and coagulation cascades pathway and downregulation of the antigen processing and presentation pathway in HCC cases versus patients with liver cirrhosis. The results of this study demonstrate the power of combining untargeted and targeted quantitation methods for a comprehensive serum proteomic analysis, to evaluate changes in protein levels and discover novel diagnostic biomarkers. All MS data have been deposited in the ProteomeXchange with identifier PXD001171 (http://proteomecentral.proteomexchange.org/dataset/PXD001171).