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Mol Biol Evol. 2016 Nov;33(11):2960-2975. Epub 2016 Aug 25.

Molecular Determinants of Mutant Phenotypes, Inferred from Saturation Mutagenesis Data.

Author information

1
Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.
2
Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India Jawaharlal Nehru Center for Advanced Scientific Research, Bangalore, India varadar@mbu.iisc.ernet.in.

Abstract

Understanding how mutations affect protein activity and organismal fitness is a major challenge. We used saturation mutagenesis combined with deep sequencing to determine mutational sensitivity scores for 1,664 single-site mutants of the 101 residue Escherichia coli cytotoxin, CcdB at seven different expression levels. Active-site residues could be distinguished from buried ones, based on their differential tolerance to aliphatic and charged amino acid substitutions. At nonactive-site positions, the average mutational tolerance correlated better with depth from the protein surface than with accessibility. Remarkably, similar results were observed for two other small proteins, PDZ domain (PSD95pdz3) and IgG-binding domain of protein G (GB1). Mutational sensitivity data obtained with CcdB were used to derive a procedure for predicting functional effects of mutations. Results compared favorably with those of two widely used computational predictors. In vitro characterization of 80 single, nonactive-site mutants of CcdB showed that activity in vivo correlates moderately with thermal stability and solubility. The inability to refold reversibly, as well as a decreased folding rate in vitro, is associated with decreased activity in vivo. Upon probing the effect of modulating expression of various proteases and chaperones on mutant phenotypes, most deleterious mutants showed an increased in vivo activity and solubility only upon over-expression of either Trigger factor or SecB ATP-independent chaperones. Collectively, these data suggest that folding kinetics rather than protein stability is the primary determinant of activity in vivo This study enhances our understanding of how mutations affect phenotype, as well as the ability to predict fitness effects of point mutations.

KEYWORDS:

deep sequencing; fitness effect prediction; mutagenesis; protein folding

PMID:
27563054
PMCID:
PMC5062330
DOI:
10.1093/molbev/msw182
[Indexed for MEDLINE]
Free PMC Article

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