Renal normothermic machine perfusion (NMP) is an organ preservation method based on the circulation of a warm (35-37 degrees C) perfusion solution through the renal vasculature to deliver oxygen and nutrients. However, its biological effects on marginal kidneys are unclear. We therefore used mass spectrometry to determine the proteomic profile of kidney tissue and urine from eight organs reconditioned for 120 min using a Kidney Assist device. Biopsies were taken during the pre-implantation histological evaluation (T-1), at the start of back table preparation (T0), and after 60 and 120 min of perfusion (T60, T120). Urine samples were collected at T0 (urine produced in the first 15 min after the beginning of normothermic reperfusion), T30, T60 and T120. Multiple algorithms, support vector machine learning and partial least squares discriminant analysis were used to select the most discriminative proteins during NMP. Statistical analysis revealed the upregulation of 169 proteins and the downregulation of 196 during NMP. Machine learning algorithms identified the top 50 most discriminative proteins, five of which were concomitantly upregulated (LXN, ETFB, NUDT3, CYCS and UQCRC1) and six downregulated (CFHR3, C1S, CFI, KNG1, SERPINC1 and F9) in the kidney and urine after NMP. Latexin (LXN), an endogenous carboxypeptidase inhibitor, resulted the most-upregulated protein at T120, and this result was confirmed by ELISA. In addition, functional analysis revealed that the most strongly upregulated proteins were involved in the oxidative phosphorylation system and ATP synthesis, whereas the downregulated proteins represented the complement system and coagulation cascade. Our proteomic analysis demonstrated that even brief periods of NMP induce remarkable metabolic and biochemical changes in marginal organs, which supports the use of this promising technique in the clinic.

Proteomics reveals specific biological changes induced by the normothermic machine perfusion of donor kidneys with a significant up-regulation of Latexin

Granata, Simona;di Bella, Caterina;Stallone, Giovanni;Gesualdo, Loreto;
2023-01-01

Abstract

Renal normothermic machine perfusion (NMP) is an organ preservation method based on the circulation of a warm (35-37 degrees C) perfusion solution through the renal vasculature to deliver oxygen and nutrients. However, its biological effects on marginal kidneys are unclear. We therefore used mass spectrometry to determine the proteomic profile of kidney tissue and urine from eight organs reconditioned for 120 min using a Kidney Assist device. Biopsies were taken during the pre-implantation histological evaluation (T-1), at the start of back table preparation (T0), and after 60 and 120 min of perfusion (T60, T120). Urine samples were collected at T0 (urine produced in the first 15 min after the beginning of normothermic reperfusion), T30, T60 and T120. Multiple algorithms, support vector machine learning and partial least squares discriminant analysis were used to select the most discriminative proteins during NMP. Statistical analysis revealed the upregulation of 169 proteins and the downregulation of 196 during NMP. Machine learning algorithms identified the top 50 most discriminative proteins, five of which were concomitantly upregulated (LXN, ETFB, NUDT3, CYCS and UQCRC1) and six downregulated (CFHR3, C1S, CFI, KNG1, SERPINC1 and F9) in the kidney and urine after NMP. Latexin (LXN), an endogenous carboxypeptidase inhibitor, resulted the most-upregulated protein at T120, and this result was confirmed by ELISA. In addition, functional analysis revealed that the most strongly upregulated proteins were involved in the oxidative phosphorylation system and ATP synthesis, whereas the downregulated proteins represented the complement system and coagulation cascade. Our proteomic analysis demonstrated that even brief periods of NMP induce remarkable metabolic and biochemical changes in marginal organs, which supports the use of this promising technique in the clinic.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/441641
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