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Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters
Johnathan G Crandall1, Xiaofan Zhou2,3, Antonis Rokas3
1Laboratory of Genetics, J. F. Crow Institute for the Study of Evolution, Center for Genomic Science Innovation, DOE Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin-Madison, Madison, WI 53726, USA.
Protein evolution enables new functions through complex interactions. In yeast sugar transporters, novel substrate transport evolved via intricate residue networks, driven by ancestral multifunctional proteins and genetic constraints.
Area of Science:
- Evolutionary biology
- Protein engineering
- Molecular biology
Background:
- Functional innovation in proteins drives evolutionary novelty.
- Protein evolution is constrained by unique histories, structures, and epistasis.
- Major Facilitator Superfamily (MFS) sugar porters are ancient, conserved, and evolvable proteins.
Purpose of the Study:
- Investigate the molecular basis of novel protein function.
- Dissect evolutionary innovation in an alpha-glucoside transporter from Saccharomyces eubayanus.
- Understand constraints and pathways for functional diversification in MFS transporters.
Main Methods:
- Dissected a recent evolutionary innovation in an alpha-glucoside transporter.
- Generated genome annotations for 332 Saccharomycotina yeast species.
- Integrated phylogenetic and phenotypic analyses.
Main Results:
- Novel substrate transport requires high-order interactions among protein regions and residues near the transport channel.
- Yeast alpha-glucoside transporters likely evolved from multifunctional ancestors via subfunctionalization.
- Additive and epistatic substitutions entrenched subfunctions, favoring multi-substitution pathways for novelty.
Conclusions:
- Protein functional innovation is context-specific and shaped by evolutionary history.
- Substrate specificity in MFS transporters can evolve through accumulated substitutions that refine ancestral functions.
- Understanding these constraints aids in protein engineering and evolutionary studies.
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