CAREER: A comprehensive computational platform for detecting yet unseen microbial pathogens

我们正处于读写DNA能力的黄金时代。自然界中发现的基因组数据的测序现在已经民主化，为拥有无数进化史文件的数字图书馆打开了大门。与此同时，为了广泛的社会效益，工程DNA的合成现在已经自动化，而且负担得起，在最近几年显示出令人难以置信的前景。事实上，最近在DNA读取和写入方面的进展有可能解决重大的全球挑战，例如提高作物产量以解决粮食短缺问题，通过碳捕获减轻污染，以及改善大流行的反应和准备。虽然这些显著的技术进步可以用于广泛的社会效益，但它们在追踪可能导致广泛的经济和公共危害的未知病原体方面没有得到充分利用。我们大规模读写DNA的能力，特别是在发现尚未发现的病原体和有意或无意地增强现有病原体方面，已经远远超过了能够跟踪和防止滥用的计算工具。为了解决这一关键差距，本提案中详细介绍的研究将侧重于开发计算工具，以帮助检测尚未发现的病原体，并防止有意或无意地滥用合成DNA。该项目将通过追求创新的计算方法和途径，倡导病原体检测和监测的新范例。研究方法将受到生物监测中经过试验和测试的方法的推动，同时追求创新的计算战略。具体地说，这个项目将解决四个基本的计算研究挑战：(1)尚未见过的病原体表征--将基于分类学的方法与相关功能联系起来，以了解如何识别新的病原体；(2)PB级的微生物暗物质编目--将概率算法开发与比较基因组方法相结合，用于查询已知和稀有的微生物基因；(3)基因工程检测--通过开发基于图形的PAN基因组与密码子使用偏向模型相结合，从自然产生的DNA中识别工程DNA，以及(4)实施模块化计算平台GuarDNA--将所有东西集成到有史以来第一个专门为生物安全和生物监控设计的综合平台中。GuarDNA将按照软件工程最佳实践进行设计，重点是代码模块化，以促进社区参与。这四项研究挑战将伴随着一项全面的测试和评估计划，该计划既提供对四项研究推进的每一项的单独评估，也提供持续的集成测试，以提供对GuarDNA平台的总体评估。这项研究工作将为生物安全和生物担保打开新的计算方法的大门。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

We are in the golden age of our ability to read and write DNA. The sequencing of genomic data found in nature is now democratized, opening the door to a digital library of countless documents of evolutionary history. In parallel, the synthesis of engineered DNA for widespread societal benefits is now automated and affordable, showing incredible promise in recent years. Indeed, recent advances in reading and writing DNA have the potential to resolve major global challenges, such as boosting crop yield to address food shortages, mitigating pollution through carbon capture, and improving pandemic response and preparedness. While these remarkable technological advances can be used for broad societal benefit, they are underutilized for tracking yet-unseen pathogens that can result in widespread economic and public harm. Our ability to read and write DNA at scale, especially with respect to uncovering yet-unseen pathogens and intentionally or unintentionally enhancing existing pathogens, has far outstripped computational tools capable of tracking and preventing misuse. To address this critical gap, the research detailed in this proposal will focus on developing computational tools to aid in detecting yet-unseen pathogens and preventing intentional or unintentional misuse of synthetic DNA. This project will advocate for a novel paradigm of pathogen detection and monitoring through the pursuit of innovative computational methods and approaches. The research methodology will be motivated by tried and tested approaches in biosurveillance while pursuing innovative computational strategies. Specifically, this project will address four fundamental computational research challenges: (1) yet-unseen pathogen characterization -- contextualizing taxonomy-based approaches with functions of concern to learn how to identify novel pathogens, (2) petabyte-scale cataloging of microbial dark matter -- combining probabilistic algorithm development with comparative genomic approaches for the query of known and rare microbial genes, (3) genetic engineering detection -- discerning engineered DNA from naturally occurring DNA through the development of graph-based pan genomes combined with codon usage bias models, and (4) implementation of the modular computational platform GuarDNA -- integrating everything together into the first-ever comprehensive platform specifically designed for both biosecurity and biosurveillance. GuarDNA will be designed following software engineering best practices, with code modularity as a key focus to facilitate community engagement. These four research challenges will be accompanied by a comprehensive test and evaluation plan, which both provides an individual assessment of each of the four research thrusts as well as continuous integration testing to provide an overarching evaluation of the GuarDNA platform. This research effort will open the door to novel computational approaches for biosecurity and biosurveillance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.