journal club 01/13/14: tech apps
Causes and effects of N-terminal codon bias (Goodman, Church and Kosuri). Science
Influential approach Combine 2 Techs
- oligo synthesis on a programmable microarray – diverse
- These authors combine with next gen sequencing – 10-200 million unique sequences in a pool
- use the next gen sequencing to measure how biology changes the diversity of the synthesized library.
- Kosuri (former Church post-doc, started OpenWetWare)
This paper’s application
- differential codon use. up 20 fold bias in ecoli between synonymous codons
- varies between genes, can be used to affect expression.
- recent observation: usage of codons varies as a function of position in the gene (along gene length).
- Start codon proximal sequence enriched for rare codons (in flies, worms, yeast and E coli).
- diverse library of sfGFP, with different 5′ sequence: strong vs weak promoter, strong vs weak RBS, the ATG, the 10 amino-acids from 137 native e coli genes, and 13 different re-codings of this n-terminal frequency.
- 2 promoters 4 RBS, 137 genes 13 codings = 14,248 plasmids
- do with oligo-array library and create 14,248 distinct E coli strains in 1 shot.
- Get 600,000 clones (average 50x coverage), could imagine doing more.
- do next gen sequencing to for the number of ecoli strains that have each plasmid.
- use ratio of mCherry to GFP to reduce effects of extrinsic noise (ribosomes conc etc).
- sort library via FACs on GFP/RFP
- each insert /plasmid is a unique barcode, can ask how many copies of this barcode do you find in each expression bin.
- Have a binned expression measurement for each of 14K sequences.
- can see how N-terminal codon bias affects expression on a 14K
- different reshuffled recodings span a range of free energies of secondary structure.
- rare codon, increase expression (on average ~2 fold, at most 100 fold)
- most rare Arg codon get a 2x more expression.
- how do rare codons increase protein expression? Reject the slow translation initation reduces traffic jams (reducing density) to increase overall speed. — Don’t see correlation with RBS strength. (other groups have also rejected this model by showing different codons translated at the same rate)
- coding variants which change secondary structure stability
- rare codons tend to destabilize secondary structure (just by straight-up correlation plot).
- what mattered was the secondary structure not the abundance. All swaps that don’t actually change commonality of the structure but do change secondary structure, see a correlation.
- look at all ones that keep deltaG constant but do change abundance, see no effect.
- max change observed in deltaG see ~10 fold change in expression level.
- rare codons are AT enriched and more expressed and less secondary structure (rare codons tend to have A in wobble base)
- previous demonstration of secondary structure had 28 or 150 constructs, now 14K constructs.
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