Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Methods for 2D and 3D Quantitative Microscopy of Biological Samples
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.
2011 (English)Doctoral 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.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2011. , 70 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 856
Keyword [en]
Image analysis, cytmetry, model organism, zebrafish, screening
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-159196ISBN: 978-91-554-8167-4 (print)OAI: oai:DiVA.org:uu-159196DiVA: diva2:443798
Public defence
2011-11-11, Room 2446, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 10:15 (English)
Opponent
Supervisors
Available from: 2011-10-21 Created: 2011-09-25 Last updated: 2014-07-21Bibliographically approved
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, 319-328 p.Article 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.

Keyword
3D image analysis, fluorescence signal segmentation, subcellular positioning, Smad detection
National Category
Computer and Information Science
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: 2012-05-09Bibliographically 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, 1159-1166 p.Article 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.

Keyword
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: 2017-12-11Bibliographically 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, 58-65 p.Article 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.

Keyword
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: 2017-07-12Bibliographically 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, 86-96 p.Article 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: 2011-11-04Bibliographically 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, 711-716 p.Article 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: 2017-12-08Bibliographically 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: 2013-09-25Bibliographically 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, 892-893 p.Article 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: 2017-12-08Bibliographically 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

Open Access in DiVA

fulltext(3238 kB)1723 downloads
File information
File name FULLTEXT01.pdfFile size 3238 kBChecksum SHA-512
f9ae9e68027cb9c8504e476bb33247d3f1610c5ea33717ddb11d63d56dd2a2c714858108402c5e89fd59017c1e041e54b29579e18ca52d1a0c846757ee199651
Type fulltextMimetype application/pdf
Buy this publication >>

Search in DiVA

By author/editor
Allalou, Amin
By organisation
Centre for Image AnalysisComputerized Image Analysis and Human-Computer Interaction
Medical Image Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 1723 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1552 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf