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Ralf Bundschuh

Publications and source records attributed to Ralf Bundschuh.

At least 19 recordsLinked to original sources

A kinetic model of shear-induced rupture of short dsDNA

Force-induced dissociation of short double-stranded DNA (dsDNA) is central to single-molecule biophysics and DNA nanotechnology, yet a physically grounded kinetic description of shear-induced rupture for finite-length constructs remains lacking. Here we develop a master equation framework built on a force-dependent nucleation-zipper pathway with single-base transitions, enabling direct calculation of dissociation rates and transition state distances over a broad force range. Applied to a DNA-gold nanoparticle-DNA construct under constant shear force, the model accurately reproduces the experimental room-temperature data in the covered force regime and provides a unified interpretation of prior measurements on similarly sheared duplexes across all force regimes. A central result is that the three-dimensional helical geometry of dsDNA is essential for correctly defining the end to end distance under shear in the rod-like polymer model of short dsDNA. We further show that the extracted transition state distances are robust to variations in ssDNA polymer parameters within the experimentally relevant regime. Finally, we analyze the temperature dependence of the transition state distance and discuss how our framework captures globally-heated rupture while identifying the additional complications introduced by localized plasmonic heating in gold nanoparticle-coupled constructs. These results provide a predictive kinetic foundation for interpreting force-rupture experiments and for designing force- and temperature-actuated DNA nanostructures.

q-bio.BM

Computational modeling of RNA-protein binding interactions under an external force

RNA binding proteins play a crucial role in post-transcriptional gene regulation by controlling the transport, processing, and translation of their target RNAs. Post-transcriptional gene regulation leads to the differential expression of genetic material and loss of regulation or over-regulation relates to a large range of cancers and diseases - many of which have directly been associated with RNA binding proteins and their target RNAs. To understand RNA, RNA binding proteins, and how they function in gene expression, it is essential to characterize how RNA binding proteins interact with their target RNAs. Here, we aim to assess the potential for single molecule force spectroscopy experiments to be used in the characterization of RNA-protein binding by investigating to what extent a change of extension due to RNA-protein binding is experimentally measurable and what aspects of the interaction can be deduced from such measurements. We predict the effect of protein binding on RNA force extension measurements via the open-source ViennaRNA package, which we have modified to simultaneously consider an external force, protein binding, and RNA secondary structure. From this work, we see protein concentration-dependent responses to external forces with discernable differences in predicted extensions around biologically relevant concentrations and a connection to protein binding domain geometry for several RNA binding proteins.

q-bio.BM

A quantitative model for a nanoscale switch accurately predicts thermal actuation behavior

Manipulation of temperature can be used to actuate DNA origami nano-hinges containing gold nanoparticles. We develop a physical model of this system that uses partition function analysis of the interaction between the nano-hinge and nanoparticle to predict the probability that the nano-hinge is open at a given temperature. The model agrees well with experimental data and predicts experimental conditions that allow the actuation temperature of the nano-hinge to be tuned over a range of temperatures from $30$${}^{\circ}\mathrm{C}$ to $45$${}^{\circ}\mathrm{C}$. Additionally, the model reveals surprising physical constraints on the system. This combination of physical insight and predictive potential is likely to inform future designs that integrate nanoparticles into dynamic DNA origami structures. Furthermore, our modeling approach could be expanded to consider the incorporation, stability, and actuation of other types of functional elements or actuation mechanisms integrated into nucleic acid devices.

q-bio.BM

Potential evolutionary advantage of a dissociative search mechanism in DNA mismatch repair

Protein complexes involved in DNA mismatch repair appear to diffuse along dsDNA in order to locate a hemimethylated incision site via a dissociative mechanism. Here, we study the probability that these complexes locate a given target site via a semi-analytic, Monte Carlo calculation that tracks the association and dissociation of the complexes. We compare such probabilities to those obtained using a non-dissociative diffusive scan, and determine that for experimentally observed diffusion constants, search distances, and search durations $\textit{in vitro}$, there is neither a significant advantage nor disadvantage associated with the dissociative mechanism in terms of probability of successful search, and that both search mechanisms are highly efficient for a majority of hemimethylated site distances. Furthermore, we examine the space of physically realistic diffusion constants, hemimethylated site distances, and association lifetimes and determine the regions in which dissociative searching is more or less efficient than non-dissociative searching. We conclude that the dissociative search mechanism is advantageous in the majority of the physically realistic parameter space.

q-bio.SC

CLEAR: Coverage-based Limiting-cell Experiment Analysis for RNA-seq

Direct cDNA preamplification protocols developed for single-cell RNA-seq have enabled transcriptome profiling of precious clinical samples and rare cells without sample pooling or RNA extraction. Currently, there is no algorithm optimized to reveal and remove noisy transcripts in limiting-cell RNA-seq (lcRNA-seq) data for downstream analyses. Herein, we present CLEAR, a workflow that identifies reliably quantifiable transcripts in lcRNA-seq data for differentially expressed gene (DEG) analysis. Libraries at three input amounts of FACS-derived CD5+ and CD5- cells from a chronic lymphocytic leukemia patient were used to develop CLEAR. When using CLEAR transcripts vs. using all transcripts, downstream analyses revealed more shared transcripts across different input RNA amounts, improved Principal Component Analysis (PCA) separation, and yielded more DEGs between cell types. As proof-of-principle, CLEAR was applied to an in-house lcRNA-seq dataset and two public datasets. When imputation is used, CLEAR is also adaptable to large clinical studies and for single cell analyses.

q-bio.GN

On the behavior of random RNA secondary structures near the glass transition

RNA forms elaborate secondary structures through intramolecular base pairing. These structures perform critical biological functions within each cell. Due to the availability of a polynomial algorithm to calculate the partition function over these structures, they are also a suitable system for the statistical physics of disordered systems. In this model, below the denaturation temperature, random RNA secondary structures exist in one of two phases: a strongly disordered, low-temperature glass phase, and a weakly disordered, high-temperature molten phase. The probability of two bases to pair decays with their distance with an exponent 3/2 in the molten phase, and about 4/3 in the glass phase. Inspired by previous results from a renormalized field theory of the glass transition separating the two phases, we numerically study this transition. We introduce distinct order parameters for each phase, that both vanish at the critical point. We finally explore the driving mechanism behind this transition.

q-bio.BM

The exon junction complex undergoes a compositional switch that alters mRNP structure and nonsense-mediated mRNA decay activity

The exon junction complex (EJC) deposited upstream of mRNA exon junctions shapes structure, composition and fate of spliced mRNA ribonucleoprotein particles (mRNPs). To achieve this, the EJC core nucleates assembly of a dynamic shell of peripheral proteins that function in diverse post-transcriptional processes. To illuminate consequences of EJC composition change, we purified EJCs from human cells via peripheral proteins RNPS1 and CASC3. We show that EJC originates as an SR-rich mega-dalton sized RNP that contains RNPS1 but lacks CASC3. After mRNP export to the cytoplasm and before translation, the EJC undergoes a remarkable compositional and structural remodeling into an SR-devoid monomeric complex that contains CASC3. Surprisingly, RNPS1 is important for nonsense-mediated mRNA decay (NMD) in general whereas CASC3 is needed for NMD of only select mRNAs. The promotion of switch to CASC3-EJC slows down NMD. Overall, the EJC compositional switch dramatically alters mRNP structure and specifies two distinct phases of EJC-dependent NMD.

q-bio.GN

RBPBind: Quantitative prediction of Protein-RNA Interactions

Summary: We introduce RBPBind, a web-based tool for the quantitative prediction of RNA-protein interactions. Given a user-specified RNA and a protein selected from a set of several common RNA-binding proteins, RBPBind computes the binding curve and effective binding constant of the reaction in question. The server also computes the probability that, at a given concentration of protein, a protein molecule will bind to any particular nucleotide along the RNA. The software for RBPBind is adapted from the Vienna RNA package, whose source code has been modified to accommodate the effects of single stranded RNA binding proteins. RBPBind thus fully incorporates the effect of RNA secondary structure on protein-RNA interactions. Availability: Our web server is available at http://bioserv.mps.ohio-state.edu/RBPBind

q-bio.BM

RNA structure generates natural cooperativity between single-stranded RNA binding proteins targeting 5' and 3'UTRs

In post-transcriptional regulation, an mRNA molecule is bound by many proteins and/or miRNAs to modulate its function. To enable combinatorial gene regulation, these binding partners of an RNA must communicate with each other, exhibiting cooperativity. Even in the absence of direct physical interactions between the binding partners, such cooperativity can be mediated through RNA secondary structures, since they affect the accessibility of the binding sites. Here we propose a quantitative measure of this structure-mediated cooperativity that can be numerically calculated for an arbitrary RNA sequence. Focusing on an RNA with two binding sites, we derive a characteristic difference of free energy differences, i.e. ΔΔG, as a measure of the effect of the occupancy of one binding site on the binding strength of another. We apply this measure to a large number of human and C. elegans mRNAs, and find that structure-mediated cooperativity is a generic feature. Interestingly, this cooperativity not only affects binding sites in close proximity along the sequence but also configurations in which one binding site is located in the 5'UTR and the other is located in the 3'UTR of the mRNA. Furthermore, we find that this end-to-end cooperativity is determined by the UTR sequences while the sequences of the coding regions are irrelevant.

q-bio.BM

Interplay between single-stranded binding proteins on RNA secondary structure

RNA protein interactions control the fate of cellular RNAs and play an important role in gene regulation. An interdependency between such interactions allows for the implementation of logic functions in gene regulation. We investigate the interplay between RNA binding partners in the context of the statistical physics of RNA secondary structure, and define a linear correlation function between the two partners as a measurement of the interdependency of their binding events. We demonstrate the emergence of a long-range power-law behavior of this linear correlation function. This suggests RNA secondary structure driven interdependency between binding sites as a general mechanism for combinatorial post-transcriptional gene regulation.

q-bio.BM

Anomalous scaling in nanopore translocation of structured heteropolymers

Translocation through a nanopore is a new experimental technique to probe physical properties of biomolecules. A bulk of theoretical and computational work exists on the dependence of the time to translocate a single unstructured molecule on the length of the molecule. Here, we study the same problem but for RNA molecules for which the breaking of the secondary structure is the main barrier for translocation. To this end, we calculate the mean translocation time of single-stranded RNA through a nanopore of zero thickness and at zero voltage for many randomly chosen RNA sequences. We find the translocation time to depend on the length of the RNA molecule with a power law. The exponent changes as a function of temperature and exceeds the naively expected exponent of two for purely diffusive transport at all temperatures. We interpret the power law scaling in terms of diffusion in a one-dimensional energy landscape with a logarithmic barrier.

q-bio.BM

Melting of Branched RNA Molecules

Stability of the branching structure of an RNA molecule is an important condition for its function. In this letter we show that the melting thermodynamics of RNA molecules is very sensitive to their branching geometry for the case of a molecule whose groundstate has the branching geometry of a Cayley Tree and whose pairing interactions are described by the Go model. Whereas RNA molecules with a linear geometry melt via a conventional continuous phase transition with classical exponents, molecules with a Cayley Tree geometry are found to have a free energy that seems smooth, at least within our precision. Yet, we show analytically that this free energy in fact has a mathematical singularity at the stability limit of the ordered structure. The correlation length appears to diverge on the high-temperature side of this singularity.

q-bio.BM

Model for Folding and Aggregation in RNA Secondary Structures

We study the statistical mechanics of RNA secondary structures designed to have an attraction between two different types of structures as a model system for heteropolymer aggregation. The competition between the branching entropy of the secondary structure and the energy gained by pairing drives the RNA to undergo a `temperature independent' second order phase transition from a molten to an aggregated phase'. The aggregated phase thus obtained has a macroscopically large number of contacts between different RNAs. The partition function scaling exponent for this phase is θ~ 1/2 and the crossover exponent of the phase transition is ν~ 5/3. The relevance of these calculations to the aggregation of biological molecules is discussed.

physics.bio-ph

Coupled dynamics of RNA folding and nanopore translocation

The translocation of structured RNA or DNA molecules through narrow pores necessitates the opening of all base pairs. Here, we study the interplay between the dynamics of translocation and base-pairing theoretically, using kinetic Monte Carlo simulations and analytical methods. We find that the transient formation of basepairs that do not occur in the ground state can significantly speed up translocation.

q-bio.BM

Numerical Method for Accessing the Universal Scaling Function for a Multi-Particle Discrete Time Asymmetric Exclusion Process

In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz's original publication [PRL 80 209 (1998)] this universality has been verified for a variety of continuous time, periodic boundary systems in the KPZ universality class. Here, we present a numerical method for directly examining the entire particle flux of the asymmetric exclusion process (ASEP), thus providing an alternative to more difficult cumulant ratios studies. Using this method, we find that the Derrida-Lebowitz scaling function (DLSF) properly characterizes the large system size limit (N-->infty) of a single particle discrete time system, even in the case of very small system sizes (N <= 22). This fact allows us to not only verify that the DLSF properly characterizes multiple particle discrete-time asymmetric exclusion processes, but also provides a way to numerically solve for quantities of interest, such as the particle hopping flux. This method can thus serve to further increase the ease and accessibility of studies involving even more challenging dynamics, such as the open boundary ASEP.

cond-mat.stat-mech

A model for codon position bias in RNA editing

RNA editing can be crucial for the expression of genetic information via inserting, deleting, or substituting a few nucleotides at specific positions in an RNA sequence. Within coding regions in an RNA sequence, editing usually occurs with a certain bias in choosing the positions of the editing sites. In the mitochondrial genes of {\it Physarum polycephalum}, many more editing events have been observed at the third codon position than at the first and second, while in some plant mitochondria the second codon position dominates. Here we propose an evolutionary model that explains this bias as the basis of selection at the protein level. The model predicts a distribution of the three positions rather close to the experimental observation in {\it Physarum}. This suggests that the codon position bias in {\it Physarum} is mainly a consequence of selection at the protein level.

physics.bio-ph

Analytical description of finite size effects for RNA secondary structures

The ensemble of RNA secondary structures of uniform sequences is studied analytically. We calculate the partition function for very long sequences and discuss how the cross-over length, beyond which asymptotic scaling laws apply, depends on thermodynamic parameters. For realistic choices of parameters this length can be much longer than natural RNA molecules. This has to be taken into account when applying asymptotic theory to interpret experiments or numerical results.

physics.bio-ph

Quantification of the differences between quenched and annealed averaging for RNA secondary structures

The analytical study of disordered system is usually difficult due to the necessity to perform a quenched average over the disorder. Thus, one may resort to the easier annealed ensemble as an approximation to the quenched system. In the study of RNA secondary structures, we explicitly quantify the deviation of this approximation from the quenched ensemble by looking at the correlations between neighboring bases. This quantified deviation then allows us to propose a constrained annealed ensemble which predicts physical quantities much closer to the results of the quenched ensemble without becoming technically intractable.

physics.bio-ph