How are biological modules (e.g. translation machinery) optimized by natural selection? Theory suggests that drift imposes a barrier on optimization, as modules where all adaptive mutations are effectively neutral (s < 1/N) are no longer subject to adaptive evolution. (2/9)
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But modules evolve in the context of organisms. If organisms evolve in the clonal interference regime, adaptations in different modules compete against each other => a module's evolution can stall if other modules produce larger-effect mutations(3/9)
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Does stalling occur? How far away from the margin of effective neutrality does it happen? To test this we started with E. coli with variously defective translation machineries (TMs) (Kacar et al 2017 mBio) and evolved them for 1000 generations. (4/9)
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Stalling happens! Strains with mildly defective TMs do not gain mutations in known TM-specific genes, while those with severe TM defects exhaust adaptive mutations in TM-specific genes well by gen 600. Even defective TMs that impose a 3% fitness cost stall! (5/9)
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Why do we care? 1) If changing environmental conditions constantly replenishes large-effect adaptive mutations in other modules, even critical modules like the TM may stall for long periods of time 2) It is really hard to understand module evolution in isolation (6/9)
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3) Only a few mutations needed to recover the defect in even highly defective TMs => high performance TM genotypes may percolate throughout TM genotype space 4) (Speculation) If optimizing the TM is hard in the context of a cell, maybe it was largely optimized pre-LUCA... (7/9)
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Big q's: How long is a module stalled for before adaptation resumes? What genomic / environmental parameters does this depend on? If everything depends on the adaptive DFE of each module, how do these distributions vary between modules? (8/9)
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This project has been quite a journey, thanks to my wonderful advisers and collaborators, esp
@betulland and@skryazhi for helping make this happen! (9/9)Prikaži ovu nit
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