Kidney transplant is the reference treatment for patients with end-stage renal disease, but patients may develop long-term rejection of the graft. However, some patients do not reject the transplant, but instead are operationally tolerant state despite withdrawal of immunosuppressive treatment. In this second article we outline a microarray-based identification of key leader genes associated respectively to rejection and to operational tolerance of the kidney transplant in humans by utilizing a non/statistical bioinformatic approach based on the identification of "key genes," either as those mostly changing their expression, or having the strongest interconnections. A uniquely informative picture emerges on the genes controlling the human transplant from the detailed comparison of these findings with the traditional statistical SAM (Tusher et al. 2001 Proc Natl Acad Sci USA 98:5116-5121) analysis of the microarrays and with the clinical study carried out in the accompanying part I article.
Conductometric monitoring of protein-protein and protein-sterol interactions is here proved feasible by coupling quartz crystal microbalance with dissipation monitoring (QCM_D) to nucleic acid programmable protein arrays (NAPPA). The conductance curves measured in NAPPA microarrays printed on quartz surface allowed the identification of binding events between the immobilized proteins and the query. NAPPA allows the immobilization on the quartz surface of a wide range of proteins and can be easily adapted to generate innumerous types of biosensors. Indeed multiple proteins on the same quartz crystal have been tested and envisaged proving the possibility of analyzing the same array for several distinct interactions. Two examples of NAPPA-based conductometer applications with clinical relevance are presented herein, the interaction between the transcription factors Jun and ATF2 and the interaction between Cytochrome P540scc and cholesterol.
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