Biology subjects

Crystal Hepp

Publications and source records attributed to Crystal Hepp.

3 recordsLinked to original sources

bioRxiv2020

Forensic analysis of Soil Microbiomes: Linking Evidence to a Geographic Location

Over the past two decades, advances in molecular biology have greatly expanded our understanding of microbiomes - the diverse assemblages of microorganisms that inhabit the human body as well as the world around us, and applications in microbiome science have become an active area of research. Differences in the diversity (i.e., richness) and composition of microbiomes has been found to be informative in varied areas of science, including human health, agronomy, and forensic science. Soil harbors microbiomes that vary based on many factors, including the geology of the soil (e.g., sand, silt, or clay), climate, and use of the soil. As a result, the microbiological composition of any two soil samples will never be exactly alike. This inherent variation between microbiomes of different locations has proven to be specific enough to be potentially useful in forensic investigations to associate a person or piece of evidence to a source site. In this study, a soil microbiome was extracted from the sock of a criminal suspect and compared to the microbiome of soil samples taken from locations traveled to by the suspect. The locations analyzed varied in their soil microbiome composition, and the microbiome profiled from the sock was found to be most similar to the location where the suspect was thought to have left the body of a murder victim. These results provide a case study illustrating that information contained in a soil microbiome may be applied to link evidence to the location where a crime took place, potentially serving as an investigative tool in law enforcement.

bioinformatics↗

bioRxiv2016

A Bacillus anthracis Genome Sequence from the Sverdlovsk 1979 Autopsy Specimens

Anthrax is a zoonotic disease that occurs naturally in wild and domestic animals but has been used by both state-sponsored programs and terrorists as a biological weapon. The 2001 anthrax letter attacks involved less than gram quantities of Bacillus anthracis spores while the earlier Soviet weapons program produced tons. A Soviet industrial production facility in Sverdlovsk proved deficient in 1979 when a plume of spores was accidentally released and resulted in one of the largest known human anthrax outbreak. In order to understand this outbreak and others, we have generated a B. anthracis population genetic database based upon whole genome analysis to identify all SNPs across a reference genome. Only ~12,000 SNPs were identified in this low diversity species and represents the breadth of its known global diversity. Phylogenetic analysis has defined three major clades (A, B and C) with B and C being relatively rare compared to A. The A clade has numerous subclades including a major polytomy named the Trans-Eurasian (TEA) group. The TEA radiation is a dominant evolutionary feature of B. anthracis, many contemporary populations, and must have resulted from large-scale dispersal of spores from a single source. Two autopsy specimens from the Sverdlovsk outbreak were deeply sequenced to produce draft B. anthracis genomes. This allowed the phylogenetic placement of the Sverdlovsk strain into a clade with two Asian live vaccine strains, including the Russian Tsiankovskii strain. The genome was examined for evidence of drug resistance manipulation or other genetic engineering, but none was found. Only 13 SNPs differentiated the virulent Sverdlovsk strain from its common ancestor with two vaccine strains. The Soviet Sverdlovsk strain genome is consistent with a wild type strain from Russia that had no evidence of genetic manipulation during its industrial production. This work provides insights into the world's largest biological weapons program and provides an extensive B. anthracis phylogenetic reference valuable for future anthrax investigations.\n\nImportanceThe 1979 Russian anthrax outbreak resulted from an industrial accident at the Soviet anthrax spore production facility in the city of Sverdlovsk. Deep genomic sequencing of two autopsy specimens generated a draft genome and phylogenetic placement of the Soviet Sverdlovsk anthrax strain. While it is known that Soviet scientists had genetically manipulated Bacillus anthracis, with the potential to evade vaccine prophylaxis and antibiotic therapeutics, there was no genomic evidence of this from the Sverdlovsk production strain genome. The whole genome SNP genotype of the Sverdlovsk strain was used to precisely identify it and its close relatives in the context of an extensive global B. anthracis strain collection. This genomic identity can now be used for forensic tracking of this weapons material on a global scale and for future anthrax investigations.

Genomics↗

bioRxiv2016

The Northern Arizona SNP Pipeline (NASP): accurate, flexible, and rapid identification of SNPs in WGS datasets

Whole genome sequencing (WGS) of bacteria is becoming standard practice in many laboratories. Applications for WGS analysis include phylogeography and molecular epidemiology, using single nucleotide polymorphisms (SNPs) as the unit of evolution. The Northern Arizona SNP Pipeline (NASP) was developed as a reproducible pipeline that scales well with the large amount of WGS data typically used in comparative genomics applications. In this study, we demonstrate how NASP compares to other tools in the analysis of two real bacterial genomics datasets and one simulated dataset. Our results demonstrate that NASP produces comparable, and often better, results to other pipelines, but is much more flexible in terms of data input types, job management systems, diversity of supported tools, and output formats. We also demonstrate differences in results based on the choice of the reference genome and choice of inferring phylogenies from concatenated SNPs or alignments including monomorphic positions. NASP represents a source-available, version-controlled, unit-tested method and can be obtained from tgennorth.github.io/NASP.

Bioinformatics↗