Smarter cell sorting: droplet microfluidics meets pick-and-place sorting

Single-cell manipulation based on image-derived selection criteria is essential for morphology-based screening applications. This requires a fast and robust 'pick-and-place' technology to single-out the identified hits from the rest of the population. However, the overall efficiency of this process is influenced by several parameters, primarily constrained by the limitation of moving only one target at a time per cycle. To overcome this bottleneck, we present a system that employs a microfluidic droplet-based approach, enabling the sequential transfer of multiple objects in each cycle. The core of this system is the microfluidic transfer tool (MTT), which enables selected cells to be sequentially 'picked' and encapsulated into individual nanoliter-scale droplets. The resulting droplet sequence serves as a temporary storage buffer for the picked objects before they are transferred to a designated target. Here, hit-containing droplets can be individually 'placed' requiring just one global movement from source to target. To demonstrate the applicability of this approach, the developed MTT was integrated into an experimental robotic environment. Fluorescent particles of about 45-63 μm diameter and different colors were used to benchmark the system. This sequential microfluidic processing resulted in an overall performance improvement by a factor of approximately 20 compared to traditional single-object pick-and-place techniques. Detailed information about the MTT design and the overall workflow are provided.

Authors

Institutions

Publication Details

Journal
Lab on a Chip
Published
2025-11-03
DOI
https://doi.org/10.1039/d5lc00550g
Citations
2
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
Type
article
Field-Weighted Citation Impact
1.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smarter cell sorting: droplet microfluidics meets pick-and-place sorting

Steffen Schneider, Michaela Dehne, Janina Bahnemann, Ralf Welsch et al.
2 citations
Lab on a Chip
Innovative Microfluidic and Catalytic Techniques Innovation
1.35
article

Smarter cell sorting: droplet microfluidics meets pick-and-place sorting

Steffen Schneider, Michaela Dehne, Janina Bahnemann, Ralf Welsch, Jialan Cao, Klaus Palme, Qiuju Yu, Alexander Groß, J. Michael Köhler, Olivia Gerhard
article en
2 citations

Abstract

Single-cell manipulation based on image-derived selection criteria is essential for morphology-based screening applications. This requires a fast and robust 'pick-and-place' technology to single-out the identified hits from the rest of the population. However, the overall efficiency of this process is influenced by several parameters, primarily constrained by the limitation of moving only one target at a time per cycle. To overcome this bottleneck, we present a system that employs a microfluidic droplet-based approach, enabling the sequential transfer of multiple objects in each cycle. The core of this system is the microfluidic transfer tool (MTT), which enables selected cells to be sequentially 'picked' and encapsulated into individual nanoliter-scale droplets. The resulting droplet sequence serves as a temporary storage buffer for the picked objects before they are transferred to a designated target. Here, hit-containing droplets can be individually 'placed' requiring just one global movement from source to target. To demonstrate the applicability of this approach, the developed MTT was integrated into an experimental robotic environment. Fluorescent particles of about 45-63 μm diameter and different colors were used to benchmark the system. This sequential microfluidic processing resulted in an overall performance improvement by a factor of approximately 20 compared to traditional single-object pick-and-place techniques. Detailed information about the MTT design and the overall workflow are provided.

Lab on a Chip
Leibniz University Hannover (DE), Technische Universität Ilmenau (DE), University of Freiburg (DE), University of Augsburg (DE), Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut (DE)
Openalex Percentile: Top 17%
Innovative Microfluidic and Catalytic Techniques Innovation
1.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.