Lambda-PCR for precise DNA assembly and modification.

Lambda-polymerase chain reaction (λ-PCR) is a novel and open-source method for DNA assembly and cloning projects. λ-PCR uses overlap extension to ultimately assemble linear and circular DNA fragments, but it allows the single-stranded DNA (ssDNA) primers of the PCR extension to first exist as double-stranded DNA (dsDNA). Having dsDNA at this step is advantageous for the stability of large insertion products, to avoid inhibitory secondary structures during direct synthesis, and to reduce costs. Three variations of λ-PCR were created to convert an initial dsDNA product into an ssDNA "megaprimer" to be used in overlap extension: (i) complete digestion by λ-exonuclease, (ii) asymmetric PCR, and (iii) partial digestion by λ-exonuclease. Four case studies are presented that demonstrate the use of λ-PCR in simple gene cloning, simultaneous multipart assemblies, gene cloning not achievable with commercial kits, and the use of thermodynamic simulations to guide λ-PCR assembly strategies. High DNA assembly and cloning efficiencies have been achieved with λ-PCR for a fraction of the cost and time associated with conventional methods and some commercial kits.

A review of metabolic and enzymatic engineering strategies for designing and optimizing performance of microbial cell factories.

Microbial cell factories (MCFs) are of considerable interest to convert low value renewable substrates to biofuels and high value chemicals. This review highlights the progress of computational models for the rational design of an MCF to produce a target bio-commodity. In particular, the rational design of an MCF involves: (i) product selection, (ii) de novo biosynthetic pathway identification (i.e., rational, heterologous, or artificial), (iii) MCF chassis selection, (iv) enzyme engineering of promiscuity to enable the formation of new products, and (v) metabolic engineering to ensure optimal use of the pathway by the MCF host. Computational tools such as (i) de novo biosynthetic pathway builders, (ii) docking, (iii) molecular dynamics (MD) and steered MD (SMD), and (iv) genome-scale metabolic flux modeling all play critical roles in the rational design of an MCF. Genome-scale metabolic flux models are of considerable use to the design process since they can reveal metabolic capabilities of MCF hosts. These can be used for host selection as well as optimizing precursors and cofactors of artificial de novo biosynthetic pathways. In addition, recent advances in genome-scale modeling have enabled the derivation of metabolic engineering strategies, which can be implemented using the genomic tools reviewed here as well.