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  • 1.
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Methods for 2D and 3D Quantitative Microscopy of Biological Samples2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    New microscopy techniques are continuously developed, resulting in more rapid acquisition of large amounts of data. Manual analysis of such data is extremely time-consuming and many features are difficult to quantify without the aid of a computer. But with automated image analysis biologists can extract quantitative measurements and increases throughput significantly, which becomes particularly important in high-throughput screening (HTS). This thesis addresses automation of traditional analysis of cell data as well as automation of both image capture and analysis in zebrafish high-throughput screening. 

    It is common in microscopy images to stain the nuclei in the cells, and to label the DNA and proteins in different ways. Padlock-probing and proximity ligation are highly specific detection methods that  produce point-like signals within the cells. Accurate signal detection and segmentation is often a key step in analysis of these types of images. Cells in a sample will always show some degree of variation in DNA and protein expression and to quantify these variations each cell has to be analyzed individually. This thesis presents development and evaluation of single cell analysis on a range of different types of image data. In addition, we present a novel method for signal detection in three dimensions. 

    HTS systems often use a combination of microscopy and image analysis to analyze cell-based samples. However, many diseases and biological pathways can be better studied in whole animals, particularly those that involve organ systems and multi-cellular interactions. The zebrafish is a widely-used vertebrate model of human organ function and development. Our collaborators have developed a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. This thesis presents improvements to the system, including accurate positioning of the fish which incorporates methods for detecting regions of interest, making the system fully automatic. Furthermore, the thesis describes a novel high-throughput tomography system for screening live zebrafish in both fluorescence and bright field microscopy. This 3D imaging approach combined with automatic quantification of morphological changes enables previously intractable high-throughput screening of vertebrate model organisms.

    List of papers
    1. A detailed analysis of 3D subcellular signal localization
    Open this publication in new window or tab >>A detailed analysis of 3D subcellular signal localization
    Show others...
    2009 (English)In: Cytometry Part A, ISSN 1552-4922, Vol. 75A, no 4, p. 319-328Article in journal (Refereed) Published
    Abstract [en]

    Detection and localization of fluorescent signals in relation to other subcellular structures is an important task in various biological studies. Many methods for analysis of fluorescence microscopy image data are limited to 2D. As cells are in fact 3D structures, there is a growing need for robust methods for analysis of 3D data. This article presents an approach for detecting point-like fluorescent signals and analyzing their subnuclear position. Cell nuclei are delineated using marker-controlled (seeded) 3D watershed segmentation. User-defined object and background seeds are given as input, and gradient information defines merging and splitting criteria. Point-like signals are detected using a modified stable wave detector and localized in relation to the nuclear membrane using distance shells. The method was applied to a set of biological data studying the localization of Smad2-Smad4 protein complexes in relation to the nuclear membrane. Smad complexes appear as early as 1 min after stimulation while the highest signal concentration is observed 45 min after stimulation, followed by a concentration decrease. The robust 3D signal detection and concentration measures obtained using the proposed method agree with previous observations while also revealing new information regarding the complex formation.

    Keywords
    3D image analysis, fluorescence signal segmentation, subcellular positioning, Smad detection
    National Category
    Computer and Information Sciences
    Identifiers
    urn:nbn:se:uu:diva-98014 (URN)10.1002/cyto.a.20663 (DOI)000264513800006 ()
    Available from: 2009-02-05 Created: 2009-02-05 Last updated: 2018-01-13Bibliographically approved
    2. Single-cell A3243G mitochondrial DNA mutation load assays for segregation analysis
    Open this publication in new window or tab >>Single-cell A3243G mitochondrial DNA mutation load assays for segregation analysis
    Show others...
    2007 (English)In: Journal of Histochemistry and Cytochemistry, ISSN 0022-1554, E-ISSN 1551-5044, Vol. 55, no 11, p. 1159-1166Article in journal (Refereed) Published
    Abstract [en]

    Segregation of mitochondrial DNA (mtDNA) is an important underlying pathogenic factor in mtDNA mutation accumulation in mitochondrial diseases and aging, but the molecular mechanisms of mtDNA segregation are elusive. Lack of high-throughput single-cell mutation load assays lies at the root of the paucity of studies in which, at the single-cell level, mitotic mtDNA segregation patterns have been analyzed. Here we describe development of a novel fluorescence-based, non-gel PCR restriction fragment length polymorphism method for single-cell A3243G mtDNA mutation load measurement. Results correlated very well with a quantitative in situ Padlock/rolling circle amplification–based genotyping method. In view of the throughput and accuracy of both methods for single-cell A3243G mtDNA mutation load determination, we conclude that they are well suited for segregation analysis.

    Keywords
    A3243G mtDNA, Aging, Heteroplasmy, Mitochondrial diseases, Mutation load, Padlock probing, PCR-RFLP, Segregation
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-12658 (URN)10.1369/jhc.7A7282.2007 (DOI)000250320100009 ()17679731 (PubMedID)
    Available from: 2008-01-09 Created: 2008-01-09 Last updated: 2022-01-28Bibliographically approved
    3. BlobFinder, a tool for fluorescence microscopy image cytometry
    Open this publication in new window or tab >>BlobFinder, a tool for fluorescence microscopy image cytometry
    2009 (English)In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 94, no 1, p. 58-65Article in journal (Refereed) Published
    Abstract [en]

    Images can be acquired at high rates with modern fluorescence microscopy hardware, giving rise to a demand for high-speed analysis of image data. Digital image cytometry, i.e., automated measurements and extraction of quantitative data from images of cells, provides valuable information for many types of biomedical analysis. There exists a number of different image analysis software packages that can be programmed to perform a wide array of useful measurements. However, the multi-application capability often compromises the simplicity of the tool. Also, the gain in speed of analysis is often compromised by time spent learning complicated software. We provide a free software called BlobFinder that is intended for a limited type of application, making it easy to use, easy to learn and optimized for its particular task. BlobFinder can perform batch processing of image data and quantify as well as localize cells and point like source signals in fluorescence microscopy images, e.g., from FISH, in situ PLA and padlock probing, in a fast and easy way.

    Keywords
    Image cytometry, Single cell analysis, FISH, Software
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Research subject
    Computerized Image Analysis
    Identifiers
    urn:nbn:se:uu:diva-87971 (URN)10.1016/j.cmpb.2008.08.006 (DOI)000264282400006 ()18950895 (PubMedID)
    Available from: 2009-01-22 Created: 2009-01-16 Last updated: 2018-06-26Bibliographically approved
    4. Robust signal detection in 3D fluorescence microscopy
    Open this publication in new window or tab >>Robust signal detection in 3D fluorescence microscopy
    2010 (English)In: Cytometry. Part A, ISSN 1552-4922, Vol. 77A, no 1, p. 86-96Article in journal (Refereed) Published
    Abstract [en]

    Robust detection and localization of biomolecules inside cells is of great importance to better understand the functions related to them. Fluorescence microscopy and specific staining methods make biomolecules appear as point-like signals on image data, often acquired in 3D. Visual detection of such point-like signals can be time consuming and problematic if the 3D images are large, containing many, sometimes overlapping, signals. This sets a demand for robust automated methods for accurate detection of signals in 3D fluorescence microscopy. We propose a new 3D point-source signal detection method that is based on Fourier series. The method consists of two parts, a detector, which is a cosine filter to enhance the point-like signals, and a verifier, which is a sine filter to validate the result from the detector. Compared to conventional methods, our method shows better robustness to noise and good ability to resolve signals that are spatially close. Tests on image data show that the method has equivalent accuracy in signal detection in comparison to Visual detection by experts. The proposed method can be used as an efficient point-like signal detection tool for various types of biological 3D image data.

    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:uu:diva-98015 (URN)10.1002/cyto.a.20795 (DOI)000273384700011 ()
    Available from: 2009-02-05 Created: 2009-02-05 Last updated: 2022-01-28Bibliographically approved
    5. High-throughput in vivo optical projection tomography of small vertebrates
    Open this publication in new window or tab >>High-throughput in vivo optical projection tomography of small vertebrates
    Show others...
    (English)Manuscript (preprint) (Other academic)
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:uu:diva-159203 (URN)
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2011-11-04
    6. Fully automated cellular-resolution vertebrate screening platform with parallel animal processing
    Open this publication in new window or tab >>Fully automated cellular-resolution vertebrate screening platform with parallel animal processing
    Show others...
    2012 (English)In: Lab on a Chip, ISSN 1473-0197, E-ISSN 1473-0189, Vol. 12, no 4, p. 711-716Article in journal (Refereed) Published
    Abstract [en]

    The zebrafish larva is an optically-transparent vertebrate model with complex organs that is widelyused to study genetics, developmental biology, and to model various human diseases. In this article, wepresent a set of novel technologies that significantly increase the throughput and capabilities of ourpreviously described vertebrate automated screening technology (VAST). We developed a robustmulti-thread system that can simultaneously process multiple animals. System throughput is limitedonly by the image acquisition speed rather than by the fluidic or mechanical processes. We developedimage recognition algorithms that fully automate manipulation of animals, including orienting andpositioning regions of interest within the microscope’s field of view. We also identified the optimalcapillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.

    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Identifiers
    urn:nbn:se:uu:diva-159202 (URN)10.1039/c1lc20849g (DOI)000299380800007 ()
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2018-01-12Bibliographically approved
    7. Image based measurements of single cell mtDNA mutation load MTD 2007
    Open this publication in new window or tab >>Image based measurements of single cell mtDNA mutation load MTD 2007
    Show others...
    2007 (English)In: Medicinteknikdagarna 2007, 2007Conference paper, Published paper (Other (popular science, discussion, etc.))
    Abstract [en]

    Cell cultures as well as cells in tissue always display a certain degree of variability,and measurements based on cell averages will miss important information contained in a heterogeneous population. These differences among cells in a population may be essential to quantify when looking at, e.g., protein expression and mutations in tumor cells which often show high degree of heterogeneity.

    Single nucleotide mutations in the mithochondrial DNA (mtDNA) can accumulate and later be present in large proportions of the mithocondria causing devastating diseases. To study mtDNA accumulation and segregation one needs to measure the amount of mtDNA mutations in each cell in multiple serial cell culture passages. The different degrees of mutation in a cell culture can be quantified by making measurements on individual cells as an alternative to looking at an average of a population. Fluorescence microscopy in combination with automated digital image analysis provides an efficient approach to this type of single cell analysis.

    Image analysis software for these types of applications are often complicated and not easy to use for persons lacking extensive knowledge in image analysis, e.g., laboratory personnel. This paper presents a user friendly implementation of an automated method for image based measurements of mtDNA mutations in individual cells detected with padlock probes and rolling-circle amplification (RCA). The mitochondria are present in the cell’s cytoplasm, and here each cytoplasm has to be delineated without the presence of a cytoplasmic stain. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.

    National Category
    Other Computer and Information Science
    Identifiers
    urn:nbn:se:uu:diva-12745 (URN)
    Available from: 2008-01-11 Created: 2008-01-11 Last updated: 2018-01-12Bibliographically approved
    8. Increasing the dynamic range of in situ PLA
    Open this publication in new window or tab >>Increasing the dynamic range of in situ PLA
    Show others...
    2011 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 8, no 11, p. 892-893Article in journal, Editorial material (Refereed) Published
    National Category
    Biological Sciences
    Identifiers
    urn:nbn:se:uu:diva-159199 (URN)10.1038/nmeth.1743 (DOI)000296891800004 ()
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2022-01-28Bibliographically approved
    9. High-throughput cellular-resolution in vivo vertebrate screening
    Open this publication in new window or tab >>High-throughput cellular-resolution in vivo vertebrate screening
    Show others...
    2011 (English)In: Proc. 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, 2011Conference paper, Published paper (Refereed)
    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:uu:diva-159201 (URN)
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2011-11-04
    Download full text (pdf)
    fulltext
  • 2.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    van de Rijke, Frans
    Jahangir Tafrechi, Roos
    Raap, Anton
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Image based measurements of single cell mtDNA mutation load MTD 20072007In: Medicinteknikdagarna 2007, 2007Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    Cell cultures as well as cells in tissue always display a certain degree of variability,and measurements based on cell averages will miss important information contained in a heterogeneous population. These differences among cells in a population may be essential to quantify when looking at, e.g., protein expression and mutations in tumor cells which often show high degree of heterogeneity.

    Single nucleotide mutations in the mithochondrial DNA (mtDNA) can accumulate and later be present in large proportions of the mithocondria causing devastating diseases. To study mtDNA accumulation and segregation one needs to measure the amount of mtDNA mutations in each cell in multiple serial cell culture passages. The different degrees of mutation in a cell culture can be quantified by making measurements on individual cells as an alternative to looking at an average of a population. Fluorescence microscopy in combination with automated digital image analysis provides an efficient approach to this type of single cell analysis.

    Image analysis software for these types of applications are often complicated and not easy to use for persons lacking extensive knowledge in image analysis, e.g., laboratory personnel. This paper presents a user friendly implementation of an automated method for image based measurements of mtDNA mutations in individual cells detected with padlock probes and rolling-circle amplification (RCA). The mitochondria are present in the cell’s cytoplasm, and here each cytoplasm has to be delineated without the presence of a cytoplasmic stain. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.

  • 3.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    van de Rijke, Frans M.
    Jahangir Tafrechi, Roos
    Raap, Anton K.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Image Based Measurements of Single Cell mtDNA Mutation Load2007In: Image Analysis, Proceedings / [ed] Ersboll BK, Pedersen KS, 2007, p. 631-640Conference paper (Refereed)
    Abstract [en]

    Cell cultures as well as cells in tissue always display a certain degree of variability, and measurements based on cell averages will miss important information contained in a heterogeneous population. This paper presents automated methods for image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. The mitochondria are present in the cell’s cytoplasm, and each cytoplasm has to be delineated. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.

  • 4.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wu, Yuelong
    Ghannad-Rezaie, Mostafa
    Eimon, Peter M.
    Yanik, Mehmet Fatih
    Automated deep-phenotyping of the vertebrate brain2017In: eLIFE, E-ISSN 2050-084X, Vol. 6, article id e23379Article in journal (Refereed)
  • 5.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    BlobFinder, a tool for fluorescence microscopy image cytometry2009In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 94, no 1, p. 58-65Article in journal (Refereed)
    Abstract [en]

    Images can be acquired at high rates with modern fluorescence microscopy hardware, giving rise to a demand for high-speed analysis of image data. Digital image cytometry, i.e., automated measurements and extraction of quantitative data from images of cells, provides valuable information for many types of biomedical analysis. There exists a number of different image analysis software packages that can be programmed to perform a wide array of useful measurements. However, the multi-application capability often compromises the simplicity of the tool. Also, the gain in speed of analysis is often compromised by time spent learning complicated software. We provide a free software called BlobFinder that is intended for a limited type of application, making it easy to use, easy to learn and optimized for its particular task. BlobFinder can perform batch processing of image data and quantify as well as localize cells and point like source signals in fluorescence microscopy images, e.g., from FISH, in situ PLA and padlock probing, in a fast and easy way.

    Download full text (pdf)
    FULLTEXT01
  • 6.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Signal Detection in 3D by Stable Wave Signal Verification2009In: Proceedings of SSBA 2009, 2009Conference paper (Other academic)
    Abstract [en]

    Detection and localization of point-source signals is an important task in many image analysis applications. These types of signals can commonly be seen in fluorescent microscopy when studying functions of biomolecules. Visual detection and localization of point-source signals in 3D is limited and time consuming, making automated methods an important task. The 3D Stable Wave Detector (3DSWD) is a new method that combines signal enhancement with a verifier/separator. The verifier/separator examines the intensity gradient around a signal, making the detection less sensitive to noise and better at separating spatially close signals. Conventional methods such as; TopHat, Difference of Gaussian, and Multiscale Product consist only of signal enhancement. In this paper we compare the 3DSWD to these conventional methods with and without the addition of a verifier/separator. We can see that the 3DSWD has the highest robustness to noise among all the methods and that the other methods are improved when a verifier/separator is added.

  • 7.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    van de Rijke, Frans
    Jahangir Tafrechi, Roos
    Raap, Anton
    Segmentation of Cytoplasms of Cultured Cells2007In: In Proceedings SSBA 2007, Symposium on image analysis, Linköping, 2007Conference paper (Other academic)
    Abstract [en]

    Cell cultures as well as cells in tissue always display a certain degree of variability, and measurements based on cell averages will miss important information contained in a heterogeneous population. This paper presents automated methods for segmentation of cells and cytoplasms. The segmentation results are applied to image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%, compared to an inter observer variability of 79% at manual delineation.

  • 8.
    Arnold, Hannah
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Panara, Virginia
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Palaeobiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Hussmann, Melina
    WWU Munster, Med Fac, Inst Cardiovasc Organogenesis & Regenerat, Munster, Germany..
    Gorniok, Beata Filipek
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Skoczylas, Renae
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Ranefall, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Gloger, Marleen
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Hogan, Benjamin M.
    Univ Melbourne, Dept Anat & Physiol, Melbourne, Vic 3000, Australia.;Univ Melbourne, Sir Peter MacCallum Dept Oncol, Melbourne, Vic 3000, Australia.;Peter MacCallum Canc Ctr, Organogenesis & Canc Program, Melbourne, Vic 3000, Australia..
    Schulte-Merker, Stefan
    WWU Munster, Med Fac, Inst Cardiovasc Organogenesis & Regenerat, Munster, Germany..
    Koltowska, Katarzyna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    mafba and mafbb differentially regulate lymphatic endothelial cell migration in topographically distinct manners2022In: Cell Reports, E-ISSN 2211-1247, Vol. 39, no 12, article id 110982Article in journal (Refereed)
    Abstract [en]

    Lymphangiogenesis, formation of lymphatic vessels from pre-existing vessels, is a dynamic process that requires cell migration. Regardless of location, migrating lymphatic endothelial cell (LEC) progenitors probe their surroundings to form the lymphatic network. Lymphatic-development regulation requires the transcription factor MAFB in different species. Zebrafish Mafba, expressed in LEC progenitors, is essential for their migration in the trunk. However, the transcriptional mechanism that orchestrates LEC migration in different lymphatic endothelial beds remains elusive. Here, we uncover topographically different requirements of the two paralogs, Mafba and Mafbb, for LEC migration. Both mafba and mafbb are necessary for facial lymphatic development, but mafbb is dispensable for trunk lymphatic development. On the molecular level, we demonstrate a regulatory network where Vegfc-Vegfd-SoxF-Mafba-Mafbb is essential in facial lymphangiogenesis. We identify that mafba and mafbb tune the directionality of LEC migration and vessel morphogenesis that is ultimately necessary for lymphatic function.

    Download full text (pdf)
    fulltext
  • 9.
    Bombrun, Maxime
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Ranefall, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Partel, Gabriele
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Solorzano, Leslie
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Qian, Xiaoyan
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Tomtebodavagen 23, S-17165 Solna, Sweden.
    Nilsson, Mats
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Tomtebodavagen 23, S-17165 Solna, Sweden.
    Wählby, Carolina
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    Decoding gene expression in 2D and 3D2017In: Image Analysis: Part II, Springer, 2017, p. 257-268Conference paper (Refereed)
    Abstract [en]

    Image-based sequencing of RNA molecules directly in tissue samples provides a unique way of relating spatially varying gene expression to tissue morphology. Despite the fact that tissue samples are typically cut in micrometer thin sections, modern molecular detection methods result in signals so densely packed that optical “slicing” by imaging at multiple focal planes becomes necessary to image all signals. Chromatic aberration, signal crosstalk and low signal to noise ratio further complicates the analysis of multiple sequences in parallel. Here a previous 2D analysis approach for image-based gene decoding was used to show how signal count as well as signal precision is increased when analyzing the data in 3D instead. We corrected the extracted signal measurements for signal crosstalk, and improved the results of both 2D and 3D analysis. We applied our methodologies on a tissue sample imaged in six fluorescent channels during five cycles and seven focal planes, resulting in 210 images. Our methods are able to detect more than 5000 signals representing 140 different expressed genes analyzed and decoded in parallel.

    Download full text (pdf)
    fulltext
  • 10.
    Chang, Tsung-Yao
    et al.
    Massachusetts Institute of Technology, USA.
    Pardo-Martin, Carlos
    Massachusetts Institute of Technology, USA.
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Yanik, Mehmet Fatih
    Massachusetts Institute of Technology, USA.
    Fully automated cellular-resolution vertebrate screening platform with parallel animal processing2012In: Lab on a Chip, ISSN 1473-0197, E-ISSN 1473-0189, Vol. 12, no 4, p. 711-716Article in journal (Refereed)
    Abstract [en]

    The zebrafish larva is an optically-transparent vertebrate model with complex organs that is widelyused to study genetics, developmental biology, and to model various human diseases. In this article, wepresent a set of novel technologies that significantly increase the throughput and capabilities of ourpreviously described vertebrate automated screening technology (VAST). We developed a robustmulti-thread system that can simultaneously process multiple animals. System throughput is limitedonly by the image acquisition speed rather than by the fluidic or mechanical processes. We developedimage recognition algorithms that fully automate manipulation of animals, including orienting andpositioning regions of interest within the microscope’s field of view. We also identified the optimalcapillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.

  • 11.
    Clausson, Carl-Magnus
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Weibrecht, Irene
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Mahmoudi, Salah
    Farnebo, Marianne
    Landegren, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Söderberg, Ola
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular tools. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Increasing the dynamic range of in situ PLA2011In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 8, no 11, p. 892-893Article in journal (Refereed)
  • 12.
    del Pozo, Ana
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience.
    Manuel, Remy
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Iglesias Gonzalez, Ana Belen
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Koning, Harmen Kornelis
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Habicher, Judith
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Zhang, Hanqing
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Kullander, Klas
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Kullander: Formation and Function of Neuronal Circuits.
    Boije, Henrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Behavioral Characterization of dmrt3a Mutant Zebrafish Reveals Crucial Aspects of Vertebrate Locomotion through Phenotypes Related to Acceleration2020In: eNeuro, E-ISSN 2373-2822, Vol. 7, no 3, article id 0047-20.2020Article in journal (Refereed)
    Abstract [en]

    Vertebrate locomotion is orchestrated by spinal interneurons making up a central pattern generator. Proper coordination of activity, both within and between segments, is required to generate the desired locomotor output. This coordination is altered during acceleration to ensure the correct recruitment of muscles for the chosen speed. The transcription factor Dmrt3 has been proposed to shape the patterned output at different gaits in horses and mice. Here, we characterized dmrt3a mutant zebrafish, which showed a strong, transient, locomotor phenotype in developing larvae. During beat-and-glide swimming, mutant larvae showed fewer and shorter movements with decreased velocity and acceleration. Developmental compensation likely occurs as the analyzed behaviors did not differ from wild-type at older larval stages. However, analysis of maximum swim speed in juveniles suggests that some defects persist within the mature locomotor network of dmrt3a mutants. Our results reveal the pivotal role Dmrt3 neurons play in shaping the patterned output during acceleration in vertebrates.

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  • 13. Eimon, Peter M
    et al.
    Ghannad-Rezaie, Mostafa
    De Rienzo, Gianluca
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Wu, Yuelong
    Gao, Mu
    Roy, Ambrish
    Skolnick, Jeffrey
    Yanik, Mehmet Fatih
    Brain activity patterns in high-throughput electrophysiology screen predict both drug efficacies and side effects.2018In: Nature Communications, E-ISSN 2041-1723, Nature Communications, ISSN 2041-1723, EISSN 2041-1723, ISSN 2041-1723, Vol. 9, no 1, article id 219Article in journal (Refereed)
    Abstract [en]

    Neurological drugs are often associated with serious side effects, yet drug screens typically focus only on efficacy. We demonstrate a novel paradigm utilizing high-throughput in vivo electrophysiology and brain activity patterns (BAPs). A platform with high sensitivity records local field potentials (LFPs) simultaneously from many zebrafish larvae over extended periods. We show that BAPs from larvae experiencing epileptic seizures or drug-induced side effects have substantially reduced complexity (entropy), similar to reduced LFP complexity observed in Parkinson's disease. To determine whether drugs that enhance BAP complexity produces positive outcomes, we used light pulses to trigger seizures in a model of Dravet syndrome, an intractable genetic epilepsy. The highest-ranked compounds identified by BAP analysis exhibit far greater anti-seizure efficacy and fewer side effects during subsequent in-depth behavioral assessment. This high correlation with behavioral outcomes illustrates the power of brain activity pattern-based screens and identifies novel therapeutic candidates with minimal side effects.

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  • 14.
    Gudmundsson, Sanna
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University.
    Wilbe, Maria
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Gorniok, Beata Filipek
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Molin, Anna-Maja
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Ekvall, Sara
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Johansson, Josefin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Gylje, Hans
    Department of Paediatrics, Central Hospital, Västerås, 721 89, Sweden..
    Kalscheuer, Vera M.
    Research Group Development and Disease, Max Planck Institute for Molecular Genetics, Berlin, 141 95, Germany..
    Ledin, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Annerén, Göran
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Bondeson, Marie-Louise
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    TAF1, associated with intellectual disability in humans, is essential for embryogenesis and regulates neurodevelopmental processes in zebrafish2019In: Scientific Reports, E-ISSN 2045-2322, Vol. 9, article id 10730Article in journal (Refereed)
    Abstract [en]

    The TATA-box binding protein associated factor 1 (TAF1) protein is a key unit of the transcription factor II D complex that serves a vital function during transcription initiation. Variants of TAF1 have been associated with neurodevelopmental disorders, but TAF1's molecular functions remain elusive. In this study, we present a five-generation family affected with X-linked intellectual disability that co-segregated with a TAF1 c. 3568C>T, p.(Arg1190Cys) variant. All affected males presented with intellectual disability and dysmorphic features, while heterozygous females were asymptomatic and had completely skewed X-chromosome inactivation. We investigated the role of TAF1 and its association to neurodevelopment by creating the first complete knockout model of the TAF1 orthologue in zebrafish. A crucial function of human TAF1 during embryogenesis can be inferred from the model, demonstrating that intact taf1 is essential for embryonic development. Transcriptome analysis of taf1 zebrafish knockout revealed enrichment for genes associated with neurodevelopmental processes. In conclusion, we propose that functional TAF1 is essential for embryonic development and specifically neurodevelopmental processes.

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  • 15.
    Habicher, Judith
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology. Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Trento, Italy.
    Varshney, Gaurav K.
    Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, United States of America .
    Waldmann, Laura
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Snitting, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Zhang, Hanqing
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Ghanem, Abdurrahman
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Öhman, Caroline
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Materials Science and Engineering, Applied Material Science.
    Dierker, Tabea
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Kjellén, Lena
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Burgess, Shawn M.
    Translational and Functional Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, United States of America .
    Ledin, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology.
    Chondroitin/dermatan sulfate glycosyltransferase genes are essential for craniofacial development2022In: PLOS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 18, no 2, article id e1010067Article in journal (Refereed)
    Abstract [en]

    Chondroitin/dermatan sulfate (CS/DS) proteoglycans are indispensable for animal development and homeostasis but the large number of enzymes involved in their biosynthesis have made CS/DS function a challenging problem to study genetically. In our study, we generated loss-of-function alleles in zebrafish genes encoding CS/DS biosynthetic enzymes and characterized the effect on development in single and double mutants. Homozygous mutants in chsy1, csgalnact1a, csgalnat2, chpfa, ust and chst7, respectively, develop to adults. However, csgalnact1a-/- fish develop distinct craniofacial defects while the chsy1-/- skeletal phenotype is milder and the remaining mutants display no gross morphological abnormalities. These results suggest a high redundancy for the CS/DS biosynthetic enzymes and to further reduce CS/DS biosynthesis we combined mutant alleles. The craniofacial phenotype is further enhanced in csgalnact1a-/-;chsy1-/- adults and csgalnact1a-/-;csgalnact2-/- larvae. While csgalnact1a-/-;csgalnact2-/- was the most affected allele combination in our study, CS/DS is still not completely abolished. Transcriptome analysis of chsy1-/-, csgalnact1a-/- and csgalnact1a-/-;csgalnact2-/- larvae revealed that the expression had changed in a similar way in the three mutant lines but no differential expression was found in any of fifty GAG biosynthesis enzymes identified. Thus, zebrafish larvae do not increase transcription of GAG biosynthesis genes as a consequence of decreased CS/DS biosynthesis. The new zebrafish lines develop phenotypes similar to clinical characteristics of several human congenital disorders making the mutants potentially useful to study disease mechanisms and treatment.

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  • 16.
    Ljungblad, Jonas
    et al.
    Hok Instrument AB, S-72131 Vasteras, Sweden..
    Hök, Bertil
    Hok Instrument AB, S-72131 Vasteras, Sweden..
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Pettersson, Håkan
    Autoliv Dev AB, Vargarda, Sweden..
    Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion2017In: Traffic Injury Prevention, ISSN 1538-9588, E-ISSN 1538-957X, Vol. 18, p. S31-S36Article in journal (Refereed)
    Abstract [en]

    Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.

    Method: The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.

    Results: Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated.The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.

    Conclusions: It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design.

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  • 17.
    Mazzaferro, Eugenia
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Metzendorf, Christoph
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Zhang, Hanqing
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Mujica, Endrina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Höijer, Ida
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Genomics and Neurobiology.
    Alavioon, Ghazal
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Campos Costa, Joao
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Cook, Naomi
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Emmanouilidou, Anastasia
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Larsson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Chemistry.
    Ameur, Adam
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    den Hoed, Marcel
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Kita crispants for systematic image-based genetic screens of complex traits in zebrafish larvaeManuscript (preprint) (Other academic)
  • 18.
    Mazzaferro, Eugenia
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Mujica, Endrina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Zhang, Hanqing
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Emmanouilidou, Anastasia
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Jenseit, Anne
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Loos, Ruth J. F.
    Vienberg, Sara Gry
    Larsson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Chemistry.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    den Hoed, Marcel
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Characterizing obesity-susceptibility genes using CRISPR/Cas9, in vivo imaging and deep learningManuscript (preprint) (Other academic)
  • 19.
    Mazzaferro, Eugenia
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Zhang, Hanqing
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Mujica, Endrina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Azizah, Isyatul
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Loos, Ruth J. F.
    Larsson, Anders
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Chemistry.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    den Hoed, Marcel
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular Tools and Functional Genomics.
    Characterizing candidate genes in GWAS-identified loci that may uncouple excess adiposity from its comorbiditiesManuscript (preprint) (Other academic)
  • 20.
    Panara, Virginia
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Yu, Oliver
    Peng, Di
    Skoczylas, Renae
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Staxäng, Karin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Hodik, Monika
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Haitina, Tatjana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hogan, Benjamin M.
    Koltowska, Katarzyna
    Distinct cis-regulatory elements drive prox1a expression in specific lymphatic vascular bedsManuscript (preprint) (Other academic)
  • 21. Pardo-Martin, Carlos
    et al.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Medina, Jaime
    Eimon, Peter M.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Yanik, Mehmet Fatih
    High-throughput hyperdimensional vertebrate phenotyping2013In: Nature Communications, E-ISSN 2041-1723, Vol. 4, p. 1467-Article in journal (Refereed)
    Abstract [en]

    Most gene mutations and biologically active molecules cause complex responses in animals that cannot be predicted by cell culture models. Yet animal studies remain too slow and their analyses are often limited to only a few readouts. Here we demonstrate high-throughput optical projection tomography with micrometre resolution and hyperdimensional screening of entire vertebrates in tens of seconds using a simple fluidic system. Hundreds of independent morphological features and complex phenotypes are automatically captured in three dimensions with unprecedented speed and detail in semitransparent zebrafish larvae. By clustering quantitative phenotypic signatures, we can detect and classify even subtle alterations in many biological processes simultaneously. We term our approach hyperdimensional in vivo phenotyping. To illustrate the power of hyperdimensional in vivo phenotyping, we have analysed the effects of several classes of teratogens on cartilage formation using 200 independent morphological measurements, and identified similarities and differences that correlate well with their known mechanisms of actions in mammals.

  • 22. Pardo-Martin, Carlos
    et al.
    Chang, Tsung-Yao
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Yanik, Mehmet Fatih
    High-throughput cellular-resolution in vivo vertebrate screening2011In: Proc. 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, 2011Conference paper (Refereed)
  • 23.
    Pinidiyaarachchi, Amalka
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Zieba, Agata
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology, Molecular tools.
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Pardali, Katerina
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology, Molecular tools.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    A detailed analysis of 3D subcellular signal localization2009In: Cytometry Part A, ISSN 1552-4922, Vol. 75A, no 4, p. 319-328Article in journal (Refereed)
    Abstract [en]

    Detection and localization of fluorescent signals in relation to other subcellular structures is an important task in various biological studies. Many methods for analysis of fluorescence microscopy image data are limited to 2D. As cells are in fact 3D structures, there is a growing need for robust methods for analysis of 3D data. This article presents an approach for detecting point-like fluorescent signals and analyzing their subnuclear position. Cell nuclei are delineated using marker-controlled (seeded) 3D watershed segmentation. User-defined object and background seeds are given as input, and gradient information defines merging and splitting criteria. Point-like signals are detected using a modified stable wave detector and localized in relation to the nuclear membrane using distance shells. The method was applied to a set of biological data studying the localization of Smad2-Smad4 protein complexes in relation to the nuclear membrane. Smad complexes appear as early as 1 min after stimulation while the highest signal concentration is observed 45 min after stimulation, followed by a concentration decrease. The robust 3D signal detection and concentration measures obtained using the proposed method agree with previous observations while also revealing new information regarding the complex formation.

  • 24.
    von der Heyde, Benedikt
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Beijer Lab, Uppsala, Sweden..
    Emmanouilidou, Anastasia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Beijer Lab, Uppsala, Sweden.
    Mazzaferro, Eugenia
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Beijer Lab, Uppsala, Sweden.
    Vicenzi, Silvia
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala Univ, Beijer Lab, Uppsala, Sweden..
    Höijer, Ida
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala Univ, Beijer Lab, Uppsala, Sweden..
    Klingström, Tiffany
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Jumaa, Sitaf
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala Univ, Beijer Lab, Uppsala, Sweden.
    Dethlefsen, Olga
    Stockholm Univ, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Natl Bioinformat Infrastruct Sweden, Stockholm, Sweden..
    Snieder, Harold
    Univ Groningen, Univ Med Ctr Groningen, Dept Epidemiol, Groningen, Netherlands..
    de Geus, Eco
    Vrije Univ Amsterdam, Dept Biol Psychol, Amsterdam, Netherlands..
    Ameur, Adam
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Beijer Lab, Uppsala, Sweden.;Monash Univ, Dept Epidemiol & Prevent Med, Melbourne, Vic, Australia..
    Ingelsson, Erik
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Stanford Univ, Dept Med, Sch Med, Div Cardiovasc Med, Stanford, CA 94305 USA.;Stanford Univ, Stanford Cardiovasc Inst, Stanford, CA 94305 USA..
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Brooke, Hannah L.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Lifestyle and rehabilitation in long term illness.
    den Hoed, Marcel
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik. Uppsala Univ, Beijer Lab, Uppsala, Sweden..
    Translating GWAS-identified loci for cardiac rhythm and rate using an in vivo image- and CRISPR/Cas9-based approach2020In: Scientific Reports, E-ISSN 2045-2322, Vol. 10, no 1Article in journal (Refereed)
    Abstract [en]

    A meta-analysis of genome-wide association studies (GWAS) identified eight loci that are associated with heart rate variability (HRV), but candidate genes in these loci remain uncharacterized. We developed an image- and CRISPR/Cas9-based pipeline to systematically characterize candidate genes for HRV in live zebrafish embryos. Nine zebrafish orthologues of six human candidate genes were targeted simultaneously in eggs from fish that transgenically express GFP on smooth muscle cells (Tg[acta2:GFP]), to visualize the beating heart. An automated analysis of repeated 30 s recordings of beating atria in 381 live, intact zebrafish embryos at 2 and 5 days post-fertilization highlighted genes that influence HRV (hcn4 and si:dkey-65j6.2 [KIAA1755]); heart rate (rgs6 and hcn4); and the risk of sinoatrial pauses and arrests (hcn4). Exposure to 10 or 25 mu M ivabradine-an open channel blocker of HCNs-for 24 h resulted in a dose-dependent higher HRV and lower heart rate at 5 days post-fertilization. Hence, our screen confirmed the role of established genes for heart rate and rhythm (RGS6 and HCN4); showed that ivabradine reduces heart rate and increases HRV in zebrafish embryos, as it does in humans; and highlighted a novel gene that plays a role in HRV (KIAA1755).

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  • 25.
    Waldmann, Laura
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Leyhr, Jake
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Filipek-Gorniok, Beata
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology. Genome Engineering Zebrafish, Science for Life Laboratory.
    Zhang, Hanqing
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Haitina, Tatjana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    An evolutionarily conserved cis-regulatory element of nkx3.2 drives jaw joint-specific expression in zebrafishManuscript (preprint) (Other academic)
  • 26.
    Waldmann, Laura
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Leyhr, Jake
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology. Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Palaeobiology.
    Zhang, Hanqing
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Science for Life Laboratory BioImage Informatics Facility.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Science for Life Laboratory BioImage Informatics Facility.
    Öhman, Caroline
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Materials Science and Engineering, Applied Material Science.
    Haitina, Tatjana
    Uppsala University, Science for Life Laboratory, SciLifeLab.
    The Role of Gdf5 in the Development of the Zebrafish Fin Endoskeleton2022In: Developmental Dynamics, ISSN 1058-8388, E-ISSN 1097-0177, Vol. 251, no 9, p. 1535-1549Article in journal (Refereed)
    Abstract [en]

    The development of the vertebrate skeleton requires a complex interaction of multiple factors to facilitate correct shaping and positioning of bones and joints. Growth and differentiation factor 5 (Gdf5), a member of the transforming growth factor-beta family (TGF-beta) is involved in patterning appendicular skeletal elements including joints. Expression of gdf5 in zebrafish has been detected within the first pharyngeal arch jaw joint, fin mesenchyme condensations and segmentation zones in median fins, however little is known about the functional role of Gdf5 outside of Amniota. 

    We generated CRISPR/Cas9 knockout of gdf5 in zebrafish and analysed the resulting phenotype at different developmental stages. Homozygous gdf5 mutant zebrafish display truncated median fin endoskeletal elements and loss of posterior radials in the pectoral fins. 

    These findings are consistent with phenotypes observed in human and mouse appendicular skeleton in response to Gdf5 knockout, suggesting a broadly conserved role for Gdf5 in Osteichthyes.

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  • 27.
    Waldmann, Laura
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Leyhr, Jake
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Zhang, Hanqing
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Öhman, Caroline
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Applied Materials Sciences. Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Materials Science and Engineering, Applied Material Science.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Haitina, Tatjana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    The Broad Role of Nkx3.2 in the Development of the Zebrafish Axial SkeletonManuscript (preprint) (Other academic)
    Abstract [en]

    The transcription factor Nkx3.2 (Bapx1) is an important chondrocyte maturation inhibitor. Previous Nkx3.2 knock-down and overexpression studies in non-mammalian gnathostomes have focused on its role in primary jaw joint development, while little is known about the function of this gene in broader skeletal development. We generated CRISPR/Cas9 knockout of nkx3.2 in zebrafish and applied a range of techniques to characterize skeletal phenotypes at developmental stages from larva to adult, revealing fusions in bones of the occiput, the loss or deformation of bony elements derived from basiventral cartilages of the vertebrae, and an increased length of the proximal radials of the dorsal and anal fins. These phenotypes are reminiscent of Nkx3.2 knockout phenotypes in mammals, suggesting that the function of this gene in axial skeletal development is ancestral to osteichthyans. Our results highlight the broad role of nkx3.2 in zebrafish skeletal development and its context-specific functions in different skeletal elements.

  • 28.
    Waldmann, Laura
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Leyhr, Jake
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Zhang, Hanqing
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. BioImage Informatics Facility, Uppsala, Sweden.
    Öhman, Caroline
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Materials Science and Engineering, Applied Material Science.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. BioImage Informatics Facility, Uppsala, Sweden.
    Haitina, Tatjana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    The broad role of Nkx3.2 in the development of the zebrafish axial skeleton2021In: PLOS ONE, E-ISSN 1932-6203, Vol. 16, no 8, article id e0255953Article in journal (Refereed)
    Abstract [en]

    The transcription factor Nkx3.2 (Bapx1) is an important chondrocyte maturation inhibitor. Previous Nkx3.2 knockdown and overexpression studies in non-mammalian gnathostomes have focused on its role in primary jaw joint development, while the function of this gene in broader skeletal development is not fully described. We generated a mutant allele of nkx3.2 in zebrafish with CRISPR/Cas9 and applied a range of techniques to characterize skeletal phenotypes at developmental stages from larva to adult, revealing loss of the jaw joint, fusions in bones of the occiput, morphological changes in the Weberian apparatus, and the loss or deformation of bony elements derived from basiventral cartilages of the vertebrae. Axial phenotypes are reminiscent of Nkx3.2 knockout in mammals, suggesting that the function of this gene in axial skeletal development is ancestral to osteichthyans. Our results highlight the broad role of nkx3.2 in zebrafish skeletal development and its context-specific functions in different skeletal elements.

    Download full text (pdf)
    FULLTEXT01
  • 29.
    Zhang, Hanqing
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Waldmann, Laura
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Manuel, Remy
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Boije, Henrik
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Boije: Zebrafish Neuronal Networks.
    Haitina, Tatjana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Evolution and Developmental Biology.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    zOPT: an open source optical projection tomography system and methods for rapid 3D zebrafish imaging2020In: Biomedical Optics Express, E-ISSN 2156-7085, Vol. 11, no 8, p. 4290-4305Article in journal (Refereed)
    Abstract [en]

    Optical projection tomography (OPT) is a 3D imaging alternative to conventional microscopy which allows imaging of millimeter-sized object with isotropic micrometer resolution. The zebrafish is an established model organism and an important tool used in genetic and chemical screening. The size and optical transparency of the embryo and larva makes them well suited for imaging using OPT. Here, we present an open-source implementation of an OPT platform, built around a customized sample stage, 3D-printed parts and open source algorithms optimized for the system. We developed a versatile automated workflow including a two-step image processing approach for correcting the center of rotation and generating accurate 3D reconstructions. Our results demonstrate high-quality 3D reconstruction using synthetic data as well as real data of live and fixed zebrafish. The presented 3D-printable OPT platform represents a fully open design, low-cost and rapid loading and unloading of samples. Our system offers the opportunity for researchers with different backgrounds to setup and run OPT for large scale experiments, particularly in studies using zebrafish larvae as their key model organism.

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1 - 29 of 29
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