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byZohreh Nourian and Christophe Danelon "Reconstituting an elementary gene expression system inside self-assembled lipid vesicles to mimic the cellular synthesis machinery is at the core of the development of a minimal cell following a bottom-up synthetic biology approach. The ability to operate the expression of multiple genes in a controlled manner and to generate the output proteins with predictable dynamics in liposomes relies on the link between genotype and phenotype. Here, we established this link in surface-tethered liposomes producing proteins from a linear DNA template using a reconstituted transcription/translation/aminoacylation apparatus fuelled by external supply of feedstock. The amounts of entrapped DNA molecules and synthesized proteins were visualized by fluorescence confocal microscopy in individual vesicles. We showed that there exists no linear correlation between the amount of encapsulated genes and the level of output proteins, which is a consequence of the compositional heterogeneity between liposomes due to the low-copy number of some constituents, as well as interfacing differences with the nutrient-containing environment. In order to decouple gene activity from those sources of variability and, thus, infer the probabilistic occupancy of transcriptionally active genes in protein synthesizing liposomes, we developed a dual gene expression assay consisting of the production of two fluorescent reporter proteins of distinguishable colors from two different DNA templates. The stochastic color-coding of the vesicles was analyzed and compared to the color pattern expected from a Poisson distribution of encapsulated genes. Unexpectedly, we found that the apparent number of transcriptionally active DNA molecules in liposomes corresponds only to ca. 10% of the bulk concentration. We believe that our study provides new insights about the relationship between the genotype and phenotype in protein synthesizing liposomes, which is of primary importance toward the construction of a programmable artificial cell implemented with regulatory gene networks of predictable dynamics."http://bit.ly/10vpfqp
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In the Internet era, research moves from professionals’ labs to amateurs’ homes
byThambisetty, Sivaramjani "This paper transposes dominant normative critiques with an institutionalist view of patent law by analysing how the multi-institutional setup of the patent system may determine the quality and coherence of change and decision-making. The institutional environment of the patent system makes it opaque, sticky and complex. These significant features are examined for the first time in this paper. Critical opportunities for statutorily determined decision-making are best described as learning needs, expressed through heuristics such as the person skilled in the art, inventive step determinations and prior art. These learning needs, set against the broader institutional environment, severely constrain current goals and limit future decision-making possibilities. In the case of an emerging technology such as synthetic biology, the management of learning needs is likely to lead to decisional outcomes marked by a desire for short-term gains in certainty and homogeneity, rather than substantive goals."http://bit.ly/1bOgxg5
byMadec, Morgan, Pecheux, Francois ; Gendrault, Yves ; Bauer, Loic, Haiech, Jacques ; Lallement, Christophe"The topic of this paper is to develop an open-source framework to help bio-engineers through the different stages of a top-down design process for new artificial biosystems (synthetic biology). The presented tools address the upstream stages of the design, starting from a high-level behavioral description of the targeted biological function and ending with a working assembly of abstract BioBricks performing that very function. For that purpose, EDA (Electronic Design Automation) tools are indeed adapted to synthetic biology. The framework involves three main steps: the interpretation of the high-level description into a netlist of logical functions, the optimization of the netlist with respect to BioBricks capabilities and the automated generation of a SystemC-AMS abstracted simulatable netlist that can be used for further analysis (low-level simulation, optimization …). Throughout the paper, each stage of the framework is detailed and illustrated with a simple (from a logical point of view) but complex (from the biological viewpoint) example: an in-vivo chemical species regulation system."http://bit.ly/19w0iEQ
Researchers demonstrate a strategy for the fabrication of memristive nanodevices with stable and tunable performance by assembling ferritin monolayer inside a on-wire lithography-generated 12 nm gap.
A synthetic biology approach for evaluating the functional contribution of designer cellulosome components to deconstruction of cellulosic substrates - up-to-the-minute news and headlines.
Synthetic genomic approaches offer unique opportunities to use powerful yeast and Escherichia coli genetic systems to assemble and modify chromosome-sized molecules before returning the modified DNA to the target host.
The hype began with the way hype often begins: an institutional news release offering us the holy grail/huge breakthrough/game-changing finding of the day.
*"Scientists have discovered a second code hiding within DNA"**Exonic Transcription Factor Binding Directs Codon Choice and Affects Protein Evolution*Andrew B. Stergachis, Eric Haugen, Anthony Shafer, Wenqing Fu, Benjamin Vernot, Alex Reynolds, Anthony Raubitschek, Steven Ziegler, Emily M. LeProust, Joshua M. Akey"Genomes contain both a genetic code specifying amino acids and a regulatory code specifying transcription factor (TF) recognition sequences. We used genomic deoxyribonuclease I footprinting to map nucleotide resolution TF occupancy across the human exome in 81 diverse cell types. We found that ~15% of human codons are dual-use codons (“duons”) that simultaneously specify both amino acids and TF recognition sites. Duons are highly conserved and have shaped protein evolution, and TF-imposed constraint appears to be a major driver of codon usage bias. Conversely, the regulatory code has been selectively depleted of TFs that recognize stop codons. More than 17% of single-nucleotide variants within duons directly alter TF binding. Pervasive dual encoding of amino acid and regulatory information appears to be a fundamental feature of genome evolution." http://bit.ly/1ddwqMfComments:*The Hidden Codes That Shape Protein Evolution*byRobert J. Weatheritt, M. Madan Babu"Despite redundancy in the genetic code (1), the choice of codons used is highly biased in some proteins, suggesting that additional constraints operate in certain protein-coding regions of the genome. This suggests that the preference for particular codons, and therefore amino acids in specific regions of the protein, is often determined by factors unrelated to protein structure or function (2, 3). On page 1367 in this issue, Stergachis et al. (4) reveal that transcription factors bind within protein-coding regions (in addition to nearby noncoding regions) in a large number of human genes. Thus, a transcription factor “binding code” may influence codon choice and, consequently, protein evolution. This “binding” code joins other “regulatory” codes that govern chromatin organization (3), enhancers (5, 6), mRNA structure (7), mRNA splicing (3), microRNA target sites (6, 8), translational efficiency (9), and cotranslational folding (10), all of which have been proposed to constrain codon choice, and thus protein evolution."http://bit.ly/1bEN84m*Scientists discover double meaning in genetic code*by Anonymous"Scientists have discovered a second code hiding within DNA. This second code contains information that changes how scientists read the instructions contained in DNA and interpret mutations to make sense of health and disease.
RT @TeselaGen: RSVP for Synthetic Biology Open Language Workshop 10 at @UCBerkeley, Jan 7-9, 2014 http://t.co/XCShbNsWbe
Methods for engineering biology. Nina DiPrimio discusses tools for design and construction and plans for future projects. Presented by Counter Culture Labs, ...
byCharles Gersbach"Elaborate competitions to build the best robot or design cages to protect falling eggs have been a rite of passage for generations of engineering students. Today, there’s a new contest with the same creativity and competitive spirit, but vastly more sophisticated projects—like mixing-and-matching bits of DNA to create new microorganisms that produce biofuels or costly medicines.
"Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady state. Our model and findings provide a general framework to guide design principles in synthetic biology." http://bit.ly/10lPH9m
by Shamees Aden
byGendrault, Yves, Madec, Morgan ; Wlotzko, Vincent ; Lallement, Christophe ; Haiech, Jacques"Synthetic biology, or biological engineering, is a new science which may take advantage of the know-how of engineering science in order to build new in-vivo biological functions. The complete design process implies lots of modeling and simulation tasks. The design flow for this technology uses “digital” models at high level of abstraction as well as “analogue” ones at low level. Nevertheless, contrary to electronics, high-level digital descriptions are far away from low-level ones. In this paper, an intermediate modeling level using the principle of fuzzy logic is proposed to fill the gap between high and low abstraction level. The main advantage of this approach is to obtain quantitative simulation results while keeping a behavioral description of mechanisms. This is pointed out through two examples. The first one, encountered in literature, tends to prove that this modeling level is sufficient to obtain reliable results in comparison with the experimental ones. The second one, which is more theoretical, demonstrates the interest of fuzzy logic from a designing point of view."http://bit.ly/1cz35ua
New gene-editing system enables large-scale studies of gene function.
An experimental exhibition at Dublin’s Science Gallery brings together artists, scientists and designers to investigate an emerging approach to genetic engineering known as ‘synthetic biology’.
Yale researchers have discovered a targeted way to make proteins not generally found in nature by expanding the information encrypted in the genetic code.
Ero.Coli | Game overview of Ero.Coli, a synthetic biology game project made by the Dsynbio Club.
Even if this discovery has been overstated doesn't mean that it doesn't capture something interesting about the way the world works.
*"The startup world is beating academics at their own game.”*
byAnonymous"Semiconductor Research Corporation (SRC), the world’s leading university-research consortium for semiconductor technologies, launched the Semiconductor Synthetic Biology (SSB) research program on hybrid bio-semiconductor systems to provide insights and opportunities for future information and communication technologies. The program will initially fund research at six universities: Massachusetts Institute of Technology, the Univ. of Massachusetts at Amherst, Yale, Georgia Tech, Brigham Young and the Univ. of Washington.
On December 9-11, the eilslabs at DKFZ and BioQuant, as part of the coordination of the Helmholtz Initiative on Synthetic Biology is hosting the International Symposium "Synthetic Biology - from understanding to application" ...
"During her master's programme in genetics from 2005 to 2008, Sarah Hird dreaded going into the lab. She was studying subspecies of red-tailed chipmunks and had become discouraged and frustrated by the uncertainties of molecular-biology experiments." http://bit.ly/1aZkrz6