Jonathan Sun University of Illinois at Urbana Champaign BIOE 506 February 15, 2010

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Presentation transcript:

Jonathan Sun University of Illinois at Urbana Champaign BIOE 506 February 15,

Outline  Introduction  Motivation  Methods  Applications  Conclusions February 15, 2010University of Illinois2

Evolution  Darwin => natural selection  1970 – John Maynard Smith Evolution is a walk from one functional protein to another in the landscape of all possible sequences “Fitness” of protein based on favorability for reproduction or based on experimenter in artificial selection February 15, 2010University of Illinois3 Romero and Arnold: Exploring Protein Fitness Landscapes by Directed Evolution

Picture (not many more to come) February 15, 2010University of Illinois4  Screening criteria is important  Stability can be used instead of improvement  Allows for functionally neutral mutations Romero and Arnold: Exploring Protein Fitness Landscapes by Directed Evolution

What is Directed Evolution?  An engineering strategy used to improve protein functionality through repeated rounds of mutation and selection  First used in the ‘70s  Around.01-1% of all random mutations estimated to be beneficial  Based off natural evolution processes, but in a much quicker timescale February 15, 2010University of Illinois5

Another (more direct?) Method  Rational design – modify protein function based on understanding consequences of certain changes  We are still relatively ignorant as to how a protein’s gene sequence encodes functionality  Directed evolution avoids this problem by creating libraries of variants possessing desired properties February 15, 2010University of Illinois6

Why is it Needed?  Biotechnology – increased demand for specific properties that don’t necessarily occur naturally  Can be used to improve existing proteins’ functionality  Can be applied as far as the ideas come – enzymes and catalysts to pharmaceuticals or crops February 15, 2010University of Illinois7

Successful Directed Evolution  Desired function should be/have: Physically feasible Biologically or evolutionarily feasible Libraries of mutants complex enough to contain rare beneficial mutations Rapid screen to find desired function  Increases understanding of protein function and evolution – disconnects protein from natural context February 15, 2010University of Illinois8

Basic Method  A parent gene is selected  Mutations/diversity are induced (mutagenesis or recombination)  Selection criteria applied  Repeat with new parent genes selected February 15, 2010University of Illinois9 Bloom and Arnold: In the light of directed evolution: Pathways of adaptive protein evolution

Random Mutagenesis  Traditional method  Point mutation based – error prone PCR  Frequency of beneficial mutations very low  Multiple mutations virtually impossible to come out positive February 15, 2010University of Illinois10

DNA Shuffling  Recombination used to create chimeric sequences containing multiple beneficial mutations  “Family shuffling” of homologous genes  “Synthetic shuffling” – oligonucleotides combined to create full-length genes  Whole-genome shuffling – accelerated phenotypic improvements  Drawback – high homology required February 15, 2010University of Illinois11

RACHITT  Random Chimeragenisis on Transient Templates  Small DNA fragments hybridized on a scaffold to create a chimeric DNA fragment  Incorporates low-homology segments February 15, 2010University of Illinois12

Even More Methods  Assembly of Designed Oligonucleotides (ADO)  Mutagenic and Unidirectional Reassembly (MURA)  Exon Shuffling  Y-Ligation-Based Block Shuffling  Nonhomologous Recombination – ITCHY, SCRATCHY, SHIPREC, NRR  Combining rational design with directed evolution February 15, 2010University of Illinois13

ADO  Nonconserved regions with conserved parts as linkers  PCR with dsDNA without primers  Full length genes in expression vector  Creates large diversity of active variants without codon bias for parental genes February 15, 2010University of Illinois14

MURA  Random fragmentation of parental gene  Reassembled with unidirectional primers for specific restriction site  Generates N-terminally truncated DNA shuffled libraries February 15, 2010University of Illinois15

Exon Shuffling  Similar to natural splicing of exons  Chimeric oligos mixed together, controlling combination of which exons to be spliced  Protein pharmaceuticals based on natural human genes – less immune response February 15, 2010University of Illinois16

Nonhomologous Recombination  Creation of new protein folds  Structures not present in nature – useful for evolution of multifunctional proteins  Incremental truncation for the creation of hybrid enzyme (ITCHY) – two genes in expression vector with unique restriction sites, blunt end digestion, ligated - >SCRATCHY  Nonhomologous random recombination – potentially higher flexibility in fragment size and crossover frequency February 15, 2010University of Illinois17

A Combination  Rational design with directed evolution  Success depends on ability to predict fitness of a sequence  Computationally demanding  Kuhlman et al created a new protein fold  Focuses library diversity for directed evolution February 15, 2010University of Illinois18

Directed Evolution in Action  Has been applied to improve polymerases, nucleases, transposases, integrases, recombinases  Applications in genetic engineering, functional genomics, and gene therapy  Optimized fluorescent proteins and small-molecule probes for imaging and techniques like FRET February 15, 2010University of Illinois19

The Case of a Fluorescent Protein  dsRED – parent protein evolved to have better solubility and shorter maturation time February 15, 2010University of Illinois20 dsRedmCherry

Biochemical Catalysts  Useful in industry because of high selectivity and minimal energy requirements  Need for high availability at low costs  Active and stable under process conditions – not naturally occuring  Some reaction enzymes still yet to be identified and produced February 15, 2010University of Illinois21

Application to Enzymes  Improve stability and activity of biochemical catalysts  Can modify pH or temperature dependence  Substrate specificity or catalytic activity  MANY applications: Proteolytic – Subtilisin in detergents Cellulolytic and esterases – biofuel production Cytochrome P450 superfamily – catalyze hydroxilation  Whole metabolic pathway evolution February 15, 2010University of Illinois22

Whole Metabolic Pathways  Closer to natural compound production  Single enzyme activity upregulation does not necessarily lead to increase in final product  Different methods: Whole genome shuffling Key enzymes targeted Naturally expressed operons targeted Target gene regulation factors February 15, 2010University of Illinois23

Pharmaceuticals  Therapeutic proteins  Antibodies – natural somatic recombination  Vaccines – improved effectiveness, less side effects  Viruses – gene therapy and vaccine development February 15, 2010University of Illinois24

Agriculture  Plants with increased tolerance for herbicides or expression of toxins  Golden rice Expresses elevated beta-carotene (Vitamin A precursor) Directed evolution - 23 times more in second version Not approved for distribution February 15, 2010University of Illinois25

Conclusions  Directed evolution can be a powerful tool taking advantage of nature’s power to improve upon itself  Used in a wide variety of applications for protein improvement – stability, activity, substrate specificity, etc  Potential for genetically engineering improved drugs or crops  Ultimately, combining tools will lead to better understanding and applications February 15, 2010University of Illinois26

Thank You! Questions? February 15, 2010University of Illinois27