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Environment-sensitive probes are frequently used in spectral and multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Python for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties. the correlation between membrane fluidity and mitochondrial potential, protein distribution in cell-cell contacts and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for easy adoption., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

The protein-ligand binding frequently occurs in living organisms and plays a crucial role in the execution of the functions of proteins and drugs. It is also an indispensable part of drug discovery and screening. While the methods for investigating protein-ligand binding are diverse, each has its own objectives, strengths, and limitations, which all influence the choice of method. Many studies concentrate on one or a few specific methods, suggesting that comprehensive summaries are lacking. Therefore in this review, these methods are comprehensively summarized and are discussed in detail: prediction and simulation methods, thermal and thermodynamic methods, spectroscopic methods, methods of determining three-dimensional structures of the complex, mass spectrometry-based methods and others. It is also important to integrate these methods based on the specific objectives of the research. With the aim of advancing pharmaceutical research, this review seeks to deepen the understanding of the protein-ligand binding process., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Feng Zhou reports financial support was provided by the National Key Research and Development Program for the 14th Five-Year Plan of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The prediction of protein 3D structure from amino acid sequence is a computational grand challenge in biophysics and plays a key role in robust protein structure prediction algorithms, from drug discovery to genome interpretation. The advent of AI models, such as AlphaFold, is revolutionizing applications that depend on robust protein structure prediction algorithms. To maximize the impact, and ease the usability, of these AI tools we introduce APACE, AlphaFold2 and advanced computing as a service, a computational framework that effectively handles this AI model and its TB-size database to conduct accelerated protein structure prediction analyses in modern supercomputing environments. We deployed APACE in the Delta and Polaris supercomputers and quantified its performance for accurate protein structure predictions using four exemplar proteins: 6AWO, 6OAN, 7MEZ, and 6D6U. Using up to 300 ensembles, distributed across 200 NVIDIA A100 GPUs, we found that APACE is up to two orders of magnitude faster than off-the-self AlphaFold2 implementations, reducing time-to-solution from weeks to minutes. This computational approach may be readily linked with robotics laboratories to automate and accelerate scientific discovery., Competing Interests: Competing interests statement:The authors declare no competing interest.

Protein-protein association and aggregation are fundamental processes that play critical roles in various biological phenomena, from cellular signaling to disease progression. Understanding the underlying biophysical principles governing these processes is crucial for elucidating their mechanisms and developing strategies for therapeutic intervention. In this review, we provide an overview of recent experimental studies focused on protein-protein association and aggregation. We explore the key biophysical factors that influence these processes, including protein structure, conformational dynamics, and intermolecular interactions. We discuss the effects of environmental conditions such as temperature, pH and related buffer-specific effects, and ionic strength and related ion-specific effects on protein aggregation. The effects of polymer crowders and sugars are also addressed. We list the techniques used to study aggregation. We analyze emerging trends and challenges in the field, including the development of computational models and the integration of multidisciplinary approaches for a comprehensive understanding of protein-protein association and aggregation.

Neurofilaments (NFs) are multisubunit, neuron-specific intermediate filaments consisting of a 10-nm diameter filament "core" surrounded by a layer of long intrinsically disordered protein (IDP) "tails." NFs are thought to regulate axonal caliber during development and then stabilize the mature axon, with NF subunit misregulation, mutation, and aggregation featuring prominently in multiple neurological diseases. The field's understanding of NF structure, mechanics, and function has been deeply informed by a rich variety of biochemical, cell biological, and mouse genetic studies spanning more than four decades. These studies have contributed much to our collective understanding of NF function in axonal physiology and disease. In recent years, however, there has been a resurgence of interest in NF subunit proteins in two new contexts: as potential blood- and cerebrospinal fluid-based biomarkers of neuronal damage, and as model IDPs with intriguing properties. Here, we review established principles and more recent discoveries in NF structure and function. Where possible, we place these findings in the context of biophysics of NF assembly, interaction, and contributions to axonal mechanics.

With an estimate of hundred thousands of protein molecules per cell and the number of metabolites several orders of magnitude higher, protein-metabolite interactions are omnipresent. In vitro analyses are one of the main pillars on the way to establish a solid understanding of how these interactions contribute to maintaining cellular homeostasis. A repertoire of biophysical techniques is available by which protein-metabolite interactions can be quantitatively characterized in terms of affinity, specificity, and kinetics in a broad variety of solution environments. Several of those provide information on local or global conformational changes of the protein partner in response to ligand binding. This review chapter gives an overview of the state-of-the-art biophysical toolbox for the study of protein-metabolite interactions. It briefly introduces basic principles, highlights recent examples from the literature, and pinpoints promising future directions., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Cell monolayers are a central model system in the study of tissue biophysics. In vivo, epithelial tissues are curved on the scale of microns, and the curvature's role in the onset of spontaneous tissue flows is still not well understood. Here, we present a hydrodynamic theory for an apical-basal asymmetric active nematic gel on a curved strip. We show that surface curvature qualitatively changes monolayer motion compared with flat space: the resulting flows can be thresholdless, and the transition to motion may change from continuous to discontinuous. Surface curvature, friction, and active tractions are all shown to control the flow pattern selected, from simple shear to vortex chains.

Bone mechanobiology is the study of the physical, biological and mechanical processes that continuously affect the multiscale multicellular system of the bone from the organ to the molecular scale. Current knowledge derives from experimental studies, which are often limited to gathering qualitative data in a cross-sectional manner, up to a restricted number of time points. Moreover, the simultaneous collection of information about 3D bone microarchitecture, cell activity as well as protein distribution and level is still a challenge. In silico models can expand qualitative information with hypothetical quantitative systems, which allow quantification, testing and comparison to existing quantifiable experimental data. An overview of multiscale, multiphysics, agent-based and hybrid techniques and their applications to bone mechanobiology is provided in the present review. The study analysed how mechanical signals, cells and proteins can be modelled in silico to represent bone remodelling and adaptation. Hybrid modelling of bone mechanobiology could combine the methods used in multiscale, multiphysics and agent-based models into a single model, leading to a unified and comprehensive understanding of bone mechanobiology. Numerical simulations of in vivo multicellular systems aided in hypothesis testing of such in silico models. Recently, in silico trials have been used to illustrate the mechanobiology of cells and signalling pathways in clinical biopsies and animal bones, including the effects of drugs on single cells and signalling pathways up to the organ level. This improved understanding may lead to the identification of novel therapies for degenerative diseases such as osteoporosis.

Highly deuterated protein samples expand the biophysics and biological tool kit by providing, among other qualities, contrast matching in neutron diffraction experiments and reduction of dipolar spin interactions from normally protonated proteins in magnetic resonance studies, impacting both electron paramagnetic resonance and NMR spectroscopy. In NMR applications, deuteration is often combined with other isotopic labeling patterns to expand the range of conventional NMR spectroscopy research in both solution and solid-state conditions. However, preparation of deuterated proteins is challenging. We present here a simple, effective, and user-friendly protocol to produce highly deuterated proteins in Escherichia coli cells. The protocol utilizes the common shaker flask growth method and the well-known pET system (which provides expression control via the T7 promotor) for large-scale recombinant protein expression. One liter expression typically yields 5 to 50 mg of highly deuterated protein. Our data demonstrate that the optimized procedure produces a comparable quantity of protein in deuterium ( 2 H 2 O) oxide M9 medium compared with that in 1 H 2 O M9 medium. The protocol will enable a broader utilization of deuterated proteins in a number of biophysical techniques., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Published by Elsevier Inc.)

Using Brownian Dynamics simulations, we study effective interactions mediated between two identical and impermeable disks (inclusions) immersed in a bath of identical, active (self-propelled), Brownian rods in two spatial dimensions, by assuming that the self-propulsion axis of the rods may generally deviate from their longitudinal axis. When the self-propulsion is transverse (perpendicular to the rod axis), the accumulation of active rods around the inclusions is significantly enhanced, causing a more expansive steric layering (ring formation) of the rods around the inclusions, as compared with the reference case of longitudinally self-propelling rods. As a result, the transversally self-propelling rods also mediate a significantly longer ranged effective interaction between the inclusions. The bath-mediated interaction arises due to the overlaps between the active-rod rings formed around the inclusions, as they are brought into small separations. When the self-propulsion axis is tilted relative to the rod axis, we find an asymmetric imbalance of active-rod accumulation around the inclusion dimer. This leads to a noncentral interaction, featuring an anti-parallel pair of transverse force components and, hence, a bath-mediated torque on the dimer., (© 2021. The Author(s).)

A method motivated by the eye's aqueous veins is described for the imaging and strain calculation within soft biological tissues. A challenge to the investigation of the biomechanics of the aqueous vein-perilimbal sclera tissue complex is resolution of tissue deformations as a function of intraocular pressure and the subsequent calculation of strain (a normalized measure of deformation). The method involves perfusion of the eye with a contrast agent during conduction of non-invasive, optical resolution photoacoustic microscopy. This imaging technique permits three-dimensional displacement measurements of tracked points on the inner walls of the veins which are used in a finite element model to determine the corresponding strains. The methods are validated against two standard strain measurement methods. Representative porcine globe perfusion experiments are presented that demonstrate the power of the method to determine complex strain fields in the veins dependent on intraocular pressure as well as vein anatomy. In these cases, veins are observed to move radially outward during increases in intraocular pressure and to possess significant spatial strain variation, possibly influenced by their branching patterns. To the authors' knowledge, these are the only such quantitative, data driven, calculations of the aqueous vein strains available in the open literature., (© 2021. The Author(s).)

Calcineurin, also known as protein phosphatase 2B, is a heterodimeric serine threonine phosphatase involved in numerous signaling pathways. During the past 50 years, calcineurin has been the subject of extensive investigation. Many of its cellular and physiological functions have been described, and the underlying biophysical mechanisms are the subject of active investigation. With the abundance of techniques and experimental designs utilized to study calcineurin and its numerous substrates, it is difficult to reconcile the available information. There have been a plethora of reports describing the role of calcineurin in cardiac disease. However, a physiological role of calcineurin in healthy cardiomyocyte function requires clarification. Here, we review the seminal biophysical and structural details that are responsible for the molecular function and inhibition of calcineurin. We then focus on literature describing the roles of calcineurin in cardiomyocyte physiology and disease.

Deep learning using neural networks relies on a class of machine-learnable models constructed using 'differentiable programs'. These programs can combine mathematical equations specific to a particular domain of natural science with general-purpose, machine-learnable components trained on experimental data. Such programs are having a growing impact on molecular and cellular biology. In this Perspective, we describe an emerging 'differentiable biology' in which phenomena ranging from the small and specific (for example, one experimental assay) to the broad and complex (for example, protein folding) can be modeled effectively and efficiently, often by exploiting knowledge about basic natural phenomena to overcome the limitations of sparse, incomplete and noisy data. By distilling differentiable biology into a small set of conceptual primitives and illustrative vignettes, we show how it can help to address long-standing challenges in integrating multimodal data from diverse experiments across biological scales. This promises to benefit fields as diverse as biophysics and functional genomics., (© 2021. Springer Nature America, Inc.)

Mechanobiology has nowadays acquired the status of a topic of fundamental importance in a degree in Biological Sciences. It is inherently a multidisciplinary topic where biology, physics and engineering competences are required. A course in mechanobiology should include lab experiences where students can appreciate how mechanical stimuli from outside affect living cell behaviour. Here we describe all the steps to build a cell stretcher inside an on-stage cell incubator. This device allows exposing living cells to a periodic mechanical stimulus similar to what happens in physiological conditions such as, for example, in the vascular system or in the lungs. The reaction of the cells to the periodic mechanical stretching represents a prototype of a mechanobiological signal integrated by living cells. We also provide the theoretical and experimental aspects related to the calibration of the stretcher apparatus at a level accessible to researchers not used to dealing with topics like continuum mechanics and analysis of deformations. We tested our device by stretching cells of two different lines, U87-MG and Balb-3T3 cells, and we analysed and discussed the effect of the periodic stimulus on both cell reorientation and migration. We also discuss the basic aspects related to the quantitative analysis of the reorientation process and of cell migration. We think that the device we propose can be easily reproduced at low-cost within a project-oriented course in the fields of biology, biotechnology and medical engineering., (© 2021. Biomedical Engineering Society.)

Many venomous organisms carry in their arsenal short polypeptides that block K + channels in a highly selective manner. These toxins may compete with the permeating ions directly via a "plug" mechanism or indirectly via a "pore-collapse" mechanism. An alternative "lid" mechanism was proposed but remained poorly defined. Here we study the Drosophila Shaker channel block by Conkunitzin-S1 and Conkunitzin-C3, two highly similar toxins derived from cone venom. Despite their similarity, the two peptides exhibited differences in their binding poses and biophysical assays, implying discrete action modes. We show that while Conkunitzin-S1 binds tightly to the channel turret and acts via a "pore-collapse" mechanism, Conkunitzin-C3 does not contact this region. Instead, Conk-C3 uses a non-conserved Arg to divert the permeant ions and trap them in off-axis cryptic sites above the SF, a mechanism we term a "molecular-lid". Our study provides an atomic description of the "lid" K + blocking mode and offers valuable insights for the design of therapeutics based on venom peptides., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Some biological questions are tough to solve through standard molecular and cell biological methods and naturally lend themselves to investigation by physical approaches. Below, a group of formally trained physicists discuss, among other things, how they apply physics to address biological questions and how physical approaches complement conventional biological approaches., (Copyright © 2021. Published by Elsevier Inc.)

Critical to viral infection are the multiple interactions between viral proteins and host-cell counterparts. The first such interaction is the recognition of viral envelope proteins by surface receptors that normally fulfil other physiological roles, a hijacking mechanism perfected over the course of evolution. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), has successfully adopted this strategy using its spike glycoprotein to dock on the membrane-bound metalloprotease angiotensin-converting enzyme 2 (ACE2). The crystal structures of several SARS-CoV-2 proteins alone or in complex with their receptors or other ligands were recently solved at an unprecedented pace. This accomplishment is partly due to the increasing availability of data on other coronaviruses and ACE2 over the past 18 years. Likewise, other key intervening actors and mechanisms of viral infection were elucidated with the aid of biophysical approaches. An understanding of the various structurally important motifs of the interacting partners provides key mechanistic information for the development of structure-based designer drugs able to inhibit various steps of the infective cycle, including neutralizing antibodies, small organic drugs, and vaccines. This review analyzes current progress and the outlook for future structural studies.

Determination of a substrate's surface energy profile is a facile and inexpensive method to indicate the substrate's interfacial thermodynamics with another substance (e.g., microorganisms, biomacromolecules, medical devices, etc). The following protocol details a goniometric method to calculate a substrate's surface energy profile which (1) directly correlates to a substrate's interfacial Gibbs energy (ΔG) and (2) predicts the interfacial interactions with other substances. We also provide a calculation template using advanced mathematics to expedite surface energy profile determination. For complete details on the use and execution of this protocol, please refer to Cavitt et al. (2020)., Competing Interests: The authors declare no competing interests., (© 2021 The Authors.)

Over the past three decades, as mechanobiology has become a distinct area of study, researchers have developed novel imaging tools to discover the pathways of biomechanical signaling. Early work with substrate engineering and particle tracking demonstrated the importance of cell-extracellular matrix interactions on the cell cycle as well as the mechanical flux of the intracellular environment. Most recently, tension sensor approaches allowed directly measuring tension in cell-cell and cell-substrate interactions. We retrospectively analyze how these various optical techniques progressed the field and suggest our vision forward for a unified theory of cell mechanics, mapping cellular mechanosensing, and novel biomedical applications for mechanobiology.

Mechanobiology seeks to understand how cells integrate their biomechanics into their function and behavior. Unravelling the mechanisms underlying these mechanobiological processes is particularly important for immune cells in the context of the dynamic and complex tissue microenvironment. However, it remains largely unknown how cellular mechanical force generation and mechanical properties are regulated and integrated by immune cells, primarily due to a profound lack of technologies with sufficient sensitivity to quantify immune cell mechanics. In this review, we discuss the biological significance of mechanics for immune cells across length and time scales, and highlight several experimental methodologies for quantifying the mechanics of immune cells. Finally, we discuss the importance of quantifying the appropriate mechanical readout to accelerate insights into the mechanobiology of the immune response.

Background: The QDOT MICRO catheter allows temperature- and flow-controlled (TFC) ablation and very-high-power short-duration (vHPSD) ablation., Objective: The purpose of this study was to compare lesion characteristics between TFC/vHPSD ablation and standard power-controlled (PC) ablation., Methods: Lesion characteristics in the right atrium, left atrium, and right ventricle (RV) of 6 sheep were compared between vHPSD (90 W/4 seconds, TC mode with 60°C target using QDOT) and standard radiofrequency settings (PC mode, 30 W/30 seconds with ThermoCool SmartTouch SF). Lesions in the left ventricle (LV) were compared, targeting 50 W for 60-second applications., Results: Forty-six focal atrial lesions, 50 RV focal lesions, and 12 linear lesions were created by vHPSD ablation and PC ablation in each group of 6 animals. vHPSD ablation produced significantly larger focal atrial lesions in length (8.3 [6.4-9.7] mm vs 6.3 [5.2-7.4] mm; P = .0002), width (6.0 [5.3-6.9] mm vs 4.6 [3.8-5.4] mm; P <.0001), and surface area (39.4 [25.4-52.4] mm 2 vs 23.6 [16.0-31.1] mm 2 ; P = .0001), with superior transmurality (89.1% vs 69.6%; P = .04) compared to PC ablation. vHPSD ablation produced significantly larger RV lesions in length (7.7 [7.0-8.7] mm vs 6.0 [4.8-6.9] mm; P <.0001), width (6.4 [5.4-7.5] mm vs 4.3 [3.6-5.2] mm; P <.0001), and area (39.4 [29.1-50.1] mm 2 vs 19.9 [14.7-25.2] mm 2 ; P <.0001) but similar volume (P = .97) with shallower lesions (2.7 [2.2-3.4] mm vs 3.8 [3.0-4.4] mm; P <.0001). Atrial linear lesions were more homogeneous (P = .02), with fewer gaps in each line (P = .003) with vHPSD ablation. LV focal lesions (15 TFC mode; 21 PC mode) were similar in volume and depth, but lesion size showed less deviation (P <.05) in TFC than PC mode. Fewer steam pops were observed in TFC mode (0% vs 28.6%; P = .03). Hemorrhagic rings around the lesion core were generally smaller with TFC/vHPSD ablation (P <.05)., Conclusion: TFC/vHPSD ablation produces larger, shallower, more homogeneous, and less hemorrhagic lesions. vHPSD Ablation produces more transmural and contiguous linear lesions compared to PC ablation. LV lesions are more homogeneous with fewer steam pops in TFC ablation., (Copyright © 2020 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

GTP Cyclohydrolase I (GCH1) catalyses the conversion of guanosine triphosphate (GTP) to dihydroneopterin triphosphate (H2NTP), the initiating step in the biosynthesis of tetrahydrobiopterin (BH4). BH4 functions as co-factor in neurotransmitter biosynthesis. BH4 homeostasis is a promising target to treat pain disorders in patients. The function of mammalian GCH1s is regulated by a metabolic sensing mechanism involving a regulator protein, GCH1 feedback regulatory protein (GFRP). Dependent on the relative cellular concentrations of effector ligands, BH4 and phenylalanine, GFRP binds GCH1 to form inhibited or activated complexes, respectively. We determined high-resolution structures of the ligand-free and -bound human GFRP and GCH1-GFRP complexes by X-ray crystallography. Highly similar binding modes of the substrate analogue 7-deaza-GTP to active and inhibited GCH1-GFRP complexes confirm a novel, dissociation rate-controlled mechanism of non-competitive inhibition to be at work. Further, analysis of all structures shows that upon binding of the effector molecules, the conformations of GCH1 or GFRP are altered and form highly complementary surfaces triggering a picomolar interaction of GFRP and GCH1 with extremely slow k off values, while GCH1-GFRP complexes rapidly disintegrate in absence of BH4 or phenylalanine. Finally, comparing behavior of full-length and N-terminally truncated GCH1 we conclude that the disordered GCH1 N-terminus does not have impact on complex formation and enzymatic activity. In summary, this comprehensive and methodologically diverse study helps to provide a better understanding of the regulation of GCH1 by GFRP and could thus stimulate research on GCH1 modulating drugs., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

In many biological systems, chemical reactions or changes in a physical state are assumed to occur instantaneously. For describing the dynamics of those systems, Markov models that require exponentially distributed inter-event times have been used widely. However, some biophysical processes such as gene transcription and translation are known to have a significant gap between the initiation and the completion of the processes, which renders the usual assumption of exponential distribution untenable. In this paper, we consider relaxing this assumption by incorporating age-dependent random time delays (distributed according to a given probability distribution) into the system dynamics. We do so by constructing a measure-valued Markov process on a more abstract state space, which allows us to keep track of the 'ages' of molecules participating in a chemical reaction. We study the large-volume limit of such age-structured systems. We show that, when appropriately scaled, the stochastic system can be approximated by a system of partial differential equations (PDEs) in the large-volume limit, as opposed to ordinary differential equations (ODEs) in the classical theory. We show how the limiting PDE system can be used for the purpose of further model reductions and for devising efficient simulation algorithms. In order to describe the ideas, we use a simple transcription process as a running example. We, however, note that the methods developed in this paper apply to a wide class of biophysical systems.

Cells respond to mechanical cues from their environment through a process of mechanosensing and mechanotransduction. Cell stretching devices are important tools to study the molecular pathways responsible for cellular responses to mechanobiological processes. We describe the development and testing of a uniaxial cell stretcher that has applications for microscopic as well as biochemical analyses. By combining simple fabrication techniques with adjustable control parameters, the stretcher is designed to fit a variety of experimental needs. The stretcher can be used for static and cyclic stretching. As a proof of principle, we visualize stretch induced deformation of cell nuclei via incremental static stretch, and changes in IEX1 expression via cyclic stretching. This stretcher is easily modified to meet experimental needs, inexpensive to build, and should be readily accessible for most laboratories with access to 3D printing., (© 2021. Published by The Company of Biologists Ltd.)

The study of the structure and dynamics of membrane domains in vivo is a challenging task. However, major advances could be achieved through the application of microscopic and spectroscopic techniques coupled with the use of model membranes, where the relations between lipid composition and the type, amount and properties of the domains present can be quantitatively studied.This chapter provides protocols to study membrane organization and visualize membrane domains by fluorescence microscopy both in artificial membrane and living cell models of Gaucher Disease (GD ). We describe a bottom-up multiprobe methodology, which enables understanding how the specific lipid interactions established by glucosylceramide, the lipid that accumulates in GD , affect the biophysical properties of model and cell membranes, focusing on its ability to influence the formation, properties and organization of lipid raft domains. In this context, we address the preparation of (1) raft-mimicking giant unilamellar vesicles labeled with a combination of fluorophores that allow for the visualization and comprehensive characterization of those membrane domains and (2) human fibroblasts exhibiting GD phenotype to assess the biophysical properties of biological membrane in living cells using fluorescence microscopy.

The use of steady-state and time-resolved fluorescence spectroscopy to study sterol and sphingolipid-enriched lipid domains as diverse as the ones found in mammalian and fungal membranes is herein described. We first address how to prepare liposomes that mimic raft-containing membranes of mammalian cells and how to use fluorescence spectroscopy to characterize the biophysical properties of these membrane model systems. We further illustrate the application of Förster resonance energy transfer (FRET) to study nanodomain reorganization upon interaction with small bioactive molecules, phenolic acids, an important group of phytochemical compounds. This methodology overcomes the resolution limits of conventional fluorescence microscopy allowing for the identification and characterization of lipid domains at the nanoscale.We continue by showing how to use fluorescence spectroscopy in the biophysical analysis of more complex biological systems, namely the plasma membrane of Saccharomyces cerevisiae yeast cells and the necessary adaptations to the filamentous fungus Neurospora crassa , evaluating the global order of the membrane, sphingolipid-enriched domains rigidity and abundance, and ergosterol-dependent properties.

Communication between cells and their environment is carried out through the plasma membrane including the action of most pharmaceutical drugs. Although such a communication typically involves specific binding of a messenger to a membrane receptor, the biophysical state of the lipid bilayer strongly influences the outcome of this interaction. Sphingolipids constitute an important part of the lipid membrane, and their mole fraction modifies the biophysical characteristics of the membrane. Here, we describe methods that can be used for measuring how sphingolipid accumulation alters the compactness, microviscosity, and dipole potential of the lipid bilayer and the mobility of membrane components.

The structure-function paradigm has guided investigations into the molecules involved in cellular signalling for decades. The peripheries of this paradigm, however, start to unravel when considering the co-operation between proteins and the membrane in signalling processes. Intrinsically disordered regions hold distinct advantages over folded domains in terms of their binding promiscuity, sensitivity to their particular environment and their ease of modulation through post-translational modifications. Low sequence complexity and bias towards charged residues are also favourable for the multivalent electrostatic interactions that occur at the surfaces of lipid bilayers. This review looks at the principles behind the successful marriage between protein disorder and membranes in addition to the role of this partnership in modifying and regulating signalling in cellular processes. The HVR (hypervariable region) of small GTPases is highlighted as a well-studied example of the nuanced role a short intrinsically disordered region can play in the fine-tuning of signalling pathways., (© 2020 The Author(s).)

Bacteria can organise themselves into communities in the forms of biofilms and swarms. Through chemical and physical interactions between cells, these communities exhibit emergent properties that individual cells alone do not have. While bacterial communities have been mainly studied in the context of biochemistry and molecular biology, recent years have seen rapid advancements in the biophysical understanding of emergent phenomena through physical interactions in biofilms and swarms. Moreover, new technologies to control bacterial emergent behaviours by physical means are emerging in synthetic biology. Such technologies are particularly promising for developing engineered living materials (ELM) and devices and controlling contamination and biofouling. In this minireview, we overview recent studies unveiling physical and mechanical cues that trigger and affect swarming and biofilm development. In particular, we focus on cell shape, motion and density as the key parameters for mechanical cell-cell interactions within a community. We then showcase recent studies that use physical stimuli for patterning bacterial communities, altering collective behaviours and preventing biofilm formation. Finally, we discuss the future potential extension of biophysical and bioengineering research on microbial communities through computational modelling and deeper investigation of mechano-electrophysiological coupling., (© 2020 The Author(s).)

Temporal interference (TI) is a non-invasive neurostimulation technique that utilizes high-frequency external electric fields to stimulate deep neuronal structures without affecting superficial, off-target structures. TI represents a potential breakthrough for treating conditions, such as Parkinson's disease and chronic pain. However, early clinical work on TI stimulation was met with mixed outcomes challenging its fundamental mechanisms and applications. Here, we apply established physics to study the mechanisms of TI with the goal of optimizing it for clinical use. We argue that TI stimulation cannot work via passive membrane filtering, as previously hypothesized. Instead, TI stimulation requires an ion-channel mediated signal rectification process. Unfortunately, this mechanism is also responsible for high-frequency conduction block in off-target tissues, thus challenging clinical applications of TI. In consequence, we propose a set of experimental controls that should be performed in future experiments to refine our understanding and practice of TI stimulation. A record of this paper's transparent peer review process is included in the Supplemental Information., Competing Interests: Declaration of Interests S.F.L. has equity in Hologram Consultants, LLC and is a member of the scientific advisory board for Abbott Neuromodulation. S.F.L. holds stock options, received research support, and serves on the scientific advisory board of Presidio Medical. M.C. is the inventor of several patents involving technologies for the electrical stimulation of the spinal cord. All other authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

While many fields have contributed to biological physics, nanotechnology offers a new scale of observation. High-speed atomic force microscopy (HS-AFM) provides nanometre structural information and dynamics with subsecond resolution of biological systems. Moreover, HS-AFM allows us to measure piconewton forces within microseconds giving access to unexplored, fast biophysical processes. Thus, HS-AFM provides a tool to nourish biological physics through the observation of emergent physical phenomena in biological systems. In this review, we present an overview of the contribution of HS-AFM, both in imaging and force spectroscopy modes, to the field of biological physics. We focus on examples in which HS-AFM observations on membrane remodelling, molecular motors or the unfolding of proteins have stimulated the development of novel theories or the emergence of new concepts. We finally provide expected applications and developments of HS-AFM that we believe will continue contributing to our understanding of nature, by serving to the dialogue between biology and physics. This article is part of a discussion meeting issue 'Dynamic in situ microscopy relating structure and function'.

Time-resolved serial femtosecond crystallography (tr-SFX) methods exploit slurries of crystalline samples that range in size from hundreds of nanometers to a few tens of micrometers, at near-physiological temperature and pressure, to generate atomic resolution models and probe authentic function with the same experiment. 'Dynamic structural biology' is often used to encompass the research philosophy and techniques. Reaction cycles for tr-SFX studies are initiated by photons or ligand addition/mixing strategies, wherein the latter are potentially generalizable across enzymology. Thus, dynamic structural biology often creates stop-motion molecular movies of macromolecular function. In metal-dependent systems, complementary spectroscopic information can also be collected from the same samples and X-ray pulses, which provides even more detailed mechanistic insights. These types of experimental data also complement quantum mechanical and classical dynamics numerical calculations. Correlated structural-functional results will yield more detailed mechanistic insights and will likely translate into better drugs and treatments impacting human health, and better catalysis for clean energy and agriculture., (Copyright © 2020 Diamond Light Source Ltd. Published by Elsevier Ltd.. All rights reserved.)

What do we know about the molecular evolution of functional protein condensation? The capacity of proteins to form biomolecular condensates (compact, protein-rich states, not bound by membranes, but still separated from the rest of the contents of the cell) appears in many cases to be bestowed by weak, transient interactions within one or between proteins. Natural selection is expected to remove or fix amino acid changes, insertions or deletions that preserve and change this condensation capacity when doing so is beneficial to the cell. A few recent studies have begun to explore this frontier of phylogenetics at the intersection of biophysics and cell biology., (© 2020 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

Biomolecules have complex structures, and noncovalent interactions are crucial to determine their conformations and functionalities. It is therefore critical to be able to describe them in an accurate but efficient manner in these systems. In this context density functional theory (DFT) could provide a powerful tool to simulate biological matter either directly for relatively simple systems or coupled with classical simulations like the QM/MM (quantum mechanics/molecular mechanics) approach. Additionally, DFT could play a fundamental role to fit the parameters of classical force fields or to train machine learning potentials to perform large scale molecular dynamics simulations of biological systems. Yet, local or semi-local approximations used in DFT cannot describe van der Waals (vdW) interactions, one of the essential noncovalent interactions in biomolecules, since they lack a proper description of long range correlation effects. However, many efficient and reasonably accurate methods are now available for the description of van der Waals interactions within DFT. In this work, we establish the accuracy of several state-of-the-art vdW-aware functionals by considering 275 biomolecules including interacting DNA and RNA bases, peptides and biological inhibitors and compare our results for the energy with highly accurate wavefunction based calculations. Most methods considered here can achieve close to predictive accuracy. In particular, the non-local vdW-DF2 functional is revealed to be the best performer for biomolecules, while among the vdW-corrected DFT methods, uMBD is also recommended as a less accurate but faster alternative.

Glutamate dehydrogenase (GDH) is a key enzyme interlinking carbon and nitrogen metabolism. Recent discoveries of the GDH specific role in breast cancer, hyperinsulinism/hyperammonemia (HI/HA) syndrome, and neurodegenerative diseases have reinvigorated interest on GDH regulation, which remains poorly understood despite extensive and long standing studies. Notwithstanding the growing evidence of the complexity of allosteric network behind GDH regulation, identifications of allosteric factors and associated mechanisms are paramount to deepen our understanding of the complex dynamics that regulate GDH enzymatic activity. Combining structural analyses of cryo-electron microscopy data with molecular dynamic simulations, here we show that the cofactor NADH is a key player in the GDH regulation process. Our structural analysis indicates that, binding to the regulatory sites in proximity of the antenna region, NADH acts as a positive allosteric modulator by enhancing both the affinity of the inhibitor GTP binding and inhibition of GDH catalytic activity. We further show that the binding of GTP to the NADH-bound GDH activates a triangular allosteric network, interlinking the inhibitor with regulatory and catalytic sites. This allostery produces a local conformational rearrangement that triggers an anticlockwise rotational motion of interlinked alpha-helices with specific tilted helical extension. This structural transition is a fundamental switch in the GDH enzymatic activity. It introduces a torsional stress, and the associated rotational shift in the Rossmann fold closes the catalytic cleft with consequent inhibition of the deamination process. In silico mutagenesis examinations further underpin the molecular basis of HI/HA dominant mutations and consequent over-activity of GDH through alteration of this allosteric communication network. These results shed new light on GDH regulation and may lay new foundation in the design of allosteric agents.

Therapeutic peptides and proteins show enormous potential in the pharmaceutical market, but high costs in discovery and development are limiting factors so far. Single or multiple point mutations are commonly introduced in protein drugs to increase their binding affinity or selectivity. They can also induce adverse properties, which might be overlooked in a functional screen, such as a decreased colloidal or thermal stability, leading to problems in later stages of the development. In this study, we address the effect of point mutations on the stability of the 4.4 kDa antimicrobial peptide plectasin, as a case study. We combined a systematic high-throughput biophysical screen of the peptide thermal and colloidal stability using dynamic light scattering and differential scanning calorimetry with structure-based methods including small-angle X-ray scattering, analytical ultracentrifugation, and nuclear magnetic resonance spectroscopy. Additionally, we applied molecular dynamics simulations to link obtained protein stability parameters to the protein's molecular structure. Despite their predicted structural similarities, all four plectasin variants showed substantially different behavior in solution. We observed an increasing propensity of plectasin to aggregate at a higher pH, and the introduced mutations influenced the type of aggregation. Our strategy for systematically assessing the stability and aggregation of protein drugs is generally applicable and is of particular relevance, given the increasing number of protein drugs in development.

Cellular traction forces influence epithelial behavior, including wound healing and cell extrusion. Here, we describe a simple in vitro traction force microscopy (TFM) protocol using ECM protein-coated polydimethylsiloxane substrate and widefield fluorescence microscopy. We include detailed steps for analysis so readers can obtain traction forces to study the mechanobiology of epithelial cells. We also provide guidelines on when to adopt another common class of TFM protocols based on polyacrylamide hydrogels. For complete details on the use and execution of this protocol, please refer to Saw et al. (2017) and Teo et al. (2020)., Competing Interests: The authors declare no competing interests., (© 2020 The Author(s).)

Bone morphogenetic proteins (BMPs) are members of the transforming growth factor-beta (TGFβ) superfamily of cytokines. While some ligand members are potent inducers of angiogenesis, others promote vascular homeostasis. However, the precise understanding of the molecular mechanisms underlying these functions is still a growing research field. In bone, the tissue in which BMPs were first discovered, crosstalk of TGFβ/BMP signaling with mechanobiology is well understood. Likewise, the endothelium represents a tissue that is constantly exposed to multiple mechanical triggers, such as wall shear stress, elicited by blood flow or strain, and tension from the surrounding cells and to the extracellular matrix. To integrate mechanical stimuli, the cytoskeleton plays a pivotal role in the transduction of these forces in endothelial cells. Importantly, mechanical forces integrate on several levels of the TGFβ/BMP pathway, such as receptors and SMADs, but also global cell-architecture and nuclear chromatin re-organization. Here, we summarize the current literature on crosstalk mechanisms between biochemical cues elicited by TGFβ/BMP growth factors and mechanical cues, as shear stress or matrix stiffness that collectively orchestrate endothelial function. We focus on the different subcellular compartments in which the forces are sensed and integrated into the TGFβ/BMP growth factor signaling.

Native mass spectrometry (MS) allows the interrogation of structural aspects of macromolecules in the gas phase, under the premise of having initially maintained their solution-phase noncovalent interactions intact. In the more than 25 years since the first reports, the utility of native MS has become well established in the structural biology community. The experimental and technological advances during this time have been rapid, resulting in dramatic increases in sensitivity, mass range, resolution, and complexity of possible experiments. As experimental methods have improved, there have been accompanying developments in computational approaches for analyzing and exploiting the profusion of MS data in a structural and biophysical context. In this perspective, we consider the computational strategies currently being employed by the community, aspects of best practice, and the challenges that remain to be addressed. Our perspective is based on discussions within the European Cooperation in Science and Technology Action on Native Mass Spectrometry and Related Methods for Structural Biology (EU COST Action BM1403), which involved participants from across Europe and North America. It is intended not as an in-depth review but instead to provide an accessible introduction to and overview of the topic-to inform newcomers to the field and stimulate discussions in the community about addressing existing challenges. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05792) focuses on software tools available to help researchers tackle some of the challenges enumerated here.

Replicating biological patterns is promising for designing materials with multifaceted properties. Twisted cholesteric liquid crystal patterns are found in the iridescent tessellated cuticles of many insects and a few fruits. Their accurate replication is extremely difficult since discontinuous patterns and colors must coexist in a single layer without discontinuity of the structures. Here, a solution is demonstrated by addressing striped insect cuticles with a complex twisted organization. Geometric constraints are met by controlling the thermal diffusion in a cholesteric oligomer bilayer subjected to local changes in the molecular anchoring conditions. A multicriterion comparison reveals a very high level of biomimicry. Proof-of-concept prototypes of anti-counterfeiting tags are presented. The present design involves an economy of resources and a high versatility of chiral patterns unreached by the current manufacturing techniques such as metallic layer vacuum deposition, template embossing and various forms of lithography which are limited and often prohibitively expensive.

The magnetic tweezer technique has become a versatile tool for unfolding or folding of individual molecules, mainly DNA. In addition to single molecule analysis, the magnetic tweezer can be used to analyze the mechanical properties of cells and extracellular matrices. We have established a magnetic tweezer that is capable of measuring the linear and non-linear viscoelastic behavior of a wide range of soft matter in precisely controlled environmental conditions, such as temperature, CO 2 and humidity. The magnetic tweezer presented in this study is suitable to detect specific differences in the mechanical properties of different cell lines, such as human breast cancer cells and mouse embryonic fibroblasts, as well as collagen matrices of distinct concentrations in the presence and absence of fibronectin crosslinks. The precise calibration and control mechanism employed in the presented magnetic tweezer setup provides the ability to apply physiological force up to 5 nN on 4.5 µm superparamagnetic beads coated with fibronectin and coupled to the cells or collagen matrices. These measurements reveal specific local linear and non-linear viscoelastic behavior of the investigated samples. The viscoelastic response of cells and collagen matrices to the force application is best described by a weak power law behavior. Our results demonstrate that the stress stiffening response and the fluidization of cells is cell type specific and varies largely between differently invasive and aggressive cancer cells. Finally, we showed that the viscoelastic behavior of collagen matrices with and without fibronectin crosslinks measured by the magnetic tweezer can be related to the microstructure of these matrices.

Extracellular vesicles (EVs) have raised high expectations as a novel class of diagnostics and therapeutics. However, variabilities in EV isolation methods and the unresolved structural complexity of these biological-nanoparticles (sub-100 nm) necessitate rigorous biophysical characterization of single EVs. Here, using atomic force microscopy (AFM) in conjunction with direct stochastic optical reconstruction microscopy (dSTORM), micro-fluidic resistive pore sizing (MRPS), and multi-angle light scattering (MALS) techniques, we compared the size, structure and unique surface properties of breast cancer cell-derived small EVs (sEV) obtained using four different isolation methods. AFM and dSTORM particle size distributions showed coherent unimodal and bimodal particle size populations isolated via centrifugation and immune-affinity methods respectively. More importantly, AFM imaging revealed striking differences in sEV nanoscale morphology, surface nano-roughness, and relative abundance of non-vesicles among different isolation methods. Precipitation-based isolation method exhibited the highest particle counts, yet nanoscale imaging revealed the additional presence of aggregates and polymeric residues. Together, our findings demonstrate the significance of orthogonal label-free surface characteristics of single sEVs, not discernable via conventional particle sizing and counts alone. Quantifying key nanoscale structural characteristics of sEVs, collectively termed 'EV-nano-metrics' enhances the understanding of the complexity and heterogeneity of sEV isolates, with broad implications for EV-analyte based research and clinical use.

Coformulations containing two therapeutic monoclonal antibodies (mAbs) could offer various benefits like enhanced therapeutic efficacy and better patient compliance. However, there are very few published studies on coformulations and binary mixtures of mAbs. It remains unclear to what extent mAbs with different physicochemical properties can be combined in solution without detrimental effects on protein stability. Here, we present a study including six model mAbs of the IgG1 subclass that are commercially available. In silico and biophysical characterization shows that the proteins have different physicochemical properties. Thus, their combinations represent various scenarios for coformulation development. We prepared all possible binary mixtures of the six mAbs and determined several biophysical parameters that are assessed during early-stage protein drug product development. The measured biophysical parameters are indicative of the conformational protein stability (inflection points of the thermal protein unfolding transitions) and the colloidal protein stability (aggregation onset temperatures and interaction parameter k D from dynamic light scattering). Remarkably, all 15 binary mAb mixtures do not exhibit biophysical parameters that indicate inferior conformational or colloidal stability compared to the least stable mAb in the mixture. Our findings suggest that the coformulation of some therapeutic monoclonal antibodies of the IgG1 subclass could be possible in a straightforward way as severe detrimental effects on the stability of these proteins in binary mixtures were not observed.

The emergence of collagen I in vertebrates resulted in a dramatic increase in the stiffness of the extracellular environment, supporting long-range force propagation and the development of low-compliant tissues necessary for the development of vertebrate traits including pressurized circulation and renal filtration. Vertebrates have also evolved integrins that can bind to collagens, resulting in the generation of higher tension and more efficient force transmission in the extracellular matrix. The stiffer environment provides an opportunity for the vertebrates to create new structures such as the stress fibers, new cell types such as endothelial cells, new developmental processes such as neural crest delamination, and new tissue organizations such as the blood-brain barrier. Molecular players found only in vertebrates allow the modification of conserved mechanisms as well as the design of novel strategies that can better serve the physiological needs of the vertebrates. These innovations collectively contribute to novel morphogenetic behaviors and unprecedented increases in the complexities of tissue mechanics and functions.

Biological nanoparticles include liposomes, extracellular vesicle and lipid-based discoidal systems. When studying such particles, there are several key parameters of interest, including particle size and concentration. Measuring these characteristics can be of particular importance in the research laboratory or when producing such particles as biotherapeutics. This article briefly describes the major types of lipid-containing nanoparticles and the techniques that can be used to study them. Such methodologies include electron microscopy, atomic force microscopy, dynamic light scattering, nanoparticle tracking analysis, flow cytometry, tunable resistive pulse sensing and microfluidic resistive pulse sensing. Whilst no technique is perfect for the analysis of all nanoparticles, this article provides advantages and disadvantages of each, highlighting the latest developments in the field. Finally, we demonstrate the use of microfluidic resistive pulse sensing for the analysis of biological nanoparticles., (Copyright © 2020 Elsevier Inc. All rights reserved.)