lbnl-metabolomics/20210915_JGI-AK_MK_506588_SoilWaterRep_final_QE-HF_C18_USDAY63680

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Soil water repellency (SWR) (i.e. soil hydrophobicity or decreased soil wettability) is a major cause of global soil degradation and a key agricultural concern. This metabolomics data will support the larger effort measuring soil water repellency and soil aggregate formation caused by microbial community composition through a combination of the standard drop penetration test, transmission electron microscopy characterization and physico-chemical analyses of soil aggregates at 6 timepoints. Model soils created from clay/sand mixtures as described in Kallenbach et al. (2016, Nature Communications) with sterile, ground pine litter as a carbon/nitrogen source were inoculated with 15 different microbial communities known to have significantly different compositions based on 16S rRNA sequencing. This data will allow assessment of the direct influence of microbial community composition on soil water repellency and soil aggregate stability, which are main causes of soil degradation. The work (proposal:https://doi.org/10.46936/10.25585/60001346) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.

Every file is self-describing: the complete run record — the full sample, instrument, and study metadata (project, sample group and replicate, extraction and chromatography details, MassIVE accession) together with the study's published manuscript (ISME Communications, 2025, https://doi.org/10.1093/ismeco/ycaf084) — is encoded directly into the mass spectra with SpectraCodec. Decode any single file to recover it. How the encoding and decoding works is documented in the SpectraCodec repository.

Authenticity

Every file is cryptographically signed. The embedded message carries a provenance block with two Ed25519 signatures: payload_signature covers the embedded run record and manuscript, and spectra_signature covers the acquired spectra themselves (via a spectral digest that excludes the carrier spectrum). Verify either with the published key — fingerprint SHA256:lbrclU9WYbrXjl/AWl8VOWFUEm5EQgGybgdSKZzTwfA:

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MCowBQYDK2VwAyEAGqP/DGL5rqwsLLD/24feNs38sLkGS2vLZVOsXlWOnxg=
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python spectra_codec.py verify <file>.mzML --key spectracodec_verification_key.pem

The same key ships as spectracodec_verification_key.pem in the SpectraCodec repository (v1.1.0).

License

Licensed CC-BY-NC-4.0. For rights to use or distribute SpectraCodec itself: Berkeley Lab Intellectual Property Office (IPO@lbl.gov).