Institute of Physical Chemistry, Friedrich Schiller University Jena, Helmholtzweg 4, Jena D-07743, Germany.
InfectoGnostics Research Campus Jena, Philosophenweg 7, Jena D-07743, Germany.
Anal Chem. 2024 Oct 1;96(39):15702-15710. doi: 10.1021/acs.analchem.4c03280. Epub 2024 Sep 18.
In the clinical environment, the identification of phylogenetic closely related genera and species like and is challenging. Both genera contain representatives of pathogenic and nonpathogenic species that need to be distinguished for a proper diagnostic read-out. Therefore, reliable and accurate detection methods must be employed for the correct identification of these genera and species. Despite their high pathogenicity, clostridial infections and food contaminations present significant challenges due to their unique cultivation conditions and developmental needs. Therefore, in many diagnostic protocols, the toxins are used for microbiological documentation. However, the applied laboratory methods suffer in accuracy, sometimes require large bacterial loads to provide reliable results, and cannot differentiate pathogenic from nonpathogenic strains. Here, Raman spectroscopy was employed to create an extensive Raman database consisting of pathogenic and nonpathogenic and species. These genera, as well as representatives of and were specifically selected for their phylogenetic relation, cultivation conditions, and metabolic activity. A chemometric evaluation of the Raman spectra of single vegetative cells revealed a high discriminating power at the genus level. However, bacilli are considerably easier to classify at the species level than clostridia. The discrimination between the genera and species was based on their phylogeny and not their aerobic and anaerobic cultivation conditions. These encouraging results demonstrated that Raman spectroscopy coupled with chemometrics is a robust and helpful method for differentiating species from , , and species. This approach has the potential to be a valuable tool in clinical diagnostics.
在临床环境中，鉴定与 和 等具有密切亲缘关系的属和种具有挑战性。这两个属都包含有致病性和非致病性物种的代表，需要加以区分，以便做出正确的诊断。因此，必须采用可靠和准确的检测方法来正确识别这些属和种。尽管梭菌具有高度的致病性，但由于其独特的培养条件和发育需求，其感染和食物污染仍然存在很大的挑战。因此，在许多诊断方案中，毒素被用于微生物学记录。然而，应用的实验室方法在准确性方面存在不足，有时需要大量的细菌负荷才能提供可靠的结果，并且无法区分致病性和非致病性菌株。在这里，我们使用拉曼光谱技术创建了一个由致病性和非致病性 和 物种组成的广泛的拉曼数据库。这些属以及 和 的代表被特别选择，是因为它们的系统发育关系、培养条件和代谢活性。对单个营养细胞的拉曼光谱进行化学计量学评估，结果表明在属水平上具有很高的区分能力。然而，与梭菌相比，杆菌在种水平上更容易分类。属和种之间的区分是基于它们的系统发育，而不是它们的需氧和厌氧培养条件。这些令人鼓舞的结果表明，拉曼光谱结合化学计量学是一种强大而有用的方法，可以区分 种与 、 和 种。这种方法有可能成为临床诊断中的一种有价值的工具。
