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Small molecule regulators of microRNAs identified by high-throughput screen coupled with high-throughput sequencing

Nguyen, Lien D., Wei, Zhiyun, Silva, M. Catarina, Barberán-Soler, Sergio, Zhang, Jiarui, Rabinovsky, Rosalia, Muratore, Christina R., Stricker, Jonathan M. S., Hortman, Colin, Young-Pearse, Tracy L., Haggarty, Stephen J., Krichevsky, Anna M.·2023·Nature Communications
DOI 10.1038/s41467-023-43293-0PMC PMC10663445

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Abstract

MicroRNAs (miRNAs) regulate fundamental biological processes by silencing mRNA targets and are dysregulated in many diseases. Therefore, miRNA replacement or inhibition can be harnessed as potential therapeutics. However, existing strategies for miRNA modulation using oligonucleotides and gene therapies are challenging, especially for neurological diseases, and none have yet gained clinical approval. We explore a different approach by screening a biodiverse library of small molecule compounds for their ability to modulate hundreds of miRNAs in human induced pluripotent stem cell-derived neurons. We demonstrate the utility of the screen by identifying cardiac glycosides as potent inducers of miR-132, a key neuroprotective miRNA downregulated in Alzheimer’s disease and other tauopathies. Coordinately, cardiac glycosides downregulate known miR-132 targets, including Tau, and protect rodent and human neurons against various toxic insults. More generally, our dataset of 1370 drug-like compounds and their effects on the miRNome provides a valuable resource for further miRNA-based drug discovery.

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Fig. 1 Experimental workflow and overview of screen results in NGN2-iNs. a NGN2-iN generation, compound treatment, and miRNA-seq workflow (N = 1 per compound, 1902 compounds in total, created with BioRender.com). b Average number of miRNA species detected per sample by miRNA-seq at various count cut-offs (N = 1371 samples). Error bars represent mean +/− SD. c Expression levels of the 100 most abundant miRNAs in vehicle-treated samples. miR-26a-5p was the most abundant miRNA detected, miR-132-3p was the 27th (N = 42 DMSO-treated samples). Error bars represent mean +/− SEM. d Shared miRNAs with the lowest coefficient of variation in the plates tested. e Waterfall plot for miR-132 expression in plate 2 was shown in blue. Samples treated with ouabain, digoxin, and the positive control forskolin showed the highest level of miR-132. miR-107, miR-103a-3p, and miR-191-5p were shown in red, green, and purple, respectively.
Fig. 1 Experimental workflow and overview of screen results in NGN2-iNs. a NGN2-iN generation, compound treatment, and miRNA-seq workflow (N = 1 per compound, 1902 compounds in total, created with BioRender.com). b Average number of miRNA species detected per sample by miRNA-seq at various count cut-offs (N = 1371 samples). Error bars represent mean +/− SD. c Expression levels of the 100 most abundant miRNAs in vehicle-treated samples. miR-26a-5p was the most abundant miRNA detected, miR-132-3p was the 27th (N = 42 DMSO-treated samples). Error bars represent mean +/− SEM. d Shared miRNAs with the lowest coefficient of variation in the plates tested. e Waterfall plot for miR-132 expression in plate 2 was shown in blue. Samples treated with ouabain, digoxin, and the positive control forskolin showed the highest level of miR-132. miR-107, miR-103a-3p, and miR-191-5p were shown in red, green, and purple, respectively.CC BY · PubMed Central
Fig. 2 Landscape of compound effects on miRNome in NGN2-iNs. a Top small molecule hits for miRNAs with neurologic relevance. b UMAP analysis of miRNomes affected by compounds (N = 1437 samples). c Clustered heatmap illustrating small molecule compounds (CC1-CC5) as modulators of miRNAs (MC1-MC4). Heatmaps showing miRNAs regulated by compounds related to cytoskeletal signaling (N = 42 vs 36) (d), neuronal signaling (N = 42 vs 204) (e), protein tyrosine kinase (N = 42 vs 67) (f), and DNA damage (N = 42 vs 80) (g), respectively (p < 0.001, t-test). Representative miRNAs affected by compounds predicted to cross the BBB (N = 948 vs 447) (h), involved in CNS system (N = 1145 vs 250) (i), and kinase inhibitors (N = 1062 vs 333) (j). p = 0.0004, 9.8E−5, and 0.0021, respectively; two-sided t-test without assumption of equal SD. k Compounds simultaneously upregulating multiple "neuroprotective" and downregulating “neurotoxic” miRNAs. l miRNAs showing the strongest positive and negative correlations with miR-132 in all sequenced samples. **p < 0.01; ***p < 0.001, unpaired two-tailed Student’s t test; CC compound cluster, MC miRNA cluster, AD Alzheimer’s disease, HD Huntington’s disease, PD Parkinson’s Disease, SP synaptic plasticity, BBB blood-brain barrier.
Fig. 2 Landscape of compound effects on miRNome in NGN2-iNs. a Top small molecule hits for miRNAs with neurologic relevance. b UMAP analysis of miRNomes affected by compounds (N = 1437 samples). c Clustered heatmap illustrating small molecule compounds (CC1-CC5) as modulators of miRNAs (MC1-MC4). Heatmaps showing miRNAs regulated by compounds related to cytoskeletal signaling (N = 42 vs 36) (d), neuronal signaling (N = 42 vs 204) (e), protein tyrosine kinase (N = 42 vs 67) (f), and DNA damage (N = 42 vs 80) (g), respectively (p < 0.001, t-test). Representative miRNAs affected by compounds predicted to cross the BBB (N = 948 vs 447) (h), involved in CNS system (N = 1145 vs 250) (i), and kinase inhibitors (N = 1062 vs 333) (j). p = 0.0004, 9.8E−5, and 0.0021, respectively; two-sided t-test without assumption of equal SD. k Compounds simultaneously upregulating multiple "neuroprotective" and downregulating “neurotoxic” miRNAs. l miRNAs showing the strongest positive and negative correlations with miR-132 in all sequenced samples. **p < 0.01; ***p < 0.001, unpaired two-tailed Student’s t test; CC compound cluster, MC miRNA cluster, AD Alzheimer’s disease, HD Huntington’s disease, PD Parkinson’s Disease, SP synaptic plasticity, BBB blood-brain barrier.CC BY · PubMed Central
Fig. 3 Validation of top miR-132-upregulating candidate compounds in primary rat cortical neurons and human NGN2-iNs. a Top compounds that showed significant upregulation of miR-132 in primary rat cortical neurons and human NGN2-iNs after 24 h treatment (RT-qPCR analysis, unpaired two-tailed Student’s t test compared to DMSO controls, N = 8 biological replicates for DMSO and forskolin, N = 4 for others). b Dose curve experiments were performed in DIV14 rat primary neurons after 24 h treatment. Solid lines were used for cardiac glycosides, and dotted lines were used for other compounds. EC50 and max fold change were calculated using sigmoidal fit, 4 parameters. (N = 3–8 biological replicates). c Cardiac glycosides, forskolin, and BIX02188 upregulated the primary transcript of miR-132 24 h after treatment in rat primary neurons (unpaired two-tailed Student’s t test compared to DMSO control, N = 4 biological replicates). d, e Upregulation of miR-132 in rat primary neurons was completely blocked by pretreatment with CREB inhibitor (N = 3 biological replicates) or actinomycin D (N = 4 biological replicates, one-way ANOVA, followed by Dunnett’s multiple comparisons test comparing to DMSO/DMSO control). f Knocking-down ATP1A1 or ATP1A3, the predominant isoforms in neurons, upregulated pri-miR-132 and mature miR-132 in rat primary neurons (unpaired two-tailed Student’s t test compared to DMSO control, N = 3-4 biological replicates for ATP1A1 KD, N = 6 for ATP1A3 KD). All error bars represent mean +/− SD. Source data are provided as a Source Data file.
Fig. 3 Validation of top miR-132-upregulating candidate compounds in primary rat cortical neurons and human NGN2-iNs. a Top compounds that showed significant upregulation of miR-132 in primary rat cortical neurons and human NGN2-iNs after 24 h treatment (RT-qPCR analysis, unpaired two-tailed Student’s t test compared to DMSO controls, N = 8 biological replicates for DMSO and forskolin, N = 4 for others). b Dose curve experiments were performed in DIV14 rat primary neurons after 24 h treatment. Solid lines were used for cardiac glycosides, and dotted lines were used for other compounds. EC50 and max fold change were calculated using sigmoidal fit, 4 parameters. (N = 3–8 biological replicates). c Cardiac glycosides, forskolin, and BIX02188 upregulated the primary transcript of miR-132 24 h after treatment in rat primary neurons (unpaired two-tailed Student’s t test compared to DMSO control, N = 4 biological replicates). d, e Upregulation of miR-132 in rat primary neurons was completely blocked by pretreatment with CREB inhibitor (N = 3 biological replicates) or actinomycin D (N = 4 biological replicates, one-way ANOVA, followed by Dunnett’s multiple comparisons test comparing to DMSO/DMSO control). f Knocking-down ATP1A1 or ATP1A3, the predominant isoforms in neurons, upregulated pri-miR-132 and mature miR-132 in rat primary neurons (unpaired two-tailed Student’s t test compared to DMSO control, N = 3-4 biological replicates for ATP1A1 KD, N = 6 for ATP1A3 KD). All error bars represent mean +/− SD. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 4 Cardiac glycosides upregulate miR-132 to downregulate miR-132 targets and provide neuroprotection in primary rat cortical neurons. a–c 100 nM oleandrin upregulated pri- and mature miR-132/212 and downregulated their mRNA targets over time (RT-qPCR analysis, N ~ 6 biological replicates, unpaired two-tailed t-test comparing to 0 h, adjusted for multiple comparisons). d–h Oleandrin downregulated total Tau (N = 13 biological replicates), pTau (AT8, N = 13, and S396, N = 7), and FOXO3a (N = 12) protein after 72 h treatment (Western blot analysis, unpaired two-tailed Student’s t test). i–k Less mature neurons were more susceptible to cardiac glycoside toxicity, whereas more mature neurons were resistant. Primary rat neurons were treated with various doses of digoxin, oleandrin, and proscillaridin A for 96 h before viability was measured using WST-1. Cells treated at DIV7 showed a dose-dependent reduction in viability. In contrast, cells treated at DIV14, 21, or 28 showed little loss of viability, particularly at EC100 for miR-132 upregulation (unpaired t-test comparing to DMSO, adjusted for multiple comparisons, N = 4–10 biological replicates per dose). l For DIV7 neurons, proscillaridin A was mildly toxic at baseline. However, both proscillaridin A and oleandrin fully rescued viability loss due to glutamate treatment (2-way ANOVA, followed by Dunnet’s multiple comparisons test, N ~ 16 biological replicates per condition). m, n For DIV21 neurons, proscillaridin A and oleandrin were not toxic at baseline and rescued viability loss due to glutamate or Aβ oligomer treatment (2-way ANOVA, followed by Dunnet’s multiple comparisons test, N ~ 16 biological replicates per condition). o Pre-transfection with miR-132 and -212 inhibitors partially reduced the rescue of viability provided by proscillaridin A and oleandrin (2-way ANOVA, followed by Tukey’s multiple comparisons test, N ~ 15 biological replicates per condition). All error bars represent mean +/− SD. Source data are provided as a Source Data file.
Fig. 4 Cardiac glycosides upregulate miR-132 to downregulate miR-132 targets and provide neuroprotection in primary rat cortical neurons. a–c 100 nM oleandrin upregulated pri- and mature miR-132/212 and downregulated their mRNA targets over time (RT-qPCR analysis, N ~ 6 biological replicates, unpaired two-tailed t-test comparing to 0 h, adjusted for multiple comparisons). d–h Oleandrin downregulated total Tau (N = 13 biological replicates), pTau (AT8, N = 13, and S396, N = 7), and FOXO3a (N = 12) protein after 72 h treatment (Western blot analysis, unpaired two-tailed Student’s t test). i–k Less mature neurons were more susceptible to cardiac glycoside toxicity, whereas more mature neurons were resistant. Primary rat neurons were treated with various doses of digoxin, oleandrin, and proscillaridin A for 96 h before viability was measured using WST-1. Cells treated at DIV7 showed a dose-dependent reduction in viability. In contrast, cells treated at DIV14, 21, or 28 showed little loss of viability, particularly at EC100 for miR-132 upregulation (unpaired t-test comparing to DMSO, adjusted for multiple comparisons, N = 4–10 biological replicates per dose). l For DIV7 neurons, proscillaridin A was mildly toxic at baseline. However, both proscillaridin A and oleandrin fully rescued viability loss due to glutamate treatment (2-way ANOVA, followed by Dunnet’s multiple comparisons test, N ~ 16 biological replicates per condition). m, n For DIV21 neurons, proscillaridin A and oleandrin were not toxic at baseline and rescued viability loss due to glutamate or Aβ oligomer treatment (2-way ANOVA, followed by Dunnet’s multiple comparisons test, N ~ 16 biological replicates per condition). o Pre-transfection with miR-132 and -212 inhibitors partially reduced the rescue of viability provided by proscillaridin A and oleandrin (2-way ANOVA, followed by Tukey’s multiple comparisons test, N ~ 15 biological replicates per condition). All error bars represent mean +/− SD. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 5 Cardiac glycosides upregulate miR-132 to downregulate miR-132 targets and provide neuroprotection in primary rat cortical neurons. WT and P301L neurons were differentiated for 6 weeks, then treated with cardiac glycosides for 24 h or 72 h. a Representative Western blot for WT neurons treated with proscillaridin A (ProsA). A dose-dependent reduction in total Tau and p-Tau S396 was observed at both 24 h and 72 h. The dotted lines indicated that separate Western blots were put together. Similar results were obtained independently 3 times. b, c In parallel, a reduction in MAPT mRNA and an increase in pri-miR-132 and miR-132 RNA were observed (N = 1 biological sample). Similar results were also observed in Tau P301L neurons by Western blot (d) and mRNA (e, f) analysis. g–r Western blot densitometry quantification of dose-dependent effects on Tau (TAU5), pTau S396 and the synaptic makers PSD95, SYN1, and β-III-Tubulin (N = 3 biological replicates) in WT and P301L neurons treated for 24 h or 72 h. The yellow shades indicate compound concentrations leading to <30% loss of at least two synaptic/microtubule markers. All error bars represent mean +/− SEM. Source data are provided as a Source Data file.
Fig. 5 Cardiac glycosides upregulate miR-132 to downregulate miR-132 targets and provide neuroprotection in primary rat cortical neurons. WT and P301L neurons were differentiated for 6 weeks, then treated with cardiac glycosides for 24 h or 72 h. a Representative Western blot for WT neurons treated with proscillaridin A (ProsA). A dose-dependent reduction in total Tau and p-Tau S396 was observed at both 24 h and 72 h. The dotted lines indicated that separate Western blots were put together. Similar results were obtained independently 3 times. b, c In parallel, a reduction in MAPT mRNA and an increase in pri-miR-132 and miR-132 RNA were observed (N = 1 biological sample). Similar results were also observed in Tau P301L neurons by Western blot (d) and mRNA (e, f) analysis. g–r Western blot densitometry quantification of dose-dependent effects on Tau (TAU5), pTau S396 and the synaptic makers PSD95, SYN1, and β-III-Tubulin (N = 3 biological replicates) in WT and P301L neurons treated for 24 h or 72 h. The yellow shades indicate compound concentrations leading to <30% loss of at least two synaptic/microtubule markers. All error bars represent mean +/− SEM. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 6 Cardiac glycosides protect human Tau P301L iPSC-neurons from diverse toxic insults. Compounds concentration effect on neuronal viability after 24 h or 72 h treatment of WT (a–c) and Tau P301L (d–f) human neurons (Data points indicate mean ± SD; N = 6 biological replicates; unpaired two-tailed Student’s t test). g Schematic of the assay used to measure neuroprotective effects by cardiac glycosides in tauopathy neurons. h–j Cardiac glycosides rescued the loss of viability in P301L neurons due to NMDA, rotenone, or Aβ42 oligomer treatment (N = 4 biological replicates, unpaired two-tailed Student’s t test). All error bars represent mean +/− SEM. k Representative images for P301L neurons at 8 weeks of differentiation treated with cardiac glycosides and each stressor compound. Total Tau (K9JA antibody) staining is shown in red, and MAP2 in green. Similar results were obtained independently 2 times. Scale bars are 200 μm. Source data are provided as a Source Data file.
Fig. 6 Cardiac glycosides protect human Tau P301L iPSC-neurons from diverse toxic insults. Compounds concentration effect on neuronal viability after 24 h or 72 h treatment of WT (a–c) and Tau P301L (d–f) human neurons (Data points indicate mean ± SD; N = 6 biological replicates; unpaired two-tailed Student’s t test). g Schematic of the assay used to measure neuroprotective effects by cardiac glycosides in tauopathy neurons. h–j Cardiac glycosides rescued the loss of viability in P301L neurons due to NMDA, rotenone, or Aβ42 oligomer treatment (N = 4 biological replicates, unpaired two-tailed Student’s t test). All error bars represent mean +/− SEM. k Representative images for P301L neurons at 8 weeks of differentiation treated with cardiac glycosides and each stressor compound. Total Tau (K9JA antibody) staining is shown in red, and MAP2 in green. Similar results were obtained independently 2 times. Scale bars are 200 μm. Source data are provided as a Source Data file.CC BY · PubMed Central
Fig. 7 Transcriptome analysis of human iPSC-neurons treated with cardiac glycosides. a Workflow of the experiment design (created with BioRender.com). b Principal component analysis (PCA) indicated the strong and dose-dependent alteration of global transcriptomic profiles after treatments. c Volcano plots showed significant down- and upregulated genes, labeled in blue and red dots, respectively. All dosages were grouped to be compared with DMSO (N = 3 vs 3). Stars highlighted dysregulated genes involved in neuronal activity and health. Wald test with FDR correction analyzed using DESeq2. d Venn diagram indicated the similarity of pathways affected by three cardiac glycosides. e Selected neuronal pathways enriched for the down-regulated genes. f Selected transcription- and response-related pathways enriched for the upregulated genes. g Effects of cardiac glycosides on the expression of transcription factors (TFs) that have binding sites on MIR132 promoter. h Working model showing the effects of cardiac glycosides: cardiac glycosides act through their conventional mechanism leading to the transcriptional upregulation of miR-132. The increase in miR-132, together with other pathways altered by cardiac glycosides, downregulated various forms of Tau and provided neuroprotection against toxic insults (created with BioRender.com).
Fig. 7 Transcriptome analysis of human iPSC-neurons treated with cardiac glycosides. a Workflow of the experiment design (created with BioRender.com). b Principal component analysis (PCA) indicated the strong and dose-dependent alteration of global transcriptomic profiles after treatments. c Volcano plots showed significant down- and upregulated genes, labeled in blue and red dots, respectively. All dosages were grouped to be compared with DMSO (N = 3 vs 3). Stars highlighted dysregulated genes involved in neuronal activity and health. Wald test with FDR correction analyzed using DESeq2. d Venn diagram indicated the similarity of pathways affected by three cardiac glycosides. e Selected neuronal pathways enriched for the down-regulated genes. f Selected transcription- and response-related pathways enriched for the upregulated genes. g Effects of cardiac glycosides on the expression of transcription factors (TFs) that have binding sites on MIR132 promoter. h Working model showing the effects of cardiac glycosides: cardiac glycosides act through their conventional mechanism leading to the transcriptional upregulation of miR-132. The increase in miR-132, together with other pathways altered by cardiac glycosides, downregulated various forms of Tau and provided neuroprotection against toxic insults (created with BioRender.com).CC BY · PubMed Central

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Metadata

Authors
Nguyen, L. D., Wei, Z., Silva, M. C., Barberán-Soler, S., Zhang, J., Rabinovsky, R., Muratore, C. R., Stricker, J. M. S., Hortman, C., Young-Pearse, T. L., Haggarty, S. J., & Krichevsky, A. M.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2023-11-21
Volume
14
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-023-43293-0
PMC
PMC10663445
Cited by
50
References
7
Language
en
Licence

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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