微生物工程:微生物捕获和检测

L. Powers, C. Lloyd, H.-Y. Mason, M. Dice, R. Tingy, C. Estes, A. Duncan, B. Wade, W. Ellis
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引用次数: 5

摘要

只提供摘要形式。最近发生的微生物污染造成的死亡,特别是食品中的微生物污染,也包括水和空气中的微生物污染,最近生物战/恐怖主义的威胁,以及结核病等疾病的重新出现,都强调了对微生物污染进行快速和准确评估的重要性。此外,无菌表面,如医疗和外科器械和装置表面的微生物污染会造成相当大的危险。利用前沿技术的独特组合,微生物捕获芯片和手持式原型检测器已经开发出来,能够对病原体(包括孢子)和外毒素的环境进行统计采样,识别特定的病原体/外毒素,并确定细胞活力。该系统足够灵敏,可以在几分钟内检测到极低水平的传染性细菌[/spl sim/20个细胞/平方厘米]。微生物捕获技术是基于铁获取和真核受体粘附策略的分子识别和发病机制。这些非抗体的配体以图案阵列的形式连接在传感器芯片上。除了对环境进行统计采样外,还可以根据哪些配体与微生物结合来鉴定病原体。捕获事件使用细胞和孢子的固有荧光来检测,例如来自代谢物、氨基酸和其他特定细胞成分的荧光。该多波长荧光检测装置集成了传感器芯片的并行“读出”,并采用模式识别算法进行病原体识别。该系统的灵敏度比电流场传感器高几个数量级,速度也比电流场传感器快几个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microbioengineering: microbe capture and detection
Summary form only given. Recent deaths from outbreaks of microbial contamination particularly in foods, but also in water and air, the recent threats of biological warfare/terrorism, and the re-emergence of such diseases as tuberculosis have emphasized the importance of quick and accurate assessments of microbial contamination. In addition, microbial contamination of sterile surfaces, such as those of medical and surgical instruments and devices, cause considerable danger. Using a unique combination of leading edge technologies, microbe capture chips and a hand-held prototype detector have been developed which are capable of statistically sampling the environment for pathogens [including spores] and exotoxins, identifying the specific pathogens/exotoxins, and determining cell viability. This system is sensitive enough to detect very low levels [/spl sim/20 cells/sq cm] of infectious bacteria in minutes. The microbe capture technology is based on molecular recognition and pathogenesis using iron acquisition and eukaryotic receptor adhesion strategies. These non-antibody-based ligands are tethered to the sensor chip in a patterned array. In addition to statistically sampling the environment, pathogen identification can be made based on which ligands are bound by microbes. Capture events are detected using intrinsic fluorescence of the cells and spores such as that from metabolites, amino acids, and other specific cell components. The multi-wavelength fluorescence detection device incorporates integrated parallel 'readout' of the sensor chip and employs a pattern recognition algorithm for pathogen identification. This system is both several orders of magnitude more sensitive and several orders of magnitude faster than current field sensors.
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