Point-of-care antimicrobial susceptibility testing based on simultaneous tracking of multi-phenotypic features of single bacterial cells

摘要 抗生素耐药性已经成为一个重大的公共卫生威胁。为了解决这个问题，一种快速的病原体 需要鉴定(ID)和药敏试验(AST)技术，以提供及时的诊断 初级卫生保健机构耐药感染的SIS和提供准确的抗生素治疗，包括- ING医院和医疗点(POC)。本项目旨在开发一种护理点AST(POCASTTM) 基于大图像体积显微镜技术的技术，使个人能够直接检测 无需培养或病原体分离的临床样本中的细菌细胞，以及一种机器学习模型 允许快速确定病原体和敏感性。为了建立这项技术，该项目将专注于 尿路感染(UTI)。尿路感染每年影响数百万人，通常导致 尿路感染是对抗菌素耐药性构成最大威胁的微生物，包括碳青霉烯- 耐药肠杆菌科细菌和产超广谱β-内酰胺酶肠杆菌 科植物。 本项目将致力于：1)开发大图像体显微技术和机器学习模型 直接在患者尿样中同时跟踪单个细菌细胞的多表型特征 对UTIS进行快速自动病原体ID和AST；2)建立原型仪器，3)验证 该仪器可用于大规模临床标本的尿路感染。成功开发和验证技术- Nology将在患者就诊的同一天提供精确的抗生素处方。 该项目将由一个在生物传感器方面具有专业知识的多学科团队(BioDesign Center for 生物电子学和生物传感器(ASU)、微生物学和传染病(免疫生物设计中心 治疗、疫苗和病毒治疗)、生物医学仪器的开发和生产(生物传感 Instrument Inc.)和临床检测(临床微生物学实验室，梅奥诊所)。 好了！

ABSTRACT Antibiotic resistance has become a significant public health threat. To combat the problem, a rapid pathogen identification (ID) and antimicrobial susceptibility testing (AST) technology is needed to provide timely diagno- sis of resistant infections and delivery of accurate antibiotic treatment at primary health-care settings, includ- ing hospitals and point-of-care (POC). The present project aims to develop a point-of-care AST (POCASTTM) technology based on a large-image-volume microscopy technique that enables direct detection of individual bacterial cells in clinical samples without culturing or pathogen isolation, and a machine-learning model that allows fast determination of pathogen and susceptibility. To establish the technology, the project will focus on urinary tract infections (UTIs). UTIs affect millions of people annually, and the pathogens that usually cause UTIs are the organisms that pose the highest threat of antimicrobial resistance, including carbapenem- resistant Enterobacteriaceae (CRE) and extended spectrum β-lactamase (ESBL)-producing Enterobacteri- aceae. This project will focus on: 1) developing the large-image-volume microscopy and machine learning model for simultaneous tracking of multi-phenotypic features of single bacterial cells directly in patient urine sample, and performing rapid automatic pathogen ID and AST for UTIs; 2) building prototype instrument, and 3) validating the instrument for UTIs using large scale clinical samples. Successful development and validation of the tech- nology will enable precise antibiotic prescription on the same day of patient visit. The project will be carried out by a multidisciplinary team with expertise in biosensors (Biodesign Center for Bioelectronics and Biosensors, ASU), microbiology and infectious diseases (Biodesign Center for Immuno- therapy, Vaccines and Virotherapy, ASU), biomedical instrument development and production (Biosensing Instrument Inc.), and clinical testing (Clinical Microbiology Laboratory, Mayo Clinic). !