SPIN: Inkjet-Driven Nanowell Workflow for Scalable and Sensitive Single-Cell Proteomics

Single-cell proteomics is emerging as a powerful approach to resolve cellular heterogeneity, yet sample processing remains challenging due to limited input material and the absence of protein amplification. We present a protocol centered on an image-guided, machine-learning-driven inkjet single-cell printer integrated with a dew-point-controlled nanowell chip to reduce loss, increase throughput, and improve reproducibility. The system dispenses single cells at >1 Hz into sealable nanoliter wells with minimal surface contact, virtually eliminating evaporation; a high-thermal-conductivity aluminum substrate and precise environmental control further ensure exceptional reproducibility. Relative to a commercial dispenser, the workflow yields significantly higher protein and peptide recovery without bias toward high-abundance species, delivering uniformly deep coverage. Biological pathway analysis emphasizes the robustness of this workflow, as there is nearly 100% protein completeness detected among the enzymes in the Krebs cycle in both A549 and astrocytes, suggesting consistency across all samples evaluated. This platform addresses core processing bottlenecks and enables reliable, scalable single-cell proteomics.

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Publication Details

Journal
Analytical Chemistry
Published
2026-03-13
DOI
https://doi.org/10.1021/acs.analchem.5c07174
Primary Topic
Microfluidic and Bio-sensing Technologies
Type
article
Field-Weighted Citation Impact
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article

SPIN: Inkjet-Driven Nanowell Workflow for Scalable and Sensitive Single-Cell Proteomics

Leonard J. Foster, Robin Coope, Kerry Cheung, Huan Zhong et al.
Analytical Chemistry
Microfluidic and Bio-sensing Technologies
article

SPIN: Inkjet-Driven Nanowell Workflow for Scalable and Sensitive Single-Cell Proteomics

Leonard J. Foster, Robin Coope, Kerry Cheung, Huan Zhong, Shuxin Chi, Eric Cheng
article en

Abstract

Single-cell proteomics is emerging as a powerful approach to resolve cellular heterogeneity, yet sample processing remains challenging due to limited input material and the absence of protein amplification. We present a protocol centered on an image-guided, machine-learning-driven inkjet single-cell printer integrated with a dew-point-controlled nanowell chip to reduce loss, increase throughput, and improve reproducibility. The system dispenses single cells at >1 Hz into sealable nanoliter wells with minimal surface contact, virtually eliminating evaporation; a high-thermal-conductivity aluminum substrate and precise environmental control further ensure exceptional reproducibility. Relative to a commercial dispenser, the workflow yields significantly higher protein and peptide recovery without bias toward high-abundance species, delivering uniformly deep coverage. Biological pathway analysis emphasizes the robustness of this workflow, as there is nearly 100% protein completeness detected among the enzymes in the Krebs cycle in both A549 and astrocytes, suggesting consistency across all samples evaluated. This platform addresses core processing bottlenecks and enables reliable, scalable single-cell proteomics.

Analytical ChemistryVol. 98(11)
University of British Columbia (CA), Upsher-Smith Laboratories (United Kingdom) (GB), Canada's Michael Smith Genome Sciences Centre (CA)
Openalex Percentile: Top 23%
Microfluidic and Bio-sensing Technologies
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