COMPREHENSIVE AND HIGH THROUGHPUT PANEL OF MOLECULAR AND PATHOLOGY DIAGNOSTIC ASSAYS FOR PORCINE RESPIRATORY DISEASE COMPLEX

<b>Project Methods</b><br> Objective 1. Develop real-time PCR arrays focused on swine viral and bacterial pathogens and inflammatory cytokine profilesSingle and multiplex real-time PCR assays are the main tools used to detect and identify pathogens. Although this method is sensitive, specific, rapid, and quantitative, each standard PCR assay only targets one gene. Therefore, a confirmed diagnosis of PRDC can only be achieved by several runs of different PCR assays, which are time-consuming and labor-intensive. Alternatively, real-time PCR arrays are more cost-efficient methods. They are constructed by parallel integration of several single or multiplex PCR assays to simultaneously detect, identify, and quantify up to hundreds of target genes in a single array platform. In human medicine, several PCR-based arrays are now commercialized and particularly useful in the diagnosis of complicated cases, such as respiratory diseases in patients with immune deficiency. To our knowledge, however, real-time PCR arrays are not, or rarely, developed and applied in veterinary medicine.A real-time PCR array will be developed by integrating multiple individual PCR tests with the same reaction conditions (denature at 95 C for 15 sec, annealing/extension at 60 C for 20 sec, repeated 45 cycles). Our current individual real-time PCR assays for the main PRDC pathogens, as well as inflammatory cytokine profiles, will be adapted or re-designed to fit this requirement. Additional real-time PCR assays for other pathogens will be established, verified, and integrate with this array system. To reduce the cost of reagents, multiplex PCR with TagMan probes and an inexpensive Syber green-based system will be used, depending on the prevalence and clinical significance of the pathogens. The positive control will be the viruses and bacteria preserved in our and other cooperative laboratories, or field samples of new pathogens discovered by metagenomics assays.Once established, cases with more than 40% of pigs getting sick (morbidity) or more than 10% death (mortality) will be subjected to this assay.Objective 2. Establish an in situ hybridization method to detect tissue-based pathogensAside from primary lung infections, respiratory signs in pigs can be attributed to stress, septicemia, endotoxemia, aspiration pneumonia, and many others factors. Pathology examinations are essential to differentiate these conditions, verify the results of molecular assays, and further explore the disease pathogenesis. In addition to assessing morphological changes under the microscope, immunohistochemistry (IHC) and in situ hybridization (ISH) are tools used to localize the pathogens in the tissues. Although IHC is routinely used for the diagnosis of many important pathogens, its application, especially in veterinary medicine, is frequently restricted by the availability of antibodies. On the other hand, ISH is performed with a synthesized DNA/RNA probe against the target gene. Once the target gene sequences are known, it can be readily applied to pathogen detection and genotyping.We will sequence the genome of pathogens by metagenomics assays and compare them with those in GenBank. A conserved region of the sequence will be used for ISH probe design. The procedure will be conducted as stated in a standard protocol. The assays will be interpreted by the pathologists and verified by pathogen isolation, PCR, or metagenomics assays.Objective 3. Develop a high-throughput pathology platform by the combination of in situ hybridization/immunohistochemistry, tissue microarray, and digital image analysisIn standard pathology examination, many individual whole-sectioned slides are reviewed and interpreted by experienced specialists (pathologists). However, the results are sometimes questionable due to the subjectivity and difficulty in describing the entire disease process in a significantly large number of cases. On the other hand, tissue microarray (TMA) is constructed by re-locating tissues from conventional paraffin blocks so that tissues from multiple individuals can be seen on the same slide. Using this method, an entire cohort of cases can be analyzed by staining fewer master array slides simultaneously instead of staining hundreds of conventional slides. Using TMA, the variation between slides will be significantly reduced or even eliminated. In addition, the close proximity of tissue cores permits more rapid and consistent biomarker scoring by pathologists and digital image analysis. Furthermore, deep learning/artificial intelligence (AI) in modern pathology is developing. It will be applied when the technology is mature in the near future.The procedure and application will be described below.Objective 4. Investigate the pathology of potentially underdiagnosed/neglected viruses, including but not limited to porcine parvovirus 2 and rotavirus, in porcine respiratory disease complex (PRDC)Currently, we recognized that porcine parvovirus 2 (PPV2) and porcine rotavirus are potentially underdiagnosed/neglected viruses in PRDC.A retrospective study will be performed using archived formalin-fixed paraffin-embedded (FFPE) samples and a high-throughput TMA. Approximately 200 cases will be selected and subjected to the construction of TMA in which 5 mm diameter tissue cores from 200 donor tissue blocks will be punched, translocated, and integrated into a TMA block as described. The section of TMA will be stained by ISH for the detection of PPV2 and rotavirus, as well as IHC for other main pathogens. Both TMA and whole tissue-section slides will be read by the pathologist to correlate the location of virus antigen with microscopic lesions. Subsequently, the stained slides will be digitized. Semi-qualification of ISH or IHC signal will be conducted using the CellSence cell count and measure module (Olympus). The data will be integrated with those from real-time PCR and records in our laboratory. An overall picture of PPV, rotavirus and multiple co-infections will be displayed by principal component analysis. The relationships among PPV, rotavirus, and other pathogens will be analyzed using Spearman's rank correlation. To identify the risk factors and extract meaningful information, the large data will be grouped by multivariate discriminant analysis and multiple logistic regression analysis. All the statistics will be performed using SAS software.In addition, we will keep discovering additional underdiagnosed, neglected, or new emerging pathogens. The viruses will be isolated if possible. Depending on the preliminary results, the viruses considered to have clinical significance will be subjected to an animal study, along with development of diagnostic reagents and vaccines.Objective 5. Conduct large scale retrospective and cross-sectional studies to understand the condition of multiple co-infection in PRDC Effective control and prevention of PRDC relies on understanding the predisposing factors and pathogenesis. In the laboratory, most of the experiments focus on animals individually inoculated with a single pathogen. However, this does not accurately simulate the natural development of PRDC, which is often characterized by co-infection with multiple identified and unidentified pathogens. Besides, PRDC is often complicated by various environmental factors and individual variations. To date, there is no clear elucidation of the fine mechanisms shaping the complex interactions occurring among the pathogens in PRDC. Instead of challenging the animals in a highly controlled laboratory, large scale of retrospective studies or cross-sectional surveillance of naturally occurred PRDC fits better with the reality in the pig farms. In this project, real-time PCR array and tissue microarray, along with the records in our laboratory, will generate large data. These data will be subjected to biostatistics analysis as described above.