An accurate bacterial DNA quantification assay for HTS library preparation of human biological samples

Development of a multiplex PCR assay and quantification of microbial markers by ddPCR for identification of saliva and vaginal fluid

The identification of biological fluids at crime scenes contributes to crime scene reconstruction and provides investigative leads. Traditional methods for body fluid identification are limited in terms of sensitivity and are mostly presumptive. Emerging methods based on mRNA and DNA methylation require high quality template source. An exploitable characteristic of body fluids is their distinct microbial profiles allowing for the discrimination of body fluids based on microbiome content. Microbial DNA is highly abundant within the body, robust and stable and can persist in the environment long after human DNA has degraded. 16S rRNA sequencing is the gold standard for microbial analysis; however, NGS is costly, and requires intricate workflows and interpretation. Also, species level resolution is not always achievable. Based on the current challenges, the first objective of this study was to develop a multiplex conventional PCR assay to identify vaginal fluid and saliva by targeting species-specific 16S rRNA microbial markers. The second objective was to employ droplet digital PCR (ddPCR) as a novel approach to quantify bacterial species alone and in a mixture of body fluids. Lactobacillus crispatus and Streptococcus salivarius were selected because of high abundance within vaginal fluid and saliva respectively. While Fusobacterium nucleatum and Gardnerella vaginalis, though present in healthy humans, are also frequently found in oral and vaginal infections, respectively. The multiplex PCR assay detected L. crispatus and G. vaginalis in vaginal fluid while F. nucleatum and S. salivarius was detected in saliva. Multiplex PCR detected F. nucleatum, S. salivarius and L. crispatus in mixed body fluid samples while, G. vaginalis was undetected in mixtures containing vaginal fluid. For samples exposed at room temperature for 65 days, L. crispatus and G. vaginalis were detected in vaginal swabs while only S. salivarius was detected in saliva swabs. The limit of detection was 0.06 copies/µl for F. nucleatum (2.5 ×10-9 ng/µl) and S. salivarius (2.5 ×10-6 ng/µl). L. crispatus and G. vaginalis had detection limits of 0.16 copies/µl (2.5 ×10-4 ng/µl) and 0.48 copies/µl (2.5 ×10-7 ng/µl). All 4 bacterial species were detected in mixtures and aged samples by ddPCR. No significant differences were observed in quantity of bacterial markers in saliva and vaginal fluid. The present research reports for the first time the combination of the above four bacterial markers for the detection of saliva and vaginal fluid and highlights the sensitivity of ddPCR for bacterial quantification in pure and mixed body fluids.

A bacterial signature-based method for the identification of seven forensically relevant human body fluids

Detection and identification of body fluids plays a crucial role in criminal investigation, as it provides information on the source of the DNA as well as corroborative evidence regarding the crime committed, scene, and/or association with persons of interest. Historically, forensic serological methods have been chemical, immunological, catalytic, spectroscopic, and/or microscopic in nature. However, most of these methods are presumptive, with few robust confirmatory exceptions. In recent years several new molecular methods (mRNA, miRNA, DNA methylation, etc.) have been proposed; although promising, these methods require high quality human DNA or RNA. Additional steps are required in RNA based methods. Additionally, RNA based methods cannot be used for old cases where only DNA extracts remain to sample from. In this study, a novel non-human DNA (microbiome) based method was developed for the identification of the majority of forensically relevant human biological samples. Eight hundred and twelve (n = 812) biological samples (semen, vaginal fluid, menstrual blood, saliva, feces, urine, and blood) were collected and preserved using methods commonly used in forensic laboratories for evidence collection. Variable region four (V4) of 16 S ribosomal DNA (16 S rDNA) was amplified using a dual-indexing strategy and then sequenced on the MiSeq FGx sequencing platform using the MiSeq Reagent Kit v2 (500 cycles) and following the manufacturer's protocol. Machine learning prediction models were used to assess the classification accuracy of the newly developed method. As there was no significant difference in bacterial communities between vaginal fluid, menstrual blood, and female urine, these were combined as female intimate samples. Except in urine, the bacterial structures associated with male and female body fluid samples were not significantly different from one another. The newly developed method accurately identified human body fluid samples with an overall accuracy of more than 88%. This newly developed bacterial signature-based method is fast (no additional steps are needed as the same DNA can be used for both body fluid identification and STR typing), efficient (consume less sample as a single test can identify all major body fluids), sensitive (needs only 5 pg of bacterial DNA), accurate, and can be easily added into a forensic high throughput sequencing (HTS) panel.

Microbial ecology of vertebrate decomposition in terrestrial ecosystems

Vertebrate decomposition results in an ephemeral disturbance of the surrounding environment. Microbial decomposers are recognized as key players in the breakdown of complex organic compounds, controlling carbon and nutrient fate in the ecosystem and potentially serving as indicators of time since death for forensic applications. As a result, there has been increasing attention on documenting the microbial communities associated with vertebrate decomposition, or the 'necrobiome'. These necrobiome studies differ in the vertebrate species, microhabitats (e.g. skin vs. soil), and geographic locations studied, but many are narrowly focused on the forensic application of microbial data, missing the larger opportunity to understand the ecology of these communities. To further our understanding of microbial dynamics during vertebrate decomposition and identify knowledge gaps, there is a need to assess the current works from an ecological systems perspective. In this review, we examine recent work pertaining to microbial community dynamics and succession during vertebrate (human and other mammals) decomposition in terrestrial ecosystems, through the lens of a microbial succession ecological framework. From this perspective, we describe three major microbial microhabitats (internal, external, and soil) in terms of their unique successional trajectories and identify three major knowledge gaps that remain to be addressed.

Machine learning clustering and classification of human microbiome source body sites

Distinct microbial signatures associated with specific human body sites can play a role in the identification of biological materials recovered from the crime scene, but at present, methods that have capability to predict origin of biological materials based on such signatures are limited. Metagenomic sequencing and machine learning (ML) offer a promising enhancement to current identification protocols. We use ML for forensic source body site identification using shotgun metagenomic sequenced data to verify the presence of microbiomic signatures capable of discriminating between source body sites and then show that accurate prediction is possible. The consistency between cluster membership and actual source body site (purity) exceeded 99% at the genus taxonomy using off-the-shelf ML clustering algorithms. Similar results were obtained at the family level. Accurate predictions were observed for genus, family, and order taxonomies, as well as with a core set of 51 genera. The accurate outcomes from our replicable process should encourage forensic scientists to seriously consider integrating ML predictors into their source body site identification protocols.

Development of a quantitative PCR-based method for studying temporal DNA degradation in waterlogged bone

While several studies have examined temporal DNA degradation in bones collected from terrestrial environments, studies on temporal DNA degradation in bones collected from aquatic environments are limited and mostly based on case studies. The objective of this study was to assess the impact of long-term submersion, aquatic environment, bone type and DNA extraction method on DNA quality and quantity. Bone samples (scapulae and ribs), collected every ~1000 ADD from a freshwater lake and river, underwent DNA extraction via ChargeSwitch^® gDNA Plant Kit and organic phenol-chloroform methods, and DNA quantitation using both TaqMan and SYBR Green-based quantitative PCR (qPCR) methods. Results suggest that in both bone types, quality of recovered DNA (i.e., degradation index) declined significantly with increase in submersion time. Among two bone types, quality of recovered DNA from scapulae declined faster than rib samples. There was no significant difference in recovered DNA quantity between bone types, DNA extraction methods, or locations but various interactions between these variables showed significant difference. Overall, it can be concluded that DNA can be extracted from waterlogged bone in sufficient quantity to generate an STR profile up to 4000 ADD.

Evaluation of 16S rRNA Hypervariable Regions for Bioweapon Species Detection by Massively Parallel Sequencing

Molecular detection and classification of the bacterial groups in a sample are relevant in several areas, including medical research and forensics. Sanger sequencing of the 16S rRNA gene is considered the gold standard for microbial phylogenetic analysis. However, the development of massively parallel sequencing (MPS) offers enhanced sensitivity and specificity for microbiological analyses. In addition, 16S rRNA target amplification followed by MPS facilitates the combined use of multiple markers/regions, better discrimination of sample background, and higher sample throughput. We designed a novel set of 16S rRNA gene primers for detection of bacterial species associated with clinical, bioweapon, and biohazards microorganisms via alignment of 364 sequences representing 19 bacterial species and strains relevant to medical and forensics applications. In silico results indicated that the hypervariable regions (V1V2), (V4V5), and (V6V7V8) support the resolution of a selected group of bacteria. Interspecies and intraspecies comparisons showed 74.23%–85.51% and 94.48%–99.98% sequencing variation among species and strains, respectively. Sequence reads from a simulated scenario of bacterial species mapped to each of the three hypervariable regions of the respective species with different affinities. The minimum limit of detection was achieved using two different MPS platforms. This protocol can be used to detect or monitor as low as 2,000 genome equivalents of bacterial species associated with clinical, bioweapon, and biohazard microorganisms and potentially can distinguish natural outbreaks of pathogenic microorganisms from those occurring by intentional release.

Metagenomic analysis of bacteria in stallion semen

Bacteria colonize stallion semen during collection and processing which may cause disease in inseminated females or negatively affect sperm quality during storage prior to insemination. Antibiotics are added to semen extenders to control the growth of these bacteria but may induce antimicrobial resistance. Research into alternatives to antibiotics for this purpose requires knowledge of which bacteria are present in semen. Not all bacteria in semen, however, can be identified by conventional microbiological techniques. The objectives of the study were to: i) determine which bacteria are present in stallion semen using metagenomics; and ii) investigate individual differences in bacterial content in semen from all stallions on one premises. Bacterial DNA was extracted from ejaculates from seven stallions (one ejaculate per stallion) and bacteria were identified using 16S sequencing. In total, 83 bacterial genera were identified, varying from 25 to 52 among different individuals. There was a negative correlation (r = -0.81212; P <  0.05) between the presence of Treponema spp. and Advenella spp. In conclusion, most of the bacteria present in stallion semen could be identified to genus level by 16S sequencing even when present at a low frequency. This method of identification may help to clarify individual variation in bacterial content and its potential effects on fertility.

Interpol review of forensic biology and forensic DNA typing 2016-2019

This review paper covers the forensic-relevant literature in biological sciences from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.

Technical pitfalls that bias comparative microbial community analyses of aquatic disease Ian Hewson

The accessibility of high-throughput DNA sequencing technologies has attracted the application of comparative microbial analyses to study diseases. These studies present a window into host microbiome diversity and composition that can be used to address ecological theory in the context of host biology and behavior. Recently, comparative microbiome studies have been used to study non-vertebrate aquatic diseases to elucidate microorganisms potentially involved in disease processes or in disease prevention. These investigations suffer from many well-described biases, especially prior to sequence analyses, that could lead to misleading conclusions. Microbiome-focused studies of aquatic metazoan diseases provide valuable documentation of microbial ecology, although, they are only a starting point for establishing disease etiology, which demands quantitative validation through targeted approaches. The microbiome approach to understanding disease is most useful after laboratory diagnostics guided by pathology have failed to identify a causative agent. This opinion piece presents several technical pitfalls which may affect wider interpretation of microbe-host interactions through comparative microbial community analyses and provides recommendations, based on studies in non-aquatic systems, for incorporation into future aquatic disease research.