Tissue-specific mitochondrial HIGD1C promotes oxygen sensitivity in carotid body chemoreceptors

  1. Alba Timón-Gómez
  2. Alexandra L Scharr
  3. Nicholas Y Wong
  4. Erwin Ni
  5. Arijit Roy
  6. Min Liu
  7. Julisia Chau
  8. Jack L Lampert
  9. Homza Hireed
  10. Noah S Kim
  11. Masood Jan
  12. Alexander R Gupta
  13. Ryan W Day
  14. James M Gardner
  15. Richard JA Wilson
  16. Antoni Barrientos  Is a corresponding author
  17. Andy J Chang  Is a corresponding author
  1. Department of Neurology, University of Miami, United States
  2. Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, United States
  3. Department of Physiology and Pharmacology, University of Calgary, Canada
  4. Hotchkiss Brain Institute, University of Calgary, Canada
  5. Alberta Children's Hospital Research Institute, University of Calgary, Canada
  6. Department of Surgery, University of California, San Francisco, United States
  7. Diabetes Center, University of California, San Francisco, United States

Abstract

Mammalian carotid body arterial chemoreceptors function as an early warning system for hypoxia, triggering acute life-saving arousal and cardiorespiratory reflexes. To serve this role, carotid body glomus cells are highly sensitive to decreases in oxygen availability. While the mitochondria and plasma membrane signaling proteins have been implicated in oxygen sensing by glomus cells, the mechanism underlying their mitochondrial sensitivity to hypoxia compared to other cells is unknown. Here, we identify HIGD1C, a novel hypoxia-inducible gene domain factor isoform, as an electron transport chain complex IV-interacting protein that is almost exclusively expressed in the carotid body and is therefore not generally necessary for mitochondrial function. Importantly, HIGD1C is required for carotid body oxygen sensing and enhances complex IV sensitivity to hypoxia. Thus, we propose that HIGD1C promotes exquisite oxygen sensing by the carotid body, illustrating how specialized mitochondria can be used as sentinels of metabolic stress to elicit essential adaptive behaviors.

Editor's evaluation

The arterial chemoreceptors are the body's primary defense against hypoxia. In particular, the carotid body glomus cells (type 1) are highly sensitive to decreases in oxygen availability where the mitochondria and plasma membrane signaling proteins have been implicated in oxygen sensing by type 1 cells. Here, Chang and colleagues identified HIGD1C, a novel hypoxia-inducible gene domain factor isoform, is essential for carotid body oxygen sensing, where it enhances complex IV sensitivity to hypoxia. Discovery of this protein and its function brings back into focus the importance of how specialized mitochondria can act as sensors to metabolic stresses like hypoxia.

https://doi.org/10.7554/eLife.78915.sa0

Introduction

The carotid bodies (CBs), located at the bifurcation of the common carotid arteries, are the major chemoreceptor for blood oxygen in mammals (De Castro, 1928; Heymans et al., 1930). Within seconds of exposure to hypoxia (reduction in PaO2 from 100 mmHg to below 80 mmHg), CB glomus cells signal to afferent nerves projecting to the brainstem to stimulate acute cardiorespiratory and/or arousal reflexes (Black et al., 1971; Lahiri and DeLaney, 1975a; Lahiri and DeLaney, 1975b; Neil and O’Regan, 1971; Verna et al., 1975; reviewed in Chang, 2017; De Castro, 2009; Kumar and Prabhakar, 2012; Ortega-Sáenz and López-Barneo, 2020). These acute reflexes are essential for optimizing tissue oxygenation of vital organs, including the brain, heart, and kidneys. However, in chronic conditions such as sleep-disorder breathing, hypertension, chronic heart failure, airway constriction, and metabolic syndrome, the CB becomes hyperactive, leading to exaggerated responses to hypoxia and sympathetic overactivity. Under these pathological conditions, suppressing CB activity improves causal symptoms such as hypertension (Abdala et al., 2012; Del Rio et al., 2016; Fletcher et al., 1992; Narkiewicz et al., 2016), cardiac arrhythmias (Del Rio et al., 2013; Marcus et al., 2014), and insulin resistance (Ribeiro et al., 2013; Sacramento et al., 2017). Thus, understanding the fundamental mechanisms of oxygen sensing in the CB is of considerable scientific and medical importance.

In a long-standing model, acute oxygen sensing in the CB is proposed to be mediated by the mitochondrial electron transport chain (ETC) in glomus cells (Chang, 2017; Holmes et al., 2018; Ortega-Sáenz and López-Barneo, 2020). In his discovery of the CB as a chemoreceptor in the 1920s, Corneille Heymans utilized cyanide to inhibit ETC complex IV (CIV) and mimic the effect of hypoxia (Heymans, 1963). More recently, genetic approaches in mice found that knockout of two ETC subunit genes attenuates CB sensory activity: the mitochondrial respiratory chain complex I (CI) core subunit Ndufs2 and the HIF2A-regulated mitochondrial respiratory chain CIV subunit Cox4i2 (Fernández-Agüera et al., 2015; Moreno-Domínguez et al., 2020). Ndufs2 is ubiquitously expressed and essential for CI activity, whereas Cox4i2 expression is limited to several tissues, including the lung, placenta, heart, tongue, breast, and adipose tissue (Shen et al., 2012; Uhlén et al., 2015; Figure 1—figure supplement 1A–D). These results are accompanied by the observations that the ETC of glomus cells is more sensitive to hypoxia compared to other cell types (Buckler and Turner, 2013; Duchen and Biscoe, 1992a; Duchen and Biscoe, 1992b; Forster, 1968; Jobsis, 1968) and the proposal that an unusual CIV contributes to oxygen sensitivity of the CB (Mills and Jöbsis, 1970; Mills and Jöbsis, 1972). However, given the breadth of Cox4i2 expression, it remains unclear whether HIF2a regulation of Cox4i2 is solely responsible for the exquisite sensitivity of glomus cell mitochondria to hypoxia compared to other tissues.

Here, we identify HIGD1C as a novel mitochondrial protein associated with ETC CIV that is almost exclusively expressed in the CB. HIGD1C is critical in mediating CB oxygen sensing and metabolic responses to hypoxia in mice. In heterologous cell culture, we demonstrate that HIGD1C regulates the activity and conformation of CIV, and when co-expressed with COX4I2, HIGD1C enhances the oxygen sensitivity of CIV to hypoxia. We propose that HIGD1C and COX4I2 comprise key components bestowing CB glomus cell mitochondria with their extreme oxygen sensitivity.

Results

HIGD1C is a novel mitochondrial protein expressed in CB glomus cells

CB sensory activity correlates with changes in ETC activity (Chang, 2017; Holmes et al., 2018; Ortega-Sáenz and López-Barneo, 2020). Therefore, we sought to identify proteins that are specifically expressed in mitochondria in the CB and are highly sensitive to changes in oxygen availability. Using whole-genome expression data from RNAseq, we looked for genes encoding putative mitochondrial proteins that are overexpressed in the adult mouse CB compared to the adrenal medulla, a similar but less oxygen-sensitive tissue (Chang et al., 2015). We found that three such genes, Higd1c, Cox4i2, and Ndufa4l2, were expressed at higher levels in the mouse CB (Figure 1A). The expression of Cox4i2 and Ndufa4l2 in the CB is found in glomus cells and regulated by Hif2a, a hypoxia-inducible transcription factor critical for CB development and function (Macias et al., 2018; Moreno-Domínguez et al., 2020; Zhou et al., 2016). We focused this study on Higd1c because it was the most differentially expressed of these genes and one of the top 10 most upregulated genes genome-wide in the mouse CB (Chang et al., 2015). RT-qPCR analysis confirmed the enrichment of Higd1c as well as Ndufa4l2 and Cox4i2 mRNAs in the human CB (Figure 1B).

Figure 1 with 5 supplements see all
Higd1c expression in carotid body glomus cells is reduced in Higd1c CRISPR mutants.

(A) Expression of genes encoding atypical mitochondrial electron transport chain (ETC) subunits in mouse carotid body (CB) versus adrenal medulla (AM) (Chang et al., 2015). RPKM, reads per kilobase of transcript, per million reads mapped. n = 3 cohorts of 10 animals each. Data as mean ± SEM. **p<0.01, ***p<0.001, ****p<0.0001 by two-way ANOVA with Sidak correction. (B) Expression of atypical ETC proteins in human CB and adrenal gland (AG). AG, one RNA sample of adrenal glands pooled from 62 individuals. CB, two RNA samples of CBs from two adults. Dotted line, 100% of GAPDH expression. Data as mean. (C) FLAG-tagged mouse and human HIGD1C (green) overexpressed in HEK293T cells co-localized with the mitochondrial marker HSP60 (red) by immunostaining. DAPI, nuclear marker. Scale bar, 10 µm. (D, E) BaseScope in situ hybridization of a wild-type C57BL/6J carotid bifurcation. (E) Boxed region from (D). SCG, superior cervical ganglion; CA, carotid arteries. Arrowheads, glomus cells. Arrows, SCG neurons. Scale bar, 100 µm (D), 10 µm (E). (F) Expression of Higd1c mRNA is reduced in CBs from Higd1c mutants measured by RT-qPCR. n = 3–6 samples. Each sample was prepared from 4 CBs/2 animals. Data as mean ± SEM. **p<0.01 by two-way ANOVA with Sidak correction. (G, H) Immunostaining of CB glomus cells. TH, tyrosine hydroxylase. DAPI, nuclear marker. Scale bar, 50 µm. (I) Quantitation of TH+ cells found no significant differences between CBs from Higd1c+/+ and Higd1c-/- animals of each allele or between alleles by two-way ANOVA with Sidak correction (p>0.05). n = 5–7 CBs from 3-7 animals. Data as mean ± SEM.

Higd1c is a novel member of the HIG1 hypoxia-inducible domain gene family that also includes Higd1a, Higd1b, and Higd2a. Higd1a and Higd2a, the mammalian orthologs of the yeast respiratory supercomplex factors 1 and 2 (Rcf1 and Rcf2), encode mitochondrial proteins that promote the biogenesis of ETC complexes and their assembly into supercomplexes (Timón-Gómez et al., 2020a). To determine the subcellular localization of HIGD1C, we overexpressed FLAG-tagged HIGD1C in HEK293T cells and observed that it co-localizes with the mitochondrial marker HSP60, suggesting that HIGD1C is targeted to mitochondria like HIGD1A and HIGD2A (Figure 1C).

Compared to mitochondrial ETC genes previously implicated in CB oxygen sensing (Ndufs2 and Cox4i2), mRNA transcripts for Higd1c are minimally detected across mouse and human tissues, with the exception of the mouse kidney (An et al., 2011; Shen et al., 2012; Uhlén et al., 2015; Figure 1—figure supplement 1A–D). We found that Higd1c is expressed at 30–600,000-fold higher levels in the CB than in other mouse tissues (Figure 1—figure supplement 2A–D, Figure 1—figure supplement 3A–D). Within the CB, glomus cells sense hypoxia to stimulate afferent nerves to increase ventilation Kumar and Prabhakar, 2012. In situ hybridization showed that Higd1c mRNA was localized in the same cells as mRNA for Th, a marker of glomus cells (Figure 1D and E, Figure 1—figure supplement 4A–D), validating single-cell RNAseq findings (Zhou et al., 2016; Figure 1—figure supplement 5A). In the rat, Higd1c was also expressed at higher levels in the CB compared to the neonatal and adult adrenal medulla and thoracic spinal cord, which contains a novel central oxygen sensor (Barioni et al., 2022; Figure 1—figure supplement 5B). Additionally, we confirmed the expression of Higd1c mRNA in mouse kidney proximal tubules as previously reported (Suganthan et al., 2014; Figure 1—figure supplement 4F–I). These results indicate that Higd1c is enriched in a population of cells in the CB essential for oxygen sensing.

To determine whether HIGD1C plays a role in CB oxygen sensing, we generated mutants in Higd1c by CRISPR/Cas9 in C57BL/6J mice. We isolated F0 mice that carried large deletions that span upstream sequences through the first coding exon and small indels in the first coding exon (Figure 1—figure supplement 2A–C). We characterized three alleles representing large deletions (3-1) and early frameshift mutations in both frames downstream of the start codon (1-1 and 5-3). The 3-1 allele was predicted to either produce no protein or a truncated protein missing the N-terminus while the 1-1 and 5-3 alleles were expected to make truncated proteins with early amino acid changes (Figure 1—figure supplement 2D). For all three alleles, heterozygous Higd1c mutant mice were fertile, and homozygous mutants were viable and not underrepresented in the progeny (Table 1). The large deletion allele 3-1 was used as a negative control in characterizing Higd1c expression by RT-qPCR and in situ hybridization because our primers and probes targeted a region that was deleted in this allele (Figure 1F, Figure 1—figure supplement 3A–D, Figure 1—figure supplement 4E and J). In 1-1 and 5-3 alleles, Higd1c mRNA levels were reduced by 40–90% in CBs and kidneys from Higd1c-/- mutants compared to Higd1c+/+ animals (Figure 1F, Figure 1—figure supplement 4K). While we infer that all three alleles alter HIGD1C protein sequence, Higd1c 1-1 and 5-3 alleles also have reduced levels of HIGD1C, perhaps due to nonsense-mediated mRNA decay.

Table 1
Genotype distribution of progeny from Higd1c+/- × Higd1c+/-crosses.
Higd1c alleleNFrequency of genotypeChi-square p-value
+/++/--/-
3-11250.220.480.300.344
1-12330.320.430.250.028
5-3780.240.530.230.891

HIGD1C mediates CB sensory and metabolic responses to hypoxia

To assess whether HIGD1C plays a role in CB oxygen sensing at the whole animal level, we performed whole-body plethysmography on awake, unanesthetized mice. A decrease in arterial blood oxygen stimulates the CB to signal the brainstem to increase ventilation within seconds (Chang, 2017; Kumar and Prabhakar, 2012; Ortega-Sáenz and López-Barneo, 2020). Higd1c-/- mutants of all three alleles had normal ventilation in normoxia but were similarly defective in the hypoxic ventilatory response (Figure 2A–D, Figure 2—figure supplement 1A–M). The defects observed in these Higd1c alleles were at least as severe as ablation or denervation of the CBs in rodents (Del Rio et al., 2013; Soliz et al., 2005). By contrast, Higd1c-/- mice maintained robust ventilatory responses to hypercapnia comparable to Higd1c+/+ animals (Figure 2E–H, Figure 2—figure supplement 2A–J). These results suggest that Higd1c specifically regulates ventilatory responses to hypoxia.

Figure 2 with 2 supplements see all
Ventilatory responses of Higd1c mutants to hypoxia and hypercapnia.

(A–H) Respiratory rate (RR), tidal volume (TV), and minute ventilation (MV) (minute ventilation = respiratory rate × tidal volume) by whole-body plethysmography of unrestrained, unanesthetized Higd1c 1-1+/+ and Higd1c 1-1-/- animals exposed to hypoxia (A–D) or hypercapnia (E–H). (D) Hypoxic response as the percentage change in hypoxia (10% O2) versus control (21% O2). (H) Hypercapnic response as the percentage change in hypercapnia (5% CO2) versus control (0% CO2). n = 11 (+/+), 11 (-/-) animals. Data as mean ± SEM. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 by two-way repeated-measures ANOVA with Sidak correction (A–C, E-G) or unpaired t-tests (D, H) with Holm–Sidak correction. Ventilatory parameters of Higd1c+/+ and Higd1c-/- animals in normal air conditions (21% O2 or 0% CO2) were not significantly different (p>0.05). For the hypoxic response (D), Cohen’s d = 1.24 (RR), 1.20 (TV), 2.13 (MV).

Because Higd1c was expressed at low levels in the petrosal ganglion and brainstem downstream of the CB in the neuronal circuit (Figure 1—figure supplement 3A and B), the reduction in hypoxic ventilatory response in Higd1c-/- mice was most likely due to loss of HIGD1C activity in the CB. When we examined the CB, the number of TH-positive glomus cells from Higd1c+/+ and Higd1c-/- animals was not significantly different for all three alleles (Figure 1G–I), and there were no gross morphological abnormalities in mutant CBs. Thus, it is unlikely that the hypoxic ventilatory response defect observed in Higd1c-/- mutants is due to a loss of glomus cells.

Next, we measured the integrated sensory output from the CB at the level of the carotid sinus nerve (CSN), the nerve that transduces signals from the CB to the brainstem (Kumar and Prabhakar, 2012). Baseline CSN activity was similar between Higd1c 1-1+/+ and Higd1c 1-1-/- tissues (Figure 3A–C). As oxygen levels were decreased, CSN activity increased in a dose-dependent manner in Higd1c 1-1+/+ tissue (Figure 3A and D). However, while this response to hypoxia was attenuated in CSNs from Higd1c 1-1-/- mutants (Figure 3B and D), the response to high CO2/H+ was unaffected (Figure 3A–D). Thus, we conclude that HIGD1C specifically mediates oxygen sensing at the level of the whole CB organ.

Figure 3 with 1 supplement see all
Higd1c mutants have defects in carotid body sensory responses to hypoxia.

(A, B) Representative traces of carotid sinus nerve (CSN) activity from Higd1c 1-1+/+ and Higd1c 1-1-/- tissue preparations exposed to hypoxia (PO2 ~ 80, 60, and 40 mmHg) or hypercapnia (PCO2 ~ 60 mmHg) normalized to activity at t = 0. (C, D) CSN activity in Higd1c 1-1+/+ and Higd1c 1-1-/- tissues at baseline (C) and in hypoxia and hypercapnia (D). Activity in hypoxia and hypercapnia normalized to baseline (D). n = 7/5 (+/+), 10/6 (-/-) preparations/animals. AU, arbitrary units. Data as box plots showing median and interquartile interval. **p<0.01, ***o<0.001 by Mann–Whitney U-test with Holm–Sidak correction. (E, F) Individual traces of GCaMP fluorescence of glomus cells from Higd1c 1-1+/+ and Higd1c 1-1-/- animals, in response to low pH (6.8), hypoxia (PO2 ~ 50 and 25 mmHg), high KCl (40 mM), and cyanide (CN, 1 mM). Data normalized to fluorescence at t = 0 s. Z stacks were collected every 45 s. (G, H) Peak (G) and mean (H) GCaMP calcium responses (F/F0) of glomus cells from Higd1c 1-1+/+ and Higd1c 1-1-/- animals. n = 296/4/3 (+/+), 201/4/3 (-/-) for pH 6.8, 312/5/4 (+/+), 214/5/4 (-/-) for all other stimuli. n as glomus cells/CBs/animals. Data as box plots showing median and interquartile interval. *p<0.05, ****p<0.0001 by Mann–Whitney U-test with Holm–Sidak correction.

Because Higd1c was expressed in glomus cells (Figure 1D and E), we evaluated whether Higd1c mutants were also defective in the sensory responses of these oxygen-sensitive cells. Glomus cells exhibit acute calcium transients in response to stimuli, which can be visualized by the genetically encoded calcium indicator GCaMP3 (Chang et al., 2015). We found that glomus cells from Higd1c 1-1-/- mutants mounted a weaker calcium response to hypoxia than those from Higd1c 1-1+/+ animals, with fewer glomus cells responding strongly to both levels of hypoxia (Figure 3E–H, Figure 3—figure supplement 1A–E). Low pH and high KCl modulate the activity of ion channels on the plasma membrane of glomus cells thought to act downstream of mitochondria in CB oxygen sensing (Buckler, 2015; Lu et al., 2013). In contrast to hypoxia, glomus cells from Higd1c 1-1-/- mutants were not significantly different from Higd1c 1-1+/+ animals in their calcium response to low pH or high KCl compared to glomus cells from Higd1c 1-1-/- animals (Figure 3E–H). Calcium responses to cyanide, a potent ETC CIV inhibitor, were also similar between Higd1c 1-1+/+ and Higd1c 1-1-/- glomus cells (Figure 3E–H), suggesting that strong ETC inhibition is still able to trigger sensory responses in glomus cells mutated in Higd1c like other mutants with defects in CB oxygen sensing (Peng et al., 2020; Peng et al., 2019). Together, these results show that HIGD1C contributes specifically to glomus cell responses to hypoxia.

To determine whether HIGD1C modulates oxygen sensitivity of mitochondria in glomus cells, we used rhodamine 123 (Rh123) to image the inner mitochondrial membrane (IMM) potential generated by ETC activity. Hypoxia inhibits ETC activity, leading to a decrease in IMM potential and an increase in Rh123 fluorescence (Perry et al., 2011). Higd1c 1-1-/- glomus cells had an attenuated response to hypoxia and a higher percentage of cells that responded poorly to FCCP, a potent uncoupler of oxidative phosphorylation that depolarizes the IMM (Figure 4A–C, Figure 4—figure supplement 1A and B). The weaker response of Higd1c 1-1-/- glomus cells to FCCP was evident even when FCCP was presented as the first stimulus (Figure 4—figure supplement 1C), suggesting that the IMM is less polarized at baseline in mutant glomus cells. This idea is also supported by the observation that in glomus cells that had a strong FCCP response > 0.2, Rh123 fluorescence was greater in Higd1c 1-1-/- glomus cells in normoxia (PO2 = 100 mmHg) (Figure 4D). Nevertheless, the increase in fluorescence in hypoxia (PO2 < 80 mmHg) was smaller than in Higd1c 1-1+/+ glomus cells (Figure 4E and F). This pattern of weaker ETC activity in normoxia that cannot be suppressed further in hypoxia seen in Higd1c 1-1-/- glomus cells resembles that of acute CII inhibition on CB sensory activity (Swiderska et al., 2021). In Higd1c 1-1+/+ CBs, we found that vascular cells, which are less oxygen-sensitive than glomus cells, had a left-shifted IMM potential response to hypoxia (Figure 4G–I), indicating that our hypoxic stimulus was in an appropriate range to detect the enhanced oxygen sensitivity of the CB over other cell types. These results demonstrate that HIGD1C enhances ETC inhibition by hypoxia in glomus cells, a response linked to CB sensory activity (Chang, 2017; Holmes et al., 2018; Ortega-Sáenz and López-Barneo, 2020).

Figure 4 with 1 supplement see all
HIGD1C regulates the hypoxic response of the electron transport chain in carotid body glomus cells.

(A) Fluorescence of a whole-mount carotid body (CB) loaded with rhodamine 123 (Rh123), a dye sensitive to changes in mitochondrial inner membrane potential, under quenching conditions. Arrowheads, glomus cell clusters; asterisk, vasculature. Scale bar, 50 µm. Rh123 fluorescence of glomus cells in Higd1c 1-1+/+ and Higd1c 1-1-/- CBs measured in response to hypoxia (PO2 < 80 mmHg), cyanide (1 mM), and FCCP (2 μM). (B) Rh123 response to hypoxia for all glomus cells quantified. Dashed line, fluorescence at the start of stimulus. n = 291/3/3 (+/+), 312/3/3 (-/-) glomus cells/CBs/animals. Data presented as the median and interquartile interval. ****p<0.0001 by Mann–Whitney U-test with Holm–Sidak correction. (C) Fraction of glomus cells that responded to FCCP at different ΔF/F. n = 291/3/3 (+/+), 312/3/3 (-/-) glomus cells/CBs/animals. *p<0.01, ***p<0.001, ****p<0.0001 by Z-test of proportions. (D–F) Rh123 response to hypoxia for glomus cells with FFCP responses of ΔF/F > 0.2. Dashed line, fluorescence at the start of stimulus. n = 98/3/3 (+/+), 102/3/3 (-/-) glomus cells/CBs/animals. Data presented as the median and interquartile interval or box plots. **p<0.01, ***p<0.001, ****p<0.0001 by Mann–Whitney U-test with Holm–Sidak correction. (G–I) Rh123 fluorescence of vascular cells in the CB compared to glomus cells with FCCP responses of ΔF/F > 0.2. n = 98/3/3 (+/+) glomus cells/CBs/animals, 49/3/3 (+/+) vascular cells/CBs/animals. Data presented as the median and interquartile interval or box plots. *p<0.05, **p<0.01, ****p<0.0001 by Mann–Whitney U-test with Holm–Sidak correction.

HIGD1C associates with and regulates ETC complex IV activity

To assess the role of HIGD1C in ETC function, we overexpressed FLAG-tagged human or mouse HIGD1C in HEK293T cells and performed biochemical and metabolic studies of mitochondria. In wild-type HEK293T cells, HIGD1C mRNA was expressed at very low levels (3 × 10–6 the level of GAPDH by RT-qPCR). Overexpressed FLAG-tagged HIGD1C associated with ETC CIV and cytochrome c (Figure 5—figure supplement 1A–C). Notably, HIGD1C overexpression severely reduced the abundance of ETC supercomplexes, and supercomplexes that did assemble contained only traces of in-gel CIV activity (Figure 5—figure supplement 1D and E). These defects in supercomplex formation correlated with a decrease in CIV enzymatic activity (Figure 5—figure supplement 1F and G) and oxygen consumption rate (OCR) (Figure 5—figure supplement 1H and I).

Because HIGD1C is most similar to HIGD1A and HIGD2A, we overexpressed HIGD1C in HIGD1A-KO and HIGD2A-KO HEK293T cell lines to determine whether it could rescue ETC defects of these KO cell lines (Timón-Gómez et al., 2020b). As in wild-type cells, HIGD1C associated with CIV and cytochrome c in HIGD1A-KO and HIGD2A-KO mutant cells (Figure 5A and B, Figure 5—figure supplement 2A–D, Figure 5—figure supplement 3A–C). Unlike HIGD1A, HIGD1C did not associate with CIII and could not rescue defects in the assembly of supercomplexes in either HIGD1A-KO or HIGD2A-KO cells (Figure 5C, Figure 5—figure supplement 2E, Figure 5—figure supplement 3D; Timón-Gómez et al., 2020b). Strikingly, however, HIGD1C overexpression restored CIV activity in HIGD1A-KO, but not HIGD2A-KO cells (Figure 5D, Figure 5—figure supplement 2F, Figure 5—figure supplement 3E and F). This could be due to non-overlapping activities of HIGD1C and HIGD2A and/or more severe defects in CIV assembly in HIGD2A-KO cells (Figure 5—figure supplement 3D). Instead of acting as a CIV assembly factor as HIGD2A, HIGD1C could play a regulatory role in modulating CIV activity like HIGD1A (Timón-Gómez et al., 2020b). Supporting this idea, we observed that cellular respiration at the overall ETC level was also restored by HIGD1C overexpression in HIGD1A-KO cells (Figure 5E and F). Overexpression of mouse HIGD1C induced a weaker rescue of CIV activity than human HIGD1C, likely due to disruption of species-specific associations between ETC subunits (Figure 5D, Figure 5—figure supplement 2F). Nonetheless, mouse HIGD1C fully rescued mitochondrial oxygen consumption due to the spare respiratory capacity of the ETC (Figure 5E and F). These rescue experiments show that HIGD1C is not involved in ETC complex or supercomplex biogenesis, but similarly to HIGD1A, it can interact with CIV to regulate its activity.

Figure 5 with 3 supplements see all
HIGD1C is a mitochondrial protein that associates with the electron transport chain complex IV and regulates cellular respiration.

HIGD1A-KO HEK293T cells overexpressing FLAG-tagged human or mouse HIGD1C and/or COX4 isoforms. EV, empty vector; HIGD1C, human HIGD1C; Higd1c, mouse HIGD1C. (A) BN-PAGE and immunoblots using antibodies for FLAG and the complex IV subunit COX5B. SDHA is used as a loading control. (B) Co-immunoprecipitation using a FLAG antibody followed by SDS-PAGE and immunoblot using antibodies for FLAG and subunits of complex I (NDUFA9), complex II (SDHA), complex III (CORE2, UQCRB), complex IV (COX1, COX4I1, COX5B), and cytochrome c. (C) Electron transport chain (ETC) complexes and supercomplexes extracted with DDM and digitonin, respectively, detected by BN-PAGE and immunoblotting. (A–C) All gels and blots were repeated three times. (D) Complex IV enzymatic activity assay. n = 3. *p<0.05, ***p<0.001, ****p<0.0001 vs. WT by one-way ANOVA with Dunnett’s test. +p<0.05, ++p<0.01, +++p<0.001, ++++p<0.0001 vs. HIGD1A-KO+EV by one-way ANOVA with Dunnett’s test. Gray symbol indicates p=0.06. (E, F) Polarographic assessment in digitonin-permeabilized cells of KCN-sensitive oxygen consumption driven by succinate and glycerol-3-phosphate, in the presence or absence of ADP (basal respiration and phosphorylating), oligomycin (resting), and the uncoupler CCCP (uncoupled). Respiratory control ratio (F) of measurements performed in (E). n = 3. Data as mean ± SEM. *p<0.05, **p<0.01, ***p<0.001 vs. HIGD1A-KO+EV by two-way ANOVA with Dunnett’s test.

HIGD1C could modulate CIV activity by (1) mediating the formation of an electron-transfer bridge between ETC CIII and IV and/or (2) changing the structure around the active center of the enzyme. The former possibility is unlikely because overexpression of HIGD1C in HIGD1A-KO cells did not increase the levels of cytochrome c present in ETC supercomplexes compared to control cell lines (Figure 5—figure supplement 2E). The CIV active center that reduces oxygen to water in the terminal step of the ETC is located in subunit 1 (COX1) and formed by a binuclear heme-copper center (heme a3-CuB) (Timón-Gómez et al., 2018). To analyze the environment around the CIV active center, we measured UV/Vis absorption spectra of total cytochromes extracted from purified mitochondria. The absence of HIGD1A produced a blue shift in the peak of heme a+a3 absorbance from 603 nm to 599 nm (Figure 6A, Figure 6—figure supplement 1A) that is associated with changes around the CIV heme a centers (Shapleigh et al., 1992). Previous studies showed that adding excess recombinant HIGD1A to highly purified oxidized CIV increases CIV activity twofold and changes the conformation around the heme a center (Hayashi et al., 2015), suggesting that HIGD1A levels modulate CIV activity. Here, the spectral shift observed in the HIGD1A-KO cell line was completely restored by expressing HIGD1A (Figure 6A, Figure 6—figure supplement 1A). While the wavelength at the peak appeared to be restored by human HIGD1C, expression of human or mouse HIGD1C generated a broader peak, probably due to the existence of a mixed population of the enzyme, to partially restore the spectral shift (Figure 6A–D, Figure 6—figure supplement 1A–C). A blue shift in the wavelength at the peak was apparent in HIGD1A-KO cells overexpressing the mouse HIGD1C alone or human HIGD1C and COX4I2 together (Figure 6A–D, Figure 6—figure supplement 1A–C), suggesting that the atypical CIV subunit COX4I2 expressed in the CB (Figure 1A and B, Figure 1—figure supplement 5A and C) can modify the effect of HIGD1C overexpression. In addition, this spectral shift resembled the unusual absorbance spectrum of cytochromes found in the CB (Streller et al., 2002). These results suggest that interaction of HIGD1C with CIV can alter the active site and activity of CIV.

Figure 6 with 1 supplement see all
HIGD1C alters complex IV (CIV) conformation and increases CIV sensitivity to hypoxia.

(A) Differential spectra (reduced minus oxidized) of total mitochondrial cytochromes measured by spectrophotometry. The absorbance of cytochromes extracted from purified mitochondria was measured from 450 to 650 nm. (B) Relative peak height of heme a + a3 normalized by cytochrome b peak as the ratio of wild-type (WT). n = 3. Data as mean ± SEM. **p<0.01 vs. WT by one-way ANOVA with Dunnett’s test. (C, D) Relative peak area (C) and peak base width (D) of a + a3 as the ratio of WT. n = 3. Data as mean ± SEM. *p<0.05, **p<0.01 vs. WT by one-way ANOVA with Dunnett’s test. (E) Ascorbate/TMPD-dependent oxygen consumption in normoxia (Nox, PO2 ~ 150 mmHg) and hypoxia (Hox, PO2 ~ 25 mmHg) by high-resolution respirometry. Ratio of hypoxic/normoxic oxygen consumption. n = 5–8. Data as the median and interquartile interval. **p<0.01 vs. WT by Kruskal–Wallis test with Dunn’s test. (F) Mitochondrial oxygen affinity (p50mito) values derived from full oxygen consumption curve in intact cells from normoxia (PO2 ~ 150 mmHg) to anoxia (PO2 = 0 mmHg) by high-resolution respirometry. n = 4. Data as mean ± SEM. **p<0.01, ***p<0.001 vs. WT by one-way ANOVA with Dunnett’s test.

HIGD1C and COX4I2 enhance the sensitivity of ETC complex IV to hypoxia

To determine whether HIGD1C can modify the sensitivity of ETC to hypoxia, we measured respiration of HIGD1A-KO cells overexpressing atypical CIV proteins found in glomus cells (Zhou et al., 2016; Figure 1—figure supplement 5A). Because CIV activity alone is sufficient to recapitulate the enhanced oxygen sensitivity of the intact ETC in glomus cells (Buckler and Turner, 2013), we used an artificial electron donor system to isolate cytochrome c-CIV activity and measured oxygen consumption. This approach allowed us to bypass CIII assembly defects of HIGD1A-KO cells that contribute to defects in total respiration and measure CIV activity derived from the cyanide-dependent component of total respiration (Figure 5D and E; Timón-Gómez et al., 2020b). Co-expression of HIGD1C and COX4I2 in HIGD1A-KO cells, which better models the ETC composition in the CB (Figure 1—figure supplement 5A and C), decreased CIV-dependent respiration in hypoxia more than wild-type and other cell lines, including one overexpressing HIGD1C alone (Figure 6E, Figure 6—figure supplement 1D). This condition also increased the oxygen pressure at half-maximal respiration (p50mito), suggesting a reduction in oxygen affinity (Figure 6F, Figure 6—figure supplement 1E). In HIGD1A-KO cells, overexpression of COX4I2 alone decreased p50mito, but additional expression of HIGD1C further modified the JO2/Jmax curve to increase p50mito over wild-type (Figure 6F, Figure 6—figure supplement 1E). These results demonstrate that co-overexpression of HIGD1C and COX4I2, two atypical mitochondrial ETC proteins expressed in CB glomus cells that mediate oxygen sensing (Moreno-Domínguez et al., 2020), can confer hypersensitivity to hypoxia in HEK293T cells. Therefore, the COX4I2-containing CIV, and its regulation by HIGD1C, emerge as necessary and sufficient factors to promote oxygen sensing by CB glomus cells.

Discussion

Previous studies found that mouse knockouts in specific CI (Ndufs2) and CIV (Cox4i2) subunits exhibit defects in CB sensory and metabolic responses to hypoxia (Fernández-Agüera et al., 2015; Moreno-Domínguez et al., 2020), phenocopying the effect of drugs that inhibit these ETC complexes. However, these subunits are expressed in multiple tissues in addition to the CB. Here, we identified HIGD1C as a novel mitochondrial CIV protein expressed almost exclusively in CB glomus cells that is essential for oxygen sensing by the CB (summarized in Figure 7A and B). We found that HIGD1C interacts with CIV to alter the conformation of its enzymatic active center. In the absence of HIGD1A, co-overexpression of HIGD1C and COX4I2 increased oxygen sensitivity of CIV in HEK293T cells (Figure 6E), and overexpression of COX4I2 increased the stability of HIGD1C (Figure 5—figure supplement 2B). Since COX4I1, the ubiquitously expressed COX4 subunit, associates with HIGD1A in CIV assembly (Timón-Gómez et al., 2020b), the alternative COX4I2 subunit may assemble with HIGD1C. In opposition to its effect in HIGD1A-KO cells, COX4I2 overexpression in the presence of HIGD1A in WT cells decreases HIGD1C abundance, suggesting that HIGD1A and HIGD1C interact with CIV in the same domains (Figure 5—figure supplement 1A). These results indicate that coalitions of different CIV proteins may assemble under varying conditions and perform distinct physiological functions.

A model for oxygen sensing by mitochondria of carotid body glomus cells.

(A) In this simplified scheme, NADH produced by the Krebs cycle transfers electrons to CI to initiate the electron transport chain (ETC). FADH2 produced by succinate metabolism can also initiate the ETC by donating electrons to CII. In the terminal step of the ETC, complex IV (CIV) transfers electrons to oxygen. Cyanide inhibits the transfer of electrons to oxygen by binding to heme a3 in CIV to mimic the effect of hypoxia on the ETC. Hypoxia and cyanide reduce flux through the ETC, increasing the production of reactive oxygen species (ROS) and lactate that are proposed to signal to downstream targets for neurotransmission in glomus cells (Chang, 2017; Holmes et al., 2018; Ortega-Sáenz and López-Barneo, 2020). HIGD1 and COX4 are ETC proteins that associate with CIV. Q, coenzyme Q; C, cytochrome c. (B) In most cells, CIV contains HIGD1A and COX4I1 proteins that form an early-assembly module during CIV biogenesis (Timón-Gómez et al., 2020b). Glomus cells express alternative isoforms of HIGD1A and COX4I2 called HIGD1C and COX4I2, respectively (Figure 1—figure supplement 5A). The combination of HIGD1C and COX4I2 increases the sensitivity of CIV to hypoxia at the level of oxygen consumption (relative activity levels denoted). Because mouse knockouts in Higd1c and Cox4i2 are defective in carotid body oxygen sensing (Figures 24 Moreno-Domínguez et al., 2020) and HIGD1C and COX4I2 overexpression in HEK293T cells enhances oxygen sensitivity of the ETC to hypoxia (Figure 6E and F), we propose that these CIV-associated proteins are necessary and sufficient for oxygen sensing by carotid body glomus cells.

HIGD1C is evolutionarily closer to HIGD1A than to HIGD2A (Timón-Gómez et al., 2020a), which could explain why in normoxic conditions HIGD1C is able to substitute for HIGD1A function partially but not for HIGD2A (Figure 5D and E, Figure 5—figure supplement 3E). Unlike HIGD1A and HIGD2A, HIGD1C does not perform any apparent role in assembling the ETC complexes or supercomplexes (Figure 5C, Figure 5—figure supplement 3D). HIGD1C interacts with cytochrome c and CIV (Figure 5A and B) and, like HIGD1A, promotes CIV enzymatic activity in normoxia (Figure 5D). However, whereas HIGD1A is a positive regulator of CIV (Hayashi et al., 2015), our data indicate that HIGD1C serves as a negative modulator of CIV activity or is less efficient than HIGD1A in promoting CIV activity under limiting oxygen conditions (Figure 6E). Importantly, HIGD1C does not act in a CIV formed by standard subunits but in a CIV containing atypical tissue-specific isoforms known to be regulated by hypoxia, such as COX4I2, because increased sensitivity of the ETC to hypoxia is apparent only when both HIGD1C and COX4I2 are overexpressed (Figure 6E and F).

Our data allow us to conclude that the interaction of HIGD1C with hypoxic CIV containing atypical subunits results in an oxygen-sensing cytochrome c oxidase enzyme in CB glomus cells. However, while we demonstrated here that HIGD1C and COX4I2 are sufficient to confer oxygen sensitivity to CIV in HEK293T cells, additional components are likely to be required to fully reconstitute the oxygen sensitivity of CB glomus cells. Other proteins upregulated in glomus cells, such as the atypical CIV subunits NDUFA4L2 and COX8B and the glycolytic enzyme PCX (Chang et al., 2015; Moreno-Domínguez et al., 2020), are attractive candidates for further study to determine their potential contribution to CB oxygen sensing. The expression of three atypical CIV subunits in the CB correlates with the sufficiency of CIV alone to recapitulate the unusual oxygen dose response of the ETC in glomus cells (Buckler and Turner, 2013), suggesting that CIV is key for CB oxygen sensing. Future studies of oxygen consumption by mitochondria of glomus cells, when feasible, will further illuminate the roles of these proteins in CB oxygen sensing. While our study addresses CB oxygen sensing at the level of the oxygen sensor, how changes in ETC caused by HIGD1C and COX4I2 alter metabolic signaling by reactive oxygen species (ROS), lactate, and adenosine phosphates in hypoxia to regulate downstream G protein-coupled receptors and ion channels that stimulate neurotransmission remain to be elucidated (Figure 7A; Chang, 2017; Evans, 2019; Holmes et al., 2018; Ortega-Sáenz and López-Barneo, 2020).

CIV is the only ETC complex known to contain subunits that are tissue-specific and/or regulated by development, physiological changes (hypoxia and low glucose), and diseases (cancer, ischemia/reperfusion injury, and sepsis) (Sinkler et al., 2017; Timón-Gómez et al., 2020a). For example, COX4I2 is upregulated in hypoxia in general and promotes hypoxic pulmonary vasoconstriction in the lung (Sinkler et al., 2017; Sommer et al., 2017). Higd1c does not appear to be expressed in the lung at appreciable levels (Figure 1—figure supplement 3C and D), and the hypoxic response of the CB is faster than that of pulmonary arterial smooth muscle (seconds vs. minutes). In addition to the CB, Higd1c is expressed in kidney proximal tubules (Suganthan et al., 2014; Figure 1—figure supplement 4G–J). Compared to other nephron segments, the proximal tubules have the highest oxygen demand, exhibit greater ETC sensitivity to hypoxia, and are most susceptible to ischemia/reperfusion injury (Hall et al., 2009). We speculate that HIGD1C modulates ETC activity and matches oxygen utilization to physiological function not only in the CB but in oxygen-sensitive cells in other organs. Due to imaging resolution limitations, our in situ hybridization results do not rule out the possibility that in the CB Higd1c is expressed in both glomus cells and sustentacular glial-like cells that ensheath them (Figure 1D and E), as these cell types are proposed to cooperate to promote sensory signaling (Leonard et al., 2018). Determining how HIGD1C and other atypical CIV proteins work together in the CB to mediate oxygen sensing will help us better understand how tissue- and condition-specific CIV subunits contribute to physiological function and disease and allow us to potentially target these proteins to treat diseases characterized by CB dysfunction.

Materials and methods

Mice

All animals were maintained in a barrier facility at 22–23°C with a 12 hr light/dark cycle and allowed ad libitum access to food and water. C57BL/6J (JAX) was used as the wild-type strain. Other mouse strains obtained from repositories were Th-Cre driver: B6.FVB(Cg)-Tg(Th-cre)FI172Gsat/Mmucd (MMRRC) (Gong et al., 2007) and ROSA-GCaMP3: B6;129S-Gt(ROSA)26Sortm38(CAG-GCaMP3)Hze/J (JAX) (Zariwala et al., 2012). Adult animals of both sexes from multiple litters were used in all experiments. Higd1c mutant strains were generated in this study by CRISPR/Cas9 gene editing. Higd1c+/+ and Higd1c-/- animals were generated from crosses between Higd1c+/- parents. All experiments with animals were approved by the Institutional Animal Care and Use Committees at the University of California, San Francisco (AN183237-03), and the University of Calgary (AC16-0204).

Human tissue

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For human tissue, CB bifurcations were procured from research-consented, deidentified organ transplant donors through a collaboration with the UCSF VITAL Core (https://surgeryresearch.ucsf.edu/laboratories-research-centers/vital-core.aspx) and designated as non-human subjects research specimens by the UCSF IRB.

Human cell lines and cell culture conditions

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Human HEK293T embryonic kidney cells (CRL-3216, RRID:CVCL-0063) were obtained from ATCC. Cells were cultured in high-glucose Dulbecco’s modified Eagle’s medium (DMEM, Life Technologies) supplemented with 10% fetal bovine serum (FBS), 2 mM L-glutamine, 1 mM sodium pyruvate, and 50 mg/ml uridine at 37°C under 5% CO2. Cell lines were routinely analyzed for mycoplasma contamination.

Transgenic mice

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Higd1c mutants were generated by injecting C57BL/6J embryos with in vitro transcribed sgRNA-1 and sgRNA-2 (10 ng/µl each) together with Cas9 mRNA (50 ng/µl) and transferring injected embryos to pseudo-pregnant CD-1 females. Six founders were born and bred to C57BL/6J animals to isolate individual mutations transmitted through the germline, and sequences around sgRNA targets were PCR amplified and sequenced to identify mutations (Figure 1—figure supplement 2A–C). Higd1c mutant lines were maintained by breeding Higd1c+/-animals to each other.

RNA purification and RT-qPCR

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For mouse CB and kidney tissue, animals were anesthetized with isoflurane and decapitated, and tissues were dissected immediately. For all other tissues, animals were anesthetized and exsanguinated by perfusing PBS through the heart before decapitation and dissection. For human tissue, CB bifurcations were stored and transported in Belzer UW Cold Storage Solution (Bridge to Life) on ice. CBs were then dissected in UW Solution within 18 hr after harvest. After dissection, tissues were transferred to RNAprotect Tissue Reagent (QIAGEN) and stored at 4°C. For CB, kidney, adrenal gland, and all neuronal tissues, tissue pieces were disrupted and homogenized in a guanidine-isothiocyanate lysis buffer (Buffer RLT, QIAGEN) using a glass tissue grinder (Corning), followed by a 23-gauge needle and syringe, and purified by silica-membrane columns using the RNeasy Micro Kit (QIAGEN). For heart, liver, lung, and spleen, tissue pieces were ground using a glass tissue grinder in TRIzol (Invitrogen), and RNA was purified by acid guanidinium thiocyanate-phenol-chloroform extraction followed by isopropanol precipitation. For cell culture, cells were pelleted and resuspended in Buffer RLT before RNA purification using columns. RNA quality was assessed by visualizing 28S and 18S rRNA by agarose gel electrophoresis, and RNA concentration was measured with a Nanodrop ND-1000 Spectrophotometer (Thermo). RNA was stored at –80°C.

Two-step RT-qPCR was performed. First, purified total RNA was synthesized into cDNA:RNA hybrids with Maxima H Minus Reverse Transcriptase (Thermo) and primed using equal amounts of oligo(dT)15 primers (Promega) and random hexamers (Thermo). RNasin Plus RNase Inhibitor (Promega) was also added to the mixture. Next, qPCR was performed using PowerUp SYBR Green Master Mix (Applied Biosystems), at 10 µl reaction volume, following the manufacturer’s instructions. Three technical replicates were performed for each reaction and plated in TempPlate 384-well PCR plates (USA Scientific). Sample plates were run using a QuantStudio 5 Real-Time PCR System (Applied Biosystems) using a 40-cycle amplification protocol.

QuantStudio software was used to calculate threshold cycle (Ct) values. Undetermined Ct values were set to Ct = 40. Ct values were averaged for all technical replicates for each biological sample and normalized to either Actb or to GAPDH, using the ΔCt method.

BaseScope in situ hybridization

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Animals were anesthetized with isoflurane, decapitated, and dissected. Tissue was fixed in RNase-free 4% PFA/PBS overnight at 4°C and equilibrated serially in 10% sucrose/PBS for >1 hr, 20% sucrose/PBS for >2 hr, and 30% sucrose/PBS overnight, all at 4°C. Tissue was then embedded in O.C.T. (TissueTek) and stored at –80°C. The tissue was sectioned at 10 μm using a Leica CM3050S cryostat and stored at –80°C.

Following the BaseScope protocol for fixed frozen sections, slides were baked for 50 min at 60°C and post-fixed with 10% neutral-buffered saline for 15 min at 60°C. This was followed by target retrieval for 5 min at 100°C and protease III treatment for 30 min at 40°C. Using the BaseScope Duplex Detection Reagent kit (Advanced Cell Diagnostics, 323810), subsequent steps of hybridization and detection followed the vendor’s protocol. Probes are listed in Table 2. The probe set for Higd1c was custom-designed to target only the first two exons of Higd1c. For detection of Th mRNA, amplification steps 7 and 8 were reduced from 30 min and 15 min, respectively, to 15 min and 7.5 min for some samples. Images were collected on a Nikon Ti widefield inverted microscope using a DS-Ri2 color camera. Two sets of experiments were performed on tissues from C57BL/6J (2), Higd1c+/+ (3), and Higd1c-/- (2) animals (Figure 1D and E, Figure 1—figure supplement 4A–E,G–J).

Table 2
Reagents and resources.
Reagent or resourceSourceIdentifier
Mouse strains
C57BL/6J (wild-type)JAX000664
B6.FVB(Cg)-Tg(Th-cre)FI172Gsat/MmucdMMRRC031029-UCD
B6;129S-Gt(ROSA)26Sortm38(CAG-GCaMP3)Hze/JJAX014538
B6.Higd1c 3-1This paper
B6.Higd1c 1-1This paper
B6.Higd1c 5-3This paper
sgRNA primers (target sequence in bold)
sgRNA-1 (forward): TAATACGACTCACTATAGGGAGTCTCTCGATTTCCGGGTTTTAGAGCTAGAAThis paper
sgRNA-2 (forward): TAATACGACTCACTATAGGCTGATTTAAGGAGTGAGTGCGTTTTAGAGCTAGAAThis paper
sgRNA (reverse, common): AAAAAAAGCACCGACTCGGTGCCACTTTTTCAAGTTGATAACGGACTA
GCCTTATTTTAACTTGCTATTTCTAGCTCTAAAAC
This paper
Genotyping primers
Higd1c-P8: GTCAGGTGGCCCCTGATGAAAThis paper
Higd1c-P9: GTGCACGAGCAGACTGGTTCTThis paper
Higd1c-P11: GGATATCACAGCCACAGAGGACGThis paper
Mouse qPCR primers
Actb-F: AGCCATGTACGTAGCCATCCThis paper
Actb-R: GCCATCTCTTGCTCGAAGTCThis paper
Higd1c (5 exon)-F: CACGTACAAGGGCTGCATGGThis paper
Higd1c (5 exon)-R: ACCTAGAGTCACGGCTCCCThis paper
Higd1c (4 exon)-F: CCAGCACGTACAAGAGAGAAAThis paper
Higd1c (4 exon)-R: ACGTGGATGAGATGAAGGGACThis paper
Rat qPCR primers
GADPH-F: CAAGTTCAACGGCACAGTCAAGKim et al., 2011
GADPH-R: ACATACTCAGCACCAGCATCACKim et al., 2011
Higd1c-F1: CCTGTGCTGATCAAAGAGCAThis paper
Higd1c-R1: CTGACCACTCATCTGAAGACThis paper
Higd1c-R2: CTGCTGACCACTCATCTGAAThis paper
Kcnk3-F: GCAGAAGCCGCAGGAGTTCKim et al., 2011
Kcnk3-R: GCCCGCACAGTTGGAGATTTAGKim et al., 2011
Kcnk9-F: CGGTGCCTTCCTCAATCTTGTGKim et al., 2011
Kcnk9-R: TGGTGCCTCTTGCGACTCTGKim et al., 2011
Th-F: TCGGAAGCTGATTGCAGAGAFeng et al., 2020
Th-R: TTCCGCTGTGTATTCCACATGFeng et al., 2020
Olr59-F: TCATTCACGCTCTCTCAGCAvon der Weid et al., 2015
Olr59-R: CCATGCCGATTTGGACTGTTvon der Weid et al., 2015
Human qPCR primers
GADPH-F: ACCACAGTCCATGCCATCACMaßberg et al., 2016
GADPH-R: TCCCACCACCCTGTTGCTGTAMaßberg et al., 2016
HIGD1A-F1: CAACAGACACAGGTGTTTCCThis paper
HIGD1A-R1: CAATTGCTGCAAAACCCGCTThis paper
HIGD2A-F: GCCCCACTGTTTACAGGAATThis paper
HIGD2A-R: GCGCATCATGAGCTGAGAGThis paper
HIGD1C-F: GAAGGCCAATTATCCCGACTThis paper
HIGD1C-R: GCTTGTAAAGACCACAGGACThis paper
COX4I1-F: CAAGCGAGCAATTTCCACCTThis paper
COX4I1-R: CCTTCTCCTTCAATGCCTTCThis paper
COX4I2-F: GAGGGATGCACAGCTCAGAAThis paper
COX4I2-R: CTTCTCCTTCTCCTTCAGGGThis paper
NDUFA4L2-F: GATGATCGGCTTAATCTGCCThis paper
NDUFA4L2-R: GTATTGGTCATTGGGGCTCAThis paper
TH-F: GCTGGACAAGTGTCATCACCTGOriGeneHP234519
TH-R: CCTGTACTGGAAGGCGATCTCAOriGeneHP234519
OR51E2-F2: TCATCCCATTGTGCGTGTTGThis paper
OR51E2-R2: CACCCGTGTTCTGATCTGTTTGThis paper
BaseScope in situ hybridization probes
BA-Mm-Higd1c-2zz-stACD862241
BA-Mm-Th-3EJ-C2ACD854771-C2
dapB-1ZZ-C1/dapB-1ZZ-C2ACD700141
Mm-Ppib-1ZZACD701081
Mm-Polr2a-1ZZ-C2ACD701101-C2
Plasmids
HIGD1C-Myc-FLAG in pCMV6-Entry (human)OriGeneRC225015
Higd1c-Myc-FLAG in pCMV6-Entry (mouse)OriGeneMR220387
COX4I1-Myc-FLAG in pCMV6-EntryOriGeneRC209374
COX4I2-Myc-FLAG in pCMV6-EntryOriGeneRC209204
pCMV6-A-Entry-HygroOriGenePS100024
pCMV6-A-Entry-BSDOriGenePS100022
HIGD1A-Myc-FLAG in pCMV6-A-Entry-HygroTimón-Gómez et al., 2020b
HIGD2A-Myc-FLAG in pCMV6-A-Entry-HygroTimón-Gómez et al., 2020b
HIGD1C-Myc-FLAG in pCMV6-A-Entry-Hygro (human)This paper
Higd1c-Myc-FLAG in pCMV6-A-Entry-Hygro (mouse)This paper
COX4I1-Myc-FLAG in pCMV6-A-Entry-BSDThis paper
COX4I2-Myc-FLAG in pCMV6-A-Entry-BSDThis paper
Primary antibodies/stains
Mouse anti-DDK/FLAGOriGeneTA50011
Mouse anti-HSP60ECM BiosciencesHM-4381
Rabbit anti-THAbcamab112
Rat anti-CD31BD Pharmingen553370
Lotus tetragonolobus lectin-FluoresceinVector LabsFL-1321
Mouse anti-ATP5AAbcamab14748
Mouse anti-β-ACTINAbcamab8227
Mouse anti-CORE2Abcamab8227
Mouse anti-COX1Abcamab14705
Mouse anti-COX4I1Abcamab14744
Rabbit anti-COX4I2AbnovaH00084701-M01
Mouse anti-COX5BSanta Cruzsc-374417
Mouse anti-β-TUBULINSigma-AldrichC4585
Rabbit anti-UQCRBAbcamab122837
Mouse anti-NDUFA9Abcamab14713
Rabbit anti-NDUFB11Abcamab183716
Rabbit anti-SDHAAbcamab14715
Mouse anti-cytochrome cSanta Cruzsc-13156

Immunostaining

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Cultured cells on coverslips were fixed with 1% or 4% PFA/PBS for 10 min at 22°C and used immediately or stored in PBS at 4°C. Tissue was fixed in 4% PFA/PBS for 10 min at 22°C and equilibrated in 30% sucrose overnight at 4°C. Tissue was embedded in O.C.T. (TissueTek) and stored at –80°C. Sections were cut at 10 μm using a Leica CM3050S cryostat and stored at –80°C. Fixed cells or tissue sections were incubated with primary antibodies overnight at 4°C. Primary antibodies were mouse anti-DDK/FLAG, mouse anti-HSP60, rabbit anti-TH, and rat anti-CD31, all used at 1:500. For kidney sections, fluorescein-labeled Lotus tetragonolobus lectin (LTL) was added during the primary antibody treatment. Incubation with secondary antibodies (1:250) conjugated to either Alexa Fluor 488, Alexa Fluor 555 (Life Technologies), or Cy3 (Jackson ImmunoResearch) was 45 min at 22°C. Samples were then incubated with DAPI (1 ng/ml, Life Technologies) for 5 min at 22°C and mounted in Mowiol 4-88 (Polysciences) with DABCO (25 mg/ml, Sigma-Aldrich). Samples were imaged using a Leica SPE confocal microscope for cell culture and a Zeiss Axio Observer D1 widefield inverted microscope for tissue sections. Quantification of TH-positive cells was performed on 1/3 of the total CB using 1 of 3 sets of adjacent sections (Figure 1G–I).

Whole-body plethysmography

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Adult mice were removed from the housing room and placed in the procedure room for a minimum of 1 hr before starting the experiment to acclimate. Ventilation of unanesthetized, awake mice was measured using a commercial system for whole-body plethysmography (Scireq). Chamber pressure was detected by a pressure transducer and temperature and humidity by a sensor. These signals were integrated using IOX2 software (Scireq) to calculate the instantaneous flow rate. Baseline breathing was established during a period of at least 30 min in control gas. The baseline was followed by two hypoxic periods and one hypercapnic period, each lasting 5 min, interspersed with recovery periods of 10 min in control gas (Figure 2—figure supplement 1A–C). Gas mixtures for control, hypoxia, and hypercapnia were 21% O2/79% N2, 10% O2/90% N2, and 5% CO2/21% O2/79% N2, respectively (Airgas). The flow rate was held constant at 1.5 l/min by a flowmeter.

Breathing traces were collected, and ventilatory parameters were calculated by IOX2 software (Scireq). Breath inclusion criteria were set in the software to the following: (1) inspiratory time (0.07–1 s), (2) expiratory time (0.1–1 s), (3) tidal volume (0.05–0.8 ml), and (4) respiratory rate (10–320 breaths/ml). Data for all accepted breaths were exported and processed using a custom R script to calculate the average respiratory rate, tidal volume, and minute ventilation for each period. Trials were rejected if many accepted breaths occurred during periods of animal sniffing, grooming, or movement; we used a respiratory rate of 215 breaths/ml as a cutoff for inclusion of trials. A trial was rejected if any of the normoxic periods had an average respiratory rate that exceeded 215 breath/min (comparable to the mean of wild-type in hypoxia) in order to assess calm breathing and exclude artifacts from sniffing, grooming, and movement that correlated with high-frequency events above the ventilation in hypoxia. If a trial was rejected, the animal was retested on subsequent days, for up to four trials, until stable ventilation was reached in control normoxic periods. Data collection and analysis were automated using above inclusion/exclusion criteria. The percentage of experiments rejected between Higd1c+/+ and Higd1c-/- animals by allele were not statistically significant by the Z-test of proportions (p=0.7039, 0.5353, and 0.7114 for 1-1, 3-1, and 5-3 alleles, respectively). Because the effect size could not be estimated and variance for Higd1c animals was unknown, no sample size determination was performed, but sample sizes were comparable to other published studies (Del Rio et al., 2013; Moreno-Domínguez et al., 2020; Soliz et al., 2005).

We did not normalize tidal volume or minute ventilation to body weight because for the animals used in our study body weight did not correlate well with respiratory rate, tidal volume, or minute ventilation in wild-type or mutant animals in normoxia or hypoxia. Body weights of Higd1c+/+ and Higd1c-/- animals were not significantly different by two-way ANOVA with Sidak correction (p=0.9905, 0.9255, and 0.9562 for 1-1, 3-1, and 5-3 alleles, respectively). Nevertheless, we verified that all differences that were statistically significant without normalizing by body weight were also significant if we normalized to body weight (p<0.05). In addition to comparing mean values of ventilatory parameters, we showed the % change in the ventilatory parameters for each animal before and after hypoxia (‘Hypoxic response’), using each animal as its own control.

Carotid sinus nerve recordings

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Animals were heavily anesthetized with isoflurane and then decapitated (lower cervical level). The carotid bifurcation, including the CB, carotid sinus nerve (CSN), and superior cervical ganglion, was quickly isolated en bloc for in vitro perfusion as described previously (Roy et al., 2012). The carotid bifurcation was then transferred to a dissection dish containing physiological saline (115 mM NaCl, 4 mM KCl, 24 mM NaHCO3, 2 mM CaCl2, 1.25 mM NaH2PO4, 1 mM MgSO4, 10 mM glucose, 12 mM sucrose) bubbling 95% O2/5% CO2. After 15–20 min, the isolated tissue was transferred to a recording chamber (AR; custom-made) with a built‐in waterfed heating circuit, and the common carotid artery was immediately cannulated for luminal perfusion with physiological saline equilibrated with 100 mmHg PO2 and 35 mmHg PCO2 (balance N2). After gross dissection, connective tissue was removed, and the CSN was carefully desheathed. The carotid sinus region was bisected. The occipital and internal and external carotid arteries were ligated, and small incisions were made on the internal and external carotid arteries to allow perfusate to exit. A peristaltic pump was used to set the perfusion rate at 7 ml/min, which was sufficient to maintain a constant pressure of 90–100 mmHg at the tip of the cannula. The perfusate was equilibrated with computer‐controlled gas mixtures using CO2 and O2 gas analyzers (CA-2A and PA1B, Sable Systems); a gas mixture of 100 mmHg PO2 and 35 mmHg PCO2 (balance N2) was used to start the experiments (yielding pH ∼ 7.4). Before reaching the cannula, the perfusate was passed through a bubble trap and heat exchanger. The temperature of the perfusate was measured continuously as it departed the preparation and maintained at 37 ± 0.5°C. The effluent from the chamber was recirculated.

Chemosensory discharge was recorded extracellularly from the whole desheathed CSN, which was placed on a platinum electrode and lifted into a thin film of paraffin oil. A reference electrode was placed close to the bifurcation. CSN activity was monitored using a differential AC amplifier (Model 1700, A‐M Systems) and a secondary amplifier (Model 440, Brownlee Precision). The neural activity was amplified, filtered (0.3–1 kHz), displayed on an oscilloscope, rectified, integrated (200 ms time constant), and stored on a computer using an analog‐to‐digital board (Digidata 1322A, Axon Instruments) and data acquisition software (Axoscope 9.0). Recording was only attempted in nerves that survived cleaning and desheathing. The presence of action potentials under baseline conditions was used as the only test of preparation viability; data was obtained from all preparations deemed viable according to this criterion.

The following protocol was used for all experiments: (1) the CB was perfused for 5 min with normoxia (100 mmHg PO2/35 mmHg PCO2) to determine baseline CSN activity; (2) neural responses were obtained by challenging the CB for 4 min with mild, moderate, and severe hypoxia (80, 60, and 40 mmHg PO2, respectively) interspersed with normoxia; and (3) a hypercapnic (60 mmHg PCO2) challenge was given for 4 min (Figure 3A and B).

Data were analyzed offline using custom software (Wilson, 2022). CSN activity was divided into 60 s time bins, and the activity in each bin was rectified and summed (expressed as integrated neural discharge). The neural responses for different conditions in the protocol were normalized to the baseline (normoxic) condition. Data acquisition and CSN activity analysis were performed blinded to genotype.

Calcium imaging

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Th-CreTg/+; ROSA-GCaMP3Tg/Tg; Higd1c+/+ and Th-CreTg/+; ROSA-GCaMP3Tg/Tg; Higd1c-/- animals expressing GCaMP3 in glomus cells were generated, and CB was imaged as previously described (Chang et al., 2015). Animals were anesthetized with isoflurane and decapitated. Carotid bifurcations were dissected and cleaned in PBS to keep only the CB attached to the bifurcation. The preparation was then incubated in a physiological buffer (115 mM NaCl, 5 mM KCl, 24 mM NaHCO3, 2 mM CaCl2, 1 mM MgCl2, 11 mM glucose) at 26°C in a tissue culture incubator with 5% CO2 before transfer to the recording chamber for imaging.

At baseline, the CB was superfused by gravity at 5 ml/min with physiological buffer bubbling 95% O2/5% CO2 in the reservoir to maintain PO2 ~ 700 mmHg and pH 7.4 in the imaging chamber at 22°C. Buffer pH was lowered to 6.8 by reducing NaHCO3 to 7 mM with equimolar substitution of NaCl while bubbling 95% O2/5% CO2. Two levels of hypoxia at PO2 ~ 25 mmHg and 50 mmHg were generated by bubbling physiological buffer in the reservoir with 90% N2/5% O2/5% CO2 and 95% N2/5% CO2, respectively. The preparation was sequentially stimulated with low pH and hypoxia for periods of 4.5 min each, with 3 min of recovery between stimuli. These were followed by KCl (40 mM) and CN (1 mM) for periods of 2.25 min each, with 4.5 min of recovery between stimuli (Figure 3E and F).

Imaging was performed on a Zeiss LSM 7 MP two-photon microscope with a Coherent Ultra II Chameleon laser and a sensitive gallium arsenide phosphide (GaAsP) detector. Preparations were excited at 960 nm, and emission was collected at 500–550 nm. Using a ×20 water immersion objective, we acquired Z-stacks at 2 µm intervals at a resolution of 1024 × 1024 pixels and up to 60–85 µm of tissue depth.

Regions of interest (ROIs) corresponding to individual glomus cells were identified and analyzed in ImageJ. All ROIs were included in the data. Fpre fluorescence was defined as the average fluorescence over the four frames immediately prior to the onset of the stimulus in the chamber. Mean and peak fluorescence were calculated over the duration when the stimulus was present in the imaging chamber. The ratio of Fstim/Fpre was calculated by dividing the mean and peak by Fpre just preceding the stimulus. Data acquisition and ROI analysis were carried out blinded to genotype.

Metabolic imaging

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Higd1c+/+ and Higd1c -/- animals were anesthetized with isoflurane and decapitated. Carotid bifurcations were dissected and cleaned in PBS to keep only the CB attached to the bifurcation. The preparation was then incubated in 50 µg/ml rhodamine 123 (Thermo Fisher) in a physiological buffer (115 mM NaCl, 5 mM KCl, 24 mM NaHCO3, 2 mM CaCl2, 1 mM MgCl2, 11 mM glucose) at 26°C in a tissue culture incubator with 5% CO2 for 30 min before transfer to the recording chamber for imaging.

At baseline, the CB was superfused by gravity at 5 ml/min with physiological buffer bubbling 95% O2/5% CO2 in the reservoir to maintain PO2 ~ 700 mmHg and pH 7.4 in the imaging chamber at 22°C. Hypoxia down to PO2 ~ 10 mmHg was generated by bubbling physiological buffer in the reservoir with 95% N2/5% CO2 for 7.5 min. PO2 was measured using a Clark style oxygen sensor (OX-50, Unisense). After 6 min of baseline recording, the preparation was stimulated with hypoxia for a period of 7.5 min followed by 7.5 min of recovery between stimuli (Figure 4—figure supplement 1). This was followed by CN (1 mM) and FCCP (2 µM) for periods of 2.25 min each, with 7.5 min of recovery between stimuli. For control experiments with a single FCCP stimulus, the protocol was as follows: 6 min physiological buffer, 2.25 min FCCP (2 µM), and 6 min physiological buffer, all in buffer bubbled with 95% N2/5% CO2. Imaging and analysis methods were the same for both experimental protocols.

Imaging was performed on a Zeiss LSM 7 MP two-photon microscope with a Coherent Ultra II Chameleon laser and a sensitive gallium arsenide phosphide (GaAsP) detector. Preparations were excited at 960 nm, and emission was collected at 500–550 nm. Using a ×20 water immersion objective, we acquired Z-stacks at 2 µm intervals at a resolution of 1024 × 1024 pixels and up to 60–85 µm of tissue depth.

ROIs corresponding to individual glomus cells were identified and analyzed in ImageJ. All ROIs were included in the data except as indicated in specific analyses. We performed baseline subtraction after linear interpolation to account for a linear decrease in baseline fluorescence occurring over the time course of the experiment. First, the fluorescence trace of each ROI was smoothed using a three-point centered rolling average, and the baseline was calculated using linear interpolation between the inter-stimulus intervals. This baseline was then subtracted from the original traces. Fpre fluorescence was defined as the fluorescence immediately prior to the onset of the stimulus in the chamber. Mean and peak fluorescence were calculated over the duration when the stimulus was present in the imaging chamber. The ratio of Fstim/Fpre was calculated by dividing the mean and peak by Fpre just preceding the stimulus. Data acquisition and ROI analysis were carried out blinded to genotype.

Stable cell line construction

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HIGD1C-Myc-DDK/FLAG constructs in pCMV6-Entry were cloned under the control of a CMV promoter in the pCMV6-A-Entry-Hygro plasmid, and COX4I1/COX4I2-Myc-DDK constructs in pCMV6-Entry were cloned in the pCMV6-A-Entry-BSD, using Sfg1 and Pme1 sites. 1–2 µg of vector DNA was mixed with 5 µl of Lipofectamine (Thermo Fisher) in OPTIMEM-I media (GIBCO) to transfect 1.5 × 106 cells according tothe manufacturer’s instructions. After 48 hr, media was supplemented with 200 µg/ml of hygromycin or 10 µg/ml of blasticidin and maintained for at least 21 days.

Cell culture experimental conditions

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HIGD1A-KO and HIGD2A-KO cells were constructed in HEK293T using the TALEN technology as described in Timón-Gómez et al., 2020b. HEK293T cells were grown in 25 mM glucose DMEM (Life Technologies) supplemented with 10% FBS, 2 mM L-glutamine, 1 mM sodium pyruvate, and 50 µg/ml uridine without antibiotics, at 37°C under 5% CO2. For metabolic imaging involving HEK293T cells, 10 mm glass coverslips were placed into 1.96 cm2 wells and coated with 0.2 mg/ml poly-D-lysine for at least 2 hrat room temperature (RT). Two days before the experiment, 7.5 × 104 cells in 500 µl of cell media were seeded into each well. For hypoxia experiments, cell cultures were exposed to 1% O2 for up to 24 hr, or as controls, to standard cell culture oxygen tension (18.6% O2). Experiments under controlled oxygen tensions were performed in a HypOxystation H35 (HypOxygen) to minimize undesired oxygen reperfusion. Routinely, cells were analyzed for mycoplasma contamination.

Mitochondrial biochemistry

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Mitochondrial fractions were obtained as previously described in Bourens et al., 2014; Fernández-Vizarra et al., 2010; Timón-Gómez et al., 2020b from ten 80% confluent 15 cm plates or from 1 l of liquid culture. Whole-cell extracts were obtained from pelleted cells solubilized in RIPA buffer (25 mM Tris–HCl [pH 7.6], 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, and 0.1% SDS) with 1 mM PMSF for 20 min. Extracts were cleared after 5 min centrifugation at 15,000 rpm at 4°C.

Proteins were extracted from purified mitochondria in native conditions with either digitonin at a proportion of 1:2 of protein or with n-dodecyl-β-D-maltoside (DDM) at a concentration of 0.4%. Samples were incubated on ice for 10 min and pelleted at 10,000 × g for 30 min at 4°C. Samples were prepared for Blue Native Electrophoresis and/or Complex I and Complex IV in-gel activity (IGA) assays as described (Timón-Gómez et al., 2020c). Immunoprecipitation of HIGD1C-Myc-DDK-tagged proteins was performed using 1 mg of mitochondria, extracted in 1.5 M aminocaproic acid, 50 mM Bis-Tris pH 7, 1% digitonin, 1 mM PMSF, and 8 µl of protease inhibitor cocktail (Sigma, P8340) for 10 min on ice. Samples were pelleted at 10,000 × g for 30 min at 4°C, and the extract (Ex) was incubated for 2–3 hr at 4°C with 30 µl of FLAG-conjugated beads (anti-DYDDDDDK beads, Sigma) or empty beads (Thermo Scientific), previously washed in PBS. Beads were washed five times in 1 ml of 1.5 M aminocaproic acid, 50 mM Bis-Tris (pH 7), 0.1% digitonin, and boiled for 5 min with 50 µl of Laemmli buffer two times to release bound material. Representative amounts of all fractions were loaded on 14% SDS-PAGE gels.

Complex specific assay and oxygen consumption rate

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Mitochondrial respiratory chain CIV activity was performed according to established methods (Barrientos et al., 2009). Citrate synthase activity was used as a control. Enzymatic activities were expressed relative to the total amount of extracted protein.

OCR in normoxia was measured polarographically using a Clark-type electrode from Hansatech Instruments (Norfolk, UK) at 37°C. Approximately 2 × 106 cells were trypsinized and washed with PBS, and then resuspended in 0.5 ml of permeabilized-cell respiration buffer (PRB) containing 0.3 M mannitol, 10 mM KCl, 5 mM MgCl2, 0.5 mM EDTA, 0.5 mM EGTA, 1 mg/ml BSA, and 10 mM KH2PO4 (pH 7.4) at 37°C, supplemented with 10 units of hexokinase. The cell suspension was immediately placed into the polarographic chamber to measure endogenous respiration. Digitonin permeabilization (0.02 mg/ml) was performed to assay substrate-driven respiration, using FADH-linked substrates (10 mM succinate plus 5 mM glycerol-3-phosphate) in the presence of 2.5 mM ADP (phosphorylation state). Oligomycin-driven ATP synthesis inhibition (0.75 µg/ml) was assayed to obtain the non-phosphorylating state. Maximal oxygen consumption was reached by successive addition of the uncoupler CCCP (up to 0.4 µM). 0.8 µM KCN was used to assess the mitochondrial specificity of the oxygen consumption measured, and values were normalized by total cell number.

High-resolution respirometry was used to determine mitochondrial oxygen consumption and ascorbate/TMPD-dependent respiration in normoxia and hypoxia. Measurements were performed in intact or digitonin-permeabilized cells, respectively, in an Oxygraph-2k (Oroboros Instruments, Austria). Assays were performed according to manufacturer’s SUIT protocols, using 2–4 × 105 cells washed with PBS and resuspended in Mir05 medium, and results were normalized by cell number. To analyze oxygen kinetics and determine the apparent Km (p50mito) for oxygen, we used the software Datlab 2 (Oroboros Instruments) by integrating a hyperbolic function of mitochondrial oxygen consumption and oxygen pressure during and transition from aerobic respiration to anoxia (Gnaiger, 2001; Gnaiger et al., 1995). For this purpose, intact cell respiration experiments were performed using 2 × 106 cells in a respiration medium containing 0.5 mM EGTA, 3 mM MgCl2, 60 mM K-lactobionate, 20 mM taurine, 10 mM KH2PO4, 20 mM HEPES, 110 mM sucrose, and 1 mg/ml BSA.

Extraction of total mitochondrial cytochromes

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8 mg of mitochondria were extracted with 330 mM KCl, 50 mM Tris–HCl (pH 7.5), and 10% potassium deoxycholate. Samples were mixed by inversion three times and pelleted for 15 min at 40,000 × g at 4°C. The clear supernatant was transferred to a new tube, and a final concentration of 2% potassium cholate was added. The extract was divided into two equal aliquots in 1 ml quartz cuvettes, and the baseline was established. Then, the reference aliquot was oxidized with potassium ferricyanide, and the other was reduced with a few grains of sodium dithionite. Differential reduced vs. oxidized spectrum was recorded from 450 to 650 nm.

Statistical analysis

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Data analysis and statistical tests were performed using Microsoft Excel, custom-written scripts in R, and GraphPad Prism software. All data are biological replicates. Group data were analyzed by the Shapiro–Wilk test to determine whether the data was normally distributed with the critical W value set at a 5% significance level. Normally distributed data are presented as mean ± standard error of the mean (SEM) and compared by one-way analysis of variance (ANOVA) followed by Tukey’s test or Holm–Sidak correction, two-way ANOVA followed by Tukey’s test for all pairwise comparisons or Sidak correction for multiple pairwise comparisons, or Dunnett’s test for multiple comparisons to a single group. For comparisons that included groups that did not fit the assumption of normal distribution, data are presented as median and interquartile interval and compared by Mann–Whitney U-tests followed by Holm–Sidak correction for multiple comparisons or Kruskal–Wallis test with Dunn’s test for multiple comparisons to a single group. For whole-body plethysmography experiments, 2/54 (hypoxia) and 7/54 (hypercapnia) data groups were not normally distributed (p<0.05 by Shapiro–Wilk test). All significant differences found by parametric statistical tests were significant using nonparametric tests. The Z-test of proportions was used to compare the proportion of glomus cells with responses at different thresholds. Chi-square test was performed for analysis of Mendelian inheritance of Higd1c alleles and to determine whether the distributions of glomus cells responsive to different hypoxic stimuli were drawn from the same population. All tests were two-tailed. No statistical method was used to predetermine sample size.

Materials availability

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All unique/stable reagents generated in this article (plasmids, cell line, and mice) are available upon request from Andy Chang (Andy.Chang@ucsf.edu) and Antoni Barrientos (abarrientos@med.miami.edu) with a completed Materials Transfer agreement. Custom scripts used for analysis are available as source code or in a public repository (Wilson, 2022).

Data availability

Data generated or analyzed during this study are included in the manuscript. Previously published RNAseq datasets were deposited in GEO under accession codes GSE72166 and GSE76579.

The following previously published data sets were used
    1. Chang AJ
    2. Ortega FE
    3. Riegler J
    4. Madison DV
    5. Krasnow MA
    (2015) NCBI Gene Expression Omnibus
    ID GSE72166. Expression profile of mouse carotid body and adrenal medulla.
    1. Matsunami H
    2. Zhou T
    3. Chien M
    (2016) NCBI Gene Expression Omnibus
    ID GSE76579. Single cell transcriptome analysis of mouse carotid body glomus cells.

References

    1. De Castro F
    (1928)
    Sur la structure et l’innervation du sinus carotidien de l’homme et des mammifères: nouveaux faits sur l’innervation et la fonction du glomus caroticum
    Trav Lab Rech Biol 25:331–380.
  1. Book
    1. Forster RE
    (1968)
    Proc Wates Foundation Symp on Arterial Chemoreceptors, Vol. 115
    Blackwell, Oxford: Chemoreceptors.
    1. Heymans C
    2. Bouckaert JJ
    3. Dautreband L
    (1930)
    Sinus carotidien et reflexes respiratoires, II. influences repiratoires reflexes de l’acidose, de d’alcalose, de l’anhydride carbonique, de l’ion hydrogene et de l’anoxemie: sinus carotidiens et echanges respiratoires dans les poumons et au dela des poumons
    Archives Internationales de Pharmacodynamie et de Therapie 39:400–408.
  2. Book
    1. Jobsis FF
    (1968)
    Section 3, respiration
    In: Jobsis FF, editors. In Handbook of Physiology. PlumX Metrics. pp. 1–109.
    1. Suganthan RN
    2. Pratap SV
    3. Morita EH
    4. Shunnosuke A
    (2014)
    Identification of a chimeric transcript formed by intergenic splicing of ubie2 and yghl1-4 in mouse
    Int Res J Biological Sci 3:52–59.

Decision letter

  1. David J Paterson
    Reviewing Editor; University of Oxford, United Kingdom
  2. Vivek Malhotra
    Senior Editor; The Barcelona Institute of Science and Technology, Spain
  3. Keith Buckler
    Reviewer; University of Oxford, United Kingdom
  4. Chris Wyatt
    Reviewer

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Decision letter after peer review:

Thank you for sending your article entitled "Tissue-specific mitochondrial HIGD1C promotes oxygen sensitivity in carotid body chemoreceptors" for peer review at eLife. Your article is being evaluated by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation is being overseen by a Reviewing Editor and Vivek Malhotra as the Senior Editor.

I am detailing below the major revisions requested by the reviewers. The list appears to be long, but many of the concerns can be addressed by rewriting and clarifying the text. The full comments of the reviewers follow the list of major revisions requested.

Major concerns

1. Parts of the manuscript are difficult to follow re data presentation since the data are densely reported in places. Eg Figure 1 Figure supplement 2 on page 9 is virtually impossible to read.

2. A tighter introduction is required re references where credit should be given to the early studies showing that hypoxia excites CB and breathing and chemodenervation abolishes the breathing responses (eg Neil; Torrance; Lahiri should be given credit in para 1 on page 3).

3. Additionally, primary references should be given for statements of fact like …'Under these pathological conditions, suppressing CB activity improves causal symptoms such as hypertension (REF), cardiac arrhythmias (REF), and insulin resistance (REF) (Iturriaga, 2018)'. Credit must be given to the primary source, not a review.

4. p 4 'We found that three such genes, Higd1c, Cox4i2, and Ndufa4l2, were expressed at higher levels in the mouse CB (Figure 1A)'. Are you confident that this expression is only in type 1 cells and not type 2 cells?

5. Much of the data presented has used parametric statistics on n of 3/3 or 4/4 samples eg Figure 1 supp 3 page 10. Are these data normally distributed to support parametric use of stats? Please comment on the sample re biological replicates v technical replicates. How were the data treated here?

6. The gel on p26 panel B looks over run. Comment?

7. Aspects of the data are very convincing. Whilst this large body of work shows the putative role of HIGD1C in oxygen sensing, the relationship between this protein and the graded response of afferent nerve firing to physiological levels of hypoxia remains to be established to support an essential role for this signalling pathway in hypoxic chemotransduction. This limitation should be acknowledged. Please comment?

8. With respect to the effects of Higd1c KO on ventilation. Although all KO's appear to have a blunted ventilatory response to hypoxia, a ventilatory response remains none the less. This is particularly evident for the 1.1 KO as shown in the example trace in Figure 2 supplement 1 A where the second response to a hypoxic stimulus looks very similar between the KO and normal mouse. This is a somewhat disappointing result in that it may limit the conclusions that can be drawn from this study. One could have hoped that a Higd1c KO would either eliminate the response to hypoxia or had no effect at all. As this is a very important piece of evidence I want to ask for more detail regarding the data and methods.

9. Forgive me if I have misunderstood but in the methods section you state that "we used a respiratory rate of 215 breaths/min (comparable to the mean of a wild type in hypoxia) as a cut off for inclusion in this study". It is unclear how this works. Are you rejecting recordings with RR in excess of this figure or below this figure? When are you making this decision, under normoxic conditions at the beginning of an experiment, under hypoxic conditions, or at any time in the recording? Can you clarify this point and indicate how often recordings were rejected by this criteria in the different mice?

10. Was there any notable difference in mouse behaviour between genotypes during plethysmography? Mice usually become much less active in hypoxia and basal metabolic rate goes down resulting in a fall in CO2 production and a drop in PaCO2 which leads to a fall in ventilation (hypoxic ventilatory decline: HVD). This often complicates the analysis/interpretation of responses to hypoxia. Over what time period do you measure changes in ventilation – over the entire period of exposure to hypoxia, at the peak? Or towards the end? Are changes in the rate of HVD influencing the comparison between KO and wt? Have you measured PaCO2 under hypoxic conditions? I would predict that it would be lower than under control conditions. Could you introduce a little CO2 in hypoxic conditions to try to neutralise this effect?

11. What happens if you do a sham switch (i.e. switch between two identical gasses/air), is there any startle response associated with just mechanically switching between two gas lines? If not what happens if you look specifically at the peak/early response to hypoxia before CO2 has much chance to fall?

12. Are Higd1c +/+ mice taken from your in house breeding programs generating Higd1c -/- mice or are they just off the shelf C57Bl/6J from Jax? If the latter how long are these mice held in your facility (under the same conditions as the KO mice) before being used?

13. In the methods section on nerve recordings you state that "Preparations were exposed to a brief hypoxic challenge (PO2 = 60 mmHg) to determine viability; preparations that failed to show a clear increase in activity during this challenge were discarded". You are testing the hypothesis that Higd1c is important/essential for the generation of the response to hypoxia so why exclude data from preparations that lack a hypoxic response? This is just what you are looking for! I hope this is just a mistake in writing up the methods, BUT if this is really what was done then the whole nerve recording study could be invalid (depending on just what proportion of preparations were actually discarded). If you want some sort of test for viability of the preparation, which is a good idea, then there are many other stimuli one could choose instead that do not involve mitochondrial function e.g hypercapnia/acidosis, high potassium, acetyl choline, TASK channel inhibitors/respiratory stimulants.

14. One of the key issues regarding the role of alternative mitochondrial subunits in the carotid body is not simply that they may affect the maximal turnover rate of cytochrome oxidase but whether they alter the kinetic parameters defining sensitivity to hypoxia (i.e. Km, oxygen affinity, P50 ). To determine these really requires making a number of measurements at different PO2 including a zero point (anoxia). This could have been done for both nerve recordings and calcium measurements. Unfortunately it was not, so we are left with data from both of these experiments which demonstrates that the response to hypoxia is smaller in the KO but we have no idea whether these kinetic parameters have changed or not. The study would be a lot stronger if you could demonstrate a change in Km in the Higd1c KO.

15. It would appear from the results obtained with Rh123 and the weak responses to FCCP that there was inadequate loading of this dye to make good measurements of mitochondrial potential (ψM) in many of the cells studied. If you look at the paper by Biscoe and Duchen they were achieving a 100% increase in Rh125 fluorescence upon adding FCCP, Anoxia or CN, not 20%. The level of loading is critical with this dye in order to get it to work properly in the de-quench mode. In addition, to correct for differences in dye loading, responses to acute hypoxia should probably be normalised not only to the baseline but also to the response to FCCP. The smaller response to hypoxia in Higd1c -/- could simply reflect lower dye loading, with consequent lower dynamic response from Rh123 to change in mitochondrial potential, rather than any actual change in ψM.

16. The response to anoxia has not been tested which again confounds attempts to determine a P50 for mitochondrial depolarisation. I note that the rate of change in PO2 (Figure 4 suppl 1 A) is rather slow so some Rh123 may also leak out of the cell during the recording. Were any corrections applied for dye leakage?

17. In summary the interpretation of this data is equivocal. Higd1c -/- may take up Rh123 less avidly than wt but is this due to a lower resting ψM or something else? This experiment needs repeating extending loading time or Rh123 concentration until robust responses to FCCP can be recorded.

18. If you want to see if genotype affects resting ψM you would probably be better not working in the quench mode but either using much lower concentrations of Rh123 or another probe, e.g. TMRM, and loading for a longer period of time (until dye uptake reaches a steady state without any quenching occuring).

19. Data in Fig6-E shows >= 40% inhibition of oxygen consumption under hypoxic conditions compared to normoxia in all HEK cell types studied. Given that the level of oxygen in hypoxia is stated to be 25 mmHg this is something of a surprise. The P50 for most cells is thought to be < 1mmHg. Something is wrong here. If you are using an Oroboros Oxygraph (as stated in methods) it should be possible to measure oxygen consumption from air all the way down to zero oxygen and derive an exact P50 for each cell type. This should be done. This is a very important experiment that proports to show that it is the combination of Higd1c and Cox4I2 that generates the unusual sensitivity of complex IV towards oxygen. Philosophically I like this hypothesis. If true it would mark a major advance in this field, but I want to see some hard data with rigorously determined kinetic measurements!

20. It would be better in future if the calcium imaging studies could be performed using the same perfused preparation that the nerve recording experiments used. This would remove the requirement for equilibrating superfusate with 95% oxygen which is far from physiological and would allow the carotid body tissue to be perfused with physiologically relevant levels of oxygen. However, superfusion with hyperoxic solutions is considered standard in many systems and so additional experiments are not required at this time.

21. Expanding the study to see if HIGD1A is expressed in carotid bodies of multiple species would strengthen the paper. It would also be interesting to see if it is absent in the carotid bodies of guinea pigs which are not acutely oxygen sensitive. Furthermore, chromaffin cells in fetal adrenal medulla are oxygen-sensitive whereas mature chromaffin cells are not, it would be fascinating to see if HIGD1A expression changes during the maturation of chromaffin cells. These possibilities might be discussed.

22. Tidal volume changes with the weight of the animals. Tidal volume should be adjusted for the weights of the animals tested. If there are weight differences between knockouts and wildtype it can have profound effects on the data.

Reviewer #1 (Recommendations for the authors):

Understanding the precise intracellular signalling pathways underpinning hypoxic sensitivity in the carotid body chemoreceptor has been a major unsolved area in sensory neurophysiology. Early studies almost 60 years ago suggested the importance of a metabolic signal coupled to the mitchrondria, which could regulate intracellular calcium homeostasis and exocystosis of excitatory transmitter in type I glomus cells.

Using RNAseq this manuscript has identified a novel gene that encodes protein regulation of Complex IV in the carotid body response to hypoxia. Here the authors found HIGD1C, a novel hypoxia-inducible gene domain factor isoform, as an electron transport chain Complex IV-interacting protein was almost exclusively expressed in the carotid body. Using a combination molecular biology, protein chemistry, genetic knock-out, calcium imaging and respiratory measurements, the authors elegantly demonstrated the physiological utlility of HIGD1C being required for carotid body oxygen sensing via enhanced Complex IV sensitivity to hypoxia. Deletion of the gene massively attenuated the chemoreceptor response to hypoxia, whereas of expression of HIGD1C could recapitulate the increased oxygen sensitivity of Complex IV in HEK 293T cells, but not the response to hypercapnia.

Whilst this large body of work shows the putative role of HIGD1C in oxygen sensing, the relationship between this protein and the graded response of afferent nerve firing to physiological levels of hypoxia remains to be established to support an essential role for this signalling pathway in hypoxic chemotransduction.

This is a large body of work supporting the idea that HIGD1C is required for hypoxic sensing in the mouse through the regulation complex IV. The experiments are well designed, complex and appear to have been carefully performed.

Specific comments for improvement:

Parts of the manuscript are difficult to follow re data presentation since the data are densely reported in places. Eg Figure 1 Figure supplement 2 on page 9 is virtually impossible to read.

A tighter introduction is required re references where credit should be given to the early studies showing that hypoxia excites CB and breathing and chemodenervation abolishes the breathing responses (eg Neil; Torrance; Lahiri should be given credit in para 1 on page 3).

Additionally, primary references should be given for statements of fact like …'Under these pathological conditions, suppressing CB activity improves causal symptoms such as hypertension (REF), cardiac arrhythmias (REF), and insulin resistance (REF) (Iturriaga, 2018)'. Credit must be given to the primary source, not a review.

p 4 'We found that three such genes, Higd1c, Cox4i2, and Ndufa4l2, were expressed at higher levels in the mouse CB (Figure 1A)'. Are you confident that this expression is only in type 1 cells and not type 2 cells?

Much of the data presented has used parametric statistics on n of 3/3 or 4/4 samples eg Figure 1 supp 3 page 10. Are these data normally distributed to support parametric use of stats? Please comment on the sample re biological replicates v technical replicates. How were the data treated here?

The gel on p26 panel B looks over run. Comment?

Aspects of the data are very convincing. Whilst this large body of work shows the putative role of HIGD1C in oxygen sensing, the relationship between this protein and the graded response of afferent nerve firing to physiological levels of hypoxia remains to be established to support an essential role for this signalling pathway in hypoxic chemotransduction. This limitation should be acknowledged. Please comment?

Reviewer #2 (Recommendations for the authors):

I have a number of major concerns about parts of this research which need to be addressed before I could comment on its conclusions and importance. Some of these may just require a better explanation or correction to the text (e.g. where there may be an ambiguity over how an experiment was conducted). Others may require further work

Major comments/Questions

General reporting of results

A very general comment I have about this paper is that numerous experiments, particularly in the latter half of this paper using HEK cells, have been conducted with an 'n' of only 3. I do not know what eLifes's normal expectations/requirements are but I would have thought that an 'n' of at least 4 or 5 independent observations should normally be required. Similarly, numerous gels/blots are presented without any indication of how often these types of experiments were repeated. This should be reported and the journal should have some policy over what is expected. To my mind there could be a substantial amount of further work that needs to be completed before this study could be formally published. Apart from this issue the statistics seem to have been done with suitable care and rigour.

Questions/suggested changes.

Plethysmography.

With respect to the effects of Higd1c KO on ventilation. Although all KO's appear to have a blunted ventilatory response to hypoxia, a ventilatory response remains none the less. This is particularly evident for the 1.1 KO as shown in the example trace in Figure 2 supplement 1 A where the second response to a hypoxic stimulus looks very similar between the KO and normal mouse. This is a somewhat disappointing result in that it may limit the conclusions that can be drawn from this study. One could have hoped that a Higd1c KO would either eliminate the response to hypoxia or had no effect at all. As this is a very important piece of evidence I want to ask for more detail regarding the data and methods.

Forgive me if I have misunderstood but in the methods section you state that "we used a respiratory rate of 215 breaths/min (comparable to the mean of a wild type in hypoxia) as a cut off for inclusion in this study". It is unclear how this works. Are you rejecting recordings with RR in excess of this figure or below this figure? When are you making this decision, under normoxic conditions at the beginning of an experiment, under hypoxic conditions, or at any time in the recording? Can you clarify this point and indicate how often recordings were rejected by this criteria in the different mice?

Was there any notable difference in mouse behaviour between genotypes during plethysmography? Mice usually become much less active in hypoxia and basal metabolic rate goes down resulting in a fall in CO2 production and a drop in PaCO2 which leads to a fall in ventilation (hypoxic ventilatory decline: HVD). This often complicates the analysis/interpretation of responses to hypoxia. Over what time period do you measure changes in ventilation – over the entire period of exposure to hypoxia, at the peak? Or towards the end? Are changes in the rate of HVD influencing the comparison between KO and wt? Have you measured PaCO2 under hypoxic conditions? I would predict that it would be lower than under control conditions. Could you introduce a little CO2 in hypoxic conditions to try to neutralise this effect?

What happens if you do a sham switch (i.e. switch between two identical gasses/air), is there any startle response associated with just mechanically switching between two gas lines? If not what happens if you look specifically at the peak/early response to hypoxia before CO2 has much chance to fall?

Are Higd1c +/+ mice taken from your in house breeding programs generating Higd1c -/- mice or are they just off the shelf C57Bl/6J from Jax? If the latter how long are these mice held in your facility (under the same conditions as the KO mice) before being used?

Nerve fibre recordings and calcium recordings.

In the methods section on nerve recordings you state that "Preparations were exposed to a brief hypoxic challenge (PO2 = 60 mmHg) to determine viability; preparations that failed to show a clear increase in activity during this challenge were discarded". You are testing the hypothesis that Higd1c is important/essential for the generation of the response to hypoxia so why exclude data from preparations that lack a hypoxic response? This is just what you are looking for! I hope this is just a mistake in writing up the methods, BUT if this is really what was done then the whole nerve recording study could be invalid (depending on just what proportion of preparations were actually discarded). If you want some sort of test for viability of the preparation, which is a good idea, then there are many other stimuli one could choose instead that do not involve mitochondrial function e.g hypercapnia/acidosis, high potassium, acetyl choline, TASK channel inhibitors/respiratory stimulants.

One of the key issues regarding the role of alternative mitochondrial subunits in the carotid body is not simply that they may affect the maximal turnover rate of cytochrome oxidase but whether they alter the kinetic parameters defining sensitivity to hypoxia (i.e. Km, oxygen affinity, P50 ). To determine these really requires making a number of measurements at different PO2 including a zero point (anoxia). This could have been done for both nerve recordings and calcium measurements. Unfortunately it was not, so we are left with data from both of these experiments which demonstrates that the response to hypoxia is smaller in the KO but we have no idea whether these kinetic parameters have changed or not. The study would be a lot stronger if you could demonstrate a change in Km in the Higd1c KO.

Rh123 experiments.

It would appear from the results obtained with Rh123 and the weak responses to FCCP that there was inadequate loading of this dye to make good measurements of mitochondrial potential (ψM) in many of the cells studied. If you look at the paper by Biscoe and Duchen they were achieving a 100% increase in Rh125 fluorescence upon adding FCCP, Anoxia or CN, not 20%. The level of loading is critical with this dye in order to get it to work properly in the de-quench mode. In addition, to correct for differences in dye loading, responses to acute hypoxia should probably be normalised not only to the baseline but also to the response to FCCP. The smaller response to hypoxia in Higd1c -/- could simply reflect lower dye loading, with consequent lower dynamic response from Rh123 to change in mitochondrial potential, rather than any actual change in ψM.

The response to anoxia has not been tested which again confounds attempts to determine a P50 for mitochondrial depolarisation. I note that the rate of change in PO2 (Figure 4 suppl 1 A) is rather slow so some Rh123 may also leak out of the cell during the recording. Were any corrections applied for dye leakage?

In summary the interpretation of this data is equivocal. Higd1c -/- may take up Rh123 less avidly than wt but is this due to a lower resting ψM or something else? This experiment needs repeating extending loading time or Rh123 concentration until robust responses to FCCP can be recorded.

If you want to see if genotype affects resting ψM you would probably be better not working in the quench mode but either using much lower concentrations of Rh123 or another probe, e.g. TMRM, and loading for a longer period of time (until dye uptake reaches a steady state without any quenching occuring).

CIV sensitivity to Hypoxia in HEK.

Data in Fig6-E shows >= 40% inhibition of oxygen consumption under hypoxic conditions compared to normoxia in all HEK cell types studied. Given that the level of oxygen in hypoxia is stated to be 25 mmHg this is something of a surprise. The P50 for most cells is thought to be < 1mmHg. Something is wrong here. If you are using an Oroboros Oxygraph (as stated in methods) it should be possible to measure oxygen consumption from air all the way down to zero oxygen and derive an exact P50 for each cell type. This should be done. This is a very important experiment that proports to show that it is the combination of Higd1c and Cox4I2 that generates the unusual sensitivity of complex IV towards oxygen. Philosophically I like this hypothesis. If true it would mark a major advance in this field, but I want to see some hard data with rigorously determined kinetic measurements!

Reviewer #3 (Recommendations for the authors):

This paper uses a range of techniques to demonstrate the presence of a novel protein (HIGD1C) that interacts with complex 4 of the mitochondrial electron transport chain. The authors demonstrate that this protein is required for hypoxic chemotransduction at the level of the whole animal (plethysmography), at the level of the in-vitro organ (carotid sinus nerve recordings) and at the level of the glomus cell (calcium imaging). The authors then go on to demonstrate that HIGD1C may interact and alter the sensitivity of complex 4 to hypoxia.

The authors are to be congratulated on a set of thorough physiological experiments that are then extended by detailed cellular respiration studies. Working with mouse carotid body tissue is incredibly challenging and the authors have done extremely well to get such high quality and valuable data.

The combination of genetic, physiological and cellular experiments make this an extremely compelling paper suitable for publication in eLife.

The question of why carotid body glomus cells are unusually sensitive to hypoxia has troubled researchers for decades. This paper makes an extremely compelling case for the expression of HIGD1C modulating complex 4 and thereby sensitizing it to hypoxia. The data seems strong and the paper is likely to have a major impact in the field of oxygen sensing.

There are several observations that would greatly strengthen the paper.

1. It would be better in future if the calcium imaging studies could be performed using the same perfused preparation that the nerve recording experiments used. This would remove the requirement for equilibrating superfusate with 95% oxygen which is far from physiological and would allow the carotid body tissue to be perfused with physiologically relevant levels of oxygen. However, superfusion with hyperoxic solutions is considered standard in many systems and so additional experiments are not required at this time.

2. Expanding the study to see if HIGD1C is expressed in carotid bodies of multiple species would strengthen the paper. It would also be interesting to see if it is absent in the carotid bodies of guinea pigs which are not acutely oxygen sensitive. Furthermore, chromaffin cells in fetal adrenal medulla are oxygen-sensitive whereas mature chromaffin cells are not, it would be fascinating to see if HIGD1C expression changes during the maturation of chromaffin cells. These possibilities might be discussed.

3. Tidal volume changes with the weight of the animals. Tidal volume should be adjusted for the weights of the animals tested. If there are weight differences between knockouts and wildtype it can have profound effects on the data.

https://doi.org/10.7554/eLife.78915.sa1

Author response

Major concerns

1. Parts of the manuscript are difficult to follow re data presentation since the data are densely reported in places. Eg Figure 1 Figure supplement 2 on page 9 is virtually impossible to read.

We strove to make the figures more legible in this revision. For example, we enlarged and redistributed the panels in Figure 1-figure supplement 2. We split the Figure 1-figure supplement 3 into two Figure supplements (Figure 1-figure supplements 3 and 5). In addition, we have now submitted full-page versions of figures that can be resized as needed.

2. A tighter introduction is required re references where credit should be given to the early studies showing that hypoxia excites CB and breathing and chemodenervation abolishes the breathing responses (eg Neil; Torrance; Lahiri should be given credit in para 1 on page 3).

We now reference the following primary papers for key early observations showing that carotid body stimulated afferent nerve activity and ventilation that can be abolished by chemo- denervation or carotid body ablation (p. 3):

De Castro F. (1928). Sur la structure et l'innervation du sinus carotidien de l'homme et des mammifères. Nouveaux faits sur l'innervation et la fonction du glomus caroticum. Trav. Lab. Rech. Biol. 25, 331–380

Heymans C., Bouckaert J. J., Dautrebande L. (1931). Au sujet du mecanisme de la bradycardie provoquée par la nicotine, la lobéline, le cyanure, le sulfure de sodium, les nitrites et la morphine, et de la bradycardie asphyxique. Arch. Int. Pharmacodyn. 41, 261–289

Neil and O’Regan, J Physiol, 1971, 215: 33-47

Black, McCloskey, and Torrance, Respir Physiol, 1971, 13: 36-49

Lahiri and DeLaney, Respir Physiol, 1975, 24: 249-266

Lahiri and DeLaney, Respir Physiol, 1975, 24:2 67-286

Verna, Roumy, and Leitner, Brain Res, 1975, 100: 13-23

We have also added this review of the history:

De Castro, F. (2009). The discovery of sensory nature of the carotid bodies--invited article. Adv Exp Med Biol, 648, 1-18

3. Additionally, primary references should be given for statements of fact like …'Under these pathological conditions, suppressing CB activity improves causal symptoms such as hypertension (REF), cardiac arrhythmias (REF), and insulin resistance (REF) (Iturriaga, 2018)'. Credit must be given to the primary source, not a review.

We now reference the primary sources for these observations (p. 3):

Hypertension

Fletcher et al., J Appl Physiol, 1992

Del Rio et al., Hypertension, 2016

Abdala et al., J Physiol, 2012

Narkiewiecz et al., 2016, JACC Basic Transl Sci

Cardiac arrhythmias

Marcus et al., 2014, J Physiol

Del Rio et al., 2013, J Am Coll Cardiol

Insulin resistance

Ribeiro et al., 2013, Diabetes

Sacramento et al., 2017, Diabetelogica

4. p 4 'We found that three such genes, Higd1c, Cox4i2, and Ndufa4l2, were expressed at higher levels in the mouse CB (Figure 1A)'. Are you confident that this expression is only in type 1 cells and not type 2 cells?

RNAseq of whole carotid body tissue (Figure 1A) cannot determine if the expression of these genes is restricted to any particular cell type. To overcome this, we performed duplex in situ hybridizations to show that Higd1c mRNA co-localizes with Th mRNA in type 1 cells (Figure 1D, E). Additional support comes from single-cell RNA studies that show high levels of expression of all three genes in glomus cells (Zhou et al., 2016, J Physiol). The pattern of gene expression of Cox4i2 and Ndufa4l2 we detected by in situ hybridization and immunostaining are consistent with the expression of these genes in type 1 cells (Zhou et al., 2016, J Physiol; Moreno-Dominguez et al., 2020, Sci Signal). To definitively show expression of Higd1c in only type 1 cells and not in both type 1 and type 2 cells in tissue sections is not possible because there is no antibody available for HIGD1C. We have added this limitation in the Discussion (p. 41) and raised the possibility that Higd1c could be expressed in both type 1 and type 2 cells, as both cell types have been proposed to work together in sensory signaling in hypoxia (Leonard et al., 2018, Front Physiol).

5. Much of the data presented has used parametric statistics on n of 3/3 or 4/4 samples eg Figure 1 supp 3 page 10. Are these data normally distributed to support parametric use of stats? Please comment on the sample re biological replicates v technical replicates. How were the data treated here?

All samples in the experiments presented were biological replicates, and all groups were analyzed by the Shapiro-Wilk test to check for normality before running parametric or non-parametric tests as appropriate (described in p. 59). We have increased the n (number of samples) to 5 or 6 samples per tissue for the RT-qPCR experiments in Figure 1-figure supplement 3 and checked for normality to justify the use of parametric tests.

6. The gel on p26 panel B looks over run. Comment?

This appearance is due to the large amount of mitochondria required to detect the mouse version of HIGD1C. This could be due to a reduced ability of mouse HIGD1C to assemble with human Complex IV proteins expressed endogenously by HEK293T cells.

7. Aspects of the data are very convincing. Whilst this large body of work shows the putative role of HIGD1C in oxygen sensing, the relationship between this protein and the graded response of afferent nerve firing to physiological levels of hypoxia remains to be established to support an essential role for this signalling pathway in hypoxic chemotransduction. This limitation should be acknowledged. Please comment?

We greatly appreciate the reviewer’s assessment of the quality of our data. We showed defects in the graded response of the carotid sinus nerve in Higd1c mutants to three physiological levels of hypoxia (PO2=80, 60, and 40 mmHg) in Figure 3A-D that stimulate carotid body sensory output and ventilation.

8. With respect to the effects of Higd1c KO on ventilation. Although all KO's appear to have a blunted ventilatory response to hypoxia, a ventilatory response remains none the less. This is particularly evident for the 1.1 KO as shown in the example trace in Figure 2 supplement 1 A where the second response to a hypoxic stimulus looks very similar between the KO and normal mouse. This is a somewhat disappointing result in that it may limit the conclusions that can be drawn from this study. One could have hoped that a Higd1c KO would either eliminate the response to hypoxia or had no effect at all. As this is a very important piece of evidence I want to ask for more detail regarding the data and methods.

Over the last several years, a nuanced view of oxygen sensing has emerged in which there are likely multiple sites beyond the carotid body and multiple molecules (even within the carotid body) involved in acute oxygen sensitivity (reviewed in Funk and Gourine, 2017, J Appl Physiol; Holmes et al., 2022, Front Physiol; Barioni et al., 2022, Sci Adv). The carotid body glomus cell mitochondrial electron transport chain is expected to be the most sensitive site, and we propose that HIGD1C is present almost exclusively in the carotid bodies when acting in combination with less exclusively (but by no means broadly) expressed ETC proteins such as COX4I2 and NDUFA4L2, is responsible for this heightened sensitivity.

With regards to multiple sites, while the carotid bodies are the major oxygen and likely the most sensitive chemoreceptors contributing to the HVR, we do not exclude a role for other oxygen-sensitive sites such as the aortic bodies, brainstem, and spinal cord (reviewed in Funk and Gourine, 2017, J Appl Physiol; Hodges and Forster, 2012, Neur Regen Res). Indeed, our recent work describes spinal oxygen sensors that can stimulate respiratory centers in the brainstem (Barioni et al., 2022, Sci Adv).

With regards to multiple molecules involved in acute oxygen sensitivity, please note Figure 3-figure supplement 1. In glomus cells from Higd1c+/+ animals, a plethora of cells respond strongly to both severe (PO2=25 mmHg) and less severe (PO2=50 mmHg) hypoxia, whereas cells from Higd1c-/- mostly respond (though be it at reduced intensity) to only severe hypoxia. This parallels the data from carotid sinus nerve recordings in Figure 3A-D. These data suggest that other molecules are capable of partially subserving HIGD1C’s role in severe hypoxia.

With regards to the investigation of HVR in Higd1c-/- animals, the magnitude of the defect in the hypoxic ventilatory response we report was at least as severe as in other rodent studies in which carotid bodies were denervated or ablated (Soliz et al., 2005, J Physiol; Del Rio et al., 2013, J Am Coll Cardiol). Moreover, the literature suggests that all experimental animal species show some degree of recovery of the HVR over time after carotid body resection or denervation when tested in an awake, unanesthetized state. Therefore, we might expect some degree of compensation by other sites/molecules in the absence of carotid body HIGD1C.

For the time course data in Figure 2-figure supplement 1A-C, please note that the last (third) challenge in Figure 2-figure supplement 1A-C is hypercapnia. The most pertinent panel is C, which shows minute ventilation (volume exchanged per minute=respiratory rate*tidal volume). Animals can increase ventilation by increasing either the respiratory rate, tidal volume, or both, and minute ventilation accounts for both respiratory rate and tidal volume changes. The difference between minute ventilation of Higd1c+/+ and Higd1c-/- animals was apparent and consistent throughout the entire duration of hypoxic periods, including ramp periods from normoxia (21% O2) to hypoxia (10% O2). See Figure 2-figure supplement 1A-C with 30 s bins for normoxic (Nox, yellow) and hypoxic (Hox, blue) periods of the time course. Ramps (no color) were 1 min. Data are shown as mean and SEM.

We have replaced Figure 2-figure supplement 1A-C because they better illustrate the reduction in HVR.

9. Forgive me if I have misunderstood but in the methods section you state that "we used a respiratory rate of 215 breaths/min (comparable to the mean of a wild type in hypoxia) as a cut off for inclusion in this study". It is unclear how this works. Are you rejecting recordings with RR in excess of this figure or below this figure? When are you making this decision, under normoxic conditions at the beginning of an experiment, under hypoxic conditions, or at any time in the recording? Can you clarify this point and indicate how often recordings were rejected by this criteria in the different mice?

We rejected trials where any of the normoxic periods had an average respiratory rate that exceeded 215 breath/min in order to assess calm breathing and exclude artefacts from sniffing, grooming, and movement that correlated with high-frequency events above the ventilation in hypoxia. Normoxic periods evaluated included the baseline at the beginning of the experiment as well as subsequent inter-stimulus normoxic periods. Ventilation in hypoxia was much more regular with few artefacts, and high frequency in hypoxia was not used as an exclusion criterion. We have now stated this exclusion criterion and our rationale more clearly in the Methods (p. 47).

Author response image 1 shows the percentage of trials rejected by genotype (number of trials indicated on bars). The percent rejected between Higd1c+/+ and Higd1c-/- animals by allele are not statistically significant by the z test of proportions (p=0.7039, 0.5353, and 0.7114 for 1-1, 3-1, and 5-3, respectively). We have added these stats to the Methods (p. 47).

Author response image 1

10. Was there any notable difference in mouse behaviour between genotypes during plethysmography? Mice usually become much less active in hypoxia and basal metabolic rate goes down resulting in a fall in CO2 production and a drop in PaCO2 which leads to a fall in ventilation (hypoxic ventilatory decline: HVD). This often complicates the analysis/interpretation of responses to hypoxia. Over what time period do you measure changes in ventilation – over the entire period of exposure to hypoxia, at the peak? Or towards the end? Are changes in the rate of HVD influencing the comparison between KO and wt? Have you measured PaCO2 under hypoxic conditions? I would predict that it would be lower than under control conditions. Could you introduce a little CO2 in hypoxic conditions to try to neutralise this effect?

No behavioral differences between Higd1c+/+ and Higd1c-/- animals during our whole-body plethysmography experiments were observed. Both genotypes became less active in hypoxia and exhibited more regular breathing.

To calculate the ventilation data for hypoxia, we first calculated the mean over the entire duration of both hypoxic stimulus periods (5 min each), and then we averaged the mean values of the two hypoxic periods. The 1-min ramp periods for the chamber to go from normoxia (21% O2) to hypoxia (10% O2) or vice versa were not included in calculations for either normoxia or hypoxia (see also time courses in response to item 8). From the time course data (see item 8), Higd1c-/- mutants had lower ventilation at all time points in hypoxia and the ramp to hypoxia.

We agree with the reviewer that hypoxia will reduce PaCO2. On the one hand, hypoxia acts to attenuate ventilation by suppressing metabolism (reducing CO2 production) and directly inhibiting neurons of the respiratory controller. On the other hand, this attenuation of ventilation is offset by central and peripheral oxygen chemoreceptors which excite the respiratory control system. In neonates, the oxygen chemoreceptors reduce but do not fully overcome the central suppressive effect of hypoxia; in adults, oxygen chemoreceptors are more potent and can fully overcome the hypoxic depression of neurons to cause a net increase in ventilation. Thus, in adults, hypoxia will cause a net reduction in PaCO2, a respiratory stimulant. As the HVR is lower in Higd1c-/- animals, we would expect Higd1c-/- to have a higher PaCO2 in hypoxia than Higd1c+/+, providing more respiratory stimulant to Higd1c-/- animals. Thus, the lower HVR during poikilocapnic hypoxia conditions in Higd1c-/- compared to Higd1c+/+ is expected to underestimate the importance of HIGD1C to the hypoxic response at the level of the oxygen chemoreceptor.

We have not attempted to regulate PaCO2 under hypoxic conditions in our mice. In large animals, blood gases can be monitored in real-time, allowing the use of feedback control to deliver appropriate CO2 to maintain PaCO2 at a constant level. This is not feasible in mice. Blood gas measurements in mice are terminal experiments that require many animals to get a single time point, more than we can breed and raise to adults in two months. In addition, collecting sufficient arterial blood for blood gas experiments in adult mice requires anesthesia, which alters the HVR, or installing carotid artery catheters in awake mice, which would ablate one carotid body.

Introducing a fixed level of CO2 during hypoxia is sometimes performed to try to mitigate the reduction in PaCO2 due to hyperventilation. However, such a maneuver is expected to (a) stimulate the carotid body in an oxygen chemoreceptor-dependent manner because of the multiplicative O2 and CO2 interaction at the carotid body, the mechanism for which is unknown, and (b) change the non-additive (likely hypoadditive) interaction between central and peripheral chemoreceptors which has not been carefully characterized in mice. Together, these effects are almost impossible to quantify. Rather than adding unknowns, we chose to opt for simplicity and perform our experiments under poikilocapnic hypoxia conditions that mimic high altitude (i.e., hypoxia without CO2 supplementation). At high altitudes, carotid body oxygen sensing causes hyperventilation, and under these conditions, reducing oxygen sensing is expected to reduce ventilation.

11. What happens if you do a sham switch (i.e. switch between two identical gasses/air), is there any startle response associated with just mechanically switching between two gas lines? If not what happens if you look specifically at the peak/early response to hypoxia before CO2 has much chance to fall?

We did not observe any startle response associated with just switching between two identical gases. From the time course data (please see item 8), Higd1c-/- mutants exhibited lower ventilation at all time points, including during the ramp and first points of hypoxia.

12. Are Higd1c +/+ mice taken from your in house breeding programs generating Higd1c -/- mice or are they just off the shelf C57Bl/6J from Jax? If the latter how long are these mice held in your facility (under the same conditions as the KO mice) before being used?

Higd1c+/+ and Higd1c-/- animals were generated from crosses between Higd1c+/- parents in our facility. We have added this detail to the Methods (p. 42).

13. In the methods section on nerve recordings you state that "Preparations were exposed to a brief hypoxic challenge (PO2 = 60 mmHg) to determine viability; preparations that failed to show a clear increase in activity during this challenge were discarded". You are testing the hypothesis that Higd1c is important/essential for the generation of the response to hypoxia so why exclude data from preparations that lack a hypoxic response? This is just what you are looking for! I hope this is just a mistake in writing up the methods, BUT if this is really what was done then the whole nerve recording study could be invalid (depending on just what proportion of preparations were actually discarded). If you want some sort of test for viability of the preparation, which is a good idea, then there are many other stimuli one could choose instead that do not involve mitochondrial function e.g hypercapnia/acidosis, high potassium, acetyl choline, TASK channel inhibitors/respiratory stimulants.

We thank the Reviewer for pointing out this mistake. Dr. Roy, who performed these challenging experiments, typically gives rat preparations a PO2=60 mmHg hypoxic pre-challenge, but he no longer does this in mice because the preparation is too delicate. We have removed this statement in the Methods and described the current practice (p. 49): “Recording was only attempted in nerves that survived cleaning and desheathing. The presence of action potentials under baseline conditions was used as the only test of preparation viability; data were obtained from all preparations deemed viable according to this criterion.”

We have also updated the representative traces in Figure 3A and B with graphs that better represents the mean data.

14. One of the key issues regarding the role of alternative mitochondrial subunits in the carotid body is not simply that they may affect the maximal turnover rate of cytochrome oxidase but whether they alter the kinetic parameters defining sensitivity to hypoxia (i.e. Km, oxygen affinity, P50 ). To determine these really requires making a number of measurements at different PO2 including a zero point (anoxia). This could have been done for both nerve recordings and calcium measurements. Unfortunately it was not, so we are left with data from both of these experiments which demonstrates that the response to hypoxia is smaller in the KO but we have no idea whether these kinetic parameters have changed or not. The study would be a lot stronger if you could demonstrate a change in Km in the Higd1c KO.

The main conclusion drawn from the calcium imaging and nerve recording experiments is that Higd1c-/- mutants are defective in graded responses to hypoxia in the physiological range (Figure 3). These experiments were performed in intact tissue to measure the activity of as many glomus cells as possible and to preserve normal cell-cell interactions that promote sensory signaling. However, because these experiments were performed in intact tissue, the PO2 experienced by individual glomus cells could not be accurately determined due to tissue heterogeneity. Thus, the PO2 of the perfusion reflected the upper limit of an unknown lower range of PO2 at the cellular level. Technically, anoxia is typically delivered in perfusion by adding a reducing agent like sodium dithionite to scavenge oxygen. However, such agents can also modify cell proteins and complicate the interpretation of results.

Furthermore, experiments at lower PO2 would not be informative for nerve recordings because carotid sinus nerve activity does not increase (and can even decrease) once PO2 is reduced below 30 mmHg (Fidone and Gonzalez, 1986, Handbook of Physiology, The Respiratory System; Hornbein et al., 1961, J Neurophysiol; Hornbein and Roos, 1963, J Physiol; Peng et al., 2020, J Neurophysiol). While intracellular calcium does continue to increase as PO2 is decreased below 30 mmHg, the lack of correlation of this additional intracellular calcium to sensory output would make it difficult to interpret these experiments (Peng et al., 2020, J Neurophysiol). We chose to focus on a more physiological PO2 range of 25-100 mmHg for carotid body sensory activity experiments, and in this range, Higd1c-/- mutants have reduced sensitivity in their response to hypoxia (Figure 3).

We thank the reviewer for the suggestion to curve fit our glomus cell imaging data to derive KmO2 values. Unfortunately, we do not have enough points in the near anoxic range to restrain a dose response curve for our current data. Dissociating large numbers of glomus cells to perform comprehensive studies at multiple oxygen levels is not feasible using adult mice, and thus, studies that report calcium and metabolic imaging from mouse glomus cells have not included this level of analysis (Fernandez-Augera et al., 2015, Cell Metab; Moreno-Dominguez et al., 2020, Sci Signal; Peng et al., 2020, J Neurophysiol, Peng et al., 2019, Respir Neurobiol Physiol; MacMillan et al., 2022, Commun Biol). The studies we have found that show derived KmO2 values utilized neonatal rats, which have larger carotid bodies and are easier to dissociate (Landuaer et al., 1995, J Physiol; Buckler and Turner, 2013, J Physiol).

We agree that determining whether alternative mitochondrial subunits change the Km of oxygen on the mitochondrial electron transport chain in glomus cells is an important question. However, the ideal experiment to make direct oxygen measurements on large numbers of purified glomus cells using cellular oxygen consumption to reduce oxygen levels is not currently possible in the mouse. We have added this limitation to the Discussion (p. 40): “Future studies of oxygen consumption by mitochondria of glomus cells, when feasible, will further illuminate the roles of these proteins in carotid body oxygen sensing.” Nevertheless, we have now determined the contribution of atypical mitochondrial proteins to Km of oxygen on electron transport chain activity in cell culture, where we could obtain more abundant material for direct oxygen measurements. We found that expression of both HIGD1C and COX4I2 in HIGD1A-KO HEK293T cells increased the p50mito to enhance the sensitivity of the electron transport chain to hypoxia (see also response to item 19).

15. It would appear from the results obtained with Rh123 and the weak responses to FCCP that there was inadequate loading of this dye to make good measurements of mitochondrial potential (ψM) in many of the cells studied. If you look at the paper by Biscoe and Duchen they were achieving a 100% increase in Rh125 fluorescence upon adding FCCP, Anoxia or CN, not 20%. The level of loading is critical with this dye in order to get it to work properly in the de-quench mode.

It is difficult to directly compare our Rh123 experiments on intact mouse carotid bodies with experiments on dissociated rabbit glomus cells used in Biscoe and Duchen, 1992, J Physiol. We expect dye loading to be more heterogeneous in intact carotid bodies, compared to dissociated cells, due to the differential accessibility of different parts of the tissue to Rh123. We accounted for this heterogeneity by normalizing fluorescence to baseline. In addition, we do not know whether there are species-specific differences between mouse and rabbit or selection during dissociation and imaging for only a subset of glomus cells with better FCCP responses in Biscoe and Duchen. In developing our protocol, we tested multiple concentrations of Rh123 and incubation times, and increasing the time of dye loading did not increase baseline fluorescence, indicating we had reached a steady-state level of dye loading.

In addition, to correct for differences in dye loading, responses to acute hypoxia should probably be normalised not only to the baseline but also to the response to FCCP.

We are not confident that the FCCP response reflects a maximum mitochondrial membrane potential response against which the other responses could be normalized. FCCP was presented after both hypoxia and cyanide at the end of a long experiment, during which Rh123 fluorescence decreased over time.

The smaller response to hypoxia in Higd1c -/- could simply reflect lower dye loading, with consequent lower dynamic response from Rh123 to change in mitochondrial potential, rather than any actual change in ψM.

Because Higd1c+/+ and Higd1c-/- carotid bodies were loaded with Rh123 under the same conditions and their morphologies and glomus cell counts were similar (Figure 1G-I), we do not believe that the smaller Rh123 responses of Higd1c-/- glomus cells to hypoxia was due to poorer dye loading but likely due to a combination of a less polarized inner mitochondrial membrane at baseline and weaker response to hypoxia. In Higd1c-/- glomus cells that had strong responses to FCCP comparable to Higd1c+/+, the response to hypoxia was still weaker than Higd1c+/+ (Figure 4D-F). To resolve this, we performed additional experiments testing FCCP responses as the first stimulus in Higd1c+/+ and Higd1c-/- carotid bodies and found that even under these more optimal conditions, there were smaller Rh123 responses to FCCP in Higd1c-/- glomus cells (p. 24, Figure 4-figure supplement 1D). This suggests that there is a defect in ψM in normoxia in Higd1c-/- glomus cells (see also response to item 17).

16. The response to anoxia has not been tested which again confounds attempts to determine a P50 for mitochondrial depolarisation. I note that the rate of change in PO2 (Figure 4 suppl 1 A) is rather slow so some Rh123 may also leak out of the cell during the recording. Were any corrections applied for dye leakage?

Yes, we did correct for dye leakage and bleaching by performing baseline subtraction with linear interpolation.

17. In summary the interpretation of this data is equivocal. Higd1c -/- may take up Rh123 less avidly than wt but is this due to a lower resting ψM or something else? This experiment needs repeating extending loading time or Rh123 concentration until robust responses to FCCP can be recorded.

We consider it likely that Higd1c-/- glomus cells had weaker responses to FCCP due to a less polarized inner mitochondrial membrane. HIGD1C could affect the function of the electron transport chain at all oxygen levels. To help resolve this, we performed additional experiments on Higd1c+/+ and Higd1c-/- carotid bodies, testing FCCP responses as a first stimulus to estimate differences in resting membrane potential while minimizing dye leakage and bleaching over time. Similar to when FCCP was presented as the third stimulus (Figure 4C), Higd1c-/- glomus cells had smaller Rh123 responses to FCCP compared to Higd1c+/+ glomus cells (Figure 4-figure supplement 1D), consistent with a defect in ψM in normoxia in Higd1c-/- glomus cells.

In developing our Rh123 imaging protocol, we tested several Rh123 concentrations up to 50 µg/ml. We did not want to increase the concentration further because Rh123 and other mitochondrial membrane potential dyes (TMRM and TMRE) begin to inhibit mitochondrial respiration at this concentration (Scaduto and Grotyohann, 1999, Biophys J). We also found empirically that extending the incubation time for dye loading did not improve the FCCP response.

18. If you want to see if genotype affects resting ψM you would probably be better not working in the quench mode but either using much lower concentrations of Rh123 or another probe, e.g. TMRM, and loading for a longer period of time (until dye uptake reaches a steady state without any quenching occuring).

To interpret imaging experiments with Rh123 and TMRM in non-quenching mode to measure resting ψM would require perfectly controlled and consistent dye loading and imaging conditions in order to compare absolute fluorescence differences. As far as we know, this has not been done in glomus cells, even using dissociated cell preparations. When performing two-photon imaging of intact carotid bodies, glomus cells are located at different depths and necessarily experience different illuminations, along with differences in exposure to Rh123 during loading. Therefore, we do not believe we can achieve the level of control necessary to draw a strong conclusion using Rh123 or TMRM in the non-quenching mode in intact tissue. We believe that testing FCCP responses by Rh123 imaging in quenching mode provides a reasonable assessment of the maximal response, especially if we deliver the stimulus at the beginning of the experiment when cells across preparations are likely to be in the most similar state (see responses to items 15-17).

19. Data in Fig6-E shows >= 40% inhibition of oxygen consumption under hypoxic conditions compared to normoxia in all HEK cell types studied. Given that the level of oxygen in hypoxia is stated to be 25 mmHg this is something of a surprise. The P50 for most cells is thought to be < 1mmHg. Something is wrong here. If you are using an Oroboros Oxygraph (as stated in methods) it should be possible to measure oxygen consumption from air all the way down to zero oxygen and derive an exact P50 for each cell type. This should be done. This is a very important experiment that proports to show that it is the combination of Higd1c and Cox4I2 that generates the unusual sensitivity of complex IV towards oxygen. Philosophically I like this hypothesis. If true it would mark a major advance in this field, but I want to see some hard data with rigorously determined kinetic measurements!

Thank you for this suggestion. We agree with the importance of deriving p50 values for HIGD1A-KO cells expressing different combinations of HIGD1C and COX4I2 to extend our data in Figure 6E and F. We performed additional experiments on these cell lines to calculate the P50 using an Oroboros Oxygraph as suggested. The new data shows that co-expression of HIGD1C and COX4I2 in HIGD1A-KO cells increased the mitochondrial oxygen affinity (p50mito) to reveal an enhanced response to hypoxia (p. 37, new Figure 6F and Figure 6—figure supplement 1E). Notice that in these assays, to calculate the p50mito, we measured endogenous whole cell respiration.

20. It would be better in future if the calcium imaging studies could be performed using the same perfused preparation that the nerve recording experiments used. This would remove the requirement for equilibrating superfusate with 95% oxygen which is far from physiological and would allow the carotid body tissue to be perfused with physiologically relevant levels of oxygen. However, superfusion with hyperoxic solutions is considered standard in many systems and so additional experiments are not required at this time.

We thank the reviewer for this suggestion, which we will strive to adopt in future calcium imaging experiments.

21. Expanding the study to see if HIGD1A is expressed in carotid bodies of multiple species would strengthen the paper. It would also be interesting to see if it is absent in the carotid bodies of guinea pigs which are not acutely oxygen sensitive. Furthermore, chromaffin cells in fetal adrenal medulla are oxygen-sensitive whereas mature chromaffin cells are not, it would be fascinating to see if HIGD1A expression changes during the maturation of chromaffin cells. These possibilities might be discussed.

We showed that Higd1c is expressed in the carotid bodies of both mouse and human. We appreciate the suggestion to expand the study to additional species, such as the poorly oxygen-sensitive guinea pig. We have added RT-qPCR data from the rat, another common animal model for carotid body studies. Higd1c was expressed at higher levels in the carotid body compared to adult and neonatal adrenal medulla and thoracic spinal cord, which contains a central oxygen sensor (Barioni et al., 2022, Sci Advances) (p. 6, Figure 1-figure supplement 4B). Higd1c expression in the adrenal medulla did not increase from neonate to adult. Testing expression in other species is beyond our capabilities at this time because of limited access to carotid body tissue.

22. Tidal volume changes with the weight of the animals. Tidal volume should be adjusted for the weights of the animals tested. If there are weight differences between knockouts and wildtype it can have profound effects on the data.

Body weights of Higd1c+/+ and Higd1c-/- animals for all three Higd1c alleles were not significantly different by two-way ANOVA with Sidak correction (see Author response image 2).

Author response image 2

We did consider normalizing tidal volume and minute ventilation to body weight as suggested, but for the animals used in our study, body weight did not correlate well with respiratory rate, tidal volume, or minute ventilation in wild-type or mutant animals in normoxia or hypoxia. When plotted against body weight, only tidal volumes for 3-1+/+ in normoxia and 5-3+/+ in hypoxia had fitted regression lines with significantly non-zero slopes at p<0.05. Nevertheless, we verified that all differences that are statistically significant (p<0.05) without normalizing by body weight are also significant if we normalize to body weight. In addition to comparing mean values of ventilatory parameters, we showed the % change in the ventilatory parameters for each animal before and after hypoxia (“Hypoxic Response”), which we feel is the most appropriate presentation as it essentially uses each animal as its own control. We have added our rationale for not normalizing by body weight in the Methods (pp. 47-48).

Reviewer #1 (Recommendations for the authors):

Understanding the precise intracellular signalling pathways underpinning hypoxic sensitivity in the carotid body chemoreceptor has been a major unsolved area in sensory neurophysiology. Early studies almost 60 years ago suggested the importance of a metabolic signal coupled to the mitchrondria, which could regulate intracellular calcium homeostasis and exocystosis of excitatory transmitter in type I glomus cells.

Using RNAseq this manuscript has identified a novel gene that encodes protein regulation of Complex IV in the carotid body response to hypoxia. Here the authors found HIGD1C, a novel hypoxia-inducible gene domain factor isoform, as an electron transport chain Complex IV-interacting protein was almost exclusively expressed in the carotid body. Using a combination molecular biology, protein chemistry, genetic knock-out, calcium imaging and respiratory measurements, the authors elegantly demonstrated the physiological utlility of HIGD1C being required for carotid body oxygen sensing via enhanced Complex IV sensitivity to hypoxia. Deletion of the gene massively attenuated the chemoreceptor response to hypoxia, whereas of expression of HIGD1C could recapitulate the increased oxygen sensitivity of Complex IV in HEK 293T cells, but not the response to hypercapnia.

Whilst this large body of work shows the putative role of HIGD1C in oxygen sensing, the relationship between this protein and the graded response of afferent nerve firing to physiological levels of hypoxia remains to be established to support an essential role for this signalling pathway in hypoxic chemotransduction.

This is a large body of work supporting the idea that HIGD1C is required for hypoxic sensing in the mouse through the regulation complex IV. The experiments are well designed, complex and appear to have been carefully performed.

We thank the reviewer for recognizing the quality of our study.

Specific comments for improvement:

Parts of the manuscript are difficult to follow re data presentation since the data are densely reported in places. Eg Figure 1 Figure supplement 2 on page 9 is virtually impossible to read.

Please see response to item 1.

A tighter introduction is required re references where credit should be given to the early studies showing that hypoxia excites CB and breathing and chemodenervation abolishes the breathing responses (eg Neil; Torrance; Lahiri should be given credit in para 1 on page 3).

Please see response to item 2.

Additionally, primary references should be given for statements of fact like …'Under these pathological conditions, suppressing CB activity improves causal symptoms such as hypertension (REF), cardiac arrhythmias (REF), and insulin resistance (REF) (Iturriaga, 2018)'. Credit must be given to the primary source, not a review.

Please see response to item 3.

p 4 'We found that three such genes, Higd1c, Cox4i2, and Ndufa4l2, were expressed at higher levels in the mouse CB (Figure 1A)'. Are you confident that this expression is only in type 1 cells and not type 2 cells?

Please see response to item 4.

Much of the data presented has used parametric statistics on n of 3/3 or 4/4 samples eg Figure 1 supp 3 page 10. Are these data normally distributed to support parametric use of stats? Please comment on the sample re biological replicates v technical replicates. How were the data treated here?

Please see response to item 5.

The gel on p26 panel B looks over run. Comment?

Please see response to item 6.

Aspects of the data are very convincing. Whilst this large body of work shows the putative role of HIGD1C in oxygen sensing, the relationship between this protein and the graded response of afferent nerve firing to physiological levels of hypoxia remains to be established to support an essential role for this signalling pathway in hypoxic chemotransduction. This limitation should be acknowledged. Please comment?

Please see response to item 7.

Reviewer #2 (Recommendations for the authors):

I have a number of major concerns about parts of this research which need to be addressed before I could comment on its conclusions and importance. Some of these may just require a better explanation or correction to the text (e.g. where there may be an ambiguity over how an experiment was conducted). Others may require further work

We thank the reviewer for detailed assessment of our manuscript. We have tried to provide additional clarification as requested and performed additional experiments.

Major comments/Questions

General reporting of results

A very general comment I have about this paper is that numerous experiments, particularly in the latter half of this paper using HEK cells, have been conducted with an 'n' of only 3. I do not know what eLifes's normal expectations/requirements are but I would have thought that an 'n' of at least 4 or 5 independent observations should normally be required. Similarly, numerous gels/blots are presented without any indication of how often these types of experiments were repeated. This should be reported and the journal should have some policy over what is expected. To my mind there could be a substantial amount of further work that needs to be completed before this study could be formally published. Apart from this issue the statistics seem to have been done with suitable care and rigour.

For most quantitative data in cell culture, a minimum n=3 (independent replicates) is enough if there is not much variability, and we have tested for normality using the Shapiro-Wilk test to justify use of parametric statistical tests when appropriate. We increased the sample size for RT-PCR experiments to increase our confidence in those results. Please see also response to item 5 above.

All gels and blots were repeated 3 times, except for in-gel activity experiments in Figure 5-figure supplement 1E, which were performed twice. We added the number of replicates to figure legends as appropriate (Figure 5 and Figure 5-figure supplements 1-3). n values for data present in bar graphs were already reported in legends.

Questions/suggested changes.

Plethysmography.

With respect to the effects of Higd1c KO on ventilation. Although all KO's appear to have a blunted ventilatory response to hypoxia, a ventilatory response remains none the less. This is particularly evident for the 1.1 KO as shown in the example trace in Figure 2 supplement 1 A where the second response to a hypoxic stimulus looks very similar between the KO and normal mouse. This is a somewhat disappointing result in that it may limit the conclusions that can be drawn from this study. One could have hoped that a Higd1c KO would either eliminate the response to hypoxia or had no effect at all. As this is a very important piece of evidence I want to ask for more detail regarding the data and methods.

Please see response to item 8.

Forgive me if I have misunderstood but in the methods section you state that "we used a respiratory rate of 215 breaths/min (comparable to the mean of a wild type in hypoxia) as a cut off for inclusion in this study". It is unclear how this works. Are you rejecting recordings with RR in excess of this figure or below this figure? When are you making this decision, under normoxic conditions at the beginning of an experiment, under hypoxic conditions, or at any time in the recording? Can you clarify this point and indicate how often recordings were rejected by this criteria in the different mice?

Please see response to item 9.

Was there any notable difference in mouse behaviour between genotypes during plethysmography? Mice usually become much less active in hypoxia and basal metabolic rate goes down resulting in a fall in CO2 production and a drop in PaCO2 which leads to a fall in ventilation (hypoxic ventilatory decline: HVD). This often complicates the analysis/interpretation of responses to hypoxia. Over what time period do you measure changes in ventilation – over the entire period of exposure to hypoxia, at the peak? Or towards the end? Are changes in the rate of HVD influencing the comparison between KO and wt? Have you measured PaCO2 under hypoxic conditions? I would predict that it would be lower than under control conditions. Could you introduce a little CO2 in hypoxic conditions to try to neutralise this effect?

Please see response to item 10.

What happens if you do a sham switch (i.e. switch between two identical gasses/air), is there any startle response associated with just mechanically switching between two gas lines? If not what happens if you look specifically at the peak/early response to hypoxia before CO2 has much chance to fall?

Please see response to item 11.

Are Higd1c +/+ mice taken from your in house breeding programs generating Higd1c -/- mice or are they just off the shelf C57Bl/6J from Jax? If the latter how long are these mice held in your facility (under the same conditions as the KO mice) before being used?

Please see response to item 12.

Nerve fibre recordings and calcium recordings.

In the methods section on nerve recordings you state that "Preparations were exposed to a brief hypoxic challenge (PO2 = 60 mmHg) to determine viability; preparations that failed to show a clear increase in activity during this challenge were discarded". You are testing the hypothesis that Higd1c is important/essential for the generation of the response to hypoxia so why exclude data from preparations that lack a hypoxic response? This is just what you are looking for! I hope this is just a mistake in writing up the methods, BUT if this is really what was done then the whole nerve recording study could be invalid (depending on just what proportion of preparations were actually discarded). If you want some sort of test for viability of the preparation, which is a good idea, then there are many other stimuli one could choose instead that do not involve mitochondrial function e.g hypercapnia/acidosis, high potassium, acetyl choline, TASK channel inhibitors/respiratory stimulants.

Please see response to item 13.

One of the key issues regarding the role of alternative mitochondrial subunits in the carotid body is not simply that they may affect the maximal turnover rate of cytochrome oxidase but whether they alter the kinetic parameters defining sensitivity to hypoxia (i.e. Km, oxygen affinity, P50 ). To determine these really requires making a number of measurements at different PO2 including a zero point (anoxia). This could have been done for both nerve recordings and calcium measurements. Unfortunately it was not, so we are left with data from both of these experiments which demonstrates that the response to hypoxia is smaller in the KO but we have no idea whether these kinetic parameters have changed or not. The study would be a lot stronger if you could demonstrate a change in Km in the Higd1c KO.

Please see response to item 14.

Rh123 experiments.

It would appear from the results obtained with Rh123 and the weak responses to FCCP that there was inadequate loading of this dye to make good measurements of mitochondrial potential (ψM) in many of the cells studied. If you look at the paper by Biscoe and Duchen they were achieving a 100% increase in Rh125 fluorescence upon adding FCCP, Anoxia or CN, not 20%. The level of loading is critical with this dye in order to get it to work properly in the de-quench mode. In addition, to correct for differences in dye loading, responses to acute hypoxia should probably be normalised not only to the baseline but also to the response to FCCP. The smaller response to hypoxia in Higd1c -/- could simply reflect lower dye loading, with consequent lower dynamic response from Rh123 to change in mitochondrial potential, rather than any actual change in ψM.

Please see response to item 15.

The response to anoxia has not been tested which again confounds attempts to determine a P50 for mitochondrial depolarisation. I note that the rate of change in PO2 (Figure 4 suppl 1 A) is rather slow so some Rh123 may also leak out of the cell during the recording. Were any corrections applied for dye leakage?

Please see response to item 16.

In summary the interpretation of this data is equivocal. Higd1c -/- may take up Rh123 less avidly than wt but is this due to a lower resting ψM or something else? This experiment needs repeating extending loading time or Rh123 concentration until robust responses to FCCP can be recorded.

Please see response to item 17.

If you want to see if genotype affects resting ψM you would probably be better not working in the quench mode but either using much lower concentrations of Rh123 or another probe, e.g. TMRM, and loading for a longer period of time (until dye uptake reaches a steady state without any quenching occuring).

Please see response to item 18.

CIV sensitivity to Hypoxia in HEK.

Data in Fig6-E shows >= 40% inhibition of oxygen consumption under hypoxic conditions compared to normoxia in all HEK cell types studied. Given that the level of oxygen in hypoxia is stated to be 25 mmHg this is something of a surprise. The P50 for most cells is thought to be < 1mmHg. Something is wrong here. If you are using an Oroboros Oxygraph (as stated in methods) it should be possible to measure oxygen consumption from air all the way down to zero oxygen and derive an exact P50 for each cell type. This should be done. This is a very important experiment that proports to show that it is the combination of Higd1c and Cox4I2 that generates the unusual sensitivity of complex IV towards oxygen. Philosophically I like this hypothesis. If true it would mark a major advance in this field, but I want to see some hard data with rigorously determined kinetic measurements!

Please see response to item 19.

Reviewer #3 (Recommendations for the authors):

This paper uses a range of techniques to demonstrate the presence of a novel protein (HIGD1C) that interacts with complex 4 of the mitochondrial electron transport chain. The authors demonstrate that this protein is required for hypoxic chemotransduction at the level of the whole animal (plethysmography), at the level of the in-vitro organ (carotid sinus nerve recordings) and at the level of the glomus cell (calcium imaging). The authors then go on to demonstrate that HIGD1C may interact and alter the sensitivity of complex 4 to hypoxia.

The authors are to be congratulated on a set of thorough physiological experiments that are then extended by detailed cellular respiration studies. Working with mouse carotid body tissue is incredibly challenging and the authors have done extremely well to get such high quality and valuable data.

The combination of genetic, physiological and cellular experiments make this an extremely compelling paper suitable for publication in eLife.

The question of why carotid body glomus cells are unusually sensitive to hypoxia has troubled researchers for decades. This paper makes an extremely compelling case for the expression of HIGD1C modulating complex 4 and thereby sensitizing it to hypoxia. The data seems strong and the paper is likely to have a major impact in the field of oxygen sensing.

We appreciate the reviewer’s recognition of the challenges of performing carotid body experiments in mice, the quality of our data, and the impact of our findings to the field. Thank you!

There are several observations that would greatly strengthen the paper.

1. It would be better in future if the calcium imaging studies could be performed using the same perfused preparation that the nerve recording experiments used. This would remove the requirement for equilibrating superfusate with 95% oxygen which is far from physiological and would allow the carotid body tissue to be perfused with physiologically relevant levels of oxygen. However, superfusion with hyperoxic solutions is considered standard in many systems and so additional experiments are not required at this time.

Please see response to item 20.

2. Expanding the study to see if HIGD1C is expressed in carotid bodies of multiple species would strengthen the paper. It would also be interesting to see if it is absent in the carotid bodies of guinea pigs which are not acutely oxygen sensitive. Furthermore, chromaffin cells in fetal adrenal medulla are oxygen-sensitive whereas mature chromaffin cells are not, it would be fascinating to see if HIGD1C expression changes during the maturation of chromaffin cells. These possibilities might be discussed.

Please see response to item 21.

3. Tidal volume changes with the weight of the animals. Tidal volume should be adjusted for the weights of the animals tested. If there are weight differences between knockouts and wildtype it can have profound effects on the data.

Please see response to item 22.

https://doi.org/10.7554/eLife.78915.sa2

Article and author information

Author details

  1. Alba Timón-Gómez

    Department of Neurology, University of Miami, Miami, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Alexandra L Scharr and Nicholas Y Wong
    Competing interests
    No competing interests declared
  2. Alexandra L Scharr

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Alba Timón-Gómez and Nicholas Y Wong
    Competing interests
    No competing interests declared
  3. Nicholas Y Wong

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Alba Timón-Gómez and Alexandra L Scharr
    Competing interests
    No competing interests declared
  4. Erwin Ni

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Validation, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
  5. Arijit Roy

    1. Department of Physiology and Pharmacology, University of Calgary, Calgary, Canada
    2. Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
    3. Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft
    Competing interests
    No competing interests declared
  6. Min Liu

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Validation, Investigation, Methodology, Writing - original draft
    Competing interests
    No competing interests declared
  7. Julisia Chau

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  8. Jack L Lampert

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5367-7707
  9. Homza Hireed

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Formal analysis, Validation, Investigation, Methodology
    Competing interests
    No competing interests declared
  10. Noah S Kim

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
  11. Masood Jan

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Investigation, Visualization
    Competing interests
    No competing interests declared
  12. Alexander R Gupta

    1. Department of Surgery, University of California, San Francisco, San Francisco, United States
    2. Diabetes Center, University of California, San Francisco, San Francisco, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  13. Ryan W Day

    Department of Surgery, University of California, San Francisco, San Francisco, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  14. James M Gardner

    1. Department of Surgery, University of California, San Francisco, San Francisco, United States
    2. Diabetes Center, University of California, San Francisco, San Francisco, United States
    Contribution
    Resources, Supervision, Methodology
    Competing interests
    No competing interests declared
  15. Richard JA Wilson

    1. Department of Physiology and Pharmacology, University of Calgary, Calgary, Canada
    2. Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
    3. Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
    Contribution
    Software, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9942-4775
  16. Antoni Barrientos

    Department of Neurology, University of Miami, Miami, United States
    Contribution
    Resources, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    abarrientos@med.miami.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9018-3231
  17. Andy J Chang

    Department of Physiology and Cardiovascular Research Institute, University of California, San Francisco, San Francisco, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    Andy.Chang@ucsf.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1247-4794

Funding

Muscular Dystrophy Association (Career Development Award 862896)

  • Alba Timón-Gómez

National Institutes of Health (UCSF Transplant T32 FAVOR Grant P0548805)

  • Alexandra L Scharr

University of California, San Francisco (Physician-Scientist Scholars Program)

  • James M Gardner

Canadian Institutes of Health Research (Research Grant 201603PJT/366421)

  • Richard JA Wilson

Alberta Innovates - Health Solutions (Senior Scholar)

  • Richard JA Wilson

National Institute of General Medical Sciences (R35 Grant GM118141)

  • Antoni Barrientos

University of California, San Francisco (Sandler Program for Breakthrough Biomedical Research New Frontier Award)

  • Andy J Chang

University of California, San Francisco (Cardiovascular Research Institute)

  • Andy J Chang

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

Acknowledgements

We thank Peter Lee for technical assistance, Alex Diaz de Arce for assistance with RNAseq analysis, Kailyss Freeman and the UCSF VITAL Core for coordinating donor tissue, ACD Bio for BaseScope in situ hybridization, Blair Gainous, Pauline Colombier, Brian Black, and the CVRI Transgenic Mouse Core for guidance and technical support in generating Higd1c mutant mice, Chris Allen for use of his two-photon microscope and cryostat, Jeremy Reiter for use of his widefield microscope, and the UCSF Nikon Imaging Center for use of their confocal and widefield microscopes. We sincerely thank Donor Network West, and most importantly the organ donors and their families, who give this precious gift to further scientific research.

Ethics

Human subjects: For human tissue, CB bifurcations were procured from research-consented, de-identified organ transplant donors through a collaboration with the UCSF VITAL Core (https://surgeryresearch.ucsf.edu/laboratories-research-centers/vital-core.aspx) and designated as non-human subjects research specimens by the UCSF IRB.

All experiments with animals were approved by the Institutional Animal Care and Use Committees at the University of California, San Francisco (AN183237-03) and the University of Calgary (AC16-0204).

Senior Editor

  1. Vivek Malhotra, The Barcelona Institute of Science and Technology, Spain

Reviewing Editor

  1. David J Paterson, University of Oxford, United Kingdom

Reviewers

  1. Keith Buckler, University of Oxford, United Kingdom
  2. Chris Wyatt

Publication history

  1. Preprint posted: October 5, 2021 (view preprint)
  2. Received: March 24, 2022
  3. Accepted: October 17, 2022
  4. Accepted Manuscript published: October 18, 2022 (version 1)
  5. Accepted Manuscript updated: October 20, 2022 (version 2)
  6. Version of Record published: November 4, 2022 (version 3)

Copyright

© 2022, Timón-Gómez, Scharr, Wong 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. Alba Timón-Gómez
  2. Alexandra L Scharr
  3. Nicholas Y Wong
  4. Erwin Ni
  5. Arijit Roy
  6. Min Liu
  7. Julisia Chau
  8. Jack L Lampert
  9. Homza Hireed
  10. Noah S Kim
  11. Masood Jan
  12. Alexander R Gupta
  13. Ryan W Day
  14. James M Gardner
  15. Richard JA Wilson
  16. Antoni Barrientos
  17. Andy J Chang
(2022)
Tissue-specific mitochondrial HIGD1C promotes oxygen sensitivity in carotid body chemoreceptors
eLife 11:e78915.
https://doi.org/10.7554/eLife.78915
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    Jacob M Winter, Heidi L Fresenius ... Jared Rutter
    Research Article

    The tumor suppressor gene PTEN is the second most commonly deleted gene in cancer. Such deletions often include portions of the chromosome 10q23 locus beyond the bounds of PTEN itself, which frequently disrupts adjacent genes. Coincidental loss of PTEN-adjacent genes might impose vulnerabilities that could either affect patient outcome basally or be exploited therapeutically. Here we describe how the loss of ATAD1, which is adjacent to and frequently co-deleted with PTEN, predisposes cancer cells to apoptosis triggered by proteasome dysfunction and correlates with improved survival in cancer patients. ATAD1 directly and specifically extracts the pro-apoptotic protein BIM from mitochondria to inactivate it. Cultured cells and mouse xenografts lacking ATAD1 are hypersensitive to clinically used proteasome inhibitors, which activate BIM and trigger apoptosis. This work furthers our understanding of mitochondrial protein homeostasis and could lead to new therapeutic options for the hundreds of thousands of cancer patients who have tumors with chromosome 10q23 deletion.