Development of a Rapid Antibiotic Susceptibility Test Capable of Detecting Heteroresistance

世界卫生组织（WHO）强调，抗生素耐药性是最大的医学威胁之一。 世纪的挑战。如果没有新的抗生素，预计抗生素耐药性感染将导致 到2050年，全球每年有1000万人死亡（超过癌症）。这些感染会抵消 现代医学的许多进步都依赖于抗生素。因此，选择有效的抗生素， 细菌亲和性将提供最大的治疗益处。 一种未被发现的抗性形式是异源抗性，其中少数亚群 是表型耐药的。这些耐药细胞在抗生素存在的情况下迅速扩增 从而可能导致治疗失败。由于异源耐药性很常见（>25%的抗生素-细菌组合）， 检测异源耐药性对于解决日益严重的抗生素耐药性危机至关重要。事实上， 证明了异源耐药的知识可用于指导成功的联合治疗， 因此甚至可以治疗泛耐药细菌。 不幸的是，临床药敏试验缺乏鉴别异源耐药的分辨率，实验室试验 对于异质电阻是耗时且缓慢的。此外，目前正在进行的下一代敏感性测试 发展主要集中在对少量细胞进行快速诊断， 罕见的细胞不可能。开发新的药敏试验由于药物敏感性试验的要求而进一步复杂化。 临床微生物学实验室;要被采用，敏感性试验必须需要最少的手工劳动， 坚固耐用，并且价格低廉-这些特性通常与高灵敏度不一致。基于这些问题， 人们普遍认为，需要一种新的技术方法。 在这里，开发了一种新的，更灵敏的敏感性试验，使用干涉测量法来测量细菌 提出了人口分布图。使用干涉测量法测量地形在世界上没有先例。 抗生素敏感性测试，在生物医学研究中几乎没有先例。然而，它通常用于 因为它快速、便宜、耐用，不需要染料或染色剂，并提供超分辨率， 测量地形。初步结果表明，干涉测量具有分辨能力， 快速检测异源耐药性并将其与易感性区分开来。我们基于干涉测量的方法是一种 临床药敏试验的实质性改进，无法检测异源耐药性，研究实验室 可以检测异源耐药性但对于临床应用来说太慢的测试，以及传统的地形图成像 方法，例如共聚焦显微镜，昂贵且缺乏分辨能力来区分 从易感性到异源抗性。在我们有希望的初步结果的基础上，这项建议将决定 将细菌地形与死亡和繁殖联系起来的潜在生物物理学。这项工作对于可靠地 将地形图转换为广泛的临床相关细菌和抗生素的敏感性谱。

The World Health Organization (WHO) has highlighted antibiotic resistance as one of the greatest medical challenges of the 21st century. Without new antibiotics, it is predicted that antibiotic resistant infections will cause 10 million annual deaths worldwide by the year 2050 (surpassing cancer). These infections are poised to negate many advances of modern medicine that rely on antibiotics. Thus, choosing effective antibiotics based on bacterial susceptibilities would provide the greatest therapeutic benefit. One form of resistance that is overwhelmingly undetected is heteroresistance, in which a minor subpopulation of bacterial cells is phenotypically resistant. These resistant cells rapidly expand in the presence of an antibiotic and thus can cause treatment failure. As heteroresistance is common (>25% of antibiotic-bacteria combinations), detecting heteroresistance is critical to address the growing crisis of antibiotic resistance. Indeed, it was recently demonstrated that knowledge of heteroresistance can be used to guide successful combination therapy, and can thus even treat pan-resistant bacteria. Unfortunately, clinical susceptibility tests lack the resolution to identify heteroresistance, and the laboratory test for heteroresistance is time consuming and slow. Further, the next-generation susceptibility tests currently under development are largely focused on rapid diagnostics performed on a small number of cells, making detection of rare cells impossible. Developing a new susceptibility test is further complicated by the requirements of the clinical microbiology laboratory; to be adopted, a susceptibility test must require minimal manual labor, work robustly, and be inexpensive – properties that are often at odds with high sensitivity. Based on these issues, there is broad agreement that a new technological approach is required. Here the development of a new, more sensitive susceptibility test using interferometry to measure bacterial population topography is proposed. The use of interferometry to measure topography has no precedence in antibiotic susceptibility testing, and little precedence in biomedical research. However, its commonly used in physical sciences as it is rapid, inexpensive, robust, doesn’t require dyes or stains, and provides super-resolution measurements of topography. Preliminary results demonstrate that interferometry has the resolving power to rapidly detect heteroresistance and distinguish it from susceptibility. Our interferometry-based approach is a substantial improvement over clinical susceptibility tests that cannot detect heteroresistance, research laboratory tests that can detect heteroresistance but are too slow for clinical application, and traditional topographic imaging approaches, e.g. confocal microscopy, that are expensive and lack the resolving power to distinguish heteroresistance from susceptibility. Building off our promising preliminary results, this proposal will determine the underlying biophysics relating bacterial topography to death and reproduction. This work is pivotal to reliably convert topography into susceptibility profiles across a broad range of clinically relevant bacteria and antibiotics.