Kelly Meiklejohn

We propose a collaborative project with two broad goals: (1) using extant data to determine practices, programs, contexts, and legal structures that promote compliance with wildlife laws and regulations with spillover impacts on public safety, and (2) developing interventions to improve compliance with conservation and safety laws.

Flies are diverse models for the study of the evolution of the parasitic habit. Multiple repeated origins of specialized feeding in flies can reveal the molecular mechanisms underlying adaptive changes that both produce and sustain the parasitic lifestyle. With 1525 described species the blow flies (family Calliphoridae), are an ideal candidate for comparative study of the genetic and behavioral determinants of feeding adaptations. In this family of flies, different species have been recorded feeding on living tissues of a vertebrates, living tissues of invertebrates; decaying organic matter-- especially carrion or wound tissue; and blood. Considering the feeding habits of their larvae, blow flies are classified in: necrosaprophagous species, which feed on decomposing tissue; facultative ectoparasites, which feed on dead organic matter (necrophagous), or infest necrotic tissues of living vertebrates; and obligate parasites, which feed only on the living tissues of their hosts. For this reason, they are important as indicator organisms in forensic cases, are major agricultural pests of livestock, and they play a major role in nearly all terrestrial ecosystems as decomposers of organic material. The origin and evolutionary history of diverse specialized feeding habits in Calliphoridae are still vastly understudied, and are limited by a lack of phylogenetic, genetic and ecological information. With this project, an established team of evolutionary, ecological and genomic scientists will collaboratively investigate the causes and consequences of trophic specialization as a driver of species diversity across three integrated dimensions of blow fly research: (1) phylogenetic: reconstructing the history of blow fly evolutionary relationships and mapping the transitions of feeding habits that occurred repeatedly in the family; (2) functional, quantifying the index of preference for different food sources, and testing the effects of selection on feeding preferences; and investigating the role of the blow fly gut microbiome in mediating diet adaptations and maintaining diverse biotic interactions; and (3) genetic/genomic, identifying genes and gene regions associated with specific specialized feeding habits and using an established CRISPR Cas9 gene editing system to test hypotheses about the lability, maintenance, and control of feeding strategies in diverse blow fly models. The project includes a novel cross laboratory training and data collection for graduate students and postdocs between NCSU and Sao Paulo, Brazil, the development of an on-line data resource of genomic, taxonomic and ecological information on blow flies, and participation in multi-institutional training and research opportunities that include resources and outreach to individuals and communities that are underrepresented in science.

Evaluation of decontamination protocols and vehicle movement to mitigate the transmission risk of PED virus as a proxy for FAD

The decline of pollinators in North America (NAm) poses a challenge to agriculture in the United States (US) and a threat to national food security (Kremen et al. 2002b, Potts et al. 2010). Anthro-pogenic landscape modifications can impose stress on native bees in the form of increased expo-sure to chemicals and pathogens, high temperatures, and loss of nesting and foraging habitat (Winfree et al. 2011a, Goulson et al. 2015), and may play a role in NAm pollinator decline (Goulson et al. 2008, Cameron et al. 2011). Yet, the physiological basis of pollinator responses to anthropogenic stress remains poorly understood. This study will assess the effects of anthropo-genic change on a native bee of economic importance, by testing for differential expression of biochemical and genetic stress markers along with pathogen detection, across urban, ag-ricultural, and natural habitats in the bumble bee Bombus impatiens. By testing how land-scape characteristics influence physiological stress, this study will provide mechanistic data to complement studies showing effects on pollinator communities, and will identify biomarkers that can be used to assess the physiological health of pollinator populations in urban and agricultural settings.

Morphological characterization of pollen associated with forensic geologic materials often is used in casework to provide distinct information on sample origin (e.g., Where was the IED built?) and assist with sample-to-sample comparisons. Despite its utility, pollen characterization is not routinely performed given it requires specialized expertise and is very laborious. With advances in sequencing technologies, studies have reported that DNA-based approaches such as DNA metabarcoding could streamline pollen characterization. In this proposed study, we will validate DNA metabarcoding for the characterization of pollen from diverse surface soils. This validation is essential before DNA metabarcoding can be implemented into casework, given previous studies have a) primarily focused on pristine soil samples, which are not representative of evidence material, and b) not completed a side-by-side comparison of the results to those obtained using the traditional morphological approach. To complete the validation, pollen present in ~350 diverse surface soils (i.e., varied climate, geology, pH, depositional history, oxidation state) collected from across the U.S. will be sourced from the U.S. Geological Survey (USGS) archive. For each sample, pollen will be characterized two ways: 1) by targeting two commonly used plant DNA metabarcoding regions (ITS2 and trnL), and 2) using traditional morphological techniques. Statistical analyses will determine whether DNA metabarcoding can be used to both qualitatively (i.e., whether the same plant taxa are identified using both methods) and quantitatively (i.e., whether the relative abundance of identified plant taxa is comparable between the methods) characterize pollen from surface soils. The results from this study would drive forward forensic geology; cost and time effective characterization of pollen from geologic materials using DNA metabarcoding could be implemented into routine casework.

Geologic materials, such as soil and dust, are ubiquitous and thus often inadvertently associated with forensic evidence. Highly trained forensic geologists use a range of particulate-based analytical approaches to characterize inorganic components, with resulting data primarily used in sample-to-sample comparisons. In many cases, such analyses provide the examiner sufficient information to conclude there is or is not a possibility that the questioned soil originated from the same source as the known. However, there are inevitably cases where the samples being compared either lack exclusionary differences or there is too little inorganic material to analyze. In these scenarios, information gleaned from new quantitative methodologies not currently used in casework might provide valuable exclusionary differences: a) characterization of biological taxa, given species are associated with specific environments, or b) novel quantitative measures of soil morphology and minerology. In this proposed study, two types of surface soils that represent scenarios that would benefit most from analysis with new methods, will be collected from across North Carolina: a) very similar parent material/inorganic content but with distinct land use (n, 15 pairs), and b) limited inorganic content for analysis (n, 15 pairs). Each sample will be collected in triplicate to assess method reproducibility and accuracy (total n, ~180). Geologists at the FBI Laboratory will complete examinations of surface soils using methods currently used in forensic practice, supplemented by three new methods: instrumental colorimetry, Raman-based identification of opaque minerals, and QEMSCAN of minerals and lithic fragments (outsourced). Biological taxa (plant, bacteria, arthropods, fungi) associated with each sample will be characterized using DNA metabarcoding at North Carolina State University. A range of statistical analyses will be employed to assess the added value of each new methodology. The results of this proposed study could demonstrate improved methods of differentiating forensic soils or, more importantly, provide analysis methods for soils containing too little mineral matter for conventional examination. As this study is being conducted in parallel with extant forensic methods, statistical analyses will quantify the benefits (or lack of benefit) of these novel approaches in augmenting existing methods. This study will also permit a business process analysis considering cost/time/performance of these novel methods in lieu of, or in addition to, current forensic soil examination methods in the FBI Laboratory. The results of this study will be shared with the larger forensic community via publications, presentations at relevant conferences and affiliations with OSAC and the Initiative on Forensic Geology.

Geologic materials, such as soil and dust, are often submitted as trace evidence to crime laboratories, and can provide valuable information to link a suspect to a crime scene, identify the origin of evidence, and for intelligence gathering. Forensic geologists routinely examine and characterize inorganic components of geologic materials (e.g., mineral content, pH, color), but the organic components (e.g., pollen, plant/insect fragments) are rarely analyzed primarily due to a lack of available expertise. To harness the full evidentiary value, analyzing biological taxa associated with geologic materials could be used to supplement traditional inorganic examinations; associations between biological taxa and their environment are possible, and thus could provide valuable information for sample-to-sample comparisons and sample origin. Research to date has primarily focused on using bacteria to characterize soils, however, before the analysis of biological taxa can be implemented into casework, the following gaps need to be addressed: 1) utility of other biological taxa, not only bacteria, 2) applicability to diverse geologic evidence, and 3) impact of temporal and spatial variables. This proposed research project will explore whether the same species of four different biological taxa are recovered from soil and dust regardless of collection season, in order to determine which taxa(on) is most appropriate to separate geologic materials. To answer these research questions, mock geologic evidence (n, 6) will be collected in triplicate monthly for one year, from an urban and agricultural site in Raleigh NC. DNA metabarcoding will be used to characterize bacteria, fungi, arthropods and plants associated with geologic material isolated from mock evidence. With this method, short yet informative regions of the genome will be amplified in multiple species simultaneously, with amplicons subsequently sequenced on the Illumina��������� MiniSeq. Sequence data will be processed through the DADA2 pipeline, and only high-quality unique sequences will be retained for searching against taxa-specific databases for identification. Taxonomic abundance charts will be created to visualize the difference between replicates, across mock evidence types, study sites and collection times. Canonical analysis of principal coordinates will be used to assess which taxa(on) can be used for sample-to-sample comparisons and spatial separation. Bray-Curtis dissimilarity will be employed to measure the dissimilarity between all 432 samples. This study will provide the forensics community with an assessment of the utility of various biological taxa for characterizing mock geologic evidence. This is necessary before this approach can be considered for use in routine casework.

This proposed study is focussed on conducting an inter-laboratory study based on 2021-S-0006 Standard for the Use of GenBank for Taxonomic Assignment of Wildlife (currently in the STRP Phase of the OSAC 2.0 Process). NC State University will source diverse specimens encountered in wildlife forensic casework from their own collection and from domestic collaborators (e.g., elephants, rhinos, lions, sea turtles, swordfish, bald eagle, sharks, elk, wolves, etc) and generate sequence data for appropriate loci targeted in casework for species level identifications. Domestic and international wildlife forensic laboratories (n, ~10) will be provided with raw Sanger sequences (n, ~10 each) and asked to follow the current standard for comparing the mock evidentiary sequences to GenBank for taxonomic identification. Participating laboratories will report back to NC State a) the taxonomic identification for each mock evidentiary sequence, b) the accession number(s) of the GenBank sequences used to make this identification, and c) which specific criteria from the standard (strong or moderate) were used to make the taxonomic identification. Each sequence will be evaluated by at least three laboratories, allowing NC State to assess the level of consistency obtained amongst laboratories when implementing the standard. NC State will evaluate each individual submitted report, complete statistical analyses, and prepare the final report/manuscript for NIST.

Geologic materials, such as soil and dust, are often submitted as trace evidence to crime laboratories, and can provide valuable information to link a suspect to a crime scene, identify the origin of evidence, and for intelligence gathering. Forensic geologists routinely examine and characterize inorganic components of geologic materials (e.g., mineral content, pH, color), but the organic components (e.g., pollen, plant/insect fragments) are rarely analyzed primarily due to a lack of available expertise. To harness the full evidentiary value, analyzing biological taxa associated with geologic materials could be used to supplement traditional inorganic examinations; associations between biological taxa and their environment are possible, and thus could provide valuable information for sample-to-sample comparisons and sample origin. Research to date has primarily focused on using bacteria to characterize soils, however, before the analysis of biological taxa can be implemented into casework, the following gaps need to be addressed: 1) utility of other biological taxa, not only bacteria, 2) applicability to diverse geologic evidence, and 3) impact of temporal and spatial variables. This proposed research project will explore whether the same species of four different biological taxa are recovered from soil and dust regardless of collection season, in order to determine which taxa(on) is most appropriate to separate geologic materials. To answer these research questions, mock geologic evidence (n, 6) will be collected in triplicate monthly for one year, from an urban and agricultural site in Raleigh NC. DNA metabarcoding will be used to characterize bacteria, fungi, arthropods and plants associated with geologic material isolated from mock evidence. With this method, short yet informative regions of the genome will be amplified in multiple species simultaneously, with amplicons subsequently sequenced on the Illumina��������� MiniSeq. Sequence data will be processed through the DADA2 pipeline, and only high-quality unique sequences will be retained for searching against taxa-specific databases for identification. Taxonomic abundance charts will be created to visualize the difference between replicates, across mock evidence types, study sites and collection times. Canonical analysis of principal coordinates will be used to assess which taxa(on) can be used for sample-to-sample comparisons and spatial separation. Bray-Curtis dissimilarity will be employed to measure the dissimilarity between all 432 samples. This study will provide the forensics community with an assessment of the utility of various biological taxa for characterizing mock geologic evidence. This is necessary before this approach can be considered for use in routine casework.

The practice of DNA forensics is on a trajectory to adopt a revolutionary new technology called next-generation sequencing (NGS). With the implementation of NGS, laboratories will be able to analyze biological evidence at an unprecedented genetic resolution, assisting investigations and augmenting criminal casework, missing persons, paternity, cold and unsolved cases. However, some critical elements must be in place to allow effective, accurate, and reliable evidence analysis by NGS. While other on-going efforts are focusing on NGS technology development and implementation, this applied research study proposes to characterize STR sequence diversity and fill the critical requirement of an NGS population database. An interdisciplinary team comprised of forensic DNA scientists, NGS experts, and computer scientists will be formed to achieve the three goals of this study. First, a robust and quality reviewed STR sequence population dataset of 1000 profiles will be generated using commercially available NGS kits. The dataset will be comprised of traditional forensic genetic markers (autosomal-, X������������������ and Y- short tandem repeats) to be backward compatible with existing criminal databases, plus yield the powerful sequence data from NGS analysis. Second, a cloud-based, open-access tool for visualizing population data, and performing genotype analysis at the locus sequence level will be developed. The cloud developed environment will be self-sustaining and in a public domain to provide longevity to the resource. Third, the database will be designed as a collective resource for forensic laboratories producing NGS data. Proficient laboratories will be identified as contributors and the dynamic web application will allow automated NGS data submission with computer-supported quality and content review. At the completion of the program, the final product will be available to the entire criminal justice community, including laboratories without sufficient resources to produce a population datasets from NGS. The database will meet a critical need in the community for adopting NGS and allow researchers and practitioners to apply statistical rigor to data generated using NGS.