AbstractMicroorganisms are essential in the decomposition of corpses and play a significant role in forensic science. However, previous studies have primarily focused on animal remains, specifically the gut, skin, and burial environment. Insufficient research has been conducted on the microbiota of human cadavers, especially in cases of advanced decomposition and additional tissues, resulting in a lack of relevant reference data.

摘要微生物在尸体分解中至关重要，在法医学中起着重要作用。然而，以前的研究主要集中在动物遗骸上，特别是肠道，皮肤和埋葬环境。对人体尸体微生物群的研究不足，特别是在晚期分解和其他组织的情况下，导致缺乏相关的参考数据。

In this study, the microbiota of eight cadavers at different stages of decomposition were detected using 16S rRNA, metagenomic sequencing and 2bRAD-M sequencing. Nine different sites, including oral and nasal cavities, heart, liver, spleen, lung, kidney, muscle and gut, were analysed and the efficacy of these methods was evaluated.

在这项研究中，使用16S rRNA，宏基因组测序和2bRAD-M测序检测了八具尸体在不同分解阶段的微生物群。分析了9个不同部位，包括口腔和鼻腔，心脏，肝脏，脾脏，肺，肾，肌肉和肠道，并评估了这些方法的疗效。

The results showed that 16S rRNA sequencing was the most cost-effective method for the study of cadavers in the early stages of decomposition, whereas for cadaveric tissues in the late stages of decomposition, 2bRAD-M could overcome host contamination more effectively than metagenomic sequencing. This paves the way for new opportunities in data retrieval and promotes in-depth investigations into the microbiota..

结果表明，16S rRNA测序是分解早期尸体研究中最具成本效益的方法，而对于分解后期的尸体组织，2bRAD-M可以比宏基因组测序更有效地克服宿主污染。这为数据检索的新机会铺平了道路，并促进了对微生物群的深入研究。。

Background & SummaryThe Human Microbiome Project (HMP) has linked variations in microbiota structure to human health, demonstrating the integral role of microorganisms in the human body, and the Integrative Human Microbiome Project (iHMP) has elucidated the interaction between microorganisms and the host1.Currently, there is extensive research and application of the distribution and function of human microbial communities during life.

背景与总结人类微生物组计划（HMP）将微生物群结构的变化与人类健康联系起来，证明了微生物在人体中的整体作用，综合人类微生物组计划（iHMP）阐明了微生物与宿主之间的相互作用。目前，人们对生命过程中人类微生物群落的分布和功能进行了广泛的研究和应用。

However, there is limited knowledge of post-mortem microbial changes. It has been demonstrated that microbial succession continues beyond individual death, and hosts’ death can be viewed as an ecological disruption to the microbiota2. Microorganisms play a crucial role in carcass decomposition3, but more research is needed to determine how microorganisms change during decomposition and correlate with environment, season, host, et al.

然而，对死后微生物变化的了解有限。已经证明，微生物的演替持续超过个体死亡，宿主的死亡可以被视为对微生物群的生态破坏2。微生物在胴体分解中起着至关重要的作用3，但需要更多的研究来确定微生物在分解过程中的变化以及与环境，季节，宿主等的关系。

Therefore, exploring the structure and changes of the thanatomicrobiome and elucidating the time-dependent change profiles of them during the stages of autolysis, putrefaction and decomposition of cadavers is crucial for forensic research.The development and maturity of DNA sequencing technology drive the interpretation of microbiota structure and diversity in different environments.

因此，探索死亡微生物组的结构和变化，并阐明它们在尸体自溶，腐烂和分解阶段的时间依赖性变化特征，对于法医研究至关重要。DNA测序技术的发展和成熟推动了对不同环境中微生物群结构和多样性的解释。

Presently, Amplicon sequencing4 and Metagenomic Sequencing5 are the most mainstream DNA sequencing technologies for microbiome research. Amplicon sequencing overwhelmingly targets the 16S rRNA gene (bacteria and archaea)6, and the internal transcribed spacer (ITS) region (fungi)7. 16S rRNA sequencing is fast, easy and can be applied to large-scale studies, thus has now become the most commonly used technique for cadaver microbiological research.

目前，扩增子测序4和宏基因组测序5是微生物组研究中最主流的DNA测序技术。扩增子测序绝大多数靶向16S rRNA基因（细菌和古细菌）6和内部转录间隔区（ITS）区域（真菌）7。16S rRNA测序快速，简单，可用于大规模研究，因此现已成为尸体微生物学研究中最常用的技术。

However, this technique offers low strain resolution which only reaches the genus leve.

然而，该技术提供的应变分辨率低，仅达到属级。

(1)

(1)

16S rRNA Sequencing Data: The raw sequence data files (FastQ format) from the 16S rRNA sequencing are accessible under the BioProject ID: PRJNA111924421.

16S rRNA测序数据：16S rRNA测序的原始序列数据文件（FastQ格式）可在BioProject ID:PRJNA111924421下访问。

(2)

(2)

Metagenomic Sequencing Data: The raw sequence data files (FastQ format) from the metagenomic sequencing are available under the BioProject ID: PRJNA112122222.

宏基因组测序数据：宏基因组测序的原始序列数据文件（FastQ格式）可在BioProject ID:PRJNA12122222下获得。

(3)

(3)

2bRAD-M Sequencing Data: The raw sequence data files (FastQ format) from the 2bRAD-M sequencing are stored in the SRA under the BioProject ID: PRJNA112059823.

2bRAD-M测序数据：来自2bRAD-M测序的原始序列数据文件（FastQ格式）存储在SRA中，生物项目ID为PRJNA112059823。

Additionally, comprehensive statistics related to the species abundance from the 16S rRNA, Metagenomic, and 2bRAD-M sequencing data are available on Figshare with the https://doi.org/10.6084/m9.figshare.2479856724. The specific sequences and procedures used to generate the data records are detailed in their respective subsections, linking directly to the corresponding data records.Technical ValidationSamples were taken aseptically by using sterilized equipment and sterile RNase and DNase-free tubes.

此外，有关16S rRNA，宏基因组学和2bRAD-M测序数据中物种丰度的综合统计数据可在Figshare上获得https://doi.org/10.6084/m9.figshare.2479856724.用于生成数据记录的特定序列和程序在各自的小节中有详细说明，直接链接到相应的数据记录。技术验证通过使用无菌设备和无菌RNase和DNase游离管无菌采集样品。

To assess the potential for contamination, we also sampled the tissue surfaces separately from the internal tissues. DNA were extracted in an RNase free environment. DNA concentration and integrity were measured with NanoDrop 2000 (Thermo Fisher Scientific, USA) and agarose gel electrophoresis. For 16S rRNA gene amplification, negative control containing PCR-grade water and PCR with bacterial primers 343 F and 798 R were used.

为了评估污染的可能性，我们还将组织表面与内部组织分开采样。在无RNase的环境中提取DNA。用NanoDrop 2000（Thermo Fisher Scientific，USA）和琼脂糖凝胶电泳测量DNA浓度和完整性。对于16S rRNA基因扩增，使用含有PCR级水的阴性对照和具有细菌引物343F和798R的PCR。

No positive or negative sequencing controls were used to obtain metagenomic data. The concentration of the 16S rRNA gene amplicons and controls was measured with a Qubit 2.0 Fluorometer and their quality were analysed using agarose gel electrophoresis.The quality of the raw 16S rRNA sequencing reads was assessed using FastQC, which provided initial insights into potential issues such as poor quality scores, overrepresented sequences, or adapter contamination.

没有使用阳性或阴性测序对照来获得宏基因组数据。用Qubit 2.0荧光计测量16S rRNA基因扩增子和对照的浓度，并使用琼脂糖凝胶电泳分析其质量。使用FastQC评估了原始16S rRNA测序读数的质量，该方法提供了对潜在问题的初步见解，例如质量得分低，序列过多或衔接子污染。

Representative sequences for each ASV were aligned and annotated against the Silva database (v 138) using the q2-feature-classifier plugin with default parameters, ensuring reliable species-level identification. Metagenomic Sequencing Reads were subjected to stringent quality filtering steps using Trimmomatic, where bases below a quality score threshold of 20 were trimmed, and reads shorter than 7.

使用带有默认参数的q2特征分类器插件，将每个ASV的代表性序列与Silva数据库（v 138）进行比对和注释，以确保可靠的物种级识别。。

Code availability

代码可用性

In this analysis, default parameters or parameters recommended by the developer were used.

在此分析中，使用了默认参数或开发人员推荐的参数。

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NCBI序列读取存档https://identifiers.org/ncbi/insdc.sra:SRP511264（2024年）。NCBI序列读取存档https://identifiers.org/ncbi/insdc.sra:SRP512408（2024年）。NCBI序列读取存档https://identifiers.org/ncbi/insdc.sra:SRP512103（2024年）。Huang，X。等人，16S rRNA，宏基因组学和2bRAD-M测序解码人类死亡微生物组。

figshare https://doi.org/10.6084/m9.figshare.24798567.v3 (2023).Download referencesAcknowledgementsThis work was supported by grants from the National Natural Science Fund of China (No.82371896, No. 82072123).Author informationAuthor notesThese authors contributed equally: Xin Huang, Jianye Zeng.Authors and AffiliationsInstitute of Forensic Science, Fudan University, Shanghai, 200032, PR ChinaXin Huang, Jianye Zeng, Shilin Li, Ji Chen, Chengtao Li & Suhua ZhangThe State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, P.R.

figshare公司https://doi.org/10.6084/m9.figshare.24798567.v3（2023年）。下载参考文献致谢这项工作得到了国家自然科学基金（No.82371896，No.82072123）的资助。作者信息作者注意到这些作者做出了同样的贡献：Xin Huang，Jianye Zeng。作者和所属单位复旦大学法医学研究所，上海，200032，中华人民共和国黄新新，曾建业，李士林，陈吉，李成涛和张素华复旦大学生命科学学院基因工程国家重点实验室和教育部当代人类学重点实验室，上海。

ChinaHongyan WangDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, PR ChinaSuhua ZhangAuthorsXin HuangView author publicationsYou can also search for this author in.

中国王红艳复旦大学基础医学院法医学系，上海，200032，中华人民共和国张素华作者黄新维作者出版物您也可以在中搜索这位作者。

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PubMed Google ScholarContributionsSuhua Zhang and Chengtao Li conceived the study and write the manuscript. Xin Huang analyzed the Metagenomic sequencing data. Ji Chen analyzed the 16S rRNA sequencing data. Jianye Zeng analyzed the 2bRAD-M sequencing data. Xin Huang and Jianye Zeng performed the experiment.

PubMed谷歌学术贡献张思华和李成涛构思了这项研究并撰写了手稿。Xin Huang分析了宏基因组测序数据。Ji Chen分析了16S rRNA测序数据。曾建业分析了2bRAD-M测序数据。黄新和曾建业进行了实验。

Shilin Li and Hongyan Wang provided suggestions for writing and revising the manuscript. All authors read and approved the final manuscript.Corresponding authorsCorrespondence to.

李士林和王红燕为撰写和修改手稿提供了建议。所有作者都阅读并批准了最终手稿。通讯作者通讯。

Chengtao Li or Suhua Zhang.Ethics declarations

李成涛或张素华。道德宣言

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