University of Heidelberg

High-Content Microscopy & Data Mining



A screening platform for automated correlative High-Content Screening covering wide field (high-throughput) to confocal (high-resolution) to super-resolution microscopy


Automated Correlative Microscopy

Concept of automated correlative microscopy: Interesting events/targets (hits) are localised during high-throughput screens and further analysed using more sensitive detection methods.



In fluorescence microscopy three major techniques are commonly used:

  • wide field microscopy
    • PROS: robust, fast, high-throughput capable
    • CONS: low information content, 2D resolution
  • confocal microscopy
    • PROS: high information content, 3D resolution
    • CONS: only medium-throughput capable
  • super-resolution microscopy
    • PROS: single molecule resolution
    • CONS: demand on dyes and substrates, no automation (so far)

Thus, a combination of these techniques would result in an integrated screening platform for


high-throughput      high-resolution   →   super-resolution


imaging. Within such a correlative microscopy platform, high-throughput (wide field) data acquisition is considered as a trigger / filter system which detects interesting events (hits) on-line during an automated large scale screen (1). The selected candidates can then be analysed more detailed downstream of the microscope pipeline via an automated switch to downscaled high-resolution confocal screening (2) which again triggers for hits in high-resolution detection mode. The overall screening pipeline thus ends up in super-resolution imaging (3) of highly interesting - not only rare - events resulting in a maximum of information content for any biological assay.

(1) order of magnitude of data sets: 106

(2) order of magnitude of data sets: 104

(3) order of magnitude of data sets: 102

Contact: E-Mail (Last update: 27/06/2014)