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We present a method to simulate ultrafast pump-probe time-resolved circular dichroism (TRCD) spectra based on time-dependent density functional theory trajectory surface hopping. The method is applied to simulate the TRCD spectrum along the photoinduced ring-opening of provitamin D. Simulations reveal that the initial decay of the signal is due to excited state relaxation, forming the rotationally flexible previtamin D. We further show that oscillations in the experimental TRCD spectrum arise from isomerizations between previtamin D rotamers with different chirality, which are associated with the helical conformation of the triene unit. We give a detailed description of the formation dynamics of different rotamers, playing a key role in the natural regulation vitamin D photosynthesis. Going beyond the sole extraction of decay rates, simulations greatly increase the amount of information that can be retrieved from ultrafast TRCD, making it a sensitive tool to unravel details in the sub-picosecond dynamics of photoinduced chirality changes.

Endocytosis is a key cellular process involved in the uptake of nutrients, pathogens or the diagnosis and therapy of diseases. Most studies have focused on spherical objects, whereas biologically relevant shapes can be highly anisotropic. In this letter, we use an experimental model system based on Giant Unilamellar Vesicles (GUVs) and dumbbell-shaped colloidal particles to mimic and investigate the first stage of the passive endocytic process: engulfment of an anisotropic object by the membrane. Our model has specific ligand-receptor interactions realized by mobile receptors on the vesicles and immobile ligands on the particles. Through a series of experiments, theory and molecular dynamics simulations, we quantify the wrapping process of anisotropic dumbbells by GUVs and identify distinct stages of the wrapping pathway. We find that the strong curvature variation in the neck of the dumbbell as well as membrane tension are crucial in determining both the speed of wrapping and the final states.

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning CG force-fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force-field on average. We show that there is flexibility in how to map all-atom forces to the CG representation, and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force-fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins Chignolin and Tryptophan Cage and published as open-source code., Comment: 44 pages, 19 figures

The Posner molecule (calcium phosphate trimer), has been hypothesized to function as a biological quantum information processor due to its supposedly long-lived entangled $^{31}$P nuclear spin states. This hypothesis was challenged by our recent finding that the molecule lacks a well-defined rotational axis of symmetry -- an essential assumption in the proposal for Posner-mediated neural processing -- and exists as an asymmetric dynamical ensemble. Following up, we investigate here the spin dynamics of the molecule's entangled $^{31}$P nuclear spins within the asymmetric ensemble. Our simulations show that entanglement between two nuclear spins prepared in a Bell state in separate Posner molecules decays on a sub-second timescale -- much faster than previously hypothesized, and not long enough for super-cellular neuronal processing. Calcium phosphate dimers however, are found to be surprisingly resilient to decoherence and are able to preserve entangled nuclear spins for hundreds of seconds, suggesting that neural processing might occur through them instead.

Coarse-grained (CG) molecular simulations have become a standard tool to study molecular processes on time- and length-scales inaccessible to all-atom simulations. Parameterizing CG force fields to match all-atom simulations has mainly relied on force-matching or relative entropy minimization, which require many samples from costly simulations with all-atom or CG resolutions, respectively. Here we present flow-matching, a new training method for CG force fields that combines the advantages of both methods by leveraging normalizing flows, a generative deep learning method. Flow-matching first trains a normalizing flow to represent the CG probability density, which is equivalent to minimizing the relative entropy without requiring iterative CG simulations. Subsequently, the flow generates samples and forces according to the learned distribution in order to train the desired CG free energy model via force matching. Even without requiring forces from the all-atom simulations, flow-matching outperforms classical force-matching by an order of magnitude in terms of data efficiency, and produces CG models that can capture the folding and unfolding transitions of small proteins.

Simultaneous identification and metabolic analysis of microbes with single-cell resolution and high throughput is necessary to answer the question of "who eats what, when, and where" in complex microbial communities. Here, we present a mid-infrared photothermal-fluorescence in situ hybridization (MIP-FISH) platform that enables direct bridging of genotype and phenotype. Through multiple improvements of MIP imaging, the sensitive detection of isotopically-labelled compounds incorporated into proteins of individual bacterial cells became possible, while simultaneous detection of FISH labelling with rRNA-targeted probes enabled the identification of the analyzed cells. In proof-of-concept experiments, we showed that the clear spectral red shift in the protein amide I region due to incorporation of $^{13}$C atoms originating from $^{13}$C-labelled-glucose can be exploited by MIP-FISH to discriminate and identify $^{13}$C-labelled bacterial cells within a complex human gut microbiome sample. The presented methods open new opportunities for single-cell structure-function analyses for microbiology.

Biofilms pose significant problems for engineers in diverse fields, such as marine science, bioenergy, and biomedicine, where effective biofilm control is a long-term goal. The adhesion and surface mechanics of biofilms play crucial roles in generating and removing biofilm. Designing customized nanosurfaces with different surface topologies can alter the adhesive properties to remove biofilms more easily and greatly improve long-term biofilm control. To rapidly design such topologies, we employ individual-based modeling and Bayesian optimization to automate the design process and generate different active surfaces for effective biofilm removal. Our framework successfully generated optimized functional nanosurfaces for improved biofilm removal through applied shear and vibration. Densely distributed short pillar topography is the optimal geometry to prevent biofilm formation. Under fluidic shearing, the optimal topography is to sparsely distribute tall, slim, pillar-like structures. When subjected to either vertical or lateral vibrations, thick trapezoidal cones are found to be optimal. Optimizing the vibrational loading indicates a small vibration magnitude with relatively low frequencies is more efficient in removing biofilm. Our results provide insights into various engineering fields that require surface-mediated biofilm control. Our framework can also be applied to more general materials design and optimization.

Anaerobic processes (e.g., methanogenesis and fermentation) largely contribute to element cycling and natural contaminant attenuation/mobilization, even in well-oxygenated porous environments, such as shallow aquifers. This paradox is commonly explained by the occurrence of small-scale anoxic microenvironments generated by the coupling of bacterial respiration and the heterogeneous oxygen (O2) transport by porewater. Such microenvironments allow facultatively and obligately anaerobic bacteria to proliferate in oxic environments. Microenvironment dynamics are still poorly understood due to the challenge of directly observing biomass and O2 distributions at the microscale within an opaque sediment and soil matrix. To overcome these limitations, we integrated a microfluidic device with transparent O2 planar optical sensors to measure the temporal behavior of dissolved O2 concentrations and biomass distributions with time-lapse video-microscopy. Our results reveal that bacterial colony morphology, which is highly variable in flowing porous systems, controls the formation of anoxic microenvironments. We rationalize our observations through a colony-scale Damkohler number comparing dissolved O2 diffusion and bacterial O2 uptake rate. Our Damkholer number enables predicting the pore space occupied by anoxic microenvironments in our system, and, given the bacterial organization, it can be applied to 3D porous systems., Comment: 29 pages + 19 pages (Supp Mat), 6 figures + 11 figures (Supp Mat)

In molecular dynamics simulations in the NPT ensemble at constant pressure, the size and shape of the periodic simulation box fluctuate with time. For particle images far from the origin, the rescaling of the box by the barostat results in unbounded position displacements. Special care is thus required when a particle trajectory is unwrapped from a projection into the central box under periodic boundary conditions to a trajectory in full three-dimensional space, e.g., for the calculation of diffusion coefficients. Here, we review and compare different schemes in use for trajectory unwrapping. We also specify the corresponding rewrapping schemes to put an unwrapped trajectory back into the central box. On this basis, we then identify a scheme for the calculation of meaningful diffusion coefficients, which is a primary application of trajectory unwrapping. In this scheme, the wrapped and unwrapped trajectory are mutually consistent and their statistical properties are preserved. We conclude with advice on best practice for the consistent unwrapping of constant-pressure simulation trajectories and the calculation of accurate translational diffusion coefficients., 30 pages, 8 figures

Markov state models represent a popular means to interpret molecular dynamics trajectories in terms of memoryless transitions between metastable conformational states. To provide a mechanistic understanding of the considered biomolecular process, these states should reflect structurally distinct conformations and ensure a timescale separation between fast intrastate and slow interstate dynamics. Adopting the folding of villin headpiece (HP35) as a well-established model problem, here we discuss the selection of suitable input coordinates or `features', such as backbone dihedral angles and interresidue distances. We show that dihedral angles account accurately for the structure of the native energy basin of HP35, while the unfolded region of the free energy landscape and the folding process are best described by tertiary contacts of the protein. To construct a contact-based model, we consider various ways to define and select contact distances, and introduce a low-pass filtering of the feature trajectory as well as a correlation-based characterization of states. Relying on input data that faithfully account for the mechanistic origin of the studied process, the states of the resulting Markov model are clearly discriminated by the features, describe consistently the hierarchical structure of the free energy landscape, and$\unicode{0x2014}$as a consequence$\unicode{0x2014}$correctly reproduce the slow timescales of the process.

Dissociative electron attachment, that is, the cleavage of chemical bonds induced by low-energy electrons, is difficult to model with standard quantum-chemical methods because the involved anions are not bound but subject to autodetachment. We present here a new computational development for simulating the dynamics of temporary anions on complex-valued potential energy surfaces. The imaginary part of these surfaces describes electron loss, whereas the gradient of the real part represents the force on the nuclei. In our method, the forces are computed analytically based on Hartree-Fock theory with a complex absorbing potential. $Ab\ initio$ molecular dynamics simulations for the temporary anions of dinitrogen, ethylene, chloroethane, and the five mono- to tetrachlorinated ethylenes show qualitative agreement with experiments and offer mechanistic insights into dissociative electron attachments. The results also demonstrate how our method evenhandedly deals with molecules that may undergo dissociation upon electron attachment and those which only undergo autodetachment., Manuscript: 10 pages, 4 figures. Supplementary Material: 41 pages, 43 figures

Post-transcriptional modifications are crucial for RNA function and can affect its structure and dynamics. Force-field based classical molecular dynamics simulations are a fundamental tool to characterize biomolecular dynamics and their application to RNA is flourishing. Here we show that the set of force-field parameters for N$^6$-methyladenosine (m$^6$A) developed for the commonly used AMBER force field does not reproduce duplex denaturation experiments and, specifically, cannot be used to describe both paired and unpaired states. Then we use reweighting techniques to derive new parameters matching available experimental data. The resulting force field can be used to properly describe paired and unpaired m$^6$A in both syn and anti conformation, and thus opens the way to the use of molecular simulations to investigate the effects of N6 methylations on RNA structural dynamics., Supporting information available as ancillary material. Version to be submitted to journal

Protein corona formation and nanoparticle aggregation have been heavily discussed over the last years since the lack of fine-mapping of these two combined effects has hindered the targeted delivery evolution and the personalized nanomedicine development. We present a multi-technique approach that combines Dynamic Light and Small-Angle X-ray Scattering techniques with cryo-Transmission Electron Microscopy in a given fashion that efficiently distinguishes protein corona from aggregates formation. This methodology was tested using 25-nm model silica nanoparticles incubated with either model proteins or biologically relevant proteomes (such as fetal bovine serum and human plasma) in buffers of low and high ionic strengths to precisely tune particle-to-protein interactions. In this work, we were able to differentiate protein corona, small aggregates formation, and massive aggregation, as well as obtain fractal information of the aggregates reliably and straightforwardly. The strategy presented here can be expanded to other particle-to-protein mixtures and might be employed as a quality control platform for samples that undergo biological tests., 14 pages, 6 figures, accepted at ACS Applied Materials and Interfaces

Phase separation is as familiar as watching vinegar separating from oil in vinegrette. The observation that phase separation of proteins and nucleic acids is widespread in living cells has opened an entire field of research into the biological significance and the biophysical mechanisms of phase separation and protein condensation in biology. Recent evidence indicate that certain proteins and nucleic acids condensates are not simple liquids and instead display both viscous and elastic behaviours, which in turn may have biological significance. The aim of this perspective is to review the state-of-the-art of this quickly emerging field focusing on the material and rheological properties of protein condensates. Finally, we discuss the different techniques that can be employed to quantify the viscoelasticity of condensates and highlight potential future directions and opportunities for interdisciplinary cross-talk between chemists, physicists and biologists., Comment: review paper; accepted in JACS Au

When examining dynamics occurring at non-zero temperatures, both energy and entropy must be taken into account while describing activated barrier crossing events. Furthermore, good reaction coordinates need to be constructed to describe different metastable states and the transition mechanisms between them. Here we use a physics-based machine learning method called the State Predictive Information Bottleneck (SPIB) to find non-linear reaction coordinates for three systems of varying complexity. The SPIB is able to predict correctly an entropic bottleneck for an analytical flat-energy double-well system and identify the entropy- and energy-dominated pathways for an analytical four-well system. Finally, for a simulation of benzoic acid permeation through a lipid bilayer, SPIB is able to discover the entropic and energetic barriers to the permeation process. Given these results, we thus establish that SPIB is a reasonable and robust method for finding the important entropy and energy/enthalpy barriers in physical systems, which can then be used for enhanced understanding and sampling of different activated mechanisms.

Bacterial cellulose biofilms are complex networks of strong interwoven nanofibers that control transport and protect bacterial colonies in the film. The design of diverse applications of these bacterial cellulose films also relies on understanding and controlling transport through the fiber mesh, and transport simulations of the films are most accurate when guided by experimental characterization of the structures and the resultant diffusion inside. Diffusion through such films is a function of their key microstructural length scales, determining how molecules, as well as particles and microorganisms, permeate them. We use microscopy to study the unique bacterial cellulose film via its pore structure and quantify the mobility dynamics of various sizes of tracer particles and macromolecules. Mobility is hindered within the films, as confinement and local movement strongly depend on the void size relative to diffusing tracers. The biofilms have a naturally periodic structure of alternating dense and porous layers of nanofiber mesh, and we tune the magnitude of the spacing via fermentation conditions. Micron-sized particles can diffuse through the porous layers but cannot penetrate the dense layers. Tracer mobility in the porous layers is isotropic, indicating a largely random pore structure there. Molecular diffusion through the whole film is only slightly reduced by the structural tortuosity. Knowledge of transport variations within bacterial cellulose networks can be used to guide the design of symbiotic cultures in these structures and enhance their use in applications like biomedical implants, wound dressings, lab-grown meat, clothing textiles, and sensors.

The rigidity and flexibility of homologous psychrophilic(P), mesophilic(M) and thermophilic(T) proteins have been investigated at the global and local levels in terms of packing factor and atomic fluctuations obtained from B-factors. For comparison of atomic fluctuations, correction of errors by considering errors in B-factors from all sources in a consolidated manner and conversion of the fluctuations to the same temperature have been suggested and validated. Results indicate no differences in the global values like average packing factor among the three classes of protein homologs but at local levels there are differences. Comparison of homologous proteins triplets show that the average atomic fluctuations at a given temperature obey the order P>M>T. Packing factors and the atomic fluctuations are anti-correlated suggesting that altering the rigidity of the active site might be a potential strategy to make tailor made psychrophilic or thermophilic proteins from their mesophilic homologs., 34 pages, 9 figures

Molecular dynamics simulations are often used to provide feedback in the design workflow of DNA nanostructures. However, even with coarse-grained models, convergence of distributions from unbiased simulation is slow, limiting applications to equilibrium structural properties. Given the increasing interest in dynamic, reconfigurable, and deformable devices, methods that enable efficient quantification of large ranges of motion, conformational transitions, and mechanical deformation are critically needed. Metadynamics is an automated biasing technique that enables the rapid acquisition of molecular conformational distributions by flattening free energy landscapes. Here we leveraged this approach to sample the free energy landscapes of DNA nanostructures whose unbiased dynamics are non-ergodic, including bistable Holliday junctions and part of a bistable origami. Taking an origami compliant joint as a case study, we further demonstrate that metadynamics can predict the mechanical response of a full DNA origami device to an applied force, showing good agreement with experiments. Our results establish an efficient framework to study free energy landscapes and force response in DNA nanodevices, which could be applied for rapid feedback in iterative design workflows and generally facilitate the integration of simulation and experiments. Metadynamics will be particularly useful to guide the design of dynamic devices for nanorobotics, biosensing, or nanomanufacturing applications., 4 figures, 7 SI figures, 3 SI tables, 2 SI discussions, methods

We consider a generic representation problem of internal coordinates (bond lengths, valence angles, and dihedral angles) and their transformation to 3-dimensional Cartesian coordinates of a biomolecule. We show that the internal-to-Cartesian process relies on correctly predicting chemically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. This general problem has been solved with machine learning for proteins, but with appropriately formulated data is extensible to any type of chain biomolecule including RNA, DNA, and lipids. We show that the internal-to-Cartesian process relies on correctly predicting chemically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. We developed a machine learning algorithm, Int2Cart, to predict bond lengths and bond angles from backbone torsion angles and residue types of a protein, and allows reconstruction of protein structures better than using fixed bond lengths and bond angles, or a static library method that relies on backbone torsion angles and residue types on a single residue. The Int2Cart algorithm has been implemented as an individual python package at https://github.com/THGLab/int2cart.

We introduce a method for elucidating and modifying the functionality of systems dominated by rare events that relies on the semiautomated tuning of their underlying free energy surface. The proposed approach seeks to construct collective variables (CVs) that encode the essential information regarding the rare events of the system of interest. The appropriate CVs are identified using harmonic linear discriminant analysis (HLDA), a machine-learning-based method that is trained solely on data collected from short ordinary simulations in the relevant metastable states of the system. Utilizing the interpretable form of the resulting CVs, the critical interaction potentials that determine the system's rare transitions are identified and purposely modified to tailor the free energy surface in a manner that alters functionality as desired. The applicability of the method is illustrated in the context of three different systems, thereby demonstrating that thermodynamic and kinetic properties can be tractably modified with little to no prior knowledge or intuition.

We recently introduced [J. Chem. Phys. 152 2020, 204103] the nuclear-electronic all-particle density matrix renormalization group method (NEAP-DMRG) to solve the molecular Schr\"{o}dinger equation, based on a stochastically optimized orbital basis, without invoking the Born-Oppenheimer approximation. In this work, we combine the DMRG with nuclear-electronic Hartree-Fock (NEHF-DMRG), treating nuclei and electrons on the same footing. Inter- and intra-species correlations are described within the DMRG without truncating the excitation degree of the full configuration interaction wave function. We extend the concept of orbital entanglement and mutual information to nuclear-electronic wave functions and demonstrate that they are reliable metrics to detect strong correlation effects. We apply NEHF-DMRG to the HeHHe$^+$ molecular ion, to obtain accurate proton densities, ground-state total energies, and vibrational transition frequencies by comparison with state-of-the-art data obtained with grid-based approaches and modern configuration interaction methods. For HCN, we improve on the accuracy of the latter approaches with respect to both ground-state absolute energy and proton density which is a major challenge for multi-reference nuclear-electronic state-of-the-art methods., Comment: 55 pages, 8 figures, 5 tables

The pharmaceutical success of atorvastatin (ATV), a widely employed drug against the “bad” cholesterol (LDL) and cardiovascular diseases, traces back to its ability to scavenge free radicals. Unfortunately, information on its antioxidant properties is missing or unreliable. Here, we report detailed quantum chemical results for ATV and its ortho- and para-hydroxy metabolites (o-ATV, p-ATV) in the methanolic phase. They comprise global reactivity indices, bond order indices, and spin densities as well as all relevant enthalpies of reaction (bond dissociation BDE, ionization IP and electron attachment EA, proton detachment PDE and proton affinity PA, and electron transfer ETE). With these properties in hand, we can provide the first theoretical explanation of the experimental finding that, due to their free radical scavenging activity, ATV hydroxy metabolites rather than the parent ATV, have substantial inhibitory effect on LDL and the like. Surprisingly (because it is contrary to the most cases currently known), we unambiguously found that HAT (direct hydrogen atom transfer) rather than SPLET (sequential proton loss electron transfer) or SET-PT (stepwise electron transfer proton transfer) is the thermodynamically preferred pathway by which o-ATV and p-ATV in methanolic phase can scavenge DPPH• (1,1-diphenyl-2-picrylhydrazyl) radicals. From a quantum chemical perspective, the ATV’s species investigated are surprising because of the nontrivial correlations between bond dissociation energies, bond lengths, bond order indices and pertaining stretching frequencies, which do not fit the framework of naive chemical intuition.

Investigation of protein self-assembly processes is important for understanding the growth processes of functional proteins as well as disease-causing amyloids. Inside cells, intrinsic molecular fluctuations are so high that they cast doubt on the validity of the deterministic rate-equation approach. Furthermore, the protein environments inside cells are often crowded with other macromolecules, with volume fractions of the crowders as high as 40%. We have developed a stochastic kinetic framework using Gillespie's algorithm for general systems undergoing particle self-assembly, including particularly protein aggregation at the cellular level. The effects of macromolecular crowding are investigated using models built on scaled-particle and transition-state theories. The stochastic kinetic method can be formulated to provide information on the dominating aggregation mechanisms in a method called reaction frequency (or propensity) analysis. This method reveals that the change of scaling laws related to the lag time can be directly related to the change in the frequencies of reaction mechanisms. Further examination of the time evolution of the fibril mass and length quantities unveils that maximal fluctuations occur in the periods of rapid fibril growth and the fluctuations of both quantities can be sensitive functions of rate constants. The presence of crowders often amplifies the roles of primary and secondary nucleation and causes shifting in the relative importance of elongation, shrinking, fragmentation, and coagulation of linear aggregates. We also show a dual effect of changing volume on the halftime of aggregation for ApoC2 which is reduced in the presence of crowders. A comparison of the results of stochastic simulations with those of rate equations gives us information on the convergence relation between them and how the roles of reaction mechanisms change as the system volume is varied.

The photo-triggered unbinding of the intrinsically disordered S-peptide from the RNase S complex is studied with the help of transient IR spectroscopy, covering a wide range of time scales from 100 ps to 10 ms. To that end, an azobenzene moiety has been linked to the S-peptide in a way that its helicity is disrupted by light, thereby initiating its complete unbinding. The full sequence of events is observed, starting from unfolding of the helical structure of the S-peptide on a 20 ns timescale while still being in the binding pocket of the S-protein, S-peptide unbinding after 300 microseconds, and the structural response of the S-protein after 3 ms. With regard to the S-peptide dynamics, the binding mechanism can be classified as an induced fit, while the structural response of the S-protein is better described as conformational selection.

S-nitrosylation, the covalent addition of NO to the thiol side chain of cysteine, is an important post-transitional modification that can alter the function of various proteins. The structural dynamics and vibrational spectroscopy of S-nitrosylation in the condensed phase is investigated for the methyl-capped cysteine model system and for myoglobin. Using conventional point charge and physically more realistic multipolar force fields for the -SNO group it is found that the SN- and NO-stretch and the SNO-bend vibrations can be located and distinguished from the other protein modes for simulations of MbSNO at 50 K. The finding of stable cis- and trans-MbSNO is consistent with experiments on other proteins as is the observation of buried -SNO. For MbSNO the observed relocation of the EF loop in the simulations by $\sim 3$ \AA\/ is consistent with the available X-ray structure and the conformations adopted by the -SNO label are in good overall agreement with the X-ray structure. Despite the larger size of the -SNO group, MbSNO is found to recruit more water molecules within 10 \AA\/ of the modification site than WT Mb due to the stronger electrostatics. Similarly, when comparing the hydration between the A- and H-helices they differ by up to 30 \% between WT and MbSNO. This suggests that local hydration can also be significantly modulated through nitrosylation.

We present a new method for calculating internal forces in DNA structures using coarse-grained models and demonstrate its utility with the oxDNA model. The instantaneous forces on individual nucleotides are explored and related to model potentials, and using our framework, internal forces are calculated for two simple DNA systems and for a recently-published nanoscopic force clamp. Our results highlight some pitfalls associated with conventional methods for estimating internal forces, which are based on elastic polymer models, and emphasise the importance of carefully considering secondary structure and ionic conditions when modelling the elastic behaviour of single-stranded DNA. Beyond its relevance to the DNA nanotechnological community, we expect our approach to be broadly applicable to calculations of internal force in a variety of structures -- from DNA to protein -- and across other coarse-grained simulation models., 39 pages, 9 figures

Lanthanide-based upconversion nanoparticles (UCNPs) generally require high power laser excitation. Here, we report wide-field upconversion microscopy at single-nanoparticle sensitivity using incoherent excitation of a 970 nm light-emitting diode (LED). We show that due to its broad emission spectrum, LED excitation is about 3 times less effective for UCNPs and generates high background compared to laser illumination. To counter this, we use time-gated luminescence detection to eliminate the residual background from the LED source, so that individual UCNPs with high sensitizer (Yb3+) doping and inert shell protection become clearly identified under LED excitation at 1.18 W cm-2, as confirmed by correlated electron microscopy images. Hydrophilic UCNPs are obtained by polysaccharide coating via a facile ligand exchange protocol to demonstrate imaging of cellular uptake using LED excitation. These results suggest a viable approach to bypassing the limitations associated with high-power lasers when applying UCNPs and upconversion microscopy to life science research.

Cryopreservation is the only fully established procedure to extend the lifespan of living cells and tissues, a key to activities spanning from fundamental biology to clinical practice. Despite its prevalence and impact, central aspects of cryopreservation, such as the cell's physico-chemical environment during freezing, remain elusive. Here we address that question by coupling in situ microscopic directional freezing to visualize cells and their surroundings during freezing with the freezing medium phase diagram. We extract the freezing medium spatial distribution in cryopreservation, providing a tool to describe the cell vicinity at any point during freezing. We show that two major events define the cells' local environment over time: the interaction with the moving ice front and with the vitreous moving front - a term we introduce here. Our correlative strategy may be applied to cells relevant in clinical research and practice, and help designing new cryoprotective media based on local physico-chemical cues., 31 pages, 4 figures, 7 supplementary figures

Molecular transport of biomolecules plays a pivotal role in the machinery of life. Yet, this role is poorly understood due the lack of quantitative information. Here, the role and properties of the C-terminal region of Escherichia coli Hfq is reported, involved in controlling the flow of a DNA solution. A combination of experimental methodologies has been used to probe the interaction of Hfq with DNA and to measure the rheological properties of the complex. A physical gel with a temperature reversible elasticity modulus is formed due to formation of non-covalent crosslinks. The mechanical response of the complexes shows that they are inhomogeneous soft solids. Our experiments indicate that Hfq C-terminal region could contribute to genome mechanical response. The reported viscoelasticity of the DNA-protein complex might have implications for cellular pro-cesses involving molecular transport of DNA or segments thereof., Comment: 19 pages 5 figures 2 tables

We present a method to probe molecular and nanoparticle diffusion within thin, solvated polymer coatings. The device exploits the confinement with well-defined geometry that forms at the interface between a planar and a hemi-spherical surface (of which at least one is coated with polymers) in close contact, and uses this confinement to analyse diffusion processes without interference of exchange with and diffusion in the bulk solution. With this method, which we call plane-sphere confinement microscopy (PSCM), information regarding the partitioning of molecules between the polymer coating and the bulk liquid is also obtained. Thanks to the shape of the confined geometry, diffusion and partitioning can be mapped as a function of compression and concentration of the coating in a single experiment. The method is versatile and can be integrated with conventional optical microscopes, and thus should find widespread use in the many application areas exploiting functional polymer coatings. We demonstrate the use of PSCM using brushes of natively unfolded nucleoporin domains rich in phenylalanine-glycine repeats (FG domains). A meshwork of FG domains is known to be responsible for the selective transport of nuclear transport receptors (NTR) and their macromolecular cargos across the nuclear envelope that separates the cytosol and the nucleus of living cells. We find that the selectivity of NTR uptake by FG domain films depends sensitively on FG domain concentration, and that the interaction of NTRs with FG domains obstructs NTR movement only moderately. These observations contribute important information to better understand the mechanisms of selective NTR transport., 27 pages and 6 figures of main text, 12 pages and 8 figures of supporting information

Living systems at the molecular scale are composed of many constituents with strong and heterogeneous interactions, operating far from equilibrium, and subject to strong fluctuations. These conditions pose significant challenges to efficient, precise, and rapid free energy transduction, yet nature has evolved numerous molecular machines that do just this. Using a simple model of the ingenious rotary machine FoF1-ATP synthase, we investigate the interplay between nonequilibrium driving forces, thermal fluctuations, and interactions between strongly coupled subsystems. This model reveals design principles for effective free energy transduction. Most notably, while tight coupling is intuitively appealing, we find that output power is maximized at intermediate-strength coupling, which permits lubrication by stochastic fluctuations with only minimal slippage., 17 pages, 12 figures. J. Phys. Chem. Lett., 2020

SARS-CoV-2, since emerging in Wuhan, China, has been a major concern because of its high infection rate and has left more than six million infected people around the world. Many studies endeavored to reveal the structure of the SARS-CoV-2 compared to the SARS-CoV, in order to find solutions to suppress this high infection rate. Some of these studies showed that the mutations in the SARS-CoV spike (S) protein might be responsible for its higher affinity to the ACE2 human cell receptor. In this work, we used molecular dynamics simulations and Monte Carlo sampling to compare the binding affinities of the S proteins of SARS-CoV and SARS-CoV-2 to the ACE2. Our results show that the protein surface of the ACE2 at the receptor binding domain (RBD) exhibits negative electrostatic potential, while a positive potential is observed for the S proteins of SARS-CoV/SARS-CoV-2. In addition, the binding energies at the interface are slightly higher for SARS-CoV-2 because of enhanced electrostatic interactions. The major contributions to the electrostatic binding energies result from the salt bridges forming between R426 and ACE-2-E329 in the case of SARS-CoV and K417 and ACE2-D30 in the SARS-CoV-2. In addition, our results indicate that the enhancement in the binding energy is not due to a single mutant but rather because of the sophisticated structural changes induced by all these mutations together. This finding suggests that it is implausible for the SARS-CoV-2 to be a lab-engineered virus.

Due to large fluctuations in cellular environments, transfer of information in biological processes without regulation is inherently error-prone. The mechanistic details of error-reducing mechanisms in biological copying processes have been a subject of active research; however, how error reduction of a process is balanced with its thermodynamic cost and dynamical properties remain largely unexplored. Here, we study the error reducing strategies in light of the recently discovered thermodynamic uncertainty relation (TUR) that sets a physical bound to the cost-precision trade-off relevant in general dissipative processes. We found that the two representative copying processes, DNA replication by the exonuclease-deficient T7 DNA polymerase and mRNA translation by the \textit{E. coli} ribosome, reduce the error rates to biologically acceptable levels while also optimizing the processes close to the physical limit dictated by TUR., 20 pages, 14 figures, 3 Tables

Zero-mode waveguide (ZMW) nano-apertures milled in metal films were proposed to improve the Förster resonance energy transfer (FRET) efficiency and enable single-molecule FRET detection beyond the 10 nm barrier, overcoming the restrictions of diffraction-limited detection in a homogeneous medium. However, the earlier ZMW demonstrations were limited to the Atto 550–Atto 647N fluorophore pair, asking the question whether the FRET enhancement observation was an artifact related to this specific set of fluorescent dyes. Here, we use Alexa Fluor 546 and Alexa Fluor 647 to investigate single-molecule FRET at large donor–acceptor separations exceeding 10 nm inside ZMWs. These Alexa fluorescent dyes feature a markedly different chemical structure, surface charge, and hydrophobicity as compared to their Atto counterparts. Our single molecule data on Alexa 546–Alexa 647 demonstrate enhanced FRET efficiencies at large separations exceeding 10 nm, extending the spatial range available for FRET and confirming the earlier conclusions. By showing that the FRET enhancement inside a ZMW does not depend on the set of fluorescent dyes, this report is an important step to establish the relevance of ZMWs to extend the sensitivity and detection range of FRET, while preserving its ability to work on regular fluorescent dye pairs.

Silica-coated gold nanoparticles are commonly employed in biomedical photoacoustic (PA) imaging applications. We investigate theoretically and experimentally the PA signal generation by silica-coated gold nanospheres in water. Our theoretical model considers thermoelastic expansion in the long-pulse illumination regime, and the PA signals are determined based on a semi-analytical solution to the thermal diffusion equations and a finite-difference in time domain (FDTD) solution to the thermoelastic equations. Both the influence of interfacial thermal (Kapitza) resistance at the gold-water boundary and the influence of the silica coating on PA signal generation were investigated. Our results indicate that for the nanosecond pulses commonly employed in PA imaging, Kapitza resistance has a negligible effect on photoacoustic signal generation. Moreover, our model shows that the presence of a silica coating causes a reduction in the PA signal amplitude, with the level of signal reduction increasing with thicker silica coating. Our theoretical predictions are qualitatively consistent with our experimental results, where suspensions of in-house-synthesized and commercially available silica-coated gold nanosphere suspensions were excited with nanosecond-pulsed laser illumination at 532 nm. The PA signal amplitudes from silica-coated nanospheres were lower than the signal amplitudes for uncoated gold nanospheres of the same core gold diameter. The amount of reduction of the experimentally PA signal amplitude due to the silica coating was found to increase with thicker silica coating, in agreement with our theoretical predictions., Comment: 38 pages, 11 figures

Inspired by recent publications doubtful of the FCS technique, we scrutinize how irreversible (static) and reversible (dynamic) quenching can influence the interpretation of such data. We consider intermediate cases where the assessment of photophysics (static quenching, blinking-like triplet state relaxation) influence on autocorrelation curves can be delicate if dye-labeled objects diffuse on comparably-rapid time scales and use tryptophan as the quencher. As our example of small-molecule dye that diffuses rapidly, we mix quencher with Alexa 488 dye, and quenching is reflected in the fact that the data become exceptionally noisy. This reflects the bidisperse population of quenched and unquenched dye when the time scales overlap between the processes of translational diffusion, quenching, and blinking. As our example of large-molecule dye-labeled object, we mixed quencher with dye-labeled bovine serum albumin. Diffusion, static quenching and blinking time scales are now separated, and inferred translational diffusion now depends weakly on quencher. We conclude that when the diffusing molecule is substantially slower to diffuse than the time scale of photophysical processes of the fluorescent dye to which it is attached, influence of quenching is self-evident and the FCS autocorrelation curves give appropriate diffusion coefficient if correct fitting functions are chosen in the analysis., Comment: 11 pages, 4 figures

Supported Lipid Bilayers (SLBs) are model membranes formed at solid substrate surfaces. This architecture renders the membrane experimentally accessible to surface sensitive techniques used to study their properties, including Atomic Force Microscopy (AFM), optical fluorescence microscopy, Quartz Crystal Microbalance (QCM) and X-Ray/Neutron Reflectometry, and allows integration with technology for potential biotechnological applications such as drug screening devices. The experimental technique often dictates substrate choice or treatment, and it is anecdotally recognised that certain substrates are suitable for the particular experiment, but the exact influence of the substrate has not been comprehensively investigated. Here, we study the behavior of a simple model bilayer, phase separating on a variety of commonly used substrates, including glass, mica, silicon and quartz, with drastically different results. The distinct micron scale domains observed on mica, identical to those seen in free-floating Giant Unilamellar Vesicles (GUVs), are reduced to nanometer scale domains on glass and quartz. The mechanism for the arrest of domain formation is investigated, and the most likely candidate is nanoscale surface roughness, acting as a drag on the hydrodynamic motion of small domains during phase separation. Evidence was found that the physico-chemical properties of the surface have a mediating effect, most likely due to changes in the lubricating interstitial water layer between surface and bilayer.

Understanding the complexity of fragmentation processes is essential for regulating intercellular communication in mechanistic biology and developing novel bottom-up approaches in a large range of multiphase flow processes. In this context, self-fragmentation proceeds without any external mechanical energy input allowing one to create efficiently micro- and nanodroplets. Here we examine self-fragmentation in emulsion nanodroplets stabilized by solid particles with different surface features. Mesoscopic modelling and accelerated dynamics simulations allow us to overcome the limitations of atomistic simulations and offer detailed insight into the interplay between the evolution of the droplet shape and the particle finite-sized effects at the interface. We show that finite-sized nanoparticles play an active role in the necking breakup, behaving like nano-scale razors, and affect strongly the thermodynamic properties of the system. The role played by the particles during self-fragmentation might be of relevance to multifunctional biomaterial design and tuning of signaling pathways in mechanistic biology., Comment: 7 pages, 5 figures

The liver performs critical physiological functions, including metabolizing and removing substances, such as toxins and drugs, from the bloodstream. Hepatotoxicity itself is intimately linked to abnormal hepatic transport and hepatotoxicity remains the primary reason drugs in development fail and approved drugs are withdrawn from the market. For this reason, we propose to analyze, across liver compartments, the transport kinetics of fluorescein-a fluorescent marker used as a proxy for drug molecules-using intravital microscopy data. To resolve the transport kinetics quantitatively from fluorescence data, we account for the effect that different liver compartments (with different chemical properties) have on fluorescein's emission rate. To do so, we develop ordinary differential equation transport models from the data where the kinetics are related to the observable fluorescence levels by "measurement parameters" that vary across different liver compartments. On account of the steep non-linearities in the kinetics and stochasticity inherent to the model, we infer kinetic and measurement parameters by generalizing the method of parameter cascades. For this application, the method of parameter cascades ensures fast and precise parameter estimates from noisy time traces., Comment: 38 pages, 7 figures

Amphiphilic molecules and their self-assembled structures have long been the target of extensive research due to their potential applications in fields ranging from materials design to biomedical and cosmetic applications. Increasing demands for functional complexity have been met with challenges in biochemical engineering, driving researchers to innovate in the design of new amphiphiles. An emerging class of molecules, namely, peptide amphiphiles, combines key advantages and circumvents some of the disadvantages of conventional phospholipids and block-copolymers. Herein, we present new peptide amphiphiles comprised of an intrinsically disordered peptide conjugated to two variants of hydrophobic dendritic domains. These molecules termed intrinsically disordered peptide amphiphiles (IDPA), exhibit a sharp pH-induced micellar phase-transition from low-dispersity spheres to extremely elongated worm-like micelles. We present an experimental characterization of the transition and propose a theoretical model to describe the pH-response. We also present the potential of the shape transition to serve as a mechanism for the design of a cargo hold-and-release application. Such amphiphilic systems demonstrate the power of tailoring the interactions between disordered peptides for various stimuli-responsive biomedical applications., Comment: 27 pages, 4 figures, supplementary information file

Kinesin motors can induce a buckling instability in a microtubule with a fixed minus end. Here we show that by modifying the surface with a protein-repellent functionalization and using clusters of kinesin motors, the microtubule can exhibit persistent oscillatory motion resembling the beating of sperm flagella. The observed period is of the order of 1 min. From the experimental images we theoretically determine a distribution of motor forces that explains the observed shapes using a maximum likelihood approach. A good agreement is achieved with a small number of motor clusters acting simultaneously on a microtubule. The tangential forces exerted by a cluster are mostly in the range 0-8 pN toward the microtubule minus end, indicating the action of 1 or 2 kinesin motors. The lateral forces are distributed symmetrically and mainly below 10 pN, while the lateral velocity has a strong peak around zero. Unlike well-known models for flapping filaments, kinesins are found to have a strong "pinning" effect on the beating filaments. Our results suggest new strategies to utilize molecular motors in dynamic roles that depend sensitively on the stress built-up in the system. peerReviewed

Living cells communicate information about physiological conditions by producing signaling molecules in a specific timed manner. Different conditions can result in the same total amount of a signaling molecule, differing only in the pattern of the molecular concentration over time. Such temporally coded information can be completely invisible to even state-of-the-art molecular sensors with high chemical specificity that respond only to the total amount of the signaling molecule. Here, we demonstrate design principles for circuits with temporal specificity, that is, molecular circuits that respond to specific temporal patterns in a molecular concentration. We consider pulsatile patterns in a molecular concentration characterized by three fundamental temporal features - time period, duty fraction and number of pulses. We develop circuits that respond to each one of these features while being insensitive to the others. We demonstrate our design principles using abstract Chemical Reaction Networks and with explicit simulations of DNA strand displacement reactions. In this way, our work develops building blocks for temporal pattern recognition through molecular computation., Comment: 7 pages, 5 figures + appendices

Allosteric interactions in DNA are crucial for various biological processes. These interactions are quantified by measuring the change in free energy as a function of the distance between the binding sites for two ligands. Here we show that trends in the interaction energy of ligands binding to DNA can be explained within an elastic birod model. The birod model accounts for the deformation of each strand as well as the change in stacking energy due to perturbations in position and orientation of the bases caused by the binding of ligands. The strain fields produced by the ligands decay with distance from the binding site. The interaction energy of two ligands decays exponentially with the distance between them and oscillates with the periodicity of the double helix in quantitative agreement with experimental measurements. The trend in the computed interaction energy is similar to that in the perturbation of groove width produced by the binding of a single ligand which is consistent with molecular simulations. Our analysis provides a new framework to understand allosteric interactions in DNA and can be extended to other rod-like macromolecules whose elasticity plays a role in biological functions.

We investigated frictional effects on the folding rates of a human Telomerase hairpin (hTR HP) and H-type pseudoknot from the Beet Western Yellow Virus (BWYV PK) using simulations of the Three Interaction Site (TIS) model for RNA. The heat capacity from TIS model simulations, calculated using temperature replica exchange simulations, reproduces nearly quantitatively the available experimental data for the hTR HP. The corresponding results for BWYV PK serve as predictions. We calculated the folding rates (kFs) from more than 100 folding trajectories for each value of the solvent viscosity (η) at a fixed salt concentration of 200 mM. Using the theoretical estimate ( where N is number of nucleotides) for folding free energy barrier, kF data for both the RNAs are quantitatively fit using one dimensional Kramers’ theory with two parameters specifying the curvatures in the unfolded basin and the barrier top. In the high-friction regime (η ≳ 10−5 Pa·s), for both HP and PK, kFs decrease as 1/η whereas in the low friction regime kFs increase as η increases, leading to a maximum folding rate at a moderate viscosity (~ 10−6 Pa·s), which is the Kramers turnover. From the fits, we find that the speed limit to RNA folding at water viscosity is between (1 − 4)μs, which is in accord with our previous theoretical prediction as well as results from several single molecule experiments. Both the RNA constructs fold by parallel pathways. Surprisingly, we find that the flux through the pathways could be altered by changing solvent viscosity, a prediction that is more easily testable in RNA than proteins.

The low-frequency collective vibrational modes in proteins as well as the protein-water interface have been suggested as dominant factors controlling the efficiency of biochemical reactions and biological energy transport. It is thus crucial to uncover the mystery of hydration structure and dynamics as well as their coupling to collective motions of proteins in aqueous solutions. Here we report dielectric properties of aqueous bovine serum albumin protein solutions as a model system using an extremely sensitive dielectric spectrometer with frequencies spanning from megahertz to terahertz. The dielectric relaxation spectra reveal several polarization mechanisms at the molecular level with different time constants and dielectric strengths, reflecting the complexity of protein-water interactions. Combining the effective-medium approximation and molecular dynamics simulations, we have determined collective vibrational modes at terahertz frequencies and the number of water molecules in the tightly-bound and loosely-bound hydration layers. High-precision measurements of the number of hydration water molecules indicate that the dynamical influence of proteins extends beyond the first solvation layer, to around 7 {\AA} distance from the protein surface, with the largest slowdown arising from water molecules directly hydrogen-bonded to the protein. Our results reveal critical information of protein dynamics and protein-water interfaces, which determine biochemical functions and reactivity of proteins., Comment: 16 pages, 5 figures, The Journal of Physical Chemistry B, 2018

The interaction between light and matter can be controlled efficiently by structuring materials at a length scale shorter than the wavelength of interest. With the goal to build optical devices that operate at the nanoscale, plasmonics has established itself as a discipline, where near-field effects of electromagnetic waves created in the vicinity of metallic surfaces can give rise to a variety of novel phenomena and fascinating applications. As research on plasmonics has emerged from the optics and solid-state communities, most laboratories employ top-down lithography to implement their nanophotonic designs. In this review, we discuss the recent, successful efforts of employing self-assembled DNA nanostructures as scaffolds for creating advanced plasmonic architectures. DNA self-assembly exploits the base-pairing specificity of nucleic acid sequences and allows for the nanometer-precise organization of organic molecules but also for the arrangement of inorganic particles in space. Bottom-up self-assembly thus bypasses many of the limitations of conventional fabrication methods. As a consequence, powerful tools such as DNA origami have pushed the boundaries of nanophotonics and new ways of thinking about plasmonic designs are on the rise.

Ultrastructural fluctuations at nanoscale are fundamental to assess properties and functionalities of advanced out-of-equilibrium materials. We have taken myelin as a model of supramolecular assembly in out-of-equilibrium living matter. Myelin sheath is a simple stable multi-lamellar structure of high relevance and impact in biomedicine. Although it is known that myelin has a quasi-crystalline ultrastructure there is no information on its fluctuations at nanoscale in different states due to limitations of the available standard techniques. To overcome these limitations, we have used Scanning micro X-ray Diffraction, which is a non-invasive probe of both reciprocal and real space to visualize statistical fluctuations of myelin order of the sciatic nerve of Xenopus Laevis. The results show that the ultrastructure period of the myelin is stabilized by large anti-correlated fluctuations at nanoscale, between hydrophobic and hydrophilic layers. The ratio between the total thickness of hydrophilic and hydrophobic layers defines the conformational parameter, which describes the different states of myelin. Our key result is that myelin in its out-of-equilibrium functional state fluctuates point-to-point between different conformations showing a correlated disorder described by a Levy distribution. As the system approaches the thermodynamic equilibrium in an aged state the disorder loses its correlation degree and the structural fluctuation distribution changes to Gaussian. In a denatured state at low pH, it changes to a completely disordered stage. Our results clarify also the degradation mechanism in biological systems by associating these states with variation of the ultrastructural dynamic fluctuations at nanoscale., 21 pages, 6 fugures

International audience; The plasma membrane of living cells is compartmentalized at multiple spatial scales ranging from the nano-to the meso-scale. This non-random organization is crucial for a large number of cellular functions. At the nanoscale, cell membranes organize into dynamic nano-assemblies enriched by cholesterol, sphingolipids and certain types of proteins. Investigating these nano-assemblies known as lipid rafts is of paramount interest in fundamental cell biology. However, this goal requires simultaneous nanometer spatial precision and microsecond temporal resolution which is beyond the reach of common microscopes. Optical antennas based on metallic nanostructures efficiently enhance and confine light into nanometer dimensions, breaching the diffraction limit of light. In this Perspective, we discuss recent progress combining optical antennas with fluorescence correlation spectroscopy (FCS) to monitor microsecond dynamics at nanoscale spatial dimensions. These new developments offer numerous opportunities to investigate lipid and protein dynamics in both mimetic and native biological membranes.

Hydrogen bond networks play vital roles in biological functions ranging from protein folding to enzyme catalysis. Here we combine electronic structure calculations and ab initio path integral molecular dynamics simulations, which incorporate both nuclear and electronic quantum effects, to show why the network of short hydrogen bonds in the active site of ketosteroid isomerase is remarkably robust to mutations along the network and how this gives rise to large local electric fields. We demonstrate that these properties arise from the network's ability to respond to a perturbation by shifting proton positions and redistributing electronic charge density. This flexibility leads to small changes in properties such as the partial ionization of residues and $pK_a$ isotope effects upon mutation of the residues, consistent with recent experiments. This proton flexibility is further enhanced when an extended hydrogen bond network forms in the presence of an intermediate analog, which allows us to explain the chemical origins of the large electric fields in the enzyme's active site observed in recent experiments., Comment: 13 pages, 10 figures (7 main text and 3 SI)

Phycobilisomes, the light-harvesting antennas of cyanobacteria, can adapt to a wide range of environments thanks to a composition and function response to stress conditions. We study how structural changes influence excitation transfer in these super-complexes. Specifically, we show the influence of the rod length on the photon absorption and subsequent excitation transport to the core. Despite the fact that the efficiency of individual disks on the rod decreases with increasing rod length, we find an optimal length for which the average rod efficiency is maximal. Combining this study with experimental structural measurements, we propose models for the arrangement of the phycobiliproteins inside the thylakoid membranes, evaluate the importance of rod length, and predict the corresponding transport properties for different cyanobacterial species. This analysis, which links the functional and structural properties of full phycobilisome complexes, thus provides further rationals to help resolving their exact structure., Comment: 7 pages, 7 figures, 2 pages supplementary material