Biology subjects

Sulc, P.

Publications and source records attributed to Sulc, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Experimental umbrella sampling of a rotary nanomachine

The free-energy landscape of a molecular system, which describes its free energy as a function of a few collective coordinates, governs its dynamics and function, but is challenging to determine experimentally. In molecular simulations, enhanced-sampling methods such as umbrella sampling use bias potentials to access regions of this landscape that are rarely visited by equilibrium fluctuations. Here, we transfer this concept to a single-molecule experiment: we combine electric-field biasing, in situ calibration of the bias potentials, and statistical reweighting to reconstruct the angular free-energy landscapes of rotary DNA nanomachines. The method resolves barriers exceeding 10 kBT and detects changes in local landscape shape caused by small modifications of the stator design. A systematic analysis of bias calibration, sampling, and finite-exposure averaging establishes the conditions required for accurate reconstruction. Experimental umbrella sampling thus relates nanoscale structure to the underlying free-energy landscape and supports the physics-informed design of artificial molecular machinery.

biophysics↗

bioRxiv2026

Engineered mRNA nanostructures expand the design space of mRNA therapeutics through programmable protein expression and immune stimulation

Messenger RNA (mRNA) therapeutics have transformed vaccination and protein replacement strategies, yet efforts to improve their performance have focused largely on sequence engineering, nucleotide modification, and delivery vehicles. Here we show that mRNA function can be controlled by rational design of higher-order RNA architectures. We develop self-assembling mRNA origami (mRNA-OG), a class of unimolecular RNA nanostructures that encode protein-coding sequences within higher-order, programmable, and compact nucleic acid architectures. Using computational design and experimental validation, we demonstrate that mRNA-OG folds into well-defined nanostructures while remaining translationally competent in mammalian cells. Although folded mRNA-OG recruits ribosomes comparably to unfolded constructs, it produces lower protein output, indicating that RNA architecture can directly influence translational efficiency. The compact geometry of mRNA-OG also enhances encapsulation by cationic lipid delivery systems, suggesting a structural route to improved cargo packaging. Beyond its effects on translation, mRNA architecture modulates innate immune recognition. In primary human dendritic cells, folded and unfolded mRNA-OG elicit distinct cytokine programs and differential activation of stress-response pathways, including a modest induction of the integrated stress response that is not fully explained by canonical PKR signaling. Our results establish programmable structure as a new design parameter for mRNA therapeutics that can affect its functionality, delivery properties, and immune sensing.

bioengineering↗

bioRxiv2026

DNA-templated Chiral Metamaterial Array as Information Bits

The growth of digital information demands physically secure information bits that combine intrinsic randomness with multi-layered optical readout. Digital metamaterials with physical unclonable function characteristics are promising, but nearly all examples operate at microwave or terahertz frequencies. Extending digital metamaterials to the visible range requires a physical property that allows binary (0/1) encoding via nanoscale geometry and is orthogonal to intensity-or color-based imaging. Chiral plasmonic metamaterials satisfy these criteria perfectly: their broken mirror symmetry yields chirality polarity in the visible spectrum whose sign and magnitude directly encode bit values ("0", spin-up; "1", spin-down), while remaining invisible under linear polarization. Here, we realize visible-range digital metamaterials by programming self-assembled DNA origami templates with asymmetrically placed gold nanorods to create discrete 3D chiral metamolecules. Using on-surface DNA origami assembly and the Silica Microsphere-Assisted Patterning by Liquid Elimination (SiMPLE) method, we fabricate large-scale bit arrays on optical active glass substrate in solution with [~]1.33 m lattice spacing, [~]86% site occupancy, and [~]12-month stability after silicification. These bottom-up fabricated digital metamaterial array exhibits two independent security layers: (1) a macroscopic spatial pattern only visible by dark-field microscopy, and (2) hidden binary information stored in the single-particle chiroptical response, read out by position-resolved circular dichroism spectroscopy. Quantitative analysis confirms reliable bit encoding and high optical randomness arising from slight structural variations. By leveraging the polarity of plasmonic chirality to translate molecular-scale handedness into robust visible-range digital signals, this work establishes a scalable nanophotonic platform for secure optical information storage, authentication, and encryption.

bioengineering↗

bioRxiv2025

Mismatch-Assisted Toehold Exchange Cascades for Magnetic Nanoparticle-Based Nucleic Acid Diagnostics

Sensitive, simple, and rapid detection of nucleic acid sequences at point-of-care (POC) settings is still an unmet quest. Magnetic readout assays combined with toehold-mediated strand displacement (TMSD)-based circuits are amplification- and wash-free, essential features for contributing to this demand. Nevertheless, nonenzymatic TMSD circuits are slow with low sensitivity for early disease diagnostics. Here, we propose novel mismatch-assisted toehold exchange (MATE) magnetic cascades, wherein magnetic susceptibility increases by dissociation of magnetic nanoparticles (MNPs) from engineered magnetic clusters upon detecting nucleic acid target in solution. The MATE relies on the generation of an allosteric toehold (TH) by spontaneous dissociation to efficiently recycle the target, amplify magnetic signal output, and enhance the assays kinetics. We show that introducing a mismatch in the allosteric TH domain enhances the overall declustering kinetics 7-fold, as also confirmed with oxDNA simulations, with the largest effect gained for the mismatch closest to where the branch migration by the target ends. By integrating MATE into magnetic diagnostics cascades, we demonstrate 3.6-fold better limit-of-detection (LoD) and 12-fold shorter assay time compared to our previous circuit design. Our work makes a major leap towards bringing MNP-based diagnostics much closer to the clinical POC settings by offering a simple, rapid, isothermal, and nonenzymatic assay workflow.

biochemistry↗

bioRxiv2024

Controlling DNA-RNA strand displacement kinetics with base distribution

DNA-RNA hybrid strand displacement underpins the function of many natural and engineered systems. Understanding and controlling factors affecting DNA-RNA strand displacement reactions is necessary to enable control of processes such as CRISPR-Cas9 gene editing. By combining multi-scale modelling with strand displacement experiments we show that the distribution of bases along the displacement domain of an invading strand has a very strong effect on reaction kinetics. Merely by redistributing bases within a displacement domain of fixed base composition, we are able to design sequences whose reaction rates span more than two orders of magnitude. We characterize this effect in reactions involving the invasion of dsDNA by an RNA strand and invasion of a hybrid duplex by a DNA strand. We show that oxNA, a recently introduced coarse-grained model of DNA-RNA hybrids, can reproduce trends in experimentally observed reaction rates. We also develop a kinetic model for predicting strand displacement rates. On the basis of these results, we argue that base distribution effects are likely to play an important role in the function of the guide RNAs that direct CRISPR-Cas systems.

biophysics↗

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-affinity binding to the SARS-CoV-2 spike trimer by a nanostructured, trivalent protein-DNA synthetic antibody

Multivalency enables nanostructures to bind molecular targets with high affinity. Although IgG antibodies can be generated against a wide range of antigens, their shape and size cannot be tuned to match a given target. DNA nanotechnology provides an attractive approach for designing customized multivalent scaffolds due to the addressability and programmability of the nanostructure shape and size. Here, we use computational simulation to guide the design and synthesis of a DNA nanostructure-based synthetic antibody ("nano-synbody"). The nano-synbody is comprised of a three-helix bundle DNA nanostructure with three identical arms terminating in a mini-binder protein that targets the SARS-CoV-2 spike protein. The structure was designed to match the valence and distance between the three receptor binding domains (RBDs) in the spike trimer, in order to enhance binding through avidity effects. Moreover, the design allowed for the display of one, two, or three protein-displaying arms, thereby systematically probing the effect of multivalency on binding affinity. The binding strength of the nano-synbody increased with the increasing number of arms, yielding 11.2 pM affinity ([~]100-fold enhancement over monovalent binding) for the wild-type spike protein for the three-arm structure. Moreover, the multivalency was able to yield a 95 pM affinity for the Omicron variant, a mutant against which the monovalent protein was ineffective. The nano-synbody could also block infection of a spike protein-bearing pseudovirus, and similarly demonstrated effective inhibition of the Omicron variant when trimerized. The structure of the three-arm nano-synbody bound to the Omicron variant spike trimer was solved by negative-stain transmission electron microscopy reconstruction, and shows the protein-DNA nanostructure with all three arms bound to the RBD domains, confirming the intended trivalent attachment. Finally, nano-synbody binding could be reversed by removing one, two, or three arms in a programmable fashion, via toehold-mediated strand displacement. The ability to tune the size and shape of the nano-synbody, as well as its potential ability to attach (and then remove) two or more different binding ligands, will enable the high-affinity binding of a range of proteins, and pave the way towards their manipulation using DNA-based nano-robotic devices.

bioengineering↗

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

DNA Nanostructure-Guided Assembly of Proteins into Programmable Shapes

The development of methods to synthesize protein oligomers with precisely controlled number and configuration of components will enable artificial protein complexes and nanostructures with diverse biological and medical applications. Using DNA hybridization to link protein-DNA conjugates provides for a programmability that can be difficult to achieve with other methods, such as engineering multiple orthogonal protein-protein interfaces. However, it is still difficult to construct well-defined protein assemblies, and the challenge is magnified if only a single type of building block is used. To overcome this hurdle, we use a DNA origami as an "assembler" to guide the linking of protein-DNA conjugates using a series of oligonucleotide hybridization and displacement operations. We constructed several isomeric protein nanostructures on a DNA origami platform by using a C3-symmetric building block comprised of a protein trimer modified with DNA handles. By changing the number of protein-DNA building blocks attached to the origami, and the sequence of the linking and displacement strands added, we were able to produce dimers, two types of trimer structures, and three types of tetramer assemblies. Our approach expands the scope for the precise design and assembly of protein-based nanostructures, and will enable the formulation of functional protein complexes with stoichiometric and geometric control.

bioengineering↗

bioRxiv2023

RNA-induced allosteric coupling drives viral capsid assembly in bacteriophage MS2

Understanding the mechanisms by which single-stranded RNA viruses regulate capsid assembly around their RNA genomes has become increasingly important for the development of both antiviral treatments and drug delivery systems. Here, we investigate the effects of RNA-induced allostery in a single-stranded RNA virus -- Levivirus bacteriophage MS2 -- using the computational methods of the Dynamic Flexibility Index (DFI) and the Dynamic Coupling Index (DCI). We show that asymmetric binding of RNA to a symmetric MS2 coat protein dimer increases the flexibility of the distant FG-loop and induces a conformational change to an asymmetric dimer that is essential for proper capsid formation. We also show that a point mutation W82R in the FG-loop creates an assembly-deficient dimer in which RNA-binding has no significant effect on FG-loop flexibility. Lastly, we show that the highly flexible disordered FG-loop of the RNA bound asymmetric dimer not only becomes the controller of the rigid FG-loop but enhances its dynamic coupling with all the distal positions in the dimer. This strong dynamic coupling allows highly regulated communication and unidirectional signal transduction that drives the formation of the experimentally observed capsid intermediates. Author summaryThe final stage of an RNA virus life cycle is the assembly of a protein shell encapsulating the viral genome prior to release from the host organism. Despite rapid advancements in both experimental and theoretical biology since the mid-20th century, little is still known about the underlying mechanisms of viral capsid assembly. However, understanding the biophysical principles of viral capsid assembly would bring us one step closer to developing new biotechnologies such as antivirals that inhibit this critical stage of the life cycle or artificial capsids for targeted drug/vaccine delivery. Although we limit the present study to one simple RNA virus that infects bacteria, we propose that the physical implications can extend to other RNA viruses including the human coronavirus SARS-CoV-2. We also propose that the allosteric regulation by specific protein-RNA interactions might be a general mechanism exploited by many other ribonucleoprotein complexes, such as CRISPR-Cas9, spliceosome or ribosome.

biophysics↗

bioRxiv2022

Generative and interpretable machine learning for aptamer design and analysis of in vitro sequence selection

Selection protocols such as SELEX, where molecules are selected over multiple rounds for their ability to bind to a target molecule of interest, are popular methods for obtaining binders for diagnostic and therapeutic purposes. With the increasing amount of such high-throughput experimental data available, machine learning techniques have become increasingly popular for molecular datasets analysis. Here, we show that Restricted Boltzmann Machines (RBMs), a two-layer neural network architecture, can successfully be trained on sequence ensembles from SELEX experiments for thrombin aptamers, and used to estimate the fitness of the sequences obtained through the experimental protocol. As a direct consequence, we show that trained RBMs can be exploited to classify as well as generate novel molecules. To confirm our findings, we experimentally verify the generated sequences from RBM.

biophysics↗

bioRxiv2021

A rhythmically pulsing leaf-spring nanoengine that drives a passive follower

Molecular engineering seeks to create functional entities for the modular use in the bottom-up design of nanoassemblies that can perform complex tasks. Such systems require fuel-consuming nanomotors that can actively drive downstream passive followers. Most molecular motors are driven by Brownian motion, but the generated forces are scattered and insufficient for efficient transfer to passive second-tier components, which is why nanoscale driver-follower systems have not been realized. Here, we describe bottom-up construction of a DNA-nanomachine that engages in an active, autonomous and rhythmical pulsing motion of two rigid DNA-origami arms, driven by chemical energy. We show the straightforward coupling of the active nanomachine to a passive follower unit, to which it then transmits its own motion, thus constituting a genuine driver-follower pair. Our work introduces a versatile fuel-consuming nanomachine that can be coupled with passive modules in nanoassemblies, the function of which depends on downstream sequences of motion.

biophysics↗

bioRxiv2021

Repeats Mimic Immunostimulatory Viral Features Across a Vast Evolutionary Landscape

An emerging hallmark across human diseases - such as cancer, autoimmune and neurodegenerative disorders - is the aberrant transcription of typically silenced repetitive elements. Once active, a subset of repeats may be capable of "viral mimicry": the display of pathogen-associated molecular patterns (PAMPs) that can, in principle, bind pattern recognition receptors (PRRs) of the innate immune system and trigger inflammation. Yet how to quantify the landscape of viral mimicry and how it is shaped by natural selection remains a critical gap in our understanding of both genome evolution and the immunological basis of disease. We propose a theoretical framework to quantify selective forces on virus-like features as the entropic cost a sequence pays to hold a non-self PAMP and show our approach can predict classes of viral-mimicry within the human genome and across eukaryotes. We quantify the breadth and conservation of viral mimicry across multiple species for the first time and integrate selective forces into predictive evolutionary models. We show HSATII and intact LINE-1 (L1) are under selection to maintain CpG motifs, and specific Alu families likewise maintain the proximal presence of inverted copies to form double-stranded RNA (dsRNA). We validate our approach by predicting high CpG L1 ligands of L1 proteins and the innate receptor ZCCHC3, and dsRNA present both intracellularly and as MDA5 ligands. We conclude viral mimicry is a general evolutionary mechanism whereby genomes co-opt pathogen-associated features generated by prone repetitive sequences, likely offering an advantage as a quality control system against transcriptional dysregulation.

systems biology↗

bioRxiv2021

Kinetics of RNA and RNA:DNA hybrid strand displacement

In dynamic nucleic acids nanotechnology, strand displacement is a widely used mechanism where one strand from a hybridized duplex is exchanged with an invading strand which binds to a toehold, a single-stranded region on the duplex. With proper design and kinetic control, strand displacement is used to perform logic operations on molecular level to trigger the conformational change in nanostructures, initiate cascaded reactions, or even for in vivo diagnostics and treatments. While systematic experimental studies have been carried out to probe the kinetics of strand displacement in DNA, there has not been a comparable systematic work done for RNA or RNA-DNA hybrid systems. Here, we experimentally study how toehold length, toehold location (5' or 3' end of the strand) and mismatches influence the strand displacement kinetics. Through comparing the reaction rates, combined with previous theoretical studies, we observed reaction acceleration with increasing toehold length and placement of toehold at 5'end of the substrate. We find that mismatches closer to the interface of toehold and duplex slow down the reaction more than remote mismatches. Comparison of RNA displacement and DNA displacement with hybrid displacement (RNA invading DNA or DNA invading RNA) is in part explainable by the thermodynamic stabilities of the respective toehold regions, but also suggest that the rearrangement from B-form to A-form helix in case of RNA invading DNA might play a role in the kinetics. The measured kinetics of toehold-mediated strand displacement will be important in understanding and construction of more complex dynamic nucleic acid systems.

bioengineering↗

bioRxiv2021

A Macro-scale Comparison Algorithm for Analysis of TCR Repertoire Completeness

Recent advances in biotechnology are beginning to generate whole immunome datasets, which will enable the comparison of immune repertoires between individuals, e.g., to assess immunocompetence. Existing algorithms cluster cell types based on the relative expression abundance of about 20 000 genes, but such algorithms have limited utility when comparing immunome datasets with many higher orders of magnitude (>1012) of variation, such as occurs in immunoreceptor sequences in highly polyclonal naive repertoires. In this paper we present a method for comparing immune repertoires by identifying macro-level features that are conserved between similar individuals. Our method allows us to detect some blind spots in naive populations and to assess whether a repertoire is likely complete by examining only a sample of its sequences. Author SummaryIn this paper we present a method for comparing the immune repertoire of different individuals. Repertoires are represented by a sample of genetic sequences. Our technique coarse grains each individuals data into groups, matches groups between individuals and finds significant differences.

bioinformatics↗

bioRxiv2021

ExpertRNA: A new framework for RNA structure prediction

Ribonucleic acid (RNA) is a fundamental biological molecule that is essential to all living organisms, performing a versatile array of cellular tasks. The function of many RNA molecules is strongly related to the structure it adopts. As a result, great effort is being dedicated to the design of efficient algorithms that solve the "folding problem": given a sequence of nucleotides, return a probable list of base pairs, referred to as the secondary structure prediction. Early algorithms have largely relied on finding the structure with minimum free energy. However, the predictions rely on effective simplified free energy models that may not correctly identify the correct structure as the one with the lowest free energy. In light of this, new, data-driven approaches that not only consider free energy, but also use machine learning techniques to learn motifs have also been investigated, and have recently been shown to outperform free energy based algorithms on several experimental data sets. In this work, we introduce the new ExpertRNA algorithm that provides a modular framework which can easily incorporate an arbitrary number of rewards (free energy or non-parametric/data driven) and secondary structure prediction algorithms. We argue that this capability of ExpertRNA has the potential to balance out different strengths and weaknesses of state-of-the-art folding tools. We test the ExpertRNA on several RNA sequence-structure data sets, and we compare the performance of ExpertRNA against a state-of-the-art folding algorithm. We find that ExpertRNA produces, on average, more accurate predictions than the structure prediction algorithm used, thus validating the promise of the approach.

bioinformatics↗

bioRxiv2020

Phenotype bias determines how RNA structures occupy the morphospace of all possible shapes

Morphospaces representations of phenotypic characteristics are often populated unevenly, leaving large parts unoccupied. Such patterns are typically ascribed to contingency, or else to natural selection disfavouring certain parts of the morphospace. The extent to which developmental bias, the tendency of certain phenotypes to preferentially appear as potential variation, also explains these patterns is hotly debated. Here we demonstrate quantitatively that developmental bias is the primary explanation for the occupation of the morphospace of RNA secondary structure (SS) shapes. Upon random mutations, some RNA SS shapes (the frequent ones) are much more likely to appear than others. By using the RNAshapes method to define coarse-grained SS classes, we can directly compare the frequencies that non-coding RNA SS shapes appear in the RNAcentral database to frequencies obtained upon random sampling of sequences. We show that: a) Only the most frequent structures appear in nature; the vast majority of possible structures in the morphospace have not yet been explored. b) Remarkably small numbers of random sequences are needed to produce all the RNA SS shapes found in nature so far. c) Perhaps most surprisingly, the natural frequencies are accurately predicted, over several orders of magnitude in variation, by the likelihood that structures appear upon uniform random sampling of sequences. The ultimate cause of these patterns is not natural selection, but rather strong phenotype bias in the RNA genotype-phenotype map, a type of developmental bias or "findability constraint", which limits evolutionary dynamics to a hugely reduced subset of structures that are easy to "find".

evolutionary biology↗

bioRxiv2020

Understanding DNA interactions in crowded environments with a coarse-grained model

Nucleic acid interactions under crowded environments are of great importance for biological processes and nanotechnology. However, the kinetics and thermodynamics of nucleic acid interactions in a crowded environment remain poorly understood. We use a coarse-grained model of DNA to study the kinetics and thermodynamics of DNA duplex and hairpin formation in crowded environments. We find that crowders can increase the melting temperature of both an 8-mer DNA duplex and a hairpin with a stem of 6-nt depending on the excluded volume fraction of crowders in solution and the crowder size. The crowding induced stability originates from the entropic effect caused by the crowding particles in the system. Additionally, we study the hybridization kinetics of DNA duplex formation and the formation of hairpin stems, finding that the reaction rate kon is increased by the crowding effect, while koff is changed only moderately. The increase in kon mostly comes from increasing the probability of reaching a transition state with one base pair formed. A DNA strand displacement reaction in a crowded environment is also studied with the model and we find that rate of toehold association is increased, with possible applications to speeding up strand displacement cascades in nucleic acid nanotechnology.

biophysics↗