CaDAVEr Database Viewer

4.1 Study Design

The study utilized three outdoor human decomposition research facilities across the United States, representing distinct bioclimatic regions: the Forensic Investigation Research Station (FIRS) at Colorado Mesa University (CMU) in a semi-arid environment, the Anthropology Research Facility (ARF) at the University of Tennessee Knoxville (UTK) in a temperate environment, and the Southeast Texas Applied Forensic Science (STAFS) facility at Sam Houston State University (SHSU) in a temperate environment. Decomposition experiments were conducted over 21-day sampling windows across multiple seasons. A total of 569 soil samples were collected from beneath and around cadavers at defined postmortem intervals throughout decomposition.

4.2 MAG Generation

Metagenomic sequencing was performed on an Illumina platform, generating paired-end short reads. Raw reads underwent quality trimming using Trimmomatic to remove adapters and low-quality bases. Trimmed reads were co-assembled per site using MEGAHIT. Genome binning was performed with a multi-binner approach using MetaBAT2, MaxBin2, and CONCOCT to maximize bin recovery. Resulting bins were dereplicated across all sites using dRep at an average nucleotide identity (ANI) threshold of ≥ 95% to yield non-redundant MAGs. Taxonomic classification was performed using GTDB-Tk against the Genome Taxonomy Database. This pipeline yielded 277 non-redundant MAGs representing a cross-site core decomposer community.

4.3 Abundance Quantification

To estimate the relative abundance of each MAG across samples, metagenomic reads from each sample were mapped back to all MAG contigs using BWA-MEM. Coverage depth was calculated using CoverM. Abundance values are expressed as TPM (transcripts per million) to enable cross-sample normalization and account for differences in sequencing depth. TPM normalization allows relative comparisons of MAG prevalence and abundance across the full 569-sample dataset.

4.4 Metabolic Annotation

Functional annotation of MAGs was performed using the DRAM (Distilled and Refined Annotation of Metabolism) pipeline. DRAM integrates multiple curated databases including KEGG, Pfam, CATH-FunFam, VOG (viral orthologous groups), and CAZy (carbohydrate-active enzymes). Pathway completeness was assessed across 11 metabolic categories relevant to decomposition ecology, including carbon cycling, nitrogen cycling, sulfur cycling, and various energy metabolism pathways. Gene annotations are linked to KEGG module completeness estimates.

4.5 Key Findings

Analysis revealed a conserved interdomain microbial network spanning bacteria, archaea, and fungi that was consistently associated with cadaver decomposition across all three geographically distinct sites. This core decomposer network was identified as predictive of postmortem interval (PMI) regardless of geographic location or season of death, suggesting robust ecological determinism in microbial succession during decomposition. Network members included phylogenetically diverse taxa with complementary metabolic roles in organic matter degradation and nutrient cycling.

4.6 Data Availability

The full dataset, including raw sequencing reads, assembled MAGs, and associated metadata, is available through the original publication at Nature Microbiology (DOI: 10.1038/s41564-023-01580-y). Processed data and analysis scripts are additionally archived on Zenodo. This database viewer presents a curated subset of the published data for interactive exploration.