The succession of microbiota is closely associated with several essential factors, including race, sex, health condition, lifestyle, postmortem interval, etc., and it has great potential application value in forensic medicine. This paper summarizes recent studies on the forensic applications of the microbiome, including individual identification, geographical feature identification, origin identification of the tissue or body fluid, and postmortem interval estimation, and introduces the current machine learning algorithms for microbiology research based on next-generation sequencing data. In addition, the current problems facing forensic microbiomics such as the extraction and preservation of samples, construction of standardization and database, ethical review and practical applicability are discussed. Future multi-omics studies are expected to explore micro ecosystems from a comprehensive and dynamic perspective, to promote the development of forensic microbiomics application.
微生物群落演替与样本种族、性别、健康状况、生活方式、死亡时间等重要因素密切相关，具有较大的法医学潜在应用价值。本文总结了近年来微生物组学应用于法医学同一认定、地域特征鉴识、组织或体液来源鉴定以及死亡时间推断等方面的研究，并介绍了基于二代测序数据用于微生物学研究的主要机器学习算法。此外，还分析了当下法医微生物组学面临的检材提取与保存、标准化和数据库建设、伦理审查和实践适用性等问题。未来借助微生物多组学技术将有望以全面动态的角度探索微生态系统，从而推动法医微生物组学的应用发展。.
Keywords: analysis of death cause; forensic medicine; geographical feature identification; individual identification; microbiomics; origin identification of tissues and body fluids; postmortem interval estimation; review.