Hetero-pentamerization determines mobility and conductance of Glycine receptor α3 splice variants.

Glycine receptors (GlyRs) are ligand-gated pentameric chloride channels in the central nervous system. GlyR-α3 is a possible target for chronic pain treatment and temporal lobe epilepsy. Alternative splicing into K or L variants determines the subcellular fate and function of GlyR-α3, yet it remains to be shown whether its different splice variants can functionally co-assemble, and what the properties of such heteropentamers would be. Here, we subjected GlyR-α3 to a combined fluorescence microscopy and electrophysiology analysis. We employ masked Pearson's and dual-color spatiotemporal correlation analysis to prove that GlyR-α3 splice variants heteropentamerize, adopting the mobility of the K variant. Fluorescence-based single-subunit counting experiments revealed a variable and concentration ratio dependent hetero-stoichiometry. Via cell-attached single-channel electrophysiology we show that heteropentamers exhibit currents in between those of K and L variants. Our data are compatible with a model where α3 heteropentamerization fine-tunes mobility and activity of GlyR-α3 channels, which is important to understand and tackle α3 related diseases.

Live Cell Imaging Demonstrates Multiple Routes Toward a STAT1 Gain-of-Function Phenotype.

Signal transducer and activator of transcription 1 (STAT1) gain-of-function (GOF) mutations result in a primary immunodeficiency (PID) characterized typically by chronic mucocutaneous candidiasis (CMC), but a wider phenotypic range is reported and remains unexplained from a pathophysiological point-of-view. We hypothesized that different STAT1 GOF mutations may result in distinct molecular mechanisms, possibly explaining the variable phenotypes observed in patients. We selected STAT1 GOF mutants (R274W, R321S, T419R, and N574I) that are spread over the protein and studied their dynamic behavior in vitro in U3A and HeLa cell lines. All GOF mutants showed increased STAT1 phosphorylation compared to STAT1 WT. Real-time imaging demonstrated three underlying mechanisms for STAT1 GOF: (i) R274W showed a faster nuclear accumulation, (ii) both R321S and N574I showed a reduced nuclear mobility and slower dephosphorylation, whereas (iii) T419R was near-immobile in the nucleus, potentially due to enhanced binding to chromatin.

Fluorescence microscopy data for quantitative mobility and interaction analysis of proteins in living cells.

The data provided with this paper are image series of slowly diffusing GlyRa3 molecules, linked to either eGFP or mCherry fluorescent proteins, at the membrane of HEK cells, acquired on a Zeiss LSM880 confocal laser scanning microscope. Raster spectral image cross-correlation spectroscopy (RSICS) is applied to the data, a technique that exploits intensity fluctuations in confocal image series recorded using a spectral detector to study the diffusion and concentration of molecules, and interactions between them. First, spectral filters are created from reference image series containing GlyRa3 labeled with a single fluorophore. Once experimental data containing GlyRa3 labeled with both fluorophores is acquired, single images are either autocorrelated, or the cross-correlation is calculated between two images, each one containing the data for eGFP or mCherry labeled GyRa 3. Data is then fit with a one-component model assuming a two-dimensional Gaussian point spread function to obtain the diffusion coefficient, D, and average number of molecules in the focus, N. The software package PAM is used to analyze all the acquired data. The data can be used as a reference for artifact-free two-color ccRICS that contains slowly diffusing interacting molecules. Additionally, the analysis workflow described in this paper helps researchers avoid common errors during a RICS experiment.

Capsid-Labelled HIV To Investigate the Role of Capsid during Nuclear Import and Integration.

The HIV-1 capsid protein performs multiple roles in virus replication both during assembly and particle release and during virus trafficking into the nucleus. In order to decipher the roles of capsid protein during early replication, a reliable method to follow its intracellular distribution is required. To complement existing approaches to track HIV-1 capsid during early infection, we developed an HIV-1 imaging strategy, relying on viruses incorporating enhanced green fluorescent protein (eGFP)-tagged capsid (CA-eGFP) protein and mCherry-tagged integrase (IN-mCherry). Wild-type infectivity and sensitivity to inhibition by PF74 point to the functionality of CA-eGFP-containing complexes. Low numbers of CA-eGFP molecules were located inside the viral core and imported into the nucleus without significant loss in intensity. Less than 5% of particles carrying both CA-eGFP and IN-mCherry retained both labelled proteins after nuclear entry, implying a major uncoating event at the nuclear envelope dissociating IN and CA. Still, 20% of all CA-eGFP-containing complexes were detected in the nucleus. Unlike for IN-mCherry complexes, addition of the integrase inhibitor raltegravir had no effect on CA-eGFP-containing complexes, suggesting that these may be not (yet) competent for integration. Our imaging strategy offers alternative visualization of viral capsid trafficking and helps clarify its potential role during integration.IMPORTANCE HIV-1 capsid protein (CA) builds a conical shell protecting viral genomic RNA inside the virus particles. Upon entry into host cells, this shell disassembles in a process of uncoating, which is coordinated with reverse transcription of viral RNA into DNA. After uncoating, a portion of CA remains associated with the viral DNA and mediates its nuclear import and, potentially, integration into host DNA. In this study, we tagged CA with eGFP to follow its trafficking in host cells and address potential CA roles in the nucleus. We found that while functional viruses import the tagged CA into the nucleus, this capsid protein is not part of integration-competent complexes. The roles of nuclear CA thus remain to be established.

Raster Image Correlation Spectroscopy Performance Evaluation.

Raster image correlation spectroscopy (RICS) is a fluorescence image analysis method for extracting the mobility, concentration, and stoichiometry of diffusing fluorescent molecules from confocal image stacks. The method works by calculating a spatial correlation function for each image and analyzing the average of those by model fitting. Rules of thumb exist for RICS image acquisitioning, yet a rigorous theoretical approach to predict the accuracy and precision of the recovered parameters has been lacking. We outline explicit expressions to reveal the dependence of RICS results on experimental parameters. In terms of imaging settings, we observed that a twofold decrease of the pixel size, e.g., from 100 to 50 nm, decreases the error on the translational diffusion constant (D) between three- and fivefold. For D = 1 µm2 s-1, a typical value for intracellular measurements, ∼25-fold lower mean-squared relative error was obtained when the optimal scan speed was used, although more drastic improvements were observed for other values of D. We proposed a slightly modified RICS calculation that allows correcting for the significant bias of the autocorrelation function at small (≪50 × 50 pixels) sizes of the region of interest. In terms of sample properties, at molecular brightness E = 100 kHz and higher, RICS data quality was sufficient using as little as 20 images, whereas the optimal number of frames for lower E scaled pro rata. RICS data quality was constant over the nM-µM concentration range. We developed a bootstrap-based confidence interval of D that outperformed the classical least-squares approach in terms of coverage probability of the true value of D. We validated the theory via in vitro experiments of enhanced green fluorescent protein at different buffer viscosities. Finally, we outline robust practical guidelines and provide free software to simulate the parameter effects on recovery of the diffusion coefficient.

Body surface area-based versus concentration-based intraperitoneal perioperative chemotherapy in a rat model of colorectal peritoneal surface malignancy: pharmacologic guidance towards standardization.

Worldwide, cytoreductive surgery (CRS) and hyperthermic intraperitoneal perioperative chemotherapy (HIPEC) are used in current clinical practice for colorectal peritoneal surface malignancy (PSM) treatment. Although, there is an acknowledged standardization regarding the CRS, we are still lacking a much-needed standardization amongst the various intraperitoneal (IP) chemotherapy protocols, including the HIPEC dosing regimen. We should rely on pharmacologic evidence building towards such a standardization. The current IP chemotherapy dosing regimens can be divided into body surface area (BSA)-based and concentration-based protocols. A preclinical animal study was designed to evaluate pharmacologic advantage (PA), efficacy and survival. WAG/Rij rats were IP injected with the rat colonic carcinoma cell line CC-531. Animals were randomized into three groups: CRS alone or CRS combined with oxaliplatin-based HIPEC (either BSA- or concentration-based). There was no difference in PA between the two groups (p=0.283). Platinum concentration in the tumor nodule was significantly higher in the concentration-based group (p<0.001). Median survival did not differ between the treatment groups (p<0.250). This preclinical study, in contrast to previous thinking, clearly demonstrates that the PA does not provide any information about the true efficacy of the drug and emphasizes the importance of the tumor nodule as pharmacologic endpoint.

Crosstalk-free multicolor RICS using spectral weighting.

Raster image cross-correlation spectroscopy (ccRICS) can be used to quantify the interaction affinities between diffusing molecules by analyzing the fluctuations between two-color confocal images. Spectral crosstalk compromises the quantitative analysis of ccRICS experiments, limiting multicolor implementations to dyes with well-separated emission spectra. Here, we remove this restriction by introducing raster spectral image correlation spectroscopy (RSICS), which employs statistical filtering based on spectral information to quantitatively separate signals of fluorophores during spatial correlation analysis. We investigate the performance of RSICS by testing how different levels of spectral overlap or different relative signal intensities affect the correlation function and analyze the influence of statistical filter quality. We apply RSICS in vitro to resolve dyes with very similar emission spectra, and carry out RSICS in live cells to simultaneously analyze the diffusion of molecules carrying three different fluorescent protein labels (eGFP, Venus and mCherry). Finally, we successfully apply statistical weighting to data that was recorded with only a single detection channel per fluorophore, highlighting the general applicability of this method to data acquired with any type of multicolor detection. In conclusion, RSICS enables artifact-free quantitative analysis of concentrations, mobility and interactions of multiple species labeled with different fluorophores. It can be performed on commercial laser scanning microscopes, and the algorithm can be easily extended to other image correlation methods. Thus, RSICS opens the door to quantitative multicolor fluctuation analyses of complex (bio-) molecular systems.