In June 2008, the Cedar River crested flooding more than 5,000 Cedar Rapids homes. Residents whose homes were flooded were invited to participate in this study. We characterized exposures and symptoms experienced by individuals inhabiting 73 flood-damaged homes. Exposures and questionnaire-based health assessments were compared at two levels of remediation, in-progress and completed. Homes with remediation in-progress (n=24), as compared to the completed homes (n=49), had significantly higher airborne concentrations of mold, bacteria, iPM, endotoxin and glucan. Residents of in-progress homes had a significantly higher prevalence of doctor diagnosed allergies (adjusted OR=3.08; 95%CI: 1.05-9.02) and all residents had elevated prevalence of self-reported wheeze (adjusted OR=3.77; 95%CI: 2.06-6.92) and prescription medication use for breathing problems (adjusted OR=1.38; 95%CI: 1.01-1.88) after the flood as compared to before. Proper post-flood remediation led to improved air quality and lower exposures among residents living in flooded homes. Recognition of endotoxin as a proinflammatory ligand for pattern recognition receptors has increased the demand for endotoxin assessment in studies of environmental lung disease. Measurements using the Limulus amebocyte lysate (LAL) assay of air and reservoir dust samples are routinely incorporated into epidemiologic studies. However, it is unknown if endotoxin reactivity in the LAL assay varies by its physical presentation as aggregates, as membrane components of whole bacteria or as shed membrane blebs or if this parallels differences in the inflammatory potency of endotoxin in vivo. Endotoxins as14C-labeled-lipooligosaccharide (14C-LOS) and 14C- labeled-lipopolysaccharide (14C-LPS) were produced from Neisseria meningitidis and Escherichia coli. The reactivity of the endotoxin presentations was assessed in the LAL assay and in vivo using a murine model. The LAL assay significantly underestimated the quantity of endotoxin in the whole bacteria form whereas there was no significant difference in detecting endotoxin in aggregate and bleb forms. The failure of the LAL assay to equally quantify endotoxin was not mirrored in vivo where all three presentations of endotoxin were equally inflammatory. The inability of the LAL assay to detect the full quantity of endotoxin presented in the whole bacteria form has troubling implications for exposure assessment studies. Various extraction methods were applied to samples of known endotoxin quantity to improve the detection ability of the LAL assay. Extraction using EDTA and Tris/EDTA significantly improved the detection of endotoxin compared to the reference method of extracting in pyrogen-free water. These extraction methods also significantly increased the quantity of endotoxin measured in house and barn dust samples. A higher quantity of endotoxin measured in the LAL assay corresponded to a higher neutrophilic response in vivo. A standardized methodology for endotoxin detection that mimics the in vivo response is necessary for accurate and consistent endotoxin analysis.

The purpose of this paper was to develop a single assay system for the enzymes which regulate GABA and glutamate concentrations in brain and nerve tissue. Since all the enzymes produce L-glutamate, their activities were measured by coupling them to L-glutamate decarboxylase. Enzymatic activity was determined by measuring the release of co2 from radioactive substrates. The glutamate decarboxylase was obtained from a commercial acetone powder by simplifying existing procedures. The glutamate decarboxylase produced was of sufficient purity to be used in the coupled assays, which were checked with commercial preparations of each enzyme, where available, and with crude brain homogenates. All of the assays were shown to be linear with respect to both time and enzyme concentration, thus assuring the feasibility of the technique.

Unregulated use of growth promoting antibiotics like Tetracyclines in agricultural feeds is becoming an increasing problem in antibiotic resistance. Undigested antibiotics leads to significant concentrations in livestock waste. These concentrations provide continuous selection pressure for the development of antibiotic resistance genes in the environment. Antibiotic resistance related deaths are projected to surpass cancer related deaths by 2050 making antibiotic resistance a pressing public health issue. The purpose of this study is to determine the abundance and persistence of tetracycline (tet) resistance genes in swine waste over a period of 100 days in an anaerobic digester system. Tet(A), tet(B), tet(G), tet(M), tet(O), tet(Q), and tet(W) were quantified by quantitative polymerase chain reaction after DNA extraction. Primers that target ribosomal protection proteins and efflux proteins were used. Antibiotic resistance genes decreased from day one but were found to be present throughout the study.

Diagnosing disease in equine neonates poses a challenge for the equine industry because of the nonspecific manifestations of many diseases and the rapid deterioration that occurs. The differential diagnostic procedure requires many laboratory tests, whose results take days to receive. Serum amyloid A (SAA) is the only major acute phase protein identified in the horse; it exists in low levels in the healthy horse and increases over 100 fold in response to inflammatory stimulus 6-8 hours post stimulus. A point of care test allows veterinarians to obtain a SAA concentration within minutes that indicates the existence of infection. Being able to test and quantify this protein at the onset of illness may reduce the time before treatment is initiated and therefore increase the chance of survival for the equine neonate, which would greatly help a large problem in the industry.

Target cell lysis is the hallmark of immune effector responses of cytotoxic T lymphocytes (CTL), natural killer (NK) cells, and monocytes. The most commonly used assay to measure target cell lysis is the 51Cr release assay and is considered the ‘gold standard’. However, this assay has many disadvantages that limit its use by most laboratories. Thus, several alternative assays have been developed. Some of these alternative assays are more sensitive, easy to perform and do not use radioactive elements. In this study, four of these assays were evaluated for their ability to detect antigen- specific CTL responses in equine blood. Three long-term equine arteritis virus (EAV) carrier stallions, two vaccinated stallions and one naïve stallion were included in this study. Peripheral blood mononuclear cells (PBMCs) were isolated from whole blood collected of these stallions to be used as effector cells. The PBMCs were stimulated with EAV in vitro for 7-10 days to generate antigen-specific effector cells. The granzyme B assay, the Carboxyfluorescein succinimidyl ester (CFSE)/7-Aminoactinomycin D (7AAD) assay and the Lactate dehydrogenase (LDH) assay were performed using these effector cells and autologous equine dermal cells (isolated from each stallion) as target cells. The first two assays (i.e., granzyme B and CFSE/7AAD assays) were difficult to optimize for this study because they work well with non-adherent targets and require immediate flow cytometry analysis. The LDH assay, however detected CTL lysis in one of the two vaccinated stallions at day 99 post vaccination and no response was detected in PBMCs isolated from carrier stallions and control stallion. Based on these findings, the LDH assay is the most suitable assay since it works well with adherent target cells, it produces quantitative data, and is ideal for high-throughput screening.

Fusarium graminearum is one of the most problematic phytopathogens in US agriculture. This fungus causes head blight, foot rot, and damping off on wheat and barley. The infection lowers the grain yield and causes contamination of the grain product with mycotoxins. Effective control measures are lacking, and new fungicides that kill F. graminearum but remain safe and economical to use are needed. Newly synthesized aminoglycosides (JL22, JL38, JL39, JL40, NEOF004, NEOF005), classic aminoglycosides (amikacin, gentamicin, kanamycin A, kanamycin B, neomycin, and ribostamycin), and a lipopeptide, syringomycin E (SRE), were studied to determine their antifungal potential to control F. graminearum. Aminoglycosides are protein synthesis inhibitors that mainly target bacteria, but a few were recently observed to kill fungi. They consist of an aminocyclitol ring bound with two or more amino sugars. Novel aminoglycosides were recently synthesized using novel glycodiversification synthetic schemes involving the replacement of the original amino sugars with unusual amino sugars. SRE is an antifungal lipodepsinonapeptide produced by Pseudomonas syringae pv. syringae. This bacterium is an opportunistic pathogen in a wide range of plant species and produces several fungicidal lipopeptides. SRE forms pores on fungal plasma membrane and causes ion fluxes. An enhancement of its antifungal activity is reported in the presence of rhamnolipid surfactants. The antifungal activities of various aminoglycosides, SRE, and a SRE-rhamnolipids mixture were determined against F. graminearum by measuring in vitro minimum inhibition concentrations (MICs) and in planta lesion area and chlorosis development using a leaf infection assay protocol. It was determined that using Tween® 20 at 0.2 % (v/v) concentration in the leaf infection assay promotes lesion development by F. graminearum with minimum phytotoxicity. In vitro, SRE, SYRA, and synthetic aminoglycoside JL38 showed the best antifungal activities. With the in planta assay, all three antifungal agents prevented infection by F. graminearum. However, inconsistent phytotoxicities were observed with SRE and SYRA that were influenced by the Tween® 20 surfactant included in the leaf infection assay. How Tween® 20 induces these phytotoxic inconsistencies is not known.

Broadly speaking, the work herein discussed encompasses the development of biomolecular assays for biomarker detection. Specific to the assays in this thesis is the design of reaction schemes that consider the unique requirements of one class of single-molecule sensors in particular: solid-state nanopores formed using a novel fabrication and conditioning technique discovered during this research at the University of Ottawa. We present three unique assays for the detection of different biomolecular targets. The first uses a class of DNA origami structures termed nanoswitches to translate the presence of a short segment of single-stranded DNA Zika virus biomarker to a large configurational change in a double-stranded DNA scaffold. The signal amplification inherent in this topological change allowed us to a achieve a high degree of specificity for detecting a small nucleic acid target by requiring two separate binding events. Furthermore, through careful design of the configurational change, the number of topological states that a solid-state nanopore can sense is limited, providing unambiguous signals in ionic current recordings. Quantification of the Zika gene was performed by sensing the relative amounts of nanoswitches in looped and linear configurations from only hundreds of individual molecules. We then explored the sensitivity of solid-state nanopores for detecting small molecular features along short DNA scaffolds. Leveraging the ability of our nanopores to detect the presence of these protrusions, we present results in which ATP, a molecule significantly too small to be directly detected by the nanopore sensor, initiated an aptamer-based DNA displacement reaction to form a protrusion along scaffolds, producing measurable changes in ionic current signatures in nanopore recordings. Finally, we present an assay in which a microRNA, a biomarker linked to various cancers, was detected through the conjugation of two probes, each of which contained a binding site to different segments of the microRNA. In addition to examining different probe set structures for optimal performance, our two-probe design aimed to improve specificity over conventional single-probe-based assays which only require one recognition step, while still providing unambiguous signals due to the greater-than-doubling in molecular complex size upon conjugation. Furthermore, the use of two individual small probes, rather than one large nanoswitch, increased the resolution with which we could differentiate microRNA concentrations. The assay enabled the quantification of six concentrations of microRNA spanning a single order of magnitude, in only several hundred events, and allowed us to take advantage of the reduced cost, material and labour, as well as increased nanopore capture rates, associated with small assembled molecules.

Altered signaling pathways, which are mediated by post-translational modifications and changes in protein expression levels, are key regulators of cancer initiation, progression, and therapeutic escape. Many aspects of cancer progression, including early carcinogenesis and immediate response to drug treatment, are beyond the scope of genetic profiling and non-invasive monitoring techniques. Global protein profiling of cancer cell line models, tumor tissues, and biofluids (e.g. serum or urine) using mass spectrometry-based proteomics produces novel biological insights, which support improved patient outcomes. Recent technological advances resulting in next-generation mass spectrometry instrumentation and improved bioinformatics workflows have led to unprecedented measurement reproducibility as well as increased depth and coverage of the human proteome. It is now possible to interrogate the cancer proteome with quantitative proteomics to identify prognostic cancer biomarkers, stratify patients for treatment, identify new therapeutic targets, and elucidate drug resistance mechanisms. There are, however, numerous challenges associated with protein measurements. Biological samples have a high level of complexity and wide dynamic range, which is even more pronounced in samples used for non-invasive disease monitoring, such as serum. Cancer biomarkers are generally found in low abundance compared to other serum proteins, particularly at early stages of disease where cancer detection would make the biggest impact on improving patient survival. Additionally, the large-scale datasets generally require bioinformatics expertise to produce useful biological insights. These difficulties converge to create obstacles for down-stream clinical translation. This dissertation research demonstrates how proteomics is applied to develop new resources and generate novel workflows to improve protein quantification in complex biosamples, which could improve translation of cancer research to benefit patient care. The studies described in this dissertation move from assessment of quantitative mass spectrometry platforms, to analytical assay development and validation, and ending with personalized biomarker development applied to patient samples. As an example, four different quantitative mass spectrometry acquisition platforms are explored and comparisons of their ability to quantify low abundance peptides in a complex background are explored. Lung cancers frequently have aberrant signaling resulting in increased kinase activity and targetable signaling hubs; kinase inhibitors have been successfully developed and implemented clinically. Therefore, changes in amounts of kinase peptides in the complex background of peptides from all ATP-utilizing enzymes in a lung cancer cell line model after kinase inhibitor treatment was selected as a model system. Traditional mass spectrometry platforms, data dependent acquisition and multiple reaction monitoring, are compared to the two newer methods, data independent acquisition and parallel reaction monitoring. Relative quantification is performed across the four methods and analytical performance as well as downstream applications, including drug target identification and elucidation of signaling changes. Liquid chromatography – multiple reaction monitoring (LC-MRM) was selected for development of multiplexed quantitative assays based on superior sensitivity and fast analysis times, allowing for larger peptide panels. Method comparison results also provide guidelines for quantitative proteomics platform selection for translational cancer researchers. Next, a multiplexed quantitative LC-MRM assay targeting a panel of 30 RAS signaling proteins was developed and described. Over 30% of all human cancers have a RAS mutation and these cancers are generally aggressive and limited treatment options, leading to poor patient prognosis. Many targeted inhibitors have successfully shut down RAS signaling, leading to tumor regression, however, acquired drug resistance is common. The multiplexed LC-MRM assays characterized and validated are a publically available resource for cancer researchers to interrogate the RAS signal transduction network. Feasibility has been demonstrated in cell line models in order to identify signaling changes that confer BRAF inhibitor resistance and biomarkers of sensitivity to treatment. This analytical LC-MRM panel could support meaningful development of new therapeutic options and identification of companion biomarkers, with the end goal of improving patient outcomes. Multiplexed LC-MRM assays developed for personalized disease biomarkers using an integrated multi-omics approach are described for Multiple Myeloma, an incurable malignancy with poor patient outcomes. This disease is characterized by clonal expansion of the plasma cells in the bone marrow, which secrete a monoclonal immunoglobulin, or M-protein. Clinical treatment decisions are based on multiple semi-quantitative assays that require manual evaluation. In the clinic, minimal residual disease quantification methods, including multi-parameter flow cytometry and immunohistochemistry, are applied to bone marrow aspirates, which is a highly invasive technique that does not provide a systemic evaluation of the disease. To address these issues, we hypothesized that unique variable region peptides could be identified and LC-MRM assays developed specific to each patient’s M-protein to improve specificity and sensitivity in non-invasive disease monitoring. A proteogenomics approach was used to design personalized assays for each patient to monitor their disease progression, which demonstrate improved specificity and up to a 500-fold increase in sensitivity compared to current clinical methods. Assays can be developed from marrow aspirates collected when the patient was at residual disease stage, which is useful if no sample with high disease burden is available. The patient-specific tests are also multiplexed with constant region peptide assays that monitor all immunoglobulin heavy and light chain classes, which could reduce analysis to a single test. In conclusion, highly sensitive patient-specific assays have been developed that could change the paradigm for patient evaluation and clinical decision-making, increasing the ability of clinicians to continue first line therapy in the hopes of achieving a cure, or to intervene at an earlier time point in disease recurrence. This study also provides a blueprint for future development of personalized diagnostics, which could be applied to biomarkers of other cancer types. Overall, these studies demonstrate how quantitative proteomics can be used to support translational cancer research, from the impact of different mass spectrometry platforms on elucidating signaling changes and drug targets to the characterization of multiplexed LC-MRM assays applied to cell line models for translational research purposes and in patient serum samples optimized for clinical translation. We believe that mass spectrometry-based proteomics is poised to play a pivotal role in personalized diagnostics to support implementation of precision medicine, an effort that will improve the quality and efficiency of patient care.

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Abstract not available