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Slide 1 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R
Slide 2 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose).
Slide 3 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation?
Slide 4 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays
Slide 5 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression
Slide 6 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts)
Slide 7 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein.
Slide 8 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values.
Slide 9 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography.
Slide 10 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose.
Slide 11 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet.
Slide 12 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins.
Slide 13 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated.
Slide 14 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein.
Slide 15 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… )
Slide 16 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?)
Slide 17 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged.
Slide 18 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more.
Slide 19 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots).
Slide 20 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes
Slide 21 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias?
Slide 22 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias? mRNA protein correlation rp = 0.93 Lets take a closer look… total: rp = 0.35 inner set:
Slide 23 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias? mRNA protein correlation rp = 0.93 Lets take a closer look… total: rp = 0.35 inner set: including progressively more, and higher-abundance, proteins in each calculation
Slide 24 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias? mRNA protein correlation rp = 0.93 Lets take a closer look… total: rp = 0.35 inner set: including progressively more, and higher-abundance, proteins in each calculation Discussion - conclusions Codon bias, an indicator of the boundaries of current 2D gel proteome analysis technology. A promising approach is the use of narrow-range focusing gels. Current proteome technology is incapable of analyzing low-abundance regulatory proteins without employing an enrichment method. For higher eukaryotes the detection of low-abundance proteins would be even harder.
Slide 25 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias? mRNA protein correlation rp = 0.93 Lets take a closer look… total: rp = 0.35 inner set: including progressively more, and higher-abundance, proteins in each calculation Discussion - conclusions Codon bias, an indicator of the boundaries of current 2D gel proteome analysis technology. A promising approach is the use of narrow-range focusing gels. Current proteome technology is incapable of analyzing low-abundance regulatory proteins without employing an enrichment method. For higher eukaryotes the detection of low-abundance proteins would be even harder. Discussion – words of the wise. Gygi et al: “This study revealed that transcript levels provide little predictive value with respect to the extent of protein expression.” Futcher et al: “there is a good correlation between protein abundance and mRNA abundance for the proteins that we have studied”.
Slide 26 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias? mRNA protein correlation rp = 0.93 Lets take a closer look… total: rp = 0.35 inner set: including progressively more, and higher-abundance, proteins in each calculation Discussion - conclusions Codon bias, an indicator of the boundaries of current 2D gel proteome analysis technology. A promising approach is the use of narrow-range focusing gels. Current proteome technology is incapable of analyzing low-abundance regulatory proteins without employing an enrichment method. For higher eukaryotes the detection of low-abundance proteins would be even harder. Discussion – words of the wise. Gygi et al: “This study revealed that transcript levels provide little predictive value with respect to the extent of protein expression.” Futcher et al: “there is a good correlation between protein abundance and mRNA abundance for the proteins that we have studied”. Discussion – biases Codon Bias. Long half lives. Low abundance proteins were not found. (T.Fs, kinases etc.) SAGE data. Met’s processed away. Comigration. Different statistical manipulations.
Slide 27 - Yeast A sampling of the yeast proteome. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI. Correlation between protein and mRNA abundance in yeast. Gygi SP, Rochon Y, Franza BR, Aebersold R Objectives Gather quantitative data for protein abundance. => Create database for yeast proteins. Correlation between mRNA level to corresponding proteins level. Correlation between codon bias* and protein levels. Protein expression patterns under various environmental conditions (i.e. ethanol/glucose). Motivation Quantitative analysis of global mRNA levels currently is a preferred method for the analysis of the state of cells and tissues. mRNA level <= ? => protein level Several methods which either provide absolute mRNA abundance or relative mRNA levels in comparative analyses are easy to apply. * Fast * Very Sensitive why claculate mRNA and protein correlation? But But But … We worked so hard on micro arrays Why Yeast? Low complexity(relative lack of introns), perfect for lab work, unicellular , well understood physiology, etc.. The genome of the yeast was sequenced. The number of mRNA molecules for each expressed gene was recently (1999) measured. (SAGE*) Codon bias tables are well known. * SAGE – Serial Analysis of Gene Expression SAGE* – mRNA frequency tables. Generating a single unique sequence tag (15 bp) of each mRNA’s 3’-most cutting site for NlaIII of the Yeast Cell. Concatenation into a single molecule and then sequencing, revealing the identity of multiple tags simultaneously. Computer software was used to calculate mRNA abundance, and creating the frequency tables. * SAGE – Serial Analysis of Gene Expression * 20,000 transcripts were made. * Estimated 15,000 mRNA molecules per cell. a 1.3-fold coverage even for mRNA molecules present at a single copy per cell. (a 72% probability of detecting single copy transcripts) Codon bias Definition: A given codon is used more (less) often to code for an amino acid over different other codons fot the same a.a. Highly biased mRNAs may use only 25 of the 61 codons. Different ways to measure C.B exist. The larger the codon bias value, the smaller the number of codons that are used to encode the protein. Codon bias - continued Use of these codons may make translation faster or more efficient and may decrease misincorporation. Codon bias is thought to be an indicator of protein expression, with highly expressed proteins having large codon bias values. Experiment Synopsis Label all Proteins with [35S] methionines & cysteines (pulse). wait . . .X min (chase). Separate Proteins via: - Centrifugation - 2D Gels Identify (various MS methods and more) Quantify Protein Amounts. (use radioactivity) phosphorimaging, scintillation counting, autoradiography. Cells extract in log phase in glucose. Results present new problems 1400 spots were visualized (1200 proteins). 3.1 poor resolution. Think McFly, Think… Solution: Use 3 different gels with different pH ranges. Problem: Comigration & coverage – weak spots can be seen only when they are well separated from strong spots. No real solution yet. Results 169 spots representing 148 proteins were identified using: peptide sequencing, MS , amino acid composition and gene overexpression. Pulse-chase experiments were made to determine protein turnover (half lives). => all spotted proteins are very stable proteins. Results – protein quantitation Effectively same half life. => radioactivity is proportional to protein abundance. The number of methionine and cysteine per identified protein is known. => the number of protein molecules can be calculated. Results – some numbers Protein abundance range of 300 fold (!). Less than a 100 proteins account for half of the total cellular protein. Correlation of protein abundance with mRNA abundance mRNA abundance SAGE. hybridization of cRNA to oligonucleotide arrays. Both methods give broadly similar results. An adjusted mRNA ratio was calculated combining the two. Elaborate correlation statistics were made. (Don’t Worry, I will not elaborate today… ) Correlation of protein abundance with adjusted mRNA abundance. Spearman rank correlation coefficient, rs, was 0.74 (P < 0.0001). Pearson correlation coefficient, rp, on log transformed data was 0.76 (P < 0.00001). A 10-fold range of protein abundance, f or mRNAs of a given abundance. (why?) Correlation of codon bias with protein abundance The rs for CAI versus protein abundance is 0.80 (P < 0.0001). (a strong correlation) When some abundant proteins were removed from consideration, The rs was essential unchanged. Additionl experiments. Changes in protein abundance on glucose and Ethanol were quantified as well. Gluconeogenesis enzymes more abundant on ethanol. Heat shock proteins more abundant on ethanol. Protein synthesis enzymes were more abundant on glucose. Phosphorylation of proteins. And more. Discussion - numbers 1200 proteins were quantified. 1/3 – 1/4 of total proteins expressed. 148 IDed. others can be IDed using gene overexpression. But There is always a (_|_) … The remaining proteins will be difficult to see and study with these methods. (weak spots are covered by strong spots). 2nd research - Correlation between protein and mRNA abundance in yeast. Similar experiments were made by Gygi et al. Similar methods (MS) were used to identify 156 proteins (products of 128 genes). Correlation Analysis between mRNA and codon bias to protein abundance levels were made. Genes with missing data were excluded. no SAGE data. ambiguous tags. no Met’s. comigration. pI did not match Mr. 106 genes Codon bias to protein Correlation. No genes were identified with codon bias values less than 0.1 even though thousands of genes exist in this category. something’s fishy!? who said bias? mRNA protein correlation rp = 0.93 Lets take a closer look… total: rp = 0.35 inner set: including progressively more, and higher-abundance, proteins in each calculation Discussion - conclusions Codon bias, an indicator of the boundaries of current 2D gel proteome analysis technology. A promising approach is the use of narrow-range focusing gels. Current proteome technology is incapable of analyzing low-abundance regulatory proteins without employing an enrichment method. For higher eukaryotes the detection of low-abundance proteins would be even harder. Discussion – words of the wise. Gygi et al: “This study revealed that transcript levels provide little predictive value with respect to the extent of protein expression.” Futcher et al: “there is a good correlation between protein abundance and mRNA abundance for the proteins that we have studied”. Discussion – biases Codon Bias. Long half lives. Low abundance proteins were not found. (T.Fs, kinases etc.) SAGE data. Met’s processed away. Comigration. Different statistical manipulations. Why Proteomics – revised quantity of large scale protein expression. the subcellular location. the state of modification. the association with ligands. the rate of change with time of such properties. GO HOME ! 