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Introduction & Background Linking social media and survey data at the individual level has the potential to add evidence to a variety of research questions. To make this data openly available to others, social media data need to be converted into useful metrics that minimise issues of disclosure while maximising utility. This research explores linkages of Twitter data and survey data in the Understanding Society Innovation panel, focusing on the usage of non-disclosive metrics created from Twitter data alongside the similarly anonymised survey data. Objectives & Approach The Innovation Panel asked for consent to link Twitter data to survey responses and data has been collected from the Twitter API. However, Twitter’s unstructured nature necessitates creating measures that can be used jointly with linked survey data. We have developed a framework to create social media metrics that can be combined with survey data that also remove any disclosive data, so these data can be widely shared for maximum utility. The current research analyses these data to understand what the metrics look like through presentation of descriptive statistics. We also begin to show these data may be used in combination with survey data through inclusion of a set of metrics in logistic regression models predicting attrition and measurement of mental health. Relevance to Digital Footprints Social media is a prevalent aspect of social life and leaves a substantial digital footprint. However, there are a number of limitations to these data, including a lack of understanding of who is producing the data, and having the ability to relate these to a variety of specific (and possibly higher quality) measures for a representative sample of the population. Linkage to surveys address these problems and can lead to new research opportunities using digital footprint data. Results While small sample sizes impact the power of some analyses, the methods developed are illustrative of ways to use this novel data source. Results show that there is high variation in the created metrics, and initial analysis shows that the inclusion of a set of user-level Twitter data is not significantly related to attrition. However, more accounts followed on Twitter and the number of user retweets are significantly related to higher levels of mental distress on the GHQ scale. Conclusions & Implications Overall, there is some evidence that social media helps to understand survey outcomes, perhaps more so on measurement outcomes. This study provides an initial start on how to use these curated linked social media and survey data, and we note there are other social media networks that we can apply this strategy to; for example, LinkedIn, particularly with changes made to Twitter (X).

Introduction & Background LinkedIn, with its extensive global network of over 900 million members across more than 200 countries, presents a unique repository for examining labour market dynamics, professional development, and the impact of social networking on employment opportunities. Despite its potential, LinkedIn's wealth of data on professional trajectories, skills, and labour market outcomes remains largely untapped in survey research due to challenges in data collection. Objectives & Approach This paper introduces a novel methodology for integrating LinkedIn data with survey responses using data from the fourteenth wave of the Innovation Panel (IP14) of Understanding Society: The UK Household Longitudinal Study (UKHLS), conducted in 2021. In IP14, we probed the extent of LinkedIn usage among the UK population and assessed users' willingness to link their LinkedIn profiles with their survey responses. Those consenting to link their accounts were asked for specific details — namely their first and last names, employer, and job title — to enable profile identification on LinkedIn. Faced with the unavailability of a unique platform identifier and the cessation of LinkedIn’s API, this information was crucial for matching profiles accurately. We crafted a framework using PhantomBuster for ethical data extraction and a probabilistic string-matching technique to ensure precise linkage between survey responses and LinkedIn profiles. PhantomBuster, a cloud-based tool, efficiently scrapes dynamic content using JavaScript in a headless browser environment, sidestepping IP-related restrictions while adhering to website terms of service. It streamlines the data collection process. Identified profiles were subjected to an iterative probabilistic string matching, using respondent-provided metadata alongside supplementary data, to maximize the accuracy of matching the profiles to our survey participants. Relevance to Digital Footprints The described method advances digital footprint research in data collection and linkage. It automates the retrieval of vast online data sets; compiles information efficiently in an organized format; saves time and labour by mechanizing monotonous tasks; circumvents platform-imposed IP restrictions; and imposes fewer barriers to entry as it requires less technical skill than other scraping tools like Selenium. Conclusions & Implications This approach not only facilitates the precise identification and collection of LinkedIn profile data but also sets a precedent for ethical considerations in web scraping practices. By documenting this methodology, we aim to equip researchers with a scalable and replicable tool for future studies, enriching the analysis of labour market outcomes and the interplay between formal education, informal training, and professional success through the integration of LinkedIn and survey data.

Introduction & Background Uses and gratification (U&G) theory posits individuals’ engagement with social media is a deliberate effort to fulfill various needs, like information seeking, entertainment, and networking. However, prior studies predominantly addressed whether individuals use social media to satisfy their needs, leaving a gap in understanding how individuals behave online to satisfy needs. This study fills this gap by merging survey responses with actual Twitter activity, to investigate how individuals behave online to satisfy distinctive motivations, including (a) self-expression, (b) seeking entertainment, (c) business and working, (d) staying informed with news, and (e) networking. We also investigated how these online behaviors vary among individuals with different demographic features, including socio-economic classes, gender, and age. Objectives & Approach Our research addressed questions by linking survey responses with actual Twitter activities within the U.K. Participants were asked to provide survey responses surrounding age, gender, socio-economic class, and motivations for using social media. They were also queried about the existence of Twitter account, willingness to disclose Twitter username, and, if agreeable, the username itself. The survey continued until a total of 2,195 individuals shared Twitter handles. Following the removal of accounts that were either suspended or nonexistent, the study proceeded with a final count of 1,915. We collected each user’s Twitter metadata with Twitter API, including tweet count, follower count, following count, and bio information, and linked each user’s metadata with survey responses. To ensure respondents’ anonymity, survey, Twitter and linked data are stored separately, and can only be accessed by designated researcher. Relevance to Digital Footprints The study's approach of linking survey responses with actual Twitter activity offers a detailed insight into the digital footprints left by users as they engage with social media to satisfy their diverse needs. By analyzing the behaviors associated with motivations, this research illuminates the specific ways individuals curate their digital presence. Results Regression analysis indicated that individuals motivated by self-expression tend to tweet (b = .28, SE = .06, p < .001), follow account (b = .38, SE = .06, p < .001), gain followers (b = .13, SE = .06, p = .035), and post bio details (b = .89, SE = .13, p < .001). Work and business motivation leads to post bio information (b = .38, SE = .15, p = .012), while networking leads to follow more accounts (b = .28, SE = .06, p < .001). Social-economic class moderated associations between networking motivation and tweet count (b = -.25, SE = .09, p = .004), and between self-expression and tweet count (b = .20, SE = .08, p = .009). For individuals with higher socio-economic, self-expression has a higher effect on tweet count, whereas networking motivation has a less effect on tweet count. Additionally, we found gender moderated the association between self-expression and tweet count (b = .25, SE = .12, p = .04) and between keeping updated with news and tweet count (b = .11, SE = .05, p = .03). Conclusions & Implications These findings offer a nuanced understanding of social media usage, highlighting how different motivations influence specific online behaviors. The novel approach of linking surveys with actual social media activity provides a more accurate representation of user behavior, contributing insights for academic and practical social media strategy and design.

Abstract Linked social media and survey data have the potential to be a unique source of information for social research. While the potential usefulness of this methodology is widely acknowledged, very few studies have explored methodological aspects of such linkage. Respondents produce planned amounts of survey data, but highly variant amounts of social media data. This study explores this asymmetry by examining the amount of social media data available to link to surveys. The extent of variation in the amount of data collected from social media could affect the ability to derive meaningful linked indicators and could introduce possible biases. Linked Twitter data from respondents to two longitudinal surveys representative of Great Britain, the Innovation Panel and the NatCen Panel, show that there is indeed substantial variation in the number of tweets posted and the number of followers and friends respondents have. Multivariate analyses of both data sources show that only a few respondent characteristics have a statistically significant effect on the number of tweets posted, with the number of followers being the strongest predictor of posting in both panels, women posting less than men, and some evidence that people with higher education post less, but only in the Innovation Panel. We use sentiment analyses of tweets to provide an example of how the amount of Twitter data collected can impact outcomes using these linked data sources. Results show that more negatively coded tweets are related to general happiness, but not the number of positive tweets. Taken together, the findings suggest that the amount of data collected from social media which can be linked to surveys is an important factor to consider and indicate the potential for such linked data sources in social research.

Abstract Background Fusarium head blight resistance genes, Fhb1 (for Type-II resistance), Fhb2 (Type-II), and Fhb5 (Type-I plus some Type-II), which originate from Sumai 3, are among the most important that confer resistance in hexaploid wheat. Near-isogenic lines (NILs), in the CDC Alsask (susceptible; n = 32) and CDC Go (moderately susceptible; n = 38) backgrounds, carrying these genes in all possible combinations were developed using flanking microsatellite markers and evaluated for their response to FHB and deoxynivalenol (DON) accumulation in eight environments. NILs were haplotyped with wheat 90 K iSelect assay to elucidate the genomic composition and confirm alleles’ presence. Other than evaluating the effects of three major genes in common genetic background, the study elucidated the epistatic gene interactions as they influence FHB measurements; identified loci other than Fhb1, Fhb2, and Fhb5, in both recurrent and donor parents and examined annotated proteins in gene intervals. Results Genotyping using 81,857 single nucleotide polymorphism (SNP) markers revealed polymorphism on all chromosomes and that the NILs carried 20% of the phenotypic variation in FHB measurements. Conclusions Immediate Sumai 3 derivatives carry a number of resistance improving minor effect alleles, other than Fhb1, Fhb2, Fhb5. Results verified that marker-assisted selection is possible for the introgression of exotic FHB resistance genes, however, the genetic background of the recipient line and epistatic interactions can have a strong influence on expression and penetrance of any given gene.

Front-of-pack labels (FOPLs) provide simplified nutritional information that aims to inform consumer choice and encourage reformulation. We conducted an online randomised controlled experiment on a representative British sample to test the effectiveness of FOPLs across a range of outcomes. The primary outcomes have been published; here, we present the secondary outcomes: the ability to rank the healthiest product and the time to complete the rankings by comparing the FOPL groups and a no-label control, as well as a descriptive analysis of the perceptions. Participants from the NatCen panel were randomised to one of five experimental groups (Multiple Traffic Lights; Nutri-Score; Warning Label; Positive Choice tick; no-label control). Six food/drink categories were selected (pizza, drinks, cakes, crisps, yoghurts, breakfast cereals), and three products were created with varying healthiness. The participants (analytic sample = 4530) were asked to rank the products in order of healthiness twice (baseline: no label; follow-up: experimental group label). Compared to the control, the probability of correctly ranking the healthiest product at follow-up was significantly greater for the N-S, MTL and WL across all products. The time to correctly complete the ranking was fastest for the N-S, PC and no-label control. The descriptive analysis showed that the FOPLs were perceived favourably, and especially N-S and MTL. The findings were supportive of the primary analyses, with those results suggesting that N-S performed the best, and then MTL.

Front of pack food labels (FOPLs) provide accessible nutritional information to guide consumer choice. Using an online experiment with a large representative British sample, we aimed to examine whether FOPLs improve participants’ ability to identify the healthiness of foods and drinks. The primary aim was to compare ability to rank between FOPL groups and a no label control. Adults (≥18 years), recruited from the NatCen panel, were randomised to one of five experimental groups (Multiple Traffic Light, MTL; Nutri-Score, N-S; Warning Label, WL; Positive Choice tick, PC; no label control). Stratification variables were year of recruitment to panel, sex, age, government office region, and household income. Packaging images were created for three versions, varying in healthiness, of six food and drink products (pizza, drinks, cakes, crisps, yoghurts, breakfast cereals). Participants were asked to rank the three product images in order of healthiness. Ranking was completed on a single occasion and comprised a baseline measure (with no FOPL), and a follow-up measure including the FOPL as per each participant’s experimental group. The primary outcome was the ability to accurately rank product healthiness (all products ranked correctly vs. any incorrect). In 2020, 4504 participants had complete data and were included in the analysis. The probability of correct ranking at follow-up, and improving between baseline and follow-up, was significantly greater across all products for the N-S, MTL and WL groups, compared to control. This was seen for only some of the products for the PC group. The largest effects were seen for N-S, followed by MTL. These analyses were adjusted for stratification variables, ethnicity, education, household composition, food shopping responsibility, and current FOPL use. Exploratory analyses showed a tendency for participants with higher compared to lower education to rank products more accurately. Conclusions: All FOPLs were effective at improving participants’ ability to correctly rank products according to healthiness in this large representative British sample, with the largest effects seen for N-S, followed by MTL.

Localized fluidization within a granular packing along an almost cylindrical chimney is observed when an upward fluid-flow, injected through a small port diameter, exceeds a critical flow-rate. Once this threshold reached, a fluidized area is first initiated in the close vicinity of the injection hole before gradually growing upward to the top surface of the granular layer. In this work, we present an experimental investigation specifically dedicated to the kinetics of chimney fluidization in an immersed granular bed. Two different transient regimes are identified depending on wether the expansion of the fluidized area is rather fast and regular, reaching the final chimney state typically in less than 10 seconds, or, on the contrary, slow and very progressively accelerated, giving rise to transient duration up to 1 hour or even more. Some systematic investigations allow to propose several empirical scaling relations for the kinetics of chimney fluidization in the fast regular regime.

We have studied the dynamics of a high mobility two-dimensional electron gas as a function of temperature. The presence of satellite reflections in the sample and magnet can be modeled in the time-domain.

Abstract Background Toll-like receptors (TLRs) on T cells can modulate their responses, however, the extent and significance of TLR expression by lung T cells, NK cells, or NKT cells in chronic obstructive pulmonary disease (COPD) is unknown. Methods Lung tissue collected from clinically-indicated resections (n = 34) was used either: (a) to compare the expression of TLR1, TLR2, TLR2/1, TLR3, TLR4, TLR5, TLR6 and TLR9 on lung CD8+ T cells, CD4+ T cells, NK cells and NKT cells from smokers with or without COPD; or (b) to isolate CD8+ T cells for culture with anti-CD3ε without or with various TLR ligands. We measured protein expression of IFN-γ, TNF-α, IL-13, perforin, granzyme A, granzyme B, soluble FasL, CCL2, CCL3, CCL4, CCL5, CCL11, and CXCL9 in supernatants. Results All the lung subsets analyzed demonstrated low levels of specific TLR expression, but the percentage of CD8+ T cells expressing TLR1, TLR2, TLR4, TLR6 and TLR2/1 was significantly increased in COPD subjects relative to those without COPD. In contrast, from the same subjects, only TLR2/1 and TLR2 on lung CD4+ T cells and CD8+ NKT cells, respectively, showed a significant increase in COPD and there was no difference in TLR expression on lung CD56+ NK cells. Production of the Tc1 cytokines IFN-γ and TNF-α by lung CD8+ T cells were significantly increased via co-stimulation by Pam3CSK4, a specific TLR2/1 ligand, but not by other agonists. Furthermore, this increase in cytokine production was specific to lung CD8+ T cells from patients with COPD as compared to lung CD8+ T cells from smokers without COPD. Conclusions These data suggest that as lung function worsens in COPD, the auto-aggressive behavior of lung CD8+ T cells could increase in response to microbial TLR ligands, specifically ligands against TLR2/1.

Abstract Background Physician reporting is commonly used to ascertain adverse events or outcomes measured in epidemiologic studies. However, little is known on the accuracy of physician reported malignancies compared to pertinent medical record review in large cohort studies. Methods The Consortium of Rheumatology Researchers of North America (CORRONA) registry gathers physician-completed questionnaires for rheumatoid arthritis (RA) patients, including request for information on incident malignancies, approximately every three months. For incident malignancies reported from October 1st, 2001, through December 31st, 2007, we retrospectively requested completion of a Targeted Adverse Event (TAE) form for additional information as well as primary source documents to adjudicate the malignancy reports. CORRONA has employed a prospective request for source documentation for these events since 2008. We classified each malignancy as definite, probable, possible, or not a malignancy. Results From 20,837 RA patients enrolled in CORRONA, 461 incident malignancies were initially reported on physician questionnaires. After review of returned source documents with adjudication, 234 were deemed definite, 69 probable, 101 possible, and 57 not an incident malignancy. The positive predictive value (PPV) of initial physician report of a malignancy versus “definite or probable” malignancy based on adjudication was 0.66 (95% CI 0.61 - 0.70). The PPV was 0.68 (95% CI 0.63 – 0.72) when the subsequent TAE form also confirmed the presence of malignancy. When possible malignancies were included, the PPV of physician-reported malignancies without a subsequent TAE form increased to 0.86 (0.83 – 0.89), and with a subsequent TAE form, 0.89 (0.85-0.91). Conclusion Twelve percent of initial physician reports of incident malignancy could not be confirmed with review of source documents. The most common reason for lack of confirmation was inability to obtain documents or insufficient data in source materials. These results suggest that timely collection of relevant medical records and an adjudication process are required to improve the accuracy of cancer reporting in epidemiologic studies.

Abstract Background A sizeable body of data demonstrates that membrane ICAM-1 (mICAM-1) plays a significant role in host defense in a site-specific fashion. On the pulmonary vascular endothelium, mICAM-1 is necessary for normal leukocyte recruitment during acute inflammation. On alveolar epithelial cells (AECs), we have shown previously that the presence of normal mICAM-1 is essential for optimal alveolar macrophage (AM) function. We have also shown that ICAM-1 is present in the alveolar space as a soluble protein that is likely produced through cleavage of mICAM-1. Soluble intercellular adhesion molecule-1 (sICAM-1) is abundantly present in the alveolar lining fluid of the normal lung and could be generated by proteolytic cleavage of mICAM-1, which is highly expressed on type I AECs. Although a growing body of data suggesting that intravascular sICAM-1 has functional effects, little is known about sICAM-1 in the alveolus. We hypothesized that sICAM-1 in the alveolar space modulates the innate immune response and alters the response to pulmonary infection. Methods Using the surfactant protein C (SPC) promoter, we developed a transgenic mouse (SPC-sICAM-1) that constitutively overexpresses sICAM-1 in the distal lung, and compared the responses of wild-type and SPC-sICAM-1 mice following intranasal inoculation with K. pneumoniae. Results SPC-sICAM-1 mice demonstrated increased mortality and increased systemic dissemination of organisms compared with wild-type mice. We also found that inflammatory responses were significantly increased in SPC-sICAM-1 mice compared with wild-type mice but there were no difference in lung CFU between groups. Conclusions We conclude that alveolar sICAM-1 modulates pulmonary inflammation. Manipulating ICAM-1 interactions therapeutically may modulate the host response to Gram negative pulmonary infections.

Abstract Background Chronic obstructive pulmonary disease (COPD) is characterized by chronic bronchitis, emphysema and irreversible airflow limitation. These changes are thought to be due to oxidative stress and an imbalance of proteases and antiproteases. Quercetin, a plant flavonoid, is a potent antioxidant and anti-inflammatory agent. We hypothesized that quercetin reduces lung inflammation and improves lung function in elastase/lipopolysaccharide (LPS)-exposed mice which show typical features of COPD, including airways inflammation, goblet cell metaplasia, and emphysema. Methods Mice treated with elastase and LPS once a week for 4 weeks were subsequently administered 0.5 mg of quercetin dihydrate or 50% propylene glycol (vehicle) by gavage for 10 days. Lungs were examined for elastance, oxidative stress, inflammation, and matrix metalloproteinase (MMP) activity. Effects of quercetin on MMP transcription and activity were examined in LPS-exposed murine macrophages. Results Quercetin-treated, elastase/LPS-exposed mice showed improved elastic recoil and decreased alveolar chord length compared to vehicle-treated controls. Quercetin-treated mice showed decreased levels of thiobarbituric acid reactive substances, a measure of lipid peroxidation caused by oxidative stress. Quercetin also reduced lung inflammation, goblet cell metaplasia, and mRNA expression of pro-inflammatory cytokines and muc5AC. Quercetin treatment decreased the expression and activity of MMP9 and MMP12 in vivo and in vitro, while increasing expression of the histone deacetylase Sirt-1 and suppressing MMP promoter H4 acetylation. Finally, co-treatment with the Sirt-1 inhibitor sirtinol blocked the effects of quercetin on the lung phenotype. Conclusions Quercetin prevents progression of emphysema in elastase/LPS-treated mice by reducing oxidative stress, lung inflammation and expression of MMP9 and MMP12.

Abstract Background Anxiety in patients with chronic obstructive pulmonary disease (COPD) is associated with self-reported disability. The purpose of this study is to determine whether there is an association between anxiety and functional measures, quality of life and dyspnea. Methods Data from 1828 patients with moderate to severe emphysema enrolled in the National Emphysema Treatment Trial (NETT), collected prior to rehabilitation and randomization, were used in linear regression models to test the association between anxiety symptoms, measured by the Spielberger State Trait Anxiety Inventory (STAI) and: (a) six-minute walk distance test (6 MWD), (b) cycle ergometry peak workload, (c) St. Georges Respiratory Questionnaire (SRGQ), and (d) UCSD Shortness of Breath Questionnaire (SOBQ), after controlling for potential confounders including age, gender, FEV1 (% predicted), DLCO (% predicted), and the Beck Depression Inventory (BDI). Results Anxiety was significantly associated with worse functional capacity [6 MWD (B = -0.944, p < .001), ergometry peak workload (B = -.087, p = .04)], quality of life (B = .172, p < .001) and shortness of breath (B = .180, p < .001). Regression coefficients show that a 10 point increase in anxiety score is associated with a mean decrease in 6 MWD of 9 meters, a 1 Watt decrease in peak exercise workload, and an increase of almost 2 points on both the SGRQ and SOBQ. Conclusion In clinically stable patients with moderate to severe emphysema, anxiety is associated with worse exercise performance, quality of life and shortness of breath, after accounting for the influence of demographic and physiologic factors known to affect these outcomes. Trail Registration ClinicalTrials.gov NCT00000606

We develop a multiscale coarse-grain model of the NIST Monoclonal Antibody Reference Material 8671 (NISTmAb) to enable systematic computational investigations of high-concentration physical instabilities such as phase separation, clustering, and aggregation. Our multiscale coarse-graining strategy captures atomic-resolution interactions with a computational approach that is orders of magnitude more efficient than atomistic models, assuming the biomolecule can be decomposed into one or more rigid bodies with known, fixed structures. This method reduces interactions between tens of thousands of atoms to a single anisotropic interaction site. The anisotropic interaction between unique pairs of rigid bodies is precomputed over a discrete set of relative orientations and stored, allowing interactions between arbitrarily oriented rigid bodies to be interpolated from the precomputed table during coarse-grained Monte Carlo simulations. We present this approach for lysozyme and lactoferrin as a single rigid body and for the NISTmAb as three rigid bodies bound by a flexible hinge with an implicit solvent model. This coarse-graining strategy predicts experimentally measured radius of gyration and second osmotic virial coefficient data, enabling routine Monte Carlo simulation of medically relevant concentrations of interacting proteins while retaining atomistic detail. All methodologies used in this work are available in the open-source software Free Energy and Advanced Sampling Simulation Toolkit., (© 2024 Author(s).)

The mRNA technology has emerged as a rapid modality to develop vaccines during pandemic situations with the potential to protect against endemic diseases. The success of mRNA in producing an antigen is dependent on the ability to deliver mRNA to the cells using a vehicle, which typically consists of a lipid nanoparticle (LNP). Self-amplifying mRNA (SAM) is a synthetic mRNA platform that, besides encoding for the antigen of interest, includes the replication machinery for mRNA amplification in the cells. Thus, SAM can generate many antigen encoding mRNA copies and prolong expression of the antigen with lower doses than those required for conventional mRNA. This work describes the morphology of LNPs containing encapsulated SAM (SAM LNPs), with SAM being three to four times larger than conventional mRNA. We show evidence that SAM changes its conformational structure when encapsulated in LNPs, becoming more compact than the free SAM form. A characteristic "bleb" structure is observed in SAM LNPs, which consists of a lipid-rich core and an aqueous RNA-rich core, both surrounded by a DSPC-rich lipid shell. We used SANS and SAXS data to confirm that the prevalent morphology of the LNP consists of two-core compartments where components are heterogeneously distributed between the two cores and the shell. A capped cylinder core-shell model with two interior compartments was built to capture the overall morphology of the LNP. These findings provide evidence that bleb two-compartment structures can be a representative morphology in SAM LNPs and highlight the need for additional studies that elucidate the role of spherical and bleb morphologies, their mechanisms of formation, and the parameters that lead to a particular morphology for a rational design of LNPs for mRNA delivery.

Monoclonal antibodies (mAbs) make up a major class of biotherapeutics with a wide range of clinical applications. Their physical stability can be affected by various environmental factors. For instance, an acidic pH can be encountered during different stages of the mAb manufacturing process, including purification and storage. Therefore, understanding the behavior of flexible mAb molecules in acidic solution environments will benefit the development of stable mAb products. This study used small-angle X-ray scattering (SAXS) and complementary biophysical characterization techniques to investigate the conformational flexibility and protein-protein interactions (PPI) of a model mAb molecule under near-neutral and acidic conditions. The study also characterized the interactions between Fab and Fc fragments under the same buffer conditions to identify domain-domain interactions. The results suggest that solution pH significantly influences mAb flexibility and thus could help mAbs remain physically stable by maximizing local electrostatic repulsions when mAbs become crowded in solution. Under acidic buffer conditions, both Fab and Fc contribute to the repulsive PPI observed among the full mAb at a low ionic strength. However, as ionic strength increases, hydrophobic interactions lead to the self-association of Fc fragments and, subsequently, could affect the aggregation state of the mAb.

In this study, we used sodium chloride (NaCl) to extensively modulate non-specific protein-protein interactions (PPI) of a humanized anti-streptavidin monoclonal antibody class 2 molecule (ASA-IgG2). The changes in PPI with varying NaCl ( C NaCl ) and monoclonal antibody (mAb) concentration ( C mAb ) were assessed using the diffusion interaction parameter k D and second virial coefficient B 22 measured from solutions with low to moderate C mAb . The effective structure factor S(q) eff measured from concentrated mAb solutions using small-angle X-ray and neutron scattering (SAXS/SANS) was also used to characterize the PPI. Our results found that the nature of net PPI changed not only with C NaCl , but also with increasing C mAb . As a result, parameters measured from dilute and concentrated mAb samples could lead to different predictions on the stability of mAb formulations. We also compared experimentally determined viscosity results with those predicted from interaction parameters, including k D and S(q) eff . The lack of a clear correlation between interaction parameters and measured viscosity values indicates that the relationship between viscosity and PPI is concentration-dependent. Collectively, the behavior of flexible mAb molecules in concentrated solutions may not be correctly predicted using models where proteins are considered to be uniform colloid particles defined by parameters derived from low C mAb .

Lipid nanodiscs can be used to solubilize functional membrane proteins (MPs) in nativelike environments. Thus, they are promising reagents that have been proven useful to characterize MPs. Both protein and non-protein molecular belts have shown promise to maintain the structural integrity of MPs in lipid nanodiscs. Small-angle neutron scattering (SANS) can be used to determine low-resolution structures of proteins in solution, which can be enhanced through the use of contrast variation methods. We present theoretical contrast variation SANS results for protein and styrene-maleic acid copolymer (SMA) belt 1,2-dimyristoyl- sn -glycero-3-phosphorylcholine (DMPC) nanodiscs with and without additional bound or transmembrane proteins. The predicted scattering properties are derived from atomistic molecular dynamics simulations to account for conformational fluctuations, and we determine deuterium-labeling conditions such that SANS intensity profiles only include contributions from the scattering of the MP of interest. We propose strategies to tune the neutron scattering length densities (SLDs) of the SMA and DMPC using selective deuterium labeling such that the SLD of the nanodisc becomes homogeneous and its scattering can essentially be eliminated in solvents containing an appropriate amount of D 2 O. These finely tuned labeled polymer-based nanodiscs are expected to be useful to extract the size and molecular shape information of MPs using SANS-based contrast variation experiments, and they can be used with MPs of any molecular weight.

Bacteria live in spatially organized aggregates during chronic infections, where they adapt to the host environment, evade immune responses, and resist therapeutic interventions. Although it is known that environmental factors such as polymers influence bacterial aggregation, it is not clear how bacterial adaptation during chronic infection impacts the formation and spatial organization of aggregates in the presence of polymers. Here, we show that in an in vitro model of cystic fibrosis (CF) containing the polymers extracellular DNA (eDNA) and mucin, O-specific antigen is a major factor determining the formation of two distinct aggregate assembly types of Pseudomonas aeruginosa due to alterations in cell surface hydrophobicity. Our findings suggest that during chronic infection, the interplay between cell surface properties and polymers in the environment may influence the formation and structure of bacterial aggregates, which would shed new light on the fitness costs and benefits of O-antigen production in environments such as CF lungs. IMPORTANCE During chronic infection, several factors contribute to the biogeography of microbial communities. Heterogeneous populations of Pseudomonas aeruginosa form aggregates in cystic fibrosis airways; however, the impact of this population heterogeneity on spatial organization and aggregate assembly is not well understood. In this study, we found that changes in O-specific antigen determine the spatial organization of P. aeruginosa cells by altering the relative cell surface hydrophobicity. This finding suggests a role for O-antigen in regulating P. aeruginosa aggregate size and shape in cystic fibrosis airways.

In the past decade, there was increased research interest in studying internal motions of flexible proteins in solution using Neutron Spin Echo (NSE) as NSE can simultaneously probe the dynamics at the length and time scales comparable to protein domain motions. However, the collective intermediate scattering function (ISF) measured by NSE has the contributions from translational, rotational, and internal motions, which are rather complicated to be separated. Widely used NSE theories to interpret experimental data usually assume that the translational and rotational motions of a rigid particle are decoupled and independent to each other. To evaluate the accuracy of this approximation for monoclonal antibody (mAb) proteins in solution, dissipative particle dynamic computer simulation is used here to simulate a rigid-body mAb for up to about 200 ns. The total ISF together with the ISFs due to only the translational and rotational motions as well as their corresponding effective diffusion coefficients is calculated. The aforementioned approximation introduces appreciable errors to the calculated effective diffusion coefficients and the ISFs. For the effective diffusion coefficient, the error introduced by this approximation can be as large as about 10% even though the overall agreement is considered reasonable. Thus, we need to be cautious when interpreting the data with a small signal change. In addition, the accuracy of the calculated ISFs due to the finite computer simulation time is also discussed., (© 2021 Author(s).)

We present a simple yet versatile method for sculpting ultra-thick, enzyme-generated hyaluronan polymer brushes with light. The patterning mechanism is indirect, driven by reactive oxygen species created by photochemical interactions with the underlying substrate. The reactive oxygen species disrupt the enzyme hyaluronan synthase, which acts as the growth engine and anchor of the end-grafted polymers. Spatial control over the grafting density is achieved through inactivation of the enzyme in an energy density dose-dependent manner, before or after polymerization of the brush. Quantitative variation of the brush height is possible using visible wavelengths and illustrated by the creation of a brush gradient ranging from 0 to 6 μm in height over a length of 56 μm (approximately a 90 nm height increase per micron). Building upon the fundamental insights presented in this study, this work lays the foundation for the flexible and quantitative sculpting of complex three-dimensional landscapes in enzyme-generated hyaluronan brushes.

Phase transitions of poloxamer 188 (P188) aqueous solutions at freezing temperatures are investigated using small-angle neutron scattering (SANS) and small- and wide-angle X-ray scatterings (SAXS and WAXS). It is shown that P188 solution (10%) undergoes the following sequence of phase transitions during cooling from 25 to -150 °C: micelle solution, solution of monomers, two-phase mixture of liquid crystalline mesophase + ice, and finally crystalline P188 + ice. Formation of the liquid crystalline phase during freezing is likely to be triggered by water freezing to ice and corresponding freeze concentration of the remaining solution. During heating of the frozen solutions, the sequence of the phase transitions is reversed: crystalline P188 + ice, liquid crystalline mesophase + ice, monomer solution + ice, monomer solution, and finally micelle solution. Similar phase transitions are detected for dilute solutions of P188 (1%) except that micelle formation is not observed at 25 °C, consistent with the literature reported critical micelle concentration (CMC) at this temperature. The present study provides new insight into P188 aqueous solutions at freezing temperatures and has practical implications on the design and development of pharmaceutical formulations.

The respiratory syncytial virus (RSV) fusion (F) protein/polysorbate 80 (PS80) nanoparticle vaccine is the most clinically advanced vaccine for maternal immunization and protection of newborns against RSV infection. It is composed of a near-full-length RSV F glycoprotein, with an intact membrane domain, formulated into a stable nanoparticle with PS80 detergent. To understand the structural basis for the efficacy of the vaccine, a comprehensive study of its structure and hydrodynamic properties in solution was performed. Small-angle neutron scattering experiments indicate that the nanoparticle contains an average of 350 PS80 molecules, which form a cylindrical micellar core structure and five RSV F trimers that are arranged around the long axis of the PS80 core. All-atom models of full-length RSV F trimers were built from crystal structures of the soluble ectodomain and arranged around the long axis of the PS80 core, allowing for the generation of an ensemble of conformations that agree with small-angle neutron and X-ray scattering data as well as transmission electron microscopy (TEM) images. Furthermore, the hydrodynamic size of the RSV F nanoparticle was found to be modulated by the molar ratio of PS80 to protein, suggesting a mechanism for nanoparticle assembly involving addition of RSV F trimers to and growth along the long axis of the PS80 core. This study provides structural details of antigen presentation and conformation in the RSV F nanoparticle vaccine, helping to explain the induction of broad immunity and observed clinical efficacy. Small-angle scattering methods provide a general strategy to visualize surface glycoproteins from other pathogens and to structurally characterize nanoparticle vaccines.

Protein therapeutics typically require a concentrated protein formulation, which can lead to self-association and/or high viscosity due to protein-protein interaction (PPI). Excipients are often added to improve stability, bioavailability, and manufacturability of the protein therapeutics, but the selection of excipients often relies on trial and error. Therefore, understanding the excipient-protein interaction and its effect on non-specific PPI is important for rational selection of formulation development. In this study, we validate a general workflow based on the site identification by ligand competitive saturation (SILCS) technology, termed SILCS-Biologics, that can be applied to protein therapeutics for rational excipient selection. The National Institute of Standards and Technology monoclonal antibody (NISTmAb) reference along with the CNTO607 mAb is used as model antibody proteins to examine PPIs, and NISTmAb was used to further examine excipient-protein interactions, in silico. Metrics from SILCS include the distribution and predicted affinity of excipients, buffer interactions with the NISTmAb Fab, and the relation of the interactions to predicted PPI. Comparison with a range of experimental data showed multiple SILCS metrics to be predictive. Specifically, the number of favorable sites to which an excipient binds and the number of sites to which an excipient binds that are involved in predicted PPIs correlate with the experimentally determined viscosity. In addition, a combination of the number of binding sites and the predicted binding affinity is indicated to be predictive of relative protein stability. Comparison of arginine, trehalose, and sucrose, all of which give the highest viscosity in combination with analysis of B 22 and k D and the SILCS metrics, indicates that higher viscosities are associated with a low number of predicted binding sites, with lower binding affinity of arginine leading to its anomalously high impact on viscosity. The present study indicates the potential for the SILCS-Biologics approach to be of utility in the rational design of excipients during biologics formulation.

Small-angle neutron scattering (SANS) measurements were pursued to study human vitronectin, a protein found in tissues and the circulation that regulates cell adhesion/migration and proteolytic cascades that govern hemostasis and pericellular proteolysis. Many of these functions occur via interactions with its binding partner, plasminogen activator inhibitor-1 (PAI-1), the chief inhibitor of proteases that lyse and activate plasminogen. We focused on a region of vitronectin that remains uncharacterized from previous X-ray scattering, nuclear magnetic resonance, and computational modeling approaches and which we propose is involved in binding to PAI-1. This region, which bridges the N-terminal somatomedin B (SMB) domain with a large central β-propeller domain of vitronectin, appears unstructured and has characteristics of an intrinsically disordered domain (IDD). The effect of osmolytes was evaluated using circular dichroism and SANS to explore the potential of the IDD to undergo a disorder-to-order transition. The results suggest that the IDD favors a more ordered structure under osmotic pressure; SANS shows a smaller radius of gyration ( R g ) and a more compact fold of the IDD upon addition of osmolytes. To test whether PAI-1 binding is also coupled to folding within the IDD structure, a set of SANS experiments with contrast variation were performed on the complex of PAI-1 with a vitronectin fragment corresponding to the N-terminal 130 amino acids (denoted the SMB-IDD because it contains the SMB domain and IDD in linear sequence). Analysis of the SANS data using the Ensemble Optimization Method confirms that the SMB-IDD adopts a more compact configuration when bound to PAI-1. Calculated structures for the PAI-1:SMB-IDD complex suggest that the IDD provides an interaction surface outside of the primary PAI-1-binding site located within the SMB domain; this binding is proposed to lead to the assembly of higher-order structures of vitronectin and PAI-1 commonly found in tissues.

Tailoring interfaces with polymer brushes is a commonly used strategy to create functional materials for numerous applications. Existing methods are limited in brush thickness, the ability to generate high-density brushes of biopolymers, and the potential for regeneration. Here we introduce a scheme to synthesize ultra-thick regenerating hyaluronan polymer brushes using hyaluronan synthase. The platform provides a dynamic interface with tunable brush heights that extend up to 20 microns - two orders of magnitude thicker than standard brushes. The brushes are easily sculpted into micropatterned landscapes by photo-deactivation of the enzyme. Further, they provide a continuous source of megadalton hyaluronan or they can be covalently-stabilized to the surface. Stabilized brushes exhibit superb resistance to biofilms, yet are locally digested by fibroblasts. This brush technology provides opportunities in a range of arenas including regenerating tailorable biointerfaces for implants, wound healing or lubrication as well as fundamental studies of the glycocalyx and polymer physics.

Polyelectrolyte brushes are important stimuli-responsive materials in a variety of technological applications as well as in biological systems. Their small size, however, introduces characterization challenges, particularly in studying 3D structure and time-dependent behavior. In this Letter, we report on the polyelectrolyte brush behavior of extra-large hyaluronan brushes (∼15 μm) recently developed using an enzyme-mediated growth process. In response to increasing ionic strength, the brush displays the osmotic brush regime and the salted brush regime. We also show a collapse of 96% when the brush is placed in a poor solvent. This collapse is rapid when changing from a good to poor solvent, but re-expansion is slow when changing back to a good solvent. The observed brush behavior described in this Letter is similar to that seen for smaller polyelectrolyte brushes, indicating that these larger brushes may serve as model systems to study more complex phenomena through confocal microscopy.

Excipients are substances that are added to therapeutic products to improve stability, bioavailability, and manufacturability. Undesirable protein-protein interactions (PPI) can lead to self-association and/or high solution viscosity in concentrated protein formulations that are typically greater than 50 mg/mL. Therefore, understanding the effects of excipients on nonspecific PPI is important for more efficient formulation development. In this study, we used National Institute of Standards and Technology monoclonal antibody (NISTmAb) reference material as a model antibody protein to examine the physical stability and viscosity of concentrated formulations using a series of excipients, by varying pH, salt composition, and the presence of cosolutes including amino acids, sugars, and nonionic surfactants. Small angle X-ray scattering (SAXS) together with differential scanning calorimetry (DSC), dynamic light scattering (DLS), and viscosity measurements were used to obtain various experimental parameters to characterize excipient modulated PPI and bulk solution viscosities. In particular, a good correlation was found between SAXS and DLS/SLS results, suggesting that the use of DLS/SLS is valid for predicting the colloidal stability of NISTmAb in concentrated solutions. Moreover, further analysis of effective structure factor S(q) eff measured from SAXS enabled the dissection of net PPI into hydrodynamic forces due to excluded volume as well as any additional attractive or repulsive interactions with the presence of excipients. It was found that although no denaturation or aggregation of NISTmAb was observed and that the net PPI were repulsive, the use of ionic excipients such as pH and salts leads to increased short-range attraction, whereas the nonionic excipients including sugars, amino acids, and polysorbate surfactants lead to increased repulsive PPI with increasing protein concentration. Results obtained from viscosity measurements showed that the use of excipients can lead to increased solution viscosities at high protein concentrations. The use of S(q) eff , interaction parameter k D , and second virial coefficient B 22 as predictors for solution viscosity was also evaluated by comparing the predicted results with the measured viscosities. Although B 22 and S(q) eff appeared to be better predictors than k D , disagreement between the predicted and measured results suggests other factors apart from PPI contribute to the bulk rheological properties of concentrated protein solutions.

Many biomolecular complexes exist in a flexible ensemble of states in solution that is necessary to perform their biological function. Small-angle scattering (SAS) measurements are a popular method for characterizing these flexible molecules because of their relative ease of use and their ability to simultaneously probe the full ensemble of states. However, SAS data is typically low dimensional and difficult to interpret without the assistance of additional structural models. In theory, experimental SAS curves can be reconstituted from a linear combination of theoretical models, although this procedure carries a significant risk of overfitting the inherently low-dimensional SAS data. Previously, we developed a Bayesian-based method for fitting ensembles of model structures to experimental SAS data that rigorously avoids overfitting. However, we have found that these methods can be difficult to incorporate into typical SAS modeling workflows, especially for users that are not experts in computational modeling. To this end, we present the Bayesian Ensemble Estimation from SAS (BEES) program. Two forks of BEES are available, the primary one existing as a module for the SASSIE web server and a developmental version that is a stand-alone Python program. BEES allows users to exhaustively sample ensemble models constructed from a library of theoretical states and to interactively analyze and compare each model's performance. The fitting routine also allows for secondary data sets to be supplied, thereby simultaneously fitting models to both SAS data as well as orthogonal information. The flexible ensemble of K63-linked ubiquitin trimers is presented as an example of BEES' capabilities., (Copyright © 2019 Biophysical Society. All rights reserved.)

Employing 2 different coarse-grained models, we evaluated the effect of intramolecular domain-domain distances and hinge flexibility on the general solution structure of monoclonal antibodies (mAbs), within the context of protein-protein steric repulsion. These models explicitly account for the hinge region, and represent antibodies at either domain or subdomain levels (i.e., 4-bead and 7-bead representations, respectively). Additionally, different levels of mAb flexibility are also considered. When evaluating mAbs as rigid structures, analysis of small-angle scattering profiles showed that changes in the relative internal distances between Fc and Fab domains significantly alter the local arrangement of neighboring molecules, as well as the molecular packing of the concentrated mAb solutions. Likewise, enabling hinge flexibility in either of the mAb models led to qualitatively similar results, where flexibility increases the spatial molecular arrangement at elevated concentrations. This occurs because fluctuations in mAb quaternary structure are modulated by the close proximity between molecules at elevated concentrations (>50 mg mL -1 ), yielding an increased molecular packing and osmotic compressibility. However, our results also showed that the mechanism behind this synergy between flexibility and packing strongly depends on both the level of structural detail and the number of degrees-of-freedom considered in the coarse-grained model., (Copyright © 2019 American Pharmacists Association®. All rights reserved.)

The scattering of neutrons can be used to provide information on the structure and dynamics of biological systems on multiple length and time scales. Pursuant to a National Science Foundation-funded workshop in February 2018, recent developments in this field are reviewed here, as well as future prospects that can be expected given recent advances in sources, instrumentation and computational power and methods. Crystallography, solution scattering, dynamics, membranes, labeling and imaging are examined. For the extraction of maximum information, the incorporation of judicious specific deuterium labeling, the integration of several types of experiment, and interpretation using high-performance computer simulation models are often found to be particularly powerful.

The member of Rho family of small GTPases Cdc42 plays important and conserved roles in cell polarity and motility. The Cdc42ep family proteins have been identified to bind to Cdc42, yet how they interact with Cdc42 to regulate cell migration remains to be elucidated. In this study, we focus on Cdc42ep1, which is expressed predominantly in the highly migratory neural crest cells in frog embryos. Through morpholino-mediated knockdown, we show that Cdc42ep1 is required for the migration of cranial neural crest cells. Loss of Cdc42ep1 leads to rounder cell shapes and the formation of membrane blebs, consistent with the observed disruption in actin organization and focal adhesion alignment. As a result, Cdc42ep1 is critical for neural crest cells to apply traction forces at the correct place to migrate efficiently. We further show that Cdc42ep1 is localized to two areas in neural crest cells: in membrane protrusions together with Cdc42 and in perinuclear patches where Cdc42 is absent. Cdc42 directly interacts with Cdc42ep1 (through the CRIB domain) and changes in Cdc42 level shift the distribution of Cdc42ep1 between these two subcellular locations, controlling the formation of membrane protrusions and directionality of migration as a consequence. These results suggest that Cdc42ep1 elaborates Cdc42 activity in neural crest cells to promote their efficient migration.

The theoretical framework to evaluate small-angle scattering (SAS) profiles for multi-component macromolecular solutions is re-examined from the standpoint of molecular simulations in the grand-canonical ensemble, where the chemical potentials of all species in solution are fixed. This statistical mechanical ensemble resembles more closely scattering experiments, capturing concentration fluctuations that arise from the exchange of molecules between the scattering volume and the bulk solution. The resulting grand-canonical expression relates scattering intensities to the different intra- and intermolecular pair distribution functions, as well as to the distribution of molecular concentrations on the scattering volume. This formulation represents a generalized expression that encompasses most of the existing methods to evaluate SAS profiles from molecular simulations. The grand-canonical SAS methodology is probed for a series of different implicit-solvent, homogeneous systems at conditions ranging from dilute to concentrated. These systems consist of spherical colloids, dumbbell particles, and highly flexible polymer chains. Comparison of the resulting SAS curves against classical methodologies based on either theoretical approaches or canonical simulations (i.e., at a fixed number of molecules) shows equivalence between the different scattering intensities so long as interactions between molecules are net repulsive or weakly attractive. On the other hand, for strongly attractive interactions, grand-canonical SAS profiles deviate in the low- and intermediate- q range from those calculated in a canonical ensemble. Such differences are due to the distribution of molecules becoming asymmetric, which yields a higher contribution from configurations with molecular concentrations larger than the nominal value. Additionally, for flexible systems, explicit discrimination between intra- and inter-molecular SAS contributions permits the implementation of model-free, structural analysis such as Guinier's plots at high molecular concentrations, beyond what the traditional limits are for such analysis.

We present experimental measurements and analysis of the dynamics and the phase behaviour of saturated DMPC and unsaturated DOPC oriented multi-lamellar bilayers. Elastic and inelastic neutron scattering were used to directly probe the dynamical processes of these membrane systems on time and length scales relevant to the internal and localized motion of lipid monomers. Mobility in this regime can be informative in elucidating the local interactions responsible for material properties of these fluid lipid systems. DMPC and DOPC are structurally similar in terms of their membrane hydrophobic thickness; however, they exhibit different mechanical properties in terms of both elastic compressibility and bending moduli. The analyses suggest that the constraint imposed by the double bonds in DOPC acyl chains restricts atomic motion in both liquid and gel phases compared to DMPC. We discuss applications of molecular dynamics to further elucidate the atomic details of the dynamical processes. Such an understanding may suggest how membrane properties can be tuned using a variety of different lipid species.

Passage of specific protein solutions through certain pumps, tubing, and/or filling nozzles can result in the production of unwanted subvisible protein particles (SVPs). In this work, surface-mediated SVP formation was investigated. Specifically, the effects of different solid interface materials, interfacial shear rates, and protein concentrations on SVP formation were measured for the National Institute of Standards and Technology monoclonal antibody (NISTmAb), a reference IgG1 monoclonal antibody (mAb). A stainless steel rotary piston pump was used to identify formulation and process parameters that affect aggregation, and a flow cell (alumina or stainless steel interface) was used to further investigate the effect of different interface materials and/or interfacial shear rates. SVP particles produced were monitored using flow microscopy or flow cytometry. Neutron reflectometry and a quartz crystal microbalance with dissipation monitoring were used to characterize adsorption and properties of NISTmAb at the stainless steel interface. Pump/shear cell experiments showed that the NISTmAb concentration and interface material had a significant effect on SVP formation, while the effects of interfacial shear rate and passage number were less important. At the higher NISTmAb concentrations, the adsorbed protein became structurally altered at the stainless steel interface. The primary adsorbed layer remained largely undisturbed during flow, suggesting that SVP formation at high NISTmAb concentration was caused by the disruption of patches and/or secondary interactions.

Protein-protein interactions in monoclonal antibody solutions are important for the stability of a therapeutic drug and directly influence viscosity in concentrated protein solutions. This study describes the use of small-angle scattering to estimate protein-protein interactions at high concentrations of the IgG1 NISTmAb reference material and validate colloidal models for interacting molecules. In particular, we studied the colloidal stability of the NISTmAb at high protein concentrations and analyzed protein-protein interactions upon adding sodium chloride and its effect on viscosity. Isotropic colloidal models for interacting molecules were combined with an ensemble of atomistic structures from molecular simulation to account for the flexibility of the NISTmAb in solution. In histidine formulation buffer, net repulsive electrostatic interactions are important for the colloidal stability of the NISTmAb at high concentrations. Addition of sodium chloride increased the viscosity of the NISTmAb and decreased the colloidal stability due to charge screening of the repulsive interactions. The interactions at high concentrations (up to ~ 250 mg/mL) were consistent with those from light scattering at low concentrations (below ~ 20 mg/mL). However, in the presence of sodium chloride, the screening of charges was less pronounced with increasing protein concentration and the interactions approached those of the repulsive hard-sphere models. Additionally, we studied the NISTmAb under frozen conditions using in situ neutron scattering to analyze the crowded state as proteins are excluded from the water-rich phase. In the frozen samples, where protein concentration can reach hundreds of mg/mL in the protein-rich phase, sodium chloride did not affect the molecular spacing and crowding of the NISTmAb. Graphical Abstract Net repulsive interactions in concentrated NISTmAb solutions assessed by small-angle neutronscattering.

Both conformational and colloidal stability of therapeutic proteins must be closely monitored and thoroughly characterized to assess the long-term viability of drug products. We characterized the IgG1 NISTmAb reference material in its histidine formulation buffer and report our findings on the higher order structure and interactions of NISTmAb under a range of conditions. In this paper we present the analysis of experimental small-angle scattering data with atomistic molecular simulations to characterize the monodisperse dilute solution of NISTmAb. In part II we describe the characterization of the NISTmAb at high protein concentration (Castellanos et al. 2018). The NISTmAb was found to be a flexible protein with a radius of gyration of 49.0 ± 1.2 Å in histidine formulation buffer using a variety of neutron and X-ray scattering measurements. Scattering data were then modeled using molecular simulation. After building and validating a starting NISTmAb structure from the Fc and Fab crystallographic coordinates, molecular dynamics and torsion-angle Monte Carlo simulations were performed to explore the configuration space sampled in the NISTmAb and obtain ensembles of structures with atomistic detail that are consistent with the experimental data. Our results indicate that the small-angle scattering profiles of the NISTmAb can be modeled using ensembles of flexible structures that explore a wide configuration space. The NISTmAb is flexible in solution with no single preferred orientation of Fc and Fab domains, but with some regions of configuration space that are more consistent with measured scattering profiles. Analysis of inter-domain atomistic contacts indicated that all ensembles contained configurations where residues between domains are ≤ 4 Å, although few contacts were observed for variable and C H 3 regions. Graphical Abstract Heavy atom self contact maps of the NISTmAb indicate a highly-flexible structure.

The pericellular matrix is a robust, hyaluronan-rich polymer brush-like structure that controls access to the cell surface, and plays an important role in cell adhesion, migration, and proliferation. We report the observation of single bottlebrush proteoglycan dynamics in the pericellular matrix of living chondrocytes. Our investigations show that the pericellular matrix undergoes gross extension on the addition of exogenous aggrecan, and that this extension is significantly in excess of that observed in traditional particle exclusion assays. The mean-square displacement of single, bound proteoglycans increases with distance to cell surface, indicating reduced confinement by neighboring hyaluronan-aggrecan complexes. This is consistent with published data from quantitative particle exclusion assays that show openings in the pericellular matrix microstructure ranging from ∼150 nm near the cell surface to ∼400 nm near the cell edge. In addition, the mobility of tethered aggrecan drops significantly when the cell coat is enriched with bottlebrush proteoglycans. Single-molecule imaging in this thick polysaccharide matrix on living cells has significant promise in the drive to elucidate the role of the pericellular coat in human health., (Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

We describe a general method to use Monte Carlo simulation followed by torsion-angle molecular dynamics simulations to create ensembles of structures to model a wide variety of soft-matter biological systems. Our particular emphasis is focused on modeling low-resolution small-angle scattering and reflectivity structural data. We provide examples of this method applied to HIV-1 Gag protein and derived fragment proteins, TraI protein, linear B-DNA, a nucleosome core particle, and a glycosylated monoclonal antibody. This procedure will enable a large community of researchers to model low-resolution experimental data with greater accuracy by using robust physics based simulation and sampling methods which are a significant improvement over traditional methods used to interpret such data., (Published by Elsevier Inc.)

The determination of monoclonal antibody interactions with protein antigens in solution can lead to important insights guiding physical characterization and molecular engineering of therapeutic targets. We used small-angle scattering (SAS) combined with size-exclusion multi-angle light scattering high-performance liquid chromatography to obtain monodisperse samples with defined stoichiometry to study an anti-streptavidin monoclonal antibody interacting with tetrameric streptavidin. Ensembles of structures with both monodentate and bidentate antibody-antigen complexes were generated using molecular docking protocols and molecular simulations. By comparing theoretical SAS profiles to the experimental data it was determined that the primary component(s) were compact monodentate and/or bidentate complexes. SAS profiles of extended monodentate complexes were not consistent with the experimental data. These results highlight the capability for determining the shape of monoclonal antibody-antigen complexes in solution using SAS data and physics-based molecular modeling., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest.

The effects of increasing the driving forces for a 1-D assembly of nanoparticles onto a surface are investigated with experimental results and models. Modifications, which take into account not only the particle-particle interactions but also particle-surface interactions, to previously established extended random sequential adsorption simulations are tested and verified. Both data and model are compared against the heterogeneous random sequential adsorption simulations, and finally, a connection between the two models is suggested. The experiments and models show that increasing the particle-surface interaction leads to narrower particle distribution; this narrowing is attributed to the surface interactions compensating against the particle-particle interactions. The long-term advantage of this work is that the assembly of nanoparticles in solution is now understood as controlled not only by particle-particle interactions but also by particle-surface interactions. Both particle-particle and particle-surface interactions can be used to tune how nanoparticles distribute themselves on a surface.

In order to increase shelf life and minimize aggregation during storage, many biotherapeutic drugs are formulated and stored as either frozen solutions or lyophilized powders. However, characterizing amorphous solids can be challenging with the commonly available set of biophysical measurements used for proteins in liquid solutions. Therefore, some questions remain regarding the structure of the active pharmaceutical ingredient during freezing and drying of the drug product and the molecular role of excipients. Neutron scattering is a powerful technique to study structure and dynamics of a variety of systems in both solid and liquid phases. Moreover, neutron scattering experiments can generally be correlated with theory and molecular simulations to analyze experimental data. In this article, we focus on the use of neutron techniques to address problems of biotechnological interest. We describe the use of small-angle neutron scattering to study the solution structure of biological molecules and the packing arrangement in amorphous phases, that is, frozen glasses and freeze-dried protein powders. In addition, we discuss the use of neutron spectroscopy to measure the dynamics of glassy systems at different time and length scales. Overall, we expect that the present article will guide and prompt the use of neutron scattering to provide unique insights on many of the outstanding questions in biotechnology.

Conventional studies of dynamic phagocytic behavior have been limited in terms of spatial and temporal resolution due to the inherent three-dimensionality and small features of phagocytosis. To overcome these issues, we use a series of frustrated phagocytosis assays to quantitatively characterize phagocytic spreading dynamics. Our investigation reveals that frustrated phagocytic spreading occurs in phases and is punctuated by a distinct period of contraction. The spreading duration and peak contact areas are independent of the surface opsonin density, although the opsonin density does affect the likelihood that a cell will spread. This reinforces the idea that phagocytosis dynamics are primarily dictated by cytoskeletal activity. Structured illumination microscopy reveals that F-actin is reorganized during the course of frustrated phagocytosis. F-actin in early stages is consistent with that observed in lamellipodial protrusions. During the contraction phase, it is bundled into fibers that surround the cell and is reminiscent of a contractile belt. Using traction force microscopy, we show that cells exert significant strain on the underlying substrate during the contraction phase but little strain during the spreading phase, demonstrating that phagocytes actively constrict during late-stage phagocytosis. We also find that late-stage contraction initiates after the cell surface area increases by 225%, which is consistent with the point at which cortical tension begins to rise. Moreover, reducing tension by exposing cells to hypertonic buffer shifts the onset of contraction to occur in larger contact areas. Together, these findings provide further evidence that tension plays a significant role in signaling late-stage phagocytic activity., (Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Small-angle scattering is a powerful technique to study molecular conformation and interactions of proteins in solution and in amorphous solids. We have investigated the role of multiple protein configurations in the interaction parameters derived from small-angle scattering for proteins in concentrated solutions. In order to account for the wide configurational space sampled by proteins, we generate ensembles of atomistic structures for lysozyme and monoclonal antibodies, representing globular and flexible proteins, respectively. While recent work has argued that a colloidal approach is inadequate to model proteins, because of the large configurational space that they sample in solution, we find a range of length scales where colloidal models can be used to describe solution scattering data while simultaneously accounting for structural flexibility. We provide insights to determine the length scales where isotropic colloidal models can be used, and find smoothly varying sets of interaction parameters that encompass ensembles of structures. This approach may play an important role in the definition of long-range interactions in coarse-grained models of flexible proteins with experimental scattering constraints. Additionally, we apply the decoupling approximation to ensembles of lysozyme structures with atomistic detail and observe remarkably different results when using geometric solids, such as ellipsoids. The insights from this study provide guidelines for the analysis of small-angle scattering profiles of proteins in crowded environments.