eprintid: 36942
rev_number: 19
eprint_status: archive
userid: 8439
dir: disk0/00/03/69/42
datestamp: 2025-07-29 14:19:58
lastmod: 2025-07-29 14:20:19
status_changed: 2025-07-29 14:19:58
type: doctoralThesis
metadata_visibility: show
creators_name: Satheesan, Sankeert
title: Design and implementation of workflow tools for multiplexed time-lapse imaging experiments in zebrafish screening
subjects: ddc-004
subjects: ddc-500
subjects: ddc-590
subjects: ddc-600
divisions: i-140001
adv_faculty: af-14
abstract: Recent high-throughput microscopy advancements have made it possible to perform multiplexed time-lapse imaging in a single experimental run. However, despite these technological improvements, a major gap remains in the practical application and optimization of multiplexed time-lapse imaging for studying dynamic biological processes in vivo. This is particularly evident when quantifying complex dynamic phenotypes, such as regeneration and cell migration, in small model organisms like zebrafish. Challenges in sample preparation, spatiotemporal sampling, and the lack of dedicated imaging protocols and bioimage analysis tools aggravate this problem. Zebrafish, with their genetic accessibility and optical transparency, provide an excellent model for live imaging and high-content screening. However, it lacks dedicated protocols and solutions to multiplexed time-lapse imaging screening experiments, hindering it from fully exploiting its potential.
To address these challenges and bridge this gap, I established a benchmark high-throughput screening platform for quantifying kidney regeneration in zebrafish embryos post-laser-induced injury. This platform integrates multiple components, optimized sample mounting strategies to ensure optimal imaging conditions over extended periods, a high-throughput laser-induced injury workflow, and a smart imaging framework that seamlessly integrates lasering and imaging to capture regenerating renal tubules efficiently. This followed a dedicated image processing pipeline that allows the detection and tracking of regenerating tissues. Utilizing open-source tools such as Fiji, Python, and KNIME, I built analysis workflows capable of stabilizing images, segmenting key regions of interest, and quantitatively assessing regeneration dynamics across hundreds of embryos. Finally, the platform was validated through experiments under different environmental conditions to verify the platform’s ability to assess regeneration efficiency and variability at an unprecedented scale.
In conclusion, using the established high-throughput platform, I set a new benchmark for multiplexed time-lapse imaging in zebrafish-based screening. The platform's protocol components and flexible analysis workflows can be applied to other dynamic phenotypes. Ultimately, through this thesis, I present a comprehensive methodology and versatile tools for long-term imaging and set a precedent for investigating dynamic phenomena across biology.
date: 2025
id_scheme: DOI
id_number: 10.11588/heidok.00036942
own_urn: urn:nbn:de:bsz:16-heidok-369428
date_accepted: 2025-07-03
advisor: HASH(0x55602a68e660)
language: eng
bibsort: SATHEESANSDESIGNANDI20250723
full_text_status: public
place_of_pub: Heidelberg
citation:   Satheesan, Sankeert  (2025) Design and implementation of workflow tools for multiplexed time-lapse imaging experiments in zebrafish screening.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/36942/1/Design%20and%20implementation%20of%20workflow%20tools%20for%20multiplexed%20time-lapse%20imaging%20experiments%20in%20zebrafish%20screening.pdf