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Automating life science labs at the single-cell level through precise ultrasonic liquid sample ejection: PULSE.
- Source :
- Microsystems & Nanoengineering; 11/20/2024, Vol. 10 Issue 1, p1-16, 16p
- Publication Year :
- 2024
-
Abstract
- Laboratory automation technologies have revolutionized biomedical research. However, the availability of automation solutions at the single-cell level remains scarce, primarily owing to the inherent challenges of handling cells with such small dimensions in a precise, biocompatible manner. Here, we present a single-cell-level laboratory automation solution that configures various experiments onto standardized, microscale test-tube matrices via our precise ultrasonic liquid sample ejection technology, known as PULSE. PULSE enables the transformation of titer plates into microdroplet arrays by printing nanodrops and single cells acoustically in a programmable, scalable, and biocompatible manner. Unlike pipetting robots, PULSE enables researchers to conduct biological experiments using single cells as anchoring points (e.g., 1 cell vs. 1000 cells per "tube"), achieving higher resolution and potentially more relevant data for modeling and downstream analyses. We demonstrate the ability of PULSE to perform biofabrication, precision gating, and deterministic array barcoding via preallocated droplet-addressable primers. Single cells can be gently printed at a speed range of 5–20 cell⋅s<superscript>−1</superscript> with an accuracy of 90.5–97.7%, which can then adhere to the substrate and grow for up to 72 h while preserving cell integrity. In the deterministic barcoding experiment, 95.6% barcoding accuracy and 2.7% barcode hopping were observed by comparing the phenotypic data with known genotypic data from two types of single cells. Our PULSE platform allows for precise and dynamic analyses by automating experiments at the single-cell level, offering researchers a powerful tool in biomedical research. [ABSTRACT FROM AUTHOR]
- Subjects :
- LIFE sciences
RESEARCH personnel
MEDICAL research
GENOTYPES
DATA modeling
Subjects
Details
- Language :
- English
- ISSN :
- 20961030
- Volume :
- 10
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Microsystems & Nanoengineering
- Publication Type :
- Academic Journal
- Accession number :
- 180991188
- Full Text :
- https://doi.org/10.1038/s41378-024-00798-y