Open-source cell culture automation system with integrated cell counting for passaging microplate cultures
Record generated from the current DIY biofabrication corpus.
- Year
- 2025
- Skill
- medium
- Docs
- limited
- Rubric
- 3.5 / 5
Implementation assessment
Scoring by criterion
Scores describe accessibility and implementation characteristics reported in the reviewed source. They are not a measure of scientific quality.
Resolution
Minimum volume evidence about 200 uL.
Scalability/Throughput
Evidence of parallel, plate-scale, multi-head, or unattended operation.
Build and Part Sourcing Complexity
Mix of common parts and custom/printed components.
Skill Complexity
Build/operation described as low-skill or basic assembly.
Equipment/Cosumable/Facility Requirement Accessibility
Uses common benchtop/desktop equipment or generic consumables.
Application Level
Presented as modular or usable across multiple workflows.
Accessibility to documentation
Open resources include several build or operation artifacts.
Validation/Troubleshooting Complexity
Validation includes standards, benchmarking, replicates, or multi-condition tests.
Speed/Cycle Time
Speed evidence suggests rapid, real-time, or automated operation.
Build Time
Build time not reported; assigned neutral score.
Record metadata
Publication data
Crossref and OpenAlex
Publication record
Abstract
Tissue culture in 96-well microplates is conventionally a tedious, highly manual process sensitive to individual technique and experimenter error. Here, we describe the Automated Cell Culture Splitter (ACCS), a system for passaging plates of adherent or suspension cells, for routine culture maintenance or specialized applications such as seeding plates for microscopy. The system is built around the Opentrons OT-2 liquid handling robot and incorporates a novel on-deck imaging-based cell counter which allows it to compensate for density disparities across a source plate and control the number of cells seeded on a per-well basis. We find this solution can cut hands-on time by 61% and the results compare favorably to our existing manual cell culture processes in terms of both seeding density precision and bio-logical outcomes, achieving a control of seeding density with a well-to-well coefficient of variation (CV) under 11%. The system is designed to be adaptable and an accessible entry point into automation for high-throughput cell culture; to that end, all of the source code and hardware designs are released under open source licenses.
Bibliographic details
Access and metrics
Topics and keywords
Perspective and practical signals
Why it matters
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Limitations
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