Cell cycle phase classification in 3D in vivo microscopy of Drosophila embryogenesis

10th International Conference on Bioinformatics - 1st ISCB Asia Joint Conference 2011, InCoB 2011/ISCB-Asia 2011: Bioinformatics - Proceedings from Asia Pacific Bioinformatics Network (APBioNet)12SUPPL. 13

Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli

<p>Abstract</p> <p>Background</p> <p>Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation of the metabolism when cells adapt to environmental changes, whole genome gene expression profiles can be analysed. Moreover, utilising a network topology based on gene relationships may facilitate interpreting this vast amount of information, and extracting significant patterns within the networks.</p> <p>Results</p> <p>Interpreting expression levels as pixels with grey value intensities and network topology as relationships between pixels, allows for an image-like representation of cellular metabolism. While the topology of a regular image is a lattice grid, biological networks demonstrate scale-free architecture and thus advanced image processing methods such as wavelet transforms cannot directly be applied. In the study reported here, one-dimensional enzyme-enzyme pairs were tracked to reveal sub-graphs of a biological interaction network which showed significant adaptations to a changing environment. As a case study, the response of the hetero-fermentative bacterium <it>E. coli </it>to oxygen deprivation was investigated. With our novel method, we detected, as expected, an up-regulation in the pathways of hexose nutrients up-take and metabolism and formate fermentation. Furthermore, our approach revealed a down-regulation in iron processing as well as the up-regulation of the histidine biosynthesis pathway. The latter may reflect an adaptive response of <it>E. coli </it>against an increasingly acidic environment due to the excretion of acidic products during anaerobic growth in a batch culture.</p> <p>Conclusion</p> <p>Based on microarray expression profiling data of prokaryotic cells exposed to fundamental treatment changes, our novel technique proved to extract system changes for a rather broad spectrum of the biochemical network.</p

Towards increased efficiency and automation in fluorescence micrograph analysis based on hand-labeled data

Held CH. Towards increased efficiency and automation in fluorescence micrograph analysis based on hand-labeled data. Bielefeld: Universität Bielefeld; 2013.In the past decade, automation in fluorescence microscopy has strongly increased, particularly in regards to image acquisition and sample preparation, which results in a huge volume of data. The amount of time required for manual assessment of an experiment is hence mainly determined by the amount of time required for data analysis. In addition, manual data analysis is often a task with poor reproducibility and lack of objectivity. Using automated image analysis software, the time required for data analysis can be reduced while quality and reproducibility of the evaluation are improved. Most image analysis approaches are based on a segmentation of the image. By arranging several image processing methods in a so-called segmentation pipeline, and by adjusting all parameters, a broad range of fluorescence image data can be segmented. The drawback of available software tools is the long time required to calibrate the segmentation pipeline for an experiment, particularly for researchers with little knowledge of image processing. As a result, many experiments that could benefit from automated image analysis are still evaluated manually. In order to reduce the amount of time users have to spend in adapting automated image analysis software to their data, research was carried out on a novel image analysis concept based on hand-labeled data. Using this concept, the user is required to provide hand-labeled cells, based on which an efficient combination of image processing methods and their parameterization is automatically calibrated, without further user input. The development of a segmentation pipeline that allows high-quality segmentation of a broad range of fluorescence micrographs in short time poses a challenge. In this work, a three-stage segmentation pipeline consisting of exchangeable preprocessing, figure-ground separation and cell-splitting methods was developed. These methods are mainly based on the state of the art, whereas some of them represent contributions to this status. Discretization of parameters must be performed carefully, as a broad range of fluorescence image data shall be supported. In order to allow calibration of the segmentation pipeline in a short time, discretization with equidistant as well as nonlinear step sizes was implemented. Apart from parameter discretization, quality of the calibration strongly depends on choice of the parameter optimization technique. In order to reduce calibration runtime, exploratory parameter space analysis was performed for different segmentation methods. This experiment showed that parameter spaces are mostly monotonous, but also show several local performance maxima. The comparison of different parameter optimization techniques indicated that the coordinate descent method results in a good parameterization of the segmentation pipeline in a small amount of time. In order to minimize the amount of time spent by the user in calibration of the system, correlation between the number of hand-labeled reference samples and the resulting segmentation performance was investigated. This experiment demonstrates that as few as ten reference samples often result in a good parameterization of the segmentation pipeline. Due to the low number of cells required for automatic calibration of the segmentation pipeline, as well as its short runtime, it can be concluded that the investigated method improves automation and efficiency in fluorescence micrograph analysis

Quantitative Analysis of the Structural Dynamics of Mitotic Chromosomes in Live Mammalian Cells

Chromatin, organized into individual chromosomes, is the physiological carrier of the genetic and epigenetic information in eukaryotes. In the nucleus of an intact cell, the structure of chromatin is dynamic and essential for genomic activities. The most dramatic changes in chromatin structure occur in mitosis, when compact metaphase chromosomes are formed, organized and partitioned equally to two daughter cells. How this vital reorganization of chromatin is accomplished remains poorly understood in vivo. To address this, in the first part of my thesis I developed quantitative assays to determine the kinetics of mitotic chromosome compaction, using multidimensional confocal microscopy of live cells stably expressing fluorescent histone 2b. Condensation was measured at three different scales: Large-scale (~800 nm), where the chromatin volume was measured by high resolution 4D imaging; medium scale (~200 nm) by statistical analysis of pixel intensities; and molecular scale (~10 nm) by a FRET reporter of histone tail environment. These measurements show that (i) mitotic compaction may start at least 20 min before prometaphase; (ii) it correlates with changes in histone tail conformation; (iii) chromatin density is not highest in metaphase but in late anaphase chromosomes. In the second part, I focused on the novel finding of highest compaction in anaphase. Single chromosome measurements revealed that chromatids compact in anaphase by a mechanism of lengthwise shortening that starts only after segregation of the sister chromatids is complete. This axial shortening was not affected in condensin-depleted cells, and was independent of the poleward pulling motion on kinetochores, but it nevertheless depended on dynamic microtubules. Perturbation of this shortening caused a severe phenotype of multi-lobulated daughter nuclei, strongly suggesting a function in post-mitotic nuclear assembly and architecture. In addition, if anaphase compaction was perturbed in condensin-depleted cells, segregation defects increased 3-fold, suggesting a second role for anaphase compaction as a rescue mechanism for segregation defects. In the third part, the quantitative compaction assays were used to probe the role of PNUTS, a major protein phosphatase 1 nuclear-targeting subunit, in the regulation of chromatin structure. In live cells depleted of PNUTS by RNAi, compaction was slowed at least 3-fold. Our collaborators in the group of Philippe Collas at the University of Oslo had shown that PNUTS accelerates chromatin decompaction in vitro. PNUTS is thus involved in mitotic chromatin structure in vivo and in vitro, and my findings make it an interesting target for future research to understand the molecular mechanism of chromosome compaction