Mobile DNA最新文献

{"title":"Exploring Material Design Space with a Deep-Learning Guided Genetic Algorithm","authors":"Kuan-Lin Chen, Rebecca Schulman","doi":"10.4230/LIPIcs.DNA.28.4","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.28.4","url":null,"abstract":"Designing complex, dynamic yet multi-functional materials and devices is challenging because the design spaces for these materials have numerous interdependent and often conflicting constraints. Taking inspiration from advances in artificial intelligence and their applications in material discovery, we propose a computational method for designing metamorphic DNA-co-polymerized hydrogel structures. The method consists of a coarse-grained simulation and a deep learning-guided optimization system for exploring the immense design space of these structures. Here, we develop a simple numeric simulation of DNA-co-polymerized hydrogel shape change and seek to find designs for structured hydrogels that can fold into the shapes of different Arabic numerals in different actuation states. We train a convolutional neural network to classify and score the geometric outputs of the coarse-grained simulation to provide autonomous feedback for design optimization. We then construct a genetic algorithm that generates and selects large batches of material designs that compete with one another to evolve and converge on optimal objective-matching designs. We show that we are able to explore the large design space and learn important parameters and traits. We identify vital relationships between the material scale size and the range of shape change that can be achieved by individual domains and we elucidate trade-offs between different design parameters. Finally, we discover material designs capable of transforming into multiple different digits in different actuation states.","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"42 1","pages":"4:1-4:14"},"PeriodicalIF":4.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80896202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling and Optimisation of a DNA Stack Nano-Device Using Probabilistic Model Checking","authors":"Bowen Li, N. Mackenzie, Ben Shirt-Ediss, N. Krasnogor, P. Zuliani","doi":"10.4230/LIPIcs.DNA.28.5","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.28.5","url":null,"abstract":"A DNA stack nano-device is a bio-computing system that can read and write molecular signals based on DNA-DNA hybridisation and strand displacement. In vitro implementation of the DNA stack faces a number of challenges affecting the performance of the system. In this work, we apply probabilistic model checking to analyse and optimise the DNA stack system. We develop a model framework based on continuous-time Markov chains to quantitatively describe the system behaviour. We use the PRISM probabilistic model checker to answer two important questions: 1) What is the minimum required incubation time to store a signal? And 2) How can we maximise the yield of the system? The results suggest that the incubation time can be reduced from 30 minutes to 5-15 minutes depending on the stack operation stage. In addition, the optimised model shows a 40% increase in the target stack yield. project “Synthetic Portabolomics: Leading the way at the crossroads of the Digital and the Bio Economies” (EP/N031962/1). Krasnogor was supported by the Royal Academy of Engineering under the Chairs in Emerging Technologies scheme.","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"9 1","pages":"5:1-5:22"},"PeriodicalIF":4.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87676767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Coupled Reconfiguration Mechanism for Single-Stranded DNA Strand Displacement Systems","authors":"H. Johnson, A. Condon","doi":"10.4230/LIPIcs.DNA.28.3","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.28.3","url":null,"abstract":"DNA Strand Displacement (DSD) systems model basic reaction rules, such as toehold-mediated strand displacement and 4-way branch migration, that modify complexes of bound DNA strands. DSD systems have been widely used to design and reason about the correctness of molecular programs, including implementations of logic circuits, neural networks, and Chemical Reaction Networks. Such implementations employ a valuable toolkit of mechanisms – sequences of basic reaction rules – that achieve catalysis, reduce errors (e.g., due to leak), or simulate simple computational units such as logic gates, both in solution and on surfaces. Expanding the DSD toolkit of DSD mechanisms can lead to new and better ways of programming with DNA. Here we introduce a new mechanism, which we call controlled reconfiguration . We describe one example where two single-stranded DSD complexes interact, changing the bonds in both complexes in a way that would not be possible for each independently on its own via the basic reaction rules allowed by the model. We use coupled reconfiguration to refer to instances of controlled reconfiguration in which two reactants change each other in this way. We note that our DSD model disallows pseudoknots and that properties of our coupled reconfiguration construction rely on this restriction of the model. A key feature of our coupled reconfiguration example, which distinguishes it from mechanisms (such as 3-way strand displacement or 4-way branch migration) that are typically used to implement molecular programs, is that the reactants are single-stranded. Leveraging this feature, we show how to use coupled reconfiguration to implement Chemical Reaction Networks (CRNs), with a DSD system that has both single-stranded signals (which represent the species of the CRN) and single-stranded fuels (which drive the CRN reactions). Our implementation also has other desirable properties; for example it is capable of implementing reversible CRNs and uses just two distinct toeholds. We discuss drawbacks of our implementation, particularly the reliance on pseudoknot-freeness for correctness, and suggest directions for future research that can provide further insight on the capabilities and limitations of controlled reconfiguration. computing (DSD) systems. a particularly well-studied abstract model of well-mixed chemical systems, in which many interesting programs can be and have been written [2, 3, 28, 36, 41]. Moreover, arbitrary CRNs can be transformed into DSD systems that implement the original CRN [7, 10, 30, 37, 39].","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"26 1","pages":"3:1-3:19"},"PeriodicalIF":4.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87141530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast and Robust Strand Displacement Cascades via Systematic Design Strategies","authors":"T. Kennedy, Cadence Pearce, Chris Thachuk","doi":"10.4230/LIPIcs.DNA.28.1","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.28.1","url":null,"abstract":"A barrier to wider adoption of molecular computation is the difficulty of implementing arbitrary chemical reaction networks (CRNs) that are robust and replicate the kinetics of designed behavior. DNA Strand Displacement (DSD) cascades have been a favored technology for this purpose due to their potential to emulate arbitrary CRNs and known principles to tune their reaction rates. Progress on leakless cascades has demonstrated that DSDs can be arbitrarily robust to spurious “leak” reactions when incorporating systematic domain level redundancy. These improvements in robustness result in slower kinetics of designed reactions. Existing work has demonstrated the kinetic and thermodynamic effects of sequence mismatch introduction and elimination during displacement. We present a systematic, sequence modification strategy for optimizing the kinetics of leakless cascades without practical cost to their robustness. An in-depth case study explores the effects of this optimization when applied to a typical leakless translator cascade. Thermodynamic analysis of energy barriers and kinetic experimental data support that DSD cascades can be fast and robust.","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"s3-43 1","pages":"1:1-1:17"},"PeriodicalIF":4.9,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90833952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Migrators within migrators: exploring transposable element dynamics in the monarch butterfly, Danaus plexippus","authors":"Tobias Baril, Alex Hayward","doi":"10.1101/2021.09.28.462135","DOIUrl":"https://doi.org/10.1101/2021.09.28.462135","url":null,"abstract":"Lepidoptera (butterflies and moths) are an important model system in ecology and evolution. A high-quality chromosomal genome assembly is available for the monarch butterfly (Danaus plexippus), but it lacks an in-depth transposable element (TE) annotation, presenting an opportunity to explore monarch TE dynamics and the impact of TEs on shaping the monarch genome. We find 6.21% of the monarch genome is comprised of TEs, a reduction of 6.85% compared to the original TE annotation performed on the draft genome assembly. Monarch TE content is low compared to two closely related species with available genomes, Danaus chrysippus (33.97% TE) and Danaus melanippus (11.87% TE). The biggest TE contributions to genome size in the monarch are LINEs and Penelope-like elements, and three newly identified families, r2-hero_dPle (LINE), penelope-1_dPle (Penelope-like), and hase2-1_dPle (SINE), collectively contribute 34.92% of total TE content. We find evidence of recent TE activity, with two novel Tc1 families rapidly expanding over recent timescales (tc1-1_dPle, tc1-2_dPle). LINE fragments show signatures of genomic deletions indicating a high rate of TE turnover. We investigate associations between TEs and wing colouration and immune genes and identify a three-fold increase in TE content around immune genes compared to other host genes. We provide a detailed TE annotation and analysis for the monarch genome, revealing a considerably smaller TE contribution to genome content compared to two closely related Danaus species with available genome assemblies. We identify highly successful novel DNA TE families rapidly expanding over recent timescales, and ongoing signatures of both TE expansion and removal highlight the dynamic nature of repeat content in the monarch genome. Our findings also suggest that insect immune genes are promising candidates for future interrogation of TE-mediated host adaptation.","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"13 1","pages":""},"PeriodicalIF":4.9,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62334954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unbiased proteomic mapping of the LINE-1 promoter using CRISPR Cas9.","authors":"Erica M Briggs, Paolo Mita, Xiaoji Sun, Susan Ha, Nikita Vasilyev, Zev R Leopold, Evgeny Nudler, Jef D Boeke, Susan K Logan","doi":"10.1186/s13100-021-00249-9","DOIUrl":"10.1186/s13100-021-00249-9","url":null,"abstract":"<p><strong>Background: </strong>The autonomous retroelement Long Interspersed Element-1 (LINE-1) mobilizes though a copy and paste mechanism using an RNA intermediate (retrotransposition). Throughout human evolution, around 500,000 LINE-1 sequences have accumulated in the genome. Most of these sequences belong to ancestral LINE-1 subfamilies, including L1PA2-L1PA7, and can no longer mobilize. Only a small fraction of LINE-1 sequences, approximately 80 to 100 copies belonging to the L1Hs subfamily, are complete and still capable of retrotransposition. While silenced in most cells, many questions remain regarding LINE-1 dysregulation in cancer cells.</p><p><strong>Results: </strong>Here, we optimized CRISPR Cas9 gRNAs to specifically target the regulatory sequence of the L1Hs 5'UTR promoter. We identified three gRNAs that were more specific to L1Hs, with limited binding to older LINE-1 sequences (L1PA2-L1PA7). We also adapted the C-BERST method (dCas9-APEX2 Biotinylation at genomic Elements by Restricted Spatial Tagging) to identify LINE-1 transcriptional regulators in cancer cells. Our LINE-1 C-BERST screen revealed both known and novel LINE-1 transcriptional regulators, including CTCF, YY1 and DUSP1.</p><p><strong>Conclusion: </strong>Our optimization and evaluation of gRNA specificity and application of the C-BERST method creates a tool for studying the regulatory mechanisms of LINE-1 in cancer. Further, we identified the dual specificity protein phosphatase, DUSP1, as a novel regulator of LINE-1 transcription.</p>","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"12 1","pages":"21"},"PeriodicalIF":4.7,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8381588/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9700931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TE Hub: A community-oriented space for sharing and connecting tools, data, resources, and methods for transposable element annotation.","authors":"Tyler A Elliott,&nbsp;Tony Heitkam,&nbsp;Robert Hubley,&nbsp;Hadi Quesneville,&nbsp;Alexander Suh,&nbsp;Travis J Wheeler","doi":"10.1186/s13100-021-00244-0","DOIUrl":"https://doi.org/10.1186/s13100-021-00244-0","url":null,"abstract":"<p><p>Transposable elements (TEs) play powerful and varied evolutionary and functional roles, and are widespread in most eukaryotic genomes. Research into their unique biology has driven the creation of a large collection of databases, software, classification systems, and annotation guidelines. The diversity of available TE-related methods and resources raises compatibility concerns and can be overwhelming to researchers and communicators seeking straightforward guidance or materials. To address these challenges, we have initiated a new resource, TE Hub, that provides a space where members of the TE community can collaborate to document and create resources and methods. The space consists of (1) a website organized with an open wiki framework,  https://tehub.org , (2) a conversation framework via a Twitter account and a Slack channel, and (3) bi-monthly Hub Update video chats on the platform's development. In addition to serving as a centralized repository and communication platform, TE Hub lays the foundation for improved integration, standardization, and effectiveness of diverse tools and protocols. We invite the TE community, both novices and experts in TE identification and analysis, to join us in expanding our community-oriented resource.</p>","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"12 1","pages":"16"},"PeriodicalIF":4.9,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13100-021-00244-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10338325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Machines from Topological Linkages","authors":"Keenan Breik, Austin Luchsinger, D. Soloveichik","doi":"10.4230/LIPIcs.DNA.27.7","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.27.7","url":null,"abstract":"Life is built upon amazingly sophisticated molecular machines whose behavior combines mechanical and chemical action. Engineering of similarly complex nanoscale devices from first principles remains an as yet unrealized goal of bioengineering. In this paper we formalize a simple model of mechanical motion (mechanical linkages) combined with chemical bonding. The model has a natural implementation using DNA with double-stranded rigid links, and single-stranded flexible joints and binding sites. Surprisingly, we show that much of the complex behavior is preserved in an idealized topological model which considers solely the graph connectivity of the linkages. We show a number of artifacts including Boolean logic, catalysts, a fueled motor, and chemo-mechanical coupling, all of which can be understood and reasoned about in the topological model. The variety of achieved behaviors supports the use of topological chemical linkages in understanding and engineering complex molecular behaviors. 2012 ACM Subject Classification Theory of computation → Models of computation; Theory of computation → Computational geometry","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"226 1","pages":"7:1-7:20"},"PeriodicalIF":4.9,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88783620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ENSnano: A 3D Modeling Software for DNA Nanostructures","authors":"N. Lévy, N. Schabanel","doi":"10.4230/LIPIcs.DNA.27.5","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.27.5","url":null,"abstract":"7 Since the 1990s, increasingly complex nanostructures have been reliably obtained out of self-assembled 8 DNA strands: from “simple” 2D shapes to 3D gears and articulated nano-objects, and even computing 9 structures. The success of the assembly of these structures relies on a fine tuning of their structure 10 to match the peculiar geometry of DNA helices. Various softwares have been developed to help 11 the designer. These softwares provide essentially four kind of tools: an abstract representation of 12 DNA helices (e.g. cadnano, scadnano, DNApen, 3DNA, Hex-tiles); a 3D view of the design (e.g., 13 vHelix, Adenita, oxDNAviewer); fully automated design (e.g., BScOR, Daedalus, Perdix, Talos, 14 Athena), generally dedicated to a specific kind of design, such as wireframe origami; and coarse grain 15 or thermodynamical physics simulations (e.g., oxDNA, MrDNA, SNUPI, Nupack, ViennaRNA,...). 16 MagicDNA combines some of these approaches to ease the design of configurable DNA origamis. 17 We present our first step in the direction of conciliating all these different approaches and 18 purposes into one single reliable GUI solution: the first fully usable version (design from scratch to 19 export) of our general purpose 3D DNA nanostructure design software ENSnano . We believe that 20 its intuitive, swift and yet powerful graphical interface, combining 2D and 3D editable views, allows 21 fast and precise editing of DNA nanostructures. It also handles editing of large 2D/3D structures 22 smoothly, and imports from the most common solutions. Our software extends the concept of 23 grids introduced in cadnano . Grids allow to abstract and articulated the different parts of a design. 24 ENSnano also provides new design tools which speeds up considerably the design of complex large 3D 25 structures, most notably: a 2D split view , which allows to edit intricate 3D structures which cannot 26 easily be mapped in a 2D view, and a copy, paste & repeat functionality, which takes advantage 27 of the grids to design swiftly large repetitive chunks of a structure. ENSnano has been validated 28 experimentally, as proven by the AFM images of a DNA origami entirely designed in ENSnano . 29 ENSnano is a light-weight ready-to-run independent single-file app, running seamlessly in most of 30 the operating systems (Windows 10, MacOS 10.13+ and Linux). Precompiled versions for Windows 31 and MacOS are ready to download on ENSnano website. As of writing this paper, our software is 32 being actively developed to extend its capacities in various directions discussed in this article. Still, 33 its 3D and 2D editing interface is already meeting our usability goals. Because of its stability and 34 ease of use, we believe that ENSnano could already be integrated in anyone’s design chain, when 35 precise editing of a larger nanostructure is needed.","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"18 1","pages":"5:1-5:23"},"PeriodicalIF":4.9,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74501231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Digital Molecular Design of Binarized Neural Networks","authors":"Johannes Linder, Yuan-Jyue Chen, David Wong, Georg Seelig, L. Ceze, K. Strauss","doi":"10.4230/LIPIcs.DNA.27.1","DOIUrl":"https://doi.org/10.4230/LIPIcs.DNA.27.1","url":null,"abstract":"Molecular programming – a paradigm wherein molecules are engineered to perform computation – shows great potential for applications in nanotechnology, disease diagnostics and smart therapeutics. A key challenge is to identify systematic approaches for compiling abstract models of computation to molecules. Due to their wide applicability, one of the most useful abstractions to realize is neural networks. In prior work, real-valued weights were achieved by individually controlling the concentrations of the corresponding “weight” molecules. However, large-scale preparation of reactants with precise concentrations quickly becomes intractable. Here, we propose to bypass this fundamental problem using Binarized Neural Networks (BNNs), a model that is highly scalable in a molecular setting due to the small number of distinct weight values. We devise a noise-tolerant digital molecular circuit that compactly implements a majority voting operation on binary-valued inputs to compute the neuron output. The network is also rate-independent, meaning the speed at which individual reactions occur does not affect the computation, further increasing robustness to noise. We first demonstrate our design on the MNIST classification task by simulating the system as idealized chemical reactions. Next, we map the reactions to DNA strand displacement cascades, providing simulation results that demonstrate the practical feasibility of our approach. We perform extensive noise tolerance simulations, showing that digital molecular neurons are notably more robust to noise in the concentrations of chemical reactants compared to their analog counterparts. Finally, we provide initial experimental results of a single binarized neuron. Our work suggests a solid framework for building even more complex neural network computation. 2012 ACM Subject Classification Theory of computation → Models of computation; Applied computing","PeriodicalId":18854,"journal":{"name":"Mobile DNA","volume":"14 1","pages":"1:1-1:20"},"PeriodicalIF":4.9,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81810808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}