Algorithms for optimizing cross-overs in DNA shuffling

Background DNA shuffling generates combinatorial libraries of chimeric genes by stochastically recombining parent genes. The resulting libraries are subjected to large-scale genetic selection or screening to identify those chimeras with favorable properties (e.g., enhanced stability or enzymatic act...

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Veröffentlicht in:BMC bioinformatics Jg. 13; H. Suppl 3; S. S3
Hauptverfasser: He, Lu, Friedman, Alan M, Bailey-Kellogg, Chris
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 21.03.2012
Springer Nature B.V
Schlagworte:
African Swine Fever Virus - enzymology
Algorithms
Amino Acid Sequence
Amino acid substitution
Amino acids
Animals
Bacteria - enzymology
beta-Lactamases - chemistry
beta-Lactamases - genetics
Bioinformatics
Biology
Biomedical and Life Sciences
Chimeras
Codon
Codons
Combinatorial libraries
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer applications
Conferences
Deoxyribonucleic acid
DNA
DNA Shuffling
DNA-directed DNA polymerase
E coli
Engineers
Enzymatic activity
Escherichia coli - enzymology
Free energy
Gene Library
Humans
Integer programming
Libraries
Life Sciences
Methods
Microarrays
Nearest-neighbor
Nucleotide sequence
Oligonucleotides
Phosphoribosylglycinamide Formyltransferase - genetics
Proceedings
Protein Engineering - methods
Rats
Recombination
Sequence Alignment
Software
Stochasticity
Studies
transformylase
Diversity Variance
African Swine Fever Virus
Codon
Free Energy
Dynamic Programming Algorithm
ISSN:1471-2105, 1471-2105
Online-Zugang:Volltext
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Zusammenfassung:Background DNA shuffling generates combinatorial libraries of chimeric genes by stochastically recombining parent genes. The resulting libraries are subjected to large-scale genetic selection or screening to identify those chimeras with favorable properties (e.g., enhanced stability or enzymatic activity). While DNA shuffling has been applied quite successfully, it is limited by its homology-dependent, stochastic nature. Consequently, it is used only with parents of sufficient overall sequence identity, and provides no control over the resulting chimeric library. Results This paper presents efficient methods to extend the scope of DNA shuffling to handle significantly more diverse parents and to generate more predictable, optimized libraries. Our C ODNS (cross-over optimization for DNA shuffling) approach employs polynomial-time dynamic programming algorithms to select codons for the parental amino acids, allowing for zero or a fixed number of conservative substitutions. We first present efficient algorithms to optimize the local sequence identity or the nearest-neighbor approximation of the change in free energy upon annealing, objectives that were previously optimized by computationally-expensive integer programming methods. We then present efficient algorithms for more powerful objectives that seek to localize and enhance the frequency of recombination by producing "runs" of common nucleotides either overall or according to the sequence diversity of the resulting chimeras. We demonstrate the effectiveness of C ODNS in choosing codons and allocating substitutions to promote recombination between parents targeted in earlier studies: two GAR transformylases (41% amino acid sequence identity), two very distantly related DNA polymerases, Pol X and β (15%), and beta-lactamases of varying identity (26-47%). Conclusions Our methods provide the protein engineer with a new approach to DNA shuffling that supports substantially more diverse parents, is more deterministic, and generates more predictable and more diverse chimeric libraries.
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ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-13-S3-S3