NiaoDuQing granules relieve chronic kidney disease symptoms by decreasing renal fibrosis and anemia

Figures

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  Figure 1. Combined systems pharmacology and experimental approach A combined approach applying systems pharmacology and in vivo experiments was developed to identify the active compounds and therapeutic mechanisms of NiaoDuQing (NDQ) granules for the treatment of chronic kidney disease (CKD). The dark blue arrow is the primary line.

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  Figure 2. Analysis of the active compounds of NDQ and preliminary GO analysis of putative NDQ targets A. Active compounds in NDQ were preliminarily screened for four ADME/Tox parameters. In total, 152 active compounds met the screening criteria. B. ADME parameter distribution for different herbs. C. GO analysis for Biological processes, Cell component, and Molecular Function terms was performed on putative NDQ targets; the top 10 terms with P < 0.05 are shown; Those at the top are the most significant ones.

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  Figure 3. Compound-target network The compound-target network was constructed by linking active compounds (compounds ID) from the different herbs and their potential targets. The nodes represent active compounds (different triangle colors represent different herbs) and targets (green dots). RRR: Radix et Rhizoma Rhei; RA: Radix Astragali; CM: Cortex Mori; RSF: Radix Sophorae Flavescentis; RAM: Rizoma Atractylodis Macrocephalae; POR: Poria; RPA: Radix Paeoniae Alba; RPM: Radix Poly Multiflori; RSM: Radix Salviae Miltiorrhizae; HP: Herba Plantaginis.

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  Figure 4. Identification of CKD-related targets by pre-existing microarray data 226 differentially expressed genes identified by the limma package were highly related to kidney disease. Blue and brown stripes represent CKD samples and normal samples, respectively. P < 0.01, FC > 2 were considered as cut-off values.

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  Figure 5. Candidate target identification and ClueGO pathway analysis A. Core protein-protein interaction (CPPI) network of NDQ targets. This network consists of 3846 nodes and 85232 edges. B. Big hubs of the NDQ CPPI network extracted from (A) whose degree is more than twice the median degree of all nodes in the network. C. PPI network of main NDQ targets extracted from (B) by calculating 6 topological features. D.-E. A functionally grouped network of enriched categories was generated for the target genes. GO terms are represented as nodes, and node size represents the term's enrichment significance. Functionally related groups partially overlap. Only the most significant term in the group was labeled. Representative enriched pathway (P < 0.05) interactions among the main NDQ targets.

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  Figure 6. NDQ treatment improves renal function in a CKD animal model A. Animal experimental processes. B.-C. Changes in serum creatinine and urinary protein in 5/6 nephrectomy rats treated for 8 weeks. D.-E. Serum urea nitrogen and Cystatin C levels in rats at the end of the experiment. F. Pathological score of kidney injury. Each color represents a pathological manifestation, the greater the area the more serious the injury. G. Representative images of histopathological findings in rat remnant kidneys analyzed on week 19 (HE staining, 200×, scale bar represents 50 μm). Data are presented as the mean ± SD. *p < 0.05, **p < 0.01, ***p < 0.001 (versus untreated model group).

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  Figure 7. Effects of NDQ on fibrosis-related indices and signaling pathways A.-D. Four fibrosis-related indexes (PCIII, COLIV, LN, and FN) were measured by ELISA. E. Histopathological findings in rat remnant kidneys analyzed on week 19. Renal tissue sections were stained with Masson's trichrome stain for interstitial fibrosis and Sirius red stain for collagen fibers (200×, scale bar represents 500 μm). F. Rat kidneys were harvested at the end of the experiment, and analyzed to identify the expression of TGF-β1, Smad2/3, p-Smad2/3, Smad7, p38MAPK, and p-p38MAPK by western blotting. GAPDH served as the loading control. G. Densitometric analysis of TGF-β1, Smad2/3, smad7, and p38MAPK expression. H. TGF-β1, p38MAPK, and Smad3 expression in the remnant kidney of CKD rats were analyzed by immunohistochemistry (200×, scale bar represents 500 μm). I. Expression of TGF-β1, p-p38MAPK, and p-Smad3 was analyzed quantitatively. Data are presented as means ± SD. *p < 0.05, **p < 0.01, ***p < 0.001 (versus untreated model group).

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  Figure 8. Effect of NDQ on renal anemia and activation of downstream mediators of the EPO receptor A.-G. Hematological data throughout the study. Hb: hemoglobin; Ht: hematocrit; RBC: red blood cells; MCH: mean cell hemoglobin; MCV: mean cell volume; Rtc: reticulocyte count; MCHC: mean cell hemoglobin concentration. H. Serum EPO level was measured by ELISA at the end of the experiment. I. EPO mRNA expression in kidney and liver was determined by real-time PCR and normalized to the expression of GAPDH. J. Rat kidneys were harvested at the end of the experiment, and tested to determine the expression of p-ERK, ERK, p-AKT, AKT, p-STAT3, STAT3, p-STAT5, and STAT5 by western blotting. GAPDH was used as the loading control. K. Densitometric analysis for ERK, AKT, STAT3 and STAT5 expression. L. ERK, AKT, STST3 and STAT5 expression in the remnant kidney of CKD rats were analyzed by immunohistochemistry (200×, scale bar represents 500 μm). M. Expression of ERK, AKT, STST3 and STAT5 was analyzed quantitatively. Data are presented as means ± SD. *p < 0.05, **p < 0.01, ***p < 0.001 (versus untreated model group).