Structure Determination of Microtubules and Pili: Past, Present, and Future Directions

Historically proteins that form highly polymeric and filamentous assemblies have been notoriously difficult to study using high resolution structural techniques. This has been due to several factors that include structural heterogeneity, their large molecular mass, and available yields. However, over the past decade we are now seeing a major shift towards atomic resolution insight and the study of more complex heterogenous samples and in situ/ex vivo examination of multi-subunit complexes. Although supported by developments in solid state nuclear magnetic resonance spectroscopy (ssNMR) and computational approaches, this has primarily been due to advances in cryogenic electron microscopy (cryo-EM). The study of eukaryotic microtubules and bacterial pili are good examples, and in this review, we will give an overview of the technical innovations that have enabled this transition and highlight the advancements that have been made for these two systems. Looking to the future we will also describe systems that remain difficult to study and where further technical breakthroughs are required.

Tracking the time evolution of soft matter systems via topological structural heterogeneity

Persistent homology is an effective topological data analysis tool to quantify the structural and morphological features of soft materials, but so far it has not been used to characterise the dynamical behaviour of complex soft matter systems. Here, we introduce structural heterogeneity, a topological characteristic for semi-ordered materials that captures their degree of organisation at a mesoscopic level and tracks their time-evolution, ultimately detecting the order-disorder transition at the microscopic scale. We show that structural heterogeneity tracks structural changes in a liquid crystal nanocomposite, reveals the effect of confined geometry on the nematic-isotropic and isotropic-nematic phase transitions, and uncovers physical differences between these two processes. The system used in this work is representative of a class of composite nanomaterials, partially ordered and with complex structural and physical behaviour, where their precise characterisation poses significant challenges. Our developed analytic framework can provide both a qualitative and quantitative characterisation of the dynamical behaviour of a wide range of semi-ordered soft matter systems.

Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand–maximize–compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

Structural Heterogeneity of an Amorphous-Nanocrystalline Alloy Fe77Cu1Si16B6 in the Nanometer Range

In this article, an alloy of the Finemet type Fe77Cu1Si16B6 obtained by quenching from a liquid state (spinning method) in the initial state is investigated. The main research methods were scanning and transmission electron microscopy. Methods for describing multiscale structural heterogeneities in amorphous-nanocrystalline alloys have been developed, allowing the structural state to be described and its influence on the physicochemical and technical properties to be determined depending on the technological conditions for obtaining these alloys. Representation of electron microscopic images in the form of Fourier spectra made it possible to reveal the nature of the formation of short- and middle-order in amorphous-nanocrystalline alloys according to the principle of self-similar spatial structures. The analysis of electron microscopic images by integral Lebesgue measures revealed density fluctuations over the alloy volume, which corresponds to the hierarchical representation of structural inhomogeneities in amorphous metallic alloys.

In-Depth Molecular Dynamics Study of All Possible Chondroitin Sulfate Disaccharides Reveals Key Insight into Structural Heterogeneity and Dynamism

GAGs exhibit a high level of conformational and configurational diversity, which remains untapped in terms of the recognition and modulation of proteins. Although GAGs are suggested to bind to more than 800 biologically important proteins, very few therapeutics have been designed or discovered so far. A key challenge is the inability to identify, understand and predict distinct topologies accessed by GAGs, which may help design novel protein-binding GAG sequences. Recent studies on chondroitin sulfate (CS), a key member of the GAG family, pinpointing its role in multiple biological functions led us to study the conformational dynamism of CS building blocks using molecular dynamics (MD). In the present study, we used the all-atom GLYCAM06 force field for the first time to explore the conformational space of all possible CS building blocks. Each of the 16 disaccharides was solvated in a TIP3P water box with an appropriate number of counter ions followed by equilibration and a production run. We analyzed the MD trajectories for torsional space, inter- and intra-molecular H-bonding, bridging water, conformational spread and energy landscapes. An in-house phi and psi probability density analysis showed that 1→3-linked sequences were more flexible than 1→4-linked sequences. More specifically, phi and psi regions for 1→4-linked sequences were held within a narrower range because of intra-molecular H-bonding between the GalNAc O5 atom and GlcA O3 atom, irrespective of sulfation pattern. In contrast, no such intra-molecular interaction arose for 1→3-linked sequences. Further, the stability of 1→4-linked sequences also arose from inter-molecular interactions involving bridged water molecules. The energy landscape for both classes of CS disaccharides demonstrated increased ruggedness as the level of sulfation increased. The results show that CS building blocks present distinct conformational dynamism that offers the high possibility of unique electrostatic surfaces for protein recognition. The fundamental results presented here will support the development of algorithms that help to design longer CS chains for protein recognition.

Side Chain Dispersity Matters: Topologically Precise and Discrete Bottlebrush Polymers

The synthesis of bottlebrush polymers with topologically precise and fully discrete structures is reported. Key features of the synthesis include the combination of scalable synthesis and separation strategies to access discrete macromonomer libraries, followed by their polymerization and further separation into topologically uniform and discrete bottlebrushes. Discrete macromonomers prove crucial for regulating the structural heterogeneity of bottlebrushes and their macroscopic properties. When assembled as a monolayer at the air-water interface, bottlebrushes with discrete side chains display high packing density and distinct three-phase Langmuir-Blodgett isotherms. The impact of precisely regulating side chain dispersity and sequence on polymer properties was further demonstrated through tailoring the interbrush interactions and thermomechanical properties of well-defined block bottlebrushes.

Features of Acoustic Emission in Tensile Testing of Dissimilar Welded Joints of Pearlitic and Austenitic Steels

This paper presents a study of acoustic emission (AE) during the deformation of dissimilar welded joints of austenitic steel to pearlitic steel. One of the specific problems in these welded joints is the presence of decarburized and carbide diffusion interlayers, which intensively increase in width during long-term high-temperature operation. The presence of wide interlayers negatively affects the mechanical properties of welded joints. Moreover, welded defects are difficult to diagnose in welded joints containing interlayers: due to the high structural heterogeneity, interlayers create structural noises that can hinder the detection of defects such as cracks, pores, or a lack of penetration. The AE method may become a complex decision for diagnosing dissimilar welded joints due to applicability to the testing of heterogenic materials with a complex microstructure. Specimens cut from dissimilar welded joints of austenitic steel to pearlitic steel were tested by tension to rupture, with parallel AE data registration. According to the research results, the characteristic features of the AE were revealed for specimens containing defects in the form of lack of penetration as well as for specimens with diffusion interlayers. The results obtained show that the AE method can be used to test both typical welding defects and diffusion interlayers in welded joints of steels of different structural classes.

A Comparison of Cysteine-Conjugated Nitroxide Spin Labels for Pulse Dipolar EPR Spectroscopy

The structure-function and materials paradigms drive research on the understanding of structures and structural heterogeneity of molecules and solids from materials science to structural biology. Functional insights into complex architectures are often gained from a suite of complementary physicochemical methods. In the context of biomacromolecular structures, the use of pulse dipolar electron paramagnetic resonance spectroscopy (PDS) has become increasingly popular. The main interest in PDS is providing long-range nanometre distance distributions that allow for identifying macromolecular topologies, validating structural models and conformational transitions as well as docking of quaternary complexes. Most commonly, cysteines are introduced into protein structures by site-directed mutagenesis and modified site-specifically to a spin-labelled side-chain such as a stable nitroxide radical. In this contribution, we investigate labelling by four different commercial labelling agents that react through different sulfur-specific reactions. Further, the distance distributions obtained are between spin-bearing moieties and need to be related to the protein structure via modelling approaches. Here, we compare two different approaches to modelling these distributions for all four side-chains. The results indicate that there are significant differences in the optimum labelling procedure. All four spin-labels show differences in the ease of labelling and purification. Further challenges arise from the different tether lengths and rotamers of spin-labelled side-chains; both influence the modelling and translation into structures. Our comparison indicates that the spin-label with the shortest tether in the spin-labelled side-group, (bis-(2,2,5,5-Tetramethyl-3-imidazoline-1-oxyl-4-yl) disulfide, may be underappreciated and could increase the resolution of structural studies by PDS if labelling conditions are optimised accordingly.