Target Discovery and Validation Reviews and Protocols

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Pancreatic Cancer 83 3.3.10. Sample Analysis (LC-MS/MS) The sample is automatically loaded onto the column by the autosampler in the HPLC system. The peptides are loaded onto the reverse phase column by using a linear gradient of 5–10% mobile phase B (90% acetonitrile, 0.4% acetic acid, and 0.005% heptafluorobutyric acid in water) during 6–8 min. No peptides will elute during this time interval. If needed, the loading time can be extended for additional washing or desalting of the sample. The peptides are subsequently separated and eluted from the column by 10–45% mobile phase B during 35–40 min, followed by 45–90% mobile phase B for 3 min. The column is finally rinsed flushed with 90% mobile phase B for 1 to 2 min and equilibrated in 5% mobile phase B for 3 min. The flow rate delivered from the pumps to the column(s) depends on the LC setup. In a tandem column setup, the flow rate should be 4 to 5 µL/min during loading and 1–1.5 µL/min for the single column setup. During peptide separation and elution, the flow rate is decreased to 250–300 nL/min for both setups. During equilibration of the column, the flow is again increased to 4 to 5 µL/min for tandem column setup and 1–1.5 µL/min for single column setup. Note that this program is only a rough guide and should be modified as required. 3.3.11. Database Search and Validation The final step of the analysis is searching the generated LC-MS/MS data by using a search engine. Several search engines are available (e.g., Mascot, SEQUEST, XTandem, and Spectrum Mill) that use their own individual search algorithms and scoring systems. Here, the Mascot search engine (version 2.0) is used as an example. Before the search can be performed, peak-list files have to be generated. Peak-list files are made from the files initially recorded during the LC-MS/MS analysis (named, e.g. RAW-files on a Micromass instrument) and contain information about the mass of the precursor selected for MS/MS fragmentation and the masses and relative intensity of the fragment ions. Depending on the type of instrument used for the LC-MS/MS analysis, the search parameters have to be adjusted accordingly. The following Mascot search parameters can be used for high-resolution type instruments (e.g., Micromass QTOF and Sciex Q-STAR). Several search parameters have to be specified on the Mascot MS/MS ion-search, including peptide tolerance (set at 0.2 Daltons), MS/MS tolerance (set at 0.2 Daltons), enzyme (used in digestion, trypsin), missed cleavages (set at 1 or 2), fixed modifications (set carbamidomethylation on cysteins), variable modifications (set oxidation on methionine), peptide charge (set +1, +2, +3), and monoi-sotopic mass. One also has to specify the type of database (e.g., NCBInr, SwissProt, or RefSeq) and taxonomy (e.g. human, mouse, bacteria, or fungi) the peak list files has to be
84 Beaty et al. search in. A widely used nonredundant database is RefSeq (53) (http:// www.ncbi.nlm.nih.gov/RefSeq/) from National Center for Biotechnology Information, which contains 1,310.800 entries from 2780 organisms. One very important aspect of the final analysis is verification of the data obtained from the database searches. Far from all proteins retrieved from the database search are correct. Peptides identified by the Mascot search engine with a peptide score under 30–40 are usually false positives and have to be discarded from the data set. In cases where protein identification is based on a single peptide, special caution has to be taken. The amino acid sequence identified by the Mascot search engine has to be verified manually to make sure that the MS/MS spectrum truly corresponds to the peptide sequence predicted by Mascot. Manual validation is therefore essential to avoid a large number of false positives in the list of identified proteins. 4. Notes 1. After processing, the array spots will no longer be visible, so demarking the boundaries is important for later positioning the labeled sample and cover slip correctly. 2. Rehydration should produce spot sizes that are enlarged by approx 20%, with the DNA distributed more uniformly within spots. 3. Bring ddH2O to a boil in the Pyrex dish and then remove from heat. Add microarrays in slide rack immediately after the boiling (bubbling) has subsided. 4. For processing oligonucleotide arrays, UV-crosslink by using 70 mJ, wash arrays in 0.2% SDS at room temperature for 10 min, wash three times in ddH2O at room temperature for 5 min each, rinse in 95% EtOH for 1 min, and then spin-dry in centrifuge at 500 rpm. 5. Often by convention, the test sample is labeled with Cy5, whereas the reference sample is labeled with Cy3. 6. Centrifuge times are estimates. If necessary, here and in subsequent Microcon steps, spin in additional 1-min increments until volume of retained solution is approx 20 µL. 7. This additional wash step serves to further remove unincorporated fluorescent nucleotides. If labeling is successful, the retained labeled cDNA mixture should be light blue. 8. PolyA and human Cot-1 preannealing serves to block undesirable hybridization to polyA tails and highly repetitive DNA, respectively, contained in a subset of cDNA microarray elements. Yeast tRNA functions to block nonspecific hybridization. 9. A total volume of 40 µL for the hybridization solution is appropriate when using a 22- × 60-mm cover slip. If using a different-sized cDNA microarray and cover slip, adjust the total volume of hybridization solution accordingly, while maintaining final SSC and SDS concentrations. 10. The described hybridization protocol is optimized for cDNA microarrays. For oligonucleotide microarrays, improved hybridization sensitivity and specificity
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METHODS IN MOLECULAR BIOLOGY 360 T
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M E T H O D S I N M O L E C U L A R
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© 2007 Humana Press Inc. 999 River
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vi Preface get. Approaches to targe
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viii Contents 10 Transgenic Animal
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x Contributors SAHOHIME MATSUMOTO
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xii Contents of Volume 2 12 Validat
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2 Sioud disease pathogenesis and pe
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4 Sioud A more fruitful approach fo
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6 Sioud both transient and permanen
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8 Sioud serum biomarkers. This syne
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10 Sioud Fig. 2. Schematic of targe
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12 Sioud 13. Magin, T. M. (1998) Le
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Harnessing the Human Genome 15 The
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Harnessing the Human Genome 17 Fig.
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Harnessing the Human Genome 23 The
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Harnessing the Human Genome 27 repr
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Harnessing the Human Genome 29 14.
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Harnessing the Human Genome 31 45.
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Page 65 and 66: 52 Imoto et al. Table 3 List of Roo
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Page 104 and 105: 5 Molecular Classification of Breas
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134 Matsumoto, Miyagishi, and Taira
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144 Fig. 1. The ribozyme-expression
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146 Sano and Taira 5. 10X L (low-sa
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148 Sano and Taira ribozymes may cl
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150 Fig. 3. A system for the identi
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152 Sano and Taira 4. Notes 1. We r
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9 Production of siRNA- and cDNA-Tra
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Transfected Cell Arrays 157 Fig. 1.
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Transfected Cell Arrays 159 2. The
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Transfected Cell Arrays 161 5. Simp
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164 Houdebine Fig. 1. Different met
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166 Houdebine concentrations become
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168 Houdebine Fig. 2. Major methods
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170 Houdebine integrate into the me
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172 Houdebine 2.2.3. Knock-In Into
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174 Houdebine as insulators. The co
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176 Houdebine Fig. 5. Different met
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178 Houdebine systems. Moreover, st
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180 Houdebine contribute to generat
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182 Houdebine Fig.7. Example of a v
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184 Houdebine more extensively. Tra
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186 Houdebine and stroma. Several o
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188 Houdebine explained at the mole
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190 Houdebine of the intestinal epi
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192 Houdebine interference of the g
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194 Houdebine 17. Whitelaw, C. B. A
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196 Houdebine 51. Bell, A. C., West
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198 Houdebine 86. Carmichael, G. G.
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200 Houdebine 121. Pailhoux, E., Vi
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202 Houdebine 156. Auerbach, A. B.,
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204 Vijayaraj, Söhl, and Magin 1.
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206 Vijayaraj, Söhl, and Magin Fig
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208 Vijayaraj, Söhl, and Magin fil
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210 Table 1 Orthologous Human and M
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212 Table 2 Orthologous Human and M
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214 Vijayaraj, Söhl, and Magin ulc
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216 Vijayaraj, Söhl, and Magin of
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218 Vijayaraj, Söhl, and Magin sug
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220 Vijayaraj, Söhl, and Magin abs
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222 Vijayaraj, Söhl, and Magin 1.2
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224 Vijayaraj, Söhl, and Magin Fig
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226 Vijayaraj, Söhl, and Magin gen
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228 Vijayaraj, Söhl, and Magin the
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230 Vijayaraj, Söhl, and Magin f.
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234 Vijayaraj, Söhl, and Magin b.
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240 Vijayaraj, Söhl, and Magin alt
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242 Table 3 Time Schedule For Aggre
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250 Vijayaraj, Söhl, and Magin 101
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12 The HUVEC/Matrigel Assay An In V
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256 Skovseth, Küchler, and Haralds
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270 Iversen and Sørensen witnessed
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272 Iversen and Sørensen Fig. 1. P
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274 Iversen and Sørensen the core
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14 An Overview of the Immune System
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Overview of Immune System 279 diffe
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Overview of Immune System 281 Fig.
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Overview of Immune System 283 then
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Overview of Immune System 285 expre
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Overview of Immune System 287 Once
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Overview of Immune System 289 solub
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Overview of Immune System 291 amino
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Overview of Immune System 293 (unre
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Overview of Immune System 297 the c
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Overview of Immune System 299 (44).
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Overview of Immune System 301 demon
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Overview of Immune System 307 some
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Overview of Immune System 309 sera
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Overview of Immune System 313 measu
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Overview of Immune System 315 42. H
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Overview of Immune System 317 74. D
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15 Potential Target Antigens for Im
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Tumor Antigen Discovery 321 develop
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Tumor Antigen Discovery 323 panel b
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Tumor Antigen Discovery 325 16. Joc
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16 Identification of Tumor Antigens
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Immunoproteomics 329 by “shot gun
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Immunoproteomics 331 isoelectric fo
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Immunoproteomics 333 3. 2D-PAGE is
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17 Protein Arrays A Versatile Toolb
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Protein Arrays 337 Table 1 Classifi
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Protein Arrays 339 fractions from c
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Protein Arrays 341 combinatorial sc
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Protein Arrays 343 The ideal proteo
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Protein Arrays 345 18. Cekaite, H.
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Protein Arrays 347 49. Yuko Kawahas
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Index 349 Index A Acetyl-CoA carbox
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Index 351 conditional by using FRT
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Index 353 Recombinant tumor antigen
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