Signatures of vaginal microbiota by 16S rRNA gene: potential bio-geographical application in Chinese Han from three regions of China

Temporal dynamics changes in the vaginal fluid microbiome: Implications for body fluid identification and estimating time since deposition (TsD) for forensics

Vaginal fluid analysis plays a crucial role in sexual assault investigations. However, vaginal fluid found at crime scenes is usually subject to a certain duration of exposure. This study thus aimed to assess the influence of different durations of exposure to indoor environment on the vaginal microbiota. The 16S rDNA high-throughput sequencing was used on vaginal fluid samples exposed for short-term (30 days) and long-term (240 days), respectively. Despite potential contamination from environmental microorganisms, particularly following long-term exposure, the results indicated that the vaginal microbiota after exposure was still dominated by Lactobacillus. Both in short-term and long-term exposure involving vaginal fluid, there were clusters with time-dependent characteristics, wherein the relative abundances of associated microbial genera showed a trend of increasing or decreasing over time. In addition, each bodily fluid presented with a unique array of dominant bacterial genera, enabling the differentiation of exposed vaginal fluid samples from other bodily fluids (semen, skin, saliva, feces) with a remarkable 98.75 % accuracy rate. Furthermore, the mean absolute error achieved by the long-term deposition time prediction model was 13.54 days. The mean absolute error for the short-term deposition time prediction model was notably lower, reaching just 2.05 days. In summary, this study investigates the variations in microbial communities within vaginal fluid subjected to different indoor exposure durations and explores their potential in body fluid identification and estimating the time since deposition, thereby contributing valuable supporting evidence in forensic investigations.

Changes in the microbial community of semen exposed to different simulated forensic situations

Semen is one of the common body fluids in sexual crime cases. The current methods of semen identification have certain limitations, so it is necessary to search for other methods. In addition, there are few reports of microbiome changes in body fluids under simulated crime scenes. It is essential to further reveal the changes in semen microbiomes after exposure to various simulated crime scenes. Semen samples from eight volunteers were exposed in closed plastic bags, soil, indoor, cotton, polyester, and wool fabrics. A total of 68 samples (before and after exposure) were collected, detected by 16S rDNA sequencing, and analyzed for the microbiome signature. Finally, a random forest model was constructed for body fluid identification. After exposure, the relative abundance of Pseudomonas and Rhodococcus changed dramatically in almost all groups. In addition, the treatment with the closed plastic bags or soil groups had a greater impact on the semen microbiome. According to the Shannon indices, the alpha diversity of the closed plastic bags and soil groups was much lower than that of the other groups. Attention should be given to the above two scenes in practical work of forensic medicine. In this study, the accuracy of semen recognition was 100%. The exposed semen can still be correctly identified as semen based on its microbiota characteristics. In summary, semen microbiomes exposed to simulated crime scenes still have good application potential for body fluid identification.

IMPORTANCE

In this study, the microbiome changes of semen exposed to different environments were observed, and the exposed semen microbiome still has a good application potential in body fluid identification.

The vaginal microbiota of healthy female cats

The vaginal microbiota of the queen (i.e., female cat) has never been described using culture independent methods. The objectives of the present research were to describe the vaginal microbiota of healthy domestic shorthair queens using both 16S rRNA sequencing and culture, and to assess the effects of age, living environment, and reproductive season on its composition. Thirty queens undergoing elective ovariectomy were included in the study. The vaginal samples were collected just before surgery, from animals under general anaesthesia. Two consecutive mini-swabs were introduced in the queens' vaginal tract. A preliminary study with 10 healthy queens aimed to negate sampling order's effect. Two consecutive samples for sequencing (5 queens, 10 swabs) and culture (5 queens, 10 swabs) were collected, confirming a match (100 % in culture, Bray-Curtis P = 0.96 in sequencing). The experiment included 20 queens that were prospectively grouped based on age (prepubertal N = 10, adult N = 10), living environment (indoor N = 10, outdoor N = 10), and time of the year, whether during the reproductive season (N = 10) or during seasonal anoestrous (N = 10). Bacteria were identified through metataxonomic analysis, amplifying the V1-V2 regions of 16S rRNA gene, and through standard culture followed by MALDI-TOF MS. The feline vaginal microbiota is dominated by Proteobacteria, Firmicutes, Bacteroidota, and Actinobacteria. Escherichia-Shigella, Streptococcus, and Pasteurella were the most abundant genera. Although culture underestimated bacterial richness and diversity compared to sequencing, Escherichia and Streptococcus were the most isolated bacteria. No bacterial growth was observed in 15 % of samples (N = 3/20), whereas growth of one or two bacterial species was observed in 64.7 % (N = 11/17) and 35.3 % (N = 6/17) of cases, respectively. No differences in terms of alpha (Kruskal-Wallis rank sum test P = 0.65) and beta diversity (Bray-Curtis, Unweighted and Weighted UniFrac analyses P > 0.5) were observed. Although a difference in alpha diversity based on phylogenetic tree (P = 0.02) was detected between indoor and outdoor queens. In conclusion, mixed and monoculture of Escherichia coli, Streptococcus canis, Staphylococcus felis, and Enterococcus spp. are normal findings within the cat vagina. Age and reproductive season do not influence the feline vaginal microbiota, whereas further research is needed to elucidate the role of the living environment.

Response of salivary microbiome to temporal, environmental, and surface characteristics under in vitro exposure

The microbiome of saliva stains deposited at crime scenes and in everyday settings is valuable for forensic investigations and environmental ecology. However, the dynamics and applications of microbial communities in these saliva stains have not been fully explored. In this study, we analyzed saliva samples that were exposed to indoor conditions for up to 1 year and to different carriers (cotton, sterile absorbent cotton swab, woolen, dacron) in both indoor and outdoor environments for 1 month using high-throughput sequencing. The analysis of microbial composition and Mfuzz clustering showed that the salivary flora, specifically Streptococcus (cluster7), which was associated with microbial contamination, remained stable over short periods of time. However, prolonged exposure led to significant differences due to the invasion of environmental bacteria such as Pseudomonas and Achromobacter. The growth and colonization of environmental flora were promoted by humidity. The neutral model predictions indicated that the assembly of salivary microbial communities in outdoor environments was significantly influenced by stochastic processes, with environmental characteristics having a greater impact on community change compared to surface characteristics. By incorporating data from previous studies on fecal and vaginal secretion microbiology, we developed RF and XGBoost classification models that achieved high accuracy (>98 %) and AUC (>0.8). Additionally, a RF regression model was created to determine the time since deposition (TsD) of the stains. Time inference models yielded a mean absolute error (MAE) of 7.1 days for stains exposed for 1 year and 14.2 h for stains exposed for 14 days. These findings enhance our understanding of the changes in the microbiome of saliva stains over time, in different environments, and on different surfaces. They also have potential applications in assessing potential microbial contamination, identifying body fluids, and inferring the time of deposition.

Comparative analysis of the vaginal bacteriome and virome in healthy women living in high-altitude and sea-level areas

The vaginal microbiota plays an important role in the health of the female reproductive tract and is closely associated with various pregnancy outcomes and sexually transmitted diseases. Plenty of internal and external factors have strong influence on the changes in a woman's vaginal microbiome. However, the effect of a high-altitude on female vaginal microbiota has not been described. In this study, we characterized the vaginal bacteriome and virome of 13 and 34 healthy women living in high-altitude and sea-level areas, using whole-metagenome shotgun sequencing of their vaginal mucus samples. The results revealed that the vaginal bacteriomes of high-altitude individuals are featured by a significant increase of species diversity, depletion of Lactobacillus crispatus, and more abundant of some anaerobic bacteria, such as Chlamydia trachomatis, Mageeibacillus indolicus, Dialister micraerophilus, and Sneathia amnii). In addition, the vagina samples of sea-level subjects harbor more Lactobacillus strains, whereas the anaerobic bacteroidetes strains mostly appeared in high-altitude subjects. Identified and assembled 191 virus operational taxonomic units (vOTUs), there were significant differences in the abundance of 107 vOTUs between the two groups. Together, the results of this study raised the understanding of bacteriome and virome in the vagina of women at different elevations, and demonstrated that the vaginal microbiome is related to the high-altitude geographic adaptation.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

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.

Alterations in vaginal microbiota in uterine fibroids patients with ultrasound-guided high-intensity focused ultrasound ablation

Introduction

Vaginal microbiota dysbiosis is closely related to diseases of the vagina and uterus. Uterine fibroids (UF) are the most common benign neoplasms of the uterus, and increased diversity in vaginal microbial of UF patients. High-intensity focused ultrasound (HIFU) is effective invasive treatment for fibroids in women who are not good surgical candidates. Whether HIFU of uterine fibroids will cause the change in vaginal microbiota has not been reported. We aimed to investigate the vaginal microbiota of UF patients with/without HIFU treatment using 16S rRNA gene sequencing.

Methods

Vaginal secretions were collected from 77 UF patients (pre-operative and post-operative) and were used for comparative composition, diversity, and richness analyses of microbial communities.

Results

The microbial α-diversity was significantly lower in the vaginal of UF patients with HIFU treatment. The relative abundance of some pathogenic bacteria of UF patients with HIFU treatment were significantly decreased in the bacterial phylum and genus level. Proteobacteria were found to be significantly upregulated as a biomarker in the HIFU treatment group in our study.

Conclusion

These findings might confirm the effectiveness of HIFU treatment from the point of view of microbiota.

Extension of bacterial rDNA sequencing for simultaneous methylation detection and its application in microflora analysis

Although polymerase chain reaction (PCR) amplification and sequencing of the bacterial 16S rDNA region has numerous scientific applications, it does not provide DNA methylation information. Herein, we propose a simple extension for bisulfite sequencing to investigate 5-methylcytosine residues in the bacterial 16S rDNA region from clinical isolates or flora. Multiple displacement amplification without DNA denaturation was used to preferentially pre-amplify single-stranded bacterial DNA after bisulfite conversion. Following the pre-amplification, the 16S rDNA region was analyzed using nested bisulfite PCR and sequencing, enabling the simultaneous identification of DNA methylation status and sequence data. We used this approach (termed sm16S rDNA PCR/sequencing) to identify novel methylation sites and a methyltransferase (M. MmnI) in Morganella morganii and different methylation motifs among Enterococcus faecalis strains from small volumes of clinical specimens. Further, our analysis suggested that M. MmnI may be correlated to erythromycin resistance. Thus, sm16S rDNA PCR/sequencing is a useful extension method for analyzing the DNA methylation of 16S rDNA regions in a microflora, providing additional information not provided by conventional PCR. Given the relationship between DNA methylation status and drug resistance in bacteria, we believe this technique can be effectively applied in clinical sample testing.

Compositional Changes in the Vaginal Bacterial Microbiome of Healthy Pregnant Women across the Three Gestational Trimesters in Ismailia, Egypt

The composition of the vaginal microbiome may lead to adverse pregnancy outcomes. Normal pregnancy is associated with changes in the vaginal bacterial community composition, which tend to be more enriched with one or two Lactobacillus species promoting a healthy vagina and favorable birth outcomes. The aim of the current study was to determine compositional changes in the healthy vaginal microbiome composition during the three trimesters of pregnancy in Ismailia, Egypt using Illumina MiSeq sequencing of the V3-V4 region of the 16S rRNA. The phylum Firmicutes and the genus Lactobacillus dominated across the three trimesters of pregnancy. L. iners was the most abundant species. However, L. coleohominis and L. reuteri represented the least dominant vaginal lactobacilli. Core microbiome analyses showed the Lactobacillus genus and L. iners species to have the highest prevalence in all the samples of our study groups. The phylum Firmicutes was found to be negatively correlated with almost all other vaginal phyla during pregnancy. Likewise, a negative correlation between Lactobacillus and almost all other genera was detected, including significant negative correlations with Dialister and Prevotella. Furthermore, negative correlations of L. iners were detected with almost all other species, including a significant negative correlation with L. helveticus, G. vaginalis, S. anginosus, and S. agalactiae.

Integrating the salivary microbiome in the forensic toolkit by 16S rRNA gene: potential application in body fluid identification and biogeographic inference

Saliva is a common body fluid with significant forensic value used to investigate criminal cases such as murder and assault. In the past, saliva identification often relied on the α-amylase test; however, this method has low specificity and is prone to false positives. Accordingly, forensic researchers have been working to find new specific molecular markers to refine the current saliva identification approach. At present, research on immunological methods, mRNA, microRNA, circRNA, and DNA methylation is still in the exploratory stage, and the application of these markers still has various limitations. It has been established that salivary microorganisms exhibit good specificity and stability. In this study, 16S rDNA sequencing technology was used to sequence the V3-V4 hypervariable regions in saliva samples from five regions to reveal the role of regional location on the heterogeneity in microbial profile information in saliva. Although the relative abundance of salivary flora was affected to a certain extent by geographical factors, the salivary flora of each sample was still dominated by Streptococcus, Neisseria, and Rothia. In addition, the microbial community in the saliva samples in this study was significantly different from that in the vaginal secretions, semen, and skin samples reported in our previous studies. Accordingly, saliva can be distinguished from the other three body fluids and tissues. Moreover, we established a prediction model based on the random forest algorithm that could distinguish saliva between different regions at the genus level even though the model has a certain probability of misjudgment which needs more in-depth research. Overall, the microbial community information in saliva stains might have prospects for potential application in body fluid identification and biogeographic inference.

Comparative Evaluation of the Salivary and Buccal Mucosal Microbiota by 16S rRNA Sequencing for Forensic Investigations

The human microbiome has emerged as a new potential biomarker for forensic investigations with the development of high-throughput sequencing and bioinformatic analysis during the last decade. The oral cavity has many different microbial habitats, with each habit colonized by specific and individualized microbiota. As saliva and buccal mucosa are common biological evidence in forensic science, understanding the differences of microbial communities between the two is important for forensic original identification. Moreover, the oral microbiota is individualized, whereas there are few studies on the application of forensic personal identification that need to be supplemented. In this study, Streptococcus was the most abundant genus, with an average relative abundance of 49.61% in the buccal mucosa, while in the saliva, Streptococcus, Veillonella, and Neisseria had similar proportions (20%, 15%, 16%) and were the dominant genera. The α and β diversity displayed a significant distinctness between the saliva and buccal mucosal groups. The community assembly mechanism stated that the deterministic process played a more significant effect in shaping the salivary bacterial community assembly than buccal mucosa, which explained the microbial differences. Of the test samples, 93.3% can be correctly classified with the random forest model based on the microbial differences. Targeting the low-abundance bacteria at the species level, 52% of experimental participants could be discriminated by using the observed unique bacterial species. In conclusion, the salivary bacterial community composition differed from that of the buccal mucosa and showed high richness and diversity. With the random forest model, the microbiota of saliva and buccal mucosa can be classified, which can be used in identifying the source of oral biological trace. Furthermore, each individual has a unique bacterial community pattern, and the presence or absence of unique bacteria and differences in the composition of the core oral microbiota are the key points for forensic personal discrimination that supplement the study of oral microbial application to forensic personal discrimination. Whether for original identification or personal discrimination, the oral microbiome has great potential for application.