Beltrán-Rosel Antonio, Palomar Ana M, Goñi Pilar, Benito Rafael, López-Alonso Beatriz, Ligero-López Jorge, Boquera-Albert Amparo, Ducons-Márquez María, Oteo Jose A
Servicio de Microbiología Clínica y Parasitología, Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain; Departamento de Microbiología, Pediatría, Radiología y Salud Pública, Facultad de Medicina, Universidad de Zaragoza, Zaragoza, Spain; Instituto Universitario de Investigación en Ciencias Ambientales de Aragón (IUCA), Zaragoza, Spain.
Departamento de Enfermedades Infecciosas, Centro de Rickettsiosis y Enfermedades Transmitidas por Artrópodos Vectores (CRETAV), Hospital San Pedro-Centro de Investigación Biomédica de La Rioja (CIBIR), Logroño, Spain.
Enferm Infecc Microbiol Clin (Engl Ed). 2025 Aug-Sep;43(7):396-401. doi: 10.1016/j.eimce.2024.12.017.
Tick bites are a growing public health concern as ticks act as vectors for various pathogens. Accurate tick species identification is vital to assess disease exposure and determine prophylactic measures. MALDI-TOF MS has emerged as a promising tool for precise tick identification. This study evaluates the performance of MALDI-TOF MS in clinical tick identification, focusing on how the number of peaks present in the reference and sample spectra influences the accuracy of the identification process.
Between April 2022 and March 2024, 42 tick specimens sent to our hospital were identified using MALDI-TOF MS. The reference spectrum was created with 70 peaks and expanded to include versions with 40, 100, and 130 peaks using Compass Biotyper Explorer v4.1.1. Spectra were analyzed with Flex Analysis v3.4 software. Identification was performed by querying sample spectra against these libraries, with a log score value (LSV)≥1.70 considered accurate for species identification.
Libraries with 40, 100, and 130 peaks improved identification scores for several species, though the degree varied. The highest scores were achieved in 64.3% of specimens. Combining all libraries as a single database yielded LSVs above the 1.70 threshold for all specimens.
The study highlights the species-specific nature of peak importance in spectra and underscores the potential of MALDI-TOF MS as a rapid and accurate tool for tick identification in clinical settings. Enhanced spectral libraries could further improve this technique, aiding timely clinical decisions and effective management of tick bites.
蜱虫叮咬作为各种病原体的传播媒介，日益成为公共卫生关注的焦点。准确识别蜱虫种类对于评估疾病暴露风险和确定预防措施至关重要。基质辅助激光解吸电离飞行时间质谱（MALDI-TOF MS）已成为精确识别蜱虫的一种有前景的工具。本研究评估了MALDI-TOF MS在临床蜱虫识别中的性能，重点关注参考光谱和样本光谱中峰的数量如何影响识别过程的准确性。
在2022年4月至2024年3月期间，使用MALDI-TOF MS对送至我院的42份蜱虫标本进行了识别。参考光谱由70个峰创建，并使用Compass Biotyper Explorer v4.1.1扩展为包含40、100和130个峰的版本。使用Flex Analysis v3.4软件对光谱进行分析。通过将样本光谱与这些库进行比对来进行识别，对数得分值（LSV）≥1.70被认为物种识别准确。
包含40、100和130个峰的库提高了几种蜱虫的识别分数，尽管程度有所不同。在64.3%的标本中获得了最高分数。将所有库组合成一个单一数据库，所有标本的LSV均高于1.70阈值。
该研究突出了光谱中峰重要性的物种特异性，并强调了MALDI-TOF MS作为临床环境中蜱虫识别的快速准确工具的潜力。增强的光谱库可以进一步改进该技术，有助于及时做出临床决策和有效管理蜱虫叮咬。
