A simplified approach to human islet quality assessment

Abstract

Background: The successful treatment of patients with type 1 diabetes by islet transplantation is affected by a multitude of factors of which infusion of the highest quality tissue is essential. The current standard pretransplant quality assessments lack sensitivity, accuracy, and objectivity in the determination of islet viability and potency. We hypothesized that a multiparametric approach focused on islet cell metabolic state, mitochondrial integrity, and in vitro glucose-stimulated insulin secretion (GSIS) could provide data predictive of in vivo function. The objective of this study was to validate a novel set of islet quality assays and develop a simplified islet quality scoring system for both basic research and clinical applications.

Methods: A series of 42 human islet preparations were screened using standard and novel methods, which included determination of yield, viability by fluorescent microscopy, GSIS, percentage of islet loss in culture, quantification of adenine nucleotides, flow cytometric measurement of viability, apoptosis, and mitochondrial membrane potential (MMP). In vivo functional potency was tested by minimal model transplant in streptozotocin-induced diabetic NOD.scid mice.

Results: Functionally potent islet preparations showed significantly greater numbers of cells with polarized MMP, higher ATP-to-ADP ratios, and increased glucose-induced insulin secretion. The MMP, ATP-to-ADP ratio, and GSIS data were combined into a single islet scoring formula that showed more than 86% accuracy in predicting in vivo functional potency.

Conclusions: Our study demonstrates that a multiparametric approach using objective assessments focused on islet cell mitochondrial integrity and in vitro function can provide data predictive of in vivo function.

Figure 1. HPLC quantification of total islet adenine nucleotides

Representative chromatograms of HPLC separation of adenine nucleotides from total cellular extracts of INS-1 cells (A), INS-1 cell extracts spiked with ATP, ADP, and AMP standards (B), non-curing (Poor) human islets (C) and curing (Good) human islets(D) when transplanted under the kidney capsule of streptozotocin-induced diabetic NOD.scid mice at a dose of 1000 IEQ/mouse. The insets show the calculated ATP/ADP nucleotide ratios after quantification of the identified peak areas. Data shown are representative of 5 independent INS-1 samples and 14 good and 25 poor human islet preparations.

Figure 2. Flow cytometry assessment of human islet cells

Representative dot plots from single-cell flow cytometry analysis of dispersed human islets. Cellular fragments and free nuclei were excluded from intact cells based upon forward (FSC-A) and side scatter (SSC-A) light parameters (A and B). Data were further restricted to single cells by gating out aggregates based upon FSC-A and forward scatter width (FSC-W) parameters (C and D). Quantification of viability (FDA and Topro3, E and F), apoptosis (Annexin V and VADFMK, G and H), and mitochondrial membrane potential (JC-1, I and J). The left-hand panels show representative staining for an islet preparation that cured STZ-induced diabetic NOD.scid mice at a dose of 1000 IEQ/mouse, while the right-hand panels show islet cell staining from a non-curing preparation.

Figure 3. Comparison of multiple islet quality assessments

Human islet preparation quality was assessed using standard methods including yield (A), viability by fluorescence microscopy of islets stained with FDA and PI (B), GSIS SI (C), and percentage of islet loss during the first 24h of culture (D)) and novel methods including (ATP/ADP ratio (E), flow cytometry quantification of islet cell MMP (F), apoptosis (G), and viability (H). Data shown are the individual values for each sample and sample size is indicated on each graph. Islet quality data was segregated into groups based upon good (closed circles) or poor (open squares) in vivo function (see Methods). Bars indicate the mean and standard deviation for each group. P value calculated by non-parametric Mann-Whitney U test.

Figure 4. Assessment of the predictive value of islet quality assays by Receiver Operator Characteristic analysis

A subset of the standard and extended islet quality assessment data shown in Figure 3 was further analyzed by ROC analysis to evaluate the ability of each test to accurately discriminate potent (“Sensitivity”) from poor functioning (“Specificity”) preparations. ROC curve graphs which illustrate the trade-off between sensitivity and specificity are shown for islet yield (A), flow cytometric quantification of islet cell MMP (B), fluorescence microscopy-based islet viability (C), HPLC ATP/ADP measurement (D), islet loss during culture (E), and glucose-induced insulin secretion (F). Tests which cannot discriminate between true and false positives (A, C, and D) show a Sensitivity plot that is not significantly different from the line of Identity and a p value >0.05 when the Area Under the Curve (AUC) is calculated.

Figure 5. Glycemic control of NOD.scid mice transplanted with human islet preparations with varying islet quality scores

Streptozotocin-induced diabetic NOD.scid mice were transplanted under the kidney capsule with 1000 or 2000 IEQ doses of human islet preparations with Islet Quality Scores (IQS) <0 (left panels) or >0 (right panels). Mice were considered cured if blood glucose levels fell below < 200 mg/dL within 14 days of transplant and were maintained at or below that level until return to the hyperglycemic state following nephrectomy of the graft bearing kidney.