↓ Skip to main content

Decision criteria for MALDI-TOF MS-based identification of filamentous fungi using commercial and in-house reference databases

Overview of attention for article published in BMC Microbiology, January 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
82 Dimensions

Readers on

mendeley
94 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Decision criteria for MALDI-TOF MS-based identification of filamentous fungi using commercial and in-house reference databases
Published in
BMC Microbiology, January 2017
DOI 10.1186/s12866-017-0937-2
Pubmed ID
Authors

Anne-Cécile Normand, Carole Cassagne, Magali Gautier, Pierre Becker, Stéphane Ranque, Marijke Hendrickx, Renaud Piarroux

Abstract

Several Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry protocols, which differ in identification criteria, have been developed for mold and dermatophyte identification. Currently, the most widely used approach is Bruker technology, although no consensus concerning the log(score) threshold has been established. Furthermore, it remains unknown how far increasing the number of spots to compare results might improve identification performance. In this study, we used in-house and Bruker reference databases as well as a panel of 422 isolates belonging to 126 species to test various thresholds. Ten distinct identification algorithms requiring one to four spots were tested. Our findings indicate that optimal results were obtained by applying a decisional algorithm in which only the highest score of four spots was taken into account with a 1.7 log(score) threshold. Testing the entire panel enabled identification of 87.41% (in-house database) and 35.15% (Bruker database) of isolates, with a positive predictive value (PPV) of 1 at the genus level for both databases as well as 0.89 PPV (in-house database) and 0.72 PPV (Bruker database) at the species level. Applying the same rules to the isolates for which the species were represented by at least three strains in the database enabled identification of 92.1% (in-house database) and 46.6% (Bruker database) of isolates, with 1 PPV at the genus level for both databases as well as 0.95 PPV (in-house database) and 0.93 PPV (Bruker database) at the species level. Depositing four spots per extract and lowering the threshold to 1.7, a threshold which is notably lower than that recommended for bacterial identification, decreased the number of unidentified specimens without altering the reliability of the accepted results. Nevertheless, regardless of the criteria used for mold and dermatophyte identification, commercial databases require optimization.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 94 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 18%
Researcher 12 13%
Student > Ph. D. Student 10 11%
Student > Bachelor 7 7%
Student > Doctoral Student 6 6%
Other 15 16%
Unknown 27 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 17%
Immunology and Microbiology 15 16%
Medicine and Dentistry 13 14%
Biochemistry, Genetics and Molecular Biology 9 10%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Other 11 12%
Unknown 27 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 25 July 2017.
All research outputs
#18,560,904
of 22,988,380 outputs
Outputs from BMC Microbiology
#2,256
of 3,206 outputs
Outputs of similar age
#310,754
of 420,336 outputs
Outputs of similar age from BMC Microbiology
#34
of 44 outputs
Altmetric has tracked 22,988,380 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% 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 15th percentile – i.e., 15% 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 420,336 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.