@article{MesserschmidtHochreinDehmetal.2016,
  author    = {Messerschmidt, Katrin and Hochrein, Lena and Dehm, Daniel and Schulz, Karina and Mueller-Roeber, Bernd},
  title     = {Characterizing seamless ligation cloning extract for synthetic biological applications},
  series = {Analytical biochemistry : methods in the biological sciences},
  volume    = {509},
  journal   = {Analytical biochemistry : methods in the biological sciences},
  publisher = {Elsevier},
  address   = {San Diego},
  issn      = {0003-2697},
  doi       = {10.1016/j.ab.2016.05.029},
  pages     = {24 -- 32},
  year      = {2016},
  abstract  = {Synthetic biology aims at designing and engineering organisms. The engineering process typically requires the establishment of suitable DNA constructs generated through fusion of multiple protein coding and regulatory sequences. Conventional cloning techniques, including those involving restriction enzymes and ligases, are often of limited scope, in particular when many DNA fragments must be joined or scar-free fusions are mandatory. Overlap-based-cloning methods have the potential to overcome such limitations. One such method uses seamless ligation cloning extract (SLiCE) prepared from Escherichia coli cells for straightforward and efficient in vitro fusion of DNA fragments. Here, we systematically characterized extracts prepared from the unmodified E. coli strain DH10B for SLiCE-mediated cloning and determined DNA sequence-associated parameters that affect cloning efficiency. Our data revealed the virtual absence of length restrictions for vector backbone (up to 13.5 kbp) and insert (90 bp to 1.6 kbp). Furthermore, differences in GC content in homology regions are easily tolerated and the deletion of unwanted vector sequences concomitant with targeted fragment insertion is straightforward. Thus, SLiCE represents a highly versatile DNA fusion method suitable for cloning projects in virtually all molecular. and synthetic biology projects. (C) 2016 Elsevier Inc. All rights reserved.},
  language  = {en}
}
@article{BaslerGrimbsNikoloski2012,
  author    = {Basler, Georg and Grimbs, Sergio and Nikoloski, Zoran},
  title     = {Optimizing metabolic pathways by screening for feasible synthetic reactions},
  series = {Biosystems : journal of biological and information processing sciences},
  volume    = {109},
  journal   = {Biosystems : journal of biological and information processing sciences},
  number    = {2},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0303-2647},
  doi       = {10.1016/j.biosystems.2012.04.007},
  pages     = {186 -- 191},
  year      = {2012},
  abstract  = {Background: Reconstruction of genome-scale metabolic networks has resulted in models capable of reproducing experimentally observed biomass yield/growth rates and predicting the effect of alterations in metabolism for biotechnological applications. The existing studies rely on modifying the metabolic network of an investigated organism by removing or inserting reactions taken either from evolutionary similar organisms or from databases of biochemical reactions (e.g., KEGG). A potential disadvantage of these knowledge-driven approaches is that the result is biased towards known reactions, as such approaches do not account for the possibility of including novel enzymes, together with the reactions they catalyze. Results: Here, we explore the alternative of increasing biomass yield in three model organisms, namely Bacillus subtilis, Escherichia coil, and Hordeum vulgare, by applying small, chemically feasible network modifications. We use the predicted and experimentally confirmed growth rates of the wild-type networks as reference values and determine the effect of inserting mass-balanced, thermodynamically feasible reactions on predictions of growth rate by using flux balance analysis. Conclusions: While many replacements of existing reactions naturally lead to a decrease or complete loss of biomass production ability, in all three investigated organisms we find feasible modifications which facilitate a significant increase in this biological function. We focus on modifications with feasible chemical properties and a significant increase in biomass yield. The results demonstrate that small modifications are sufficient to substantially alter biomass yield in the three organisms. The method can be used to predict the effect of targeted modifications on the yield of any set of metabolites (e.g., ethanol), thus providing a computational framework for synthetic metabolic engineering.},
  language  = {en}
}