Viral community succession during cadaver decomposition and its potential for estimating postmortem intervals
We present a viral succession-based framework for estimating PMI in buried remains. Our study identifies stage-specific viral biomarkers and identified nine viral families significantly correlated with PMI. By combining metagenomics and machine learning, we developed an Extremely Randomized Trees (ERT) model that achieved a low prediction error (test set: <i>R</i>² = 0.96, MAE = 2.54 days). Furthermore, our findings demonstrate that viral and bacterial communities exhibit significant consistency and correlation during cadaver decomposition. This study not only provides a novel tool for the accurate estimation of forensic PMI but also advances our insight into viral regulation of bacteria and their interactions during cadaver decomposition.
Authors
- Kewen Zhang (ORCID: https://orcid.org/0009-0001-4649-5008)
- Jiangwei Yan (ORCID: https://orcid.org/0000-0002-0359-4508)
- Liuyaoxing Zhang
- Yuntian Xiao (ORCID: https://orcid.org/0000-0002-7139-9501)
- Daijing Yu (ORCID: https://orcid.org/0009-0004-1396-9029)
- Liwei Zhang (ORCID: https://orcid.org/0000-0003-1919-3765)
- Bo Chen (ORCID: https://orcid.org/0000-0003-3750-2533)
- Jun Zhang (ORCID: https://orcid.org/0000-0002-3113-4963)
- Meng Zhang (ORCID: https://orcid.org/0009-0002-3140-7500)
- Tian Wang (ORCID: https://orcid.org/0000-0002-9038-5009)
- Yi Mai
- Bo Shao (ORCID: https://orcid.org/0000-0003-0488-3966)
- Niu Gao
Institutions
- Shanxi Medical University (CN)
- Shanxi Coal Transportation and Sales Group (China) (CN)
- Institute of Forensic Science (CN)
- Shanxi University of Traditional Chinese Medicine (CN)
- Institute of Coal Chemistry (CN)
- Inner Mongolia Medical University (CN)
Publication Details
- Journal
- Applied and Environmental Microbiology
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1128/aem.01453-25
- Citations
- 2
- Primary Topic
- Forensic Entomology and Diptera Studies
- Type
- article
- Field-Weighted Citation Impact
- 3.34