Background

The majority of Legionnaires’ disease cases is attributed to Legionella pneumophila serogroup 1 (Lp1). Moreover, pathogenicity loci lvh and rtxA were associated with the ability of Lp strains to cause the disease. Consequently, except from serogroup assignment the detection of the aforementioned virulence genes during Legionella detection in water samples, could help environmental risk assessment and the implementation of targeted control measures.

Aim

To establish and validate a rapid and robust MALDI-TOF MS-based method for the assignment of Lp isolates to serogroup, and identify distinct peak biomarkers for the detection of lvh and rtxA loci during environmental investigations.

Method

Fifteen reference strains and 150 Lp environmental isolates (70 Lp1 and 80 Lp2-15 strains) were used. All strains were PCR-tested for the presence of lvh and rtxA loci. Independent training and validation strain sets were constituted and all strains were protein-extracted and submitted to MALDI-TOF MS analysis. The raw spectra of the training set strains obtained, were introduced into the Mass-Up software platform for biomarker detection, for both serogroup assignment and pathogenicity loci detection. Validation of the assigned biomarkers followed using the validation set strains.

Results

For serogroup assignment, the Mass-up analysis indicated five potential discriminating peaks and correctly classified 115 out of 132 validation set strains, displaying sensitivity of 87.5%, specificity of 86.7% and 87.1% accuracy. Concerning the pathogenicity loci detection, the Mass-up analysis indicated two ion peaks for rtxA locus discrimination and one peak for lvh locus discrimination. Concerning the lvh virulence gene, the algorithm correctly classified 113 out of 137 positive and all negative strains 14 in total-showing sensitivity of 82.5%, specificity of 100.% and 84.1% accuracy. For rtxA locus, 134 out of 134 positive and 14 out of 17 negative strains were correctly classified with sensitivity of 100%, specificity of 76.5% and 97.4% accuracy.

Conclusion

MALDI-TOF MS displayed good performance for Lp serogroup assignment and detection of the lvh and rtxA virulence genes. These findings could contribute to the rapid, inexpensive and comprehensive case investigation and risk assessment. Further studies are needed to standardize and evaluate the method using the direct target plate protein profiling instead of protein extraction in order to simplify the protocol. .

中文翻译：

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使用MALDI-TOF MS对嗜肺军团杆菌环境分离株进行血清分型和病原性基因座检测。

背景

多数退伍军人病病例归因于嗜肺军团菌血清群1（Lp 1）。此外，致病性位点lvh和rtx A与Lp菌株引起疾病的能力有关。因此，除了血清组分配外，在水样中进行军团菌检测期间检测上述毒力基因，可能有助于环境风险评估和有针对性的控制措施的实施。

目标

建立并验证一种快速可靠的基于MALDI-TOF MS的方法，用于将Lp分离物分配至血清群，并在环境研究过程中确定用于检测lvh和rtx A基因座的独特峰生物标记。

方法

使用了15个参考菌株和150 Lp的环境分离株（70 Lp 1和80 Lp 2-15菌株）。对所有菌株进行PCR测试以检测lvh和rtx A基因座的存在。组成独立的训练和验证菌株集，并对所有菌株进行蛋白质提取，然后进行MALDI-TOF MS分析。将获得的训练集菌株的原始光谱引入到Mass-Up软件平台中，以进行生物标记物检测，以进行血清群分配和致病性基因座检测。使用验证集菌株验证分配的生物标记。

结果

对于血清群分配，Mass-up分析显示了五个潜在的区分峰，并在132个验证集菌株中正确分类了115个，显示出87.5％的灵敏度，86.7％的特异性和87.1％的准确度。关于致病性基因座检测，Mass-up分析表明，rtx A基因座识别有两个离子峰，lvh基因座识别有一个离子峰。关于lvh毒力基因，该算法正确分类了137个阳性和所有阴性菌株14中的113个，总敏感性为82.5％，特异性为100.％，准确度为84.1％。对于rtx正确分类了134个阳性菌株中的134个和17个阴性菌株中的14个基因座，敏感性为100％，特异性为76.5％，准确度为97.4％。

结论

MALDI-TOF MS在Lp血清群分配和lvh和rtx A毒力基因检测中表现出良好的性能。这些发现可能有助于快速，廉价和全面的案件调查和风险评估。需要进一步的研究来标准化和评估使用直接靶板蛋白谱分析而不是蛋白质提取的方法，以简化方案。。