Image analysis and empirical modeling of gene and protein expression

Protein gradients and gene expression patterns are major determinants in the differentiation and fate map of the developing embryo. Here we discuss computational methods to quantitatively measure the positions of gene expression domains and the gradients of protein expression along the dorsal–ventral axis in the Drosophila embryo. Our methodology involves three layers of data. The first layer, or the primary data, consists of z-stack confocal images of embryos processed by in situ hybridization and/or antibody stainings. The secondary data are relationships between location, usually an x-axis coordinate, and fluorescent intensity of gene or protein detection. Tertiary data comprise the optimal parameters that arise from fits of the secondary data to empirical models. The tertiary data are useful to distill large datasets of imaged embryos down to a tractable number of conceptually useful parameters. This analysis allows us to detect subtle phenotypes and is adaptable to any set of genes or proteins with a canonical pattern. For example, we show how insights into the Dorsal transcription factor protein gradient and its target gene ventral-neuroblasts defective (vnd) were obtained using such quantitative approaches

Dynamic Heterogeneity and DNA Methylation in Embryonic Stem Cells

Cell populations can be strikingly heterogeneous, composed of multiple cellular states, each exhibiting stochastic noise in its gene expression. A major challenge is to disentangle these two types of variability and to understand the dynamic processes and mechanisms that control them. Embryonic stem cells (ESCs) provide an ideal model system to address this issue because they exhibit heterogeneous and dynamic expression of functionally important regulatory factors. We analyzed gene expression in individual ESCs using single-molecule RNA-FISH and quantitative time-lapse movies. These data discriminated stochastic switching between two coherent (correlated) gene expression states and burst-like transcriptional noise. We further showed that the “2i” signaling pathway inhibitors modulate both types of variation. Finally, we found that DNA methylation plays a key role in maintaining these metastable states. Together, these results show how ESC gene expression states and dynamics arise from a combination of intrinsic noise, coherent cellular states, and epigenetic regulation

Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1–2 d for progressing through the analysis procedure

Calcium signals are necessary to establish auxin transporter polarity in a plant stem cell niche

In plants mechanical signals pattern morphogenesis through the polar transport of the hormone auxin and through regulation of interphase microtubule (MT) orientation. To date, the mechanisms by which such signals induce changes in cell polarity remain unknown. Through a combination of time-lapse imaging, and chemical and mechanical perturbations, we show that mechanical stimulation of the SAM causes transient changes in cytoplasmic calcium ion concentration (Ca^(2+)) and that transient Ca^(2+) response is required for downstream changes in PIN-FORMED 1 (PIN1) polarity. We also find that dynamic changes in Ca^(2+) occur during development of the SAM and this Ca^(2+) response is required for changes in PIN1 polarity, though not sufficient. In contrast, we find that Ca^(2+) is not necessary for the response of MTs to mechanical perturbations revealing that Ca^(2+) specifically acts downstream of mechanics to regulate PIN1 polarity response

Calcium signals are necessary to establish auxin transporter polarity in a plant stem cell niche

In plants mechanical signals pattern morphogenesis through the polar transport of the hormone auxin and through regulation of interphase microtubule (MT) orientation. To date, the mechanisms by which such signals induce changes in cell polarity remain unknown. Through a combination of time-lapse imaging, and chemical and mechanical perturbations, we show that mechanical stimulation of the SAM causes transient changes in cytoplasmic calcium ion concentration (Ca^(2+)) and that transient Ca^(2+) response is required for downstream changes in PIN-FORMED 1 (PIN1) polarity. We also find that dynamic changes in Ca^(2+) occur during development of the SAM and this Ca^(2+) response is required for changes in PIN1 polarity, though not sufficient. In contrast, we find that Ca^(2+) is not necessary for the response of MTs to mechanical perturbations revealing that Ca^(2+) specifically acts downstream of mechanics to regulate PIN1 polarity response

Model based dynamics analysis in live cell microtubule images

Background: The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data. Results: In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior. Conclusion: Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior

Variable Length Open Contour Tracking Using a Deformable Trellis

This paper focuses on contour tracking, an important problem in computer vision, and specifically on open contours that often directly represent a curvilinear object. Compelling applications are found in the field of bioimage analysis where blood vessels, dendrites, and various other biological structures are tracked over time. General open contour tracking, and biological images in particular, pose major challenges including scene clutter with similar structures (e.g., in the cell), and time varying contour length due to natural growth and shortening phenomena, which have not been adequately answered by earlier approaches based on closed and fixed end-point contours. We propose a model-based estimation algorithm to track open contours of time-varying length, which is robust to neighborhood clutter with similar structures. The method employs a deformable trellis in conjunction with a probabilistic (hidden Markov) model to estimate contour position, deformation, growth and shortening. It generates a maximum a posteriori estimate given observations in the current frame and prior contour information from previous frames. Experimental results on synthetic and real-world data demonstrate the effectiveness and performance gains of the proposed algorithm