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Updated: Mar 24, 2026

Generating Transposon Insertion Libraries in Gram-Negative Bacteria for High-Throughput Sequencing
Published on: July 7, 2020
Automated workflow for genotyping individual transposon library variants.
Lorea Alejaldre1,2, Ana-Mariya Anhel2,3, Lewis Grozinger1
1Systems Biology Department, Centro Nacional de Biotecnología (CSIC), Madrid 28049, Spain.
This study presents an automated workflow for genotyping transposon insertion libraries using open-source liquid handlers, reducing hands-on time and errors. The robust, scalable method enables reliable variant identification in genome engineering and synthetic biology.
Area of Science:
- Genome Engineering
- Synthetic Biology
- Laboratory Automation
Background:
- High-throughput screening is crucial for genome engineering and synthetic biology but often relies on expensive equipment.
- Genotyping individual clones in transposon libraries is labor-intensive, despite advances in population-level screening.
- Open-source liquid handlers offer accessibility but require programming expertise or validated protocols.
Purpose of the Study:
- To develop a step-by-step automated workflow for individual variant genotyping of transposon insertion libraries.
- To address challenges of cost, programming expertise, and protocol availability in laboratory automation.
- To utilize an open-source OT-2 liquid handler and a custom Python package for efficient and reproducible genotyping.
Main Methods:
- An automated protocol with six modular steps: colony picking, counter-selection, PCR assays, and sequencing with custom Python annotation.
- Utilized standardized vectors (SEVA guidelines) and Lab Automation Protocol (LAP) scripts for reproducibility.
- Demonstrated workflow on a transposon insertion library in Pseudomonas putida KT2440.
Main Results:
- Validated automated workflow for reliable genotyping of individual variants within 4-5 days.
- Achieved successful identification of genomic insertion sites for 40 out of 46 variants with no spurious integrations detected.
- Demonstrated the robustness, accessibility, and scalability of the open-source workflow.
Conclusions:
- The automated workflow reliably reduces hands-on time and human error in genotyping.
- Its modular and standardized design promotes protocol reuse, sharing, and broader access to open-source automation.
- Provides a scalable and reproducible foundation for variant genotyping in genome engineering and synthetic biology.
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