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Acta crystallographica / Section D 77(6), 820 - 834 (2021). doi:10.1107/S2059798321003855, Fixed-target serial crystallography has become an important method for the study of protein structure and dynamics at synchrotrons and X-ray free-electron lasers. However, sample homogeneity, consumption and the physical stress on samples remain major challenges for these high-throughput experiments, which depend on high-quality protein microcrystals. The batch crystallization procedures that are typically applied require time- and sample-intensive screening and optimization. Here, a simple protein crystallization method inside the features of the HARE serial crystallography chips is reported that circumvents batch crystallization and allows the direct transfer of canonical vapor-diffusion conditions to in-chip crystallization. Based on conventional hanging-drop vapor-diffusion experiments, the crystallization solution is distributed into the wells of the HARE chip and equilibrated against a reservoir with mother liquor. Using this simple method, high-quality microcrystals were generated with sufficient density for the structure determination of four different proteins. A new protein variant was crystallized using the protein concentrations encountered during canonical crystallization experiments, enabling structure determination from ∼55 µg of protein. Additionally, structure determination from intracellular crystals grown in insect cells cultured directly in the features of the HARE chips is demonstrated. In cellulo crystallization represents a comparatively un­explored space in crystallization, especially for proteins that are resistant to crystallization using conventional techniques, and eliminates any need for laborious protein purification. This in-chip technique avoids harvesting the sensitive crystals or any further physical handling of the crystal-containing cells. These proof-of-principle experiments indicate the potential of this method to become a simple alternative to batch crystallization approaches and also as a convenient extension to canonical crystallization screens., Published by Wiley, Bognor Regis

α-Crystallins are small heat-shock proteins that act as holdase chaperones. In humans, αA-crystallin is expressed only in the eye lens, while αB-crystallin is found in many tissues. α-Crystallins have a central domain flanked by flexible extensions and form dynamic, heterogeneous oligomers. Structural models show that both the C- and N-terminal extensions are important for controlling oligomerization through domain swapping. α-Crystallin prevents aggregation of damaged β- and γ-crystallins by binding to the client protein using a variety of binding modes. α-Crystallin chaperone activity can be compromised by mutation or posttranslational modifications, leading to protein aggregation and cataract. Because of their high solubility and their ability to form large, functional oligomers, α-crystallins are particularly amenable to structure determination by solid-state nuclear magnetic resonance (NMR) and solution NMR, as well as cryo-electron microscopy.

Amyloid fibril formation is central to the etiology of a wide range of serious human diseases, such as Alzheimer’s disease and prion diseases. Despite an ever growing collection of amyloid fibril structures found in the Protein Data Bank (PDB) and numerous clinical trials, therapeutic strategies remain elusive. One contributing factor to the lack of progress on this challenging problem is incomplete understanding of the mechanisms by which these locally ordered protein aggregates self-assemble in solution. Many current models of amyloid deposition diseases posit that the most toxic species are oligomers that form either along the pathway to forming fibrils or in competition with their formation, making it even more critical to understand the kinetics of fibrillization. A recently introduced topological model for aggregation based on network Hamiltonians is capable of recapitulating the entire process of amyloid fibril formation, beginning with thousands of free monomers and ending with kinetically accessible and thermodynamically stable amyloid fibril structures. The model can be parameterized to match the five topological classes encompassing all amyloid fibril structures so far discovered in the PDB. This paper introduces a set of network statistical and topological metrics for quantitative analysis and characterization of the fibrillization mechanisms predicted by the network Hamiltonian model. The results not only provide insight into different mechanisms leading to similar fibril structures, but also offer targets for future experimental exploration into the mechanisms by which fibrils form.

The SARS-CoV-2 main protease (Mpro) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant selection pressure, with new Mpromutations arising over time. Identification and structural characterization of Mprovariants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine Mprovariants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery.

Divalent metal cations can play a role in protein aggregation diseases, including cataract. Here we compare the aggregation of human γS-crystallin, a key structural protein of the eye lens, via mutagenesis, ultraviolet light damage, and the addition of metal ions. All three aggregation pathways result in globular, amorphous-looking structures that do not elongate into fibers. We also investigate the molecular mechanism underlying copper(II)-induced aggregation. This work was motivated by the observation that zinc(II)-induced aggregation of γS-crystallin is driven by intermolecular bridging of solvent-accessible cysteine residues, while in contrast, copper(II)-induced aggregation of this protein is exacerbated by the removal of solvent-accessible cysteines via mutation. Here we find that copper(II)-induced aggregation results from a complex mechanism involving multiple interactions with the protein. The initial protein-metal interactions result in the reduction of Cu(II) to Cu(I) with concomitant oxidation of γS-crystallin. In addition to the intermolecular disulfides that represent a starting point for aggregation, intramolecular disulfides also occur in the cysteine loop, a region of the N-terminal domain that was previously found to mediate the early stages of cataract formation. This previously unobserved ability of γS-crystallin to transfer disulfides intramolecularly suggests that it may serve as an oxidation sink for the lens after glutathione levels have become depleted during aging. γS-Crystallin thus serves as the last line of defense against oxidation in the eye lens, a result that underscores the chemical functionality of this protein, which is generally considered to play a purely structural role.

Background The eye lens crystallins are highly soluble proteins that are required to last the lifespan of an organism due to low protein turnover in the lens. Crystallin aggregation leads to formation of light-scattering aggregates known as cataract. The G18V mutation of human γS-crystallin (γS-G18V), which is associated with childhood-onset cataract, causes structural changes throughout the N-terminal domain and increases aggregation propensity. The holdase chaperone protein αB-crystallin does not interact with wild-type γS-crystallin, but does bind its G18V variant. The specific molecular determinants of αB-crystallin binding to client proteins is incompletely charcterized. Here, a new variant of γS, γS-G18A, was created to test the limits of αB-crystallin selectivity. Methods Molecular dynamics simulations were used to investigate the structure and dynamics of γS-G18A. The overall fold of γS-G18A was assessed by circular dichroism (CD) spectroscopy and intrinsic tryptophan fluorescence. Its thermal unfolding temperature and aggregation propensity were characterized by CD and DLS, respectively. Solution-state NMR was used to characterize interactions between αB-crystallin and γS-G18A. Results γS-G18A exhibits minimal structural changes, but has compromised thermal stability relative to γS-WT. The placement of alanine, rather than valine, at this highly conserved glycine position produces minor changes in hydrophobic surface exposure. However, human αB-crystallin does not bind the G18A variant, in contrast to previous observations for γS-G18V, which aggregates at physiological temperature. Conclusions αB-crystallin is capable of distinguishing between aggregation-prone and function-preserving variants, and recognizing the transient unfolding or minor conformers that lead to aggregation in the disease-related variant. General significance Human αB-crystallin distinguishes between highly similar variants of a structural crystallin, binding the cataract-related γS-G18V variant, but not the function-preserving γS-G18A variant, which is monomeric at physiological temperature.

Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactions between particles, and hence is related to aggregation propensity, a property of considerable scientific and practical interest. Estimating the second virial coefficient from experimental data is challenging due both to the degree of precision required and the complexity of the error structure involved. In contrast to conventional approaches based on heuristic ordinary least squares estimates, Bayesian inference for the second virial coefficient allows explicit modeling of error processes, incorporation of prior information, and the ability to directly test competing physical models. Here, we introduce a fully Bayesian model for static light scattering experiments on small-particle systems, with joint inference for concentration, index of refraction, oligomer size, and the second virial coefficient. We apply our proposed model to study the aggregation behavior of hen egg-white lysozyme and human γS-crystallin using in-house experimental data. Based on these observations, we also perform a simulation study on the primary drivers of uncertainty in this family of experiments, showing in particular the potential for improved monitoring and control of concentration to aid inference.

Background Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms. Methods Using comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution. We utilize network analytic techniques to identify similarities and differences in chitinase topology. Results Here, we report molecular models and functional predictions from protein structure networks for eleven new chitinases from D. capensis, including a novel class IV chitinase with two active domains. This architecture has previously been observed in microorganisms but not in plants. We use a combination of comparative and de novo structure prediction followed by molecular dynamics simulation to produce models of the mature forms of these proteins in aqueous solution. Protein structure network analysis of these and other plant chitinases reveal characteristic features of the two major chitinase families. General significance This work demonstrates how computational techniques can facilitate quickly moving from raw sequence data to refined structural models and comparative analysis, and to select promising candidates for subsequent biochemical characterization. This capability is increasingly important given the large and growing body of data from high-throughput genome sequencing, which makes experimental characterization of every target impractical.

The tunicate (Ciona intestinalis) βγ-crystallin represents an intermediate case between the calcium-binding proteins ancestral to the vertebrate βγ-crystallin fold and the vertebrate structural crystallins. Unlike the structural βγ-crystallins in the vertebrate eye lens, this βγ-crystallin strongly binds Ca(2+). Furthermore, Ca(2+) binding greatly stabilizes the protein, an effect that has previously been observed in microbial βγ-crystallins but not in those of vertebrates. This relationship between binding and protein stabilization makes the tunicate βγ-crystallin an interesting model for studying the evolution of the human βγ-crystallin. We also compare and contrast the binding sites of tunicate βγ-crystallin with other βγ-crystallins in order to develop hypotheses as to the functional origin of the lack of the Ca(2+) binding sites in the human crystallins.

We describe a simplified method for improving the reproducibility of transceiver coil fabrication for nuclear magnetic resonance (NMR) through single-use templates made from 3D-printed polymer forms. The utility of dissolvable inserts for achieving performance enhanced resonators (DIAPERs) is tested herein by a comparison of RF homogeneity along the rotor axis for variable-pitch solenoids with different inter-turn spacing. Simulated B1 field profiles are compared to experimental homogeneity measurements, demonstrating the potential of this approach for making NMR coils quickly and reproducibly.

Simulations of intrinsically disordered proteins (IDP) pose numerous challenges to comparative analysis, prominently including highly dynamic conformational states and a lack of well-defined secondary structure. Machine learning (ML) algorithms are especially effective at discriminating among high-dimensional inputs whose differences are extremely subtle, making them well suited to the study of IDPs. In this work, we apply various ML techniques, including support vector machines (SVM) and clustering, as well as related methods such as principal component analysis (PCA) and protein structure network (PSN) analysis, to the problem of uncovering differences between configurational data from molecular dynamics simulations of two variants of the same IDP. We examine molecular dynamics (MD) trajectories of wild-type amyloid beta (Abeta 1-40) and its ``Arctic'' variant (E22G), systems that play a central role in the etiology of Alzheimer's disease. Our analyses demonstrate ways in which ML and related approaches can be used to elucidate subtle differences between these proteins, including transient structure that is poorly captured by conventional metrics.

Many advances in instrumentation and methodology have furthered the use of solid-state NMR as a technique for determining the structures and studying the dynamics of molecules involved in complex biological assemblies. Solid-state NMR does not require large crystals, has no inherent size limit, and with appropriate isotopic labeling schemes, supports solving one component of a complex assembly at a time. It is complementary to cryo-EM, in that it provides local, atomic-level detail that can be modeled into larger-scale structures. This review focuses on the development of high-field MAS instrumentation and methodology; including probe design, benchmarking strategies, labeling schemes, and experiments that enable the use of quadrupolar nuclei in biomolecular NMR. Current challenges facing solid-state NMR of biological assemblies and new directions in this dynamic research area are also discussed.

In plants, esterase/lipases perform transesterification reactions, playing an important role in the synthesis of useful molecules, such as those comprising the waxy coatings of leaf surfaces. Plant genomes and transcriptomes have provided a wealth of data about expression patterns and the circumstances under which these enzymes are upregulated, e.g. pathogen defense and response to drought; however, predicting their functional characteristics from genomic or transcriptome data is challenging due to weak sequence conservation among the diverse members of this group. Although functional sequence blocks mediating enzyme activity have been identified, progress to date has been hampered by the paucity of information on the structural relationships among these regions and how they affect substrate specificity. Here we present methodology for predicting overall protein flexibility and active site flexibility based on molecular modeling and analysis of protein structure networks (PSNs). We define two new types of specialized PSNs: sequence region networks (SRNs) and active site networks (ASNs), which provide parsimonious representations of molecular structure in reference to known features of interest. Our approach, intended as an aid to target selection for poorly characterized enzyme classes, is demonstrated for 26 previously uncharacterized esterase/lipases from the genome of the carnivorous plant Drosera capensis and validated using a case/control design. Analysis of the network relationships among functional blocks and among the chemical moieties making up the catalytic triad reveals potentially functionally significant differences that are not apparent from sequence analysis alone.

In his 1875 monograph on insectivorous plants, Darwin described the feeding reactions of Drosera flypaper traps and predicted that their secretions contained a “ferment” similar to mammalian pepsin, an aspartic protease. Here we report a high-quality draft genome sequence for the cape sundew, Drosera capensis}, the first genome of a carnivorous plant from order Caryophyllales, which also includes the Venus flytrap (Dionaea) and the tropical pitcher plants (Nepenthes). This species was selected in part for its hardiness and ease of cultivation, making it an excellent model organism for further investigations of plant carnivory. Analysis of predicted protein sequences yields genes encoding proteases homologous to those found in other plants, some of which display sequence and structural features that suggest novel functionalities. Because the sequence similarity to proteins of known structure is in most cases too low for traditional homology modeling, 3D structures of representative proteases are predicted using comparative modeling with all-atom refinement. Although the overall folds and active residues for these proteins are conserved, we find structural and sequence differences consistent with a diversity of substrate recognition patterns. Finally, we predict differences in substrate specificities using in silico experiments, providing targets for structure/function studies of novel enzymes with biological and technological significance. This article is protected by copyright. All rights reserved.

We demonstrate that the effect of protein crowding is critically dependent on the stability of the protein’s hydration shell, which can dramatically vary between different proteins. In the human eye lens, γS-crystallin (γS-WT) forms a densely packed transparent hydrogel with a high refractive index, making it an ideal system for studying the effects of protein crowding. A single point mutation generates the cataract-related variant γS-G18V, dramatically altering the optical properties of the eye lens. This system offers an opportunity to explore fundamental questions regarding the effect of protein crowding, using γS-WT and γS-G18V: (i) how do the diffusion dynamics of hydration water change as a function of protein crowding?; and (ii) upon hydrogel formation of γS-WT, has a dynamic transition occurred generating a single population of hydration water, or do populations of bulk and hydration water coexist? Using localized spin probes, we separately probe the local translational diffusivity of both surface hydration and interstitial water of γS-WT and γS-G18V in solution. Surprisingly, we find that under the influence of hydrogel formation at highly crowded γS-WT concentrations up to 500 mg/mL, the protein hydration shell remains remarkably dynamic, slowing by less than a factor of two, if at all, compared to that in dilute protein solutions of ~5 mg/mL. Upon self-crowding, the population of this robust surface hydration water increases, while a significant bulk-like water population coexists even at ~500 mg/mL protein concentrations. In contrast, surface water of γS-G18V irreversibly dehydrates with moderate concentration increases or subtle alterations to the solution conditions, demonstrating that the effect of protein crowding is highly dependent on the stability of the protein-specific hydration shell. The core function of γS-crystallin in the eye lens may be precisely its capacity to preserve a robust hydration shell, whose stability is abolished by a single G18V mutation.

Carnivorous plants represent a so far underexploited reservoir of novel proteases with potentially useful activities. Here we investigate 44 cysteine proteases from the Cape sundew, Drosera capensis, predicted from genomic DNA sequences. D. capensis has a large number of cysteine protease genes; analysis of their sequences reveals homologs of known plant proteases, some of which are predicted to have novel properties. Many functionally significant sequence and structural features are observed, including targeting signals and occluding loops. Several of the proteases contain a new type of granulin domain. Although active site residues are conserved, the sequence identity of these proteases to known proteins is moderate to low; therefore, comparative modeling with all-atom refinement and subsequent atomistic MD-simulation is used to predict their 3D structures. The structure prediction data, as well as analysis of protein structure networks, suggest multifarious variations on the papain-like cysteine protease structural theme. This in silico methodology provides a general framework for investigating a large pool of sequences that are potentially useful for biotechnology applications, enabling informed choices about which proteins to investigate in the laboratory., Graphical abstract Image 1, Highlights • 44 new cysteine proteases from the carnivorous plant Drosera capensis are described. • Structure prediction and molecular dynamics simulation predict overall folds similar to papain. • Functionally significant sequence and structural features are observed, including targeting signals and occluding loops. • Several of the proteases contain a new type of granulin domain. • Protein structure networks reveal global differences in interactions among chemical groups.

Background The objective of this study was to determine whether the cataract-related G18V variant of human γ S-crystallin has increased exposure of hydrophobic residues that could explain its aggregation propensity and/or recognition by α B-crystallin. Methods We used an ANS fluorescence assay and NMR chemical shift perturbation to experimentally probe exposed hydrophobic surfaces. These results were compared to flexible docking simulations of ANS molecules to the proteins, starting with the solution-state NMR structures of γ S-WT and γ S-G18V. Results γ S-G18V exhibits increased ANS fluorescence, suggesting increased exposed hydrophobic surface area. The specific residues involved in ANS binding were mapped by NMR chemical shift perturbation assays, revealing ANS binding sites in γ S-G18V that are not present in γ S-WT. Molecular docking predicts three binding sites that are specific to γ S-G18V corresponding to the exposure of a hydrophobic cavity located at the interdomain interface, as well as two hydrophobic patches near a disordered loop containing solvent-exposed cysteines, all but one of which is buried in γ S-WT. Conclusions Although both proteins display non-specific binding, more residues are involved in ANS binding to γ S-G18V, and the affected residues are localized in the N-terminal domain and the nearby interdomain interface, proximal to the mutation site. General significance Characterization of changes in exposed hydrophobic surface area between wild-type and variant proteins can help elucidate the mechanisms of aggregation propensity and chaperone recognition, presented here in the context of cataract formation. Experimental data and simulations provide complementary views of the interactions between proteins and the small molecule probes commonly used to study aggregation. This article is part of a Special Issue entitled Crystallin Biochemistry in Health and Disease.

The Droserasins, aspartic proteases from the carnivorous plant Drosera capensis, contain a 100-residue plant-specific insert (PSI) that is post-translationally cleaved and independently acts as an antimicrobial peptide. PSIs are of interest not only for their inhibition of microbial growth, but also because they modify the size of lipid vesicles and strongly interact with biological membranes. PSIs may therefore be useful for modulating lipid systems in NMR studies of membrane proteins. Here we present the expression and biophysical characterization of the Droserasin 1 PSI (D1 PSI.) This peptide is monomeric in solution and maintains its primarily &alpha, helical secondary structure over a wide range of temperatures and pH values, even under conditions where its three disulfide bonds are reduced. Vesicle fusion assays indicate that the D1 PSI strongly interacts with bacterial and fungal lipids at pH 5 and lower, consistent with the physiological pH of D. capensis mucilage. It binds lipids with a variety of head groups, highlighting its versatility as a potential stabilizer for lipid nanodiscs. Solid-state NMR spectra collected at a field strength of 36 T, using a unique series-connected hybrid magnet, indicate that the peptide is folded and strongly bound to the membrane. Molecular dynamics simulations indicate that the peptide is stable as either a monomer or a dimer in a lipid bilayer. Both the monomer and the dimer allow the passage of water through the membrane, albeit at different rates.

The refractive index gradient of the eye lens is controlled by the concentration and distribution of its component crystallin proteins, which are highly enriched in polarizable amino acids. The current understanding of the refractive index increment ([Formula: see text]) of proteins is described using an additive model wherein the refractivity and specific volume of each amino acid type contributes according to abundance in the primary sequence. Here we present experimental measurements of [Formula: see text] for crystallins from the human lens and those of aquatic animals under uniform solvent conditions. In all cases, the measured values are much higher than those predicted from primary sequence alone, suggesting that structural factors also contribute to protein refractive index.

Liquid–liquid phase separation (LLPS) of proteins is important to a variety of biological processes both functional and deleterious, including the formation of membraneless organelles, molecular condensations that sequester or release molecules in response to stimuli, and the early stages of disease-related protein aggregation. In the protein-rich, crowded environment of the eye lens, LLPS manifests as cold cataract. We characterize the LLPS behavior of six structural γ-crystallins from the eye lens of the Antarctic toothfish Dissostichus mawsoni, whose intact lenses resist cold cataract in subzero waters. Phase separation of these proteins is not strongly correlated with thermal stability, aggregation propensity, or cross-species chaperone protection from heat denaturation. Instead, LLPS is driven by protein–protein interactions involving charged residues. The critical temperature of the phase transition can be tuned over a wide temperature range by selective substitution of surface residues, suggesting general principles for controlling this phenomenon, even in compactly folded proteins.

© 2014 American Chemical Society. The γS1- and γS2-crystallins, structural eye lens proteins from the Antarctic toothfish (Dissostichus mawsoni), are homologues of the human lens protein γS-crystallin. Although γS1 has the higher thermal stability of the two, it is more susceptible to chemical denaturation by urea. The lower thermodynamic stability of both toothfish crystallins relative to human γS-crystallin is consistent with the current picture of how proteins from organisms endemic to perennially cold environments have achieved low-temperature functionality via greater structural flexibility. In some respects, the sequences of γS1- and γS2-crystallin are typical of psychrophilic proteins; however, their amino acid compositions also reflect their selection for a high refractive index increment. Like their counterparts in the human lens and those of mesophilic fish, both toothfish crystallins are relatively enriched in aromatic residues and methionine and exiguous in aliphatic residues. The sometimes contradictory requirements of selection for cold tolerance and high refractive index make the toothfish crystallins an excellent model system for further investigation of the biophysical properties of structural proteins.

Transparency in the eye lens is maintained via specific, functional interactions among the structural βγ- and chaperone α-crystallins. Here we report the structure and α-crystallin binding interface of the G18V variant of human γS-crystallin (γS-G18V), which is linked to hereditary childhood-onset cortical cataract. Comparison of the solution NMR structures of wild-type and G18V γS-crystallin, both presented here, reveal that the increased aggregation propensity of γS-G18V results from neither global misfolding nor the solvent exposure of a hydrophobic residue, but instead involves backbone rearrangement within the N-terminal domain. αB-crystallin binds more strongly to the variant, via a well-defined interaction surface that represents the first such interface directly observed between a variant structural crystallin and α-crystallin. In the context of the αB-crystallin structure and the finding that it forms heterogeneous multimers, our structural studies suggest a potential mechanism for cataract formation via the depletion of the finite αB-crystallin population of the lens.

In systems where the dipolar couplings are partially averaged by molecular motion, cross-polarization is modulated by sample spinning. The cross-polariation efficiency in Variable Angle Spinning (VAS) and Switched Angle Spinning (SAS) experiments on mobile samples is therefore strongly dependent on the spinning angle. We describe simulations and experimental measurements of these effects over a range of spinning angles from 0° to 90°.

Molecular dynamics (MD) simulations, circular dichroism (CD), and dynamic light scattering (DLS) measurements were used to investigate the aggregation propensity of the eye-lens protein γS-crystallin. The wild-type protein was investigated along with the cataract-related G18V variant and the symmetry-related G106V variant. The MD simulations suggest that local sequence differences result in dramatic differences in dynamics and hydration between these two apparently similar point mutations. This finding is supported by the experimental measurements, which show that although both variants appear to be mostly folded at room temperature, both display increased aggregation propensity. Although the disease-related G18V variant is not the most strongly destabilized, it aggregates more readily than either the wild-type or the G106V variant. These results indicate that γS-crystallin provides an excellent model system for investigating the role of dynamics and hydration in aggregation by locally unfolded proteins.

Purpose Cataract results from the formation of light-scattering precipitates due to point mutations or accumulated damage in the structural crystallins of the eye lens. Although excised cataracts are predominantly amorphous, in vitro studies show that crystallins are capable of adopting a variety of morphologies depending on the preparation method. Here we characterize thermal, pH-dependent, and UV-irradiated aggregates from wild-type human γS-crystallin (γS-WT) and its aggregation-prone variant, γS-G18V. Methods Aggregates of γS-WT and γS-G18V were prepared under acidic, neutral, and basic pH conditions and held at 25°C or 37°C for 48 hours. UV-induced aggregates were produced by irradiation with a 355-nm laser. Aggregation and fibril formation were monitored via turbidity and thioflavin T (ThT) assays. Aggregates were characterized using intrinsic aromatic fluorescence, powder x-ray diffraction, and mass spectrometry. Results γS-crystallin aggregates displayed different characteristics depending on the preparation method. γS-G18V produced a larger amount of detectable aggregates than did γS-WT and at less-extreme conditions. Aggregates formed under basic and acidic conditions yielded elevated ThT fluorescence; however, aggregates formed at low pH did not produce strongly turbid solutions. UV-induced aggregates produced highly turbid solutions but displayed only moderate ThT fluorescence. X-ray diffraction confirms amyloid character in low-pH samples and UV-irradiated samples, although the relative amounts vary. Conclusions γS-G18V demonstrates increased aggregation propensity compared to γS-WT when treated with heat, acid, or UV light. The resulting aggregates differ in their ThT fluorescence and turbidity, suggesting that at least two different aggregation pathways are accessible to both proteins under the conditions tested.