School of Mathematical and Natural Sciences, Arizona State University, Phoenix, Arizona 85069, USA.
Mass Spectrom Rev. 2013 May-Jun;32(3):188-217. doi: 10.1002/mas.21359. Epub 2012 Sep 19.
Since the advent of the use of matrix-assisted laser desorption/ionization (MALDI) time-of-flight mass spectrometry (TOF MS) as a tool for microbial characterization, efforts to increase the taxonomic resolution of the approach have been made. The rapidity and efficacy of the approach have suggested applications in counter-bioterrorism, prevention of food contamination, and monitoring the spread of antibiotic-resistant bacteria. Strain-level resolution has been reported with diverse bacteria, using library-based and bioinformatics-enabled approaches. Three types of characterization at the strain level have been reported: strain categorization, strain differentiation, and strain identification. Efforts to enhance the library-based approach have involved sample pre-treatment and data reduction strategies. Bioinformatics approaches have leveraged the ever-increasing amount of publicly available genomic and proteomic data to attain strain-level characterization. Bioinformatics-enabled strategies have facilitated strain characterization via intact biomarker identification, bottom-up, and top-down approaches. Rigorous quantitative and advanced statistical analyses have fostered success at the strain level with both approaches. Library-based approaches can be limited by effects of sample preparation and culture conditions on reproducibility, whereas bioinformatics-enabled approaches are typically limited to bacteria, for which genetic and/or proteomic data are available. Biological molecules other than proteins produced in strain-specific manners, including lipids and lipopeptides, might represent other avenues by which strain-level resolution might be attained. Immunological and lectin-based chemistries have shown promise to enhance sensitivity and specificity. Whereas the limits of the taxonomic resolution of MALDI TOF MS profiling of bacteria appears bacterium-specific, recent data suggest that these limits might not yet have been reached.
自基质辅助激光解吸/电离（MALDI）飞行时间质谱（TOF MS）作为微生物特征分析工具问世以来，人们一直在努力提高该方法的分类分辨率。该方法的快速性和有效性使其在反生物恐怖主义、预防食物污染和监测抗生素耐药菌传播方面得到了应用。使用基于文库和生物信息学的方法，已经报道了多种细菌的菌株水平分辨率。已经报道了三种菌株水平的特征化类型：菌株分类、菌株分化和菌株鉴定。为了增强基于文库的方法，已经涉及了样品预处理和数据减少策略。生物信息学方法利用了越来越多的公开基因组和蛋白质组数据，以实现菌株水平的特征化。生物信息学方法通过完整生物标志物的识别、自下而上和自上而下的方法，促进了菌株特征化。严格的定量和先进的统计分析促进了两种方法在菌株水平上的成功。基于文库的方法可能会受到样品制备和培养条件对重现性的影响，而生物信息学方法通常仅限于具有遗传和/或蛋白质组数据的细菌。除了以菌株特异性方式产生的蛋白质之外的生物分子，包括脂质和脂肽，可能代表获得菌株水平分辨率的其他途径。免疫和凝集素化学已显示出提高灵敏度和特异性的潜力。尽管 MALDI TOF MS 细菌分析的分类分辨率的限制似乎是细菌特异性的，但最近的数据表明，这些限制可能尚未达到。
