The findings that amyotrophic lateral sclerosis (ALS) patients almost universally display pathological mislocalization of the RNA-binding protein TDP-43 and that mutations in its gene cause familial ALS have nominated altered RNA metabolism as a disease mechanism. However, the RNAs regulated by TDP-43 in motor neurons and their connection to neuropathy remain to be identified. Here we report transcripts whose abundances in human motor neurons are sensitive to TDP-43 depletion. Notably, expression of STMN2, which encodes a microtubule regulator, declined after TDP-43 knockdown and TDP-43 mislocalization as well as in patient-specific motor neurons and postmortem patient spinal cord. STMN2 loss upon reduced TDP-43 function was due to altered splicing, which is functionally important, as we show STMN2 is necessary for normal axonal outgrowth and regeneration. Notably, post-translational stabilization of STMN2 rescued neurite outgrowth and axon regeneration deficits induced by TDP-43 depletion. We propose that restoring STMN2 expression warrants examination as a therapeutic strategy for ALS.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Data availability

The authors will make all data available to readers upon reasonable request. The RNA-seq data discussed in this publication have been deposited in the Gene Expression Omnibus61 and are accessible through GEO series accession number GSE121569. The patient spinal cord RNA-seq data are available through dbGaP (phs000747.v2.p1).

Additional information

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


  1. 1.

    Taylor, J. P., Brown, R. H. & Cleveland, D. W. Decoding ALS: from genes to mechanism. Nature 539, 197–206 (2016).

  2. 2.

    Ravits, J. et al. Deciphering amyotrophic lateral sclerosis: what phenotype, neuropathology and genetics are telling us about pathogenesis. Amyotroph. Lateral Scler. Frontotemporal Degener. 14, 5–18 (2013).

  3. 3.

    Miller, R. G., Mitchell, J. D. & Moore, D. H. Riluzole for amyotrophic lateral sclerosis (ALS)/motor neuron disease (MND). Cochrane Database Syst. Rev. 3, CD001447 (2012).

  4. 4.

    Ling, S.-C., Polymenidou, M. & Cleveland, D. W. Converging mechanisms in ALS and FTD: disrupted RNA and protein homeostasis. Neuron 79, 416–438 (2013).

  5. 5.

    Neumann, M. et al. Ubiquitinated TDP-43 in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Science 314, 130–133 (2006).

  6. 6.

    Alami, N. H. et al. Axonal transport of TDP-43 mRNA granules is impaired by ALS-causing mutations. Neuron 81, 536–543 (2014).

  7. 7.

    Lee, E. B., Lee, V. M.-Y. & Trojanowski, J. Q. Gains or losses: molecular mechanisms of TDP43-mediated neurodegeneration. Nat. Rev. Neurosci. 13, 38–50 (2012).

  8. 8.

    Sreedharan, J. et al. TDP-43 mutations in familial and sporadic amyotrophic lateral sclerosis. Science 319, 1668–1672 (2008).

  9. 9.

    Kraemer, B. C. et al. Loss of murine TDP-43 disrupts motor function and plays an essential role in embryogenesis. Acta Neuropathol. 119, 409–419 (2010).

  10. 10.

    Polymenidou, M. et al. Long pre-mRNA depletion and RNA missplicing contribute to neuronal vulnerability from loss of TDP-43. Nat. Neurosci. 14, 459–468 (2011).

  11. 11.

    Tollervey, J. R. et al. Characterizing the RNA targets and position-dependent splicing regulation by TDP-43. Nat. Neurosci. 14, 452–458 (2011).

  12. 12.

    Han, S. S. W., Williams, L. A. & Eggan, K. C. Constructing and deconstructing stem cell models of neurological disease. Neuron 70, 626–644 (2011).

  13. 13.

    Di Giorgio, F. P., Boulting, G. L., Bobrowicz, S. & Eggan, K. C. Human embryonic stem cell-derived motor neurons are sensitive to the toxic effect of glial cells carrying an ALS-causing mutation. Stem Cell 3, 637–648 (2008).

  14. 14.

    Davis-Dusenbery, B. N., Williams, L. A., Klim, J. R. & Eggan, K. How to make spinal motor neurons. Development 141, 491–501 (2014).

  15. 15.

    van Eersel, J. et al. Cytoplasmic accumulation and aggregation of TDP-43 upon proteasome inhibition in cultured neurons. PLoS One 6, e22850 (2011).

  16. 16.

    Shiga, A. et al. Alteration of POLDIP3 splicing associated with loss of function of TDP-43 in tissues affected with ALS. PLoS One 7, e43120 (2012).

  17. 17.

    Yang, C. et al. Partial loss of TDP-43 function causes phenotypes of amyotrophic lateral sclerosis. Proc. Natl. Acad. Sci. USA 111, E1121–E1129 (2014).

  18. 18.

    Grenningloh, G., Soehrman, S., Bondallaz, P., Ruchti, E. & Cadas, H. Role of the microtubule destabilizing proteins SCG10 and stathmin in neuronal growth. J. Neurobiol. 58, 60–69 (2004).

  19. 19.

    Shin, J. E., Geisler, S. & DiAntonio, A. Dynamic regulation of SCG10 in regenerating axons after injury. Exp. Neurol. 252, 1–11 (2014).

  20. 20.

    Kasashima, K., Sakashita, E., Saito, K. & Sakamoto, H. Complex formation of the neuron-specific ELAV-like hu RNA-binding proteins. Nucleic Acids Res. 30, 4519–4526 (2002).

  21. 21.

    Martin, K. R. et al. Over-expression of RCAN1 causes Down syndrome-like hippocampal deficits that alter learning and memory. Hum. Mol. Genet. 21, 3025–3041 (2012).

  22. 22.

    Ariyannur, P. S. et al. Methamphetamine-induced neuronal protein NAT8L is the NAA biosynthetic enzyme: implications for specialized acetyl coenzyme A metabolism in the CNS. Brain Res. 1335, 1–13 (2010).

  23. 23.

    Boulting, G. L. et al. A functionally characterized test set of human induced pluripotent stem cells. Nat. Biotechnol. 29, 279–286 (2011).

  24. 24.

    Egawa, N. et al. Drug screening for ALS using patient-specific induced pluripotent stem cells. Sci. Transl. Med. 4, 145ra104–145ra104 (2012).

  25. 25.

    Serio, A. et al. Astrocyte pathology and the absence of non-cell autonomy in an induced pluripotent stem cell model of TDP-43 proteinopathy. Proc. Natl. Acad. Sci. USA 110, 4697–4702 (2013).

  26. 26.

    Bilican, B. et al. Mutant induced pluripotent stem cell lines recapitulate aspects of TDP-43 proteinopathies and reveal cell-specific vulnerability. Proc. Natl. Acad. Sci. USA 109, 5803–5808 (2012).

  27. 27.

    Zhang, Z. et al. Downregulation of microRNA-9 in iPSC-derived neurons of FTD/ALS patients with TDP-43 mutations. PLoS One 8, e76055 (2013).

  28. 28.

    Park, Y.-Y. et al. TARDBP regulates glycolysis in hepatocellular carcinoma by regulating PFKP through miR-520. Hepatology (Baltimore, MD) 58, 182–191 (2013).

  29. 29.

    Colombrita, C. et al. From transcriptomic to protein level changes in TDP-43 and FUS loss-of-function cell models. Biochim. Biophys. Acta Gene Regul. Mech. 1849, 1398–1410 (2015).

  30. 30.

    Chauvin, S. & Sobel, A. Neuronal stathmins: a family of phosphoproteins cooperating for neuronal development, plasticity and regeneration. Prog. Neurobiol. 126, 1–18 (2015).

  31. 31.

    Bieche, I. et al. Expression of stathmin family genes in human tissues: non-neural-restricted expression for SCLIP. Genomics 81, 400–410 (2003).

  32. 32.

    Smith, B. N. et al. Exome-wide rare variant analysis identifies TUBA4A mutations associated with familial ALS. Neuron 84, 324–331 (2014).

  33. 33.

    Wu, C.-H. et al. Mutations in the profilin 1 gene cause familial amyotrophic lateral sclerosis. Nature 488, 499–503 (2012).

  34. 34.

    Nicolas, A. et al. Genome-wide analyses identify KIF5A as a novel ALS gene. Neuron 97, 1268–1283.e6 (2018).

  35. 35.

    Ling, J. P., Pletnikova, O., Troncoso, J. C. & Wong, P. C. TDP-43 repression of nonconserved cryptic exons is compromised in ALS-FTD. Science 349, 650–655 (2015).

  36. 36.

    Humphrey, J., Emmett, W., Fratta, P., Isaacs, A. M. & Plagnol, V. Quantitative analysis of cryptic splicing associated with TDP-43 depletion. BMC Med. Genomics 10, 38 (2017).

  37. 37.

    White, M. A. et al. TDP-43 gains function due to perturbed autoregulation in a Tardbp knock-in mouse model of ALS-FTD. Nat. Neurosci. 21, 552–563 (2018).

  38. 38.

    Rabin, S. J. et al. Sporadic ALS has compartment-specific aberrant exon splicing and altered cell–matrix adhesion biology. Hum. Mol. Genet. 19, 313–328 (2009).

  39. 39.

    Highley, J. R. et al. Loss of nuclear TDP‐43 in amyotrophic lateral sclerosis (ALS) causes altered expression of splicing machinery and widespread dysregulation of RNA splicing in motor neurones. Neuropathol. Appl. Neurobiol. 40, 670–685 (2014).

  40. 40.

    D’Erchia, A. M. et al. Massive transcriptome sequencing of human spinal cord tissues provides new insights into motor neuron degeneration in ALS. Sci. Rep. 7, 10046 (2017).

  41. 41.

    Tararuk, T. et al. JNK1 phosphorylation of SCG10 determines microtubule dynamics and axodendritic length. J. Cell Biol. 173, 265–277 (2006).

  42. 42.

    Shin, J. E. et al. SCG10 is a JNK target in the axonal degeneration pathway. Proc. Natl. Acad. Sci. USA 109, E3696–E3705 (2012).

  43. 43.

    Kaplan, A. et al. Neuronal matrix metalloproteinase-9 Is a determinant of selective neurodegeneration. Neuron 81, 333–348 (2014).

  44. 44.

    Kiskinis, E. et al. Pathways disrupted in human ALS motor neurons identified through genetic correction of mutant SOD1. Cell Stem Cell 14, 781–795 (2014).

  45. 45.

    Pietro Fratta et al. Mice with endogenous TDP‐43 mutations exhibit gain of splicing function and characteristics of amyotrophic lateral sclerosis. EMBO J. 37, e98684 (2018).

  46. 46.

    de Boer, A. S. et al. Genetic validation of a therapeutic target in a mouse model of ALS. Sci. Transl. Med. 6, 248ra104–248ra104 (2014).

  47. 47.

    Bellouze, S. et al. Stathmin 1/2-triggered microtubule loss mediates Golgi fragmentation in mutant SOD1 motor neurons. Mol. Neurodegeneration 11, 43 (2016).

  48. 48.

    Amoroso, M. W. et al. Accelerated high-yield generation of limb-innervating motor neurons from human stem cells. J. Neurosci. 33, 574–586 (2013).

  49. 49.

    Yuan, S. H. et al. Cell-surface marker signatures for the isolation of neural stem cells, glia and neurons derived from human pluripotent stem cells. PLoS One 6, e17540 (2011).

  50. 50.

    Steinbaugh, M. J. et al. bcbioRNASeq: R package for bcbio RNA-seq analysis. F1000Res. 6, 1976 (2017).

  51. 51.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome. Biol. 15, 550 (2014).

  52. 52.

    Anders, S., Reyes, A. & Huber, W. Detecting differential usage of exons from RNA-seq data. Genome Res. 22, 2008–2017 (2012).

  53. 53.

    Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 14, 417–419 (2017).

  54. 54.

    Soneson, C., Love, M. I. & Robinson, M. D. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res. 4, 1521 (2016).

  55. 55.

    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B 57, 289–300 (1995).

  56. 56.

    Son, E. Y. et al. Conversion of mouse and human fibroblasts into functional spinal motor neurons. Cell Stem Cell 9, 205–218 (2011).

  57. 57.

    Labun, K., Montague, T. G., Gagnon, J. A., Thyme, S. B. & Valen, E. CHOPCHOP v2: a web tool for the next generation of CRISPR genome engineering. Nucleic Acids Res. 44, W272–W276 (2016).

  58. 58.

    Meijering, E. et al. Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. Cytometry Part A 58A, 167–176 (2004).

  59. 59.

    Ferreira, T. A. et al. Neuronal morphometry directly from bitmap images. Nat. Methods 11, 982–984 (2014).

  60. 60.

    Taylor, A. M. et al. A microfluidic culture platform for CNS axonal injury, regeneration and transport. Nat. Methods 2, 599–605 (2005).

  61. 61.

    Edgar, R., Domrachev, M. & Lash, A. E. Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210 (2002).

Download references


This research was supported by HHMI, Project ALS, HSCI, Target ALS and the NINDS grant NIH5R01NS089742 to K.E. J.R.K. is the Project ALS Tom Kirchhoff Family Postdoctoral Fellow. B.N.D.-D. was supported by the Milton Safenowitz postdoctoral fellowship from the ALS Association. A. Burberry was supported by the US National Institutes of Health (1K99AG057808–01A1). D.A.M. was funded by the MGH training grant (5T32CA009216) and is grateful for the assistance of the Massachusetts ADRC neuropathology core in preparing tissue samples. B.J.W. is a New York Stem Cell Foundation – Robertson Investigator. We thank D. Cleveland for the generous gift of TDP-43 (FL9) antibody.

Author information

Author notes

    • Luis A. Williams
    •  & Seth H. Cassel

    Present address: Q-State Biosciences, Cambridge, MA, USA

    • Brandi N. Davis-Dusenbery
    •  & Seth H. Cassel

    Present address: Seven Bridges Genomics, Cambridge, MA, USA

    • Rob Moccia
    •  & Brian J. Wainger

    Present address: Pfizer, Inc., Cambridge, MA, USA

  1. These authors contributed equally: Joseph R. Klim and Luis A. Williams.


  1. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA

    • Joseph R. Klim
    • , Luis A. Williams
    • , Francesco Limone
    • , Irune Guerra San Juan
    • , Brandi N. Davis-Dusenbery
    • , Daniel A. Mordes
    • , Aaron Burberry
    • , Kanchana K. Gamage
    • , Rob Moccia
    • , Seth H. Cassel
    •  & Kevin Eggan
  2. Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA

    • Joseph R. Klim
    • , Luis A. Williams
    • , Francesco Limone
    • , Irune Guerra San Juan
    • , Brandi N. Davis-Dusenbery
    • , Daniel A. Mordes
    • , Aaron Burberry
    • , Kanchana K. Gamage
    • , Rob Moccia
    • , Seth H. Cassel
    •  & Kevin Eggan
  3. Harvard Stem Cell Institute, Harvard University, Cambridge, MA, USA

    • Joseph R. Klim
    • , Luis A. Williams
    • , Francesco Limone
    • , Irune Guerra San Juan
    • , Brandi N. Davis-Dusenbery
    • , Daniel A. Mordes
    • , Aaron Burberry
    • , Kanchana K. Gamage
    • , Rob Moccia
    • , Seth H. Cassel
    •  & Kevin Eggan
  4. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    • Joseph R. Klim
    • , Luis A. Williams
    • , Francesco Limone
    • , Irune Guerra San Juan
    • , Brandi N. Davis-Dusenbery
    • , Daniel A. Mordes
    • , Aaron Burberry
    • , Kanchana K. Gamage
    • , Rob Moccia
    • , Seth H. Cassel
    •  & Kevin Eggan
  5. Hubrecht Institute for Developmental Biology and Stem Cell Research, Royal Netherlands Academy of Arts and Sciences, Utrecht, The Netherlands

    • Francesco Limone
  6. Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    • Irune Guerra San Juan
  7. Department of Pathology, Massachusetts General Hospital, Boston, MA, USA

    • Daniel A. Mordes
  8. Harvard T. H. Chan School of Public Health, Boston, MA, USA

    • Michael J. Steinbaugh
    •  & Rory Kirchner
  9. Amgen Research, Amgen, Inc., Cambridge, MA, USA

    • Kanchana K. Gamage
  10. Harvard Medical School, Boston, MA, USA

    • Seth H. Cassel
  11. Medical Scientist Training Program, Harvard Medical School, Boston, MA, USA

    • Seth H. Cassel
  12. FM Kirby Neurobiology Center, Boston Children’s Hospital and Department of Neurobiology, Harvard Medical School, Boston, MA, USA

    • Kuchuan Chen
    • , Brian J. Wainger
    •  & Clifford J. Woolf
  13. Massachusetts General Institute for Neurodegenerative Disease, Massachusetts General Hospital, Boston, MA, USA

    • Brian J. Wainger


  1. Search for Joseph R. Klim in:

  2. Search for Luis A. Williams in:

  3. Search for Francesco Limone in:

  4. Search for Irune Guerra San Juan in:

  5. Search for Brandi N. Davis-Dusenbery in:

  6. Search for Daniel A. Mordes in:

  7. Search for Aaron Burberry in:

  8. Search for Michael J. Steinbaugh in:

  9. Search for Kanchana K. Gamage in:

  10. Search for Rory Kirchner in:

  11. Search for Rob Moccia in:

  12. Search for Seth H. Cassel in:

  13. Search for Kuchuan Chen in:

  14. Search for Brian J. Wainger in:

  15. Search for Clifford J. Woolf in:

  16. Search for Kevin Eggan in:


L.A.W., B.N.D.-D. and K.E. conceived the approach for identifying hMN RNA targets of TDP-43. L.A.W. and B.N.D.-D. performed siRNA experiments. J.R.K. and F.L. performed iPSC and proteostasis studies. L.A.W. and I.G.S.J. characterized STMN2 expression in neurons with S.H.C. J.R.K., M.J.S., B.N.D.-D., R.K. and R.M. analyzed RNA-Seq and microarray data. J.R.K. and I.G.S.J. generated STMN2 knockouts. I.G.S.J. performed outgrowth and regrowth assays with support from J.R.K., F.L. and K.G. J.R.K., L.A.W. and A.B. developed the cell surface profile to sort neurons. D.A.M. collected the postmortem samples and performed immunohistochemistry. K.C. and B.J.W. performed electrophysiological recordings with support from C.J.W. J.R.K. and L.A.W. contributed equally to the manuscript. F.L. and I.G.S.J. contributed equally to these studies. J.R.K., L.A.W. and K.E. wrote the manuscript. K.E. supervised all aspects of the study. All authors reviewed and edited this manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Kevin Eggan.

Integrated supplementary information

  1. Supplementary Figure 1 Production of differentiated human motor neurons.

    a, hMN differentiation, purification, and culture strategy. b, Flow-cytometric analysis of differentiated HUES3 Hb9::GFP cells. Cells not treated with the RA and SHH pathway agonist were used as negative control for the gating of GFP expression. c–f, Micrographs and quantification of purified Hb9::GFP+ cells immunostained for HB9 and counterstained with DAPI (c) (Scale bar, 10 μm) or immunostained for ISL1 and the neuronal markers β-III tubulin and MAP2 (e) (Scale bar, 20 μm). g–i, Differentiated motor neurons are electrophysiologically active as determined by whole-cell patch-clamp recordings. g, On depolarization in voltage-clamp mode, cells exhibited fast inward currents followed by slow outward currents, indicating the expression and opening of voltage-activated sodium and potassium channels, respectively. h, In current-clamp mode, depolarization elicited repetitive action potential firing. i, Response to Kainate is consistent with the expression of functional receptors for excitatory glutamatergic transmitters. Similar results were obtained for these experiments in n = 2 independent experiments.

  2. Supplementary Figure 2 TDP-43 knockdown in cultured hMNs.

    a, RNAi strategy for TDP-43 knockdown in cultured motor neurons. b, Phase and red fluorescence micrographs of cultured hMNs 4 days after treatment with different siRNAs including scrambled siRNA conjugated to Alexa Fluor 555 (siRED). c, Flow-cytometric analysis of hMNs after treatment with different siRNAs. d, Relative levels of TDP-43 mRNA in motor neurons exposed to different siRNAs for 2, 4 or 6 days. Levels for each sample were normalized to GAPDH and expressed relative to the no transfection control. Data are displayed as mean of technical replicates with s.d. of replicates from n = 2 experiments. e, Immunoblot analysis of hMNs after RNAi treated with the indicated siRNAs. Each sample was normalized using GAPDH, and TDP-43 protein levels were calculated relative to the siRED-treated control sample. Similar results were obtained for these experiments in n = 3 independent experiments.

  3. Supplementary Figure 3 Human motor neuron RNA-seq.

    a, Transcriptional analysis of motor neurons treated as indicated represented as a heat map for control (n = 9) and TDP43 knockdown (n = 6) samples for n = 2 independent experiments. b, Analysis of TDP-43 transcript abundance after RNA-Sequencing validated the knockdown. Data are displayed as mean with s.d. of replicates from n = 2 independent (Wald test and a cutoff of 0.05 for Benjamini–Hochberg adjusted P values).

  4. Supplementary Figure 4 Enrichment of postmitotic hMNs by FACS.

    a, Using a cell surface marker screen, we identified antibodies enriched on GFP+ motor neurons (Quadrant 1) and GFP- cells (Quadrant 3). b, After sorting for NCAM+ and EpCAM- cells, we used high content imaging to determine our sorting method can deplete the cultures of mitotic cells (EdU+) and significantly enrich for motor neurons (Isl1+) and neurons (MAP2+). n = 6 different iPSC lines (unpaired t-test, two-sided, P < 0.05). c–e, qRT-PCR analysis of sorted and unsorted cultures for the neuronal marker βIII-tubulin (c) and the motor neuron markers ISL1 (d) and VaCHT1 (e) revealed enrichment after sorting for NCAM+ and EpCAM- cells. Data are displayed as mean of technical replicates with s.d. from n = 6 iPSC lines (unpaired t-test, two-sided, P < 0.05). f, Flow-cytometric analysis with phycoerythrin (PE)-conjugated antibodies to EpCAM (anti-epCAM–PE) and Alexa Fluor 700–conjugated antibodies to NCAM (anti-NCAM–AF700) of cultures differentiated from the indicated healthy controls (gray) and TDP-43 mutant lines (red). g, The percentage of NCAM+ cells for the indicated lines. Data are displayed as mean with s.d. from n = 4 independent differentiations (unpaired t-test, two-sided, P < 0.05). h–i, NCAM+ neurons from 11a were plated onto multielectrode arrays to measure neuronal activities including spiking and bursting over time. Similar results were obtained for n = 3 iPSC lines sorted using NCAM.

  5. Supplementary Figure 5 Patient-specific induced pluripotent stem cell characterization.

    a, Sequencing chromatograms of Exon6 of TARDBP in the indicated iPSC lines to confirm the heterozygous mutations in the patient lines. b, Representative micrographs of control and patient neurons immunostained for TDP-43 (red), β-III tubulin (green) and counterstained with DAPI (blue). Scale bar, 100 μm. n = 4 control and three patient lines with similar results in two independent experiments. c, The nuclear TDP-43 intensity and the cytoplasmic TDP-43 intensity was determined to compare the nuclear/cytoplasmic ratio between the neurons differentiated from the indicated cell lines. Data are displayed as individual neurons n = 4 control and three patient lines with similar results in two independent experiments (unpaired t-test, two-sided, P < 0.05). d–e, Immunoblot analysis of TDP-43 in the detergent-soluble (RIPA) (d) and detergent-insoluble (urea) (e) fractions in the indicated cell lines. Protein levels were normalized to GAPDH and are expressed relative to the normalized population average. Data are displayed as two technical replicates from two independent experiments from n = 4 control and four patient iPSC lines. (unpaired t-test, two-sided, P < 0.05). Similar results were obtained in two independent experiments.

  6. Supplementary Figure 6 TDP-43 regulates STMN2 in hMNs and TDP-43 binding sites are enriched in STMN2.

    ac, qRT-PCR validation of the downregulation of ALS genes on siRNA treatments. Expression of (a) TARDBP, (b) FUS and (c) C9ORF72 was assessed for all the controls and each siRNA used. Data are displayed as mean with s.d. of technical replicates. Similar results were obtained from n = 2 independent experiments. d, Western blot analysis of STMN2 protein in different cell types along the motor neuron differentiation. Similar results were obtained from n = 3 independent experiments. e, RNA-Seq expression levels for the Stathmin family in motor neurons treated with either siSCR (−) or siTDP43 (+) oligos. Data are displayed as box and whisker plots showing min to max for control (n = 9) and TDP43 knockdown (n = 6) samples and significance was tested using the Wald test and a cutoff of 0.05 for Benjamini–Hochberg adjusted P values with no log2 fold-change ratio cutoff. Only STMN2 levels were altered after TDP-43 knockdown. f–g, TDP-43 binding sites within the Stathmin family of genes (f) normalized to gene length (g). STMN2 has the greatest number of binding motifs.

  7. Supplementary Figure 7 TDP-43 regulates cryptic exon splicing in hMNs.

    ab, Visualization of the cryptic exons for PFKP (a), ELAVL3 (b), for the cells treated with scrambled siRNAs or targeting TDP-43 transcript. c, Visualization of the cryptic exon in STMN2 for n = 5 controls and n = 5 ALS patients compared to in vitro hMNs treated with control or siTDP-43 siRNAs. Orange arrows indicate the cryptic exon and splice ribbons from exon 1 to the cryptic exon are highlighted in orange. Read coverage and splice junctions are shown for alignment to the human hg19 genome.

  8. Supplementary Figure 8 STMN2 expression is decreased in human motor neurons expressing TDP-43 from the AAVS1 locus.

    a, AAVS1 gene targeting and genotyping strategy. b, Genotyping the AAVS1 locus after targeting demonstrates a single copy integration. Similar data were obtained for two independent experiments. c, qRT-PCR analysis of STMN2 in motor neurons differentiated from the HUES3 Hb9::GFP and the gene targeted lines expressing wildtype or mutant TDP-43. Data are displayed as mean with s.d. of technical replicates from n = 2 independent experiments (unpaired t-test, two-sided, P < 0.05).

  9. Supplementary Figure 9 Proteasome activity assays.

    a, MG-132 neuronal survival experimental outline. b, Dose response curve for hMNs cultured with indicated concentrations of MG-132 for the indicated times. Data are displayed as technical replicates from n = 2 independent experiments and the lines represent the mean. Cells were viable after 1 day of treatment at all concentrations tested and lower concentrations were tolerated for more extended periods of time. Similar results have been obtained for n = 4 independent experiments. c, Following cleavage by the proteasome, substrate for luciferase is liberated, which allows for quantitative measurement of proteasome activity. Neurons treated with MG-132 show significantly decreased proteasome activity. Data are displayed as box and whisker plots showing min to max for technical replicate from n = 2 independent experiments (unpaired t-test, two-sided, P < 0.05).

  10. Supplementary Figure 10 STMN2 levels are decreased in the TDP-43 mislocalization model.

    a, Experimental strategy used to assess the effect of proteasome inhibition on TDP-43 localization in hMNs. b, Pearson’s correlation analysis for TDP-43 immunostaining and DAPI fluorescence of cells treated with MG-132 (1 μM). Data are displayed as dots representing individual neurons with mean and s.d. (unpaired t-test, two-sided, P value for untreated versus DMSO (0.53), Day 1(< 0.0001), Day 2 (< 0.0001), Day 3 (< 0.0001), Day 4 (0.0018), Day 5 (0.69), Day 6 (0.26) and Day 7 (0.78)). c, Micrographs of HUES3 hMNs untreated or treated with MG-132 and immunostained for TDP-43 (red), β-III tubulin (green) and counterstained with DAPI (blue). Scale bar, 100 μm. Similar results were obtained in n = 2 independent experiments. d, hMNs were treated with DMSO or MG-132 (1 μM) for 24 h and then immunostained for TDP-43 (red), β-III tubulin (green) and counterstained with DAPI (blue). The nuclear TDP-43 intensity and the cytoplasmic TDP-43 intensity was determined to compare the nuclear/cytoplasmic ratio between the MG-132-treated cells and DMSO-treated cells. Data are displayed as dots representing individual neurons with mean and s.d. (unpaired t-test, two-sided, P < 0.05). Similar results were obtained in n = 2 independent experiments. e, Immunoblot analysis of TDP-43 in the detergent-soluble (RIPA) and detergent-insoluble (urea) fractions in neurons treated with MG-132 (unpaired t-test, P < 0.05). Similar results were obtained in n = 4 biologically independent experiments. f, qRT-PCR analysis of STMN2 expression for motor neurons treated with MG-132 at the indicated concentrations and durations relative to DMSO control (unpaired t-test, two-sided, P < 0.05). Similar results were obtained in n = 2 independent experiments. gh, Diagram of RT-PCR detection stratagey for STMN2 cryptic exon (g) and Sanger sequencing of the PCR product confirmed the splicing of STMN2 Exon 1 with the cryptic exon (h). Similar results were obtained in n = 2 independent experiments.

  11. Supplementary Figure 11 STMN2 regulates neuronal outgrowth.

    ac, CRISPR-mediated STMN2 knockout in the WA01 line was confirmed by RT-PCR analysis of genomic DNA (a), by immunoblot analysis (b) and by immunofluorescence (c). d–f, Sholl analysis of hMNs with and without STMN2 and in the presence of a Y-27632 (10 μM), a ROCK inhibitor (f). Lines represent sample means and shading represent the SEM with unpaired t-test between siTDP43 and siSCR, two-sided, P < 0.05 with all full statistical analysis in Supplementary Table 1. Similar results were obtained in n = 2 biologically independent experiments. gh, Axonal regrowth after injury. Representative micrographs of hMNs in the microfluidics device prior to and after axotomy (g). Analysis of axonal regrowth after axotomy. Individual neurites are displayed as dots along with the mean and s.d. (unpaired t-test, two-sided, P < 0.05 at 18 h= 0.0002, 24 h=< 0.0001, 48 h= <0.0001). Similar results were obtained in n = 4 devices from two independent experiments. i, Representative micrographs of hMNs cultured in the microfluidic devices immunostained for MAP2 (red), β-III tubulin (green) and counterstained with DAPI (blue). White lines indicate the borders of the channels. The absence of MAP2 in the opposite chamber suggests an axonal identity for the traversing neurites.

  12. Supplementary Figure 12 Molecular model of ALS pathogenesis.

    Our study highlights splicing defects downstream of TDP-43 perturbations including decline after TDP-43 knockdown, patient-specific mutations, following TDP-43 mislocalization, and in postmortem patient spinal cord. These perturbations commonly affect STMN2 levels, which is a critical factor for motor neuron axonal outgrowth and regeneration. Inhibiting JNK can boost STMN2 protein levels to rescue neuronal outgrowth deficits associated with TDP-43 knockdown.

  13. Supplementary Figure 13 Uncropped immunoblot and DNA gel images.

    ad, Immunoblots from Fig. 3b (1. No Tx 2. siRed 3. siSCR1 4. siSCR2 5. siTDP43–1 6. siTDP43-) and the immunoprecipitation in Fig. 3d. e, Immunoblots from Fig. 6c and Supplementary Fig. 11b. f–g, Immunoblots from Fig. 8. h–i, Immunoblots from Supplementary Fig. 2h,i. j–k, Immunoblots from Supplementary Fig. 5d,e. l–m, Immunoblots from Supplementary Fig. 6d. n–o, Immunoblots from supplementary Fig. 10e. p, Agarose gel images from Fig. 6b and Supplementary Fig. 11a. q, Tapestation gel from Supplementary Fig. 10g.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–13

  2. Reporting Summary

  3. Supplementary Table 1

    Sholl analysis statistical data

About this article

Publication history