I-Corps: A bioinformatic software platform for rapid microbe diagnoses in plants

这个I-Corps项目的更广泛的影响/商业潜力是开发一种植物疾病诊断测试，该测试开发速度更快，诊断结果更快，比目前的诊断工具更可靠和灵敏。今天的诊断测试是有限的，通常不能确定你可能有哪种流感病毒，或者哪种感冒病毒，或者你是否有细菌引起的鼻窦感染。 此外，快速开发诊断测试并证明其准确性的能力对于紧急应对新的疾病爆发至关重要。诊断技术还必须克服时间上的限制，在保持低成本的同时取得成果。 拟议中的技术可以允许保健医生在一次测试中测试多种生物体，以快速告知需要采取哪些行动来帮助患者。这项拟议中的技术将是对呼吸道疾病的已知微生物原因的测试。都是细菌感染对一个病人进行检测的费用可能与目前技术检测一种病原体的费用相同。 然后，患者可以针对其呼吸系统疾病进行适当和专门的治疗。 这个I-Corps项目是基于计算软件的开发，该软件允许快速开发病原体特异性探针和从任何类型的样品中对高通量序列（HTS）数据进行计算机查询。该技术有可能应用于许多领域，包括兽医和人类医学，植物病理学，水质，食品安全和生物威胁的环境监测。 目前的诊断技术需要10-24小时来对每个样本、每个病原体进行“是”或“否”诊断。最初的证明-该概念已与美国监管关注的30种柑橘病原体进行了研究。拟议的技术能够从开始到结束在短短30分钟至3小时内诊断单个样品中是否存在多种病原体。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的评估来支持。影响审查标准。

The broader impact/commercial potential of this I-Corps project is the development of a plant disease diagnostic test that is faster to develop, quicker turn around to diagnostic results, and more reliable and sensitive than current diagnostic tools. Today’s diagnostic tests are limited and typically cannot determine which strain of flu you might have, or which cold virus, or whether what you have is a bacterially-caused sinus infection. In addition, the ability to quickly develop a diagnostic test and prove its accuracy is critical to emergency response to a new disease outbreak. Diagnostic technology also must overcome constraints in time to result while keeping costs low. The proposed technology may allow a health practitioner to test for multiple organisms in one test to quickly inform what actions are needed to help the patient. The proposed technology will be a test for known microbial causes of respiratory disease. all bacterial infections. It may be possible for a patient to be tested for the same cost as current technology tests for just one pathogen. The patient may then be appropriately and specifically treated for their respiratory illness. This I-Corps project is based on the development of computing software that allows rapid development of pathogen-specific probes and in-silico query of high throughput sequence (HTS) data from any kind of sample. The technology has the potential to be applied in many fields, including veterinary and human medicine, plant pathology, water quality, food safety, and environmental monitoring for biological threats. Current diagnostic technology requires 10-24 hours to a “yes” or “no” diagnosis per sample, per pathogen. The initial proof-of-concept has been conducted with 30 citrus pathogens of regulatory concern to the U.S. The proposed technology is capable of diagnosing presence or absence of multiple pathogens in a single sample in as little as 30 minutes to 3 hours from start to finish.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.