Nonspecific DNA Sensors for Scalable Pathogen Diagnostics

病原体的快速鉴定对临床诊断和生物防御至关重要。有了及时的信息，临床医生可以开出更好的治疗方案，减缓耐药细菌的增长，美国的生物监测工作可以追踪现有病原体和新进化病原体的出现和传播。虽然大多数快速诊断测试都有专门用于检测一种病原体的传感器，但这项研究正在开发新的DNA传感技术，以便仅用几个传感器就能有效地检测大量病原体。通过减少必要传感器的数量，新的病原体监测设备可以便携且廉价地用于日常使用。该技术还提供了一种检测新出现的新型病原体的方法，而无需创建和部署新的检测试剂盒。除了进一步开发新的病原体识别技术外，该项目还开发了一个实践实验模块，探索这种方法，并在莱斯大学的生物传感和成像课程中实施，服务于本科生和研究生工程专业的学生。这项研究应用了压缩传感技术，它只允许几个DNA探针(1)给每个物种一个指纹响应，(2)当几个病原体在同一个样本中时，分解这些指纹信号。压缩感知假设样本是稀疏的。出现稀疏性的原因是，尽管可能有数十或数百种可能的物种需要考虑，但来自患者或环境的任何单个样本都只有少数相关应用感兴趣的病原体。对于病原体检测，每个DNA探针与微生物物种结合多次。几个探针和微生物之间的结合事件的数量给了数百个物种中的每个物种一个“指纹”反应，就像10个数字可以给每个美国人一个唯一的电话号码一样。该项目的第一个目标是开发一种新的DNA信号放大技术，使更少的结合事件被检测到。这种放大策略还允许信号为正或负，有效地允许指纹信号进一步扩散。传感器的非相干性增强对压缩感知非常有帮助。第二个目标是利用微流体中的新技术捕获非常小的液滴中的单个病原体细胞，并分别从每个液滴中获取指纹信号。通过分析每个液滴，该项目推动单细胞分辨率，这将使其在任何需要表征未知微生物的任务中得到更广泛的应用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The rapid identification of pathogens is essential for clinical diagnostics and biodefense. Given timely information, clinicians can prescribe better treatments and slow the rise of drug resistant bacteria, and U.S. biosurveillance efforts can track the emergence and spread of both existing and newly evolved pathogens. While most rapid diagnostic tests have sensors that are each specialized to detect only one kind of pathogen, this research effort is developing new DNA sensing techniques to efficiently detect large numbers of pathogens with just a few sensors. By minimizing the number of necessary sensors, new pathogen surveillance devices could be portable and inexpensive for routine use. The technology additionally provides an approach to detecting emerging novel pathogens without the need to create and deploy new test kits. In addition to furthering development of new pathogen identification technologies, the project develops a hands-on experimental module exploring this methodology and implements it in a biosensing and imaging course serving undergraduate and graduate engineering students at Rice University. This research effort applies compressed sensing which allows just a few DNA probes to (1) give each species a fingerprint response and (2) unmix these fingerprint signals when a few pathogens are in the same sample. Compressed sensing assumes that the sample is sparse. Sparsity occurs because although there may be dozens or hundreds of possible species to account for, any single sample from a patient or the environment will have only a few pathogens of interest for relevant applications. For pathogen detection, DNA probes each bind multiple times to microbial species. The number of binding events between a few probes and the microbes gives each of hundreds of species a “fingerprint” response, much like how 10 digits can give everyone in the U.S. a unique phone number. The first aim of this project is to develop a new DNA signal amplification technique that allows fewer binding events to be detectable. This amplification strategy also lets signals be positive or negative, effectively allowing fingerprint signals to spread further apart. The enhanced incoherence of the sensors is known to be very helpful for compressed sensing. The second aim is to use new technologies in microfluidics to capture individual pathogen cells in very small droplets and acquire fingerprint signals from each droplet separately. By analyzing every droplet, this project pushes towards single-cell resolution which would enable its broader application in any task that demands the characterization of unknown microbes.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.