Figures 1, 2, 3, 4, 6, 8 and Tables 2, 3, 10, 15, 16 are modified from Ref29. This work was supported by the National Science Foundation (grant NSF-CCF 1117143 and NSF-CCF 1162141 to G.S.). Y.-J. C. was supported by Taiwanese Government Fellowships. S.D.R was supported by the National Science Foundation Graduate Research Fellowship Program (GRFP).

<ol>
	<li>Zhang, D. Y., Seelig, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+DNA+nanotechnology+using+strand-displacement+reactions.">Dynamic DNA nanotechnology using strand-displacement reactions.</a> Nat. Chem. 3, 103-113 (2011).</li><li>Krishnan, Y., Simmel, F. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nucleic+acid+based+molecular+devices.">Nucleic acid based molecular devices.</a> Angew. Chem. Int. Ed. Engl. 50, 3124-3156 (2011).</li><li>Zhang, D. Y., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Control+of+DNA+strand+displacement+kinetics+using+toehold+exchange.">Control of DNA strand displacement kinetics using toehold exchange.</a> J. Am. Chem. Soc. 131, 17303-17314 (2009).</li><li>Qian, L., Winfree, E., Bruck, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+network+computation+with+DNA+strand+displacement+cascades.">Neural network computation with DNA strand displacement cascades.</a> Nature. 475, 368-372 (2011).</li><li>Qian, L., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scaling+up+digital+circuit+computation+with+DNA+strand+displacement+cascades.">Scaling up digital circuit computation with DNA strand displacement cascades.</a> Science. 332, 1196-1201 (2011).</li><li>Zadegan, R. M., Jepsen, M. D., Hildebrandt, L. L., Birkedal, V., Kjems, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Construction+of+a+fuzzy+and+boolean+logic+gates+based+on+DNA.">Construction of a fuzzy and boolean logic gates based on DNA.</a> Small. 11, 1811-1817 (2015).</li><li>Seelig, G., Soloveichik, D., Zhang, D. Y., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enzyme-free+nucleic+acid+logic+circuits.">Enzyme-free nucleic acid logic circuits.</a> Science. 314, 1585-1588 (2006).</li><li>Zadegan, R. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Construction+of+a+4+zeptoliters+switchable+3D+DNA+box+origami.">Construction of a 4 zeptoliters switchable 3D DNA box origami.</a> ACS Nano. 6, 10050-10053 (2012).</li><li>Andersen, E. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Self-assembly+of+a+nanoscale+DNA+box+with+a+controllable+lid.">Self-assembly of a nanoscale DNA box with a controllable lid.</a> Nature. 459, 73-76 (2009).</li><li>Zhang, D. Y., Hariadi, R. F., Choi, H. M., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrating+DNA+strand-displacement+circuitry+with+DNA+tile+self-assembly.">Integrating DNA strand-displacement circuitry with DNA tile self-assembly.</a> Nat. Commun. 4, (1965).</li><li>Yurke, B., Turberfield, A. J., Mills, A. P., Simmel, F. C., Neumann, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+DNA-fuelled+molecular+machine+made+of+DNA.">A DNA-fuelled molecular machine made of DNA.</a> Nature. 406, 605-608 (2000).</li><li>Green, S. J., Lubrich, D., Turberfield, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+hairpins:+fuel+for+autonomous+DNA+devices.">DNA hairpins: fuel for autonomous DNA devices.</a> Biophys. J. 91, 2966-2975 (2006).</li><li>Venkataraman, S., Dirks, R. M., Rothemund, P. W., Winfree, E., Pierce, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+autonomous+polymerization+motor+powered+by+DNA+hybridization.">An autonomous polymerization motor powered by DNA hybridization.</a> Nat. Nanotechnol. 2, 490-494 (2007).</li><li>Green, S. J., Bath, J., Turberfield, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coordinated+chemomechanical+cycles:+a+mechanism+for+autonomous+molecular+motion.">Coordinated chemomechanical cycles: a mechanism for autonomous molecular motion.</a> Phys. Rev. Lett. 101, 238101 (2008).</li><li>Omabegho, T., Sha, R., Seeman, N. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+bipedal+DNA+Brownian+motor+with+coordinated+legs.">A bipedal DNA Brownian motor with coordinated legs.</a> Science. 324, 67-71 (2009).</li><li>Turberfield, A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+fuel+for+free-running+nanomachines.">DNA fuel for free-running nanomachines.</a> Phys. Rev. Lett. 90, 118102 (2003).</li><li>Dirks, R. M., Pierce, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Triggered+amplification+by+hybridization+chain+reaction.">Triggered amplification by hybridization chain reaction.</a> Proc. Natl. Acad. Sci. U. S. A. 101, 15275-15278 (2004).</li><li>Seelig, G., Yurke, B., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Catalyzed+relaxation+of+a+metastable+DNA+fuel.">Catalyzed relaxation of a metastable DNA fuel.</a> J. Am. Chem. Soc. 128, 12211-12220 (2006).</li><li>Zhang, D. Y., Turberfield, A. J., Yurke, B., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Engineering+entropy-driven+reactions+and+networks+catalyzed+by+DNA.">Engineering entropy-driven reactions and networks catalyzed by DNA.</a> Science. 318, 1121-1125 (2007).</li><li>Yin, P., Choi, H. M., Calvert, C. R., Pierce, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Programming+biomolecular+self-assembly+pathways.">Programming biomolecular self-assembly pathways.</a> Nature. 451, 318-322 (2008).</li><li>Chen, X., Briggs, N., McLain, J. R., Ellington, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stacking+nonenzymatic+circuits+for+high+signal+gain.">Stacking nonenzymatic circuits for high signal gain.</a> Proc. Natl. Acad. Sci. U. S. A. 110, 5386-5391 (2013).</li><li>Phillips, A., Cardelli, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+programming+language+for+composable+DNA+circuits.">A programming language for composable DNA circuits.</a> J. R. Soc. Interface. 6, S419-S436 (2009).</li><li>Lakin, M. R., Youssef, S., Polo, F., Emmott, S., Phillips, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visual+DSD:+a+design+and+analysis+tool+for+DNA+strand+displacement+systems.">Visual DSD: a design and analysis tool for DNA strand displacement systems.</a> Bioinformatics. 27, 3211-3213 (2011).</li><li>Lakin, M. R., Youssef, S., Cardelli, L., Phillips, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Abstractions+for+DNA+circuit+design.">Abstractions for DNA circuit design.</a> J. R. Soc. Interface. 9, 470-486 (2012).</li><li>Zhang, D. Y., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Robustness+and+modularity+properties+of+a+non-covalent+DNA+catalytic+reaction.">Robustness and modularity properties of a non-covalent DNA catalytic reaction.</a> Nucleic Acids Res. 38, 4182-4197 (2010).</li><li>Ducani, C., Kaul, C., Moche, M., Shih, W. M., Hogberg, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enzymatic+production+of+'monoclonal+stoichiometric'+single-stranded+DNA+oligonucleotides.">Enzymatic production of 'monoclonal stoichiometric' single-stranded DNA oligonucleotides.</a> Nat. Methods. 10, 647-652 (2013).</li><li>Lin, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+cloning+of+artificial+DNA+nanostructures.">In vivo cloning of artificial DNA nanostructures.</a> Proc. Natl. Acad. Sci. U. S. A. 105, 17626-17631 (2008).</li><li>Bhatia, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Icosahedral+DNA+nanocapsules+by+modular+assembly.">Icosahedral DNA nanocapsules by modular assembly.</a> Angew. Chem. Int. Ed. Engl. 48, 4134-4137 (2009).</li><li>Chen, Y. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Programmable+chemical+controllers+made+from+DNA.">Programmable chemical controllers made from DNA.</a> Nat. Nanotechnol. 8, 755-762 (2013).</li><li>Arkin, A., Ross, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+functions+in+biochemical+reaction+networks.">Computational functions in biochemical reaction networks.</a> Biophys. J. 67, 560-578 (1994).</li><li>&#201;rdi, P., T&#243;th, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Mathematical models of chemical reactions: theory and applications of deterministic and stochastic models. , (1989).</li><li>Magnasco, M. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemical+kinetics+is+Turing+universal.">Chemical kinetics is Turing universal.</a> Phys. Rev. Lett. 78, 1190 (1997).</li><li>Oishi, K., Klavins, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomolecular+implementation+of+linear+I/O+systems.">Biomolecular implementation of linear I/O systems.</a> IET Syst. Biol. 5, 252-260 (2011).</li><li>Senum, P., Riedel, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rate-independent+constructs+for+chemical+computation.">Rate-independent constructs for chemical computation.</a> PLoS One. 6, (2011).</li><li>Soloveichik, D., Cook, M., Winfree, E., Bruck, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computation+with+finite+stochastic+chemical+reaction+networks.">Computation with finite stochastic chemical reaction networks.</a> Natural Computing. 7, 615-633 (2008).</li><li>Soloveichik, D., Seelig, G., Winfree, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+as+a+universal+substrate+for+chemical+kinetics.">DNA as a universal substrate for chemical kinetics.</a> Proc. Natl. Acad. Sci. U. S. A. 107, 5393-5398 (2010).</li><li>Tyson, J. J., Chen, K. C., Novak, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sniffers,+buzzers,+toggles+and+blinkers:+dynamics+of+regulatory+and+signaling+pathways+in+the+cell.">Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell.</a> Curr. Opin. Cell. Biol. 15, 221-231 (2003).</li><li>Cardelli, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Two-domain+DNA+strand+displacement.">Two-domain DNA strand displacement.</a> Math. Struct. Comput. Sci. 23, 247-271 (2013).</li><li>Angluin, D., Aspnes, J., Eisenstat, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple+population+protocol+for+fast+robust+approximate+majority.">A simple population protocol for fast robust approximate majority.</a> Distrib. Comput. 21, 87-102 (2008).</li><li>Cardelli, L., Csikasz-Nagy, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cell+cycle+switch+computes+approximate+majority.">The cell cycle switch computes approximate majority.</a> Sci. Rep. 2, 656 (2012).</li><li>Zadeh, J. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NUPACK:+Analysis+and+design+of+nucleic+acid+systems.">NUPACK: Analysis and design of nucleic acid systems.</a> J. Comput. Chem. 32, 170-173 (2011).</li><li>Lee, P. Y., Costumbrado, J., Hsu, C. Y., Kim, Y. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Agarose+gel+electrophoresis+for+the+separation+of+DNA+fragments.">Agarose gel electrophoresis for the separation of DNA fragments.</a> J. Vis. Exp. , (2012).</li><li>Gibson, D. G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Enzymatic+assembly+of+DNA+molecules+up+to+several+hundred+kilobases.">Enzymatic assembly of DNA molecules up to several hundred kilobases.</a> Nat. Methods. 6, 343-345 (2009).</li><li>Froger, A., Hall, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transformation+of+plasmid+DNA+into+E.+coli+using+the+heat+shock+method.">Transformation of plasmid DNA into E. coli using the heat shock method.</a> J. Vis. Exp. , e253 (2007).</li><li>Lessard, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Transformation+of+E.+coli+via+electroporation.">Transformation of E. coli via electroporation.</a> Methods Enzymol. 529, 321-327 (2013).</li><li>Nasri, M., Thomas, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alteration+of+the+specificity+of+PvuII+restriction+endonuclease.">Alteration of the specificity of PvuII restriction endonuclease.</a> Nucleic Acids Res. 15, 7677-7687 (1987).</li><li>Dalchau, N., Seelig, G., Phillips, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computational+design+of+reaction-diffusion+patterns+using+DNA-based+chemical+reaction+networks.">Computational design of reaction-diffusion patterns using DNA-based chemical reaction networks.</a> DNA Computing and Molecular Programming. , 84-99 (2014).</li><li>Scalise, D., Schulman, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Designing+modular+reaction-diffusion+programs+for+complex+pattern+formation.">Designing modular reaction-diffusion programs for complex pattern formation.</a> Technology. 2, 55-66 (2014).</li></ol>

The authors declare no competing financial interests.

This paper describes a method for deriving ndsDNA gates from highly pure plasmid DNA. Moreover, a protocol is presented for characterizing gate performance using a fluorescence kinetics assay. Experimental data shows that the plasmid-derived system outperforms its synthetic counterpart even if the synthetic system is assembled from strands purified using polyacrylamide gel electrophoresis (PAGE). Likely, the improved performance of plasmid-derived gates is primarily due to the very high purity of the biological DNA. Synthetic DNA contains a variety of errors, in particular deletions that result in oligonucleotides of length n-1, and such side products are typically not completely removed in PAGE or high-performance liquid chromatography (HPLC) purification procedures. Similar improvements to the ones reported here were also observed in a previous study of a catalyzed hairpin amplifier that used DNA derived from biological sources21.
However, even the use of plasmid-derived gates cannot completely eliminate errors in the gate performance, for which there are at least two reasons: first over-digestion or lack of cut precision can lead to gates with too many nicks or nicks in the wrong positions. In either case, gates are more likely to participate in undesired reactions. Such problems may be eased by optimizing the amount of enzyme used (see Figure 4). Second, in these experiments, most inputs and auxiliary strands were synthetic DNA and thus contained deletions and mutations. In principle, all single-stranded input and auxiliary strands could also be obtained from phagemid DNA through a nicking enzyme digestion of the pre-encoded m13 viral genome26. Perhaps the circuit performance can be further improved using ssDNA derived from the bacterial genome.
While the use of plasmid-derived gates was found to improve circuit performance, an analysis of the cost and processing times revealed that while the production of plasmid-derived gates is slightly cheaper (Table 15), it takes 2-3 times longer processing time compared to assembly and purification of gates from commercially synthesized oligos (Table 16). The primary costs of plasmid-derived gates are gene synthesis and the use of restriction enzymes. For 300 pmole of gates (enough for 15 reactions at 30 nM), the estimated cost for Join gates is approximately $170 and $200 for Fork gates, the cost difference being due to the use of different nicking enzymes. In contrast, the chemical synthesis of the strands for the same gate costs around $260 including a PAGE purification fee. The primary time cost for plasmid-derived gates is in the cloning procedure, which, just like DNA synthesis, can be outsourced to a gene synthesis company. However, once assembled, plasmid-derived gates have the advantage that the host plasmids can easily be replicated and can be stored in the form of bacterial glycerol stocks. This makes it possible to reuse the gates many times over.
Looking forward, the improved performance of plasmid-derived gates could enable a much larger range of dynamics behaviors than have been experimentally demonstrated so far with DNA CRNs. For example, recent theoretical work47,48 suggested that self-organized spatial patterns at the macro-scale can be realized with DNA CRNs through a reaction diffusion mechanism. The method presented here provides a viable path for constructing the underlying molecular components for such self-patterning DNA materials. Though challenging, developing macro-scale morphologies in a programmable way would have significant implications in areas ranging from biomaterials research to regenerative medicine.

The predictability of Watson-Crick base pairing has allowed dynamic DNA nanotechnology to emerge as a programmable way to design molecular devices with dynamic properties1,2. In particular, DNA strand displacement &#8212; a programmable, competitive hybridization reaction &#8212; has proved to be a powerful mechanism for engineering dynamic DNA systems. In a DNA strand displacement reaction, an incoming oligonucleotide displaces a previously bound &#8220;output&#8221; strand from a complementary binding partner. Multiple such reactions can be chained together into multi-step reaction cascades with a high degree of control over the order and timing of individual reaction steps3. DNA strand displacement cascades have been used to create digital and analog molecular circuits4-7, switchable nanostructures8-10, autonomous molecular motors11-15, and non-covalent catalytic amplifiers13,16-21. Moreover, DNA devices using strand displacement reactions can be simulated and designed for diverse applications using computer-assisted design software22-24.
Currently, chemically synthesized DNA serves as the main material for DNA nanotechnology. However, errors in the DNA synthesis process, and the resulting imperfect oligonucleotides, are believed to limit performance of dynamic DNA devices by causing erroneous side reactions. For example, &#8220;leak&#8221; reactions can result in the release of an output oligonucleotide even in the absence of a reaction trigger. Such effects are most obvious in autocatalytic reaction cascades where even a minimal amount of initial leak will eventually result in the full activation of the cascade19,20. Conversely, reactions often fail to reach the expected level of activation because some components do not trigger even in the presence of the intended input7,25. To make the performance of DNA-based nanodevices comparable to their biological protein-based counterparts, such error modes need to be dramatically reduced.
Bacterial plasmids or other biological DNA could serve as a relatively cheap source of highly pure DNA for nanotechnology applications. Large amounts of DNA can be generated by replication in bacteria and the intrinsic proofreading abilities of living systems ensure the purity of the resulting DNA. In fact, several recent papers have recognized the potential utility of biological DNA for nanotechnology applications21,26-28. However, the fully double-stranded nature of plasmid DNA has so far prohibited its use as a material for making dynamic DNA devices, which typically consist of multiple oligonucleotides and contain both double-stranded and single-stranded domains. In a recent paper29 this issue was addressed and a new DNA gate architecture that consists primarily of nicked double-stranded DNA (ndsDNA) was introduced.
Importantly, systems of ndsDNA gates can be designed that realize the dynamics specified by any formal chemical reaction network (CRN)29. ndsDNA gates could thus be used, in principle, to create dynamical systems that exhibit oscillations and chaos, bistability and memory, Boolean logic or algorithmic behaviors30-38. For example, Ref. 29 demonstrated a three-reaction CRN that provided a molecular implementation of a &#8220;consensus&#8221; protocol, a type of distributed computing algorithm29,39,40. This work first demonstrated a novel use for the CRN formalism as a &#8220;programming language&#8221; for rapidly synthesizing functional molecular systems (Figure 1A).
Here, a detailed protocol for deriving ndsDNA gates from plasmid DNA is provided. First is a review of the sequence design process. Then follows an explanation of how synthetic oligonucleotides containing the gate sequences are cloned into plasmids and sequence verified and amplified via bacterial culture. Next, it is shown how ndsDNA gates can be derived from the plasmids by enzymatic processing (see Figure 2). Finally, a method for testing gate behavior using fluorescence kinetics assays is outlined.
Reaction mechanism 
As an example, the protocol focuses on the catalytic chemical reaction A+B-&#62;B+C. The species A, B, and C (&#8220;signals&#8221;, Figure 1B) all correspond to a different single-stranded DNA molecule. The sequences of these molecules are completely independent and the strands do not react with one another directly. The sequences of all signals have two different functional domains, i.e., subsequences that act together in strand displacement reactions: 1) a short toehold domain (labels ta, tb, tc) that is used for initiation of strand displacement reaction, and 2) a long domain (labels a, b, c) that determines the signal identity.
Interactions between signal strands are mediated by nicked double-stranded DNA (ndsDNA) gate complexes (called JoinAB and ForkBC) and auxiliary single-stranded species (&#60;tr r&#62;, &#60;b tr&#62;, &#60;c tb&#62; and &#60;i tc&#62;). The formal reaction A+B-&#62;B+C is executed through a series of strand displacement reaction steps, where each reaction step exposes a toehold for a subsequent reaction (Figure 1B). In this example, signals A and B are initially free in solution while signal C is bound to the fork gate. At the end of the reaction B and C are in solution. More generally, signals that are bound to a gate are inactive while signals that are free in solution are active, that is, they can participate in a strand displacement reaction as an input. The time course of the reaction is followed using a fluorescent reporter strategy (Figure 1C). In previous work29, it was demonstrated that this reaction mechanism not only realizes the correct stoichiometry but also the kinetics of the target reaction.

<table border="0">
	<tbody>
		<tr>
			<td>Phusion High-Fidelity PCR Master Mix with HF Buffer</td>
			<td>NEB</td>
			<td>M0531S</td>
			<td></td>
		</tr>
		<tr>
			<td>PvuII-HF</td>
			<td>NEB</td>
			<td>R3151L</td>
			<td></td>
		</tr>
		<tr>
			<td>PstI-HF</td>
			<td>NEB</td>
			<td>R3140S</td>
			<td></td>
		</tr>
		<tr>
			<td>Gibson Assembly Master Mix</td>
			<td>NEB</td>
			<td>E2611S</td>
			<td></td>
		</tr>
		<tr>
			<td>Terrific Broth, Modified</td>
			<td>SIGMA-ALDRICH</td>
			<td>T0918-250G</td>
			<td></td>
		</tr>
		<tr>
			<td>QIAprep Spin Miniprep Kit (250)</td>
			<td>QIAGEN</td>
			<td>27106</td>
			<td></td>
		</tr>
		<tr>
			<td>QIAGEN Hispeed Maxi-prep Kit</td>
			<td>QIAGEN</td>
			<td>12662</td>
			<td></td>
		</tr>
		<tr>
			<td>Nb.BsrDI</td>
			<td>NEB</td>
			<td>R0648L</td>
			<td></td>
		</tr>
		<tr>
			<td>Nt.BstNBI</td>
			<td>NEB</td>
			<td>R0607L</td>
			<td></td>
		</tr>
		<tr>
			<td>NanoDrop 2000c</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Double-stranded Genomic Blocks</td>
			<td>IDT</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Horiba Jobin-Yvon Spex Fluorolog-3 Fluorimeter</td>
			<td>Horiba/Jobin Yvon</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Synthetic Quartz Cells&#160;</td>
			<td>Starna</td>
			<td>23-5.45-S0G-5</td>
			<td></td>
		</tr>
		<tr>
			<td>QIAGEN Gel Extraction Kit</td>
			<td>QIAGEN</td>
			<td>28706</td>
			<td></td>
		</tr>
		<tr>
			<td>Plasmid Backbones</td>
			<td>BioBrick</td>
			<td>E0240-pSB1A2</td>
			<td>High copy number plasmid with Ampicillin resistance. Sequence can be found from http://parts.igem.org</td>
		</tr>
	</tbody>
</table>

plasmid-derived dna strand displacement gates for implementing chemical reaction networks

DNA nanotechnology requires large amounts of highly pure DNA as an engineering material. Plasmid DNA could meet this need since it is replicated with high fidelity, is readily amplified through bacterial culture and can be stored indefinitely in the form of bacterial glycerol stocks. However, the double-stranded nature of plasmid DNA has so far hindered its efficient use for construction of DNA nanostructures or devices that typically contain single-stranded or branched domains. In recent work, it was found that nicked double stranded DNA (ndsDNA) strand displacement gates could be sourced from plasmid DNA. The following is a protocol that details how these ndsDNA gates can be efficiently encoded in plasmids and can be derived from the plasmids through a small number of enzymatic processing steps. Also given is a protocol for testing ndsDNA gates using fluorescence kinetics measurements. NdsDNA gates can be used to implement arbitrary chemical reaction networks (CRNs) and thus provide a pathway towards the use of the CRN formalism as a prescriptive molecular programming language. To demonstrate this technology, a multi-step reaction cascade with catalytic kinetics is constructed. Further it is shown that plasmid-derived components perform better than identical components assembled from synthetic DNA.

Watch this Scientific Journal Video about Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks at JoVE.com

Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks

This protocol describes a method for deriving DNA strand displacement gates from plasmids and testing them using fluorescence kinetics measurements. Gates can be modularly composed into multi-component systems to approximate the behavior of formal chemical reaction networks (CRN), demonstrating a new use for CRNs as a molecular programming language.

DNA nanotechnology requires large amounts of highly pure DNA as an engineering material. Plasmid DNA could meet this need since it is replicated with high ...

plasmid-derived-dna-strand-displacement-gates-for-implementing

Research

JoVE Journal

Biology

14.0K Views.  University of Washington. This protocol describes a method for deriving DNA strand displacement gates from plasmids and testing them using fluorescence kinetics measurements. Gates can be modularly composed into multi-component systems to approximate the behavior of formal chemical reaction networks (CRN), demonstrating a new use for CRNs as a molecular programming language. 

Video: Plasmid-derived DNA Strand Displacement Gates for Implementing Chemical Reaction Networks

Analysis of DNA Double-strand Break (DSB) Repair in Mammalian Cells

DNA double-strand breaks are the most dangerous DNA lesions that may lead to massive loss of genetic information and cell death. Cells repair DSBs using two major pathways: nonhomologous end joining (NHEJ) and homologous recombination (HR). Perturbations of NHEJ and HR are often associated with premature aging and tumorigenesis, hence it is important to have a quantitative way of measuring each DSB repair pathway. Our laboratory has developed fluorescent reporter constructs that allow sensitive and quantitative measurement of NHEJ and HR. The constructs are based on an engineered GFP gene containing recognition sites for a rare-cutting I-SceI endonuclease for induction of DSBs. The starting constructs are GFP negative as the GFP gene is inactivated by an additional exon, or by mutations. Successful repair of the I-SceI-induced breaks by NHEJ or HR restores the functional GFP gene. The number of GFP positive cells counted by flow cytometry provides quantitative measure of NHEJ or HR efficiency.

Analysis of DNA Double-strand Break DSB Repair in Mammalian Cells

This article describes GFP-based fluorescence in vivo assays that separately quantify homologous recombination and nonhomologous end joining in mammalian cells.

DNA double-strand breaks are the most dangerous DNA lesions that may lead to massive loss of genetic information and cell death.  Cells repair DSBs using ...

How to Culture, Record and Stimulate Neuronal Networks on Micro-electrode Arrays (MEAs)

For the last century, many neuroscientists around the world have dedicated their lives to understanding how neuronal networks work and why they stop working in various diseases. Studies have included neuropathological observation, fluorescent microscopy with genetic labeling, and intracellular recording in both dissociated neurons and slice preparations. This protocol discusses another technology, which involves growing dissociated neuronal cultures on micro-electrode arrays (also called multi-electrode arrays, MEAs).
There are multiple advantages to using this system over other technologies. Dissociated neuronal cultures on MEAs provide a simplified model in which network activity can be manipulated with electrical stimulation sequences through the array's multiple electrodes. Because the network is small, the impact of stimulation is limited to observable areas, which is not the case in intact preparations. The cells grow in a monolayer making changes in morphology easy to monitor with various imaging techniques. Finally, cultures on MEAs can survive for over a year in vitro which removes any clear time limitations inherent with other culturing techniques.1
Our lab and others around the globe are utilizing this technology to ask important questions about neuronal networks. The purpose of this protocol is to provide the necessary information for setting up, caring for, recording from and electrically stimulating cultures on MEAs. In vitro networks provide a means for asking physiologically relevant questions at the network and cellular levels leading to a better understanding of brain function and dysfunction.

How to Culture, Record and Stimulate Neuronal Networks on Micro-electrode Arrays MEAs

This protocol provides the necessary information for setting up, caring for, recording from and electrically stimulating cultures on MEAs. In vitro networks provide a means for asking physiologically relevant questions at the network and cellular levels leading to a better understanding of brain function and dysfunction.

For the last century, many neuroscientists around the world have dedicated their lives to understanding how neuronal networks work and why they stop ...

Bioengineering Human Microvascular Networks in Immunodeficient Mice

The future of tissue engineering and cell-based therapies for tissue regeneration will likely rely on our ability to generate functional vascular networks in vivo. In this regard, the search for experimental models to build blood vessel networks in vivo is of utmost importance 1. The feasibility of bioengineering microvascular networks in vivo was first shown using human tissue-derived mature endothelial cells (ECs) 2-4; however, such autologous endothelial cells present problems for wide clinical use, because they are difficult to obtain in sufficient quantities and require harvesting from existing vasculature. These limitations have instigated the search for other sources of ECs. The identification of endothelial colony-forming cells (ECFCs) in blood presented an opportunity to non-invasively obtain ECs 5-7. We and other authors have shown that adult and cord blood-derived ECFCs have the capacity to form functional vascular networks in vivo 7-11. Importantly, these studies have also shown that to obtain stable and durable vascular networks, ECFCs require co-implantation with perivascular cells. The assay we describe here illustrates this concept: we show how human cord blood-derived ECFCs can be combined with bone marrow-derived mesenchymal stem cells (MSCs) as a single cell suspension in a collagen/fibronectin/fibrinogen gel to form a functional human vascular network within 7 days after implantation into an immunodeficient mouse. The presence of human ECFC-lined lumens containing host erythrocytes can be seen throughout the implants indicating not only the formation (de novo) of a vascular network, but also the development of functional anastomoses with the host circulatory system. This murine model of bioengineered human vascular network is ideally suited for studies on the cellular and molecular mechanisms of human vascular network formation and for the development of strategies to vascularize engineered tissues.

Here, we describe a methodology to deliver human cord blood-derived endothelial colony-forming cells (ECFCs) and bone marrow-derived mesenchymal stem cells (MSCs), embedded in a collagen/fibronectin gel, subcutaneously into immunodeficient mice. This cell/gel combination generates a human vascular network that connects with the mouse vasculature.

The future of tissue engineering and cell-based therapies for tissue regeneration will likely rely on our ability to generate functional vascular networks ...

Iterative Optimization of DNA Duplexes for Crystallization of SeqA-DNA Complexes

Escherichia coli SeqA is a negative regulator of DNA replication that prevents premature reinitiation events by sequestering hemimethylated GATC clusters within the origin of replication1. Beyond the origin, SeqA is found at the replication forks, where it organizes newly replicated DNA into higher ordered structures2. SeqA associates only weakly with single GATC sequences, but it forms high affinity complexes with DNA duplexes containing multiple GATC sites. The minimal functional and structural unit of SeqA is a dimer, thereby explaining the requirement of at least two GATC sequences to form a high-affinity complex with hemimethylated DNA3. Additionally, the SeqA architecture, with the oligomerization and DNA-binding domains separated by a flexible linker, allows binding to GATC repeats separated by up to three helical turns. Therefore, understanding the function of SeqA at a molecular level requires the structural analysis of SeqA bound to multiple GATC sequences. In protein-DNA crystallization, DNA can have none to an exceptional effect on the packing interactions depending on the relative sizes and architecture of the protein and the DNA. If the protein is larger than the DNA or footprints most of the DNA, the crystal packing is primarily mediated by protein-protein interactions. Conversely, when the protein is the same size or smaller than the DNA or it only covers a fraction of the DNA, DNA-DNA and DNA-protein interactions dominate crystal packing. Therefore, crystallization of protein-DNA complexes requires the systematic screening of DNA length4 and DNA ends (blunt or overhang)5-7. In this report, we describe how to design, optimize, purify and crystallize hemimethylated DNA duplexes containing tandem GATC repeats in complex with a dimeric variant of SeqA (SeqA&Delta;(41-59)-A25R) to obtain crystals suitable for structure determination.

Crystal structure of protein&#x2013;DNA complexes can provide insight into protein function, mechanism, as well as, the nature of the specific interaction. Here, we report how to optimize the length, sequence and ends of duplex DNA for co-crystallization with Escherichia coli SeqA, a negative regulator of replication initiation.

Escherichia coli SeqA is a negative regulator of DNA replication that prevents premature reinitiation events by sequestering hemimethylated GATC clusters ...

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to identify commensal or mutualistic bacteria species. The latter ones, have been observed to serve multiple functions to the insect, i.e. helping in insect reproduction1, boosting the immune response2, pheromone production3, as well as nutrition, including the synthesis of essential amino acids4, among others. &#160; &#160;
Due to the importance of these associations, many efforts have been made to characterize the communities down to the individual members. However, most of these efforts were either based on cultivation methods or relied on the generation of 16S rRNA gene fragments which were sequenced for final identification. Unfortunately, these approaches only identified the bacterial species present in the gut and provided no information on the metabolic activity of the microorganisms.
To characterize the metabolically active bacterial species in the gut of an insect, we used stable isotope probing (SIP) in vivo employing 13C-glucose as a universal substrate. This is a promising culture-free technique that allows the linkage of microbial phylogenies to their particular metabolic activity. This is possible by tracking stable, isotope labeled atoms from substrates into microbial biomarkers, such as DNA and RNA5. The incorporation of 13C isotopes into DNA increases the density of the labeled DNA compared to the unlabeled (12C) one. In the end, the 13C-labeled DNA or RNA is separated by density-gradient ultracentrifugation from the 12C-unlabeled similar one6. Subsequent molecular analysis of the separated nucleic acid isotopomers provides the connection between metabolic activity and identity of the species.
Here, we present the protocol used to characterize the metabolically active bacteria in the gut of a generalist insect (our model system), Spodoptera littoralis (Lepidoptera, Noctuidae). The phylogenetic analysis of the DNA was done using pyrosequencing, which allowed high resolution and precision in the identification of insect gut bacterial community. As main substrate, 13C-labeled glucose was used in the experiments. The substrate was fed to the insects using an artificial diet.

Identification of Metabolically Active Bacteria in the Gut of the Generalist Spodoptera littoralis via DNA Stable Isotope Probing Using 13C-Glucose

The active bacterial community associated with the gut of Spodoptera littoralis, was determined by stable-isotope-probing (SIP) coupled to pyrosequencing. Using this methodology, identification of the metabolically active bacteria species within the community was done with high resolution and precision.

Guts of most insects are inhabited by complex communities of symbiotic nonpathogenic bacteria. Within such microbial communities it is possible to ...

Protocols for Implementing an Escherichia coli Based TX-TL Cell-Free Expression System for Synthetic Biology

Ideal cell-free expression systems can theoretically emulate an in vivo cellular environment in a controlled in vitro platform.1 This is useful for expressing proteins and genetic circuits in a controlled manner as well as for providing a prototyping environment for synthetic biology.2,3 To achieve the latter goal, cell-free expression systems that preserve endogenous Escherichia coli transcription-translation mechanisms are able to more accurately reflect in vivo cellular dynamics than those based on T7 RNA polymerase transcription. We describe the preparation and execution of an efficient endogenous E. coli based transcription-translation (TX-TL) cell-free expression system that can produce equivalent amounts of protein as T7-based systems at a 98% cost reduction to similar commercial systems.4,5 The preparation of buffers and crude cell extract are described, as well as the execution of a three tube TX-TL reaction. The entire protocol takes five days to prepare and yields enough material for up to 3000 single reactions in one preparation. Once prepared, each reaction takes under 8 hr from setup to data collection and analysis. Mechanisms of regulation and transcription exogenous to E. coli, such as lac/tet repressors and T7 RNA polymerase, can be supplemented.6 Endogenous properties, such as mRNA and DNA degradation rates, can also be adjusted.7 The TX-TL cell-free expression system has been demonstrated for large-scale circuit assembly, exploring biological phenomena, and expression of proteins under both T7- and endogenous promoters.6,8 Accompanying mathematical models are available.9,10 The resulting system has unique applications in synthetic biology as a prototyping environment, or "TX-TL biomolecular breadboard."

Protocols for Implementing an Escherichia coli Based TX-TL Cell-Free Expression System for Synthetic Biology

This five-day protocol outlines all steps, equipment, and supplemental software necessary for creating and running an efficient endogenous Escherichia coli based TX-TL cell-free expression system from scratch. With reagents, the protocol takes 8 hours or less to setup a reaction, collect, and process data.

Ideal cell-free expression systems can theoretically emulate an in vivo cellular environment in a controlled in vitro platform.1 This is useful for ...

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

The growing realization that both the temporal and spatial regulation of gene expression can have important consequences on cell function has led to the development of diverse techniques to visualize individual RNA transcripts in single living cells. One promising technique that has recently been described utilizes an oligonucleotide-based optical probe, ratiometric bimolecular beacon (RBMB), to detect RNA transcripts that were engineered to contain at least four tandem repeats of the RBMB target sequence in the 3&#8217;-untranslated region. RBMBs are specifically designed to emit a bright fluorescent signal upon hybridization to complementary RNA, but otherwise remain quenched. The use of a synthetic probe in this approach allows photostable, red-shifted, and highly emissive organic dyes to be used for imaging. Binding of multiple RBMBs to the engineered RNA transcripts results in discrete fluorescence spots when viewed under a wide-field fluorescent microscope. Consequently, the movement of individual RNA transcripts can be readily visualized in real-time by taking a time series of fluorescent images. Here we describe the preparation and purification of RBMBs, delivery into cells by microporation and live-cell imaging of single RNA transcripts.

Ratiometric bimolecular beacons (RBMBs) can be used to image single engineered RNA transcripts in living cells. Here, we describe the preparation and purification of RBMBs, delivery of RBMBs into cells by microporation and fluorescent imaging of single RNA transcripts in real-time.

The growing realization that both the temporal and spatial regulation of gene expression can have important consequences on cell function has led to the ...

Reduced-gravity Environment Hardware Demonstrations of a Prototype Miniaturized Flow Cytometer and Companion Microfluidic Mixing Technology

Until recently, astronaut blood samples were collected in-flight, transported to earth on the Space Shuttle, and analyzed in terrestrial laboratories. If humans are to travel beyond low Earth orbit, a transition towards space-ready, point-of-care (POC) testing is required. Such testing needs to be comprehensive, easy to perform in a reduced-gravity environment, and unaffected by the stresses of launch and spaceflight. Countless POC devices have been developed to mimic laboratory scale counterparts, but most have narrow applications and few have demonstrable use in an in-flight, reduced-gravity environment. In fact, demonstrations of biomedical diagnostics in reduced gravity are limited altogether, making component choice and certain logistical challenges difficult to approach when seeking to test new technology. To help fill the void, we are presenting a modular method for the construction and operation of a prototype blood diagnostic device and its associated parabolic flight test rig that meet the standards for flight-testing onboard a parabolic flight, reduced-gravity aircraft. The method first focuses on rig assembly for in-flight, reduced-gravity testing of a flow cytometer and a companion microfluidic mixing chip. Components are adaptable to other designs and some custom components, such as a microvolume sample loader and the micromixer may be of particular interest. The method then shifts focus to flight preparation, by offering guidelines and suggestions to prepare for a successful flight test with regard to user training, development of a standard operating procedure (SOP), and other issues. Finally, in-flight experimental procedures specific to our demonstrations are described.

Spaceflight blood diagnostics need innovation. Few demonstrations have been published illustrating in-flight, reduced-gravity health diagnostic technology. Here we present a method for construction and operation of a parabolic flight test rig for a prototype point-of-care flow-cytometry design, with components and preparation strategies adaptable to other setups.

Until recently, astronaut blood samples were collected in-flight, transported to earth on the Space Shuttle, and analyzed in terrestrial laboratories. If ...

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This protocol provides step-by-step instructions for the development and application of quantitative assays using selected reaction monitoring (SRM) mass spectrometry (MS). First, likely quantotypic target peptides are identified based on numerous criteria. This includes identifying proteotypic peptides, avoiding sites of posttranslational modification, and analyzing the uniqueness of the target peptide to the target protein. Next, crude external peptide standards are synthesized and used to develop SRM assays, and the resulting assays are used to perform qualitative analyses of the biological samples. Finally, purified, quantified, heavy isotope labeled internal peptide standards are prepared and used to perform isotope dilution series SRM assays. Analysis of all of the resulting MS data is presented. This protocol was used to accurately assay the absolute abundance of proteins of the chemotaxis signaling pathway within RAW 264.7 cells (a mouse monocyte/macrophage cell line). The quantification of Gi2 (a heterotrimeric G-protein &#945;-subunit) is described in detail.

This protocol describes how to perform absolute quantification assays of target proteins within complex biological samples using selected reaction monitoring. It was used to accurately quantify proteins of the mouse macrophage chemotaxis signaling pathway. Target peptide selection, assay development, and qualitative and quantitative assays are described in detail.

Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This ...

In Vivo Alkaline Comet Assay and Enzyme-modified Alkaline Comet Assay for Measuring DNA Strand Breaks and Oxidative DNA Damage in Rat Liver

Unrepaired DNA damage can lead to genetic instability, which in turn may enhance cancer development. Therefore, identifying potential DNA damaging agents is important for protecting public health. The in vivo alkaline comet assay, which detects DNA damage as strand breaks, is especially relevant for assessing the genotoxic hazards of xenobiotics, as its responses reflect the in vivo absorption, tissue distribution, metabolism and excretion (ADME) of chemicals, as well as DNA repair process. Compared to other in vivo DNA damage assays, the assay is rapid, sensitive, visual and inexpensive, and, by converting oxidative DNA damage into strand breaks using specific repair enzymes, the assay can measure oxidative DNA damage in an efficient and relatively artifact-free manner. Measurement of DNA damage with the comet assay can be performed using both acute and subchronic toxicology study designs, and by integrating the comet assay with other toxicological assessments, the assay addresses animal welfare requirements by making maximum use of animal resources. Another major advantage of the assays is that they only require a small amount of cells, and the cells do not have to be derived from proliferating cell populations. The assays also can be performed with a variety of human samples obtained from clinically or occupationally exposed individuals.

In Vivo Alkaline Comet Assay and Enzyme-modified Alkaline Comet Assay for Measuring DNA Strand Breaks and Oxidative DNA Damage in Rat Liver

The alkaline comet assay measures DNA strand breaks in eukaryotic cells. By adding an Endonuclease III or human 8-oxoguanine-DNA-N-glycosylase digestion step, the assay can efficiently detect oxidative DNA damage. We describe methods for using these assays to detect DNA damage in rat liver.

Unrepaired DNA damage can lead to genetic instability, which in turn may enhance cancer development. Therefore, identifying potential DNA damaging agents ...