Research ArticlePhysiology

Hypusine biosynthesis in β cells links polyamine metabolism to facultative cellular proliferation to maintain glucose homeostasis

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Science Signaling  03 Dec 2019:
Vol. 12, Issue 610, eaax0715
DOI: 10.1126/scisignal.aax0715

Translating into a bigger pancreas

The evolutionarily conserved mRNA translation factor eIF5A is critical for cell proliferation in developmental and oncogenic contexts, and its activity depends on hypusination, a posttranslational modification that is unique to eIF5A. Levasseur et al. found that eIF5A hypusination was critical for postnatal expansion of β cell mass in the pancreas. Mice that could not perform hypusination in β cells did not produce sufficient cyclin D2 to sustain cell cycling and developed diabetes in response to diet-induced obesity. Thus, eIF5A hypusination links increased insulin demand caused by insulin resistance with β cell proliferation to maintain glucose homeostasis.


Deoxyhypusine synthase (DHPS) uses the polyamine spermidine to catalyze the hypusine modification of the mRNA translation factor eIF5A and promotes oncogenesis through poorly defined mechanisms. Because germline deletion of Dhps is embryonically lethal, its role in normal postnatal cellular function in vivo remains unknown. We generated a mouse model that enabled the inducible, postnatal deletion of Dhps specifically in postnatal islet β cells, which function to maintain glucose homeostasis. Removal of Dhps did not have an effect under normal physiologic conditions. However, upon development of insulin resistance, which induces β cell proliferation, Dhps deletion caused alterations in proteins required for mRNA translation and protein secretion, reduced production of the cell cycle molecule cyclin D2, impaired β cell proliferation, and induced overt diabetes. We found that hypusine biosynthesis was downstream of protein kinase C-ζ and was required for c-Myc–induced proliferation. Our studies reveal a requirement for DHPS in β cells to link polyamines to mRNA translation to effect facultative cellular proliferation and glucose homeostasis.


The natural polyamines (putrescine, spermidine, and spermine), which are generated endogenously through the action of the enzyme ornithine decarboxylase (ODC), promote cellular proliferation and maintenance (1). Among the polyamines, only spermidine is a substrate for the enzyme deoxyhypusine synthase (DHPS), which transfers a butylamine moiety to the ε-amine of Lys50 of eukaryotic translation initiation factor 5A (eIF5A) to form the rare amino acid hypusine (2). The polyamines, DHPS, and eIF5A have been studied largely in the context of cancer, where they promote oncogenesis by enabling the production of proteins involved in cellular migration and growth (25). These factors are also important in normal cells during development, because germline deletion of the genes encoding ODC (the enzyme that regulates polyamine production), DHPS, and eIF5A in mice induces lethality during early embryonic stages (68). Whereas conditional knockouts of ODC have been described in the context of macrophage polarization (9, 10), the absence of animal models to study either DHPS or eIF5A in the postnatal state has precluded analysis of the potential role of these factors in the maintenance of normal cellular function.

The growth and function of islet β cells are necessary for fuel homeostasis and viability in mammals. β Cells produce insulin, a hormone necessary for glucose disposal and the suppression of ketogenesis and gluconeogenesis. β Cells are considered to have facultative proliferative activity, because they are largely replication-quiescent postnatally (11, 12), but can be induced to proliferate under pathophysiological conditions. For example, during obesity, generalized insulin resistance increases the demand for insulin secretion from β cells to maintain glucose homeostasis (13). In rodents, this increase in insulin secretion is partially met through expansion of β cell mass (14). Although no longitudinal data are available in humans, cross-sectional studies similarly suggest that obese humans have greater β cell mass compared to lean controls (15). Cellular replication is believed to be the dominant mechanism for gains in β cell mass in mice (16), and replicating β cells have been detected in humans, especially in younger individuals (11, 17). The molecular mechanisms governing proliferation in β cells remain incompletely characterized. Given a role for polyamines in oncogenesis, we surmised that DHPS may be critical for the function of polyamines in enabling proliferation of β cells. We previously showed that the hypusine modification is important in the production of stress-responsive proteins during cytokine signaling and endoplasmic reticulum (ER) stress in the pancreatic islet (1820), but a role in facultative proliferation remained speculative.

In this study, we hypothesized that facultative gains in β cell mass during obesity were mediated by the action of DHPS through its downstream hypusine modification of eIF5A. To test this hypothesis, we developed a mouse model to permit inducible, tissue-specific deletion to investigate the role of DHPS during cellular replication of β cells and glucose metabolism in vivo. Collectively, our studies reveal a requirement for hypusine to link specific mRNAs with the translational machinery to effect facultative cellular proliferation.


High-fat diet feeding results in diabetes with attendant loss of β cell mass in Dhps∆β animals

To achieve inducible, tissue-specific deletion of Dhps in mice, we first generated mice in which exons 2 to 7 of the Dhps allele were flanked by Cre recombinase recognition sequences (loxP) (fig. S1A). These mice were backcrossed for 10 generations onto the C57BL6/J background and then crossed to C57BL6/J mice harboring a transgene encoding the Cre recombinase–modified estrogen receptor fusion protein under control of the mouse Ins1 promoter (MIP1-CreERT) (21). Some of the mice were also crossed to Rosa26R-Tomato mice to monitor Cre-mediated recombination (22). The crosses resulted in the generation of multiple different mouse genotypes, which were confirmed by polymerase chain reaction (PCR) genotyping (fig. S1B). Administration of tamoxifen to DhpsloxP/loxP;MIP1-CreERT mice at 8 weeks of age resulted in the generation of β cell–specific knockout mice (henceforth referred to as Dhps∆β mice), as shown by overlapping immunostaining of Tomato fluorescent protein and insulin, indicating β cell–specific recombination at the Rosa26R-Tomato locus (fig. S1C), and by immunoblotting, showing reduced DHPS protein in pancreatic islets but not in the hypothalamus or liver (fig. S1D). One week after the final tamoxifen injection, no alterations in glucose tolerance [by intraperitoneal glucose tolerance test (GTT)] were observed in Dhps∆β mice compared to littermate controls (which included both Cre-positive and loxP/loxP mice) (fig. S1, E and F), a finding suggesting that the acute loss of DHPS in β cells does not immediately affect glucose homeostasis.

To interrogate the role of DHPS in facultative cellular proliferation, we next subjected Dhps∆β and control littermates (including Cre-positive, loxP/loxP, and wild-type controls) to either a high-fat diet (HFD; 60% calories from fat), which induces β cell proliferation (23), or a normal chow diet (NCD; 16% calories from fat). After 4 weeks of feeding (Fig. 1A), both control and Dhps∆β animals on an HFD gained equivalent weight and body fat, which was greater than their NCD-fed counterparts (Fig. 1, B and C). Glucose tolerance as assessed by GTT did not differ between NCD-fed Dhps∆β mice or control mice (Fig. 1, D and E). By contrast, HFD-fed Dhps∆β mice exhibited frank diabetes with significantly worse glucose tolerance compared to HFD-fed control animals (Fig. 1, F and G). Although insulin sensitivity (based on insulin tolerance testing) was reduced in HFD-fed animals, Dhps∆β mice did not differ from control mice (Fig. 1, H and I), suggesting that worsened glucose tolerance in Dhps∆β mice was not due to inherent alterations in insulin sensitivity.

Fig. 1 β Cell–specific knockout of Dhps impairs glucose tolerance after HFD feeding.

Control [wild-type (WT), Cre+, or DhpsloxP/loxP] and Dhps∆β (βKO) mice were fed for 4 weeks with a normal chow diet (NCD) or high-fat diet (HFD), and metabolic parameters were assessed. (A) Schematic timeline showing the period of tamoxifen (TAM) injections and feeding. (B) Body weight at the conclusion of the feeding regimen. Data from n = 5 mice per group. (C) Percent body fat at the conclusion of the feeding regimen. Data from n = 4 mice per group. (D) Glucose tolerance test (GTT) in NCD-fed mice. (E) Area under the curve (AUC) analysis of GTTs in (D). (F) GTT in HFD-fed mice. (G) AUC analysis of GTTs in (F). (H) Insulin tolerance test in NCD- and HFD-fed mice. (I) Area over the curve (AOC) of insulin tolerance test in (H). (J) Serum insulin levels during a GTT. (K) Images of whole pancreatic sections from representative HFD-fed control and Dhps∆β mice immunostained for insulin (brown) and counterstained with hematoxylin. Scale bars, 1000 μm. (L) Quantitation of pancreatic β cell mass. Data from n = 3 to 6 mice per group. (M) Representative images of pancreata stained for TUNEL (red), insulin (green), and nuclei (DAPI, blue). Scale bars, 50 μm. (N) Quantification of TUNEL immunostaining (n = 3 mice per group). Data presented as means ± SEM; *P < 0.05 for the comparisons shown by one-way ANOVA.

To evaluate β cell function in HFD-fed Dhps∆β mice, we performed glucose-stimulated insulin secretion studies in vivo. Whereas insulin levels were similar between Dhps∆β and controls on an NCD, HFD-fed Dhps∆β mice showed significantly lower absolute insulin levels 2 min after an intraperitoneal glucose load and lower incremental changes in insulin levels compared to HFD-fed controls, consistent with an impairment in insulin secretion (Fig. 1J). HFD-fed Dhps∆β mice failed to gain β cell mass in contrast to HFD-fed controls (whose mass was greater than that in animals placed on an NCD) (Fig. 1, K and L). This failure to gain β cell mass was likely caused by the lack of cellular accrual (proliferation) rather than an increase in cellular death, because we did not observe increases in TUNEL (terminal deoxynucleotidyl transferase–mediated deoxyuridine triphosphate nick end labeling) staining of β cells in pancreas sections from Dhps∆β mice compared to controls (Fig. 1, M and N).

Gene expression and proteomics analyses suggest a potential defect in mRNA translation

To interrogate the molecular effects of DHPS deficiency, we next performed RNA deep sequencing and global proteomics analyses on isolated islets from Dhps∆β and control animals from the HFD-fed group. In RNA deep-sequencing studies, islets from HFD-fed controls (one Cre-positive and two loxP/loxP animals) and Dhps∆β mice showed distinct clustering in principal components analysis, with greater variance seen among control than Dhps∆β islets (Fig. 2A). Deletion of Dhps resulted in a total of 747 genes that were significantly differentially expressed in islets from 4-week HFD-fed mice, when using the criteria of P < 0.05 and fold change > 2.0 (Fig. 2B). By Gene Ontology Enrichment Analysis, the greatest enrichment of genes in Dhps∆β islets was observed in pathways affecting cell cycle, mitotic nuclear division, and cell division (Fig. 2C). Virtually, all of the genes involved in cellular replication were significantly increased in Dhps∆β islets compared to control islets (Fig. 2D). Because the primary role of DHPS is the posttranslational activation of the mRNA translation factor eIF5A, we also performed tandem mass spectrometry (MS/MS)–based proteomics analysis on islets from HFD-fed mice. A total of 130 proteins (out of a total of 1991 proteins identified) were significantly altered in Dhps∆β islets compared to controls (using P < 0.05; Fig. 2E). Application of Gene Ontology Enrichment Analysis showed that these proteins clustered in pathways affecting primarily mRNA translation, protein folding, exocytosis, and oxidation-reduction processes (Fig. 2F)—all pathways consistent with effects of eIF5A on translation and protein trafficking through the ER. Because of their low abundance relative to others in the β cell, cell cycle proteins either were not detected or were not statistically significantly changed in this analysis.

Fig. 2 RNA sequencing and proteomics of control and β cell–specific Dhps knockout islets.

Control (Cre+ and DhpsloxP/loxP) and Dhps∆β (βKO) mice were fed an NCD or HFD for 4 weeks. Data from n = 3 mice per group. (A) Principal components analysis displaying the variance of RNA sequencing data obtained from control and βKO islets. (B) Volcano plot of differentially expressed mRNAs in comparison between control and Dhps∆β islets. FC, fold change. (C) Gene Ontology Enrichment Analysis for mRNA sequencing data. (D) Heatmap of differentially expressed genes involved in cellular proliferation. (E) Volcano plot of differentially expressed proteins in comparison between control and Dhps∆β mice. Data from n = 3 to 6 mice per group. (F) Gene Ontology Enrichment Analysis from proteomics data.

β Cell proliferation after HFD feeding is impaired in Dhps∆β mice

Because Dhps∆β mice did not accrue β cell mass, the increases in mRNAs encoding pro-proliferative proteins suggested to us a possible transcriptional compensatory response. β Cell proliferation is observed as early as 1 week after initiation of HFD feeding (2326). We therefore examined phenotypic and molecular characteristics in control and Dhps∆β mice after 1 week of NCD or HFD feeding. Immunoblots and immunostaining of islets revealed that the levels of hypusinated eIF5A (eIF5AHyp) increased in control animals upon HFD feeding (Fig. 3, A and B, and fig. S1G), whereas in islets from Dhps∆β animals, eIF5AHyp levels by immunostaining were significantly reduced and not detectably changed upon HFD feeding (Fig. 3, A and B). The intensity of immunostaining for eIF5ATotal did not change with diet or genotype (Fig. 3, C and D), suggesting that the changes in eIF5AHyp levels are a result of posttranslational modification. Glucose tolerance, circulating insulin, and β cell mass did not differ between Dhps∆β mice and littermate controls on an NCD (Fig. 4, A to D), whereas HFD-fed Dhps∆β mice exhibited a small, but statistically insignificant, improvement in glucose tolerance compared to control mice after 1 week of feeding (Fig. 4, E and F). Consistent with this finding, circulating insulin levels in HFD-fed Dhps∆β mice were slightly but significantly higher than in the control animals (Fig. 4G). At this time point, β cell mass was similar between Dhps∆β and control mice fed an HFD (Fig. 4H). To interrogate alterations in β cell proliferation, we performed immunofluorescence staining of pancreas sections from NCD- and HFD-fed animals for Ki67, a marker of cellular proliferation. One week of HFD feeding increased the frequency of Ki67-positive β cells compared to NCD in control littermates, an increase that did not occur in Dhps∆β mice (Fig. 4, I and J). Moreover, Ki67 positivity remained significantly lower in Dhps∆β compared to control littermates when fed either an NCD or HFD (Fig. 4J). Together, these results suggest that loss of Dhps impairs the early β cell proliferative response to an HFD.

Fig. 3 Hypusination of eIF5A is increased after 1 week of HFD feeding.

Control Cre+ and Dhps∆β (βKO) mice were fed for 1 week with NCD or HFD, and eIF5AHyp and eIF5ATotal levels were assessed by immunostaining of pancreas sections. (A) Representative images of pancreata stained for eIF5AHyp (magenta), insulin (green), and nuclei (DAPI, blue). Scale bars, 50 μm. (B) Quantification of eIF5AHyp immunostaining in (A) from n = 3 animals per group. (C) Representative images of pancreata stained for eIF5ATotal (magenta), insulin (green), and nuclei (DAPI, blue). Scale bars, 50 μm. (D) Quantification of eIF5ATotal immunostaining in (C). Data from n = 3 animals per group. Data presented as means ± SEM; *P < 0.05 for the comparisons shown by one-way ANOVA.

Fig. 4 β Cell–specific Dhps knockout mice exhibit normal glucose tolerance after 1 week of HFD feeding.

Control (Cre+, WT, and DhpsloxP/loxP) and Dhps∆β (βKO) mice were fed for 1 week with NCD or HFD, and metabolic parameters were assessed. (A) GTT in NCD-fed mice. (B) AUC analysis for GTT from NCD-fed mice in (A). (C) Serum insulin levels in NCD-fed mice in (A). Data from n = 3 Cre+ and DhpsloxP/loxP mice and n = 5 Dhps∆β mice. (D) β Cell mass in NCD-fed mice in (A). n = 3 mice per group. (E) GTT in HFD-fed mice. (F) AUC analysis for GTTs in (E). (G) Serum insulin levels in HFD-fed mice in (E). Data from n = 3 Cre+ and DhpsloxP/loxP mice and n = 4 Dhps∆β mice. (H) β Cell mass in HFD-fed mice in (E). Data from n =3 Cre+ and DhpsloxP/loxP mice and n = 5 Dhps∆β mice. (I) Representative images of pancreata from the indicated mice stained for Ki67 (magenta, arrow), insulin (green), and nuclei (DAPI, blue). Scale bar, 50 μm. (J) Quantification of Ki67 immunostaining in (I). Data from n = 3 to 5 animals per group. Data presented as means ± SEM; *P < 0.05 by one-way ANOVA.

Dhps deficiency in β cells impairs Ccnd2 mRNA translation during HFD feeding

To clarify the molecular alterations that contribute to the defective β cell proliferative phenotype in Dhps∆β mice, we evaluated in isolated islets the expression of specific genes involved in cell cycle progression at the G1-S boundary (Fig. 5A). The levels of several key mRNAs crucial to β cell proliferation, including Ccnd2 (encoding cyclin D2), Ccnd1 (encoding cyclin D1), and Ccna2 (encoding cyclin A2), did not differ between HFD-fed control and Dhps∆β islets (Fig. 5B). However, cyclin D2 protein levels in islets were significantly reduced in Dhps∆β islets compared to controls after 1 week of HFD feeding (Fig. 5C). By contrast, no differences were seen in the protein levels of cyclin D1 (Fig. 5C).

Fig. 5 Decreased mRNA translation of cyclin D2 in Dhps∆β mice.

(A) Schematic showing experimental design. Control (Cre+) and Dhps∆β (βKO) mice were fed an HFD for 1 week, and islets were isolated and subjected to RT-PCR and polyribosome profiling (PRP) analysis. (B) Quantitative RT-PCR from islets for the genes indicated. Data from n = 5 to 6 animals per group. (C) Representative immunoblot analysis from islets for cyclin D2, cyclin D1, and ERK1/2 (left) and quantification of immunoblots (right). Data from n = 3 to 5 animals per group. (D) PRP of isolated islets (left) and quantification of P/M ratio (right). Data from n = 3 mice per group. (E) Quantitative RT-PCR of Cycd2 in polyribosomal fractions. Data from n = 3 to 4 mice per group. (F) Quantitative RT-PCR of Cycd1 in polyribosomal fractions. Data from n = 3 to 4 mice per group. Data presented as means ± SEM; *P < 0.05 by t test.

Given the dissociation between mRNA levels and protein levels for cyclin D2, we next asked whether loss of DHPS impaired the translation of Ccnd2 mRNA. We performed polyribosome profiling (PRP) studies using lysates from islets of 1-week HFD-fed animals. PRP involves sucrose gradient sedimentation of cellular extracts to fractionate total RNAs based on their association with ribosomes (27). RNAs associated with monoribosomes sediment higher in the gradient compared with those that are associated with multiple ribosomes (polyribosomes)—and hence are actively translated. Dhps∆β islets were similar to Cre-positive control islets in terms of the polyribosome:monoribosome (P/M) ratio (which reflects the relative association of RNAs with polyribosomes compared to monoribosomes) (Fig. 5D). This result suggested that global translation of RNAs was unaffected by deletion of Dhps in β cells. To interrogate the translation of specific mRNAs, we performed reverse transcription PCR (RT-PCR) analysis for Ccnd2 and Ccnd1 on sedimentation gradient fractions. Ccnd2 mRNA exhibited a shift in occupancy toward monoribosomes in Dhps∆β islets compared to Cre-positive control islets, indicating its absence of engagement with polyribosomes (Fig. 5E). In contrast, the polyribosome engagement of Ccnd1 mRNA was similar between Dhps∆β islets and Cre-positive controls (Fig. 5F). Collectively, these results suggest reduced translational initiation of Ccnd2 in Dhps∆β mouse islets.

ODC and c-Myc lie upstream of DHPS activity

DHPS uses the polyamine spermidine as a substrate to generate hypusine on eIF5A. We asked whether depletion of polyamines in mice impaired β cell proliferation similarly to loss of DHPS. The rate-limiting enzyme for the production of polyamines is ODC, which is irreversibly inhibited by difluoromethylornithine (DFMO) (28). Male C57BL/6J mice were given DFMO (or vehicle) in their drinking water for 5 days before and concurrently with 1 week of HFD feeding. DFMO-treated mice had similar body weight, glucose tolerance, and β cell mass as vehicle-treated mice (fig. S2, A to D). Similar to Dhps∆β mice, DFMO-treated mice exhibited reduced β cell proliferation compared to controls (fig. S2, E and F), suggesting that ODC activity and polyamines are required for the β cell proliferative response to HFD feeding.

The transcriptional activity of the gene encoding ODC (Odc1) is regulated, in part, by the oncogenic transcription factor c-Myc (29). To test the possibility that the proliferation axis involving c-Myc and ODC depends upon the downstream activity of DHPS, we used a small-molecule activator of c-Myc (harmine) (30) and a specific inhibitor of DHPS (Gc7) (31, 32) in mouse islets in vitro. Mouse islets treated with harmine exhibited an increase in levels of cyclin D2 by immunoblot, but concurrent treatment with both harmine and Gc7 abolished this effect (Fig. 6A). Flow cytometry analysis (Fig. 6B and fig. S3A) of islet cells demonstrated that a marker of cellular mitosis (phosphorylated histone H3) was increased upon 72 hours of harmine treatment and was reduced to baseline upon concurrent treatment with Gc7. To confirm that the effects seen with Gc7 are likely mediated through inhibition of DHPS, we next tested the effects of harmine on islets from Dhps∆β mice. After harmine treatment, islets from Cre-positive control mice exhibited a significant increase in proliferation as measured by Ki67 staining compared to vehicle treatment; by contrast, treatment of Dhps∆β mouse islets did not result in a significant increase in Ki67 immunostaining after harmine treatment (Fig. 6C and fig. S3B).

Fig. 6 DHPS inhibition attenuates harmine-induced β cell proliferation in mouse and human islets.

(A) Islets were isolated from male 8- to 9-week old CD1 mice and then treated in vitro with vehicle (V), harmine (H), and Gc7 (G). Representative immunoblot (top) and quantification of protein levels (bottom) for cyclin D2. Data are from n = 6 mice per group. (B) Islets were isolated from male 8- to 9-week old CD1 mice and then treated in vitro with vehicle (V), harmine (H), and Gc7, followed by flow cytometry analysis of dispersed islet cells immunostained for phospho–histone H3. Data are from n = 4 to 6 mice per group. (C). Islets were isolated from control (Cre+) and Dhps∆β (βKO) mice and then treated in vitro with vehicle (V) or harmine (H), and percent of β cells that immunostained for Ki67 was calculated. Data are from n = 3 animals per group. (D) Human islets from four donors were treated in vitro with vehicle, harmine, and/or Gc7 (G), dispersed, immunostained for phospho–histone H3, and then subjected to flow cytometry analysis. BMI, body mass index. Graphs show a single technical replicate for each donor. Data in (A) to (C) are presented as means ± SEM; *P < 0.05 by one-way ANOVA.

To interrogate the c-Myc/ODC/DHPS axis in human islets, we performed flow cytometry for phosphorylated histone H3 in human islets incubated with Gc7 and/or harmine. Harmine treatment resulted in an increase in phosphorylated histone H3–positive cells in each of the four islet donors, with inhibition of this effect by concurrent Gc7 treatment (Fig. 6D and fig. S4). Collectively, these data in mouse and human islets suggest that c-Myc induction of human islet cell proliferation requires DHPS activity.

The activity of DHPS depends on PKC-ζ

A key pathway that links extracellular mitogenic signals to mRNA translation and β cell proliferation is the growth factor/mTORC1 (mammalian target of rapamycin complex 1) pathway (23, 3337). Protein kinase C-ζ (PKC-ζ) is proximal to mTORC1 (38, 39), and in mice harboring kinase-dead PKC-ζ protein in β cells (β-KD-PKC-ζ), the proliferative response to obesity and insulin resistance is impaired (23)—a phenotype similar to Dhps∆β mice. To determine how the mTORC1 pathway might be linked to the ODC/DHPS/eIF5A pathway, we examined the levels of eIF5AHyp in the islets of HFD-fed β-KD-PKC-ζ mice by immunostaining. The staining intensity for eIF5AHyp was increased in the islets of control animals, but not in those of β-KD-PKC-ζ mice upon HFD feeding (Fig. 7, A and B). Staining intensity of eIF5ATotal did not change with diet or genotype (Fig. 7, C and D). These findings suggest that the phenotype of β-KD-PKC-ζ mice may be due to the loss of eIF5AHyp formation. To confirm that DHPS is downstream of PKC-ζ, we next examined whether activation of PKC-ζ (through its phosphorylation at residue Thr410) occurred in Dhps∆β mice. Immunostaining showed that the phosphorylation of PKC-ζ did not differ between control and Dhps∆β mice fed either an NCD or HFD (Fig. 7, E and F). Collectively, these data suggest that DHPS lies downstream of PKC-ζ.

Fig. 7 Hypusine generation requires PKC-ζ.

WT and kinase-dead PKC-ζ (KD) mice were fed an NCD or HFD for 1 week. (A) Representative images of pancreata stained for eIF5AHyp (magenta), insulin (green), and nuclei (DAPI, blue). (B) Quantification of eIF5AHyp levels from (A). Data are from n = 3 mice per group. (C) Representative images of pancreata stained for eIF5ATotal (magenta), insulin (green), and nuclei (DAPI, blue). (D) Quantification of eIF5ATotal levels from (B). Data are from n = 3 mice per group. (E) Representative images of NCD- and HFD-fed control and Dhps∆β (βKO) mouse pancreata immunostained for phospho-PKC-ζ (red), insulin (green), and nuclei (DAPI, blue). Scale bars, 50 μm. (F) Quantification of phospho-PKC-ζ immunostaining in insulin-positive cells shown in (E). Data are from n = 3 mice per group. Data presented as means ± SEM; *P < 0.05 for the comparisons shown by one-way ANOVA.


The polyamines putrescine, spermidine, and spermine participate in cellular replication, and their depletion by inhibition of ODC has been a focus of antiproliferative therapies for several cancers (40, 41). A specific role for spermidine was suggested in our previous zebrafish study (42), showing that inhibition of ODC, which results in reduced pancreatic cell proliferation, can be rescued by supplementation with spermidine. However, the mechanism of this rescue remained elusive. A specific role of DHPS as a downstream effector of spermidine has not been rigorously tested in mammals in vivo, owing, in part, to the embryonic lethality of mice harboring germline homozygous mutations in Dhps (6, 7). Our studies using a conditional knockout mouse model of Dhps allowed the demonstration of a role of Dhps in β cell proliferation.

Two concepts regarding the growth and replication of postnatal β cells have emerged. First, although β cells were originally considered to be postmitotic cells in the adult mammal, it is now recognized that they exhibit a slow rate of replication that decreases with age (11, 12, 17, 43). Second, the mass of β cells can be altered to compensate for insulin resistance that occurs during physiologic or pathologic processes, such as growth, gestation, and obesity and insulin resistance (44, 45). The mechanisms that underlie the compensatory gains in β cell mass are thought to involve both increases in cell size and number, and with respect to the latter, the molecular pathways triggering cell cycle entry remain incompletely understood. In this study, we focused on the molecular mechanisms at the onset of compensatory β cell mass expansion during obesity/insulin resistance. Using an inducible β cell–specific knockout mouse model, we found that DHPS activity was increased in islets in response to HFD feeding, that DHPS was necessary for the induction of β cell replication and for the maintenance of normal glucose homeostasis after HFD feeding, that DHPS promoted the mRNA translation of the critical cell cycle regulator Ccnd2, and that DHPS activity was downstream of c-Myc and PKC-ζ. Our studies do not entirely rule out a role for DHPS in the maintenance of β cell function (in addition to mass); in many cases, mass and function are closely intertwined, and the defects we observed in our proteomics data (with alterations in pathways of protein translation and secretion) may suggest some loss in β cell function.

DHPS catalyzes the first and rate-limiting step of the hypusine modification of eIF5A (2). eIF5AHyp facilitates the elongation and termination phases of mRNA translation in yeast (46). In mammals, it is unclear whether eIF5AHyp functions as a general translation factor or a factor specific for certain mRNAs. A proteomics study of eIF5A-depleted HeLa cells has revealed alterations in protein folding and mRNA translation pathways, suggestive of a role for the factor in ER stress–related processes (47). In our study, we demonstrated that loss of DHPS resulted in the expected reduction in eIF5AHyp levels and acute reduction in the translation of a key cell cycle gene whose product, cyclin D2, was necessary for adaptive β cell replication. Notably, the loss of Dhps in β cells did not acutely affect translation globally, because there were no changes in either the islet PRP analysis or the specific translation of another cell cycle gene (Ccnd1). Moreover, the loss of Dhps appeared to cause an mRNA translation initiation block, rather than a block in translation elongation or termination. With respect to the latter point, our findings suggest that Dhps had an effect that was independent of eIF5AHyp, a possibility that we think is unlikely or that resulted from the accumulation of the unhypusinated form of eIF5A. Resolution of these possibilities will require the conditional deletion of the gene encoding eIF5A. We should note that our findings are distinct but mechanistically consistent with our prior observations that DHPS promotes the translation of key proteins involved in the apoptotic phase of ER stress in pancreatic islets (20).

Little is known about the regulation of eIF5AHyp formation. We linked two regulators of cellular proliferation, PKC-ζ and c-Myc, to hypusination. PKC-ζ is an atypical Ser/Thr protein kinase that lies proximal to mTOR activation (23, 39). The phenotype of β-KD-PKC-ζ mice is similar to that of Dhps∆β mice described here, in which defects in HFD-induced cyclin D2 activation and β cell proliferation result in a diabetic phenotype (23). This observation led us to explore a possible link between the PKC-ζ/mTOR and DHPS/eIF5AHyp pathways, and we observed that eIF5A hypusination in β cells in response to HFD feeding required intact PKC-ζ activity. Conversely, activation of PKC-ζ (as assessed by phospho-PKC-ζ immunostaining) did not appear to be dependent upon DHPS. These findings therefore place PKC-ζ upstream of DHPS/eIF5AHyp in a pathway that links nutritional signals from HFD feeding to β cell replication. c-Myc is an oncogenic transcription factor that can drive rodent and human β cell replication (30, 48, 49). Because c-Myc is a direct transcriptional activator of the gene encoding ODC (Odc1) (29), we surmised that the effect of c-Myc in inducing proliferation may be mediated at least partially through the ODC/DHPS/eIF5AHyp axis. Our studies using the DYRK1A inhibitor harmine (which indirectly activates c-Myc) (30) suggest that the pro-proliferative effects of c-Myc are abrogated when DHPS is inhibited in mouse and human islets.

In conclusion, we demonstrated a role for DHPS in β cell replication. Our studies involving the PKC-ζ/mTOR and c-Myc/ODC pathways implicate DHPS as a key node through which these pathways affect replication in the β cell (Fig. 8). Our work opens several future avenues of investigation, including the mechanism by which PKC-ζ influences eIF5A hypusination (through ODC compared to DHPS), the role of exogenously and endogenously derived spermidine as a substrate for DHPS during facultative proliferation, and the potential independent effect of accumulating unhypusinated eIF5A on the proliferative response. The resolution of these and other related issues must await the analysis of animal models with conditional knockout of Odc1 and Eif5a1.

Fig. 8 Proposed pathway linking PKC-ζ, c-Myc, and polyamines to adaptive proliferation in β cells.

The schematic diagram shows the proposed positioning of the PI3K-PKC-ζ-mTOR pathway (left arm of the diagram) and the polyamine-eIF5A pathway (right arm of the diagram) relative to the adaptive translational and proliferative responses. The hierarchy of the factors depicted in red (PKC-ζ, c-Myc, ODC, and DHPS) have been shown in this study or others to serve as key nodes through which proliferative responses are mediated—deletion or inhibition of these factors severely restricts the ability of the β cell to produce cyclin D2 and undergo replication. This study demonstrated that DHPS is downstream of PKC-ζ, c-Myc, and ODC functions. This study does not explicitly rule out the possibility that PKC-ζ might directly or indirectly regulate the function of DHPS (shown as a dashed line with a question mark).


Animal studies

Mice containing the floxed Dhps alleles were crossed to MIP1-CreERT (21) mice to generate Dhps∆β mice on the C57BL/6J background. Animals were maintained under protocols approved by the Indiana University School of Medicine Institutional Animal Care and Use Committee. The following primers were used for genotyping Dhps∆β mice: 5′-GTAAACTAGAGTTCTGCGATGGGTGG-3′ (forward) and 5′-TCAATCTGGTCATAAGGGCACAGG-3′ (reverse), and were expected to generate a 319–base pair (bp) band for the wild-type allele and 396 bp for the floxed allele. Mice were crossed to B6.Cg-Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J, and pancreas tissue was harvested to visualize Tomato expression. Male mice with the desired genotype were then weaned and used for all the experiments in this study. Mice were administered three daily intraperitoneal injections of 2.5 mg of tamoxifen dissolved in peanut oil at 8 weeks of age. Mice were then allowed to acclimate for 1 week before being placed on either an NCD (16% kcal from fat; Research Diets; D12492) or HFD (60% kcal from fat; Research Diets; D12492). Glucose and insulin tolerance tests were performed as described (18). Mice harboring β-KD-PKC-ζ (23) were placed on either an NCD or HFD at 8 weeks of age, as previously described (23), and euthanized for pancreas tissue after 1 week.

Cell isolation and culture

Mouse islets were cultured in 11 mM glucose as previously described (50). Human islets were obtained from the Integrated Islet Distribution Program or from the University of Alberta and maintained in complete Standard Islet Medium (Prodo Labs) and supplemented with ciprofloxacin (Thermo Fisher Scientific). Mouse and human islets were pretreated with 100 μM Gc7 or vehicle (10 mM acetic acid) for 16 hours before concurrent treatment with 10 μM harmine (Sigma-Aldrich) or vehicle (dimethyl sulfoxide) for 48 or 72 hours before collection for Western blot or flow cytometry analysis.

Immunostaining and morphometric assessment of β cell mass and β cell death

β Cell mass was calculated as previously detailed using at least five mice per group (51). Pancreata and isolated islets were stained using the following antibodies: anti-insulin (1:350, #A0564, Dako), anti-Ki67(1:200, #Ab66155-200, Abcam), anti-eIF5AHyp (1:200, IU-44), anti-eIF5ATotal (1:200, #611977, BD Pharmingen), and anti–phospho–PKC-ζ [1:100, SAB4503773, Sigma-Aldrich; 4′,6-diamidino-2-phenylindole (DAPI), Thermo Fisher]. Apoptosis was detected using the ApopTag Red In Situ Apoptosis Detection Kit (Millipore Sigma). Images were acquired using a Zeiss LSM 800 microscope (Carl Zeiss).


PRP experiments using isolated islets proceeded as described previously (52). Total RNA from the PRP fractions was reverse-transcribed and subjected to SYBR Green I–based quantitative RT-PCR. P/M ratios were quantitated by calculating the area under the curve (AUC) corresponding to the polyribosome peaks (more than two ribosomes) divided by the AUC for the monoribosome (80S) peak. Primers for Ccnd2, Ccna2, and Ccnd1 were described previously (24, 26).

Immunoblot analysis

Whole-cell extracts from mouse islets were prepared as described previously and subjected to a 4 to 20% gradient SDS–polyacrylamide gel electrophoresis (53). For immunoblots, antibodies were as follows: anti-eIF5AHyp (1:3000) (54), anti-eIF5ATotal (1:3000, clone 26, BD Biosciences), anti-ERK1/2 (extracellular signal–regulated kinase 1/2) (1:1000, sc-94, Santa Cruz Biotechnology), anti–cyclin D2 (1:1000, AB-2, Thermo Fisher Scientific), anti–cyclin D1 (1:1000, AB-1, Thermo Fisher Scientific), anti–β-tubulin (1:3000, 9F3, Cell Signaling), and anti-DHPS (1:1000, sc-365077, Santa Cruz Biotechnology). Immunoblots were visualized using fluorescently labeled secondary antibodies (LI-COR Biosciences) and were quantified using LI-COR software.

RNA sequencing library preparation and sequencing

Purified total RNA was first evaluated for its quantity and quality using an Agilent Bioanalyzer 2100. All RNA samples had a RIN (RNA integrity number) of 8 or higher. Ten nanograms of total RNA per sample was used for library preparation. Complementary DNA (cDNA) was first synthesized through RT with poly-dT priming, using the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara Clontech Laboratories Inc.), followed by cDNA shearing with Covaris AFA sonicator (Covaris) and size selection with AMPure beads (Beckman Coulter). Barcoded cDNA library was then prepared using the Ion Plus Fragment Library Kit (Thermo Fisher Scientific). Each library was quantified and its quality was assessed using Agilent Bioanalyzer, and multiple libraries were pooled in equal molarity. Average size of library insert was about 150 bp. Eight microliters of 100 pM pooled libraries was applied to ion sphere particle (ISP) template preparation and amplification using Ion OneTouch 2, followed by ISP loading onto a PI Chip and sequencing on an Ion Proton semiconductor (Thermo Fisher Scientific). Each PI Chip allows loading of about 140 million ISP templates, generating about 100 million reads up to 10 to 15 Gbp. A Phred quality score (Q score) was used to measure the quality of sequencing. More than 90% of the sequencing reads reached Q30 (99.9% base call accuracy).

RNA sequencing alignment and analysis

All sequenced libraries were mapped to the mouse genome (UCSC mm10) using STAR RNA-seq aligner (55). The reads distribution across the genome was assessed using bamutils (from NGSUtils) (56). Uniquely mapped sequencing reads were assigned to mm10 refGene genes using featureCounts (57). Differential expression analyses were performed using edgeR v3.22.3 implemented in the Bioconductor package (58) to identify differentially expressed mRNAs between control and Dhps∆β samples. Biological coefficients of variation between the samples were estimated using an empirical Bayes approach under the assumption that the data follow a negative binomial distribution. We filtered out low-expression transcripts based on percentage of samples (less than 50%) and CPM (counts per million) cutoff of 1. Statistical significance was defined as P ≤0.05 and a fold change ≥2 of expression level between comparison of knockout mice and controls. The heatmap and locus-by-locus volcano plot were performed using R package. DAVID was used for the functional enrichment analysis (59), based on annotation files from Gene Ontology (60), to identify biological pathways that were significantly enriched.

Liquid chromatography–MS/MS

Isolated islet samples were treated with 8 M urea in 50 mM tris-HCl and sonicated for protein extraction. For each sample set, an equal amount of protein starting material was reduced and alkylated with tris(2-carboxyethyl)phosphine (TCEP) and chloroacetamide (CAM) and digested with Trypsin Gold (Promega) overnight. Samples were labeled with 0.2 mg of TMT mass tagging reagents (Proteome Sciences via Thermo Fisher Scientific). About 100 μg of the mixed sample was fractionated using the Pierce High pH Reversed-Phase Peptide Fractionation Kit (Thermo Fisher Scientific) and subject to liquid chromatography–MS/MS (LC–MS/MS) analysis.

Column chromatography was performed in line with a Fusion Lumos Orbitrap mass spectrometer with advanced precursor determination and Easy-IC using a Nanoflex Easy nanospray ion source. Data were acquired with the full MS acquisition performed at a resolution of 60,000, and MS/MS analysis was performed at a resolution of 50,000. MS/MS fragmentation was performed by higher-energy collision dissociation with a collision energy of 36.

MS/MS database search was performed with the relevant UniProt FASTA database using SEQUEST HT within Proteome Discoverer 2.2 (PD 2.2, Thermo Fisher Scientific). The reporter ion quantitation node within PD 2.2 was used for quantitation following sample normalization based on the total amount of protein detected for each reporter group. For significance analysis, P values were calculated using an analysis of variance (ANOVA) and a Tukey honestly significantly different post hoc test. Locus-by-locus volcano plot was performed using R package.

Flow cytometry

Islets were dispersed using 1 ml of Accumax (#07921, STEMCELL Technologies) containing deoxyribonuclease I (2 U/ml) and Pluronic F-127 for 15 min at 37°C. Single cells were stained with 25 μM Newport Green PDX for 90 min at 37°C. Cells were washed, resuspended in 1 ml of phosphate-buffered saline, and incubated at 37°C for 30 min. Cells were fixed with 2% paraformaldehyde for 10 min and subsequently permeabilized with Transcription Factor Staining Buffer Set (Invitrogen). Intracellular staining was carried out in perm/wash buffer containing Ki67-PE (phycoerythrin) (clone 16A8, BioLegend) and histone H3 (pS28) Alexa Fluor 647 (clone HTA28, BD Biosciences) overnight 4°C. After staining, the cells were washed, filtered, and acquired on a FACSCanto II cytometer (BD Biosciences). Data were analyzed using FlowJo software (Tree Star).

Statistical analysis

All data are presented as means ± SEM. For comparisons of two groups, a two-tailed unpaired Student’s t test was used. For comparisons of more than two groups, a one-way ANOVA was used followed by a Tukey posttest.


Fig. S1. β Cell–specific deletion of Dhps and its effect on glucose homeostasis.

Fig. S2. ODC inhibition attenuates HFD-induced β cell proliferation.

Fig. S3. DHPS inhibition attenuates harmine-induced β cell proliferation in mouse islets.

Fig. S4. DHPS inhibition decreases harmine-induced β cell proliferation in human islets.


Acknowledgments: We thank K. Orr, K. Randhave, and J. Nelson from the Indiana University Diabetes Research Center Islet and Translation Cores for technical assistance with islet isolations and PCRs. We also thank the Integrated Islet Distribution Program and the University of Alberta for provision of human islets and L. Philipson (University of Chicago) for provision of the MIP-CreERT mice. Funding: This work was supported by an American Physiological Society Porter Fellowship (to E.M.L.), a JDRF Career Development Award (to T.L.M.), a JDRF Postdoctoral Fellowship (to F.S.), and NIH grants R01 DK060581 and R01 DK105588 (to R.G.M.) and R01 DK113079, R01 DK105015, and R01 DK077096 (to A.G.-O.). This work used core services supported by NIH grant P30 DK097512 (to Indiana University), and core services supported by NIH grant P30 DK020595 (to University of Chicago) were used for the creation of the MIP-CreERT mice. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Author contributions: E.M.L., K.Y., A.R.P., Y.L., B.M., A.L.M., D.S., E.B.-M., L.C.A., A.G.-O., S.A.T., and R.G.M. designed research. E.M.L., K.Y., W.W., A.R.P., F.S., K.S.O., E.A.-B., T.L.M., A.L.M., D.S., A.G.-O., S.A.T., and R.G.M. performed research. E.M.L., K.Y., A.R.P., W.W., E.A.-B., T.L.M., Y.L., A.L.M., E.B.-M., L.C.A., D.S., A.G.-O., S.A.T., and R.G.M. analyzed data. E.M.L., S.A.T., and R.G.M. wrote the manuscript; all authors edited and approved the final draft of the manuscript. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The RNA sequencing data have been deposited to NCBI GEO with the dataset identifier GSE136581. The MS proteomics data have been deposited to ProteomeXchange with the dataset identifier PXD015414. All other data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials. The DhpsloxP/loxP mice presented in this study were generated by the authors and require a materials transfer agreement for use outside of Indiana University.

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