Description

Automated single cell isolation from suspension with computer vision

Rita Ungai-Salánki^1,2,3, Tamás Gerecsei³, Péter Fürjes⁴, Norbert Orgovan^2,3, Noémi Sándor⁵, Eszter Holczer⁴, Robert Horvath², Bálint Szabó^2,3,6 *

¹Doctoral School of Molecular- and Nanotechnologies, University of Pannonia, Veszprém, Hungary; ²Nanobiosensorics Group, Institute of Technical Physics and Materials Science, Centre for Energy Research, Hung. Acad. Sci., Budapest, Hungary; ³Department of Biological Physics, Eötvös University, Pázmány Péter sétány 1A, Budapest, H-1117 Hungary; ⁴MEMS Lab, Institute of Technical Physics and Materials Science, Centre for Energy Research, Hung. Acad. Sci., Budapest, Hungary; ⁵MTA-ELTE Immunology Research Group, Budapest, Hungary; ⁶CellSorter Company for Innovations, Budapest, Hungary

*Corresponding author

Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently isolate intact individual cells for subsequent analysis, e.g., DNA/RNA sequencing in 1–2 nanoliters from a thin (~100 μm) layer of cell suspension. It can retrieve rare cells, needs minimal sample preparation, and can be applied for virtually any tissue cell type. Combination of 1 μm positioning precision, adaptive cell targeting and below 1 nl liquid handling precision resulted in an unprecedented accuracy and efficiency in robotic single cell isolation. Single cells were injected either into the wells of a miniature plate with a sorting speed of 3 cells/min or into standard PCR tubes with 2 cells/min. We could isolate labeled cells also from dense cultures containing ~1,000 times more unlabeled cells by the successive application of the sorting process. We compared the efficiency of our method to that of single cell entrapment in microwells and subsequent sorting with the automated micropipette: the recovery rate of single cells was greatly improved.

Reference: R. Ungai-Salánki et al.: Automated single cell isolation from suspension with computer vision, Nature Scientific Reports 6, Article number: 20375 (2016)

Funding acknlowledgement: Our work was supported by the “Lendület” Program of the Hung. Acad. Sci. to R. H. N. S. was supported by the K104838 OTKA. B. S. was supported by the Bolyai Scholarship. N. S. and B. S. were supported by the MedInProt grant of the Hung. Acad. Sci.