Accessible and Accurate Cytometry Analysis Using Fluorescence Microscopes

Overview

Journal bioRxiv

Date 2025 Feb 3

PMID 39896570

Authors

Daniel Foyt

Yiming Kuang

Samma Rehem

Klaus Yserentant

Bo Huang

Affiliations

Soon will be listed here.

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 as a reporter.

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