Selection of chromosomal DNA libraries using a multiplex CRISPR system.

The directed evolution of biomolecules to improve or change their activity is central to many engineering and synthetic biology efforts. However, selecting improved variants from gene libraries in living cells requires plasmid expression systems that suffer from variable copy number effects, or the use of complex marker-dependent chromosomal integration strategies. We developed quantitative gene assembly and DNA library insertion into the Saccharomyces cerevisiae genome by optimizing an efficient single-step and marker-free genome editing system using CRISPR-Cas9.

Scalable plasmid transfer using engineered P1-based phagemids.

Dramatic improvements to computational, robotic, and biological tools have enabled genetic engineers to conduct increasingly sophisticated experiments. Further development of biological tools offers a route to bypass complex or expensive mechanical operations, thereby reducing the time and cost of highly parallelized experiments. Here, we engineer a system based on bacteriophage P1 to transfer DNA from one E.

Algorithms for automated DNA assembly.

Generating a defined set of genetic constructs within a large combinatorial space provides a powerful method for engineering novel biological functions. However, the process of assembling more than a few specific DNA sequences can be costly, time consuming and error prone. Even if a correct theoretical construction scheme is developed manually, it is likely to be suboptimal by any number of cost metrics.

Solving a Hamiltonian Path Problem with a bacterial computer.

Background: The Hamiltonian Path Problem asks whether there is a route in a directed graph from a beginning node to an ending node, visiting each node exactly once. The Hamiltonian Path Problem is NP complete, achieving surprising computational complexity with modest increases in size. This challenge has inspired researchers to broaden the definition of a computer.

Evaluation of three automated genome annotations for Halorhabdus utahensis.

Genome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors.