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Kidney transplantation is the optimal treatment for end-stage kidney disease1,2,3,4; however, transplanted kidneys are often lost prematurely, with up to 50% graft loss at 10 years post-transplant5. Affected patients have increased morbidity and mortality and pose a major economic burden on healthcare systems6. A major cause of premature graft loss is the injury sustained by the graft at the time of transplantation, known as ischemia-reperfusion injury (IRI). IRI is an unavoidable injury caused by diminished blood flow, followed by reperfusion7. Ischemia is characterized by tissue succinate accumulation, which drives reverse electron flow in the mitochondrial respiratory chain, leading to superoxide production and subsequent injury early after reperfusion8. IRI in transplanted organs increases the risk of primary non-function, delayed graft function (DGF), rejection, and inferior graft outcomes8,9. DGF, defined as the need for dialysis in the first week post-transplant9, is a manifestation of severe IRI10. Histologically, IRI-associated DGF is manifested as acute tubular necrosis (ATN), and injury to the microvasculature. Functionally, there is a decrease in the glomerular filtration rate (GFR) and urine output, features of acute kidney injury (AKI) in the allograft11. Despite its importance, there are currently no treatments for ischemia-reperfusion-associated post-transplant AKI. The lack of treatments stems from an incomplete understanding of disease mechanisms and a lack of markers to identify patients at the highest risk of graft dysfunction during the critical time points in which injury may be reversible12.
Accumulating evidence suggests that altered energy metabolism in the allograft mediates AKI and may underpin DGF13,14,15. Kidney cells generate energy via two major mechanisms: mitochondrial respiration and glycolysis16. In IRI, reperfusion results in mitochondrial dysfunction17. Consequently, glycolysis becomes the main energy source13,18,19,20. The metabolic shift in IRI promotes tubular and microvascular endothelial cell death, leading to AKI21,22,23,24. In a previous work, ATN was associated with increased expression of glycolytic enzymes and altered levels of mitochondrial proteins25, in keeping with IRI in the graft13,18. Moreover, in a porcine kidney auto-transplantation model, ischemia followed by cold storage led to reduced levels of kidney mitochondrial proteins and increased lactate excretion26. Altogether, these findings solidify the clinical importance of monitoring the metabolic phenotype of kidney allografts, even before transplant, since basal metabolic features in the allograft can be predictive of allograft dysfunction27.
Clinical prediction models of short-term risk of allograft rejection and loss have been developed28,29. However, these models lack precision and do not consider the molecular features of the graft30,31,32. Recent studies aimed to address this unmet need through the identification of molecular patterns at the tissue level that are associated with inferior graft outcomes, such as allograft dysfunction and rejection13,14,15,25,33,34. These studies rely on steady state molecular measurements at the gene33,34,35, protein25,26, and metabolite level13,14, leaving an incomplete picture of the metabolic phenotype of the allograft. This gap in knowledge is partly due to an inability to measure the metabolic function and the energy state of kidney-derived samples at a particular moment in time. The development of a standardized protocol to determine the metabolic phenotype of biopsy-derived kidney cells, which can potentially be translated into the study of patient samples, is warranted. This article describes a unique workflow to assess mitochondrial respiration (by means of oxygen consumption rate), glycolysis (extracellular acidification rate), and intracellular ATP levels in biopsy-derived kidney cell suspensions. The methodology has been optimized using kidney biopsy cores from healthy adult male pigs. To facilitate future clinical implementation, the biopsy cores were obtained using an 18 G needle, as in the standard clinical protocols of renal graft sampling36,37. Finally, the utility of the protocol implementation in discriminating experimental conditions had been validated in a porcine model of auto-transplantation.