Kaposi's Sarcoma-associated Herpesvirus (KSHV/HHV-8) is a prime example of an infectious etiological agent of cancer, discovered using molecular techniques (representational difference analysis (RDA) rather than conventional culture techniques. In 1994 by Moore and Chang discovered KSHV, ending a decade long search for the cause of Kaposi's Sarcoma and there is still no infectious model for this virus. Where are the current bottlenecks in the detection of novel pathogens associated with chronic disease and cancer? (1) Strength of Association. KSHV could be linked to KS, since only 5% of US blood donors harbor KSHV, while >90% of KS patients have KSHV DNA in their lesion. Infectious agents of chronic diseases are probably present in a wide number of chronic carriers, but increase in load or pathogen combination in afflicted individuals. Hence, quantitative differences of pathogen genome load rather than qualitative differences need to be assessed. (2) Clinical interation. KSHV drew attention, because of an exponential increase in AIDS-patients who developed full-blown disease. Chronic diseases and cancer are already prevalent. Hence, the discovery of novel pathogens (i) need to be integrated into routine clinical sampling to be at the physicians disposal, when that odd, novel indicator case comes along, or (ii) be adopted to high-throughput sampling of patient populations. (3) Exclusion of false leads. Cytomegalovirus for a long time was associated with KS, since the virus is ubiquitous in the human population and reactivates in AIDS patients. For their analysis Chang and Moore picked KS tumor samples from the few CMV negative patients in the cohort. Hence, a high throughput screen for known, but not conventionally cultivatable microbes will identify those patients in which a hunt for novel etiological agents is most promising. Based on our previously published expertise, we propose to adopt quantitative real-time PCR to address these bottlenecks, leading to the following specific aims: (1) We will develop a multi-well panel of real-time RT-PCR and PCR primers, which can specifically and selectively quantify all known human viruses. Using a unified methodology for all agents in a tissue biopsy will prove faster, more cost-effective and remove variability. (2) We will adopt this assay to high throughput screening of clinical samples and develop the bioinformatics tools to (a) organize the data, (b) uncover correlative prevalence between patterns of disease and known viruses. (3) We will adopt current degenerate and consensus PCR methods to a multi-well quantitative real-time PCR format, which would only amplify novel targets. A differential outcome in the PCR between AIMI and AIM 3 would indicate a novel pathogen. All three aims can be viewed as steps in an iterative learning algorithm. With the analysis of each new biopsy, we will evaluate how well our PCR-assay for novel pathogens (aim 3) correlates with pattern of known viruses (aim 1). Heuristic computations would increase or decrease the degeneracy of primers to reduce false positive and increase the possibility to amplify more distantly related sequences.