The envelope glycoprotein (Env) gp120/gp41 is required for HIV-1 infection of host cells. Although in general it has been perceived that more Env gives rise to higher infectivity, the precise quantitative dependence of HIV-1 virion infectivity on Env density has remained unknown. Here we have developed a method to examine this dependence. This method involves 1) production of a set of single-cycle HIV-1 virions with varied density of Env on their surface, 2) site-specific labeling of Envspecific antibody Fab with a fluorophore at high efficiency, and 3) optical trapping virometry to measure the number of gp120 molecules on individual HIV-1 virions. The resulting gp120 density per virion is then correlated with the infectivity of the virions measured in cell culture. In the presence of DEAE-dextran, the polycation known to enhance HIV-1 infectivity in cell culture, virion infectivity follows gp120 density as a sigmoidal dependence and reaches an apparent plateau. This quantitative dependence can be described by a Hill equation, with a Hill coefficient of 2.4 ؎ 0.6. In contrast, in the absence of DEAE-dextran, virion infectivity increases monotonically with gp120 density and no saturation is observed under the experimental conditions. These results provide the first quantitative evidence that Env trimers cooperate on the virion surface to mediate productive infection by HIV-1. Moreover, as a result of the low number of Env trimers on individual virions, the number of additional Env trimers per virion that is required for the optimal infectivity will depend on the inclusion of facilitating agents during infection.Like other enveloped viruses, HIV-1 uses the trimer-of-hairpins mechanism to catalyze the fusion between viral and cell membranes, an essential step during the life cycle of all envel- (7), suggesting that more Env may indeed confer selective advantages in HIV-1 transmission. At the mechanistic level, however, how the Env copy number may enhance virion transmission is not well understood. Although greater amounts of Env have been observed to increase infectivity (8), the dependence of HIV-1 virion infectivity on Env density has not been precisely described or explained.In this paper, we introduce a quantitative approach to this problem. In our approach, we use a provirus clone that is env Ϫ together with a separate wild-type env plasmid (pEnv) to generate HIV-1 virions (9). It is essential that the provirus is env Ϫ so that we can titrate pEnv from low to high quantities (8) to generate a set of virions that are expected to carry varied densities of Env on their surface, limited by the pEnv inputs (10). Meanwhile, the resulting virions are only infectious for a single cycle. The infectivity of the virions can thus be correlated with the Env content of these virions that can be directly measured by singlemolecule techniques without the complications from multiple rounds of infection.To determine Env density on individual virions, we have recently developed a technique named optical trapping virometry (OTV)...

Standard deviation measurements of intensity profiles of stationary single fluorescent molecules are useful for studying axial localization, molecular orientation, and a fluorescence imaging system’s spatial resolution. Here we report on the analysis of the precision of standard deviation measurements of intensity profiles of single fluorescent molecules imaged using an EMCCD camera. We have developed an analytical expression for the standard deviation measurement error of a single image which is a function of the total number of detected photons, the background photon noise, and the camera pixel size. The theoretical results agree well with the experimental, simulation, and numerical integration results. Using this expression, we show that single-molecule standard deviation measurements offer nanometer precision for a large range of experimental parameters.

Astrocytes are essential cells of the central nervous system, characterized by dynamic relationships with neurons that range from functional metabolic interactions and regulation of neuronal firing activities, to the release of neurotrophic and neuroprotective factors. In Parkinson's disease (PD), dopaminergic neurons are progressively lost during the course of the disease, but the effects of PD on astrocytes and astrocyte-to-neuron communication remains largely unknown. This study focuses on the effects of the PD-related mutation LRRK2 G2019S in astrocytes generated from patient-derived induced pluripotent stem cells. We report the alteration of extracellular vesicle (EV) biogenesis in astrocytes, and we identify the abnormal accumulation of key PD-related proteins within multi vesicular bodies (MVBs). We found that dopaminergic neurons internalize astrocyte-secreted EVs and that LRRK2 G2019S EVs are abnormally enriched in neurites and fail to provide full neurotrophic support to dopaminergic neurons. Thus, dysfunctional astrocyte-to-neuron communication via altered EV biological properties may participate in the progression of PD.

The rapid advancement of live‐cell imaging technologies has enabled biologists to generate high‐dimensional data to follow biological movement at the microscopic level. Yet, the “perceived” ease of use of modern microscopes has led to challenges whereby sub‐optimal data are commonly generated that cannot support quantitative tracking and analysis as a result of various ill‐advised decisions made during image acquisition. Even optimally acquired images often require further optimization through digital processing before they can be analyzed. In writing this article, we presume our target audience to be biologists with a foundational understanding of digital image acquisition and processing, who are seeking to understand the essential steps for particle/object tracking experiments. It is with this targeted readership in mind that we review the basic principles of image‐processing techniques as well as analysis strategies commonly used for tracking experiments. We conclude this technical survey with a discussion of how movement behavior can be mathematically modeled and described. © 2019 by John Wiley & Sons, Inc.