Biology subjects

Matthies, M.

Publications and source records attributed to Matthies, M..

5 recordsLinked to original sources

bioRxiv2024

Single-Molecule Force Spectroscopy of Toehold-Mediated Strand Displacement

Toehold-mediated strand displacement (TMSD) is extensively utilized in dynamic DNA nanotechnology and is the foundation for a wide range of DNA or RNA-based reaction circuits. Previous studies have typically relied on bulk fluorescence measurements to investigate the kinetics of TMSD, which only provide effective, bulk-averaged reaction rates and do not resolve the process on the level of individual molecules or even base pairs. In this work, we addressed this limitation by exploring the dynamics of strand displacement processes at the single-molecule level using single-molecule force spectroscopy (SMFS) with an optical trap supported by state-of-the-art coarse-grained simulations. By probing the ends of the hairpin of a toehold structure, we can trigger and observe TMSD in real time with microsecond and nanometer resolution. Using a microfluidic assay where we expose the hairpin to a solution of trigger strands, we find that under load, TMSD proceeds very rapidly, with single step times of 1 s. Introducing mismatches into the invader sequence allows us to tune stability such that invasion and re-invasion occur in equilibrium, even under load. This allows us to study thousands of invasion/re-invasion events on a single molecule and analyze the kinetics of the invasion process. Extrapolating our findings to zero load, we find single step times for DNA invading DNA four times faster than for RNA invading RNA. Moreover, we used force to study the kinetics of DNA invading RNA, a process that in the absence of force would rarely occur. Our results reveal the importance of sequence effects for the TMSD process and have importance for a wide range of applications in nucleic acid nanotechnology and synthetic biology.

biophysics↗

bioRxiv2023

High-speed 3D DNA-PAINT and unsupervised clustering for unlocking 3D DNA origami cryptography

DNA origami information storage is a promising alternative to silicon-based data storage, offering a secure molecular cryptography technique that conceals information within arbitrarily folded DNA origami nanostructures. Routing, sliding, and interlacing staple strands lead to the creation of a large 700-bit key size. The realization of practical DNA data storage requires high information density, robust security, and accurate and rapid information retrieval. To meet these requirements, advanced readout techniques and large encryption key sizes are essential. In this study, we report an enhanced DNA origami cryptography protocol to encrypt information in 2D and 3D DNA origami structures, increasing the number of possible scaffold routings and increasing the encryption key size. We employed all-DNA-based steganography with fast readout through high-speed 2D and 3D DNA-PAINT super-resolution imaging, which enables higher information density. By combining 2D and 3D DNA-PAINT data with unsupervised clustering, we achieved an accuracy of up to 89% and high ratios of correct-to-wrong readout, despite the significant flexibility in the 3D DNA origami structure shown by oxDNA simulation. Furthermore, we propose design criteria that ensure complete information retrieval for the DNA origami cryptography protocol. Our findings demonstrate that DNA-based cryptography is a highly secure and versatile solution for transmitting and storing information, making it an attractive choice for the post-silicon era.

biophysics↗

bioRxiv2023

Differentiable Partition Function Calculation for RNA

AO_SCPLOWBSTRACTC_SCPLOWRibonucleic acid (RNA) is an essential molecule in a wide range of biological functions. In 1990, McCaskill introduced a dynamic programming algorithm for computing the partition function of an RNA sequence. This forward model is widely used for understanding the thermodynamic properties of a given RNA. In this work, we introduce a generalization of McCaskills algorithm that is well-defined over continuous inputs and is differentiable. This allows us to tackle the inverse folding problem--designing a sequence with desired equilibrium thermodynamic properties--directly using gradient optimization. This has applications to creating RNA-based drugs such as mRNA vaccines. Furthermore, it allows McCaskills foundational algorithm to be incorporated into machine learning pipelines directly since we have made it end-to-end differentiable. This work highlights how principles from differentiable programming can be translated to existing physical models to develop powerful tools for machine learning. We provide a concrete example by implementing an effective and interpretable RNA design algorithm.

bioinformatics↗

bioRxiv2020

Design, optimization, and analysis of large DNA and RNA nanostructures through interactive visualization, editing, and molecular simulation

This work seeks to remedy two deficiencies in the current nucleic acid nanotechnology software environment: the lack of both a fast and user-friendly visualization tool and a standard for common structural analyses of simulated systems. We introduce here oxView, a web browser-based visualizer that can load structures with over 1 million nucleotides, create videos from simulation trajectories, and allow users to perform basic edits to DNA and RNA designs. We additionally introduce open-source software tools for extracting common structural parameters to characterize large DNA/RNA nanostructures simulated using the coarse-grained modeling tool, oxDNA, which has grown in popularity in recent years and is frequently used to prototype new nucleic acid nanostructural designs, model biophysics of DNA/RNA processes, and rationalize experimental results. The newly introduced software tools facilitate the computational characterization of DNA/RNA designs by providing multiple analysis scripts, including mean structures and structure flexibility characterization, hydrogen bond fraying, and interduplex angles. The output of these tools can be loaded into oxView, allowing users to interact with the simulated structure in a 3D graphical environment and modify the structures to achieve the required properties. We demonstrate these newly developed tools by applying them to in silico design, optimization and analysis of a range of DNA and RNA nanostructures.

biophysics↗

bioRxiv2018

DNA-Encircled Lipid Bilayers

Lipid bilayers and lipid-associated proteins play a crucial role in biology. As in vivo studies and manipulation are inherently difficult, several membrane-mimetic systems have been developed to enable investigation of lipidic phases, lipid-protein interactions, membrane protein function and membrane structure in vitro. Controlling the size and shape, or site-specific functionalization is, however, difficult to achieve with established membrane mimetics based on membrane scaffolding proteins, polymers or peptides. In this work, we describe a route to leverage the unique programmability of DNA nanotechnology and create DNA-encircled bilayers (DEBs), which are made of multiple copies of an alkylated oligonucleotide hybridized to a single-stranded minicircle. To stabilize the hydrophobic rim of the lipid bilayer, and to prevent formation of lipid vesicles, we introduced up to 2 alkyl chains per helical that point to the inside of the toroidal DNA ring and interact with the hydrophobic side chains of the encapsulated lipid bilayer. The DEB approach described herein provides unprecedented control of size, and allows the orthogonal functionalizations and arrangement of engineered membrane nanoparticles and will become a valuable tool for biophysical investigation of lipid phases and lipid-associated proteins and complexes including structure determination of membrane proteins and pharmacological screenings of membrane proteins.

biophysics↗