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bioRxiv2020

Semi-analytical dynamic modeling of DNA surface-hybridization via AC Electro-kinetic steering

The change in electrical property (capacitance) upon hybridization of the desired ssDNA to a capture probe has been proposed as a promising technology platform in biomedical research and practice. An appropriate mathematical model is needed for understanding and optimizing the process occurring at the electrode/electrolyte interface. It is also informative for examining the forces generated by the AC electric fields on the DNA molecules as well as the suspending buffer solution in the experimental pool. Here, we provide the development, formulation and validation of a semi-analytical model of DNA hybridization with deoxynucleotide molecules chemically tethered to a solid gold electrode. The parameters of the proposed model have been estimated using available experimental data. We demonstrate that the detection limit and specificity of our surface-based genosensor are not only dependent on the probe/target binding affinity, but also on the Self-Assembled Monolayer (SAM) density and on the interfacial electric field. The label-free Electrochemical Impedance Spectroscopy (EIS)-based oligonucleotide biosensor with integrated DC-biased can achieve rapid hybridization, high selectivity and sensitive detection for DNA target samples. SIGNIFICANCEDNA hybridization, wherein strands of DNA form duplex through noncovalent, sequence-specific interactions, is one of the most fundamental processes in biology. Fast and reliable determination of miniature amounts of DNA plays important role in clinical forensic and pharmaceutical applications. Thus, developing a better understanding of the kinetic and dynamic properties of DNA hybridization will help in the elucidation of all mechanisms involved in numerous biochemical processes. Moreover, because DNA hybridization has been widely adapted in biotechnology, its study is invaluable to the development of a range of commercially important processes. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the characteristics of the strands is crucial, and hence a computer aided numerical model for the design and optimization of a DNA biosensor has been implemented.

biophysics↗

bioRxiv2020

Modelling FtsZ nucleation, hydrolysis and treadmilling activity with Monte Carlo methods

Bacterial cell division is tightly coupled to the dynamic behavior of FtsZ, a tubulin homolog. Recent experimental work in vitro and in vivo has attributed FtsZs assembly dynamics to treadmilling, where subunits add to the bottom and dissociate from the top of protofilaments. However, the molecular mechanisms producing treadmilling have yet to be characterized and quantified. We have developed a Monte Carlo model for FtsZ assembly that explains treadmilling and assembly nucleation by the same mechanisms. A key element of the model is a conformational change from R (relaxed), which is highly favored for monomers, to T (tense), which is favored for subunits in a protofilament. This model was created in MATLAB. Kinetic parameters were converted to probabilities of execution during single, small time steps, and these were used to stochastically determine FtsZ dynamics. Our model is able to accurately describe the results of several in vitro and in vivo studies for a variety of FtsZ flavors. With standard conditions, the model FtsZ polymerized and produced protofilaments that treadmilled at 28 nm/s, hydrolyzed GTP at 2.8 to 4.2 GTP min-1 FtsZ-1, and had an average length of 25 to 54 subunits, all similar to experimental results. Adding a bottom capper resulted in shorter protofilaments and higher GTPase, similar to the effect of the known the bottom capper protein MciZ. The model could match nucleation kinetics of several flavors of FtsZ using the same parameters as treadmilling and varying only the R to T transition of monomers. SIGNIFICANCEFtsZ assembly dynamics are now known to be governed by treadmilling, where subunits add to the bottom and dissociate from the top of protofilaments. We have generated a Monte Carlo model of treadmilling based on (a) a conformational transition of FtsZ subunits between two states, and (b) stochastic GTP hydrolysis. Importantly, the nucleation of new protofilaments is explained by the same mechanisms as treadmilling. We have determined kinetic parameters that match a wide range of experimental data. The model is available to users for their own in silico experiments.

biophysics↗

bioRxiv2020

The role of replication-removal spatial correlations and cellular replicative lifespan in corneal epithelium homeostasis

Homeostasis in adult tissues relies on the replication dynamics of stem cells, their progenitors and the spatial balance between them. This spatial and kinetic coordination is crucial to the successful maintenance of tissue size and its replenishment with new cells. However, our understanding of the role of cellular replicative lifespan and spatial correlation between cells in shaping tissue integrity is still lacking. We developed a mathematical model for the stochastic spatial dynamics that underlie the rejuvenation of corneal epithelium. Our model takes into account different spatial correlations between cell replication and cell removal. We derive the tradeoffs between replicative lifespan, spatial correlation length, and tissue rejuvenation dynamics. We determine the conditions that allow homeostasis and are consistent with biological timescales, pattern formation, and mutants phenotypes. Our results can be extended to any cellular system in which spatial homeostasis is maintained through cell replication.

biophysics↗

bioRxiv2020

SRRF 'n' TIRF - FCS: Simultaneous spatiotemporal super-resolution microscopy

Super-resolution microscopy and single molecule fluorescence spectroscopy require mutually exclusive experimental strategies optimizing either time or spatial resolution. To achieve both, we implement a GPU-supported, camera-based measurement strategy that highly resolves spatial structures (~60 nm), temporal dynamics ([≤] 2 ms), and molecular brightness from the exact same data set. We demonstrate the applicability and advantages of multi-parametric measurements to monitor the super-resolved structure and dynamics of two different biomolecules, the actin binding polypeptide LifeAct, and the epidermal growth factor receptor (EGFR). Simultaneous super-resolution of spatial and temporal details leads to an improved precision in estimating the diffusion coefficient of LifeAct in dependence of the cellular actin network. Multi-parametric analysis suggests that the domain partitioning of EGFR is primarily determined by EGFR-membrane interactions, possibly sub-resolution clustering and inter-EGFR interactions but is largely independent of EGFR-actin interactions. These results demonstrate that pixel-wise cross-correlation of parameters obtained from different techniques on the same data set enables robust physicochemical parameter estimation and provides new biological knowledge that cannot be obtained from sequential measurements.

biophysics↗

bioRxiv2020

Model of ciprofloxacin subdiffusion in Pseudomonas aeruginosa biofilm formed in artificial sputum medium

We study theoretically and empirically ciprofioxacin antibiotic diffusion through a gel-like artificial sputum medium (ASM) mimicking physiological conditions typical for a cystic fibrosis layer, in which regions occupied by Pseudomonas aeruginosa bacteria are present. Our theoretical model is based on the subdiffusion-absorption equation with a fractional time derivative that describes molecules diffusion in a medium structured as Thompsons plumpudding model; the pudding background represents ASM and the plums represent the bacterial biofilm. We show that the process can be divided into three successive stages: (1) only antibiotic subdiffusion with constant biofilm parameters, (2) subdiffusion and absorption of antibiotic molecules with variable biofilm parameters, (3) subdiffusion and absorption in the medium but biofilm parameters are constant. Stage 2 is interpreted as the appearance of an intensive defence bulid-up of bacteria against the action of an antibiotic, in the stage 3 it is likely that the bacteria have been inactivated. Times at which stages change are determined from the experimentally obtained temporal evolution of the amount of substance that has diffused through the ASM with bacteria. Our analysis shows good agreement between experimental and our theoretical results.

biophysics↗

bioRxiv2020

Continuum theory of active phase separation in cellular aggregates

Dense cellular aggregates are common in many biological settings, ranging from bacterial biofilms to organoids, cell spheroids and tumors. Motivated by Neisseria gonorrhoeae biofilms as a model system, we present a hydrodynamic theory to study dense, active, viscoelastic cellular aggregates. The dynamics of these aggregates, driven by forces generated by individual cells, is intrinsically out-of-equilibrium. Starting from the force balance at the level of individual cells, we arrive at the dynamic equations for the macroscopic cell number density via a systematic coarse-graining procedure taking into account a nematic tensor of intracellular force dipoles. We describe the basic process of aggregate formation as an active phase separation phenomenon. Our theory furthermore captures how two cellular aggregates coalesce. Merging of aggregates is a complex process exhibiting several time scales and heterogeneous cell behaviors as observed in experiments. In our theory, it emerges as a coalescence of active viscoelastic droplets where the key timescales are linked to the turnover of the active force generation. Our theory provides a general framework to study the rheology and dynamics of dense cellular aggregates out of thermal equilibrium.

biophysics↗

bioRxiv2020

Myosin 1b Flattens and Prunes Branched Actin Filaments.

Motile and morphological cellular processes require a spatially and temporally coordinated branched actin network that is controlled by the activity of various regulatory proteins including the Arp2/3 complex, profilin, cofilin and tropomyosin. We have previously reported that myosin 1b regulates the density of the actin network in the growth cone. Using in vitro F-actin gliding assays and total internal reflection fluorescence (TIRF) microscopy we show in this report that this molecular motor flattens the Arp2/3-dependent actin branches up to breaking them and reduces the probability to form new branches. This experiment reveals that myosin 1b can produce force sufficient enough to break up the Arp2/3-mediated actin junction. Together with the former in vivo studies, this work emphasizes the essential role played by myosins in the architecture and in the dynamics of actin networks in different cellular regions. Short summaryUsing in vitro F-actin gliding assays and total internal reflection fluorescence (TIRF) microscopy we show that myosin flattens the Arp2/3-dependent actin branches up to breaking them and reduces the probability to form new branches

biophysics↗

bioRxiv2020

Widefield light sheet microscopy using an Airy beam combined with deep-learning super-resolution

Imaging across length scales and in depth has been an important pursuit of widefield optical imaging. This promises to reveal fine cellular detail within a widefield snapshot of a tissue sample. Current advances often sacrifice resolution through selective sub-sampling to provide a wide field of view in a reasonable time scale. We demonstrate a new avenue for recovering high-resolution images from sub-sampled data in light-sheet microscopy using deep-learning super-resolution. We combine this with the use of a widefield Airy beam to achieve high-resolution imaging over extended fields of view and depths. We characterise our method on fluorescent beads as test targets. We then demonstrate improvements in imaging amyloid plaques in a cleared brain from a mouse model of Alzheimers disease, and in excised healthy and cancerous colon and breast tissues. This development can be widely applied in all forms of light sheet microscopy to provide a two-fold increase in the dynamic range of the imaged length scale. It has the potential to provide further insight into neuroscience, developmental biology and histopathology.

biophysics↗

bioRxiv2020

Correlating single-molecule characteristics of the yeast aquaglyceroporin Fps1 with environmental perturbations directly in living cells

Membrane proteins play key roles at the interface between the cell and its environment by mediating selective import and export of molecules via plasma membrane channels. Despite a multitude of studies on transmembrane channels, understanding of their dynamics directly within living systems is limited. To address this, we correlated molecular scale information from living cells with real time changes to their microenvironment. We employed super-resolved millisecond fluorescence microscopy with a single-molecule sensitivity, to track labelled molecules of interest in real time. We use as example the aquaglyceroporin Fps1 in the yeast Saccharomyces cerevisiae to dissect and correlate its stoichiometry and molecular turnover kinetics with various extracellular conditions. In this way we shed new light on aspects of architecture and dynamics of glycerol-permeable plasma membrane channels.

biophysics↗

bioRxiv2020

Sequence-based Prediction of Metamorphic Behavior in Proteins

An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, where each fold is stabilized by a distinct local environment. So far, about 90 metamorphic proteins have been identified in the Protein Databank (PDB), but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic vs. monomorphic (i.e. having just one-fold). We constructed a reference dataset to train our classification method, which includes a novel compilation of 140 likely-monomorphic proteins, and a set of 201 metamorphic proteins taken from the literature. Our model is able to classify proteins as metamorphic vs. monomorphic with a Matthews correlation coefficient of [~]0.4 and true positive / true negative rates of [~]65% / 80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information. Statement of SignificanceThis paper introduces the diversity index as a descriptor to distinguish metamorphic proteins, which possess multiple stable folds, from monomorphic proteins that possess only one fold. The diversity index is designed to measure uncertainty in computationally predicted secondary structure, which we hypothesize is elevated for metamorphic proteins. We tested our hypothesis by training a binary classifier using the diversity index and an annotated dataset of metamorphic and monomorphic proteins, and found an optimal Matthews correlation coefficient of 0.4, supporting the hypothesis and demonstrating for the first time that it is possible to predict metamorphic behavior in proteins using only sequence information. The sequence-based classifier has broader applicability compared to methods that rely on making comparison to experimentally measured structures.

biophysics↗

bioRxiv2020

Non-Langmuir kinetics of DNA surface hybridization

Hybridization of complementary single strands of DNA represents a very effective natural molecular recognition process widely exploited for diagnostic, biotechnology and nanotechnology applications. A common approach relies on the immobilization on a surface of single stranded DNA probes that bind complementary targets in solution. However, despite the deep knowledge on DNA interactions in bulk solution, the modelling of the same interactions on a surface are still challenging and perceived as strongly system-dependent. Here we show that a two dimensional analysis of the kinetics of hybridization, performed at different target concentration and probe surface density by a label-free optical biosensor, reveals peculiar features inconsistent with an ideal Langmuir-like behaviour. We propose a simple non-Langmuir kinetic model accounting for an enhanced electrostatic repulsion originating from the surface immobilization of nucleic acids and for steric hindrance close to full hybridization of the surface probes. The analysis of the kinetic data by the model enables to quantify the repulsive potential at the surface, as well as to retrieve the kinetic parameters of isolated probes. We show that the strength and the kinetics of hybridization at large probe density can be improved by a 3D immobilization strategy of probe strands with a double stranded linker. Statement of SignificanceHybridization of nucleic acids strands with complementary sequences is a fundamental biological process and is also widely exploited for diagnostic purposes. Despite the availability of effective models for the equilibrium strength of freely diffusing strands, a general predictive model for surface hybridization is still missing. Moreover, the kinetics of hybridization is not fully understood neither in solution nor on a surface. In this work we show that the analysis of the kinetics of hybridization on a surface reveals and enables to quantify two main additional contributions: electrostatic repulsion and steric hindrance. These are general effects expected to occur not only on a surface but in any condition with large density of nucleic acids, comparable to that of the cellular nucleus.

biophysics↗

bioRxiv2020

Subphase Material Stabilizes Films of Pulmonary Surfactant

When compressed by the shrinking alveolar surface area during exhalation, films of pulmonary surfactant in situ reduce surface tension to levels, at which surfactant monolayers collapse from the surface in vitro. Vesicles of pulmonary surfactant added below these monolayers slow collapse. X-ray scattering here determined the structural changes that improve stability. Grazing incidence X-ray diffraction on monolayers of extracted calf surfactant detected an ordered phase. Mixtures of dipalmitoyl phosphatidylcholine and cholesterol, but not the phospholipid alone, mimic that structure. At concentrations that stabilize the monolayers, vesicles in the subphase had no effect on the unit cell, and the film remained monomolecular. The added vesicles, however, produced a concentration-dependent increase in the diffracted intensity. These results suggest that the enhanced resistance to collapse results from components of an ordered interfacial phase which partition from subphase to the surface, increasing the area of the ordered structure. SIGNIFICANCELow alveolar surface tensions are essential for maintaining the integrity of the pulmonary air-sacks during normal breathing. Films of pulmonary surfactant cause the low tensions. The interfacial structures required for the low surface tensions remain uncertain. These studies used X-ray scattering to determine the initial structure of pulmonary surfactant monolayers, and to establish how vesicles of pulmonary surfactant enhance the ability of those initial monolayers to sustain low tensions. The initial monolayers contained ordered structures that differ from the crystalline forms widely speculated to occur in alveolar films. The added vesicles had no effect on the local structure of the initial monolayer, but substantially increased the area of the ordered regions. This structural change reasonably explains the functional improvement.

biophysics↗

bioRxiv2020

Designing membrane-reshaping nanostructures through artificial evolution

In this paper we combine the rules of natural evolution with molecular dynamics simulations to design a nanostructure with a desired function. We apply this scheme to the case of a ligand-covered nanoparticle and evolve ligand patterns that promote efficient cell uptake. Surprisingly, we find that in the regime of low ligand number the fittest structures are characterised by ligands arranged into long one-dimensional chains that pattern the surface of the particle. We show that these chains of ligands provide particles with high rotational freedom and they lower the free energy barrier for membrane crossing. This demonstrates the efficacy of artificial evolution to identify non-intuitive design rules and reveals a new principle of design that can be used to inform artificial nanoparticle construction and the search for inhibitors of viral entry.

biophysics↗

bioRxiv2020

Fluorophore-labelled RNA aptamers to common protein tags as super-resolution imaging reagents.

Developing labelling methods that densely and specifically label targeted cellular structures is critically important for centroid localization-based super-resolution microscopy. Being easy and inexpensive to produce in the laboratory and of relatively small size, RNA aptamers have potential as a substitute for conventional antibody labelling. By using aptamers selected against common protein tags - GFP (green fluorescent protein) in this case - we demonstrate labelling methods using dSTORM-compatible fluorophores for STORM and hybridizable imager strands for DNA-PAINT super-resolution optical imaging of any cellular proteins fused to the aptamer binding target. We show that we can label both extracellular and intracellular proteins for super-resolution imaging, and that the method in particular, offers some interesting advantages for live cell super-resolution imaging of plasma membrane proteins. KEY POINTSO_LIA simple to use RNA aptamer method for super-resolution STORM and PAINT imaging in cells expressing common protein tags. C_LIO_LIThe method has a number of unique advantages for live cell imaging at the nanometer scale. C_LIO_LIProvides a means to quantify the number of proteins being trafficked on the plasma membrane. C_LI

biophysics↗

bioRxiv2020

Data-driven polymer model for mechanistic exploration of diploid genome organization

Chromosomes are positioned non-randomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome: it is data-driven as all parameters can be derived from Hi-C data; it is also a mechanistic model since the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific inter-chromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large scale rearrangements in genome structure upon cell differentiation and tumor progression.

biophysics↗

bioRxiv2020

Molecular goniometers for single-particle cryo-EM of DNA-binding proteins

Correct reconstruction of macromolecular structure by cryo-electron microscopy relies on accurate determination of the orientation of single-particle images. For small (<100 kDa) DNA-binding proteins, obtaining particle images with sufficiently asymmetric features to correctly guide alignment is challenging. DNA nanotechnology was conceived as a potential tool for building host nanostructures to prescribe the locations and orientations of docked proteins. We used DNA origami to construct molecular goniometers--instruments to precisely orient objects--to dock a DNA-binding protein on a double-helix stage that has user-programmable tilt and rotation angles. Each protein orientation maps to a distinct barcode pattern specifying particle classification and angle assignment. We used goniometers to obtain a 6.5 [A] structure of BurrH, an 82-kDa DNA-binding protein whose helical pseudosymmetry prevents accurate image orientation using classical cryo-EM. Our approach should be adaptable for other DNA-binding proteins, and a wide variety of other small proteins, by fusing DNA binding domains to them.

biophysics↗

bioRxiv2020

Structure-guided DNA-DNA attraction mediated by divalent cations

Probing the role of surface structure in electrostatic interactions, we report the first observation of sequence-dependent dsDNA condensation by divalent alkali cations. Disparate behaviors were found between two repeating sequences with 100% AT content, a poly(A)-poly(T) duplex (AA-TT) and a poly(AT)-poly(TA) duplex (AT-TA). While AT-TA exhibits non-distinguishable behaviors from random-sequence genomic DNA, AA-TT condenses in all divalent alkali ions (Mg2+, Ca2+, Sr2+, and Ba2+). We characterized these interactions experimentally and investigated the underlying principles using all-atom computer simulations. Both experiment and simulation demonstrate that AA-TT condensation is driven by nonspecific ion-DNA interactions, which depend on the structures of ions and DNA surface. Detailed analyses reveal sequence-enhanced major groove binding (SEGB) of point-charged alkali ions as the major difference between AA-TT and AT-TA, which originates from the continuous and close stacking of nucleobase partial charges in AA-TT but not in AT-TA. These SEGB cations elicit attraction via spatial correlations with the phosphate backbone of neighboring helices, reminiscent of the "DNA-zipper" model, which though assumes non-electrostatic cation groove binding a priori. Our study thus presents a distinct molecular mechanism of DNA-DNA interaction in which sequence-directed surface motifs act with abundant divalent alkali cations non-specifically to enact sequence-dependent behaviors. This physical insight allows a renewed understanding of the function of repeating DNA sequences in genome organization and regulation and offers a facile approach for DNA technology to control the assembly process of DNA nanostructures.

biophysics↗

bioRxiv2020

Two particle picking procedures for filamentous proteins: SPHIRE-crYOLO filament mode and SPHIRE-STRIPER

Structure determination of filamentous molecular complexes involves the selection of filaments from cryo-EM micrographs. The automatic selection of helical specimens is particularly difficult and thus many challenging samples with issues such as contamination or aggregation are still manually picked. Here we present two approaches for selecting filamentous complexes: one uses a trained deep neural network to identify the filaments and is integrated in SPHIRE-crYOLO, the other one, called SPHIRE-STRIPER, is based on a classical line detection approach. The advantage of the crYOLO based procedure is that it accurately performs on very challenging data sets and selects filaments with high accuracy. Although STRIPER is less precise, the user benefits from less intervention, since in contrast to crYOLO, STRIPER does not require training. We evaluate the performance of both procedures on tobacco mosaic virus and filamentous F-actin data sets to demonstrate the robustness of each method.

biophysics↗