Spatial and temporal influences on bacterial profiling of forensic soil samples

Bacterial content may be helpful in differentiating forensic soil samples; however, the effectiveness of bacterial profiling depends on several factors, including uniqueness among different habitat types, the level of heterogeneity within a habitat, and changes in bacterial communities over time. To examine these, soils from five diverse habitats were tested over a 1 year period using terminal restriction fragment length polymorphism (TRFLP) analysis. Soil samples were collected at central locations monthly, and 10 feet in cardinal directions quarterly. Similarity indices were found to be least related among habitats, while the greatest bacterial similarities existed among collection locations within a habitat. Temporally, however, bacterial content varied considerably, and there was substantial overlap in similarity indices among habitats during different parts of the year. Taken together, the results indicate that while bacterial DNA profiling may be useful for forensic soil analysis, certain variables, particularly time, must be considered.     

Assessing the potential of bacterial DNA profiling for forensic soil comparisons

A pilot study was undertaken to evaluate DNA profiling of the bacterial community in soil as an alternative to geological methods for forensic soil comparisons. Soil samples from three different ecosystems were compared, and the variation within and between ecologically different sites was determined by using terminal restriction fragment (TRF) analysis of 16S ribosomal DNA. Comparison of TRF profiles revealed that samples from within a specific ecosystem (e.g., a field) showed a significantly higher similarity to each other than to those from another ecosystem (e.g., a forest). In addition, some profile features were unique to specific ecosystems. These features may allow the determination of characteristic profiles that will facilitate identification of ecologically different sites, so that a given sample collected from a suspect could be identified as originating from, for example, a field, rather than a forest. The implications of these preliminary findings for forensic investigations are discussed.     

Microbial metagenome profiling using amplicon length heterogeneity-polymerase chain reaction proves more effective than elemental analysis in discriminating soil specimens

The combination of soil's ubiquity and its intrinsic abiotic and biotic information can contribute greatly to the forensic field. Although there are physical and chemical characterization methods of soil comparison for forensic purposes, these require a level of expertise not always encountered in crime laboratories. We hypothesized that soil microbial community profiling could be used to discriminate between soil types by providing biological fingerprints that confer uniqueness. Three of the six Miami-Dade soil types were randomly selected and sampled. We compared the microbial metagenome profiles generated using amplicon length heterogeneity-polymerase chain reaction analysis of the 16S rRNA genes with inductively coupled plasma optical emission spectroscopy analysis of 13 elements (Al, B, Ca, Cu, Fe, K, Mg, Mn, Na, P, S, Si, and Zn) that are commonly encountered in soils. Bray-Curtis similarity index and analysis of similarity were performed on all data to establish differences within sites, among sites, and across two seasons. These data matrices were used to group samples that shared similar community patterns using nonmetric multidimensional scaling analysis. We concluded that while chemical characterization could provide some differentiation between soils, microbial metagenome profiling was better able to discriminate between the soil types and had a high degree of reproducibility, therefore proving to be a potential tool for forensic soil comparisons.     

土壤细菌群体多样性的T-RFLP分析应用探讨

目的探讨土壤细菌群体多样性的末端限制性片段长度多态性（terminal restriction fragment length polymorphism，T-RFLP）分析在法庭科学应用的相关问题。方法依据不同土壤中的细菌群体存在多样性和差异，联合利用细菌16SrDNA序列、末端限制性片段长度多态性（terminal restriction fragment length polymorphism，T-RFLP）方法对5个来源不同的土壤样品和4个同一来源土壤样品的细菌群体多样性进行比较分析，计算土壤样品间的相似系数。结果不同来源的5个土壤样品间相似系数，最大者为0．44，最小为0．3；同一来源的4个土壤样品相似系数，最大为0．87，最小为0．76。结论不同来源土壤的细菌群体多样性存在差异。     

Time Radically Alters Ex Situ Evidentiary Soil 16S Bacterial Profiles Produced Via Next‐Generation Sequencing,,

Previous research has revealed the potential of soil bacterial profiling for forensic purposes; however, investigators have not thoroughly examined fluctuations in microbial profiles from soil aged on evidence. In this research, soils collected from multiple habitats were placed on evidence items and sampled over time, and then bacterial profiles were generated via next‐generation sequencing of the 16S rRNA locus. Bacterial abundance charts and nonmetric multidimensional scaling plots provided visual representation of bacterial profiles temporally, while supervised classification was used to statistically associate evidence to a source. The ex situ evidence soils displayed specific, consistent taxonomic changes as they aged, resulting in their drift in multidimensional space, but never toward a different habitat. Ninety‐five percent of the 364 evidentiary profiles statistically classified to the correct habitat, with misclassification generally stemming from evidence type and increased age. Ultimately, understanding bacterial changes that occur temporally in ex situ soils should enhance their use in forensic investigations.     

Identifying background microbiomes in an evidence recovery laboratory: A preliminary study

16S rRNA profiling of bacterial communities may have forensic utility in the identification or association of individuals involved with criminal activities. Microbial profiling of evidence may, in the future, be performed within environments currently utilised for human DNA recovery, such as a forensic biology laboratory. It would be important to establish the background microbiome of such an environment to determine the potential presence of human or environmental microbial signatures to assist forensic scientists in the appropriate interpretation of target microbial communities. This study sampled various surfaces of an Evidence Recovery Laboratory (ERL) on three occasions including (a) before a monthly deep-clean, (b) immediately following the deep-clean, and (c) immediately after the laboratory’s use by a single participant for the purposes of routine item examinations. Microbial profiles were also generated for the involved participant and researcher for comparison purposes. Additionally, human nuclear DNA was profiled for each of the samples collected, using standard forensic profiling techniques, to provide a prospective link to the presence or absence of a background microbial signature within the ERL after its use. Taxonomic distributions across ERL samples revealed no consistent signature of any of the items sampled over time, however, major phyla noted within all ERL samples across the three timepoints were consistent with those found in human skin microbiomes. PCoA plots based on the Unweighted Unifrac metric revealed some clustering between participant microbial reference samples and surfaces of the ERL after use, suggesting that despite a lack of direct contact, and adherence to standard operating procedures (SOPs) suitable for human DNA recovery, microbiomes may be deposited into a forensic setting over time. The reference samples collected from the involved participant and researcher generated full STR profiles. Human DNA was observed to varying degrees in samples taken from the ERL across each of the sampling timepoints. There was no correlation observed between samples that contained or did not contain detectable quantities of human nuclear DNA and microbial profile outputs.     

Next‐Generation Sequencing of the Bacterial 16S rRNA Gene for Forensic Soil Comparison: A Feasibility Study

Soil has the potential to be valuable forensic evidence linking a person or item to a crime scene; however, there is no established soil individualization technique. In this study, the utility of soil bacterial profiling via next‐generation sequencing of the 16S rRNA gene was examined for associating soils with their place of origin. Soil samples were collected from ten diverse and nine similar habitats over time, and within three habitats at various horizontal and vertical distances. Bacterial profiles were analyzed using four methods: abundance charts and nonmetric multidimensional scaling provided simplification and visualization of the massive datasets, potentially aiding in expert testimony, while analysis of similarities and k‐nearest neighbor offered objective statistical comparisons. The vast majority of soil bacterial profiles (95.4%) were classified to their location of origin, highlighting the potential of bacterial profiling via next‐generation sequencing for the forensic analysis of soil samples.     

Bioinformatics Approach to Assess the Biogeographical Patterns of Soil Communities: The Utility for Soil Provenance,

Soil DNA profiling has potential as a forensic tool to establish a link between soil collected at a crime scene and soil recovered from a suspect. However, a quantitative measure is needed to investigate the spatial/temporal variability across multiple scales prior to their application in forensic science. In this study, soil DNA profiles across Miami‐Dade, FL, were generated using length heterogeneity PCR to target four taxa. The objectives of this study were to (i) assess the biogeographical patterns of soils to determine whether soil biota is spatially correlated with geographic location and (ii) evaluate five machine learning algorithms for their predictive ability to recognize biotic patterns which could accurately classify soils at different spatial scales regardless of seasonal collection. Results demonstrate that soil communities have unique patterns and are spatially autocorrelated. Bioinformatic algorithms could accurately classify soils across all scales with Random Forest significantly outperforming all other algorithms regardless of spatial level.     

Bacterial Profiling of Soil Using Genus‐Specific Markers and Multidimensional Scaling*

Abstract: Forensic identification of soil based on microbial DNA fingerprinting has met with mixed success, with research efforts rarely considering temporal variability or local heterogeneity in soil’s microbial makeup. In the research presented, the nitrogen fixing bacteria rhizobia were specifically examined. Soils were collected monthly from five habitats for 1 year, and quarterly in each cardinal direction from the main collection site. When all habitats were compared simultaneously using Terminal Restriction Fragment Length Polymorphism analysis of the rhizobial recA gene and multidimensional scaling, only two were differentiated over a year’s time, however pairwise comparisons allowed four of five soils to be effectively differentiated. Adding in 10‐foot distant soils as “questioned” samples correctly grouped them in 40–70% of cases, depending on restriction enzyme used. The results indicate that the technique has potential for forensic soil identification, although extensive anthropogenic manipulation of a soil makes such identification much more tentative.     

Limitations and recommendations for successful DNA extraction from forensic soil samples: A review

Soil is commonly used in forensic casework to provide discriminatory power to link a suspect to a crime scene. Standard analyses examine the intrinsic properties of soils, including mineralogy, geophysics, texture and colour; however, soils can also support a vast amount of organisms, which can be examined using DNA fingerprinting techniques. Many previous genetic analyses have relied on patterns of fragment length variation produced by amplification of unidentified taxa in the soil extract. In contrast, the development of advanced DNA sequencing technologies now provides the ability to generate a detailed picture of soil microbial communities and the taxa present, allowing for improved discrimination between samples. However, DNA must be efficiently extracted from the complex soil matrix to achieve accurate and reproducible DNA sequencing results, and extraction efficacy is highly dependent on the soil type and method used. As a result, a consideration of soil properties is important when estimating the likelihood of successful DNA extraction. This would include a basic understanding of soil components, their interactions with DNA molecules and the factors that affect such interactions. This review highlights some important considerations required prior to DNA extraction and discusses the use of common chemical reagents in soil DNA extraction protocols to achieve maximum efficacy. Together, the information presented here is designed to facilitate informed decisions about the most appropriate sampling and extraction methodology, relevant both to the soil type and the details of a specific forensic case, to ensure sufficient DNA yield and enable successful analysis.     

Soil sample metagenome NGS data management for forensic investigation

Soil analysis is a valuable resource in forensic investigation. Classical forensic soil analysis involves examination of its physical characteristics and chemical composition, such as soil type, colour, particle size, shape, pH, elemental, mineral and organic content. However the limited variability of these parameters is not always allowing adequate discrimination between soil samples. As soil supports extreme diversity of microorganisms and eukaryotic communities, microbiological approaches have been proposed. Several molecular approaches for microbial DNA profiling are available; however there is a lack of published data of implementation of the next generation sequencing (NGS) approaches for forensic soil analysis.The aim of the current study was elaboration of criteria for soil metagenome data management and database searching. We used our previously sequenced collection of 11 samples collected from different environments (forests, fields, grasslands, urban park) with different flora. The single sample collection includes 9 soil samples per one sampling area (30 m × 30 m) spaced by 15 m. In the current study we concentrated mainly on 18S rRNA gene V2-V3 region for fungi however SSU rRNA region for arbuscular mycorrhizal (AMF) fungi and V2-V3 hypervariable region of 16S rRNA gene for bacterial communities were taken into account. The sequencing was performed by Roche/454 platform. For data analysis OTU based approach on mothur software and NCBI BLASTN search were used. NCBI BLASTN analysis revealed altogether 2983 AMF matches and 8997 18S matches as well as 25477 OTUs (16S) were determined. Several data filtration approaches were used for data management. We found that 18S marker results could be used to create and run a filtered database that is computationally much more efficient and flexible. Our results have broad impact; however more samples have to be analysed, additional studies performed and cooperation between soil scientists and forensic scientists is required to be able to implement these novel techniques into the routine forensic practice.     

Forensic comparison of soils by bacterial community DNA profiling

This preliminary investigation has shown that a soil microbial community DNA profile can be obtained from the small sample of soil recovered from the sole of a shoe, and from soil stains on clothing. We have also shown that these profiles are representative of the site of collection and therefore could potentially be used as associative evidence to prove a link between suspects and crime scenes. Soil community profiles were obtained using the T-RFLP fingerprinting method that uses fluorescent primer technology and semi-automated analysis techniques similar to those used in human DNA profiling in forensic laboratories.     

High‐throughput Sequencing of Trace Quantities of Soil Provides Reproducible and Discriminative Fungal DNA Profiles

High‐throughput sequencing (HTS) offers improved resolution between forensic soil samples by characterizing individual taxa present; however, the heterogeneous distribution of taxa in soils, and limited quantity of material available, may hinder the reliability of HTS in casework. Using HTS of the internal transcribed spacer, we examined the effect of soil mass (50, 150, and 250 mg) on fungal DNA profiles, focusing on reproducibility and discriminatory power between close proximity soils, and samples with similar textural classification. The results show that reduced soil mass had no significant effect on sample differentiation and that 150 mg soil provides the most reproducible DNA profiles across different soil types. In addition, Ascomycota was identified as a robust fungal target for forensic intelligence as this phylum was detected consistently across all samples regardless of sample quantity. Overall, this study highlights the value of trace quantities of soil for use in forensic casework.     

The Microbiome Forensics Database UZH

Microbial communities in biological stains can provide valuable information to assist forensic scientists identify the body fluid/tissue present in these. As these microbial communities are characteristic of body habitats, DNA sequencing of microbes can be used to predict bodily origin. Promising predictive results have been obtained with supervised machine learning algorithms trained on bacterial abundance data from human body sites. Importantly, prediction accuracy is dependent on the training dataset, yet compiling a large and comprehensive training reference is a non-trivial issue requiring substantial efforts. Here we present a new online database and associated data-mining platform which is, to our knowledge, the first one customised for forensic scientists investigating body fluids/tissues. Our database features samples originating from ten human body sites, with selection options through an online platform. Users can download bacterial abundance as well as taxonomic data, which can then be used to train predictive models and test their accuracy. Future stages of the development of the platform will include curation of the samples to decrease potential errors in sample labelling, as well as access to an online tool to conduct exploratory analyses.     

Informativeness of NGS Analysis for Vaginal Fluid Identification

The identification of vaginal fluids in forensic examinations plays an important role in crime scene reconstruction. Molecular detection of vaginal bacterial communities can lead to the correct discrimination of body fluids. These kinds of studies can be performed through multiplex real‐time PCR using primers for a specific selection of bacteria. The availability of next‐generation sequencing (NGS) protocols provided for the extension of the analysis to evaluate the prokaryotes present in specimens. In this study, DNA was extracted from 18 samples (vaginal, oral, fecal, yoghurt) and analyzed by real‐time PCR and NGS. The comparison between the two approaches has demonstrated that the information developed through NGS can augment the more conventional real‐time PCR detection of a few key bacterial species to provide a more probative result and the correct identification of vaginal fluid from samples that are more forensically challenged.     

“YFlag” – A Single‐base Extension Primer Based Method for Gender Determination

Assigning the gender of a DNA contributor in forensic analysis is typically achieved using the amelogenin test. Occasionally, this test produces false‐positive results due to deletions occurring on the Y chromosome. Here, a four‐marker “YFlag” method is presented to infer gender using single‐base extension primers to flag the presence (or absence) of Y‐chromosome DNA within a sample to supplement forensic STR profiling. This method offers built‐in redundancy, with a single marker being sufficient to detect the presence of male DNA. In a study using 30 male and 30 female individuals, detection of male DNA was achieved with c. 0.03 ng of male DNA. All four markers were present in male/female mixture samples despite the presence of excessive female DNA. In summary, the YFlag system offers a method that is reproducible, specific, and sensitive, making it suitable for forensic use to detect male DNA.     

Bacterial Profiling of Soil For Forensic Investigations: Consideration of Ex Situ Changes in Questioned and Known Soil Samples

Soil, being diverse and ubiquitous, can potentially link a suspect or victim to a crime scene. Recently scientists have examined the microbial makeup of soil for determining its origin, and differentiating soil samples is well-established. However, when soil is transferred to evidence its microbial makeup may change over time, leading to false exclusions. In this research, “known” soils from diverse habitats were stored under controlled conditions, while evidence soils were aged on mock evidence. Limited quantities of soil were also assayed. Bacterial profiles were produced using next-generation sequencing of the 16S rRNA gene. Overall, known soils stored open at room temperature were more similar to evidence soils over time than were known soils stored bagged and/or frozen. Evidence soils, even as little as 1 mg, associated with the correct habitat 99% of the time, accentuating the importance of considering ex situ microbial changes in soil for its successful use as forensic evidence.     

Use of the genomic matching technique to complement multiplex STR profiling reduces DNA profiling costs in high volume crimes and intelligence led screens

The genomic matching technique (GMT) targets duplicated polymorphic sequences within genomic blocks in the human major histocompatibility complex (MHC), differentiating between individuals at the DNA level using a single primer pair per block. The GMT is currently used to supplement human leukocyte antigen (HLA) typing to match donor and recipient pairs for bone marrow transplantation and has the potential to be employed as a powerful exclusion tool in forensic biology. The GMT is highly reproducible, produces DNA profiles from less than 1 ng of DNA and was successfully employed to profile a range of forensic samples including buccal swabs, handled objects and fingerprints. Furthermore, GMT profiles from a single genomic block in the MHC are likely to be more discriminatory than known highly polymorphic short tandem repeat (STR) loci such as ACTBP2. As such, the GMT can reduce the cost of investigations that require profiling of multiple suspects or samples from one or more crime scenes and could be extended to profile genomic blocks in other polymorphic genetic systems in the human genome.     

Comparison of two whole genome amplification methods for STR genotyping of LCN and degraded DNA samples

The analysis of LCN or highly degraded DNA samples presents a challenge for forensic science. Improving the quantity and/or quality of samples would greatly increase the profiling success rate from LCN and degraded samples. Whole genome amplification (WGA) is one method that has such potential. Two commercially available WGA kits, GenomePlex and GenomiPhi, were investigated for use on LCN and degraded DNA samples. Both kits amplified genomic DNA, producing microgram quantities from sub-nanogram templates. Profiling success of LCN DNA samples was increased, with improvements of over 700% from 10pg template DNA compared to non-WGA-amplified control samples. The amplification success with degraded DNA was also improved by WGA. Degraded DNA was simulated using restriction enzymes to demonstrate that the application of WGA can result in the typing of STR loci that could not previously be amplified. An increase in artefacts, such as stutter alleles and amplification biases, were observed in many samples. Results show that WGA is capable of increasing both the quality and quantity of DNA, and has the potential to improve profiling success from difficult samples in forensic casework.     

Understanding Variations of Soil Mapping Units and Associated Data for Forensic Science

Soil samples have potential to be useful in forensic investigations, but their utility may be limited due to the inherent variability of soil properties, the wide array of analytical methods, and complexity of data analysis. This study examined the differentiation of similar soils based on both gross (texture, color, mineralogy) and explicit soil properties (elemental composition, cation exchange, Fe‐oxyhydroxides). Soils were collected from Fallbrook and adjacent map units from Riverside and San Diego Counties in California. Samples were characterized using multiple techniques, including chemical extracts, X‐ray diffraction (XRD), and Fourier transform infrared spectroscopy. Results were analyzed using multiple analytical approaches to compare counties and land uses. Some analyses (XRD, extractions) were better at distinguishing among samples than others (color, texture). Ratios of rare earth elements were particularly useful for distinguishing samples between counties. This potential to “fingerprint” soils illustrates the usefulness of a comprehensive soil database for criminal investigators.