Hewen Yao , Yanyun Wang , Shuangshuang Wang , Chaoran Sun , Yuxiang Zhou , Lanrui Jiang , Zefei Wang , Xindi Wang , Zhirui Zhang , Tingting Yang , Feng Song , Haibo Luo
{"title":"用于鉴定体液和皮肤样本来源的多重微生物分析系统","authors":"Hewen Yao , Yanyun Wang , Shuangshuang Wang , Chaoran Sun , Yuxiang Zhou , Lanrui Jiang , Zefei Wang , Xindi Wang , Zhirui Zhang , Tingting Yang , Feng Song , Haibo Luo","doi":"10.1016/j.fsigen.2024.103124","DOIUrl":null,"url":null,"abstract":"<div><p>Determining the source of body fluids is crucial in forensic investigations, as it provides valuable information about suspects and the nature of the crime. Microbial markers that trace the source of tissues and body fluids based on site specificity and temporal stability are often used effectively for this purpose. In this study, a multiplex system comprising seven microbial markers (<em>Finegoldia magna</em>, <em>Corynebacterium tuberculostearicum</em>, <em>Cutibacterium acnes</em>, <em>Haemophilus parainfluenzae</em>, <em>Streptococcus oralis</em>, <em>Prevotella melaninogenica</em> and <em>Faecalibacterium prausnitzii</em>) was developed to distinguish between skin, saliva, and feces samples. Based on these markers, the system produces electropherograms that are specific for each sample type. We collected 492 samples from six different skin sites (palm, antecubital crease, inguinal crease, cheek, upper back, and toe web space), the buccal mucosa, and stool were collected to further test the system. Beta diversity analysis revealed distinct clustering among the three sample groups. Additionally, skin microenvironment cluster analysis was used to identify skin sites accurately. This analysis classified skin samples into four distinct microenvironments: dry, moist, oily, and foot. Finally, we established a machine learning prediction model based on random forest regression to identify the skin microenvironment, achieving an overall prediction accuracy of 79 %. The multiplex system developed in this study accurately identifies the sources of body fluids, and the skin microenvironment. These findings offer new insights into the application of microbial markers in forensic science.</p></div>","PeriodicalId":50435,"journal":{"name":"Forensic Science International-Genetics","volume":"73 ","pages":"Article 103124"},"PeriodicalIF":3.2000,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multiplex microbial profiling system for the identification of the source of body fluid and skin samples\",\"authors\":\"Hewen Yao , Yanyun Wang , Shuangshuang Wang , Chaoran Sun , Yuxiang Zhou , Lanrui Jiang , Zefei Wang , Xindi Wang , Zhirui Zhang , Tingting Yang , Feng Song , Haibo Luo\",\"doi\":\"10.1016/j.fsigen.2024.103124\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Determining the source of body fluids is crucial in forensic investigations, as it provides valuable information about suspects and the nature of the crime. Microbial markers that trace the source of tissues and body fluids based on site specificity and temporal stability are often used effectively for this purpose. In this study, a multiplex system comprising seven microbial markers (<em>Finegoldia magna</em>, <em>Corynebacterium tuberculostearicum</em>, <em>Cutibacterium acnes</em>, <em>Haemophilus parainfluenzae</em>, <em>Streptococcus oralis</em>, <em>Prevotella melaninogenica</em> and <em>Faecalibacterium prausnitzii</em>) was developed to distinguish between skin, saliva, and feces samples. Based on these markers, the system produces electropherograms that are specific for each sample type. We collected 492 samples from six different skin sites (palm, antecubital crease, inguinal crease, cheek, upper back, and toe web space), the buccal mucosa, and stool were collected to further test the system. Beta diversity analysis revealed distinct clustering among the three sample groups. Additionally, skin microenvironment cluster analysis was used to identify skin sites accurately. This analysis classified skin samples into four distinct microenvironments: dry, moist, oily, and foot. Finally, we established a machine learning prediction model based on random forest regression to identify the skin microenvironment, achieving an overall prediction accuracy of 79 %. The multiplex system developed in this study accurately identifies the sources of body fluids, and the skin microenvironment. These findings offer new insights into the application of microbial markers in forensic science.</p></div>\",\"PeriodicalId\":50435,\"journal\":{\"name\":\"Forensic Science International-Genetics\",\"volume\":\"73 \",\"pages\":\"Article 103124\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Forensic Science International-Genetics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1872497324001200\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forensic Science International-Genetics","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1872497324001200","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
A multiplex microbial profiling system for the identification of the source of body fluid and skin samples
Determining the source of body fluids is crucial in forensic investigations, as it provides valuable information about suspects and the nature of the crime. Microbial markers that trace the source of tissues and body fluids based on site specificity and temporal stability are often used effectively for this purpose. In this study, a multiplex system comprising seven microbial markers (Finegoldia magna, Corynebacterium tuberculostearicum, Cutibacterium acnes, Haemophilus parainfluenzae, Streptococcus oralis, Prevotella melaninogenica and Faecalibacterium prausnitzii) was developed to distinguish between skin, saliva, and feces samples. Based on these markers, the system produces electropherograms that are specific for each sample type. We collected 492 samples from six different skin sites (palm, antecubital crease, inguinal crease, cheek, upper back, and toe web space), the buccal mucosa, and stool were collected to further test the system. Beta diversity analysis revealed distinct clustering among the three sample groups. Additionally, skin microenvironment cluster analysis was used to identify skin sites accurately. This analysis classified skin samples into four distinct microenvironments: dry, moist, oily, and foot. Finally, we established a machine learning prediction model based on random forest regression to identify the skin microenvironment, achieving an overall prediction accuracy of 79 %. The multiplex system developed in this study accurately identifies the sources of body fluids, and the skin microenvironment. These findings offer new insights into the application of microbial markers in forensic science.
期刊介绍:
Forensic Science International: Genetics is the premier journal in the field of Forensic Genetics. This branch of Forensic Science can be defined as the application of genetics to human and non-human material (in the sense of a science with the purpose of studying inherited characteristics for the analysis of inter- and intra-specific variations in populations) for the resolution of legal conflicts.
The scope of the journal includes:
Forensic applications of human polymorphism.
Testing of paternity and other family relationships, immigration cases, typing of biological stains and tissues from criminal casework, identification of human remains by DNA testing methodologies.
Description of human polymorphisms of forensic interest, with special interest in DNA polymorphisms.
Autosomal DNA polymorphisms, mini- and microsatellites (or short tandem repeats, STRs), single nucleotide polymorphisms (SNPs), X and Y chromosome polymorphisms, mtDNA polymorphisms, and any other type of DNA variation with potential forensic applications.
Non-human DNA polymorphisms for crime scene investigation.
Population genetics of human polymorphisms of forensic interest.
Population data, especially from DNA polymorphisms of interest for the solution of forensic problems.
DNA typing methodologies and strategies.
Biostatistical methods in forensic genetics.
Evaluation of DNA evidence in forensic problems (such as paternity or immigration cases, criminal casework, identification), classical and new statistical approaches.
Standards in forensic genetics.
Recommendations of regulatory bodies concerning methods, markers, interpretation or strategies or proposals for procedural or technical standards.
Quality control.
Quality control and quality assurance strategies, proficiency testing for DNA typing methodologies.
Criminal DNA databases.
Technical, legal and statistical issues.
General ethical and legal issues related to forensic genetics.