Assessment of structure factors for analysis of small-angle scattering data from desired or undesired aggregates

Validation of electron-microscopy maps using solution small-angle X-ray scattering

The determination of the atomic resolution structure of biomacromolecules is essential for understanding details of their function. Traditionally, such a structure determination has been performed with crystallographic or nuclear resonance methods, but during the last decade, cryogenic transmission electron microscopy (cryo-TEM) has become an equally important tool. As the blotting and flash-freezing of the samples can induce conformational changes, external validation tools are required to ensure that the vitrified samples are representative of the solution. Although many validation tools have already been developed, most of them rely on fully resolved atomic models, which prevents early screening of the cryo-TEM maps. Here, a novel and automated method for performing such a validation utilizing small-angle X-ray scattering measurements, publicly available through the new software package AUSAXS, is introduced and implemented. The method has been tested on both simulated and experimental data, where it was shown to work remarkably well as a validation tool. The method provides a dummy atomic model derived from the EM map which best represents the solution structure.

Recovery from desensitization in GluA2 AMPA receptors is affected by a single mutation in the N-terminal domain interface

AMPA-type ionotropic glutamate receptors (AMPARs) are central to various neurological processes, including memory and learning. They assemble as homo- or heterotetramers of GluA1, GluA2, GluA3, and GluA4 subunits, each consisting of an N-terminal domain (NTD), a ligand-binding domain, a transmembrane domain, and a C-terminal domain. While AMPAR gating is primarily controlled by reconfiguration in the ligand-binding domain layer, our study focuses on the NTDs, which also influence gating, yet the underlying mechanism remains enigmatic. In this investigation, we employ molecular dynamics simulations to evaluate the NTD interface strength in GluA1, GluA2, and NTD mutants GluA2-H229N and GluA1-N222H. Our findings reveal that GluA1 has a significantly weaker NTD interface than GluA2. The NTD interface of GluA2 can be weakened by a single point mutation in the NTD dimer-of-dimer interface, namely H229N, which renders GluA2 more GluA1-like. Electrophysiology recordings demonstrate that this mutation also leads to slower recovery from desensitization. Moreover, we observe that lowering the pH induces more splayed NTD states and enhances desensitization in GluA2. We hypothesized that H229 was responsible for this pH sensitivity; however, GluA2-H229N was also affected by pH, meaning that H229 is not solely responsible and that protons exert their effect across multiple domains of the AMPAR. In summary, our work unveils an allosteric connection between the NTD interface strength and AMPAR desensitization.

Structural basis for kinase inhibition in the tripartite E. coli HipBST toxin-antitoxin system

Many bacteria encode multiple toxin-antitoxin (TA) systems targeting separate, but closely related, cellular functions. The toxin of the Escherichia coli hipBA system, HipA, is a kinase that inhibits translation via phosphorylation of glutamyl-tRNA synthetase. Enteropathogenic E. coli O127:H6 encodes the hipBA-like, tripartite TA system; hipBST, in which the HipT toxin specifically targets the tryptophanyl-tRNA synthetase, TrpS. Notably, in the tripartite system, the function as antitoxin has been taken over by the third protein, HipS, but the molecular details of how activity of HipT is inhibited remain poorly understood. Here, we show that HipBST is structurally different from E. coli HipBA and that the unique HipS protein, which is homologous to the N-terminal subdomain of HipA, inhibits the kinase through insertion of a conserved Trp residue into the active site. We also show how auto-phosphorylation at two conserved sites in the kinase toxin serve different roles and affect the ability of HipS to neutralize HipT. Finally, solution structural studies show how phosphorylation affects overall TA complex flexibility.

Periostin C-Terminal Is Intrinsically Disordered and Interacts with 143 Proteins in an In Vitro Epidermal Model of Atopic Dermatitis

Human periostin is a 78-91 kDa matricellular protein implicated in extracellular matrix remodeling, tumor development, metastasis, and inflammatory diseases like atopic dermatitis, psoriasis, and asthma. The protein consists of six domains, including an N-terminal Cys-rich CROPT domain, four fasciclin-1 domains, and a C-terminal domain. The exons encoding the C-terminal domain may be alternatively spliced by shuffling four exons, generating ten variants of unknown function. Here, we investigate the structure and interactome of the full-length variant of the C-terminal domain with no exons spliced out. The structural analysis showed that the C-terminal domain lacked a tertiary structure and was intrinsically disordered. In addition, we show that the motif responsible for heparin-binding is in the conserved very C-terminal part of periostin. Pull-down confirmed three known interaction partners and identified an additional 140 proteins, among which nine previously have been implicated in atopic dermatitis. Based on our findings, we suggest that the C-terminal domain of periostin facilitates interactions between connective tissue components in concert with the four fasciclin domains.

Critical nanomaterial attributes of iron-carbohydrate nanoparticles: Leveraging orthogonal methods to resolve the 3-dimensional structure

Intravenous iron-carbohydrate nanomedicines are widely used to treat iron deficiency and iron deficiency anemia across a wide breadth of patient populations. These colloidal solutions of nanoparticles are complex drugs which inherently makes physicochemical characterization more challenging than small molecule drugs. There have been advancements in physicochemical characterization techniques such as dynamic light scattering and zeta potential measurement, that have provided a better understanding of the physical structure of these drug products in vitro. However, establishment and validation of complementary and orthogonal approaches are necessary to better understand the 3-dimensional physical structure of the iron-carbohydrate complexes, particularly with regard to their physical state in the context of the nanoparticle interaction with biological components such as whole blood (i.e. the nano-bio interface).

Shape2SAS: a web application to simulate small-angle scattering data and pair distance distributions from user-defined shapes

Shape2SAS is a web application that allows researchers and students to build intuition about and understanding of small-angle scattering. It is available at https://somo.chem.utk.edu/shape2sas. The user defines a model of arbitrary shape by combining geometrical subunits, and Shape2SAS then calculates and displays the scattering intensity and the pair distance distribution, as well as a visualization of the user-defined shape. Simulated data with realistic noise are also generated. Here, it is demonstrated how Shape2SAS can calculate and display the different scattering patterns for various geometrical shapes, such as spheres and cylinders. It is also shown how the effect of structure factors can be visualized. Finally, it is indicated how multi-contrast particles can readily be generated, and how the calculated scattering may be used to validate and visualize analytical models generated in analysis software for fitting small-angle scattering data.

Derivation of the small-angle scattering profile of a target biomacromolecule from a profile deteriorated by aggregates. AUC-SAS

Aggregates cause a fatal problem in the structural analysis of a biomacro-mol-ecule in solution using small-angle X-ray or neutron scattering (SAS): they deteriorate the scattering profile of the target molecule and lead to an incorrect structure. Recently, an integrated method of analytical ultracentrifugation (AUC) and SAS, abbreviated AUC-SAS, was developed as a new approach to overcome this problem. However, the original version of AUC-SAS does not offer a correct scattering profile of the target molecule when the weight fraction of aggregates is higher than ca 10%. In this study, the obstacle point in the original AUC-SAS approach is identified. The improved AUC-SAS method is then applicable to a solution with a relatively larger weight fraction of aggregates (≤20%).

Modeling of flexible membrane-bound biomolecular complexes for solution small-angle scattering

Recent advances in protein expression protocols, sample handling, and experimental set up of small-angle scattering experiments have allowed users of the technique to structurally investigate biomolecules of growing complexity and structural disorder. Notable examples include intrinsically disordered proteins, multi-domain proteins and membrane proteins in suitable carrier systems. Here, we outline a modeling scheme for calculating the scattering profiles from such complex samples. This kind of modeling is necessary for structural information to be refined from the corresponding data. The scheme bases itself on a hybrid of classical form factor based modeling and the well-known spherical harmonics-based formulation of small-angle scattering amplitudes. Our framework can account for flexible domains alongside other structurally elaborate components of the molecular system in question. We demonstrate the utility of this modeling scheme through a recent example of a structural model of the growth hormone receptor membrane protein in a phospholipid bilayer nanodisc which is refined against experimental SAXS data. Additionally we investigate how the scattering profiles from the complex would appear under different scattering contrasts. For each contrast situation we discuss what structural information is contained and the related consequences for modeling of the data.

Computational Reverse-Engineering Analysis for Scattering Experiments for Form Factor and Structure Factor Determination ("P(q) and S(q) CREASE")

In this paper, we present an open-source machine learning (ML)-accelerated computational method to analyze small-angle scattering profiles [I(q) vs q] from concentrated macromolecular solutions to simultaneously obtain the form factor P(q) (e.g., dimensions of a micelle) and the structure factor S(q) (e.g., spatial arrangement of the micelles) without relying on analytical models. This method builds on our recent work on Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) that has either been applied to obtain P(q) from dilute macromolecular solutions (where S(q) ∼1) or to obtain S(q) from concentrated particle solutions when P(q) is known (e.g., sphere form factor). This paper's newly developed CREASE that calculates P(q) and S(q), termed as "P(q) and S(q) CREASE", is validated by taking as input I(q) vs q from in silico structures of known polydisperse core(A)-shell(B) micelles in solutions at varying concentrations and micelle-micelle aggregation. We demonstrate how "P(q) and S(q) CREASE" performs if given two or three of the relevant scattering profiles-I _total(q), I _A(q), and I _B(q)-as inputs; this demonstration is meant to guide experimentalists who may choose to do small-angle X-ray scattering (for total scattering from the micelles) and/or small-angle neutron scattering with appropriate contrast matching to get scattering solely from one or the other component (A or B). After validation of "P(q) and S(q) CREASE" on in silico structures, we present our results analyzing small-angle neutron scattering profiles from a solution of core-shell type surfactant-coated nanoparticles with varying extents of aggregation.

Tuning the Phytoglycogen Size and Aggregate Structure with Solvent Quality: Influence of Water-Ethanol Mixtures Revealed by X-ray and Light Scattering Techniques

Phytoglycogen (PG) is a hyperbranched polysaccharide with promising properties for biomedical and pharmaceutical applications. Herein, we explore the size and structure of sweet corn PG nanoparticles and their aggregation in water-ethanol mixtures up to the ethanol mole fraction x_EtOH = 0.364 in dilute concentrations using small-angle X-ray scattering (SAXS) and dynamic light scattering (DLS) measurements. Between 0 ≤ x_EtOH ≤ 0.129, the conformation of PG contracts gradually decreasing up to ca. 80% in hydrodynamic volume, when measured shortly after ethanol addition. For equilibrated PG dispersions, SAXS suggests a lower PG volume decrease between 19 and 67% at the corresponding x_EtOH range; however, the inflection point of the DLS volume contraction coincides with the onset of reduced colloidal stability observed with SAXS. Up to x_EtOH = 0.201, the water-ethanol mixtures yield labile fractal and globular aggregates, as evidenced by their partial breakup under mild ultrasonic treatment, demonstrated by the decrease in their hydrodynamic size. Between 0.235 ≤ x_EtOH ≤ 0.364, PG nanoparticles form larger, more cohesive globular aggregates that are less affected by ultrasonic shear forces.

A model on an absolute scale for the small-angle X-ray scattering from bovine casein micelles

Casein micelles extracted from milk are 100-400 nm-sized particles, made up of proteins and calcium phosphates, with the latter as colloidal calcium phosphate particles (CCPs) in a size range of 2-4 nm embedded in a protein network. The hierarchical structures give rise to a variation of scattering intensity over many orders of magnitude, which can be measured by small-angle X-ray scattering and static light scattering. Expressions for the scattering intensity of a general simple model for composite particles with polydispersities of overall size and subparticles are derived, and some approximations are checked by generating scattering data for systems generated by Monte Carlo simulations. Based on the simpler models, a new model has been developed for casein micelles, where the scattering is expressed on an absolute scale and where the concentrations of, respectively, protein and CCPs are used as constraints, providing a consistent model. The CCPs are modelled as oblate ellipsoids and the protein as star structures. Correlations between the substructures of CCPs and protein structures are taken into account in terms of partial structure factors. The overall structure as well as some heterogeneities at intermediate length scale are modelled as polydisperse spheres. The model fits the data very well on all length scales and demonstrates that both the scattering from CCPs and protein is important. Thus, the model provides a detailed description of the casein structure, which is consistent with the information available in the literature.

Computational Reverse-Engineering Analysis for Scattering Experiments (CREASE) with Machine Learning Enhancement to Determine Structure of Nanoparticle Mixtures and Solutions

We present a new open-source, machine learning (ML) enhanced computational method for experimentalists to quickly analyze high-throughput small-angle scattering results from multicomponent nanoparticle mixtures and solutions at varying compositions and concentrations to obtain reconstructed 3D structures of the sample. This new method is an improvement over our original computational reverse-engineering analysis for scattering experiments (CREASE) method (ACS Materials Au2021, 1 (2 (2), ), 140-156), which takes as input the experimental scattering profiles and outputs a 3D visualization and structural characterization (e.g., real space pair-correlation functions, domain sizes, and extent of mixing in binary nanoparticle mixtures) of the nanoparticle mixtures. The new gene-based CREASE method reduces the computational running time by >95% as compared to the original CREASE and performs better in scenarios where the original CREASE method performed poorly. Furthermore, the ML model linking features of nanoparticle solutions (e.g., concentration, nanoparticles' tendency to aggregate) to a computed scattering profile is generic enough to analyze scattering profiles for nanoparticle solutions at conditions (nanoparticle chemistry and size) beyond those that were used for the ML training. Finally, we demonstrate application of this new gene-based CREASE method for analysis of small-angle X-ray scattering results from a nanoparticle solution with unknown nanoparticle aggregation and small-angle neutron scattering results from a binary nanoparticle assembly with unknown mixing/segregation among the nanoparticles.

Structure and Orientation of the SARS-Coronavirus-2 Spike Protein at Air-Water Interfaces

The SARS coronavirus 2 (SARS-CoV-2) spike protein is located at the outermost perimeter of the viral envelope and is the first component of the virus to make contact with surrounding interfaces. The stability of the spike protein when in contact with surfaces plays a deciding role for infection pathways and for the viability of the virus after surface contact. While cryo-EM structures of the spike protein have been solved with high resolution and structural studies in solution have provided information about the secondary and tertiary structures, only little is known about the folding when adsorbed to surfaces. We here report on the secondary structure and orientation of the S1 segment of the spike protein, which is often used as a model protein for in vitro studies of SARS-CoV-2, at the air-water interface using surface-sensitive vibrational sum-frequency generation (SFG) spectroscopy. The air-water interface plays an important role for SARS-CoV-2 when suspended in aerosol droplets, and it serves as a model system for hydrophobic surfaces in general. The SFG experiments show that the S1 segment of the spike protein remains folded at the air-water interface and predominantly binds in its monomeric state, while the combination of small-angle X-ray scattering and two-dimensional infrared spectroscopy measurements indicate that it forms hexamers with the same secondary structure in aqueous solution.

Small-angle X-ray scattering to quantify the incorporation and analyze the disposition of magnetic nanoparticles inside cells

Access to detailed information on cells loaded with nanoparticles with nanoscale precision is of a long-standing interest in many areas of nanomedicine. In this context, designing a single experiment able to provide statistical mean data from a large number of living unsectioned cells concerning information on the nanoparticle size and aggregation inside cell endosomes and accurate nanoparticle cell up-take is of paramount importance. Small-angle X-ray scattering (SAXS) is presented here as a tool to achieve such relevant data. Experiments were carried out in cultures of B16F0 murine melanoma and A549 human lung adenocarcinoma cell lines loaded with various iron oxide nanostructures displaying distinctive structural characteristics. Five systems of water-dispersible magnetic nanoparticles (MNP) of different size, polydispersity and morphology were analyzed, namely, nearly monodisperse MNP with 11 and 13 nm mean size coated with meso-2,3-dimercaptosuccinic acid, more polydisperse 6 nm colloids coated with citric acid and two nanoflowers (NF) systems of 24 and 27 nm in size resulting from the aggregation of 8 nm MNP. Up-take was determined for each system using B16F0 cells. Here we show that SAXS pattern provides high resolution information on nanoparticles disposition inside endosomes of the cytoplasm through the structure factor analysis, on nanoparticles size and dispersity after their incorporation by the cell and on up-take quantification from the extrapolation of the intensity in absolute scale to null scattering vector. We also report on the cell culture preparation to reach sensitivity for the observation of MNP inside cell endosomes using high brightness SAXS synchrotron source. Our results show that SAXS can become a valuable tool for analyzing MNP in cells and tissues.

An Atomistic Model Describing the Structure and Morphology of Cu-Doped C-S-H Hardening Accelerator Nanoparticles

Calcium silicate hydrate (C-S-H) is the main binding phase in Portland cement. The addition of C-S-H nanoparticles as nucleation seeds has successfully been used to accelerate the hydration process and the precipitation of binding phases either in conventional Portland cement or in alternative binders. Indeed, the modulation of the hydration kinetics during the early-stage dissolution-precipitation reactions, by acting on the nucleation and growth of binding phases, improves the early strength development. The fine-tuning of concrete properties in terms of compressive strength and durability by designed structural modifications can be achieved through the detailed description of the reaction products at the atomic scale. The nano-sized, chemically complex and structurally disordered nature of these phases hamper their thorough structural characterization. To this aim, we implement a novel multi-scale approach by combining forefront small-angle X-ray scattering (SAXS) and synchrotron wide-angle X-ray total scattering (WAXTS) analyses for the characterization of Cu-doped C-S-H nanoparticles dispersed in a colloidal suspension, used as hardening accelerator. SAXS and WAXTS data were analyzed under a unified modeling approach by developing suitable atomistic models for C-S-H nanoparticles to be used to simulate the experimental X-ray scattering pattern through the Debye scattering equation. The optimization of atomistic models against the experimental pattern, together with complementary information on the structural local order from ²⁹Si solid-state nuclear magnetic resonance and X-ray absorption spectroscopy, provided a comprehensive description of the structure, size and morphology of C-S-H nanoparticles from the atomic to the nanometer scale. C-S-H nanoparticles were modeled as an assembly of layers composed of 7-fold coordinated Ca atoms and decorated by silicate dimers and chains. The structural layers are a few tens of nanometers in length and width, with a crystal structure resembling that of a defective tobermorite, but lacking any ordering between stacking layers.

Size-induced amorphous structure in tungsten oxide nanoparticles

The properties of functional materials are intrinsically linked to their atomic structure. When going to the nanoscale, size-induced structural changes in atomic structure often occur, however these are rarely well-understood. Here, we systematically investigate the atomic structure of tungsten oxide nanoparticles as a function of the nanoparticle size and observe drastic changes when the particles are smaller than 5 nm, where the particles are amorphous. The tungsten oxide nanoparticles are synthesized by thermal decomposition of ammonium metatungstate hydrate in oleylamine and by varying the ammonium metatungstate hydrate concentration, the nanoparticle size, shape and structure can be controlled. At low concentrations, nanoparticles with a diameter of 2-4 nm form and adopt an amorphous structure that locally resembles the structure of polyoxometalate clusters. When the concentration is increased the nanoparticles become elongated and form nanocrystalline rods up to 50 nm in length. The study thus reveals a size-dependent amorphous structure when going to the nanoscale and provides further knowledge on how metal oxide crystal structures change at extreme length scales.

Computational Reverse-Engineering Analysis for Scattering Experiments of Assembled Binary Mixture of Nanoparticles

In this paper, we describe a computational method for analyzing results from scattering experiments on dilute solutions of supraparticles, where each supraparticle is created by the assembly of nanoparticle mixtures. Taking scattering intensity profiles and nanoparticle mixture composition and size distributions in each supraparticle as input, this computational approach called computational reverse engineering analysis for scattering experiments (CREASE) uses a genetic algorithm to output information about the structure of the assembled nanoparticles (e.g., real space pair correlation function, extent of nanoparticle mixing/segregation, sizes of domains) within a supraparticle. We validate this method by taking as input in silico scattering intensity profiles from coarse-grained molecular simulations of a binary mixture of nanoparticles, forming a close-packed structure and testing if our computational method can correctly reproduce the nanoparticle structure observed in those simulations. We test the strengths and limitations of our method using a variety of in silico scattering intensity profiles obtained from simulations of a spherical or a cubic supraparticle comprising binary nanoparticle mixtures with varying chemistries, with and without dispersity in sizes, that exhibit well-mixed to strongly segregated structures. The strengths of the presented method include its capability to analyze scattering intensity profiles even when the wavevector q range is limited, to handily provide all of the pairwise radial distribution functions, and to correctly determine the extent of segregation/mixing of the nanoparticles assembled in complex geometries.

From Nanoparticle Heteroclusters to Filament Networks by Self-Assembly at the Water-Oil Interface of Reverse Microemulsions

Surface self-assembly of spherical nanoparticles of sizes below 10 nm into hierarchical heterostructures is under arising development despite the inherent difficulties of obtaining complex ordering patterns on a larger scale. Due to template-mediated interactions between oil-dispersible superparamagnetic nanoparticles (MNPs) and polyethylenimine-stabilized gold nanoparticles (Au(PEI)NPs) at the water-oil interface of microemulsions, complex nanostructured films can be formed. Characterization of the reverse microemulsion phase by UV-vis absorption revealed the formation of heteroclusters from Winsor type II phases (WPII) using Aerosol-OT (AOT) as the surfactant. SAXS measurements verify the mechanism of initial nanoparticle clustering in defined dimensions. XPS suggested an influence of AOT at the MNP surface. Further, cryo-SEM and TEM visualization demonstrated the elongation of the reverse microemulsions into cylindrical, wormlike structures, which subsequently build up larger nanoparticle superstructure arrangements. Such WPII phases are thus proven to be a new form of soft template, mediating the self-assembly of different nanoparticles in hierarchical network-like filaments over a substrate during solvent evaporation.

Understanding the Structural Pathways for Lipid Nanodisc Formation: How Styrene Maleic Acid Copolymers Induce Membrane Fracture and Disc Formation

Lipid nanodiscs formed by mixtures of styrene maleic acid (SMA) copolymers and lipid membranes are important tools for studying membrane proteins in many biotechnological applications. However, molecular interactions leading up to their formation are not well understood. Here, we elucidate the nanodisc formation pathways for SMA/lipid vesicle mixtures using small-angle X-ray scattering (SAXS) that allows detailed in situ nanostructural information. SMA copolymer that is initially aggregated in solution inserts its styrene units into the lipid bilayer hydrocarbon region, leading to fractures in the membrane. The initial copolymer-lipid interactions observed in the vesicles are also present in the formed discs, with excess copolymer distributed along the normal of the bilayer. The size and SMA distribution in the resulting discs strongly depend on the temperature, lipid/copolymer ratio, and lipid type. We find that the solubilization limit increases for membranes above the melting point, suggesting that defects in gel-like lipid membranes play a significant role in membrane fracturing and nanodisc formation. These findings provide unique insights into the formation of nanodiscs as well as into the microscopic mechanism of solubilization, which plays an important role in many applications and products ranging from household goods to biotechnology and medicine.