TY - JOUR
T1 - Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories
AU - Kalinski, Jarmo Charles
AU - Ruiz Brandão da Costa, Bruno
AU - Schramm, Tilman
AU - Buckett, Lance R.
AU - Carlson, Laura T.
AU - Coffey, Nicole R.
AU - Damiani, Tito
AU - Dechent, Elias
AU - Abiead, Yasin El
AU - Heuckeroth, Steffen
AU - Jennings, Elaine K.
AU - Kaesler, Jan
AU - Stock, Naomi L.
AU - Orme, Alice M.
AU - Torres, Ralph R.
AU - Trojahn, Sara
AU - Whelton, Helen L.
AU - Yan, Yingfei
AU - Aron, Allegra T.
AU - Boiteau, Rene M.
AU - Bull, Ian D.
AU - Dorrestein, Pieter C.
AU - Dang, Duc Huy
AU - Evershed, Richard P.
AU - Gledhill, Marta
AU - Gleixner, Gerd
AU - Haas, Andreas F.
AU - Hansen, Martin
AU - Harder, Tilmann
AU - Hopmans, Ellen C.
AU - Ingalls, Anitra E.
AU - Karst, Uwe
AU - Kew, William
AU - Kido Soule, Melissa
AU - Koch, Boris P.
AU - Kujawinski, Elizabeth B.
AU - Lechtenfeld, Oliver J.
AU - Longnecker, Krista
AU - Pluskal, Tomáš
AU - Pohnert, Georg
AU - Redman, Zachary C.
AU - Rivas-Ubach, Albert
AU - Schmitt-Kopplin, Philippe
AU - Singer, Gabriel
AU - Tebben, Jan
AU - Tomco, Patrick L.
AU - Ward, Nicholas D.
AU - Aluwihare, Lihini I.
AU - Simon, Carsten
AU - Hawkes, Jeffrey
AU - Petras, Daniel
N1 - Publisher Copyright:
© 2026 The Authors. Published by American Chemical Society
PY - 2026/2/17
Y1 - 2026/2/17
N2 - Non-targeted liquid chromatography tandem high-resolution mass spectrometry (LC–MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC–MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and feature-based molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC–MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.
AB - Non-targeted liquid chromatography tandem high-resolution mass spectrometry (LC–MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC–MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and feature-based molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC–MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.
KW - DOM
KW - LC–MS/MS
KW - dissolved organic matter
KW - high resolution tandem mass spectrometry
KW - interlaboratory comparison
KW - non-targeted analysis
KW - non-targeted metabolomics
KW - structure-resolved chemical analysis
UR - https://www.scopus.com/pages/publications/105030302283
UR - https://www.scopus.com/pages/publications/105030302283#tab=citedBy
U2 - 10.1021/acs.est.5c12691
DO - 10.1021/acs.est.5c12691
M3 - Article
C2 - 41649479
AN - SCOPUS:105030302283
SN - 0013-936X
VL - 60
SP - 4814
EP - 4829
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 6
ER -