The Protective Effects of Cryptochlorogenic Acid on β-Cells Function in Diabetes in vivo and vitro via Inhibition of Ferroptosis

Abstract

Purpose: Mulberry leaf extract has exerted better antidiabetic activities, while the effects of major active components in mulberry leaf extract are still unclear. Cryptochlorogenic acid (CCA) as the major active component in mulberry leaf extracts was investigated herein.

Materials and methods: Rats were treated with 50mg/kg streptozotocin for the establishment of diabetic model in vivo, and cells were treated with 33.3 mM glucose for the establishment of cell model in vitro. HE staining assay was performed for observation of pancreatic pathology and aldehyde fuchsin staining assay for examining islet cell numbers. The iron content was detected via Perls staining assay with iron assay kit (ab83366). The malondialdehyde (MDA), glutathione (GSH) and oxidized glutathione (GSSG) were detected by corresponding kits. Real-time quantitative polymerase chain reaction (RT-qPCR) was performed for assessment of gene level and Western blot for measurement of protein expression level. The cell survival was detected via CCK-8 assay.

Results: The blood glucose level, iron content, accumulation of lipid peroxides and islet injury in diabetic model were all improved by CCA via a concentration-dependent manner. CCA functions via inhibition of ferroptosis by activation of cystine/glutamate transporter system (XC^-)/glutathione peroxidase 4(GPX4)/Nrf2 and inhibition of nuclear receptor coactivator 4 (NCOA4) in diabetes.

Conclusion: CCA exerted excellent antidiabetic effects via inhibition of ferroptosis, so it may be a promising agent for diabetes therapy, providing a new avenue for diabetes treatment.

Keywords: NCOA4; Nrf2; XC-/GPX4; cryptochlorogenic acid; diabetes; ferroptosis.

Figure 1

The effects of CCA on blood glucose level in vivo. The blood glucose level in the study groups before/after DM model establishment and drug treatment for one week/two weeks. ***P < 0.001 vs. control group; ^###P < 0.001 vs. model group; ^ΔP < 0.05 vs. CCA-high group.

Figure 2

The effects of CCA on pancreatic pathology and islet cell numbers in vivo. The pancreatic pathology and islet cell numbers evaluated by hematein–eosin HE staining (A) and aldehyde fuchsin staining assay (B) respectively in the different groups.

Figure 3

The effects of CCA on iron content in vivo. The iron deposit evaluated by Perls stain (A) and the iron content detected by iron assay kit (ab83366) (B) in the different groups. ***P < 0.001 vs. control group; ^##P < 0.01 vs. model group; ^ΔP < 0.05 vs. CCA-high group.

Figure 4

The effects of CCA on MDA, GSH, GSSG and GSH/GSSG level in vivo. The MDA level in the study groups (A), the levels of GSH, GSSG and GSH/GSSG in the different groups (B); the GPX4 level in the study groups (C). ***P < 0.001 vs. control group; ^#P < 0.05, ^##P < 0.01 and ^###P < 0.001 vs. model group ; ^ΔP < 0.05 ^ΔΔP < 0.01 and ^ΔΔΔP < 0.001vs. CCA-high group.

Figure 5

The effects of CCA on related proteins in ferroptosis in vivo. The levels of SLC7A11, SLC3A2, GPX4, TFR1, Nrf2 and NCOA4 evaluated by PCR in the study groups. ***P < 0.001 vs. control group; ^#P < 0.05, ^##P < 0.01 and ^###P < 0.001 vs. model group; ^ΔP < 0.05, ^ΔΔP<0.01 and ^ΔΔΔP < 0.001vs. CCA-high group.

Figure 6

The effects of CCA on related proteins in ferroptosis in vivo. The levels of SLC7A11, SLC3A2, GPX4, TFR1, Nrf2 and NCOA4 evaluated by Western blot in the study groups. ***P < 0.001 vs. control group; ^#P < 0.05, ^##P < 0.01 and ^###P < 0.001 vs. model group; ^ΔP < 0.05 and ^ΔΔΔP < 0.001vs. CCA-high group.

Figure 7

The effects of CCA on cell viability, iron content and MDA level. The cell survival (A), iron content (B) and MDA level (C) in the study groups. ***P < 0.001 vs. control group; ^#P < 0.05, ^##P < 0.01 and ^###P < 0.001 vs. model group.

Figure 8

The effects of CCA on related proteins in ferroptosis in vitro. The levels of SLC7A11, SLC3A2, GPX4, TFR1, Nrf2 and NCOA4 evaluated by Western blot in the study groups. ***P < 0.001 vs. control group; ^#P < 0.05, ^##P < 0.01 and ^###P < 0.001 vs. model group.