{"title":"Succession changes of microbial community for inferring the time since deposition of saliva","authors":"Xiaoye Jin, Shunyi Tian, Hongling Zhang, Zheng Ren, Qiyan Wang, Yubo Liu, Hao Zheng, Meiqing Yang, Jiang Huang","doi":"10.1002/elps.202300267","DOIUrl":null,"url":null,"abstract":"<p>Saliva is a common biological examination material at crime scenes and has high application value in forensic case investigations. It can reflect the suspect's time of crime at the scene and provide evidence of the suspect's criminal facts. Even though many researchers have proposed their experimental protocols for estimating the time since deposition (TsD) of saliva, there is still a relative lack of research on the use of microorganisms to estimate TsD. In the current study, the succession change of microbial community in saliva with different TsD values was explored to discern the microbial markers related to TsD of saliva. We gathered saliva samples from six unrelated healthy Han individuals living in Guizhou, China and exposed these samples to indoor conditions at six time points (0, 1, 3, 7, 15, and 28 days). Temporal changes of microbial compositions in these samples were investigated by 16S rRNA sequencing (V3–V4 regions). By assessing temporal variation patterns of microbial abundance at the genus level, four bacteria (<i>Brucella</i>, <i>Prevotella</i>, <i>Pseudomonas</i>, and <i>Fusobacterium</i>) were observed to show good time dependence in these samples. In addition, the hierarchical clustering and principal co-ordinates analysis results revealed that these saliva samples could be classified into t-short (≤7 days) and t-long (>7 days) groups. In the end, the random forest model was developed to predict the TsD of these samples. For the model, the root mean square error, <i>R</i><sup>2</sup>, and mean absolute error between predicted and actual TsD values were 1.5213, 0.9851, and 1.1969, respectively. To sum up, we identified TsD-related microbial markers in saliva samples, which could be viewed as valuable markers for inferring the TsD of saliva.</p>","PeriodicalId":11596,"journal":{"name":"ELECTROPHORESIS","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ELECTROPHORESIS","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/elps.202300267","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Saliva is a common biological examination material at crime scenes and has high application value in forensic case investigations. It can reflect the suspect's time of crime at the scene and provide evidence of the suspect's criminal facts. Even though many researchers have proposed their experimental protocols for estimating the time since deposition (TsD) of saliva, there is still a relative lack of research on the use of microorganisms to estimate TsD. In the current study, the succession change of microbial community in saliva with different TsD values was explored to discern the microbial markers related to TsD of saliva. We gathered saliva samples from six unrelated healthy Han individuals living in Guizhou, China and exposed these samples to indoor conditions at six time points (0, 1, 3, 7, 15, and 28 days). Temporal changes of microbial compositions in these samples were investigated by 16S rRNA sequencing (V3–V4 regions). By assessing temporal variation patterns of microbial abundance at the genus level, four bacteria (Brucella, Prevotella, Pseudomonas, and Fusobacterium) were observed to show good time dependence in these samples. In addition, the hierarchical clustering and principal co-ordinates analysis results revealed that these saliva samples could be classified into t-short (≤7 days) and t-long (>7 days) groups. In the end, the random forest model was developed to predict the TsD of these samples. For the model, the root mean square error, R2, and mean absolute error between predicted and actual TsD values were 1.5213, 0.9851, and 1.1969, respectively. To sum up, we identified TsD-related microbial markers in saliva samples, which could be viewed as valuable markers for inferring the TsD of saliva.
期刊介绍:
ELECTROPHORESIS is an international journal that publishes original manuscripts on all aspects of electrophoresis, and liquid phase separations (e.g., HPLC, micro- and nano-LC, UHPLC, micro- and nano-fluidics, liquid-phase micro-extractions, etc.).
Topics include new or improved analytical and preparative methods, sample preparation, development of theory, and innovative applications of electrophoretic and liquid phase separations methods in the study of nucleic acids, proteins, carbohydrates natural products, pharmaceuticals, food analysis, environmental species and other compounds of importance to the life sciences.
Papers in the areas of microfluidics and proteomics, which are not limited to electrophoresis-based methods, will also be accepted for publication. Contributions focused on hyphenated and omics techniques are also of interest. Proteomics is within the scope, if related to its fundamentals and new technical approaches. Proteomics applications are only considered in particular cases.
Papers describing the application of standard electrophoretic methods will not be considered.
Papers on nanoanalysis intended for publication in ELECTROPHORESIS should focus on one or more of the following topics:
• Nanoscale electrokinetics and phenomena related to electric double layer and/or confinement in nano-sized geometry
• Single cell and subcellular analysis
• Nanosensors and ultrasensitive detection aspects (e.g., involving quantum dots, "nanoelectrodes" or nanospray MS)
• Nanoscale/nanopore DNA sequencing (next generation sequencing)
• Micro- and nanoscale sample preparation
• Nanoparticles and cells analyses by dielectrophoresis
• Separation-based analysis using nanoparticles, nanotubes and nanowires.