The hierarchical emergence of worm-like chain behaviour from globular domain polymer chains

Biological organisms make use of hierarchically organised structures to modulate mechanical behaviour across multiple lengthscales, allowing microscopic objects to generate macroscopic effects. Within these structural hierarchies, the resultant physical behaviour of the entire system is determined not only by the intrinsic mechanical properties of constituent subunits, but also by their organisation in three-dimensional space. When these subunits are polyproteins, colloidal chains or other globular domain polymers, the Kratky–Porod model is often assumed for the individual subunits. Hence, it is implicitly asserted that the polymeric object has an intrinsic parameter, the persistence length, that defines its flexibility. However, the persistence lengths extracted from experiment vary, and are often relatively small. Through a series of simulations on polymer chains formed of globular subunits, we show that the persistence length itself is a hierarchical structural property, related not only to the intrinsic mechanical properties of the underlying monomeric subunits, but emerging due to the organisation of inhomogenous geometry along the polymer contour

Hierarchical biomechanics: student engagement activities with a focus on biological physics

Hierarchical structure and mechanics are crucial in biological systems as they allow for smaller molecules, such as proteins and sugars, to be used in the construction of large scale biological structures exhibiting properties such as structural support functionality. By exploring the fundamental principles of structure and mechanics at the macroscale, this general theme provides a clear insight into how physics can be applied to the complex questions of biology. With a focus on biopolymer networks and hydrogels, we present a series of interactive activities which cover a range of biophysical concepts at an introductory level, such as viscoelasticity, biological networks and ultimately, hierarchical biomechanics. These activities enable us to discuss multidisciplinary science with a general audience and, given the current trends of research science, this conceptualisation of science is vital for the next generation of scientists

Hierarchical biomechanics: an introductory teaching framework

Biological organisms function as the result of a multitude of complex physical systems all interacting with one another at different length scales and over different time scales. At stages of education below university undergraduate level, this complexity often prevents the discussion of physics within a biological context, subtly implying that the two fields are completely distinct from one another. With science becoming steadily more interdisciplinary at the level of research, this distinction can therefore be quite counterproductive, and potentially even misleading for students with regard to the nature of the scientific method. To explore the interplay between biology and physics with prospective STEM students, we present a series of formal teaching activities utilising a novel piece of experimental equipment we have designed called BioNetGrid. We are able to use BioNetGrid to cover a range of physical concepts at an introductory level, such as Hooke’s law, springs in series and parallel, Poisson’s ratio, elastic modulus and energy distribution. These can be presented together with specific biological systems as examples, such as biopolymer networks, enabling a discussion of the importance of biophysics in research at an earlier stage in a student’s academic career

Exploring the dynamics of flagellar dynein within the axoneme with Fluctuating Finite Element Analysis

Flagellar dyneins are the molecular motors responsible for producing the propagating bending motions of cilia and flagella. They are located within a densely packed and highly organised super-macromolecular cytoskeletal structure known as the axoneme. Using the mesoscale simulation technique Fluctuating Finite Element Analysis (FFEA), which represents proteins as viscoelastic continuum objects subject to explicit thermal noise, we have quantified the constraints on the range of molecular conformations that can be explored by dynein-c within the crowded architecture of the axoneme. We subsequently assess the influence of crowding on the 3D exploration of microtubule-binding sites, and specifically on the axial step length. Our calculations combine experimental information on the shape, flexibility and environment of dynein-c from three distinct sources; negative stain electron microscopy, cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET). Our FFEA simulations show that the super-macromolecular organisation of multiple protein complexes into higher-order structures can have a significant influence on the effective flexibility of the individual molecular components, and may, therefore, play an important role in the physical mechanisms underlying their biological function

Control of Nanoscale In Situ Protein Unfolding Defines Network Architecture and Mechanics of Protein Hydrogels

Hierarchical assemblies of proteins exhibit a wide-range of material properties that are exploited both in nature and by artificially by humankind. However, little is understood about the importance of protein unfolding on the network assembly, severely limiting opportunities to utilize this nanoscale transition in the development of biomimetic and bioinspired materials. Here we control the force lability of a single protein building block, bovine serum albumin (BSA), and demonstrate that protein unfolding plays a critical role in defining the architecture and mechanics of a photochemically cross-linked native protein network. The internal nanoscale structure of BSA contains “molecular reinforcement” in the form of 17 covalent disulphide “nanostaples”, preventing force-induced unfolding. Upon addition of reducing agents, these nanostaples are broken rendering the protein force labile. Employing a combination of circular dichroism (CD) spectroscopy, small-angle scattering (SAS), rheology, and modeling, we show that stapled protein forms reasonably homogeneous networks of cross-linked fractal-like clusters connected by an intercluster region of folded protein. Conversely, in situ protein unfolding results in more heterogeneous networks of denser fractal-like clusters connected by an intercluster region populated by unfolded protein. In addition, gelation-induced protein unfolding and cross-linking in the intercluster region changes the hydrogel mechanics, as measured by a 3-fold enhancement of the storage modulus, an increase in both the loss ratio and energy dissipation, and markedly different relaxation behavior. By controlling the protein’s ability to unfold through nanoscale (un)stapling, we demonstrate the importance of in situ unfolding in defining both network architecture and mechanics, providing insight into fundamental hierarchical mechanics and a route to tune biomaterials for future applications

Fluctuating Finite Element Analysis (FFEA): A continuum mechanics software tool for mesoscale simulation of biomolecules

Fluctuating Finite Element Analysis (FFEA) is a software package designed to perform continuum mechanics simulations of proteins and other globular macromolecules. It combines conventional finite element methods with stochastic thermal noise, and is appropriate for simulations of large proteins and protein complexes at the mesoscale (length-scales in the range of 5 nm to 1 μm), where there is currently a paucity of modelling tools. It requires 3D volumetric information as input, which can be low resolution structural information such as cryo-electron tomography (cryo-ET) maps or much higher resolution atomistic co-ordinates from which volumetric information can be extracted. In this article we introduce our open source software package for performing FFEA simulations which we have released under a GPLv3 license. The software package includes a C ++ implementation of FFEA, together with tools to assist the user to set up the system from Electron Microscopy Data Bank (EMDB) or Protein Data Bank (PDB) data files. We also provide a PyMOL plugin to perform basic visualisation and additional Python tools for the analysis of FFEA simulation trajectories. This manuscript provides a basic background to the FFEA method, describing the implementation of the core mechanical model and how intermolecular interactions and the solvent environment are included within this framework. We provide prospective FFEA users with a practical overview of how to set up an FFEA simulation with reference to our publicly available online tutorials and manuals that accompany this first release of the package

Continuum Mechanical Parameterisation of Cytoplasmic Dynein from Atomistic Simulation

Cytoplasmic dynein is responsible for intra-cellular transport in eukaryotic cells. Using Fluctuating Finite Element Analysis (FFEA), a novel algorithm that represents proteins as continuum viscoelastic solids subject to thermal noise, we are building computational tools to study the mechanics of these molecular machines. Here we present a methodology for obtaining the material parameters required to represent the flexibility of cytoplasmic dynein within FFEA from atomistic molecular dynamics (MD) simulations, and show this continuum representation is sufficient to capture the principal dynamic properties of the motor

Family presence during resuscitation: Validation of the risk–benefit and self-confidence scales for student nurses

© 2016, © The Author(s) 2016. Background. There is increasing debate about the advantages and disadvantages of family-witnessed resuscitation. Research about the views of healthcare providers depends upon reliable tools to measure their perceptions. Two tools have been developed for use with nurses (26-item cost-benefit tool, 17-item self-confidence tool). Objectives. Firstly, to validate these tools for use with student nurses in the UK. Secondly, to report on the perceived risks and benefits reported by student nurses, and their self-confidence in dealing with this situation. Methods. A sample of 79 student nurses were invited to complete the tools. Item-total correlations and Cronbach’s α were used to determine internal consistency. Factor analysis was computed to assess construct validity. The correlation between the two scales was explored. Results. 69 students completed a questionnaire. Very few had experience of family-witnessed resuscitation. Mean total scores were 3.16 (standard deviation 0.37; range 2.04–4.12) on the risk-benefit scale and 3.14 (standard deviation 0.66; range 1.94–4.82) on the self-confidence scale. Four of the original items were removed from the risk-benefit scale (Cronbach's α 0.86; 95% confidence interval ≥0.82). None were removed from the self-confidence scale (Cronbach's α 0.93; 95% confidence interval ≥0.91). There was a significant correlation between the two scales (r = 0.37, p = 0.002). Conclusions. There is growing evidence that these tools are valid and reliable for measuring student nurses’ perceptions about family-witnessed resuscitation

An Experiment on Prediction Markets in Science

Prediction markets are powerful forecasting tools. They have the potential to aggregate private information, to generate and disseminate a consensus among the market participants, and to provide incentives for information acquisition. These market functionalities can be very valuable for scientific research. Here, we report an experiment that examines the compatibility of prediction markets with the current practice of scientific publication. We investigated three settings. In the first setting, different pieces of information were disclosed to the public during the experiment. In the second setting, participants received private information. In the third setting, each piece of information was private at first, but was subsequently disclosed to the public. An automated, subsidizing market maker provided additional incentives for trading and mitigated liquidity problems. We find that the third setting combines the advantages of the first and second settings. Market performance was as good as in the setting with public information, and better than in the setting with private information. In contrast to the first setting, participants could benefit from information advantages. Thus the publication of information does not detract from the functionality of prediction markets. We conclude that for integrating prediction markets into the practice of scientific research it is of advantage to use subsidizing market makers, and to keep markets aligned with current publication practice

Nano-encapsulated Escherichia coli Divisome Anchor ZipA, and in Complex with FtsZ

The E. coli membrane protein ZipA, binds to the tubulin homologue FtsZ, in the early stage of cell division. We isolated ZipA in a Styrene Maleic Acid lipid particle (SMALP) preserving its position and integrity with native E. coli membrane lipids. Direct binding of ZipA to FtsZ is demonstrated, including FtsZ fibre bundles decorated with ZipA. Using Cryo-Electron Microscopy, small-angle X-ray and neutron scattering, we determine the encapsulated-ZipA structure in isolation, and in complex with FtsZ to a resolution of 1.6 nm. Three regions can be identified from the structure which correspond to, SMALP encapsulated membrane and ZipA transmembrane helix, a separate short compact tether, and ZipA globular head which binds FtsZ. The complex extends 12 nm from the membrane in a compact structure, supported by mesoscale modelling techniques, measuring the movement and stiffness of the regions within ZipA provides molecular scale analysis and visualisation of the early divisome