Thiprampai Thamamongood, Nathaniel Z. L. Lim, Trevor Y.H. Ho, Shotaro Ayukawa, Daisuke Kiga, and King L. Chow
"The main goal of synthetic biology is to create new biological modules that augment or modify the behavior of living organisms in performing different tasks. These modules are useful in a wide range of applications, such as medicine, agriculture, energy and environmental remediation. The concept is simple, but a paradigm shift needs to be in place among future life scientists and engineers to embrace this new direction. The international Genetically Engineered Machine (iGEM) competition fits this purpose well as a synthetic biology competition mainly for undergraduate students. Participants design and construct biological devices using standardized and customized biological parts that are then characterized and submitted to an existing and ever expanding library. Overall, iGEM is an eye-opening learning experience for undergraduate students. It has made a strong educational impact on participating students and cultivated a future cohort of synthetic biology practitioners and ambassadors. "
""Synthetic biology" is defined as applying engineering principles to biological parts. It is "an area of research focused on the design and construction of new biological parts and devices, or re-design of existing biological systems."
The genetic code of simple organisms, for example, can be constructed in the laboratory using techniques that sew together a strand of specific A's, T's, G's, and C's. Several potential applications have been touted, including creating organisms that are useful in cleaning up biofuels, drug delivery, and drug studies. A recent study involved creating E. coli that are addicted to caffeine, which could be helpful in purifying water and treating asthma. While some interesting research has come out in this area, the practical applications have not yet caught up with the hype from several years ago when Craig Venter replicated the entire genome of a known bacterium and reinserted it in a cell (see our comments here). The lag is partly due to a couple of fundamental assumptions in synthetic biology that might pose problems in actual applications. For one, synthetic biology assumes gene expression is the fundamental building block of organisms, which is a reductionistic view of how life works. Certainly, there are some cases where a particular gene codes for a particular disease or a particular function. One classic example is Huntington's disease, which has a very specific genetic marker. Those with the genetic marker will get the disease. However, as we have seen from the results of the ENCODE project, there are many factors that affect whether a gene is expressed, and how proteins function. Second, according to Drew Endy, one of the authors of two papers on mass-producing synthetic biological components, many biologists have been trying to assemble the component parts of biological systems in a modular, piecemeal fashion (Nucl. Acid Res. published concurrently with Nature Methods). One reason for Endy's team's success is the way that they have approached biological systems. Rather than in terms of modular pieces, they took a more integrated approach. From an article in New Scientist: The team found that bundling parts together according to their specific function gave more reliable results than considering them separately. This is how nature does it, says Endy, but the dogma had been that all parts should be clearly separated and assembled in a more modular way, which was the principle used to set up the BioBricks registry, an existing library of parts, in 2003. It was a case of "let's change our religion on how you assemble things", says Endy.This view takes an engineering perspective on biological systems, which is counter to the typical neo-Darwinian style. Darwinism assumes that organisms are built from the bottom-up, where complexity comes from the incorporation of additional components via chance and selection pressure. An engineering perspective assumes that biological systems are built from the top-down.In other words, the end function is already in mind when the biological system is constructed. Because of this, the system functions as a cohesive whole, rather than as modular components. Furthermore, and as Endy's group in particular points out, the parts of the biological systems are not interchangeable like Lego blocks. They have specific functions. Evolutionary theory says that trial and error lead to the biological structures that we see today. But this same trial-and-error method does not work in the laboratory setting, so why should we assume that it worked in nature? In synthetic biology, we have a field of science that applies engineering principles to biological systems. For practical purposes, it assumes that biological systems are engineered and that we can use design principles to re-construct these systems. Maybe that represents more than just a working assumption."
"Despite the multidisciplinary dimension of the kinds of research conducted under the umbrella of synthetic biology, the US-based founders of this new research area adopted a disciplinary profile to shape its institutional identity. In so doing they took inspiration from two already established fields with very different disciplinary patterns. The analogy with synthetic chemistry suggested by the term 'synthetic biology' is not the only model. Information technology is clearly another source of inspiration. The purpose of the paper, with its focus on the US context, is to emphasize the diversity of views and agendas coexisting under the disciplinary label synthetic biology, as the two models analysed are only presented as two extreme postures in the community. The paper discusses the question: in which directions the two models shape this emerging field? Do they chart two divergent futures for synthetic biology?"
*It’s alive! Researchers use 3D printer to create human-like cells*
by Meghan Kelly
"A team of scientists at Oxford University have printed — yes, printed — what could be the predecessors to usable synthetic human tissue.
The researchers released a paper called A Tissue-Like Material, announcing that they created their own version of a 3D printer, saying the current ones on the market couldn’t print what they were after, according to PhsyOrg. And what were they after? A protein sack of water that can mold itself into different shapes and perform similar functions to human cells. After developing the printer, the team was able to print out a series of droplets that formed a network of human-like cells that could act like nerves and send electrical signals across the network.“We aren’t trying to make materials that faithfully resemble tissues but rather structures that can carry out the functions of tissues,” said Oxford University Chemistry Professor Hagan Bayley, according to PhsyOrg.The researchers say that while their cells were nearly five times bigger than that of an average human cell, they believe the cells could be printed far smaller. They also noted that while their research only led them to print out two different types of cells, 50 or more kinds could be replicated. The cells currently only live for a few weeks."
by Gabriel Villar, Alexander D. Graham, Hagan Bayley
"Living cells communicate and cooperate to produce the emergent properties of tissues. Synthetic mimics of cells, such as liposomes, are typically incapable of cooperation and therefore cannot readily display sophisticated collective behavior. We printed tens of thousands of picoliter aqueous droplets that become joined by single lipid bilayers to form a cohesive material with cooperating compartments. Three-dimensional structures can be built with heterologous droplets in software-defined arrangements. The droplet networks can be functionalized with membrane proteins; for example, to allow rapid electrical communication along a specific path. The networks can also be programmed by osmolarity gradients to fold into otherwise unattainable designed structures. Printed droplet networks might be interfaced with tissues, used as tissue engineering substrates, or developed as mimics of living tissue." http://bit.ly/12F01JC
"Scientists at Oxford Genetics have developed a range of synthetic DNA products that they believe will revolutionize the genetic research sector. They say the new technology, called SnapFast™, provides a fully interchangeable module-based genetic engineering platform that offers research scientists improved efficiency and flexibility.
Managing director of Oxford Genetics Ryan Cawood, Ph.D., who invented the system, describes the cloning platform as “Lego for DNA”. Dr. Cawood explains how it works: “Historically, most genetic engineering has been performed with pieces of DNA, gathered from a variety of sources that were never intended to fit together. This can often make genetic engineering time-consuming and frustrating. What we are doing at Oxford Genetics is providing all of the standard DNA components that researchers use on a regular basis, and putting them into a compatible and ‘easy to clone’ format.” Oxford Genetics has developed a modular system in which every DNA component can be exchanged for hundreds of other DNA components that have been predesigned to offer a range of research functions, according to Dr. Cawood. This is the concept of SnapFast. “The system really allows you to make very complicated DNA research tools in quite a short amount of time,” he added. “We are also offering bespoke cloning and DNA synthesis services, allowing our customers to use us as a ‘one stop shop’ for genetic engineering.”"
"Synthetic biology presents a challenge to traditional accounts of biology: Whereas traditional biology emphasizes the evolvability, variability, and heterogeneity of living organisms, synthetic biology envisions a future of homogeneous, humanly engineered biological systems that may be combined in modular fashion. The present paper approaches this challenge from the perspective of the epistemology of technoscience. In particular, it is argued that synthetic-biological artifacts lend themselves to an analysis in terms of what has been called ‘thing knowledge’. As such, they should neither be regarded as the simple outcome of applying theoretical knowledge and engineering principles to specific technological problems, nor should they be treated as mere sources of new evidence in the general pursuit of scientific understanding. Instead, synthetic-biological artifacts should be viewed as partly autonomous research objects which, qua their material-biological constitution, embody knowledge about the natural world—knowledge that, in turn, can be accessed via continuous experimental interrogation."
*Enzyme-free translation of DNA into sequence-defined synthetic polymers structurally unrelated to nucleic acids*
by Jia Niu,Ryan Hili& David R. Liu
"The translation of DNA sequences into corresponding biopolymers enables the production, function and evolution of the macromolecules of life. In contrast, methods to generate sequence-defined synthetic polymers with similar levels of control have remained elusive. Here, we report the development of a DNA-templated translation system that enables the enzyme-free translation of DNA templates into sequence-defined synthetic polymers that have no necessary structural relationship with nucleic acids. We demonstrate the efficiency, sequence-specificity and generality of this translation system by oligomerizing building blocks including polyethylene glycol, α-(D)-peptides, and β-peptides in a DNA-programmed manner. Sequence-defined synthetic polymers with molecular weights of 26 kDa containing 16 consecutively coupled building blocks and 90 densely functionalized β-amino acid residues were translated from DNA templates using this strategy. We integrated the DNA-templated translation system developed here into a complete cycle of translation, coding sequence replication, template regeneration and re-translation suitable for the iterated in vitro selection of functional sequence-defined synthetic polymers unrelated in structure to nucleic acids."
by Peter Reuell "...As described in a recent paper in Nature Chemistry, a team of researchers led by David Liu, a professor of chemistry and chemical biology at Harvard, has developed a new method to create synthetic polymers using the coding of genetic material. The method may eventually be used to evolve synthetic polymers with new or improved properties such as the ability to serve as catalysts in chemical reactions or enhanced therapeutic potential. "The word polymer, unfortunately, is pretty vague, but in biology, large molecules like DNA, RNA, and proteins are the most common polymers," Liu said. "These polymers can have remarkable properties. Our ability to create man-made polymers with tailor-made properties, by comparison, is much more limited, in part because we don't have a way to evolve synthetic polymers—that's really the problem we set out to address." Other researchers have managed to create synthetic polymers using genetic coding, but their efforts were hampered by the fact that the new molecules necessarily resembled the genetic template used to create them. To solve that problem, Liu and colleagues turned to a process similar to one found in nature. Rather than allow the building blocks of a new polymer to interact directly with the DNA template, the system relies on an "adapter" molecule. The adapters, each of which carries a part of the polymer, bind to the template, forming the new polymer. In the final step of the process, Liu said, the adapters are cut away, leaving a synthetic polymer created according to the genetic template...." http://bit.ly/10E2HHC
"A biomolecular network is called adaptive if its output returns to the original value after a transient response even under a persisting stimulus. The conditions for adaptation have been investigated thoroughly with systems theory approaches in the literature and it is easy to check whether they are satisfied in the linear approximation. In contrast, it is in general not easy to modify a non-adaptive network model such that it gains adaptive behaviour, especially for medium- and large-scale networks. The authors present a systematic approach based on the notion of kinetic perturbations to construct adaptive biomolecular network models from non-adaptive ones. An advantage of kinetic perturbations in this application is that neither the stoichiometry nor the steady state of the system is changed. Furthermore, the method covers both parameter and network structure modifications and can be applied to any reaction rate formalism and even to medium-scale or partially unknown models. The approach is exemplified at a small- and a medium-sized biomolecular network, illustrating its potential to systematically evaluate the different network modifications for adaptation. The proposed method will be useful either in iterative model building to construct mathematical models of adaptive biomolecular networks, or in synthetic biology where it can be applied to design or modify synthetic networks for adaptation."
"Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks. Here we present a general methodology for analyzing the fidelity with which different statistics of a fluctuating input are represented, or encoded, in the output of a signaling system over time. We identify two orthogonal sources of error that corrupt perfect representation of the signal: dynamical error, which occurs when the network responds on average to other features of the input trajectory as well as to the signal of interest, and mechanistic error, which occurs because biochemical reactions comprising the signaling mechanism are stochastic. Trade-offs between these two errors can determine the system's fidelity. By developing mathematical approaches to derive dynamics conditional on input trajectories we can show, for example, that increased biochemical noise (mechanistic error) can improve fidelity and that both negative and positive feedback degrade fidelity, for standard models of genetic autoregulation. For a group of cells, the fidelity of the collective output exceeds that of an individual cell and negative feedback then typically becomes beneficial. We can also predict the dynamic signal for which a given system has highest fidelity and, conversely, how to modify the network design to maximize fidelity for a given dynamic signal. Our approach is general, has applications to both systems and synthetic biology, and will help underpin studies of cellular behavior in natural, dynamic environments."
"Researchers have created networks of water droplets that mimic some properties of cells in biological tissues. Using a three-dimensional printer, a team at the University of Oxford, UK, assembled tiny water droplets into a jelly-like material that can flex like a muscle and transmit electric signals like chains of neurons. The work is published today in Science1.
These networks, which can contain up to 35,000 droplets, could one day become a scaffold for making synthetic tissues or provide a model for organ functions, says co-author Gabriel Villar of Cambridge Consultants, a technology-transfer company in Cambridge, UK. “We want to see just how far we can push the mimicry of living tissue,” he says."
Treating patients with cells may one day become as common as it is now to treat the sick with drugs made from engineered proteins, antibodies or smaller chemicals, according to UC San Francisco researchers.
"Developing mechanistic models has become an integral aspect of systems biology, as has the need to differentiate between alternative models. Parameterizing mathematical models has been widely perceived as a formidable challenge, which has spurred the development of statistical and optimisation routines for parameter inference. But now focus is increasingly shifting to problems that require us to choose from among a set of different models to determine which one offers the best description of a given biological system. We will here provide an overview of recent developments in the area of model selection. We will focus on approaches that are both practical as well as build on solid statistical principles and outline the conceptual foundations and the scope for application of such methods in systems biology." http://bit.ly/10TK0hR
A wide range of bacteria species are known to communicate through the so called quorum sensing (QS) mechanism by means of which they produce a small molecule that can freely diffuse in the environment and in the cells.
Gerd Moe-Behrens's insight:
by Marc Weber and Javier Buceta
A wide range of bacteria species are known to communicate through the so called quorum sensing (QS) mechanism by means of which they produce a small molecule that can freely diffuse in the environment and in the cells. Upon reaching a threshold concentration, the signalling molecule activates the QS-controlled genes that promote phenotypic changes. This mechanism, for its simplicity, has become the model system for studying the emergence of a global response in prokaryotic cells. Yet, how cells precisely measure the signal concentration and act coordinately, despite the presence of fluctuations that unavoidably affects cell regulation and signalling, remains unclear. ResultsWe propose a model for the QS signalling mechanism in Vibrio fischeri based on the synthetic strains lux01 and lux02. Our approach takes into account the key regulatory interactions between LuxR and LuxI, the autoinducer transport, the cellular growth and the division dynamics. By using both deterministic and stochastic models, we analyze the response and dynamics at the single-cell level and compare them to the global response at the population level. Our results show how fluctuations interfere with the synchronization of the cell activation and lead to a bimodal phenotypic distribution. In this context, we introduce the concept of precision in order to characterize the reliability of the QS communication process in the colony. We show that increasing the noise in the expression of LuxR helps cells to get activated at lower autoinducer concentrations but, at the same time, slows down the global response. The precision of the QS switch under non-stationary conditions decreases with noise, while at steady-state it is independent of the noise value. ConclusionsOur in silico experiments show that the response of the LuxR/LuxI system depends on the interplay between non-stationary and stochastic effects and that the burst size of the transcription/translation noise at the level of LuxR controls the phenotypic variability of the population. These results, together with recent experimental evidences on LuxR regulation in wild-type species, suggest that bacteria have evolved mechanisms to regulate the intensity of those fluctuations......"
Zhong Jin, Wei Sun, Yonggang Ke, Chih-Jen Shih, Geraldine L.C. Paulus,Qing Hua Wang, Bin Mu, Peng Yin & Michael S. StranoAffiliationsContributions
"The vision for graphene and other two-dimensional electronics is the direct production of nanoelectronic circuits and barrier materials from a single precursor sheet. DNA origami and single-stranded tiles are powerful methods to encode complex shapes within a DNA sequence, but their translation to patterning other nanomaterials has been limited. Here we develop a metallized DNA nanolithography that allows transfer of spatial information to pattern two-dimensional nanomaterials capable of plasma etching. Width, orientation and curvature can be programmed by specific sequence design and transferred, as we demonstrate for graphene. Spatial resolution is limited by distortion of the DNA template upon Au metallization and subsequent etching. The metallized DNA mask allows for plasmonic enhanced Raman spectroscopy of the underlying graphene, providing information on defects, doping and lattice symmetry. This DNA nanolithography enables wafer-scale patterning of two-dimensional electronic materials to create diverse circuit elements, including nanorings, three- and four-membered nanojunctions, and extended nanoribbons."
"DNA’s unique structure is ideal for carrying genetic information, but scientists have recently found ways to exploit this versatile molecule for other purposes: By controlling DNA sequences, they can manipulate the molecule to form many different nanoscale shapes.
Chemical and molecular engineers at MIT and Harvard University have now expanded this approach by using folded DNA to control the nanostructure of inorganic materials. After building DNA nanostructures of various shapes, they used the molecules as templates to create nanoscale patterns on sheets of graphene. This could be an important step toward large-scale production of electronic chips made of graphene, a one-atom-thick sheet of carbon with unique electronic properties.“This gives us a chemical tool to program shapes and patterns at the nanometer scale, forming electronic circuits, for example,” says Michael Strano, a professor of chemical engineering at MIT and a senior author of a paper describing the technique in the April 9 issue of Nature Communications ("Metallized DNA nanolithography for encoding and transferring spatial information for graphene patterning")."
Fulco I, Largo RD, Miot S, Wixmerten A, Martin I, Schaefer DJ, Haug MD.
"Since the late 1960s, surgeons and scientists envisioned use of tissue engineering to provide an alternative treatment for tissue and organ damage by combining biological and synthetic components in such a way that a long-lasting repair was established. In addition to the treatment, the patient would also benefit from reduced donor site morbidity and operation time as compared with the standard procedures. Tremendous efforts in basic research have been done since the late 1960s to better understand chondrocyte biology and cartilage maturation and to fulfill the growing need for tissue-engineered cartilage in reconstructive, trauma, and orthopedic surgery. Starting from the first successful generation of engineered cartilaginous tissue, scientists strived to improve the properties of the cartilaginous constructs by characterizing different cell sources, modifying the environmental factors influencing cell expansion and differentiation and applying physical stimuli to modulate the mechanical properties of the construct. All these efforts have finally led to a clinical phase I trial to show the safety and feasibility of using tissue-engineered cartilage in reconstructive facial surgery. However, to bring tissue engineering into routine clinical applications and commercialize tissue-engineered grafts, further research is necessary to achieve a cost-effective, standardized, safe, and regulatory compliant process"
A giant in the field of genomics, Dr. Venter will share his insights on the promise and possibilities of synthetic biology.
The annual A. Richard Newton Lecture, sponsored by the UC Ber...
Gerd Moe-Behrens's insight:
*J. Craig Venter speaks April 16, Synthetic Biology Institute, UC Berkeley*
"A. Richard Newton Memorial Lecture in Synthetic Biology, the signature annual event of the UC Berkeley Synthetic Biology Institute, this year featuring J. Craig Venter as our guest speaker. The lecture will take place on Tuesday, April 16, from 4 - 5 p.m. in Sibley Auditorium, Bechtel Engineering Center, UC Berkeley."
"Accurate and controllable regulatory elements such as promoters and ribosome binding sites (RBSs) are indispensable tools to quantitatively regulate gene expression for rational pathway engineering. Therefore, de novo designing regulatory elements is brought back to the forefront of synthetic biology research. Here we developed a quantitative design method for regulatory elements based on strength prediction using artificial neural network (ANN). One hundred mutated Trc promoter & RBS sequences, which were finely characterized with a strength distribution from 0 to 3.559 (relative to the strength of the original sequence which was defined as 1), were used for model training and test. A precise strength prediction model, NET90_19_576, was finally constructed with high regression correlation coefficients of 0.98 for both model training and test. Sixteen artificial elements were in silico designed using this model. All of them were proved to have good consistency between the measured strength and our desired strength. The functional reliability of the designed elements was validated in two different genetic contexts. The designed parts were successfully utilized to improve the expression of BmK1 peptide toxin and fine-tune deoxy-xylulose phosphate pathway in Escherichia coli. Our results demonstrate that the methodology based on ANN model can de novo and quantitatively design regulatory elements with desired strengths, which are of great importance for synthetic biology applications."
"Jay Keasling wants to build an even better mosquito trap. As French drug maker Sanofi ramps up production of semisynthetic artemisinin — initially developed in Keasling’s University of California, Berkeley, lab — Keasling and others are moving forward with a new nonprofit to explore how to cheaply get synthetic biology-created antimalarial drugs to the world's neediest populations. “The idea is to get the drug out to everyone who needs it,” said Keasling, who I interviewed for this week's print edition story on the synthetic biology process used to invent a potentially cheaper and steadier source of the antimalarial drug artemisinin."
"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."
by Reynoso CM, Miller MA, Bina JE, Gallivan JP, Weiss DS.
"The study of many important intracellular bacterial pathogens requires an understanding of how specific virulence factors contribute to pathogenesis during the infection of host cells. This requires tools to dissect gene function, but unfortunately, there is a lack of such tools for research on many difficult-to-study, or understudied, intracellular pathogens. Riboswitches are RNA-based genetic control elements that directly modulate gene expression upon ligand binding. Here we report the application of theophylline-sensitive synthetic riboswitches to induce protein expression in the intracellular pathogen Francisella. We show that this system can be used to activate the bacterial expression of the reporter β-galactosidase during growth in rich medium. Furthermore, we applied this system to control the expression of green fluorescent protein during intracellular infection by the addition of theophylline directly to infected macrophages. Importantly, we could control the expression of a novel endogenous protein required for growth under nutrient-limiting conditions and replication in macrophages, FTN_0818. Riboswitch-mediated control of FTN_0818 rescued the growth of an FTN_0818 mutant in minimal medium and during macrophage infection. This is the first demonstration of the use of a synthetic riboswitch to control an endogenous gene required for a virulence trait in an intracellular bacterium. Since this system can be adapted to diverse bacteria, the ability to use riboswitches to regulate intracellular bacterial gene expression will likely facilitate the in-depth study of the virulence mechanisms of numerous difficult-to-study intracellular pathogens such as Ehrlichia chaffeensis, Anaplasma phagocytophilum, and Orientia tsutsugamushi, as well as future emerging pathogens. IMPORTANCE: Determining how specific bacterial genes contribute to virulence during the infection of host cells is critical to understanding how pathogens cause disease. This can be especially challenging with many difficult-to-study intracellular pathogens. Riboswitches are RNA-based genetic control elements that can be used to help dissect gene function, especially since they can be used in a broad range of bacteria. We demonstrate the utility of riboswitches, and for the first time show that riboswitches can be used to functionally control a bacterial gene that is critical to the ability of a pathogen to cause disease, during intracellular infection. Since this system can be adapted to diverse bacteria, riboswitches will likely facilitate the in-depth study of the virulence mechanisms of numerous difficult-to-study intracellular pathogens, as well as future emerging pathogens."
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