Skip to main content
NCBI home page
In Vivo logoLink to In Vivo
. 2026 Oct 29;40(6):3491–3503. doi: 10.21873/invivo.14492

Impact of SPAK Deficiency on Glomerular Injury and Mitochondrial Homeostasis in Adriamycin-Induced FSGS

CHIEN-WEI HUANG 1,2, HSIN-HUNG CHEN 3, JIN-SHUEN CHEN 1,4
PMCID: PMC13723969  PMID: 42957228

Abstract

Background/Aim

Focal segmental glomerulosclerosis (FSGS) is characterized by podocyte injury, mitochondrial dysfunction, oxidative stress, and metabolic remodeling. STE20/SPS1-related proline-alanine-rich kinase (SPAK), a downstream component of WNK signaling, regulates renal ion transport and has been implicated in inflammatory and stress responses. This study examined the impact of SPAK deficiency on renal injury and mitochondrial homeostasis in Adriamycin-induced FSGS.

Materials and Methods

Eight-week-old male wild-type and global SPAK knockout C57BL/6 mice received a single intravenous injection of Adriamycin (18 mg/kg) or saline and were followed for four weeks. Renal function, proteinuria, glomerular histology, podocyte markers, mitochondrial dynamics, oxidative stress, apoptosis, and targeted metabolic profiles were assessed using biochemical assays, histology, immunohistochemistry, TUNEL staining, western blotting, quantitative PCR, and LC-MS-based metabolomics.

Results

Adriamycin induced proteinuria, serum creatinine elevation, glomerulosclerosis, and reduced nephrin and podocin expression in both wild-type and SPAK knockout mice. The severity of renal functional and histological injury was comparable between the two FSGS groups. SPAK deficiency was associated with baseline mitochondrial and apoptotic abnormalities, including reduced ATP5A1 expression and increased TUNEL-positive cells. In FSGS kidneys, SPAK deficiency did not restore ATP5A1, OPA1, PGC-1α, redox balance, or glycolytic remodeling, and SPAK-knockout FSGS mice exhibited greater apoptosis than wild-type FSGS mice.

Conclusion

SPAK deficiency modifies mitochondrial and apoptotic responses but does not attenuate Adriamycin-induced glomerular injury. These findings suggest that SPAK contributes to glomerular homeostasis and that its role in kidney injury is context-dependent.

Keywords: Focal segmental glomerulosclerosis, SPAK, WNK signaling, podocyte, mitochondrial dysfunction, Adriamycin nephropathy

Introduction

Focal segmental glomerulosclerosis (FSGS) is a pattern of kidney injury that leads to nephrotic syndrome and end-stage renal disease (ESRD) (1). The condition involves scarring of discrete segments of glomeruli, the kidney’s filtering units, causing a progressive decline in renal function (2). The primary cell affected in FSGS is the podocyte, a terminally differentiated epithelial cell that forms the outer layer of the glomerular filtration barrier (3). Podocytes extend elaborate foot processes that interdigitate with those of adjacent cells, creating a specialized filtration slit known as the slit diaphragm. This structure is essential for preventing protein leakage into the urine (4-5). When podocytes are injured or lost, the filtration barrier breaks down, triggering proteinuria and a cascade of responses that culminate in glomerulosclerosis and progressive nephron loss (6). The causes of podocyte injury in FSGS are varied and include genetic mutations, immune dysregulation, hemodynamic alterations, and metabolic dysfunction (7). Current treatments rely primarily on general immunosuppressants such as corticosteroids, which are not universally effective and carry substantial side effects (1, 8).

The STE20/SPS1-related proline-alanine-rich kinase (SPAK) is a serine-threonine kinase within the With-No-Lysine (WNK) kinase signaling pathway, activated by changes in osmotic and ionic conditions (9). The WNK-SPAK axis is best characterized in the distal nephron, where it regulates ion cotransporters including the Na-Cl cotransporter (NCC) and the Na-K-2Cl cotransporter (NKCC2), which are essential for blood pressure regulation and electrolyte homeostasis (10-11). Mutations in WNK genes cause familial hyperkalemic hypertension, a monogenic form of hypertension (12). While SPAK’s tubular functions are well established, its role in the glomerulus remains poorly understood. Emerging evidence suggests that SPAK participates in inflammation and cellular stress beyond its canonical ion transport functions (13). Selective deletion of SPAK in macrophages reduces kidney inflammation and fibrosis in mice maintained on a low-potassium diet (14), indicating that SPAK may exert distinct effects across different renal cell types and disease contexts. Whether SPAK plays a meaningful role in podocyte biology or glomerular disease has not been examined.

Mitochondrial dysfunction is now recognized as a central contributor to podocyte injury and FSGS progression (15-16). Podocytes are metabolically demanding cells with abundant mitochondria, rendering them particularly susceptible to mitochondrial damage and bioenergetic stress (17). In FSGS and related kidney diseases, defects in mitochondrial biogenesis, impaired regulation of mitochondrial fusion-fission dynamics, deficient mitophagy, and increased oxidative stress collectively promote podocyte loss and glomerulosclerosis (18-20). Mitochondrial fusion is mediated by OPA1, MFN1, and MFN2, while fission is driven by DRP1 and FIS1 (21-22). In FSGS, excessive mitochondrial fission produces fragmented organelles that are more vulnerable to further injury (21-23). The master regulator of mitochondrial biogenesis, PGC-1α, is frequently suppressed in kidney disease, reducing mitochondrial mass and respiratory capacity (24).

Under healthy conditions, podocytes rely predominantly on oxidative phosphorylation (OXPHOS) for ATP production. In disease, they shift toward aerobic glycolysis, analogous to the Warburg effect observed in cancer cells (25). This shift is accompanied by upregulation of glycolytic enzymes such as lactate dehydrogenase A (LDHA) and generates metabolic byproducts that amplify inflammation and podocyte injury (25-26). The pentose phosphate pathway (PPP) maintains redox balance through NADPH production; impairment of the PPP exacerbates oxidative stress (26). NAD+/SIRT1 signaling supports mitochondrial function and may influence cellular adaptation to metabolic stress (27). The mTOR signaling pathway may also be aberrantly activated in glomerular disease, contributing to metabolic dysregulation and podocyte injury (26-27). Given SPAK’s emerging involvement in cellular stress responses and the established importance of mitochondrial and metabolic integrity for podocyte survival, we investigated whether global SPAK deletion modifies susceptibility to Adriamycin-induced FSGS and its associated mitochondrial, oxidative, apoptotic, and metabolic phenotypes (8, 16).

Materials and Methods

Animal model and experimental design. All animal experiments were approved by the Institutional Animal Care and Use Committee at Kaohsiung Veterans General Hospital (Approval No. IACUC-2401-251223039) and conducted in full compliance with institutional guidelines for laboratory animal care. Global SPAK knockout (KO) mice on a C57BL/6 background were used alongside age-matched male C57BL/6 wild-type (WT) mice as controls. The C57BL/6 background was selected because the available global SPAK knockout line and the corresponding WT controls were maintained on this genetic background, allowing genotype-matched comparison. Although C57BL/6 susceptibility to Adriamycin nephropathy is known to be substrain- and dose-dependent, recent work has shown that Adriamycin nephropathy can be induced in selected C57BL/6 substrains under appropriate dosing conditions (28-30). At 8 weeks of age, mice were assigned to four groups: WT Control (Ctrl), WT FSGS, SPAK KO Ctrl, and SPAK KO FSGS. FSGS was induced by a single intravenous injection of Adriamycin (18 mg/kg body weight, TRC-D558000; Toronto Research Chemicals, Toronto, ON, Canada); control mice received an equivalent volume of saline. Animals were monitored for four weeks, with weekly measurements of body weight and urine collection. At study termination, blood samples and kidney tissues were collected for subsequent analyses.

Renal function assessment. Urine was collected using metabolic cages. Urinary protein concentration was measured with a Dual-Range™ BCA Protein Assay Kit (BC03-500, Visual Protein, Taipei, Taiwan), and urinary creatinine was quantified using a VITROS 350 System (Ortho Clinical Diagnostics, Raritan, NJ, USA). The urinary protein-to-creatinine ratio (UPCR) was calculated as an index of proteinuria severity. Blood was drawn at sacrifice to measure serum blood urea nitrogen (BUN) and creatinine levels using commercial colorimetric kits.

Histological analysis. Kidney tissues were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned at 4 μm. Sections were stained with hematoxylin and eosin (H&E) and Periodic acid-Schiff (PAS) for morphological evaluation. Glomerulosclerosis was scored on PAS-stained sections by a pathologist blinded to experimental group assignments. At least 50 glomeruli per mouse were evaluated on a scale of 0 to 4 (0=normal; 1=less than 25% sclerosis; 2=25-50% sclerosis; 3=50-75% sclerosis; 4=greater than 75% sclerosis), and the mean score was used to calculate the glomerulosclerosis index.

Immunohistochemistry and immunofluorescence. For immunohistochemistry (IHC), paraffin-embedded kidney sections underwent antigen retrieval before incubation with primary antibodies against SPAK (83081-2-RR; Proteintech, Rosemont, IL, USA), PGC-1α (A12348; ABclonal, Woburn, MA, USA), DRP1 (A2586; ABclonal), MFN2 (ab56889; Abcam, Cambridge, UK), FIS1 (ABclonal, A5821, Woburn, MA, USA), and 4-hydroxynonenal (4-HNE) (bs-6313R; Bioss, Woburn, MA, USA). Detection was performed with the Leica Novolink Polymer Detection System kit (RE7140-K; Leica Biosystems, Nussloch, Germany) according to the manufacturer’s protocol. Apoptosis was detected using the In Situ Cell Death Detection Kit (12156792910; Roche, Basel, Switzerland) according to the manufacturer’s protocol, with nuclei counterstained with DAPI. Images were acquired by fluorescence microscopy, and the percentage of TUNEL-positive cells was quantified.

Western blot analysis. Kidney cortex tissues were homogenized in RIPA lysis buffer supplemented with protease and phosphatase inhibitors. Protein concentration was determined using the Dual-Range™ BCA Protein Assay Kit (BC03-500; Visual Protein, Taipei, Taiwan). Equal amounts of protein (20-40 μg) were resolved by SDS-PAGE and transferred to polyvinylidene fluoride membranes. Membranes were probed with primary antibodies against nephrin (22912-1-AP; Proteintech), podocin (A17337; ABclonal), ATP5A1 (A11217; ABclonal), OPA1 (A9833; ABclonal), LC3B (A17424; ABclonal), PINK1 (GeneTex, GTX107851, Irvine, CA, USA), Parkin (GTX658911; GeneTex), NGAL (30700-1-AP; Proteintech), and β-actin (GTX109639; GeneTex). After incubation with HRP-conjugated secondary antibody (NA934; Cytiva, Marlborough, MA, USA), bands were visualized by enhanced chemiluminescence substrate (K-12045-D50; Advansta, San Jose, CA, USA) and quantified using ImageJ software (National Institutes of Health, Bethesda, MD, USA), with normalization to β-actin.

Real-Time Quantitative PCR. Total RNA was extracted from kidney cortex tissue using RNAzol® RT (RN-190; Molecular Research Center, Cincinnati, OH, USA), and cDNA was synthesized from 1 μg of total RNA. Quantitative RT-PCR was performed with with iQ™ SYBR® Green Supermix (#170-8882, Bio-Rad, Hercules, CA, USA). Relative mRNA expression of Spak, Dnm1l, Fis1, Mfn2, Ldha, and Ldhb was calculated using the 2−ΔΔCt method with GAPDH as the reference gene.

Targeted metabolomic profiling. Kidney tissue samples were snap-frozen in liquid nitrogen. Metabolites were extracted and profiled by liquid chromatography-mass spectrometry (LC-MS). Levels of metabolites related to glycolysis, the TCA cycle, and the pentose phosphate pathway were quantified. Data were normalized, and statistical analyses including principal component analysis (PCA) and volcano plot visualization were used to identify significant between-group differences. For volcano plot analysis, fold change was calculated as the ratio of mean metabolite abundance between comparison groups, and log2-transformed fold change was plotted on the x-axis. The log10(p-value) was plotted on the y-axis. Between-group p-values were calculated using the Mann-Whitney U-test. Differentially abundant metabolites were defined as metabolites with p<0.05 and an absolute log2 fold change meeting the predefined cutoff indicated by the vertical dashed lines in the volcano plots.

Statistical analysis. All quantitative data are presented as mean ± standard deviation (SD). Given the small sample sizes (n=3 or n=4 per group), which preclude assumptions of normality, nonparametric tests were applied throughout. The Mann-Whitney U-test was used for comparisons between two groups, and the Kruskal-Wallis test was used for comparisons among multiple groups. A p-value less than 0.05 was considered statistically significant. Data analyses were performed using SPSS software version 22.0 for all statistical analyses (IBM Corp., Armonk, NY, USA).

Results

Comparable Adriamycin-induced renal injury in wild-type and SPAK knockout mice. PCR genotyping confirmed the SPAK knockout allele (189 bp) and the absence of the wild-type allele (1147 bp) (Figure 1A). Quantitative RT-PCR further verified an approximately 95% reduction in Spak mRNA in the kidneys of SPAK KO mice relative to WT controls (Figure 1B). The experimental timeline is shown in Figure 1C. Both WT and SPAK KO mice treated with Adriamycin developed significant renal injury. Body weight declined to approximately 17-19 g in both FSGS groups by week four, while control animals remained between 19-22 g. The UPCR rose to approximately 2.8-3.0 mg/mg in both FSGS groups, indicating severe proteinuria. Serum creatinine increased to approximately 0.25-0.35 mg/dl in both FSGS groups compared to approximately 0.10 mg/dl in controls, and BUN levels remained similar across all groups at approximately 20-25 mg/dl (Figure 1D). No significant differences in any renal function parameter were observed between WT FSGS and SPAK KO FSGS mice at any time point.

Figure 1.

Figure 1

Figure 1

Open in a new tab

Comparable Adriamycin-induced renal injury in wild-type and SPAK-knockout mice. (A) PCR genotyping confirmed the SPAK-knockout allele (189 bp) and WT allele (1147 bp). (B) Quantitative PCR confirmed reduced Spak mRNA expression in SPAK KO kidneys. (C) Experimental design. (D) Body weight, UPCR, BUN and serum creatinine over four weeks. (E) Representative hematoxylin and eosin/periodic acid-Schiff-stained kidney sections. (F) Colloidal iron staining. (G) Glomerulosclerosis score. (H) Western blotting and quantification of nephrin and podocin. Data are mean±SD. *p<0.05; **p<0.01; ***p<0.001. Scale bar=100 μm. SPAK, Ste20-related proline-alanine-rich kinase; KO, knockout; WT, wild type; ctrl, control; IV: intravenous; UPCR, urinary protein-to-creatinine ratio; BUN, blood urea nitrogen; H&E, hematoxylin and eosin; PAS, periodic acid-Schiff.

Histological examination showed comparable glomerular structural damage and segmental sclerosis in both FSGS groups on H&E and PAS staining (Figure 1E). Colloidal iron staining revealed increased mucopolysaccharide deposition in the glomerular basement membrane in both FSGS groups (Figure 1F). The glomerulosclerosis index was approximately 35% in both WT FSGS and SPAK KO FSGS mice, with no statistically significant difference between groups (Figure 1G). Western blot analysis showed reduced nephrin expression in WT FSGS mice compared with WT controls, with a similar reduction observed in SPAK KO FSGS mice. Podocin expression also showed a decreasing trend in both FSGS groups, without evidence of preservation in SPAK KO FSGS mice (Figure 1H). These findings indicate that SPAK deletion did not prevent the loss of essential podocyte proteins.

Persistent mitochondrial dysfunction, oxidative stress, and apoptosis after SPAK deletion. IHC confirmed the absence of SPAK protein in the glomeruli of SPAK KO mice (Figure 2A). PGC-1α expression, a key regulator of mitochondrial biogenesis, was downregulated in WT FSGS glomeruli (decreasing from approximately 40% to 35% of control levels). In SPAK KO FSGS mice, PGC-1α expression was approximately 37% of control levels, only marginally higher than in WT FSGS mice (Figure 2B). DRP1 expression did not change significantly across the four groups (Figure 2C). FIS1 expression was elevated in both WT FSGS and SPAK KO control mice relative to WT controls, with SPAK KO FSGS mice showing the highest FIS1 expression at approximately 38% (Figure 2D). MFN2 expression remained stable across all groups (Figure 2E).

Figure 2.

Figure 2

Figure 2

Open in a new tab

Persistent mitochondrial stress, oxidative stress and apoptosis after SPAK deletion. (A) SPAK immunohistochemistry confirmed loss of SPAK protein in SPAK KO glomeruli. (B) PGC-1α immunostaining. (C) DRP1 immunostaining. (D) FIS1 immunostaining. (E) MFN2 immunostaining. (F) 4-HNE immunostaining as a marker of lipid peroxidation. (G) TUNEL staining with DAPI counterstaining and quantification of TUNEL-positive cells. Data are mean±SD. *p<0.05; **p<0.01; ***p<0.001. Scale bar=100 μm. SPAK, Ste20-related proline-alanine-rich kinase; KO, knockout; WT, wild type; ctrl, control.

Oxidative stress, assessed by 4-HNE staining, was significantly elevated in both WT FSGS and SPAK KO FSGS mice relative to their respective controls, with no significant difference between the two FSGS groups (Figure 2F). Apoptosis, detected by TUNEL staining, increased in both FSGS groups; however, the apoptosis rate was significantly higher in SPAK KO FSGS mice (approximately 30%) than in WT FSGS mice (approximately 20%). SPAK KO control mice also exhibited a higher baseline apoptosis rate (approximately 23%) compared to WT controls (approximately 9%) (Figure 2G).

SPAK deletion leaves metabolic reprogramming and mitochondrial protein remodeling uncorrected. RT-PCR confirmed a 95% reduction in Spak mRNA in SPAK KO mice (Figure 3A). Dnm1l and Fis1 expression was slightly elevated in both FSGS groups, with no significant difference between them (Figure 3B, 3C). Mfn2 expression was reduced in WT FSGS mice (approximately 0.8-fold of control), and SPAK KO mice showed even lower baseline Mfn2 expression (approximately 0.4-fold in controls and 0.3-fold in FSGS mice) (Figure 3D). Ldha mRNA, a marker of glycolytic activity, was increased in both FSGS groups: approximately 1.9-fold in WT FSGS mice and 2.4-fold in SPAK KO FSGS mice (Figure 3E). Ldhb expression, associated with oxidative phosphorylation, was reduced in both FSGS groups (Figure 3F).

Figure 3.

Figure 3

Open in a new tab

Gene expression of mitochondrial dynamics and metabolic markers. (A) Spak mRNA expression. (B) Dnm1l expression. (C) Fis1 expression. (D) Mfn2 expression. (E Ldha expression. (F) Ldhb expression. Gene expression was normalized to GAPDH. Data are mean±SD. *p<0.05; **p<0.01; ***p<0.001. SPAK, Ste20-related proline-alanine-rich kinase; KO, knockout; WT, wild type; ctrl, control.

At the protein level, Western blot analysis of ATP5A1, a subunit of mitochondrial ATP synthase, showed that WT FSGS mice had reduced ATP5A1 expression (approximately 0.25-fold relative to control). SPAK KO control mice had markedly lower ATP5A1 levels (approximately 0.1-fold), and SPAK KO FSGS mice showed the lowest levels (approximately 0.08-fold) (Figure 4A, 4B). OPA1 expression was reduced in both WT FSGS and SPAK KO FSGS mice (Figure 4A, 4C). NGAL, a kidney injury marker, was elevated in both FSGS groups (Figure 4A, 4D). LC3B, an autophagy marker, was markedly elevated in WT FSGS mice; SPAK KO control mice also showed high baseline LC3B levels, while SPAK KO FSGS mice had lower LC3B than both WT FSGS and SPAK KO control mice (Figure 4A, 4E). PINK1 expression was reduced in both FSGS groups, while Parkin expression was slightly elevated in both control groups (Figure 4A, 4F, 4G).

Figure 4.

Figure 4

Open in a new tab

Western blot analysis of mitochondrial and autophagy-related proteins. (A) Representative western blots for ATP5A1, OPA1, NGAL, LC3B, PINK1, Parkin and β-actin. (B-G) Quantification of ATP5A1, OPA1, NGAL, LC3B, PINK1 and Parkin, respectively. Band intensities were normalized to β-actin. Data are mean±SD. *p<0.05; **p<0.01; ***p<0.001. SPAK, Ste20-related proline-alanine-rich kinase; KO, knockout; WT, wild type; ctrl, control.

Targeted metabolomics shows limited divergence between SPAK knockout and wild-type FSGS profiles. Targeted metabolomic profiling revealed distinct metabolic changes in WT FSGS mice compared to controls, characterized by altered glycolytic, TCA-cycle, and pentose phosphate pathway-related metabolites (Figure 5A). PCA showed clear separation between WT FSGS and WT control samples (Figure 5B). SPAK KO FSGS samples clustered closer to WT FSGS samples than to SPAK KO control samples, indicating that SPAK deletion did not substantially alter the FSGS metabolic phenotype (Figure 5B). Volcano plot analysis was revised to display log2 fold change on the x-axis and -log10(p-value) on the y-axis, with the horizontal dashed line indicating p=0.05 and the vertical dashed lines indicating the fold-change cutoff (Figure 5C, 5D). Red dots indicate metabolites meeting both the statistical and fold-change criteria, and representative differentially abundant metabolites are annotated directly on the plots. The redox balance, measured by the ratio of reduced to oxidized PPP intermediates, was significantly lower in WT FSGS mice than in controls. SPAK KO FSGS mice showed an identical redox balance to WT FSGS mice, confirming that SPAK deletion did not improve the oxidative stress associated with FSGS (Figure 5E).

Figure 5.

Figure 5

Figure 5

Open in a new tab

Targeted metabolomic profiling of kidney tissues. (A) Heatmap of selected metabolites related to glycolysis, the tricarboxylic acid cycle and the pentose phosphate pathway. (B) Principal component analysis of WT control, WT FSGS, SPAK KO control and SPAK KO FSGS samples. (C) Volcano plot comparing WT FSGS with WT control. (D) Volcano plot comparing SPAK KO FSGS with SPAK KO control. In panels C and D, the x-axis represents log2 fold change, and the y-axis represents −log10(p-value). The horizontal dashed line indicates p=0.05, and vertical dashed lines indicate the fold-change cutoff. Red dots indicate differentially abundant metabolites meeting the predefined statistical and fold-change criteria; gray dots indicate metabolites that did not meet these criteria. (E) Redox balance index based on reduced versus oxidized pentose phosphate pathway intermediates. Data are mean±SD. *p<0.05; **p<0.01; ***p<0.001. SPAK, Ste20-related proline-alanine-rich kinase; KO, knockout; WT, wild type; ctrl, control.

Discussion

This study showed that global SPAK deletion does not reduce the severity of Adriamycin-induced glomerular injury in a manner consistent with renal protection. Both SPAK KO and WT mice developed comparable degrees of renal injury, proteinuria, and glomerulosclerosis, indicating that SPAK is not a critical mediator of podocyte injury in this model. The C57BL/6 background was used because the SPAK KO line and matched WT controls were available on this genetic background, which allowed a genotype-controlled comparison. We acknowledge that C57BL/6 mice were historically considered relatively resistant to Adriamycin nephropathy compared with susceptible strains such as BALB/c. However, recent studies have demonstrated that susceptibility in C57BL/6 mice is substrain-, dose-, and protocol-dependent, with C57BL/6N showing greater susceptibility and C57BL/6J showing more modest susceptibility under selected conditions (28-30). In the present study, the 18 mg/kg Adriamycin protocol produced clear proteinuria, elevated creatinine, glomerulosclerosis, and loss of podocyte markers in both WT and SPAK KO mice, supporting the model’s adequacy for testing genotype-dependent effects. The absence of protection is notable given SPAK’s established involvement in cellular stress and inflammatory signaling. One explanation is that the direct nephrotoxicity of Adriamycin, together with severe mitochondrial and oxidative stress responses, overwhelms any potential modulatory effects of SPAK deletion (8, 16-18). In this context, the dominant injury mechanisms may operate independently of SPAK.

An unexpected finding was the presence of baseline abnormalities in SPAK KO control mice, including elevated apoptosis rates, increased LC3B expression, and markedly reduced ATP5A1 levels compared to WT controls. These observations suggest that SPAK may contribute to the maintenance of normal glomerular cell homeostasis under physiological conditions. The elevated apoptosis and autophagy in SPAK KO controls could reflect a state of chronic low-grade cellular stress, possibly related to altered ion transport or signaling in the absence of SPAK. Despite these baseline differences, SPAK KO FSGS mice did not develop worse outcomes than WT FSGS mice, which may indicate that once Adriamycin induces severe injury, the baseline effects of SPAK deletion become less consequential. Compensatory mechanisms activated in the global knockout model could also obscure potential protective effects (9-11, 18).

Analysis of mitochondrial dynamics showed that SPAK deletion did not correct the changes in DRP1 and MFN2 expression observed in FSGS. The discordance between Mfn2 mRNA and protein levels in SPAK KO mice points to complex post-transcriptional regulation of MFN2 in the absence of SPAK, a phenomenon that warrants further investigation (21-23). Metabolic profiling showed that SPAK deletion did not prevent the glycolytic shift characteristic of FSGS; in fact, SPAK KO FSGS mice had higher Ldha mRNA expression than WT FSGS mice, suggesting that SPAK deletion may further promote glycolysis. This finding is consistent with the lower baseline ATP5A1 expression in SPAK KO mice, which implies a reduced capacity for mitochondrial respiration even under normal conditions. The metabolomic data corroborated this interpretation, as SPAK KO FSGS mice clustered with WT FSGS mice rather than with SPAK KO controls. Redox balance was also not restored in SPAK KO FSGS mice, confirming that SPAK deletion does not alleviate the oxidative stress associated with FSGS (18, 26). The higher apoptosis rates in SPAK KO FSGS mice compared to WT FSGS mice raise the possibility that SPAK exerts a pro-survival function in podocytes, potentially through interactions with WNK-SPAK/OSR1 signaling and mitochondrial stress pathways (9-11, 18, 21).

Study limitations. The use of a global SPAK knockout model prevents attribution of observed effects to specific cell types, and compensatory adaptations in non-podocyte cells may confound interpretation. Podocyte-specific SPAK knockout models would provide more mechanistic clarity. Additionally, the Adriamycin model represents only one form of FSGS, and findings may not generalize to other etiologies of glomerular disease. Because susceptibility to Adriamycin nephropathy differs among C57BL/6 substrains, the findings should also be interpreted within the context of the specific genetic background and dosing protocol used in this study. Future validation in additional substrains or susceptible strains would strengthen model generalizability. The basis for the baseline mitochondrial and apoptotic abnormalities in SPAK KO mice remains unclear and merits dedicated investigation.

Data Availability

Data generated or analyzed during this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The Authors declare no conflicts of interest in relation to this study.

Authors’ Contributions

Chien-Wei Huang contributed to conceptualization, methodology, investigation, formal analysis and original draft preparation. Hsin-Hung Chen contributed to methodology, formal analysis and data curation. Jin-Shuen Chen contributed to conceptualization, supervision, funding acquisition and manuscript review and editing. All authors approved the final manuscript.

Acknowledgements

The Authors thank Chian-Huei Guo and Ling-Chun Yeh for technical assistance.

Funding

This work was supported by Kaohsiung Veterans General Hospital grants KSVGH-113-049 and KSVGH-114-083.

Artificial Intelligence (AI) Disclosure

During the preparation of this manuscript, a large language model (ChatGPT, OpenAI) was used solely for language editing and stylistic improvements in select paragraphs. No sections involving the generation, analysis, or interpretation of research data were produced by generative AI. All scientific content was created and verified by the authors. Furthermore, no figures or visual data were generated or modified using generative AI or machine learning–based image enhancement tools.

References

  • 1.D'Agati VD, Kaskel FJ, Falk RJ. Focal segmental glomerulosclerosis. N Engl J Med. 2011;365(25):2398–2411. doi: 10.1056/NEJMra1106556. [DOI] [PubMed] [Google Scholar]
  • 2.Rosenberg AZ, Kopp JB. Focal segmental glomerulosclerosis. Clin J Am Soc Nephrol. 2017;12(3):502–517. doi: 10.2215/CJN.05960616. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Kopp JB, Anders HJ, Susztak K, Podestà MA, Remuzzi G, Hildebrandt F, Romagnani P. Podocytopathies. Nat Rev Dis Primers. 2020;6(1):68. doi: 10.1038/s41572-020-0196-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Martin CE, Jones N. Nephrin signaling in the podocyte: an updated view of signal regulation at the slit diaphragm and beyond. Front Endocrinol (Lausanne) 2018;9:302. doi: 10.3389/fendo.2018.00302. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Wen Y, Shah S, Campbell KN. Molecular mechanisms of proteinuria in focal segmental glomerulosclerosis. Front Med (Lausanne) 2018;5:98. doi: 10.3389/fmed.2018.00098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Shankland SJ. The podocyte's response to injury: Role in proteinuria and glomerulosclerosis. Kidney Int. 2006;69(12):2131–2147. doi: 10.1038/sj.ki.5000410. [DOI] [PubMed] [Google Scholar]
  • 7.Kim JS, Han BG, Choi SO, Cha SK. Secondary focal segmental glomerulosclerosis: from podocyte injury to glomerulosclerosis. Biomed Res Int. 2016;2016:1630365. doi: 10.1155/2016/1630365. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Lee VW, Harris DC. Adriamycin nephropathy: A model of focal segmental glomerulosclerosis. Nephrology (Carlton) 2011;16(1):30–38. doi: 10.1111/j.1440-1797.2010.01383.x. [DOI] [PubMed] [Google Scholar]
  • 9.Shekarabi M, Zhang J, Khanna AR, Ellison DH, Delpire E, Kahle KT. WNK kinase signaling in ion homeostasis and human disease. Cell Metab. 2017;25(2):285–299. doi: 10.1016/j.cmet.2017.01.007. [DOI] [PubMed] [Google Scholar]
  • 10.McCormick JA, Ellison DH. The WNKs: atypical protein kinases with pleiotropic actions. Physiol Rev. 2011;91(1):177–219. doi: 10.1152/physrev.00017.2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Vitari AC, Deak M, Morrice NA, Alessi DR. The WNK1 and WNK4 protein kinases that are mutated in Gordon's hypertension syndrome phosphorylate and activate SPAK and OSR1 protein kinases. Biochem J. 2005;391(Pt 1):17–24. doi: 10.1042/BJ20051180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Wu A, Zhang Y, Bock F, Arroyo JP, Delpire E, Zhang MZ, Harris RC, Terker AS. Macrophage SPAK deletion limits a low potassium-induced kidney inflammatory program. Am J Physiol Renal Physiol. 2024;327(5):F899–F909. doi: 10.1152/ajprenal.00175.2024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Grimm PR, Coleman R, Delpire E, Welling PA. Constitutively active SPAK causes hyperkalemia by activating NCC and remodeling distal tubules. J Am Soc Nephrol. 2017;28(9):2597–2606. doi: 10.1681/ASN.2016090948. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Galvan DL, Green NH, Danesh FR. The hallmarks of mitochondrial dysfunction in chronic kidney disease. Kidney Int. 2017;92(5):1051–1057. doi: 10.1016/j.kint.2017.05.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Hagiwara M, Yamagata K, Capaldi RA, Koyama A. Mitochondrial dysfunction in focal segmental glomerulosclerosis of puromycin aminonucleoside nephrosis. Kidney Int. 2006;69(7):1146–1152. doi: 10.1038/sj.ki.5000207. [DOI] [PubMed] [Google Scholar]
  • 16.Li Y, Fan J, Zhu W, Niu Y, Wu M, Zhang A. Therapeutic potential targeting podocyte mitochondrial dysfunction in focal segmental glomerulosclerosis. Kidney Dis (Basel) 2023;9(4):254–264. doi: 10.1159/000530344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Bhatia D, Capili A, Choi ME. Mitochondrial dysfunction in kidney injury, inflammation, and disease: Potential therapeutic approaches. Kidney Res Clin Pract. 2020;39(3):244–258. doi: 10.23876/j.krcp.20.082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Menon MC, Chuang PY, He CJ. The glomerular filtration barrier: components and crosstalk. Int J Nephrol. 2012;2012:749010. doi: 10.1155/2012/749010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Zuk A, Bonventre JV. Acute kidney injury. Annu Rev Med. 2016;67:293–307. doi: 10.1146/annurev-med-050214-013407. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Mishra P, Chan DC. Mitochondrial dynamics and inheritance during cell division, development and disease. Nat Rev Mol Cell Biol. 2014;15(10):634–646. doi: 10.1038/nrm3877. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Smirnova E, Griparic L, Shurland DL, van der Bliek AM. Dynamin-related protein Drp1 is required for mitochondrial division in mammalian cells. Mol Biol Cell. 2001;12(8):2245–2256. doi: 10.1091/mbc.12.8.2245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Kang HM, Ahn SH, Choi P, Ko YA, Han SH, Chinga F, Park AS, Tao J, Sharma K, Pullman J, Bottinger EP, Goldberg IJ, Susztak K. Defective fatty acid oxidation in renal tubular epithelial cells has a key role in kidney fibrosis development. Nat Med. 2015;21(1):37–46. doi: 10.1038/nm.3762. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Semenza GL. Hypoxia-inducible factors in physiology and medicine. Cell. 2012;148(3):399–408. doi: 10.1016/j.cell.2012.01.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Stincone A, Prigione A, Cramer T, Wamelink MM, Campbell K, Cheung E, Olin-Sandoval V, Grüning NM, Krüger A, Tauqeer Alam M, Keller MA, Breitenbach M, Brindle KM, Rabinowitz JD, Ralser M. The return of metabolism: biochemistry and physiology of the pentose phosphate pathway. Biol Rev Camb Philos Soc. 2015;90(3):927–963. doi: 10.1111/brv.12140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Cantó C, Auwerx J. NAD+ as a signaling molecule modulating metabolism. Cold Spring Harb Symp Quant Biol. 2011;76:291–298. doi: 10.1101/sqb.2012.76.010439. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Laplante M, Sabatini DM. mTOR signaling in growth control and disease. Cell. 2012;149(2):274–293. doi: 10.1016/j.cell.2012.03.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Lieberthal W, Levine JS. Mammalian target of rapamycin and the kidney. II. Pathophysiology and therapeutic implications. Am J Physiol Renal Physiol. 2012;303(2):F180–F191. doi: 10.1152/ajprenal.00015.2012. [DOI] [PubMed] [Google Scholar]
  • 28.Watanabe M, Kakutani M, Hiura K, Sasaki H, Sasaki N. Differences in susceptibility to ADR nephropathy among C57BL/6 substrains. Exp Anim. 2023;72(4):520–525. doi: 10.1538/expanim.23-0003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Bryant C, Cianciolo R, Govindarajan R, Agrawal S. Adriamycin-induced nephropathy is robust in N and modest in J substrain of C57BL/6. Front Cell Dev Biol. 2022;10:924751. doi: 10.3389/fcell.2022.924751. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Arif E, Solanki AK, Nihalani D. Adriamycin susceptibility among C57BL/6 substrains. Kidney Int. 2016;89(3):721–723. doi: 10.1016/j.kint.2015.10.019. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data generated or analyzed during this study are available from the corresponding author upon reasonable request.

Articles from In Vivo are provided here courtesy of International Institute of Anticancer Research

RESOURCES