From high-content to super-resolution investigation of cell behaviour on nanostructured surfaces

The environment in which cells find themselves is a complex, three dimensional one which provides a variety of inputs and cues capable of controlling and guiding cell behaviour. These environmental signals take a fertilised egg through development to become an adult human being made up of trillions of cells. As such, the power of environmental cues to provide context and guidance to cell behaviour cannot be understated. Without attempting to directly mimic the in vivo environment, it has been shown that micro- and nanostructured surfaces can influence cell behaviour when we try and engineer biology in vitro. Identification and optimisation of powerful topographies is, however, tedious, and so this thesis provides techniques to expedite the discovery of new and potent surfaces to drive cell behaviour. A new fabrication technique has been developed which allows for the fabrication of gradients of feature height at both the micro- and nanoscale. This involves the use of plasma polymer gradients as novel etch masks alongside existing lithographic techniques. After fabrication and mass replication by injection moulding, use of these surfaces as platforms for the high-content screening of cell response is demonstrated. These can be considered high-content due to both the range of surface structures on a single sample, and also the microscopy techniques used to investigate cell response. Distinct cell types were found to respond differently to topographical cues, exhibiting varying degrees of alignment, proliferation, and organisation in both mono- and co-culture systems. A new cell culture device has also been developed and patented which ensures that screening experiments begin with an accurate and repeatable distribution of cells across the high content array. The impact of uneven cell seeding on studies involving stem cell differentiation was also investigated – showing the importance of improved control. Finally, the interaction of cells with such nanostructured surfaces is investigated using new super-resolution microscopy techniques. New methods are presented for the correlation of multiple nanoscale imaging techniques to view cell-nanostructure interactions with unprecedented resolution. This reveals insights into the way in which the cellular substructure is being modulated by underlying nanotopography. Indeed, it paints a picture which is remarkably different to the structure observed under a standard widefield microscope over the past 10 years

Program and abstracts from the 24th Fungal Genetics Conference

Abstracts of the plenary and poster sessions from the 24th Fungal Genetics Conference, March 20-25, 2007, Pacific Grove, CA

A toolkit for visualization of patterns of gene expression in live Drosophila embryos

Developing biological systems can be approximately described as complex, three dimensional cellular assemblies that change dramatically across time as a consequence of cell proliferation, differentiation and movements. The presented project aims to overcome problems of limited resolution in both space and time of classical analysis by in situ hybridization on fixed tissue. The employment of the newly developed Single Plane Illumination Microscopy (SPIM) combined with new approaches for in vivo data acquisition and processing promise to yield high-resolution four-dimensional data of the complete Drosophila embryogenesis. We developed a toolkit for high-throughput gene engineering in flies, that provides means for creating faithful in vivo reporters of gene expression during Drosophila melanogaster development. The cornerstone of the toolkit is a fosmid genomic library enabling high-throughput recombineering and φC31 mediated site-specific transgenesis. The dominant, 3xP3-dsRed fly selectable marker on the fosmid backbone allows, in principle, transgenesis of the fosmid clones into any non-melanogaster species. In order to extend the capabilities of the gene engineering toolkit to include “evo-devo” studies, we generated genomic fosmid libraries for other sequenced Drosophilidae: D. virilis, D.simulans and D. pseudoobscura. The libraries for these species were constructed in the pFlyFos vector allowing for recombineering modification and φC31 transgenesis of non-melanogaster genomic loci into D. melanogaster. We have developed a PCR pooling strategy to identify clones for a specific gene from the libraries without extensive clone sequencing and mapping. The clones from these libraries will be primarily used for cross-species gene expression studies. As another application, transgenes originating from closely related species can be used to rescue D. melanogaster RNAi phenotypes and establish their specificity. Together with SPIM microscopy, the toolkit will allow to visualize gene expression patterns throughout Drosophila development

Development and Application of Chemometric Methods for Modelling Metabolic Spectral Profiles

The interpretation of metabolic information is crucial to understanding the functioning of a biological system. Latent information about the metabolic state of a sample can be acquired using analytical chemistry methods, which generate spectroscopic profiles. Thus, nuclear magnetic resonance spectroscopy and mass spectrometry techniques can be employed to generate vast amounts of highly complex data on the metabolic content of biofluids and tissue, and this thesis discusses ways to process, analyse and interpret these data successfully. The evaluation of J -resolved spectroscopy in magnetic resonance profiling and the statistical techniques required to extract maximum information from the projections of these spectra are studied. In particular, data processing is evaluated, and correlation and regression methods are investigated with respect to enhanced model interpretation and biomarker identification. Additionally, it is shown that non-linearities in metabonomic data can be effectively modelled with kernel-based orthogonal partial least squares, for which an automated optimisation of the kernel parameter with nested cross-validation is implemented. The interpretation of orthogonal variation and predictive ability enabled by this approach are demonstrated in regression and classification models for applications in toxicology and parasitology. Finally, the vast amount of data generated with mass spectrometry imaging is investigated in terms of data processing, and the benefits of applying multivariate techniques to these data are illustrated, especially in terms of interpretation and visualisation using colour-coding of images. The advantages of methods such as principal component analysis, self-organising maps and manifold learning over univariate analysis are highlighted. This body of work therefore demonstrates new means of increasing the amount of biochemical information that can be obtained from a given set of samples in biological applications using spectral profiling. Various analytical and statistical methods are investigated and illustrated with applications drawn from diverse biomedical areas

Molecular prognostic and predicitive markers of therapy response in sporadic colon cancer

Colon cancer is the third most frequent malignancy in the Western world. Average 5 year-survival is around 70% and depends on the stage of the disease being very poor (under 10% 5-year survival) for stage IV patients and excellent (more than 90% 5 year survival) for stage I patients. The prognosis of patients with stage II varies between 80 and 60% 5-year survival. The causes of this variation remain unclear. Furthermore, the prognosis of patients with stage III has improved significantly, reaching 70% 5-year survival, since the introduction of adjuvant chemotherapy. However, still 30% of the patients with stage III disease that do not respond to chemotherapy. Therefore, reliable predictive and prognostic markers in stage II and III colon carcinoma are necessary to be able to elucidate whether a patient is going to respond to therapy or not and to be able to offer personalized treatment. In this research project, we aimed to identify predictive markers of therapy response in stage III disease and prognostic markers in stage II and III colon carcinoma. The first three chapters focus on the value of known single nucleotide polymorphisms (SNP) in genes involved in the activation, metabolism of chemotherapeutic drugs like 5-fluorouracil and oxaliplatin as well as in the repair of DNA damage caused by these drugs as predictive markers for therapy response. In the remaining chapters , the focus is placed on the identification of molecular prognostic markers in stages II and III. Several mutations in known cancer driver genes and genes involved in signal transduction have been studied.Fontys Hogescholen, Instituut TNW; Onderzoeksfonds Catharina Ziekenhuis Eindhoven; Roche Nederland BV; Pfizer BV.UBL - phd migration 201

Automatic core segmentation and registration for fast tissue microarray de-arraying

International audienceTissue core de-arraying is one of the most important steps in tissue microarray (TMA) image analysis. However, few solutions and mathematical frameworks are available. This paper presents a robust TMA de-arraying method adapted for digital images from classical optical and new fluorescent devices. The proposed algorithm is composed of three modules: (a) detection, (b) segmentation, and (c) array indexing. The detection of TMA cores is performed by local adaptive thresholding of isotropic wavelet transform coefficients. The segmentation component uses parametric ellipse to delineate the boundaries of potential tissue cores. Array indices of each core are computed by using thin-plate splines to estimate the deformation of the deposited core grid. Our method is appropriate for non-linear deformation and is able to quantify the deformation of TMA grids when compared to existing algorithms