Molecular epidemiology of waterborne zoonoses in the North Island of New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science (Epidemiology and Public Health) at Institute of Veterinary, Animal and Biomedical Sciences (IVABS), Massey University, Palmerston North, New Zealand

Campylobacter, Cryptosporidium and Giardia species are three important waterborne zoonotic pathogens of global public health concern. This PhD opens with an interpretive overview of the literature on Campylobacter, Cryptosporidium and Giardia spp. in ruminants and their presence in surface water (Chapter 1), followed by five epidemiological studies of Campylobacter, Cryptosporidium and Giardia spp. in cattle, sheep and aquatic environment in New Zealand (Chapters 2-6). The second chapter investigated four years of retrospective data on Campylobacter spp. (n=507) to infer the source, population structure and zoonotic potential of Campylobacter jejuni from six high-use recreational rivers in the Wanganui- Manawatu region of New Zealand through the generalised additive model, generalised linear/logistic regression model, and minimum spanning trees. This study highlights the ubiquitous presence of Campylobacter spp. in both low and high river flows, and during winter months. It also shows the presence of C. jejuni in 21% of samples containing highly diverse strains, the majority of which were associated with wild birds only. These wild birds-associated C. jejuni have not been detected in human, suggesting they may not be infectious to human. However, the presence of some poultry and ruminant-associated strains that are potentially zoonotic suggested the possibility of waterborne transmission of C. jejuni to the public. Good biosecurity measures and water treatment plants may be helpful in reducing the risk of waterborne Campylobacter transmission In the third study, a repeated cross-sectional study was conducted every month for four months to investigate the source of drinking source-water contamination. A total of 499 ruminant faecal samples and 24 river/stream water samples were collected from two rural town water catchments (Dannevirke and Shannon) in the Manawatu- Wanganui region of New Zealand, and molecular analysis of those samples was performed to determine the occurrence of Campylobacter, Cryptosporidium, and Giardia spp. and their zoonotic potential. The major pathogens found in faecal samples were Campylobacter (n=225 from 7/8 farms), followed by Giardia (n=151 from 8/8 farms), whereas Giardia cysts were found in many water samples (n=18), followed by Campylobacter (n=4). On the contrary, Cryptosporidium oocysts were only detected in a few faecal (n=18) and water (n=3) samples. Cryptosporidium and Giardia spp. were detected in a higher number of faecal samples from young animals (≤ 3 months) than juvenile and adult animals, whereas Campylobacter spp. were highly isolated in the faecal samples from juvenile and adult ruminants. PCRsequencing of the detected pathogens indicated the presence of potentially zoonotic C. jejuni and C. coli, Cryptosporidium parvum (gp60 allelic types IIA18G3R1 and IIA19G4R1) and Giardia duodenalis (assemblages AII, BII, BIII, and BIV) in cattle and sheep. In addition, potentially zoonotic C. jejuni and Giardia duodenalis assemblages AII, BI, BII, and BIV were also determined in water samples. These findings indicate that these three pathogens of public health significance are present in ruminant faecal samples of farms and in water, and may represent a possible source of human infection in New Zealand. In the fourth study, PCR-sequencing of Cryptosporidium spp. isolates obtained from the faeces of 6-week- old dairy calves (n=15) in the third study were investigated at multiple loci (18S SSU rDNA, HSP70, Actin and gp60) to determine the presence of mixed Cryptosporidium spp. infections. Cryptosporidium parvum (15/15), C. bovis (3/15) and C. andersoni (1/15), and two new genetic variants were determined along with molecular evidence of mixed infections in five specimens. Three main Cryptosporidium species of cattle, C. parvum, C. bovis and C. andersoni, were detected together in one specimen. Genetic evidence of the presence of C. Anderson and two new Cryptosporidium genetic variants are provided here for the first time in New Zealand. These findings provided additional evidence that describes Cryptosporidium parasites as genetically heterogeneous populations and highlighted the need for iterative genotyping at multiple loci to explore the genetic makeup of the isolates. The C. jejuni and C. coli isolates (n=96) obtained from cattle, sheep and water in the third study were subtyped to determine their genetic diversity and zoonotic potential using a modified, novel multi-locus sequence typing method (“massMLST”; Chapter 5). Primers were developed and optimised, PCR-based target-MLST alleles’ amplification were performed, followed by next generation sequencing on an Illumina MiSeq machine. A bioinformatics pipeline of the sequencing data was developed to define C. jejuni and C. coli multi-locus sequence types. This study demonstrated the utility and potential of this novel typing method, massMLST, as a strain typing method. In addition to identifying the possible C. jejuni/coli clonal complexes or sequence types of 68/96 isolates from ruminant faeces and water samples, this study reported three new C. jejuni strains in cattle in New Zealand, along with many strains, such as CC-61, CC-828 and CC-21, that have also been found in humans, indicating the public health significance of these isolates circulating on the farms in the two water catchment areas. Automation of the massMLST method and may allow a cost-effective high-resolution typing method in the near future for multilocus sequence typing of large collections of Campylobacter strains. In the final study (Chapter 6), a pilot metagenomic study was carried out to obtain a snapshot of the microbial ecology of surface water used in the two rural towns of New Zealand for drinking purposes, and to identify the zoonotic pathogens related to waterborne diseases. Fresh samples collected in 2011 and 2012, samples from the same time that were frozen, and samples that were kept in the preservative RNAlater were sequenced using whole-genome shotgun sequencing on an Illumina MiSeq machine. Proteobacteria was detected in all the samples characterised, although there were differences in the genus and species between the samples. The microbial diversity reported varied between the grab and stomacher methods, between samples collected in the year 2011 and 2012, and among the fresh, frozen and RNAlater preserved samples. This study also determined the presence of DNA of potentially zoonotic pathogens such as Cryptosporidium, Campylobacter and Mycobacterium spp. in water. Use of metagenomics could potentially be used to monitor the ecology of drinking water sources so that effective water treatment plans can be formulated, and for reducing the risk of waterborne zoonosis. As a whole, this PhD project provides new data on G. duodenalis assemblages in cattle, sheep and surface water, new information on mixed Cryptosporidium infections in calves, a novel “massMLST” method to subtype Campylobacter species, and shows the utility of shotgun metagenomic sequencing for drinking water monitoring. Results indicate that ruminants (cattle and sheep) in New Zealand shed potentially zoonotic pathogens in the environment and may contribute to the contamination of surface water. A better understanding of waterborne zoonotic transmission would help in devising appropriate control strategies, which could reduce the shedding of Campylobacter, Cryptosporidium, and Giardia spp. in the environment and thereby reduce waterborne transmission

¹³C NMR metabolomics: applications at natural abundance.

(13)C NMR has many advantages for a metabolomics study, including a large spectral dispersion, narrow singlets at natural abundance, and a direct measure of the backbone structures of metabolites. However, it has not had widespread use because of its relatively low sensitivity compounded by low natural abundance. Here we demonstrate the utility of high-quality (13)C NMR spectra obtained using a custom (13)C-optimized probe on metabolomic mixtures. A workflow was developed to use statistical correlations between replicate 1D (13)C and (1)H spectra, leading to composite spin systems that can be used to search publicly available databases for compound identification. This was developed using synthetic mixtures and then applied to two biological samples, Drosophila melanogaster extracts and mouse serum. Using the synthetic mixtures we were able to obtain useful (13)C-(13)C statistical correlations from metabolites with as little as 60 nmol of material. The lower limit of (13)C NMR detection under our experimental conditions is approximately 40 nmol, slightly lower than the requirement for statistical analysis. The (13)C and (1)H data together led to 15 matches in the database compared to just 7 using (1)H alone, and the (13)C correlated peak lists had far fewer false positives than the (1)H generated lists. In addition, the (13)C 1D data provided improved metabolite identification and separation of biologically distinct groups using multivariate statistical analysis in the D. melanogaster extracts and mouse serum

Near-optimal irrevocable sample selection for periodic data streams with applications to marine robotics

We consider the task of monitoring spatiotemporal phenomena in real-time by deploying limited sampling resources at locations of interest irrevocably and without knowledge of future observations. This task can be modeled as an instance of the classical secretary problem. Although this problem has been studied extensively in theoretical domains, existing algorithms require that data arrive in random order to provide performance guarantees. These algorithms will perform arbitrarily poorly on data streams such as those encountered in robotics and environmental monitoring domains, which tend to have spatiotemporal structure. We focus on the problem of selecting representative samples from phenomena with periodic structure and introduce a novel sample selection algorithm that recovers a near-optimal sample set according to any monotone submodular utility function. We evaluate our algorithm on a seven-year environmental dataset collected at the Martha's Vineyard Coastal Observatory and show that it selects phytoplankton sample locations that are nearly optimal in an information-theoretic sense for predicting phytoplankton concentrations in locations that were not directly sampled. The proposed periodic secretary algorithm can be used with theoretical performance guarantees in many real-time sensing and robotics applications for streaming, irrevocable sample selection from periodic data streams.Comment: 8 pages, accepted for presentation in IEEE Int. Conf. on Robotics and Automation, ICRA '18, Brisbane, Australia, May 201

Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization

A Novel Unsupervised Method to Identify Genes Important in the Anti-viral Response: Application to Interferon/Ribavirin in Hepatitis C Patients

Background: Treating hepatitis C with interferon/ribavirin results in a varied response in terms of decrease in viral titer and ultimate outcome. Marked responders have a sharp decline in viral titer within a few days of treatment initiation, whereas in other patients there is no effect on the virus (poor responders). Previous studies have shown that combination therapy modifies expression of hundreds of genes in vitro and in vivo. However, identifying which, if any, of these genes have a role in viral clearance remains challenging. Aims: The goal of this paper is to link viral levels with gene expression and thereby identify genes that may be responsible for early decrease in viral titer. Methods: Microarrays were performed on RNA isolated from PBMC of patients undergoing interferon/ribavirin therapy. Samples were collected at pre-treatment (day 0), and 1, 2, 7, 14 and 28 days after initiating treatment. A novel method was applied to identify genes that are linked to a decrease in viral titer during interferon/ribavirin treatment. The method uses the relationship between inter-patient gene expression based proximities and inter-patient viral titer based proximities to define the association between microarray gene expression measurements of each gene and viral-titer measurements. Results: We detected 36 unique genes whose expressions provide a clustering of patients that resembles viral titer based clustering of patients. These genes include IRF7, MX1, OASL and OAS2, viperin and many ISG's of unknown function. Conclusion: The genes identified by this method appear to play a major role in the reduction of hepatitis C virus during the early phase of treatment. The method has broad utility and can be used to analyze response to any group of factors influencing biological outcome such as antiviral drugs or anti-cancer agents where microarray data are available. © 2007 Brodsky et al