Atomic force microscopy differentiates discrete size distributions between membrane protein containing and empty nanolipoprotein particles

AbstractTo better understand the incorporation of membrane proteins into discoidal nanolipoprotein particles (NLPs) we have used atomic force microscopy (AFM) to image and analyze NLPs assembled in the presence of bacteriorhodopsin (bR), lipoprotein E4 n-terminal 22k fragment scaffold and DMPC lipid. The self-assembly process produced two distinct NLP populations: those containing inserted bR (bR-NLPs) and those that did not (empty-NLPs). The bR-NLPs were distinguishable from empty-NLPs by an average increase in height of 1.0 nm as measured by AFM. Streptavidin binding to biotinylated bR confirmed that the original 1.0 nm height increase corresponds to br-NLP incorporation. AFM and ion mobility spectrometry (IMS) measurements suggest that NLP size did not vary around a single mean but instead there were several subpopulations, which were separated by discrete diameters. Interestingly, when bR was present during assembly the diameter distribution was shifted to larger particles and the larger particles had a greater likelihood of containing bR than smaller particles, suggesting that membrane proteins alter the mechanism of NLP assembly

Expressions 1987

https://openspace.dmacc.edu/expressions/1030/thumbnail.jp

Validating the predicted lateral straggling of MeV-energy proton beams.

Proton imaging is a potential nondestructive method for characterizing NIF (National Ignition Facility) targets in two- and three-dimensions with micron-scale spatial resolution. The main limitation for high resolution imaging with proton beams, especially for thick samples, is the positional blurring of the proton beam, known as 'lateral straggling'. Accurate prediction of the amount of lateral straggling and, consequently, the achievable spatial resolution in pertinent NIF target material combinations and geometries requires validated proton transport models. We present results of Monte Carlo simulations of MeV-energy proton transport through thin ({approx}1 micron thick) metal foils. The calculated residual proton distributions are compared to recent lateral straggling measurements obtained at the LLNL 4-MV Pelletron accelerator

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

Isolation, Characterization, and Stability of Discretely-Sized Nanolipoprotein Particles Assembled with Apolipophorin-III

Background: Nanolipoprotein particles (NLPs) are discoidal, nanometer-sized particles comprised of self-assembled phospholipid membranes and apolipoproteins. NLPs assembled with human apolipoproteins have been used for myriad biotechnology applications, including membrane protein solubilization, drug delivery, and diagnostic imaging. To expand the repertoire of lipoproteins for these applications, insect apolipophorin-III (apoLp-III) was evaluated for the ability to form discretely-sized, homogeneous, and stable NLPs. Methodology: Four NLP populations distinct with regards to particle diameters (ranging in size from 10 nm to.25 nm) and lipid-to-apoLp-III ratios were readily isolated to high purity by size exclusion chromatography. Remodeling of the purified NLP species over time at 4uC was monitored by native gel electrophoresis, size exclusion chromatography, and atomic force microscopy. Purified 20 nm NLPs displayed no remodeling and remained stable for over 1 year. Purified NLPs with 10 nm and 15 nm diameters ultimately remodeled into 20 nm NLPs over a period of months. Intra-particle chemical cross-linking of apoLp-III stabilized NLPs of all sizes. Conclusions: ApoLp-III-based NLPs can be readily prepared, purified, characterized, and stabilized, suggesting their utilit

An Ontological Approach to Inform HMI Designs for Minimizing Driver Distractions with ADAS

ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and efficiency as well as comfort for drivers in the driving process. Recent studies have noticed that when Human Machine Interface (HMI) is not designed properly, an ADAS can cause distraction which would affect its usage and even lead to safety issues. Current understanding of these issues is limited to the context-dependent nature of such systems. This paper reports the development of a holistic conceptualisation of how drivers interact with ADAS and how such interaction could lead to potential distraction. This is done taking an ontological approach to contextualise the potential distraction, driving tasks and user interactions centred on the use of ADAS. Example scenarios are also given to demonstrate how the developed ontology can be used to deduce rules for identifying distraction from ADAS and informing future designs