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Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.
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Engineering and modification of microbial chassis for systems and synthetic biology

Engineering and modification of microbial chassis for systems and synthetic biology | SynBioFromLeukipposInstitute | Scoop.it
Engineering and modifying synthetic microbial chassis is one of the best ways not only to unravel the fundamental principles of life but also to enhance applications in the health, medicine, agricultural, veterinary, and food industries. The two primary strategies for constructing a microbial chassis are the top-down approach (genome reduction) and the bottom-up approach (genome synthesis). Research programs on this topic have been funded in several countries. The ‘Minimum genome factory’ (MGF) project was launched in 2001 in Japan with the goal of constructing microorganisms with smaller genomes for industrial use. One of the best examples of the results of this project is E. coli MGF-01, which has a reduced-genome size and exhibits better growth and higher threonine production characteristics than the parental strain [1]. The ‘cell factory’ project was carried out from 1998 to 2002 in the Fifth Framework Program of the EU (European Union), which tried to comprehensively understand microorganisms used in the application field. One of the outstanding results of this project was the elucidation of proteins secreted by Bacillus subtilis, which was summarized as the ‘secretome’ [2]. The GTL (Genomes to Life) program began in 2002 in the United States. In this program, researchers aimed to create artificial cells both in silico and in vitro, such as the successful design and synthesis of a minimal bacterial genome by John Craig Venter's group [3]. This review provides an update on recent advances in engineering, modification and application of synthetic microbial chassis, with particular emphasis on the value of learning about chassis as a way to better understand life and improve applications.
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New Technologies To Enhance In Vivo Reprogramming for Regenerative Medicine

Cellular identity and state are determined by a collection of molecular components that are specified during development and stabilized thereafter to maintain and protect tissue functions. Alteration of the molecular elements (gene expression program and chromatin state) as a result of disease or age can induce somatic cells to assume different identities or modulate functions. Therapeutic use of this technique, called 'cellular reprogramming', is very promising for regenerative medicine, but implementation of reprogramming-based strategies in vivo has been precluded by technological and safety limitations. Recent advances in transcriptional control and improved transmembrane delivery strategies now offer exciting potential to more efficiently reprogram cell fates as well as to control the reprogramming timeline and scale of delivery to improve safety.
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A Logic Programming Language for Computational Nucleic Acid Devices

Computational nucleic acid devices show great potential for enabling a broad range of biotechnology applications, including smart probes for molecular biology research, in vitro assembly of complex compounds, high-precision in vitro disease diagnosis and, ultimately, computational theranostics inside living cells. This diversity of applications is supported by a range of implementation strategies, including nucleic acid strand displacement, localization to substrates, and the use of enzymes with polymerase, nickase, and exonuclease functionality. However, existing computational design tools are unable to account for these strategies in a unified manner. This paper presents a logic programming language that allows a broad range of computational nucleic acid systems to be designed and analyzed. The language extends standard logic programming with a novel equational theory to express nucleic acid molecular motifs. It automatically identifies matching motifs present in the full system, in order to apply a specified transformation expressed as a logical rule. The language supports the definition of logic predicates, which provide constraints that need to be satisfied in order for a given rule to be applied. The language is sufficiently expressive to encode the semantics of nucleic strand displacement systems with complex topologies, together with computation performed by a broad range of enzymes, and is readily extensible to new implementation strategies. Our approach lays the foundation for a unifying framework for the design of computational nucleic acid devices.
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Functionally diverse type V CRISPR-Cas systems

Functionally diverse type V CRISPR-Cas systems | SynBioFromLeukipposInstitute | Scoop.it
Type V CRISPR-Cas systems are distinguished by a single RNA-guided RuvC domain-containing effector, Cas12. Although effectors of subtypes V-A (Cas12a) and V-B (Cas12b) have been studied in detail, the distinct domain architectures and diverged RuvC sequences of uncharacterized Cas12 proteins suggest unexplored functional diversity. Here, we identify and characterize Cas12c, g, h, and i. Cas12c, h, and i demonstrate RNA-guided double-stranded (ds) DNA interference activity. Cas12i exhibits markedly different efficiencies of crRNA spacer complementary and non-complementary strand cleavage resulting in predominant dsDNA nicking. Cas12g is an RNA-guided RNase with collateral RNase and single-stranded DNase activities. Our study reveals the functional diversity emerging along different routes of type V CRISPR-Cas evolution and expands the CRISPR toolbox.
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Programmable and printable Bacillus subtilis biofilms as engineered living materials

Nat Chem Biol. 2018 Dec 3. doi: 10.1038/s41589-018-0169-2.[Epub ahead of print]...
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Synthetic biology approaches in immunology\

Breakthroughs in gene synthesis has allowed synthetic biologists the ability to design any DNA sequence of interest, enabling the possibility to create complex systems inside cells with novel functions to tackle problems in immunology. Synthetic immunology of mammalian cells expressing natural or synthetic genes can guide and induce immune responses in patients. Through recent developments in engineering chimeric receptors, it is now feasible to customize control over engineered cells to target the disease sites with specificity. These cells can avoid immune rejection if derived from expandable cell types (e.g. stem cells or T cells) and then can be grown in abundance before implantation. However, safety concerns of engineered cells in circulation necessitates the development of a wide range of mechanisms to kill cells after their therapeutic life ends. This therapeutic effect is still predominantly the secretion of therapeutic proteins but novel therapeutic interventions have been explored by synthetic biologists. In the pursuit of engineering new cell functions for synthetic immunology, it is possible that many problems previously thought intractable may actually be possible.
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Programming Bacteria With Light-Sensors and Applications in Synthetic Biology

Photo-receptors are widely present in both prokaryotic and eukaryotic cells, which serves as the foundation of tuning cell behaviors with light. While practices in eukaryotic cells have been relatively established, trials in bacterial cells have only been emerging in the past few years. A number of light sensors have been engineered in bacteria cells and most of them fall into the categories of two-component and one-component systems. Such a sensor toolbox has enabled practices in controlling synthetic circuits at the level of transcription and protein activity which is a major topic in synthetic biology, according to the central dogma. Additionally, engineered light sensors and practices of tuning synthetic circuits have served as a foundation for achieving light based real-time feedback control. Here, we review programming bacteria cells with light, introducing engineered light sensors in bacteria and their applications, including tuning synthetic circuits and achieving feedback controls over microbial cell culture.
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Bio-inspired pneumatic shape-morphing elastomers

Bio-inspired pneumatic shape-morphing elastomers | SynBioFromLeukipposInstitute | Scoop.it
Shape-morphing structures are at the core of future applications in aeronautics1, minimally invasive surgery2, tissue engineering3 and smart materials4. However, current engineering technologies, based on inhomogeneous actuation across the thickness of slender structures, are intrinsically limited to one-directional bending5. Here, we describe a strategy where mesostructured elastomer plates undergo fast, controllable and complex shape transformations under applied pressure. Similar to pioneering techniques based on soft hydrogel swelling6,7,8,9,10, these pneumatic shape-morphing elastomers, termed here as ‘baromorphs’, are inspired by the morphogenesis of biological structures11,12,13,14,15. Geometric restrictions are overcome by controlling precisely the local growth rate and direction through a specific network of airways embedded inside the rubber plate. We show how arbitrary three-dimensional shapes can be programmed using an analytic theoretical model, propose a direct geometric solution to the inverse problem, and illustrate the versatility of the technique with a collection of configurations.
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Analysis of a genetic-metabolic oscillator with piecewise linear models

Interactions between gene regulatory networks and metabolism generate a diversity of dynamics, including multistability and oscillatory behavior. Here, we characterize a regulatory mechanism that drives the emergence of periodic oscillations in metabolic networks subject to genetic feedback regulation by pathway intermediates. We employ a qualitative formalism based on piecewise linear models to systematically analyze the behavior of gene-regulated metabolic pathways. For a pathway with two metabolites and three enzymes, we prove the existence of two co-existing oscillatory behaviors: damped oscillations towards a fixed point or sustained oscillations along a periodic orbit. We show that this mechanism closely resembles the "metabolator", a genetic-metabolic circuit engineered to produce autonomous oscillations in vivo.
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Nucleus Synthetic Biology: Cell Press

We use cookies to help provide and enhance our service and tailor content and ads. By continuing you agree to the use of cookies. Copyright © 2018 Elsevier Inc. except certain content provided by third parties
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Programmed DNA destruction by miniature CRISPR-Cas14 enzymes

CRISPR-Cas9 systems have been causing a revolution in biology. Harrington et al. describe the discovery and technological implementation of an additional type of CRISPR system based on an extracompact effector protein, Cas14. Metagenomics data, particularly from uncultivated samples, uncovered the CRISPR-Cas14 systems containing all the components necessary for adaptive immunity in prokaryotes. At half the size of class 2 CRISPR effectors, Cas14 appears to target single-stranded DNA without class 2 sequence restrictions. By leveraging this activity, a fast and high-fidelity nucleic acid detection system enabled detection of single-nucleotide polymorphisms.
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A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference 

A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference  | SynBioFromLeukipposInstitute | Scoop.it
A central strategy of synthetic biology is to understand the basic processes of living creatures through engineering organisms using the same building blocks. Biological machines described in terms of parts can be studied by computer simulation in any of several languages or robotically assembled in vitro. In this paper we present a language, the Genetic Circuit Description Language (GCDL) and a compiler, the Genetic Circuit Compiler (GCC). This language describes genetic circuits at a level of granularity appropriate both for automated assembly in the laboratory and deriving simulation code. The GCDL follows Semantic Web practice and the compiler makes novel use of the logical inference facilities that are therefore available. We present the GCDL and compiler structure as a study of a tool for generating κ-language simulations from semantic descriptions of genetic circuits.
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Computing with biological switches and clocks

Computing with biological switches and clocks | SynBioFromLeukipposInstitute | Scoop.it
The complex dynamics of biological systems is primarily driven by molecular interactions that underpin the regulatory networks of cells. These networks typically contain positive and negative feedback loops, which are responsible for switch-like and oscillatory dynamics, respectively. Many computing systems rely on switches and clocks as computational modules. While the combination of such modules in biological systems leads to a variety of dynamical behaviours, it is also driving development of new computing algorithms. Here we present a historical perspective on computation by biological systems, with a focus on switches and clocks, and discuss parallels between biology and computing. We also outline our vision for the future of biological computing.
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Engineering Epigenetic Regulation Using Synthetic Read-Write Modules

Engineering Epigenetic Regulation Using Synthetic Read-Write Modules | SynBioFromLeukipposInstitute | Scoop.it
Chemical modifications to DNA and histone proteins are involved in epigenetic programs underlying cellular differentiation and development. Regulatory networks involving molecular writers and readers of chromatin marks are thought to control these programs. Guided by this common principle, we established an orthogonal epigenetic regulatory system in mammalian cells using N6-methyladenine (m6A), a DNA modification not commonly found in metazoan epigenomes. Our system utilizes synthetic factors that write and read m6A and consequently recruit transcriptional regulators to control reporter loci. Inspired by models of chromatin spreading and epigenetic inheritance, we used our system and mathematical models to construct regulatory circuits that induce m6A-dependent transcriptional states, promote their spatial propagation, and maintain epigenetic memory of the states. These minimal circuits were able to program epigenetic functions de novo, conceptually validating “read-write” architectures. This work provides a toolkit for investigating models of epigenetic regulation and encoding additional layers of epigenetic information in cells.
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Droplet based synthetic biology: chemotaxis and interface with biology Unitn-eprints.PhD - University of Trento

Life-like behaviors such as fission, fusion and movement can be artificially re-created exploiting highly simplified protocell systems. This thesis is mainly focused on chemotaxis protocell systems and their integration with biological systems in order to show potential future applications. 1-Decanol droplets, formed in an aqueous medium containing decanoate at high pH, become chemotactic when a chemical gradient is placed in the external aqueous environment. We investigated the behavior of these droplets, their ability to transport and deposit living and non-living objects and to interface them with biofilms. To make the artificial system compatible with natural living systems we developed a partially hydrophobic alginate capsule as a protective unit that can be precisely embedded in a droplet, transported along chemical gradients and deposited. We developed a system that was able to transport: Escherichia coli, Bacillus subtilis and Saccharomyces cerevisiae. Both bacteria survived the transport. However, yeast survived but not in a consistent and repeatable way. Next, we evolved the system to transport human cell lines. We found that A549 cells survive encapsulation but not the transport. A549 cells are in fact very sensitive to toxic 1-decanol. We however found out that this cell line secretes compounds able to decrease the surface tension and to increase the capsule-droplet affinity. Finally we discuss future solutions for the effective transport of human cells.
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The automatic-design tools that are changing synthetic biology

The automatic-design tools that are changing synthetic biology | SynBioFromLeukipposInstitute | Scoop.it
Your smartphone and laptop are made of electronic circuits. Genetic circuits, modelled on the electronic ones, are human-designed combinations of genetic components that interact to produce one or more proteins or RNA molecules, for example, in response to a given stimulus, such as a toxin. Under the right conditions, the circuit might be triggered to make “protein A, which then interacts with protein B to give outcome C”, says David Riglar, a synthetic biologist at Harvard Medical School in Boston, Massachusetts. But until a decade or so ago, these two kinds of circuits were made in very different ways.

Electronics engineers design circuits using automated computer-aided design (CAD) tools. Genetic engineers, by contrast, have had to design biological circuits manually, and one at a time — a laborious, iterative and error-prone process. Computerized genetic-design tools are changing that. They automate the process by which researchers design complex genetic circuits that can program cells — especially bacteria and yeast — to carry out specific actions, such as activating a particular enzyme or churning out a certain protein. Synthetic biologists have used single-celled organisms in this way to produce drugs, biological sensors that include cells or antibodies, enzymes for use in industry, and more.

“Design tools for genetic circuits should greatly expand the accessibility of the kinds of genetic manipulations typically considered to be ‘synthetic biology’,” says Elizabeth Strychalski, a microbial engineer at the US National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland. Her group uses the genetic-design tools Cello and j5 to develop “living measurement systems”, she says: cells that can act as sensors and respond to their environment. “Those genetically engineered organisms then become tools in their own right, allowing anyone new ways to understand and control biology at the cellular scale.”

According to Douglas Densmore, who heads the Cross-Disciplinary Integration of Design Automation Research lab at Boston University, such tools represent a fundamental shift in how genetic circuits are designed. Previously, he explains, genetic-circuit design was mostly a bespoke process. As a result, designs were difficult to share, improve and scale up. “It is not realistic to build an industry on artisanal approaches,” he says. Although these “are great for early-stage research”, they ultimately can’t be transferred to a large scale. That’s where automation comes in. “Automation will begin the process of getting designs out of notebooks and into software,” he says.

A growing collection of circuit-design tools suggests that the field agrees. Yet software development for synthetic biology is in flux. One tool, Genetic Constructor, was abruptly terminated by its parent company, CAD software developer Autodesk Research in San Rafael, California, in August. But researchers working in single-celled organisms still have access to some open-source or freely available tools, including Cello, j5 and another called iBioSim. They can use these tools to weave circuits into whole genomes or to design thousands of variants to examine different combinations of genes, enzymes or protein domains.

“CAD tools are absolutely required for the design of biological systems,” says Andrew Hessel, a genomic futurist and chief executive of Humane Genomic in San Francisco, California.

Genetic CAD
Densmore, who developed Cello, has a background in electronic design automation — and it shows. Researchers can direct Cello to design a genetic circuit that meets certain specifications without having to tell the software anything about how to actually build it, just like with electronic-design tools. Users instruct the software — available both as source code and as a web application — using Verilog, the same computer language that electronics engineers use to describe their silicon circuits. “You specify the function you want, not the way it is created,” Densmore explains. For instance, users could ask Cello to design a genetic circuit that produces a protein when it senses the presence of two particular antibodies. The software would then work out which components must be put together to make that happen, and output the nucleic-acid sequences required to physically build it. Cello also predicts how well its circuits are likely to perform.

Densmore designed Cello in collaboration with the lab of synthetic biologist Christopher Voigt at the Massachusetts Institute of Technology in Cambridge, for use in the bacterium Escherichia coli. Now, they are jointly expanding the tool to work in yeast, he says. Densmore and Voigt are using Cello to design circuits that produce a small signalling molecule in response to the presence of two other molecules, and are working on circuits with memory that function in different ways depending on the order in which they sense the targets, says Densmore.

Unlike Cello, other automated tools including iBioSim, j5 and GenoCAD do not spit out predictions for how well genetic circuits will perform or whether they’re correct. And they all require the user to know and input information about how the circuit will be structured.

A genetic grammar
GenoCAD, which is commercial but has an open-source version, provides rules that define which functional parts of DNA sequences can go together, treating the sequences like programming code. “DNA sequences have the same linguistic complexity as programming languages — there are rules that people need to respect,” explains Jean Peccoud, founder and chief executive of GenoFAB in San Francisco, which developed the software as the foundation for a broader set of genetic-design tools and services. “It’s a grammar. All those rules are formal representations of biological knowledge.” And from them, the software can translate a circuit design into the sequence for a physical piece of DNA, from which the circuit can be built. (Cello is built on a similar set of rules: a language called Eugene, which Densmore developed.)

Created by the Joint BioEnergy Institute in Emeryville, California, and licensed exclusively to in San Francisco, j5 allows researchers to design genetic circuits by dragging and dropping genetic control elements onto a canvas. “You lay down a series of symbols that say, ‘I want a promoter here, I want a ribosome binding site,’” says Densmore. Users can select multiple components that they might want to test in a particular location, for instance to work out which combination produces the most robust output. “Then you use rules to say, ‘Don’t put part A with part B, but part C has to be after part D’, and then it enumerates all the different combinations,” says Densmore. Researchers at non-profit universities and institutes can use the software through a free account; the firm also offers commercial accounts.

No special skills are required to use automated DNA-design tools, but because they do call for detailed specification of elements, familiarity with computer programming helps. “I don’t think the learning curve is too steep right now, even in the more sophisticated tools,” says Hessel. “None of these tools are so sophisticated that they couldn’t be learned in a few days.” The hard part, Hessel says, is building and testing the resulting circuits. Peccoud says he can teach even molecular biologists who have no computer-science background to use GenoCAD in just a few hours.

For those who need help, the greater synthetic-biology community is probably the best place to start. “Researchers in this field are generally accessible and helpful,” says , a microbial engineer who works with Strychalski at NIST. “I would encourage someone just starting to reach out for advice and take full advantage of the considerable online resources” such as the GitHub code repository, he says.

One unfilled niche involves tools that are accessible for non-experts, but powerful and scalable enough to handle millions of base pairs of DNA and many designs. Before it shut down in August — along with Autodesk’s entire life-sciences team — Genetic Constructor did just that. The closure “was an internal strategic decision”, says Eli Groban, a computational biologist who led project management and strategy for the Autodesk life-sciences group When the company announced by e-mail that Genetic Constructor was ending, Groban says, it got replies from individual research groups asking them to keep it going. The tool’s user interface was designed to be more accessible to the wider community of biologists than are tools aimed just at synthetic biologists, he says. “The gaps that Genetic Constructor wanted to fix still apply.”

The use of genetic circuit-design tools is increasing among synthetic biologists, says Strychalski, albeit slowly. Groban says that the problem is one of economics. “In the academic community, there’s this hesitation to pay for software. No one really does that cost–benefit analysis” that it might be cheaper to spend even tens of thousands of dollars on paid software than to get graduate students to spend significant amounts of time building their own version, or designing circuits in the old-fashioned way.

Right now, “most biologists don’t work at scale”, says Hessel, but that could be changing. He tells students that in their careers, they will operate on a vastly larger scale than their current lab work, managing liquid-handling robots and testing much bigger data sets of genetic variants. Automated genetic-design tools might well be required to make that happen.
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The dynamical interplay between a megadalton peptide nanocage and solutes probed by microsecond atomistic MD; implications for design

Understanding the assembly and dynamics of protein-based supramolecular capsids and cages is of fundamental importance and could lead to applications in synthetic biology and biotechnology.Here we present long and large atomistic molecular dynamics simulations of de novo designed self-assembling ...
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Ethics aside, does the CRISPR baby experiment make scientific sense?

Ethics aside, does the CRISPR baby experiment make scientific sense? | SynBioFromLeukipposInstitute | Scoop.it
Before the news broke Sunday that Chinese researcher He Jiankui had used the genome-editing technology CRISPR to create genetically altered twins, he was little known in scientific circles. But the controversial experiment to make humans potentially resistant to HIV also thrust another player into the limelight: CCR5, an immune system molecule that He attempted to cripple. Here’s the scientific logic behind that choice—and the concerns.

What is CCR5?
CCR5 studs the surface of white blood cells, where it acts as a receptor for chemokines. These chemical messengers boss around different populations of immune cells. HIV, which selectively targets white blood cells, uses CCR5 to latch onto them and breach their membranes. Researchers discovered more than 20 years ago that a mutant version of the CCR5 gene, which is missing 32 DNA base pairs, prevents HIV from infecting these cells and thus confers resistance infection. It’s this mutant—known as CCR5-δ32—that interests He.

What did He do with CRISPR?
He’s team used in vitro fertilization to make embryos and then applied CRISPR to those embryos in an attempt to turn the normal CCR5 gene into a mutant that resembles the δ32 version. As an informed consent form for volunteers who participated in this trial explains, He viewed this as a genetic form of vaccination. “The main objective of this project is to produce infants who have the ability to immunize against HIV-1 virus.” the form states.

Who naturally has the mutation?
Nearly 10% of people in Europe and the United States have inherited CCR5-δ32 genes from at least one parent. Most of these people also have one normal variant, however, and remain just as susceptible to the AIDS virus as everyone else. But the 1% who inherit the mutation from both parents—so-called homozygotes—are highly resistant: Studies show that if they’re exposed to HIV, they’re 100 times less likely to become infected. (There are rare cases where they have become infected by HIV variants that favor a different chemokine receptor.) Timothy Ray Brown, an HIV-infected man who received a bone marrow transplant in 2007 from a donor who was homozygous for CCR5-δ32, became the only person ever cured of an HIV infection. The case added further evidence that the crippled receptors provide a strong defense against the virus.

What are the risks of using CRISPR to mutate CCR5 in human embryos?
CRISPR can make unintended, “off-target” edits in the genome, which theoretically could lead to cancers and other health problems.

How well did CRISPR work in He’s experiment?
There is no published paper to examine, but He says one of the implanted embryos was homozygous for the disrupted CCR5. The other only had one of the two genes altered. Only the homozygous baby would potentially become resistant to HIV. He presented evidence today that neither baby had off-target mutations, but researchers still remain skeptical that his analysis was sufficiently thorough.

Is it possible that CRISPR led to mutations that didn’t cripple CCR5?
Yes. Mutated genes sometimes still produce functional proteins. As of yet, He has not shown any data that the mutated CCR5 in the babies are crippled, but he said he plans to take blood samples from the infants to try and infect their cells with HIV.

Do people who are homozygous for CCR5-δ32 suffer any related health problems?
Potentially. For a decade, it seemed as though the mutation caused no harm. But researchers showed in 2005 that West Nile virus is highly fatal in mice engineered to be homozygous for the mutation. Epidemiological studies of West Nile disease subsequently found that humans homozygous for the CCR5 mutation suffer more serious disease and higher rates of death from that virus. It’s now clear that the unmutated gene regulates the trafficking of white blood cells to brains infected with the West Nile virus. It thus likely plays a role in fighting other infections by similar mechanisms.

How could crippling CCR5 with CRISPR help slow the HIV/AIDS epidemic?
He contends that his experiment meets an “unmet medical need,” a key ethical principle for conducting CRISPR experiments on human embryos that might lead to heritable changes. He bases this on the fact that new infection rates of HIV remain high in many countries; babies who are exposed to but uninfected by the virus (from their mothers in utero, during birth, or through breastfeeding) may still have health problems; and many infected people face discrimination. But this rationale has left many HIV/AIDS researchers scratching their heads. Even if CRISPR can safely cripple CCR5 in embryos, it would require a massive IVF campaign followed by the birth of an unfathomably large number of genetically altered babies to have an impact on the epidemic.

Are there other potential benefits to crippling CCR5?
The Medical Ethics Approval Application Form posted on He’s website asserts that CCR5-δ32 mutations might make people “significantly resistant” to smallpox and cholera. But the scientific support for this is scant.
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A primer on deep learning in genomics

A primer on deep learning in genomics | SynBioFromLeukipposInstitute | Scoop.it
Deep learning methods are a class of machine learning techniques capable of identifying highly complex patterns in large datasets. Here, we provide a perspective and primer on deep learning applications for genome analysis. We discuss successful applications in the fields of regulatory genomics, variant calling and pathogenicity scores. We include general guidance for how to effectively use deep learning methods as well as a practical guide to tools and resources. This primer is accompanied by an interactive online tutorial.
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Artificial cells gain communication skills

Researchers have created artificial cells that may be the most eukaryotelike cell mimics yet developed. Like the real things, they can exchange protein signals and have an interactive nucleus that responds to other cells. The membrane of the synthetic cells is porous polymerized acrylate, and their gel nucleus contains DNA. When researchers add ribosomes and other necessary materials, the synthetic cells begin to produce fluorescent proteins and send these signals to their neighbors. Researchers demonstrated that these cell mimics can also communicate by using other proteins and show a collective response called quorum sensing, in which cells' behavior changes depending on their density.
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Selection of Protein-Protein Interactions of Desired Affinities with a Bandpass Circuit

We have developed a genetic circuit in Escherichia coli that can be used to select for protein-protein interactions of different strengths by changing antibiotic concentrations in the media. The genetic circuit links protein-protein interaction strength to β-lactamase activity, while simultaneously imposing tuneable positive and negative selection pressure for β-lactamase activity. Cells only survive if they express interacting proteins with affinities that fall within set high- and low-pass thresholds, i.e. the circuit acts as a bandpass filter for protein-protein interactions. We show that the circuit can be used to recover protein-protein interactions of desired affinity from a mixed population with a range of affinities. The circuit can also be used to select for inhibitors of protein-protein interactions of defined strength.
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Biologists create the most lifelike artificial cells yet

Biologists create the most lifelike artificial cells yet | SynBioFromLeukipposInstitute | Scoop.it
Cell mimics make and pass on proteins that influence their neighbors...
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Models for Cell-free Synthetic Biology: Make Prototyping Easier, Better and Faster

Cell-free TX-TL is an increasingly mature and useful platform for prototyping, testing and engineering biological parts and systems. However, to fully accomplish the promises of synthetic biology, mathematical models are required to facilitate the design and predict the behaviour of biological components in cell-free extracts. We review here the latest models accounting for transcription, translation, competition and depletion of resources as well as genome scale models for lysate-based cell-free TX-TL systems, including their current limitations. These models will have to find ways to account for batch-to-batch variability before being quantitatively predictive in cell-free lysate-based platforms.
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A biomimetic receptor for glucose

A biomimetic receptor for glucose | SynBioFromLeukipposInstitute | Scoop.it
Specific molecular recognition is routine for biology, but has proved difficult to achieve in synthetic systems. Carbohydrate substrates are especially challenging, because of their diversity and similarity to water, the biological solvent. Here we report a synthetic receptor for glucose, which is biomimetic in both design and capabilities. The core structure is simple and symmetrical, yet provides a cavity which almost perfectly complements the all-equatorial β-pyranoside substrate. The receptor’s affinity for glucose, at Ka ~ 18,000 M−1, compares well with natural receptor systems. Selectivities also reach biological levels. Most other saccharides are bound approximately 100 times more weakly, while non-carbohydrate substrates are ignored. Glucose-binding molecules are required for initiatives in diabetes treatment, such as continuous glucose monitoring and glucose-responsive insulin. The performance and tunability of this system augur well for such applications.
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