recent SynBio papers
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A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity
Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems provide bacteria and archaea with adaptive immunity against viruses and plasmids by using CRISPR RNAs (crRNAs) to guide the silencing of invading nucleic acids. We show here that in a subset of these systems, the mature crRNA that is base-paired to trans-activating crRNA (tracrRNA) forms a two-RNA structure that directs the CRISPR-associated protein Cas9 to introduce double-stranded (ds) breaks in target DNA. At sites complementary to the crRNA-guide sequence, the Cas9 HNH nuclease domain cleaves the complementary strand, whereas the Cas9 RuvC-like domain cleaves the noncomplementary strand. The dual-tracrRNA:crRNA, when engineered as a single RNA chimera, also directs sequence-specific Cas9 dsDNA cleavage.
Synthetic Biology: Mapping the Scientific Landscape
Results The Rise of Synthetic Biology As of January 2012 a total of 1,255 publications were listed in Web of Science for synthetic biology and synthetic genomics in the period to the end of December 2011 ( Figure 1 ).
Genetic information storage and processing rely on just two polymers, DNA and RNA, yet whether their role reflects evolutionary history or fundamental functional constraints is currently unknown. With the use of polymerase evolution and design, we show that genetic information can be stored in and recovered from six alternative genetic polymers based on simple nucleic acid architectures not found in nature [xeno-nucleic acids (XNAs)]. We also select XNA aptamers, which bind their targets with high affinity and specificity, demonstrating that beyond heredity, specific XNAs have the capacity for Darwinian evolution and folding into defined structures. Thus, heredity and evolution, two hallmarks of life, are not limited to DNA and RNA but are likely to be emergent properties of polymers capable of information storage. <p style="text-align:right;color:#A8A8A8"></p>
Synthetic Genetic Polymers Capable of Heredity and Evolution
Abstract Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness).
Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit
Trends in Biotechnology - Distributed computation: the new wave of synthetic biology devices
Distributed computation: the new wave of synthetic biology devices Volume 30, Issue 6 , Pages 342-349, Publication Date 18 April 2012 Copyright © 2012 Elsevier Ltd All rights reserved. DOI: 10.1016/j.tibtech.2012.03.006 Javier Macía
Researchers often require customised variations of plasmids that are not commercially available. Here we demonstrate the applicability and versatility of standard synthetic biological parts (biobricks) to build custom plasmids. For this purpose we have built a collection of 52 parts that include multiple cloning sites (MCS) and common protein tags, protein reporters and selection markers, amongst others. Importantly, most of the parts are designed in a format to allow fusions that maintain the reading frame.
A Biobrick Library for Cloning Custom Eukaryotic Plasmids
Abstract Cellular efficiency in protein translation is an important fitness determinant in rapidly growing organisms. It is widely believed that synonymous codons are translated with unequal speeds and that translational efficiency is maximized by the exclusive use of rapidly translated codons. Here we estimate the in vivo translational speeds of all sense codons from the budding yeast Saccharomyces cerevisiae . Surprisingly, preferentially used codons are not translated faster than unpreferred ones. We hypothesize that this phenomenon is a result of codon usage in proportion to cognate tRNA concentrations, the optimal strategy in enhancing translational efficiency under tRNA shortage.
Balanced Codon Usage Optimizes Eukaryotic Translational Efficiency
† School of Biological and Health Systems Engineering, Arizona State University , Tempe, Arizona 85287, United States ‡ Laboratory of Cellular and Molecular Engineering, University of Bologna , I-47521 Cesena, Italy § Department of Systems Biology, Harvard Medical School , Boston, Massachusetts 02115, United States
A Sensitive Switch for Visualizing Natural Gene Silencing in Single Cells - ACS Synthetic Biology
Yeast is an ideal organism for the development and application of synthetic biology, yet there remain relatively few well-characterised biological parts suitable for precise engineering of this chassis. In order to address this current need, we present here a strategy that takes a single biological part, a promoter, and re-engineers it to produce a fine-graded output range promoter library and new regulated promoters desirable for orthogonal synthetic biology applications. A highly constitutive Saccharomyces cerevisiae promoter, PFY1 p, was identified by bioinformatic approaches, characterised in vivo and diversified at its core sequence to create a 36-member promoter library.
Rational Diversification of a Promoter Providing Fine-Tuned Expression and Orthogonal Regulation for Synthetic Biology
We describe an autonomous DNA nanorobot capable of transporting molecular payloads to cells, sensing cell surface inputs for conditional, triggered activation, and reconfiguring its structure for payload delivery. The device can be loaded with a variety of materials in a highly organized fashion and is controlled by an aptamer-encoded logic gate, enabling it to respond to a wide array of cues. We implemented several different logical AND gates and demonstrate their efficacy in selective regulation of nanorobot function. As a proof of principle, nanorobots loaded with combinations of antibody fragments were used in two different types of cell-signaling stimulation in tissue culture. Our prototype could inspire new designs with different selectivities and biologically active payloads for cell-targeting tasks. <p style="text-align:right;color:#A8A8A8"></p>
A Logic-Gated Nanorobot for Targeted Transport of Molecular Payloads
Microfluidic biofilm engineering circuit The microfluidic biofilm engineering (μBE) signalling circuit was constructed in E. coli using two engineered biofilm-dispersing proteins, Hha13D6 (ref. 15 ) and BdcAE50Q 16 , along with the P. aeruginosa LasI/LasR QS system ( Fig. 1a ) for use in the novel microfluidic device ( Fig. 1b ) . E. coli hha 31 was used as the host as deletion of hha increases biofilm formation 14 and provides a background in which there is no wild-type Hha. Lactococcal promoter CP25 32 was used as the strong constitutive promoter for two of the three proteins on each plasmid.
Synthetic quorum-sensing circuit to control consortial biofilm formation and dispersal in a microfluidic device : Nature Communications
Science Translational Medicine stm.sciencemag.org Sci Transl Med 26 October 2011: Vol. 3, Issue 106, p. 106ps42 Sci. Transl. Med. DOI: 10.1126/scitranslmed.3002944 Perspective Bioengineering
From DNA to Targeted Therapeutics: Bringing Synthetic Biology to the Clinic
Author Affiliations Edited by Peter J. Bickel, University of California, Berkeley, CA, and approved July 27, 2011 (received for review December 1, 2010) Abstract Here we introduce a new design framework for synthetic biology that exploits the advantages of Bayesian model selection. We will argue that the difference between inference and design is that in the former we try to reconstruct the system that has given rise to the data that we observe, whereas in the latter, we seek to construct the system that produces the data that we would like to observe, i.e., the desired behavior.