1. Cell Biology

SLC4A1 mutations that cause distal renal tubular acidosis alter cytoplasmic pH and cellular autophagy

  1. Grace Essuman
  2. Midhat Rizvi
  3. Ensaf Almomani
  4. Shahid AKM Ullah
  5. Sarder MA Hasib
  6. Forough Chelangarimiyandoab
  7. Priyanka Mungara
  8. Manfred J Schmitt
  9. Marguerite Hureaux
  10. Rosa Vargas-Poussou
  11. Nicolas Touret
  12. Emmanuelle Cordat  Is a corresponding author
  1. Department of Physiology, University of Alberta, Canada
  2. Department of Basic Medical Sciences, Faculty of Medicine, Al-Balqa Applied University, Jordan
  3. Department of Medicine, University of Alberta, Canada
  4. Department of Molecular and Cell Biology, Department of Biosciences (FR 8.3) and Center of Human and Molecular Biology (ZHMB), Saarland University, Germany
  5. Department of Genetics, Georges Pompidou European Hospital, France
  6. Department of Biochemistry, University of Alberta, Canada
https://doi.org/10.7554/eLife.108253.3
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Cite this article
  1. Grace Essuman
  2. Midhat Rizvi
  3. Ensaf Almomani
  4. Shahid AKM Ullah
  5. Sarder MA Hasib
  6. Forough Chelangarimiyandoab
  7. Priyanka Mungara
  8. Manfred J Schmitt
  9. Marguerite Hureaux
  10. Rosa Vargas-Poussou
  11. Nicolas Touret
  12. Emmanuelle Cordat
(2026)
SLC4A1 mutations that cause distal renal tubular acidosis alter cytoplasmic pH and cellular autophagy
eLife 14:RP108253.
https://doi.org/10.7554/eLife.108253.3
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eLife Assessment

This work reports the characterization of newly identified genetic variants of SLC4A1 in patients with distal renal tubular acidosis. Cell culture studies supplemented with histological analysis of a previously established disease mouse model provide convincing evidence that some of the variants increase intracellular pH, reduce ATP synthesis, and attenuate autophagic degradative flux. The study is valuable in establishing a mechanistic framework for future exploration of the link between intracellular pH and mutations in SLC4A1 in vivo.

https://doi.org/10.7554/eLife.108253.3.sa0

Abstract

Distal renal tubular acidosis (dRTA) is a disorder characterized by the inability of the collecting duct system to secrete acids during metabolic acidosis. The pathophysiology of dominant or recessive SLC4A1 variant-related dRTA has been linked with the mis-trafficking defect of mutant kAE1 protein. However, in vivo studies in kAE1 R607H dRTA mice and humans have revealed a complex pathophysiology implicating a loss of kAE1-expressing intercalated cells and intracellular relocation of the H+-ATPase in the remaining type-A intercalated cells. These cells also displayed accumulation of ubiquitin and p62 autophagy markers. The highly active transport properties of collecting duct cells require the maintenance of cellular energy and homeostasis, a process dependent on intracellular pH. Therefore, we hypothesized that the expression of dRTA variants affects intracellular pH and autophagy pathways. In this study, we report the characterization of newly identified dRTA variants and provide evidence of abnormal autophagy and degradative pathways in mouse inner medullary collecting duct cells and kidneys from mice expressing kAE1 R607H dRTA mutant protein. We show that reduced transport activity of the kAE1 variants correlated with increased cytosolic pH, reduced ATP synthesis, attenuated downstream autophagic pathways pertaining to the fusion of autophagosomes and lysosomes and/or lysosomal degradative activity. Our study elucidated a close relationship between the expression of defective kAE1 proteins, reduced mitochondrial activity, and decreased autophagy and protein degradative flux.

Introduction

Distal renal tubular acidosis (dRTA) is a disorder characterized by the inability of the collecting duct system to secrete acids during metabolic acidosis (Giglio et al., 2021). In addition to hyperchloremic metabolic acidosis, patients with this disease can present with hypokalemia, kidney stones, urinary sodium waste, and difficulty thriving. Expression of pathogenic variants in the ATP6V0A4, ATP6V1B1, FOXI1, WDR72, and SLC4A1 genes are the usual genetic etiologies (Escobar et al., 2016; Rungroj et al., 2018; Enerbäck et al., 2018). The SLC4A1 gene encodes the anion exchanger 1 (AE1) protein, which is an electroneutral chloride/bicarbonate exchanger (Toye et al., 2004). It exists in two forms: a 911 amino acid erythroid isoform known to interact with erythroid cytoskeletal proteins and participate in red cell respiration and integrity, and a 65 amino acid (NH2-terminal) truncated isoform primarily found in the basolateral membrane of renal type A intercalated cells (A-IC) (Kollert-Jons et al., 1993; Nuiplot et al., 2015) and podocytes (Wu et al., 2010). This isoform participates in bicarbonate reabsorption and through its physical and functional interaction with the cytosolic carbonic anhydrase II and apical H+-ATPase, it supports apical proton export and urine acidification (Cordat and Reithmeier, 2014).

Pathogenic variants in the SLC4A1 gene can result in either red cell defects (such as Southeast Asian ovalocytosis [Sawasdee et al., 2006; Cheung et al., 2005] and hereditary spherocytosis [Tang et al., 2020]), renal cell defects (dRTA; Sawasdee et al., 2006) or both in patients with homozygous (Band 3 Coimbra and Band 3 Courcouronnes; Ribeiro et al., 2000; Toye et al., 2008) or compound heterozygous variants (Chang et al., 2009; Khositseth et al., 2012). Renal SLC4A1 disease-causing variants have only been found in the transmembrane domain—where it could impact protein structure and its transport function—or in the short carboxyl domain—where it possibly affects protein–protein interactions. The pathophysiology of dominant or recessive SLC4A1-related dRTA (hereafter named dRTA) has originally been linked with the mis-trafficking defect of mutant kAE1 protein (Sawasdee et al., 2006; Cordat, 2006). However, recent in vivo studies in R607H (orthologous to human R589H dRTA variant) and L919X knockin mice and dRTA patients have revealed a complex pathophysiology where kAE1-expressing intercalated cells were lost, and in the remaining type-A intercalated cells, the H+-ATPase relocated intracellularly and accumulated autophagy marker p62 and ubiquitin-positive material (Mumtaz et al., 2017).

The highly active transport properties of collecting duct cells require the tight maintenance of cellular energy and homeostasis. The autophagy-mediated turnover of damaged organelles is necessary for protecting collecting duct cells as in most renal cells (Festa et al., 2018). The chloride/bicarbonate exchange function of kAE1 in A-ICs confers a pivotal role in pH homeostasis and thus is a major contributor to cellular homeostasis. kAE1 protein interacts with several proteins such as integrin-like kinase (ILK), adaptor-related protein complex 1, 3, and 4 (AP-1, AP-3, and AP-4 mu1A), transmembrane protein 139 (TMEM139), kinesin family member 3B (KIF3B), and clathrin, among others (Nuiplot et al., 2015; Keskanokwong et al., 2007; Duangtum et al., 2011; Sawasdee et al., 2010) that support protein stability and trafficking. It also interacts with homeostatic proteins including the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) Su et al., 2011 and the antioxidant enzyme peroxiredoxin 6 (PRDX 6) (Sorrell et al., 2016), which play major roles in cellular energy metabolism and oxidative stress response, respectively.

In this study, we report the characterization of newly identified dRTA genetic variations and provide evidence of abnormal autophagy and degradative pathways in cells and kidneys from mice expressing dRTA mutant kAE1 proteins.

Results

The dRTA kAE1 variants traffic to the basolateral membrane but have reduced transport activity in mIMCD3 cells

We first characterized three newly identified dRTA mutations and compared them with kAE1 WT or previously characterized kAE1 R589H mutant. Figure 1A depicts the alpha fold predicted structure of kAE1 showing amino acids mutated in each kAE1 mutant. kAE1 R295H is a recessively inherited substitution in the N-terminal cytosolic domain of the protein. kAE1 Y413H is a dominantly inherited substitution in transmembrane domain (TM) 1 of the core domain. In the gate domain, dominantly inherited S525F and R589H substitutions occur in TM 5 and TM 6, respectively. We generated the newly identified dRTA variant cDNAs and expressed them or kAE1 WT in mIMCD3 cells. As seen on Figure 1B, kAE1 R295H, S525F, and R589H variants display two typical bands similar to kAE1 WT. The top band (open circle) encompasses kAE1 proteins carrying a complex oligosaccharide that have reached the Golgi and beyond, while the bottom band (black circle) corresponds to high mannose-carrying kAE1 proteins located in the endoplasmic reticulum. However, kAE1 Y413H mutant bands intensity was overall weaker than WT and displayed a predominant single band aligned with high mannose-carrying kAE1 proteins. These results indicate that the three newly described dRTA mutants are successfully expressed in mIMCD3 cells. We next localized these mutants by immunofluorescence in polarized mIMCD3 cells. Both kAE1 WT and mutants appropriately co-localized with basolateral membrane marker beta-catenin in polarized mIMCD3 cells (Figure 1C). kAE1 R589H location has previously been reported at the basolateral membrane in polarized mIMCD3 cells (Cordat, 2006). However, staining for kAE1 Y413H was again weaker and seemed more intracellular than other mutants. To address a possible premature degradation of this variant, we measured its lifetime and observed that its degradation begins 6 hours post-synthesis while kAE1 WT abundance remained stable for 24 hours (Figure 1D). Finally, to assess the transport activity of the mutants, we examined the steady-state cytosolic pH (pHi) and rate of intracellular alkalinization of mIMCD3 cells expressing kAE1 WT or mutants (Figure 1E–G). Using BCECF-AM, we observed that the steady state intracellular pH (pHi) of kAE1 mutant cells was more alkaline than WT cells (except for kAE1 R295H cell pHi, which has a similar trend but is not significantly different from WT) (Figure 1F), in agreement with rate of intracellular alkalinization (Figure 1G). Note that transport activity, measured as rate of alkalinization, is measured by reverting kAE1 exchange activity from bicarbonate export to import (see ‘Materials and methods, protocol for transport assay), hence a reduced alkalinization rate is observed in cells expressing defective kAE1 protein compared to WT (Figure 1G). Overall, these results indicate that except for the kAE1 Y413H mutant, the other newly described variants are expressed and traffic to the basolateral membrane of polarized mIMCD3 cells, similar to the previously published kAE1 R589H mutant. Given that the premature degradation of kAE1 Y413H mutant likely explains the dRTA phenotype, we did not perform further assays on cells expressing this protein.

Figure 1
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kAE1 R295H, Y413H, S525F, and R589H dRTA mutants are either dysfunctional or prematurely degraded.

(A) Alpha Fold predicted structure of the kidney isoform of Band 3 anion exchanger 1 (kAE1) with core and gate domains highlighted. The dRTA kAE1 mutation sites are colored in blue with line extensions detailing specific amino acids mutated. (B) Immunoblot showing expression of kAE1 WT, R295H, Y413H, S525F, and R589H and corresponding actin band in mIMCD3 cells treated with and without doxycycline for 24 hours. Mouse anti-HA antibody was used to detect kAE1-HA, top (open circle) and bottom bands (closed circle) correspond to kAE1 carrying complex and high mannose oligosaccharides, respectively. (C) Immunostaining of kAE1 WT or mutant (red) and β-catenin (green) in polarized mIMCD3 cells. Scale bar = 10 μm. Red = kAE1, green = ß-catenin. (D) Immunoblot of cycloheximide (CHX) chase assay with corresponding actin in kAE1 mIMCD3 WT and Y413H cells showing the degradation of kAE1 Y413H after 3 hours CHX incubation. (E) Cartoon depicting the transporter activity and expected changes in pHi in cells expressing kAE1 WT (left) or inactive mutant (right). (F) Graphical representation of intracellular pH (pHi) measurement of mIMCD3 kAE1 WT, R295H, Y413H, S525F, and R589H cells. Error bars correspond to mean ± SEM, n=minimum 32. *p<0.05, **p<0.01 using one-way ANOVA followed by a Dunnett’s post hoc test. (G) Rate of intracellular alkalinization in WT or mutant mIMCD3 cells normalized to WT + Dox. **** indicates p<0.0001 using one-way ANOVA followed by a Dunnett’s post hoc test. Error bars correspond to mean ± SEM, n=minimum 4.

Autophagy processes are altered in mIMC3 cells expressing the kAE1 R295H, S525F, and R589H dRTA mutants and in R607H knock-in kidney lysates

In mice expressing kAE1 R607H (the murine equivalent to human dRTA R589H substitution), a striking reduction in type-A intercalated cells was noted, and in the remaining cells, autophagy marker p62 and ubiquitin accumulated in these abnormally enlarged cells (Mumtaz et al., 2017). We therefore investigated the autophagy machinery in dRTA mutant mIMCD3 cells and in R607H knock-in (KI) mice. We first examined the ratio of autophagosome marker LC3BII protein relative to the total intensities of LC3BI and LC3BII as well as p62 levels. These experiments were performed at steady state, upon autophagy induction by starvation, or after autophagy inhibition by Bafilomycin (Baf) A1 (Figure 2A–C). Figure 2A–I shows a consistent increase in the ratio of LC3B II to total LC3B (I+II) in the mutant cells at steady state (Figure 2D), with starvation (Figure 2F) and with Baf A1 (Figure 2H) except for the kAE1 R295H mutant which was not significantly different from WT. This suggests an altered autophagy process in the mutant cells, in agreement with preliminary findings from Mumtaz and colleagues (Mumtaz et al., 2017). There was no significant difference in p62 abundance in mutant cells compared to WT at steady state and with starvation (Figure 2E and G). However, with Baf A1, R589H mutant cells had significantly lower p62 abundance compared to WT (Figure 2I). To confirm these findings, we next assessed the abundance of these markers in whole kidney lysates from the kAE1 R607H KI mice. We observed that the total LC3B abundance was significantly higher in homozygous KI mice (KI/KI) compared to WT, with no difference in p62 (Figure 2J–L). Overall, these results suggest an abnormal autophagy in mutant mIMCD3 cells and in kidneys of R607H KI mice. Given the lack of difference in phenotype between the recessive kAE1 R295H and kAE1 WT mIMCD3 cells, we focused the subsequent experiments on dominant kAE1 S525F and R589H mutant cells. Further investigations will be needed to understand the pathophysiology associated with the kAE1 R295H novel variant.

Figure 2
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Autophagy is upregulated in dRTA kAE1 mutants in vitro and in vivo.

. (A–C) Representative immunoblots of LC3B and p62 with corresponding actin abundance in kAE1 WT, R295H, S525F, and R589H mIMCD3 cells at steady state, under starvation (Starv) or 400 nM Bafilomycin A1 (Baf) treatment. Note that p62 and LC3B were detected on the same blot for (A) and (C); therefore, the same actin blot is shown for both panels. (D–I) Quantification of all immunoblots showing the ratio of LC3B II to total LC3B and p62. Error bars correspond to mean ± SEM, n=3–8. *p<0.05, ** p<0.01, ***p<0.005, ****p<0.001 using one-way ANOVA followed by a Tukey’s post hoc test. Immunoblots (J) and quantification (K, L) of LC3B and p62 abundance in kAE1 R607H KI mouse whole kidney lysates. Error bars correspond to mean ± SEM, n=minimum 5. ***p<0.005 using one-way ANOVA followed by a Tukey’s post hoc test.

Late autophagy steps are blocked in dRTA kAE1 mutant-expressing cells due to their alkaline intracellular pH

Given these preliminary findings of abnormal autophagy in dRTA mutant cells, we examined in more detail their autophagy machinery by transiently transfecting them with the eGFP-RFP-LC3 construct and monitoring the rate of autophagosome and autolysosome formation. In this assay, the green fluorescent protein (eGFP) fused to LC3 is quenched in the acidic environment of the autolysosome, while both eGFP and red fluorescent protein (RFP) fluoresce in vesicles in the neutral lumen of the autophagosome (Zhou et al., 2012; Kimura et al., 2007). To avoid the poor efficiency of transient transfection in polarized cells, experiments were conducted in sub-confluent cells, pending that the mutant proteins are present at the plasma membrane. We therefore performed cell surface biotinylations on 70–80% sub-confluent cells, which confirmed a robust plasma membrane abundance of both kAE1 R589H and S525F that was not significantly different from the WT protein (Figure 3A and B). Therefore, we next assessed the efficiency of the autophagy machinery in WT or dRTA mutant-expressing cells (Figure 3C–F). Focusing on cells expressing either kAE1 WT, kAE1 S525F, or R589H, we quantified the number RFP+ (red, acidic autolysosomes) and double eGFP+/RFP+ (yellow, not acidic autophagosomes) vesicles. kAE1 S525F mutant cells have significantly more autophagosomes than WT counterparts (Figure 3D), and both kAE1 S525F and R589H have significantly more autolysosomes than WT (Figure 3E). Figure 3F shows that both mutants had significantly more autophagosomes (yellow) than autolysosomes (red). This finding suggests an upregulation of autophagy and inhibition in the downstream steps of the process that involves the fusion of autophagosomes with the lysosome (Mizushima, 2018). As autolysosomes require luminal v-H+-ATPase-dependent acidification to efficiently clear cell debris (Hu et al., 2022), the higher intracellular pH seen in mutant cells (Figure 1F) may be detrimental to v-H+-ATPase full activity and impair proper autolysosomal acidification (Berezhnov et al., 2016). We therefore wondered whether chemically acidifying the pHi in mutant cells would rescue the autophagy machinery (Figure 3G–K). We first determined that incubation of mIMCD3 cells in 0.033 µM nigericin in cell culture medium at pH 6.6 for 2 hours acidified cytosolic pH to 6.9 without causing cell death (Figure 3—figure supplement 1). Next, we observed that chemically reducing pHi to 6.9 in mutant expressing cells reduced the ratio of LC3B II to total LC3B (Figure 3J) and the abundance of lysosomal-associated membrane protein 1 (LAMP1) in R589H cells (Figure 3K) to levels similar to WT cells at steady state. These findings suggest that abnormal autophagy in the mutant cells may be caused by their alkaline pHi, resulting from a reduced anion exchange activity of the mutant kAE1 protein.

Figure 3 with 1 supplement see all
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dRTA kAE1 mutants have more alkaline steady-state intracellular pH and altered autophagy flux.

(A) Representative immunoblots of cell surface biotinylation experiments in mIMCD3 cells expressing kAE1 WT or mutants (top panels), with control staining of plasma membrane marker Na+/K+-ATPase (middle panel) and intracellular marker actin (bottom panel). (B) Quantification of three independent cell surface biotinylation experiments. Data are represented by a single representative blot for each variant. n.s., not significant using one-way ANOVA. Error bars correspond to mean ± SEM, n=3. (C) Immunofluorescence staining in eGFP-RFP-LC3 transfected mIMCD3 cells expressing kAE1. GFP = green, RFP = red, kAE1=cyan, nuclei = dark blue (merge only). Scale bar = 2 μm. Graphical representation of number of yellow (autophagosomes) (D) and red (autolysosomes) (E) puncta per cell expressing kAE1. Error bars correspond to mean ± SEM, n=minimum 32. **p<0.01, *** p<0.005, ****p<0.001 using one-way ANOVA followed by a Tukey’s post hoc test. (F) Grouped graph of the number of yellow (autophagosomes) and red (autolysosomes) puncta per cell expressing kAE1, respectively. Note that the statistical analysis displayed only compared yellow and red groups for simplification. Error bars correspond to mean ± SEM, n=minimum 32. **p<0.01, ****p<0.001 using two-way ANOVA followed by a Sidak’s post hoc test. (G–I) Immunoblot of LC3B, LAMP1, and actin in kAE1 WT, S525F, and R589H mIMCD3 cells at steady state and under chemically reduced intracellular pH conditions. Graphical representation of the ratio of LC3B II to total LC3B ratio (J) or LAMP1 (K) at steady state versus at low pHi in mIMCD3 kAE1 WT, S525F, and R589H. Black circles indicate steady state cells and triangles indicate low pHi cells. Error bars correspond to mean ± SEM, n=3. ** indicates p<0.01 using two-way ANOVA followed by a Sidak’s post hoc test.

mIMCD3 cells expressing dRTA kAE1 mutants and R607H KI kidney tissues have abnormal lysosome number and size

The accumulation of autophagosomes and autolysosomes as seen above may suggest one or a combination of the following: an inability of autophagosomes to fuse with lysosomes and/or a defect in lysosomal degradative activity in the mutant cells (Button et al., 2017; Festa et al., 2018). We first examined the lysosomal degradative activity by assessing lysosomal protease Cathepsin B activity using Magic Red staining, a probe that fluoresces upon lysosomal protease cleavage (Figure 4A and B). In agreement with increased RFP+ vesicles (Figure 3E), the kAE1 S525F mutant cells had a significantly higher number of Magic Red-positive vesicles than WT, whereas the kAE1 R589H mutant cells had significantly larger Magic Red-positive vesicles, suggesting an accumulation of undigested material (de Araujo et al., 2020). To validate this finding in vivo, we performed immunostaining and quantified LAMP1-positive staining in ß1 ATPase-positive cells (a marker of ICs) in WT and R607H KI mouse kidney sections. The KI mice showed significantly more and larger LAMP1-positive vesicles compared to WT mice in both cortex and medulla (Figure 4C–F). We probed further into the lysosomal activity by quantifying lysosomal protease Cathepsin D (immature, intermediate, and mature) protein abundance by immunoblot in isolated primary murine A-ICs. Although the abundance of immature and intermediate cathepsin D did not differ between genotypes, the KI mice showed a significantly decreased abundance of mature cathepsin D (Figure 4—figure supplement 1). Thus, in line with in vitro findings, A-IC from homozygous R607H KI mice display relatively more and larger lysosomes with reduced active protease abundance than WT littermates, suggesting a lysosomal defect in the dRTA kAE1 mutant cells.

Figure 4 with 1 supplement see all
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dRTA kAE1 mutants have bigger or more lysosomes than WT in vitro and in vivo.

(A) Immunofluorescence images of kAE1 WT, S525F, and R589H mIMCD3 cells incubated with Magic Red substrate for 1 hour at 37°C in the dark. Green = kAE1, magenta = active lysosomes, blue = nuclei. Scale bar = 16 µm. (B) Graphical representation of number and size of active lysosomes per cell. Error bars correspond to mean ± SEM, n=minimum 30. ****p<0.0001 using one-way ANOVA followed by Tukey’s post hoc test. Immunofluorescence images of LAMP1 and ß1 ATPase in kidney cortex (C) or medulla (E) from kAE1 WT and R607H KI mice. Blue = nuclei, magenta = LAMP1 (lysosomes), yellow = ß1 ATPase, light blue ‘G’ indicates the location of a glomerulus. Scale bar = 8 μm. Graphical representation of the number and volume of LAMP1 vesicles in ß1 ATPase-positive cells in the kidney cortex (D) or medulla (F) of WT or R607H KI mice. Error bars correspond to mean ± SEM, n=60. ****p<0.001 using Student’s t-test.

dRTA kAE1 mutant cells have lower ATP production rate and abnormal mitochondrial content

Lysosomal degradation is highly dependent on a low luminal pH generated in part by the vacuolar-type H+-ATPase (Ratto et al., 2022) whose activity depends on ATP hydrolysis. We therefore analyzed the ATP production rate in mIMCD3 cells, specifically glycolysis and oxidative phosphorylation. We measured the oxygen consumption rate (OCR) (Figure 5A) and extracellular acidification rate (ECAR) (Figure 5B) in empty vector-transfected, kAE1 WT, or mutant cells. Both kAE1 S525F and R589H mutant cells had a lower ATP production rate compared to WT (Figure 5C). More specifically, the R589H mutant cells had a lower mitochondrial ATP production rate (Figure 5D), whereas the kAE1 S525F mutant cells exhibited a lower glycolytic ATP production rate (Figure 5E). With the mitochondria being the major ATP-producing organelles (Jonckheere et al., 2012), we assessed mitochondrial content by immunostaining of translocase of the outer membrane 20 (TOM20) both in vitro and in vivo. Both kAE1 S525F and R589H mutant cells have higher mitochondrial content compared to WT as determined by total overall intensity of TOM20-positive puncta (Figure 5F and G). In line with this result, although a decreased fluorescence intensity was observed in the cortex, there was a significantly higher TOM20 fluorescence intensity in medullary kidneys of homozygous R607H KI mutant mice compared to WT littermates (Figure 5H–K).

Figure 5
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dRTA kAE1 mutant cells have lower ATP production rate and abnormal mitochondrial content.

Oxygen consumption rate (OCR) (A) and extra cellular acidification rate (ECAR) (B) of empty vector (EV) transfected cells, kAE1 WT, S525F, or R589H mIMCD3 cells analyzed in a Seahorse XFe96 Extracellular Flux Analyzer with the ATP Rate Assay Test Kit. All cell lines, including EV-transfected cells, were incubated with doxycycline to eliminate a potential effect of doxycycline on measurements. (C) Graphical representation of the combination of ATP production rates from mitochondrial respiration (mitoATP) and glycolysis (glycoATP) of kAE1 WT, S525F, and R589H mIMCD3 cells measured in real-time following sequential injections of oligomycin and Rotenone + Antimycin-A. Error bars correspond to mean ± SEM, n=minimum. *p<0.05, ****p<0.0001 using one-way ANOVA followed by Tukey’s post hoc test. Graphical representations of mitochondrial respiration (D) and glycolytic ATP production (E) in kAE1 WT, S525F, and R589H mIMCD3 cells. Error bars correspond to mean ± SEM, n=minimum 8. **p<0.01, ****p<0.0001 using one-way ANOVA followed by Tukey’s post hoc test. (F) Immunofluorescence staining of TOM20 and kAE1 in kAE1 WT, S525F, and R589H mIMCD3 cells. Blue = nuclei, magenta = TOM20, green = kAE1. Scale bar = 8 µm. (G) Graphical representation of total TOM20 fluorescence intensity per cell expressing kAE1. Error bars correspond to mean ± SEM, n=minimum 40. ***p<0.001, ****p<0.0001 using one-way ANOVA followed by Tukey’s post hoc test. Immunofluorescence images of TOM20 and ß1 ATPase in kidney cortex (H) or medulla (J) of kAE1 R607H WT and KI mice exposed to a salt-depleted diet with an acid challenge (Mungara et al., 2024). Blue = nuclei, magenta = TOM20 (mitochondria), yellow = ß1 ATPase, light blue ‘G’ indicates the location of a glomerulus. Scale bar = 8 μm. Graphical representation of the total TOM20 fluorescence intensity in ß1 ATPase-positive cells in the cortex (I) or medulla (K) of the kidney. Error bars correspond to mean ± SEM, n=90. *p<0.05, ****p<0.0001 using Student’s t-test.

Discussion

In this study, we characterized three newly identified dRTA-causing kAE1 variations. Combining in vivo and in vitro studies, we demonstrated that reduced transport activity of the kAE1 mutants correlated with increased cytosolic pH, reduced ATP synthesis, attenuated downstream autophagic pathways, and lysosomal dysfunction, pertaining to the fusion of autophagosomes and lysosomes and/or lysosomal degradative activity (see summary in Tables 1 and 2).

Table 1
Summary of findings in dRTA kAE1 variant expressing cells compared to WT.
dRTA variantTransport activityIntracellular pHLC3B accumulationAutophagy fluxCellular lysosome sizeCellular lysosome numberCellular mitochondrial abundanceRescued autophagy
R295HUnchangedUnchangedUnchangedN/AN/AN/AN/AN/A
S525FReducedIncreasedIncreasedBlocked downstreamUnchangedIncreasedIncreasedYes
R589HSlightly ReducedIncreasedIncreasedBlocked downstreamIncreasedUnchangedIncreasedYes

  1. N/A, not applicable.

Table 2
Summary of findings in intercalated cells from dRTA R607H knock-in (KI) relative to WT mice.
GenotypeLC3B accumulationIntercalated cell lysosome sizeIntercalated cell lysosome numberIntercalated cell mitochondrial abundance
R607H KI/KIIncreased total LC3BIncreasedIncreasedIncreased

In line with previous observations in mIMCD3 cells (Mumtaz et al., 2017), the kAE1 R295H, Y413H, and S525F mutants were properly localized to the basolateral membrane after polarization. When expressed in Madin-Darby canine kidney (MDCK) cells, other dRTA-causing kAE1 mutants such as dRTA R602H, G701D, V488M, deltaV850 variants exhibited a plasma membrane trafficking defect (Sawasdee et al., 2006; Yang et al., 2023; Deejai et al., 2022). In contrast, the kAE1 R589H mutant was correctly targeted to the plasma membrane (Mumtaz et al., 2017). Functionally, cells expressing the Y413H and S525F mutants exhibit about 60% reduction in chloride/bicarbonate exchange activity compared to kAE1 WT, similar to the previously characterized recessive G701D mutant but unlike the R295H mutant (Chu et al., 2013). Therefore, the mechanism causing dRTA remains unclear in the case of the newly identified recessive R295H variant. Additionally, the kAE1 Y413H variant exhibited a shorter half-life than the WT counterpart, likely explaining dRTA, and thus was not further investigated. These findings add to the growing list of SLC4A1 gene variations causing dRTA.

We next investigated the roots of the altered autophagy briefly reported in R607H KI mice (Mumtaz et al., 2017) using mIMCD3 cells and whole kidney lysates. In the kidneys of the KI mice, a decrease in the number of A-IC, accumulation of p62 and ubiquitinylated proteins, and enlarged remaining A-ICs suggested altered autophagy processes in dRTA mutant cells and in homozygous R607H KI mice (Mumtaz et al., 2017; Chu et al., 2013). During the autophagy process, LC3B I (a marker for autophagosomes) is converted to lipidated LC3B II (Dhingra et al., 2018) and p62 aggregates to facilitate the degradation of ubiquitinated proteins within the autophagosome complex (Huang et al., 2023). In mIMCD3 cells expressing dRTA kAE1 S525F and R589H variants, LC3B lipidation was increased compared to WT, an increase that persisted with both Baf A1 treatment and starvation. Although opposite effects were expected under inhibition or induction of autophagy, such similar effect has been previously described. In the proximal tubule of obese mice, LC3B accumulation indicating a stagnated autophagy flux was observed with both chloroquine treatment and 24-hour starvation (Yamamoto et al., 2017). Similarly, in NRK-52E cells, a disruption of the autophagy machinery in high cadmium-stressed cells resulted in LC3B II accumulation under either Baf A1 or rapamycin (an autophagy inducer) treatment (Lee et al., 2017). Although LC3B II is elevated during both increased autophagy flux and disrupted autophagy, we did not observe significant accumulation of p62 in mIMCD3 cells expressing dRTA mutants. p62 is specifically a marker of autophagy-mediated protein clearance (Brown et al., 2021; Mizushima et al., 2002; Klionsky et al., 2012). Therefore, p62 accumulation in R607H KI mouse kidney sections strongly suggests a compromised autophagy-mediated clearance, while the increased LC3B lipidation without significant changes in p62 in mIMCD3 cells points towards either an increased autophagic flux and/or a disrupted autophagy.

To obtain a clearer picture of the precise autophagic pathway altered in the dRTA mutants, we probed further into the different stages of autophagy and autophagy flux. We noted an accumulation of autophagosomes and autolysosomes in the S525F and R589H mutant cells. This was recapitulated in the R607H KI mice which showed significantly more and larger LAMP1-positive vesicles in both kidney cortex and medulla, suggesting a blockage in late steps of autophagy flux in both dRTA mutant cells and KI mice. Such blockage has been implicated in the pathophysiology of several diseases. In lysosomal storage disease, lysosome accumulation in proximal tubule cells is a key component in the pathways mediating epithelial dysfunction (Festa et al., 2018). In this study, restoring autophagy flux attenuated disease progression. Another study in SK-N-SH, RT4-D6P2T, and HeLa cells implicated autophagosome and lysosome accumulation in cellular toxicity associated with neurodegenerative diseases (Button et al., 2017). In agreement with altered lysosomal function, we also noted a greater abundance and size of active cathepsin B lysosomal protease vesicles in mIMCD3 cells. Increased cathepsin B activity affects lysosomal biogenesis, autophagy initiation, and cellular homeostasis (Liu et al., 2024). In the renal context, cathepsin B knockout mice demonstrated a higher resistance and quicker recovery from glomerular damage (Höhne et al., 2018), suggesting that cathepsin B accumulation may be detrimental to the cells. Increased cathepsin B abundance in the dRTA mutant cells also correlates with the accumulation of lysosomes. Overall, these findings suggest that the pathogenesis of dRTA in our in vitro and in vivo models involves an inhibition of autophagy flux at the downstream steps involving autophagosome-lysosome fusion and lysosomal protein clearance (Ballabio and Gieselmann, 2009; Eskelinen, 2006; Mizushima, 2018; de Araujo et al., 2020).

The question remained as to how these dRTA variants altered autophagy. The SLC4A1-3 gene family that includes AE1 are regulators of intracellular pH in different cell types (Thornell and Bevensee, 2015; Zhang et al., 2023; Romero et al., 2013). The reduced anion exchange activity in mIMCD3 cells expressing the R589H and S525F variants expectedly correlated with an increased pHi compared to WT counterparts. Given that pHi variations can impact autophagy (Berezhnov et al., 2016; Korolchuk et al., 2011; Heuser, 1989; Xu et al., 2011; Ratto et al., 2022), we wondered whether this was the case for cells expressing kAE1 dRTA mutants. We observed that an acidic pHi in mutant cells restored autophagy levels similar to WT. Previous studies reported more perinuclear localization of lysosomes and autophagosome-lysosome fusion in cells with an increased pHi (Korolchuk et al., 2011; Heuser, 1989). Although not examined in our study, an increase in intracellular pH due to starvation decreased the levels of lysosomal kinesin superfamily member KIF2 and ADP-ribosylation factor-like 8B (ARL8), which are responsible for redistributing lysosomes to the cell periphery. This reduction subsequently inhibited mTORC1, resulting in increased autophagosome synthesis and autophagosome-lysosome fusion (Korolchuk et al., 2011).

While an alkaline cytosolic pH partially explains the impairment in autophagy flux, a close relationship also exists between intracellular pH and cellular energy dynamics and metabolic stress, all of which are key regulators of autophagy (Mizushima and Komatsu, 2011). Therefore, it was plausible that the kAE1 variant-induced autophagy dysregulation occurs through a signaling pathway akin to that of energy deprivation-induced autophagy. This hypothesis is supported by our findings of reduced ATP production rate in dRTA kAE1 S525F and R589H mutant cells compared to kAE1 WT cells. We also found that both kAE1 S525F and R589H mutant cells have higher mitochondrial content compared to kAE1 WT cells. The increased mitochondrial content coupled with low ATP points towards improper mitochondrial function in dRTA variant cells. Low ATP levels as seen in dRTA mutant cells may impair autophagy, as was shown in human RPE cells (Schütt et al., 2012). ATP reduction in RPE cells led to complex mitochondrial changes such as structural disorganization, enzyme activity decline, and oxidative damage to mitochondrial components and DNA (Schütt et al., 2012). Similarly, in pancreatic islet cells, an alkaline pHi led to increased uptake of phosphate by mitochondria, accelerating the production of superoxide, promoting mitochondrial permeability transition, and inducing translational attenuation due to endoplasmic reticulum stress, ultimately impairing insulin secretion (Nguyen et al., 2016). Overall, our data support that expression of the kAE1 variants increases pHi, which alters mitochondrial function and leads to reduced cellular energy levels that eventually attenuate energy-dependent autophagic pathways including autophagosome-lysosome fusion and lysosomal protein clearance.

In light of these observations, we postulated that correcting the alkaline pHi of dRTA mutant-expressing mIMCD3 cells will alleviate this blockage in autophagy flux. We observed that a chemically engineered pHi of 6.9 (Lyons et al., 1992) reduced LC3B II accumulation and LAMP1 abundance in mIMCD3 mutant cells to expression levels similar to that of WT cells at baseline. This suggests that a chemically reduced pHi facilitated protein clearance in the two dRTA mutant cells (Berezhnov et al., 2016; Korolchuk et al., 2011) as noted in other studies. In one such study, treatment of SH-SY5Y cells with FCCP and nigericin also acidified intracellular pH and triggered autophagy and mitophagy (Berezhnov et al., 2016). Similarly, acid loading in proximal tubular cells under chronic metabolic acidosis showed increased autophagic flux and mitophagy (Namba et al., 2014). These findings are in line with our results and establish a link between altered autophagy flux and the alkaline pHi of dRTA variant cells. Overall, our study provides one pathway (altered pHi) by which dRTA may arise. However, different variants induce different degrees of functional defects as seen in Figure 1F & G. The kAE1 R295H, the only reported amino acid substitution in the amino-terminal cytosol causing dRTA, does not affect the transporter’s function or pHi. Therefore, this variant may cause dRTA via a different pathway, for example, defective protein–protein interactions, than transport-defective S525F or partially inactive R589H variants.

In conclusion, our study established a strong relationship between the expression of defective kAE1 proteins, reduced mitochondrial activity, decreased autophagy, and impaired protein degradative flux. Whether this abnormal degradative pathway explains the premature loss of A-IC will need to be elucidated in further studies.

Materials and methods

Antibodies and chemicals

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Mouse anti-HA antibody (hemagglutinin, Biolegend, formerly Covance), mouse anti-β-actin antibody (Sigma Aldrich or anti-β-actin HRP clone 2F1-1 Biolegend cat#643807), mouse anti-LC3B antibody (Cell Signaling), mouse anti-IVF 12s antibody (Developmental Studies Hybridoma Bank), rat anti-ATP6V1B1 antibody (BiCell #20901), rabbit anti-mTOR antibody and phospho mTOR antibody (Cell Signaling), rabbit anti-4E-BP1 antibody and phospho 4E-BP1 (Ser65) antibody (Cell Signaling), mouse anti-p62 antibody (Abcam), mouse anti-p53 antibody (Cell Signaling), rabbit anti-Cleaved caspase 3 antibody (Cell Signaling), mouse monoclonal anti Na+/K+-ATPase H-3 antibody (Santa Cruz Biotechnology, Dallas, TX), goat anti-mouse antibody horseradish peroxidase conjugated (HRP) (Cell Signaling Technology), Cy3-conjugated donkey anti-mouse antibody, anti-rabbit and anti-goat antibodies (Jackson Immunoresearch), X-tremeGENE.

Newly identified SLC4A1 variations from dRTA patients

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The patient carrying the R295H mutation was a boy carrying the variation in the homozygous state, whose genetic diagnosis was made at the age of 5, following growth retardation of –2 SD for both weight and height, with bicarbonate at 18 mmol/L, potassium at 2.8 mmol/L, chloridemia at 94 mmol/L, calcemia at 2.55 mmol/L, and a urinary pH of 7.5. He also had a history of a pyeloureteral junction syndrome that was surgically managed at the age of 3. The R295H dRTA variation is a nonsense homozygous substitution characterized by a replacement of guanine (G) on position 884 by adenine (A) in the coding sequence. It has an allelic frequency of 0.14% in the European population.

For the Y413H variant, the patient was a female diagnosed at 1 month old, with a urinary pH of 7.5, evidence of nephrocalcinosis, and failure to thrive. The S525F variant has been previously reported (Bertocchio et al., 2020), but in brief, the patient was a 13-year-old female with plasma pH of 7.25, plasma bicarbonate at 15.3 mmol/L who also presented with polyurethral junction syndrome, nephrocalcinosis, and nephrolithiasis since childhood. The Y413H and S525F dRTA variations are nonsense heterozygous substitutions characterized by a replacement of thymine (T) at position 1237 by cytosine (C) and a replacement of cytosine (C) at position 1574 by thymine (T), respectively. The R589H dRTA variation has been previously described (Mumtaz et al., 2017). No follow-up data were available for all patients.

Mice

Transgenic mice carrying the R607H knockin (KI) mutation (murine equivalent to human R589H mutation) were previously described (Mumtaz et al., 2017). Homozygous mice used throughout the study display incomplete dRTA with alkaline urine without metabolic acidosis at baseline as previously reported (Mumtaz et al., 2017). Homozygous mice or wild-type (WT) littermates were fed a standard rodent chow (Picolab Rodent Diet 20 # 5053, LabDiet, ST. Louis, MO, USA) or for Figure 5H-K, a salt-depleted diet with acid challenge as previously reported (Mungara et al., 2024) with adequate and constant water supply, and maintained on a 12hour light and dark cycle throughout their lifespan.

Cell lines, transfections, and viral infection

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Mouse inner medullary collecting duct (mIMCD) cells (ATCC# CRL2123) were used for preparing kAE1 wild type and mutant cell lines. The pLVX TRE3G kAE1 construct was generated from the shuttling of human kAE1 cDNA with an external hemagglutinin (HA) epitope in position 557 (on eAE1) into pLVX-TRE3G plasmid (Clontech) (Lashhab et al., 2019). This construct encodes a protein described as kAE1 throughout this paper. The kAE1 S525F and R589H mutants were generated with Q5 site-directed mutagenesis. All plasmids were introduced into the mIMCDs using a viral single-shot packaging kit (Clontech).

Mouse intercalated cell isolation and tissue homogenate preparation

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Kidney tissue homogenates were prepared as previously described (Mungara et al., 2025). Briefly, after decapsulation, freshly dissected kidneys were homogenized in cold lysis buffer (0.3 M sucrose, 25 mM imidazole, 1 mM EDTA, 8.5 µM leupeptin, 1 mM PMSF), and vortexed over 1 hour every 15 min. The homogenates were then centrifuged at 14,000 rpm for 15 minutes at 4°C prior to measurement of protein concentration by Bicinchoninic Acid Protein Assay. Primary intercalated cells were prepared from homozygous kAE1 R607H transgenic mice. After cardiac perfusion with PBS, heparin, and collagenase B (Sigma Aldrich), kidneys were homogenized by MACS dissociation and intercalated cells enriched using CD 117 magnetic sorting (Miltenyi Biotec) as previously described (Saxena et al., 2021). During the selection, intercalated cells were kept in MACS buffer (PBS, 2 mM EDTA, and 0.5% FBS). Cells were lysed with RIPA lysis buffer (2 mM EDTA, 2% deoxycholate, 0.3 M NaCl, 20 mM Tris/HCl pH 7.5, 2% Triton X-100, 0.2% SDS, pH 7.4), supplemented with complete EDTA-free protease inhibitors, and PhoSTOP phosphatase inhibitor (Roche), PMSF, pepstatin, leupeptin, and aprotinin. An aliquot was saved for bicinchoninic acid assay to determine protein concentration, and remaining lysates were kept in Laemmli buffer at –20°C for immunoblotting.

Bicarbonate transport assay

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This assay has been previously described (Sterling and Casey, 1999). Briefly, confluent kAE1 WT-HA or mutant mIMCDs cells grown on coverslips were incubated with 1 μg/mL doxycycline (Sigma-Aldrich) for 18–24 hours at 37°C to induce kAE1 expression. They were then incubated with 2',7'-Bis-(2-Carboxyethyl)–5-(and-6)-Carboxyfluorescein, Acetoxymethyl Ester (BCECF–AM, Thermo Scientific), a fluorophore which excites at 440 and 490 nm and emits 510 nm wavelength for 30 minutes at 37°C. Using a fluorometer from Photon Technologies International (PTI) (London, Ontario, Canada), coverslips were perfused with NaCl-based Ringer’s buffer (5 mM glucose, 5 mM potassium gluconate, 1 mM calcium gluconate, 1 mM magnesium sulfate, 10 mM HEPES, 2.5 mM sodium dihydrogen phosphate, 25 mM sodium bicarbonate, 140 mM sodium chloride) for 5–10 minutes. Once stable, initial fluorescence (corresponding to steady-state pHi) was recorded for the first 30 seconds before switching to chloride-free containing sodium gluconate-based Ringer’s buffer of same osmolality. BCECF fluorescence was calibrated by perfusing cells with different pH buffers (6.5, 7, 7.5) in the presence of 10 mM nigericin. The Ringer’s buffers were continuously bubbled with an air:CO2 mixture (19:1), providing 5% CO2. Transport rates of the cells were determined by linear regression of the initial fluorescence variations (over the first 60 seconds), normalized to pH calibration measurements. All measurements were done using PTI FelixGX software.

Cell treatments and immunoblotting

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For autophagy experiments, kAE1 WT or mutant cells were seeded to 70% confluency on 10 cm culture plates and treated with 1 μg/mL doxycycline (Sigma-Aldrich) for 48 hours. Cells were then either treated with 400 nM bafilomycin A1 for 4 hours to inhibit autophagy or with Hanks balanced salt solution (HBSS, Gibco) to starve cells and induce autophagy or given no treatment. To chemically modify pHi of cells, 90–100% confluent cells were treated with 1 µg/mL of doxycycline (Sigma-Aldrich) overnight. Cells were then incubated in Ringer’s buffer with pH 6.6, supplemented with 0.03 μM nigericin with a final potassium concentration of 168 mM for 2 hours at 37°C. Steady-state cells were incubated in normal pH media without nigericin prior to lysis. Under treated conditions, pHi was similar to pHe (Figure 3—figure supplement 1). Cells were lysed with RIPA lysis buffer (1% deoxycholate, 1 mM EDTA, 0.15 M NaCl, 0.1% SDS, 10 mM TRIS/HCl [pH 7.5], 1% Triton X-100) with phosphatase inhibitors (cat. no. 04906837001; Roche PhosSTOP) and protease inhibitors (cat. no. 04693159001; Roche Complete Tablets, Mini EDTA-free) and stored at −20°C with or without 2x Laemmli buffer. The aliquot without Laemmli buffer was used for a bicinchoninic acid (BCA) assay to determine protein concentration. Following the BCA, 10–30 mg of total protein was loaded on SDS-PAGE gels. Proteins were transferred to PVDF membranes and antibodies listed above were used for detecting the proteins of interest. Primary antibodies were diluted in 1% milk and incubated on membranes overnight at 4°C followed by secondary antibodies linked with horseradish peroxidase (HRP) for 1 hour at room temperature. Protein detection was done with the Enhanced Chemiluminescence reagent (ECL Prime, Invitrogen), and a BioRad Imager. The ImageLab software (BioRad) was utilized for the quantification of relative band intensities.

Cell surface biotinylation assay

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mIMCD3 cells stably expressing kAE1 WT, S525F, or R589H were seeded to 70–80% confluency. The cells were incubated with sulfo-N-hydroxysuccinimide-SS-biotin (Thermo cat.# 21331) (1.5 mg/mL in ice-cold PBS) for an hour at 4°C, quenched with 100 mM glycine and lysed with RIPA lysis buffer, supplemented with complete EDTA-free protease inhibitors, and PhoSTOP phosphatase inhibitor (Roche), PMSF, pepstatin, leupeptin, and aprotinin. Total protein levels were measured by BCA, and an aliquot was saved as ‘Total’ fraction. 450 mg of each lysate was subsequently incubated with 100 μL streptavidin slurry beads for 1 hour on a rocker at 4°C. Following centrifugation, the supernatant was collected, and an aliquot kept as the ‘unbiotinylated’ fraction. After six washes, the beads were resuspended in 50 μL of 2X Laemmli buffer and incubated at room temperature for 30 minutes. The eluted biotinylated proteins were subsequently collected by centrifugation (‘Biotinylated’ fraction). The biotinylated fraction (45 μL) was loaded on SDS-PAGE gel for immunoblot analysis along with 3 μg of the Total fraction and a matched volume of unbound fraction per well. In addition to anti-HA antibody, the blots were probed for actin to ensure cell membrane integrity was intact during the biotinylation procedure, and for Na+/K+-ATPase as cell surface control.

Magic Red assay

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80% confluent kAE1 WT or mutant mIMCD3 cells were treated with 1 μg/mL doxycycline (Sigma-Aldrich) for 48 hours to induce kAE1 expression. Different treatments, including a 4-hour incubation with 400 nM bafA1 to inhibit autophagy, a 2-hour starvation in HBSS to induce autophagy, or no treatment (steady state), were applied. Cells were then incubated with 1% Magic Red reagent (ImmunoChemistry Technologies) in DMEM-F12 medium at 37°C in the dark for 30–60 minutes. Cells were then fixed with 4% PFA, quenched with 100 mM glycine, permeabilized with 0.2% Triton X-100, blocked with 1% BSA, and incubated with mouse anti-HA primary antibody and donkey anti-mouse Alexa Fluor 488 conjugated secondary antibody for 30 minutes each. Cells were then incubated with 4′,6-diamidino-2-phenylindole (DAPI) for 5 minutes before mounting using DAKO Mounting Medium (Agilent Technologies). A WaveFX confocal microscope was used to image the slides, and the images were analyzed blindly using the Fiji software.

Autophagy flux assay

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kAE1 WT-HA or mutant mIMCD3 cells seeded to 70% confluency in a 6-well plate on coverslips were transiently transfected with the eGFP-RFP-LC3 cDNA construct (kind gift from Dr. Goping, Department of Biochemistry, University of Alberta) using the X-tremeGENE HP DNA transfection reagent (Roche). 4 hours after transfection, the cells were incubated with 1 μg/mL doxycycline for 48 hours at 37°C to induce kAE1 expression. Following this incubation, cells were incubated with blocking medium, mouse anti-HA primary antibody (1:200), and donkey anti-mouse Alexa Fluor 649 (Jackson ImmunoResearch). Hoechst stain (ImmunoChemistry Technologies) was used to stain cellular nuclei. A WaveFX confocal microscope together with the Velocity and Fiji software was used to capture and analyze images.

Assessment of mitochondrial content

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kAE1 WT-HA or mutant mIMCD3 cells seeded to 50% confluency in a 6-well plate on coverslips were incubated with 1 μg/mL doxycycline for 48 hours at 37°C and overnight in complete medium with no antibiotics. Cells were then fixed with 4% PFA, quenched with 100 mM glycine, permeabilized with 0.2% Triton X-100, blocked with 1% BSA, and incubated with mouse anti-HA and rabbit anti-TOM20 primary antibodies and then with donkey anti-mouse Alexa Fluor 488 and anti-rabbit Cy3 conjugated secondary antibodies. Cells were then incubated with DAPI for 5 minutes before mounting using DAKO Mounting Medium (Agilent Technologies). A WaveFX confocal microscope was used to image the slides, and the images were analyzed blindly using the Fiji software.

Metabolic flux analysis

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kAE1 WT-HA or mutant mIMCD3 cells were treated with 1 μg/mL doxycycline for 48 hours followed by an overnight incubation in complete media with no antibiotics and cells seeded at 2 × 104 cells per well in Seahorse XFe 96-well plates overnight to form a uniform monolayer. On the day of assay, culture medium was replaced with XF DMEM Medium pH 7.4 (103575-100, Agilent Technologies) with glucose (10 mM), pyruvate (1 mM), and L-glutamine (2 mM) and incubated in a non-CO2, 37°C incubator for 1 hour prior to their placement into the XFe96 Analyzer. Using the ATP production rate assay kit (#103592-100, Agilent Technologies) and XF cell Mito Stress Test kit (#103015-100, Agilent Technologies), metabolic indices were obtained from the Seahorse XFe96 Analyzer following manufacturer’s procedures previously described (Sawasdee et al., 2010). The total ATP rate is the sum of ATP production rate from both glycolysis and oxidative phosphorylation. Glycolysis releases protons in a 1:1 ratio with ATP; hence, the glycolytic ATP rate is calculated from the glycolytic proton efflux rate (glycoPER). GlycoPER is determined by subtracting respiration-linked proton efflux from total proton efflux by inhibiting complex I and III. The empty vector transfected cells provided a control for a potential effect of doxycycline on measurements. Oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were measured at various time points at basal state followed by injections of oligomycin (1.5 μM) and Rotenone + Antimycin A (0.5 μM).

Tissue preparation and immunostaining of kidney sections

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Kidneys collected after perfusion were stored in 4% PFA overnight at 4°C. The PFA solution was switched to 15% sucrose for 2 hours and then transferred to 30% sucrose solution overnight at 4°C. Thereafter, kidneys were fixed in O.C.T (Tissue-Tek) and snap frozen in liquid nitrogen. These tissues were stored at –80°C until cryo-sectioning. Ten (10) micron tissue sections were fixed on a charged glass slide (Thermo Fisher) and used immediately or stored at –80°C until immunostaining. For immunostaining, the slices were first air-dried for 20 minutes, washed with PBS for 5 minutes, and fixed with 4% PFA for 20 minutes at 4°C. The sections were quenched with 100 mM glycine for 15 minutes, permeabilized, and blocked with 5% or 10% serum in 0.2% Triton in PBS for 1 hour at room temperature. Slices were incubated in primary antibody diluted in 5% or 10% serum overnight at 4°C followed by secondary antibody diluted in 5% or 10% serum for 1 hour at room temperature. Slices were washed with 0.1% Tween 20 in PBS and incubated with DAPI for 5 minutes at room temperature, mounted with DAKO mounting medium, and sealed. Slides were air-dried and then stored at –20°C. Note that kidney sections analyzed in Figure 5H–K were obtained from mice fed a ‘salt-depletion with acid load’ diet consisting of a low sodium and chloride diet for 8 days, complemented with 0.28 M NH4Cl with 0.5% sucrose in drinking water for six additional days as previously described (Escobar et al., 2016). This diet triggered a metabolic acidosis, significantly lower plasma bicarbonate with a more alkaline urine in the homozygous KI mice compared to WT littermates.

Confocal imaging and image analysis

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Immunofluorescent imaging was done with a WaveFX confocal microscope (Quorum Technologies, Guelph, Ontario, Canada) powered by a Volocity software (Quorum Technologies). Images were taken with ×40 oil immersion objective with z-stacks at 0.5 µm intervals. Quantitative image analysis was performed using the Volocity analysis software or by open-source cell image analysis software CellProfiler (Stirling et al., 2021) and Fiji (Schindelin et al., 2012).

Image analysis

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Cell profiler was used to analyze TOM20 staining in mIMCD3 cells. After converting the three-channel RGB images to grayscale using the split method, we manually outlined each cell in the channel corresponding to kAE1 staining and inputted it back into the pipeline. The objects were then converted to a binary image and the TOM20 channel was used as the input channel to measure intensity of TOM20 staining in the manually outlined objects. The raw data, including the sum of TOM20 pixel intensity per cell, were then analyzed using GraphPad Prism software. A minimum of 30 cells were analyzed.

Fiji software was used to analyze images from Magic Red staining and autophagy flux experiment. After each multichannel image was opened and merged in Fiji, the ‘multi point’ tool was used to label all regions of interest. Freehand selection tool was used to manually draw the outline of all selected regions of interest, followed by the ‘Analyze’ command to extract number and size of puncta in pixels. Pixel values were then converted to microns and data analysis was completed using GraphPad Prism. A minimum of 30 cells was analyzed.

Volocity software was used for analysis of kidney sections. From B1 H+-ATPase-positive single cells cropped from confocal images of medullary or cortical mouse kidney sections, the channel of interest was used to find objects using the ‘Find objects’ command. Refinement within the selection was made based on object size. The minimum object size thresholds were 0.016 μm2 for LAMP1 puncta and 0.02 μm2 for TOM20 staining. This was then labeled as ‘population one’. From population one, touching objects were separated using a size guide of 0.02 μm2 for LAMP1 puncta only with the ‘Separate touching objects’ function. For TOM20 staining, all RFP-positive stain within individual cells was characterized under one mask without separating touching objects. The minimum object size was set to 0.02 mm2 and everything less than that was considered background staining. The sum of TOM20 fluorescence intensity per cell was collected and analyzed using GraphPad Prism. For LAMP1 images, an exclusion criterion removing objects lesser than or equal to 0.02 mm2 was used to remove small background objects. Once the regions of interest in the image were properly outlined, data, including number of puncta, intensity of puncta, area/ volume of puncta, among other measurements, were exported and data analyzed with GraphPad Prism. A minimum of 60 cells was analyzed.

Statistical analysis

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All the experiments were independently repeated a minimum of three times. Experimental results were analyzed using the GraphPad Prism software and are summarized as mean ± SEM. All statistical comparisons were made using unpaired Student’s t-test or one/two-way ANOVA followed by a post hoc test as indicated in figure legends. A p-value <0.05 was considered statistically significant. All datasets were assessed for normality, and outliers identified by Prism were excluded.

Data availability

Source Data (including Western Blot source data) are available at: https://doi.org/10.5061/dryad.2bvq83c4f.

The following data sets were generated
    1. Essuman G
    2. Rizvi M
    3. Almomani E
    4. Ullah SAKM
    5. Hasib SMA
    6. Chelangarimiyandoab F
    7. Mungara P
    8. Schmitt MJ
    9. Hureaux M
    10. Vargas-Poussou R
    11. Touret N
    12. Cordat E
    (2026) Dryad Digital Repository
    Data: SLC4A1 mutations that cause distal renal tubular acidosis alter cytoplasmic pH and cellular autophagy.
    https://doi.org/10.5061/dryad.2bvq83c4f

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    101. Brunetti-Pierri N
    102. Brunk UT
    103. Bulman DE
    104. Bultman SJ
    105. Bultynck G
    106. Burbulla LF
    107. Bursch W
    108. Butchar JP
    109. Buzgariu W
    110. Bydlowski SP
    111. Cadwell K
    112. Cahová M
    113. Cai D
    114. Cai J
    115. Cai Q
    116. Calabretta B
    117. Calvo-Garrido J
    118. Camougrand N
    119. Campanella M
    120. Campos-Salinas J
    121. Candi E
    122. Cao L
    123. Caplan AB
    124. Carding SR
    125. Cardoso SM
    126. Carew JS
    127. Carlin CR
    128. Carmignac V
    129. Carneiro LAM
    130. Carra S
    131. Caruso RA
    132. Casari G
    133. Casas C
    134. Castino R
    135. Cebollero E
    136. Cecconi F
    137. Celli J
    138. Chaachouay H
    139. Chae HJ
    140. Chai CY
    141. Chan DC
    142. Chan EY
    143. Chang RCC
    144. Che CM
    145. Chen CC
    146. Chen GC
    147. Chen GQ
    148. Chen M
    149. Chen Q
    150. Chen SSL
    151. Chen W
    152. Chen X
    153. Chen X
    154. Chen X
    155. Chen YG
    156. Chen Y
    157. Chen Y
    158. Chen YJ
    159. Chen Z
    160. Cheng A
    161. Cheng CHK
    162. Cheng Y
    163. Cheong H
    164. Cheong JH
    165. Cherry S
    166. Chess-Williams R
    167. Cheung ZH
    168. Chevet E
    169. Chiang HL
    170. Chiarelli R
    171. Chiba T
    172. Chin LS
    173. Chiou SH
    174. Chisari FV
    175. Cho CH
    176. Cho DH
    177. Choi AMK
    178. Choi D
    179. Choi KS
    180. Choi ME
    181. Chouaib S
    182. Choubey D
    183. Choubey V
    184. Chu CT
    185. Chuang TH
    186. Chueh SH
    187. Chun T
    188. Chwae YJ
    189. Chye ML
    190. Ciarcia R
    191. Ciriolo MR
    192. Clague MJ
    193. Clark RSB
    194. Clarke PGH
    195. Clarke R
    196. Codogno P
    197. Coller HA
    198. Colombo MI
    199. Comincini S
    200. Condello M
    201. Condorelli F
    202. Cookson MR
    203. Coombs GH
    204. Coppens I
    205. Corbalan R
    206. Cossart P
    207. Costelli P
    208. Costes S
    209. Coto-Montes A
    210. Couve E
    211. Coxon FP
    212. Cregg JM
    213. Crespo JL
    214. Cronjé MJ
    215. Cuervo AM
    216. Cullen JJ
    217. Czaja MJ
    218. D’Amelio M
    219. Darfeuille-Michaud A
    220. Davids LM
    221. Davies FE
    222. De Felici M
    223. de Groot JF
    224. de Haan CAM
    225. De Martino L
    226. De Milito A
    227. De Tata V
    228. Debnath J
    229. Degterev A
    230. Dehay B
    231. Delbridge LMD
    232. Demarchi F
    233. Deng YZ
    234. Dengjel J
    235. Dent P
    236. Denton D
    237. Deretic V
    238. Desai SD
    239. Devenish RJ
    240. Di Gioacchino M
    241. Di Paolo G
    242. Di Pietro C
    243. Díaz-Araya G
    244. Díaz-Laviada I
    245. Diaz-Meco MT
    246. Diaz-Nido J
    247. Dikic I
    248. Dinesh-Kumar SP
    249. Ding WX
    250. Distelhorst CW
    251. Diwan A
    252. Djavaheri-Mergny M
    253. Dokudovskaya S
    254. Dong Z
    255. Dorsey FC
    256. Dosenko V
    257. Dowling JJ
    258. Doxsey S
    259. Dreux M
    260. Drew ME
    261. Duan Q
    262. Duchosal MA
    263. Duff K
    264. Dugail I
    265. Durbeej M
    266. Duszenko M
    267. Edelstein CL
    268. Edinger AL
    269. Egea G
    270. Eichinger L
    271. Eissa NT
    272. Ekmekcioglu S
    273. El-Deiry WS
    274. Elazar Z
    275. Elgendy M
    276. Ellerby LM
    277. Eng KE
    278. Engelbrecht AM
    279. Engelender S
    280. Erenpreisa J
    281. Escalante R
    282. Esclatine A
    283. Eskelinen EL
    284. Espert L
    285. Espina V
    286. Fan H
    287. Fan J
    288. Fan QW
    289. Fan Z
    290. Fang S
    291. Fang Y
    292. Fanto M
    293. Fanzani A
    294. Farkas T
    295. Farré JC
    296. Faure M
    297. Fechheimer M
    298. Feng CG
    299. Feng J
    300. Feng Q
    301. Feng Y
    302. Fésüs L
    303. Feuer R
    304. Figueiredo-Pereira ME
    305. Fimia GM
    306. Fingar DC
    307. Finkbeiner S
    308. Finkel T
    309. Finley KD
    310. Fiorito F
    311. Fisher EA
    312. Fisher PB
    313. Flajolet M
    314. Florez-McClure ML
    315. Florio S
    316. Fon EA
    317. Fornai F
    318. Fortunato F
    319. Fotedar R
    320. Fowler DH
    321. Fox HS
    322. Franco R
    323. Frankel LB
    324. Fransen M
    325. Fuentes JM
    326. Fueyo J
    327. Fujii J
    328. Fujisaki K
    329. Fujita E
    330. Fukuda M
    331. Furukawa RH
    332. Gaestel M
    333. Gailly P
    334. Gajewska M
    335. Galliot B
    336. Galy V
    337. Ganesh S
    338. Ganetzky B
    339. Ganley IG
    340. Gao FB
    341. Gao GF
    342. Gao J
    343. Garcia L
    344. Garcia-Manero G
    345. Garcia-Marcos M
    346. Garmyn M
    347. Gartel AL
    348. Gatti E
    349. Gautel M
    350. Gawriluk TR
    351. Gegg ME
    352. Geng J
    353. Germain M
    354. Gestwicki JE
    355. Gewirtz DA
    356. Ghavami S
    357. Ghosh P
    358. Giammarioli AM
    359. Giatromanolaki AN
    360. Gibson SB
    361. Gilkerson RW
    362. Ginger ML
    363. Ginsberg HN
    364. Golab J
    365. Goligorsky MS
    366. Golstein P
    367. Gomez-Manzano C
    368. Goncu E
    369. Gongora C
    370. Gonzalez CD
    371. Gonzalez R
    372. González-Estévez C
    373. González-Polo RA
    374. Gonzalez-Rey E
    375. Gorbunov NV
    376. Gorski S
    377. Goruppi S
    378. Gottlieb RA
    379. Gozuacik D
    380. Granato GE
    381. Grant GD
    382. Green KN
    383. Gregorc A
    384. Gros F
    385. Grose C
    386. Grunt TW
    387. Gual P
    388. Guan JL
    389. Guan KL
    390. Guichard SM
    391. Gukovskaya AS
    392. Gukovsky I
    393. Gunst J
    394. Gustafsson AB
    395. Halayko AJ
    396. Hale AN
    397. Halonen SK
    398. Hamasaki M
    399. Han F
    400. Han T
    401. Hancock MK
    402. Hansen M
    403. Harada H
    404. Harada M
    405. Hardt SE
    406. Harper JW
    407. Harris AL
    408. Harris J
    409. Harris SD
    410. Hashimoto M
    411. Haspel JA
    412. Hayashi S
    413. Hazelhurst LA
    414. He C
    415. He YW
    416. Hébert MJ
    417. Heidenreich KA
    418. Helfrich MH
    419. Helgason GV
    420. Henske EP
    421. Herman B
    422. Herman PK
    423. Hetz C
    424. Hilfiker S
    425. Hill JA
    426. Hocking LJ
    427. Hofman P
    428. Hofmann TG
    429. Höhfeld J
    430. Holyoake TL
    431. Hong MH
    432. Hood DA
    433. Hotamisligil GS
    434. Houwerzijl EJ
    435. Høyer-Hansen M
    436. Hu B
    437. Hu CAA
    438. Hu HM
    439. Hua Y
    440. Huang C
    441. Huang J
    442. Huang S
    443. Huang WP
    444. Huber TB
    445. Huh WK
    446. Hung TH
    447. Hupp TR
    448. Hur GM
    449. Hurley JB
    450. Hussain SNA
    451. Hussey PJ
    452. Hwang JJ
    453. Hwang S
    454. Ichihara A
    455. Ilkhanizadeh S
    456. Inoki K
    457. Into T
    458. Iovane V
    459. Iovanna JL
    460. Ip NY
    461. Isaka Y
    462. Ishida H
    463. Isidoro C
    464. Isobe K
    465. Iwasaki A
    466. Izquierdo M
    467. Izumi Y
    468. Jaakkola PM
    469. Jäättelä M
    470. Jackson GR
    471. Jackson WT
    472. Janji B
    473. Jendrach M
    474. Jeon JH
    475. Jeung EB
    476. Jiang H
    477. Jiang H
    478. Jiang JX
    479. Jiang M
    480. Jiang Q
    481. Jiang X
    482. Jiang X
    483. Jiménez A
    484. Jin M
    485. Jin S
    486. Joe CO
    487. Johansen T
    488. Johnson DE
    489. Johnson GVW
    490. Jones NL
    491. Joseph B
    492. Joseph SK
    493. Joubert AM
    494. Juhász G
    495. Juillerat-Jeanneret L
    496. Jung CH
    497. Jung YK
    498. Kaarniranta K
    499. Kaasik A
    500. Kabuta T
    501. Kadowaki M
    502. Kagedal K
    503. Kamada Y
    504. Kaminskyy VO
    505. Kampinga HH
    506. Kanamori H
    507. Kang C
    508. Kang KB
    509. Kang KI
    510. Kang R
    511. Kang YA
    512. Kanki T
    513. Kanneganti TD
    514. Kanno H
    515. Kanthasamy AG
    516. Kanthasamy A
    517. Karantza V
    518. Kaushal GP
    519. Kaushik S
    520. Kawazoe Y
    521. Ke PY
    522. Kehrl JH
    523. Kelekar A
    524. Kerkhoff C
    525. Kessel DH
    526. Khalil H
    527. Kiel J
    528. Kiger AA
    529. Kihara A
    530. Kim DR
    531. Kim DH
    532. Kim DH
    533. Kim EK
    534. Kim HR
    535. Kim JS
    536. Kim JH
    537. Kim JC
    538. Kim JK
    539. Kim PK
    540. Kim SW
    541. Kim YS
    542. Kim Y
    543. Kimchi A
    544. Kimmelman AC
    545. King JS
    546. Kinsella TJ
    547. Kirkin V
    548. Kirshenbaum LA
    549. Kitamoto K
    550. Kitazato K
    551. Klein L
    552. Klimecki WT
    553. Klucken J
    554. Knecht E
    555. Ko BCB
    556. Koch JC
    557. Koga H
    558. Koh JY
    559. Koh YH
    560. Koike M
    561. Komatsu M
    562. Kominami E
    563. Kong HJ
    564. Kong WJ
    565. Korolchuk VI
    566. Kotake Y
    567. Koukourakis MI
    568. Kouri Flores JB
    569. Kovács AL
    570. Kraft C
    571. Krainc D
    572. Krämer H
    573. Kretz-Remy C
    574. Krichevsky AM
    575. Kroemer G
    576. Krüger R
    577. Krut O
    578. Ktistakis NT
    579. Kuan CY
    580. Kucharczyk R
    581. Kumar A
    582. Kumar R
    583. Kumar S
    584. Kundu M
    585. Kung HJ
    586. Kurz T
    587. Kwon HJ
    588. La Spada AR
    589. Lafont F
    590. Lamark T
    591. Landry J
    592. Lane JD
    593. Lapaquette P
    594. Laporte JF
    595. László L
    596. Lavandero S
    597. Lavoie JN
    598. Layfield R
    599. Lazo PA
    600. Le W
    601. Le Cam L
    602. Ledbetter DJ
    603. Lee AJX
    604. Lee BW
    605. Lee GM
    606. Lee J
    607. Lee JH
    608. Lee M
    609. Lee MS
    610. Lee SH
    611. Leeuwenburgh C
    612. Legembre P
    613. Legouis R
    614. Lehmann M
    615. Lei HY
    616. Lei QY
    617. Leib DA
    618. Leiro J
    619. Lemasters JJ
    620. Lemoine A
    621. Lesniak MS
    622. Lev D
    623. Levenson VV
    624. Levine B
    625. Levy E
    626. Li F
    627. Li JL
    628. Li L
    629. Li S
    630. Li W
    631. Li XJ
    632. Li Y
    633. Li YP
    634. Liang C
    635. Liang Q
    636. Liao YF
    637. Liberski PP
    638. Lieberman A
    639. Lim HJ
    640. Lim KL
    641. Lim K
    642. Lin CF
    643. Lin FC
    644. Lin J
    645. Lin JD
    646. Lin K
    647. Lin WW
    648. Lin WC
    649. Lin YL
    650. Linden R
    651. Lingor P
    652. Lippincott-Schwartz J
    653. Lisanti MP
    654. Liton PB
    655. Liu B
    656. Liu CF
    657. Liu K
    658. Liu L
    659. Liu QA
    660. Liu W
    661. Liu YC
    662. Liu Y
    663. Lockshin RA
    664. Lok CN
    665. Lonial S
    666. Loos B
    667. Lopez-Berestein G
    668. López-Otín C
    669. Lossi L
    670. Lotze MT
    671. Lőw P
    672. Lu B
    673. Lu B
    674. Lu B
    675. Lu Z
    676. Luciano F
    677. Lukacs NW
    678. Lund AH
    679. Lynch-Day MA
    680. Ma Y
    681. Macian F
    682. MacKeigan JP
    683. Macleod KF
    684. Madeo F
    685. Maiuri L
    686. Maiuri MC
    687. Malagoli D
    688. Malicdan MCV
    689. Malorni W
    690. Man N
    691. Mandelkow EM
    692. Manon S
    693. Manov I
    694. Mao K
    695. Mao X
    696. Mao Z
    697. Marambaud P
    698. Marazziti D
    699. Marcel YL
    700. Marchbank K
    701. Marchetti P
    702. Marciniak SJ
    703. Marcondes M
    704. Mardi M
    705. Marfe G
    706. Mariño G
    707. Markaki M
    708. Marten MR
    709. Martin SJ
    710. Martinand-Mari C
    711. Martinet W
    712. Martinez-Vicente M
    713. Masini M
    714. Matarrese P
    715. Matsuo S
    716. Matteoni R
    717. Mayer A
    718. Mazure NM
    719. McConkey DJ
    720. McConnell MJ
    721. McDermott C
    722. McDonald C
    723. McInerney GM
    724. McKenna SL
    725. McLaughlin B
    726. McLean PJ
    727. McMaster CR
    728. McQuibban GA
    729. Meijer AJ
    730. Meisler MH
    731. Meléndez A
    732. Melia TJ
    733. Melino G
    734. Mena MA
    735. Menendez JA
    736. Menna-Barreto RFS
    737. Menon MB
    738. Menzies FM
    739. Mercer CA
    740. Merighi A
    741. Merry DE
    742. Meschini S
    743. Meyer CG
    744. Meyer TF
    745. Miao CY
    746. Miao JY
    747. Michels PAM
    748. Michiels C
    749. Mijaljica D
    750. Milojkovic A
    751. Minucci S
    752. Miracco C
    753. Miranti CK
    754. Mitroulis I
    755. Miyazawa K
    756. Mizushima N
    757. Mograbi B
    758. Mohseni S
    759. Molero X
    760. Mollereau B
    761. Mollinedo F
    762. Momoi T
    763. Monastyrska I
    764. Monick MM
    765. Monteiro MJ
    766. Moore MN
    767. Mora R
    768. Moreau K
    769. Moreira PI
    770. Moriyasu Y
    771. Moscat J
    772. Mostowy S
    773. Mottram JC
    774. Motyl T
    775. Moussa CEH
    776. Müller S
    777. Muller S
    778. Münger K
    779. Münz C
    780. Murphy LO
    781. Murphy ME
    782. Musarò A
    783. Mysorekar I
    784. Nagata E
    785. Nagata K
    786. Nahimana A
    787. Nair U
    788. Nakagawa T
    789. Nakahira K
    790. Nakano H
    791. Nakatogawa H
    792. Nanjundan M
    793. Naqvi NI
    794. Narendra DP
    795. Narita M
    796. Navarro M
    797. Nawrocki ST
    798. Nazarko TY
    799. Nemchenko A
    800. Netea MG
    801. Neufeld TP
    802. Ney PA
    803. Nezis IP
    804. Nguyen HP
    805. Nie D
    806. Nishino I
    807. Nislow C
    808. Nixon RA
    809. Noda T
    810. Noegel AA
    811. Nogalska A
    812. Noguchi S
    813. Notterpek L
    814. Novak I
    815. Nozaki T
    816. Nukina N
    817. Nürnberger T
    818. Nyfeler B
    819. Obara K
    820. Oberley TD
    821. Oddo S
    822. Ogawa M
    823. Ohashi T
    824. Okamoto K
    825. Oleinick NL
    826. Oliver FJ
    827. Olsen LJ
    828. Olsson S
    829. Opota O
    830. Osborne TF
    831. Ostrander GK
    832. Otsu K
    833. Ou JJ
    834. Ouimet M
    835. Overholtzer M
    836. Ozpolat B
    837. Paganetti P
    838. Pagnini U
    839. Pallet N
    840. Palmer GE
    841. Palumbo C
    842. Pan T
    843. Panaretakis T
    844. Pandey UB
    845. Papackova Z
    846. Papassideri I
    847. Paris I
    848. Park J
    849. Park OK
    850. Parys JB
    851. Parzych KR
    852. Patschan S
    853. Patterson C
    854. Pattingre S
    855. Pawelek JM
    856. Peng J
    857. Perlmutter DH
    858. Perrotta I
    859. Perry G
    860. Pervaiz S
    861. Peter M
    862. Peters GJ
    863. Petersen M
    864. Petrovski G
    865. Phang JM
    866. Piacentini M
    867. Pierre P
    868. Pierrefite-Carle V
    869. Pierron G
    870. Pinkas-Kramarski R
    871. Piras A
    872. Piri N
    873. Platanias LC
    874. Pöggeler S
    875. Poirot M
    876. Poletti A
    877. Poüs C
    878. Pozuelo-Rubio M
    879. Prætorius-Ibba M
    880. Prasad A
    881. Prescott M
    882. Priault M
    883. Produit-Zengaffinen N
    884. Progulske-Fox A
    885. Proikas-Cezanne T
    886. Przedborski S
    887. Przyklenk K
    888. Puertollano R
    889. Puyal J
    890. Qian SB
    891. Qin L
    892. Qin ZH
    893. Quaggin SE
    894. Raben N
    895. Rabinowich H
    896. Rabkin SW
    897. Rahman I
    898. Rami A
    899. Ramm G
    900. Randall G
    901. Randow F
    902. Rao VA
    903. Rathmell JC
    904. Ravikumar B
    905. Ray SK
    906. Reed BH
    907. Reed JC
    908. Reggiori F
    909. Régnier-Vigouroux A
    910. Reichert AS
    911. Reiners JJ
    912. Reiter RJ
    913. Ren J
    914. Revuelta JL
    915. Rhodes CJ
    916. Ritis K
    917. Rizzo E
    918. Robbins J
    919. Roberge M
    920. Roca H
    921. Roccheri MC
    922. Rocchi S
    923. Rodemann HP
    924. Rodríguez de Córdoba S
    925. Rohrer B
    926. Roninson IB
    927. Rosen K
    928. Rost-Roszkowska MM
    929. Rouis M
    930. Rouschop KMA
    931. Rovetta F
    932. Rubin BP
    933. Rubinsztein DC
    934. Ruckdeschel K
    935. Rudich A
    936. Rucker EB
    937. Rudolf E
    938. Ruiz-Opazo N
    939. Russo R
    940. Rusten TE
    941. Ryan KM
    942. Ryter SW
    943. Sabatini DM
    944. Sadoshima J
    945. Saha T
    946. Saitoh T
    947. Sakagami H
    948. Sakai Y
    949. Salekdeh GH
    950. Salomoni P
    951. Salvaterra PM
    952. Salvesen G
    953. Salvioli R
    954. Sanchez AMJ
    955. Sánchez-Alcázar JA
    956. Sánchez-Prieto R
    957. Sandri M
    958. Sankar U
    959. Sansanwal P
    960. Santambrogio L
    961. Saran S
    962. Sarkar S
    963. Sarwal M
    964. Sasakawa C
    965. Sasnauskiene A
    966. Sass M
    967. Sato K
    968. Sato M
    969. Schapira AHV
    970. Scharl M
    971. Schätzl HM
    972. Scheper W
    973. Schiaffino S
    974. Schneider C
    975. Schneider ME
    976. Schneider-Stock R
    977. Schoenlein PV
    978. Schorderet DF
    979. Schüller C
    980. Schwartz GK
    981. Scorrano L
    982. Sealy L
    983. Seglen PO
    984. Segura-Aguilar J
    985. Seiliez I
    986. Seleverstov O
    987. Sell C
    988. Seo JB
    989. Separovic D
    990. Setaluri V
    991. Setoguchi T
    992. Settembre C
    993. Shacka JJ
    994. Shanmugam M
    995. Shapiro IM
    996. Shaulian E
    997. Shaw RJ
    998. Shelhamer JH
    999. Shen HM
    1000. Shen WC
    1001. Sheng ZH
    1002. Shi Y
    1003. Shibuya K
    1004. Shidoji Y
    1005. Shieh JJ
    1006. Shih CM
    1007. Shimada Y
    1008. Shimizu S
    1009. Shintani T
    1010. Shirihai OS
    1011. Shore GC
    1012. Sibirny AA
    1013. Sidhu SB
    1014. Sikorska B
    1015. Silva-Zacarin ECM
    1016. Simmons A
    1017. Simon AK
    1018. Simon HU
    1019. Simone C
    1020. Simonsen A
    1021. Sinclair DA
    1022. Singh R
    1023. Sinha D
    1024. Sinicrope FA
    1025. Sirko A
    1026. Siu PM
    1027. Sivridis E
    1028. Skop V
    1029. Skulachev VP
    1030. Slack RS
    1031. Smaili SS
    1032. Smith DR
    1033. Soengas MS
    1034. Soldati T
    1035. Song X
    1036. Sood AK
    1037. Soong TW
    1038. Sotgia F
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Article and author information

Author details

  1. Grace Essuman

    Department of Physiology, University of Alberta, Edmonton, Canada
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Investigation, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3002-7880

  2. Midhat Rizvi

    Department of Physiology, University of Alberta, Edmonton, Canada
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Writing – review and editing
    Competing interests
    No competing interests declared

  3. Ensaf Almomani

    Department of Basic Medical Sciences, Faculty of Medicine, Al-Balqa Applied University, Al-Salt, Jordan
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared

  4. Shahid AKM Ullah

    1. Department of Physiology, University of Alberta, Edmonton, Canada
    2. Department of Medicine, University of Alberta, Edmonton, Canada
    Contribution
    Data curation, Formal analysis, Validation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared

  5. Sarder MA Hasib

    Department of Molecular and Cell Biology, Department of Biosciences (FR 8.3) and Center of Human and Molecular Biology (ZHMB), Saarland University, Saarbrücken, Germany
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Writing – review and editing
    Competing interests
    No competing interests declared

  6. Forough Chelangarimiyandoab

    Department of Physiology, University of Alberta, Edmonton, Canada
    Contribution
    Data curation, Formal analysis, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0255-2242

  7. Priyanka Mungara

    Department of Physiology, University of Alberta, Edmonton, Canada
    Contribution
    Data curation, Formal analysis, Validation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared

  8. Manfred J Schmitt

    Department of Molecular and Cell Biology, Department of Biosciences (FR 8.3) and Center of Human and Molecular Biology (ZHMB), Saarland University, Saarbrücken, Germany
    Contribution
    Supervision, Funding acquisition, Validation, Writing – review and editing
    Competing interests
    No competing interests declared

  9. Marguerite Hureaux

    Department of Genetics, Georges Pompidou European Hospital, Paris, France
    Contribution
    Data curation, Formal analysis, Funding acquisition, Validation, Writing – review and editing
    Competing interests
    No competing interests declared

  10. Rosa Vargas-Poussou

    Department of Genetics, Georges Pompidou European Hospital, Paris, France
    Contribution
    Data curation, Formal analysis, Funding acquisition, Validation, Writing – review and editing
    Competing interests
    No competing interests declared

  11. Nicolas Touret

    Department of Biochemistry, University of Alberta, Edmonton, Canada
    Contribution
    Formal analysis, Supervision, Investigation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3700-6302

  12. Emmanuelle Cordat

    Department of Physiology, University of Alberta, Edmonton, Canada
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing
    For correspondence
    cordat@ualberta.ca
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9875-5804

Funding

Canadian Institutes of Health Research (PJT#168871)

  • Emmanuelle Cordat

Natural Sciences and Engineering Research Council of Canada (RGPIN-2017-06432)

  • Forough Chelangarimiyandoab

Kidney Foundation of Canada (2020KHRG-666615)

  • Emmanuelle Cordat

Deutsche Forschungsgemeinschaft (IRTG1830)

  • Manfred J Schmitt

Deutscher Akademischer Austauschdienst (PhD Scholarship)

  • Sarder MA Hasib

Canadian Institutes of Health Research (PS165816)

  • Nicolas Touret

Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05783)

  • Nicolas Touret

University of Alberta (Multiple Scholarships)

  • Grace Essuman
  • Midhat Rizvi
  • Forough Chelangarimiyandoab
  • Priyanka Mungara

Canadian Institutes of Health Research (Canada Graduate Scholarship-Master's)

  • Midhat Rizvi

Natural Sciences and Engineering Research Council of Canada (CREATE Graduate Studentship)

  • Shahid AKM Ullah

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Kristina MacNaughton, Jared Bouchard, Kiera Smith, and Hilmar Strickfaden for excellent technical assistance. Imaging experiments were performed at the University of Alberta Faculty of Medicine & Dentistry Cell Imaging Core, RRID:SCR_019200, which receives financial support from the Faculty of Medicine & Dentistry, the University Hospital Foundation, Striving for Pandemic Preparedness – The Alberta Research Consortium, and Canada Foundation for Innovation (CFI) awards to contributing investigators. Services were provided by the University of Alberta Faculty of Medicine & Dentistry Workshop, RRID:SCR_019181, which receives financial support from the Faculty of Medicine & Dentistry. This study was funded by the Canadian Institutes of Health Research (PJT#168871) and the Kidney Foundation of Canada (2020KHRG-666615) to EC, by a grant from the Deutsche Forschungsgemeinschaft to MJS (IRTG 1830), and operating funds from Natural Sciences and Engineering Research Council of Canada (RGPIN-2018–05783) and the Canadian Institutes of Health Research (PS#165816) to NT. GE received a Graduate Student Engagement Scholarship, a Faculty of Medicine and Dentistry Delnor Scholarship, and a Faculty of Medicine and Dentistry 75th Anniversary award. MR received a Sir Frederick Banting and Dr. Charles Best Canada Graduate Scholarship-Master’s (CGS-M) from the Canadian Institutes of Health Research; Walter H Johns Graduate Fellowship; a University of Alberta Faculty of Medicine and Dentistry/Alberta Health Services Graduate Student Recruitment Studentship (GSRS) and an Alberta Graduate Excellence Scholarship (AGES). AKMSU received an NSERC CREATE graduate studentship. FC was supported by a Discovery Grant to EC from the Natural Sciences and Engineering Research Council (RGPIN-2017-06432), and was awarded a Graduate Recruitment scholarship from the University of Alberta. SMAH received a PhD scholarship from the DAAD (Deutscher Akademischer Austauschdienst).

Ethics

This study was conducted in accordance with all national and institutional animal care guidelines and approved by the University of Alberta's Animal Care and Use Committee (AUP #1277).

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© 2025, Essuman et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Grace Essuman
  2. Midhat Rizvi
  3. Ensaf Almomani
  4. Shahid AKM Ullah
  5. Sarder MA Hasib
  6. Forough Chelangarimiyandoab
  7. Priyanka Mungara
  8. Manfred J Schmitt
  9. Marguerite Hureaux
  10. Rosa Vargas-Poussou
  11. Nicolas Touret
  12. Emmanuelle Cordat
(2026)
SLC4A1 mutations that cause distal renal tubular acidosis alter cytoplasmic pH and cellular autophagy
eLife 14:RP108253.
https://doi.org/10.7554/eLife.108253.3

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