Salbreiter Markus, Wagenhaus Annette, Rösch Petra, Popp Jürgen
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, Jena, Germany.
InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany.
Analyst. 2025 Apr 8;150(8):1652-1661. doi: 10.1039/d5an00115c.
Accurate and reliable bacterial identification at the genus and species levels is essential for effective clinical diagnostics. Pathogens such as , , , and pose significant challenges due to their unique cultivation requirements and developmental traits. Building on our previous work demonstrating the differentiation of vegetative cells from non- genera, we now aim to extend this approach to distinguish endospores of the same species. Raman spectroscopy was utilized to develop a comprehensive library of endospore spectra, encompassing both pathogenic and non-pathogenic species. This extensive dataset forms the foundation for advanced analytical capabilities. Chemometric analysis of single-endospore Raman spectra revealed significant discriminatory power across multiple hierarchical levels, facilitating the distinction between vegetative cells and endospores. Furthermore, this method enabled precise genus- and species-level classification of endospores, underscoring its potential for high-resolution bacterial endospore identification. These results highlight the versatility and efficacy of Raman spectroscopy in addressing the challenges associated with the identification of bacterial endospores in diverse clinical and environmental contexts. These findings present the first comprehensive library of endospore Raman spectra, demonstrating that Raman spectroscopy combined with chemometric analysis is a robust and reliable method for differentiating endospores of species from those of , , and . This approach holds significant promise as a precise diagnostic tool for bacterial endospore identification in clinical settings.
在属和种水平上准确可靠地鉴定细菌对于有效的临床诊断至关重要。诸如[此处原文缺失具体病原体名称]等病原体，由于其独特的培养要求和发育特性，带来了重大挑战。基于我们之前展示从非[此处原文缺失具体属名]属区分营养细胞的工作，我们现在旨在扩展这种方法以区分同一物种的芽孢。利用拉曼光谱法建立了一个包含致病和非致病物种的芽孢光谱综合库。这个广泛的数据集构成了先进分析能力的基础。对单个芽孢拉曼光谱的化学计量分析显示在多个层次水平上具有显著的鉴别能力，有助于区分营养细胞和芽孢。此外，该方法能够对芽孢进行精确的属和种水平分类，突出了其在高分辨率细菌芽孢鉴定方面的潜力。这些结果凸显了拉曼光谱法在应对不同临床和环境背景下细菌芽孢鉴定相关挑战方面的多功能性和有效性。这些发现展示了首个芽孢拉曼光谱综合库，表明拉曼光谱法结合化学计量分析是一种区分[此处原文缺失具体物种名称]物种芽孢与[此处原文缺失具体物种名称]、[此处原文缺失具体物种名称]和[此处原文缺失具体物种名称]芽孢的强大且可靠的方法。这种方法作为临床环境中细菌芽孢鉴定的精确诊断工具具有重大前景。
