Sarah E. Schmedes

A draft genome of Yersinia pestis from victims of the Black Death

Technological advances in DNA recovery and sequencing have drastically expanded the scope of genetic analyses of ancient specimens to the extent that full genomic investigations are now feasible and are quickly becoming standard. This trend has important implications for infectious disease research because genomic data from ancient microbes may help to elucidate mechanisms of pathogen evolution and adaptation for emerging and re-emerging infections. Here we report a reconstructed ancient genome of Yersinia pestis at 30-fold average coverage from Black Death victims securely dated to episodes of pestilence-associated mortality in London, England, 1348–1350. Genetic architecture and phylogenetic analysis indicate that the ancient organism is ancestral to most extant strains and sits very close to the ancestral node of all Y. pestis commonly associated with human infection. Temporal estimates suggest that the Black Death of 1347–1351 was the main historical event responsible for the introduction and widespread dissemination of the ancestor to all currently circulating Y. pestis strains pathogenic to humans, and further indicates that contemporary Y. pestis epidemics have their origins in the medieval era. Comparisons against modern genomes reveal no unique derived positions in the medieval organism, indicating that the perceived increased virulence of the disease during the Black Death may not have been due to bacterial phenotype. These findings support the notion that factors other than microbial genetics, such as environment, vector dynamics and host susceptibility, should be at the forefront of epidemiological discussions regarding emerging Y. pestis infections.

Evaluation of the Illumina® Beta Version ForenSeq™ DNA Signature Prep Kit for use in genetic profiling

While capillary electrophoresis-based technologies have been the mainstay for human identity typing applications, there are limitations with this methodologys resolution, scalability, and throughput. Massively parallel sequencing (MPS) offers the capability to multiplex multiple types of forensically-relevant markers and multiple samples together in one run all at an overall lower cost per nucleotide than traditional capillary electrophoresis-based methods; thus, addressing some of these limitations. MPS also is poised to expand forensic typing capabilities by providing new strategies for mixture deconvolution with the identification of intra-STR allele sequence variants and the potential to generate new types of investigative leads with an increase in the overall number and types of genetic markers being analyzed. The beta version of the Illumina ForenSeq DNA Signature Prep Kit is a MPS library preparation method with a streamlined workflow that allows for targeted amplification and sequencing of 63 STRs and 95 identity SNPs, with the option to include an additional 56 ancestry SNPs and 22 phenotypic SNPs depending on the primer mix chosen for amplification, on the MiSeq desktop sequencer (Illumina). This study was divided into a series of experiments that evaluated reliability, sensitivity of detection, mixture analysis, concordance, and the ability to analyze challenged samples. Genotype accuracy, depth of coverage, and allele balance were used as informative metrics for the quality of the data produced. The ForenSeq DNA Signature Prep Kit produced reliable, reproducible results and obtained full profiles with DNA input amounts of 1ng. Data were found to be concordant with current capillary electrophoresis methods, and mixtures at a 1:19 ratio were resolved accurately. Data from the challenged samples showed concordant results with current DNA typing methods with markers in common and minimal allele drop out from the large number of markers typed on these samples. This set of experiments indicates the beta version of the ForenSeq DNA Signature Prep Kit is a valid tool for forensic DNA typing and warrants full validation studies of this MPS technology.

Validation of high throughput sequencing and microbial forensics applications

High throughput sequencing (HTS) generates large amounts of high quality sequence data for microbial genomics. The value of HTS for microbial forensics is the speed at which evidence can be collected and the power to characterize microbial-related evidence to solve biocrimes and bioterrorist events. As HTS technologies continue to improve, they provide increasingly powerful sets of tools to support the entire field of microbial forensics. Accurate, credible results allow analysis and interpretation, significantly influencing the course and/or focus of an investigation, and can impact the response of the government to an attack having individual, political, economic or military consequences. Interpretation of the results of microbial forensic analyses relies on understanding the performance and limitations of HTS methods, including analytical processes, assays and data interpretation. The utility of HTS must be defined carefully within established operating conditions and tolerances. Validation is essential in the development and implementation of microbial forensics methods used for formulating investigative leads attribution. HTS strategies vary, requiring guiding principles for HTS system validation. Three initial aspects of HTS, irrespective of chemistry, instrumentation or software are: 1) sample preparation, 2) sequencing, and 3) data analysis. Criteria that should be considered for HTS validation for microbial forensics are presented here. Validation should be defined in terms of specific application and the criteria described here comprise a foundation for investigators to establish, validate and implement HTS as a tool in microbial forensics, enhancing public safety and national security.

A high volume extraction and purification method for recovering DNA from human bone

DNA recovery, purity and overall extraction efficiency of a protocol employing a novel silica-based column, Hi-Flow(®) (Generon Ltd., Maidenhead, UK), were compared with that of a standard organic DNA extraction methodology. The quantities of DNA recovered by each method were compared by real-time PCR and quality of DNA by STR typing using the PowerPlex(®) ESI 17 Pro System (Promega Corporation, Madison, WI) on DNA from 10 human bone samples. Overall, the Hi-Flow method recovered comparable quantities of DNA ranging from 0.8ng±1 to 900ng±159 of DNA compared with the organic method ranging from 0.5ng±0.9 to 855ng±156 of DNA. Complete profiles (17/17 loci tested) were obtained for at least one of three replicates for 3/10 samples using the Hi-Flow method and from 2/10 samples with the organic method. All remaining bone samples yielded partial profiles for all replicates with both methods. Compared with a standard organic DNA isolation method, the results indicated that the Hi-Flow method provided equal or improved recovery and quality of DNA without the harmful effects of organic extraction. Moreover, larger extraction volumes (up to 20mL) can be employed with the Hi-Flow method which enabled more bone sample to be extracted at one time.

Expansion of Microbial Forensics

ABSTRACT Microbial forensics has been defined as the discipline of applying scientific methods to the analysis of evidence related to bioterrorism, biocrimes, hoaxes, or the accidental release of a biological agent or toxin for attribution purposes. Over the past 15 years, technology, particularly massively parallel sequencing, and bioinformatics advances now allow the characterization of microorganisms for a variety of human forensic applications, such as human identification, body fluid characterization, postmortem interval estimation, and biocrimes involving tracking of infectious agents. Thus, microbial forensics should be more broadly described as the discipline of applying scientific methods to the analysis of microbial evidence in criminal and civil cases for investigative purposes.

Effective removal of co-purified inhibitors from extracted DNA samples using synchronous coefficient of drag alteration (SCODA) technology

Various types of biological samples present challenges for extraction of DNA suitable for subsequent molecular analyses. Commonly used extraction methods, such as silica membrane columns and phenol–chloroform, while highly successful may still fail to provide a sufficiently pure DNA extract with some samples. Synchronous coefficient of drag alteration (SCODA), implemented in Boreal Genomics’ Aurora Nucleic Acid Extraction System (Boreal Genomics, Vancouver, BC), is a new technology that offers the potential to remove inhibitors effectively while simultaneously concentrating DNA. In this initial study, SCODA was tested for its ability to remove various concentrations of forensically and medically relevant polymerase chain reaction (PCR) inhibitors naturally found in tissue, hair, blood, plant, and soil samples. SCODA was used to purify and concentrate DNA from intentionally contaminated DNA samples containing known concentrations of hematin, humic acid, melanin, and tannic acid. The internal positive control (IPC) provided in the Quantifiler™ Human DNA Quantification Kit (Life Technologies, Foster City, CA) and short tandem repeat (STR) profiling (AmpFℓSTR® Identifiler® Plus PCR Amplification Kit; Life Technologies, Foster City, CA) were used to measure inhibition effects and hence purification. SCODA methodology yielded overall higher efficiency of purification of highly contaminated samples compared with the QIAquick® PCR Purification Kit (Qiagen, Valencia, CA). SCODA-purified DNA yielded no cycle shift of the IPC for each sample and yielded greater allele percentage recovery and relative fluorescence unit values compared with the QIAquick® purification method. The Aurora provided an automated, minimal-step approach to successfully remove inhibitors and concentrate DNA from challenged samples.

Increasing the reach of forensic genetics with massively parallel sequencing

The field of forensic genetics has made great strides in the analysis of biological evidence related to criminal and civil matters. More so, the discipline has set a standard of performance and quality in the forensic sciences. The advent of massively parallel sequencing will allow the field to expand its capabilities substantially. This review describes the salient features of massively parallel sequencing and how it can impact forensic genetics. The features of this technology offer increased number and types of genetic markers that can be analyzed, higher throughput of samples, and the capability of targeting different organisms, all by one unifying methodology. While there are many applications, three are described where massively parallel sequencing will have immediate impact: molecular autopsy, microbial forensics and differentiation of monozygotic twins. The intent of this review is to expose the forensic science community to the potential enhancements that have or are soon to arrive and demonstrate the continued expansion the field of forensic genetics and its service in the investigation of legal matters.

A Comparison and Integration of MiSeq and MinION Platforms for Sequencing Single Source and Mixed Mitochondrial Genomes.

Single source and multiple donor (mixed) samples of human mitochondrial DNA were analyzed and compared using the MinION and the MiSeq platforms. A generalized variant detection strategy was employed to provide a cursory framework for evaluating the reliability and accuracy of mitochondrial sequences produced by the MinION. The feasibility of long-read phasing was investigated to establish its efficacy in quantitatively distinguishing and deconvolving individuals in a mixture. Finally, a proof-of-concept was demonstrated by integrating both platforms in a hybrid assembly that leverages solely mixture data to accurately reconstruct full mitochondrial genomes.

Forensic human identification using skin microbiomes.

ABSTRACT The human microbiome contributes significantly to the genetic content of the human body. Genetic and environmental factors help shape the microbiome, and as such, the microbiome can be unique to an individual. Previous studies have demonstrated the potential to use microbiome profiling for forensic applications; however, a method has yet to identify stable features of skin microbiomes that produce high classification accuracies for samples collected over reasonably long time intervals. A novel approach is described here to classify skin microbiomes to their donors by comparing two feature types: Propionibacterium acnes pangenome presence/absence features and nucleotide diversities of stable clade-specific markers. Supervised learning was used to attribute skin microbiomes from 14 skin body sites from 12 healthy individuals sampled at three time points over a >2.5-year period with accuracies of up to 100% for three body sites. Feature selection identified a reduced subset of markers from each body site that are highly individualizing, identifying 187 markers from 12 clades. Classification accuracies were compared in a formal model testing framework, and the results of this analysis indicate that learners trained on nucleotide diversity perform significantly better than those trained on presence/absence encodings. This study used supervised learning to identify individuals with high accuracy and associated stable features from skin microbiomes over a period of up to almost 3 years. These selected features provide a preliminary marker panel for future development of a robust and reproducible method for skin microbiome profiling for forensic human identification. IMPORTANCE A novel approach is described to attribute skin microbiomes, collected over a period of >2.5 years, to their individual hosts with a high degree of accuracy. Nucleotide diversities of stable clade-specific markers with supervised learning were used to classify skin microbiomes from a particular individual with up to 100% classification accuracy for three body sites. Attribute selection was used to identify 187 genetic markers from 12 clades which provide the greatest differentiation of individual skin microbiomes from 14 skin sites. This study performs skin microbiome profiling from a supervised learning approach and obtains high classification accuracy for samples collected from individuals over a relatively long time period for potential application to forensic human identification.

Targeted sequencing of clade-specific markers from skin microbiomes for forensic human identification

The human skin microbiome is comprised of diverse communities of bacterial, eukaryotic, and viral taxa and contributes millions of additional genes to the repertoire of human genes, affecting human metabolism and immune response. Numerous genetic and environmental factors influence the microbiome composition and as such contribute to individual-specific microbial signatures which may be exploited for forensic applications. Previous studies have demonstrated the potential to associate skin microbial profiles collected from touched items to their individual owner, mainly using unsupervised methods from samples collected over short time intervals. Those studies utilize either targeted 16S rRNA or shotgun metagenomic sequencing to characterize skin microbiomes; however, these approaches have limited species and strain resolution and susceptibility to stochastic effects, respectively. Clade-specific markers from the skin microbiome, using supervised learning, can predict individual identity using skin microbiomes from their respective donors with high accuracy. In this study the hidSkinPlex is presented, a novel targeted sequencing method using skin microbiome markers developed for human identification. The hidSkinPlex (comprised of 286 bacterial (and phage) family-, genus-, species-, and subspecies-level markers), initially was evaluated on three bacterial control samples represented in the panel (i.e., Propionibacterium acnes, Propionibacterium granulosum, and Rothia dentocariosa) to assess the performance of the multiplex. The hidSkinPlex was further evaluated for prediction purposes. The hidSkinPlex markers were used to attribute skin microbiomes collected from eight individuals from three body sites (i.e., foot (Fb), hand (Hp) and manubrium (Mb)) to their host donor. Supervised learning, specifically regularized multinomial logistic regression and 1-nearest-neighbor classification were used to classify skin microbiomes to their hosts with up to 92% (Fb), 96% (Mb), and 100% (Hp) accuracy. All samples (n=72) regardless of body site origin were correctly classified with up to 94% accuracy, and body site origin could be predicted with up to 86% accuracy. Finally, human short tandem repeat and single-nucleotide polymorphism profiles were generated from skin swab extracts from a single subject to highlight the potential to use microbiome profiling in conjunction with low-biomass samples. The hidSkinPlex is a novel targeted enrichment approach to profile skin microbiomes for human forensic identification purposes and provides a method to further characterize the utility of skin microflora for human identification in future studies, such as the stability and diversity of the personal skin microbiome.