Work

Accessible and accurate cytometry analysis using fluorescence microscopes

Year: 2025

Type: preprint

Abstract: We have developed a method along with a python-based analysis tool to capture images and produce flow cytometry like data utilizing simple accessible microscopes. Utilizing the recently developed generalist algorithms for cell segmentation, our approach easily segments semi-adherent or suspended cells facilitating quantification of fluorescent intensity similar to flow cytometry. We have shown that our approach exhibits similar speed and enhanced sensitivity when compared to typical flow cytometry. The utility of our approach is demonstrated by screening a set of 88 prime editing conditions utilizing the integration of mNeonGreen 11 as a reporter.

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.1101/2025.01.22.634380

Authors: Daniel Foyt, Yiming Kuang, Samma Rehem, Klaus Yserentant, Bo Huang

Institutions: University of California, San Francisco, University of California, Berkeley, Barnard College, Chan Zuckerberg Biohub San Francisco

Language: English

Topic: Cell Image Analysis Techniques

Subfield: Biophysics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funder: National Institutes of Health

Award: G9000105031

OpenAlex ID: W4406803931

Cites: 19

Cited by:

Related to: 10