Combatting antibiotic resistance with synthetic biology technologies

项目总结/摘要 抗生素耐药性的出现是对我们整个人口最严重的健康威胁之一。 耐药细菌的感染现在太常见了，一些病原体已经对耐药细菌产生了耐药性。 多种抗生素类别。疾病控制和预防中心（CDC）最近估计， 在美国，每年有超过200万种疾病和超过23，000人死亡是由耐药细菌引起的。 随着耐药感染率的上升，迫切需要新的诊断方法， 确定对感染最有效的治疗方法。不幸的是，目前执行的方法 抗生素敏感性测试（AST）涉及从临床样本中培养微生物并确定 通过细胞生长来改变对抗生素的敏感性。这种“黄金标准”技术极其耗时 （至少48-72小时），并可能导致适当治疗的显著延迟，长期患病， 死亡风险、抗生素使用不当和耐药性传播增加。对于一些感染，如 淋病，AST甚至没有在诊所进行，而是根据治疗失败进行推断。总之就是 迫切需要开发新的策略来快速诊断和防止药物扩增， 阻力抗生素暴露可以触发易感微生物中一组标志性mRNA的表达 在短短几分钟内，提高了令人兴奋的可能性，使用RNA检测-而不是细胞生长-作为一个 快速、基于表型的AST的新方法。我们将开发创新的RNA传感器技术， 在临床相关、低成本和易于使用的诊断平台内评估这些分子特征。 为了实现这一目标，我们将使用合成生物学方法来设计高度敏感的基因传感器， mRNA。这些传感器将被部署在无细胞表达系统中，可以阵列和冷冻干燥 在低成本的固态基底上，比如纸张。其结果将是一类新的抗生素诊断， 理想的性能、存储和分布特性。将开发RNA传感器技术， 经高优先级细菌微生物验证。值得注意的是，我们将首次定义 对N.淋病，疾病预防控制中心最近将其列为美国关注的主要原因。 并且AST能力目前在临床环境中不存在。这项工作将迎来一个新的 快速诊断抗生素耐药性的技术，有可能改变 当今日益严重的抗生素耐药性问题。

PROJECT SUMMARY / ABSTRACT The emergence of antimicrobial resistance is one of the most serious health threats to our entire population. Infections from resistant bacteria are now too common, and some pathogens have become resistant to multiple antibiotic classes. The Centers for Disease Control and Prevention (CDC) recently estimated that drug-resistant bacteria account for more than 2 million illnesses and over 23,000 deaths every year in the U.S. With rising rates of drug-resistant infections, there is pressing need for new diagnostic methods that can rapidly determine the most effective therapy for an infection. Unfortunately, the current method for performing antibiotic susceptibility testing (AST) involves growing microorganisms from clinical samples and determining their sensitivity to antibiotics through cell growth. This “gold standard” technique is extremely time-consuming (minimum 48-72 hours) and can result in significant delays in appropriate therapy, prolonged illness, greater risk of death, inappropriate antibiotic use, and increased spread of resistance. For some infections like gonorrhea, AST is not even performed in the clinic and instead inferred based on treatment failure. In short, it is imperative that new strategies are developed to rapidly diagnose and prevent the amplification of drug resistance. Antibiotic exposure can trigger the expression of a signature set of mRNAs in susceptible microbes in as rapidly as a few minutes, raising the exciting possibility of using RNA detection – not cell growth – as a new means for rapid, phenotype-based AST. We will develop innovative RNA sensor technology that evaluates these molecular signatures within a clinically-relevant, low-cost, and easy-to-use diagnostic platform. To achieve this, we will use synthetic biology approaches to engineer highly-sensitive genetic sensors of mRNA. These sensors will be deployed in cell-free expression systems that can be arrayed and freeze-dried onto low-cost, solid-state substrates like paper. The result will be a new class of antibiotic diagnostics with ideal performance, storage, and distribution characteristics. The RNA sensor technology will be developed and validated with high priority bacterial organisms. Notably, we will, for the first time, define RNA signatures of susceptibility for N. gonorrhoeae, which the CDC recently elevated as a major cause for concern in the U.S. and for which AST capabilities do not currently existing in the clinical setting. This work will usher in a new technology for rapidly diagnosing antibiotic resistance, with the potential to transform the management of today's growing antimicrobial resistance problem.