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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

CRISPR Cas9 searches for a protospacer adjacent motif by one-dimensional diffusion

Since its discovery, the CRISPR/Cas9 system has been at the focus of fundamental researchers, genome engineers, and the general public alike. Despite being in the spotlight for several years, aspects of the precise molecular mechanism of Cas9 activity remain ambiguous. We use single-molecule Foerster resonance energy transfer (smFRET) to reveal Cas9 target search mechanism with nanometer sensitivity. We have developed single-molecule assays to monitor transient interactions of Cas9 and DNA in real time. Our study shows that Cas9 interacts with the protospacer adjacent motif (PAM) sequence weakly, yet probing neighboring sequences via lateral diffusion. This dynamic mode of interactions leads to translocation of Cas9 to another PAM nearby and consequently an on-target sequence. We propose a model in which lateral diffusion competes with 3-dimensional diffusion and thus might aid PAM finding and consequently on-target binding.

biophysics↗

bioRxiv2018

Multiplex single-molecule DNA barcoding using an oligonucleotide ligation assay

Detection of specific nucleic acid sequences is invaluable in biological studies such as genetic disease diagnostics and genome profiling. Here we developed a highly sensitive and specific detection method that combines an advanced oligonucleotide ligation assay (OLA) with multicolor single-molecule fluorescence. We demonstrated that 7-nt long DNA barcodes have the optimal short length to ascertain specificity while being long enough for sufficient ligation. Using four spectrally separated fluorophores to label DNA barcodes, we simultaneously distinguished four DNA target sequences differing by only a single nucleotide. Our new single-molecule approach will allow for accurate identification of low abundance molecules without the need for target DNA pre-amplification.

biophysics↗

bioRxiv2018

Measuring the self-assembly kinetics of individual viral capsids

The formation of a viral capsid-the highly--ordered protein shell that surrounds the genome of a virus--is the canonical example of self-assembly1. The capsids of many positive-sense RNA viruses spontaneously assemble from in vitro mixtures of the coat protein and RNA2. The high yield of proper capsids that assemble is remarkable, given their structural complexity: 180 identical proteins must arrange into three distinct local configurations to form an icosahedral capsid with a triangulation number of 3 (T = 3)1. Despite a wealth of data from structural studies3-5 and simulations6-10, even the most fundamental questions about how these structures assemble remain unresolved. Experiments have not determined whether the assembly pathway involves aggregation or nucleation, or how the RNA controls the process. Here we use interferometric scattering microscopy11,12 to directly observe the in vitro assembly kinetics of individual, unlabeled capsids of bacteriophage MS2. By measuring how many coat proteins bind to each of many individual MS2 RNA strands on time scales from 1 ms to 900 s, we find that the start of assembly is broadly distributed in time and is followed by a rapid increase in the number of bound proteins. These measurements provide strong evidence for a nucleation-and-growth pathway. We also find that malformed structures assemble when multiple nuclei appear on the same RNA before the first nucleus has finished growing. Our measurements reveal the complex assembly pathways for viral capsids around RNA in quantitative detail, including the nucleation threshold, nucleation time, growth time, and constraints on the critical nucleus size. These results may inform strategies for engineering synthetic capsids13 or for derailing the assembly of pathogenic viruses14.

biophysics↗

bioRxiv2018

MiLeSIM: combining super-resolution and machine learning permits high-throughput virus structure analysis

Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools in the investigation of the structure of supramolecular assemblies such as viruses. Here, we report on a new methodology which combines Structured Illumination Microscopy (SIM) with machine learning algorithms to image and classify the structure of large populations of biopharmaceutical viruses with high resolution. The method offers information on virus morphology that can ultimately be linked with functional performance. We demonstrate the approach on viruses produced for oncolytic viriotherapy (Newcastle Disease Virus) and vaccine development (Influenza). This unique tool enables the rapid assessment of the quality of viral production with high throughput obviating the need for traditional batch testing methods which are complex and time consuming. We show that our method also works on non-purified samples from pooled harvest fluids directly from the production line.

biophysics↗

bioRxiv2018

Quantifying configuration-sampling error in Langevin simulations of complex molecular systems

While Langevin integrators are popular in the study of equilibrium properties of complex systems, it is challenging to estimate the timestep-induced discretization error: the degree to which the sampled phase-space or configuration-space probability density departs from the desired target density due to the use of a finite integration timestep. In [1], Sivak et al. introduced a convenient approach to approximating a natural measure of error between the sampled density and the target equilibrium density, the KL divergence, in phase space, but did not specifically address the issue of configuration-space properties, which are much more commonly of interest in molecular simulations. Here, we introduce a variant of this near-equilibrium estimator capable of measuring the error in the configuration-space marginal density, validating it against a complex but exact nested Monte Carlo estimator to show that it reproduces the KL divergence with high fidelity. To illustrate its utility, we employ this new near-equilibrium estimator to assess a claim that a recently proposed Langevin integrator introduces extremely small configuration-space density errors up to the stability limit at no extra computational expense. Finally, we show how this approach to quantifying sampling bias can be applied to a wide variety of stochastic integrators by following a straightforward procedure to compute the appropriate shadow work, and describe how it can be extended to quantify the error in arbitrary marginal or conditional distributions of interest.

biophysics↗

bioRxiv2018

Binding of general anesthetics to ion channels

The direct-site hypothesis assumes general anesthetics bind ion channels to impact protein equilibrium and function, inducing anesthesia. Despite advancements in the field, a first-principle all-atom demonstration of this structure-function premise misses. We focus on clinically used sevoflurane interaction to anesthetic-sensitive Kv1.2 mammalian channel to resolve if sevoflurane binds the proteins well-characterized open and closed structures in a conformation-dependent manner to shift channel equilibrium. We employ an innovative approach relying on extensive docking calculations and free-energy perturbation and find sevoflurane binds open and closed structures at multiple sites under complex saturation and concentration effects. Results point to a non-trivial interplay of conformation-dependent modes of action involving distinct binding sites that increase channel open-probability at diluted ligand concentrations. Given the challenge in exploring more complex processes potentially impacting channel-anesthetic interaction, the result is reassuring as demonstrates that the process of multiple binding events alone may account for open-probability shifts recorded in measurements.

biophysics↗

bioRxiv2018

Constriction rate modulation can drive cell size control and homeostasis in C. crescentus

Rod-shaped bacteria typically grow first via sporadic and dispersed elongation along their lateral walls, then via a combination of zonal elongation and constriction at the division site to form the poles of daughter cells. Although constriction comprises up to half of the cell cycle, its impact on cell size control and homeostasis has rarely been considered. To reveal the roles of cell elongation and constriction in bacterial size regulation during cell division, we captured the shape dynamics of Caulobacter crescentus with time-lapse structured illumination microscopy and used molecular markers as cell-cycle landmarks. We perturbed constriction rate using a hyperconstriction mutant or fosfomycin inhibition. We report that constriction rate contributes to both size control and homeostasis, by determining elongation during constriction, and by compensating for variation in pre-constriction elongation on a single-cell basis.

biophysics↗

bioRxiv2018

DNA sequence context controls the binding and processivity of T7 DNA primase

Primases are key enzymes involved in DNA replication. They act on single-stranded DNA, and catalyze the synthesis of short RNA primers used by DNA polymerases. Here, we investigate the DNA-binding and activity of the bacteriophage T7 primase using a new workflow called High-Throughput Primase Profiling (HTPP). Using a unique combination of high-throughput binding assays and biochemical analyses, HTPP reveals a complex landscape of binding specificity and functional activity for the T7 primase, determined by sequences flanking the primase recognition site. We identified specific features, such as G/T-rich flanks, which increase primase-DNA binding up to 10-fold and, surprisingly, also increase the length of newly formed RNA (up to 3-fold). To our knowledge, variability in primer length has not been reported for this primase. We expect that applying HTPP to additional enzymes will reveal new insights into the effects of DNA sequence composition on the DNA recognition and functional activity of primases.

biophysics↗

bioRxiv2018

DeepLoco: Fast 3D Localization Microscopy Using Neural Networks

Single-molecule localization super-resolution microscopy (SMLM) techniques like STORM and PALM have transformed cellular microscopy by substantially increasing spatial resolution. In this paper we introduce a new algorithm for a critical part of the SMLM process: estimating the number and locations of the fluorophores in a single frame. Our algorithm can analyze a 20000-frame experimental 3D SMLM dataset in about one second -- substantially faster than real-time and existing algorithms. Our approach is straightforward but very different from existing algorithms: we train a neural network to minimize the Bayes risk under a generative model for single SMLM frames. The neural network maps a frame directly to a collection of fluorophore locations, which we compare to the ground truth using a novel loss function. While training the neural network takes several hours, it only has to be done once for a given experimental setup. After training, localizing fluorophores in new images is extremely fast -- orders of magnitude faster than existing algorithms. Faster recovery opens the door to real-time calibration and accelerated acquisition, and future work could tackle more complicated optical systems and more realistic simulators.

biophysics↗

bioRxiv2018

Collective motion conceals fitness differences in crowded cellular populations

Many cellular populations are tightly-packed, for example microbial colonies and biofilms [39, 10, 41], or tissues and tumors in multi-cellular organisms [11, 29]. Movement of one cell inside such crowded assemblages requires movement of others, so that cell displacements are correlated over many cell diameters [28, 6, 31]. Whenever movement is important for survival or growth [15, 34, 38, 9], such correlated rearrangements could couple the evolutionary fate of different lineages. Yet, little is known about the interplay between mechanical stresses and evolution in dense cellular populations. Here, by tracking deleterious mutations at the expanding edge of yeast colonies, we show that crowding-induced collective motion prevents costly mutations from being weeded out rapidly. Joint pushing by neighboring cells generates correlated movements that suppress the differential displacements required for selection to act. Such mechanical screening of fitness differences allows the mutants to leave more descendants than expected under non-mechanical models, thereby increasing their chance for evolutionary rescue [2, 5]. Our work suggests that mechanical interactions generally influence evolutionary outcomes in crowded cellular populations, which has to be considered when modeling drug resistance or cancer evolution [1, 22, 34, 30, 36, 42].

biophysics↗

bioRxiv2018

Cryo-EM structure of the adenosine A2A receptor coupled to an engineered heterotrimeric G protein

The adenosine A2A receptor (A2AR) is a prototypical G protein-coupled receptor (GPCR) that couples to the heterotrimeric G protein GS. Here we determine the structure by electron cryo-microscopy (cryo-EM) of A2AR at pH 7.5 bound to the small molecule agonist NECA and coupled to an engineered heterotrimeric G protein, which contains mini-GS, the {beta}{gamma} subunits and nanobody Nb35. Most regions of the complex have a resolution of ~3.8 [A] or better. Comparison with the 3.4 [A] resolution crystal structure shows that the receptor and mini-GS are virtually identical and that the density of the side chains and ligand are of comparable quality. However, the cryo-EM density map also indicates regions that are flexible in comparison to the crystal structures, which unexpectedly includes regions in the ligand binding pocket. In addition, an interaction between intracellular loop 1 of the receptor and the {beta} subunit of the G protein was observed.

biophysics↗

bioRxiv2018

Spatial moment description of birth-death-movementprocesses incorporating the effects of crowding andobstacles

Birth-death-movement processes, modulated by interactions between individuals, are fundamental to many cell biology processes. A key feature of the movement of cells within in vivo environments are the interactions between motile cells and stationary obstacles. Here we propose a multi-species model of individual-level motility, proliferation and death. This model is a spatial birth-death-movement stochastic process, a class of individual-based model (IBM) that is amenable to mathematical analysis. We present the IBM in a general multi-species framework, and then focus on the case of a population of motile, proliferative agents in an environment populated by stationary, non-proliferative obstacles. To analyse the IBM, we derive a system of spatial moment equations governing the evolution of the density of agents and the density of pairs of agents. This approach avoids making the usual mean-field assumption so that our models can be used to study the formation of spatial structure, such as clustering and aggregation, and to understand how spatial structure influences population-level outcomes. Overall the spatial moment model provides a reasonably accurate prediction of the system dynamics, including important effects such as how varying the properties of the obstacles leads to different spatial patterns in the population of agents.

biophysics↗

bioRxiv2018

High precision wavefront control in Point Spread Function engineering for single emitter localization

Point spread function (PSF) engineering is used in single emitter localization to measure the emitter position in 3D and possibly other parameters such as the emission color or dipole orientation as well. Advanced PSF models such as spline fits to experimental PSFs or the vectorial PSF model can be used in the corresponding localization algorithms in order to model the intricate spot shape and deformations correctly. The complexity of the optical architecture and fit model makes PSF engineering approaches particularly sensitive to optical aberrations. Here, we present a calibration and alignment protocol for fluorescence microscopes equipped with a spatial light modulator (SLM) with the goal of establishing a wavefront error well below the diffraction limit for optimum application of complex engineered PSFs. We achieve high-precision wavefront control, to a level below 20 m{lambda} wavefront aberration over a 30 minute time window after the calibration procedure, using a separate light path for calibrating the pixel-to-pixel variations of the SLM, and alignment of the SLM with respect to the optical axis and Fourier plane within 3 {micro}m (x/y) and 100 {micro}m (z) error. Aberrations are retrieved from a fit of the vectorial PSF model to a bead z-stack and compensated with a residual wavefront error comparable to the error of the SLM calibration step. This well-calibrated and corrected setup makes it possible to create complex 3D+{lambda} PSFs that fit very well to the vectorial PSF model. Proof-of-principle bead experiments show precisions below 10 nm in x, y, and{lambda} , and below 20 nm in z over an axial range of 1 {micro}m with 2000 signal photons and 12 background photons.

biophysics↗

bioRxiv2018

Live single molecule microscopy of HIV-1 assembly in host T cells reveals a spatio-temporal effect of the viral genome.

Monitoring virus assembly dynamic at the nanoscale level in host cells remains a major challenge. Human Immunodeficiency Virus type 1 (HIV-1) components are addressed to the plasma membrane where they assemble to form spherical particles of 100nm in diameter. HIV-1 Gag protein expression alone is sufficient to produce virus-like particles (VLPs) that resemble immature virus. Here, we monitored Gag assembly in host CD4 T lymphocytes using single molecule dynamics microscopy and energy mapping. A workflow allowing long time recordings of single Gag molecule localization, diffusion and effective energy maps was developed for robust quantitative analysis of HIV assembly and budding. Comparison of numerous cell plasma membrane assembling platforms in cells expressing wild type or assembly-defective Gag proteins showed that VLP formation last 15 minutes, with an assembly time of 5 minutes, and that the nucleocapsid domain is mandatory. Importantly, it reveals that the viral genome coordinates spatio-temporally HIV-1 assembly.

biophysics↗

bioRxiv2018

Efflux Pumps Represent Possible Evolutionary Convergence onto the Beta Barrel Fold

There are around 100 types of integral outer membrane proteins in each Gram negative bacteria. All of these proteins have the same fold--an up-down {beta}-barrel. It has been suggested that all membrane {beta}-barrels other than lysins are homologous. Here we suggest that {beta}-barrels of efflux pumps have converged on this fold as well. By grouping structurally-solved outer membrane {beta}-barrels (OMBBs) by sequence we find evidence that the membrane environment may have led to convergent evolution of the barrel fold. Specifically, the lack of sequence linkage to other barrels coupled with distinctive structural differences, such as differences in strand tilt and barrel radius, suggest that efflux pumps have evolutionarily converged on the barrel. Finally, we find a possible ancestor for the OMBB efflux pumps as they are related to periplasmic components of the same pumps.

biophysics↗

bioRxiv2018

Identification and Structure-Activity Relationship of HDAC6 Zinc-finger Ubiquitin Binding Domain Inhibitors

HDAC6 plays a central role in the recruitment of protein aggregates for lysosomal degradation, and is a promising target for combination therapy with proteasome inhibitors in multiple myeloma. Pharmacologically displacing ubiquitin from the zinc-finger ubiquitin-binding domain (ZnF-UBD) of HDAC6 is an underexplored alternative to catalytic inhibition. Here, we present the discovery of a HDAC6 ZnF-UBD-focused chemical series and its progression from virtual screening hits to low micromolar inhibitors. A carboxylate mimicking the C-terminal extremity of ubiquitin, and an extended aromatic system stacking with W1182 and R1155 are necessary for activity. One of the compounds induced a conformational remodeling of the binding site where the primary binding pocket opens-up onto a ligand-able secondary pocket that may be exploited to increase potency. The preliminary structure-activity relationship accompanied by nine crystal structures should enable further optimization into a chemical probe to investigate the merit of targeting the ZnF-UBD of HDAC6 in multiple myeloma and other diseases.

biophysics↗

bioRxiv2018

Dissecting Conformational Changes in APP’s Transmembrane Domain Linked to Altered ε-Efficiency of Familial Alzheimer’s Disease Mutants

The mechanism by which familial Alzheimers disease (FAD) mutations within the transmembrane domain (TMD) of the Amyloid Precursor Protein (APP) affect [a]-endoproteolysis is only poorly understood. Thereby, mutations in the cleavage domain reduce [a]-efficiency of a-secretase cleavage and some even shift entry into production lines. Since cleavage occurs within the TMD, a relationship between processing and TMD structure and dynamics seems obvious. Using molecular dynamic simulations, we dissect the dynamic features of wild type and seven FAD-mutants into local and global components. Mutations consistently enhance hydrogen8 bond fluctuations upstream of the [a]-cleavage sites but maintain strong helicity there. Dynamic perturbation response scanning reveals that FAD-mutants target backbone motions utilized in the bound state. Those motions, obscured by large-scale motions in the pre-bound state, provide (i) a dynamic mechanism underlying the proposedcoupling between binding and [a]-cleavage, (ii) key sites consistent with experimentally determined docking sites, and (iii) the distinction between mutants and wild-type.

biophysics↗

bioRxiv2018

Information transfer in QT-RR dynamics: Towards a model-free QT correction method

The relation between the electrical properties of the heart and the beating rate is essential for the heart functioning. This relation is central when calculating the \"corrected QT interval\" -- an important measure of the risk of potentially lethal arrhythmias. We use the transfer entropy method from information theory to quantitatively study the mutual dynamics of the ventricular action potential duration (the QT interval) and the length of the beat-to-beat (RR) interval. We show that for healthy individuals there is a strong asymmetry in the information transfer: the information flow from RR to QT dominates over the opposite flow (from QT to RR), i.e. QT depends on RR to a larger extent than RR on QT. Moreover, the history of the intervals has a strong effect on the information transfer: at sufficiently long QT history length the information flow asymmetry inverts and the RR influence on QT dynamics weakens. Finally, we demonstrate that the widely used QT correction methods cannot properly capture the changes in the information flows between QT and RR. We conclude that our results obtained through a model-free informational perspective can be utilised to improve and test the QT correction schemes in clinics.

biophysics↗