Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS

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

doi:10.3389/fmicb.2019.02098

Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS

Front Microbiol. 2019 Sep 20:10:2098. doi: 10.3389/fmicb.2019.02098. eCollection 2019.

Authors

Anna F Lau¹, Robert C Walchak², Heather B Miller³, E Susan Slechta⁴, Kamal Kamboj⁵, Katherine Riebe⁶, Amy E Robertson⁷, Jeremy J Gilbreath⁸, Kaitlin F Mitchell⁹, Meghan A Wallace⁹, Alexandra L Bryson¹⁰, Joan-Miquel Balada-Llasat⁵, Amanda Bulman¹¹, Blake W Buchan⁶, Carey-Ann D Burnham⁹, Susan Butler-Wu⁸, Uma Desai¹, Christopher D Doern¹⁰, Kimberly E Hanson^{4

12}, Christina M Henderson¹, Markus Kostrzewa¹¹, Nathan A Ledeboer⁶, Thomas Maier¹¹, Preeti Pancholi⁵, Audrey N Schuetz⁷, Gongyi Shi¹¹, Nancy L Wengenack², Sean X Zhang³, Adrian M Zelazny¹, Karen M Frank¹

Affiliations

¹ Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States.
² Division of Clinical Microbiology, Mayo Clinic, Rochester, MN, United States.
³ Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
⁴ ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, United States.
⁵ Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United States.
⁶ Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, United States.
⁷ Clinical Microbiology Laboratory, Weill Cornell Medical Center/New York Presbyterian Hospital, New York, NY, United States.
⁸ Department of Laboratory Medicine, University of Washington, Seattle, WA, United States.
⁹ Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States.
¹⁰ Department of Pathology, Virginia Commonwealth University School of Medicine, Richmond, VA, United States.
¹¹ Bruker Daltonics, Inc., Billerica, MA, United States.
¹² Department of Pathology, Division of Clinical Microbiology, The University of Utah, Salt Lake City, UT, United States.

Abstract

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.

Keywords: MALDI-TOF MS; filamentous fungi; identification; mold; rapid.

Copyright © 2019 Lau, Walchak, Miller, Slechta, Kamboj, Riebe, Robertson, Gilbreath, Mitchell, Wallace, Bryson, Balada-Llasat, Bulman, Buchan, Burnham, Butler-Wu, Desai, Doern, Hanson, Henderson, Kostrzewa, Ledeboer, Maier, Pancholi, Schuetz, Shi, Wengenack, Zhang, Zelazny and Frank.