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Ribosomal protein biomarkers provide root nodule bacterial identification by MALDI-TOF MS
Journal article   Open access   Peer reviewed

Ribosomal protein biomarkers provide root nodule bacterial identification by MALDI-TOF MS

D. Ziegler, J.F. Pothier, J. Ardley, R.K. Fossou, V. Pflüger, S. De Meyer, G. Vogel, M. Tonolla, J. Howieson, W. Reeve, …
Applied Microbiology and Biotechnology, Vol.99(13), pp.5547-5562
2015
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Abstract

Accurate identification of soil bacteria that form nitrogen-fixing associations with legume crops is challenging given the phylogenetic diversity of root nodule bacteria (RNB). The labor-intensive and time-consuming 16S ribosomal RNA (rRNA) sequencing and/or multilocus sequence analysis (MLSA) of conserved genes so far remain the favored molecular tools to characterize symbiotic bacteria. With the development of mass spectrometry (MS) as an alternative method to rapidly identify bacterial isolates, we recently showed that matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) can accurately characterize RNB found inside plant nodules or grown in cultures. Here, we report on the development of a MALDI-TOF RNB-specific spectral database built on whole cell MS fingerprints of 116 strains representing the major rhizobial genera. In addition to this RNB-specific module, which was successfully tested on unknown field isolates, a subset of 13 ribosomal proteins extracted from genome data was found to be sufficient for the reliable identification of nodule isolates to rhizobial species as shown in the putatively ascribed ribosomal protein masses (PARPM) database. These results reveal that data gathered from genome sequences can be used to expand spectral libraries to aid the accurate identification of bacterial species by MALDI-TOF MS.

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Collaboration types
Domestic collaboration
International collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.97 Plant Pathology
3.97.892 Rhizobium-Legume Symbiosis
Web Of Science research areas
Biotechnology & Applied Microbiology
ESI research areas
Biology & Biochemistry
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