|Title:||Ribosomal protein biomarkers provide root nodule bacterial identification by MALDI-TOF MS|
|Authors :||Ziegler, Dominik|
Pothier, Joël F.
Kouakou Fossou, Romain
de Meyer, Sofie
|Published in :||Applied Microbiology and Biotechnology|
|Publisher / Ed. Institution :||Springer|
|Publisher / Ed. Institution:||Berlin|
|License (according to publishing contract) :||Licence according to publishing contract|
|Type of review:||Peer review (Publication)|
|Subjects :||Bacterial fingerprints; Phylogeny; Rhizobia; Legume nodules; GEBA-RNB; Cluster analysis|
|Subject (DDC) :||570: Biology|
|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.|
|Departement:||Life Sciences and Facility Management|
|Organisational Unit:||Institute of Natural Resource Sciences (IUNR)|
|Publication type:||Article in scientific Journal|
|Published as part of the ZHAW project :||MALDI-TOF MS for microorganism identification: from pattern recognition towards marker based approaches|
|Appears in Collections:||Publikationen Life Sciences und Facility Management|
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