Artificial intelligence-driven microbiome data analysis for estimation of postmortem interval and crime location

Ze Wu; Yaoxing Guo; Miren Hayakawa; Wei Yang; Yansong Lu; Jingyi Ma; Linghui Li; Chuntao Li; Yingchun Liu; Jun Niu

doi:10.3389/fmicb.2024.1334703

Artificial intelligence-driven microbiome data analysis for estimation of postmortem interval and crime location

Front Microbiol. 2024 Jan 19:15:1334703. doi: 10.3389/fmicb.2024.1334703. eCollection 2024.

Authors

Ze Wu^#¹, Yaoxing Guo^#^{2

3

4}, Miren Hayakawa⁵, Wei Yang¹, Yansong Lu¹, Jingyi Ma¹, Linghui Li¹, Chuntao Li¹, Yingchun Liu¹, Jun Niu¹

Affiliations

¹ Department of Dermatology, General Hospital of Northern Theater Command, Shenyang, China.
² Department of Dermatology, The First Hospital of China Medical University, Shenyang, China.
³ Key Laboratory of Immunodermatology, Ministry of Education and NHC, Shenyang, China.
⁴ National Joint Engineering Research Center for Theranostics of Immunological Skin Diseases, Shenyang, China.
⁵ Beijing Anzhen Hospital, Capital Medical University, Beijing, China.

^# Contributed equally.

Abstract

Microbial communities, demonstrating dynamic changes in cadavers and the surroundings, provide invaluable insights for forensic investigations. Conventional methodologies for microbiome sequencing data analysis face obstacles due to subjectivity and inefficiency. Artificial Intelligence (AI) presents an efficient and accurate tool, with the ability to autonomously process and analyze high-throughput data, and assimilate multi-omics data, encompassing metagenomics, transcriptomics, and proteomics. This facilitates accurate and efficient estimation of the postmortem interval (PMI), detection of crime location, and elucidation of microbial functionalities. This review presents an overview of microorganisms from cadavers and crime scenes, emphasizes the importance of microbiome, and summarizes the application of AI in high-throughput microbiome data processing in forensic microbiology.

Keywords: artificial intelligence; crime location; forensic microbiology; microbiome; postmortem interval.

Publication types

Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was funded and supported by Liaoning Province Technological Innovation Planned Project (grant number 2022JH2/101500012) and Shenyang Science and Technology Planned Project (grant number 22–321–33-34).