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Ribosomal subunit protein typing using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification and discrimination of Aspergillus species

Overview of attention for article published in BMC Microbiology, April 2017
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Title
Ribosomal subunit protein typing using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification and discrimination of Aspergillus species
Published in
BMC Microbiology, April 2017
DOI 10.1186/s12866-017-1009-3
Pubmed ID
Authors

Sayaka Nakamura, Hiroaki Sato, Reiko Tanaka, Yoko Kusuya, Hiroki Takahashi, Takashi Yaguchi

Abstract

Accurate identification of Aspergillus species is a very important subject. Mass spectral fingerprinting using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is generally employed for the rapid identification of fungal isolates. However, the results are based on simple mass spectral pattern-matching, with no peak assignment and no taxonomic input. We propose here a ribosomal subunit protein (RSP) typing technique using MALDI-TOF MS for the identification and discrimination of Aspergillus species. The results are concluded to be phylogenetic in that they reflect the molecular evolution of housekeeping RSPs. The amino acid sequences of RSPs of genome-sequenced strains of Aspergillus species were first verified and compared to compile a reliable biomarker list for the identification of Aspergillus species. In this process, we revealed that many amino acid sequences of RSPs (about 10-60%, depending on strain) registered in the public protein databases needed to be corrected or newly added. The verified RSPs were allocated to RSP types based on their mass. Peak assignments of RSPs of each sample strain as observed by MALDI-TOF MS were then performed to set RSP type profiles, which were then further processed by means of cluster analysis. The resulting dendrogram based on RSP types showed a relatively good concordance with the tree based on β-tubulin gene sequences. RSP typing was able to further discriminate the strains belonging to Aspergillus section Fumigati. The RSP typing method could be applied to identify Aspergillus species, even for species within section Fumigati. The discrimination power of RSP typing appears to be comparable to conventional β-tubulin gene analysis. This method would therefore be suitable for species identification and discrimination at the strain to species level. Because RSP typing can characterize the strains within section Fumigati, this method has potential as a powerful and reliable tool in the field of clinical microbiology.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 18%
Researcher 6 16%
Student > Master 4 11%
Student > Ph. D. Student 4 11%
Student > Doctoral Student 3 8%
Other 5 13%
Unknown 9 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 18%
Biochemistry, Genetics and Molecular Biology 7 18%
Medicine and Dentistry 5 13%
Chemistry 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 4 11%
Unknown 12 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 April 2017.
All research outputs
#14,934,072
of 22,968,808 outputs
Outputs from BMC Microbiology
#1,610
of 3,206 outputs
Outputs of similar age
#183,659
of 309,828 outputs
Outputs of similar age from BMC Microbiology
#29
of 62 outputs
Altmetric has tracked 22,968,808 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,206 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 309,828 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.