<p>Development of serological assays for the diagnosis of Baylisascaris larva migrans in birds and non-human primates</p>

<p dir="ltr">Lymphoma is a prevalent malignancy in dogs. Diffuse large B-cell Lymphoma (DLBCL) is the common subtype that represents about 50% of the clinically seen lymphoma cases. DLBCL diagnosis relies on cytological examination of a fine needle aspirate and histological evaluation by immunohistochemistry (IHC) in most common practices. This workflow is sufficient to confirm the diagnosis; however, it may be challenging to differentiate reactive and neoplastic forms in some controversial cases. In such cases, PCR-based clonality assays and flow cytometry (FC) can help with more conclusive diagnoses. So, finding more biomarkers that can detect and track DLBCL early and over time is a must for a final diagnosis and helps us learn more about how DLBCL starts at the molecular level. MicroRNAs (miRNAs), the small non-coding RNAs, regulate gene expression by binding to the 3'-untranslated region of protein-coding RNAs, leading to either RNA degradation or translational repression. They can switch on and off genes to regulate physiological and pathological processes. MicroRNA stability features and tissue availability make them promising biomarkers for identifying and sub-classifying patients and sequentially evaluating the disease status or the response toward a specific medicine. This dissertation investigates the small RNA sequence analysis, the differentially expressed miRNAs between healthy and DLBCL-affected lymph nodes, and the miRNA profile in DLBCL cases with different outcomes.</p>

<p>Atopic dermatitis (AD) is a common pruritic skin disease in people and domestic animals that can be severely debilitating and stressful to the patient and the caregiver. The diagnosis of AD requires time consuming and expensive procedures, and treatment is often lifelong at considerable cost. Alterations in the lipid composition of the epidermis are a hallmark of the disease, and these may represent changes caused by the inflammation and defects in the lipid barrier. Liquid chromatography tandem mass spectrometry (LC-MS/MS) and, more recently, untargeted profiling using high-resolution time-of-flight instruments have been used to quantify the lipid composition in skin and other tissues, but these approaches are highly demanding in sample preparation and instrument time. In addition, these methods either detect only a limited number of lipids at the time or the identification of detected mass-to-charge ratio (m/z) is problematic when untargeted profiling is used. New lipidomic approaches that generate lipid profiles in a faster and more efficient manner can lead to a better understanding of these lipid changes. </p><p>The mass spectrometry analytical strategy used in this study, multiple reaction monitoring (MRM)-profiling, rapidly identifies discriminant lipids of the epidermis by flow injection. MRM-profiling is a small molecule accelerated discovery workflow performed in two parts using a triple quadrupole mass spectrometer with electrospray ionization as the ion source. Briefly, the first step consists of discovery experiments based on neutral loss and precursor ion scans to detect lipids in pooled samples by targeting class-specific chemical motifs such as polar heads of phospholipids or sphingoid bases of ceramides. The second step of the MRM-profiling is the screening of individual samples for the transitions detected in the discovery phase. </p><p>We first developed the experimental approach of the MRM-profiling methodology using epidermal samples of mice with AD-like inflammatory skin disease (chronic proliferative dermatitis, cpdm). Subsequently, we investigated lipid changes as the disease in mice progressed from minimal to severe. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. First, we built linear models linking the presence of every lipid monitored to disease stage information. The top 10 lipids, ranked based on η2 effect size, were used to build a predictive elastic-net (E-net) regression model linking the lipid ions detected by MRM-profiling with disease progression. The developed model accurately identified disease stages based on the variations in relative amounts of lipid ions corresponding to phosphatidylcholines, cholesterol esters, and glycerolipids-containing and eicosapentaenoic acid fatty acyl residues. Finally, we investigated the lipid profile of the epidermis in dogs with canine AD using the previously developed methodology. Epidermis from client owned patients and healthy controls were collected. Patients were sampled from affected and unaffected skin avoiding areas with secondary infections and the canine atopic dermatitis extent and severity index (CADESI-4) was recorded. The monitored lipids substantially separated the samples of healthy dogs from atopic dogs and distinguished the affected from the unaffected skin of patients. Samples were grouped into two cohorts for low-score and high-score CADESI-4, the first principal component was able to differentiate the control group from the low and high-score group. Differences in the lipid composition associated with low and high score CADESI-4 were significantly different only after separating the samples by sex of the dogs, demonstrating sexual dimorphism in the lipid changes associated with disease. The compositional data was feature extracted using the CADESI-4 to build linear models that identified oleic acid-containing triacylglycerides, long-chain acylcarnitines and sphingolipids as highly predictive lipids and were subsequently used to construct a predictive E-net regression. The lipid fingerprint obtained from the MRM-profiling was highly correlated (R2=0.89) with the classification of the standardized CADESI-4 score. </p><p>This research showed that changes in the lipid composition of the epidermis can be detected by MRM-profiling in atopic dogs even when the skin looks clinically healthy and that sex is a modifying factor in the lipid profile of canine atopic dermatitis (CAD). We expect that this research leads to a better understanding of the lipid changes in the epidermis during the onset of AD and as the chronic inflammatory process develops. The high prediction rate given by the lipid biomarkers for disease progression identified here by the machine learning strategy provides a potential molecular assessment tool for the diagnosis and monitoring of atopic dermatitis and the patient response to treatment.</p><div><br></div>

<p>Bovine respiratory disease (BRD) is an ongoing health and economic issue in the dairy and beef cattle industry. Also, there are multiple risk factors that make an animal susceptible to BRD and it's diagnosis and treatment is a challenge for producers. Four bacterial species, <em>Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, </em>and<em> Mycoplasma bovis</em> have been associated with BRD mortalities. Hence, this study aims to characterize the cattle nasal microbiome as a potential additional diagnostic method to identify animals suspected to have a lung infection. Quantitative PCR and 16S rRNA gene sequencing were used to determine the bacterial load of these four bacterial pathogens in the nasal microbiome of apparently healthy (N=75) and (N=58) affected by BRD Holstein steers. We then sought to identify a value or equation that could be used to discriminate between BRD and healthy animals using a Linear Discriminant Model (LDA). Additionally, co-occurrence between commensal bacterial and BRD-pathogens were also identified. Cattle diagnosed with BRD presented lower richness, evenness and phylogenetic diversity than healthy pen-mates. Bacterial species and genera <em>Truperella pyrogenes </em>and <em>Bibersteina</em> were increased in the BRD group, and the species <em>Mycoplasma bovirhinis</em> and <em>Clostridium sensu stricto</em> increased in the healthy group. Prevalence of <em>H. somni </em>(98%)<em> </em>and <em>P. multocida </em>(97%) were the highest regardless of disease diagnosis in all the samples. Prevalence of <em>M. haemolytica </em>(81 vs. 61%) and<em> M. bovis </em>(74 vs. 50.7%) were higher in the BRD group. The bacterial density of <em>M. haemolytica</em> and<em> M. bovis </em>was also higher in the BRD group, whereas <em>Histophilus somni</em> was lower in the BRD group. Five different models were tested using LDA, and one model produced a sensitivity and specificity of 60% and 81% agreement with diagnosis based on animal symptoms. Co-occurrence analysis demonstrated that the nasal microbiome members are more likely to interact with each other than associations between BRD-pathogens and nasal microbiome members. This study offers insight into the BRD-pathogens prevalence and difference in nasal microbiome between healthy and BRD animals and provides a potential platform for future studies and potential pen-side diagnostic testing.</p>

<p><em>Background:</em> UC is the most common urogenital cancer, comprising up to 2% of all naturally occurring neoplasia in dogs and can be challenging to diagnose. With early diagnosis, the disease can be controlled in most dogs with a good quality of life. MiRNAs are small non-coding RNAs that function by post-transcriptional regulation of gene expression. Their abundant presence and stability in the body make them promising tools for disease diagnosis. </p> <p><em>Hypothesis:</em> A microRNA (miRNA) signature can be used to differentiate canine urothelial carcinoma (UC) from other lower urinary tract diseases.</p> <p><em>Literature review:</em> There is an overlap of miRNA expression changes between normal physiologic processes, non-infectious and non-inflammatory conditions, infectious and/or inflammatory conditions, and neoplasia. Additionally, the mechanism of action of these overlapping miRNAs varies depending on the disease process. There is a lack of standardization of miRNA evaluation and consistency within a single evaluation method. Herein we evaluate three papers on miRNA expression in canine UC and compared the reported expression profile to human UC literature and identified experimentally validated targets of the dysregulated miRNA. </p> <p><em>Methods and results:</em> <strong>(Aim 1)</strong> Using reverse transcriptase quantitative PCR (RT-qPCR), we assessed the effects of sample handling on miRNA expression in formalin-fixed Paraffin-embedded (FFPE) tissue and urine sediment. We showed that the time of tissue fixation in formalin does not alter the detection of miRNA expression, but the inclusion of the muscularis layer altered the miRNA expression profile in bladder tissue. Additionally, miRNAs in urine sediment were proven to be stable despite the storage temperature for up to two weeks. <strong>(Aim 2)</strong> Using Next Generation Sequencing (NGS) with validation of findings via RT-qPCR, we evaluated differential miRNA expression in bladder tissue collected from normal canine urothelium and the invasive type of UC (iUC) to elucidate the dysregulated pathways. We found that twenty-eight miRNAs were differentially expressed (DE). The DE miRNAs were most often associated with gene silencing by miRNA, miRNAs in cancer, and miRNAs involved in DNA damage responses. Proteins involved include HRAS, KRAS, ARAF, RAF1, MAPK1, MAP2K1, MAPK3, FGFR3, EGFR, HBEGF, RASSF1, E2F2, E2F3, ERBB2, SRC, MMP1, and UP3KA. <strong>(Aim 3)</strong> Using RT-qPCR, expression of miR-214, miR-181a, miR-361, and miR-145 were evaluated. We failed to reject the null hypothesis that the relative gene expression in all groups was the same for any miRNA, nor did we find any multivariate summary that could effectively differentiate UC from inflammatory and non-neoplastic transitional cells. </p> <p><em>Conclusions:</em>   The findings within this thesis highlight the need for standardized methods for miRNA evaluation, support the use of stored samples for miRNA expression analysis, and show the importance of isolating the tissue of interest in FFPE. We defined the miRNome of iUC and investigated numerous protein pathways affected by dysregulation of differentially expressed miRNA in urothelial carcinoma. While we failed to reject our null hypothesis that the miRNA signature we evaluated could be utilized as a diagnostic tool for canine urothelial carcinoma, we showed the promise of miRNA as diagnostic tools and highlight several novel pathways that miRNA regulation affects in this disease. </p>