School of Engineering, University of Vermont, Burlington, Vermont 05405, USA.
J Appl Physiol (1985). 2013 Jun;114(11):1544-9. doi: 10.1152/japplphysiol.00099.2013. Epub 2013 Mar 21.
Bacterial pneumonia is one of the leading causes of disease-related morbidity and mortality in the world, in part because the diagnostic tools for pneumonia are slow and ineffective. To improve the diagnosis success rates and treatment outcomes for bacterial lung infections, we are exploring the use of secondary electrospray ionization-mass spectrometry (SESI-MS) breath analysis as a rapid, noninvasive method for determining the etiology of lung infections in situ. Using a murine lung infection model, we demonstrate that SESI-MS breathprints can be used to distinguish mice that are infected with one of seven lung pathogens: Haemophilus influenzae, Klebsiella pneumoniae, Legionella pneumophila, Moraxella catarrhalis, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae, representing the primary causes of bacterial pneumonia worldwide. After applying principal components analysis, we observed that with the first three principal components (primarily comprised of data from 14 peaks), all infections were separable via SESI-MS breathprinting (P < 0.0001). Therefore, we have shown the potential of this SESI-MS approach for rapidly detecting and identifying acute bacterial lung infections in situ via breath analysis.
细菌性肺炎是导致全球发病率和死亡率的主要原因之一,部分原因是肺炎的诊断工具缓慢且低效。为了提高细菌性肺部感染的诊断成功率和治疗效果,我们正在探索使用二次电喷雾电离-质谱(SESI-MS)呼吸分析作为一种快速、非侵入性的方法,用于原位确定肺部感染的病因。使用小鼠肺部感染模型,我们证明 SESI-MS 呼吸谱可用于区分感染七种肺部病原体的小鼠:流感嗜血杆菌、肺炎克雷伯菌、嗜肺军团菌、卡他莫拉菌、铜绿假单胞菌、金黄色葡萄球菌和肺炎链球菌,这些病原体是全球细菌性肺炎的主要病因。在应用主成分分析后,我们观察到,在前三个主成分(主要由 14 个峰的数据组成)中,所有感染都可以通过 SESI-MS 呼吸谱进行分离(P < 0.0001)。因此,我们已经证明了这种 SESI-MS 方法通过呼吸分析快速检测和识别原位急性细菌性肺部感染的潜力。