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通过基质辅助激光解吸电离飞行时间质谱对环境分离株进行菌株水平表征

Strain-Level Characterization of Environmental Isolates via MALDI-TOF-MS.

作者信息

Schwake David Otto, Sandrin Todd, Zhang Lin, Abbaszadegan Morteza

机构信息

Department of Natural Sciences, Middle Georgia State University, 100 University Pkwy, Macon, GA 31206, USA.

School of Mathematical and Natural Sciences, New College of Interdisciplinary Arts & Sciences, Arizona State University at the West Campus, 4701 W. Thunderbird Road, Glendale, AZ 85306, USA.

出版信息

Microorganisms. 2022 Dec 20;11(1):8. doi: 10.3390/microorganisms11010008.

Abstract

As a waterborne pathogen of increasing concern, techniques for cost-effective and rapid characterization of are vital. This study examines the development of a Matrix Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF-MS) analysis methodology for this microbe. First, optimal sample preparation methods for the analysis of environmental isolates via MALDI-TOF-MS were determined. These methods were then implemented to perform strain-level characterization of environmental isolates from central Arizona. Results demonstrate that a MALDI-TOF-MS method involving BCYE agar-based culturing and protein extraction-based sample preparation yield high-quality mass spectra. Twenty-eight environmental isolates originating from two separate drinking water distribution systems were analyzed. Multiple species were detected, and strain-level characterization was achieved, with 12 unique strains distinguished. In addition, isolates of , the most common species observed in the study, were correctly assigned to specific sampling sites. These results demonstrate the potential for this technique to be applied for sub-species characterization of with significant benefits over established methodologies.

摘要

作为一种日益受到关注的水传播病原体,对其进行经济高效且快速表征的技术至关重要。本研究考察了用于这种微生物的基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF-MS)分析方法的开发。首先,确定了通过MALDI-TOF-MS分析环境分离株的最佳样品制备方法。然后将这些方法用于对亚利桑那州中部的环境分离株进行菌株水平的表征。结果表明,一种涉及基于BCYE琼脂培养和基于蛋白质提取的样品制备的MALDI-TOF-MS方法可产生高质量的质谱图。对来自两个独立饮用水分配系统的28株环境分离株进行了分析。检测到多个物种,并实现了菌株水平的表征,区分出12个独特菌株。此外,该研究中观察到的最常见物种——嗜肺军团菌的分离株被正确地分配到特定的采样地点。这些结果证明了该技术用于嗜肺军团菌亚种表征的潜力,与既定方法相比具有显著优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d77/9863361/1ee9e8acfbd3/microorganisms-11-00008-g001.jpg

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