Bayesian Model Selection Applied to the Analysis of Fluorescence Correlation Spectroscopy Data of Fluorescent Proteins in Vitro and in Vivo

Fluorescence correlation spectroscopy (FCS) is a powerful technique to investigate molecular dynamics with single molecule sensitivity. In particular, in the life sciences it has found widespread application using fluorescent proteins as molecularly specific labels. However, FCS data analysis and interpretation using fluorescent proteins remains challenging due to typically low signal-to-noise ratio of FCS data and correlated noise in autocorrelated data sets. As a result, naive fitting procedures that ignore these important issues typically provide similarly good fits for multiple competing models without clear distinction of which model is preferred given the signal-to-noise ratio present in the data. Recently, we introduced a Bayesian model selection procedure to overcome this issue with FCS data analysis. The method accounts for the highly correlated noise that is present in FCS data sets and additionally penalizes model complexity to prevent over interpretation of FCS data. Here, we apply this procedure to evaluate FCS data from fluorescent proteins assayed in vitro and in vivo. Consistent with previous work, we demonstrate that model selection is strongly dependent on the signal-to-noise ratio of the measurement, namely, excitation intensity and measurement time, and is sensitive to saturation artifacts. Under fixed, low intensity excitation conditions, physical transport models can unambiguously be identified. However, at excitation intensities that are considered moderate in many studies, unwanted artifacts are introduced that result in nonphysical models to be preferred. We also determined the appropriate fitting models of a GFP tagged secreted signaling protein, Wnt3, in live zebrafish embryos, which is necessary for the investigation of Wnt3 expression and secretion in development. Bayes model selection therefore provides a robust procedure to determine appropriate transport and photophysical models for fluorescent proteins when appropriate models are provided, to help detect and eliminate experimental artifacts in solution, cells, and in living organisms.National Science Foundation (U.S.). Physics of Living Systems ProgramNational Institute of Mental Health (U.S.) (Award U01MH106011

Imaging Single Retrovirus Entry through Alternative Receptor Isoforms and Intermediates of Virus-Endosome Fusion

A large group of viruses rely on low pH to activate their fusion proteins that merge the viral envelope with an endosomal membrane, releasing the viral nucleocapsid. A critical barrier to understanding these events has been the lack of approaches to study virus-cell membrane fusion within acidic endosomes, the natural sites of virus nucleocapsid capsid entry into the cytosol. Here we have investigated these events using the highly tractable subgroup A avian sarcoma and leukosis virus envelope glycoprotein (EnvA)-TVA receptor system. Through labeling EnvA pseudotyped viruses with a pH-sensitive fluorescent marker, we imaged their entry into mildly acidic compartments. We found that cells expressing the transmembrane receptor (TVA950) internalized the virus much faster than those expressing the GPI-anchored receptor isoform (TVA800). Surprisingly, TVA800 did not accelerate virus uptake compared to cells lacking the receptor. Subsequent steps of virus entry were visualized by incorporating a small viral content marker that was released into the cytosol as a result of fusion. EnvA-dependent fusion with TVA800-expressing cells occurred shortly after endocytosis and delivery into acidic endosomes, whereas fusion of viruses internalized through TVA950 was delayed. In the latter case, a relatively stable hemifusion-like intermediate preceded the fusion pore opening. The apparent size and stability of nascent fusion pores depended on the TVA isoforms and their expression levels, with TVA950 supporting more robust pores and a higher efficiency of infection compared to TVA800. These results demonstrate that surface receptor density and the intracellular trafficking pathway used are important determinants of efficient EnvA-mediated membrane fusion, and suggest that early fusion intermediates play a critical role in establishing low pH-dependent virus entry from within acidic endosomes

Novel animal models for studying complex brain disorders: BAC-driven miRNA-mediated in vivo silencing of gene expression

In schizophrenia, glutamic acid decarboxylase 1 (GAD1) disturbances are robust, consistently observed, cell-type specific and represent a core feature of the disease. In addition, neuropeptide Y (NPY), which is a phenotypic marker of a sub-population of GAD1-containing interneurons, has shown reduced expression in the prefrontal cortex in subjects with schizophrenia, suggesting that dysfunction of the NPY+ cortical interneuronal sub-population might be a core feature of this devastating disorder. However, modeling gene expression disturbances in schizophrenia in a cell type-specific manner has been extremely challenging. To more closely mimic these molecular and cellular human post-mortem findings, we generated a transgenic mouse in which we downregulated GAD1 mRNA expression specifically in NPY+ neurons. This novel, cell type-specific in vivo system for reducing gene expression uses a bacterial artificial chromosome (BAC) containing the NPY promoter-enhancer elements, the reporter molecule (eGFP) and a modified intron containing a synthetic microRNA (miRNA) targeted to GAD1. The animals of isogenic strains are generated rapidly, providing a new tool for better understanding the molecular disturbances in the GABAergic system observed in complex neuropsychiatric disorders such as schizophrenia. In the future, because of the small size of the silencing miRNAs combined with our BAC strategy, this method may be modified to allow generation of mice with simultaneous silencing of multiple genes in the same cells with a single construct, and production of splice-variant-specific knockdown animals