Bioimage informatics for understanding spatiotemporal dynamics of cellular processes

Quantitative analysis of subcellular distributions with an open-source, object-based tool

The subcellular localization of objects, such as organelles, proteins, or other molecules, instructs cellular form and function. Understanding the underlying spatial relationships between objects through colocalization analysis of microscopy images is a fundamental approach used to inform biological mechanisms. We generated an automated and customizable computational tool, the SubcellularDistribution pipeline, to facilitate object-based image analysis from three-dimensional (3D) fluorescence microcopy images. To test the utility of the SubcellularDistribution pipeline, we examined the subcellular distribution of mRNA relative to centrosomes within syncytial Drosophila embryos. Centrosomes are microtubule-organizing centers, and RNA enrichments at centrosomes are of emerging importance. Our open-source and freely available software detected RNA distributions comparably to commercially available image analysis software. The SubcellularDistribution pipeline is designed to guide the user through the complete process of preparing image analysis data for publication, from image segmentation and data processing to visualization.This article has an associated First Person interview with the first author of the paper.

Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation

Spatiotemporal regulation of molecular activities dictates cellular function and fate. Investigation of dynamic molecular activities in live cells often requires the visualization and quantitation of fluorescent ratio image sequences with subcellular resolution and in high throughput. Hence, there is a great need for convenient software tools specifically designed with these capabilities. Here we describe a well-characterized open-source software package, Fluocell, customized to visualize pixelwise ratiometric images and calculate ratio time courses with subcellular resolution and in high throughput. Fluocell also provides group statistics and kinetic analysis functions for the quantified time courses, as well as 3D structure and function visualization for ratio images. The application of Fluocell is demonstrated by the ratiometric analysis of intensity images for several single-chain Förster (or fluorescence) resonance energy transfer (FRET)-based biosensors, allowing efficient quantification of dynamic molecular activities in a heterogeneous population of single live cells. Our analysis revealed distinct activation kinetics of Fyn kinase in the cytosolic and membrane compartments, and visualized a 4D spatiotemporal distribution of epigenetic signals in mitotic cells. Therefore, Fluocell provides an integrated environment for ratiometric live-cell image visualization and analysis, which generates high-quality single-cell dynamic data and allows the quantitative machine-learning of biophysical and biochemical computational models for molecular regulations in cells and tissues.

High resolution snapshot imaging spectrometer using a fusion algorithm based on grouping principal component analysis

We reported a high resolution snapshot imaging spectrometer (HR-SIS) and a fusion algorithm based on the properties of the HR-SIS. The system consists of an imaging branch and a spectral branch. The imaging branch captures a high spatial resolution panchromatic image with 680 × 680 pixels, while the spectral branch acquires a low spatial resolution spectral image with spectral resolution of 250 cm^-1. By using a fusion algorithm base on grouping principal component analysis, the spectral image is highly improved in spatial resolution. Experimental results demonstrated that the performance of the proposed algorithm is competitive with other state-of-the-art algorithms. The computing time for a single frame is less than 1 min with an Intel Core i5-4200H CPU, which can be further reduced by utilizing a graphics processing unit (GPU).

Biostatistical analysis of quantitative immunofluorescence microscopy images

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization.

Lipid raft-based membrane order is important for antigen-specific clonal expansion of CD4(+) T lymphocytes

Background

Lipid rafts are cholesterol and saturated lipid-rich, nanometer sized membrane domains that are hypothesized to play an important role in compartmentalization and spatiotemporal regulation of cellular signaling. Lipid rafts contribute to the plasma membrane order and to its spatial asymmetry, as well. The raft nanodomains on the surface of CD4⁺ T lymphocytes coalesce during their interaction with antigen presenting cells (APCs). Sensing of foreign antigen by the antigen receptor on CD4⁺ T cells occurs during these cell-cell interactions. In response to foreign antigen the CD4⁺ T cells proliferate, allowing the expansion of few antigen-specific primary CD4⁺ T cell clones. Proliferating CD4⁺ T cells specialize in their function by undergoing differentiation into appropriate effectors tailored to mount an effective adaptive immune response against the invading pathogen.

Results

To investigate the role of lipid raft-based membrane order in the clonal expansion phase of primary CD4⁺ T cells, we have disrupted membrane order by incorporating an oxysterol, 7-ketocholesterol (7-KC), into the plasma membrane of primary CD4⁺ T cells expressing a T cell receptor specific to chicken ovalbumin_323–339 peptide sequence and tested their antigen-specific response. We report that 7-KC, at concentrations that disrupt lipid rafts, significantly diminish the c-Ovalbumin_323–339 peptide-specific clonal expansion of primary CD4⁺ T cells.

Conclusions

Our findings suggest that lipid raft-based membrane order is important for clonal expansion of CD4⁺ T cells in response to a model peptide.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-014-0058-8) contains supplementary material, which is available to authorized users.