Improved characterization of soil organic matter by integrating FTICR-MS, liquid chromatography tandem mass spectrometry and molecular networking: a case study of root litter decay under drought conditions
DiDonato, N.; Rivas-Ubach, A.; Kew, W.; Clendinen, C.; Sokol, N.; Kyle, J. E.; Martinez, C. E.; Foley, M. M.; Tolic, N.; Pett-Ridge, J.; Pasa-Tolic, L.
Show abstract
Knowledge of the type of carbon contained in soils is important for predicting carbon fluxes in a warming climate, yet most soil organic matter (SOM) components are unknown. We used an integrated three-part approach to characterize SOM from decaying root-detritus microcosms subject to either drought or normal conditions. To observe broad differences in SOM compositions we employed direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FTICR-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 spectra cosine similarity scores to relate unknowns and library matches through molecular networks. This approach allowed us to corroborate DI-FTICR-MS molecular formulas using library matches and infer structures of unknowns from molecular networks to improve SOM annotation. We found matches to fungal metabolites, and under drought conditions, greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas, and lower average nominal oxidation state of SOM carbon, suggesting reduced decomposition of carbon and/or microbes under stress. We propose this integrated approach as more comprehensive than individual analyses in parallel, with the potential to improve knowledge of the chemical composition and persistence of SOM. SynopsisStructural characterization and identifications are lacking for soil organic matter components. This study integrates molecular formula assignments and structural information from fragment ion spectra into molecular networks to better characterize unknown soil organic matter components. For Table of Contents Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/545455v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@140a98org.highwire.dtl.DTLVardef@1c3b26forg.highwire.dtl.DTLVardef@f7b82aorg.highwire.dtl.DTLVardef@15c012f_HPS_FORMAT_FIGEXP M_FIG C_FIG
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Using Community Science to Reveal the Global Chemogeography of River Metabolomes 95%
- Matrix selection for the visualization of small molecules and lipids in brain tumors using untargeted MALDI-TOF mass spectrometry imaging 93%
- Scan-Centric, Frequency-Based Method for Characterizing Peaks from Direct Injection Fourier transform Mass Spectrometry Experiments 93%
Similar papers in this journal
- Re-modeling of foliar membrane lipids in a seagrass allows for growth in phosphorus deplete conditions 92%
- Towards robust machine olfaction: debiasing GC-MS data enhances prostate cancer diagnosis from urine volatiles 92%
- High-throughput DNA extraction and cost-effective miniaturized metagenome and amplicon library preparation of soil samples for DNA sequencing 92%
Similar papers in this journal
- MetaboDirect: An Analytical Pipeline for the processing of FTICR-MS-based Metabolomics Data 95%
- Ultra-sensitive Protein-SIP to quantify activity and substrate uptake in microbiomes with stable isotopes 94%
- Critical Assessment of MetaProteome Investigation 2 (CAMPI-2): Multi-laboratory assessment of sample processing methods to stabilize fecal microbiome for functional analysis 94%
Similar papers in this journal
Similar papers in this journal
- Influences of chemotype and parental genotype on metabolic fingerprints of tansy plants uncovered by predictive metabolomics. 93%
- Particulate Matter emission sources and meteorological parameters combine to shape the airborne microbiome communities in the Ligurian coast, Italy 91%
- Tissue-wide metabolomics reveals wide impact of gut microbiota on mice metabolite composition 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.