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An open-source microscopy framework for simultaneous control of image acquisition, reconstruction, and analysis
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics.
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences (SCI), Applied Physics.ORCID iD: 0000-0003-0972-0816
KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0003-1769-972x
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2023 (English)In: HardwareX, ISSN 2468-0672, Vol. 13, p. e00400-e00400, article id e00400Article in journal (Refereed) Published
Abstract [en]

We present a computational framework to simultaneously perform image acquisition, reconstruction, and analysis in the context of open-source microscopy automation. The setup features multiple computer units intersecting software with hardware devices and achieves automation using python scripts. In practice, script files are executed in the acquisition computer and can perform any experiment by modifying the state of the hardware devices and accessing experimental data. The presented framework achieves concurrency by using multiple instances of ImSwitch and napari working simultaneously. ImSwitch is a flexible and modular open-source software package for microscope control, and napari is a multidimensional image viewer for scientific image analysis. The presented framework implements a system based on file watching, where multiple units monitor a filesystem that acts as the synchronization primitive. The proposed solution is valid for any microscope setup, supporting various biological applications. The only necessary element is a shared filesystem, common in any standard laboratory, even in resource-constrained settings. The file watcher functionality in Python can be easily integrated into other python-based software. We demonstrate the proposed solution by performing tiling experiments using the molecular nanoscale live imaging with sectioning ability (MoNaLISA) microscope, a high-throughput super-resolution microscope based on reversible saturable optical fluorescence transitions (RESOLFT).

Place, publisher, year, edition, pages
Elsevier BV , 2023. Vol. 13, p. e00400-e00400, article id e00400
Keywords [en]
Automation, RESOLFT, Software
National Category
Other Physics Topics
Identifiers
URN: urn:nbn:se:kth:diva-326025DOI: 10.1016/j.ohx.2023.e00400ISI: 000994831800001PubMedID: 36824447Scopus ID: 2-s2.0-85147606174OAI: oai:DiVA.org:kth-326025DiVA, id: diva2:1752425
Funder
European CommissionVinnova, 2020-04702 Imaging-omicsEU, Horizon 2020, IMAGEOMICS 964016
Note

QC 20230620

Available from: 2023-04-21 Created: 2023-04-21 Last updated: 2023-06-20Bibliographically approved
In thesis
1. Automated super-resolution microscopy for high-throughput imaging
Open this publication in new window or tab >>Automated super-resolution microscopy for high-throughput imaging
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Fluorescence microscopes enable the visualization of biological samples with high contrast by labeling specific structures with fluorescent molecules. However, the spatial resolution of widely used microscopy techniques, such as widefield and confocal microscopy, is limited by the size of a focused spot of light, which roughly corresponds to half the wavelength of the illumination. To overcome this limitation, optical fluorescence nanoscopy techniques were developed, which achieve a higher spatial resolution by switching the fluorescent molecules within the sample between bright and dark states. 

Optical fluorescence nanoscopy techniques can be divided into two categories. The first, namely coordinate-targeted nanoscopy, switches the fluorescent molecules in a spatially annotated way, where it is known where and when the switching is induced. Instead, in stochastic approaches, the emitting molecules appear randomly in the sample and their location can be annotated with high spatial precision. 

This thesis focuses on reversible saturable optical fluorescence transitions (RESOLFT), a coordinate-targeted nanoscopy technique that initially relied on a beam of light that is moved across the sample (i.e., point scanning). Beams of different shapes and wavelengths are synchronized in time to generate super-resolution images. However, this approach creates a trade-off between imaging speed and the field of view. While it can acquire small fields of view at a fast speed, imaging larger areas can take up to several minutes. To overcome this limitation, the molecular nanoscale live imaging with sectioning ability (MoNaLISA) microscope employs patterns of light to parallelize RESOLFT imaging, collecting the fluorescence at different points simultaneously.

Throughput in microscopy is characterized as the number of cells per unit of time and area that a microscope can image. Achieving high throughput enables capturing fast cell dynamics and understanding how they correlate over large fields of view, providing insights into biological processes. Therefore, in this thesis I developed strategies to increase the throughput of coordinate-targeted nanoscopy methods. 

Firstly, I was involved in the mathematical formulation of fluorophore switching and its relationship to image resolution, in order to provide a framework to relate different parameters to image quality (Paper I). Secondly, I developed ImSwitch, an open-source software for microscope control. It implements a software architecture that enables flexibility and adaptability between different microscopy modalities (Paper II). Thirdly, I built a setup that increases the field of view by more than four times than previous implementations of MoNaLISA (Paper III). Finally, I combined MoNaLISA and ImSwitch to provide a framework to parallelize image acquisition, reconstruction, and visualization using multiple computational units (Paper IV).

Abstract [sv]

Optiska fluorescensmikroskop möjliggör avbildning av biologiska prover med hög kontrast tack vare inmärkning av specifika cellulära strukturer med fluorescerance molekyler. Den spatiella upplösningen med de vanligaste mikroskopimetoderna är däremot begränsad till hur väl man kan fokusera en ljusstråle, den så kallade diffraktionsgränsen. Metoder inom fluorescensnanoskopi kan uppnå spatiella upplösningar under denna gräns genom att använda fluorescerance molekyler med ljusa och mörka tillstånd.

Koordinatriktad nanoskopi är en familj av metoder inom fluorescensnanoskopi som använder ljusstrålar med olika våglängder och former för att ta superupplösta avbildningar. Nanoskopi i levande celler är särskilt möjligt med en typ av koordinatriktad nanoskopi som kallas RESOLFT (reversible saturable optical fluorescence transitions). I mikroskopiavbildning av levande celler är det speciellt viktigt att kunna avbilda snabba och dynamiska cellulära processer, samt att samla data från ett stort antal celler per experiment för att uppnå en hög genomströmning av data. I denna riktning har MoNaLISA (molecular nanoscale live imaging with sectioning ability) utvecklats – ett mikroskop som använder stationära ljusmönster för att parallellisera RESOLFT-mikroskopi genom att spela in fluorescens från olika punkter samtidigt. 

Den här avhandlingen fokuserar på att utveckla metoder för att höja genomströmningen av koordinatriktade nanoskopimetoder. I den första studien var jag involverad i den matematiska formuleringen av växlingen mellan olika ljusa och mörka tillstånd för fluorescerande molekyler och hur detta påverkar den spatiella upplösningen i avbildningen, för att utveckla ett ramverk för att relatera olika parametrar till bildkvalitet (Paper I). I den andra studien utecklade jag ImSwitch, en open-source mjukvara för mikroskopkontroll. ImSwitch implementerar en mjukvaruarkitektur som tillåter flexibilitet och anpassningsförmåga mellan olika mikroskopimetoder (Paper II). I den tredje studien utvecklade och byggde jag ett mikroskop som ökar synfältet mer än fyra gånger jämfört med tidigare implementationer av MoNaLISA (Paper III). I den fjärde och sista studien kombinerade jag MoNaLISA och ImSwitch i ett ramverk för parallelliserad bildtagning, bildrekonstruktion och visualisering genom att använda flera datorer och beräkningsenheter (Paper IV).

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2023. p. 71
Series
TRITA-SCI-FOU ; 2023:13
Keywords
RESOLFT, throughput, microscopy automation, nanoscopy
National Category
Biophysics
Research subject
Biological Physics
Identifiers
urn:nbn:se:kth:diva-326026 (URN)978-91-8040-559-1 (ISBN)
Public defence
2023-05-15, Air&Fire, Tomtebodevägen 23, Solna, 09:00 (English)
Opponent
Supervisors
Note

QC 2023-04-24

Available from: 2023-04-24 Created: 2023-04-21 Last updated: 2025-02-20Bibliographically approved

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Moreno, Xavier CasasMendes Silva, MarilinePennacchietti, FrancescaTesta, Ilaria

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