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We need to begin a serious debate about whether artificially evolved humans are our future, and if we should put an end to these experiments before it is too late
DNA IS SUPPOSED to rescue us from a computing rut. With advances using silicon petering out, DNA-based computers hold the promise of massive parallel computing architectures that are impossible today.
But there’s a problem: The molecular circuits built so far have no flexibility at all. Today, using DNA to compute is “like having to build a new computer out of new hardware just to run a new piece of software,” says computer scientist David Doty. So Doty, a professor at UC Davis, and his colleagues set out to see what it would take to implement a DNA computer that was in fact reprogrammable.
As detailed in a paper published this week in Nature, Doty and his colleagues from Caltech and Maynooth University demonstrated just that. They showed it’s possible to use a simple trigger to coax the same basic set of DNA molecules into implementing numerous different algorithms. Although this research is still exploratory, reprogrammable molecular algorithms could be used in the future to program DNA robots, which have already successfully delivered drugs to cancerous cells.
“This is one of the landmark papers in the field,” says Thorsten-Lars Schmidt, an assistant professor for experimental biophysics at Kent State University who was not involved in the research. “There was algorithmic self-assembly before, but not to this degree of complexity.”
In electronic computers like the one you’re using to read this article, bits are the binary units of information that tell a computer what to do. They represent the discrete physical state of the underlying hardware, usually the presence or absence of an electrical current. These bits, or rather the electrical signals implementing them, are passed through circuits made up of logic gates, which perform an operation on one or more input bits and produce one bit as an output.
Unnatural gene expression imposes a load on engineered microorganisms that decreases their growth and subsequent production yields, a phenomenon known as burden. In the last decade, the field of synthetic biology has made progress on the development of biomolecular feedback control systems and other approaches that can improve the growth of engineered cells, as well as the genetic stability, portability and robust performance of cell-hosted synthetic constructs. In this review, we highlight recent work focused on the development of host-aware synthetic biology. https://www.sciencedirect.com/science/article/pii/S245231001930006X
Modeling all the chemical reactions that take place in a minimal cell will help us to understand the fundamental interactions that power life.
"In this mini review, we will briefly introduce the rapid development of DNA conformational polymorphism in biosensing field, including canonical DNA duplex, triplex, quadruplex, DNA origami, as well as more functionalized DNAs (aptamer, DNAzyme etc.). Various DNA structuresare adopted to play important roles in sensor construction, through working as recognition receptor, signal reporter or linking staple for signal motifs, etc. We will mainly summarize their recent developments in DNA-based electrochemical and fluorescent sensors. For the electrochemical sensors, several types will be included, e.g. the amperometric, electrochemical impedance, electrochemiluminescence, as well as field-effect transistor sensors. For the fluorescent sensors, DNA is usually modified with fluorescent molecules or novel nanomaterials as report probes, excepting its core recognition function. Finally, general conclusion and future perspectives will be discussed for further developments." https://www.sciencedirect.com/science/article/pii/S0956566319301216?dgcid=raven_sd_via_email
Article | Published: 04 March 2019
DNA-based communication in populations of synthetic protocells
Alex Joesaar, Shuo Yang, Bas Bögels, Ardjan van der Linden, Pascal Pieters, B. V. V. S. Pavan Kumar, Neil Dalchau, Andrew Phillips, Stephen Mann & Tom F. A. de Greef
Nature Nanotechnology (2019) | Download Citation
Abstract
Developing molecular communication platforms based on orthogonal communication channels is a crucial step towards engineering artificial multicellular systems. Here, we present a general and scalable platform entitled ‘biomolecular implementation of protocellular communication’ (BIO-PC) to engineer distributed multichannel molecular communication between populations of non-lipid semipermeable microcapsules. Our method leverages the modularity and scalability of enzyme-free DNA strand-displacement circuits to develop protocellular consortia that can sense, process and respond to DNA-based messages. We engineer a rich variety of biochemical communication devices capable of cascaded amplification, bidirectional communication and distributed computational operations. Encapsulating DNA strand-displacement circuits further allows their use in concentrated serum where non-compartmentalized DNA circuits cannot operate. BIO-PC enables reliable execution of distributed DNA-based molecular programs in biologically relevant environments and opens new directions in DNA computing and minimal cell technology.
DNA and RNA are naturally composed of four nucleotide bases that form hydrogen bonds in order to pair. Hoshika et al. added an additional four synthetic nucleotides to produce an eight-letter genetic code and generate so-called hachimoji DNA. Coupled with an engineered T7 RNA polymerase, this expanded DNA alphabet could be transcribed into RNA. Thus, new forms of DNA that add information density to genetic biopolymers can be generated that may be useful for future synthetic biological applications.
Science , this issue p. [884][1]
We report DNA- and RNA-like systems built from eight nucleotide “letters” (hence the name “hachimoji”) that form four orthogonal pairs. These synthetic systems meet the structural requirements needed to support Darwinian evolution, including a polyelectrolyte backbone, predictable thermodynamic stability, and stereoregular building blocks that fit a Schrödinger aperiodic crystal. Measured thermodynamic parameters predict the stability of hachimoji duplexes, allowing hachimoji DNA to increase the information density of natural terran DNA. Three crystal structures show that the synthetic building blocks do not perturb the aperiodic crystal seen in the DNA double helix. Hachimoji DNA was then transcribed to give hachimoji RNA in the form of a functioning fluorescent hachimoji aptamer. These results expand the scope of molecular structures that might support life, including life throughout the cosmos.
[1]: /lookup/doi/10.1126/science.aat0971
As part of the launch of the journal section "Machine Learning and Artificial Intelligence in Bioinformatics", BMC Bioinformatics is excited to announce that we are now accepting manuscripts for the thematic series Machine learning for computational and systems biology. The purpose of this thematic series is to bring together latest advances in machine learning and artificial intelligence methods in computational and systems biology, including their applications to problems in bioinformatics. We welcome manuscripts describing novel computational techniques to analyse high throughput data such as sequences and gene/protein expressions, as well as machine learning techniques such as graphical models, neural networks or kernel methods. This includes, but is not limited to: Data integration/fusion/multi-view learning Deep learning Kernel methods Multitask/structured output prediction Epigenetics Genome-wide association studies Metabolomic modelling Synthetic biology Please submit directly to BMC Bioinformatics stating in your cover letter that it is for the “Machine learning for computational and systems biology” collection. Alternatively you can email your pre-submission queries to the Editor of BMC Bioinformatics at alison.cuff@biomedcentral.com All manuscripts submitted for inclusion in the series by May 6th 2019 will be considered.
Structural DNA nanotechnology takes DNA, a biopolymer, far beyond being the molecule that stores and transmits genetic information in biological systems. DNA has been employed as building blocks for the assembly of designed, nanoscaled, supramolecular DNA architectures for applications in biophysics, structure determination, synthetic biology, diagnostics, and drug delivery. Herein, we review a symmetric approach of tile-based DNA self-assembly. This approach allows construction of DNA nanostructures from minimal numbers of different types of DNA strands based on sequence and structural symmetries. Some examples of the applications of this approach in siRNA delivery are discussed as well.
Structure-guided protein engineering of Cas12a yields variants that have increased activity and that can edit sites with previously inaccessible PAMs.
Here, the authors provide protocols for CRISPR–Cas9-based genetic manipulation of Candida albicans, using a gene-drive strategy that allows genetic interaction networks to be established for this important fungal pathogen.
AbstractSynthetic biology holds great promise to deliver transformative technologies to the world in the coming years. However, several challenges still remain to be addressed before it can deliver on its promises. One of the most important issues to address is the lack of reproducibility within research of the life sciences. This problem is beginning to be recognised by the community and solutions are being developed to tackle the problem. The recent emergence of automated facilities that are open for use by researchers (such as biofoundries and cloud labs) may be one of the ways that synthetic biologists can improve the quality and reproducibility of their work. In this perspective article, we outline these and some of the other technologies that are currently being developed which we believe may help to transform how synthetic biologists approach their research activities.
CRISPR gene-editing technology co-inventor Jennifer Doudna addressed the opportunities and challenges of editing genomes in a Thursday conversation with political...
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A set of 355 self-assembling DNA ‘tiles’ can be reprogrammed to implement many different computer algorithms—including sorting, palindrome testing and divisibility by three—suggesting that molecular self-assembly could be a reliable algorithmic component in programmable chemical systems.
In biological systems, large-scale behaviour can be achieved by the collective coupling and coordination of stochastically (randomly) moving small-scale components. For example, living cells aggregate and migrate collectively during the healing of wounds and when cancer spreads. Inspired by these biological mechanisms, in a paper in Nature, Li et al.1 report a collective robotic system in which deterministic locomotion is a result of the stochastic movement of many loosely coupled, disc-shaped components. The results show that stochasticity offers a promising approach to developing large-scale, collective robotic systems that exhibit robust deterministic behaviour.
Isoprenoids are an attractive class of metabolites for enzymatic synthesis from renewable substrates. However, metabolic engineering of microorganisms for monoterpenoid production is limited by the need for time-consuming, and often non-intuitive, combinatorial tuning of biosynthetic pathway variations to meet design criteria. Towards alleviating this limitation, the goal of this work was to build a modular, cell-free platform for construction and testing of monoterpenoid pathways, using the fragrance and flavoring molecule limonene as a model. In this platform, multiple Escherichia coli lysates, each enriched with a single overexpressed pathway enzyme, are mixed to construct the full biosynthetic pathway. First, we show the ability to synthesize limonene from six enriched lysates with mevalonate substrate, an adenosine triphosphate (ATP) source, and cofactors. Next, we extend the pathway to use glucose as a substrate, which relies on native metabolism in the extract to convert glucose to acetyl-CoA along with three additional enzymes to convert acetyl-CoA to mevalonate. We find that the native E. coli farnesyl diphosphate synthase (IspA) is active in the lysate and diverts flux from the pathway intermediate geranyl pyrophospahte to farnesyl pyrophsophate and the byproduct farnesol. By adjusting the relative levels of cofactors NAD+, ATP and CoA, the system can synthesize 0.66 mM (90.2 mg l−1) limonene over 24 h, a productivity of 3.8 mg l−1 h−1. Our results highlight the flexibility of crude lysates to sustain complex metabolism and, by activating a glucose-to-limonene pathway with 9 heterologous enzymes encompassing 20 biosynthetic steps, expands an approach of using enzyme-enriched lysates for constructing, characterizing and prototyping enzymatic pathways.
"Control theory, a branch of engineering devoted to the analysis and design of robust systems through feedback control, has been instrumental for many technological applications. It has been proposed that control theory is also a productive framework to analyze biological systems and advance their engineering. Examples confirming this perspective include the design of schemes of biomolecular sequestration to implement integral negative feedback for perfect disturbance rejection and the discovery of control theoretic tradeoffs between stability and performance in the glycolytic pathway in Saccharomyces cerevisiae. Here, we briefly review some concepts and tools from classical feedback control theory that have been invoked in the study of biological systems, and argue for the need to develop new control concepts specifically tailored to biology." https://www.sciencedirect.com/science/article/pii/S2452310019300113
Engineered immune-cell-based cancer therapies have demonstrated robust efficacy in B cell malignancies, but challenges such as the lack of ideal targetable tumour antigens, tumour-mediated immunosuppression and severe toxicity still hinder their therapeutic efficacy and broad applicability. Synthetic biology can be used to overcome these challenges and create more robust, effective adaptive therapies that enable the specific targeting of cancer cells while sparing healthy cells. In this Progress article, we review recently developed gene circuit therapies for cancer using immune cells, nucleic acids and bacteria as chassis. We conclude by discussing outstanding challenges and future directions for realizing these gene circuit therapies in the clinic.
Genome-reduced bacteria often show impaired growth under laboratory conditions. Here the authors use adaptive laboratory evolution to optimise growth performance and show transcriptome and translatome-wide remodeling of the organism.
An epidemic of Lassa fever in Nigeria that has killed 69 people this year is on track to be the worst ever recorded anywhere. Now, in the hope of reducing deaths from Lassa in years to come, researchers in Nigeria are trying out a new diagnostic test based on the gene-editing tool CRISPR.
The test relies on CRISPR’s ability to hunt down genetic snippets ― in this case, RNA from the Lassa virus ― that it has been programmed to find. If the approach is successful, it could help to catch a wide range of viral infections early so that treatments can be more effective and health workers can curb the spread of infection.
Scientists in Honduras and California are testing CRISPR diagnostics for dengue viruses, Zika viruses and strains of human papillomavirus (HPV) associated with cancer. And a study to explore a CRISPR test for the Ebola virus is pending in the Democratic Republic of the Congo.
A robust, user-friendly test could reduce the death rates from Lassa fever, which can be as high as 60%, says Jessica Uwanibe, a molecular biologist developing a Lassa diagnostic at Redeemer’s University in Ede, Nigeria. “I’m working on something that could save a lot of lives.”
The advancement of synthetic biology requires the ability to create new DNA sequences to produce unique behaviors in biological systems. Automation is increasingly employed to carry out well-established assembly methods of DNA fragments in a multiplexed, high-throughput fashion, allowing many different configurations to be tested simultaneously. However, metrics are required to determine when automation is warranted based on factors such as assembly methodology, protocol details, and number of samples. The goal of our synthetic biology automation work is to develop and test protocols, hardware, and software to investigate and optimize DNA assembly through quantifiable metrics. We performed a parameter analysis of DNA assembly to develop a standardized, highly efficient, and reproducible MoClo protocol, suitable to be used both manually and with liquid-handling robots. We created a key DNA assembly metric (Q-metric) to characterize a given automation method's advantages over conventional manual manipulations with regard to researchers' highest-priority parameters: output, cost, and time. A software tool called Puppeteer was developed to formally capture these metrics, help define the assembly design, and provide human and robotic liquid-handling instructions. Altogether, we contribute to a growing foundation of standardizing practices, metrics, and protocols for automating DNA assembly.
Self-Assembling RNA Nanoparticle for Gene Expression Regulation in a Model System...
The emerging field of RNA nanotechnology harnesses the versatility of RNA molecules to generate nature-inspired systems with programmable structure and functionality. Such methodology ha
CRISPR–CasX represents a distinct RNA-guided platform that is functionally separate from Cas9 and Cas12a and is active for bacterial and human genome modification.
We present a scheme for implementing a version of task switching in engineered bacteria, based on the manipulation of plasmid copy numbers. Our method allows for the embedding of multiple computations in a cellular population, whilst minimising resource usage inefficiency. We describe the results of computational simulations of our model, and discuss the potential for future work in this area.
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