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bioRxiv2023

Robust and resource-optimal dynamic pattern formation of Min proteins in vivo

The Min system in Escherichia coli plays a crucial role in cellular reproduction by preventing minicell formation through pole-to-pole oscillations. Despite extensive research, predicting the onset of Min protein concentrations for oscillation and understanding the systems robustness under physiological perturbations remains challenging. Our study aims to address these gaps. We show that the Min systems dynamic pattern formation is robust across a wide range of Min protein levels and varying growth physiology. Using genetically engineered E. coli strains, we independently modulated the expression of minCD and minE in E. coli under both fast and slow growth conditions. This led to the construction of a MinD-MinE phase diagram, which revealed not just a large oscillation regime but also complex dynamic patterns such as traveling and standing waves. Interestingly, we found that the natural expression level of Min proteins is nearly optimal. Our work combines experimental findings with biophysical theory based on reaction-diffusion models, reproducing the experimental phase diagram and other key properties quantitatively. This includes the observation of an invariant wavelength of dynamic Min patterns across our phase diagram. Crucially, the success of our model depends on the switching of MinE between its latent and active states, indicating its essential role as a robustness module for Min oscillation in vivo. Our results underline the potential of integrating quantitative cell physiology and biophysical modeling in understanding the fundamental mechanisms controlling cell division machinery, offering insights applicable to other biological processes.

biophysics↗

bioRxiv2023

The Immune-Evasive Proline 283 Substitution in Influenza Nucleoprotein Increases Aggregation Propensity Without Altering the Native Structure

Nucleoprotein (NP) is a key structural protein of influenza ribonucleoprotein complexes and is central to viral RNA packing and trafficking. In human cells, the interferon induced Myxovirus resistance protein 1 (MxA) binds to NP and restricts influenza replication. This selection pressure has caused NP to evolve a few critical MxA-resistant mutations, particularly the highly conserved Pro283 substitution. Previous work showed that this essential Pro283 substitution impairs influenza growth, and the fitness defect becomes particularly prominent at febrile temperature (39 {degrees}C) when host chaperones are depleted. Here, we biophysically characterize Pro283 NP and Ser283 NP to test if the fitness defect is owing to Pro283 substitution introducing folding defects. We show that the Pro283 substitution changes the folding pathway of NP without altering the native structure, making NP more aggregation prone during folding. These findings suggest that influenza has evolved to hijack host chaperones to promote the folding of otherwise biophysically incompetent viral proteins that enable innate immune system escape. TeaserPro283 substitution in flu nucleoprotein introduces folding defects, and makes influenza uniquely dependent on host chaperones.

biophysics↗

bioRxiv2023

Theory on the power-law distribution of the Michaelis-Menten enzyme kinetic parameters

We show on the biophysical basis that the observed enzyme kinetic parameters related to the substrate binding, product turnover and catalytic efficiency follow power-law type density functions. These finding are validated with the available datasets on various enzymes across different substrates. The product turnover rates and catalytic efficiencies seems to follow a bimodal type density functions in line with the single molecule experiments on enzyme catalysis which can be explained by a sum of two different power-law type density functions. The curve geometry of the density functions is decided by the underlying biophysical factors and the location of the peak is dictated by the natural selection pressure.

biophysics↗

bioRxiv2023

Sensitivity analysis identifies the factors driving the enzymatic saccharification of lignocellulose

Corn stover is the most abundant form of crop residue that can serve as a source of lignocellulosic biomass in biorefinery approaches, for instance for the production of bioethanol. In such biorefinery processes, the constituent polysaccharide biopolymers are typically broken down into simple monomeric sugars by enzymatic saccharification, for further downstream fermentation into bioethanol. However, the recalcitrance of this material to enzymatic saccharification invokes the need for innovative pre-treatment methods to increase sugar conversion yield. Here, we focus on experimental glucose conversion time-courses for corn stover lignocellulose that has been pre-treated with different acid-catalysed processes and intensities. We identify the key parameters that determine enzymatic saccharification dynamics by performing a Sobols sensitivity analysis on the comparison between the simulation results from our complex stochastic biophysical model, and the experimental data that we accurately reproduce. We find that the parameters relating to cellulose crystallinity and those associated with the cellobiohydrolase activity are predominantly driving the enzymatic saccharification dynamics. We confirm our computational results using mathematical calculations for a purely cellulosic substrate. On the one hand, having identified that only five parameters drastically influence the saccharification dynamics allows us to reduce the dimensionality of the parameter space (from nineteen to five parameters), which we expect will significantly speed up our fitting algorithm for comparison of experimental and simulated saccharification time-courses. On the other hand, these parameters directly highlight key targets for experimental endeavours in the optimisation of pre-treatment and saccharification conditions. Finally, this systematic and two-fold theoretical study, based on both mathematical and computational approaches, provides experimentalists with key insights that will support them in rationalising their complex experimental results. O_TEXTBOXSIGNIFICANCE The recalcitrance of lignocellulosic biomass to enzymatic saccharification processes necessitates innovative biorefinery pre-treatment processes with the goal of increasing glucose conversion yields. We implement a systematic Sobols sensitivity analysis on the comparison between the simulation results from our complex stochastic biophysical model, and experimental glucose conversion time-courses data for pre-treated corn stover lignocellulose that we accurately reproduce with our model. Our results, reinforced with analytical calculations, highlight the key parameters which govern the dynamics of enzymatic saccharification of lignocellulose. Thus, this study does not only drastically reduce the model parameter space from nineteen free parameters to only five key ones, but it also provides valuable insights that can guide future experiment design efforts, and the rationalisation of complex experimental datasets. C_TEXTBOX

biophysics↗

bioRxiv2023

The Physical Biology of Nucleolus Disassembly

During cell division, precise and regulated distribution of cellular material between daughter cells is a critical step and is governed by complex biochemical and biophysical mechanisms. To achieve this, membraneless organelles and condensates often require complete disassembly during mitosis. The biophysical principles governing the disassembly of condensates remain poorly understood. Here, we used a physical biology approach to study how physical and material properties of the nucleolus, a prominent nuclear membraneless organelle in eukaryotic cells, change during mitosis and across different scales. We found that nucleolus disassembly proceeds continuously through two distinct phases with a slow and reversible preparatory phase followed by a rapid irreversible phase that was concurrent with the nuclear envelope breakdown. We measured microscopic properties of nucleolar material including effective diffusion rates and binding affinities as well as key macroscopic properties of surface tension and bending rigidity. By incorporating these measurements into the framework of critical phenomena, we found evidence that near mitosis surface tension displays a power-law behavior as a function of biochemically modulated interaction strength. This two-step disassembly mechanism, which maintains structural and functional stability of nucleolus while allowing for its rapid and efficient disassembly in response to cell cycle cues, may be a universal design principle for the disassembly of other biomolecular condensates.

biophysics↗

bioRxiv2023

Inference and design of antibody specificity: from experiments to models and back

Exquisite binding specificity is essential for many protein functions but is difficult to engineer. Many biotechnological or biomedical applications require the discrimination of very similar ligands, which poses the challenge of designing protein sequences with highly specific binding profiles. Current methods for generating specific binders rely on in vitro selection experiments, but these have limitations in terms of library size and control over specificity profiles. We present a multi-stage approach that overcomes these limitations by combining high-throughput sequencing of phage display experiments with machine learning and biophysical modeling. Our models predict the binding profiles of antibodies against multiple ligands and generate antibody sequences with desired specificity profiles. The approach involves the identification of different binding modes, each associated with a particular ligand against which the antibodies are either selected or not. We demonstrate that the model successfully disentangles these modes, even when they are associated with chemically very similar ligands. Additionally, we demonstrate and validate experimentally the computational design of antibodies with customized specificity profiles, either with specific high affinity for a particular target ligand, or with cross-specificity for multiple target ligands. Overall, our results showcase the potential of leveraging a biophysical model learned from selections against multiple ligands to design proteins with tailored specificity, with applications to protein engineering extending beyond the design of antibodies.

biophysics↗

bioRxiv2023

Unsupervised modeling of mutational landscapes of adeno-associated viruses viability

Adeno-associated viruses 2 (AAV2) are minute viruses renowned for their capacity to infect human cells and akin organisms. They have recently emerged as prominent candidates in the field of gene therapy, primarily attributed to their inherent non-pathogenic nature in humans and the safety associated with their manipulation. The efficacy of AAV2 as gene therapy vectors hinges on their ability to infiltrate host cells and subsequently replicate within them, a phenomenon reliant on their competence to construct a capsid capable of breaching the nucleus of the target cell. To enhance their infection potential, researchers have extensively scrutinized various combinatorial libraries by introducing mutations into the capsid, aiming to boost their effectiveness. The emergence of high-throughput experimental techniques, like Deep Mutational Scanning (DMS), has made it feasible to experimentally assess the fitness of these libraries for their intended purpose. Notably, machine learning is starting to demonstrate its potential in addressing predictions within the mutational landscape from sequence data. In this context, we introduce a biophysically-inspired model designed to predict the viability of genetic variants in DMS experiments. This model is tailored to a specific segment of the CAP region within AAV2s capsid protein. To evaluate its effectiveness, we conduct model training with diverse datasets, each tailored to explore different aspects of the mutational landscape influenced by the selection process. Our assessment of the biophysical model centers on two primary objectives: (i) providing quantitative forecasts for the log-selectivity of variants and (ii) deploying it as a binary classifier to categorize sequences into viable and non-viable classes.

biophysics↗

bioRxiv2023

Assessing mechanical agency during apical apoptotic cell extrusion

Epithelial tissues maintain homeostasis through the continual addition and removal of cells. Homeostasis is necessary for epithelia to maintain barrier function and prevent the accumulation of defective cells. Unfit, excess, and dying cells can be removed from epithelia by the process of extrusion. Controlled cell death and extrusion in the epithelium of the larval zebrafish tail fin coincides with oscillation of cell area, both in the extruding cell and its neighbors. Both cell-autonomous and non-autonomous factors have been proposed to contribute to extrusion but have been challenging to test by experimental approaches. Here we develop a dynamic cell-based biophysical model that recapitulates the process of oscillatory cell extrusion to test and compare the relative contributions of these factors. Our model incorporates the mechanical properties of individual epithelial cells in a two-dimensional simulation as repelling active particles. The area of cells destined to extrude oscillates with varying durations or amplitudes, decreasing their mechanical contribution to the epithelium and surrendering their space to surrounding cells. Quantitative variations in cell shape and size during extrusion are visualized by a hybrid weighted Voronoi tessellation technique that renders individual cell mechanical properties directly into an epithelial sheet. To explore the role of autonomous and non-autonomous mechanics, we vary the biophysical properties and behaviors of extruding cells and neighbors such as the period and amplitude of repulsive forces, cell density, and tissue viscosity. Our data suggest that cell autonomous processes are major contributors to the dynamics of extrusion, with the mechanical microenvironment providing a less pronounced contribution. Our computational model based on in vivo data serves as a tool to provide insights into the cellular dynamics and localized changes in mechanics that promote elimination of unwanted cells from epithelia during homeostatic tissue maintenance.

biophysics↗

bioRxiv2023

Estimation of the mass density of biological matter from refractive index measurements

The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms by utilizing models that explicitly depend on physical observables. One of the basic biophysical properties is the mass density (MD), which determines the degree of crowdedness. It impacts the dynamics in sub-cellular compartments and further plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for a priori and a posteriori assumptions about the biochemical composition of the sample as well as respective RI measurements. To that aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations as well as Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well characterized complex mixtures given by bovine milk and intralipid emulsion. Further, we employ it to estimate the mass density of trunk tissue of living zebrafish (Danio rerio) larvae. Our results enable quantifying changes of mass density estimates based on variations in the a priori assumptions. This illustrates the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.

biophysics↗

bioRxiv2023

Phosphorylation regulates tau's phase separation behavior and interactions with chromatin

Tau is a microtubule-associated protein often found in neurofibrillary tangles (NFTs) in the brains of patients with Alzheimers disease (AD). Beyond this context, mounting evidence suggests that tau localizes into the nucleus, where it may play a role in DNA protection and heterochromatin regulation. Models of tau depletion or pathology show loss of genetically silent heterochromatin, aberrant expression of heterochromatic genes, and transposable element activation. The molecular mechanisms behind these observations are currently unclear. Using in vitro biophysical experiments, here we demonstrate that tau can undergo liquid-liquid phase separation (LLPS) with DNA, mononucleosomes, and reconstituted nucleosome arrays under low salt conditions. Low concentrations of tau promote chromatin compaction and protect DNA from digestion. While the material state of samples at physiological salt is dominated by chromatin oligomerization, tau can still associate strongly and reversibly with nucleosome arrays. These properties are driven by taus strong interactions with linker and nucleosomal DNA, while magic angle spinning (MAS) solid-state NMR experiments show that tau binding does not drastically alter nucleosome structure and dynamics. In addition, tau co-localizes into droplets formed by nucleosome arrays and phosphorylated HP1, a key heterochromatin constituent thought to function through an LLPS mechanism. Importantly, LLPS and chromatin interactions are disrupted by aberrant tau hyperphosphorylation. These biophysical properties suggest that tau may directly impact DNA and chromatin accessibility and that loss of these interactions could contribute to the aberrant nuclear effects seen in tau pathology.

biophysics↗

bioRxiv2024

SAXS/MC studies of the mixed-folded protein Cdt1 reveal monomeric, folded over conformations

Cdt1 is a protein critical for DNA replication licensing and is well-established to be a binding partner of the minichromosome maintenance (MCM) complex. Cdt1 has also been demonstrated to have an emerging, "moonlighting" role at the kinetochore via direct binding to microtubules and to the Ndc80 complex. However, it is not known how the structure and conformations of Cdt1 could allow for these multiple, completely unique sets of protein complexes. And while there exist multiple robust methods to study entirely folded or entirely unfolded proteins, structure-function studies of combined, mixed folded/disordered proteins remain challenging. It this work, we employ multiple orthogonal biophysical and computational techniques to provide a detailed structural characterization of human Cdt1 92-546. DSF and DSCD show both folded winged helix (WH) domains of Cdt1 are relatively unstable. CD and NMR show the N-terminal and the linker regions are intrinsically disordered. Using DLS and SEC-MALS, we show that Cdt1 is polydisperse, monomeric at high concentrations, and without any apparent inter-molecular self-association. SEC-SAXS of the monomer in solution enabled computational modeling of the protein in silico. Using the program SASSIE, we performed rigid body Monte Carlo simulations to generate a conformational ensemble. Using experimental SAXS data, we filtered for conformations which did and did not fit our data. We observe that neither fully extended nor extremely compact Cdt1 conformations are consistent with our SAXS data. The best fit models have the N-terminal and linker regions extended into solution and the two folded domains close to each other in apparent "folded over" conformations. The best fit Cdt1 conformations are consistent with a function as a scaffold protein which may be sterically blocked without the presence of binding partners. Our studies also provide a template for combining experimental and computational biophysical techniques to study mixed-folded proteins.

biophysics↗

bioRxiv2024

Photo-crosslinking hERG channels causes a U.V.-driven, state-dependent disruption of kinetics and voltage dependence of activation

Human ether-a-go-go related gene (hERG) voltage-activated potassium channels are critical for cardiac excitability. Characteristic slow closing (deactivation) in hERG is regulated by direct interaction between the N-terminal Per-Arnt-Sim (PAS) domain and the C-terminal cyclic nucleotide binding homology domain (CNBHD). We aim to understand how the PAS domain that is distal to the pore rearranges during gating to allosterically regulate the channel pore (and ion flux). To achieve this, we utilized the non-canonical amino acid 4-Benzoyl-L-phenylalanine (BZF) which is a photo-activatable cross-linkable probe, that when irradiated with ultraviolet (U.V.) light forms a double radical capable of forming covalent cross-links with C-H bond-containing groups, enabling selective and potent U.V.-driven photoinactivation of ion channel dynamics. Here we incorporate BZF directly into the hERG potassium channel PAS domain at three locations (G47, F48, and E50) using TAG codon suppression technology. hERG channels with BZF incorporated into the PAS domain (hERG-BZF) showed a significant change in the biophysical properties of the channel. hERG-G47BZF activated slowly when irradiated in the closed state (-100mV) but deactivated quickly when irradiated in both the open (0mV) and closed state. hERG-F48BZF channels showed a state independent and U.V. dose-dependent change in channel activation (slowing down) and channel deactivation (speeding up), as well as a marked change (right-shift) in the voltage-dependence of conductance. When irradiated at -100 mV hERG-E50BZF showed a state dependent and U.V. dose-dependent change in a channel activation (slowing down) and deactivation (speeding up) of channel deactivation, as well as a marked change (right-shift) in the voltage-dependence of conductance that occurred only when the channel was irradiated in the closed state (-100mV). This approach demonstrated that direct photo-crosslinking of the PAS domain in hERG channels causes a measurable change in biophysical parameters and more broadly stabilized the closed state of the channel. We propose that altered channel gating is as a direct result of reduced dynamic motions in the PAS domain of hERG due to photo-chemical crosslinking.

biophysics↗

bioRxiv2024

Engineering CRBN for rapid identification of next generation binders

The majority of clinical degrader candidates utilize an immunomodulatory imide drug (IMiD)-based derivative, that directs their target substrate to the E3 ligase receptor Cereblon (CRBN), however, concomitant neo-substrate degradation by IMiDs often results in severe off-target effects. Further biophysical screening is needed to discover CRBN binders that might overcome these safety concerns, but the previously reported CRBN protein constructs suffer significant limitations that reduce their applicability as tools for biophysical assays making large-scale screening efforts a costly endeavor. This is due to the requirement of CRBN co-expression with DDB1 in insect cells to produce soluble protein that contains all the reported structural features necessary for proper compound interaction. Here, a near full-length human CRBN construct was designed that retains these required features, but for the first time allows the generation of highly homogenous and cost-efficient expression in E.coli, eliminating the need for DDB1 co-expression. We have extensively profiled the new construct against the existing CRBN constructs in binary and ternary degrader complexes, showing it to be the "best of both worlds" in terms of binding characteristics and ease of protein production. We then designed the Enamine CRBN focused IMiD library of 4480-compounds and demonstrated applicability of the new construct to high throughput screening by identifying novel CRBN binders with high potency and ligand efficiency. The new methods described here should serve as valuable tools for the development of the next generation IMiD-based degraders.

biophysics↗

bioRxiv2024

Different fluorescent labels report distinct components of spHCN channel voltage sensor movement

Voltage clamp fluorometry was used to probe the S4 helix movement in the voltage sensing domain of the sea urchin HCN channel expressed in Xenopus oocytes. Markedly different fluorescence responses were obtained with either ALEXA-488 or MTS-TAMRA covalently linked to Cys332 at the N-terminal end of S4. With hyperpolarizing steps, ALEXA-488 fluorescence increased rapidly showing characteristics consistent with it reporting the initial inward movement of S4 in agreement with previous studies. In contrast, MTS-TAMRA fluorescence was slower and correlated with the early phase of channel opening. In addition, a slow fluorescence component was resolved with both labels that tracked the development of the mode shift or channel hysteresis. This was quantitated as an increased deactivation tail current delay with concomitantly longer activation periods and was found to depend strongly on the presence of K+ ions in the pore. This indicated that the microenvironment of the fluorescent probes attached to Cys332 was strongly influenced by conformational changes in the pore domain. Collisional quenching experiments established that ALEXA-488 was more exposed to solvent than MTS-TAMRA. This was supported by structural predictions based on homology modelling of spHCN in the closed and open conformations with covalently linked fluorophores. This study demonstrates that components of S4 movement during channel activation can be kinetically resolved using different fluorescent probes to reveal three distinct biophysical properties: voltage-sensor movement, early channel opening and mode-shift. These data support the use of different labelling probes to interrogate distinct biophysical aspects of voltage-gated membrane proteins. SummaryVoltage clamp fluorometry was used to probe the S4 helix movement in the voltage sensing domain of the spHCN channel expressed in Xenopus oocytes, labeled with either ALEXA-488 or MTS-TAMRA. Each fluorophore reported different components of S4 movement.

biophysics↗

bioRxiv2024

Deciphering the molecular mechanism of DNA-protein interactive co-condensates

Nucleic acid and protein co-condensates exhibit diverse morphologies crucial for fundamental cellular processes. Despite their significance, the molecular mechanisms governing morphology transitions remain poorly understood. To address this gap in knowledge, we investigated DNA and the human transcription factor p53 as a model system, specifically focusing on DNA-protein interactive co-condensates (DPICs)--a scenario where neither dsDNA nor the protein demonstrates phase-separation behavior individually. Through a combination of experimental assays and theoretical approaches, we elucidated: (i) the phase diagram of DPICs, identifying two distinct transition phenomena--a phase transition between viscoelastic fluid and viscoelastic solid states, and a morphology transition from droplet-like to "pearl chain"-like DPICs; (ii) the growth dynamics of DPICs. Droplet-like and "pearl chain"-like DPICs, although with dramatically distinct final morphologies and material properties, share a common initial critical microscopic cluster (CMC) size at the nanometer scale during the early stage of phase separation. These findings provide novel insights into the biophysical mechanisms underlying multi-component phase separations within cellular environments. Significance StatementNucleic acids and proteins have the capacity to form co-condensates, exhibiting various morphologies, including droplet-like and "pearl chains" formations. Despite this observation, the underlying biophysical mechanisms remain poorly understood. In this study, we employed DNA and the protein p53 as a model system. Our investigation revealed that the strength of the DNA-p53 interactions dictates the material properties of the co-condensates, leading to a transition from a viscoelastic fluid to a viscoelastic solid phase. This transition is accompanied by a morphological shift from droplet-like formations to structures resembling "pearl chains". Additionally, we explored the growth dynamics of these co-condensates and demonstrated that the strength of p53-DNA interactions influences the relaxation time of the co-condensates, thereby potentially determining their morphological features.

biophysics↗

bioRxiv2024

Lipid membrane topographies are regulators for the spatial distribution of liquid protein condensates

Liquid protein condensates play important roles in orchestrating subcellular organization and in serving as hubs for biochemical reactions. Recent studies have established associations between lipid membranes and proteins capable of forming liquid condensates, and shown that liquid protein condensates can remodel lipid membranes. However, little is known about how the topography of membranes affects liquid condensates. Here, we devised a cell-free system to reconstitute liquid condensates on lipid membranes with microstructured topographies and demonstrated an important role of lipid membranes topography as a biophysical regulator. By employing membrane surfaces designed with microwells, we found that liquid condensates assemble into orderly patterns. Furthermore, we demonstrated that membrane topographies influence the shape of liquid condensates. Finally, we showed that capillary forces, mediated by membrane topographies, led to the directed fusion of liquid condensates. Our results demonstrate that membrane topography is a potent biophysical regulator for the localization and shape of mesoscale liquid protein condensates.

biophysics↗

bioRxiv2024

Controlled Protein-Membrane Interactions Regulate Self-Organization of Min Protein Patterns

Self-organizing protein patterns play an essential role in life, governing important cellular processes, such as polarization and division. While the field of protein self-organization has reached a point where basic pattern-forming mechanisms can be reconstituted in vitro using purified proteins, understanding how cells can dynamically switch and modulate these patterns, especially when transiently needed, remains an interesting frontier. Here, we demonstrate the efficient regulation of self-organizing protein patterns through modulation of simple biophysical membrane parameters. Our investigation focusses on the impact of membrane affinity changes on Min protein patterns at lipid membranes composed of E. coli lipids or minimal lipid composition and we present three major results. First, we observed the emergence of a diverse array of pattern phenotypes, ranging from waves to snowflake-like structures. Second, we establish the dependency of these patterns on the density of protein-membrane linkers. Finally, we demonstrate the fine-tuning of snow-flake-like patterns by regulating membrane charge through lipid composition. Our results demonstrate the significant influence of membrane linkage as a straightforward biophysical parameter governing protein pattern formation. Our research points towards a simple yet intriguing mechanism by which cells can adeptly tune and switch protein patterns on the mesoscale.

biophysics↗

bioRxiv2024

Atomistic Tuning of the GeoCas9 Recognition Lobe Modulates Allosteric Motions and Guide RNA Interactions

The intuitive manipulation of specific amino acids to alter the activity or specificity of CRISPR-Cas9 has been a topic of great interest. As a large multi-domain RNA-guided endonuclease, the intricate molecular crosstalk within the Cas9 protein hinges on its conformational dynamics, but a comprehensive understanding of the extent and timescale of the motions that drive its allosteric function and association with nucleic acids remains elusive. Here, we investigated the structure and multi-timescale molecular motions of the recognition (Rec) lobe of GeoCas9, a thermophilic Cas9 from Geobacillus stearothermophilus. Our results provide new atomic details about the GeoRec subdomains (GeoRec1, GeoRec2) and the full-length domain in solution. Two rationally designed mutants, K267E and R332A, enhanced and redistributed micro-millisecond flexibility throughout GeoRec, and NMR studies of the interaction between GeoRec and its guide RNA showed that mutations reduced this affinity and the stability of the ribonucleoprotein complex. Despite measured biophysical differences due to the mutations, DNA cleavage assays reveal no functional differences in on-target activity, and similar specificity. These data suggest that guide RNA interactions can be tuned at the biophysical level in the absence of major functional losses but also raise questions about the underlying mechanism of GeoCas9, since analogous single-point mutations have significantly impacted on- and off-target DNA editing in mesophilic S. pyogenes Cas9. A K267E/R332A double mutant did also did not enhance GeoCas9 specificity, highlighting the robust tolerance of mutations to the Rec lobe of GeoCas9 and species-dependent complexity of Rec across Cas9 paralogs. Ultimately, this work provides an avenue by which to modulate the structure, motion, and guide RNA interactions at the level of the Rec lobe of GeoCas9, setting the stage for future studies of GeoCas9 variants and their effect on its allosteric mechanism.

biophysics↗