Introduction

Methods and Materials

Experimental Design

This study is composed of four parts:

• Pilot studies covering the histology of the pancreas, insulin measurement methods, optimization of the glucose tolerance test, and establishment of a protocol for STZ-mediated induction of diabetes in the axolotl.
• Investigation of the induction of diabetes and the potential regeneration of β cells in the axolotl by measuring changes in blood glucose levels over time.
• Histological examination of the diabetic state on day 22, 35, and 84 of the experiment.
• Characterization of systemic effects of the STZ-induced disease.

In part I, several pilot studies (PS1-5) were conducted to find the optimal dosage regime of STZ (Figure 2). Previously, I have examined a protocol inspired by a study in zebrafish[90], in which 0.35 mg/g body mass of STZ was i.p. (intraperitoneal) injected at day 0, 1, 2, 11, and 18 of the experiment. However, the pilot study resulted in high mortality and premature termination[91]. In this study, I investigate several dosage regimes inspired by rodent studies to find a treatment protocol that makes the animals diabetic without causing high mortality. Firstly, PS1 was treated with 0.05 mg/g body mass of STZ on 5 consecutive days, group PS2 received 0.05 mg/g body mass of STZ at day 0, 2, 4, 12, and 19, and PS3 was given a single dose of STZ of 0.2 mg/g body mass at day 0. Two additional pilot groups were included, in which PS4 was treated with 0.15 mg/g body mass of STZ, and PS5 was given 0.2 mg/g body mass of STZ, both at 5 consecutive days. The best protocol was decided by evaluation of blood glucose levels using fasting blood glucose levels and a glucose tolerance test.

In part II, the optimal STZ treatment protocol was applied to two groups, one receiving STZ (stz_d84) and one receiving a sham treatment (sham_d84). Stz_d84 was subjected to a glucose tolerance test at day 22 to confirm hyperglycemia caused by the treatment, and again at day 32, 42, 52, and 72 of the experiment to monitor changes in blood glucose levels over time to identify potential regeneration of β cells. Sham_d84 was subjected to the glucose tolerance test at day 22, 42, and 72.

In part III, four additional groups were included – stz_d22 and stz_d35, which received the STZ treatment, and sham_d22 and sham_d35, which received a sham treatment. The diabetic state after the STZ treatment was investigated at three distinct stages: 1. When hyperglycemia peaked (day 22), 2. When the regenerative process was assumed to initiate (day 35), and 3. When β cell function was restored (day 84) (Figure 3).

In part IV, potential whole-body effects of the STZ-induced diabetes were characterized by examination of changes in body mass, percentage of red blood cells in whole blood, plasma osmolarity, and several plasma and urine parameters.

Table 2. Data table of the animal groups used in the pilot study and the main study.

Table 2. Data table of the animal groups used in the pilot study and the main study.

Group name	Treatment type	Mean start body mass (g)	Mean end body mass (g)	Mean of start and end length (snout to tail) (cm)	# animals at the endpoint	Color*	Birth date
Pilot study groups
PS1	STZ	21.6±2.8	20.0±1.7	14.5±0.5	3	WT: 33.3% Leu: 33.3% Alb: 33.3%	10 March 2020
PS2	STZ	21.7±6.4	20.9±3.3	14.8±1.2	3	WT: 33.3% Leu: 33.3% Alb: 33.3%	10 March 2020
PS3	STZ	22.6±3.5	22.8±4.0	15.1±0.6	3	WT: 66.6% Leu: 33.3% Alb: 0%	10 March 2020
PS4	STZ	24.7±3.8	38.4±2.0	14.6±0.4	3	WT: 33.3% Leu: 66.6% Alb: 0%	10 March 2020
PS5	STZ	22.3±4.0	31.5±1.2	14.2±1.1	3	WT: 66.6% Leu: 33.3% Alb: 0%	10 March 2020
PS_control	-	20.1±3.2	-	14.4±1.0	3	WT: 33.3% Leu: 33.3% Alb: 33.3%	10 March 2020
Ins_baseline	-	40.3±9.1	-	-	3	WT: 66.6% Leu: 0% Alb: 33.3%	Mixed
Main study groups
Stz_d22	STZ	29.5±8.1	44.4±22.8	16.0±1.1	6	WT: 66.6% Leu: 33.3% Alb: 0%	Mixed
Sham_d22	Sham	30.8±7.6	32.3±7.2	15.5±0.2	4	WT: 75% Leu: 25% Alb: 0%	Mixed
Stz_d35	STZ	23.4±3.9	32.5±11.5	14.8±0.2	4	WT: 50% Leu: 25% Alb: 25%	Mixed
Sham_d35	Sham	24.5±7.7	26.9±7.3	15.7±1.4	3	WT: 33.3% Leu: 66.6% Alb: 0%	Mixed
Stz_d84	STZ	23.2±2.5	30.3±4.1	16.1±0.6**	5	WT: 0% Leu: 100% Alb: 0%	10 March 2020
Sham_d84	Sham	22.7±4.5	31.3±3.9	16.5±0.9**	6	WT: 33.3% Leu: 66.6% Alb: 0%	10 March 2020

*wt: wild type, leu: leucistic, alb: albino ** endpoint length only, as the start length of sham_d84 was not registered.

Tissue Sample Harvest

Blood was harvested either from gill arteries or directly from the heart (only at the endpoint) with firstly a heparin-coated 0.5 mL insulin syringe, followed by an EDTA (ethylenediaminetetraacetic acid)-coated syringe (Figure 4A). Whole blood was transferred to a pre-weighted Eppendorf tube and spun at 6000 rpm for 5 min, and plasma was collected and deposited in a new pre-weighed tube. The tubes were weighed, from which the percentage of red blood cells was calculated, followed by immediate snap-freezing in liquid nitrogen and storage at -80°C.

The thoracic cavity was opened using micro scissors by removing skin, muscle, and the cartilage plates protecting the heart, followed by an incision in the pericardium. The outflow tract was severed from which blood could be collected, followed by severing of other vessels (sinus venosus, among others) to free the heart (Figure 4B). The heart was moved to a petri dish with amphibian Ringer’s solution, in which it remained pulsating until most blood had exited the heart, and it was transferred to a mold and covered with OCT cryo embedding matrix (CellPath) before snap freezing in liquid nitrogen and stored in -80°C.

Next, the abdominal cavity was opened to expose the bladder. Urine was removed by carefully inserting a syringe while extending the bladder with a tweezer, and collected urine was transferred to a tube and snap-frozen.

A piece of the left liver lobe was excised and transferred to a mold and covered in OCT cryo embedding matrix followed by snap freezing (Figure 4C).

The pancreas was removed by first separating the liver lobe from the pancreas (Figure 5B), then severing the duodenum from the stomach (Figure 5C), and severing pancreas tissue from connecting tissue (Figure 5D). The pancreas was cleaned by rinsing with amphibian Ringer’s solution through the duodenal opening and by removing blood clots (Figure 5E). Next, the pancreas was severed at the midpoint, and the half attached to the duodenal part closest to the stomach was separated from the duodenum and transferred to a tube for later insulin measurements (Figure 5F). The other half was placed in OCT and snap-frozen.

The kidneys were removed by opening to the lower part of the abdominal cavity and first severing the rectum as close to the cloaca as possible, followed by separation of the kidney tissue from the abdominal wall (Figure 4D). It was transferred to an OCT-embedded mold and snap-frozen.

Lastly, the eyes were removed carefully with micro scissors, and the left eye was OCT-embedded in a mold, while the right eye was transferred to a tube and snap-frozen.

Figure 5. The dissection method of the pancreas. A) The triangular pancreas, in which dotted lines frame the organ and the striped line shows the incision from connective tissue. B) Pancreas is separated from the liver lobe. C) The duodenum is cut near the pylorus. D) Connective tissue is separated from the pancreas. E) The duodenum is rinsed with amphibian Ringer’s solution. F) The pancreas is connected to a superior duodenal (SD) part near the pylorus (P) and a descending part (DD). Striped lines indicate the incision points, in which the part connected to SD is transferred to a tube for ELISA, and the part connected to DD is transferred to a mold.

Figure 5. The dissection method of the pancreas. A) The triangular pancreas, in which dotted lines frame the organ and the striped line shows the incision from connective tissue. B) Pancreas is separated from the liver lobe. C) The duodenum is cut near the pylorus. D) Connective tissue is separated from the pancreas. E) The duodenum is rinsed with amphibian Ringer’s solution. F) The pancreas is connected to a superior duodenal (SD) part near the pylorus (P) and a descending part (DD). Striped lines indicate the incision points, in which the part connected to SD is transferred to a tube for ELISA, and the part connected to DD is transferred to a mold.

Imaging and Analysis

All stained slides were imaged using a slide scanner (Upright Widefield Fluorescence) Olympus VS120 at Health Bioimaging Core Facility, Aarhus University.

Hematoxylin-stained slides were imaged in 20x magnification, while immunofluorescence-stained slides were imaged in 40x magnification.

Insulin-positive cells and EdU-positive cells were quantified using QuPath v0.3.2 Software. The pancreas was defined as the region of interest using the QuPath toolset and by comparing it to the hematoxylin stains of neighbor sections (Figure 7A). The total number of cells was detected using the DAPI channel with the Cell Detection tool accessed by the following commands: Ctrl+L => Cell detection (Figure 7B). With small adjustments to the nucleus parameters and a threshold of 100, nuclei were detected for all cells in the region. To find a fitting threshold for all channel detections, intensity measurements of all detected cells were evaluated by the following commands: Measure => Show detection measurements.

For EdU-positive cells, FITC-stained nuclei were detected by following commands: Ctrl+L => Positive cell detection (Figure 7C). The sigma value was set to 3, the threshold to 100, and the tool was set to detect the mean FITC intensity in the nucleus.

For insulin-positive cells, FITC-stained cells were detected by first detecting DAPI-positive cells and then classifying insulin-positive cells with the following commands: Classify => Object classification => Create single measurement classifier (Figure 7D). The classifier was set to measure FITC mean intensity in the total cell with a threshold of 3000. To detect cells fitting this classification: Classify => Object classification => Load object classifier.

For both EdU-positive cells and insulin-positive cells, the percentage of positive cells compared to the total number of cells was calculated for each section. Four sections per animal were used in the analyses, and a mean percentage of positive cells was found for each animal and used for statistical analysis.

Figure 7. Analyses of immunofluorescence staining in pancreas using QuPath Software. A) Pancreas tissue is outlined using QuPath tools, and the hematoxylin-stained neighbor section is used as reference. B) The settings for cell detection using the DAPI nuclear stain. C) The settings used for detecting EdU-positive cells. D) The settings used for the detection of insulin-positive cells.

Figure 7. Analyses of immunofluorescence staining in pancreas using QuPath Software. A) Pancreas tissue is outlined using QuPath tools, and the hematoxylin-stained neighbor section is used as reference. B) The settings for cell detection using the DAPI nuclear stain. C) The settings used for detecting EdU-positive cells. D) The settings used for the detection of insulin-positive cells.

Results

Part I: Pilot Studies

Characterization of the Pancreas in the Axolotl

To examine the diabetogenic effect of STZ in the axolotl, the axolotl pancreas was characterized, as there is a limited number of studies on this topic. The pancreas of the axolotl is a triangular organ, which connects directly to the duodenum and the liver (Figure 5). In hematoxylin-stained sections of the pancreas, the exocrine and endocrine pancreas can be clearly distinguished. The endocrine cells are located in islet-like structures, as seen in other species, and have a darker, well-rounded nucleus and light cytoplasm compared to exocrine cells, in which the cytoplasm is light purple and the nucleus is not so well defined (Figure 19D). As the endocrine islet structures contain not only β cells but all endocrine cells in the pancreas, the β cells were identified by staining insulin-positive cells (Figure 19E). Insulin is accumulated in the cytoplasm but is also found in the nucleus.

As GLUT2/Glut2/glut2 is the primary glucose transporter in the pancreas of mice and zebrafish, but not humans (Table 1), a mouse anti-Glut2 antibody was tested to investigate the presence of this transporter in the β cells of the axolotl, also to attain a membrane-associated β cell marker. However, this antibody resulted in unspecific staining in liver and kidney tissue and no signal in pancreas tissue (Figure 8). Consequently, another antibody must be investigated for the detection of the glucose transporter.

Figure 8. Immunofluorescence staining of glut2 in liver tissue of control animals. The procedure led to unspecific staining in liver tissue. The nuclear stain (blue) (A) overlaps with the stain of glut2 (red) (C), as can be seen in B.

Figure 8. Immunofluorescence staining of glut2 in liver tissue of control animals. The procedure led to unspecific staining in liver tissue. The nuclear stain (blue) (A) overlaps with the stain of glut2 (red) (C), as can be seen in B.

Optimizing the Glucose Tolerance Test

The glucose tolerance test is used as a diagnostic tool in the clinic, but also in diabetes research to investigate disease in animal models. I have previously adjusted it for use in the axolotl, as the axolotl, like other amphibians[25], has a slower metabolic rate[91]. In this study, I have further optimized the protocol. Intravenous injection of 1.75 mg/g body mass results in a massive increase in blood glucose levels (approx. 22-27 mmol/L after 10 min), and approx. 60% of glucose is consumed after 14h[91]. Previously, blood glucose levels were measured 0h, 10 min, and 14h after glucose injection. Three additional time points were included: 4h 40 min, 9h 20 min, and 24h after glucose injection. These time points were included to further study the glucose consumption over the span of 24h, including the 24h measurement, as glucose is fully consumed at this point in healthy axolotls (see PS_control in Figure 9).

Furthermore, I investigated if larger blood samples could be collected during the glucose tolerance test for later analysis and to generate a blood insulin curve to examine the relationship between glucose and insulin in the axolotl. For this, a group of healthy animals (n=6) was subjected to the optimized glucose tolerance test. 60 µL of blood was collected from each animal 0h, 4h 40 min, and 9h 20 min after glucose injection and was planned to be collected 14h and 24h after glucose injection as well, but the blood collections resulted in difficulty in returning from the anesthetic state at first and, later in the test, mortality for 4/6 animals. As a consequence, the pilot study was ended prematurely.

Another pilot group (Ins_baseline) (n=3) was subjected to the glucose tolerance test, and 30-40 µL of blood was collected 0h, 14, and 24h after glucose injection. This group did not experience the complications seen in the previous pilot group, and blood glucose levels were able to return to fasting levels, as seen in a control group (PS_control), in which blood only was collected in small amounts for the glucose measurements. Even though blood glucose levels after 24h (5.4±1.8 mmol/L) were higher than fasting blood glucose levels (3.7±0.7 mmol/L) in Ins_baseline, the difference was not statistically significant (p=0.12) (Figure 9). Therefore, it is possible to collect small quantities of blood at several points during the glucose tolerance test, but not all. Also, blood must be collected carefully to not cause mortality.

Quantification of Insulin in Blood Samples and Pancreas Tissue Using ELISA

As diabetes is characterized by the destruction of the insulin-producing β cells, insulin content in the pancreas or blood is an indicator of the diabetic state of an animal model. Therefore, ELISA was investigated as a potential method to measure insulin content in both pancreas and blood of axolotls.

For this, a mouse insulin ELISA kit (Invitrogen) was evaluated, using blood samples and pancreas tissue extraction from two healthy animals – one animal fasting for one day, the other receiving a meal 4-5h before tissue harvest. As the method should be able to measure insulin levels in diabetic animals, thus with low insulin content in the blood, animals were not subjected to a glucose tolerance test before tissue harvest. The ELISA kit was not able to measure insulin concentration in diluted blood samples, and only insignificant amounts in undiluted blood samples, indicating that a kit with a lower range is necessary for measurements of insulin in axolotl blood samples.

As for the pancreas, more than a 400-fold dilution was necessary to stay within range of the kit, and the control sample measured an insulin concentration of 176.13 mlU/mL.

Thus, the ELISA kit can measure insulin content in pancreas tissue after a 400-fold dilution, but plasma insulin levels are too low in the axolotl for measurements with this assay, and another kit must be assessed for this.

Finding the Optimal STZ Treatment Protocol to INDUCE diabetes in the Axolotl

Previously, a STZ dosage of 0.35 mg/g body mass given five times over the span of 18 days resulted in severe systemic toxicity and premature termination of the experiment[91]. Thus, five new treatment strategies were evaluated (Figure 2).

Three pilot study groups (PS1-3) were included with three animals in each group. PS1 was given 0.05 mg/g body mass on five consecutive days, PS2 received 0.05 mg/g body mass on day 0, 2, 4, 12, and 19, and PS3 was given a single dose of 0.2 mg/g body mass. As for other adjustments to the previous STZ protocol, animals were fasted for one week prior to the experimental start. This makes the body mass-dependent STZ treatment more precise and effective because STZ is a glucose analogue and competes with glucose for transportation, therefore improving STZ uptake in β cells by fasting.

To assess their glycemic state, animals were subjected to the optimized glucose tolerance test. PS1 and PS3 were subjected to the glucose tolerance test 10 days after the last STZ injection (experimental day 14 and 10, respectively), and PS1, PS2, and PS3 were all subjected to the test on day 22 of the experiment. The STZ-treated groups were compared to a control group, which consisted of healthy, untreated animals (PS_control).

On day 10 after the last STZ injection, blood glucose levels were measured 0h, 10 min, and 14h after glucose injection. Blood glucose levels were not significantly higher at baseline for either PS1 or PS3 (p=0.11 and p=0.19, respectively), but PS1 displayed a significantly higher blood glucose level 14h after glucose injection (p=0.013), whereas PS3 did not differ from PS_control after 14h (p=0.12) (Figure 10A).

On day 22 of the experiment, blood glucose levels were measured at 0h, 10 min, 4h 40 min, 9h 20 min, 14h, and 24h after glucose injection (Figure 10B). PS1 and PS3 had fasting blood glucose levels of 4.9±0.2 and 4.1±0.002 mmol/L, which is significantly higher than the blood glucose levels of 2.4±0.4 mmol/L seen in PS_control (p=0.00050) and p=0.0020), respectively), while PS2 did not have significantly higher fasting blood glucose levels (p=0.23). After 4h 40 min, PS1 and PS3 displayed significantly higher blood glucose levels compared to the PS_control (p=0.034 and p=0.015, respectively), while PS2 did not have higher blood glucose levels (p=0.050). After 9h 20 min, 14h, and 24h, all pilot groups displayed significantly higher blood glucose levels compared to PS_control. After 9h 20 min, PS1 had blood glucose levels of 16.5±3.4 mmol/L (p=0.027), PS2 of 13.9±2.3 mmol/L(p=0.041), and PS3 of 14.6±1.3 mmol/L(p=0.007) compared to 9.4±1.2 mmol/L in PS_control. After 14h, blood glucose levels were 12.5±3.5 mmol/L for PS1(p=0.019), 10.3±2.7 mmol/L for PS2 (p=0.024), and 9.8±2.2 mmol/L for PS3 (p=0.017) compared to 4.7±0.5 mmol/L in PS_control. After 24h, blood glucose levels had normalized in PS_control (1.8±0.1 mmol/L), whereas all STZ-treated groups displayed hyperglycemia. PS1 had blood glucose levels of 11.3±2.2 mmol/L (p=0.0016), PS2 had 6.4±2.6 mmol/L (p=0.036), and PS3 had 6.3±0.8 mmol/L (p=0.00056).

These results indicate that all pilot groups developed a hyperglycemic response to the STZ treatment, thus displaying symptoms of diabetes. On the tenth day after the last STZ treatment, neither PS1 nor PS3 displayed the full effect of the STZ treatment. On day 22 of the experiment, PS1 and PS3 displayed the most severe hyperglycemic response of the pilot groups, as both blood glucose levels at baseline and during the glucose tolerance test were significantly higher than the blood glucose levels of PS_control, indicating that these are the most effective treatment protocols to induce diabetes.

To test if I had found the most optimal protocol in which the STZ treatment resulted in maximal hyperglycemia, but not systemic toxicity as seen previously[91], two additional pilot study groups (PS4 and PS5) were included, and each received a higher dose of STZ but followed the same schedule as used in PS1. PS4 and PS5 were treated for five consecutive days receiving 0.15 and 0.2 mg/g body mass, respectively. Animals were scheduled to be subjected to the glucose tolerance test on day 22 of the experiment, however, all animals were prematurely terminated on either day 16 or 17, as PS4 and PS5 increased their body mass by 57.2±15.1% and 44.0±19.8% since day 0. This change in body mass was not seen in the other pilot groups (Figure 11).

Therefore, the PS1 treatment protocol of 0.05 mg/g body mass of STZ at five consecutive days made the most optimal protocol, as it resulted in severe hyperglycemia in the glucose tolerance test without detrimental effects at day 22 of the experiment.

Figure 11. Changes in body mass in the pilot groups over the experimental period. Plotted data show mean group values ± SD normalized to the average body mass of all the groups at day 0 of the experiment. PS1, PS2, and PS3 did not experience any significant changes in mean body mass, but PS4 and PS5 increased their body mass by 57.2±15.1% and 44.0±19.8%, respectively, since day 0, resulting in premature euthanasia.

Figure 11. Changes in body mass in the pilot groups over the experimental period. Plotted data show mean group values ± SD normalized to the average body mass of all the groups at day 0 of the experiment. PS1, PS2, and PS3 did not experience any significant changes in mean body mass, but PS4 and PS5 increased their body mass by 57.2±15.1% and 44.0±19.8%, respectively, since day 0, resulting in premature euthanasia.

Induction of Diabetes at Day 22

At day 22, 3/9 of stz_d84 were affected by swelling, and one was excluded from the experiment prior to the glucose tolerance test due to a weight gain of 89.2% since day 0. Animals were given glucose injections normalized to their weight with the assumption that glucose is distributed in the whole body, unaffected by swelling.

Blood glucose levels were significantly higher in stz_d84 compared to sham_d84, even when excluding the swollen animals (Figure 12). Fasting blood glucose levels were significantly higher in stz_d84 compared to sham_d84 (2.5±0.7 mmol/L), both with (4.0±0.7 mmol/L) (p=0.0027) and without (4.3±0.6 mmol/L) (p=0.0013) the swollen animals. After glucose injection, blood glucose levels were significantly higher after 10 min (26.1±1.7 mmol/L) (p=0.0033), 14h (9.5±2.4 mmol/L) (p=0.012), and 24h (7.5±2.9 mmol/L) (p=0.022) in stz_d84 compared to sham_d84 (10 min: 20.8 mmol/L, 14h: 6.1±1.7 mmol/L, 24h: 3.8±2.0 mmol/L). By excluding the swollen animals, blood glucose levels were still significantly increased after 10 min (25.9±0.6 mmol/L) (p=0.0113), 14h (8.5±0.8 mmol/L) (p=0.0090), and 24h (6.1±0.9 mmol/L) (p=0.0265). These results show that the STZ treatment made the animals hyperglycemic, indicating that I was able to induce diabetes in stz_d84.

Figure 12. Blood glucose levels in the glucose tolerance test at day 22 of the experiment for stz_d84 (all), stz_d84 (without swollen/edema animals) and sham_d84. Plotted data show mean group values ± SD. An asterisk (*) indicates significant differences between a group compared to the sham_d84 determined with a Student’s T-test (*p=0.05). stz_d84 both with (red) and without (black) swollen animals have significantly higher blood glucose levels throughout the test compared to sham_d84 (grey).

Figure 12. Blood glucose levels in the glucose tolerance test at day 22 of the experiment for stz_d84 (all), stz_d84 (without swollen/edema animals) and sham_d84. Plotted data show mean group values ± SD. An asterisk (*) indicates significant differences between a group compared to the sham_d84 determined with a Student’s T-test (*p=0.05). stz_d84 both with (red) and without (black) swollen animals have significantly higher blood glucose levels throughout the test compared to sham_d84 (grey).

Figure 13. stz_d84 and sham_d84 were subjected to the glucose tolerance test throughout the experiment. Plotted data show mean group values ± SD. An octothorpe (#) indicates significant differences between the blood glucose levels of stz_d84 measured at different days determined with an ANOVA test (#p=0.05). An asterisk (*) indicates significant differences between a group compared to the sham_d84 determined with a Student’s T-test (*p=0.05). A) Blood glucose levels at day 22 (red) and 72 (black) of stz_d84 compared to sham_d84 (grey). B) Blood glucose levels at day 22 (triangle) statistically compared to day 42 (square) and 72 (circle) of sham_d84. C-E) Blood glucose values of stz_d84 (black) in the glucose tolerance test at different days compared to sham_d84 (grey) 0h (C), 14h (D), and 24h (E) after glucose injection.

Figure 13. stz_d84 and sham_d84 were subjected to the glucose tolerance test throughout the experiment. Plotted data show mean group values ± SD. An octothorpe (#) indicates significant differences between the blood glucose levels of stz_d84 measured at different days determined with an ANOVA test (#p=0.05). An asterisk (*) indicates significant differences between a group compared to the sham_d84 determined with a Student’s T-test (*p=0.05). A) Blood glucose levels at day 22 (red) and 72 (black) of stz_d84 compared to sham_d84 (grey). B) Blood glucose levels at day 22 (triangle) statistically compared to day 42 (square) and 72 (circle) of sham_d84. C-E) Blood glucose values of stz_d84 (black) in the glucose tolerance test at different days compared to sham_d84 (grey) 0h (C), 14h (D), and 24h (E) after glucose injection.

Blood Glucose Levels Normalized over the Span of 72 Days

Blood glucose levels were monitored during the experiment by subjecting stz_d84 day 22, 32, 42, 52, and 72 and sham_d84 at day 22, 42, and 72 to the glucose tolerance test. 4/9 of stz_d84 were excluded from the blood glucose analysis, as animals experienced swelling and were sacrificed over the course of the experiment.

The blood glucose levels of stz_d84 decreased over time, showing maximal hyperglycemia at day 22 and normalizing over time, nearly returning to blood glucose levels seen in sham-treated animals by day 72 of the experiment (Figure 13A). Using a one-way repeated measures ANOVA test and a pairwise paired T-test, blood glucose measured 0h, 10, 14h, and 24h after glucose injection at each day were compared. According to the ANOVA test, there was a significant difference between the fasting blood glucose levels measured at the different days for stz_d84 (p=0.025), especially between day 22 and day 32 (p=0.024), 52 (p=0.042), and 72(p=0.049) (Figure 13C). There was no significant difference between the days at the 10 min measurement (p=0.18). However, this significant change over time was also seen at the 14h glucose measurement(p=0.021) (Figure 13D). The pairwise paired T-Test showed that blood glucose levels at day 22 differed from day 42 (p=0.0079), day 52 (p=0.038), and day 72 (p=0.031). The blood glucose levels after 24h also differed significantly between the days (p=6.67×10^-5), in which blood glucose levels differed between day 22 and day 32 (p=0.021), 42 (p=0.0018), 52 (p=0.0009), and 72 (p=0.0052), and blood glucose levels measured day 32 differed from day 72 (p=0.011) (Figure 13E). At blood glucose measurements after 14h and 24h, stz_d84 also displayed variations between the subjects (p=0.020 and p=0.0050, respectively).

As for sham_d84, there was no difference between blood glucose measurements at after 14h or 24h, but there was a difference after 10 min between day 72 and day 22 (p=0.0057) and 42(p=0.043) (Figure 13B). However, the difference in blood glucose levels 10 min after glucose injection did not affect the glucose consumption rate throughout the glucose tolerance test, as blood glucose levels did not differ between the test days 14h (p=0.28) and 24h (p=0.23) after glucose injection. Thus, blood glucose levels 10 min after glucose injection does not seem to reflect true blood glucose levels, but more an unequal distribution of glucose in the body tissues at this timepoint, or other factors which makes the exact level at this timepoint insignificant.

Thus, measurements were pooled at each timepoint for sham_d84 to compare to the blood glucose levels at each test day for stz_d84. Using a Student’s T-Test, fasting blood glucose levels showed to be significantly higher at day 22 (p=9.76×10^-7), 32 (p=0.0030), 42 (p=0.00021), 52 (p=0.0044), and 72 (p=0.0027) compared to pooled sham_d84 (Figure 13C). However, fasting blood glucose levels decreased from 4.3±0.7 mmol/L to 3.1±0.4 mmol/L from day 22 to day 72 (paired T-Test: p=0.049) compared to 2.1±0.6 mmol/L in pooled sham_d84, showing a normalization of fasting blood glucose levels over time.

As for 14h and 24h after glucose injection, only blood glucose levels at day 22 were significantly higher compared to sham_d84 (Figure 13D, E). At day 22, stz_d84 had blood glucose levels of 8.4±0.8 mmol/L compared to 6.4±1.2 mmol/L seen in sham_d84 14h after glucose injection (p=0.0028), and blood glucose levels of 5.8±0.7 mmol/L compared to 3.2±1.3 mmol/L seen in sham_d84 24h after glucose injection (p=0.00037).

Thus, stz_d84 displayed maximal hyperglycemia at day 22, and blood glucose levels normalized over the span of the experiment.

Blood Ketone Levels Were High at Day 22 and Decreased over Time in stz_d84

As ketone bodies are an alternative metabolic fuel used by the body when suffering from severe diabetes, and since increased ketone bodies in the blood are seen in other amphibians after a pancreatectomy[25], the changes in blood ketone levels over the course of the experiment was measured before every glucose tolerance test on both stz_d84 and sham_d84. For stz_d84, blood ketone levels decreased over time, from blood ketone levels of 0.46±0.02 mmol/L at day 22 to 0.16±0.003 mmol/L at day 84 (Figure 14A). Using the one-way repeated measures ANOVA test and the pairwise paired T-Test, the change in blood ketone levels from day 22 to day 84 was analyzed, showing a significant change over time (p=0.0001), especially between blood ketone levels day 22 and day 42 (p=0.0093), 72 (p=0.0093), and 84 (p=0.013), and also between ketone levels at day 32 and day 72 (p=0.030) and 84 (p=0.020). However, sham_d84 also showed a significant change in blood ketone levels over the span of the experiment (p=0.030), between blood ketone levels day 84 and day 22 (p=0.011) and 42 (p=0.041), suggesting that another factor than the STZ treatment resulted in the decrease in blood ketone levels seen at day 84. However, blood ketone levels were significantly higher in stz_d84 than in sham_d84 at day 22 (p=0.042) (Figure 14B), indicating that the STZ treatment has resulted in an initial increase in ketone content in the blood.

Part III: Diabetic State at Day 22, Day 35, and Day 84

As I was able to induce hyperglycemia and, thus, diabetes-like disease in stz_d84, four additional groups were included in the study to investigate the histological changes in the pancreas. Two groups, stz_d22 and sham_d22, were treated with STZ and sham, respectively, and sacrificed on day 22, as the blood glucose measurements in stz_d84 indicated maximal hyperglycemic response at this time point. The other groups, stz_d35 and sham_d35, were also treated with STZ and sham, respectively, but sacrificed at day 35, as blood glucose levels of stz_d84 decreased in the period between day 22 and 42, suggesting a physiological response causing normalization of blood glucose levels, possibly caused by β cell regeneration.

The weight, length, and age of the animals differed both internally and externally between the groups (Table 2), but they were used nonetheless with the assumption that the STZ protocol adjusted for body mass differences.

The STZ Treatment Did not Induce Hyperglycemia in stz_d22 and stz_d35

At the day of euthanasia, all animals were subjected to a glucose tolerance test and were sacrificed 9h 20 min after glucose injection, in which blood glucose was measured 0h, 5 min, and 9h 20min after glucose injection. Neither stz_d22 nor stz_d35 differed from sham_d22 and sham_d35 when comparing blood glucose levels at all time points, whereas stz_d84 had a blood glucose of 9.6 ±1.9 mmol/L after 9h, which was lower than what was seen in sham_d84 (Figure 15C).

The STZ-treated groups were compared using the single factor ANOVA test and the pairwise T-Test, showing a significant difference in fasting blood glucose levels (p=0.0231), especially between stz_d22 and stz_d84 (p=0.012) (Figure 15A). Blood glucose levels also differed after 10 min (p=0.038), as blood glucose levels were lower for stz_d84 than stz_d22 (p=0.045) and stz_d35 (p=0.036) (Figure 15B). The blood glucose levels of the STZ-treated animals also differed significantly at the endpoint (p=0.012), especially between stz_d35 and stz_d84 (p=0.011) (Figure 15C). However, conducting the same comparison between the sham-treated groups showed a significant difference in fasting blood glucose levels (p=0.0027) (Figure 15A), but no difference was seen in blood glucose levels after 10 min or at the endpoint. This suggests that animal variations affect fasting blood glucose levels. However, as there was no significant difference between blood glucose measurements between Stz_d22 and Stz_d35 compared to sham_d22 and sham_d35, respectively, there are no indications of diabetes based on blood glucose measurements, and I was therefore not able to induce diabetes in these animals.

Figure 15. Blood glucose levels in the glucose tolerance test at the day of euthanasia. Plotted data show mean group values ± SD of the STZ-treated (black) and sham-treated (grey) groups. An octothorpe (#) indicates significant differences between the blood glucose levels of either STZ-treated or sham-treated groups determined with an ANOVA test and a pairwise T-Test (#p=0.05). An asterisk (*) indicates significant differences determined with a Student’s T-test (*p=0.05). A) Fasting blood glucose levels. There is a significant difference between both the STZ-treated and the sham-treated groups. B) Blood ketone levels 10 min after glucose injection. There is a significant difference between STZ-treated group, as stz_d84 has lower blood glucose levels than stz_d22 and stz_d35. C) Blood glucose levels 9h after glucose injection. Stz_d84 has significant lower blood glucose levels than stz_22 and stz_d35, but also sham_d84.

Figure 15. Blood glucose levels in the glucose tolerance test at the day of euthanasia. Plotted data show mean group values ± SD of the STZ-treated (black) and sham-treated (grey) groups. An octothorpe (#) indicates significant differences between the blood glucose levels of either STZ-treated or sham-treated groups determined with an ANOVA test and a pairwise T-Test (#p=0.05). An asterisk (*) indicates significant differences determined with a Student’s T-test (*p=0.05). A) Fasting blood glucose levels. There is a significant difference between both the STZ-treated and the sham-treated groups. B) Blood ketone levels 10 min after glucose injection. There is a significant difference between STZ-treated group, as stz_d84 has lower blood glucose levels than stz_d22 and stz_d35. C) Blood glucose levels 9h after glucose injection. Stz_d84 has significant lower blood glucose levels than stz_22 and stz_d35, but also sham_d84.

The STZ Treatment Did not affect BLOOD Ketone Levels in stz_d22 or stz_d35

As stz_d84 displayed higher blood ketone levels at day 22, which decreased over time, the blood ketone levels were measured in all groups at the endpoint right before the glucose injection. There was no significant difference between STZ-treated groups and sham-treated groups at day 22, 35, or 84, but stz_d84 displayed significantly lower blood ketone levels than stz_d22 and stz_d35 (p=0.021), and sham_d84 displayed significantly lower blood ketone levels than sham_d22 and sham_d35 (p=0.0033) (Figure 16). However, the measurements do not suggest that the STZ treatment affected the blood ketone levels in any ways.

The Percentage of Insulin-positive CELLS is Lower in STZ-Treated Animals at Day 84, but not at Day 22 or 35

To study the effect of STZ on the pancreatic β cells, insulin-positive cells were detected using immunofluorescence staining in the pancreas of all groups (Figure 19B, E). The β cell mass was quantified, and the percentage of insulin-positive cells was calculated.

According to a Student’s T-Test, there was no significant difference between STZ-treated and sham-treated groups at day 22 (p=0.20) or day 35 (p=0.99) (Figure 17), supporting the analysis of the blood glucose measurements showing that I was not able to induce hyperglycemia in these animals.

However, stz_d84 experienced a lower percentage of insulin-positive cells in the pancreas compared to sham_d84 (p=0.022) (Figure 17). There was 1.82±0.73% of insulin-positive cells in stz_d84 compared to 3.97±0.73% in sham_d84, suggesting that the STZ treatment resulted in a reduction of β cell mass in stz_d84, which has not been replenished at day 84. Furthermore, it indicates that this percentage of insulin-positive cells is enough to restore blood glucose levels, as the glucose tolerance test at day 84 showed normalized blood glucose levels when comparing to sham_d84 (Figure 15).

The pancreatic number of insulin-positive cells was compared between the STZ-treated groups and the sham-treated groups. There was no difference between the STZ-treated groups, but a significant difference between the sham groups (p=0.049), with a pairwise T-Test showing that sham_d84 had a significantly higher percentage of insulin-positive cells than sham_d22 (p=0.035), but this could be caused by the variations seen between the animals, such as age and body mass (Table 2).

Figure 17. Percentage of insulin-positive cells of total cells in the pancreas of stz_d22 (n=4), sham_d22 (n=3), stz_d35 (n=4), sham_d35 (n=3), stz_d84 (n=3), and sham_d84 (n=3). An octothorpe (#) indicates significant differences between either STZ-treated or sham-treated groups determined with an ANOVA test and a pairwise T-Test (#p=0.05). An asterisk (*) indicates significant differences determined with a Student’s T-test (*p=0.05). For each animal, four pancreas sections were used, the percentage of insulin-positive cells was calculated, and the mean for all sections was used as the value for the animal. Plotted data show mean group values ± SD of the STZ-treated (black) and sham-treated (grey) groups. stz_d84 had a significantly lower percentage of insulin-positive cells in the pancreas compared to sham_d84. There was no difference between the STZ-treated groups at day 22, 35, and 84, but sham_d84 had a significantly higher percentage of insulin-positive cells than sham_d35.

Figure 17. Percentage of insulin-positive cells of total cells in the pancreas of stz_d22 (n=4), sham_d22 (n=3), stz_d35 (n=4), sham_d35 (n=3), stz_d84 (n=3), and sham_d84 (n=3). An octothorpe (#) indicates significant differences between either STZ-treated or sham-treated groups determined with an ANOVA test and a pairwise T-Test (#p=0.05). An asterisk (*) indicates significant differences determined with a Student’s T-test (*p=0.05). For each animal, four pancreas sections were used, the percentage of insulin-positive cells was calculated, and the mean for all sections was used as the value for the animal. Plotted data show mean group values ± SD of the STZ-treated (black) and sham-treated (grey) groups. stz_d84 had a significantly lower percentage of insulin-positive cells in the pancreas compared to sham_d84. There was no difference between the STZ-treated groups at day 22, 35, and 84, but sham_d84 had a significantly higher percentage of insulin-positive cells than sham_d35.

Cell Proliferation is Unchanged at Day 35

To investigate if the axolotl regenerates β cells after the STZ treatment and if a proliferative response is the cause of the blood glucose normalization seen in stz_d84, the pancreas of stz_d35 and sham_d35 were stained for proliferative cells using an EdU kit to detect DNA proliferation.

There was no significant difference in the percentage of proliferating cells between stz_d35 and sham_d35 (p=0.20) (Figure 18), and proliferation was scattered in the tissue, not centered in the endocrine islets (Figure 19C).

Staining of Apoptosis Resulted in Whole-Organ Stain

To investigate if cell apoptosis was visible in the endocrine islet structures in the pancreas of STZ-treated animals, pancreas tissue was stained for DNA fragmentation in both STZ-treated animals and sham-treated animals. However, this TUNEL staining protocol resulted in staining of nearly all cells in the pancreas of all animals, indicating that the staining protocol must be optimized for the staining of axolotl pancreas before further analysis (Figure 19B, E).

Figure 19. Immunohistochemistry of pancreas. The tissue is from a STZ-treated animal, and the pancreas is halved. A) Hematoxylin-stained pancreas, showing the halved pancreatic tissue with darker islets of endocrine cells. B) Insulin- and TUNEL-stained pancreas. DAPI-stained nuclei are shown in blue, insulin in green and TUNEL in red. Insulin-positive β cells are located in islets, scattered randomly throughout the pancreas tissue. The TUNEL assay has stained nuclei of numerous cells, indicating that the assay must be optimized for axolotl pancreas to detect apoptosis, or that another marker for apoptosis must be used. C) EdU-staining (green) and DAPI-staining (blue) in the pancreas, showing that proliferating cells are scattered throughout the tissue. D) An endocrine islet in the hematoxylin-stained pancreas. E) The same islet as seen in (D) is stained for insulin (green), apoptosis (red), and nuclei (blue).

Figure 19. Immunohistochemistry of pancreas. The tissue is from a STZ-treated animal, and the pancreas is halved. A) Hematoxylin-stained pancreas, showing the halved pancreatic tissue with darker islets of endocrine cells. B) Insulin- and TUNEL-stained pancreas. DAPI-stained nuclei are shown in blue, insulin in green and TUNEL in red. Insulin-positive β cells are located in islets, scattered randomly throughout the pancreas tissue. The TUNEL assay has stained nuclei of numerous cells, indicating that the assay must be optimized for axolotl pancreas to detect apoptosis, or that another marker for apoptosis must be used. C) EdU-staining (green) and DAPI-staining (blue) in the pancreas, showing that proliferating cells are scattered throughout the tissue. D) An endocrine islet in the hematoxylin-stained pancreas. E) The same islet as seen in (D) is stained for insulin (green), apoptosis (red), and nuclei (blue).

Part IV: Systemic Effects of the STZ Treatment

Even though STZ is known to selectively target β cells, STZ has been seen to cause nonspecific toxicity[63], and the STZ treatment resulted in swelling and abnormal weight gain in both pilot groups (Figure 11) and the main study groups (Appendix B. – Body mass of experimental animals). Also, systemic effects have previously been seen in the STZ-treated axolotl, such as bleedings in the skin, liver, and kidney, including accumulation of fluid in the pericardium and the abdomen[91]. However, systemic effects can also be a result of hyperglycemia, as diabetes is also known to affect other organs, such as the kidneys and liver. Therefore, systemic effects can both be a non-specific effect of STZ, but also a result of diabetes, and these systemic effects was investigated by measuring blood and urine parameters.

The STZ Treatment Resulted in Massive Weight Gain Caused by Edema in Some Animals, but not All

10/19 animals in the STZ-treated groups responded to the STZ treatment by a gain of body mass. This was seen in 4/6 of stz_d22, 2/4 of stz_d35, and 4/9 of stz_d84 (Appendix B. – Body mass of experimental animals).

In stz_d22, two animals had increased their weight by 20.3±0.4%, and two animals had increased their weight by 111.1±56.3% over the period of 22 days (day 0 to 22). Two animals in stz_d35 had increased their weight by 65.5±13.8% over the period of 35 days (day 0 to 35). In stz_d84, three animals increased their weight by 70.5±24.7% over the period of 22 days (day 0 to 22), and one animal increased its weight by 43.9% over the period of 49 days (day 0 to 49) (Figure 20). These animals in stz_d84 were therefore euthanized and excluded from the rest of the experiment. These changes in body mass were observed to happen suddenly and over a short period. The other animals only experienced slight changes in body mass and were thus unaffected by this effect of STZ. Interestingly, this change in body mass was primarily seen early in the experiment (around day 20), but one animal in stz_d84 suffered from edema after 43 days (Figure 20B).

Of all swollen animals, 8/10 were of wild type, whereas two were leucistic, indicating that the color of the animal could influence the effect of STZ on body mass.

By autopsy, it was discovered that this massive change in body mass was a result of edema (Figure 20A), as fluid was found in the pericardium, skin, and abdomen, among other locations. The assembling of fluid in pericardium was so extensive in some animals that it slowed the heart rate. Furthermore, animals affected by edema had punctured, emptied bladders.

Figure 20. Macroscopic changes in some STZ-treated animals. A) Two pictures that show an axolotl suffering from edema after STZ treatment, seen from two different angles. B) Body masses of the individual animals in stz_d84 normalized to the average body mass of the group at day 0 of the experiment. Some animals steadily increase their mass over time, whereas some (stz_d84 a, d, e, and g) suddenly increase their body mass by 40-100%, resulting in euthanasia.

Figure 20. Macroscopic changes in some STZ-treated animals. A) Two pictures that show an axolotl suffering from edema after STZ treatment, seen from two different angles. B) Body masses of the individual animals in stz_d84 normalized to the average body mass of the group at day 0 of the experiment. Some animals steadily increase their mass over time, whereas some (stz_d84 a, d, e, and g) suddenly increase their body mass by 40-100%, resulting in euthanasia.

The Osmolarity and Red Blood Cell Fraction Were Abnormal in the Blood of the Swollen Animals

Hyperosmolarity is seen in diabetic patients and STZ-treated animal models[92]. To investigate if the STZ treatment influenced the concentration of osmolytes in the animals which suffered from edema, plasma osmolarity was measured. Mean plasma osmolarity was 131±6.8 mOsmol/L for PS4 and PS5 (n=5), which is lower than the osmolarity of healthy animals (p=4.17×10^-8), which our group previously has measured as 208±8 mOsmol/L (n=6) (Figure 21C).

Furthermore, the fraction of red blood cells in whole blood was examined, as the swollen STZ-treated animals were observed to have thin blood. There was no difference in the fraction of red blood cells between the stz_d22 and sham_d22, stz_d35 and sham_d35, and stz_d84 and sham_d84 (Figure 21A). Thus, the swollen STZ-treated animals of stz_d22, stz_d35, and stz_d84 (n=7) were grouped for the analysis and their fraction of red blood cells was compared to all sham-treated animals (n=13), showing that swollen STZ-treated animals have a significantly lower fraction of red blood cells in whole blood (p=0.011) (Figure 21B).

Consequently, the STZ treatment does not result in changes in the blood composition of red blood cells, but animals suffering from edema are affected by hypoosmolarity and lowered fraction of red blood cells in the blood.

Blood Creatinine, Albumin, and Alkaline Phosphatase Activity Were not Altered in STZ-Treated Animals, but Animals Affected by Edema Had Lowered Alkaline Phosphatase Activity in the Blood

STZ has been reported to cause hepatic and renal failure[64,66,67], and these organs can also be affected by hyperglycemia in diabetic patients[66,67,93]. To address this, albumin concentration, creatinine concentration, and alkaline phosphatase activity were measured in plasma to study liver and kidney function. Plasma was analyzed from the same 3-4 animals from each group. No statistically significant differences were detected by comparing STZ-treated animals with sham-treated animals at each day, and there was no significant change between STZ-treated groups or sham-treated groups (Figure 22A, C, E). However, by pooling animals affected by edema from stz_d22 and stz_d35 and comparing their plasma values with a pooled sham-treated group, it showed that animals affected by edema had a significantly lower alkaline phosphatase activity (p=0.0024) (Figure 22D).

Urine Glucose Levels Were Significantly Higher in stz_d84

In diabetic patients, the body regulates hyperglycemia by excreting glucose in the urine when the glucose amount surpasses the amount which can be reabsorbed by the proximal tubules in the kidneys, resulting in glycosuria[94]. Changes in urine glucose levels can therefore be used to identify diabetes. Therefore, glucose amount was measured in urine, first using the handheld device used for blood glucose measurements, and secondly by performing a glucose assay. Unfortunately, the sample size was small in the STZ-treated groups day 22 and 35, as edema resulted in puncture of the bladder, and I was therefore not able to collect urine from those animals.

Using the handheld device, urine glucose levels measured 20.8±0.6 mmol/L in stz_d22 (n=3) and 11.45±1.3 mmol/L in sham_d22, which is significantly higher in STZ-treated animals (p=0.0016) (Figure 23A). There was no significant difference between stz_d35 (n=2) (17.7±13.2 mmol/L) and sham_d35 (n=2) (8.5±7.4 mmol/L), but glucose measurements also displayed great variance between the subjects. Urine glucose levels of stz_d84 were not measured using the handheld device, but sham_d84 (n=6) had urine glucose levels of 6.7±1.0 mmol/L.

Using the glucose assay, urine glucose levels measured 3.5±0.4 mmol/L in stz_d22 (n=4), 3.8±0.4 mmol/L in sham_d22 (n=2), 3.5±0.3 mmol/L in stz_d35 (n=2), and 3.3±1.4 mmol/L in sham_d35 (n=3), but there was no significant difference between STZ-treated and sham-treated animals (Figure 23B). However, the urine glucose levels were significantly higher in stz_d84 (n=5) with levels of 3.9±0.4 mmol/L compared to 2.7±0.5 mmol/L in sham_d84 (n=6) (p=0.0021), suggesting that stz_d84 have a higher glucose excretion through urine. However, this could also suggest that the kidney function is inhibited by STZ treatment, even though the blood measurements did not indicate kidney dysfunction. Furthermore, the measurements using the glucose assay indicate that the handheld device cannot be used for urine sample measurements, as the glucose assay is a more reliable and thoroughly tested method.

Figure 23. Glucose levels in the urine of STZ-treated and sham-treated groups measured with the handheld device (A) and a glucose assay (B). Plotted data show mean group values ± SD. An asterisk (*) indicates significant differences determined with a Student’s T-test (*p=0.05). The handheld device is normally used to measure blood glucose, but it was assessed if this easily used tool could measure urine glucose. However, it overestimated the values massively and measured differences between stz_d22 and sham_d22, even though the glucose assay did not detect any differences at day 22. Instead, the glucose assay showed a significant difference between stz_d84 and sham_d84, in which urine glucose was higher in the STZ-treated animals.

Figure 23. Glucose levels in the urine of STZ-treated and sham-treated groups measured with the handheld device (A) and a glucose assay (B). Plotted data show mean group values ± SD. An asterisk (*) indicates significant differences determined with a Student’s T-test (*p=0.05). The handheld device is normally used to measure blood glucose, but it was assessed if this easily used tool could measure urine glucose. However, it overestimated the values massively and measured differences between stz_d22 and sham_d22, even though the glucose assay did not detect any differences at day 22. Instead, the glucose assay showed a significant difference between stz_d84 and sham_d84, in which urine glucose was higher in the STZ-treated animals.

Urine Protein Levels Were Unaltered in STZ-Treated Animals

As mentioned previously, diabetic nephropathy is a common complication of diabetes and is characterized by proteinuria[39]. To investigate this, urine protein levels were measured in stz_d22 (n=3), sham_d22 (n=2), stz_d35 (n=2), sham_d35 (m=2), stz_d84 (n=5), and sham_d84 (n=6). There was no significant difference between urine protein levels between STZ-treated animals at day 22 (p=0.10), day 35 (p=0.35), or day 84 (p=0.64), but a comparison of the STZ-treated groups showed a significant difference between protein levels at day 22 compared to day 35 and 84 (p=0.012) (Figure 24). Therefore, there is a tendency that the STZ treatment increases urine protein levels at the start of the treatment, which decreases over time, but there is no significant difference between STZ-treated and sham-treated animals.

Discussion

Conclusions

Abbreviations

References

1. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2018. Diabetes Care 2018, 41 (Supplement_1), S13–S27. [CrossRef]
2. Holt, R.I.G.; et al. Textbook of diabetes. 2017.
3. IDF Diabetes Atlas. 2021; Available from: https://diabetesatlas.org/atlas/tenth-edition/?dlmodal=active&dlsrc=https%3A%2F%2Fdiabetesatlas.org%2Fidfawp%2Fresource-files%2F2021%2F07%2FIDF_Atlas_10th_Edition_2021.pdf.
4. Harjutsalo, V.; Sjöberg, L.; Tuomilehto, J. Time trends in the incidence of type 1 diabetes in Finnish children: a cohort study. Lancet 2008, 371, 1777–1782. [Google Scholar] [CrossRef]
5. Taplin, C.E.; et al. The rising incidence of childhood type 1 diabetes in New South Wales, 1990–2002. Medical Journal of Australia 2005, 183, 243–246. [Google Scholar] [CrossRef]
6. Diabetes i tal. 2020; Available from: https://videncenterfordiabetes.dk/viden-om-diabetes/generelt-om-diabetes/diabetes-i-tal.
7. Akil, A.A.-S.; et al. Diagnosis and treatment of type 1 diabetes at the dawn of the personalized medicine era. Journal of Translational Medicine 2021, 19, 137. [Google Scholar] [CrossRef]
8. Zhou, Q.; Melton, D.A. Pancreas regeneration. Nature 2018, 557, 351–358. [Google Scholar] [CrossRef] [PubMed]
9. Vertex Provides Updates on Phase 1/2 Clinical Trial of VX-880 for the Treatment of Type 1 Diabetes. 2022, Vertex.
10. Vertex Announces Positive Day 90 Data for the First Patient in the Phase 1/2 Clinical Trial Dosed With VX-880, a Novel Investigational Stem Cell-Derived Therapy for the Treatment of Type 1 Diabetes. 2021, Vertex.
11. CRISPR Therapeutics and ViaCyte, Inc. Announce First Patient Dosed in Phase 1 Clinical Trial of Novel Gene-Edited Cell Replacement Therapy for Treatment of Type 1 Diabetes (T1D). 2022, ViaCyte.
12. Butler, P.C.; Gale, E.A.M. Reversing type 1 diabetes with stem cell–derived islets: a step closer to the dream? Journal of Clinical Investigation 2022, 132. [Google Scholar] [CrossRef] [PubMed]
13. Petersen, M.C.; Shulman, G.I. Mechanisms of Insulin Action and Insulin Resistance. Physiological Reviews 2018, 98, 2133–2223. [Google Scholar] [CrossRef] [PubMed]
14. Sylow, L.; et al. The many actions of insulin in skeletal muscle, the paramount tissue determining glycemia. Cell Metabolism 2021, 33, 758–780. [Google Scholar] [CrossRef] [PubMed]
15. Shanta, D.; Peter, M. Insulin signalling in islets. Biochemical Society Transactions 2008, 36, 290–293. [Google Scholar]
16. Leibiger, B.; et al. Selective Insulin Signaling through A and B Insulin Receptors Regulates Transcription of Insulin and Glucokinase Genes in Pancreatic β Cells. Molecular Cell 2001, 7, 559–570. [Google Scholar] [CrossRef] [PubMed]
17. Slack, J.M. Developmental biology of the pancreas. Development 1995, 121, 1569–1580. [Google Scholar] [CrossRef]
18. Jennings, R.E.; et al. Human pancreas development. Development 2015, 142, 3126–3137. [Google Scholar] [CrossRef]
19. Rukstalis, J.M.; Habener, J.F. Neurogenin3: A master regulator of pancreatic islet differentiation and regeneration. Islets 2009, 1, 177–184. [Google Scholar] [CrossRef]
20. Matsuda, H. Zebrafish as a model for studying functional pancreatic β cells development and regeneration. Development, Growth & Differentiation 2018, 60, 393–399. [Google Scholar]
21. Collombat, P.; et al. Opposing actions of Arx and Pax4 in endocrine pancreas development. Genes & Development 2003, 17, 2591–2603. [Google Scholar] [CrossRef] [PubMed]
22. Collombat, P.; et al. The Ectopic Expression of Pax4 in the Mouse Pancreas Converts Progenitor Cells into α and Subsequently β Cells. Cell 2009, 138, 449–462. [Google Scholar] [CrossRef]
23. Collombat, P.; et al. The simultaneous loss of Arx and Pax4 genes promotes a somatostatin-producing cell fate specification at the expense of the α-and β-cell lineages in the mouse endocrine pancreas. Development 2005, 132, 2969–2980. [Google Scholar] [CrossRef]
24. Pearl, E.J.; et al. Xenopus pancreas development. Developmental Dynamics 2009, 238, 1271–1286. [Google Scholar] [CrossRef] [PubMed]
25. Penhos, J.C.; Ramey, E. Studies on the Endocrine Pancreas of Amphibians and Reptiles. American Zoologist 1973, 13, 667–698. [Google Scholar] [CrossRef]
26. Brenes-Soto, A.; Dierenfeld, E.S.; Janssens, G.P.J. The interplay between voluntary food intake, dietary carbohydrate-lipid ratio and nutrient metabolism in an amphibian, (Xenopus laevis). PLOS ONE 2018, 13, e0208445. [Google Scholar] [CrossRef]
27. Verbrugghe, A.; et al. The glucose and insulin response to isoenergetic reduction of dietary energy sources in a true carnivore: the domestic cat (Felis catus). British Journal of Nutrition 2010, 104, 214–221. [Google Scholar] [CrossRef]
28. Yang, B.; Covington, B.A.; Chen, W. In vivo generation and regeneration of β cells in zebrafish. Cell regeneration (London, England) 2020, 9, 9–9. [Google Scholar] [CrossRef]
29. Chen, C.; et al. Human beta cell mass and function in diabetes: Recent advances in knowledge and technologies to understand disease pathogenesis. Molecular Metabolism 2017, 6, 943–957. [Google Scholar] [CrossRef]
30. Klinke, D.J. Extent of Beta Cell Destruction Is Important but Insufficient to Predict the Onset of Type 1 Diabetes Mellitus. PLoS ONE 2008, 3, e1374. [Google Scholar] [CrossRef]
31. Sreenan, S.; et al. Increased beta-cell proliferation and reduced mass before diabetes onset in the nonobese diabetic mouse. Diabetes 1999, 48, 989–996. [Google Scholar] [CrossRef]
32. Song, I.; et al. Beta Cell Mass Restoration in Alloxan-Diabetic Mice Treated with EGF and Gastrin. PLOS ONE 2015, 10, e0140148. [Google Scholar] [CrossRef]
33. Rahier, J.; et al. Pancreatic β-cell mass in European subjects with type 2 diabetes. Diabetes, Obesity and Metabolism 2008, 10, 32–42. [Google Scholar] [CrossRef] [PubMed]
34. Saisho, Y.; et al. β-Cell Mass and Turnover in Humans. Diabetes Care 2013, 36, 111–117. [Google Scholar] [CrossRef] [PubMed]
35. Mezza, T.; et al. Insulin resistance alters islet morphology in nondiabetic humans. Diabetes 2014, 63, 994–1007. [Google Scholar] [CrossRef] [PubMed]
36. Camastra, S.; et al. Cell Function in Morbidly Obese Subjects During Free Living: Long-Term Effects of Weight Loss. Diabetes 2005, 54, 2382–2389. [Google Scholar] [CrossRef] [PubMed]
37. Dhatariya, K.K.; et al. Diabetic ketoacidosis. Nature Reviews Disease Primers 2020, 6. [Google Scholar] [CrossRef] [PubMed]
38. Frank, R.N. Diabetic Retinopathy. New England Journal of Medicine 2004, 350, 48–58. [Google Scholar] [CrossRef] [PubMed]
39. Forbes, J.M.; Cooper, M.E. Mechanisms of Diabetic Complications. Physiological Reviews 2013, 93, 137–188. [Google Scholar] [CrossRef] [PubMed]
40. Haffner, S.M.; et al. Mortality from Coronary Heart Disease in Subjects with Type 2 Diabetes and in Nondiabetic Subjects with and without Prior Myocardial Infarction. New England Journal of Medicine 1998, 339, 229–234. [Google Scholar] [CrossRef] [PubMed]
41. Bonner-Weir, S.; et al. Compensatory Growth of Pancreatic β-Cells in Adult Rats After Short-Term Glucose Infusion. Diabetes 1989, 38, 49–53. [Google Scholar] [CrossRef]
42. Montanya, E.; et al. Linear correlation between beta-cell mass and body weight throughout the lifespan in Lewis rats: role of beta-cell hyperplasia and hypertrophy. Diabetes 2000, 49, 1341–1346. [Google Scholar] [CrossRef]
43. Parsons; J. A.; Brelje, T.C.; Sorenson, R.L. Adaptation of islets of Langerhans to pregnancy: increased islet cell proliferation and insulin secretion correlates with the onset of placental lactogen secretion. Endocrinology 1992, 130, 1459–1466. [Google Scholar] [CrossRef]
44. Dor, Y.; et al. Adult pancreatic β-cells are formed by self-duplication rather than stem-cell differentiation. Nature 2004, 429, 41–46. [Google Scholar] [CrossRef]
45. Moro, E.; et al. Analysis of beta cell proliferation dynamics in zebrafish. Developmental Biology 2009, 332, 299–308. [Google Scholar] [CrossRef] [PubMed]
46. Bonner-Weir, S.; Sharma, A. Pancreatic stem cells. The Journal of Pathology 2002, 197, 519–526. [Google Scholar] [CrossRef] [PubMed]
47. Aguayo-Mazzucato, C.; Bonner-Weir, S. Pancreatic β Cell Regeneration as a Possible Therapy for Diabetes. Cell Metabolism 2018, 27, 57–67. [Google Scholar] [CrossRef]
48. Xu, X.; et al. β Cells Can Be Generated from Endogenous Progenitors in Injured Adult Mouse Pancreas. Cell 2008, 132, 197–207. [Google Scholar] [CrossRef]
49. Zhang, M.; et al. Growth factors and medium hyperglycemia induce Sox9+ ductal cell differentiation into β cells in mice with reversal of diabetes. Proceedings of the National Academy of Sciences 2016, 113, 650–655. [Google Scholar] [CrossRef] [PubMed]
50. Kopp, J.L.; et al. Sox9+ ductal cells are multipotent progenitors throughout development but do not produce new endocrine cells in the normal or injured adult pancreas. Development 2011, 138, 653–665. [Google Scholar] [CrossRef] [PubMed]
51. Solar, M.; et al. Pancreatic Exocrine Duct Cells Give Rise to Insulin-Producing β Cells during Embryogenesis but Not after Birth. Developmental Cell 2009, 17, 849–860. [Google Scholar] [CrossRef] [PubMed]
52. Kopinke, D. and L.C. Murtaugh, Exocrine-to-endocrine differentiation is detectable only prior to birth in the uninjured mouse pancreas. BMC Developmental Biology 2010, 10, 38. [Google Scholar] [CrossRef] [PubMed]
53. Desai, B.M.; et al. Preexisting pancreatic acinar cells contribute to acinar cell, but not islet β cell, regeneration. Journal of Clinical Investigation 2007, 117, 971–977. [Google Scholar] [CrossRef] [PubMed]
54. Delaspre, F.; et al. Centroacinar Cells Are Progenitors That Contribute to Endocrine Pancreas Regeneration. Diabetes 2015, 64, 3499–3509. [Google Scholar] [CrossRef] [PubMed]
55. Xiao, X.; et al. Endogenous Reprogramming of Alpha Cells into Beta Cells, Induced by Viral Gene Therapy, Reverses Autoimmune Diabetes. Cell Stem Cell 2018, 22, 78–90.e4. [Google Scholar] [CrossRef]
56. Thorel, F.; et al. Conversion of adult pancreatic α-cells to β-cells after extreme β-cell loss. Nature 2010, 464, 1149–1154. [Google Scholar] [CrossRef]
57. Chera, S.; et al. Diabetes recovery by age-dependent conversion of pancreatic δ-cells into insulin producers. Nature 2014, 514, 503–507. [Google Scholar] [CrossRef]
58. Ye, L.; et al. glucagon is essential for alpha cell transdifferentiation and beta cell neogenesis. Development 2015, 142, 1407–1417. [Google Scholar] [CrossRef] [PubMed]
59. Lu, J. Transdifferentiation of pancreatic α-cells into insulin-secreting cells: From experimental models to underlying mechanisms. World Journal of Diabetes 2014, 5, 847. [Google Scholar] [CrossRef] [PubMed]
60. Yang, Y.-P.; et al. Context-specific α-to-β-cell reprogramming by forced Pdx1 expression. Genes & Development 2011, 25, 1680–1685. [Google Scholar] [CrossRef] [PubMed]
61. Wilcox, C.L.; et al. Pancreatic α-Cell Specific Deletion of Mouse Arx Leads to α-Cell Identity Loss. PLoS ONE 2013, 8, e66214. [Google Scholar] [CrossRef] [PubMed]
62. King, A.J. The use of animal models in diabetes research. British Journal of Pharmacology 2012, 166, 877–894. [Google Scholar] [CrossRef]
63. Goyal, S.N.; et al. Challenges and issues with streptozotocin-induced diabetes – A clinically relevant animal model to understand the diabetes pathogenesis and evaluate therapeutics. Chemico-Biological Interactions 2016, 244, 49–63. [Google Scholar] [CrossRef]
64. Kume, E.; et al. Hepatic changes in the acute phase of streptozotocin (SZ)-induced diabetes in mice. Experimental and Toxicologic Pathology 2004, 55, 467–480. [Google Scholar] [CrossRef] [PubMed]
65. Laguens, R.; et al. Streptozotocin-Induced Liver Damage in Mice. Hormone and Metabolic Research 1980, 12, 197–201. [Google Scholar] [CrossRef]
66. Tay, Y.-C.; et al. Can murine diabetic nephropathy be separated from superimposed acute renal failure? Kidney International 2005, 68, 391–398. [Google Scholar] [CrossRef]
67. Palm, F.; et al. Differentiating between effects of streptozotocinper seand subsequent hyperglycemia on renal function and metabolism in the streptozotocin-diabetic rat model. Diabetes/Metabolism Research and Reviews 2004, 20, 452–459. [Google Scholar] [CrossRef]
68. Wold, L.E.; Ren, J. Streptozotocin directly impairs cardiac contractile function in isolated ventricular myocytes via a p38 map kinase-dependent oxidative stress mechanism. Biochemical and Biophysical Research Communications 2004, 318, 1066–1071. [Google Scholar] [CrossRef]
69. Muller, Y.D.; et al. Immunosuppressive Effects of Streptozotocin-Induced Diabetes Result in Absolute Lymphopenia and a Relative Increase of T Regulatory Cells. Diabetes 2011, 60, 2331–2340. [Google Scholar] [CrossRef] [PubMed]
70. Bonner-Weir, S.; Trent, D.F.; Weir, G.C. Partial pancreatectomy in the rat and subsequent defect in glucose-induced insulin release. Journal of Clinical Investigation 1983, 71, 1544–1553. [Google Scholar] [CrossRef]
71. Watanabe, H.; et al. Aging is associated with decreased pancreatic acinar cell regeneration and phosphatidylinositol 3-kinase/Akt activation. Gastroenterology 2005, 128, 1391–1404. [Google Scholar] [CrossRef]
72. Rankin, M.M.; Kushner, J.A. Adaptive Beta-Cell Proliferation Is Severely Restricted With Advanced Age. Diabetes 2009, 58, 1365–1372. [Google Scholar] [CrossRef] [PubMed]
73. Moss, J.B.; et al. Regeneration of the Pancreas in Adult Zebrafish. Diabetes 2009, 58, 1844–1851. [Google Scholar] [CrossRef]
74. Pisharath, H.; et al. Targeted ablation of beta cells in the embryonic zebrafish pancreas using E. coli nitroreductase. Mechanisms of Development 2007, 124, 218–229. [Google Scholar] [CrossRef]
75. Singleman, C.; Holtzman, N.G. Growth and Maturation in the Zebrafish, Danio Rerio: A Staging Tool for Teaching and Research. Zebrafish 2014, 11, 396–406. [Google Scholar] [CrossRef] [PubMed]
76. Benchoula, K.; et al. Optimization of Hyperglycemic Induction in Zebrafish and Evaluation of Its Blood Glucose Level and Metabolite Fingerprint Treated with Psychotria malayana Jack Leaf Extract. Molecules 2019, 24, 1506. [Google Scholar] [CrossRef]
77. Schloissnig, S.; et al. The giant axolotl genome uncovers the evolution, scaling, and transcriptional control of complex gene loci. Proceedings of the National Academy of Sciences 2021, 118, e2017176118. [Google Scholar] [CrossRef]
78. McCusker, C.; Gardiner, D.M. The Axolotl Model for Regeneration and Aging Research: A Mini-Review. Gerontology 2011, 57, 565–571. [Google Scholar] [CrossRef] [PubMed]
79. McCusker, C.; Bryant, S.V.; Gardiner, D.M. The axolotl limb blastema: cellular and molecular mechanisms driving blastema formation and limb regeneration in tetrapods. Regeneration 2015, 2, 54–71. [Google Scholar] [CrossRef]
80. Gardiner, D.M. Regenerative engineering and developmental biology : principles and applications. CRC Press Series In Regenerative Engineering. 2018, Boca Raton, Florida ;: CRC Press.
81. Thygesen, M.; et al. A clinically relevant blunt spinal cord injury model in the regeneration competent axolotl (Ambystoma mexicanum) tail. Experimental and Therapeutic Medicine 2019, 17, 2322–2328. [Google Scholar] [CrossRef]
82. Dittrich, A.; Lauridsen, H. Cryo-injury Induced Heart Regeneration in the Axolotl and Echocardiography and Unbiased Quantitative Histology to Evaluate Regenerative Progression. Journal of Visualized Experiments 2021, 171, e61966. [Google Scholar] [CrossRef]
83. Jensen, T.B.; et al. Lung injury in axolotl salamanders induces an organ-wide proliferation response. Dev Dyn 2021, 250, 866–879. [Google Scholar] [CrossRef]
84. Nowoshilow, S.; Tanaka, E.M. Introducing www.axolotl-omics.org – an integrated -omics data portal for the axolotl research community. Experimental Cell Research 2020, 394, 112143. [Google Scholar] [CrossRef]
85. Whited, J.L.; Lehoczky, J.A.; Tabin, C.J. Inducible genetic system for the axolotl. Proceedings of the National Academy of Sciences 2012, 109, 13662–13667. [Google Scholar] [CrossRef]
86. Tilley, L.; et al. The use of transgenics in the laboratory axolotl. Developmental Dynamics 2021, 251, 942–956. [Google Scholar] [CrossRef]
87. Sobkow, L.; et al. A germline GFP transgenic axolotl and its use to track cell fate: dual origin of the fin mesenchyme during development and the fate of blood cells during regeneration. Dev Biol 2006, 290, 386–397. [Google Scholar] [CrossRef]
88. Denis, J.-F.; et al. Axolotl as a Model to Study Scarless Wound Healing in Vertebrates: Role of the Transforming Growth Factor Beta Signaling Pathway. Advances in Wound Care 2013, 2, 250–260. [Google Scholar] [CrossRef]
89. Monaghan, J.R.; et al. Experimentally induced metamorphosis in axolotls reduces regenerative rate and fidelity. Regeneration 2014, 1, 2–14. [Google Scholar] [CrossRef] [PubMed]
90. Intine, R.V.; Olsen, A.S.; Sarras, M.P. A Zebrafish Model of Diabetes Mellitus and Metabolic Memory. Journal of Visualized Experiments 2013, 72, e50232. [Google Scholar] [CrossRef]
91. Sørensen, P.L. Effect of streptozotocin in the axolotl (Ambystoma mexicanum): A pilot study. 2021.
92. Serino, R.; et al. Upregulation of hypothalamic nitric oxide synthase gene expression in streptozotocin-induced diabetic rats. Diabetologia 1998, 41, 640–648. [Google Scholar] [CrossRef]
93. Mertens, J.; et al. Hepatopathy Associated With Type 1 Diabetes: Distinguishing Non-alcoholic Fatty Liver Disease From Glycogenic Hepatopathy. Frontiers in Pharmacology 2021, 12, 768576. [Google Scholar] [CrossRef] [PubMed]
94. Monobe, K.; et al. Clinical and genetic determinants of urinary glucose excretion in patients with diabetes mellitus. Journal of Diabetes Investigation 2021, 12, 728–737. [Google Scholar] [CrossRef]
95. Allmdal, T. Diabetisk ketoacidose. 2021 [cited 2021 07/06]; Available from: https://www.sundhed.dk/borger/patienthaandbogen/hormoner-og-stofskifte/sygdomme/diabetes-type-1-hvad-er-det/diabetisk-ketoacidose/.
96. Sharma, U.; Pal, D.; Prasad, R. Alkaline Phosphatase: An Overview. Indian Journal of Clinical Biochemistry 2014, 29, 269–278. [Google Scholar] [CrossRef]
97. Hillyard, S.; et al. Osmotic and Ion Regulation in Amphibians. 2008, p. 367-441.
98. Howland, R.B. Experiments on the effect of removal of the pronephros of Amblystoma punctatum. Journal of Experimental Zoology 1921, 32, 355–396. [Google Scholar] [CrossRef]
99. Toews, D.P.; Wentzell, L.A. The Role of the Lymphatic System for Water Balance and Acid-Base Regulation in the Amphibia. 1995, Springer Berlin Heidelberg. p. 201-214.
100. Sullivan, M.A.; Forbes, J.M. Glucose and glycogen in the diabetic kidney: Heroes or villains? EBioMedicine 2019, 47, 590–597. [Google Scholar] [CrossRef]
101. Olsen, A.S.; Sarras, M.P.; Intine, R.V. Limb regeneration is impaired in an adult zebrafish model of diabetes mellitus. Wound Repair and Regeneration 2010, 18, 532–542. [Google Scholar] [CrossRef]