Petter Ranefall | Publications | Projects | Downloads

SciLifeLab supported projects

Here is a list of projects where development of image analysis methods were fully or partly supported by SciLifeLab. Many of the projects were also supported by other funding, and involved PhD students from the lab.

  1. Multicolor Read-Out Increases the Dynamic Range of in situ PLA.


    Collaborators:

    Carl-Magnus Clausson, Ola Söderberg, Dept. of Genetics and Pathology, UU.


    Image analysis:

    A. Allalou and C. Wählby.


    Funding of image analysis:

    : SciLifeLab, TN-faculty, UU.


    Date:

    2010-02--2011-12-31


    Abstract:

    A novel approach to increase the dynamic range of in situ PLA has been developed at Dept. of Genetics and Pathology, UU. Using several probes with different concentrations the dynamic range can be extended significantly. Signal detection previously developed at CBA, UU, (3DSWD) is used to quantify the number of signals in the different concentrations (Clausson et. al. Nature Methods).

  2. Optical Projection Tomography.


    Collaborators:

    Amin Allalou, Izolde AB, Uppsala; Johan Ledin, Evolutionary Biology Centre, Zebrafish platform, SciLifeLab Uppsala; Jos Buijs, Ridgeview Uppsala, Carlos Pardo, Mehmet F. Yanik, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, USA.


    Image analysis:

    A. Pacureanu, O. Ishaq and C. Wählby.


    Funding of image analysis:

    SciLifeLab; TN-faculty, UU.


    Date:

    2010-09--2013-12


    Abstract:

    Isotropic 3D imaging of biological specimens is instrumental for further breakthroughs in life sciences. Many biological specimens with high relevance for basic research, disease studies and drug discovery, such as model organisms or 3D cell cultures, are semi-transparent to visible light. This lead to the advent of the technique dubbed optical projection tomography (OPT). The 3D internal structure is revealed by the attenuation variations of the light traversing the specimen. In OPT transverse slices of the specimen are reconstructed from a set of angular projections and stacked together into a volumetric image. This method enables in vivo imaging of relatively large samples with high spatial resolution. A high-throughput platform for cellular resolution, in vivo OPT of zebrafish has been developed at MIT, Cambridge, USA. With this system we have shown that OPT of zebrafish embryos can provide 3D information enabling high-throughput screening of subtle phenotypic changes in relation to drug treatment, as published in Nature Communications in February 2013. However, OPT imaging systems in general are still quite sophisticated and costly. We are therefore developing a system for optical 3D isotropic imaging at microscopic scale, based on readily accessible hardware. The total price of the setup is kept under 1000 euros and the components can be easily obtained around the world. We have assembled the image acquisition system, acquired, and reconstructed images of zebrafish embryos and of 3D cell cultures. We are complementing the simple hardware with open source computational tools, embedding algorithms for image alignment, correction and reconstruction. Our goal is to enable every life sciences research laboratory to have access to valuable 3D information on biological specimens. In 2013, besides working on improving imaging of zebrafish embryos, we attempted to image 3D cell cultures with our system, in collaboration with Jos Buijs (Ridgeview). A human ovarian carcinoma cell line has been used to grow 3D cell cultures in borosilicate thin tubes. We also tested growing the cells in agar gels and performing a 'biopsy' to extract the cells and transfer them into borosilicate tubes for imaging.

  3. Tracking of Unstained Cells in Microfluidic Systems.


    Collaborators:

    Johen Kreuger, Sara Thorslund, Gradientech AB, Uppsala


    Image analysis:

    S. K. Sadanandan, M. Simonsson and C. Wählby.


    Funding of image analysis:

    SciLifeLab; eSSENCE; Dept. of IT, UU


    Date:

    2011-08--


    Abstract:

    Tracking of cell movements in various cell culture setups is essential to many researchers in the life science sector. Gradientech AB, a Swedish biotech company, has developed CellDirector, a unique microfluidic system that academic researchers can use to study how concentration gradients of soluble proteins impact cell migration. The current project is focused on developing software for analyzing cell behavior and cell migration. The free open-source software CellProfiler developed at the Broad Institute will be used as a platform for a high-throughput system with automated high quality imaging, adapted for unlabeled cells, which are analyzed with regard to directionality of migration, speed, and acceleration. Apart from analyzing cell migration, the cell tracking aims at producing lineages, where cellular events such as cell division and cell death can be scored for single cells. A graphical user interface for visualizing and editing tracks imported from CellProfiler has been developed. This will be used for manual feed back in an iterative parameter optimization process, which aims to improve the automatic tracking. The progress of the project was presented in the poster session at eSSENCE Academy 2013 workshop at Lund.

  4. In Situ Sequencing of mRNA.


    Collaborators:

    Mats Nilsson, Rongqin Ke, Marco Mignardi, Thomas Hauling, Xiaoyan Qian, SciLifeLab Stockholm/Stockholm University


    Image analysis:

    C. Wählby, A. Pacureanu and P. Ranefall.


    Funding of image analysis:

    SciLifeLab; TN-faculty, UU


    Date:

    2011-09--


    Abstract:

    Profiling of gene expression is prerequisite for understanding the function of cells, organs and organisms, in health and disease. The sequencing techniques currently in use rely on homogenization of the samples. Therefore, the obtained information represents either the average expression profile of the tissue sample or expression profiles of isolated single cells. Our collaborators have developed a new molecular method, enabling in situ sequencing of mRNA, so that protein expression can be observed directly in cultured cells or tissue samples. We have developed image analysis tools for automated analysis of sequencing data, mapping, and visualization of gene expression patterns. We presented the work as part of a Special Session on Advances in Computer-Aided Histopathology at the IEEE International Symposium on Biomedical Imaging (ISBI 2014) in Beijing. The project was also presented at the 1st annual conference for the Society of Biomolecular Imaging and Informatics SBI2, at the JB Martin Conference Center at Harvard Medical School, Boston, MA, USA, where Carolina Wählby was honored with the SBI2 'President's innovation award' for her presentation on 'Combining image-based in situ RNA screening with quantitative analysis of cell and tissue morphology'.

  5. TissueMaps

    TissueMaps: Integrating spatial and genetic information via automated image analysis and interactive visualization of tissue data.


    Collaborators:

    Mats Nilsson, Thomas Hauling, Xiaoyan Qian, Jessica Svedlund, Elin Lundin, SciLifeLab Stockholm/Stockholm University


    Image analysis:

    C. Wählby, P. Ranefall, O. Ishaq, M. Mignardi, M. Bombrun.


    Funding of image analysis:

    SciLifeLab; TN-faculty, UU; International Postdoctoral fellowship to Marco Mignardi; ERC


    Date:

    2011-09--


    Abstract:

    Digital imaging of tissue samples and genetic analysis by next generation sequencing are two rapidly emerging fields in pathology. The exponential growth in digital imaging in pathology is catalyzed by more advanced imaging hardware, comparable to the complete shift from analog to digital images that took place in radiology a couple of decades ago: Entire glass slides can be digitized at near the optical resolution limits in only a few minutes' time, and fluorescence as well as bright field stains can be imaged in parallel.
    Genetic analysis, and particularly transcriptomics, is rapidly evolving thanks to the impressive development of next generation sequencing technologies, enabling genome-widensingle-cell analysis of DNA and RNA in thousands of cells at constantly decreasing costs. However, most of today's available technologies result in a genetic analysis that is decoupled from the morphological and spatial information of the original tissue sample, while many important questions in tumor- and developmental biology require single cell spatial resolution to understand tissue heterogeneity.
    In this project, we develop computational methods that bridge these two emerging fields. We combine spatially resolved high-throughput genomics analysis of tissue sections with digital image analysis of tissue morphology. Together with collaborators from the biomedical field, we work with advanced digital image processing methods for spatially resolved genomics (see Ke et al, Nature Methods 2013). Going beyond visual assessment of this rich digital data will be a fundamental component for the future development of histopathology, both as a diagnostic tool and as a research field. We published a review paper on spatially resolved genomics and proteomics in the Journal of Molecular Biology (Koos et al J Mol Bio 2015).

  6. Automated Classification of Immunostaining Patterns in Breast Tissue from the Human Protein Atlas


    Collaborators:

    Caroline Kampf, The Human Protein Atlas (HPA); Virginie Uhlmann, Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA, USA; S. Issac Niwas, P. Palanisamy, Dept. of ECE, National Institute of Technology (NIT), Tiruchirappalli, India


    Image analysis:

    A. Kårsnäs, M. Simonsson, C. Wählby and R. Strand.


    Funding of image analysis:

    SciLifeLab.


    Date:

    2012-01--2013-03


    Abstract:

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/) and contains a large number of histological images of sections from human tissue. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumor grading. In this project we have tested a new method based on complex wavelets textural features as well as an approach inspired by WNDCHARM (Weighted Neighbor Distances using a Compound Hierarchy of Algorithms Representing Morphology) for classifying nuclear versus cytoplasmic staining. During 2013, a paper was published in Journal of Pathology Informatics.

  7. Computational Methods for Quantification in Vascular Biology


    Collaborators:

    Lena Claesson-Welsh, Xiujuan Li, Makoto Hayashi, Jeremy Adler, Eric Morin, Dept. of Immunology, Genetics and Pathology, Rudbeck Laboratory, SciLife Lab Uppsala.


    Image analysis:

    A. Pacureanu and C. Wählby.


    Funding of image analysis:

    SciLifeLab.


    Date:

    2012-02--


    Abstract:

    The formation of new blood vessels, angiogenesis, represents a key process in the growth of tissues from embryonic development to wound healing and cancerous tumors. Our collaborators are working on understanding how angiogenesis is induced, but also how it can be suppressed. We developed image analysis pipelines for several projects concerning assessment of endothelial cell response to treatment, the role of neuropilin-1 in wound healing or quantification of vessel formation in mice tumors. The methods include image enhancement, cell segmentation, detection and quantification of phenotypic changes. The image analysis pipelines were built in the open source software CellProfiler.

  8. Automated Quantification of Zebrafish Tail Deformation for High-throughput Drug Screening


    Collaborators:

    Joseph Negri, Mark-Anthony Bray, Randall T. Peterson, Broad Institute of Harvard and MIT.


    Image analysis:

    O. Ishaq, A. Pacureanu and C. Wählby.


    Funding of image analysis:

    SciLifeLab.


    Date:

    2012-03--2013-04


    Abstract:

    Zebrafish (Danio rerio) is an important model organism in biomedical research due to its ease of handling and translucent body and consequently many human disease models have been established in the Zebrafish. Zebrafish embryos undergo spinal deformation upon exposure to chemical agents, such as Camptothecin (Cpt), that inhibit DNA repair. We are developing automated image-based quantification of spine deformation enabling whole-organism based assays for use in early-phase drug discovery campaigns. Our automated method for accurate high-throughput measurement of tail deformations in multi-fish micro-plate wells generates refined medial representations of partial tail-segments. Subsequently, these disjoint segments are analyzed and fused to generate complete Zebrafish tails. Based on these estimated tail curvatures we reach a classification accuracy of 91% on individual animals as compared to known control treatment. This accuracy is increased to 95% when combining scores for fish in the same well. A paper describing the methods and results was published and presented at the International Symposium for Biomedical Imaging (ISBI) in April 2013.

  9. Image-based Approaches for Drug Tablet Quality Assessment.


    Collaborators:

    Mark Nicholas, Mats Josefson, AstraZeneca, Mölndal, Sweden.


    Image analysis:

    I.-M. Sintorn and C. Wählby.


    Funding of image analysis:

    Pre-study grant from AIMDay Image, UU Innovation.


    Date:

    2012-04--2013-02


    Abstract:

    It is known qualitatively that microstructural differences in solid dosage forms (e.g. tablets and inhalation powders) affect the performance of the medication. The microstructural differences are differences in the spatial distribution of active and inactive compounds. The aim of this project is to characterize these microstructural differences in order to determine whether imaging techniques such as CLSM (confocal laser scanning microscopy), wide-field fluorescence microscopy, and TOF-SIMS (Time-Of-Flight Secondary Ion Mass Spectroscopy) can reveal quantifiable differences in structure. The problem was addressed using a combination of local intensity features and texture measurements (including granulometry, Zernike moments, and Haralick features), and measurements were correlated with tablet characteristics/treatments. Due to a relatively limited dataset, it was difficult to find statistically significant differences. The data was presented to AstraZeneca researchers in January 2013.

  10. Computational Methods for Quantification in Neural Stem Cells.


    Collaborators:

    Karin Forsberg-Nilsson, Tanja Paavilainen, Soumi Kundu, Grzegorz Wicher, Lisa Rebello, Anqi Xiong, Tobias Bergström, Dept. of Immunology, Genetics and Pathology, Rudbeck Laboratory, SciLifeLab Uppsala.


    Image analysis:

    A. Pacureanu, C. Wählby, M. Simonsson .


    Funding of image analysis:

    SciLifeLab


    Date:

    2012-10--


    Abstract:

    Neural stem cells are the building blocks of the nervous system. In the view of finding better treatments for neurodegenerative diseases and for deeper understanding of mammalian development, our collaborators are investigating how neural stem cells proliferate and differentiate and which factors govern these processes. For these studies, thousands of images of cell cultures need to be quantitatively analyzed, in order to determine for example how effective are various techniques for control of the stem cells differentiation. Based on CellProfiler and CellProfiler Analyst, we have developed methods for automatic analysis of these images. In 2013, the master thesis of Tanja Paavilainen has been successfully completed and we continued the collaboration with researchers from the Karin Forsberg group. For example, we have been working together with Tobias Bergström on quantification of the OLIG2 expression in different glioma cell lines and with Soumi Kundu on blood vessels segmentation.

  11. Segmentation and Tracking of E.coli Bacteria in Bright-Field Microscopy Images.


    Collaborators:

    Johan Elf, David Fange, Alexis Boucharin, Dept. of Cell & Molecular Biology, UU; Klas E. G. Magnusson, Joakim Jaldén, ACCESS Linnaeus Centre, KTH.


    Image analysis:

    S. K. Sadanandan, C. Wählby and P. Ranefall.


    Funding of image analysis:

    SciLifeLab, eSSENCE, VR junior researcher grant to CW


    Date:

    2012-10--


    Abstract:

    Live cell experiments pave way to understand the complex biological functions of living organisms. Most live cell experiments require monitoring of cells under different conditions over several generations. The biological experiments display wide variations even when performed under similar conditions, and therefore need to include large population studied over several generations to provide statistically verifiable conclusions. Time-lapse images of such experiments usually generate large quantities of data, which become extremely difficult for human observers to evaluate. Thus, automated systems are helpful to analysis of such data and provide valuable inference from the experiment. In this project we segment and track E. coli bacteria cells over time. We developed a novel segmentation method, which is fast and robust in delineating bacterial cells in phase contrast microscopy images. The methods were published in IEEE Journal of Selected Topics in Signal Processing (KS Sadanandan et al 2015).

  12. Detection and Localization of Florescent Signals in STORM Data Using Compressed Sensing.


    Collaborators:

    Johan Elf, Gustaf Ullman, Fredrik Persson, Dept. of Cell & Molecular Biology, UU.


    Image analysis:

    O. Ishaq, A. Pacureanu and C. Wählby.


    Funding of image analysis:

    SciLifeLab, eSSENCE, VR junior researcher grant to CW


    Date:

    2012-11--


    Abstract:

    Stochastic optical reconstruction microscopy (STORM) is a super-resolution microscopy image acquisition technique for single-molecule localization. Like other stochastic super-resolution microscopy techniques it incorporates a trade-off between spatialand temporal-resolution. Recently, a compressed-sensing (CS) based variant of STORM, called FasterSTORM, has been developed which substantially increases the temporal sampling of a stack of STORM image frames. This improvement is realized by increasing the density of activated fluorophores in each frame, followed by a subsequent CS-based retrieval of single-molecule positions even with overlapping fluorescent signals. However, the CS-based retrieval/decoding step is time consuming and can take as much as three hours for each image frame. We have accelerated the FasterSTORM method through parallel processing on multi-core processors. Additionally, we have tested and tried a number of L1-solvers for CS-based recovery of molecule positions. We are in the process of comparing the performance of the FasterSTORM against a wavelet-based approach to localize fluorescent signals in time-lapse images of bacterial cells.

  13. Studying Exocytosis by Time Lapse Microscopy.


    Collaborators:

    Anne Wuttke, Dept. of Medical Cell Biology, UU


    Image analysis:

    M. Simonsson and C. Wählby.


    Funding of image analysis:

    SciLifeLab, eSSENCE, VR junior research grant to CW


    Date:

    2012-11--


    Abstract:

    Insulin secreting cells perform exocytosis and this can be detected with a GFP-modified protein as an increase in fluorescence signal. Time-lapse sequences are acquired with a time interval of one second during one hour, observing changes in fluorescence signaling at different treatments of the cells. This results in huge data sets with more than 3000 images for a single experiment. The focus of this project is to extract relevant information from the image data and in an efficient way analyze and visualize the data. Preliminary results were presented in a PhD thesis by our collaborator Anne Wuttke.

  14. SciLifeLab Cancer Stem Cell Program.


    Collaborators:

    Sven Nelander, Ingrid Lönnstedt, Cecilia Krona, Linnèa Schmidt, Karin Forsberg-Nilsson, Irina Alafuzoff, Ulf Landegren, Anna Segerman, Tobias Sjöblom, Lene Urborn, and Bengt Westermark, Dept. of Immunology, Genetics and Pathology and SciLifeLab, UU, Bo Lundgres, the Karolinska Institute and SciLifeLab, Stockholm, Rebecka Jörnsten, Chalmers, Gothenburg, and Göran Hesselager, UU Hospital, Uppsala .


    Image analysis:

    D. Matuszewski, P. Ranefall, C. Wählby and I.-M. Sintorn.


    Funding of image analysis:

    AstraZeneca-Science for Life Laboratory Joint Research Program


    Date:

    2013-03--


    Abstract:

    The SciLifeLab Cancer Stem Cell Program is a cross-platform initiative to characterize cancer stem cells (CSCs). Previously, the development of drugs targeting the CSC population in solid tumors has been curbed by the lack of valid cell model systems, and the complex genetic heterogeneity across tumors, factors that make it hard to assess new targets or predict drug responses in the individual patient. To solve these problems, our aim is to develop a biobank of highly characterized CSC cultures as a valid model of cancer heterogeneity. We will combine mathematical and experimental approaches, including image-based high-throughput cell screening, to define the spectrum of therapeutically relevant regulatory differences between patients. This will help elucidate mechanisms of action and enable accurate targeting of disease subgroups. Patient data is continuously collected, and close to one hundred primary cell lines have been established. The cultured cells are exposed to known and novel drug compounds at varying doses, and imaged by fluorescence as well as bright-field microscopy. In 2015 algorithms for cell cycle analysis and automatic selection of potentially effective treatments were developed, and presented at BioImage Informatics 2015 in Gaithersburg, MD, USA. Current research focus is on extracting meaningful morphological descriptors from the image data. As part of the project we also evaluate the infiltration of tumor cells upon injection of stem cells in mice brains.

  15. Quantification of Zebrafish Lipid Droplets.


    Collaborators:

    Marcel den Hoed, Manoj Bandaru, Erik Ingelsson, Dept. of Medical Sciences and SciLifeLab, UU.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2013-08--


    Abstract:

    The aim of this project is to identify novel targets for the therapeutic intervention of coronary artery disease. This is done by following-up results from genome-wide association studies in epidemiological studies using a zebrafish model system. Using image analysis we try to identify and characterize causal genes within loci that have so far been identified as associated with coronary heart disease by (high-throughput) screening of atherogenic processes in wildtype and mutant zebrafish, both before and after feeding on a control diet or a diet high in cholesterol. Using confocal microscopy we can image fat accumulation in the zebrafish. We have also developed methods for length and volume measurements as well as quantification of macrophages, neutrophils, IK17 and the overlap with these expressions and stationary lipids. Our results confirm that zebrafish larvae represent a promising model system for early-stage atherosclerosis.

  16. Evaluation of the Effect of Compaction Oligonucleotides on the Strength and Integrity of Fluorescent Signals.


    Collaborators:

    Carl-Magnus Clausson, Linda Arngården, Ola Söderberg, Dept. of Immunology, Genetics and Pathology, UU.


    Image analysis:

    O. Ishaq, P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2013-10--2015-06


    Abstract:

    Rolling circle amplification (RCA) performs nucleic acid replication for rapid synthesis of multiple concatenated copies of circular DNA. These molecules can be visually observed through the use of fluorescent markers. Moreover, the introduction of a compaction oligonucleotide during RCA results in brighter and more compact signals. The project aims to evaluate the effect of compaction oligonucleotides on the strength and integrity of fluorescent signals. A paper describing the method, including image analysis approaches for methods evaluation, was published in Nature Scientific Reports 2015.

  17. Segmentation of Neurons.


    Collaborators:

    Laureanne Pilar Lorenzo, Niklas Dahl, Dept of Immunology, Genetics and Pathology, UU.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2014-02--


    Abstract:

    The goal of this project is to analyze neurons grown from stem cells in vitro. The aim is to assess the percentage of neurons (using B-tubulin) and certain neuron subtypes (GABA) by immunofluorescence. We used CellProfiler to segment the cells and CellProfiler Analyst to classify positive cells.

  18. Vascular Networks.


    Collaborators:

    Elisabet Olin, Ross Smith, Chiara Testini, Lena Claesson-Welsh, Dept of Immunology, Genetics and Pathology, UU.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2014-06--


    Abstract:

    In this project we analyze vascular networks in the mouse brain, retina networks and cell junction activations. We have several applications where we skeletonize the networks and extract branch points in the skeleton. For the cell junction activations we have initially used an approach where we compute the area of the activated junctions (green) between the cells and use that as a measurement of activation.

  19. Cell Time-Lapse Analysis.


    Collaborators:

    Grigorios Kyriatzis, Jennifer Feenstra, Theresa Vincent, Physiology and Pharmacology, KI.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2014-10--


    Abstract:

    The aim of the project is to interpret differences in migration-proliferation of cells with different treatments and express those in a quantitative manner. We used a 'scratch assay' approach, or 'wound healing assay' as it sometimes is called, where cells are grown in wells, and then the surface is 'scratched' and loose cells are washed away. Then the wells are imaged, possibly followed by adding a drug substance, and imaging the wells again at a suitable time interval. The area filled at time point T is a measure of the migration speed.

  20. A Model System for Analysis of Spinal Cord Injury.


    Collaborators:

    Nils Hailer and Nikos Schizas, Dept. of Surgical Sciences, UU.


    Image analysis:

    C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-01--


    Abstract:

    Following spinal cord injury neurons die due to neurotoxicity and inflammation. We study these effects in a model system with spinal cord slice cultures, aiming to find methods to reduce neurotoxicity. Our focus is quantitative image analysis methods that delineate activated cells and quantify protein expression as a response to injury and treatment.

  21. Detection of Fluorescent Signals using Deep Learning Architectures.


    Collaborators:

    Vladimir Curic, Martin Linden, Johan Elf, Dept. of Cell & Molecular Biology, UU.


    Image analysis:

    O. Ishaq and C. Wählby.


    Funding of image analysis:

    SciLifeLab, eSSENCE, VR junior researcher grant to Carolina Wählby


    Date:

    2015-01--


    Abstract:

    Detection of fluorescent spots is an important component of bioimaging. A number of detection methods have been proposed. Recently, deep learning methods have become popular for a range of computer vision tasks and have resulted in competitive results. In this project we utilize a number of these deep learning methods and compare them against model-based spot detection methods. In addition, we also explore the effect of training both shallow- and deep-learning spot detection approaches on synthetic, semisynthetic and real data and evaluate their performance on manually annotated real data in the form of quantitative results. The annotation of real data is facilitated by the development of a specialized annotation tool based on a two-alternative forced-choice (2AFC) approach. The annotation performance is validated through rater reliability statistics. The project has resulted in two manuscripts, one of which has been submitted to a conference and the other is being adapted for a journal publication.

  22. Global and Local Adaptive Gray-level Thresholding Based on Object Features.


    Image analysis:

    P. Ranefall, S. K. Sadanandan and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-01--2015-12


    Abstract:

    We have developed two new algorithms for global and local adaptive thresholding based on object features such as size, ellipse fit, etc. The algorithms are efficient with little computational overhead compared to histogram based gray-level thresholding, but with much more stable results. This makes them very suitable for high-throughput analysis in microscopy applications like segmentation of cell nuclei or fluorescent spots. The algorithms have been implemented as plugins to ImageJ and CellProfiler and have been used in several different applications. We have written two papers that both are accepted for publication in Cytomerty A and at ISBI 2016.

  23. Objective Automated Quantification of Fluorescence Labeling in Histologic Sectionsof Rat Lens.


    Collaborators:

    Per Söderberg and Nooshin Talebizadeh, Dept. of Neuroscience, UU.


    Image analysis:

    C. Wählby and N. Z. Hagström.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-01--


    Abstract:

    The lens epithelium of the eye is a single layer of cells covering the anterior face of the lens. In this project we study how UV light affects the lens epithelial cells by quantitatively analyzing fluorescent signal from biomarkers in cell nuclei and cytoplasms. We have developed an automated method to delineate lens epithelial cells and to quantify expression of fluorescent signal of biomarkers in each nucleus and cytoplasm of lens epithelial cells in a histological section.

  24. PopulationProfiler.


    Collaborators:

    Jordi Carreras Puigvert, SciLifeLab and Helleday Laboratory, Karolinska Institutet, Stockholm.


    Image analysis:

    D. Matuszewski, C. Wählby and I.-M. Sintorn.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-01--


    Abstract:

    PopulationProfiler is a cross-platform open-source tool developed for data analysis in image-based screening experiments. The main idea is to reduce per-cell measurements to per-well distributions, each represented by a histogram. These can be optionally further reduced to sub-type counts based on gating (setting bin ranges) of known control distributions and local adjustments to histogram shape. Such analysis is necessary in a wide variety of applications, e.g. DNA damage assessment using foci intensity distributions, assessment of cell type specific markers, and cell cycle analysis. The source code, sample dataset and an executable program (for Windows only) are freely available at PopulationProfiler.html .

  25. Ubiquitin Screen.


    Collaborators:

    Johan Boström, Jordi Carreras Puigvert, Mikael Altun, Molecular Biochemistry and Biophysics, KI.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-02--


    Abstract:

    Ubiquitin is a small protein that is found in almost all cellular tissues in humans and other eukaryotic organisms, which helps to regulate the processes of other proteins in the body. Cultured cells respond to treatments such as silencing of genes or exposure to radiation and/or drugs by changing their morphology, giving us hints on mechanisms of action. We develop methods for image-based high-throughput screening to identify subtle changes in individual cells, not accessible by bulk-methods, here focusing on the ubiquitin pathway.

  26. Cell Distribution and Protein Expression in the Ectocervix.


    Collaborators:

    Anna Gibbs, Maria Röhl, Annelie Tjernlund, Dept. of Medicine, KI.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-04--


    Abstract:

    This research project is focused on mucosal immunology in the female genital tract and HIV. The female genital mucosa presents a comprehensive natural immune defense against HIV infection, although during exposure to a high dose of virus this is not enough to protect the individual against viral transmission. Some individuals have a stronger resistance against HIV than others and therefore it is highly important to investigate which factors that contribute to an effective local protection against sexual infection. The aim of this study is to quantify gene expression in the target cells of HIV in ectocervix, and measure the distance to the vaginal lumen, as well as epithelial thickness. These parameters will be compared in women involved in sex work between the groups of HIV-infected, highly HIV exposed HIV uninfected that seems to be resistant, and HIV uninfected women who have been involved in sex work for a short period.

  27. Infiltration of T Cells in Thyroid Glands.


    Collaborators:

    Susanne Kerje, Dept of Medical Biochemistry and Microbiology, UU.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-04--


    Abstract:

    The aim of the project is to estimate the degree of infiltration of T cells in thyroid glands of chicken in order to better understand auto-immunity and rare genetic disease. We have developed an image analysis pipeline, using ilastik, CellProfiler, and some Python scripts, that extracts the regions of interest from the full glass slide images and classifies the tissue into infiltration or normal. The whole dataset contained 558 slides and the analysis was run on a powerful local server at the BMC.

  28. Rat Spinal Cord.


    Collaborators:

    Lada Stålhandske, Wei Sun, Georgy Bakalkin, Dept Pharm Biosci, UU.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-06--


    Abstract:

    Our collaborators newly established an way of staining the activity in the endogenous opioid system in the rat spinal cord, and the aim of the project is to quantify the ammount and localization of mRNA staining. We have developed image analysis approaches for quantifying the amount of cells with positive signals and associate those to manually outlined regions of interest within the spinal cord of rats. We have applied our new method for local adaptive thresholding based on ellipse fit to segment nuclei, and use ilastik to classify positive/negative cells.

  29. Analysis of Keratin Aggregates.


    Collaborators:

    Hanqian Zhang and Hans Törmä, Dept. of Medical Sciences, Dermatology and Venereology.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-10--


    Abstract:

    Epidermolytic hyperkeratosis (EH) is a rare genetic skin disorder caused by mutation of keratin 1 or 10, and characterized by blistering in the epidermis and hyperkeratosis. The skin may blister easily following mechanical injury and exposure to heat etc. Immortalized keratinocyte cell lines were established by our collaborators at the Dept. of Medical Sciences, Dermatology and Venereology, and these cell lines show promise as a screening model to test new potential drugs for treating EH patients. Large-scale screening requires robust, efficient and effective image analysis methods, and we are currently developing methods to analyze keratin aggregates in cultured EH cells.

  30. Kidney Morphology and Topology of the Glomerular Filtration Barrier.


    Collaborators:

    David Unnersjö Jess, Hans Gunnar Blom, Dept of Applied Physics, KTH.


    Image analysis:

    P. Ranefall and C. Wählby.


    Funding of image analysis:

    SciLifeLab


    Date:

    2015-10--


    Abstract:

    Our collaborators have developed a super-resolution immunofluorescence microscopy protocol for the study of the filtration barrier in the kidney. The aim of the project is to quantitatively evaluate the morphology and topology of the glomerular filtration barrier in the kidney. The most promising approach for analyzing these challenging 3D images seems to be a 3D version of the adaptive local thresholding based on ellipse fit.

  31. Quantification of lipid droplets in human pre-adipocyte.


    Collaborators:

    Hui Gao, Niklas Mejhert, Mikael Rydén, Peter Arner, Dept. of Medicine (H7) Karolinska Institute


    Image analysis:

    P. Ranefall, M. Bombrun and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-03-11-


    Abstract:

    Adipocytes store lipids, predominantly triglycerides (TGs), in lipid droplets (LDs). Upon energy shortage, TGs are hydrolyzed into non-esterified fatty acids and glycerol in an enzymatic process termed lipolysis. LDs are highly dynamic and undergo fragmentation or fusion under lipolytic and lipogenic conditions, respectively. The aim of this project is to unravel the molecular mechanisms governing LD formation and investigate connections between LD morphology and lipolysis rate. We will perform a high throughput image analysis of TG (BODIPY)-stained adipocytes treated with siRNAs that target lipolysis regulating genes. Images will be acquired by an automated microphotography pipeline. Using the proposed image analysis, we aim to quantitatively measure the effects on LD morphology and lipolysis rate for each gene. The results from this screen are compared with clinical measures in our cross-sectional and prospective cohorts. This will constitute an invaluable resource for in-depth and hypothesis-driven analyses, which will improve our understanding of the mechanisms controlling human adipocyte lipolysis.

  32. Amyotrophic lateral sclerosis


    Collaborators:

    Jordi Carreras Puigvert, Oskar Fernandez-Capetillo.


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-01-13-


    Abstract:

    Amyotrophic lateral sclerosis is a neurodegenerative disease characterized by the loss of motor neurons in the cortex brain stem and spinal chord. The incidence is 1 in 50 000 combining US and EU populations. The disease is fatal in approximately 5 years and there is currently no cure for AL. Morover, given the low incidence of case, finding new treatments for ALS is not a priority of the Pharma industry. At Scilifelab, we are developing several image based assays to discover strategies that can alleviate the death of ALS-motoneurons..

  33. Assessing Bacterial Growth Kinetics and Morphology Using Time-lapse Microscopy Data


    Collaborators:

    Elisabet Nielsen, Dept. of Pharm. Biosci., UU; Pikkei Yuen, Pernilla Lagerbäck, Thomas Tängdén Otto Cars, Dept. of Med. Sci., UU


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-06-


    Abstract:

    In vitro methods are often used to study the concentration-effect relationship for antimicrobial agents. Time-kill curve experiments have long been the standard methodology, with bacterial counts followed over time using viable count assessments on agar plates. This method is labor-intensive and recently digital time-lapse microscopy methods have become available which might allow a more rapid assessment of antibiotic activity. Additionally, these methods could add information related to drug-induced morphological changes. The aim of this project is to integrate information obtained from time-lapse microscopy in the characterization of antibiotic effect on bacterial growth and morphology.

  34. Effects of mixtures of endocrine disrupting compounds (EDC) on Wnt/beta-catenin signaling in developing zebrafish


    Collaborators:

    Maria Jönsson


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-09-02-


    Abstract:

    Wnt/beta-catenin signaling is involved in proliferation and fate of cells thus playing fundamental roles during embryo development. The specific aims of this part of the EU project are to 1) develop methods for detection of chemically induced changes in Wnt/beta-catenin signaling and to 2) determine developmental effects of EDC mixtures on Wnt/beta-catenin signaling. EDC-induced changes in Wnt/beta-catenin signaling are visualized and studied by transgenic zebrafish carrying a beta-catenin signaling fluorescent reporter (Tcf/Lef-miniP: d2EGFP).

  35. Automated quantification of axonal growth


    Collaborators:

    Sarah Pan, Nils Hailer and Nikos Schizas. Dept. of Surgical Sciences, UU.


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-10-04-


    Abstract:

    The aim of this project is to establish a standardised method for measuring axonal growth from spinal cord slice cultures using ImageJ and CellProfiler softwares. To measure the area of axons outside the explant body, pictures of spinal cord slice cultures are captured through a light microscope and then analysed in ImageJ and CellProfiler. Our plan is to use this method in future experiments on axonal regeneration and growth from the spinal cord.

  36. Mouse Brain Tumor segmentation


    Collaborators:

    Riasat Islam, Cecilia Krona and Sven Nelander. Dept. of Immunology, Genetics and Pathology, UU.


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-10-07-


    Abstract:

    The aim of this project is to segment tumors in stained mice brain images.

  37. Pigment gene expression in the early developing crow feather


    Collaborators:

    Chi-Chih Wu, Axel Klaesson, Ola Söderberg and Jochen Wolf. Dept. of Immunology, Genetics and Pathology, UU.


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2016-11-08-


    Abstract:

    The project is to quantify and compare pigment-associated gene expressions between two closest related crow species that carrion crow has black feathers and hooded crow has gray feathers in the belly. The cooperators have adapted in situ PLA with padlock probes to label targeted mRNAs across varied developmental stages of melanocytes in feathers. We are developing a CellProfiler pipeline and scripts to recognize and quantify signals across complex tissues with strong autofluorescence.

  38. Effect of perfluorononanoic acid (PFNA) on early embryo development in vitro


    Collaborators:

    Ida Hallberg, Ylva Sjunnesson. Dept. of Clinical Sciences, SLU.


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2017-01-19-


    Abstract:

    For the last decades a concern has been raised that female fertility is declining - more than could be explained by the fact that we choose to have children later in life and possible genetic effects. Subfertility - and infertility - is a devastating experience for those who are affected and as the subject is also somewhat of a taboo - the numbers affected are most likely higher than perceived among the general public. In our environment, we are continuously exposed to a number of exogenous chemicals, originating from industries, agriculture and other. As many of these chemicals show persistence and are very bio-accumulative, they will concentrate higher up in the food-chain, in both wildlife and humans. Many of the chemicals are new - and have yet not been investigated regarding their full toxicological potential. Perfluorononanoic acid (PFNA) This project aim to further investigate perfluorononanoic acid (PFNA) and its effect on the early embryo development. This chemical is closely related to know toxic substances such as PFOS and PFOA, but is in contrary to those - little research has yet been done regarding PFNAs potential toxicological effects. We have used a bovine model, where we collect material from the slaughter-house that are normally disposed. We have exposed egg-cells to PFNA and followed the egg cells in the lab as they develop into very early embryos. The embryos are then investigated regarding morphology and with different staining helping us identifying differences in for example fat-metabolism of exposed embryos.

  39. Visualization of uncharacterized archaea in lake and marine sediments


    Collaborators:

    Disa Bäckström, Thijs Ettema. Dept. of Cell & Molecular Biology, UU.


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2017-03-02-


    Abstract:

    Most of the archaea found in marine and lake sediments have only been characterized by their 16S sequences or by metagenomic binning. The goal of the current project is to assess the archaeal diversity in sediments from Århus Bay, Lake Erken and Lake Plåten and visualize the cells through fluorescent in situ hybridization (FISH). This allows us to study the morphology of poorly characterized archaeal lineages. Once a reliable protocol for has been developed it opens up for the possibility to proceed with targeted cell sorting and single cell genomics. It is difficult to analyse the images by eye in a standardized and objective way, so CellProfiler will be used to process the images and determine the ratio of cells with positive hybridization signal.

  40. Protein inheritance in asymmetric cell division


    Collaborators:

    Alexander Julner-Dunn(1), Zhijian Li(2), Charles Boone(2) and Victoria Menendez-Benito(1), (1)Department of Biosciences and Nutrition, Karolinska Institute, Sweden; (2)The Donelly Center, University of Toronto, Canada


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2017-04-28-


    Abstract:

    In some cells, such as yeast and stem cells, proteins are asymmetrically inherited during cell division. By doing this, cells can control cell fate and protect specific progeny from aging. Examples of age-dependent symmetric inheritance include centrosomes, histones, oxidized proteins and old mitochondria. Yet, we do not have a global view on which proteins in the cell are asymmetrically inherited. In this project, we address this question by developing a systems-based approach to explore protein inheritance in yeasts. We use a technique, named recombination induced epitope tag (RITE), which is a living pulse-chase that allows tracking old (maternal) and new proteins by genetic switching between two fluorescent protein fusions. Our specific goals are:
    1. To create the first yeast library for single-cell analysis of protein inheritance, by tagging each gene with RITE at its chromosomal location.
    2. To generate a map of the proteome inheritance in budding yeast, by measuring the abundance and localization of old/new proteins in the yeast RITE library, using high-content microscopy and automated image analyses.
    We will generate resources, data and novel information that will facilitate the discovery of new asymmetries in protein inheritance that control cell fate, epigenetic memory and/or cellular ageing.

  41. Influence of the extracellular matrix on the epithelial cell microenvironment


    Collaborators:

    Katie Hansel, Molly Stevens(1,2), (1)Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, (2) Imperial College, London


    Image analysis:

    P. Ranefall and C. Wählby


    Funding of image analysis:

    SciLifeLab


    Date:

    2017-05-17-


    Abstract:

    We are studying the influence of the extracellular matrix (ECM) on the epithelial cell microenvironment, since the ECM influences the bulk, shape and strength of many tissues in vivo. The basement membrane (BM) is a thin layer of specialised ECM consisting primarily of laminin and collagen that lines all epithelia and guides cell adhesion, polarity and differentiation. During the epithelial-to-mesenchymal transition (EMT), polarized epithelial cells lose their adherens junctions and tight junctions and transition to a migratory mesenchymal phenotype which is able to disrupt and penetrate through the BM, an event at the onset of cancer metastasis and tissue fibrosis. This transition is associated with the formation of prominent stress fibres and mature focal adhesions, along with a change in matrix metalloproteinase (MMP) expression and activation of multiple signalling pathways. Our group has identified a biologically-active fragment of the β1-chain of laminin that is released by matrix metalloproteinase 2 (MMP2) in the course of EMT. This laminin-β1 fragment has been shown to modulate EMT signalling via α3β1–integrin expressed on the surface of epithelial cells. Treatment of mouse mammary gland epithelial (NMuMg) cells undergoing transforming growth factor beta-1 (TGF-β1)-induced EMT with the fragment decreases the expression and activity of MMP2 (which is upregulated in EMT) and alters EMT related gene and protein expression. How this laminin fragment signals and how the BM is involved in regulating EMT and cell migration remains elusive. Therefore, microscopy has been used to assess the biochemical pathways affected by the fragment downstream of α3β1-integrin. We will analyse transcription factor localisation, focal adhesion distribution, ECM protein breakdown, and invadopodia formation in fixed images, and will also assess cell migration and clustering in live images.

  42. Effects of repeated islet transplantation on islet engraftment in a mouse model


    Collaborators:

    Hanna Liljebäck, Per-Ola Carlsson, Department of Medical Cell Biology, Uppsala Universitet


    Image analysis:

    P. Ranefall


    Funding of image analysis:

    SciLifeLab


    Date:

    2017-10-16-


    Abstract:

    The outcome of islet transplantation has improved progressively. However, the lack of organ donors makes islet transplantation available only to type I diabetes patients with the most severe glycemic lability. In the clinic, a second transplantation is often required to boost graft function and extend the time until recurrence of insulin dependence. Often, the second graft proves to work better than the initial islet transplant. In this study, we aimed to, in a mouse model with GFP positive islets, investigate whether this reflected differences in engraftment is caused by the repeated islet infusion procedure.