Subtyping of
            <i>Staphylococcus</i>
            spp. Based upon MALDI‐TOF MS Data Analysis

Xu, Zhen; Olkun, Ali; Vranckx, Katleen; Mkrtchyan, Hermine V.; Shah, Ajit J.; Pot, Bruno; Cutler, Ronald R.; Shah, Haroun N.

doi:10.1002/9781118960226.ch22

Cited by 1 publication

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“…A total of 411 isolates were recovered from the general public and various environmental sites in London. The MALDI-TOF MS data was analysed using the software BioNumerics (Applied Maths; Vranckx, De Bruyne and Pot, 2017) and evidence of clustering within the same sites were apparent with the human hand being the reservoir (Xu et al, 2017;). Nineteen species of staphylococci were identified, most of which were coagulase negative.…”

Section: Establishing Maldi-tof Ms In Clinical Microbiologymentioning

confidence: 99%

MALDI-TOF MS and currently related proteomic technologies in reconciling bacterial systematics.

Shah¹,

Shah²,

Belgacem³

et al. 2020

Trends in the Systematics of Bacteria and Fungi

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This book chapter presents an overview and discussion of the use of MALDI-TOF MS for fungal identification. The major known limitations of the technique for fungal taxonomy, and how to overcome these, are also discussed. Moreover, this should guarantee that spectra deposited in such MALDI-TOF MS database would remain public, preferably in open free access. To avoid misidentification, these stored spectra must be curated and based on well-established standard operating procedures. The number of spectra available within species needs to be increased to accommodate the diversity and geographic differences, unique strain traits and the varied culture conditions and procedures in order to establish a single public and open access MALDITOF MS database. This could then be used with metadata analysis and artificial intelligence algorithms, to provide reliable fungal identification.

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Section: Establishing Maldi-tof Ms In Clinical Microbiologymentioning

confidence: 99%