Raw Sequencing and LC-HRMS Data from an Integrated Study of Bee Bread

Description

This dataset contains the raw experimental data generated for the study “Beyond Floral Origin: Partially Decoupled Botanical, Polyphenolic, Bacterial, and Predicted Functional Profiles in Bee Bread”. It includes raw paired-end sequencing data from ITS2 metabarcoding and 16S rRNA gene sequencing, together with raw LC-HRMS data acquired in positive and negative ionization modes. The dataset comprises 18 seasonal composite bee bread samples obtained from nine Apis mellifera colonies located in three stationary apiaries in the Benevento province, Southern Italy. Processed data and results are provided as Supplementary Material accompanying the associated research article.

Steps to reproduce

Bee bread was collected from nine Apis mellifera colonies located in three stationary apiaries in the Benevento province, Southern Italy (three colonies per apiary). Two independent sampling series were obtained from each colony, resulting in 18 seasonal composite samples. For botanical and bacterial profiling, DNA was analysed by ITS2 metabarcoding and 16S rRNA gene amplicon sequencing, respectively. Raw paired-end sequencing reads were generated by Eurofins Genomics Europe Sequencing GmbH (Ebersberg, Germany). In the workflow used for the associated study, reads were quality controlled and preprocessed using Cutadapt v2.7, fastp v0.20.0 and Seqtk v1.0, merged using FLASH v2.2.00, and processed with DADA2 for ASV inference. Taxonomic assignments were performed against the UNITE database for ITS2 and the SILVA database for 16S rRNA gene sequences. Bee_Bread_2026_revisionato_Intr… The polyphenolic fraction of the same 18 bee bread samples was analysed by LC-HRMS in both positive and negative ionisation modes. The repository contains the original raw LC-HRMS files from both acquisition modes. In the associated study, LC-HRMS data were processed using MZmine for feature detection and chromatographic alignment, while MS/MS information was evaluated using GNPS-based spectral-library matching and complementary annotation approaches. Bee_Bread_2026_revisionato_Intr… Detailed experimental procedures, data-processing parameters, quality-control criteria and downstream statistical analyses are reported in the associated research article and its Supplementary Material. Sample identifiers are preserved across the deposited datasets to allow correspondence among ITS2, 16S and LC-HRMS data.

Institutions

• University of Molise

  Molise, Campobasso

Categories

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