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通过从室温存档中进行通用、可扩展的生化筛选来建立全球规模的核酸文库。

Enabling global-scale nucleic acid repositories through versatile, scalable biochemical selection from room-temperature archives.

作者信息

Berleant Joseph D, Banal James L, Rao Dhriti K, Bathe Mark

机构信息

Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.

Present address: Cache DNA, Inc. 733 Industrial Rd., San Carlos, CA 94070 USA.

出版信息

medRxiv. 2025 Jan 27:2024.04.12.24305660. doi: 10.1101/2024.04.12.24305660.

Abstract

Conventional collection, preservation, and retrieval of nucleic acid specimens, particularly unstable RNA, require costly cold-chain infrastructure and rely on inefficient robotic sample handling, hindering downstream analyses. These generate critical bottlenecks for global pathogen surveillance and genomic biobanking efforts, prohibiting large-scale nucleic acid sample collection and analyses that are needed to empower pathogen tracing, as well as rare disease diagnostics. Here, we introduce a scalable nucleic acid storage system that enables rapid and precise retrieval on pooled nucleic acid samples-stored at room-temperature with minimal physical footprint-using versatile database-like queries on barcoded, encapsulated samples. Queries can incorporate numerical ranges, categorical filters, and combinations thereof, which is a significant advancement beyond previous demonstrations limited to single-sample retrieval or Boolean classifiers. We apply our system to a pool of ninety-six mock SARS-CoV-2 genomic samples identified with theoretical patient data including patient age, geographic location, and diagnostic state, allowing rapid, multiplexed nucleic acid sample retrieval in a scalable manner to empower genomic analyses. By avoiding expensive and cumbersome freezer storage and retrieval systems, our approach in principle scales to millions of samples without loss of fidelity or throughput, thereby supporting the development of large-scale pathogen and genomic repositories in under-resourced or isolated regions of the US and worldwide.

摘要

传统的核酸样本采集、保存和检索,尤其是不稳定的RNA,需要昂贵的冷链基础设施,并依赖低效的机器人样本处理,这阻碍了下游分析。这些为全球病原体监测和基因组生物样本库工作带来了关键瓶颈,阻碍了为病原体追踪以及罕见病诊断所需的大规模核酸样本采集和分析。在此,我们引入了一种可扩展的核酸存储系统,该系统能够使用对条形码封装样本的通用数据库式查询,在室温下以最小的物理空间对汇集的核酸样本进行快速精确检索。查询可以包含数值范围、分类过滤器及其组合,这是超越以往仅限于单样本检索或布尔分类器演示的重大进展。我们将我们的系统应用于一组96个模拟的SARS-CoV-2基因组样本,这些样本用包括患者年龄、地理位置和诊断状态在内的理论患者数据进行了识别,从而能够以可扩展的方式快速、多路复用地检索核酸样本,以支持基因组分析。通过避免昂贵且繁琐的冷冻存储和检索系统,我们的方法原则上可以扩展到数百万个样本,而不会损失保真度或通量,从而支持在美国和全球资源匮乏或偏远地区建立大规模病原体和基因组储存库。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b46/11781500/0e26552b1e1b/nihpp-2024.04.12.24305660v2-f0001.jpg

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