Biology subjects

Kimchi, O.

Publications and source records attributed to Kimchi, O..

11 recordsLinked to original sources

bioRxiv2026

Intersegmental transfers drive target search in an RNA-targeting CRISPR system

Sequence-specific RNA-binding proteins (RBPs) must efficiently locate their targets among a multitude of cellular RNAs. Cas13, an RNA-guided CRISPR protein, represents an ideal model system in which to study this search process. Cas13 combats bacteriophage infection by cleaving RNA nonspecifically upon binding of its crRNA to the target RNA sequence; thus, Cas13s search for its RNA target comes with a time constraint determined by the rate of phage multiplication. The mechanism by which Cas13 locates its target within this critical window remains unknown. Here, we investigate Cas13s mechanism of target search through integration of biophysical modeling, activity assays, and biochemical characterization. We show that Cas13 employs facilitated diffusion to accelerate its search, and find that Cas13s search time when targeting RNAs of different lengths cannot be explained by 1D sliding, the search mechanism used by many DNA-binding proteins. We propose that Cas13 primarily searches for its RNA target by intersegmental transfers (ITs), non-specifically binding the RNA at two locations and directly switching between them without fully dissociating from the RNA. We develop a biophysical model for ITs in an RNA context that we subsequently validate experimentally. Furthermore, we demonstrate that ITs can differentially accelerate the search process for a broad class of RNA-binding proteins, as opposed to their DNA-binding counterparts, due to RNAs short persistence length and the heterogeneity of RNA lengths in the cell. Our results illuminate how Cas13 achieves rapid target recognition in a complex RNA environment, and implicate ITs as a potentially widespread solution to the RNA search problem.

biophysics↗

bioRxiv2025

Genome-wide mapping of mesoscale neuronal RNA organization and condensation

Subcellular RNA organization can affect critical cellular functions. However, our understanding of RNA microenvironments, particularly biomolecular condensates, remains limited, largely due to a lack of technologies to comprehensively interrogate mesoscale RNA organization. Here, we adapt Split-Pool Recognition of Interactions by Tag Extension to map micron-scale RNA-RNA spatial proximity genome-wide across cell regions (RNA-SPRITE). Deploying RNA-SPRITE, we find extensive, conserved organization of mature mRNAs, with increased colocalization between mRNAs that share RNA-binding protein (RBP) motifs or encode functionally related proteins. Both effects are especially strong in dendrites and axons, suggesting prevalent mRNA co-regulation. Moreover, mRNAs with less compact folding, lower translation efficiency, and specific RBP motifs are more likely to be in RNA-rich condensates. However, perturbations that broadly dissolve or enhance condensation reveal that RBP motif and encoded protein-mediated colocalizations largely remain intact, independent of condensation. These results demonstrate the power of RNA-SPRITE in revealing critical aspects of RNAs functional organization. In BriefUnbiased, genome-wide maps of RNA-RNA mesoscale spatial proximity uncover extensive subcellular organization and its governing principles. HighlightsO_LIRNA-SPRITE reveals micron-scale RNA colocalization genome-wide across cell regions C_LIO_LImRNA colocalization specificity is driven by shared motifs and encoded protein function C_LIO_LImRNAs with less compact folding, lower translation efficiency, and distinct protein-binding motifs are more likely to be in condensates C_LIO_LINeurites have a particularly high degree of sequence and function-dependent mRNA organization C_LI

molecular biology↗

bioRxiv2024

Bacterial defense and phage counter-defense lead to coexistence in a modeled ecosystem

Bacteria have evolved many defenses against invading viruses (phage). Typically, each bacterium carries several defense systems, while each phage may carry multiple counter-defense systems. Despite the many bacterial defenses and phage counter-defenses, in most environments, bacteria and phage coexist, with neither driving the other to extinction. How is coexistence realized in the context of the bacteria/phage arms race, and how are the sizes of the bacterial immune and phage counter-immune repertoires determined in conditions of coexistence? Here we develop a simple mathematical model to consider the evolutionary and ecological dynamics of competing bacteria and phage with different immune/counter-immune repertoires. An analysis of our model reveals an ecologically stable fixed point exhibiting coexistence. This fixed point agrees with the experimental observation that each individual bacterium typically carries multiple defense systems, though fewer than the maximum number possible. However, in simulations, the populations typically remain dynamic, exhibiting chaotic fluctuations around this fixed point. We obtain quantitative predictions for the mean, amplitude, and timescale of these dynamics. Our results provide a framework for understanding the evolutionary and ecological dynamics of the bacteria/phage arms race, and demonstrate how bacteria/phage coexistence can stably arise from the coevolution of bacterial defense systems and phage counter-defense systems.

microbiology↗

bioRxiv2023

RNA structure modulates Cas13 activity and enables mismatch detection

The RNA-targeting CRISPR nuclease Cas13 has emerged as a powerful tool for applications ranging from nucleic acid detection to transcriptome engineering and RNA imaging1-6. Cas13 is activated by the hybridization of a CRISPR RNA (crRNA) to a complementary single-stranded RNA (ssRNA) protospacer in a target RNA1,7. Though Cas13 is not activated by double-stranded RNA (dsRNA) in vitro, it paradoxically demonstrates robust RNA targeting in environments where the vast majority of RNAs are highly structured2,8. Understanding Cas13s mechanism of binding and activation will be key to improving its ability to detect and perturb RNA; however, the mechanism by which Cas13 binds structured RNAs remains unknown9. Here, we systematically probe the mechanism of LwaCas13a activation in response to RNA structure perturbations using a massively multiplexed screen. We find that there are two distinct sequence-independent modes by which secondary structure affects Cas13 activity: structure in the protospacer region competes with the crRNA and can be disrupted via a strand-displacement mechanism, while structure in the region 3 to the protospacer has an allosteric inhibitory effect. We leverage the kinetic nature of the strand displacement process to improve Cas13-based RNA detection, enhancing mismatch discrimination by up to 50-fold and enabling sequence-agnostic mutation identification at low (<1%) allele frequencies. Our work sets a new standard for CRISPR-based nucleic acid detection and will enable intelligent and secondary-structure-guided target selection while also expanding the range of RNAs available for targeting with Cas13.

molecular biology↗

bioRxiv2023

Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch-probe arrays

We describe a simple method to infer intramolecular connections in a population of long RNA molecules in vitro. First we add DNA oligonucleotide "patches" that perturb the RNA connections, then we use a microarray containing a complete set of DNA oligonucleotide "probes" to record where perturbations occur. The pattern of perturbations reveals couplings between different regions of the RNA sequence, from which we infer connections as well as their prevalences in the population. We validate this patch-probe method using the 1,058-nucleotide RNA genome of satellite tobacco mosaic virus (STMV), which has previously been shown to have multiple long-range connections. Our results not only indicate long duplexes that agree with previous structures but also reveal the prevalence of competing connections. Together, these results suggest that globally-folded and locally-folded structures coexist in solution. We show that the prevalence of connections changes when pseudouridine, an important component of natural and synthetic RNA molecules, is substituted for uridine in STMV RNA.

biophysics↗

bioRxiv2022

Lytic and temperate phage naturally coexist in a dynamic population model

Obligate lytic and temperate phage preying on the same bacteria coexist despite the presumption that a single resource should only support a single competitor. We construct a mathematical model demonstrating that such coexistence is a natural outcome of chaotic dynamics arising from competition among multiple phage and their lysogens. While obligate lytic (virulent) phage populations typically dominate, surprisingly, they also more readily fluctuate to extinction within a local community.

ecology↗

bioRxiv2022

The assembly yield of complex, heterogeneous structures: A computational toolbox

The self-assembly of complex structures from a set of non-identical building blocks is a hallmark of soft matter and biological systems, including protein complexes, colloidal clusters, and DNA-based assemblies. Predicting the dependence of the equilibrium assembly yield on the concentrations and interaction energies of building blocks is highly challenging, owing to the difficulty of computing the entropic contributions to the free energy of the many structures that compete with the ground state configuration. While these calculations yield well known results for spherically symmetric building blocks, we discovered that they do not hold when the building blocks have internal rotational degrees of freedom. Here we present an approach for solving this problem that works with arbitrary building blocks, including proteins with known structure and complex colloidal building blocks. Our algorithm combines classical statistical mechanics with recently developed computational tools for automatic differentiation. Automatic differentiation allows efficient evaluation of equilibrium averages over configurations that would otherwise be intractable. We demonstrate the validity of our framework by comparison to molecular dynamics simulations of simple examples, and apply it to calculate the yield curves for known protein complexes and for the assembly of colloidal shells.

biophysics↗

bioRxiv2022

Uncovering the mechanism for aggregation in repeat expanded RNA reveals a reentrant transition

Repeat expanded RNA molecules aggregate under certain conditions both in vitro and in vivo. Understanding the mechanism for aggregation--including how aggregation properties change with sequence and environmental conditions--would explain and predict the behavior of RNA-based biomolecular condensates, and enable the rational design of RNA-based materials. Here, we introduce an analytical framework to predict aggregation for any repeat RNA sequence, accounting for both intra- and inter-molecular bonding. By enumerating the equilibrium landscape of multimers, we reveal the driving force for aggregation: the increased configurational entropy associated with the multiplicity of ways to form bonds in the aggregate. Our model uncovers rich phase behavior, including a sequence-dependent reentrant phase transition, and repeat parity-dependent aggregation. We validate our results by comparison to a complete computational enumeration of the landscape, and to previously published molecular dynamics simulations. Our work unifies and extends published results, and enables the design of programmable RNA condensates.

biophysics↗

bioRxiv2020

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design

As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses.

bioinformatics↗

bioRxiv2020

Self-assembly based post-translational protein oscillators

Recent advances in synthetic post-translational protein circuits are significantly impacting the landscape of biomimicry engineering. However, designing sustained dynamic phenomena in these circuits remains an outstanding challenge. Inspired by the KaiABC system regulating the circadian clock in cyanobacteria, we develop two experimentally realizable post-translational oscillators. The oscillators rely on a small number of components interacting only through reversible binding and phosphorylation/dephosphorylation reactions.

systems biology↗

bioRxiv2018

RNA structure prediction including pseudoknots through direct enumeration of states

The accurate prediction of RNA secondary structure from primary sequence has had enormous impact on research from the past forty years. While many algorithms are available to make these predictions, the inclusion of non-nested loops, termed pseudoknots, still poses challenges. Here, we describe a new method to compute the entire free energy landscape of secondary structures of RNA resulting from a primary RNA sequence, by combining a polymer physics model for the entropy of pseudoknots with exhaustive enumeration of the set of possible structures. Our polymer physics model can address arbitrarily complex pseudoknots and has only two free loop entropy parameters that correspond to concrete physical quantities, over an order of magnitude fewer than even the sparsest state-of-the-art algorithms. Our model outperforms previously published methods in predicting pseudoknots, while performing on par with current methods in the prediction of non-pseudoknotted structures. For RNA sequences of ~ 45 nucleotides, or ~ 90 with minimal heuristics, the complet-e enumeration of possible secondary structures can be accomplished quickly despite the NP-complete nature of the problem.

biophysics↗