Models for synthetic biology

Synthetic biological engineering is emerging from biology as a distinct discipline based on quantification. The technologies propelling synthetic biology are not new, nor is the concept of designing novel biological molecules. What is new is the emphasis on system behavior

Local Delivery of Human Tissue Kallikrein Gene Accelerates Spontaneous Angiogenesis in Mouse Model of Hindlimb Ischemia

Background —Human tissue kallikrein (HK) releases kinins from kininogen. We investigated whether adenovirus-mediated HK gene delivery is angiogenic in the context of ischemia. Methods and Results —Hindlimb ischemia, caused by femoral artery excision, increased muscular capillary density ( P 1 receptor gene ( P 1 receptors blunted ischemia-induced angiogenesis ( P 2 receptor antagonism was ineffective. Intramuscular delivery of adenovirus containing the HK gene (Ad.CMV-cHK) enhanced the increase in capillary density caused by ischemia (969±32 versus 541±18 capillaries/mm 2 for control, P P P 1 or B 2 receptors prevented HK-induced angiogenesis. Conclusions —HK gene delivery enhances the native angiogenic response to ischemia. Angiogenesis gene therapy with HK might be applicable to peripheral occlusive vascular disease

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Ribozyme-based insulator parts buffer synthetic circuits from genetic context

Synthetic genetic programs are built from circuits that integrate sensors and implement temporal control of gene expression. Transcriptional circuits are layered by using promoters to carry the signal between circuits. In other words, the output promoter of one circuit serves as the input promoter to the next. Thus, connecting circuits requires physically connecting a promoter to the next circuit. We show that the sequence at the junction between the input promoter and circuit can affect the input-output response (transfer function) of the circuit. A library of putative sequences that might reduce (or buffer) such context effects, which we refer to as 'insulator parts', is screened in Escherichia coli. We find that ribozymes that cleave the 5′ untranslated region (5′-UTR) of the mRNA are effective insulators. They generate quantitatively identical transfer functions, irrespective of the identity of the input promoter. When these insulators are used to join synthetic gene circuits, the behavior of layered circuits can be predicted using a mathematical model. The inclusion of insulators will be critical in reliably permuting circuits to build different programs.Life Technologies, Inc.United States. Defense Advanced Research Projects Agency (DARPA CLIO N66001-12-C-4018)United States. Office of Naval Research (N00014-10-1-0245)National Science Foundation (U.S.) (CCF-0943385)National Institutes of Health (U.S.) (AI067699)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SynBERC, SA5284-11210

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10[superscript 54] circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.United States. Air Force Office of Scientific Research (Award FA9550-11-C-0028)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship (32 CFR 168a)United States. Defense Advanced Research Projects Agency. Chronical of Lineage Indicative of Origins (N66001-12-C-4016)United States. Office of Naval Research (N00014-13-1-0074)National Institutes of Health (U.S.) (GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SA5284-11210

OptCircuit: An optimization based method for computational design of genetic circuits

<p>Abstract</p> <p>Background</p> <p>Recent years has witnessed an increasing number of studies on constructing simple synthetic genetic circuits that exhibit desired properties such as oscillatory behavior, inducer specific activation/repression, etc. It has been widely acknowledged that that task of building circuits to meet multiple inducer-specific requirements is a challenging one. This is because of the incomplete description of component interactions compounded by the fact that the number of ways in which one can chose and interconnect components, increases exponentially with the number of components.</p> <p>Results</p> <p>In this paper we introduce OptCircuit, an optimization based framework that automatically identifies the circuit components from a list and connectivity that brings about the desired functionality. Multiple literature sources are used to compile a comprehensive compilation of kinetic descriptions of promoter-protein pairs. The dynamics that govern the interactions between the elements of the genetic circuit are currently modeled using deterministic ordinary differential equations but the framework is general enough to accommodate stochastic simulations. The desired circuit response is abstracted as the maximization/minimization of an appropriately constructed objective function. Computational results for a toggle switch example demonstrate the ability of the framework to generate the complete list of circuit designs of varying complexity that exhibit the desired response. Designs identified for a genetic decoder highlight the ability of OptCircuit to suggest circuit configurations that go beyond the ones compatible with digital logic-based design principles. Finally, the results obtained from the concentration band detector example demonstrate the ability of OptCircuit to design circuits whose responses are contingent on the level of external inducer as well as pinpoint parameters for modification to rectify an existing (non-functional) biological circuit and restore functionality.</p> <p>Conclusion</p> <p>Our results demonstrate that OptCircuit framework can serve as a design platform to aid in the construction and finetuning of integrated biological circuits.</p

Experimental Verification of a Predicted Intronic MicroRNA in Human NGFR Gene with a Potential Pro-Apoptotic Function

Neurotrophins (NTs) are a family of secreted growth factor proteins primarily involved in the regulation of survival and appropriate development of neural cells, functioning by binding to their specific (TrkA, TtkB, and TrkC) and/or common NGFR receptor. NGFR is the common receptor of NTs, binding with low-affinity to all members of the family. Among different functions assigned to NGFR, it is also involved in apoptosis induction and tumorigenesis processes. Interestingly, some of the functions of NGFR appear to be ligand-independent, suggesting a probable involvement of non-coding RNA residing within the sequence of the gene. Here, we are reporting the existence of a conserved putative microRNA, named Hsa-mir-6165 [EBI accession#: FR873488]. Transfection of a DNA segment corresponding to the pre-mir-6165 sequence in Hela cell line caused the generation of mature exogenous mir-6165 (a ∼200,000 fold overexpression). Furthermore, using specific primers, we succeeded to detect the endogenous expression of mir-6165 in several glioma cell lines and glioma primary tumors known to express NGFR. Similar to the pro-apoptotic role of NGFR in some cell types, overexpression of pre-mir-6165 in U87 cell line resulted in an elevated rate of apoptosis. Moreover, coordinated with the increased level of mir-6165 in the transfected U87 cell line, two of its predicted target genes (Pkd1 and DAGLA) were significantly down-regulated. The latter findings suggest that some of the previously attributed functions of NGFR could be explained indirectly by co-transcription of mir-6165 in the cells