High-content screening identifies a role for Na(+) channels in insulin production

Abstract

Insulin production is the central feature of functionally mature and differentiated pancreatic β-cells. Reduced insulin transcription and dedifferentiation have been implicated in type 2 diabetes, making drugs that could reverse these processes potentially useful. We have previously established ratiometric live-cell imaging tools to identify factors that increase insulin promoter activity and promote β-cell differentiation. Here, we present a single vector imaging tool with eGFP and mRFP, driven by the Pdx1 and Ins1 promoters, respectively, targeted to the nucleus to enhance identification of individual cells in a high-throughput manner. Using this new approach, we screened 1120 off-patent drugs for factors that regulate Ins1 and Pdx1 promoter activity in MIN6 β-cells. We identified a number of compounds that positively modulate Ins1 promoter activity, including several drugs known to modulate ion channels. Carbamazepine was selected for extended follow-up, as our previous screen also identified this use-dependent sodium channel inhibitor as a positive modulator of β-cell survival. Indeed, carbamazepine increased Ins1 and Ins2 mRNA in primary mouse islets at lower doses than were required to protect β-cells. We validated the role of sodium channels in insulin production by examining Nav1.7 (Scn9a) knockout mice and remarkably islets from these animals had dramatically elevated insulin content relative to wild-type controls. Collectively, our experiments provide a starting point for additional studies aimed to identify drugs and molecular pathways that control insulin production and β-cell differentiation status. In particular, our unbiased screen identified a novel role for a β-cell sodium channel gene in insulin production.

Keywords: high-content screening; insulin synthesis; islet beta-cells; live-cell imaging; sodium channels.

Figure 1.

Targeting fluorescent reporters for Pdx1 and Ins1 to the nucleus and validation. (a) Nuclear localization sequences were added to mRFP and eGFP fluorescent proteins for nuclear targeting. (b) FACS plots of MIN6 cells infected with the original Pdx1/Ins1 dual-reporter vector expressing cytoplasmic fluorescent proteins (left panel), and the new Pdx1/Ins1 dual-reporter vector expressing nuclear-targeted fluorescent proteins (right panel). (c) Insulin1 and insulin2 mRNA were measured by qRT-PCR in vector-infected, FACS-purified Pdx1⁺/Ins1⁻ cells and Pdx1⁺/Ins1⁺ MIN6 cells (n=3), *p<0.05. Pdx1 mRNA was not different between these cell populations. (d) Original Pdx1/Ins1 dual-reporter vector labelled the cytoplasm of MIN6 cells (top panels), whereas the new nuclear-targeted reporters mark only the nucleus of labelled cells (bottom panels).

Figure 2.

Self-organizing response groupings of a three-parameter high-content screen to assay Ins1 promoter activity, Pdx1 promoter activity and cell proliferation/survival. (a) Experimental design for a three-parameter, high-throughput imaging screen using MIN6 β-cells. (b) Self-organizing heat maps of nine result groups generated with AcuityXpress software. In these heat maps, red represents high and green represents low. Screen hits were chosen based on their clustering with positive controls. For example, follistatin is a positive control for a factor that increases Ins1 promoter activity and β-cell differentiation. The blow-up of group 4 (bottom panel) contains the hits that were followed up in this study.

Figure 3.

Effects of drugs on Ins1 promoter activity, Pdx1 promoter activity and cell proliferation/survival. (a–c) Data for the Prestwick library drugs for all three parameters is shown ranked according to their effects on increasing total cell number (bottom panel). Factors outside of the arbitrary purple and green vertical lines were deemed to have potential effects on cell viability and/proliferation. Drugs that fell outside of the blue lines in (a,b), which show 2xMAD (median absolute deviation), were then assessed as possible hits. Hits were chosen for their effects on several outputs such as inducing β-cell maturation by increasing the relative number of mature Pdx1⁺/Ins1⁺ cells (top) and concomitantly reducing the relative number of immature Pdx1⁺/Ins1^low cells (middle). Positive controls are marked in orange.

Figure 4.

Validation of the effects of selected drugs on insulin gene expression using primary mouse islets. After 24 h of drug treatment, Ins1, Ins2 and Pdx1 gene expression were quantified with qRT-PCR relative to DMSO controls in primary mouse islets (n=8). *p<0.05.

Figure 5.

Dose–response profile of carbamazepine on insulin gene expression in primary mouse islets. After 24 h of carbamazepine treatment, Ins1, Ins2 and Pdx1 gene expression were quantified with qRT-PCR relative to DMSO controls in primary mouse islets (n=7). *p<0.05.

Figure 6.

Carbamazepine inhibits Nav1.7 channels. (a,c) Nav1.7 current was measured from a holding potential of −80 mV in HEK 293 cells (a) or −120 mV in islet cells (c). Carbamazepine 100 (a) or 300 μM (c) inhibited the current reversibly. Insets show Na⁺ currents in the absence and presence of drug taken as indicated by the letters (a,b). (b) Steady-state inhibition of Nav1.7 in HEK 293 cells. The half-maximal inactivation was determined as V_0.5 and was −50.2±3.8 for control and −57.8±3.8 and −84.7±7.5 for 100 and 300 μM carbamazepine, respectively. (d) Dose–response curves. In HEK 293 cells, cumulative inhibition was measured. The results from five to six cells per concentration were averaged and the curve calculated by a Hill equation (solid line). Similar results were obtained in isolated islet cells at HP −120 mV (open circles) or HP −80 mV (open blue circle).

Figure 7.

Cumulative effect of sodium channel loss-of-function on insulin production in vivo. Insulin content in islets from female, >1 year old, wild-type or Nav1.7 (Scn9a) knockout mice (n=5,6). *p<0.05.