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GST Colloquium 2013-02-20

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Lang Ho Lee

on 20 February 2013

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Transcript of GST Colloquium 2013-02-20

OBSTACLE1 OBSTACLE2 OBSTACLE3 Secrets of Expression Control Start Protein half-life
: traditional cycloheximide
chase experiments A model of expression control 1. Is the labeling surely working? half lives comparison between rep. 1 and 2 2. Does protein abundance
matters? 1. Second independent large-scale experiment
2. Removing less-consistant data Proteomics Team for GST Colloquium (2013-02-20)
Presenters: Weili Xiong and Lang Ho Lee

OUR JOURNEY
TO GET SECRETS
OF
GENE EXPRESSION
CONTROL Can this data be confirmed by other methods? So, How about
reproducibility and
systematic noises? I got IDEA!! 5,279 PROTEIN and GENE EXPRESSION DATA Labeling efficiency Protein abundance Protein quantification
: spike-in experiments mRNA copy number (Read #)
: NanoString technology copy # comparison between rep. 1 & 2 Transcription rate and translation rate
comparison between rep. 1 & 2 Removing data points Half-life and copy # of proteins and genes Functional characteristics
and protein & mRNA half-lives Game Clear! Before start a game Systematic approach to understand biological problem How does the combined effect of all regulatory levels process the genomic information into a specific cellular proteome?

Transcriptional control
Regulation of the transcription rates:
transcription factors



Post-Transcriptional Control
Pre-mRNAs processing into mature mRNA;
mRNA stability ; small RNA; sequence
feature


Translational Control
Regulation of the translation rates:
initiation, elongation factors; ribosome
occupancy; codon bias


Post-Translational Control
Protein modification; protein stability Gene regulation in Eukaryotes The correlation between mRNA and protein levels in previous studies is poor!

Methodological constraints: limited hundreds of genes quantified
Incomparability: different experiments
Dynamic levels: synthesis and degradation (turnover) Limitations for gene expression quantification FEBS Lett. 2009,17;583(24):3966-73 Technological advances in the quantitative analysis of mRNA and proteins Quantify cellular mRNA and protein
expression levels and turnover in parallel in a
population of nonsynchronized, unperturbed
mammalian cells. Objective Experimental Design Absolute mRNA copies

Newly synthesized / pre-existing RNA ratios

Absolute protein copies

Newly synthesized / pre-existing protein ratios Data collection Model data: NIH3T3 mouse fibroblast
Validation data: NIH3T3 replicate
Prediction data: human breast cancer cell line MCF7 Protein degradation rate mRNA degradation rate Translation rate Transcription rate Modeling and validation What is the correlation between protein and mRNA levels and half lives?

How much protein abundance is controlled at the transcriptional, post-transcriptional, translational and post-translational levels?

Whether genes with specific combinations of mRNA and protein stability have distinct biological functions? Questions to be answered How much are protein and gene expressions correlated?
Half-lives are not correlated, but copy numbers are lightly correlated.

How much protein abundance is controlled at the transcriptional, post-transcriptional, translational and post-translational levels?
It's varied by species and cell types, but translation dominates other factors in this experiment.

Whether genes with specific combinations of mRNA and protein stability have distinct biological functions?
Genes of basic metabolisms show higher stability, while cell division genes show short half-lives. Translation rate of abundant proteins are saturated to around 120-240 (proteins / mRNA & hour), which means translation rate is limited regardless of mRNA amounts and protein amounts. Basic metabolism
related genes Cell division related transcription factor genes RNA processing Extracellular proteins
Full transcript