Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions.


Journal

Analytical chemistry
ISSN: 1520-6882
Titre abrégé: Anal Chem
Pays: United States
ID NLM: 0370536

Informations de publication

Date de publication:
11 Jul 2024
Historique:
medline: 11 7 2024
pubmed: 11 7 2024
entrez: 11 7 2024
Statut: aheadofprint

Résumé

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. We present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ∼5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

Identifiants

pubmed: 38991201
doi: 10.1021/acs.analchem.4c00184
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Nicole DiDonato (N)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Albert Rivas-Ubach (A)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

William Kew (W)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Noah W Sokol (NW)

Lawrence Livermore National Laboratory, Livermore, California 94550, United States.

Chaevien S Clendinen (CS)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Jennifer E Kyle (JE)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Carmen Enid Martínez (CE)

Cornell University, Ithaca, New York 14850, United States.

Megan M Foley (MM)

Northern Arizona University, Flagstaff, Arizona 86011, United States.

Nikola Tolić (N)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Jennifer Pett-Ridge (J)

Lawrence Livermore National Laboratory, Livermore, California 94550, United States.

Ljiljana Paša-Tolić (L)

Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Classifications MeSH