Combining human STR and microbial population profiling: Two case reports.

In forensic case investigations involving human traces, cell type identification has become increasingly important. No longer only the donor of a trace (sub-source level), but also the actions which could have led to the deposition of the trace ('beyond-the-source'/activity level) need to be evaluated by forensic experts. For this evaluation determining the cellular source of a DNA profile can be beneficial. In this report two criminal cases are described where both human STR profiling and microbial population profiling were applied to the same trace sample. Human STR profiling was used to evaluate the sub-source question and microbial population profiling was used to evaluate the source question. The Bayesian framework was used to evaluate the evidence.

Human-associated microbial populations as evidence in forensic casework.

In forensic investigations involving human biological traces, cell type identification is often required. Identifying the cell type from which a human STR profile has originated can assist in verifying scenarios. Several techniques have been developed for this purpose, most of which focus on molecular characteristics of human cells. Here we present a microarray method focusing on the microbial populations that are associated with human cell material. A microarray with 863 probes targeting (sets of) species, specific genera, groups of genera or families was designed for this study and evaluated with samples from different body sites: hand, foot, groin, penis, vagina, mouth and faeces. In total 175 samples from healthy individuals were analysed. Next to human faeces, 15 feline and 15 canine faeces samples were also included. Both clustering and classification analysis were used for data analysis. Faecal and oral samples could clearly be distinguished from vaginal and skin samples, and also canine and feline faeces could be differentiated from human faeces. Some penis samples showed high similarity to vaginal samples, others to skin samples. Discriminating between skin samples from different skin sites proved to be challenging. As a proof of principle, twenty-one mock case samples were analysed with the microarray method. All mock case samples were clustered or classified within the correct main cluster/group. Only two of the mock case samples were assigned to the wrong sub-cluster/class; with classification one additional sample was classified within the wrong sub-class. Overall, the microarray method is a valuable addition to already existing cell typing techniques. Combining the results of microbial population analysis with for instance mRNA typing can increase the evidential value of a trace, since both techniques focus on independent targets within a sample.

Microbial population analysis improves the evidential value of faecal traces in forensic investigations.

The forensic science community has a growing interest in microbial population analysis, especially the microbial populations found inside and on the human body. Both their high abundance, microbes outnumber human cells by a factor 10, and their diversity, different sites of the human body harbour different microbial communities, make them an interesting tool for forensics. Faecal material is a type of trace evidence which can be found in a variety of criminal cases, but is often being ignored in forensic investigations. Deriving a human short tandem repeat (STR) profile from a faecal sample can be challenging. However, the microbial communities within faecal material can be of additional criminalistic value in linking a faecal trace to the possible donor. We present a microarray technique in which the faecal microbial community is used to differentiate between faecal samples and developed a decision model to predict the possible common origin of questioned samples. The results show that this technique may be a useful additional tool when no or only partial human STR profiles can be generated.

Vaginal microbial flora analysis by next generation sequencing and microarrays; can microbes indicate vaginal origin in a forensic context?

Forensic analysis of biological traces generally encompasses the investigation of both the person who contributed to the trace and the body site(s) from which the trace originates. For instance, for sexual assault cases, it can be beneficial to distinguish vaginal samples from skin or saliva samples. In this study, we explored the use of microbial flora to indicate vaginal origin. First, we explored the vaginal microbiome for a large set of clinical vaginal samples (n = 240) by next generation sequencing (n = 338,184 sequence reads) and found 1,619 different sequences. Next, we selected 389 candidate probes targeting genera or species and designed a microarray, with which we analysed a diverse set of samples; 43 DNA extracts from vaginal samples and 25 DNA extracts from samples from other body sites, including sites in close proximity of or in contact with the vagina. Finally, we used the microarray results and next generation sequencing dataset to assess the potential for a future approach that uses microbial markers to indicate vaginal origin. Since no candidate genera/species were found to positively identify all vaginal DNA extracts on their own, while excluding all non-vaginal DNA extracts, we deduce that a reliable statement about the cellular origin of a biological trace should be based on the detection of multiple species within various genera. Microarray analysis of a sample will then render a microbial flora pattern that is probably best analysed in a probabilistic approach.

Statistical data analysis of bacterial t-RFLP profiles in forensic soil comparisons.

Soil can play an important role in forensic investigations in linking suspects or objects to a crime scene. Bacterial populations are one of the biotic parameters in soil which can be used for comparisons. Terminal restriction fragment length polymorphism (t-RFLP) is used to visualize these populations. Here we present a method to compare soil t-RFLP profiles based on Bray-Curtis distances. We developed a decision model to predict the possible common source of unknown samples. Test cases in cooperation with the Police Academy of the Netherlands were used to validate the decision model. The results of these test cases are very promising, indicating that bacterial profiling is a useful additional tool in forensic soil comparisons.