Article | Published:

Striatal neurons directly converted from Huntington’s disease patient fibroblasts recapitulate age-associated disease phenotypes

Nature Neurosciencevolume 21pages341352 (2018) | Download Citation


In Huntington’s disease (HD), expansion of CAG codons in the huntingtin gene (HTT) leads to the aberrant formation of protein aggregates and the differential degeneration of striatal medium spiny neurons (MSNs). Modeling HD using patient-specific MSNs has been challenging, as neurons differentiated from induced pluripotent stem cells are free of aggregates and lack an overt cell death phenotype. Here we generated MSNs from HD patient fibroblasts through microRNA-based direct neuronal conversion, bypassing the induction of pluripotency and retaining age signatures of the original fibroblasts. We found that patient MSNs consistently exhibited mutant HTT (mHTT) aggregates, mHTT-dependent DNA damage, mitochondrial dysfunction and spontaneous degeneration in culture over time. We further provide evidence that erasure of age stored in starting fibroblasts or neuronal conversion of presymptomatic HD patient fibroblasts results in differential manifestation of cellular phenotypes associated with HD, highlighting the importance of age in modeling late-onset neurological disorders.


HD is a progressive neurodegenerative disorder caused by an abnormal expansion of CAG codons in the huntingtin (HTT) gene1,2. HD symptoms typically manifest in midlife and may include motor deficits, psychiatric symptoms and cognitive decline3. While healthy individuals have an average HTT CAG tract size of 17–20 repeats, HD patients have an expansion of 36 or more CAGs4. Moreover, CAG repeat length is directly correlated to the severity of the disease and inversely related to the age of onset5. Expanded CAG trinucleotides encode a polyglutamine stretch that can accumulate into proteinaceous cytoplasmic and intranuclear aggregates that are thought to be neurotoxic3, although the formation of inclusion bodies has also been suggested to be a neuroprotective mechanism6. HD pathology is characterized by the selective degeneration of MSNs while other neuronal subpopulations are relatively spared7.

Because of the clinical importance of MSNs in HD, differentiation protocols have been developed to generate MSNs from induced pluripotent stem cells (iPSCs)8,9. However, modeling HD with iPSC-derived neurons often requires additional cellular insults to detect HD-relevant phenotypes10,11,12,13. For example, neurons differentiated from patient iPSCs showed elevated levels of caspase activity only upon trophic factor withdrawal, treatment with hydrogen peroxide, or high levels of glutamate, but otherwise display no overt cell death phenotype9,10,13. Additionally, iPSC-derived neurons do not exhibit mHTT aggregates even after the addition of cellular stressors11, and other studies required culturing cells for at least 6–8 months and treatment with proteasome inhibitors before aggregates could be detected12,14. Therefore, an alternative reprogramming approach that generates an enriched population of patient-derived MSNs that more robustly display HD phenotypes will greatly facilitate the modeling of HD.

Ectopic expression of the brain-enriched microRNAs (miRNAs) miR-9/9* and miR-124 (miR-9/9*-124) in human adult fibroblasts has been shown to directly convert fibroblasts to neurons through extensive chromatin reconfigurations. The miRNA-9/9*-124-induced neuronal state, generated by miRNA instruction in switching the activities of chromatin remodeling complexes15,16, allows terminal selector genes to guide neuronal conversion to produce a highly enriched population of specific neuronal subtypes16, specifically MSNs with CTIP2, DLX1, DLX2 and MYT1L (CDM)17. In contrast to neurons differentiated from iPSCs, in which the age stored in original fibroblasts is erased during the induction of pluripotency18,19, directly converted neurons have been shown to retain age-associated marks of starting adult human fibroblasts, including the epigenetic age (also known as the epigenetic clock19), oxidative stress, DNA damage, miRNAome, telomere lengths and transcriptome20,21. This feature offers potential advantages in modeling adult-onset disorders; however, the value of MSNs directly converted from HD patient fibroblasts in modeling HD remains to be determined.

Here we propose the generation of HD patient-derived MSNs (HD-MSNs) through miR-9/9*-124-CDM-based conversion of fibroblasts as a cellar model of HD. We focused on HD samples with 40–50 CAG repeats, which represent the majority of HD cases4. HD-MSNs recapitulated essential HD-associated phenotypes, including the formation of mHTT aggregates, DNA damage, spontaneous neuronal death in culture, and a decline in mitochondrial function. We further provide evidence that cellular age is an essential component underlying the manifestation of HD phenotypes. By inducing HD-fibroblasts into iPSCs and redifferentiating them back into embryonic fibroblasts for neuronal conversion, we discovered that age-associated reduction in protein homeostasis levels was primarily responsible for mHTT aggregation in adult HD-MSNs. Furthermore, MSNs reprogrammed from presymptomatic HD patients were less vulnerable to mHTT-induced toxicity than MSNs reprogrammed from symptomatic patients, despite comparable levels of mHTT aggregates. Finally, modifying the terminal neuronal cell fate to cortical neurons alleviated mHTT-induced toxicity. These results underscore the importance of direct neuronal conversion for modeling age-related phenotypes of late-onset diseases with specific neuronal subtypes.


Generation of MSNs from HD patient fibroblasts

We first tested the efficacy of miR-9/9*-124-CDM-based neuronal conversion in fibroblasts from ten symptomatic HD patients, including males and females ranging from 6 to 71 years of age with various CAG repeat expansions (Supplementary Table 1). HD-fibroblasts could be directly reprogrammed to MSNs regardless of age or CAG repeat number (Fig. 1 and Supplementary Fig. 1), and we focused our analyses on patient samples with CAG repeats lower than 50, as this range reflects most adult-onset cases3 but remains understudied. We validated MSN conversion in three independent HD patient fibroblast samples containing 40, 43 or 44 CAG repeats (HD.40, HD.43 and HD.44) and their respective age- and sex-matched healthy controls (Ctrls) with 19, 17 or 18 CAG repeats (Ctrl.19, Ctrl.17 and Ctrl.18) (Fig. 1). At post-induction day 30 (PID 30), HD-MSNs expressed the neuronal markers TUBB3, NeuN and MAP2, the GABAergic neuron marker GABA, and the MSN marker DARPP-32 (Fig. 1a and Supplementary Fig. 1). We found no significant differences in the reprogramming efficiency between HD and control samples, generating approximately 90% MAP2- and 70–80% GABA- and DARPP-32-positive neurons (Fig. 1b,c). Furthermore, CAG repeat lengths remained stable after neuronal conversion (Supplementary Fig. 2).

Fig. 1: HD patient fibroblasts can be directly reprogrammed into MSNs.
Fig. 1

Fibroblasts from three HD patients (with mHTT expansions of 40, 43 and 44 CAGs) and their respective age- and sex-matched controls (CAG sizes of 19, 17 and 18) reprogrammed into MSNs with miR-9/9*-124-CDM. a, Reprogrammed HD.40 cells at PID 30 immunostained for TUBB3, and HD.44 immunostained for TUBB3, NeuN, MAP2, DARPP-32 and GABA. b, Images of all three pairs of cell lines immunostained for GABA and DARPP-32. c, Quantification of TUBB3-, GABA- and DARPP-32-positive cells at PID 30; averages of 1,000 cells from 3 independent HD and control lines. Unpaired t-test corrected for multiple comparisons using the Holm-Sidak method; (from left, P = 0.98, 0.97, 0.98; d.f. = 4). Scale bars: 50 μm. Mean ± s.e.m.; n.s., not significant.

We carried out whole-cell recordings to determine functional properties of HD-MSNs in comparison to Ctrl-MSNs. All recorded cells displayed multiple action potentials and robust inward and outward currents upon stimulation (Fig. 2). HD- and Ctrl-MSNs displayed spontaneous action potentials at similar frequencies and had similar action potential thresholds (Fig. 2a–c). Notably, more HD-MSNs than Ctrl-MSNs fired multiple action potentials (Fig. 2d). However, all other passive membrane properties recorded did not differ significantly between HD- and Ctrl-MSNs (Fig. 2c). To further access electrophysiological properties under the same recording condition, HD-MSNs (HD.40, HD.43 and HD.44) and Ctrl-MSNs (Ctrl.17, Ctrl.18 and Ctrl.19) were cocultured and recorded on the same coverslip (Supplementary Fig. 3a). At PID 35, all six reprogrammed lines fired action potentials, but, as in cells that were cultured separately, a higher percentage of HD-MSNs fired multiple action potentials than Ctrl-MSNs upon current injection (Supplementary Fig. 3b,c) and displayed spontaneous generation of action potentials (Supplementary Fig. 3d). Whereas passive membrane properties measured remained similar between HD- and Ctrl-MSNs, we detected increased current responses with high-voltage stimulus in HD-MSNs (Supplementary Fig. 3e–g), reflecting increased excitability and firing complexity in HD-MSNs.

Fig. 2: Electrophysiological analysis of HD and control MSNs.
Fig. 2

pSynapsin-tRFP-labeled reprogrammed cells were plated onto primary rat glial cultures and cultured for 28 d (HD: HD.47, Ctrl: Ctrl.16). a,b, Voltage-clamp recordings of evoked action potentials (APs) and inset of progressive current-injection steps; current-clamp recordings of inward and outward currents and inset of sodium currents; spontaneous firing of APs; ramp protocol to determine AP threshold. Representative traces from Ctrl-MSNs in gray (a) and traces from HD-MSNs in blue (b). c, All properties measured were quantified and found to not differ significantly. Two-tailed Student’s t-test (from left, top row: P = 0.19 d.f. = 23, P = 0.61 d.f. = 23, P = 0.75 d.f. = 18, P = 0.18 d.f. = 19; from left, bottom row: P = 0.48 d.f. = 17, P = 0.72 d.f. = 19, P = 0.15 d.f. = 19, P = 0.28 d.f. = 4). d, Venn diagram of recorded cells showing increased firing complexity in HD-MSNs. All reprogrammed cells in both groups fired APs (n = 10 HD-MSNs and 12 Ctrl-MSNs). Mean ± s.d.; n.s., not significant.

To further analyze the acquisition of MSN fate, we performed RNA sequencing (RNA-seq) at PID 32 and compared the gene expression profiles between fibroblasts and converted neurons in HD and control samples. Analysis of 15 representative fibroblast-associated genes and 53 genes highly enriched in the striatum revealed the successful acquisition of MSN fate in neurons converted from HD and control samples (Fig. 3a). To identify genes potentially dysregulated in HD-MSNs, we carried out transcriptional analysis of seven independent HD-MSN and five Ctrl-MSN samples (Supplementary Table 1). Principal component analysis indicated sample segregation based on the genotype (mHTT vs. healthy control) as well as the sex of sample donors (Fig. 3b). Analysis of protein-coding genes revealed 1,127 differentially expressed genes (DEGs) between sex-matched HD-MSNs and Ctrl-MSNs (false-discovery rate (FDR) ≤ 0.01 and log2(fold change) (LFC) ≥ 0.5 or ≤ –0.5) (Fig. 3c). Gene ontology analysis showed DEGs in HD-MSNs to be significantly enriched for genetic networks associated with cell differentiation (P = 1.51 × 10−10), neurotransmission (P = 1.31 × 10−8), calcium signaling (P = 5.31 × 10−6), HD (P = 7.22 × 10−4) and apoptosis (P = 1.19 × 10−2) (Fig. 3d and Supplementary Table 2). Several DEGs identified in HD-MSNs have been previously implicated in HD. For example, we detected the upregulation of matrix metalloproteinase 9 (MMP9), which has been shown to be increased in postmortem human HD-affected brains22 and to significantly decrease the survival of striatal neurons23. Moreover, our analysis revealed the downregulation of huntingtin-associated protein-1 (HAP1) in HD-MSNs (LFC –0.55 and FDR 5.04 × 10−4; Fig. 3c), which has previously been shown to antagonize mHTT-mediated cytotoxicity and enhance cell viability24. Additionally, we detected the downregulation of 7-dehydrocholesterol reductase (DHCR7) in HD-MSNs (LFC –0.71 and FDR 2.8 × 10−5; Fig. 3c), an enzyme previously shown to have reduced expression in patients and mouse models of HD and thought to be involved in HD-specific metabolic pathway alterations25,26. Notably, many DEGs upregulated in HD-MSNs were associated with neurophysiological processes, such as the voltage-gated potassium channel subunit KCNA4 (LFC 1.15 and FDR 1.1 × 10−4) (Fig. 3c) and several subunits of GABA type-A receptors and AMPA receptors, suggesting increased neurotransmission in HD-MSNs (Fig. 3c,d and Supplementary Fig. 4). We also detected upregulation of α-synuclein (SNCA) (LFC 1.15 and FDR 1.1 × 10−4), an aggregation-prone protein shown to accumulate in mHTT polyglutamine inclusions27. Overexpression of α-synuclein has been reported to accelerate the onset of HD symptoms in multiple mouse models28. Further, we found NTRK2 (also known as TRKB), the main receptor for brain-derived neurotrophic factor (BDNF), to be downregulated in HD-MSNs (LFC –0.77 and FDR 7.44 × 10−3) (Fig. 3c). The loss of BDNF in HD pathology has been investigated extensively and proposed to be critical in the degeneration of MSNs29,30; our results indicate that mHTT may induce downregulation of BDNF signaling at the receptor level in HD-MSNs. The impairment of TRKB receptor was suggested to mediate postsynaptic dysfunction of MSNs in mouse models of HD, although changes in NTRK2 mRNA levels were not detected in HD mouse models31. Our analysis also uncovered DEGs with no previous association with HD. For instance, SP9, a zinc finger transcription factor recently shown to be necessary for the maintenance and survival of striatopallidal MSNs32, was significantly downregulated (LFC –1.7 and FDR 1.49 × 10−8) in HD-MSNs. Several of these genes, including SP9, HAP1 and NTRK2, were further validated by quantitative PCR (qPCR) in reprogrammed MSNs at PID 35 (Supplementary Fig. 4).

Fig. 3: HD-MSNs properly acquire striatal cell fate identity and display differentially expressed genes (DEGs).
Fig. 3

Analysis of fibroblast- and MSN-specific genes at PID 32 in HD.40 and HD.43 reprogrammed MSNs, Ctrl-MSNs and respective fibroblasts, as well as further analysis of a set of seven HD- and five Ctrl-MSN lines by RNA-seq. a, Heat map representation of average expression values at PID 32 for 25 fibroblast-enriched genes and 48 MSN-enriched genes including CDM factors (n = 2 biological replicates per sample of 2 HD- and Ctrl-MSNs and their corresponding fibroblasts). b, Principal component analysis of gene expression data for 12 independent samples analyzed at PID 32, plotting the first three principal components (X1, X2 and X3) (n = 2 technical replicates for each of 5 Ctrl-MSN and 7 HD-MSN samples). c, Pairwise comparison of HD-MSNs and Ctrl-MSNs shows many distinct genes differentially expressed in HD-MSNs (FDR < 0.01, log(fold change) > 0.5, EdgeR). Mapped reads are displayed in log2(counts per million) (log2CPM) and fold change in HD-MSN expression is displayed as a color gradient, with upregulated genes shown in gray and downregulated genes in blue (averages of 2 technical replicates for 5 Ctrl-MSN and 7 HD-MSN samples). d, Gene ontology analysis of DEGs with MetaCore reveals many critical cellular processes, including a significant enrichment of genes associated with HD. Further analysis of these HD-related genes points to dysfunction in neurophysiological processes (n = 1,127 DEGs from c based on the analysis of 5 Ctrl-MSN and 7 HD-MSN samples); ACM: cholinergic receptor, muscarinin.

Mutant HTT aggregates in MSNs directly converted from HD-fibroblasts

Because polyglutamine expansion in HTT leads to the formation of insoluble structures of aggregated mHTT, or inclusion bodies3, we performed immunocytochemistry and ultrastructural and biochemical analyses to assess whether HD-MSNs would display mHTT inclusions. Notably, HD-MSNs exhibited mHTT aggregates, in contrast to their corresponding fibroblasts or Ctrl-MSNs (Fig. 4a–c). Non-reprogrammed HD-fibroblasts were devoid of detectable aggregates even upon cellular insults, including the induction of oxidative stress with hydrogen peroxide or cellular senescence by serial passaging (Supplementary Fig. 5a,b). Furthermore, mimicking reprogramming using CDM factors with a nonspecific microRNA, a condition previously shown to be ineffective for neuronal conversion17, did not lead to detectable mHTT aggregates (Supplementary Fig. 5c), demonstrating the specificity of the aggregation phenotype to successfully reprogrammed neurons. Cytoplasmic (Fig. 4c,d) and intranuclear (Fig. 4d) mHTT aggregates were evident in HD-MSNs reprogrammed from all HD patient samples as early as PID 14 when analyzed with antibodies (MW8 and EM48) that selectively recognize aggregated mHTT inclusion bodies colocalized with ubiquitin (Fig. 4f and Supplementary Fig. 5d–f). HD models that have been engineered to overexpress mHTT with a large number of CAG repeats report high levels of cells with inclusions. However, studies analyzing postmortem HD patient brains found that only up to 10% of MSNs showed inclusion bodies33, similar to the levels we detected in HD-MSNs (Fig. 4e). Examining the ultrastructure of immunogold-labeled mHTT inclusions by transmission electron microscopy (TEM) in converted MSNs (HD.40 and Ctrl.19) plated in microdishes (Fig. 4g) revealed the presence of nanogold particles labeling mHTT aggregates, as well as structures of fibrillar morphology, found only in HD-MSNs (Fig. 4h and Supplementary Fig. 6a,d). We further confirmed the expression of mHTT by immunoblot analysis at PID 28 in three HD-MSN samples (HD.42, HD.46 and HD.47; Supplementary Fig. 7) using the monoclonal antibody MW1,which was shown to specifically detect the polyglutamine domain of HTT exon 1 while showing no detectable binding to normal HTT34. Additionally, insoluble aggregated HTT could be detected in all reprogrammed HD samples, but not in Ctrl-MSNs (Ctrl.16 MSNs) using the HTT aggregate-specific monoclonal antibody MW834 (Supplementary Fig. 7). In our TEM studies, we found immunogold particles compartmentalized inside autophagosomes, cytosolic double-membrane vesicles involved in macroautophagy (Fig. 4i). This suggests that autophagic vacuoles can recognize and trap cytosolic mHTT inclusions in HD-MSNs harboring low CAG repeats. In fact, we observed colocalization of mHTT and LC3-II, a well-established marker of autophagosomes, in HD-MSNs reprogrammed from three independent HD lines, which is similar to previously reported findings in a HD mouse model35 (Fig. 4i and Supplementary Fig. 6f).

Fig. 4: Mutant HTT aggregates in HD-MSNs.
Fig. 4

ac, HTT aggregation is not present in HD-fibroblasts (FBs) or Ctrl-MSNs but is detectable in HD-MSNs. Analysis at PID 30 by EM48 antibody. Boxed region is magnified at right. These experiments were repeated independently >3 times with similar results. d, HD-MSNs contain both cytoplasmic (arrowheads) and intranuclear (arrows) inclusions, as detected by EM48 antibody at PID 30. Boxed region is magnified at right. e, Quantification of percentage of Ctrl- and HD-MSNs displaying inclusion bodies (IBs) by MW8 antibody at PID 30 (mean ± s.e.m.; *P = 0.019 by two-tailed Student’s t-test; t = 3.787, d.f. = 4; averages of 400 cells from 3 independent HD patients and controls). f, MAP2-positive HD-MSNs exhibit colocalization of EM48 (red) with ubiquitin (Ub; green). Boxed region is magnified at right. Experiment has been repeated independently once. g,h, HD-MSNs on μ-dishes with squares 500 μm on a side immunolabeled for TUBB3 and HTT by MW8 conjugated to fluoro-nanogold reveal intranuclear inclusions by TEM; N, nucleus. Dense labeling by gold particles within the nucleus of HD-MSNs is marked by a red box. i, Left, ultrastructural analysis also detected mutant HTT inside double-membrane vesicles (arrowhead) resembling autophagosomes. Right, immunostaining with the autophagosome marker LC3-II confirmed colocalization with HTT (MW8) at PID 30. Experiment was repeated with 3 more pairs of HD- and Ctrl-MSNs, and was performed independently twice. Magnified images from dotted red-outlined regions are shown in red frames. Scale bars: 10 μm, except in h, where they are 2 μm, and left panel of i, 100 nm.

Induction of pluripotency alters mHTT aggregation propensity

Because our findings contrasted with previous studies that report the lack of mHTT aggregates in iPSC-derived neurons from HD patients, we tested whether altering the cellular state of adult HD-fibroblasts to an embryonic-like stage18 would affect the aggregation propensity of mHTT in HD-MSNs. We derived HD-iPSCs from adult HD fibroblasts and differentiated these iPSCs back into fibroblasts to generate human embryonic fibroblasts (HEFs)18 (Fig. 5a and Supplementary Fig. 8a). Briefly, HD.40 fibroblasts were transduced with Sendai viral vectors to express the four reprogramming factors (OCT4, SOX2, KLF4 and c-MYC), which resulted in integration-free iPSCs that expressed markers of pluripotency and retained a normal karyotype and the same number of CAG repeats (Supplementary Fig. 8b–e). iPSC-derived HD-HEFs expressed fibroblast markers fibronectin and vimentin (Fig. 5b). We confirmed that HD-HEFs exhibited cellular markers associated with the re-induction of an embryonic state, including high expression of the nuclear lamina-associated protein 2α (LAP2α)18 (Supplementary Fig. 8f). Upon direct conversion of HD-HEFs to MSNs (human embryonic MSNs, heMSNs), little to no aggregated mHTT was detectable in HD-heMSNs at PID 21 (Fig. 5c,d). We further verified these results using another, independent iPSC line from a symptomatic 37-year-old HD patient with 50 CAG repeats in HTT (HD.50; Supplementary Fig. 8g,h). We then investigated differences between adult MSNs and heMSNs in mHTT aggregation propensity to elucidate the contribution of aging to protein aggregation in HD. We began by ectopically expressing EGFP fused to 23 or 74 polyglutamine repeats (GFP-23Q or GFP-74Q) in either HD adult fibroblasts or HD-HEFs to track protein aggregation by live imaging (Fig. 5e). While the expression of GFP-23Q stayed diffuse, we observed a rapid rate of GFP-74Q aggregate formation (Fig. 5e) in adult fibroblasts, with over 70% of HD-fibroblasts displaying GFP-74Q aggregates and increased fluorescence density indicating the formation of inclusion bodies after 24 h, whereas in HEFs aggregates were only visible in fewer than 10% of cells at each time point analyzed (Fig. 5f). Given that aggregates can be induced by treatment with proteasome inhibitors in iPSC-derived MSNs12, we postulated that a higher proteasome activity in HEFs likely prevented GFP-74Q from forming aggregates. We performed qPCR analysis for 17 genes associated with the ubiquitin–proteasome system (UPS), the main protein quality control machinery in the cell, in HD adult fibroblasts and two lines of HEFs differentiated from two independent HD-iPSC clones. We found eight genes consistently upregulated in HEFs (Supplementary Fig. 9). The upregulated UPS genes included the heat-shock transcription factor HSF1, a protein that regulates the expression of genes involved in protein homeostasis36 and is reduced in the striatum of HD patients37. To directly test whether proteasome activity was preventing the formation of inclusions in HEFs, we treated GFP-74Q-expressing HEFs with the proteasome inhibitor lactacystin. Lactacystin-treated HEFs had significantly more cells bearing inclusions than DMSO-treated HEFs (Fig. 5g).

Fig. 5: Proteostasis collapses in directly reprogrammed MSNs but remains functional in cells derived from iPSCs.
Fig. 5

a, Deriving HD-MSNs from adult fibroblasts (HD-FB) versus embryonic fibroblasts (HD-HEFs). heMSNs: MSNs reprogrammed from HEFs. OSKM: Oct3/4, Sox2, Klf4, c-Myc. b, Vimentin (VIM)- and fibronectin (FN)-positive HD.40-HEFs and HD.40-FBs. c, HD.50-MSNs and HD.50-heMSNs analyzed for neuronal and MSN markers and mutant HTT aggregates (MW8). Boxed region is magnified at right and shown within red-framed panel. Experiment has been repeated with 1 additional line and independently 3 times. d, Quantification of inclusion bodies (IBs) (average of 400 cells from 3 biological replicates; one-way ANOVA (F(2,6) = 18.67, P = 0.0027) with post hoc Tukey’s test (from left, **P = 0.0039 and 0.0051; n.s. P = 0.95)). Scale bars in b, 100 μm; in c, 10 μm. e, Live imaging in HD.40-FB and HD.40-HEFs expressing 23 or 74 polyglutamine repeats fused to GFP; scale bar: 50 μm. Arrowheads mark IBs. Experiment has been repeated independently 3 times. f, Quantification of IBs after transfection (average of 30 cells in each group for 3 independent experiments; one-way ANOVA (F(5,12) = 228.7, P = 1.8 × 10–11) with post hoc Tukey’s test (from left, ***P = 2.3 × 10–8, 2.7 × 10–7, 3.2 × 10–10 and 5.2 × 10–10; n.s. P = 0.129 and 0.99)). g, Treatment of HEFs with 5 μM lactacystin induces IBs (average of 30 cells from 3 independent experiments; two-tailed Student’s t-test; P = 7.2 × 10–5 d.f. = 4). h,i, 20 S proteasome activity measured by cleavage of fluorogenic peptide LLVY-AMC for 1 h (n = 3 samples from each group; one-way ANOVA (F(4,10) = 282.3, P = 3.1 × 10–10) with post hoc Tukey’s test (from left, ***P = 5.2 × 10–7, 5.4 × 10–7, 9.8 × 10–8 and 6.3 × 10–6; n.s. P = 0.99)). j, Microarray analysis of MSNs from neonatal or older healthy individuals shows reduction in ubiquitin–proteasome system (UPS) gene expression with age. Mean ± s.e.m.; n.s., not significant.

Although iPSCs have been previously shown to possess higher proteasome activities than their originating fibroblasts, differentiation of iPSCs into neurons also was shown to reduce proteasome activity38. To determine whether changes in the proteasome activity could account for the detection of mHTT aggregates in MSNs but not in heMSNs, we assessed the functional activity of the proteasome in converted MSNs with the fluorogenic peptide LLVY-AMC. We discovered that proteostasis was collapsed in HD-MSNs in comparison to heMSNs, which retained the proteasome activity comparable to that in iPSCs (Fig. 5h,i). Aggregation propensity was not dependent on HTT mutation, as evidenced by similar levels of proteostasis between HD and control samples (Fig. 5f,i). To explore the age-dependent collapse in proteostasis, we analyzed the expression of 300 UPS-associated genes in a previously published dataset generated by the transcriptional profiling of MSNs converted from fibroblasts of young (3 d, 5 months and 1 year old) or old (aged 90, 92 and 92 years old) donors20. By comparing gene expression in young versus old fibroblasts and MSNs, we determined that fibroblasts did not display drastic changes in the expression of UPS-related genes with age, but MSNs from older individuals showed a dramatic increase in the number of downregulated UPS-related genes (Fig. 5j and Supplementary Fig. 9). In fact, gene ontology analysis of downregulated genes in old MSNs showed significant enrichment for the positive regulation of proteolysis (P = 2.01 × 10−2). These data suggest that the proteostasis collapse in MSNs, but not in originating fibroblasts or iPSC-derived neurons, depends on the cellular age of converted neurons.

mHTT-mediated DNA damage and spontaneous degeneration

Because aging contributes to the onset of HD, we tested whether direct conversion would allow detection of spontaneous neuronal death in HD-MSNs. We first measured DNA damage in HD-MSNs converted from three independent HD patients in comparison to starting fibroblasts and Ctrl-MSNs. At PID 30, HD-MSNs exhibited increased oxidative DNA damage as determined by levels of 8-hydroxy-2′-deoxyguanosine (8-OHdG) (Fig. 6a,b), as well as increased double-stranded breaks as assessed by the presence of nuclear 53BP1-positive foci (Fig. 6c,d). Analysis by single-cell gel electrophoresis that visualizes the migration of broken DNA strands from individual agarose-embedded cells (also known as the comet assay) showed a marked increase in comet tail lengths in comparison to Ctrl-MSNs at PID 30 while no significant difference was detected between HD and control fibroblasts (Fig. 6e,f). Next we quantified spontaneous cell death in three controlled pairs of HD- and Ctrl-MSNs using SYTOX green, a nucleic acid stain impermeable to live cells, at multiple time-points during reprogramming (Fig. 6g,h). Cell death levels were comparable at PID 30, but increased drastically for HD-MSNs in relation to their controls at PID 35 and 40 (Fig. 6h), further evidenced by a stark reduction of DARPP-32-positive HD-MSNs (Supplementary Fig. 10). The detected DNA damage depended on HTT, as AAV-shRNA-mediated reduction of HTT significantly reduced 8-OHdG levels and number of 53BP1 foci in HD-MSNs (Fig. 6i). Given that the neuronal death of HD-MSNs was preceded by extensive DNA damage, we tested whether HD-MSN cell death would be amenable to pharmacological intervention by treating HD-MSNs with KU60019, an inhibitor of ataxia-telangiectasia mutated (ATM) kinase. ATM is a central regulator of the DNA damage response activated upon DNA damage or oxidative stress to induce apoptosis, and KU60019 has been previously reported to reduce mHTT-induced cell death39. Consistent with these findings, we found that the treatment of HD-MSNs with 0.5 μM KU60019 significantly reduced levels of spontaneous and stress-induced neuronal death in HD-MSNs (Supplementary Fig. 10).

Fig. 6: DNA damage and neurodegeneration in HD-MSNs.
Fig. 6

a,b, HD-MSNs show increased oxidative DNA damage by 8-OHdG immunostaining (one-way ANOVA (F(3,8) = 13.5, P = 0.0016) with Tukey’s test (*P = 0.016, n.s. = 0.96); averages from 70 cells from 3 independent samples per group). c,d, HD-MSNs show increased doubled-stranded breaks detected by 53BP1 immunostaining (one-way ANOVA (F(3,8) = 20.68, P = 0.0004) with Tukey’s test (**P = 0.0026, n.s. = 0.85); averages from 100 cells from 3 independent HD and control lines). e,f, Comet assay detected significantly more double-stranded DNA breaks (one-way ANOVA (F(3,8) = 7.329, P = 0.0111) with Tukey’s test (*P = 0.030, n.s. P = 0.99) in HD-MSNs; averages from 20 cells from 3 independent samples per group). g, Representative images of SYTOX staining. h, Quantification of SYTOX-positive cells as a fraction of Hoechst-positive (one-way ANOVA (F(7,16) = 36.71, P = 1 × 10–8), with Tukey’s test (*P = 0.026 and **P = 0.0013, n.s. P = 0.99); averages of 6,000 cells from 3 independent samples per group and time point). Solid lines represent the average while each line is shown separately as a dotted line. i, AAV-mediated shRNA knockdown of HTT at PID 14 in HD-MSNs attenuates DNA damage at PID 35; AAV nonspecific (ns) shRNA used as control (8-OHdG: n = 50 cells per group. One-way ANOVA (F(3,196) = 16.46, P = 1.3 × 10–9) with Tukey’s test (from left, ***P = 4.4 × 10–7 and 4.9 × 10–6, n.s. P = 0.90 and 0.95); 53BP1: averages of 100 cells per group from 3 independent experiments. One-way ANOVA (F(3,8) = 35.1, P = 5.9 × 10–5) with Tukey’s test (from left, ***P = 1.6 × 10–4 and 3.0 × 10–4, n.s. P = 0.80 and 0.90)). j, Representative RNA-seq tracks for SP9. Experiment was done once with 7 HD-MSN samples and 5 controls. k, Validation by qPCR with SP9-specific primers (two-tailed Student’s t-test; *P = 0.027, t = 2.702, d.f. = 8; n = 5 independent HD and control lines). l, Restoring expression of SP9 by lentiviral transduction at PID 14 rescues cell death phenotype at PID 35. Quantification of SYTOX-positive cells as a percentage of Hoechst-positive (one-way ANOVA (F(3,8 = 9.792, P = 0.0047) with Tukey’s test (from left, **P = 0.009 and 0.008, n.s. P = 0.99); averages of 1,000 cells from 3 independent samples per group). af, PID 30; il, PID 35; j PID 32. al, ***P < 0.001; **P < 0.01; *P < 0.05; n.s., not significant. Scale bars in a and e, 100 μm; in c, 10 μm; in g, 500 μm. Mean ± s.e.m.

We also discovered that the neuronal death seen in HD-MSNs was responsive to genetic perturbations. For instance, we found SP9, a transcription factor necessary for the maintenance and survival of MSNs32, to be significantly downregulated in HD-MSNs by RNA-seq analysis (Fig. 6j) and further validated it by qPCR in five independent HD-MSN samples (Fig. 6k). We then cloned the cDNA of SP9 downstream of the ubiquitous EF1α promoter in a lentiviral vector to allow the consistent expression of SP9 in HD-MSNs. At PID 14 of neuronal conversion, three HD-MSN (HD.40, HD.42 and HD.46) and three Ctrl-MSN (Ctrl.16, Ctrl.17b and Ctrl.19) samples were transduced with lentivirus carrying the SP9 cDNA construct, cultured until PID 35, and then assayed for cell death with SYTOX green. We found that restoring SP9 expression in HD-MSNs reduced cell death to levels indistinguishable from those of controls (Fig. 6l). Although loss of SP9 has been previously shown to lead to apoptosis of MSNs in mice32, further studies are needed to probe the neuroprotective mechanism of this transcription factor and its potential role in HD pathogenesis. Our results show that directly converted HD-MSNs could potentially serve as a useful platform for identifying pharmacological and genetic factors that have therapeutic potential for treating HD.

Mitochondrial dysfunction, oxidative stress and metabolic deficits in HD-MSNs

Ultrastructural analysis in HD-MSNs and Ctrl-MSNs (HD.40 and Ctrl.19) revealed HD-MSNs to be enriched with lipofuscin granules, aging pigments that accumulate due to incomplete lysosomal degradation of damaged mitochondria, which are commonly detected in the brains of HD patients35,40 (Supplementary Fig. 6b,c). HD-MSNs also exhibited high levels of mitophagy, a selective degradation of dysfunctional mitochondria typical of apoptotic cells41 (Supplementary Fig. 6e). HD-MSNs further showed the accumulation of cytoplasmic lipid droplets, which are known to be caused by oxidative stress and mitochondrial dysfunction42 (Supplementary Fig. 6e). To gain insight into the mitochondrial and metabolic dysfunction present in HD-MSNs, we reprogrammed six lines (HD.42, HD.46, HD.47, Ctrl. 19, Ctrl.20, Ctrl.17c and Ctrl. 18b; Supplementary Fig. 11) to quantify mitochondrial functions. We first determined, using the mitochondrial indicator MitoTracker Red, that the total pool of mitochondria was unchanged between HD- and Ctrl-MSNs (Fig. 7a). We next assessed changes in the mitochondrial membrane potential with TMRE, an indicator of active and polarized mitochondria, and found significantly lower levels of TMRE signal in HD-MSNs, indicating decreased membrane potential of mitochondria (Fig. 7b). Increased production of reactive oxygen species by mitochondria is thought to be a major cause of oxidative stress in HD and a critical component in the progression of the disease43. Live imaging of HD-MSNs with the superoxide indicator MitoSOX Red revealed significantly higher levels of reactive oxygen species in HD-MSNs (Fig. 7c). HD-MSNs displayed significantly larger lipid droplets than controls as measured by the lipid dye BODIPY 498/503 (Fig. 7d). Since our results indicated impaired mitochondrial health, we measured levels of mitophagy in HD-MSNs (Supplementary Fig. 11a). Converted MSNs were labeled with MitoTracker and immunostained for the autophagosome marker LC3-II for colocalization analysis. Two out of three HD-MSNs derived from independent patients showed higher cytoplasmic LC3-II than controls, although the difference was not statistically significant (Supplementary Fig. 11b). However, we found a greater percentage of mitochondria and autophagosome colocalization in HD-MSNs (Supplementary Fig. 11c). Collectively, these results point to substantial mitochondrial dysfunction in HD-MSNs.

Fig. 7: Mitochondrial and metabolic dysfunction in HD-MSNs.
Fig. 7

a, MitoTracker Red staining shows that the total pool of mitochondria is unchanged between Ctrl- and HD-MSNs (two-tailed Student’s t-test; P = 0.92 t = 0.1034 d.f. = 4; averages of 100 cells from 3 independent HD and control lines). b, Live imaging of active mitochondria by TMRE (tetramethylrhodamine ethyl ester) reveals significant loss of mitochondrial membrane potential in HD-MSNs (two-tailed Student’s t-test; P = 0.0052 t = 5.54 d.f. = 4; averages of 60 cells from 3 independent HD and control lines). c, Mitochondrial superoxide indicator MitoSOX Red shows increased superoxide production in HD-MSNs (two-tailed Student’s t-test; P = 0.0007 t = 9.384 d.f. = 4; averages of 100 cells from 3 independent HD and control lines). d, Accumulation of lipid droplets in HD-MSNs, visualized by BODIPY 493/503 dye (two-tailed Student’s t-test; P = 0.0318 t = 3.237 d.f. = 4; averages of 100 cells from 3 independent HD and control lines). ***P < 0.001; **P < 0.01; *P < 0.05; n.s., not significant. Scale bars in ac, 50 μm; in d, 5 μm. Mean ± s.e.m.

Differential vulnerability of neuronal subtypes to mHTT toxicity

Although HTT is ubiquitously expressed throughout the brain, mHTT leads to selective degeneration of MSNs and, to a lesser extent, cortical neurons as the disease progresses44. Human postmortem studies have shown that, at a stage when neuronal loss is low in the cortex but high in the striatum, mHTT aggregates are more common in the cortex than in the striatum33. We hypothesized that conversion of HD fibroblasts to cortical neurons (HD-CNs) could model the selective vulnerability of HD-MSNs to neurodegeneration. We transduced control and HD-patient fibroblasts either with miR-9/9*-124-CDM or with miR-9/9*-124 in conjunction with NeuroD2, ASCL1 and MYT1L (DAM) (miR-9/9*-124-DAM), a transcription factor cocktail shown to guide the neuronal conversion to cortical neurons45 (Supplementary Fig. 12a–c). Surprisingly, HD-CNs exhibited lower levels of DNA damage (Supplementary Fig. 12d,e) and cell death than HD-MSNs (Supplementary Fig. 12f) but a higher level of mHTT aggregation, (Supplementary Fig. 12g), suggesting that cellular properties intrinsic to MSNs render them differentially vulnerable to neurodegeneration.

Manifestation of HD cellular phenotypes is dependent on patient age

The maintenance of aging signatures upon neuronal conversion has long been postulated to be an important advantage of using directly converted patient neurons to model late-onset diseases. However, no studies have provided empirical evidence that age information stored in a donor’s somatic cells contributes to the manifestation of disease-related phenotypes in converted neurons. Even though our findings from HD-heMSNs were insightful (Fig. 5), to further evaluate the significance of cellular age in HD phenotype manifestation in HD-MSNs we investigated the properties of MSNs reprogrammed from HD-fibroblasts sampled before disease onset. We acquired six fibroblast lines from presymptomatic HD patients (pre-HD), sampled 13 to 17 years before the onset of clinical symptoms, with CAG tract sizes of 42–49 repeats (Supplementary Table 1). All six pre-HD fibroblasts were reprogrammed using miR-9/9*-124-CDM to generate MSNs (pre-HD-MSNs), alongside fibroblasts from three controls and three symptomatic HD patients (Fig. 8a,b). Pre-HD-MSNs were less vulnerable to mHTT-induced toxicity at PID 35, with lower levels of cell death and oxidative DNA damage (Fig. 8c,d). Notably, pre-HD-MSNs still contained mHTT aggregates at a level similar to that in symptomatic HD-MSNs (Fig. 8c,d). These results are noteworthy as they directly show that the age-dependent onset of HD can be modeled with directly converted HD-MSNs, which provide a human cellular model for examining the contributions of age and genetic factors to disease onset.

Fig. 8: HD-MSNs reprogrammed from presymptomatic patients are less vulnerable to mHTT-induced toxicity.
Fig. 8

MSNs reprogrammed from six presymptomatic HD patients with 42–49 CAG repeats collected at least 13 years before disease onset are phenotypically normal despite bearing similar levels of mHTT inclusions to symptomatic HD-MSNs. a, Conversion of preclinical HD-fibroblasts by miR-9/9*-124-CDM (pre-HD MSNs). b, All six primary fibroblasts samples from preclinical patients tested were successfully reprogrammed by miR-9/9*-124-CDM as shown by TUBB3 staining at PID 30. This experiment was repeated independently 2 times. c,d, Representative images and quantification of Ctrl-, pre-HD- and HD-MSNs at PID 35 assayed for cell death with SYTOX green (averages of 1,000 cells per group; one-way ANOVA (F(2,9) = 9.433, P = 0.0062) with post hoc Tukey’s test (*P = 0.0115 and **P = 0.0084, n.s. P = 0.69)), oxidative DNA damage with 8-OHdG (one-way ANOVA (F(2,9) = 21.8, P = 0.0004) with post hoc Tukey’s test (from left, ***P = 0.0006 and ***P = 0.0007, n.s. P = 0.54); averages of 100 cells per group) and mutant HTT inclusion bodies (IBs) with EM48 (averages of 100 cells per group; one-way ANOVA (F(2,9) = 9.911, P = 0.0053) with post hoc Tukey’s test (*P = 0.0138 and **P = 0.0058, n.s. P = 0.46)). *P < 0.001; **P < 0.01; *P < 0.05; n.s., not significant; averages from 3 independent control lines, 6 independent pre-HD lines and 3 independent HD lines. Scale bars, 100 μm except in right column of c, where they are 20 μm. Mean ± s.e.m.


Since neurological disorders often affect distinct neuronal subpopulations, studies using generic protocols to induce unrestricted neuronal fates are likely only capturing a partial snapshot of factors that contribute to disease onset and progression. The direct conversion of fibroblasts of symptomatic HD patients generates MSNs that retain their cellular age status. To test the involvement of cellular age in the manifestation of disease-relevant phenotypes in HD-MSNs, we applied two distinct cellular reprogramming approaches that diverge in the maintenance of age signatures from donor cells. The induction of pluripotency has been well documented to erase age marks and reset the age of donor cells to an embryonic state18,19 while direct neuronal conversion has been shown to maintain age-related transcriptional, cellular and epigenetic signatures20,21. In this study, we demonstrate that age retention through direct neuronal conversion is crucial for modeling HD, exemplified by the detection of mHTT aggregates, a direct reflection of the age-associated decline in proteostasis that is absent in iPSC-derived neurons.

We found that mHTT-induced DNA damage contributed to the spontaneous degeneration of HD-MSNs, as treating the cells with an inhibitor of the DNA damage response protein ATM rescued the cell death phenotype, similarly to iPSC-derived neurons undergoing degeneration upon BDNF withdrawal39. We also provide evidence that controlling the specificity of MSN fate during neuronal conversion is critical for the manifestation of disease phenotypes, as altering the terminal neuronal fate of HD-fibroblasts to CNs drastically reduced the levels of DNA damage and cell death, despite the persistence of mHTT aggregates. Although cortical neurons are not completely spared in HD, they degenerate at a much slower rate during disease progression than MSNs, even though mHTT aggregates are more common in the cortex than in the striatum33. Accordingly, postmortem studies in HD patients have also shown significantly less DNA damage in the cortex than in the striatum46. The cellular properties that render MSNs selectively vulnerable to mHTT-induced toxicity are poorly understood, and subtype-specific neuronal conversion approaches may offer an experimental means to examine neuroprotective attributes in discrete neuronal subtypes. The ability to model the progression of HD in an age-dependent manner provides a patient-based platform for applications in human disease modeling and a means to gain mechanistic insight into the pathogenesis of HD.


Plasmids and lentiviral preparation

The construction of all plasmids used in this study has been previously described17,47, and they are publicly available at Addgene as pTight-9-124-BclxL (#60857), rtTA-N144 (#66810), pmCTIP2-N106 (#66808), phMYT1L-N174 (#66809), phDLX1-N174 (#66859), phDLX2-N174 (#66860), with the exception of hSP9-N174, which was cloned in-house and not previously published. Polyglutamine fusion protein constructs pEGFP-23Q and pEGFP-74Q were generated by David Rubinsztein’s lab and acquired from Addgene (#40261 and #40262), and transfected into human fibroblasts. Lentiviral production was carried out separately for each plasmid, but they were transduced together as a single cocktail as previously described47. Briefly, supernatant was collected 60–70 h after transfection of Lenti-X 293LE cells (Clontech) with each plasmid, in addition to psPAX2 and pMD2.G (Addgene), using polyethyleneimine (Polysciences). Collected lentiviruses were filtered through 0.45 µm PES membranes and concentrated at 70,000 g for 2 h at 4 °C. Viral pellets were resuspended in Dulbecco’s phosphate-buffered saline (DPBS, Gibco) and stored at –80 °C until transduction.

Cell lines and culture

Adult dermal fibroblasts from symptomatic HD patients (Coriell NINDS and NIGMS Repositories: ND33947, ND30013, GM02173, GM09197, GM04230, GM04194, GM04196, GM04198, GM02147, GM04687), presymptomatic HD patients (GM04717, GM04861, GM04855, GM04831, GM04853, GM04829) and healthy controls (Coriell NINDS, NIA and NIGMS Repositories: ND34769, AG04148, GM02171, GM05879, AG16409, AG11357, AG11483, GM05879, AG16409, AGO5265, AG09599, AG04062, AG04060) were acquired from the Coriell Institute for Medical Research. One additional healthy control adult dermal fibroblast line was acquired from the Washington University School of Medicine iPSC Core Facility (#F09-238). The International Cell Line Authentication Committee (ICLAC) lists none of these primary cells as commonly misidentified cell lines. In regards to deidentified skin fibroblasts samples and induced pluripotent stem cells (iPSCs) acquired from the Coriell Institute for Medical Research, we do not have access to the master list to reidentify subjects. This activity is not considered to meet federal definitions under the jurisdiction of an institutional review board, and is thus exempt from the definition of human subject. All fibroblasts were cultured in fibroblast medium (FM): Dulbecco’s Modified Eagle Medium (DMEM) with high glucose containing 15% FBS (Gibco), 0.01% β-mercaptoethanol (BME), 1% nonessential amino acids (NEAA), 1% sodium pyruvate, 1% GlutaMAX, 1% 1 M HEPES buffer solution and 1% penicillin/streptomycin solution (all from Invitrogen). We routinely check all our cell cultures and confirm them to be free of mycoplasma contamination. Our step-by-step MSN conversion protocol has been previously published47. Briefly, the lentiviral cocktail of rtTA, pTight-9-124-BclxL, CTIP2, MYT1L, DLX1 and DLX2 was added to fibroblasts for 16 h, then cells were washed and fed with FM containing 1 μg/mL doxycycline (DOX). Cells were fed at post-induction day (PID) 3 with FM + puromycin (3 μg/mL) + blasticidin (3 μg/mL) + DOX and replated at PID 5 onto polyornithine/fibronectin/laminin-coated glass coverslips in FM + DOX. Medium was switched on PID 6 to Reprogramming Neuronal Medium (RNM): Neuronal Medium (NM; ScienCell Research Laboratories) with 200 μM dibutyl cyclic AMP, 1 mM valproic acid, 10 ng/mL BDNF, 10 ng/mL NT-3 and 1 μM retinoic acid, supplemented with DOX. Half-volume medium changes with RNM were performed every 4 d with addition of DOX every 2 d thereafter until PID 30–35. Addition of puromycin and blasticidin was terminated after PID 14.

DNA extraction and CAG sizing

Fibroblasts were expanded in culture, collected by cell scraper, pelleted, and lysed for DNA extraction and ethanol precipitation following typical lab procedures with proteinase K (Roche). DNA samples were CAG sized by Laragen, Inc (Culver City, CA).


Cells were fixed using 4% paraformaldehyde (PFA) for 20 min and permeabilized using 0.2% Triton-X solution for 10 min following three phosphate-buffered saline (PBS) washes. Cells were blocked for 1 h at room temperature using 1% normal goat serum (NGS) and 5% bovine serum albumin (BSA) in PBS. Primary antibodies were added in the presence of blocking buffer overnight at 4 °C. Secondary antibodies were added following three PBS washes at 1:1,000 in blocking buffer at room temperature for 1 h. The following primary antibodies were used for the immunofluorescence studies: mouse anti-MAP2 (Sigma-Aldrich #M9942 clone HM2, 1:750), rabbit anti-β-III tubulin (BioLegend #MMS-435P, 1:2,000), chicken anti-NeuN (Aves, #NUN 1:500), rabbit anti-GABA (Sigma #A2052, 1:2,000), mouse anti-GABA (Sigma #A0310 clone GB-69, 1:500), rabbit anti-DARPP32 (Santa Cruz Biotechnology #sc-11365, 1:400), rabbit anti-S100A4 (FSP1) (Abcam #124805, 1:200), mouse anti-HTT (mEM48, Millipore #MAB5374, 1:50) (MW8, Developmental Studies Hybridoma Bank, 1:100), rabbit anti-ubiquitin (Abcam #ab7780, 1:50), mouse anti-vimentin (Sigma-Aldrich, #V6630 1:500), rabbit anti-fibronectin (Sigma-Aldrich, #F3648 1:500), mouse anti-phospho-histone H2A.X (Millipore #05-636-I, 1:200), rabbit anti-lap2-α (Abcam #ab5162, 1:500), rabbit anti-53BP1 (Abcam #ab21083, 1:200), mouse anti-8OHdG (Santa Cruz Biotechnology #sc-139586, 1:1,000), rabbit anti-LC3B (Sigma-Aldrich # L7543, 1:1,000). The secondary antibodies were goat anti-rabbit or mouse IgG conjugated with Alexa-488, Alexa-594 or Alexa-647 (Invitrogen). Images were captured using a Leica SP5X white light laser confocal system with Leica Application Suite (LAS) Advanced Fluorescence All staining quantification was performed by counting number of positive-stained cells over DAPI signal. Antibodies were validated by staining fibroblasts as negative controls, and they exhibited low background.

Immunoblot analysis

At PID 28, cells were lysed in SDS lysis buffer (1 M Tris-HCl pH 6.8, 2% SDS, 30% glycerol) supplemented with protease inhibitors (Roche, #04693132001). The concentrations of whole-cell lysates were measured using the Pierce BCA protein assay kit (Thermo Scientific, #23227). Equal amounts of whole cell lysates were resolved by SDS-PAGE and transferred to a nitrocellulose membrane (GE Healthcare Life Sciences, #10600006) using a transfer apparatus according to the manufacturer’s protocols (Bio-Rad). After incubation with 5% BSA in TBS containing 0.1% Tween-20 (TBST) for 30 min, the membrane was incubated with primary antibodies at 4 °C overnight: MW8 (Developmental Studies Hybridoma Bank, 1:500) and MW1 (Developmental Studies Hybridoma Bank, 1:500). Following incubation, membranes were incubated with a horseradish peroxidase–conjugated anti-mouse or anti-rabbit antibody for 1 h. Blots were developed with the ECL system (Thermo Scientific, #34080) according to the manufacturer’s protocols.

Mitochondrial assays

The cell-permeant mitochondrial indicator MitoTracker Red CMXRos (ThermoFisher Scientific #M7512) was added directly to live cells at final concentration of 50 nm in serum-free medium. After 20 min of incubation in 37 °C, cells were imaged with an epifluorescence microscope and then fixed and processed for immunostaining as described above. Analysis of colocalization of MitoTracker Red and LC3-II (Anti-LC3B antibody, Sigma-Aldrich # L7543) was performed using Metamorph bioimaging software after image acquisition using a Leica SP5X white light laser confocal system with Leica Application Suite (LAS). Mitochondrial membrane potential was assayed with the TMRE Mitochondrial Membrane Potential Assay Kit (Abcam #ab113852) following the manufacturer’s protocol. Briefly, TMRE was added to live cells at a final concentration of 20 nm in serum-free medium. After 15 min of incubation at 37 °C, coverslips were removed from medium and Vaseline was applied to edges of coverslips to create a rim for live mounting and microscopy and imaged using a Leica SP5X white light laser confocal system with Leica Application Suite (LAS). Lipid droplets were stained with BODIPY 493/503 (4,4-difluoro-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-indacene) (ThermoFisher Scientific #D3922) at a final concentration of 0.1 μm in serum-free medium. After 30 min of incubation in 37 °C, cells were imaged with an epifluorescence microscope and quantified with Leica Application Suite (LAS) quantification tools.


Whole-cell patch-clamp recordings were performed at PID 28–35 with miR-9/9*-124-CDM. At PID 14, cells undergoing reprogramming were transduced with pSYNAPSIN tRFP or GFP, and the next day they were trypsinized and plated together on top of rat primary neurons and glia isolated from perinatal pups, with the exception of recordings shown in Supplementary Fig. 3h, which were performed in monoculture in the absence of rat primary cells. Fluorescent reporter expression was visible within days and remained segregated for each population. Data were acquired using pCLAMP 10 software with MultiClamp 700B amplifier and Digidata 1550 digitizer (Molecular Devices). Electrode pipettes were pulled from borosilicate glass (World Precision Instruments) and typically ranged between 4 and 6 MΩ resistance. Solutions used to study intrinsic neuronal properties were the same as previously reported17. Postsynaptic potentials were detected spontaneously. Data were collected in Clampex and initially analyzed in Clampfit (Molecular Devices).

RNA extraction and gene expression profiling

Total RNA was extracted and isolated with TRIzol reagent (Thermo Fisher Scientific) according to manufacturer’s instructions. cDNA was generated from isolated RNA with Superscript III Reverse Transcriptase (Thermo Fisher Scientific) primed with random hexamers. qPCR was performed with the primer sets listed in Supplementary Table 3. For RNA-seq, reads were aligned to the human genome (assembly hg38) with STAR version 2.4.2a [23104886]. Gene counts were derived from the number of uniquely aligned unambiguous reads by Subread:featureCount [23558742], version 1.4.6, with GENCODE gene annotation (V23) [22955987]. All gene-level transcript counts were then imported into the R/Bioconductor package EdgeR [19910308] and TMM normalized to adjust for differences in library size. Genes not expressed in any sample were excluded from further analysis. The fits of the trended and tagwise dispersion estimates were then plotted to confirm proper fit of the observed mean-to-variance relationship, where the tagwise dispersions are equivalent to the biological coefficients of variation of each gene. Differentially expressed genes were then filtered for those having fold-changes (FC) > 1.5 together with false-discovery rate (FDR) adjusted P-values ≤ 0.05. Gene expression heat maps were generated using Z-scores for expression values of each gene among different samples (GENE-E Matrix Visualization and Analysis Platform, Broad Institute). MSN-specific genes were selected from previous studies that have profiled transcriptome profiles of isolated MSNs48. RNA-seq data are publicly available at GEO (accession code GSE84013).

Dead-cell staining

SYTOX green nucleic acid staining (Thermo Fisher Scientific) was performed following manufacturer’s suggestions, adapted as follows: a final concentration of 0.1 μM SYTOX green was added directly to the medium of live cells. In addition, Hoechst 33342 solution (Thermo Fisher Scientific) was added as a counterstain to label all nuclei at a final concentration of 1 μg/ml in culture medium. Samples were incubated for at least 10 min in 37 °C. Images were captured using a Leica DMI 400B inverted microscope with Leica Application Suite (LAS) Advanced Fluorescence. Three images were taken from random areas of each coverslip for at least three biological replicates per experiment. Quantification performed by counting number of SYTOX-positive cells over total Hoechst signal.

Comet assay

DNA damage was assessed by using the CometAssay reagent kit for single-cell gel electrophoresis assay (Trevigen, MD USA), following the recommended protocol for neutral conditions and adapting the gel electrophoresis methods for use in the Sub-Cell GT electrophoresis system (Bio-Rad, CA USA). Briefly, cells were collected from coverslips by treatment with 0.25% trypsin, pelleted, resuspended at 100,000 cells/ml in DPBS (Ca2+ and Mg2+ free; Thermo Fisher Scientific) and verified to be greater than 95% viable by trypan blue exclusion using an automated cell counter before continuing analysis. Approximately 5,000 cells were embedded in low-melting agarose, plated on slides and lysed overnight. The next day, electrophoresis was run at 30 V for 30 min in 1× TBE (National Diagnostics). Samples were fixed in 70% ethanol for 5 min, and slides were immersed in TE buffer pH 8.0 (Ambion) with SYBR green nucleic acid stain (10,000×, Thermo Fisher Scientific). Fluorescence images were captured using a Leica DMI 400B inverted microscope for scoring.

Generation of iPSCs and derivation of HEFs

iPSC lines used in this study were either directly acquired from the Coriell Institute for Medical Research NINDS Biorepository (#ND42235) or derived from adult dermal fibroblast acquired from the Coriell NINDS Biorepository (#ND33947) with the assistance of the Washington University School of Medicine Genome Engineering and iPSC Center (GEiC). For the generation of ND33947 iPSCs, fibroblasts were transduced with integration-free Sendai reprogramming vectors for Oct3/4, Sox2, Klf4 and c-Myc and characterized by the expression of the pluripotency markers Oct4, SSEA4, SOX2 and TRA-1-60 (PSC 4-Marker Immunocytochemistry Kit, Molecular Probes). Cytogenetic analysis was performed on twenty G-banded metaphase cells from iPSC line at passage 5, and all 20 cells demonstrated an apparently normal karyotype (Cell Line Genetics, Madison WI). In addition, an embryoid body formation assay confirmed the potential for acquisition of all three germ layers. iPSCs were expanded on ES-grade Matrigel (Corning)-coated plates cultured in mTeSR medium (Stemcell Technologies) or DMEM/F-12 with 20% KnockOut Serum Replacement, 1% GlutaMAX, 0.1 mM NEAA, 10 ng/mL fibroblast growth factor-basic (bFGF) and 55 μM BME. To differentiate iPSCs into human embryonic fibroblasts (HEFs), culture medium was replaced with DMEM plus 20% FBS without bFGF for at least three passages. HEFs were transduced and reprogrammed to MSNs following our established protocol previously reported in detail47.

Drug treatment

The ATM kinase inhibitor KU-60019 was obtained from Abcam (ab144817), solubilized in DMSO and directly added to the cell culture medium for a final concentration of 0.5 μM at 30 d after miR-9/9*-124 induction, and then cell death was assessed by SYTOX at PID 35. Controls were treated with the same volume of DMSO but no drug. At day 35, cells treated with DMSO or KU-60019 also were treated with 1 mM H2O2 for 3 h. SYTOX green and Hoechst stain were added as already described and imaged for scoring.

20 S proteasome activity assay

Adherent cells were dissociated with 0.25% trypsin, pelleted by centrifugation and washed in cold PBS twice. Cell pellets were then resuspended in chilled cell lysis buffer (50 mM HEPES (pH 7.5), 5 mM EDTA, 150 mM NaCl, 1% Triton X-100 and 2 mM ATP) and incubated on ice for 30 min, vortexing every 10 min. Cell lysates were then centrifuged at 15,000g for 15 min at 4 °C. Lysate was then transferred to a microcentrifuge tube, and 10 μl of each sample was used to determine protein concentration with a BCA protein assay kit (Thermo Scientific, Prod. #23227) following the manufacturer’s recommendations. Proteasome activity was assayed using 10 μg of each lysate with a 20 S proteasome activity assay kit (Millipore, APT280). Fluorescence intensity was measured every 5 min for 1 h with a microplate reader. Data were analyzed following previously reported methods38.

Electron microscopy

Cells cultured in gridded glass-bottom μ-dishes (Ibidi, Madison, WI) were fixed with EM grade 4% PFA + 0.05% glutaraldehyde (GA) (Electron Microscopy Sciences) in PBS with 2 mM CaCl2 at 37 °C for 5 min (min) then transferred to ice for 1 h. Samples were then incubated for 5 min in 50 mM glycine in PBS and permeabilized with 0.05% saponin with 1% BSA in PBS for 30 min. Cells were blocked with 1% BSA in PBS for 15 min and incubated with primary antibodies (mouse anti-HTT (MW8), 1:100, and rabbit anti-β-III tubulin BioLegend, 1:2,000) at room temperature for 2 h with gentle agitation. After washing in PBS-BSA three times for 10 min each, cells were incubated for an additional 2 h with Alexa Fluor 594 fluoro-nanogold secondary antibody (Nanoprobes, Yaphank, NY #7301) at a 1:250 dilution in PBS and 1% BSA at room temperature with gentle agitation while wrapped in foil. After washing in PBS three times for 10 min each, cells were fixed with 1% GA for 5 min and labeled with DAPI (1:10,000) for 5 min. After fluorescence imaging, the samples were rinsed twice in ultrapure water for 1 min each and then rinsed in 0.02 M citrate buffer (pH 4.8) three times for 5 min each. The fluoro-nanogold label was silver enhanced using HQ Silver (Nanoprobes, Yaphank, NY) for 9–11 min and the samples immediately rinsed with ultrapure water twice for 5 min each. The culture dishes were then rinsed in PBS buffer three times for 10 min each and subjected to a secondary fixation step for 1 h in 1% osmium tetroxide, 0.3% potassium ferrocyanide in PBS on ice. The samples were then washed in ultrapure water three times for 10 min each and then stained en bloc for 1 h with 2% aqueous uranyl acetate. After staining was complete, samples were briefly washed in ultrapure water, dehydrated in a graded ethanol series (50%, 70%, 90%, 100% twice) for 10 min in each step, and infiltrated with microwave assistance (Pelco BioWave Pro, Redding, CA) into LX112 resin. Samples were cured in an oven at 60 °C for 48 h. Once the resin was cured, the gridded glass coverslips were etched away with concentrated hydrofluoric acid and the exposed cells were excised with a jeweler’s saw and mounted onto blank resin blocks with epoxy, oriented in the coverslip growing plane. Sections 70 nm thick were then taken and imaged on a TEM (JEOL JEM 1400 Plus, Tokyo, Japan) at 80 KeV.


For all quantified data, multiple cells were counted from at least three biological replicates from multiple independent experiments or multiple lines. Statistical analyses were performed in GraphPad Prism using a two-tailed Student’s t-test or a one-way ANOVA followed by a post hoc Tukey’s test with P < 0.05 considered significant. Multiple comparisons were corrected with the Bonferroni or Holm-Sidak method as described in the figure legends. Studies were performed blindly and automated whenever possible with the aid of ImageJ cell counting tools, and multiple investigators confirmed quantification results. Data distribution was assumed to be normal, but this was not formally tested. Data in graphs are expressed as mean and error bars represent s.e.m. unless noted otherwise. Outliers were detected and excluded with Grubbs’ test for α levels of 0.05. In total for this study, only two data points were excluded, from the Supplementary Fig. 10c,d control DMSO group (9 total data points), following pre-established criteria. No statistical methods were used to predetermine sample sizes, but our sample sizes are similar to those reported in previous publications11,12,13. Data collection was not randomized, but was always done in parallel with controls. Allocation of primary patient cells acquired from Coriell Biorepository into the HD group was done randomly. Samples were allocated into the Control group by age- and sex-matching healthy controls with HD samples acquired and available through Coriell Biorepository.

Life Sciences Reporting Summary

Further information on experimental design is available in the Life Sciences Reporting Summary.

Data availability

Gene expression data generated for this study have been made public at NCBI’s Gene Expression Omnibus (GEO), accession GSE84013. All other data supporting the findings of this study are available from the corresponding author upon reasonable request.

A step-by-step protocol for this study is available at Nature Protocols47.

Additional information

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


  1. 1.

    Gusella, J. F. et al. A polymorphic DNA marker genetically linked to Huntington’s disease. Nature 306, 234–238 (1983).

  2. 2.

    The Huntington’s Disease Collaborative Research Group. A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington’s disease chromosomes. Cell 72, 971–983 (1993).

  3. 3.

    Ross, C. A. et al. Huntington disease: natural history, biomarkers and prospects for therapeutics. Nat. Rev. Neurol. 10, 204–216 (2014).

  4. 4.

    Kremer, B. et al. A worldwide study of the Huntington’s disease mutation. The sensitivity and specificity of measuring CAG repeats. N. Engl. J. Med. 330, 1401–1406 (1994).

  5. 5.

    Brinkman, R. R., Mezei, M. M., Theilmann, J., Almqvist, E. & Hayden, M. R. The likelihood of being affected with Huntington disease by a particular age, for a specific CAG size. Am. J. Hum. Genet. 60, 1202–1210 (1997).

  6. 6.

    Arrasate, M., Mitra, S., Schweitzer, E. S., Segal, M. R. & Finkbeiner, S. Inclusion body formation reduces levels of mutant huntingtin and the risk of neuronal death. Nature 431, 805–810 (2004).

  7. 7.

    Vonsattel, J. P. & DiFiglia, M. Huntington disease. J. Neuropathol. Exp. Neurol. 57, 369–384 (1998).

  8. 8.

    Arber, C. et al. Activin A directs striatal projection neuron differentiation of human pluripotent stem cells. Development 142, 1375–1386 (2015).

  9. 9.

    Camnasio, S. et al. The first reported generation of several induced pluripotent stem cell lines from homozygous and heterozygous Huntington’s disease patients demonstrates mutation related enhanced lysosomal activity. Neurobiol. Dis. 46, 41–51 (2012).

  10. 10.

    An, M. C. et al. Genetic correction of Huntington’s disease phenotypes in induced pluripotent stem cells. Cell. Stem Cell. 11, 253–263 (2012).

  11. 11.

    HD iPSC Consortium. Induced pluripotent stem cells from patients with Huntington’s disease show CAG-repeat-expansion-associated phenotypes. Cell. Stem Cell. 11, 264–278 (2012).

  12. 12.

    Jeon, I. et al. Neuronal properties, in vivo effects, and pathology of a Huntington’s disease patient-derived induced pluripotent stem cells. Stem Cells 30, 2054–2062 (2012).

  13. 13.

    Zhang, N., An, M. C., Montoro, D. & Ellerby, L. M. Characterization of human Huntington’s disease cell model from induced pluripotent stem cells. PLoS. Curr. 2, RRN1193 (2010).

  14. 14.

    Nekrasov, E. D. et al. Manifestation of Huntington’s disease pathology in human induced pluripotent stem cell-derived neurons. Mol. Neurodegener. 11, 27 (2016).

  15. 15.

    Yoo, A. S., Staahl, B. T., Chen, L. & Crabtree, G. R. MicroRNA-mediated switching of chromatin-remodelling complexes in neural development. Nature 460, 642–646 (2009).

  16. 16.

    Abernathy, D. G. et al. MicroRNAs induce a permissive chromatin environment that enables neuronal subtype-specific reprogramming of adult human fibroblasts. Cell. Stem Cell. 21, 332–348 (2017).

  17. 17.

    Victor, M. B. et al. Generation of human striatal neurons by microRNA-dependent direct conversion of fibroblasts. Neuron 84, 311–323 (2014).

  18. 18.

    Miller, J. D. et al. Human iPSC-based modeling of late-onset disease via progerin-induced aging. Cell. Stem Cell. 13, 691–705 (2013).

  19. 19.

    Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 14, R115 (2013).

  20. 20.

    Huh, C. J. et al. Maintenance of age in human neurons generated by microRNA-based neuronal conversion of fibroblasts. Elife 5, e18648 (2016).

  21. 21.

    Mertens, J. et al. Directly reprogrammed human neurons retain aging-associated transcriptomic signatures and reveal age-related nucleocytoplasmic defects. Cell. Stem Cell. 17, 705–718 (2015).

  22. 22.

    Silvestroni, A., Faull, R. L., Strand, A. D. & Möller, T. Distinct neuroinflammatory profile in post-mortem human Huntington’s disease. Neuroreport 20, 1098–1103 (2009).

  23. 23.

    Xue, M. et al. Contributions of multiple proteases to neurotoxicity in a mouse model of intracerebral haemorrhage. Brain 132, 26–36 (2009).

  24. 24.

    Li, S. H. et al. Lack of huntingtin-associated protein-1 causes neuronal death resembling hypothalamic degeneration in Huntington’s disease. J. Neurosci. 23, 6956–6964 (2003).

  25. 25.

    Lee, J. H. et al. Reinstating aberrant mTORC1 activity in Huntington’s disease mice improves disease phenotypes. Neuron 85, 303–315 (2015).

  26. 26.

    Valenza, M. et al. Dysfunction of the cholesterol biosynthetic pathway in Huntington’s disease. J. Neurosci. 25, 9932–9939 (2005).

  27. 27.

    Tomás-Zapico, C. et al. α-Synuclein accumulates in huntingtin inclusions but forms independent filaments and its deficiency attenuates early phenotype in a mouse model of Huntington’s disease. Hum. Mol. Genet. 21, 495–510 (2012).

  28. 28.

    Corrochano, S. et al. α-Synuclein levels modulate Huntington’s disease in mice. Hum. Mol. Genet. 21, 485–494 (2012).

  29. 29.

    Strand, A. D. et al. Expression profiling of Huntington’s disease models suggests that brain-derived neurotrophic factor depletion plays a major role in striatal degeneration. J. Neurosci. 27, 11758–11768 (2007).

  30. 30.

    Zuccato, C. & Cattaneo, E. Role of brain-derived neurotrophic factor in Huntington’s disease. Prog. Neurobiol. 81, 294–330 (2007).

  31. 31.

    Plotkin, J. L. et al. Impaired TrkB receptor signaling underlies corticostriatal dysfunction in Huntington’s disease. Neuron 83, 178–188 (2014).

  32. 32.

    Zhang, Q. et al. The zinc finger transcription factor Sp9 is required for the development of striatopallidal projection neurons. Cell. Rep. 16, 1431–1444 (2016).

  33. 33.

    Gutekunst, C. A. et al. Nuclear and neuropil aggregates in Huntington’s disease: relationship to neuropathology. J. Neurosci. 19, 2522–2534 (1999).

  34. 34.

    Ko, J., Ou, S. & Patterson, P. H. New anti-huntingtin monoclonal antibodies: implications for huntingtin conformation and its binding proteins. Brain Res. Bull. 56, 319–329 (2001).

  35. 35.

    Zheng, S. et al. Deletion of the huntingtin polyglutamine stretch enhances neuronal autophagy and longevity in mice. PLoS. Genet. 6, e1000838 (2010).

  36. 36.

    Taipale, M., Jarosz, D. F. & Lindquist, S. HSP90 at the hub of protein homeostasis: emerging mechanistic insights. Nat. Rev. Mol. Cell. Biol. 11, 515–528 (2010).

  37. 37.

    Gomez-Pastor, R. et al. Abnormal degradation of the neuronal stress-protective transcription factor HSF1 in Huntington’s disease. Nat. Commun. 8, 14405 (2017).

  38. 38.

    Vilchez, D. et al. Increased proteasome activity in human embryonic stem cells is regulated by PSMD11. Nature 489, 304–308 (2012).

  39. 39.

    Lu, X. H. et al. Targeting ATM ameliorates mutant Huntingtin toxicity in cell and animal models of Huntington’s disease. Sci. Transl. Med. 6, 268ra178 (2014).

  40. 40.

    Goebel, H. H., Heipertz, R., Scholz, W., Iqbal, K. & Tellez-Nagel, I. Juvenile Huntington chorea: clinical, ultrastructural, and biochemical studies. Neurology 28, 23–31 (1978).

  41. 41.

    Kim, I., Rodriguez-Enriquez, S. & Lemasters, J. J. Selective degradation of mitochondria by mitophagy. Arch. Biochem. Biophys. 462, 245–253 (2007).

  42. 42.

    Liu, L. et al. Glial lipid droplets and ROS induced by mitochondrial defects promote neurodegeneration. Cell 160, 177–190 (2015).

  43. 43.

    Kumar, A. & Ratan, R. R. Oxidative stress and Huntington’s disease: the good, the bad, and the ugly. J. Huntingt. Dis. 5, 217–237 (2016).

  44. 44.

    Vonsattel, J. P. et al. Neuropathological classification of Huntington’s disease. J. Neuropathol. Exp. Neurol. 44, 559–577 (1985).

  45. 45.

    Yoo, A. S. et al. MicroRNA-mediated conversion of human fibroblasts to neurons. Nature 476, 228–231 (2011).

  46. 46.

    Dragunow, M. et al. In situ evidence for DNA fragmentation in Huntington’s disease striatum and Alzheimer’s disease temporal lobes. Neuroreport 6, 1053–1057 (1995).

  47. 47.

    Richner, M., Victor, M. B., Liu, Y., Abernathy, D. & Yoo, A. S. MicroRNA-based conversion of human fibroblasts into striatal medium spiny neurons. Nat. Protoc. 10, 1543–1555 (2015).

  48. 48.

    Lobo, M. K., Karsten, S. L., Gray, M., Geschwind, D. H. & Yang, X. W. FACS-array profiling of striatal projection neuron subtypes in juvenile and adult mouse brains. Nat. Neurosci. 9, 443–452 (2006).

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The authors thank A. Bowman and L. Solnica-Krezel for suggestions, B. Steger and J. Peyer for data quantification, the Washington University Center for Cellular Imaging (WUCCI) for their help in generating electron microscopy data, the Genome Technology Access Center (GTAC) for generating transcriptome datasets, and the Core Usage Funding Program from the Institute of Clinical and Translational Services (ICTS) and the Genome Engineering and iPSC Center (GEiC) at Washington University School of Medicine for their assistance in generating and characterizing iPSC lines. M.B.V. is supported by a National Science Foundation Graduate Research Fellowship (DGE-1143954) and a NIH/NIA dissertation award (1R36AG053444-01). A.S.Y. is supported by the Andrew B. and Virginia C. Craig Faculty Fellowship endowment, an NIH Director’s Innovator Award (DP2NS083372-01), a Seed Grant from Washington University Center of Regenerative Medicine, the Ellison Medical Foundation New Scholar in Aging Award, Cure Alzheimer’s Fund (CAF) and a Presidential Early Career Award for Scientists and Engineers (PECASE) (4DP2NS083372-02).

Author information


  1. Department of Developmental Biology, Center for Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, USA

    • Matheus B. Victor
    • , Michelle Richner
    • , Hannah E. Olsen
    • , Seong Won Lee
    • , Chunyu Ma
    • , Christine J. Huh
    • , Bo Zhang
    •  & Andrew S. Yoo
  2. Graduate Program in Neuroscience, Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA

    • Matheus B. Victor
  3. The Raymond G Perelman Center for Cellular and Molecular Therapeutics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    • Alejandro M. Monteys
    •  & Beverly L. Davidson
  4. Department of Pathology & Laboratory Medicine, The University of Pennsylvania, Philadelphia, PA, USA

    • Beverly L. Davidson
  5. Center for Neurobehavioral Genetics, Semel Institute for Neuroscience & Human Behavior, University of California, Los Angeles (UCLA), Los Angeles, CA, USA

    • X. William Yang


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M.B.V., M.R. and A.S.Y. designed experiments and wrote the manuscript. M.B.V., M.R. and H.E.O performed the experiments and analyzed data. H.E.O. edited the manuscript. C.M. and B.Z. aligned and analyzed the genomic data. C.J.H. contributed to the microarray data analysis and interpretation. S.W.L. contributed to the supplementary data. X.W.Y. contributed to data interpretation and conceived the experiments with the small-molecule ATM-kinase inhibitor. A.M.M. and B.L.D. made and pseudotyped AVV-HTT shRNA and control viruses and conceived the related experiments.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrew S. Yoo.

Integrated supplementary information

  1. Supplementary Figure 1 Neuronal reprogramming independent of donor’s age or CAG-repeat size and DARPP-32 antibody validation.

    Additional HD lines carrying large number of CAG repeats can be reprogrammed into functional neurons by miR-9/9*-124+CDM, and DARPP-32 (Santa Cruz - H62 Clone) antibody shows specificity to striatum in both mouse and human striatal sections. (a), Electrophysiolocal properties were analyzed in monoculture free of rat or mouse primary glia/neurons. HD.59 was analyzed at PID 23 while HD.180 was analyzed at PID 30. Experiment was repeated independently over 3 times (b), RNA-seq analysis at PID 32 of adult control and HD patient fibroblasts reprogrammed with miR-9/9*-124+CDM reveals expression of the full length DARPP-32 transcript. Representative tracks from RNA-seq analysis of 7 HD-MSNs and 5 controls. (c), Immunostaining with an additional anti-DARPP-32 antibody (abcam; ab40801) also produced positive cells, although with less intensity (Cells depicted were reprogrammed from GM04855 fibroblasts). (d), We further validated the up-regulation of DARPP-32 by qPCR with DARPP-32 specific probes. n = 3 technical replicates from MSNs reprogrammed from a single HD patient. Mean and S.E.M. (e), DARPP-32 (Santa Cruz - H62 Clone) showed specificity to MSNs in the striatum of an adult mouse brain as seen by immunohistochemistry analysis, where only the striatum is labeled (shown in red) in a brain coronal section. Similarly, immunohistochemistry performed in a human postmortem brain section of globus pallidus with putamen of a 89 year old healthy female obtained from NIH NeuroBioBank shows antibody labeling specificity to the striatum. Experiments in C,D and E were only performed once.

  2. Supplementary Figure 2 CAG-sizing of primary fibroblasts and microRNA-derived MSNs.

    CAG repeat analysis confirmed HTT mutation and number of CAGs in cell lines mainly used in this study. After several passages in culture and subsequent reprogramming into MSNs by miR-9/9*-124+CDM for three weeks, CAG size was stable (for each group non-transduced fibroblasts are shown on the left and reprogrammed MSNs on the right).

  3. Supplementary Figure 3 Reprogramming HD patient fibroblasts generates functional neurons.

    Reprogramming HD patient fibroblasts generates functional neurons. (a), GFP labeled Ctrl-MSNs and tRFP labeled HD-MSNs (pseudo-colored gray) co-cultured and seeded atop rat primary neural cells for whole-cell recording. (b), Representative traces from current-clamp recordings of Ctrl-MSNs (green traces) at PID 35, and (c), HD-MSNs (gray traces); Ctrl-MSNs and HD-MSNs displayed similar firing patterns, with HD-MSNs having a greater percentage of cells that fired multiple action potentials. Inset display single trace at increasing stimulus steps and total number of cells that fired single or multiple action potentials. Voltage-clamp recordings demonstrate inward sodium and outward calcium currents typical of neurons. (d), HD-MSNs displayed spontaneous action potentials. (e), I-V curve. n = 11 from 3 control samples; n = 13 from 3 HD samples. Evoked response at 90 mV in HD-MSNs is significantly higher. One-way ANOVA (F39,440 = 24.21 P < 0.001) with post hoc Tukey’s test; ** p = 0.0068; Mean ± S.D. (f), Analysis of passive membrane properties. n = 3 averages for each line, totaling 18 controls and 20 HD-MSNs. Experiment was repeated independently twice. Mean ± s.e.m. Two-tailed unpaired t-test; p-value > 0.05 df = 4 Scale bar in a, 10 μm. (g), All recorded properties during electrophysiological analysis displayed for each reprogrammed line.

  4. Supplementary Figure 4 Collection of Huntington’s disease–associated genes differentially expressed in HD-MSNs and validated by qPCR.

    (a) Ingenuity pathway analysis (IPA) of differentially expressed genes identified in RNA-seq studies uncovered many genes that have been experimentally associated with HD. Genes shown in subcellular organization. Red genes are upregulated while green genes are downregulated in HD-MSNs, with darker colors representing higher expression levels. (b) qPCR Validation of Differentially Expressed Genes Identified in RNA-seq Analysis. Ctrl: MSNs converted from control fibroblasts. HD: MSNs converted from Huntington’s disease patient fibroblasts. A number of genes detected to be differentially expressed between HD and Ctrl MSNs were verified by qPCR. BDNF was not detected to be differentially expressed in RNA-seq analysis, and confirmed to be unchanged by qPCR, while MMP9 was detected to be differentially expressed between HD and Ctrls, but shows only a trend by qPCR analysis. Mean ± s.d.; n = 3 biological replicates per group. Two-tailed student’s t-test; df = 4; TRKB ***P = 7.3E-5; SP9 **P = 0.0025; HAP1 *P = 0.033; SCNA *P = 0.034; KCNA4 ***P = 0.0009; AEN **P = 0.0042; ITIH5 *P = 0.0468; BDNF n.s. = 0.68; MMP9 n.s. = 0.11; n.s. = not significant.

  5. Supplementary Figure 5 HD fibroblasts do not exhibit inclusion bodies, even upon cellular insult.

    HD fibroblasts do not exhibit inclusion bodies, even upon cellular insults. (a), Fibroblasts induced to age in vitro by serial passaging (18 times), forced to exit cell cycle by contact inhibition, and then cultured for an additional 7 weeks, do not exhibit inclusion bodies. (b), Ctrl (Ctrl.19) or HD fibroblasts (HD.40) challenged with 1 mM H2O2 to induce oxidative stress do not exhibit inclusion bodies. (c), HD.40 fibroblasts transduced with CDM and a non-specific microRNA (miR-N.S.) to mimic reprogramming conditions but not neuronal induction, do not form inclusion bodies. The formation of inclusion bodies is present in all three lines reprogrammed from HD patients. (d), All three HD MSNs lines examined exhibit aggregated HTT inclusions (IBs) at post-induction day 30 (PID) analyzed by MW8 immunostaining. (e), Quantification with EM48 yields similar number of cells displaying inclusions to MW8 staining; Two-tailed student’s t-test, n = 4 biological replicates per group; ***P = 0.0003 df = 6. (f), The appearance of aggregated cytoplasmic HTT protein in HD.40 MSNs is detected as early as PID 14. By PID 21 HTT inclusions are numerous and after PID 28, inclusions are bigger and more defined, with little to no granules. Quantification of inclusion formation shows significant changes by PID 14; n = 3 biological replicates with each sample containing approximately 100 cells; Mean ± s.e.m. One-Way ANOVA (F6,17 = 65.47, P< 0.0001) with post hoc Tukey’s test (from left, n.s. = 0.19, **P = 0.0028, ***P = 3.2E-10. (f), Time course analysis with Ctrl.20 and HD.42 for the appearance of oxidative DNA damage phenotype by 8OH-dG staining. Significant differences between controls and HD MSNs is detected as early as PID 20, and continue to augment with time in culture. One-Way ANOVA (F9,190 = 30.86, P < 0.0001) with post hoc Tukey’s test (from left, n.s. = 0.99, n.s. = 0.34, **P = 0.0012, ***P = 5.8E-11, ***P = 1.0E-14; ***P < 0.001; **P < 0.01; n.s. = not significant. n = 20 cells per time point for each line. Mean ± s.d. a-c experiments were repeated independently twice and d, over 3 times. f-g experiments have not been independently repeated.

  6. Supplementary Figure 6 Ultrastructural analysis of HD-MSNs.

    (a), Immunogold labeling of HTT in HD-MSNs shows fibrillar-like structures. (b), Immunogold labeling of HTT in HD.40-MSNs at PID 21 is prominent within single and double-membrane autophagosome-like structures (black arrowheads), as well as accumulated as non-membrane bound cytoplasmic structures (red arrowheads). In addition there is marked presence of lipofuscin granules which are known to accumulate with aging (labeled with an asterisk) and quantified in (c), for 3 independent control and HD lines. Two-tailed student’s t-test, n = average of all visible lipofuscins in 10 cells per line; * = p-value = 0.0172 t = 3.925 df = 4. (d), Greater magnification of red arrows in (b), where fibrilar-like structures can be seen. (e), Ultrastructural analysis in HD.40 was also marked by mitophagy (left), accumulation of lipid droplets (middle) and swollen mitochondria typical of apoptotic cells (right); N = nucleus. (f), Colocalization of HTT (EM48) and the autophagosome marker LC3 in additional HD lines. a-f Experiments were repeated in 3 pairs of HD and control MSNs and independently repeated twice.

  7. Supplementary Figure 7 Biochemical analysis of mutant HTT expression in reprogrammed MSNs.

    (a), Four samples used for western blotting, all reprogrammed with miR-9/9*-124+CDM and lysed for protein extraction at post-infection day (PID) 28. (b) Anti-huntingtin monoclonal antibody MW1 specifically binds to the polyglutamine domain of HTT exon 1 and therefore recognizes expanded polyglutamine while showing no detectable binding to normal HTT. Our analysis confirms the expression of soluble mutant HTT in MSNs reprogrammed from primary fibroblasts samples from HD patients. (c) Unlike MW1, the monoclonal anti-huntingtin antibody MW8 recognizes amino acids 83-90 near the c terminus of exon 1 of HTT and specifically recognizes aggregated forms of mutant HTT. Our analysis with MW8 reveals detectable levels of insoluble aggregated HTT in HD-MSNs. These experiments were repeated independently twice.

  8. Supplementary Figure 8 Adult HD fibroblasts can be induced to pluripotency and rederived to human embryonic fibroblasts (HEFs).

    (a), Schematic of HEF derivation. (b), Cells transduced with OCT4, SOX2, KLF4 and c-MYC (OSKM) express stem cell markers, (c), and retain a normal karyotype. (d), Induced pluripotent stem cells (iPSCs) can be differentiated into HEFs by addition of 20% fetal bovine serum (FBS) to culture media and passaging at least three times. (e), CAG sizing confirms that HEFs retain repeat number. (f), LAP2α levels are restored in HEFs; n = 1,000 cells from 3 independent experiments; Two-tailed student’s t-test p-value = 0.0230; df = 4 (g), MSNs directly converted from HD.40 FBs and HEFs express TUBB3, while heMSNs are nearly devoid of mHTT aggregates (MW8) at PID 21. (h), Quantification of mHTT aggregates in MSNs versus heMSNs of HD.50 in comparison to Ctrl.17 ; n = Average of 200 cells from 3 biological replicates; One-way ANOVA (F2,6 = 21.85 P = 0.0018) followed by Tukey’s test (P** = 0.0112, P* = 0.0016, n.s. = 0.16); Mean ± s.e.m; **P < 0.01; *P < 0.05. Experiments in b, c, e, were not repeatedly independently, while experiments shown in d, f and g were repeated independently over 3 times.

  9. Supplementary Figure 9 Induction of pluripotency alters expression of ubiquitin–proteasome system (UPS)-related genes and also differs in MSNs reprogrammed from young or old fibroblast donors.

    (a) HD.40 fibroblasts (HD-FB) and two iPSC clones derived from HD.40 fibroblasts were differentiated into embryonic fibroblasts (HD-HEF.1 and HD-HEF.2) and analyzed by qPCR for the expression of UPS-related genes. HD-HEFs have higher expression of many UPS genes. Mean ± s.e.m.; One-Way ANOVA (F50,102 = 20.17, P< 0.0001) with Holm-Sidak correction. n = 3 samples per group. PSMB6 *P = 0.017, UBE3A ***P = 1.2E-10, HSF1 *P = 0.038, HSPA8 ***P = 4.4E-14, DNAJB2 *P = 0.014, HSPA5 ***P = 5.1E-7, HSPB1 ***P = 7.5E-10. Only significant changes (P < 0.05) are marked, and represents p-values consistent for both HD-FB versus HD-HEF.1 or HD-HEF.2 tests. The expression of ATG12 was only significantly different in HEF2 (**P = 0.002). (b) Ubiquitin-proteosome system (UPS)-related genes differentially expressed from young (three days, five months and one year old) or old (aged 90, 92, and 92 years old) miR-9/9*-124+CDM reprogrammed MSNs by microarray analysis.

  10. Supplementary Figure 10 Spontaneous degeneration in culture is associated with loss of DARPP-32-positive neurons and can be attenuated upon ATM inhibition.

    Since major cell loss only occurs past PID 35, the levels of TUBB3-positive and DARPP-32-positive cells were quantified at PID 30 and PID 40 to determine extent to which DARPP-32-positive cells degenerate in culture. (a), Ctrl.17c and HD.42 fibroblasts were transduced with miR-9/9*-124+CDM concurrently and immunostained at PID 30 and at PID 40. At PID 35 cells were confirmed to have altered levels of cell death (data are quantified and shown in the Fig. 8 of the main text). Non-transduced fibroblasts were used as a negative control for immunostaining. (b), From PID 30 to PID 40, there are no changes observed in the number of TUBB3-positive cells in control samples, in contrast to HD samples in which the level of TUBB3-positive cells is dramatically reduced One-Way ANOVA (F3,8 = 32.25, P = 8.1E-5) with post hoc Tukey’s test (from left, n.s = 0.35, ***P = 0.0004, ***P = 0.0002). In addition, while the percent of DARPP-32-positive cells remains unchanged in control MSNs from PID 30 to PID 40, this percentage is reduced in HD samples at PID 40 in comparison to control. One-Way ANOVA (F3,8 = 5.211, P = 0.0276) with post hoc Tukey’s test (from left, n.s. = 0.52, *P = 0.022). n = averages from 100 cells from 3 random fields-of-view from 3 biological replicates for each time point. (c),Treatment with KU60019 reduces cell death levels at PID 35; One-Way ANOVA (F3,31 = 13.28, P = 9.5E-6) with post hoc Tukey’s test (***P = 6.5E-6, *p = 0.019, n.s. = 0.54). (d), KU60019 protects HD-MSNs against H2O2-induced oxidative stress; One-Way ANOVA (F3,31 = 12.58, P = 1.5E-5) with post hoc Tukey’s test (***P = 2.9E-6, *p = 0.048, n.s. = 0.14). n = averages from 1,000 cells from 8 or 9 biological replicates; Scale bars: 100 μm. ***P < 0.001; **P < 0.01; *P < 0.05; n.s. = not significant. Mean ± s.e.m.

  11. Supplementary Figure 11 Evidence of increased mitophagy in HD-MSNs.

    Evidence of increased mitophagy in HD-MSNs. (a), Additional HD and control lines used in this study stain positive for TUBB3 and successfully undergo direct conversion by miR-9/9*-124+CDM. Experiment has been repeated independently 3 times. (b) LC3-II staining at multiple intervals during direct conversion. At PID 20, analysis of 3 independent HD and control lines shows that 2 out of 3 HD-MSNs lines have a higher number of autophagosomes, however the overall change was not significantly different. Two-tailed student’s t-test; t = 1.31 df = 4 p = 0.2604; n = averages from 10 cells per group. (c) Co-staining of MitoTracker Red and LC3-II at PID 40 in two pairs of HD and control lines shows higher percentage of colocalization in HD-MSNs. One-Way ANOVA (F3,8 = 61.48, P = 7.2E-6) with post hoc Tukey’s test (from left, ***P = 2E-4, 5.7E-6, 8E-5, *P = 0.014); n = Averages from approximately 2,000 LC3-II puncta from 3 random field-of-views per group. Colocalization was measured using images acquired through confocal microscopy at 100x objective and analyzed post-acquisition by automated colocalization analysis. One-Way ANOVA with post hoc Tukey’s test; ***P < 0.001; **P < 0.01; *P < 0.05; n.s. = not significant. Mean ± s.e.m.

  12. Supplementary Figure 12 Differential vulnerability to degeneration in distinct subtypes of HD neurons.

    (a), HD.40 fibroblasts were reprogrammed into cortical-like neurons (CNs) with miR-9/9*-124+DAM (NeuroD2, ASCL1 and Myt1L) (b), HD.40 CNs immunostained with TUBB3 at PID 21. This experiment was repeated independently over 3 times. (c), qPCR analysis for the expression of cortical genes as well as MSN-marker DARPP-32 at PID 30; n = 3 samples per group; Two-tailed student’s t-test with Holm-Sidak correction (from left, ***P = 0.003, 0.001, 0.0016,*P = 0.037, 0.043, 0.043, df = 4). (d), Comet assay; One-Way ANOVA (F3,195 = 20.15, P = 2E-11) with post hoc Tukey’s test (from left, ***P = 4.4E-8, 7.1E-11, n.s. = 0.14); n = 50 cells per group. (e), Immunostaining and quantification of the DNA damage marker γH2AX; One-Way ANOVA (F3,8 = 18.23, P = 0.0006) with post hoc Tukey’s test (**P = 0.0074, ***P = 0.001, n.s. = 0.99); n = averages from 500 cells per group in 3 independent experiments. (f), SYTOX staining reveals differences in subtype-dependent cell death levels at PID 35; n = averages from 1,200 cells per group in 3 independent experiments; One-Way ANOVA (F3,8 = 29.2, P = 0.0001) with post hoc Tukey’s test (**P = 0.002, ***P = 0.0001, n.s. = 0.18). (g), HTT aggregation detected by MW8 antibody at PID 35 in HD-MSNs and HD-CNs and quantification of the percentage of cells with IBs in MSNs and CNs. n = averages from 100 cells per group in 3 independent experiments; One-Way ANOVA (F3,8 = 58.75, P = 8.5E-6) with post hoc Tukey’s test (from left, **P = 0.001 and 0.002, ***P = 2.1E-5). ***P < 0.001; **P < 0.01. Mean ± s.e.m. Scale bar in b,d,f, 100 μm; and in e, 20 μm.

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