A new method to detect methylation profiles for forensic body fluid identification combining ARMS-PCR technique and random forest model

Development of a novel panel for blood identification based on blood-specific CpG-linked SNP markers

Blood-containing mixtures often appear in murder and robbery cases, and their identification plays a significant role in solving crimes. In recent years, the co-detection of DNA methylation markers (CpG) and single nucleotide polymorphism (SNP) markers has been shown to be a promising tool for the identification of semen and its donor. However, similar research on blood stains that are frequently found at crime scenes has not yet been reported. In this study, we employed blood-specific CpG-linked SNP markers (CpG-SNP) for blood-specific genotyping and the linking of blood and its donor. The tissue-specific CpG markers were screened from the literature and further verified by combining bisulfite conversion with amplification-refractory mutation system (ARMS) technology. Meanwhile, adjacent SNP markers with a minor allele frequency (MAF) greater than 0.1 were selected within 400 bp upstream and downstream of the CpG markers. SNP genotyping was performed using SNaPshot technology on a capillary electrophoresis (CE) platform. Finally, a multiplex panel, including 19 blood-specific CpG linked to 23 SNP markers, as well as 1 semen-specific CpG, 1 vaginal secretion-specific CpG, and 1 saliva-specific CpG marker, was constructed successfully. The panel showed good tissue specificity and blood stains stored at room temperature for up to nine months and moderately degraded (4 < DI < 10) could be effectively identified. Moreover, it could also be detected when blood content in the mixed stains was as low as 1%. In addition, 15 ng of DNA used for bisulfite conversion was required for obtaining a complete profile. The cumulative discrimination power of the panel among the Han population of northern China could reach 0.999983. This is the first investigation conducted for the simultaneous identification of blood and its donor regardless of other body fluids included in mixed stains. The successful construction of the panel will play a vital role in the comprehensive analysis of blood-containing mixtures in forensic practice.

A high-throughput droplet digital PCR system aiming eight DNA methylation targets for age prediction

The droplet digital Polymerase Chain Reaction (ddPCR) has garnered recognition for its distinctive attribute of absolute quantification. And it has found practical utility in age prediction through DNA methylation profiles. However, a prevalent limitation in current ddPCR methodologies is the restricted capacity to detect only two targets concurrently in most instruments, leading to high costs, sample wastage, and labor-intensive procedures. To address the limitations, a novel high-throughput ddPCR system allowing for the simultaneous detection of eight targets was developed. Through the implementation of a new 8-plex ddPCR assay, coupled with comprehensive linear regression analyses involving primers and probes ratios, diverse inputs of single CpG sites with distinct primers and probes, and varying plex assay configurations, stable DNA methylation values for four CpGs and stable measurement precisions for distinct multiplex systems were consistently observed. These findings pave the way for advancing the field of chemistry science by enabling more efficient and cost-effective methods. Furthermore, the comparative validation of ddPCR and SNaPshot demonstrated a remarkable concordance in results, and the system also displayed well in the field of various aspects, including species specificity, DNA input, and aged samples. In this study, the recommended input of bisulfite-converted DNA was determined to be 10-50 ng due to the double-positive droplets. Notably, the Pearson correlation coefficient squared values of four CpGs were 0.4878 (ASPA), 0.4832 (IGSF1), 0.6881 (COL1A1), and 0.6475 (MEIS1-AS3). And the testing set exhibited a mean absolute error of 4.5923 years, indicating the robustness and accuracy of the age-predictive model.

A novel approach for exploring the regional features of vaginal fluids based on microbial relative abundance and alpha diversity

Vaginal fluids are one of the most common biological samples in forensic sexual assault cases, and their characterization is vital to narrow the scope of investigation. Presently, approaches for identifying vaginal fluids in different regions are not only rare but also have certain limitations. However, the microbiome has shown the potential to identify the source of body fluids and reveal the characteristics of individuals. In this study, 16S rRNA gene high-throughput sequencing was used to characterize the vaginal microbial community from three regions, Sichuan, Hainan and Hunan. In addition, data on relative abundance and alpha diversity were used to construct a random forest model. The results revealed that the dominant genera in the three regions were Lactobacillus, followed by Gardnerella. In addition, Ureaplasma, Nitrospira, Nocardiodes, Veillonella and g-norank-f-Vicinamibacteraceae were significantly enriched genera in Sichuan, llumatobacter was enriched in Hainan, and Pseudomonas was enriched in Hunan. The random forest classifier based on combined data on relative abundance and alpha diversity had a good ability to distinguish vaginal fluids with similar dominant microbial compositions in the three regions. The study suggests that combining high-throughput sequencing data with machine learning models has good potential for application in the biogeographic inference of vaginal fluids.

Identification of Mixtures of Two Types of Body Fluids Using the Multiplex Methylation System and Random Forest Models

OBJECTIVE

Body fluid mixtures are complex biological samples that frequently occur in crime scenes, and can provide important clues for criminal case analysis. DNA methylation assay has been applied in the identification of human body fluids, and has exhibited excellent performance in predicting single-source body fluids. The present study aims to develop a methylation SNaPshot multiplex system for body fluid identification, and accurately predict the mixture samples. In addition, the value of DNA methylation in the prediction of body fluid mixtures was further explored.

METHODS

In the present study, 420 samples of body fluid mixtures and 250 samples of single body fluids were tested using an optimized multiplex methylation system. Each kind of body fluid sample presented the specific methylation profiles of the 10 markers.

RESULTS

Significant differences in methylation levels were observed between the mixtures and single body fluids. For all kinds of mixtures, the Spearman's correlation analysis revealed a significantly strong correlation between the methylation levels and component proportions (1:20, 1:10, 1:5, 1:1, 5:1, 10:1 and 20:1). Two random forest classification models were trained for the prediction of mixture types and the prediction of the mixture proportion of 2 components, based on the methylation levels of 10 markers. For the mixture prediction, Model-1 presented outstanding prediction accuracy, which reached up to 99.3% in 427 training samples, and had a remarkable accuracy of 100% in 243 independent test samples. For the mixture proportion prediction, Model-2 demonstrated an excellent accuracy of 98.8% in 252 training samples, and 98.2% in 168 independent test samples. The total prediction accuracy reached 99.3% for body fluid mixtures and 98.6% for the mixture proportions.

CONCLUSION

These results indicate the excellent capability and powerful value of the multiplex methylation system in the identification of forensic body fluid mixtures.

Construction and evaluation of in-house methylation-sensitive SNaPshot system and three classification prediction models for identifying the tissue origin of body fluid

The identification of tissue origin of body fluid can provide clues and evidence for criminal case investigations. To establish an efficient method for identifying body fluid in forensic cases, eight novel body fluid-specific DNA methylation markers were selected in this study, and a multiplex singlebase extension reaction (SNaPshot) system for these markers was constructed for the identification of five common body fluids (venous blood, saliva, menstrual blood, vaginal fluid, and semen). The results indicated that the in-house system showed good species specificity, sensitivity, and ability to identify mixed biological samples. At the same time, an artificial body fluid prediction model and two machine learning prediction models based on the support vector machine (SVM) and random forest (RF) algorithms were constructed using previous research data, and these models were validated using the detection data obtained in this study (n=95). The accuracy of the prediction model based on experience was 95.79%; the prediction accuracy of the SVM prediction model was 100.00% for four kinds of body fluids except saliva (96.84%); and the prediction accuracy of the RF prediction model was 100.00% for all five kinds of body fluids. In conclusion, the in-house SNaPshot system and RF prediction model could achieve accurate tissue origin identification of body fluids.

Unlocking the potential of forensic traces: Analytical approaches to generate investigative leads

Forensic investigation involves gathering the information necessary to understand the criminal events as well as linking objects or individuals to an item, location or other individual(s) for investigative purposes. For years techniques such as presumptive chemical tests, DNA profiling or fingermark analysis have been of great value to this process. However, these techniques have their limitations, whether it is a lack of confidence in the results obtained due to cross-reactivity, subjectivity and low sensitivity; or because they are dependent on holding reference samples in a pre-existing database. There is currently a need to devise new ways to gather as much information as possible from a single trace, particularly from biological traces commonly encountered in forensic casework. This review outlines the most recent advancements in the forensic analysis of biological fluids, fingermarks and hair. Special emphasis is placed on analytical methods that can expand the information obtained from the trace beyond what is achieved in the usual practices. Special attention is paid to those methods that accurately determine the nature of the sample, as well as how long it has been at the crime scene, along with individualising information regarding the donor source of the trace.

On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime

Body fluid and body tissue identification are important in forensic science as they can provide key evidence in a criminal investigation and may assist the court in reaching conclusions. Establishing a link between identifying the fluid or tissue and the DNA profile adds further weight to this evidence. Many forensic laboratories retain techniques for the identification of biological fluids that have been widely used for some time. More recently, many different biomarkers and technologies have been proposed for identification of body fluids and tissues of forensic relevance some of which are now used in forensic casework. Here, we summarize the role of body fluid/ tissue identification in the evaluation of forensic evidence, describe how such evidence is detected at the crime scene and in the laboratory, elaborate different technologies available to do this, and reflect real life experiences. We explain how, by including this information, crucial links can be made to aid in the investigation and solution of crime.

A novel multiplex assay system based on 10 methylation markers for forensic identification of body fluids

Identifying the source of body fluids found at a crime scene is an essential forensic step. Some methods based on DNA methylation played significant role in body fluids identification. Since DNA methylation is related to multiple factors, such as race, age, and diseases, it is necessary to know the methylation profile of a given population. In this study, we tested 19 body fluid-specific methylation markers in a Chinese Han population. A novel multiplex assay system based on the selected markers with smaller variation in methylation and stronger tissue-specific methylation were developed for the identification of body fluids. The multiplex assay were tested in 265 body fluid samples. A random forest model was established to predict the tissue source based on the methylation data of the 10 markers. The multiplex assay was evaluated by testing the sensitivity, the mixtures, and old samples. For the result, the novel multiplex assay based on 10 selected methylation markers presented good methylation profiles in all tested samples. The random forest model worked extremely well in predicting the source of body fluids, with an accuracy of 100% and 97.5% in training data and test data, respectively. The multiplex assay could accurately predict the tissue source from 0.5 ng genomic DNA, six-months-old samples and distinguish the minor component from a mixture of two components. Our results indicated that the methylation multiplex assay and the random forest model could provide a convenient tool for forensic practitioners in body fluid identification.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Application of fragment analysis based on methylation status mobility difference to identify vaginal secretions

Identifying vaginal secretions attaching or adhering to a suspect's belongings would be beneficial for reconstructing the events that have taken place during a sexual assault. The present study describes a novel approach to identify vaginal secretions by fragment analysis using capillary electrophoresis, based on the mobility differences of PCR amplicons from bisulfite-treated DNA depending on methylation status. We targeted three genome regions including each of three vaginal secretion-specific methylated CpG sites reported previously: cg25416153, cg09765089, and cg14991487. In all three genome regions, the amplicon peaks for methylated genomic DNA (gDNA) sequences were only detected in vaginal samples, whereas samples of other body fluids (blood, saliva, semen, and deposit on skin surface) only showed amplicon peaks for unmethylated gDNA sequences. In vaginal secretions, the methylation ratio of each of the three targeted regions between samples was variable, while the ratios at the three regions in each sample were similar. Furthermore, commercial vaginal epithelial cells were completely methylated at the three regions. Therefore, vaginal secretion-specific methylation may derive from vaginal epithelial cells present in the sample. In forensic cases with a limited amount of DNA, the reproducibility of a detected peak using the present method is not high due to degradation of DNA by bisulfite treatment and subsequent stochastic PCR bias. However, it was possible to detect peaks from methylated DNA sequences by performing PCR and capillary electrophoresis in triplicate after bisulfite treatment, even when bisulfite treatment was performed using 0.5 ng of gDNA from vaginal secretions. In addition, the level of methylation at each targeted region was found to be stable in vaginal secretions stored for 1 year at room temperature. Therefore, we conclude that detection of the visual peak from vaginal secretion-specific methylated DNA sequence is useful to prove the presence of vaginal secretions. This approach has the potential to analyze multiple marker regions simultaneously, and may provide a new multiplex assay to identify various body fluids.

Entropy Indicators: An Approach for Low-Speed Bearing Diagnosis

To increase the competitiveness of wind energy, the maintenance costs of offshore floating and fixed wind turbines need to be reduced. One strategy is the enhancement of the condition monitoring techniques for pitch bearings, because their low operational speed and the high loads applied to them make their monitoring challenging. Vibration analysis has been widely used for monitoring the bearing condition with good results obtained for regular bearings, but with difficulties when the operational speed decreases. Therefore, new techniques are required to enhance the capabilities of vibration analysis for bearings under such operational conditions. This study proposes the use of indicators based on entropy for monitoring a low-speed bearing condition. The indicators used are approximate, dispersion, singular value decomposition, and spectral entropy of the permutation entropy. This approach has been tested with vibration signals acquired in a test rig with bearings under different health conditions. The results show that entropy indicators (EIs) can discriminate with higher-accuracy damaged bearings for low-speed bearings compared with the regular indicators. Furthermore, it is shown that the combination of regular and entropy-based indicators can also contribute to a more reliable diagnosis.