Multi‑omics profiling of oral Porphyromonas gingivalis challenge in autoimmune‑prone and circadian‑disrupted mice

This dataset accompanies the manuscript “Association of Porphyromonas Gingivalis Infection with Exocrine Autoimmunity and Gut Microbiome–Metabolome Signatures in Sjögren’s Syndrome Like Experimental Models” and contains raw and processed multi‑omics data generated to investigate the impact of oral Porphyromonas gingivalis (PG) infection on autoimmune glandular inflammation, the gut microbiome, and systemic metabolism in two murine models: NOD.B10Sn‑H2b/J (NOD) mice and cryptochrome 1/2 double knockout (Cry1/2DKO) mice. 

Contents of this repository

 Proteomics

Processed protein‑level quantification tables (normalized intensities)

A sample metadata sheet (mouse ID, strain, sex, treatment).

Fecal metabolomics

Processed metabolite abundance matrices (normalized values).

A sample metadata sheet aligned with the microbiome and proteome datasets.

Fecal microbiome (16S rRNA amplicon sequencing)

Processed feature table (ASV/OTU count matrix) and taxonomy assignments used in the manuscript.

Representative sequences file.

Mapping/metadata file (mouse ID, strain, sex, treatment, cage).

Supplementary summary tables

Differential abundance lists of significantly altered microbial taxa.

Differential abundance lists of significantly altered fecal metabolites.

These correspond to the main and supplementary figures/tables in the Journal of Autoimmunity article.

Methods overviewNOD.B10Sn‑H2b/J and Cry1/2DKO mice were orally challenged with P. gingivalis or sham solution and followed longitudinally. Salivary gland histology, qPCR, and mucin staining were combined with multi‑omics profiling of serum and feces at 2–4 weeks post‑challenge. Serum proteomes were generated by high‑resolution mass spectrometry and processed with standard database search pipelines and false discovery rate control. Fecal metabolomes were acquired by untargeted LC‑MS, followed by peak detection, annotation against public and in‑house libraries, and normalization. Microbiome profiling was performed using 16S rRNA gene amplicon sequencing, with quality control, ASV inference, and taxonomic assignment conducted using common microbiome analysis workflows. Full experimental and analytical details are provided in the associated Journal of Autoimmunity manuscript.

File organization

/proteomics

/metabolomics

/microbiome

/Supplementary Datasets

Usage notes

Processed tables include the main contrasts used in the manuscript (e.g., PG vs sham within each strain). Users wishing to re‑analyze the data with alternative pipelines or thresholds can start from the raw files provided.

When re‑using these data, please cite both this Zenodo record (DOI) and the associated Journal of Autoimmunity article.