Pathogen to read: a rapid, automated workflow for public health-ready microbial sequencing

Area of Science:

• Microbiology
• Genomics
• Bioinformatics

Background:

• Next Generation Sequencing (NGS) is vital for microbial surveillance in public health.
• Current methods suffer from human error, bias, and low yields, hindering scalability.
• Automated, non-bias extraction methods like bead beating are difficult to scale.

Purpose of the Study:

• To develop a fully automated, single-cartridge workflow for microbial NGS sample preparation.
• To reduce hands-on time and minimize bias in Gram-positive and Gram-negative extraction.
• To create a scalable solution for low-throughput, cost-sensitive settings.

Main Methods:

• Integrated enzymatic lysis, extraction, and library preparation in a single workflow.
• Utilized a capillary-based liquid handler for automation.
• Benchmarked the workflow on a standardized mock microbial community.

Main Results:

• Reduced hands-on time from 8-10 hours to under 45 minutes.
• Achieved high-quality libraries with an average yield of 80.5 ng/µL and quality score of 33.6.
• Demonstrated a 2.46-fold improvement in Gram-positive representation compared to standard lysis.

Conclusions:

• This is the first fully integrated capillary-based workflow for microbial NGS preparation on low-throughput platforms.
• The automated approach addresses limitations of existing high-throughput systems.
• Offers a foundation for increased efficiency and reproducibility in pathogen genomics for enhanced surveillance.