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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.

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).)

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.)

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.)

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.)

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 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.

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.

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.

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.

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.)

Background: Articular cartilage has a high-weight-bearing area and a low-weight-bearing area, the macroscopic elastic moduli of the two regions are different. Chondrocytes are affected by the applied force at the microscopic level. Currently, the modulus of the two areas at the micro and nano levels is unknown, and studies on the relationship between macro-, micro- and nano-scale elastic moduli are limited. Such information may be important for further understanding of cartilage mechanics. Moreover, the surface morphology, proteoglycan content, and micro and nano structure of the two areas, which influences the mechanical properties of cartilage should be discussed., Methods: Safranin-O/Fast Green staining was used to evaluate the surface morphology and semi-quantify proteoglycan content of porcine femoral head cartilage between the two weight-bearing areas. The unconfined compression test was used to determine the macro elastic modulus. Atomic force microscope was used to measure the micro and nano compressive elastic modulus as well as the nano structure. Scanning electron microscope was employed to evaluate the micro structure., Results: No significant differences in the fibrillation index were observed between two areas (P = 0.5512). The Safranin-O index of the high-weight-bearing area was significantly higher than that of the low-weight-bearing area (P = 0.0387). The compressive elastic modulus of the high-weight-bearing area at the macro and micro level was significantly higher than that of the low-weight-bearing area (P = 0.0411 for macro-scale, and P = 0.0001 for micro-scale), while no statistically significant differences were observed in the elastic modulus of collagen fibrils at the nano level (P = 0.8544). The density of the collagen fibers was significantly lower in the high-weight-bearing area (P = 0.0177). No significant differences were observed in the structure and diameter of the collagen fibers between the two areas (P = 0.7361)., Conclusions: A higher proteoglycan content correlated with a higher compressive elastic modulus of the high-weight-bearing area at the micro level than that of the low-weight-bearing area, which was consistent with the trend observed from the macroscopic compressive elastic modulus. The weight-bearing level was not associated with the elastic modulus of individual collagen fibers and the diameter at the nano level. The micro structure of cartilage may influence the macro- and micro-scale elastic modulus.

Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved ( a ) detection/segmentation of tumor subregions and ( b ) computer-aided diagnostic/prognostic/predictive modeling. This article presents a summary of ( a ) biophysical growth modeling and simulation,( b ) inverse problems for model calibration, ( c ) these models' integration with imaging workflows, and ( d ) their application to clinically relevant studies. We anticipate that such quantitative integrative analysis may even be beneficial in a future revision of the World Health Organization (WHO) classification for CNS tumors, ultimately improving patient survival prospects.

Many biomolecular condensates appear to form via spontaneous or driven processes that have the hallmarks of intracellular phase transitions. This suggests that a common underlying physical framework might govern the formation of functionally and compositionally unrelated biomolecular condensates. In this review, we summarize recent work that leverages a stickers-and-spacers framework adapted from the field of associative polymers for understanding how multivalent protein and RNA molecules drive phase transitions that give rise to biomolecular condensates. We discuss how the valence of stickers impacts the driving forces for condensate formation and elaborate on how stickers can be distinguished from spacers in different contexts. We touch on the impact of sticker- and spacer-mediated interactions on the rheological properties of condensates and show how the model can be mapped to known drivers of different types of biomolecular condensates.

Background/aims: This study aimed to establish a precise and well-defined working model, assessing pharmaceutical effects on vascular smooth muscle cell monolayer in-vitro. It describes various analysis techniques to determine the most suitable to measure the biomechanical impact of vasoactive agents by using CellDrum technology., Methods: The so-called CellDrum technology was applied to analyse the biomechanical properties of confluent human aorta muscle cells (haSMC) in monolayer. The cell generated tensions deviations in the range of a few N/m² are evaluated by the CellDrum technology. This study focuses on the dilative and contractive effects of L-type Ca 2+ channel agonists and antagonists, respectively. We analyzed the effects of Bay K8644, nifedipine and verapamil. Three different measurement modes were developed and applied to determine the most appropriate analysis technique for the study purpose. These three operation modes are called, particular time mode" (PTM), "long term mode" (LTM) and "real-time mode" (RTM)., Results: It was possible to quantify the biomechanical response of haSMCs to the addition of vasoactive agents using CellDrum technology. Due to the supplementation of 100nM Bay K8644, the tension increased approximately 10.6% from initial tension maximum, whereas, the treatment with nifedipine and verapamil caused a significant decrease in cellular tension: 10nM nifedipine decreased the biomechanical stress around 6,5% and 50nM verapamil by 2,8%, compared to the initial tension maximum. Additionally, all tested measurement modes provide similar results while focusing on different analysis parameters., Conclusion: The CellDrum technology allows highly sensitive biomechanical stress measurements of cultured haSMC monolayers. The mechanical stress responses evoked by the application of vasoactive calcium channel modulators were quantified functionally (N/m²). All tested operation modes resulted in equal findings, whereas each mode features operation-related data analysis., Competing Interests: The authors have no conflicts of interest to declare., (© Copyright by the Author(s). Published by Cell Physiol Biochem Press.)

This is a PLOS Computational Biology Education paper. The idea that the brain functions so as to minimize certain costs pervades theoretical neuroscience. Because a cost function by itself does not predict how the brain finds its minima, additional assumptions about the optimization method need to be made to predict the dynamics of physiological quantities. In this context, steepest descent (also called gradient descent) is often suggested as an algorithmic principle of optimization potentially implemented by the brain. In practice, researchers often consider the vector of partial derivatives as the gradient. However, the definition of the gradient and the notion of a steepest direction depend on the choice of a metric. Because the choice of the metric involves a large number of degrees of freedom, the predictive power of models that are based on gradient descent must be called into question, unless there are strong constraints on the choice of the metric. Here, we provide a didactic review of the mathematics of gradient descent, illustrate common pitfalls of using gradient descent as a principle of brain function with examples from the literature, and propose ways forward to constrain the metric., Competing Interests: The authors have declared that no competing interests exist.

The mechanobiology of receptor-ligand interactions and force-induced enzymatic turnover can be revealed by simultaneous measurements of force response and fluorescence. Investigations at physiologically relevant high labeled substrate concentrations require total internal reflection fluorescence microscopy or zero mode waveguides (ZMWs), which are difficult to combine with atomic force microscopy (AFM). A fully automatized workflow is established to manipulate single molecules inside ZMWs autonomously with noninvasive cantilever tip localization. A protein model system comprising a receptor-ligand pair of streptavidin blocked with a biotin-tagged ligand is introduced. The ligand is pulled out of streptavidin by an AFM cantilever leaving the receptor vacant for reoccupation by freely diffusing fluorescently labeled biotin, which can be detected in single-molecule fluorescence concurrently to study rebinding rates. This work illustrates the potential of the seamless fusion of these two powerful single-molecule techniques., (© 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Objective: The flow kinetics generated with a pulsatile wave that travel along the channel has prime relevance in various processes in physiology and industry. The aim here is to investigate such phenomenon with Bingham fluid with chemically reacting species in terms of their homogeneous and heterogeneous characteristics., Method: To formulate the mathematical descriptions Bingham fluid with heat and mass equations is accounted. Using the similarity solutions, the proposed leading partial differential equations of the flow phenomena transferred into the nonlinear ordinary differential equations and boundary conditions are solved analytically. Such considerations perceive prime importance in medicine and genetics where heterogeneity in a cell makes several diseases difficult to execute., Results: Further the physical aspect of human tabular organs i.e., porosity in a medium is retained in the analysis. The utility of magnetic field in reference to medicine is employed. The walls are considered flexible. The whole problem is set to lubrication approach for simplification of resulting system. The attained results are tested on physical grounds by plotting graphs., Conclusion: It is analyzed that the Hartman number and porosity parameter reduce the velocity and temperature profiles. The elastic wall parameters E 1 and E 2 enhances both the velocity and temperature fields while E 3 enrolls an adverse effect., (Copyright © 2019. Published by Elsevier B.V.)

In light chain amyloidosis (AL), fibrillar deposition of monoclonal immunoglobulin light chains (LCs) in vital organs, such as heart, is associated with their severe dysfunction. In addition to the cellular damage caused by fibril deposition, direct toxicity of soluble prefibrillar amyloidogenic proteins has been reported, in particular, for cardiotoxicity. However, the molecular bases of proteotoxicity by soluble LCs have not been clarified. Here, to address this issue, we rationally engineered the amino acid sequence of the highly cardiotoxic LC H6 by introducing three residue mutations, designed to reduce the dynamics of its native state. The resulting mutant (mH6) is less toxic than its parent H6 to human cardiac fibroblasts and C. elegans. The high sequence and structural similarity, together with the different toxicity, make H6 and its non-toxic designed variant mH6 a test case to shed light on the molecular properties underlying soluble toxicity. Our comparative structural and biochemical study of H6 and mH6 shows closely matching crystal structures, whereas spectroscopic data and limited proteolysis indicate that H6 displays poorly cooperative fold, higher flexibility, and kinetic instability, and a higher dynamic state in its native fold. Taken together, the results of this study show a strong correlation between the overall conformational properties of the native fold and the proteotoxicity of cardiotropic LCs., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The higher-order structure (HOS) of protein therapeutics is a critical quality attribute directly related to their function. Traditionally, the HOS of protein therapeutics has been characterized by methods with low to medium structural resolution such as Fourier-transform infrared (FTIR), circular dichroism (CD), and intrinsic fluorescence spectroscopy, and differential scanning calorimetry (DSC). Recently, high-resolution nuclear magnetic resonance (NMR) methods have emerged as powerful tools for HOS characterization. NMR is a multi-attribute method with unique capabilities to provide information about all the structural levels of proteins in solution. We have in this study compared 1 D 1 H Profile NMR with the established biophysical methods for HOS assessments using a set of blended samples of the monoclonal antibodies belonging to the subclasses IgG1 and IgG2. The study shows that Profile NMR can distinguish between most sample combinations (93%), DSC can differentiate 61% of the sample combinations, and near-ultraviolet CD spectroscopy can differentiate 52% of the sample combinations, whereas no significant distinction could be made between any samples using FTIR or intrinsic fluorescence. Our data therefore show that NMR has superior ability to address differences in HOS, a feature that could be directly applicable in comparability and similarity assessments., (Copyright © 2020 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)

Intrinsically disordered proteins (IDPs) have no single, fixed tertiary structure, yet they take on many vital functions in biology. In recent years, considerable effort has been put into the structural characterization of their conformational ensembles, to understand the link between the transient, short- and long-range organizations of IDPs and their functions. Such biophysical studies require substantial amounts of pure protein, representing a major bottleneck in the studies of IDPs. However, the unique physicochemical properties resulting from their compositional bias may be exploited for simple yet effective purification strategies. In this chapter, we provide tips and tricks for IDP production and describe the most important analyses to carry out before bringing an IDP of interest to the laboratory. We outline four purification protocols utilizing the unique properties of IDPs as well as some commonly encountered challenges and pitfalls.

Integral membrane proteins have historically been challenging targets for biophysical research due to their low solubility in aqueous solution. Their importance for chemical and electrical signaling between cells, however, makes them fascinating targets for investigators interested in the regulation of cellular and physiological processes. Since membrane proteins shunt the barrier imposed by the cell membrane, they also serve as entry points for drugs, adding pharmaceutical research and development to the interests. In recent years, detailed understanding of membrane protein function has significantly increased due to high-resolution structural information obtained from single-particle cryo-EM, X-ray crystallography, and NMR. In order to further advance our mechanistic understanding on membrane proteins as well as foster drug development, it is crucial to generate more biophysical and functional data on these proteins under defined conditions. To that end, different techniques have been developed to stabilize integral membrane proteins in native-like environments that allow both structural and biophysical investigations-amphipols, lipid bicelles, and lipid nanodiscs. In this chapter, we provide detailed protocols for the reconstitution of membrane proteins according to these three techniques. We also outline some of the possible applications of each technique and discuss their advantages and possible caveats.

Cancer has become a key healthcare problem worldwide. The background of cancer research has brought the advent of cross-disciplinary collaborations that has enabled us to get an idea of the disease mechanisms at spatial and temporal scales. Understanding the combination of biology and physics of cancer presents a promising field of research with apprehensions in better clarity over both cellular and molecular mechanisms impacting cancer therapy. Investigation of cancer biology has provided a wealth of knowledge on cancer initiation and propagation and has provided newer treatment strategies in the fight against cancer. Understanding the physics of cancer provides wonderful set of equations that take advantage of mechanisms of force production, propagation by the cancer cells and mechanical properties of the tumor tissue. The spatial tissue arrangement in which the tumor growth occurs can be better understood with biophysics. Thus, the combination of biology and physics of cancer contributes crucially in impacting the correct treatment of cancer. The present review is aimed at providing an overview of regulatory networks, regulation of cell division and differentiation, the signal transduction pathways and integration of all sciences including physics, biology, and medicine which is very well needed to tackle the war against cancer and thus influence cancer therapy. These circuits will help us understand whether the therapy will work wonders or cause failure. As cancer is much more than a genetic disease, more insights into the malignancy with physical approaches are designed to use cancer therapy effectively., (Copyright © 2019 Elsevier Inc. All rights reserved.)

We present new methods for cell line classification using multivariate time series bioimpedance data obtained from electric cell-substrate impedance sensing (ECIS) technology. The ECIS technology, which monitors the attachment and spreading of mammalian cells in real time through the collection of electrical impedance data, has historically been used to study one cell line at a time. However, we show that if applied to data from multiple cell lines, ECIS can be used to classify unknown or potentially mislabeled cells, factors which have previously been associated with the reproducibility crisis in the biological literature. We assess a range of approaches to this new problem, testing different classification methods and deriving a dictionary of 29 features to characterize ECIS data. Most notably, our analysis enriches the current field by making use of simultaneous multi-frequency ECIS data, where previous studies have focused on only one frequency; using classification methods to distinguish multiple cell lines, rather than simple statistical tests that compare only two cell lines; and assessing a range of features derived from ECIS data based on their classification performance. In classification tests on fifteen mammalian cell lines, we obtain very high out-of-sample predictive accuracy. These preliminary findings provide a baseline for future large-scale studies in this field.

Endothelial cells have been established to generate intercellular stresses and tractions, but the role gap junctions play in endothelial intercellular stress and traction generation is currently unknown. Therefore, we present here a mechanics-based protocol to probe the influence of gap junction connexin 43 (Cx43) has on endothelial biomechanics by exposing confluent endothelial monolayers to a known Cx43 inhibitor 2,5-dihydroxychalcone (chalcone) and measuring the impact this inhibitor has on tractions and intercellular stresses. We present representative results, which show a decrease in both tractions and intercellular stresses under a high chalcone dosage (2 µg/mL) when compared to control. This protocol can be applied to not just Cx43, but also other gap junctions as well, assuming the appropriate inhibitor is used. We believe this protocol will be useful in the fields of cardiovascular and mechanobiology research.

Recent advances in fluorogen-binding "light-up" RNA aptamers have enabled protein-free detection of RNA in cells. Detailed biophysical characterization of folding of G-Quadruplex (GQ)-based light-up aptamers such as Spinach, Mango and Corn is still lacking despite the potential implications on their folding and function. In this work we employ single-molecule fluorescence-force spectroscopy to examine mechanical responses of Spinach2, iMangoIII and MangoIV. Spinach2 unfolds in four discrete steps as force is increased to 7 pN and refolds in reciprocal steps upon force relaxation. In contrast, GQ-core unfolding in iMangoIII and MangoIV occurs in one discrete step at forces >10 pN and refolding occurred at lower forces showing hysteresis. Co-transcriptional folding using superhelicases shows reduced misfolding propensity and allowed a folding pathway different from refolding. Under physiologically relevant pico-Newton levels of force, these aptamers may unfold in vivo and subsequently misfold. Understanding of the dynamics of RNA aptamers will aid engineering of improved fluorogenic modules for cellular applications.

Human undulatory underwater swimming (UUS) is an underwater propelling technique in competitive swimming and its propulsive mechanism is poorly understood. The purpose of this study was to visualize the three-dimensional (3D) flow field in the wake region during human UUS in a water flume. A national level male swimmer performed 41 UUS trials in a water flume. A motion capture system and stereo particle image velocimetry (PIV) equipment were used to investigate the 3D coordinates of the swimmer and 3D flow fields in the wake region. After one kick cycle was divided into eight phases, we conducted coordinate transformations and phase averaging method to construct quasi 3D flow fields. At the end of the downward kick, the lower limbs external rotations of the lower limbs were observed, and the feet approached towards each other. A strong downstream flow, i.e. a jet was observed in the wake region during the downward kick, and the paired vortex structure was accompanied by a jet. In the vortex structure, a cluster of vortices and a jet were generated in the wake during the downward kick, and the vortices were subsequently shed from the feet by the rotated leg motion. This suggested that the swimmer gained a thrust by creating vortices around the foot during the downward kick, which collided to form a jet. This paper describes, illustrates, and explains the propulsive mechanism of human UUS., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

All scientific measurements are affected to some degree by both systematic and random errors. The quantification of these errors supports correct interpretation of data, thus supporting scientific progress. Absence of information regarding reliability and accuracy can slow scientific progress, and can lead to a reproducibility crisis. Here we consider both measurement theory and plant biomechanics literature. Drawing from measurement theory literature, we review techniques for assessing both the accuracy and uncertainty of a measurement process. In our survey of plant biomechanics literature, we found that direct assessment of measurement accuracy and uncertainty is not yet common. The advantages and disadvantages of efforts to quantify measurement accuracy and uncertainty are discussed. We conclude with recommended best practices for improving the scientific rigor in plant biomechanics through attention to the issues of measurement accuracy and uncertainty., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The primary plant cell wall is a dynamically regulated composite material of multiple biopolymers that forms a scaffold enclosing the plant cells. The mechanochemical make-up of this polymer network regulates growth, morphogenesis, and stability at the cell and tissue scales. To understand the dynamics of cell wall mechanics, and how it correlates with cellular activities, several experimental frameworks have been deployed in recent years to quantify the mechanical properties of plant cells and tissues. Here we critically review the application of biomechanical tool sets pertinent to plant cell mechanics and outline some of their findings, relevance, and limitations. We also discuss methods that are less explored but hold great potential for the field, including multiscale in silico mechanical modeling that will enable a unified understanding of the mechanical behavior across the scales. Our overview reveals significant differences between the results of different mechanical testing techniques on plant material. Specifically, indentation techniques seem to consistently report lower values compared with tensile tests. Such differences may in part be due to inherent differences among the technical approaches and consequently the wall properties that they measure, and partly due to differences between experimental conditions., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

There is a growing interest in materials that can dynamically change their properties in the presence of cells to study mechanobiology. Herein, we exploit the 365 nm light mediated [4+4] photodimerization of anthracene groups to develop cytocompatible PEG-based hydrogels with tailorable initial moduli that can be further stiffened. A hydrogel formulation that can stiffen from 10 to 50 kPa, corresponding to the stiffness of a healthy and fibrotic heart, respectively, was prepared. This system was used to monitor the stiffness-dependent localization of NFAT, a downstream target of intracellular calcium signaling using a reporter in live cardiac fibroblasts (CFbs). NFAT translocates to the nucleus of CFbs on stiffening hydrogels within 6 h, whereas it remains cytoplasmic when the CFbs are cultured on either 10 or 50 kPa static hydrogels. This finding demonstrates how dynamic changes in the mechanical properties of a material can reveal the kinetics of mechanoresponsive cell signaling pathways that may otherwise be missed in cells cultured on static substrates., (© 2019 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Recent decades brought a revolution to biology, driven mainly by exponentially increasing amounts of data coming from "'omics" sciences. To handle these data, bioinformatics often has to combine biologically heterogeneous signals, for which methods from statistics and engineering (e.g. machine learning) are often used. While such an approach is sometimes necessary, it effectively treats the underlying biological processes as a black box. Similarly, systems biology deals with inherently complex systems, characterized by a large number of degrees of freedom, and interactions that are highly non-linear. To deal with this complexity, the underlying physical interactions are often (over)simplified, such as in Boolean modelling of network dynamics. In this review, we argue for the utility of applying a biophysical approach in bioinformatics and systems biology, including discussion of two examples from our research which address sequence analysis and understanding intracellular gene expression dynamics.