Challenges in long-term imaging and quantification of single-cell dynamics.
Continuous analysis of single cells, over several cell divisions and for up to weeks at a time, is crucial to deciphering rare, dynamic and heterogeneous cell responses, which would otherwise be missed by population or single-cell snapshot analysis. Although the field of long-term single-cell imaging, tracking and analysis is constantly advancing, several technical challenges continue to hinder wider implementation of this important approach. This is a particular problem for mammalian cells, where in vitro observation usually remains the only possible option for uninterrupted long-term, single-cell observation. Efforts must focus not only on identifying and maintaining culture conditions that support normal cellular behavior while allowing high-resolution imaging over time, but also on developing computational methods that enable semiautomatic analysis of the data. Solutions in microscopy hard- and software, computer vision and specialized theoretical methods for analysis of dynamic single-cell data will enable important discoveries in biology and beyond.
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Stavroula
S
Skylaki
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Oliver
O
Hilsenbeck
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Timm
T
Schroeder
D000818:Animals; D002468:Cell Physiological Phenomena / Q000502:physiology*; D058948:Cell Tracking / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008137:Longitudinal Studies; D008853:Microscopy / Q000379:methods*; D057054:Molecular Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*