Levasseur Marceau, Hebra Téo, Elie Nicolas, Guérineau Vincent, Touboul David, Eparvier Véronique
CNRS, Institut de Chimie des Substances Naturelles (ICSN), UPR 2301, Université Paris-Saclay, Avenue de la Terrasse, 91 198 Gif-sur-Yvette, France.
Laboratoire de Chimie Moléculaire (LCM), CNRS UMR 9168, École Polytechnique, Institut Polytechnique de Paris, Route de Saclay, CEDEX, 91 128 Palaiseau, France.
Microorganisms. 2022 Apr 17;10(4):831. doi: 10.3390/microorganisms10040831.
During the last two decades, MALDI-ToF mass spectrometry has become an efficient and widely-used tool for identifying clinical isolates. However, its use for classification and identification of environmental microorganisms remains limited by the lack of reference spectra in current databases. In addition, the interpretation of the classical dendrogram-based data representation is more difficult when the quantity of taxa or chemotaxa is larger, which implies problems of reproducibility between users. Here, we propose a workflow including a concurrent standardized protein and lipid extraction protocol as well as an analysis methodology using the reliable spectra comparison algorithm available in MetGem software. We first validated our method by comparing protein fingerprints of highly pathogenic bacteria from the Robert Koch Institute (RKI) open database and then implemented protein fingerprints of environmental isolates from French Guiana. We then applied our workflow for the classification of a set of protein and lipid fingerprints from environmental microorganisms and compared our results to classical genetic identifications using 16S and ITS region sequencing for bacteria and fungi, respectively. We demonstrated that our protocol allowed general classification at the order and genus level for bacteria whereas only the Botryosphaeriales order can be finely classified for fungi.
在过去二十年中,基质辅助激光解吸/电离飞行时间质谱(MALDI-ToF MS)已成为鉴定临床分离株的一种高效且广泛使用的工具。然而,由于当前数据库中缺乏参考光谱,其在环境微生物分类和鉴定方面的应用仍然受到限制。此外,当分类单元或化学分类单元的数量较多时,基于传统树形图的数据表示的解释会更加困难,这意味着不同用户之间存在可重复性问题。在此,我们提出了一种工作流程,包括并行的标准化蛋白质和脂质提取方案以及使用MetGem软件中可用的可靠光谱比较算法的分析方法。我们首先通过比较来自罗伯特·科赫研究所(RKI)开放数据库的高致病性细菌的蛋白质指纹图谱来验证我们的方法,然后对法属圭亚那环境分离株的蛋白质指纹图谱进行分析。然后,我们将我们的工作流程应用于一组环境微生物的蛋白质和脂质指纹图谱的分类,并将我们的结果与分别使用16S和ITS区域测序对细菌和真菌进行的经典基因鉴定结果进行比较。我们证明,我们的方案能够对细菌进行目和属水平的一般分类,而对于真菌,只有葡萄座腔菌目可以进行精细分类。