FIGURE 5. Plot of peptide charge state ratios. Quality Control Concept Figure 6 shows a concept for the implementation of quality control as system suitability.

Slides:



Advertisements
Similar presentations
Protein Quantitation II: Multiple Reaction Monitoring
Advertisements

Using Skyline to Monitor Long- Term Performance Metrics of High-Resolution Mass Spectrometers J. Will Thompson and M. Arthur Moseley Duke Proteomics Core.
The Proteomics Core at Wayne State University
Conclusion The workflow presented provides a strategy to incorporate unbiased glycopeptide identification to generate an initial list of targets for data.
UC Mass Spectrometry Facility & Protein Characterization for Proteomics Core Proteomics Capabilities: Examples of Protein ID and Analysis of Modified Proteins.
De Novo Sequencing v.s. Database Search Bin Ma School of Computer Science University of Waterloo Ontario, Canada.
Proteomics Informatics – Protein identification II: search engines and protein sequence databases (Week 5)
Announcements: Proposal resubmissions are due 4/23. It is recommended that students set up a meeting to discuss modifications for the final step of the.
Proteomics Informatics Workshop Part I: Protein Identification
Improving Throughput for Highly Multiplexed Targeted Quantification Methods Using Novel API-Remote Instrument Control and State-Model Data Acquisition.
Overview Purpose: Accurately estimate peptide retention based on spectrum library data utilizing commonly observed peptides in place of synthetic standards.
Proteomics Josh Leung Biology 1220 April 13 th, 2010.
Proteomics Informatics (BMSC-GA 4437) Course Director David Fenyö Contact information
Spectral Counting. 2 Definition The total number of identified peptide sequences (peptide spectrum matches) for the protein, including those redundantly.
Proteomics Informatics Workshop Part III: Protein Quantitation
Fa 05CSE182 CSE182-L9 Mass Spectrometry Quantitation and other applications.
Proteomics Informatics – Overview of Mass spectrometry (Week 2)
Evaluated Reference MS/MS Spectra Libraries Current and Future NIST Programs.
Conclusion  Comprehensive workflow identified approximately 70% more high confident peptide as compare to general search strategy.  The comprehensive.
Tryptic digestion Proteomics Workflow for Gel-based and LC-coupled Mass Spectrometry Protein or peptide pre-fractionation is a prerequisite for the reduction.
Comparison of chicken light and dark meat using LC MALDI-TOF mass spectrometry as a model system for biomarker discovery WP 651 Jie Du; Stephen J. Hattan.
Production of polypeptides, Da, and middle-down analysis by LC-MSMS Catherine Fenselau 1, Joseph Cannon 1, Nathan Edwards 2, Karen Lohnes 1,
Chapter 9 Mass Spectrometry (MS) -Microbial Functional Genomics 조광평 CBBL.
HPP Preliminary Results La Cristalera, August 2012 Montserrat Carrascal, Joan Villanueva, Joaquín Abián LP-CSIC/UAB.
Center for Human Health and the Environment
An introduction and possible applications Ariane Kahnt
Mass spectrometry session. Summary Fiehn (1) Standardization important Reporting important, but has to be feasible Does not matter which MS instrument.
Proteomics and Biomarker Discovery “Research-grade” Targeted Proteomics Assay Development: PRMs for PTM Studies with Skyline or, “How I learned to ditch.
Acknowledgements This work is supported by NSF award DBI , and National Center for Glycomics and Glycoproteomics, funded by NIH/NCRR grant 5P41RR
Common parameters At the beginning one need to set up the parameters.
Integrated Targeted Quantitative Method for Insulin and its Therapeutic Analogs Eric Niederkofler 1, Dobrin Nedelkov 1, Urban Kiernan 1, David Phillips.
Analysis of Complex Proteomic Datasets Using Scaffold Free Scaffold Viewer can be downloaded at:
Additional file 1 1.1Workflow of large-scale proteomic analysis of normal human kidney glomerulus 1.2Detailed procedure of LC-MS/MS analysis Additional.
A Comprehensive Comparison of the de novo Sequencing Accuracies of PEAKS, BioAnalyst and PLGS Bin Ma 1 ; Amanda Doherty-Kirby 1 ; Aaron Booy 2 ; Bob Olafson.
A Phospho-Peptide Spectrum Library for Improved Targeted Assays Barbara Frewen 1, Scott Peterman 1, John Sinclair 2, Claus Jorgensen 2, Amol Prakash 1,
Software Project MassAnalyst Roeland Luitwieler Marnix Kammer April 24, 2006.
Improving the Detection of Hydrophilic Peptides for Increased Protein Sequence Coverage and Enhanced Proteomic Analyses Brian S. Hampton 1 and Amos H.
EBI is an Outstation of the European Molecular Biology Laboratory. In silico analysis of accurate proteomics, complemented by selective isolation of peptides.
Isotope Labeled Internal Standards in Skyline
Proteomics Informatics (BMSC-GA 4437) Instructor David Fenyö Contact information
Salamanca, March 16th 2010 Participants: Laboratori de Proteomica-HUVH Servicio de Proteómica-CNB-CSIC Participants: Laboratori de Proteomica-HUVH Servicio.
C HROMOSOME 16 Marta Mendes Ignacio Casal Centro de Investigaciones Biológicas August 2012.
The world leader in serving science For Research Use Only. Not for use in diagnostic procedures Quantitative Analysis of 4 Immunosuppressant Drugs in Whole.
DIA Method Design, Data Acquisition, and Assessment
Introduction to Liquid Phase Mass Spectrometry
Forensic Toxicology Use Only Analysis of ETG, ETS using the Thermo Scientific Exactive Mass Spectrometer Kent Johnson Fortes lab, Portland Oregon.
Collecting and mining mass spectrometry quality control data Wout Bittremieux, Pieter Kelchtermans, Dirk Valkenborg, Lennart Martens, Bart Goethals, Kris.
H M Arif Ullah, Hye Jin Chung*
Plasma Free Metanephrines Analysis using LC-MS/MS with Porous Graphitic Carbon Column Xiang He (Kevin) and Marta Kozak Thermo Fisher Scientific.
ABRF 2017 Annual Meeting Workflow Interest Network (WIN) Presentation A QC And Benchmark Study Of LC-MS/MS Methods Among MS Laboratories.
Table 1. Quality Parameters Being Considered for Evaluation
Multi-Analyte LC-MS/MS Methods – Best Practice.
An integrated GC-MS workflow solution for the determination of (semi)volatiles in drinking water and solid waste according to the U.S. EPA guidelines B.
Dr Berwyck Poad Compiled: 3 February 2017 Updated: 28 March 2017
Open source tools for data analysis
Fan Liu Utrecht University, The Netherlands
KTYDSYLGDDYVR Linearity
PROTOCOL OPTIMIZATION
Now, More Than Ever, Proteomics Needs Better Chromatography
Relative quantitation of phosphopeptides from conditioned media from subtype specific breast cancer cell lines. Relative quantitation of phosphopeptides.
Top-down protein identification.
Overview of the analytical workflow used in this study and a representative MS/MS spectrum.a, Overview of the analytical workflow used in this study. Overview.
Is Proteomics the New Genomics?
Shotgun Proteomics in Neuroscience
Stability and variation of metrics over a range of sample injection amounts. Stability and variation of metrics over a range of sample injection amounts.
Performance metrics for triplicate analyses of a tryptic digest of the CPTAC yeast reference proteome on four LTQ-Orbitraps at three different sites in.
Illustration of chromatography metric C-2A applied to LC-MS/MS data from three Thermo LTQ systems in analyses of yeast proteome samples in CPTAC Study.
Top-down analysis of intact bovine carbonic anhydrase II by LTQ Orbitrap Velos. Top-down analysis of intact bovine carbonic anhydrase II by LTQ Orbitrap.
Mass spectrometry (MS) is an analytical technique that can be used to determine the mass, elemental composition or chemical structure of molecules. Mass.
Presentation transcript:

FIGURE 5. Plot of peptide charge state ratios. Quality Control Concept Figure 6 shows a concept for the implementation of quality control as system suitability test as a system check before samples are analyzed and a concept for including a quality control sample in the sample queue. After the data acquisition of the quality control sample is finished, a quality control check is done automatically and the system is stopped if it does not fulfill minimum quality requirements. FIGURE 6. Outlook on a quality control system within Xcalibur / Proteome Discoverer software. 1. System suitability test QC sample and QC analysis, QC sample re-injection after corrective actions if system shows low performance 2. Quality control sample in sample sequence QC sample in sequence (and sequence pause if QC shows low system performance) Conclusion New Rawputator node allows  Extraction of additional dynamic precursor ion information  Diagnosis of instrument performance (LC + MS) and sample integrity  Identification of outliers  Method development and optimization References 1.Rudnick PA et al. Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses. Mol Cell Proteomics Feb;9(2): Köcher T, Pichler P, Swart R, Mechtler K. Quality control in LC-MS/MS. Proteomics Mar;11(6): All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others. Overview Purpose: Implementation of proteomics data evaluation for quality control and method optimization. Methods: Hybrid linear ion trap-Orbitrap TM mass spectrometer with specialized proteomics software. Results: Rawputator tool delivers quantitative system performance assessment, method optimization and result verification. Introduction One of the biggest recurring questions in proteomics in a high-throughput environment is whether or not all parameters in the acquisition method are set optimally and the acquired data meets your quality criteria. Good practice therefore is to include quality controls in between the samples to assess the system performance. Figure 1 shows the system in a proteomic workflow which comprises sample preparation as well as LC, MS and data analysis. Why quality control? Optimum performance of the analytical system for the reproducible analysis of complex samples Identification of the source of the sub-optimal performance and variability Evaluation of the impact of the changes or improvements in the analytical system Documentation of the system performance metrics to support the assessment of the proteomic differences between biologically interesting samples Methods Sample Preparation Different enzymatic degradation preparations of complex proteomes were prepared using standard protocols. Liquid Chromatography All samples were separated by a Thermo Scientific EASY-nLC II liquid chromatograph using a peptide trap (C18 BioBasic, 100 μm inner diameter, 2 cm length) and a C18 analytical column (C18 BioBasic, 75 μm inner diameter, 10 cm length, both NanoSeparations, NL), at a flow rate of 300 nL/min using standard data-dependent acquisition methods. Mass Spectrometry Proteomic data sets were acquired using a Thermo Scientific LTQ Orbitrap Velos hybrid mass spectrometer. Data Analysis Data analysis was done using Thermo Scientific Proteome Discoverer software evaluation version 1.3. FIGURE 1. Proteomic workflow. Results Rawputator Node in Proteome Discoverer Software The Rawputator node can be easily added to any database search workflow within Proteome Discoverer TM software and extracts from the raw file additional dynamic precursor ion parameter per MS/MS spectrum as shown in Figure 2. The extracted values are stored in the.msf search output format. The additional time for the extraction is almost neglectable as well as the file size increase of the.msf output. The big advantage of having all that information in the search output is the additional connection to the search score. This can be used to evaluate the system performance. FIGURE 2. Rawputator node in Proteome Discoverer software. Lockmass Correction One example is to plot the lockmass correction over time (see Figure 3). Low (internal) lockmass correction values indicate on the one hand a valid external mass calibration and on the other hand indicate appropriate external mass calibration intervals. FIGURE 3. Lockmass correction over time. Charge state ratios One example for a digestion quality check is the plot of the charge state ratios of all ions triggered for MS/MS. Figure 4 shows a plot of all precursor ions triggered for MS/MS per charge state and identified peptides per charge state for a single run. If the same enzyme is used for digestion and other instrument parameters are not changed then the ratio of the triggered precursor ions (2+/3+, 2+/4+, 3+/4+,...) should be on the same level (see Figure 5). This plot also allows the identification of possible outliers. In this example the same sample is analyzed in triplicates with different gradient lengths. The number of identified proteins is for the 90-min and 45-min runs at the same level but for the 75-min and 60-min runs one outlier per triplicate can be spotted. For 75-min run 2 and for 60-min run 3 shows deviation from the normal distribution for the precursor ion charge states as well as in the number of identified proteins. FIGURE 4. Number of precursor ions triggered for MS/MS and identified peptides per charge state. Rawputator – A New Tool to Combine Proteomic Data Mining PP443 with Method Development, Result Validation and Quality Control Martin Zeller, Bernard Delanghe, Christoph Henrich, Torsten Ueckert Thermo Fisher Scientific, Bremen, Germany Sample preparation Mass spectrometryData analysis Proteome Digest Ionization (ESI) Full MS MS/MS Quantitation Identification Extraction of the dynamic parameter: - Precursor S/N - TIC - Ion inject time - Elapsed scan time - Effective collision energy [eV] - Lockmass correction Additional „costs“: - ~ 6%.msf file size increase - < 3 min per search job (complex cell lysate sample, MS/MS)