High Throughput and Large Scale Proteomics Analysis Austin
- Slides: 35
High Throughput and Large Scale Proteomics Analysis Austin Yang, Ph. D. Department of Pharmaceutical Sciences, University of Southern California
Overview 1. Shotgun proteomics and ESI mass spectrometry 2. Proteomic data mining 3. and data visualization
12, 000 proteins
Are We Ready for Mammalian Proteomics ? Shotgun Proteomics 2 -D Gel Cytoskelatal Proteins m. M, 1 x 109 copies/cell Metabolism 0. 1 m. M, 1 x 108 Ribosomes 10 m. M, 1 x 107 Kinases 1 m. M, 1 x 106 Cyclins 0. 1 m. M, 1 x 105 Transcription factors 10 n. M, 1 x 104 Synaptic Markers 0. 1 n. M, 1 x 103
Advantages of Proteomics Using LC-MS/MS • No pre-selection of biased targets (hypothesis-free, open approach) • Protein variants are detected simultaneously • Protein isolation and detection are on a small scale (~ 10 fmol from complex mixtures – subcellular fractions, whole cells, or tissue) • Obtain sequence information of peptides (not just masses) and can sequence ~4, 000 proteins in a single experiment
Liquid Chromatography Quadrupole Ion Trap Tandem Mass Spectrometer
Electrospray vs Nanospray
Splitless Nano-Liquid Chromatography
Five Independent Loop Injections
10 -cycle Mud. PIT Analysis SCX (NH 4 OAc) RF#1 RF#2 100 m. M MSM Wash MSM MSS 600 m. M Wash 700 m. M MSM 800 m. M Wash 900 m. M MS 1000 m. M Wash MSM Wash MSS Wash MS 200 m. M 300 m. M 400 m. M 500 m. M
Multidimensional Protein Identification Technology (Mud. PIT) Digested protein complexes 0 -500 m. M NH 4 OAc SCX Column RP #1 500 400 300 200 100 RP #2 400 300 200 1, 000 -2, 000 Sequencing Attempts in 60 Minutes 20, 000 MS/MS spectra/day
Isotope-Coded Affinity Tags (ICAT)
Electrospray Ionization (ESI) Ions in gaseous phase Ions in solution LC Spray tip Ion source opening for the MS
Theoretical CID of a Tryptic Peptide + + F L G K + K b 3 y 1 + + CID G K b 2 + F L G K y 2 + + F L G K b 1 + F L G K y 3 Non-dissociated Parent ions Daughter ions y 1 + F L G K y 3 b 1 Relative Intensity Parent ions + MS/MS Spectrum y 2 b 2 K G L F L G F b 3 K m/z (464. 29)
Sequest. Queue (6, 000 dta x 50 = 300, 000 ms/ms scans)
Data Mining through SEQUEST and PAULA Database Search Time • Yeast ORFs (6, 351 entries) 52 sec: 0. 104 sec/s • Non-redundant protein (100 k entries) 3500 min: • EST (100 K entries, 3 -frames) 5 -10, 000 min:
SEQUEST Algorithm Step 1. Determine Parent STEP 1. Ion molecular Step 2. Theoretical MS/MS spectra SEQ 1 mass SEQ 2 SEQ 3 (Experimental MS/MS Spectrum) SEQ 4 500 peptides with masses closest to that of the parent ion are retrieved from a protein database. Computer generates a theoretical MS/MS Spectrum for each peptide sequence (SEQ 1, 2, 3, 4, …) ZSA-charge assignment Step 4. Scores are ranked and Protein Identifications are made based on these cross correlation scores. Step 3. STEP 3. Experimental Spectrum is compared with each theoretical spectra and correlation scores are assigned. Unified Scoring Function (Experimental MS/MS Spectrum)
One spectrum TWO protein identifications Spectrum A was used to search against NCBI human database: Macrophage inhibitory factor was identified Mol Cell Proteomics. 2003 Jul; 2(7): 428 -42. Same spectrum was used to search against non-redundant database. Bovine G-protein gamma was identified. Since the primary amino acid sequence of human G-protein gamma is almost identical to bovine, this protein was later identified as human G-protein Gamma. The initial false ID was due to an entry missing of human g-protein in human database. The sequence was later reentered Into the human database and the third search yielded correct ID. Fragment ions match both sequences are indicated by * Spectrum B has two additional ions matched to G-protein gamma
Distribution of Xcorr from correctly and incorrectly identified peptides
X-correlation vs Peptide length
Distribution of Xcorr vs Charge State
F-score and probability-based peptide assignment
Identification of modified LRP in APP/PS 1 Transgenic Mice
Neurotransmitter Receptors Tg Peptide A) 1. (Q 9 WV 18) Gamma-aminobutyric acid type B receptor, subunit 1 precursor (GABA-B-R 1) 2. (NP_032102. 1) gamma-aminobutyric acid (GABA-A) receptor, subunit rho 2 3. (NP_034382. 1) gamma-aminobutyric acid A receptor, gamma 1 4. (NP_033733. 1) cholinergic receptor, nicotinic, epsilon polypeptide; acetylcholine receptor 5. (NP_150372. 1) cholinergic receptor, muscarinic 3, cardiac; ACh. R M 3 6. (S 28058) serotonin receptor 5 7. (NP_031903. 1) dopamine receptor 3; D 3 receptor 8. (Q 60934) Glutamate receptor, ionotropic kainate 1 precursor (Glutamate receptor 5) 9. (I 49696) glutamate receptor chain B (version flip) B) 1. (NP_038589. 1) 5 -hydroxytryptamine (serotonin) receptor 3 A 2. (P 30545) Alpha-2 B adrenergic receptor (Alpha-2 B adrenoceptor) 3. (NP_032195. 1) glutamate receptor, ionotropic, NMDA 1 (zeta 1) 4. (NP_032198. 1) glutamate receptor, ionotropic, NMDA 2 D (epsilon 4); Glu. Repsilon 4 5. (I 49696) glutamate receptor chain B (version flip) C) 1 2. (NP_034428. 1) glycine receptor, beta subunit (JC 4262) glutamate transporter 2
Proteomic Data Visualization and Future Directions • information overload • data integration • ease of visualization
Network for NMDA and glutamate receptors
Network for NMDA and glutamate receptors (Zoom-in)
Scoring Algorithm for Spectral Analysis SEQUEST Raw Unidentified Spectra (~10, 000 -100, 000) SALSA Identified Sequence
SALSA Overview * product ion chargedloss neutral loss Mass difference A GD W T ion series • SALSA is a tool for identifying MS-MS spectra in Xcalibur analysis files that display specific user-defined characteristics. Because these characteristics correspond to structural features of a peptide, SALSA allows the user to selectively locate MS-MS spectra of specific peptides or their variant or modified forms.
Construction of SALSA ruler GAIIGLMGGVV GAIIGLMGGVV GAIIGLM GAIIGL GAIIG GAII GA GAI Methionine Oxidation 16 amu (one oxygen atom) m/z GAIIGLMGGV GAIIGLMGG GAIIGLM GAIIGL GAIIG GAII GA GAIIGLMGGVV
Absolute Quantification Analysis Quantification of Methionine Oxidation GAIIGLMVGGVV: +7 amu
- Small vs large scale maps
- The definition of map scale
- Map scale ratio
- Introduction to topographic maps
- Geography skills handbook
- Mini trans-blot module
- History of proteomics
- Sac seismic
- Prionproteine
- Comparative proteomics kit ii western blot module
- Comparative proteomics kit ii western blot module
- Comparative proteomics kit ii western blot module
- High throughput screening 원리
- High throughput phenotyping
- Mass_947
- High throughput satellite
- Berk atikoglu
- A comparison of approaches to large-scale data analysis
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- Throughput in networking
- The anatomy of a large scale hypertextual web search engine
- Oogoogle translate
- Large rotating air mass
- Small scale fermenter
- Large map scale
- Ultra large scale integrated circuit
- Large scale global investment
- Automatic wrappers for large scale web extraction
- Large scale fading in wireless communication
- Large-scale cluster management at google with borg
- Large scale interventions
- Large scale entry example
- Distbelief
- How do maps help focus the reader's attention
- Pregel: a system for large-scale graph processing
- Large scale systems