病原体DNA解析を自動化し感染症監視を高速化(Researchers develop automated system to accelerate outbreak detection and disease surveillance)

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2026-07-21 ブラウン大学

ブラウン大学の研究チームは、感染症の原因となる病原体DNAのシーケンス解析に必要な試料調製法を大幅に効率化する新技術を開発した。従来は病原体DNAを解析するために複数の精製工程や時間のかかる前処理が必要であり、臨床現場や感染症流行時の迅速な診断を妨げる要因となっていた。新たな手法では、検体から病原体DNAをより簡便かつ高効率に抽出・濃縮し、次世代シーケンサー(NGS)による解析精度を維持したまま、試料調製時間と作業負担を大幅に削減できることを実証した。これにより、細菌やウイルスなどの病原体を迅速に同定し、薬剤耐性遺伝子や変異の解析も効率的に行える可能性が高まる。本技術は、感染症診断やアウトブレイク時の病原体監視、公衆衛生対策を加速するとともに、臨床検査や研究機関でのゲノム解析の普及にも貢献することが期待されている。

<関連情報>

病原体解析:公衆衛生に即した微生物配列決定のための迅速かつ自動化されたワークフロー Pathogen to read: a rapid, automated workflow for public health-ready microbial sequencing

Kathryn Whitehead,Trinity Williams,Christopher Grim,Shreyas Shah,Lloyd Bwanali,Padmini Ramachandran & Anubhav Tripathi
BMC Genomics  Published:19 June 2026
DOI:https://doi.org/10.1186/s12864-026-13075-1  Unedited version

Abstract

Background
Next Generation Sequencing (NGS) based microbial surveillance has become a critical tool for public health initiatives, providing insights into complex interactions within microbial communities. This understanding can be used to facilitate outbreak investigations, pathogen surveillance, and resistance prevention. However, current sample preparation methods are prone to human error and sample bias resulting in skewed Gram +/- coverages and low yields. Methods that have been optimized for non-bias extraction, like mechanical bead beating, are not easily integrated with automation, preventing widespread scalability. Here, we present an innovative, fully automated method that integrates enzymatic lysis, extraction, and library preparation in a single-operator, single-cartridge workflow. The workflow was designed to substantially reduce hands-on time and minimize Gram-stain-related biased extraction.

Results
A capillary-based liquid handler is leveraged to reduce hands-on time from 8 to 10 h to less than 45 min. Using mixed microbial communities, we demonstrated that the workflow consistently produces high-quality sequencing libraries with an average yield of 80.5 ng/µL, average quality score of 33.6, and using the ZymoBIOMICS Microbial Community Standard, a 2.46-fold improvement in Gram-positive representation relative to a standard lysis protocol.

Conclusions
To our knowledge, this is the first demonstration of a fully integrated capillary-based workflow combining enzymatic lysis, extraction, and library preparation compatible with low-throughput platforms. While automated NGS preparation systems exist, they predominantly rely on high-throughput liquid handling robotics, require separate equipment/workflows for extraction and library preparation, or do not support unified workflows for Gram-positive and Gram-negative extraction. The present approach addresses the low-throughput, cost-sensitive, rapid-turnaround requirements of public health and clinical microbiology settings. This proof-of-concept study demonstrates a fully automated workflow for microbial NGS sample preparation, benchmarked on a standardized mock community. This work offers a transformational engineering foundation with the potential to increase efficiency and reproducibility of pathogen genomics workflows, enabling faster outbreak detection and more comprehensive surveillance programs.

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