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

ObjectivesRapid 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 a...

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Main Authors: 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
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-09-01
Series:Frontiers in Microbiology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fmicb.2019.02098/full
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author 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
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
spellingShingle 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
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
Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS
Frontiers in Microbiology
mold
filamentous fungi
MALDI-TOF MS
rapid
identification
author_facet 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
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
author_sort Anna F. Lau
title Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS
title_short Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS
title_full Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS
title_fullStr Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS
title_full_unstemmed Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MS
title_sort multicenter study demonstrates standardization requirements for mold identification by maldi-tof ms
publisher Frontiers Media S.A.
series Frontiers in Microbiology
issn 1664-302X
publishDate 2019-09-01
description ObjectivesRapid 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.MethodsThe 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).ResultsA 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.ConclusionSuccessful 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.
topic mold
filamentous fungi
MALDI-TOF MS
rapid
identification
url https://www.frontiersin.org/article/10.3389/fmicb.2019.02098/full
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spelling doaj-3ef951886c184360935a132b521c9f312020-11-25T02:42:27ZengFrontiers Media S.A.Frontiers in Microbiology1664-302X2019-09-011010.3389/fmicb.2019.02098485592Multicenter Study Demonstrates Standardization Requirements for Mold Identification by MALDI-TOF MSAnna F. Lau0Robert C. Walchak1Heather B. Miller2E. Susan Slechta3Kamal Kamboj4Katherine Riebe5Amy E. Robertson6Jeremy J. Gilbreath7Kaitlin F. Mitchell8Meghan A. Wallace9Alexandra L. Bryson10Joan-Miquel Balada-Llasat11Amanda Bulman12Blake W. Buchan13Carey-Ann D. Burnham14Susan Butler-Wu15Uma Desai16Christopher D. Doern17Kimberly E. Hanson18Kimberly E. Hanson19Christina M. Henderson20Markus Kostrzewa21Nathan A. Ledeboer22Thomas Maier23Preeti Pancholi24Audrey N. Schuetz25Gongyi Shi26Nancy L. Wengenack27Sean X. Zhang28Adrian M. Zelazny29Karen M. Frank30Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United StatesDivision of Clinical Microbiology, Mayo Clinic, Rochester, MN, United StatesDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, United StatesDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United StatesDepartment of Pathology, Medical College of Wisconsin, Milwaukee, WI, United StatesClinical Microbiology Laboratory, Weill Cornell Medical Center/New York Presbyterian Hospital, New York, NY, United StatesDepartment of Laboratory Medicine, University of Washington, Seattle, WA, United StatesDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United StatesDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States0Department of Pathology, Virginia Commonwealth University School of Medicine, Richmond, VA, United StatesDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United States1Bruker Daltonics, Inc., Billerica, MA, United StatesDepartment of Pathology, Medical College of Wisconsin, Milwaukee, WI, United StatesDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United StatesDepartment of Laboratory Medicine, University of Washington, Seattle, WA, United StatesDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States0Department of Pathology, Virginia Commonwealth University School of Medicine, Richmond, VA, United StatesARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, United States2Department of Pathology, Division of Clinical Microbiology, The University of Utah, Salt Lake City, UT, United StatesDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United States1Bruker Daltonics, Inc., Billerica, MA, United StatesDepartment of Pathology, Medical College of Wisconsin, Milwaukee, WI, United States1Bruker Daltonics, Inc., Billerica, MA, United StatesDepartment of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, United StatesClinical Microbiology Laboratory, Weill Cornell Medical Center/New York Presbyterian Hospital, New York, NY, United States1Bruker Daltonics, Inc., Billerica, MA, United StatesDivision of Clinical Microbiology, Mayo Clinic, Rochester, MN, United StatesDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United StatesDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United StatesDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, United StatesObjectivesRapid 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.MethodsThe 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).ResultsA 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.ConclusionSuccessful 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.https://www.frontiersin.org/article/10.3389/fmicb.2019.02098/fullmoldfilamentous fungiMALDI-TOF MSrapididentification