EGNAS: an exhaustive DNA sequence design algorithm

DNA nanostructure decoration: a how-to tutorial

DNA Nanotechnology is being applied to multiple research fields. The functionality of DNA nanostructures is significantly enhanced by decorating them with nanoscale moieties including: proteins, metallic nanoparticles, quantum dots, and chromophores. Decoration is a complex process and developing protocols for reliable attachment routinely requires extensive trial and error. Additionally, the granular nature of scientific communication makes it difficult to discern general principles in DNA nanostructure decoration. This tutorial is a guidebook designed to minimize experimental bottlenecks and avoid dead-ends for those wishing to decorate DNA nanostructures. We supplement the reference material on available technical tools and procedures with a conceptual framework required to make efficient and effective decisions in the lab. Together these resources should aid both the novice and the expert to develop and execute a rapid, reliable decoration protocols.

Generation of DNA oligomers with similar chemical kinetics via in-silico optimization

Networks of interacting DNA oligomers are useful for applications such as biomarker detection, targeted drug delivery, information storage, and photonic information processing. However, differences in the chemical kinetics of hybridization reactions, referred to as kinetic dispersion, can be problematic for some applications. Here, it is found that limiting unnecessary stretches of Watson-Crick base pairing, referred to as unnecessary duplexes, can yield exceptionally low kinetic dispersions. Hybridization kinetics can be affected by unnecessary intra-oligomer duplexes containing only 2 base-pairs, and such duplexes explain up to 94% of previously reported kinetic dispersion. As a general design rule, it is recommended that unnecessary intra-oligomer duplexes larger than 2 base-pairs and unnecessary inter-oligomer duplexes larger than 7 base-pairs be avoided. Unnecessary duplexes typically scale exponentially with network size, and nearly all networks contain unnecessary duplexes substantial enough to affect hybridization kinetics. A new method for generating networks which utilizes in-silico optimization to mitigate unnecessary duplexes is proposed and demonstrated to reduce in-vitro kinetic dispersions as much as 96%. The limitations of the new design rule and generation method are evaluated in-silico by creating new oligomers for several designs, including three previously programmed reactions and one previously engineered structure.

An optical aptasensor for real-time quantification of endotoxin: From ensemble to single-molecule resolution

Endotoxin is a deadly pyrogen, rendering it crucial to monitor with high accuracy and efficiency. However, current endotoxin detection relies on multistep processes that are labor-intensive, time-consuming, and unsustainable. Here, we report an aptamer-based biosensor for the real-time optical detection of endotoxin. The endotoxin sensor exploits the distance-dependent scattering of gold nanoparticles (AuNPs) coupled to a gold nanofilm. This is enabled by the conformational changes of an endotoxin-specific aptamer upon target binding. The sensor can be used in an ensemble mode and single-particle mode under dark-field illumination. In the ensemble mode, the sensor is coupled with a microspectrometer and exhibits high specificity, reliability (i.e., linear concentration to signal profile in logarithmic scale), and reusability for repeated endotoxin measurements. Individual endotoxins can be detected by monitoring the color of single AuNPs via a color camera, achieving single-molecule resolution. This platform can potentially advance endotoxin detection to safeguard medical, food, and pharmaceutical products.

Extracellular Vesicle Antibody Microarray for Multiplexed Inner and Outer Protein Analysis

Proteins are found both outside and inside of extracellular vesicles (EVs) and govern the properties and functions of EVs, while also constituting a signature of the cell of origin and of biological function and disease. Outer proteins on EVs can be directly bound by antibodies to either enrich EVs, or probe the expression of a protein on EVs, including in a combinatorial manner. However, co-profiling of inner proteins remains challenging. Here, we present the high-throughput, multiplexed analysis of EV inner and outer proteins (EVPio). We describe the optimization of fixation and heat-induced protein epitope retrieval for EVs, along with oligo-barcoded antibodies and branched DNA signal amplification for sensitive, multiplexed, and high-throughput assays. We captured four subpopulations of EVs from colorectal cancer (CRC) cell lines HT29 and SW403 based on EpCAM, CD9, CD63, and CD81 expression, and quantified the co-expression of eight outer [integrins (ITGs) and tetraspanins] and four inner (heat shock, endosomal, and inner leaflet) proteins. The differences in co-expression patterns were consistent with the literature and known biological function. In conclusion, EVPio analysis can simultaneously detect multiple inner and outer proteins in EVs immobilized on a surface, opening the way to extensive combinatorial protein profiles for both discovery and clinical translation.

Using ultraviolet absorption spectroscopy to study nanoswitches based on non-canonical DNA structures

Non-canonical forms of DNA are attracting increasing interest for applications in nanotechnology. It is frequently convenient to characterize DNA molecules using a label-free approach such as ultraviolet absorption spectroscopy. In this paper we present the results of our investigation into the use of this technique to probe the folding of quadruplex and triplex nanoswitches. We confirmed that four G-quartets were necessary for folding at sub-mM concentrations of potassium and found that the wrong choice of sequence for the linker between G-tracts could dramatically disrupt folding, presumably due to the presence of kinetic traps in the folding landscape. In the case of the triplex nanoswitch we examined, we found that the UV spectrum showed a small change in absorbance when a triplex was formed. We anticipate that our results will be of interest to researchers seeking to design DNA nanoswitches based on quadruplexes and triplexes.

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Ultraviolet absorption spectroscopy can probe non-canonical DNA structures.

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Absorbance at 295 nm tends to increase as G-quadruplexes form.

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Four G-quartets are needed to form a quadruplex with less than 1 mM potassium.

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Formation of DNA triplexes can also yield a small change in UV spectra.

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UV absorption is a cheap label-free method for studying DNA nanoswitches.

A Single Transcript Knockdown-Replacement Strategy Employing 5' UTR Secondary Structures to Precisely Titrate Rescue Protein Translation

One overarching goal of gene therapy is the replacement of faulty genes with functional ones. A significant hurdle is presented by the fact that under- or over-expression of a protein may cause disease as readily as coding mutations. There is a clear and present need for pipelines to translate experimentally validated gene therapy strategies to clinical application. To address this we developed a modular, single-transgene expression system for replacing target genes with physiologically expressed variants. In order to accomplish this, we first designed a range of 5' UTR "attenuator" sequences which predictably diminish translation of the paired gene. These sequences provide wide general utility by allowing control over translation from high expression, ubiquitous promoters. Importantly, we demonstrate that this permits an entirely novel knockdown and rescue application by pairing microRNA-adapted shRNAs alongside their respective replacement gene on a single transcript. A noteworthy candidate for this corrective approach is the degenerative and uniformly fatal motor neuron disease ALS. A strong proportion of non-idiopathic ALS cases are caused by varied mutations to the SOD1 gene, and as clinical trials to treat ALS are being initiated, it is important to consider that loss-of-function mechanisms contribute to its pathology as strongly as any other factor. As a generalized approach to treat monogenic diseases caused by heterogeneous mutations, we demonstrate complete and predictable control over replacement of SOD1 in stable cell lines by varying the strength of attenuators.

Dodecin as carrier protein for immunizations and bioengineering applications

In bioengineering, scaffold proteins have been increasingly used to recruit molecules to parts of a cell, or to enhance the efficacy of biosynthetic or signalling pathways. For example, scaffolds can be used to make weak or non-immunogenic small molecules immunogenic by attaching them to the scaffold, in this role called carrier. Here, we present the dodecin from Mycobacterium tuberculosis (mtDod) as a new scaffold protein. MtDod is a homododecameric complex of spherical shape, high stability and robust assembly, which allows the attachment of cargo at its surface. We show that mtDod, either directly loaded with cargo or equipped with domains for non-covalent and covalent loading of cargo, can be produced recombinantly in high quantity and quality in Escherichia coli. Fusions of mtDod with proteins of up to four times the size of mtDod, e.g. with monomeric superfolder green fluorescent protein creating a 437 kDa large dodecamer, were successfully purified, showing mtDod's ability to function as recruitment hub. Further, mtDod equipped with SYNZIP and SpyCatcher domains for post-translational recruitment of cargo was prepared of which the mtDod/SpyCatcher system proved to be particularly useful. In a case study, we finally show that mtDod-peptide fusions allow producing antibodies against human heat shock proteins and the C-terminus of heat shock cognate 70 interacting protein (CHIP).

Enzymatic Weight Update Algorithm for DNA-Based Molecular Learning

Recent research in DNA nanotechnology has demonstrated that biological substrates can be used for computing at a molecular level. However, in vitro demonstrations of DNA computations use preprogrammed, rule-based methods which lack the adaptability that may be essential in developing molecular systems that function in dynamic environments. Here, we introduce an in vitro molecular algorithm that ‘learns’ molecular models from training data, opening the possibility of ‘machine learning’ in wet molecular systems. Our algorithm enables enzymatic weight update by targeting internal loop structures in DNA and ensemble learning, based on the hypernetwork model. This novel approach allows massively parallel processing of DNA with enzymes for specific structural selection for learning in an iterative manner. We also introduce an intuitive method of DNA data construction to dramatically reduce the number of unique DNA sequences needed to cover the large search space of feature sets. By combining molecular computing and machine learning the proposed algorithm makes a step closer to developing molecular computing technologies for future access to more intelligent molecular systems.

Plasmonic Biosensor Based on Vertical Arrays of Gold Nanoantennas

Implementing large arrays of gold nanowires as functional elements of a plasmonic biosensor is an important task for future medical diagnostic applications. Here we present a microfluidic-channel-integrated sensor for the label-free detection of biomolecules, relying on localized surface plasmon resonances. Large arrays (∼1 cm²) of vertically aligned and densely packed gold nanorods to receive, locally confine, and amplify the external optical signal are used to allow for reliable biosensing. We accomplish this by monitoring the change of the optical nanostructure resonance in the presence of biomolecules within the tight focus area above the nanoantennas, combined with a surface treatment of the nanowires for a specific binding of the target molecules. As a first application, we detect the binding kinetics of two distinct DNA strands as well as the following hybridization of two complementary strands (cDNA) with different lengths (25 and 100 bp). Upon immobilization, a redshift of 1 nm was detected; further backfilling and hybridization led to a peak shift of additional 2 and 5 nm for 25 and 100 bp, respectively. We believe that this work gives deeper insight into the functional understanding and technical implementation of a large array of gold nanowires for future medical applications.

In vitro molecular machine learning algorithm via symmetric internal loops of DNA

Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular machine learning, has yet to be experimentally verified. Here, we present a novel molecular learning in vitro model in which symmetric internal loops of double-stranded DNA are exploited to measure the differences between training instances, thus enabling the molecules to learn from small errors. The model was evaluated on a data set of twenty dialogue sentences obtained from the television shows Friends and Prison Break. The wet DNA-computing experiments confirmed that the molecular learning machine was able to generalize the dialogue patterns of each show and successfully identify the show from which the sentences originated. The molecular machine learning model described here opens the way for solving machine learning problems in computer science and biology using in vitro molecular computing with the data encoded in DNA molecules.

GENESUS: a two-step sequence design program for DNA nanostructure self-assembly

DNA has been recognized as an ideal material for bottom-up construction of nanometer scale structures by self-assembly. The generation of sequences optimized for unique self-assembly (GENESUS) program reported here is a straightforward method for generating sets of strand sequences optimized for self-assembly of arbitrarily designed DNA nanostructures by a generate-candidates-and-choose-the-best strategy. A scalable procedure to prepare single-stranded DNA having arbitrary sequences is also presented. Strands for the assembly of various structures were designed and successfully constructed, validating both the program and the procedure.