Identification to species level of live single microalgal cells from plankton samples with matrix-free laser/desorption ionization mass spectrometry

被引:14
|
作者
Baumeister, Tim U. H. [1 ]
Vallet, Marine [1 ]
Kaftan, Filip [2 ]
Guillou, Laure [3 ]
Svatos, Ales [2 ]
Pohnert, Georg [1 ,4 ]
机构
[1] Max Planck Inst Chem Ecol, Max Planck Fellow Grp Plankton Community Interact, Hans Knoll Str 8, D-07745 Jena, Germany
[2] Max Planck Inst Chem Ecol, Res Grp Mass Spectrometry Prote, Hans Knoll Str 8, D-07745 Jena, Germany
[3] Sorbonne Univ, CNRS, UMR7144 Adaptat & Divers Milieu Marin Ecol Marine, SBR, F-29680 Roscoff, France
[4] Friedrich Schiller Univ Jena, Inst Inorgan & Analyt Chem, Dept Bioorgan Analyt, Lessingstr 8, D-07743 Jena, Germany
关键词
Microalgal identification; Live single-cell mass spectrometry; Matrix-free laser desorption; ionization high-resolution mass spectrometry; Spectral pattern matching; Spectrum similarity; Metabolic fingerprinting; CLASSIFICATION;
D O I
10.1007/s11306-020-1646-7
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Introduction Marine planktonic communities are complex microbial consortia often dominated by microscopic algae. The taxonomic identification of individual phytoplankton cells usually relies on their morphology and demands expert knowledge. Recently, a live single-cell mass spectrometry (LSC-MS) pipeline was developed to generate metabolic profiles of microalgae. Objective Taxonomic identification of diverse microalgal single cells from collection strains and plankton samples based on the metabolic fingerprints analyzed with matrix-free laser desorption/ionization high-resolution mass spectrometry. Methods Matrix-free atmospheric pressure laser-desorption ionization mass spectrometry was performed to acquire single-cell mass spectra from collection strains and prior identified environmental isolates. The computational identification of microalgal species was performed by spectral pattern matching (SPM). Three similarity scores and a bootstrap-derived confidence score were evaluated in terms of their classification performance. The effects of high and low-mass resolutions on the classification success were evaluated. Results Several hundred single-cell mass spectra from nine genera and nine species of marine microalgae were obtained. SPM enabled the identification of single cells at the genus and species level with high accuracies. The receiver operating characteristic (ROC) curves indicated a good performance of the similarity measures but were outperformed by the bootstrap-derived confidence scores. Conclusion This is the first study to solve taxonomic identification of microalgae based on the metabolic fingerprints of the individual cell using an SPM approach.
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页数:10
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