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Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

  • Jarmo Charles Kalinski
  • , Bruno Ruiz Brandão da Costa
  • , Tilman Schramm
  • , Lance R. Buckett
  • , Laura T. Carlson
  • , Nicole R. Coffey
  • , Tito Damiani
  • , Elias Dechent
  • , Yasin El Abiead
  • , Steffen Heuckeroth
  • , Elaine K. Jennings
  • , Jan Kaesler
  • , Naomi L. Stock
  • , Alice M. Orme
  • , Ralph R. Torres
  • , Sara Trojahn
  • , Helen L. Whelton
  • , Yingfei Yan
  • , Allegra T. Aron
  • , Rene M. Boiteau
  • Ian D. Bull, Pieter C. Dorrestein, Duc Huy Dang, Richard P. Evershed, Marta Gledhill, Gerd Gleixner, Andreas F. Haas, Martin Hansen, Tilmann Harder, Ellen C. Hopmans, Anitra E. Ingalls, Uwe Karst, William Kew, Melissa Kido Soule, Boris P. Koch, Elizabeth B. Kujawinski, Oliver J. Lechtenfeld, Krista Longnecker, Tomáš Pluskal, Georg Pohnert, Zachary C. Redman, Albert Rivas-Ubach, Philippe Schmitt-Kopplin, Gabriel Singer, Jan Tebben, Patrick L. Tomco, Nicholas D. Ward, Lihini I. Aluwihare, Carsten Simon, Jeffrey Hawkes, Daniel Petras

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)4814-4829
Number of pages16
JournalEnvironmental Science and Technology
Volume60
Issue number6
DOIs
StatePublished - Feb 17 2026

Bibliographical note

Publisher Copyright:
© 2026 The Authors. Published by American Chemical Society

Keywords

  • DOM
  • LC–MS/MS
  • dissolved organic matter
  • high resolution tandem mass spectrometry
  • interlaboratory comparison
  • non-targeted analysis
  • non-targeted metabolomics
  • structure-resolved chemical analysis

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