清脆的
生物医学
核酸
核酸检测
计算生物学
计算机科学
序列(生物学)
人工智能
生物
生物信息学
遗传学
基因
作者
Sreekar Mantena,Priya P. Pillai,Brittany A. Petros,Nicole L. Welch,Cameron Myhrvold,Pardis C. Sabeti,Hayden C. Metsky
标识
DOI:10.1101/2023.09.20.557569
摘要
Generating maximally-fit biological sequences has the potential to transform CRISPR guide RNA design as it has other areas of biomedicine. Here, we introduce model-directed exploration algorithms (MEAs) for designing maximally-fit, artificial CRISPR-Cas13a guides-with multiple mismatches to any natural sequence-that are tailored for desired properties around nucleic acid diagnostics. We find that MEA-designed guides offer more sensitive detection of diverse pathogens and discrimination of pathogen variants compared to guides derived directly from natural sequences, and illuminate interpretable design principles that broaden Cas13a targeting.
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