Project description:The TripleTOF 5600 System, a hybrid quadrupole time-of-flight mass spectrometer, was evaluated to explore the key figures of merit in generating peptide and protein identifications that included spectral acquisition rates, data quality, proteome coverage, and biological depth. Employing a Saccharomyces cerevisiae tryptic digest, careful consideration of several performance features demonstrated that the speed of the TripleTOF contributed most to the resultant data. The TripleTOF system was operated with 8, 20, and 50 MS/MS events in an effort to compare with other MS technologies and to demonstrate the abilities of the instrument platform.
Project description:The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.
Project description:We analyzed total proteome of three methyltransferase gene knockouts strains of Escherichia coli: ΔrsmF (JW5301), ΔrlmC (JW2756), ΔrlmE (JW3146) from Keio collection and wild type (WT). Proteins were assessed using IDA approach (i.e. Information Dependent Acquisition) and SWATH (Data-Independent Acquisition) on Sciex TripleTof 5600+ mass‐spectrometer with a NanoSpray III ion source (ABSciex, Canada) coupled to a NanoLC Ultra 2D+ nano‐HPLC system (Eksigent). Dataset covers 16 samples.
Project description:Plasma proteomic experiments performed rapidly and economically using several of the latest high-resolution mass spectrometers were compared. Four quantitative hyperfractionated plasma proteomics experiments were analyzed in replicates by two AB SCIEX TripleTOF 5600 and three Thermo Scientific Orbitrap (Elite/LTQ-Orbitrap Velos/Q Exactive) instruments. Each experiment compared two iTRAQ isobaric-labeled immunodepleted plasma proteomes, provided as 30 labeled peptide fractions, and 480 LC-MS/MS runs delivered >250 GB of data in 2 months. Several analysis algorithms were compared. At 1% false discovery rate, the relative comparative findings concluded that the Thermo Scientific Q Exactive Mass Spectrometer resulted in the highest number of identified proteins and unique sequences with iTRAQ quantitation. The confidence of iTRAQ fold-change for each protein is dependent on the overall ion statistics (Mascot Protein Score) attainable by each instrument. The benchmarking also suggested how to further improve the mass spectrometry parameters and HPLC conditions. Our findings highlight the special challenges presented by the low abundance peptide ions of iTRAQ plasma proteome because the dynamic range of plasma protein abundance is uniquely high compared with cell lysates, necessitating high instrument sensitivity.
Project description:MS²PIP is a data-driven tool that accurately predicts peak intensities for a given peptide's fragmentation mass spectrum. Since the release of the MS²PIP web server in 2015, we have brought significant updates to both the tool and the web server. In addition to the original models for CID and HCD fragmentation, we have added specialized models for the TripleTOF 5600+ mass spectrometer, for TMT-labeled peptides, for iTRAQ-labeled peptides, and for iTRAQ-labeled phosphopeptides. Because the fragmentation pattern is heavily altered in each of these cases, these additional models greatly improve the prediction accuracy for their corresponding data types. We have also substantially reduced the computational resources required to run MS²PIP, and have completely rebuilt the web server, which now allows predictions of up to 100 000 peptide sequences in a single request. The MS²PIP web server is freely available at https://iomics.ugent.be/ms2pip/.
Project description:Cone snails produce highly complex venom comprising mostly small biologically active peptides known as conotoxins or conopeptides. Early estimates that suggested 50-200 venom peptides are produced per species have been recently increased at least 10-fold using advanced mass spectrometry. To uncover the mechanism(s) responsible for generating this impressive diversity, we used an integrated approach combining second-generation transcriptome sequencing with high sensitivity proteomics. From the venom gland transcriptome of Conus marmoreus, a total of 105 conopeptide precursor sequences from 13 gene superfamilies were identified. Over 60% of these precursors belonged to the three gene superfamilies O1, T, and M, consistent with their high levels of expression, which suggests these conotoxins play an important role in prey capture and/or defense. Seven gene superfamilies not previously identified in C. marmoreus, including five novel superfamilies, were also discovered. To confirm the expression of toxins identified at the transcript level, the injected venom of C. marmoreus was comprehensively analyzed by mass spectrometry, revealing 2710 and 3172 peptides using MALDI and ESI-MS, respectively, and 6254 peptides using an ESI-MS TripleTOF 5600 instrument. All conopeptides derived from transcriptomic sequences could be matched to masses obtained on the TripleTOF within 100 ppm accuracy, with 66 (63%) providing MS/MS coverage that unambiguously confirmed these matches. Comprehensive integration of transcriptomic and proteomic data revealed for the first time that the vast majority of the conopeptide diversity arises from a more limited set of genes through a process of variable peptide processing, which generates conopeptides with alternative cleavage sites, heterogeneous post-translational modifications, and highly variable N- and C-terminal truncations. Variable peptide processing is expected to contribute to the evolution of venoms, and explains how a limited set of ? 100 gene transcripts can generate thousands of conopeptides in a single species of cone snail.
Project description:Dedifferentiated liposarcoma (DDLPS) is an aggressive mesenchymal cancer marked by amplification of MDM2, an inhibitor of the tumor suppressor TP53. DDLPS patients with higher MDM2 amplification have lower chemotherapy sensitivity and worse outcome than patients with lower MDM2 amplification. We hypothesized that MDM2 amplification levels may be associated with changes in DDLPS metabolism. Six patient-derived DDLPS cell line models were subject to comprehensive metabolomic (Metabolon) and lipidomic (SCIEX 5600 TripleTOF-MS) profiling to assess associations with MDM2 amplification and their responses to metabolic perturbations. Comparing metabolomic profiles between MDM2 higher and lower amplification cells yielded a total of 17 differentially abundant metabolites across both panels (FDR < 0.05, log2 fold change < 0.75), including ceramides, glycosylated ceramides, and sphingomyelins. Disruption of lipid metabolism through statin administration resulted in a chemo-sensitive phenotype in MDM2 lower cell lines only, suggesting that lipid metabolism may be a large contributor to the more aggressive nature of MDM2 higher DDLPS tumors. This study is the first to provide comprehensive metabolomic and lipidomic characterization of DDLPS cell lines and provides evidence for MDM2-dependent differential molecular mechanisms that are critical factors in chemoresistance and could thus affect patient outcome.
Project description:Blood as connective tissue potentially contains evidence of all processes occurring within the organism, at least in trace amounts (Petricoin et al., 2006) . Because of their small size, peptides penetrate cell membranes and epithelial barriers more freely than proteins. Among the peptides found in blood, there are both fragments of proteins secreted by various tissues and performing their function in plasma and receptor ligands: hormones, cytokines and mediators of cellular response (Anderson et al., 2002) . In addition, in minor amounts, there are peptide disease markers (for example, oncomarkers) and even foreign peptides related to pathogenic organisms and infection agents. To propose an approach for detailed peptidome characterization, we carried out an LC-MS/MS analysis of blood serum and plasma samples taken from 20 healthy donors on a TripleTOF 5600+ mass-spectrometer. We prepared samples based on our previously developed method of peptide desorption from the surface of abundant blood plasma proteins followed by standard chromatographic steps (Ziganshin et al., 2011) . The mass-spectrometry peptidomics data presented in this article have been deposited to the ProteomeXchange Consortium (Deutsch et al., 2017)  via the PRIDE partner repository with the dataset identifier PXD008141 and 10.6019/PXD008141.
Project description:Background:Nephrolithiasis is a systemic metabolic disease with a high prevalence worldwide and is closely related to lipid-mediated oxidative stress and inflammation. Orthosiphon stamineus Benth. (OS) is a traditional medicinal herb mainly containing flavonoids, caffeic acid derivatives, and terpenoids, which has the effect of treating urinary stones. However, the active ingredients of OS for the treatment of kidney stones and their regulatory mechanisms remain unknown. As a powerful antioxidant, flavonoids from herbs can mitigate calcium oxalate stone formation by scavenging radical. Thus, this work focused on EtOAc extract of OS (EEOS, mainly flavonoids) and aimed to reveal the potential intrinsic mechanism of EEOS in the treatment of kidney stones disease. Methods:Firstly, 75% ethanol extract of OS was further extracted with EtOAc to obtain EtOAc extract containing 88.82% flavonoids. Secondly, the extract was subjected to component analysis and used in animal experiments. Then, an untargeted lipidomics based on ultrahigh performance liquid chromatography coupled with TripleTOF 5600 mass spectrometer (UPLC-QTOF-MS) was performed to test the lipid changes of kidneys in the control group, model group and EEOS treatment groups. Finally, multivariate statistical analysis was used to identify differences between the lipid profiles of mice in the model group and the EEOS group. Results:Fifty-one lipid metabolites were significantly different between the mice in the model group and the EEOS intervention group, including glycerophosphocholines, glycerophosphoethanolamines, glycerophosphoinositols, and glycerophosphoglycerols. And the composition of glycerophospholipids-esterified ?-3 polyunsaturated fatty acids and glycerophospholipid subclasses in the kidneys of the EEOS group significantly changed compared to model group. Conclusions:The EEOS can inhibit the stones formation by improving oxidative stress and inflammation mediated by glycerophospholipid metabolism. This study reveals the potential mechanism of EEOS for kidney stones treatment at the lipid molecule level, providing a new direction for further study of the efficacy of OS.
Project description:In past two decades, numerous lipidomics approaches based on mass spectrometry with or without liquid chromatography separation have been established for identification and quantification of lipids in plants. In this study, we developed an efficient and comprehensive lipidomics approach based on UPLC with an Acquity UPLCTM BEH C18 column coupled to TripleTOF using ESI in positive ion mode and MS/MSALL scan for data collection. Lipid extract was prepared to 2 mg/ml solution according to dry tissue weight and mixed with 13 kinds of internal standards including PA, PC, PE, and PG. Each analysis required single injection of 5-10 ?l lipid solvent and completed in 32 min. A target method dataset was generated using the LipidView software for prediction of the accurate mass of target lipid species. The dataset was uploaded into the PeakView to create processing datasets to search target lipid species, which achieved batch data processing of multiple samples for lipid species-specific identification and quantification. As proof of concept, we profiled the lipids of different tissues of rapeseed. Thirteen lipid classes including 218 glycerolipids were identified including 46 TAGs, 15 DAGs, 20 PCs, 24 PEs, 13 PGs, 14 PIs, 26 PSs, 12 PAs, 16 MGDGs, 16 DGDGs, 6 LysoPCs, 5 LysoPEs, and 5 LysoPGs. Together, our approach permits the analysis of glycerolipids in plant tissues with simplicity in sample analysis and data processing using UPLC-TripleTOF.