Harnessing DNA computing and nanopore decoding for practical applications: from informatics to microRNA-targeting diagnostics.

DNA computing represents a subfield of molecular computing with the potential to become a significant area of next-generation computation due to the high programmability inherent in the sequence-dependent molecular behaviour of DNA. Recent studies in DNA computing have extended from mathematical informatics to biomedical applications, with a particular focus on diagnostics that exploit the biocompatibility of DNA molecules. The output of DNA computing devices is encoded in nucleic acid molecules, which must then be decoded into human-recognizable signals for practical applications.

Silicon chambers for enhanced incubation and imaging of microfluidic droplets.

Droplet microfluidics has become a powerful tool in life sciences, underlying digital assays, single-cell sequencing or directed evolution, and it is making foray in physical sciences as well. Imaging and incubation of droplets are crucial, yet they are encumbered by the poor optical, thermal and mechanical properties of PDMS, a material commonly used in microfluidics labs. Here we show that Si is an ideal material for droplet chambers.

Molecular Computation for Molecular Classification.

DNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal-processing capabilities. Whether influenced by the silicon world or inspired by natural computation, molecular programming has gained attention for diagnosis applications. Of particular interest for this review, molecular classifiers have shown promising results for disease pattern recognition and sample classification.

Accelerating the Finite-Element Method for Reaction-Diffusion Simulations on GPUs with CUDA.

DNA nanotechnology offers a fine control over biochemistry by programming chemical reactions in DNA templates. Coupled to microfluidics, it has enabled DNA-based reaction-diffusion microsystems with advanced spatio-temporal dynamics such as traveling waves. The Finite Element Method (FEM) is a standard tool to simulate the physics of such systems where boundary conditions play a crucial role.

Massively parallel and multiparameter titration of biochemical assays with droplet microfluidics.

Biochemical systems in which multiple components take part in a given reaction are of increasing interest. Because the interactions between these different components are complex and difficult to predict from basic reaction kinetics, it is important to test for the effect of variations in the concentration for each reagent in a combinatorial manner. For example, in PCR, an increase in the concentration of primers initially increases template amplification, but large amounts of primers result in primer-dimer by-products that inhibit the amplification of the template.

High-throughput and long-term observation of compartmentalized biochemical oscillators.

We report the splitting of an oscillating DNA circuit into ∼700 droplets with picoliter volumes. Upon incubation at constant temperature, the droplets display sustained oscillations that can be observed for more than a day. Superimposed to the bulk behaviour, we find two intriguing new phenomena - slow desynchronization between the compartments and kinematic spatial waves - and investigate their possible origin.

Scaling down DNA circuits with competitive neural networks.

DNA has proved to be an exquisite substrate to compute at the molecular scale. However, nonlinear computations (such as amplification, comparison or restoration of signals) remain costly in term of strands and are prone to leak. Kim et al.

In vitro regulatory models for systems biology.

The reductionist approach has revolutionized biology in the past 50 years. Yet its limits are being felt as the complexity of cellular interactions is gradually revealed by high-throughput technology. In order to make sense of the deluge of "omic data", a hypothesis-driven view is needed to understand how biomolecular interactions shape cellular networks.

Computing with competition in biochemical networks.

Cells rely on limited resources such as enzymes or transcription factors to process signals and make decisions. However, independent cellular pathways often compete for a common molecular resource. Competition is difficult to analyze because of its nonlinear global nature, and its role remains unclear.

A microfluidic device for on-chip agarose microbead generation with ultralow reagent consumption.

Water-in-oil microdroplets offer microreactors for compartmentalized biochemical reactions with high throughput. Recently, the combination with a sol-gel switch ability, using agarose-in-oil microdroplets, has increased the range of possible applications, allowing for example the capture of amplicons in the gel phase for the preservation of monoclonality during a PCR reaction. Here, we report a new method for generating such agarose-in-oil microdroplets on a microfluidic device, with minimized inlet dead volume, on-chip cooling, and in situ monitoring of biochemical reactions within the gelified microbeads.

Reversible logic circuits made of DNA.

We report reversible logic circuits made of DNA. The circuits are based on an AND gate that is designed to be thermodynamically and kinetically reversible and to respond nonlinearly to the concentrations of its input molecules. The circuits continuously recompute their outputs, allowing them to respond to changing inputs.

Remote toehold: a mechanism for flexible control of DNA hybridization kinetics.

Hybridization of DNA strands can be used to build molecular devices, and control of the kinetics of DNA hybridization is a crucial element in the design and construction of functional and autonomous devices. Toehold-mediated strand displacement has proved to be a powerful mechanism that allows programmable control of DNA hybridization. So far, attempts to control hybridization kinetics have mainly focused on the length and binding strength of toehold sequences.