Table_1_Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS.pdf (118.8 kB)
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Table_1_Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS.pdf

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posted on 20.09.2019, 13:06 authored by Anna F. Lau, Robert C. Walchak, Heather B. Miller, E. Susan Slechta, Kamal Kamboj, Katherine Riebe, Amy E. Robertson, Jeremy J. Gilbreath, Kaitlin F. Mitchell, Meghan A. Wallace, Alexandra L. Bryson, Joan-Miquel Balada-Llasat, Amanda Bulman, Blake W. Buchan, Carey-Ann D. Burnham, Susan Butler-Wu, Uma Desai, Christopher D. Doern, Kimberly E. Hanson, Christina M. Henderson, Markus Kostrzewa, Nathan A. Ledeboer, Thomas Maier, Preeti Pancholi, Audrey N. Schuetz, Gongyi Shi, Nancy L. Wengenack, Sean X. Zhang, Adrian M. Zelazny, Karen M. Frank
Objectives

Rapid and accurate mold identification is critical for guiding therapy for mold infections. MALDI-TOF MS has been widely adopted for bacterial and yeast identification; however, few clinical laboratories have applied this technology for routine mold identification due to limited database availability and lack of standardized processes. Here, we evaluated the versatility of the NIH Mold Database in a multicenter evaluation.

Methods

The NIH Mold Database was evaluated by eight US academic centers using a solid media extraction method and a challenge set of 80 clinical mold isolates. Multiple instrument parameters important for spectra optimization were evaluated, leading to the development of two specialized acquisition programs (NIH method and the Alternate-B method).

Results

A wide range in performance (33–77%) was initially observed across the eight centers when routine spectral acquisition parameters were applied. Use of the NIH or the Alternate-B specialized acquisition programs, which are different than those used routinely for bacterial and yeast spectral acquisition (MBT_AutoX), in combination with optimized instrument maintenance, improved performance, illustrating that acquisition parameters may be one of the key limiting variable in achieving successful performance.

Conclusion

Successful mold identification using the NIH Database for MALDI-TOF MS on Biotyper systems was demonstrated across multiple institutions for the first time following identification of critical program parameters combined with instrument optimization. This significantly advances our potential to implement MALDI-TOF MS for mold identification across many institutions. Because instrument variability is inevitable, development of an instrument performance standard specific for mold spectral acquisition is suggested to improve reproducibility across instruments.

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