Preliminary Content

Acknowledgements

I thank my supervisor

  • Prof. Dr. Virginie Lecaudey

and mentor

  • Prof. Dr. Manfred Schliwa

and students

  • Dmitri Baulin (M.Sc. Thesis)
  • Felix Godron (B.Sc. Thesis)
  • Andreas Ebert (B.Sc. Thesis)
  • Gelwa Helmand (B.Sc. Thesis)
  • Bianca Rodrigues Lima (Master student)
  • Ivan Alcantara (Master student)

for trust shown in the process, for support and demand. For their patience, engagement and hard work! And I thank my animals, without whom this work would not have been possible.

About

Beside a print version, there is also an electronic version1 of this thesis.

In addition, data analysis scripts, figures and tables are stored in a dedicated git repository2. If you need to have access please contact me.

  • Including Acknowlegements and Preface
  • Lateral line primordium flipbook
    • right pages (odd numbers) show the wildtype
    • left pages (even numbers) show the mutant

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Foreword

“The most exciting time in the history of developmental biology is right now. Fueled both by new technologies and by new thought from other fields, we are exploding old notions and opening fantastic new horizons in embryology. […] Next, let’s discuss why developmental biology — both normal and pathological — holds such enduring fascination. I see two intertwined explanations. Obviously, it’s the ultimate personal creation story, telling each of us both where we came from and how we were constructed. Less obvious, but perhaps more tantalizing for us scientists, is the sheer complexity of the process. A single cell with a single genome can somehow create trillions of cells in hundreds of radically different types, and those cells can organize themselves into a specific form. The scale of this self-organization process is mind boggling, surely the most amazing of emergent properties.” - John B. Wallingford, 20193

Abbreviations

Index Abbreviation Elaboration
0-9 2-/3-D Two or Three Dimensional
A A.I. apical index
AB Antibody
C CC Cell Cluster
CNN Convolutional Neural Network
CI confidence interval
D dpf days post fertilization
DSH Dishevelled
E ECDF Empirical Cumulative Distribution Function
EDF Extended Depth of Field
F Fgf Fibroblast Growth Factor
Fgfr1 Fgf receptor 1
FOV Field of View
FRZ Frizzled
H hpf hours post fertilization
I IJ ImageJ
ISH In Situ Hybridization
K KDE Kernel Density Estimation
k.s. Kolmogorov-Smirnov
L l.e. leading edge
LL Lateral Line
LOESS Locally Weighted Scatterplot Smoothing
LSFM Light sheet fluorescence microscope
LUT Lookup Table
LMPA low melting point agarose
M MaxIP Maximum Intensity Projection
MO Morpholino
mQ milli-Q water
N N.A. Numerical Aperture3
NGS Normal Goat Serum
NICD Notch intracellular domain
NM Neuromast
NMII Non muscle myosin II
O o.n. over night
P p.Hist phospho-Histone
PCR Polymerase chain reaction
PFA Paraformaldehyd
pLLP Posterior Lateral Line Primordium
R Rock Rho-Kinase
ROI Region of Interest
S SBD Shroom binding domain
SEM Scanning Electron Microscopy
SNR Signal to Noise Ratio
T TALEN Transcription activator-like effector nuclease
TF Transcription Factor

Publications

This thesis contains material from the following papers. The rights have been granted by the publisher to include the material in this dissertation. Some passages have been quoted verbatim for the scientific accuracy from the following sources:

  1. Kleinhans, D. S. & Lecaudey, V. Standardized mounting method of (zebrafish) embryos using a 3D-printed stamp for high-content, semi-automated confocal imaging. BMC Biotechnol. 19, 1–10 (2019).

  1. https://kleinhansda.github.io/phd_thesis/↩︎

  2. https://github.com/KleinhansDa/phd_thesis↩︎

  3. “We Are All Developmental Biologists,” Developmental Cell, Vol.50, Issue 2, Jul 22, 2019↩︎