Alpha-methyl-para-tyrosine and amphetamine ameliorate hyperactivity in a novel mouse model of dopamine transporter deficiency syndrome
Emma E Russo, Ameneh Rezayof, Conner Wallace, Erin Q Williams, Pieter Beerepoot, Marija Milenkovic, Maria Novalen, Aled Blundell, Tatiana V Lipina, Jason Locke, Raveen Christian, Peter S B Finnie, Landon J Edgar, Rachel F Tyndale, Dawn Watkins-Chow, Amy J Ramsey, Sara R Jones
TL;DR
Researchers created a mouse model for a dopamine transporter disorder and found that two FDA-approved drugs can reduce hyperactivity in these mice.
Contribution
A novel mouse model of dopamine transporter deficiency syndrome was developed, and two FDA-approved drugs were identified as potential treatments.
Findings
A313V knock-in mice show hyperactivity, reduced dopamine, and impaired dopamine uptake.
Alpha-methyl-para-tyrosine and amphetamine reduce hyperactivity in A313V mice.
Pifithrin-μ increases DAT levels in the midbrain of A313V mice.
Abstract
The dopamine transporter is essential for dopamine homeostasis maintenance. Therefore, single amino acid changes in its gene can be sufficient to induce disease, such as dopamine transporter deficiency syndrome (DTDS). DTDS-associated variants may lead to DAT protein misfolding, retention in the endoplasmic reticulum, and reduced DAT surface expression. In turn, proper dopaminergic regulation is lost. Current treatments for DTDS are largely ineffective, necessitating better options. We developed a novel mouse model of DTDS harboring the A313V knock-in DAT variant, a proxy for the human A314V variant. The A313V mice are hyperactive, have decreased striatal tissue content of dopamine and increases in its metabolite HVA, and impaired dopamine uptake. FDA approved compounds alpha-methyl-para-tyrosine and amphetamine ameliorate the observed hyperactivity. Moreover, alpha-methyl-para-tyrosine…
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Figure 17- —http://dx.doi.org/10.13039/501100000024Canadian Institutes of Health Research (CIHR)
- —Canada Research Chairs Program
- —http://dx.doi.org/10.13039/100014405Centre for Addiction and Mental Health Foundation (CAMH)
- —http://dx.doi.org/10.13039/100010523Centre for Addiction and Mental Health (CAMH)
- —Canadian Foundation for Innovation/Ontario Research Funds
- —National Institute of Health of United States National Institute on Alcohol Abuse and Alcoholism
- —http://dx.doi.org/10.13039/100000026HHS | NIH | National Institute on Drug Abuse (NIDA)
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Taxonomy
TopicsAmino Acid Enzymes and Metabolism · Neurotransmitter Receptor Influence on Behavior · Tryptophan and brain disorders
The paper explainedProblemDopamine transporter deficiency syndrome (DTDS) is a rare, complex movement disorder typically characterized first by symptoms of hyperkinesia, followed over time by symptoms of Parkinsonism. Patients with DTDS rarely live beyond adolescence, and treatment options are largely ineffective or provide only temporary clinical relief. Thus, better treatment options are greatly needed. In this study, we generated a DTDS mouse model harboring the A313V dopamine transporter (DAT) knock-in variant, which models the DTDS-causing A314V DAT variant in humans, to determine treatment endpoints and test several pharmacological therapeutic options.ResultsWe observed marked hyperactivity in the A313V DAT knock-in mice, impaired dopamine uptake, and increased striatal tissue content of dopamine and DOPAC, whereas HVA levels were decreased. FDA-approved compound alpha-methyl-para-tyrosine and amphetamine were able to reduce the hyperactivity seen in the A313V DAT knock-in mice. Noribogaine, a pharmacological chaperone for DAT in cell systems, was unable to rescue the expression of the A313V DAT variant, but pifithrin-u, as HSP70 inhibitor, significantly increased midbrain levels of DAT in the A313V mice.ImpactOur study characterizes, for the first time, a mouse model of a DTDS-causing DAT variant in humans. Further, we provide evidence for two novel treatments for DTDS, for which current options do not suffice. Importantly, one of these treatments, alpha-methyl-para-tyrosine, may be disease modifying by addressing the hyperdopaminergic tone underlying the symptoms of hyperactivity in these mice.
Introduction
The dopamine transporter (DAT) is a 12 transmembrane domain protein that is expressed in dopamine neurons (Ciliax et al, 1995; Ciliax et al, 1999; Chen and Reith, 2000; Bu et al, 2021). DAT is critically involved in dopamine (DA) homeostasis by coupling the transport of extracellular DA with Na+ and Cl− back into the presynaptic neuron (Giros et al, 1996; Salahpour et al, 2008; Vaughan and Foster, 2013), similar to other members of the neurotransmitter symporter solute carrier 6 (SLC6) family, including the norepinephrine transporter, the serotonin transporter, and the GABA transporter (Kanner and Zomot, 2008).
Variants in the DAT gene, SLC6A3, have been implicated in several diseases (Vaughan and Foster, 2013) including Autism Spectrum Disorder (DiCarlo et al, 2019; Hamilton et al, 2013), Attention Deficit Hyperactivity Disorder (ADHD) (Mazei-Robison et al, 2005), Bipolar Disorder (Pinsonneault et al, 2011), and dopamine transporter deficiency syndrome (DTDS) (Assmann et al, 2004; Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014; Yildiz et al, 2016; Galiart et al, 2017; Kuster et al, 2018; Heidari et al, 2020; Nasehi et al, 2020; Tehreem and Kornitzer, 2020; Baga et al, 2021; Mir et al, 2022; Silva et al, 2023). DTDS is typically characterized first by symptoms of hyperactivity; these symptoms progress over time to a state of Parkinsonism–dystonia through unknown mechanisms and are accompanied by increased levels of DA metabolites present in cerebrospinal fluid (Ng et al, 2014). Patients diagnosed with DTDS rarely live beyond adolescence due to secondary complications of the disease, such as orthopedic, gastrointestinal, and respiratory issues (Kurian et al, 2011; Ng et al, 2014; Spaull and Kurian, 2023). Importantly, DTDS is considered a “pharmaco-resistant condition” (Ng et al, 2014). Treatment strategies such as muscle relaxants, dopaminergic, anticholinergic, and GABAergic medications, along with surgical interventions, have generally proven unsuccessful (Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014). Thus, effective treatments for DTDS are greatly needed.
SLC6A3 missense and deletion variants associated with DTDS are posited to cause protein misfolding, which disrupts trafficking of DAT and reduces protein levels at the cell membrane (Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014), needed to maintain typical physiological functions (Sanders and Myers, 2004). The quality control machinery in the endoplasmic reticulum (ER) normally prevents misfolded proteins with aberrant conformations from advancing along the secretory pathway. However, the ER can excessively retain and degrade proteins that are potentially functional, leading to inadequate levels of the protein at its physiological destination (Morello et al, 2000). In the case of DTDS-causing variants, impeded DAT maturation through the ER leads to low levels or no surface expression of the protein, reduced DA uptake, and consequent disease (Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014; Beerepoot et al, 2016; Asjad et al, 2017).
Pharmacological chaperones are exogenously-applied, small molecule ligands that bind to an intermediately-folded protein of interest and assist in its exit from the ER, providing an opportunity for “rescue” of misfolded membrane proteins. This “rescue” is proposed to be mediated through stabilization of a native-like conformation of the target protein, allowing it to exit from the ER (Leidenheimer and Ryder 2014; Bhat et al, 2021). Successful rescue with pharmacological chaperones has been demonstrated for clinically-relevant misfolded disease-causing variants of several proteins, such as the V2 vasopressin receptor (Morello et al, 2000), alpha-galactosidase A (Germain et al, 2019), the F508del cystic fibrosis transmembrane conductance receptor (Baatallah et al, 2021) and the gonadotropin releasing hormone receptor (Janovick et al, 2013). SLC6 transporters are likewise amenable to rescue via pharmacological chaperones (Freissmuth et al, 2018), as demonstrated for SERT (Bhat et al, 2021; El-Kasaby et al, 2024; El-Kasaby et al, 2010) and DAT (Beerepoot et al, 2016; Asjad et al, 2017; Bhat et al, 2021; Kasture et al, 2016). For both SERT and DAT, rescue can be achieved using ibogaine and noribogaine, the less cardiotoxic (Litjens and Brunt, 2016) active metabolite of ibogaine, as well as bupropion (Beerepoot et al, 2016; Asjad et al, 2017; Bhat et al, 2021; Kasture et al, 2016; Sutton et al, 2022).
In order to gain further insight into DTDS and identify potential pharmacotherapies, we have generated a novel line of transgenic knock-in mice carrying one of the DTDS missense variants. The knock-in mouse (mA313V variant) models the human DTDS hA314V variant and was chosen for this study because (1) Patients harboring the hA314V variant can live to adulthood (Ng et al, 2014), providing a window for pharmacological intervention, and (2) This hA314V DAT variant can be rescued by pharmacological chaperones in vitro (Beerepoot et al, 2016). In this study, we show that the mA313V mice recapitulate a subset of defining phenotypes observed in human DTDS patients, including hyperlocomotion and changes in DA metabolites. The mA313V DAT model also has reduced expression and uptake of DA, providing the first support from a mammalian model for observations originally made in heterologous cell systems. Our attempts to rescue the ER-retained, misfolded A313V DTDS variant using the pharmacological chaperone noribogaine were unsuccessful. However, findings show that AMPH and the tyrosine hydroxylase inhibitor alpha-methyl-para-tyrosine (ɑMPT) can effectively reduce the hyperactivity of the DTDS animals. These key findings are of both clinical and translational interest. Indeed, ɑMPT, an FDA-approved drug that is used for clinical management of hypertension, (1) Reduces hyperactivity of the mA313V mice, and (2) may have disease modifying properties and reduce disease burden by inhibiting excess dopamine synthesis and neurotransmission. Altogether, our study reports upon the efficacy of pharmacological treatment via clinically available drugs that may be translated to human DTDS patients.
Results
Neurochemical characterization
HEK cells harboring the DTDS-causing human A314V SLC6A3 variant were reported to express reduced mature (fully glycosylated) DAT and an increased ratio of immature to mature (core-glycosylated) DAT protein (Beerepoot et al, 2016). However, to date, no study has assessed the maturation status of a DTDS-causing variant in a mammalian model. As shown in Fig. 1A–D, striatal (WT: 100 ± 9.93% of WT average vs A313V: 23.01 ± 5.79% of WT average, t = 6.115, df = 8, *P *= 0.0003) and midbrain (WT: 100 ± 6.77% of WT average vs A313V: 24.39 ± 3.57% of WT average, *t *= 9.876, df = 6, P < 0.0001) homogenates from the A313V knock-in mice express significantly decreased levels of mature DAT (Fig. 1A–D) and an increased percentage of immature DAT to total DAT levels in the midbrain (WT: 3.66 ± 0.20% immature DAT vs A313V: 31.67 ± 3.73% immature DAT, t = 7.499, df = 6, P = 0.0003) (Fig. 1E). Indeed, there is a 75% decrease in mature DAT protein expression in the striatum and midbrain of A313V mice as compared to WT littermate controls, while there is a marked (~sixfold) increase in immature protein in the midbrains of A313V mice.Figure 1. Western blot analysis of striatal and midbrain DAT levels in WT and A313V mice.(A) Representative western blot depicting striatal dopamine transporter (DAT) levels in wild-type (WT) (n = 6, 1 male, 5 females) and DAT A313V-knock in (A313V) (n = 4, 1 male and 3 female) mice, with a DAT knock-out (DKO) negative control. (B) Quantification of striatal DAT levels in WT and A313V mice relative to WT levels and normalized to GAPDH loading control showing A313V have significantly less striatal DAT compared to WT mice (WT: 100 ± 9.93% of WT average vs A313V: 23.01 ± 5.79% of WT average, t = 6.115, df = 8, P = 0.0003). (C) Representative western blot depicting DAT levels in WT (n = 4, 3 midbrains/lane, total of 12 animals; mixed sexes amongst samples) and A313V (n = 4, 3 midbrains/lane, total of 12 animals; mixed sexes amongst samples) mice. Arrows indicate the mature and immature forms of the DAT protein. (D) Quantification of midbrain DAT levels in WT and A313V mice relative to WT levels and normalized to total protein loading control showing A313V mice have significantly lower levels of midbrain DAT compared to WT mice (WT: 100 ± 6.77% of WT average vs A313V: 24.39 ± 3.57% of WT average, t = 9.876, df = 6, P < 0.0001). (E) Bar graph quantification showing the percentage of immature DAT levels to total DAT levels in the midbrain in WT and A313V mice demonstrating A313V mice have a greater percentage of immature DAT relative to total DAT compared to WT mice (WT: 3.66 ± 0.20% immature DAT vs A313V: 31.67 ± 3.73% immature DAT, t = 7.499, df = 6, P = 0.0003). (F) Quantification of midbrain DAT levels in WT (n = 6, 3 male and 3 females) and A313V (n = 5, 3 males and 2 females) mice relative to WT levels and normalized to total protein loading control showing A313V mice have significantly lower levels of midbrain DAT compared to WT mice (WT: 100 ± 10.76% of WT average vs A313V: 53.26 ± 10.97% of WT average, t = 3.042, df = 8.847, P = 0.0143). (G) The higher molecular weight band represents the mature, fully glycosylated dopamine transporter (DAT) with complex oligosaccharides, which were removed with the enzyme PNGase F in wild-type (WT) (lanes 1 and 2) and DAT A313V knock-in (A313V) (lanes 6 and 7) mice. The lower molecular weight band represents the immature, core glycosylated DAT localized to the ER, as evident by digestion with the enzyme endoglycosidase (EndoH) in A313V midbrain samples (lanes 8 and 9). Each lane has 3 midbrains per sample, with mixed-sexes in each sample. Closed circular points represent values from female mice, and open square points represent values from male mice. X’s represent value from mixed-sex samples. Student’s unpaired, two-tailed t tests were conducted. All results are presented as mean ± SEM, *P ≤ 0.05, ***P ≤ 0.001, ****P < 0.0001. Source data are available online for this figure.
To molecularly confirm that the higher molecular weight band is mature DAT, while the lower molecular weight band is immature DAT, midbrain homogenates were next digested with the glycosidases peptide N-glycosidase F (PNGase F) and endoglycosidase H (EndoH). As shown in Fig. 1G, results confirm that the upper molecular weight band in the brain western blot samples indeed represents the mature, fully glycosylated DAT protein, whereas the lower band represents the immature, core-glycosylated DAT protein localized to the ER (Fig. 1G). This is the first evidence that a DTDS-disease causing variant leads to DAT retention in the ER and an increase in immature DAT protein species in a mammalian model.
Next, to determine whether the decreases in DAT protein levels are only due to ER retention, we assessed levels of DAT mRNA in midbrain samples from WT and A313V mice. DAT mRNA levels were reduced by ~50% in A313V mice as compared to WT animals (WT: 100 ± 10.76% of WT average vs A313V: 53.26 ± 10.97% of WT average, *t *= 3.042, df = 8.847, P = 0.0143) (Fig. 1F). This result suggests that, in addition to ER retention affecting total A313V DAT protein levels, reduced A313V mRNA levels also potentially contribute to the overall reduced expression of this variant as compared to WT DAT.
In the striatum of DAT-KO mice, tyrosine hydroxylase (TH) levels have been shown to be decreased by 90% (Jaber et al, 1999). To determine if similar compensatory mechanisms occur in the A313V mice as a result of decreased DAT levels, levels of TH and phosphor TH-ser40 (pTH s40) were measured in the striatum of WT and A313V mice. As shown in Fig. 2A–D, A313V mice show an approximately 35% reduction in total TH (Fig. 2B) (WT: 100 ± 9.34% of WT vehicle average, vs A313V: 65.11 ± 5.53% of WT vehicle average, t = 3.495, df = 7.679, P = 0.0087), and a near 50% reduction in pTH s40 (Fig. 2C) (WT: 100 ± 11.81% of WT vehicle average, A313V: 45.92 ± 2.90% of WT vehicle average, t = 4.447, df = 5.600, P = 0.0051), with no statistically significant difference in the pTH s40/TH ratio (Fig. 2D) (WT: 100 ± 13.66% of WT average vs A313V: 68.06 ± 5.25% of WT average, t = 2.183, df = 6.446, P = 0.0687) (Fig. 2D). Furthermore, WT mice have approximately twofold greater midbrain TH mRNA (WT: 100 ± 11.38% of WT average vs A313V: 48.43 ± 9.18% of WT average, t = 3.528, df = 8.909, P = 0.0065) (Fig. 2E), and midbrain VMAT2 mRNA (WT: 100 ± 15.33% of WT average vs A313V: 50.69 ± 10.98% of WT average, t = 2.615, df = 8.612, P = 0.029) compared to A313V mice (Fig. EV1C). These results suggest that, similar to what is seen in DAT-KO mice, compensatory mechanisms arise in response to the A313V DAT variant in key regulators of dopamine neurotransmission.Figure 2. Western blot analysis of striatal and midbrain TH levels and analysis of midbrain DAT protein species in WT and A313V mice.(A) Representative western blot depicting striatal tyrosine hydroxylase (TH) and phospho-TH s40 (pTH s40) levels in wild-type (WT) and dopamine transporter (DAT) A313V knock-in (A313V) mice. (B) Quantification of striatal TH levels in WT (n = 7, 4 males and 3 females) and A313V (n = 7, 6 males and 1 female) mice relative to WT levels and normalized to total protein loading control showing that A313V have significantly less striatal TH compared to WT mice (WT: 100 ± 9.34% of WT vehicle average, vs A313V: 65.11 ± 5.53% of WT vehicle average, t = 3.495, df = 7.679, *P *= 0.0087). (C) Quantification of striatal pTH s40 levels in WT (n = 6, 4 males and 2 females) and A313V (n = 6, 5 males and 1 female) mice relative to WT levels and normalized to GAPDH control showing that A313V mice have significantly less striatal pTH s40 compared to WT mice (WT: 100 ± 11.81% of WT vehicle average, A313V: 45.92 ± 2.90% of WT vehicle average, t = 4.447, df=5.600, P = 0.0051). (D) Quantification of striatal pTH s40/TH levels in WT (n = 6, 4 males and 2 females) and A313V (n = 6, 5 males and 1 female) mice showing that there is no significant difference between A313V mice and WT mice (WT: 100 ± 13.66% of WT average vs A313V: 68.06 ± 5.25% of WT average, t = 2.183, df=6.446, p = 0.0687). (E) rt-qPCR performed on midbrain samples showing that WT mice have approximately twofold greater Th (tyrosine hydroxylase, TH) (WT: 100 ± 11.38% of WT average vs A313V: 48.43 ± 9.18% of WT average, t = 3.528, df = 8.909, P = 0.0065) mRNA compared to A313V mice. (B–E) All results are presented as mean ± SEM. Closed circular points represent values from female mice, and open square points represent values from male mice. Welch’s unpaired, two-tailed t tests were conducted, *P ≤ 0.05, ***P ≤ 0.001. Source data are available online for this figure.
Lower abundance of mature DAT in the striatum suggests that A313V mice may have impaired presynaptic DA recycling, and thus depleted reserve pools of dopamine, similar to what has been described in DAT- knock out (DAT-KO) animals (Jones et al, 1998; Sotnikova et al, 2005). Analysis of striatal tissue content of dopamine and its metabolites revealed that the A313V mice have a dramatic (approximately fourfold) decrease in dopamine tissue levels (WT: 471.23 ± 47.51 pg/mg vs A313V: 104.13 ± 6.35 pg/mg, t = 10.63, df = 9, P < 0.0001) and nearly 50% less DOPAC compared to WT mice (WT: 113.321857 ± 3.96 pg/mg vs A313V: 56.27 ± 7.00 pg/mg, t = 6.323, df = 10, P < 0.0001) (Fig. 3A,B). Conversely, the A313V show significantly elevated levels of homovanillic acid (HVA), increased by over 100% (WT: 42.99 ± 3.72 pg/mg vs A313V: 136.94 ± 13.09 pg/mg, t = 5.868, df = 10, P = 0.0002) (Fig. 3C), and increased ratios of DOPAC/DA (WT: 0.25 ± 0.037 pg/mg vs A313V: 0.56 ± 0.08 pg/mg, t = 3.079, df = 10, P = 0.0117) and HVA/DA (WT: 0.09 ± 0.00 pg/mg vs A313V: 1.20 ± 0.091 pg/mg, t = 11.11, df = 9, P < 0.0001) (Fig. 3D,E). With the exception of DOPAC, these neurochemical measures replicate that which has been reported in DAT-KO mice, which completely lack DAT protein expression. While there is a 50% reduction of DOPAC levels in the mA313V mice, no changes in DOPAC levels were reported in DAT-KO mice (Jones et al, 1998).Figure 3. Striatal tissue content of dopamine and metabolites, dopamine kinetics measured in striatal slices from WT and A313V mice, and weight comparison and body composition analysis in WT, A313V, and DAT-KO mice.HPLC analysis on striatal homogenates from wild-type (WT) (n = 5, 3 females and 2 males) and dopamine transporter (DAT) A313V knock-in mice (A313V) (n = 7, 3 females and 4 males) showed that levels of (A) dopamine (DA) (WT: 471.23 ± 47.51 pg/mg vs A313V: 104.13 ± 6.35 pg/mg, t = 10.63, df = 9, P < 0.0001) and (B) DOPAC (WT: 113.321857 ± 3.96 pg/mg vs 56.27 ± 7.00 pg/mg, t = 6.323, df = 10, P < 0.0001) were greater, while (C) HVA (WT: 42.99 ± 3.72 pg/mg vs A313V: 136.94 ± 13.09 pg/mg, t = 5.868, df = 10, P = 0.0002) was lower in WT mice compared to A313V mice. (D) Ratios of DOPAC/DA (WT: 0.25 ± 0.037 pg/mg vs A313V: 0.56 ± 0.08 pg/mg, *t *= 3.079, df = 10, P = 0.0117) and (E) HVA/DA (WT: 0.09 ± 0.00 pg/mg vs A313V: 1.20 ± 0.091 pg/mg, t = 11.11, df = 9, P < 0.0001) were lower in WT than A313V mice, indicating higher DA turnover in the A313V mice. Fast scan cyclic voltammetry was used to record dopamine responses to single electrical pulses (750 µA, 4 msec, biphasic) in dorsal striatal slices from wild-type (WT) WT (n = 59 slices from 12 animals, 5 females and 7 males) and dopamine transporter (DAT) A313V knock-in mice (A313V) (n = 58 slices from 11 animals, 6 females, 5 males). (F) Averaged raw dopamine concentration (µM) versus time in seconds (s) plots with SEMs from WT and A313V mice showed higher peaks and slower returns to baseline (clearance) in A313V mice (n = 57–59). (G) The maximal velocity of dopamine uptake (V_max_), determined using the Michaelis-Menten model, was greater in WT compared to A313V mice (WT: 4.24 ± 0.18 μM/s vs A313V: 0.76 ± 0.03 μM/s, t = 18.61, df = 21, P < 0.0001). (H) Dopamine uptake as measured by the average time constant (tau), from an exponential decay model showed increased tau in A313V mice compared to WT mice (WT: 0.53 ± 0.02 s vs A313V: 5.22 ± 0.17 s, t = 28.51, df = 21, P < 0.0001). (I) Bodyweight in grams was assessed in wild-type (WT), dopamine transporter (DAT) A313V knock-in (A313V), and DAT-knock out (DAT-KO) mice. A one-way ANOVA on genotype was performed (F2,25 = 8.592, P = 0.0014) and Tukey’s multiple comparisons test showed that there is no statistically significant difference in weight between WT (n = 11, 6 males and 5 females, 30.03 ± 1.25 g) and A313V (n = 11, 6 males and 5 females, 25.88 ± 1.33 g) mice (P = 0.0744) or between A313V and DAT-KO (n = 6, 3 males and 3 females, 21.24 ± 1.64 g) mice (P = 0.0974), whereas DAT-KO weighed less than WT mice (P = 0.0011). Body composition in the same group of mice was then assessed using the dual energy X-ray absorptiometry (DEXA) technique to examine (J) lean mass as a fraction of body weight, (K) fat mass as a fraction of body weight, (L) bone mineral content (BMC) as a fraction of body weight, and (M) bone area. There was a significant effect of genotype between WT, A313V, and DAT-KO mice for lean mass/body weight (F2,24 = 14.26, P < 0.0001), fat mass/body weight (F2,23 = 13.70, P = 0.0001), and bone area (F2,25 = 27.99, P < 0.0001), but not BMC/body weight (F2,25 = 1.252, P = 0.3034) as revealed by separate one-way ANOVAs. Tukey’s multiple comparisons showed that WT mice (n = 11, 6 males and 5 females, 0.473 ± 0.18) have a smaller lean mass/body weight ratio compared to A313V mice (n = 11, 6 males and 5 females, 0.553 ± 0.01) (*P *= 0.0002) and DAT-KO mice (n = 5, 2 males and 3 females, 0.560 ± 0.00) (P = 0.0011), whereas there is no difference between A313V and DAT-KO lean mass/body weight (P = 0.9387). WT mice (n = 11, 6 males and 5 females, 0.468 ± 0.02) have a greater fat mass/body weight ratio than A313V mice (n = 11, 6 males and 5 females, 0.386 ± 0.01) (P = 0.0004) and DAT-KO mice (n = 4, one male and 3 females, 0.367 ± 0.00) (P = 0.0013), whereas there is no difference between A313V and DAT-KO mice (P = 0.7299). Lastly, WT mice (n = 11, 6 males and 5 females, 8.258 ± 0.09) have a greater bone area than both A313V (n = 11, 6 males and 5 females, 7.755 ± 0.09) (P = 0.0071) and DAT-KO mice (n = 6, 3 males and 3 females, 6.920 ± 0.20) (P < 0.0001). A313V mice also have a greater bone area than DAT-KO mice (P = 0.0003). All results are presented as mean ± SEM. In bar graphs, closed circular points represent values from female mice, and open square points represent values from male mice. Student’s unpaired, two-tailed t tests and one-way ANOVAs to assess the effect of genotype with Tukey’s multiple comparisons were conducted. *P ≤ 0.05, ***P ≤ 0.001, ****P < 0.0001, ^#^P < 0.05. For post hoc effects: ^##^P ≤ 0.01, ^###^P ≤ 0.001, ^####^*P *< 0.0001. Source data are available online for this figure.
To test whether the reduced DA tissue content levels in the A313V mice were accompanied by a corresponding impairment in measured dopamine release and uptake, fast scan cyclic voltammetry was used to measure the rate of dopamine clearance from the extracellular space following electrically-evoked release in striatal slices (Fig. 3F). The A313V mice have a near 80% reduction in V_max_ (WT: 4.24 ± 0.18 μM/s vs A313V: 0.76 ± 0.03 μM/s, t = 18.61, df = 21, P < 0.0001) (Fig. 3G). When DA clearance was fit to an exponential curve, A313V mice exhibited a longer decay time constant, tau, compared to WT mice (WT: 0.53 ± 0.02 s vs A313V: 5.22 ± 0.17 s, *t *= 28.51, df = 21, P < 0.0001) (Fig. 3H). Indeed, the average tau value in A313V mice was approximately tenfold greater than in WT mice. Both phenotypes are indicative of decreased dopamine clearance, caused by lower levels of functional DAT as a result of the A313V variant.
Behavioral characterization
Tight regulation of intra- and extracellular dopamine levels is critical for many cognitive and behavioral processes and can be affected by DAT levels. To examine the consequences of the A313V DAT variant on general body composition and dopamine-dependent behaviors, a variety of tests were conducted. We first assessed body weight in comparison to WT and DAT-KO mice. A one-way ANOVA indicated a significant effect of genotype on weight (F_2,25_ = 8.592, P = 0.0014), and Tukey’s post-hoc multiple comparisons showed that A313V (25.88 ± 1.33 g) did not differ significantly from either WT (30.03 ± 1.25 g) (P = 0.0744) or DAT-KO mice (21.21 ± 1.64 g) (P = 0.0974), unlike DAT-KO mice which are underweight as compared to WT mice (P = 0.0011) (Bossé et al, 1997) (Fig. 3I). Next, a body composition analysis was performed. There was an effect of genotype on lean mass/body weight ratio (F2,24 = 14.26, *P *< 0.0001) (Fig. 3J), fat mass/body weight ratio (F2,23 = 13.70, P = 0.0001) (Fig. 3K), and bone area (F2,25 = 27.99, P < 0.0001) (Fig. 3M), but not on bone mineral content (BMC)/weight ratio (F2,25 = 1.252, P = 0.3034) (Fig. 3L). Post-hoc Tukey’s multiple comparisons tests showed that A313V mice have a greater lean mass/body weight ratio than WT mice (WT: 0.473 ± 0.012 vs A313V: 0.553 ± 0.006, P = 0.002) but show no difference compared to DAT-KO mice (DAT-KO: 0.56 ± 0.003, P = 0.9387) (Fig. 3J). Similarly, A313V mice have a lower fat mass/body weight ratio compared to WT mice (WT: 0.468 ± 0.186 vs A313V: 0.386 ± 0.0006, P = 0.0004) but not compared to DAT-KO mice (DAT-KO: 0.367 ± 0.0011, P = 0.7299) (Fig. 3K). Bone area, a measure of bone mineral content (BMC)/bone mineral density (BMD), was significantly decreased in A313V mice (7.755 ± 0.094 cm^2^) compared to WT mice (8.258 ± 0.093 cm^2^, P = 0.0071), and significantly increased compared to DAT-KO mice (6.920 ± 0.2 cm^2^, P = 0.0003) (Fig. 3M). These results suggest that A313V mice are more similar to DAT-KO mice than WT mice in terms of body composition.
Next, we conducted various behavioral measurements. The dorsal immobility response (DIR)—a stereotyped limb extension and immobility when mice are lifted by the nape of the neck—is shorter in duration when dopaminergic transmission is elevated (Lalonde and Strazielle, 2022). A313V mice tested with this assay were approximately three times as fast to move (decreased DIR) than their WT counterparts (WT: 64.89 ± 8.68 s vs A313V: 26.80 ± 5.99 s, t = 3.675, df = 17, P = 0.0019) (Fig. 4I), suggestive of a state of hyperdopaminergia due to reduced dopamine uptake. Consistent with this finding, when placed into a novel open-field arena for 150 min, adult A313V mice traveled over three times the mean total distance (total distance the subject has traveled; defines the subject’s location as the centroid of the subject) as their WT counterparts (WT: 3320.08 ± 153.95 cm vs A313V: 11303.43 ± 765.44 cm, t = 9.873, df = 52, P < 0.0001) (Fig. 4A,E), and roughly two times greater mean horizontal activity (count of horizontal beam breaks) (WT: 15682.84 ± 519.67 beam breaks vs A313V: 37977.06 ± 1561.93 beam breaks, t = 12.72, df = 52, P < 0.0001) (Fig. 4B,F), vertical activity/rearing behavior (count of vertical beam breaks) (WT: 628.67 ± 44.97 beam breaks vs A313V: 1238.28 ± 107.49 beam breaks, t = 5.097, df = 54, P < 0.0001 (Fig. 4C,G), and number of stereotypic behaviors (the number of beam breaks due to stereotypic activity; when the animal breaks the same beam or set of beams repeatedly) (9818.7 ± 493.73 vs 23,804.04 beam breaks ± 1079.89 beam breaks, t = 11.63, df = 53, P < 0.0001) (Fig. 4D,H). When aged to 15 months, the A313V mice continued to be three-times as hyperactive compared to age-matched WT mice (3548.40 ± 648.59 cm vs 8659.40 ± 233.89 cm, t = 7.413, df = 8, P < 0.0001) (Fig. EV1A,B). Additionally, there was no observation of dystonia in A313V mice compared to WT mice as assessed during the pole reversal test in either T turn latency (WT: 7.72 ± 2.21 s vs A313V: 10.76 ± 2.54 s vs DAT-KO: 5.68 ± 1.44 s, F2,23 = 0.9805, P = 0.3902) or latency to descend (WT: 18.82 ± 3.64 s vs A313V: 16.02 ± 2.63 s vs DAT-KO: 13.1 ± 1.95 s, F2,23 = 0.5415, P = 0.5892) (Fig. EV1D,E). Similarly, there was no difference in percentage of foot faults between WT, A313V, and DAT-KO mice as assessed through the foot fault test (WT: 4.31 ± 0.41% of foot faults vs A313V: 3.99 ± 0.95% of foot faults vs DAT-KO: 3.95 ± 0.75% of foot faults, F2,6 = 0.070, P = 0.933 (Fig. EV1F). A tertiary measure of dystonia, the tail suspension test (Liu et al, 2015; Pappas et al, 2015), was also performed, and severity of clasping was recorded. A one-way ANOVA revealed no difference in clasping severity between WT, A313V, and DAT-KO mice (WT: 1.71 ± 0.64 clasping severity score vs A313V: 1.5 ± 0.45 clasping severity score vs DKO: 1.43 ± 0.61 clasping severity score, F2,21 = 0.06414, P = 0.9381) (Fig. EV1G).Figure 4. Baseline locomotor activity of adult WT and A313V mice.Baseline locomotor behavior of wild-type (WT), and dopamine transporter (DAT) A313V knock-in (A313V) mice. (A) Total distance, (B) vertical activity (C) horizontal activity, and (D) number of stereotypic counts were recorded in 5-min bins for 150 min in an open field chamber. An i.p. injection of saline was given at 60 min. A313V mice showed significantly greater summed levels of (E) total distance (WT: 3320.08 ± 153.95 cm vs 11303.43 ± 765.44 cm, t = 9.873, df = 52, P < 0.0001), (F) horizontal activity (WT: 15,682.84 ± 519.67 beam breaks vs A313V: 37977.06 ± 1561.93 beam breaks, t = 12.72, df = 52, P < 0.0001), (G) vertical activity (WT: 628.67 ± 44.97 beam breaks vs A313V: 1238.28 ± 107.49 beam breaks, t = 5.097, df = 54, P < 0.0001), and (H) stereotypic count (WT: 9818.7 ± 493.73 beam breaks vs A313v: 23,804.04 ± 1079.89 beam breaks, t = 11.63, df = 53, P < 0.0001) (WT n = 26, 10 females and 16 males; A313V n = 28, 14 females and 14 males). (I) Latency to move in WT (n = 9, 5 males and 4 females) and DAT A313V (n = 10, 5 males and 5 females) mice was measured after clasping the animal by the nape of the neck to elicit the dorsal immobility response (DIR). A313V mice were significantly faster than WT mice to move (WT: 64.89 ± 8.68 s vs A313V: 26.80 ± 5.99 s, t = 3.675, df = 17, P = 0.0019). (J) Mean stride length as a percentage of body length was assessed in WT (n = 11, 5 males and 6 females) and A313V) (n = 11, 5 males and 6 females) mice. There was no significant difference in this measure between WT and A313V mice (WT: 84.84 + /− 0.73% of body length vs A313V: 82.23 ± 1.68% of body length t = 1.369, df = 19, P = 0.1868) (n = 10–11). Closed circular points represent values from female mice, and open square points represent values from male mice. Results are presented as mean ± SEM. Student’s unpaired, two-tailed t tests were conducted, **P ≤ 0.01, ****P < 0.0001. Source data are available online for this figure.
Habituation of locomotor exploration was quantified using a habituation index (time in minutes to reach half of the maximal locomotor activity divided by total distance traveled using linear regression) (Mielnik et al, 2021). Habituation rate in A313V mice was roughly half that of WT controls (WT: 62.93 ± 0.72 min vs A313V: 124.71 ± 13.75 min, *t *= 4.402, df = 51, P < 0.0001) (Fig. EV1H). This suggests that in addition to being hyperactive, the A313V mice have impaired locomotor habituation to a novel environment relative to WT mice.
A subset of DAT-KO mice, which fully lack DAT activity, have been reported to display gait abnormalities compared to WT mice, in the form of decreased stride length (Cyr et al, 2003). We therefore performed gait analysis in A313V mice and mean stride length was measured as a percentage of body length. Our results show that there is no difference in mean stride length between A313V and WT mice (WT: 84.84 + /− 0.73% of body length, vs A313V: 82.23 ± 1.68% of body length, t = 1.369, df = 19, P = 0.1868) (Fig. 4J). Dopamine tone has also been shown to be modulatory in motor learning (Ogura et al, 2005; Beeler et al, 2010), including in drosophila harboring the R445C DTDS-disease causing DAT variant, which exhibit impaired motor coordination (Aguilar et al, 2021). We next performed a nine-day rotarod experiment to measure both coordination (Deacon, 2013) and motor learning (Beeler et al, 2010). A mixed model analysis revealed no significant effect of genotype (F1,13 = 0.6625, P = 0.4303), or a genotype by trial interaction (F5,50 = 1.727, P = 0.1455). There was a significant effect of trial (F5.65 = 14.79, P < 0.0001) (Fig. EV2A,B). In summary, the animals as a whole performed better over the consecutive trials. Rotarod performance was not significantly influenced by genotype or a genotype by trial interaction, suggesting no differences between A313V and WT animals throughout the experimental timeline.
Symptom management with pharmacotherapy
While amphetamine (AMPH) injection induces hyperactivity in WT mice, AMPH decreases locomotor activity in DAT-KO mice (Gainetdinov et al, 1999). To address the hyperactivity symptoms observed at the early stages of DTDS, AMPH was administered to the A313V and WT mice and their locomotor activity was recorded. A two-way ANOVA was performed on the sum of total distance traveled post-treatment in WT and A313V mice. There were no main effects of genotype (F1,17 = 0.3093, P = 0.5853) or treatment (F1,17 = 0.06423, P = 0.8030), but there was a genotype by treatment interaction (F1,17 = 22.38, P = 0.0002). Šidák’s multiple comparisons within genotype revealed a significant difference between WT mice treated with vehicle or AMPH and between A313V mice treated with vehicle or AMPH. WT mice treated with 3 mg/kg AMPH showed an eightfold increase in locomotor activity compared to vehicle-treated WT animals (vehicle: 378.75 ± 64.65 cm vs 3 mg/kg AMPH: 3190.20 ± 693.61 cm, P = 0.0171) (Fig. 5A,C). However, A313V mice treated with 3 mg/kg AMPH traveled approximately six times less than A313V mice that received vehicle (vehicle: 3698.60 ± 1052.91 cm vs 3 mg/kg AMPH: 568.86 ± 216.98 cm, P = 0.0029) (Fig. 5B,C).Figure 5. Amphetamine decreases locomotor activity in A313V mice.Total distance was recorded in 5-min bins for 150 min in wild-type (WT) and dopamine transporter (DAT) A313V knock-in (A313V) mice. The test began with a 60-min baseline followed by intraperitoneal (i.p.) administration of vehicle or amphetamine (AMPH) at the 60-min timepoint. Drug intervention is marked with an arrow. (A) total distance traveled over time and (C) cumulatively in WT and (B, C) A313V mice treated with 3 mg/kg AMPH. A two-way ANOVA on the sum of total distance traveled post-treatment showed no main effects of genotype (F1,17 = 0.3093, P = 0.5853) or treatment (F1,17 = 0.06423, P = 0.8030). There was a genotype by treatment interaction (F1,17 = 22.38, P = 0.0002). WT animals treated with AMPH (n = 5, 3 females and 2 males) traveled more than those treated with vehicle (n = 4, 2 males and 2 females) (vehicle: 378.75 ± 64.65 cm vs AMPH: 3190.20 ± 693.61 cm, P = 0.0171), whereas A313V animals treated with AMPH (n = 7, 2 males and 5 females) traveled significantly less than those treated with vehicle (n = 5, 3 males and 2 females) (vehicle: 3698.60 ± 1052.91 cm vs AMPH 568.86 ± 216.98 cm, P = 0.0029), as revealed by Šidák’s multiple comparisons within genotype. In bar graphs, closed circular points represent values from female mice, and open square points represent values from male mice. Results are presented as mean ± SEM. A two-way ANOVA examining treatment, genotype, and interactions, with Šidák’s multiple comparisons was conducted. For post hoc effects: ^#^P < 0.05, ^##^P ≤ 0.01. Source data are available online for this figure.
Next, we assessed the effects of methylphenidate (MPH), which has also been shown to reduce hyperactivity of DAT-KO mice similarly to AMPH (Gainetdinov et al, 1999). Moreover, MPH and AMPH are both clinically used for the treatment of ADHD. Interestingly, MPH administration was not able to decrease hyperactivity in the A313V mice compared to vehicle-treated animals, as revealed by a two-way ANOVA with Tukey’s multiple comparisons performed on the sum of total distance traveled post-treatment. There was a significant main effect of treatment (F2,79 = 30.25, *P *< 0.0001), genotype (F1,79 = 17.31, P < 0.0001), and a significant genotype by treatment interaction (F2,79 = 10.59, P < 0.0001). Tukey’s multiple comparisons showed that, in WT mice, total distance traveled upon treatment of both 30 mg/kg and 40 mg/kg was increased compared to vehicle (vehicle: 652.62 ± 63.32 cm vs 30 mg/kg MPH: 8156.67 ± 750.17 cm, *P *< 0.0001; vehicle: 652.62 ± 63.32 cm vs 40 mg/kg MPH: 4468.40 ± 1127.82, P = 0.0020, respectively) (Fig. EV3A,C,D). For A313V mice, there was no significant differences between vehicle and 30 mg/kg MPH (vehicle: 5658.48 ± 576.75 cm vs 30 mg/kg MPH: 7357.29 ± 535.62 cm, P = 0.1693), and vehicle and 40 mg/kg MPH (vehicle: 5658.48 ± 576.75 cm vs 40 mg/kg MPH: 7623.44 ± 715.31 cm, P = 0.0581) (Fig. EV3A–H). This observation is in contrast to what has been reported in DAT-KO mice: treatment with 30 mg/kg of MPH decreased locomotor activity in DAT-KO mice compared with vehicle controls (Gainetdinov et al, 1999).
Tyrosine hydroxylase (TH) is the rate limiting enzyme in the synthesis of DA, and inhibition of TH with alpha-methyl-para-tyrosine (ɑMPT) greatly reduces the behavioral hyperactivity of DAT-KO mice (Sotnikova et al, 2005). Therefore, the effects of ɑMPT on A313V and WT mice in the open-field arena were assessed at doses of 250 mg/kg, 125 mg/kg, 62.5 mg/kg, and 31 mg/kg. A two-way ANOVA conducted on the sum of total distance post-treatment showed a main effect of treatment (F3,74 = 6.690, P = 0.0005) and genotype (F1,74 = 9.174, *P *= 0.0034), and a genotype by treatment interaction (F3,74 = 7.401, P= 0.0002). Tukey’s multiple comparisons within genotype showed that compared to vehicle, neither of the four doses of ɑMPT lead to significant changes in the sum total distance post-treatment in WT mice (Fig. 6A,C,E) (vehicle: 652.62 ± 63.32 cm vs 250 mg/kg ɑMPT: 559.00 ± 172.21 cm, P = 0.994; vehicle: 652.62 ± 63.32 cm vs 125 mg/kg ɑMPT: 1320.67 ± 222.12 cm, P = 0.9418; vehicle: 652.62 ± 63.32 cm vs 62.5 mg/kg ɑMPT: 986.33 ± 194.15 cm, P = 0.9920). In contrast, A313V mice treated with 250 mg/kg ɑMPT traveled fivefold less than those treated with vehicle (vehicle: 5658.48 ± 576.75 cm vs 250 mg/kg ɑMPT: 1032.29 ± 215.05 cm, *P *< 0.0001) (Fig. 6B,E). Moreover, both doses of 125 mg/kg (vehicle: 5658.48 ± 576.75 cm vs 125 mg/kg ɑMPT: 2240.00 ± 44.60, P = 0.0239) and 62.5 mg/kg (vehicle: 5658.48 ± 576.75 cm vs 62.5 mg/lg ɑMPT: 2171.00 ± 186.81 cm, P = 0.0204) also decreased total distance traveled by over half (Fig. 6B,D). Treatment with 31 mg/kg ɑMPT led to a main effect of genotype (F1,19 = 43.81, *P *< 0.0001), no main effect of treatment (F1,19 = 3.241, *P *= 0.0877), and a significant genotype by treatment interaction (F1,19 = 6.445, P = 0.0200). Šidák’s multiple comparison test showed that compared to vehicle, the sum of total distance post-treatment was decreased in A313V mice that received 31 mg/kg ɑMPT (vehicle: 5197.34 ± 912.52 cm vs 31 mg/kg ɑMPT: 3033.25 ± 503.64 cm, P = 0.0147), but there was no difference between treatments in WT animals (vehicle: 629.97 ± 122.53 cm vs 998.15 ± 276.48 cm, P = 0.8391) (Fig. 6E).Figure 6. Analysis of four different doses of alpha-methyl-para-tyrosine in WT and A313V Mice and dose response to alpha-methyl-para-tyrosine in DAT-KO mice.Total distance was recorded in 5-min bins for 150 min in wild-type (WT) and dopamine transporter (DAT) A313V knock-in (A313V) mice. The test began with a 60 min baseline followed by intraperitoneal (i.p.) administration of vehicle or alpha-methyl-para-tyrosine (ɑMPT) at the 60-min timepoint. (A) Total distance over time in WT and (B) A313V mice treated with vehicle (WT n = 26, 16 males and 10 females; A3123V n = 28, 14 males and 14 females) or 250 mg/kg ɑMPT (WT n = 8, 6 males and 2 females; A313V n = 9, 5 males and 4 females). An arrow indicates the time point at which treatment was administered. This graph is representative and illustrates the temporal pattern of ɑMPT administration and effect for one dose. (C, D) Bar graph displaying the effects of vehicle or decreasing doses of ɑMPT at 250 mg/kg, 125 mg/kg, 62.5 mg/kg, and (E) 31 mg/kg on the sum of total distance traveled post-treatment. A two-way-ANOVA with Tukey’s multiple comparisons showed that A313V mice treated with 250 mg/kg (vehicle: 5658.48 ± 576.75 cm vs 250 mg/kg: 1032.29 ± 215.05 cm, *P *< 0.0001), 125 mg/kg (n = 3, 2 males and 1 female) (vehicle: 5658.48 ± 576.75 cm vs 125 mg/kg: 2240.00 ± 44.60 cm, P = 0.0239), and 62.5 mg/kg (n = 3, 1 male and 2 females) (vehicle: 5658.48 ± 576.75 cm vs 62.5 mg/kg: 2171.00 ± 186.81 cm, P = 0.0204) ɑMPT traveled less than those treated with vehicle, whereas there were no such changes seen in WT mice (125 mg/kg n = 3, 2 males and 1 female; 62.g mg/kg *n *= 3, 1 male and 2 females). A separate two-way ANOVA with Šidák’s multiple comparisons showed similar decreases in total distance traveled in A313V mice treated with 31 mg/kg ɑMPT (vehicle n = 5, 3 males and 3 females; ɑMPT n = 6, 3 males and 3 females) (vehicle: 5197.34 ± 912.52 cm vs 31 mg/kg: 3033.25 ± 503.64 cm, P = 0.0147), but not in WT mice (vehicle n = 6, 3 males and 3 females, ɑMPT n = 5, 3 males and 3 females, p = 0.8391). Total distance was recorded in 5-min bins for 150 min in dopamine transporter (DAT) knock-out (DAT-KO) mice as a model of extreme dopamine transporter deficiency syndrome (DTDS) (no expression of DAT). The test began with a 60 min baseline followed by intraperitoneal (i.p.) administration of vehicle or alpha-methyl-para-tyrosine (ɑMPT) at the 60-min timepoint. ɑMPT was given at doses of (F) 62.5 mg/kg, (G) 31 mg/kg, (H) 15.5 mg/kg, (I) 7 mg/kg, and (J) 3.5 mg/kg. An arrow indicates the time point at which treatment was administered in each experiment. (K) A two-way ANOVA conducted on the total distance traveled post-treatment revealed a main effect of dose (F4,35 = 20.50, P < 0.0001) and treatment (F1,35 = 74.04, P < 0.0001) and a significant interaction effect (F4,35 = 3.824, P = 0.0111). Post-hoc Šídák’s multipole comparisons showed that compared to DAT-KO mice treated with vehicle, ɑMPT doses of 62.5 mg/kg (vehicle: 18117.75 ± 3191. 35 cm [n = 4, 2 males and 2 females] vs 62.5 mg/kg: 1078.75 ± 251.89 cm [n = 4, 3 males and 4 females], P < 0.0001), 31 mg/kg (vehicle: 15746 ± 236.55 cm [n = 3, one male and three females] vs 31 mg/kg: 2401.6 ± 597.04 cm [n = 5, 2 males and 3 females], P = 0.0009), 15.5 mg/kg (vehicle: 16804.6 ± 4632.92 cm [n = 5, 3 males and 2 females] vs 15.5 mg/kg: 5551 ± 987.34 cm [n = 5, 2 males and 3 females], P < 0.0001), and 7 mg/kg (vehicle: 23526.4 ± 2175.47 cm [n = 5, 3 males and 2 females] vs 7 mg/kg: 15573 ± 1706.54 cm [n = 5, 3 females and 2 males], P = 0.0330) significantly decreased total distance traveled, but 3 mg/kg did not (vehicle: 25861 ± 1852.69 cm [n = 5, 3 males and 3 females] vs 3 mg/kg: 22554.2 ± 2811.8 cm [n = 5, 2 males and 3 females], P = 0.7443). In bar graphs, closed circular points represent values from female mice, and open square points represent values from male mice. Results are presented as mean ± SEM. For post hoc effects: ^#^P ≤ 0.05, ^###^P ≤ 0.001, ^####^P < 0.0001. Source data are available online for this figure.
While ɑMPT treatment seems to be beneficial in reducing hyperactivity in the A313V animals without fully inhibiting motor activity, there is a possibility that administering moderate to high doses of ɑMPT could worsen symptoms of Parkinsonism–dystonia in fully DAT-deficient DTDS patients. Indeed, administering high doses of ɑMPT (250 mg/kg) to DAT-KO mice results in full dopamine depletion and is used as an acute model of Parkinson’s disease due to the reliable induction of symptoms of akinesia and rigidity (Sotnikova et al, 2006). However, we hypothesized that lower doses of ɑMPT could be used to normalize hyperactivity in DAT-KO mice without causing unwanted side effects of Parkinsonism–dystonia. Accordingly, DAT-KO mice were used here as a model of extreme DTDS (zero expression of DAT) (Illiano et al, 2017; Ng et al, 2021) and were treated with a series of low doses (62.5 mg/kg, 32 mg/kg, 15.5 mg/kg, 7 mg/kg, and 3.5 mg/kg) of ɑMPT, and locomotor activity was assessed over time compared to vehicle treated animals (Fig. 6F–J). A two-way ANOVA conducted on the total distance traveled post-treatment revealed a main effect of dose (F4,35 = 20.50, *P *< 0.0001) and treatment (F1,35 = 74.04, P < 0.0001) and a significant dose by treatment interaction (F4,35 = 3.824, P = 0.0111). Post-hoc Šídák’s multiple comparisons showed that compared to DAT-KO mice treated with vehicle, ɑMPT doses of 62.5 mg/kg (vehicle: 18117.75 ± 3191. 35 cm vs 62.5 mg/kg: 1078.75 ± 251.89 cm, P < 0.0001), 31 mg/kg (vehicle: 15746 ± 236.55 cm vs 31 mg/kg: 2401.6 ± 597.04 cm, P = 0.0009), 15.5 mg/kg (vehicle: 16804.6 ± 4632.92 cm vs 15.5 mg/kg: 5551 ± 987.34 cm, P < 0.0001), and 7 mg/kg (vehicle: 23526.4 ± 2175.47 cm vs 7 mg/kg: 15573 ± 1706.54 cm, P = 0.0330) had significantly decreased total distance traveled, but 3 mg/kg did not (vehicle: 25861 ± 1852.69 cm vs 3 mg/kg: 22554.2 ± 2811.8 cm, P = 0.7443) (Fig. 6K). Notably, 7 mg/kg ɑMPT did not block locomotor activity in DAT-KO mice as is seen in the moderate doses of 62.5, 31, and 15.5 mg/kg ɑMPT. Thus, this data suggests that even in DTDS patients with profound reductions of DAT protein levels, treatment of hyperactivity symptoms may be possible with low doses of ɑMPT without potentially causing Parkinsonism–dystonia, and that ɑMPT doses can be personalized to individual patients based on the severity of their DAT deficiency.
Disease modification using pharmacological chaperones and inhibitors of ER-associated degradation
It has been shown that pharmacological chaperones of DAT, including ibogaine and noribogaine, can rescue expression of select DTDS disease causing variants in cells (Beerepoot et al, 2016; Asjad et al, 2017; Kasture et al, 2016). Moreover, noribogaine was shown to rescue motor and sleep impairments of the G108Q, V158F, and G327R DTDS variants in Drosophila (Asjad et al, 2017; Kasture et al, 2016). In order to assess whether pharmacological chaperones could also rescue the A313V variant in vivo in a mammalian system, a series of experiments were performed with noribogaine, one of the most efficacious DAT pharmacological chaperones. Cell based studies have shown that high doses of noribogaine (50–100 μM) are needed to achieve pharmacological chaperone activity (Beerepoot et al, 2016). Thus, pharmacokinetic (PK) studies were first conducted to establish the proper dosing regimen that would allow achievement of the 50–100 μM brain concentration needed for pharmacological chaperone activity. Detailed PK studies were conducted via oral gavage based on experiments conducted by (Mash et al, 2016), as ICV injections of noribogaine could not achieve brain doses in the range needed for our studies (unpublished observations). As a first step, mean noribogaine concentrations were measured by LC/MS/MS in cerebellar brain tissues at 2 and 24 h after oral administration of 100 mg/kg. As shown in Fig. EV4A, this dose resulted in 27.84 μM ± 3.34 and 1.06 ± 0.46 μM of noribogaine in the brain after 2 and 24 h, respectively, which are below the concentrations needed for pharmacological chaperone activity (Fig. EV4A). The dosing regimen was therefore modified, and another cohort of mice received 500 mg/kg of noribogaine via oral gavage followed by a second 250 mg/kg dose (oral gavage) 5 h later. As shown in Fig. EV4B, brain noribogaine levels were above 100 μM (179.56 ± 95.94 μM) at 1 h and following the second injection and remained above this for at least 24 h (Fig. EV4B). Thus, a dosing regimen of 500 mg/kg noribogaine via oral gavage followed by a second dose of 250 mg/kg 5 h later is sufficient to achieve 100 μM noribogaine in the brain that is largely stable across at least 19 h.
Next, it was important to determine the effective duration that noribogaine concentrations in the brain remained above 100 μM. The same dosing regimen (500 mg/kg noribogaine via oral gavage followed by 250 mg/kg five hours later) was carried out and plasma was collected at different time points (1, 5, 6, 12, 24, 48, 72, 80, 96, 120, and 144 h) after the initial 500 mg/kg noribogaine dose. Brains were also collected at the 72, 80, 96, 120, 144, and 168 h timepoints. After the 500 + 250 mg/kg oral gavage, brain noribogaine concentrations fell below 100 μM at ~24 h and below 50 μM at ~36 h after first oral gavage (Fig. EV4C). Regression analysis of plasma vs. brain μM noribogaine from the experiment in Fig. EV4B,C gave an R-squared value of 0.8731, suggesting that plasma noribogaine concentration can be used to estimate noribogaine concentrations in the brain (Fig. EV4D).
A fourth experiment explored the effects of repeated noribogaine dosing on plasma and brain noribogaine concentrations. Here, the above 500 + 250 mg/kg noribogaine schedule was administered every 48 h over the course of 9 days, with brains collected on day 10, 24 h after the 4th noribogaine dose. Blood was also collected from two groups of animals on day 2 (group 1) and 4 (group 2), 24 h after the 500 mg/kg noribogaine administration on days 1 and 3, respectively. The experiment timeline is illustrated in Fig. EV5A. The mean noribogaine plasma concentration on day 2 was 30.93 μM ± 5.17 and on day 4 was 21.23 ± 2.36 μM (Fig. EV5B). The mean noribogaine brain concentration on day 10 was 35.68 μM ± 4.60 (Fig. EV5B). The brain concentrations of noribogaine were estimated based on the previously established relationship between plasma and brain noribogaine concentrations. This indicated that on day 2, brain noribogaine concentrations were approximately 169.94 μM and 116.64 μM on day 4. This experiment suggests that following repeated dosing 48 h apart, noribogaine levels in the brain fall below 100 μM at approximately 96 h (4 days, Fig. EV5C).
Having optimized the noribogaine administration paradigm to achieve 100 μM concentrations in the brain, an experiment was conducted to assess whether the ER-retained A313V DTDS variant could be rescued with noribogaine. The experiment was carried out over the course of four days (Fig. 7A). The noribogaine dosing combination of 500 mg/kg + 250 mg/kg was administered twice, 48 h apart, on day 1 and day 3. Locomotor activity was assessed 24 h after noribogaine administration on day 4, and brains were collected upon completion of the open field test. A two-way ANOVA was conducted on the sum of total distance traveled. There was a main effect of treatment (F1,25 = 22.95, P < 0.0001) and genotype (F1,25 = 39.24, P < 0.0001), but no interaction effect (F1,25 = 2.356, P = 0.1374), suggesting that treatment with noribogaine decreased levels of locomotor activity similarly in both WT (vehicle: 3687.86 ± 336.01 cm vs noribogaine: 1912.71 ± 311.13 cm) and A313V (vehicle: 7939.86 ± 836.61 cm vs noribogaine: 4491.25 ± 525.87 cm) mice (Fig. 7B–E). Western blots were then performed on striatal and midbrain tissue to assess levels of DAT in animals treated with vehicle or noribogaine. In WT animals, the difference in levels of DAT in the striatum (vehicle: 100.00 ± 16.49% of WT vehicle-treated average vs noribogaine: 100.68 ± 15.43% of WT vehicle-treated average, t = 0.03025, df = 10, P = 0.9764) and midbrain (vehicle: 100.00 ± 11.11% of WT vehicle-treated average vs noribogaine: 71.38 ± 12.15% of WT vehicle-treated average t = 1.566, df = 7, P = 0.1614) were not significantly different between vehicle and noribogaine treated animals (Fig. 8A–D). Similarly, there was no difference in the levels of DAT in the striatum (vehicle: 100.00 ± 15.90% of A313V vehicle-treated average vs noribogaine: 88.65 ± 6.17% of A313V vehicle-treated average, *t *= 0.7063, df = 11, *P *= 0.4947) or midbrain (vehicle: 100.00 ± 23.33% of A313V vehicle-treated average vs noribogaine: 134.20 ± 44.83% of A313V vehicle-treated average, t = 0.6352, df = 9, P = 0.5411) in A313V mice treated with vehicle or noribogaine (Fig. 8E–H). This result shows that, although this noribogaine regimen can reduce hyperactivity of both WT and A313V animals, it does not increase DAT expression as assessed by western blotting, which is in contrast to what has been reported in cell-based studies.Figure 7. Chronic noribogaine administration reduces locomotor activity in WT and A313V mice.(A) Noribogaine was administered via oral gavage according to the established dosing regimen of 500 mg/kg followed by 250 mg/kg five hours later (“Noribogaine Treatment”). This dosing regimen was done on day 1 and on day 3, 48 h apart. Locomotor activity was assessed 24 h after the final dose (day 4, Locomotion). Total distance traveled over time and cumulative distance in wild-type (WT) (B, D) and A313V (C, D) mice treated with vehicle (WT n = 7, 3 males and 4 females; A313V *n *= 7, 4 males and 3 females) or noribogaine (WT n = 7, 3 males and 4 females; A313V n = 8, 5 males and 3 females). A two-way ANOVA found a main effect of treatment (F1,25 = 22.95, P < 0.0001) and genotype (F1,25 = 39.24, P < 0.0001), but no interaction effect (F1,25 = 2.356, P = 0.1374), suggesting that treatment with noribogaine decreased levels of locomotor activity similarly in both WT (vehicle: 3687.86 ± 336.01 cm vs noribogaine: 1912.71 ± 311.13 cm) and A313V (vehicle: 7939.86 ± 836.61 cm vs noribogaine: 4491.25 ± 525.87 cm) mice. Closed circular points represent values from female mice, and open square points represent values from male mice. Bar graphs results are presented as mean ± SEM. A two-way ANOVA examining treatment, genotype, and interactions was conducted. For main effects: ****P < 0.0001. Source data are available online for this figure.Figure 8DAT expression levels in the striatum and midbrain of WT and A313V mice after treatment of noribogaine or vehicle.Dopamine transporter (DAT) levels were assessed in wild-type (WT) and A313V DAT knock-in (A313V) mice in the (A, B, E, F) striata and (C, D, G, H) midbrains of animals treated with vehicle or noribogaine. DAT-knockout (DKO) mouse samples were used as a negative control to confirm antibody specificity and to identify the appropriate regions for DAT analysis. The lower panels show a cropped total protein stain, used here to visualize approximately even protein loading. Lanes are labeled to indicate DKO, vehicle-treated, and noribogaine-treated samples. Molecular weight is shown in kDA to the left. DAT signal intensity was normalized to the total protein loading control and is expressed as a percentage of the mean vehicle-treated value. There was no statistically significant difference in DAT levels in the striata of WT (vehicle: 100.00 ± 16.49% of WT vehicle-treated average vs noribogaine: 100.6833 ± 15.43% of WT vehicle-treated average, t = 0.03025, df = 10, P = 0.9765) or A313V (vehicle: 100.00 ± 15.90% of A313V vehicle-treated average vs noribogaine: 88.65 ± 6.17% of A313V vehicle-treated average, t = 0.7063, df = 11, P = 0.4947) mice between animals treated with vehicle (WT n = 6; A313V n = 6) or noribogaine (WT n = 6, A313V n = 7). There was no statistically significant difference in DAT levels in the midbrain of WT (vehicle: 100.00 ± 11.11% of WT vehicle-treated average vs noribogaine: 71.38 ± 12.15% of WT vehicle-treated average, t = 1.566, df = 7, P = 0.1614) or A313V (vehicle: 100.00 ± 23.34% of A313V vehicle-treated average vs noribogaine: 134.20 ± 44.83% of A313V vehicle-treated average, t = 0.6352, df = 9, P = 0.5411) mice between animals treated with vehicle (WT n = 3; A313V n = 5) or noribogaine (WT n = 6; A313V n = 6). Closed circular points represent values from female mice, and open square points represent values from male mice. Bar graphs results are presented as mean ± SEM. Student’s unpaired, two-tailed t test were conducted separately for WT and A313V mice. Source data are available online for this figure.
Previous work in Drosophila with DAT variants suggests that pifithrin-μ, an inhibitor of a HSP70 (Leu et al, 2009), could increase DAT expression similar to noribogaine treatment (Kasture et al, 2016; Asjad et al, 2017). Given these findings, we administered 3 mg/kg pifithrin-μ three times, 48 h apart, for 5 days (regimen adapted from He et al, 2012). Locomotor activity was assessed 48 h after last pifithrin-μ administration on day 5, and brains were collected upon completion of the open field locomotor test (Fig. 9A). A two-way ANOVA was conducted on the sum of total distance traveled. There was a main effect of genotype (F1,14 = 210.1, P < 0.0001), but no effect of treatment (F1,14 = 1.042, P = 0.3247), nor was there a genotype by treatment interaction (F1,14 = 0.1242, P = 0.7298) (Fig. 9B–D). Western blots were then performed on striatal and midbrain tissue to assess levels of DAT in animals treated with vehicle or pifithrin-μ. Analysis shows that there was no difference in striatal DAT levels between animals treated with pifithrin-μ or vehicle (vehicle: 100 ± 8.27% of WT vehicle-treated average vs pifithrin-μ: 96.80 ± 4.17% of WT vehicle-treated average, t = 0.3451, df = 7.279, *P *= 0.7398) (Fig. 9B), or in midbrain DAT levels of WT animals (vehicle: 100 ± 17.49% of WT vehicle-treated average vs pifithrin-μ: 111.90 ± 49.55% of WT vehicle-treated average) (Fig. 10A–D). In contrast, while there was no statistically significant difference in striatal DAT levels between A313V mice treated with pifithrin-μ or vehicle (vehicle: 100 ± 8.96% of A313V vehicle-treated average vs pifithrin-μ: 83.41 ± 6.41% of A313V vehicle-treated average), there was a fourfold increase in the levels of mature DAT in the midbrain of pifithrin-μ treated mice (vehicle: 100 ± 15.50% of A313V vehicle-treated average vs pifithrin-μ: 390.83 ± 18.57) (Fig. 10E–H). Although pifithrin-μ was able to significantly increase the levels of DAT in the midbrain in A313V mice, DAT levels in the striatum were not changed, and this may explain the lack of an effect on locomotor behavior (Fig. 9C,D).Figure 9. Chronic pifithrin-μ administration does not change locomotor activity in WT and A313V mice.(A) Pifithrin-μ was administered via intraperitoneal injection at 3 mg/kg on day 1, day 3, and day 5, 48 h apart. Locomotor activity was assessed 48 h after the final dose (day 7, locomotion). Total distance traveled over time and cumulative distance traveled in wild-type (WT) (B, D) and (C, D) A313V dopamine transporter (DAT) knock-in (A313V) mice treated with vehicle (WT n = 5, 1 male and 4 females; A313V n = 3, 2 females and 1 male) or pifithrin-μ (WT n = 5, 1 male and 4 females; A313V n = 5, 3 males and 2 females). A two-way ANOVA showed no main effect of treatment (F1,14 = 1.042, *P *= 0.3247), a significant effect of genotype (F1,14 = 210.1, *P *< 0.0001), and no interaction effect (F1,14 = 0.1242, P = 0.7298). In bar graphs, closed circular points represent values from female mice, and open square points represent values from male mice. Bar graphs results are presented as mean ± SEM. A two-way ANOVA examining treatment, genotype, and interactions was conducted. For main effects: ****P < 0.0001. Source data are available online for this figure.Figure 10DAT expression levels in the striatum and midbrain of WT and A313V mice after treatment of pifithrin-μ or vehicle.Dopamine transporter (DAT) levels were assessed in wild-type (WT) and A313V DAT knock-in (A313V) mice in the (A, B, E, F) striata and (C, D, G, H) midbrains of animals treated with vehicle or pifithrin-μ. There was no statistically significant difference in DAT levels in the striata of WT (vehicle: 100.00 ± 8.27% of WT vehicle-treated average vs pifithrin-μ: 96.80 ± 4.17% of WT vehicle-treated average, *t *= 0.3451, df = 7.279, P = 0.7398) or A313V (vehicle: 100.00 ± 8.96% of A313V vehicle-treated average vs noribogaine: 83.41 ± 6.41% of A313V vehicle-treated average, t = 1.506, df = 5.927, P = 0.1833) mice between animals treated with vehicle (WT n = 6, 2 males and 4 females; A313V n = 4, 1 male and 3 females) or pifithrin-μ (WT n = 6, 2 males and 4 females; A313V n = 6, 3 males and 3 females). In the midbrain of WT mice, there was no statistically significant difference in DAT levels in animals treated with vehicle (n = 6, 2 males and 4 females) or pifithrin-μ (n = 6, 2 males and 4 females) (t = 0.4451, df = 9.786, P = 0.6660). However, there was a statistically significant increase in the midbrain levels of DAT in A313V mice treated with pifithrin-μ (n = 4, 1 male and 3 females) compared to vehicle (n = 4, 1 male and 3 females) (t = 12.02, df = 5.813, P < 0.0001)). In bar graphs, closed circular points represent values from female mice, and open square points represent values from male mice. Bar graphs results are presented as mean ± SEM. Student’s unpaired, two-tailed t test with Welch’s corrections were conducted separately for WT and A313V mice. ****P < 0.0001. Source data are available online for this figure.
Discussion
Because folding efficiency is not 100% even for most wild-type proteins (Schubert et al, 2000), a single amino acid change is often sufficient to induce disease pathogenesis by leading to protein misfolding (Guerois et al, 2002). Indeed, misfolding of membrane proteins is linked to a number of diseases such as nephrogenic diabetes insipidus, cystic fibrosis, Fabry disease, and hypogonadotropic hypogonadism. Misfolding of eukaryotic membrane proteins typically occurs in the endoplasmic reticulum, where the misfolded protein is retained and targeted for degradation (Sanders and Myers, 2004).
Dopamine transporter deficiency syndrome (DTDS) is believed to be caused by an analogous mechanism wherein variations in SLC6A3 lead to DAT protein misfolding, retention in the ER, and consequent low levels of functional DAT in striatal nerve terminals. Indeed, DAT is synthesized in the cell bodies of dopamine neurons within the midbrain and then trafficked to nerve terminals in the striatum (Vecchio et al, 2014; Nepal et al, 2023). In the initial part of this study, the neurochemical phenotype of the DAT A313V DTDS mice was examined, which models the human A314V DTDS variant. Firstly, results showed that the A313V DAT variant indeed leads to the retention of the immature, core glycosylated DAT protein in the midbrain, coincident with a decrease in mature, fully glycosylated DAT in the striatum. Furthermore, A313V have a twofold reduction in midbrain DAT mRNA. These show that the mechanism by which the A313V DAT variant leads to DTDS is due to (1) altered transcriptional regulation of DAT, (2) DAT retention in the ER, and (3) the consequent low levels of functional DAT needed to maintain normal, physiological function. Moreover, the observation that TH protein levels in the striatum and TH and VMAT2 mRNA levels in the midbrain are significantly decreased compared to WT mice suggest that complex compensatory mechanisms are occurring in response to changes in DAT levels, similar to that which has been reported in DAT-KO mice as a consequence of hyperdopaminergia (Gainetdinov and Caron, 2003, Jaber et al, 1999, Efimova et al, 2016, Savchenko et al, 2023).
Levels of dopamine metabolites, including HVA, are increased in cerebral spinal fluid of human patients with DTDS (Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014) and these changes in dopamine metabolites are one of the diagnostic criteria for the disease (Spaull and Kurian, 2023). The A313V knock-in mice recapitulate this neurochemical change, as observations also demonstrate increased amounts of HVA in these animals compared to WT mice. Additionally, these results show that there is decreased tissue levels of DA in the A313V mice, consistent with the hypothesis that low levels of functional DAT led to decreased DA recycling and ultimately reduced DA tissue levels in the A313V mice. Such reduction in DA tissue levels is also observed in DAT-KO mice (Jones et al, 1998; Sotnikova et al, 2005). Interestingly, results show that the A313V mice had lower levels of DOPAC compared to WT mice yet increased levels of HVA. This is consistent with DOPAC representing mostly intracellular dopamine metabolism by MAO, (Eisenhofer et al, 2004; Meiser et al, 2013), while HVA primarily reflects metabolism by extraneuronal catechol-O-methyltransferase (COMT) in glial cells (Meiser et al, 2013; Kaufman, 2007) potentially after transport into the cell by the organic cation transporters (Holleran et al, 2020).
In addition to reduced striatal DA tissue content levels, the A313V mice also showed a significantly longer decay time constant, tau, and a significant reduction in V_max_, when DA release and clearance were assessed using fast scan cyclic voltammetry. These results are indicative of decreased DA clearance that most likely arises from lower levels of functional DAT. However, as shown in Fig. 3F, the maximal electrically-stimulated release of DA as measured by ‘peak-height’ is approximately 4uM in the A313V mice, but 3uM in the WT mice. Our observations are similar to Sørensen et al, 2021, who showed that in DAT-AAA mice, which harbor a PDZ-binding sequence mutation, DAT expression and DA tissue content is reduced. However, the DAT-AAA mice also show enhanced electrically-stimulated DA release (peak-height) compared to WT mice as measured by FSCV. Sørensen et al, 2021 hypothesize that low uptake capacity of the DAT-AAA variant is still sufficient to maintain a releasable pool of DA, and, in combination with the reduced uptake capacity, this could lead to larger DA peak values. Indeed, in FSCV measurements, peak-height of the DA signal correlates more with uptake ability than dopamine tissue content. For example, when measuring DA release in vivo with FSCV, one of the main effects observed with DAT blockers is increased peakheight of the DA signal. This could be interpreted as ‘increased’ release, but is mostly due to the fact that dopamine remains longer in the extracellular space and can diffuse farther to reach the FSCV electrode (Hersey et al, 2023). Therefore, the moderate (~30% increase in peak-height) seen in the A313V mice compared to WT animals is most likely due to impaired dopamine uptake in A313V compared to WT and does not necessarily mean that there is increased dopamine release in A313V mice.
The principal role of the DAT is to spatially and temporally modulate DA neurotransmission through uptake of DA from the extracellular space after release, where it can then be repackaged into vesicles to be released again. Low levels of DAT lead to decreased DA uptake, consequently increased DA levels in the extracellular space, and thus increased dopaminergic neurotransmission. The reported initial behavioral symptoms of patients with DTDS are reflective of this hyperdopaminergia, characterized by features of chorea, ballismus, and orolingual dyskinesia (Spaull and Kurian, 2023). The behavioral characterization of the A313V mice recapitulates this hyperkinetic stage of the disease. Results showed that the A313V mice have decreased dorsal immobility response (DIR) time and are hyperactive in the open field test compared to their WT littermates. These are both proxies for increased dopaminergic neurotransmission in mice.
Importantly, results suggest that two compounds are able to reduce the hyperactivity seen in the A313V mice: amphetamine (AMPH) and alpha-methyl-para-tyrosine (ɑMPT). Both of these drugs are currently approved for use in human patients and could be of translational interest for DTDS patients (Martin and Le, 2025; Brogden et al, 1981). Of particular interest is ɑMPT because of its potential to be a disease-modifying treatment for DTDS. The mechanism of action of ɑMPT is inhibition of conversion of tyrosine to L-DOPA by tyrosine hydroxylase, therefore blocking the production of dopamine (Brogden et al, 1981). This effectively lowers the amount of dopamine neurotransmission, which in turn reduces locomotor activity of the A313V mice. It is well known that both intracellular and extracellular dopamine can induce toxicity (Cyr et al, 2003; Hattori et al, 1998; Liu et al, 2001; Chen et al, 2008; Jiang et al, 2008; Mosharov et al, 2009; Benedetto et al, 2010) and up to 40% of dopamine transporter knock-out (DAT-KO) mice develop gait abnormalities and tremor due to loss of GABAergic striatal medium spiny neurons (Cyr et al, 2003). Importantly, in DAT-KO mice, chronic treatment with ɑMPT was able to ameliorate the behavioral manifestation of this neurodegeneration and reduce mortality rate over a 40-week period to 0% (Cyr et al, 2003). Considering the similar effects we observed on the motor activity of A313V mice after ɑMPT treatment, we believe that ɑMPT has the potential to modify the disease course of DTDS and reduce disease burden when used during the initial stages of the disease. As mentioned previously, ɑMPT is currently used in humans to treat symptoms associated with pheochromocytoma at doses of 600–3500 mg daily (Brogden et al, 1981). Side effects at these doses include sedation, diarrhea, anxiety, nightmares, crystalluria, galactorrhea, and extrapyramidal symptoms (Young, 2016). However, (Ankenman and Salvatore, 2007b) suggest that at low doses these side effects can be mitigated. We show in our studies that ɑMPT can dose-dependently reduce hyperactivity of A313V mice with doses as low as 31 mg/kg. This suggests that low to moderate dosing of ɑMPT could also have potential clinical benefit for DTDS patients with potentially modest adverse effects.
However, given that DAT-KO mice are hypersensitive to ɑMPT and can develop akinesia, rigidity, and tremor in response to ɑMPT administration (Sotnikova et al, 2006), it is possible that DTDS patients with particularly low expression of DAT may also display worsening symptoms of Parkinsonism–dystonia if treated with ɑMPT. As such, this would be a major limitation for clinical translation of ɑMPT. To address this concern, we administered a series of low doses of ɑMPT to DAT-KO mice which is a model of extreme DTDS (zero DAT expression) (Ng et al, 2014). Our results show that 7 mg/kg of ɑMPT was sufficient to significantly reduce locomotor activity without decreasing locomotor activity to zero or inducing immobility. Therefore, it may be possible to identify a therapeutic dose of ɑMPT for individual DTDS patients based on DAT expression and avoid development/worsening of Parkinsonism–dystonia while still achieving therapeutic benefit through inhibition of tyrosine hydroxylase.
Ibogaine and noribogaine have been shown to act as pharmacological chaperones of DAT and rescue the A314V DTDS disease causing variant in cells (Beerepoot et al, 2016; Asjad et al, 2017; Kasture et al, 2016; Sutton et al, 2022). With this in mind, experiments were conducted with noribogaine and assessed its potential efficacy as a disease modifying treatment to rescue the levels of the ER-retained A313V DAT. Both WT and A313V animals treated with noribogaine showed decreased levels of locomotor activity, but this may be due to a general sedating effect of noribogaine, as acute ibogaine has been found to reduce locomotor activity in WT mice. No changes were observed in DAT protein levels as assessed by western blots in the striatum or midbrain in WT and A313V animals treated with vehicle or noribogaine. This result indicated that under the current experimental conditions, it was not possible to observe rescue of A313V DAT protein expression in vivo with noribogaine. There could be several reasons explaining the lack of effect of noribogaine. The simplest explanation could be that noribogaine is not able to act as a pharmacological chaperone of DAT in vivo in a mammalian model, in contrast to what has previously been described in cell-based systems. Alternatively, it is possible that the analysis of DAT levels with western blots is not sensitive enough to detect minor upregulation of DAT protein. Indeed, Drosophila studies that observe increases in DAT in response to noribogaine utilize methods such as DA uptake (Kasture et al, 2016; Asjad et al, 2017). Therefore, future studies may need to incorporate additional complimentary techniques in addition to western blot to measure DAT activity and altered levels that may result from pharmacological treatment.
Lastly, it is possible that the right dosing regimen of noribogaine was not achieved to observe its pharmacological chaperoning effect in vivo, in mice. This may, however, be unlikely, as extensive PK studies were performed to ensure that proper levels of noribogaine were attained in the brain. What remains puzzling is that Asjad et al, 2017 demonstrated the ability to detect expression of human DAT G140Q or V158F variants in axonal compartments of Drosophila when flies were fed with noribogaine beginning in the instar larval stage throughout adulthood. Interestingly, Kasture et al, 2016 showed that feeding adult Drosophila with noribogaine for only 5 days was also sufficient to achieve this effect. However, in our studies, where noribogaine was administered to the A313V mice only in adulthood, rescue was not achieved. Perhaps treatment with noribogaine needs to begin earlier in life, and for a longer duration, to observe DAT rescue in mice. However, this is difficult to experimentally verify because noribogaine levels in the brain fall below the efficacious 100 μM levels after ~84 h of administration, despite repeated dosing every 48 h. Therefore, it may not be pharmacokinetically feasible to conduct prolonged noribogaine studies with early intervention in mice. Moreover, the findings that the A313V mice have reduced levels of midbrain DAT mRNA, in addition to an increase in the immature DAT protein species, may partially explain the lack of rescue by noribogaine. Indeed, the hypothesized mechanism of rescue of noribogaine is through increased maturation and protein exit from the ER, which could be diminished if DAT mRNA is decreased. Additional studies with longer noribogaine treatments might be needed to fully rule out the potential of this compound to rescue A313V DAT variant in vivo.
Pifithrin-μ is an inhibitor of HSP70, which is involved in several degradation pathways, such as the chaperone-assisted ubiquitin-proteasome pathway, the chaperone-mediated autophagy pathway, and the chaperone-assisted endosomal microautophagy and macroautophagy pathways (Fernández-Fernández et al, 2017). Both Kasture et al, 2016 and Asjad et al, 2017 showed that pifithrin-μ is able to increase the expression of ER-retained DAT variants in drosophila. Similarly, we show that pifithrin-μ can increase the levels of the A313V DAT variant in the midbrain of A313V mice treated with pifithrin-μ compared to those treated with vehicle. However, we did not observe any increases in striatal DAT levels, nor did we observe a change in the locomotor activity of A313V mice treated with pifithrin-μ. The mechanisms and timeframe of DAT trafficking from the midbrain, where it is synthesized in cell bodies, to the striatum, is not well understood (Bagalkot et al, 2021; Nirenberg et al, 1996, Nirenberg et al, 1997). Data from (Bagalkot et al, 2021) suggests that diffusion is the primary mechanism of long-distance DAT transport and that it takes approximately 21 days to turn over 50% of the plasma membrane DAT in medial forebrain bundle axonal tracts. Moreover, (Fleckenstein et al, 1996) used intrastriatal injection of irreversible DAT inhibitor RTI-76 to demonstrate that the half-time of transporter recovery is estimated at 6 days. Taken together, these results suggest that DAT turnover is a temporally extended process. Given that in our design pifithrin-μ was administered only for 5 days, it is possible that increases in DAT were only detectable in the midbrain but that our treatment was not long enough to result in detectable increases of DAT in the striatum. In addition, previous studies have shown that there is a synergistic effect of administering both pifithrin-μ and noribogaine concurrently to produce the largest increase in the mature, glycosylated form of DAT, as opposed to administration of either drug alone (Kasture et al, 2016, Asjad et al, 2017). Accordingly, future research may aim to utilize this combination to achieve a greater rescue of the A313V DAT in this mouse model.
As mentioned previously, the second stage of DTDS is characterized by Parkinson’s-like symptoms, manifesting as dystonic posturing, resting and action tremor, bradykinesia, and rigidity in humans. In the A313V animals, we did not observe or report any “Parkinson’s disease-like” or dystonic phenotypes, even when locomotor activity was assessed in aged 15-month-old animals (Fig. EV1A,B). The only motor symptom that could be consistently observed was that of hyperkinesia, which mimics the early stage of DTDS. Indeed, we did not observe the presence of dystonic features in A313V or DAT-KO mice as assessed by the pole reversal test, the foot fault test, or in clasping severity score (Fig EV1D–G). These findings are in contrast to two previous studies which have shown that DAT-KO mice exhibit an increased T-Turn time and latency to descend in the pole reversal test (Ng et al, 2021; Illiano et al, 2017), and an increased percentage of foot faults (Ng et al, 2021). The discrepancy between these results and our results could be due to differences in experimental conditions, such as differences in testing equipment, or differences in interrater scoring, and, perhaps more importantly, differences in general animal housing conditions
One potential reason for this may be that mice have a substantially greater capacity to cope with DA depletion than humans, otherwise known as a greater motor reserve. Indeed, developmental ablation of nearly 90% of ventral tegmental area and substantia pars compacta dopaminergic neurons in mice produces no notable motor phenotype (Golden et al, 2013), while it is known that in humans, the clinical motor symptoms of Parkinson’s Disease emerge when approximately 50-60% of substantia nigra axon terminals have been lost (Cheng et al, 2010). Therefore, it may not be possible to capture the dystonic late-stage Parkinsonian symptoms of DTDS in a mouse model, limiting insights solely to the initial stage of the disease.
Alternatively, the Parkinsonism symptoms of DTDS may arise through an orthogonal mechanism related to ER retention of DAT. Patients harboring other *SLC6A3/*DAT variants that are not hypothesized to be ER-retained such as T356M (Hamilton et al, 2013), A559V (Mazei-Robison et al, 2005; Grünhage et al, 2000), and E602G (Grünhage et al, 2000) do not show symptoms of parkinsonism. Further, young-onset Parkinson’s disease is treated with levodopa/dopamine therapy (Drossos and Hunter, 2011; Klepac et al, 2013), while DTDS patients do not respond to this treatment (Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014); this suggests a potential alternative pathology by which DTDS Parkinsonism–dystonia arises. However, neuropathology analyses have not yet been performed in DTDS patients to elucidate if there is neurodegeneration in these patients, and, if so, in which neuronal population(s).
In summary, we have recapitulated some of the key DTDS symptoms and neurochemical changes seen in humans in our A313V-DAT mouse model. Furthermore, we have provided evidence for two treatments for the hyperkinetic symptoms of the disease: AMPH and ɑMPT. Importantly, we believe that ɑMPT may serve as a disease-modifying treatment for DTDS by directly addressing the increased dopaminergic tone seen in the disease. Overall, this study presents a new model of DAT hypofunction that displays a unique set of phenotypes distinct from DAT-KO mice, identifying potential translational biomarkers relevant to dopamine-related disorders, such as DTDS.
Methods
Reagents and tools tableReagent/resourceReference or sourceIdentifier or catalog number Experimental models Slc6A3 A313V knock-in C57BL/6 J (*M. musculus)*This studyC57BL/6 J Wildtype (M. musculus)This studySlc6A3 knock-out (*M. musculus)*Giros et al, 1996 Recombinant DNA
Antibodies Goat anti-DATSanta Cruz#sc-1433 (discontinued)Mouse anti-DATThermo Fisher#MA5-24796Rabbit anti-DATSigma-Aldrich#D6944Rabbit anti-THMillipore Sigma#AB152Rabbit anti-phosphoTH-ser40PhosphoSolutions#p1580-40mouse anti-GAPDHMillipore Sigma#G8795Donkey-anti-goat IRDye 800 CW secondary antibodyLI-COR Bio#925-33214Goat anti-mouse IRDye 680 RD secondary antibodyLI-COR Bio#925-68070Anti-rabbit IgG (H + L) (DyLight 680 Conjugate) secondary antibodyCell Signaling Technology#5366SDonkey anti-mouse IRDye 800 CW secondary antibodyLI-COR Bio#926-33212Anti-mouse IgG (H + L) (DyLight) 680 Conjugate secondary antibodyCell Signaling Technology#5470SAnti-rabbit IgG (H + L) (DyLight) 800 4x PEG ConjugateCell Signaling Technology#5151 PDonkey anti-goat 680 secondary antibodyLI-COR Bio#925-68074 Oligonucleotides and other sequence-based reagents DAT1ForwardIntegrated DNA TechnologiesDAT ReverseIntegrated DNA TechnologiesTH ForwardIntegrated DNA TechnologiesTH ReverseIntegrated DNA TechnologiesVMAT2 ForwardIntegrated DNA TechnologiesVMAT2 ReverseIntegrated DNA TechnologiesPGK1 ForwardIntegrated DNA TechnologiesPGK1 ReverseIntegrated DNA TechnologiesNR4A2 ForwardIntegrated DNA TechnologiesNR4A2 ReverseIntegrated DNA Technologies Chemicals, enzymes and other reagents LeupeptinBioshopAPR600BenzamidineBioshopBEN601PMSFBioshopPMS123Na pyro-phosphateBioshopSPP310β-glycerophosphateBioshopGYP001NaFBioshopSFL001Na3VO4BioshopSOV664Licor Blocking BufferLI-COR Bio#927-60001Licor Total Protein StainLI-COR BioLIC-926-11010N-glycosidase FNew England BioLabs#P0704SEndoHNew England BioLabs#P0702SPowerUp SYBR Green Master MixThermoFisher#A25742DreamTaq polymeraseThermo Scientific#FEREP0702Ibogaine hydrochlorideIbogaworld.comAmphetamineToronto Research Chemicals#A634295Threo-Methylphenidate hydrochloride (MPH)Tocris Bioscience#298-59-9alpha-methyl-D,L-p-tyrosine, Methyl Ester (ɑMPT)ChemCruz, Santa Cruz Biotechnology, Inc#sc-219470NoribogaineSynthesized from ibogaine by Dalriada Drug Discovery, Mississauga, ON, CA, and by Dr. Landon Edgar at the University of Toronto, Toronto, ON, CAPifithrin-μMillipore Sigma#P0122 Software Odyssey ImagingLI-COR BioPrism versions 9 and 10GraphPadEmperia StudioLI-COR BioImage StudioLI-COR BioDigiGaitMouse SpecificsMatLabMathWorks, https://www.mathworks.com/products/matlab.htmlDeepLabCut v2.3.7deeplabcut.github.io/DeepLabCut/ChromelonThermo ScientificDemon Voltammetry SoftwareYorgason et al, 2011Vision DXAHologicFusion SoftwareOmnitech Electronics Other DigiGait TreadmillMouse Specifics, IncAgilent 1260 LC systemAgilentC18 Column 5 µm 2.1 ×150 mm, 5 µmAgilentZorbax SB-C18QuantStudio 5ThermoFisher#A28574HPLC-EC; ESAThermo ScientificReverse Phase Column Luna 100 × 3.0 mm C18 3 μmPhenomenexElectrochemical Detector CellThermo Fisher ScientificModel 5011 ACoulochem III Electrochemical DetectorThermo ScientificDemon Voltammetry HardwareYorgason et al, 2011UltraFocusDXAFaxitron Bioptics, LLCDigital Activity MonitorsOmnitech ElectronicsVersaMax SuperFlex Open Field SystemOmnitech ElectronicsRotarodUgo Basile#47650PureLink™ PCR Purification KitInvitrogen#K310001BCA assayThermo Fisher Scientific#23227Novex 10% Tris-Glycine Wedgewell gelThermo Fisher Scientific#XP00105BOXImmobilon-FL PVDF transfer membraneMillipore#IPFL00005FluoroTrans PVDF transfer membranePall Life Sciences#BSP0161Superscript IV VILO kitThermoFisher#11766050
Preparation of experimental models and subject details
Mice and genotyping
Experiments were conducted in adult mice. Mice within a genotype were arbitrarily assigned to an experimental group so that each group contained approximately equal numbers of males and females depending on colony availability. Group sized were based on previous work (Masoud et al, 2015; Salahpour et al, 2008; Vecchio et al, 2021). In most cases, the experimenter was not aware of the genotype of the mice until the point of statistical analyses. Western blots were an exception, as these were loaded such that samples within a genotype of treatment group neighbored each other on the blot. Mice were housed with littermates on a 12-hour light-dark cycle with food and water available ad libitum. All experimentation was conducted during the light phase. SLC6A3^A313V+/+^ (A313V) mice were created via CRISPR-Cas9 endonuclease-mediated transgenesis. Targeting was performed on an FVB/N × C57BL/6J hybrid F1 background using an sgRNA designed to a 20 bp target within Exon 7 of SLC6A3 (target sequence: GGAGAAGCACACCTGGGTGG). A 127 bp ssODN was provided for homology-directed repair to introduce the desired nucleotide change (NM_010020.3:c.1095 C > T; p.Ala313Val) along with a second silent nucleotide change made to facilitate targeting (NM_010020.3:c.1093 T > C; p.Asp312Asp) (ssODN sequence: (CGGGTGGAACTAACTCACATCCCATTCTCTCTGATCATCTTCCTCATGCTCTCCCATCTCTGGCTGTGACAGGTGTGGATCGACGTCGCCACCCAGGTGTGCTTCTCCCTTGGCGTTGGGTTTGGGG). Founder mice were identified by Sanger sequencing and bred to a C57BL/6 J background to generate wild-type (WT) and A313V mice. Following germline transmission, A313V mice were backcrossed onto the C57Bl/6J background, and continuously backcrossed for at least 9 generations prior to starting experimentation. Mice were genotyped using two separate PCRs for each allele: the WT and A313V variant allele amplification primers (552-bp amplicon) (along with a control reaction for PCR); WT forward: ACA GGT GTG GAT CGA TGC, reverse: GGA GAG AGG ATG GAG AAG AGA A; A313V forward: ACA GGT GTG GAT CGA CGT, reverse: GGA GAG AGG ATG GAG AAG AGA A. Both reactions are run side-by-side. Touchdown PCR was used with DreamTaq DNA Polymerase (Thermo Fisher Scientific): 2 min at 96 degrees, then each cycle after is 94 degrees for 20 s, annealing for 30 s. The initial 12 cycles are touchdown from 64-58 degrees (0.5 degrees/cycle), with the remaining 28 cycles with an annealing temperature of 58 degrees (40 cycles total), with extension of 30 s for each cycle. Animals were genotyped prior to experiments and after experiments were completed to confirm the correct genotype.
Sex as a biological variable
Sex was not considered as a biological variable in our studies. It is difficult to determine if sex contributes to DTDS pathology and symptomology in humans, as a limited number of cases have been reported (Ng et al, 2014). However, similar number of males and females with DTDS have been described in (Assmann et al, 2004; Kurian et al, 2009; Kurian et al, 2011; Ng et al, 2014; Yildiz et al, 2016; Galiart et al, 2017; Kuster et al, 2018; Heidari et al, 2020; Nasehi et al, 2020; Tehreem and Kornitzer, 2020; Baga et al, 2021; Mir et al, 2022; Silva et al, 2023): 15 males and 19 females. Therefore, for the initial characterization of the A313V mice, data from male and female mice were combined.
Reverse-transcriptase qPCR
Reverse-transcriptase qPCR was used to determine total levels of Slc6A3 (DAT), Th (tyrosine hydroxylase), Slc18A2 (VMAT2), and Nurr1 mRNA on midbrain dissections from WT and A313V mice. 200 ng of RNA was used to obtain complementary DNA using the SuperScript IV VILO kit (ThermoFisher, #11766050) according to the manufacturer’s instructions. Quantitative RT-qPCR was performed using the PowerUp SYBR Green Master Mix (ThermoFisher, #A25742) on the QuantStudio 5 instrument (ThermoFisher, #A28574). To ensure that the levels of Slc6A3, Th, and Slc18A2 mRNA levels were normalized to the volume of dopaminergic cells within the dissection area, Slc6A3 (forward primer: 5’-ggcctgggcctcaacgacac; reverse primer: 5’-ggtgcagcacaccacgctcaa), Th (forward primer: 5’-cgggcttctctgaccaggcg; reverse primer: 5’-tggggaattggctcaccctgct), and Slc18A2 (forward primer: 5’ctgctcaccgtcgtagttcc; reverse primer: 5’-ctggcagtctggatttccgt) mRNA levels are presented as a ratio of the normalized expression (normalized to reference gene PGK1 (forward primer: 5’-gaggaagaagggaagggaa; reverse primer: 5’-aggctcggcccgcatcaa)) to the normalized expression of Nurr1 (forward primer: 5’cagagctacagttaccactcttc; reverse primer: 5’-tggtgaggtccatgctaaac). The relative quantification of all targets was obtained using the 2-∆∆CT method.
mDAT coding region sequencing
To confirm that CRISPR-Cas9 generation of the A313V mouse line did not produce off-target effects, the entire mDAT coding region was confirmed by sequencing the cDNA (see above for preparation of cDNA methodology) by PCR and then sequencing the resulting PCR products. PCR reactions were performed using DreamTaq polymerase (Thermo Scientific), the products were purified using the PureLink™ PCR Purification Kit (Invitrogen) and sequenced. The purified products were sequenced with suitable primers (see Table S1 in Appendix) and aligned with NM_010020.3 (see Appendix for alignments). Sequencing result files can be found here: https://osf.io/vmupw/.
Drugs
See Table 1 for details of drugs used in this manuscript.Table 1. Drugs.DrugSourceAmphetamineToronto Research Chemicals, #A634295Threo-Methylphenidate hydrochloride (MPH)Tocris Bioscience, #298-59-9Alpha-methyl-D,L-p-tyrosine, Methyl Ester (ɑMPT)ChemCruz, Santa Cruz Biotechnology, Inc. #sc-219470IbogaineIbogaworld, ibogaworld.comNoribogaineSynthesized from ibogaine by Dalriada Drug Discovery, Mississauga, ON, CA, and by Dr. Landon Edgar at the University of Toronto, Toronto, ON, CAPifithrin-μMillipore Sigma, #P0122
Noribogaine synthesis
Ibogaine hydrochloride (3 g, 9.66 mmol) was dissolved in 100 mL of anhydrous DCM (0.1 M). The reaction flask was purged with nitrogen and cooled to −78 °C before 1 M solution of boron tribromide in DCM (5 eq., 48.32 mmol) was added dropwise over 20 min. The reaction was left stirring in the dark for 5 h. The crude was poured slowly into sat. aq. NaHCO_3_ and extracted 200 mL of 15% MeOH in CHCl_3_ three times. The aqueous layer was diluted with aq. NH_4_OH and extracted successively with 200 mL EtOAc four times. The organic fractions were combined, dried over MgSO_4_, filtered, and concentrated in vacuo. The organic fractions were then purified by silica gel flash column chromatography (3–15% MeOH in DCM) to yield pure noribogaine free base (4.08 g, 70% yield). TLC: (MeOH:DCM 1.5:10 v/v) R_F_ = 0.5.
Noribogaine was stirred in 100 mL of 4 M HCl solution in 1,4-dioxane in the dark for 2 h. The crude was concentrated in vacuo, suspended in diethyl ether (100 mL), and the precipitate was filtered under reduced pressure. The precipitate was reconstituted in a 30% MeCN in water and lyophilized to yield noribogaine HCl as a beige powder. See Appendix Figs. S1 and S2 for ^1^H NMR of noribogaine HCl in CD_3_OD and ^13^C NMR of noribogaine HCl in CD_3_OD.
Western blotting
See Appendix Table S2 for a summary of methods.
Midbrain
For the midbrain western blot in Fig. 1C, three midbrains per tube were combined and homogenized with glass-teflon homogenizer at setting 7, 12 times in 3 ml of 20 mM HEPES/1 mM EDTA+ protease inhibitors (PIs) leupeptin (Bioshop, LEU001.50), 5 μg/μl pepstatin A (Bioshop, PEP605), 1.5 μg/ml aprotinin (Bioshop, APR600), 0.1 μg/ml benzamidine (Bioshop, BEN601), 100 μm PMSF (Bioshop, PMS123), 2.5 mm Na pyro-phosphate (Bioshop, SPP310), 1 mm β-glycerophosphate (Bioshop, GYP001), 10 mm NaF (Bioshop, SFL001), and 1 mm Na_3_VO_4_ (Bioshop SOV664). The samples were then transferred to a 13 ml tube and homogenized with a polytron for 3 × 15 s at the maximum setting. Samples were then spun at 600× g for 10 min at 4 °C. The supernatant was then transferred to a thick walled sorval tube and the pelleted nuclear fractions were discarded. The supernatant was spun at 40,000× g for 15 min at 4 °C. The supernatant was then discarded and the pellet was resuspended in 100 μl of HEPES/EDTA + PI buffer. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Membrane protein extracts were then separated by 10% SDS-PAGE and transferred to a PVDF membrane. Approximately even loading and transfer were confirmed using Ponceau S stain before proceeding with immunodetection. Blot was blocked for 1 h at room temperature with LI-COR (Lincoln, NE) blocking buffer and stained overnight at 4 degrees with goat anti-DAT (1:500, Santa Cruz #sc-1433 [discontinued]). The blot was then incubated with a donkey anti-goat secondary for 1 h at room temperature (1:10,000). Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Image Studio software.
For the midbrain western blots in Fig. 8C,G, individual midbrains were homogenized in RIPA buffer + PIs. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Membrane protein extracts were then separated by 10% SDS-PAGE and transferred to a PVDF membrane. Approximately even loading and transfer were confirmed using LI-COR Total Protein stain (LI-COR, LIC-926-11010) before proceeding with immunodetection. Blots were blocked for 1 h at room temperature with LI-COR (Lincoln, NE) blocking buffer and stained overnight at 4 degrees with a rabbit anti-DAT primary antibody (1:500, Sigma-Aldrich, #D6944). The blots were then incubated with an anti-rabbit secondary for 1 h at room temperature (1:7500). Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Emperia Studio software. Levels of DAT were calculated as follows: ((DAT signal/Total Protein Signal)/(Vehicle Average (DAT signal/Total Protein Signal)) * 100.
Individual midbrains in Fig. 10C,G were homogenized in RIPA buffer + PIs. The samples were incubated on ice for 10 min and spun at 13,000 rpm for 10 min at 4 °C. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Membrane protein extracts were then separated by 10% SDS-PAGE and transferred to a PVDF membrane. Approximately even loading and transfer were confirmed using LI-COR Total Protein stain (LI-COR, LIC-926-11010) before proceeding with immunodetection. Blots were blocked for 1 h at room temperature with LI-COR (Lincoln, NE) blocking buffer and stained for 72 h at 4 °C with a rabbit anti-DAT primary antibody (1:500, Sigma-Aldrich, #D6944). The blots were then incubated with an anti-rabbit secondary for 1 h at room temperature (1:7500). Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Emperia Studio software. Levels of DAT were calculated as follows: ((DAT signal/Total Protein Signal)/(Vehicle Average (DAT signal/Total Protein Signal)) * 100.
Striata
Striata in Fig. 1A were homogenized with glass-teflon homogenizer at setting 7, 12 times in 3 ml of 20 mM HEPES/1 mM EDTA or 25 mm Tris-2 mM EDTA, and PIs. The samples were then transferred to a 13 ml tube and homogenized with a polytron for 3 × 15 s at the maximum setting. Samples were then spun at 600× g for 10 min at 4 °C. The supernatant was then transferred to a thick walled sorval tube and the pelleted nuclear fractions were discarded. The supernatant was spun at 40,000× g for 15 min at 4 °C. The supernatant was then discarded and the pellet was resuspended in 100 μl of HEPES/EDTA + PI buffer. Protein concentration was determined using a BCA protein assay kit (Thermo Fischer Scientific, Pierce BCA Protein Assay Kit, #23227). Membrane protein extracts were then separated by 10% SDS-PAGE and transferred to a PVDF membrane. Approximately even loading and transfer were confirmed using Ponceau S stain before proceeding with immunodetection. Blot was blocked for 1 h at room temperature with LI-COR (Lincoln, NE) blocking buffer and stained overnight at 4 °C with goat anti-DAT (1:500, Santa Cruz #sc-1433 [discontinued]). The blot was then incubated with a donkey anti-goat secondary for 1 h at room temperature (1:10,000) overnight at 4 °C. Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Image Studio software or Emperia Studio software. Levels of DAT were calculated as follows: ((DAT signal/Total Protein Signal)/(Vehicle Average (DAT signal/Total Protein Signal)) * 100.
Striata in Fig. 2A were dissected and homogenized in a buffer containing 25 mM Tris/2 mM EDTA + PIs. The samples were incubated on ice for 10 min and spun at 13,000 rpm for 10 min at 4 °C. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Samples proteins were then separated by 10% SDS-PAGE and transferred to PVDF membranes. Approximately even loading and transfer were confirmed using LI-COR Total Protein stain (LI-COR, LIC-926-11010) before proceeding with immunodetection. Blots were blocked with 5% BSA in TBS for 1 h at room temperature and then stained overnight at 4 °C with rabbit anti-TH (1:3000, Millipore Sigma #AB152) in 5% BSA in TBS-T. The blot was then incubated for 1 h at room temperature in a secondary anti-rabbit antibody (1:7500) in 5% BSA in TBS-T. Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Emperia Studio software. After scanning, the blot was stripped for 60 min at room temperature with 62.5 mM Tris-Cl (pH 6.7), 2% SDS, and 6.9 μl βME/mL. The blot was then again blocked in 5% BSA for 1 h at room temperature and incubated overnight at 4 °C with rabbit anti-phosphoTH-ser40 (1:2000, PhosphoSolutions #p1580-40) and mouse anti-GAPDH (1:5000) in 5% BSA in TBS-T. Afterwards, the blot was incubated for 1 h at room temperature with anti-mouse and anti-rabbit secondary antibodies (1:7500) in 5% BSA in TBS-T. Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Emperia Studio software. Levels of TH were calculated as follows: ((TH signal/Total Protein Signal)/(WT Average (TH signal/Total Protein Signal)) * 100. Levels of phosphoTH-ser40 were calculated as follows: ((pTH s40signal/GAPDH Signal)/(WT Average (pTH s40 signal/GAPDH Signal)) * 100. Levels of pTH s40/TH were calculated as follows: ((pTH s40 signal/GAPDH Signal)/(TH signal/Total Protein Signal))/(WT Average (pTH s40 signal/GAPDH Signal)/(TH signal/Total Protein Signal)) * 100.
Striata in Fig. 8A,E were homogenized in 2 mL of 30 mM phosphate buffer (pH 7.9) containing 0.32 M sucrose + PIs. Homogenates were centrifuged at 1000 rpm at 4 °C for 10 min. The supernatant was transferred to a new tube and centrifuged twice at 18,000 rpm for 20 min at 4 °C. The supernatant was discarded and the resulting pellet was resuspended in 100 µl of buffer. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Membrane protein extracts were then separated by 10% SDS-PAGE and transferred to a PVDF membrane. Approximately even loading and transfer were confirmed using LI-COR Total Protein stain (LI-COR, LIC-926-11010) before proceeding with immunodetection. Blot was blocked for 1 h at room temperature with 5% BSA in TBS and stained overnight at 4 degrees with rabbit anti-DAT primary antibody (1:500, Sigma-Aldrich, #D6944). The blot was then incubated with an anti-rabbit secondary for 1 h at room temperature (1:7500). Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Emperia Studio software. Levels of DAT were calculated as follows: ((DAT signal/Total Protein Signal)/(Vehicle Average (DAT signal/Total Protein Signal)) * 100.
Striata in Fig. 10A,E were homogenized using a glass Teflon homogenizer in 3 mL of 30 mM phosphate buffer (pH 7.9) containing 0.32 M sucrose + PIs. Homogenates were centrifuged at 1000 rpm at 4 °C for 10 min. The supernatant was transferred to a new tube and centrifuged at 18,000 rpm for 20 min at 4 °C. The supernatant was discarded and the resulting pellet was resuspended in 100 µl of buffer. Protein concentration was determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Membrane protein extracts were then separated by 10% SDS-PAGE and transferred to a PVDF membrane. Approximately even loading and transfer were confirmed using LI-COR Total Protein stain (LI-COR, LIC-926-11010) before proceeding with immunodetection. Blot was blocked for 1 h at room temperature with 5% BSA in TBS and stained for 48 h at 4 degrees with mouse anti-DAT primary antibody (Thermo Fisher #MA5-24796 or 1:500, Sigma-Aldrich, #D6944). The blot was then incubated with an anti-mouse secondary for 1 h at room temperature (1:7500). Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Emperia Studio and ImageJ software. Levels of DAT were calculated as follows: ((DAT signal/Total Protein Signal)/(Vehicle Average (DAT signal/Total Protein Signal)) * 100.
EndoH/ PNGase F experiment
The midbrain (3 samples/tube) was dissected and homogenized in a buffer containing RIPA buffer + PI. The samples were incubated on ice for 10 min and spun at 13,000 rpm for 10 min at 4 °C. Protein concentrations were determined using a BCA protein assay kit (Thermo Fisher Scientific, Pierce BCA Protein Assay Kit, #23227). Samples were digested with the glycosidases peptide N-glycosidase F (PNGase F) and EndoH (New England Biolabs, catalog #P0704S and #P0702S, respectively). Sample proteins were then separated by 10% SDS-PAGE and transferred to PVDF membranes. Approximately even loading and transfer were confirmed using LI-COR Total Protein stain (LI-COR, LIC-926-11010) before proceeding with immunodetection. Blots were blocked with 5% BSA in TBS for 1 h at room temperature and stained for 1 h at room temperature and then overnight at 4 degrees Celsius with mouse anti-DAT (1:250, Thermo Fisher Scientific, MA, USA, #MA5-24796). The blots were then incubated with a secondary anti-mouse (1:7500) antibody. Protein bands were visualized using the Odyssey Imaging System (LI-COR) and Image Studio software.
Tissue content of dopamine and metabolites
Dopamine levels were determined using high-performance liquid chromatography with electrochemical detection (HPLC-EC; ESA/Thermo Scientific, Chelmsford, MA; 37). Separation of neurotransmitters and their metabolites was achieved using a reverse phase column (Luna 100 × 3.0 mm C18 3 μm, Phenomenex, Torrance, CA) with a mobile phase made up of 75 mM NaH2PO4, 1.7 mM 1-octanesulfonic acid sodium salt, 100 µL/L triethylamine, 25 µM EDTA, 10% acetonitrile v/v; pH 3.0. Analyte detection was carried out using a high-sensitivity analytical cell 5011 A (Thermo Fisher Scientific, Sunnyvale, CA) at +220 mV on a Coulochem III Electrochemical Detector (ESA/Thermo Scientific, Chelmsford, MA). Chromeleon software (ESA/Thermo Scientific, Chelmsford, MA) was used to quantify analytes using an external calibration curve of standards of known dopamine and metabolite concentrations.
Fast-scan cyclic voltammetry (FSCV)
Mice were anesthetized with 5% isoflurane and decapitated. Brains were removed and placed into oxygenated (95% O_2_/5% CO_2_) artificial cerebrospinal fluid composed of (in mM): 126 mM NaCl, 2.5 mM KCl, 1.2 mM NaH_2_PO_4_, 2.4 mM CaCl_2_, 1.2 mM MgCl_2_, 25 mM NaHCO_3_, 11 mM D-glucose, and 0.4 mM L-ascorbic acid, with pH adjusted to 7.4. Brains were sliced into 300 µm coronal sections between +1.7 to +0.74 mm from bregma with a vibrating tissue slicer. Slices were allowed to equilibrate for one hour in oxygenated aCSF flowing at 1 mL/min. A glass capillary-pulled carbon fiber recording microelectrode was placed 75 µm into the slice next to a bipolar stimulating electrode. Dopamine release was evoked by single monophasic electrical pulses (750 µA, 4 ms) occurring every 300 s until signals were stable ( < 10% change in peak height) for at least three measurements. Recordings were taken for 15 s (wild-type) or 30 s (A313V) by the recording electrode that scanned a triangular waveform between -0.4 V and 1.2 V against Ag/AgCl reference at a rate of 400 V/s every 100 ms. Dopamine oxidation current (nA) was converted to concentration (µM) with calibration factors based on the size of the electrode background current, which reflects active carbon surface area and thereby sensitivity to dopamine, to predict the magnitude of signal in response to a known (3 µM) concentration of dopamine, based on 100+ typical electrode responses. Dopamine recordings were taken in the dorsolateral striatum. Recording and analysis were conducted with Demon Voltammetry and Analysis Software (Yorgason et al, 2011). Stable baseline collections were first analyzed using a least squares fitting equation to assess peak height and decay (tau). Subsequently, baseline recordings and drug collections were analyzed via Michaelis-Menten kinetic modeling to determine dopamine release (µM) and maximal rate of dopamine uptake (Vmax; µM/s). Representative traces were generated by taking the raw current versus time plots for one stable baseline recording per slice, then dividing all time points in that recording by the electrode calibration factor for that experiment.
LC-MS/MS noribogaine plasma and brain concentration analysis
Concentrations of noribogaine in plasma and brain were measured using LC-MS/MS with clonazepam-d_4_ (CLZ-d_4_) as internal standard. The analysis was done on an Agilent 1260 LC system (Agilent 1260 Quaternary pump, Agilent 1260 Infinity Standard Autosampler and temperature-controlled column compartment) using a C18 column (Zorbax SB-C18, 5 µm 2.1 × 150 mm, 5 µm; Agilent) at ambient temperature. Noribogaine and internal standard were resolved with a gradient elution where the mobile phase A was Milli-Q water + 0.1% formic acid, and B was HPLC-grade acetonitrile + 0.1% formic acid. Gradient elution is detailed in Table S3.
The LC system was coupled to an Agilent 6430 triple quadrupole mass spectrometer (Agilent, Santa Clara, CA) operated in positive Electrospray Ionization (ESI) mode with source temperature maintained at 350 °C. The mass transitions monitored were m/z 297.2 to 122.1 (used for quantification) and 297.2 to 160 for noribogaine and 320.1 to 274 for CLZ- d_4._
For sample preparation, a stock mixture of the internal standard solution of CLZ-d4 was dissolved in methanol with 1% formic acid to a concentration of 50 ng/mL. Calibration curves were prepared in plasma for analysis of plasma samples (1, 10, 100, 500, 1000 and 5000 ng/mL) and in brain homogenate where 1 part tissue was homogenized in 3 volumes of 0.01 HCl (1, 10, 100, 500, 1000 and 5000 ng/mL). For analysis of the plasma samples, 40 µL of 50 ng/mL internal standard solution was added to 20 µL of the plasma sample or calibrator for a final concentration of 100 ng/mL in plasma. Samples and calibrators were vortexed vigorously for mixing, and centrifuged at ~15,000× g (12,000 rpm on small tabletop centrifuge) for 15 min, 30 µL of the supernatant was transferred to LCMS vial inserts and 30 µL of water was added to reduce methanol content. The injection volume used was 20 µL. For the brain samples, 100 µL of 50 ng/mL internal standard was added to 50 µL of the brain homogenate (1:3 in 0.01 M HCl) sample or calibrator for a final concentration of 100 ng/mL in brain homogenate. Samples and calibrators were vortexed vigorously for mixing and centrifuged at ~15,000× g (12,000 rpm on small tabletop centrifuge) for 15 min,50 µL of the supernatant was transferred to LCMS vial inserts and 50 µL of water was added to reduce methanol content. The injection volume was 20 µL.
Recovery and matrix effects were determined for two concentrations (200 and 2000 ng/mL) for plasma and brain homogenate to range between 71.1–86.8% for noribogaine in brain homogenate and 37.1–49.4% in plasma, respectively. The internal standard peak area response ratio was tested for linearity between the concentration 10–10,000 ng/ml). Six calibration samples are enough to describe the relationship (10, 100, 500, 1000, 5000 and 10,000 ng/ml) with weighing (1/x2). The limit of quantification (LOQ) was determined to 10 ng/mL for noribogaine. Intraday accuracy and precision were determined using replicates of 3 QC samples (10, 200 and 2000 ng/ml) in plasma and brain homogenate matrices. Inter-day accuracy was 85.4–113.4% for plasma and 90.9–112.3% for brain homogenate, and precision (%CV) was 8.8–10.2% for plasma and 5.1–11.2% for brain homogenate.
Behavioral assessments
Body composition analysis with dual energy X-ray absorptiometry (DEXA)
Body composition analysis was performed using the UltraFocusDXA instrument (Faxitorn Bioptics, LLC) and analyzed with the Vision DXA software. Mice were weighed and placed into an anesthetic induction chamber and administered 4% isoflurane. Once the mouse was adequately sedated, the animals was transferred into the x-ray chamber in a prone position with its nose in an anesthetic cone. The body of the mouse was positioned with its limbs at the sides of its body and its tail curved along the left side of the body. A DEXA image map was produced for each animal and analyzed to generate bone area, bone mineral density, bone mineral content, lean mass, and fat mass data for each mouse. Once the scan was completed, animals were returned to their home cage and placed half on a heating pad and monitored until fully recovered from anesthesia.
Dorsal immobility response
Animals were clasped by the nape of the neck and gently elevated into the air to elicit the dorsal immobility response. Latency to begin moving was recorded for each animal.
Open field test
Locomotor activity and stereotypy were measured using digital activity monitors (Omnitech Electronics, Columbus, OH, USA). Animals were placed in Plexiglas chambers (20 × 20 × 45 cm^3^) and their locomotor activity and stereotypic behavior were recorded for 60 min. After 60 min, for all experiments except the noribogaine and pifithrin-μ experiments, mice were given i.p. injections of vehicle or drug. Infrared light beam sensors were used to track the animal’s movement. Total distance traveled in centimeters, horizontal activity, vertical activity, stereotypy number and stereotypy time were collected in 5-min bins. Mice were naïve to the task and had not been exposed to the arena prior to testing. Data was discarded for mice who escaped from the arena during testing. Data were combined for animals that received 0.9% saline as a drug vehicle and whose activity was monitored using the VersaMax Legacy Open Field equipment (Omnitech Electronics, Inc. Columbus, Ohio, USA) (baseline, 30 mg/kg MPH, 40 mg/kg MPH, 250 mg/kg αMPT, 125 mg/kg αMPT. and 62.5 mg/kg αMPT). Open field experiments performed using the VersaMax SuperFlex Open Field System and Fusion Software (Omnitech Electronics, Inc., Columbus, OH, USA) had their own dedicated vehicle groups and were not combined with others (31 mg/kg αMPT, noribogaine, DAT-KO αMPT experiments, pifithrin-μ).
Habituation index
The habituation index, representing the time in minutes to reach half-maximal activity in the open field test, was calculated following Mielnik et al, 2021. To determine this index, the Y-intercept from the activity data between the first time point (5 min) and the last time point (150 min) was divided by 2, and this result was then divided by the slope of the data from 5 to 150 min. The absolute value of this calculation was used for statistical testing for each animal.
Rotarod
A computer controlled rotarod apparatus (46750 Rota-Rod NG, Ugo Basile, Gemonio, VA, Italy) with a rod of 3 cm diameter was set to accelerate from 4 to 40 revolutions per minute over 300 s, and latency to fall was recorded. Motor learning was assessed using a method adapted from Beeler et al, 2010, wherein mice received 5 consecutive trials per session, 1 session per day. Rest between trials was ~30 s. Mice were trained for 5 days, then received a 3 day break, and were tested again on the 9th day.
Gait analysis
Gait analysis was performed using the DigiGait treadmill by Mouse Specifics, Inc. The equipment consists of a walking compartment of 25 cm with a clear polymer bonded belt. A high-speed digital video camera images the underside of the walking animals. Gait was recorded from each animal for a minimum of 3 s at a walking speed of 20 centimeters per second. The DigiGait software generated digital paw prints and dynamic gait signals that were analyzed automatically using MatLab. The positions of 14 body parts were labeled in each video frame (nose, tail base and tip, torso center, left and right torso flanks, base of palm and 1st joint of middle digit on each paw) using custom neural network models in the Python 3.11-based DeepLabCut v2.3.7 software toolbox (see deeplabcut.github.io/DeepLabCut/; Nath et al, 2019). Two Resnet-50-based network models were trained to estimate the position of an animal’s 4 paws either (A) throughout all video frames, or (B) exclusively when a given paw was planted on the treadmill surface. The latter model (accessible at https://osf.io/gm6hs/files/d3wc6) was used to extract the stride length dataset reported here. Asymptotic model performance (2.24 px train error and 2.55 px test error with a 0.6 probability estimate cutoff) was reached following 150,000 training iterations, including manual labeling a total of 340 video frames from 16 training set video segments.
Tail tip was inconsistently visible throughout each video and did not contribute to subsequent analyses. An experimenter blinded to experimental design/group manually corrected any residual tracking errors while viewing DLC-labeled body parts overlaid on each video snippet (see tracking example video at https://osf.io/gm6hs/).
In total, 5 complete stride cycles were analyzed for each experimental subject (5 left and 5 right strides), curated based on the visibility of all body parts during continuous forward walking motion (excluding intervals in which the mouse displayed prominent lateral locomotion, grooming, rearing, ground/wall whisking, halted momentum). These exclusion criteria were implemented to isolate differences in fine motor coordination during forward locomotion independently from gross differences in behavioral activity (i.e., exploration, arousal/excitability, compulsive grooming, etc.), which are better captured in the OFT and other behavioral assays. Stride length was calculated as the distance between the forward- and backward-most extension, respectively, of the forepaw and hind paw on each side of the body. As these positions typically occurred asynchronously during a stride, nose position was used to correct for overall changes in body position across frames (thus isolating stride length relative to the mouse, despite ongoing acceleration/deceleration on the treadmill). Animal length (mean difference in Cartesian position of nose and tail base in each frame that met inclusion criteria) was used to scale the stride length as a proportion of body length. The mean body lengths of WT (398.89 px) and Het (399.34 px) groups did not differ statistically (t42 = 0.0898, *P *= 0.929). Thus, the mean stride length for each animal was calculated as the average of 10 strides, as a percentage of their body length. Microsoft Excel was used to compute all relevant position metrics from raw DLC pose estimates.
Pole reversal
Each mouse was placed head upwards at the end of a round metal rough-surfaced pole. The pole was inclined at 90° and the time taken for the mouse to turn downwards (scored as a T turn) and completely descend the pole back to its cage (scored as latency to descend) were recorded for a maximum time of 80 s. Five consecutive trials were performed and averaged.
Foot fault test
Mice were placed on a metal grid with 10 mm × 10 mm squares and allowed to freely explore for 2.5 min. The animals were filmed during this time. From these video recordings, the total number of steps and the number of slips for the forelimbs and hindlimbs were counted. A positive foot fault was considered if the animal fell through the grid.
Tail suspension test
The tail suspension test was adapted from the previously described Miedel et al, 2017. Animals were suspended in the air by the tail for 10 s and the animal’s hind and forepaws were recorded while suspended. The limb clasping was scored from the videos on a scale from 0-4 based on the following criteria: (1) No limb clasping. Normal escape extension. One hind limb exhibits incomplete splay and loss of mobility. Toes exhibit normal splay; (2) Both hind limbs exhibit incomplete splay and loss of mobility. Toes exhibit normal splay; (3) Both hind limbs exhibit clasping with curled toes and immobility; (4) Forelimbs and hind limbs exhibit clasping and are crossed, curled toes and immobility. The scoring investigator was blinded to genotype during scoring.
Noribogaine experiments
Noribogaine was suspended in 5% ethanol, 5% glucose at a concentration of 10, 25, or 50 mg/mL for doses of 100 mg/kg, 250 mg/kg, or 500 mg/kg, respectively. Noribogaine was administered via oral gavage. Blood was collected as indicated from the saphenous vein using lithium heparin tubes (Sarstedt #16.443.100). Blood samples were spun at 5000× g for 10 min, and the supernatant (plasma) was collected for further analysis. Animals were killed via rapid conscious cervical dislocation and brains were flash frozen in isopentane. Midbrains and striata were dissected for analysis of DAT levels via western blotting, and cerebellums, cortical tissue, or whole brain were dissected for noribogaine concentration analysis via LCMS.
Pifithrin-μ experiment
Pifithrin-μ was dissolved in 10% DMSO for a dose of 3 mg/kg and administered via intraperitoneal injection every 48 h for 5 days (adapted from He et al, 2012). Forty-eight hours after administration on day 5, locomotor activity was recorded using the open field test (see details above). Animals were then killed via cervical dislocation under isoflurane anesthesia and brains were flash frozen in isopentane. Midbrains and striata were dissected for analysis of DAT levels via western blotting.
Statistical analyses
Outliers within each group were identified and removed using the interquartile range method for all behavioral assays and for analysis of dopamine and metabolites tissue content. For each variable, the first quartile (Q1) and third quartile (Q3) were calculated. The interquartile range (IQR) was defined as the difference between Q3 and Q1 (IQR = Q3–Q1). Data points were considered outliers if they fell below the lower bound (Q1–1.5× IQR) or above the upper bound (Q3 + 1.5 × IQR). Outlier detection was performed for all datasets aside from the noribogaine PK and PCR experiments (Figs. 1F, 2E, and EV1C). Statistics were performed after outliers were removed. All statistical analyses were performed for each group by a Student’s t test, Welch’s t test, one-way ANOVA, two-way ANOVA, or mixed model, indicated in each figure legend where appropriate. Tukey’s or Šidák’s multiple comparisons were performed after the ANOVA or mixed model analysis if the interaction between variables was significant. Significance is reported where P ≤ 0.05. Data was visualized for normality and homogeneity of variance to confirm the data conformed to a normal distribution with homogenous variability, and tests were chosen based on previous work (Masoud et al, 2015; Salahpour et al, 2008; Vecchio et al, 2021). All statistical testing was carried out using GraphPad Prism version 9 or 10.
Study approval
Animal housing and experiments were conducted in accordance with the Canadian Council on Animal Care and the University of Toronto Faculty of Medicine and Pharmacy Animal Care Committee (Ankenman and Salvatore (2007b); Assmann et al (2004); Brogden (1981); Efimova et al (2016); Guerois et al (2002); Jaber et al (1999); Kanner and Zomot (2008); Liu et al (2015); Mosharov et al (2009); Nirenberg et al (1997); Sotnikova et al (2005); Spaull and Kurian (2023).
Supplementary information
Appendix Peer Review File Source data Fig. 1 Source data Fig. 2 Source data Fig. 3 Source data Fig. 4 Source data Fig. 5 Source data Fig. 6 Source data Fig. 7 Source data Fig. 8 Source data Fig. 9 Source data Fig. 10 Figure EV1 Source Data Figure EV2 Source Data Figure EV3 Source Data Figure EV4 Source Data Figure EV5 Source Data Expanded View Figures
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