In this study, robust biological filters with an external control to match a desired input/output (I/O) filtering response are engineered based on the well-characterized promoter-RBS libraries and a cascade gene circuit topology. In the field of synthetic biology, the biological filter system serves as a powerful detector or sensor to sense different molecular signals and produces a specific output response only if the concentration of the input molecular signal is higher or lower than a specified threshold. The proposed systematic design method of robust biological filters is summarized into three steps. Firstly, several well-characterized promoter-RBS libraries are established for biological filter design by identifying and collecting the quantitative and qualitative characteristics of their promoter-RBS components via nonlinear parameter estimation method. Then, the topology of synthetic biological filter is decomposed into three cascade gene regulatory modules, and an appropriate promoter-RBS library is selected for each module to achieve the desired I/O specification of a biological filter. Finally, based on the proposed systematic method, a robust externally tunable biological filter is engineered by searching the promoter-RBS component libraries and a control inducer concentration library to achieve the optimal reference match for the specified I/O filtering response.
In Synthetic Biology, biomolecular networks are designed and constructed to perform specified tasks. Design strategies for these networks tend to center on tuning the parameters of mathematical models to achieve a specified behavior, and implementing these parameters experimentally. This design strategy often assumes a fixed network structure that defines the possible behaviors, which may be too restrictive for our purposes. This paper investigates the extent to which the state space of a synthetic network can also be designed and shaped by parametric tuning. We exploit timescale separation to implement new, nonlinear, tunable conservation relations that hold for all times beyond a fast transient. We demonstrate an application of this design strategy by flexibly constraining the possible behaviors of a gene regulatory network through the design of fast protein interactions.
In April 2015, a paper by Chinese scientists about their attempts to edit the DNA of a human embryo rocked the scientific world and set off a furious debate. Leading scientists warned that altering the human germ line without studying the consequences could have horrific consequences. Geneticists with good intentions could mistakenly engineer changes in DNA that generate dangerous mutations and cause painful deaths. Scientists — and countries — with less noble intentions could again try to build a race of superhumans.
Human DNA is, however, merely one of many commercial targets of ethical concern. The DNA of every single organism — every plant, every animal, every bacterium — is now fair game for genetic manipulation. We are entering an age of backyard synthetic biology that should worry everybody. And it is coming about because of CRISPRs: clustered regularly interspaced short palindromic repeats.
Dr. J. Craig Venter discusses what the near future holds for the world of synthetic biology and our understanding of the human genome. Subscribe to The World ...
Organic electronics has many advantages: it is inexpensive, flexible and lightweight. In terms of applications, we are only limited by our imaginations. There has been a lot of development in polymers since the phenomenon of conducting and semi-conducting plastics was discovered and in 2000 awarded a Nobel Prize. Their weakness is still speed; plastics conduct a charge slowly, compared to silicon, for instance.
A polymer consists of long chains of hydrocarbon, where other elements are bound, which give the particular plastic its properties. Research is underway, and researchers and developers in the chemical industry have developed new polymers that conduct better.
“The charge is transported two to three times faster in the latest generation polymers,” explains Dr Simone Fabiano, researcher at the Laboratory of Organic Electronics, Linköping University, Campus Norrköping. He is the lead author of the article being published in theProceedings of the National Academy of Sciences, PNAS.
Until now people have tried to get the polymer chains to lie as well ordered as possible. The idea is that it should be easy for the charge to jump between the chains if they are organised in rows. Dr Fabiano compares the polymer chains to spaghetti, that you try to line up next to each other, instead of all tangled up, like when it has been tipped from a pot.
The CRISPR-Cas9 system has been in the limelight mainly as a revolutionary genome engineering tool used to modify specific gene sequences within the vast sea of an organism's DNA. Cas9, a naturally occurring protein in the ...
Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome.
Another step forward has just been taken in the area of synthetic biology. Research teams from Inserm and CNRS (French National Centre for Scientific Research) Montpellier, in association with Montpellier Regional University Hospital and Stanford University, have transformed bacteria into “secret agents” that can give warning of a disease based solely on the presence of characteristic molecules in the urine or blood. To perform this feat, the researchers inserted the equivalent of a computer programme into the DNA of the bacterial cells. The bacteria thus programmed detect the abnormal presence of glucose in the urine of diabetic patients. This work, published in the journalScience Translational Medicine, is the first step in the use of programmable cells for medical diagnosis.
A major challenge in computational biology is to find simple representations of high-dimensional data that best reveal the underlying structure. In this work, we present an intuitive and easy-to-implement method based on ranked neighborhood comparisons that detects structure in unsupervised data. The method is based on ordering objects in terms of similarity and on the mutual overlap of nearest neighbors. This basic framework was originally introduced in the field of social network analysis to detect actor communities. We demonstrate that the same ideas can successfully be applied to biomedical data sets in order to reveal complex underlying structure. The algorithm is very efficient and works on distance data directly without requiring a vectorial embedding of data. Comprehensive experiments demonstrate the validity of this approach. Comparisons with state-of-the-art clustering methods show that the presented method outperforms hierarchical methods as well as density based clustering methods and model-based clustering. A further advantage of the method is that it simultaneously provides a visualization of the data. Especially in biomedical applications, the visualization of data can be used as a first pre-processing step when analyzing real world data sets to get an intuition of the underlying data structure. We apply this model to synthetic data as well as to various biomedical data sets which demonstrate the high quality and usefulness of the inferred structure.
Biomolecular self-assemblies are of great interest to nanotechnologists because of their functional versatility and their biocompatibility1. Over the past decade, sophisticated single-component nanostructures composed exclusively of nucleic acids2, 3, 4, 5, peptides6, 7, 8 and proteins9, 10, 11, 12, 13, 14, 15 have been reported, and these nanostructures have been used in a wide range of applications, from drug delivery16 to molecular computing17. Despite these successes, the development of hybrid co-assemblies of nucleic acids and proteins has remained elusive. Here we use computational protein design to create a protein–DNA co-assembling nanomaterial whose assembly is driven via non-covalent interactions. To achieve this, a homodimerization interface is engineered onto the Drosophila Engrailed homeodomain (ENH), allowing the dimerized protein complex to bind to two double-stranded DNA (dsDNA) molecules. By varying the arrangement of protein-binding sites on the dsDNA, an irregular bulk nanoparticle or a nanowire with single-molecule width can be spontaneously formed by mixing the protein and dsDNA building blocks. We characterize the protein–DNA nanowire using fluorescence microscopy, atomic force microscopy and X-ray crystallography, confirming that the nanowire is formed via the proposed mechanism. This work lays the foundation for the development of new classes of protein–DNA hybrid materials. Further applications can be explored by incorporating DNA origami, DNA aptamers and/or peptide epitopes into the protein–DNA framework presented here.
Stanford scientists produced a common cancer drug – previously only available from an endangered plant – in a common laboratory plant. This work could lead to a more stable supply of the drug and allow scientists to manipulate that drug to make it even safer and more effective. By Amy Adams Many of the drugs we take today to treat pain, fight cancer or thwart disease were originally identified in plants, some of which are endangered or hard to grow. In many cases, those plants are still the primary source of the drug.
Now Elizabeth Sattely, an assistant professor of chemical engineering at Stanford, and her graduate student Warren Lau have isolated the machinery for making a widely used cancer-fighting drug from an endangered plant. They then put that machinery into a common, easily grown laboratory plant, which was able to produce the chemical. The technique could potentially be applied to other plants and drugs, creating a less expensive and more stable source for those drugs.
"People have been grinding up plants to find new chemicals and testing their activity for a really long time," Sattely said. "What was striking to us is that with a lot of the plant natural products currently used as drugs, we have to grow the plant, then isolate the compound, and that's what goes into humans."
In her work, published Sept. 10 in the journal Science, Sattely and her team used a novel technique to identify proteins that work together in a molecular assembly line to produce the cancer drug. Her group then showed that the proteins could produce the compound outside the plant – in this case, they had put the machinery in a different plant, but they hope to eventually produce the drug in yeast. Either the plant or yeast would provide a controlled laboratory environment for producing the drug.
This work could lead to new ways of modifying the natural pathways to produce derivative drugs that are safer or more effective than the natural source.
Genetic circuits and metabolic pathways can be reengineered to allow organisms to process signals and manufacture useful chemicals. However, their functions currently rely on organism-specific regulatory parts, fragmenting synthetic biology and metabolic engineering into host-specific domains. To unify efforts, here we have engineered a cross-species expression resource that enables circuits and pathways to reuse the same genetic parts, while functioning similarly across diverse organisms. Our engineered system combines mixed feedback control loops and cross-species translation signals to autonomously self-regulate expression of an orthogonal polymerase without host-specific promoters, achieving nontoxic and tuneable gene expression in diverse Gram-positive and Gram-negative bacteria. Combining 50 characterized system variants with mechanistic modelling, we show how the cross-species expression resource’s dynamics, capacity and toxicity are controlled by the control loops’ architecture and feedback strengths. We also demonstrate one application of the resource by reusing the same genetic parts to express a biosynthesis pathway in both model and non-model hosts.
A new market report published by Transparency Market Research is Synthetic Biology Market (Synthetic DNA, Synthetic Genes, Synthetic Cells, XNA, Chassis Organisms, DNA Synthesis, Oligonucleotide Synthesis) - Global Industry Analysis, Size, Share, Growth, Trends and Forecast,2013 - 2019
Posted via Industry Today. Are you into it? Follow us on Twitter @IndustryToday
The global synthetic biology market: Increased government participation and investments being routed into scientific research as well as active initiatives taken by private players in R&D.
Besides pharmaceutical and nutrition-related applications, synthetic biology has been used for mitigating the damaging effects of marine pollution. The process has been extensively applied for developing engineered microorganisms to limit oil spill damages. Additionally, researchers have successfully used synthetic biology to convert regular plastics into microplastics that can be re-used. With DNA sequencing prices taking a plunge, the synthetic biology market will gain momentum. However, the global synthetic biology market is still impeded by ethical issues relating to synthetic biology products.
The TMR reports offers a highly detailed study of the global synthetic biology market by classifying it on three fronts: Application, products and technologies.
By application, the synthetic biology market is classified according to sectors such as: Healthcare, chemicals, agriculture and others. Of these, the healthcare segment will demonstrate continued growth thanks to factors such synthetic DNA and genes now being commercially available, which in turn supports the development of affordable pharma products.
The segmentation of the synthetic biology market by product has been done as follows: Core products and enabling products. The core products segment is further segregated as: XNA, synthetic DNA, synthetic cells, synthetic genes, and chassis organisms. The enabling products segment, on the other hand, is further divided into products for oligonucleotide synthesis and those for DNA synthesis. According to 2012 estimates, the core products segment enjoyed a larger share of market revenues as compared to enabling products. Based on the type of technology used in synthetic biology processes, the market is segmented as: Biological components and integrated systems, genome engineering, bioinformatics, and DNA sequencing. Technology for synthetic biology genome engineering is observed to be the most widely used as of 2012, because it can efficiently modify specific areas within the DNA to attain better reproducibility.
With advances in synthetic biology and biofabrication, cellular networks can be functionalized and connected with unprecedented sophistication. We describe a platform for the creation of a 'bioproduction breadboard'. This would consist of physically isolated product-producing cell populations, product capture devices, and other unit operations that function as programmed in place, using unique, orthogonal inputs. For product synthesis, customized cell populations would be connected through standardized, generic inputs allowing 'plug and play' functionality and primary, user-mediated regulation. In addition, through autonomous pathway redirection and balancing, the cells themselves would provide secondary, self-directed regulation to optimize bioproduction. By leveraging specialization and division of labor, we envision diverse cell populations linked to create new pathway designs.
n contrast to the versatility of regulatory mechanisms in natural systems, synthetic genetic circuits have been so far predominantly composed of transcriptionally regulated modules. This is about to change as the repertoire of foundational tools for post-transcriptional regulation is quickly expanding. We provide an overview of the different types of translational regulators: protein, small molecule and ribonucleic acid (RNA) responsive and we describe the new emerging circuit designs utilizing these tools. There are several advantages of achieving multilevel regulation via translational switches and it is likely that such designs will have the greatest and earliest impact in mammalian synthetic biology for regenerative medicine and gene therapy applications.
Year 12 student at Orewa College, whose presentation, Synthetic Biology - Engineering the Future, won her the Secondary category and Premier Award at the 2015 Sir Paul Callaghan EUREKA! Awards.
To get content containing either thought or leadership enter:
To get content containing both thought and leadership enter:
To get content containing the expression thought leadership enter:
You can enter several keywords and you can refine them whenever you want. Our suggestion engine uses more signals but entering a few keywords here will rapidly give you great content to curate.
Your new post is loading...
Scoop.it!
