Characterization and Purification of Polydisperse Reconstituted Lipoproteins and Nanolipoprotein Particles

Heterogeneity is a fact that plagues the characterization and application of many self-assembled biological constructs. The importance of obtaining particle homogeneity in biological assemblies is a critical goal, as bulk analysis tools often require identical species for reliable interpretation of the results—indeed, important tools of analysis such as x-ray diffraction typically require over 90% purity for effectiveness. This issue bears particular importance in the case of lipoproteins. Lipid-binding proteins known as apolipoproteins can self assemble with liposomes to form reconstituted high density lipoproteins (rHDLs) or nanolipoprotein particles (NLPs) when used for biotechnology applications such as the solubilization of membrane proteins. Typically, the apolipoprotein and phospholipids reactants are self assembled and even with careful assembly protocols the product often contains heterogeneous particles. In fact, size polydispersity in rHDLs and NLPs published in the literature are frequently observed, which may confound the accurate use of analytical methods. In this article, we demonstrate a procedure for producing a pure, monodisperse NLP subpopulation from a polydisperse self-assembly using size exclusion chromatography (SEC) coupled with high resolution particle imaging by atomic force microscopy (AFM). In addition, NLPs have been shown to self assemble both in the presence and absence of detergents such as cholate, yet the effects of cholate on NLP polydispersity and separation has not been systematically examined. Therefore, we examined the separation properties of NLPs assembled in both the absence and presence of cholate using SEC and native gel electrophoresis. From this analysis, NLPs prepared with and without cholate showed particles with well defined diameters spanning a similar size range. However, cholate was shown to have a dramatic affect on NLP separation by SEC and native gel electrophoresis. Furthermore, under conditions where different sized NLPs were not sufficiently separated or purified by SEC, AFM was used to deconvolute the elution pattern of different sized NLPs. From this analysis we were able to purify an NLP subpopulation to 90% size homogeneity by taking extremely fine elutions from the SEC. With this purity, we generate high quality NLP crystals that were over 100 μm in size with little precipitate, which could not be obtained utilizing the traditional size exclusion techniques. This purification procedure and the methods for validation are broadly applicable to other lipoprotein particles

Atomic-Resolution Simulations Predict a Transition State for Vesicle Fusion Defined by Contact of a Few Lipid Tails

Membrane fusion is essential to both cellular vesicle trafficking and infection by enveloped viruses. While the fusion protein assemblies that catalyze fusion are readily identifiable, the specific activities of the proteins involved and nature of the membrane changes they induce remain unknown. Here, we use many atomic-resolution simulations of vesicle fusion to examine the molecular mechanisms for fusion in detail. We employ committor analysis for these million-atom vesicle fusion simulations to identify a transition state for fusion stalk formation. In our simulations, this transition state occurs when the bulk properties of each lipid bilayer remain in a lamellar state but a few hydrophobic tails bulge into the hydrophilic interface layer and make contact to nucleate a stalk. Additional simulations of influenza fusion peptides in lipid bilayers show that the peptides promote similar local protrusion of lipid tails. Comparing these two sets of simulations, we obtain a common set of structural changes between the transition state for stalk formation and the local environment of peptides known to catalyze fusion. Our results thus suggest that the specific molecular properties of individual lipids are highly important to vesicle fusion and yield an explicit structural model that could help explain the mechanism of catalysis by fusion proteins

Persistence, adherence, and all-cause healthcare costs in atazanavir- and darunavir-treated patients with human immunodeficiency virus in a real-world setting

<p><b>Objectives:</b></p> <p>Atazanavir (ATV) and darunavir (DRV) are protease inhibitors approved for HIV treatment in combination with ritonavir (/r). The objectives of this study were to compare persistence (time to treatment discontinuation/modification), adherence, and healthcare costs among patients with human immunodeficiency virus (HIV) initiating ATV/r or DRV/r.</p> <p><b>Methods:</b></p> <p>This retrospective cohort study used commercial and Medicaid administrative insurance claims data. Patients initiating ATV/r or DRV/r from 2006–2013 with continuous enrollment for ≥6 months before and ≥3 months after initiation were included. Patients were followed from initiation until discontinuation/modification (≥30 day gap in ATV or DRV or initiation of a new antiretroviral medication), during which time adherence (proportion of days covered [PDC], with PDC ≥80% or 95% considered adherent) and per-patient per-month (PPPM) total healthcare costs were measured. DRV/r patients were propensity score matched to ATV/r patients at a 1:1 ratio to achieve balance on potentially confounding demographic and clinical factors. Commercial and Medicaid samples were analyzed separately, as were antiretroviral (ART)-naïve and experienced patients.</p> <p><b>Results:</b></p> <p>The final samples comprised 2988 commercially-insured and 1158 Medicaid-insured patients. There were no significant differences in hazards of discontinuation/modification between the ATV/r or DRV/r cohorts. With respect to odds of being adherent, the only marginally significant result was comparing odds of achieving PDC ≥80% among ART-naïve Medicaid patients, which favored ATV/r. All other adherence comparisons were not significant. Although ATV/r cohorts tended to have lower PPPM costs, the majority of these differences were not statistically significant.</p> <p><b>Conclusions:</b></p> <p>Patients with HIV treated with either ATV/r or DRV/r had similar time to treatment discontinuation/modification, adherence, and monthly healthcare costs. Results were similar across the pre-specified sub-groups. These findings are useful not only as an insight into clinical practice, but also as a resource for healthcare providers and payers evaluating treatment options for HIV+ individuals.</p

Predictors of Heterogeneity in Cognitive Function: APOE-e4, Sex, Education, Depression, and Vascular Risk

OBJECTIVE: Mild cognitive impairment and dementia are clinically heterogeneous disorders influenced by diverse risk factors. Improved characterization of the effect of multiple risk factors influence on specific cognitive functions may improve understanding of mechanisms in early cognitive change and lead to more effective interventions. METHODS: Structural equation modeling (SEM) simultaneously examined the effects of modifiable (education, depression, and metabolic/vascular risk) and nonmodifiable risk factors (age, sex, and apolipoprotein E-ɛ4 allele [APOE-e4] status) on specific cognitive domains in 461 cognitively normal older adults. RESULTS: The hypothesized model(s) provided an adequate fit for the data. Sex differences in cognition, depression, and vascular risk were found. On average, men were higher in vascular risk with generally lower cognitive performance than women; women were more likely to have depression. APOE-e4 associated with depression but not age, sex, or metabolic/vascular risk. Depression associated with lower executive attention, memory, and language performance, whereas metabolic/vascular risk associated with lower executive attention, memory, and working memory. Older age and lower education are associated with worse performance across the cognitive domains. The combined risk factors accounted for 16%-47% of the variance in the cognitive domains. CONCLUSIONS: Results highlight the combined effect of risk factors on cognitive function. Future research is needed to determine whether the multifactorial risk effects on cognition vary by sex. Precision medicine approaches that integrate neuropsychological services may improve diagnostic accuracy and earlier identification of those at risk of cognitive decline