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Traumatic injury compromises nucleocytoplasmic transport and leads to TDP-43 pathology

  1. Eric N Anderson
  2. Andrés A Morera
  3. Sukhleen Kour
  4. Jonathan D Cherry
  5. Nandini Ramesh
  6. Amanda Gleixner
  7. Jacob C Schwartz
  8. Christopher Ebmeier
  9. William Old
  10. Christopher J Donnelly
  11. Jeffrey P Cheng
  12. Anthony E Kline
  13. Julia Kofler
  14. Thor D Stein
  15. Udai Bhan Pandey  Is a corresponding author
  1. Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, United States
  2. Department of Chemistry and Biochemistry, University of Arizona, United States
  3. Department of Pathology and Laboratory Medicine, Boston University School of Medicine, United States
  4. Boston VA Healthcare System, United States
  5. Department of Neurobiology, University of Pittsburgh School of Medicine, United States
  6. LiveLike Lou Center for ALS Research, Brain Institute, University of Pittsburgh School of Medicine, United States
  7. Molecular, Cellular & Developmental Biology, University of Colorado, United States
  8. Physical Medicine & Rehabilitation; Safar Center for Resuscitation Research, University of Pittsburgh, United States
  9. Center for Neuroscience; Center for the Neural Basis of Cognition; Critical Care Medicine, University of Pittsburgh, United States
  10. Department of Pathology, University of Pittsburgh, United States
  11. Department of Human Genetics, University of Pittsburgh School of Public Health, United States
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Cite this article as: eLife 2021;10:e67587 doi: 10.7554/eLife.67587

Abstract

Traumatic brain injury (TBI) is a predisposing factor for many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), Alzheimer’s disease (AD), Parkinson’s disease (PD), and chronic traumatic encephalopathy (CTE). Although defects in nucleocytoplasmic transport (NCT) is reported ALS and other neurodegenerative diseases, whether defects in NCT occur in TBI remains unknown. We performed proteomic analysis on Drosophila exposed to repeated TBI and identified resultant alterations in several novel molecular pathways. TBI upregulated nuclear pore complex (NPC) and nucleocytoplasmic transport (NCT) proteins as well as alter nucleoporin stability. Traumatic injury disrupted RanGAP1 and NPC protein distribution in flies and a rat model and led to coaggregation of NPC components and TDP-43. In addition, trauma-mediated NCT defects and lethality are rescued by nuclear export inhibitors. Importantly, genetic upregulation of nucleoporins in vivo and in vitro triggered TDP-43 cytoplasmic mislocalization, aggregation, and altered solubility and reduced motor function and lifespan of animals. We also found NUP62 pathology and elevated NUP62 concentrations in postmortem brain tissues of patients with mild or severe CTE as well as co-localization of NUP62 and TDP-43 in CTE. These findings indicate that TBI leads to NCT defects, which potentially mediate the TDP-43 pathology in CTE.

Introduction

Traumatic brain injury (TBI) is one of the most common causes of death and disability worldwide (Zaninotto et al., 2018). Indeed, secondary injuries resulting from TBI can lead to long-term neurological and neuropsychiatric sequalae, including neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) (Chen et al., 2007; Peters et al., 2013), Alzheimer’s disease (AD) (Lye and Shores, 2000; Sivanandam and Thakur, 2012), and Parkinson’s disease (Goldman et al., 2006; Harris et al., 2013; Taylor et al., 2016). TBI is also linked with development of chronic traumatic encephalopathy (CTE), a progressive neurodegenerative syndrome associated with repeated head trauma (Chauhan, 2014; Gardner and Yaffe, 2015; Stern et al., 2011). Postmortem brain tissues from repeated trauma patients such as CTE as well as animal models of TBI show microtubule-associated protein (TAU) and TAR DNA/RNA binding protein (TDP-43) pathology (Blennow et al., 2012; Huang et al., 2017; Mckee et al., 2018; McKee et al., 2010; Tan et al., 2018; Wang et al., 2015; Wiesner et al., 2018). TDP-43 pathology is a hallmark of neurodegeneration and is present in ~97 % of ALS cases, ~45 % of cases with frontotemporal dementia (FTD) (Ling et al., 2013), and ~60 % of AD cases (Amador-Ortiz et al., 2007; Arai et al., 2009; Uryu et al., 2008). Despite evidence of TDP-43 pathology as a biomarker of neurodegeneration, it remains unclear how repeated trauma promotes TDP-43 proteinopathy.

TDP-43 is a predominantly nuclear DNA/RNA-binding protein that shuttles between the nucleus and cytoplasm (Ayala et al., 2008). TDP-43 regulates RNA processing such as gene transcription, mRNA splicing, mRNA stability, and mRNA transport and localization, and pathological mutations disrupt RNA metabolism (Arnold et al., 2013; Bose et al., 2008; Buratti and Baralle, 2001; Polymenidou et al., 2012). In many neurodegenerative diseases, TDP-43 mislocalizes from the nucleus and aggregate in the cytoplasm of cells. Cytoplasmic TDP-43 aggregates are proposed to be an important mechanistic link to neurodegeneration because these aggregates are abnormally phosphorylated and ubiquitinated (Arai et al., 2009; Arai et al., 2006; Neumann et al., 2006). Multiple mechanisms have been proposed to explain abnormal cytoplasmic accumulation of TDP-43 and progressive spreading of TDP-43 pathology in the context of neurodegenerative diseases.

TDP-43 contains a prion-like low complexity domain and has an intrinsically disordered region (IDR) that renders TDP-43 aggregation-prone (Calabretta and Richard, 2015; Johnson et al., 2009; Mann et al., 2019). IDRs in RNA binding proteins (RBPs) are thought to play key roles in assembly of ribonuclear protein granules such as P-bodies, stress granules, and neuronal granules (Bakthavachalu et al., 2018; Jain et al., 2016; Kedersha et al., 2013), suggesting that mutations or abnormal aggregation of RBPs may disrupt dynamics of these granules (Molliex et al., 2015; Murakami et al., 2015; Patel et al., 2015). Further, IDRs in RBPs such as TDP-43 undergo liquid-liquid phase separation, and pathological mutations in TDP-43 alter liquid-liquid phase separation, which may contribute to disease processes (Conicella et al., 2016; Johnson et al., 2009; McGurk et al., 2018). Alteration in RBPs such as TDP-43 could therefore be an important indicator of neurodegeneration. However, although these mechanisms potentially explain the role of pathological mutations of TDP-43 in the context of neurodegenerative disease, how TDP-43 aggregates form and lead to neurodegeneration in the absence of mutations, such as in the brains of repeated trauma patients, is unclear.

TDP-43 aggregates in ALS/FTD were recently reported to sequester nucleoporins, transport proteins, and other factors, suggesting that TDP-43 aggregation strongly impairs nucleocytoplasmic transport (NCT) and nucleopore complexes (Chou et al., 2018). Moreover, NCT is also disrupted in AD (Eftekharzadeh et al., 2018), ALS (Zhang et al., 2015), and Huntington’s disease (HD) (Gasset-Rosa et al., 2017; Grima et al., 2017), suggesting a common dysfunctional pathway in these neurodegenerative diseases. However, the mechanism of TDP-43 pathology in neurodegeneration resulting from repeated head trauma is unknown. We previously demonstrated that repetitive trauma leads to ubiquitin, p62, and TDP-43 inclusion as well as stress granule pathology in Drosophila brains (Anderson et al., 2018). Here, we performed proteomic analysis on Drosophila brains to identify the molecular pathways that were altered in response to traumatic injury.

In this manuscript, we found that repeated trauma upregulates nuclear pore proteins, alter nucleoporin stability, and NCT proteins as well as alters RanGAP1 and nucleoporins distribution, and NCT in vivo. In addition, pharmacological inhibition of nuclear export protects against TBI-mediated lethality and NCT defects. Intriguingly, upregulation of nucleoporins in vivo and in vitro leads to TDP-43 mislocalization, aggregation, phosphorylation, and alteration in solubility, and decreased motor function as well as lifespan. Our findings of NUP62 pathology and increased NUP62 concentrations in brain tissues from patients with CTE suggest that NCT defects are linked with traumatic injury, which potentially mediates TDP-43 pathology.

Results

TBI alters the Drosophila brain proteome, perturbs NCT proteins, and Nup protein level

To examine the mechanism of TBI, we used a well-characterized Drosophila model of TBI that exhibits robust phenotypes such as TDP-43 homolog (Tbph), p62, stress granules, and ubiquitin pathology (Anderson et al., 2018; Katzenberger et al., 2015; Katzenberger et al., 2013) to identify and investigate changes in the brain proteome post-TBI (Figure 1A). An unbiased proteomics analysis of 2000 proteins from third instar control (w1118) Drosophila larval brains exposed to repeated TBI identified 361 proteins that were significantly changed in response to traumatic injury (p ≤ 0.05, student’s T-test). Complex network analysis based on gene ontology (GO) association analysis in BiNGO (Cytoscape 3) of the TBI-associated brain proteome compared to non-TBI controls identified distinct categories of altered proteins, with the majority upregulated (Figure 1B and C; Figure 1—figure supplement 1A-E; Supplementary files 1 and 3). Top categories that were upregulated after TBI were microtubule cytoskeleton, protein folding, and the proteasome. In addition, we also identified proteins involved in the ribonuclear protein complex and spliceosome. Components of the nuclear pore complex (NPC) and NCT pathway were a major subset of proteins upregulated post-TBI (Figure 1—figure supplement 1F). The NPC pathway has not previously been linked to trauma-mediated neurodegeneration but has been reported to be disrupted in ALS/FTD, AD, HD, and other neurodegenerative diseases (Chou et al., 2018; Eftekharzadeh et al., 2018; Grima et al., 2017; Zhang et al., 2015). Therefore, we decided to further examine the NPC alteration in mediating TDP-43 pathology in TBI.

Figure 1 with 1 supplement see all
Proteomic analysis of Drosophila brains identifies novel components of the nucleocytoplasmic transport machinery that are disrupted in response to TBI.

(A) Schematic flow of Drosophila larval brain traumatic injury, dissection, and proteomics analysis. (B) Volcano plot showing fold-change and p-values for all detected proteins (student’s t-test, assuming equal variances). (C) Heat map showing change in protein expression for 2000 detected proteins. Proteins with a significant change (p < 0.05) are indicated. (D) Volcano plot showing fold change and p-values of all nucleoporins and nuclear transport proteins. Traumatic injury upregulates components of the nuclear pore and nucleocytoplasmic transport. (E) Heat map and p-values for proteins with more than ±1.4-fold change with the indicated nucleoporins. (F–I) Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) analysis of nucleoporins identified in the proteomics analysis showed significant increases in (F) Nup93-2, (G) Nup54, (H) Nup62, and (I) Nup214 mRNA levels in w1118 Drosophila larval brains exposed to trauma (eight hits @ 50° angle) compared to control animals (n = 3, *p < 0.05, **p < 0.01, ****p < 0.0001). (J–L) qPCR analysis of Nup62 (J, **p < 0.01), Nup214 (K, **p < 0.01), and Nup54 (L, **p < 0.001) mRNA levels in adult Drosophila brains showed a significant increase in response to trauma as compared to control brains (n = 3). (M) qRT-PCR analysis of nuclear export factor Emb (exportin) mRNA post-trauma compared to non-trauma controls (n = 3, ***p < 0.001). (N) Western blot of Drosophila larval brains exposed to trauma (one or eight hits @ 50° angle) and controls (0 hits) probed for Nup214 protein. Drosophila Gapdh is shown as a loading control. (O) Quantification of western blots of Drosophila Nup214 protein levels compared to controls (n = 3, **p < 0.01, ***p < 0.001, n.s. = not significant). (P) Western blot of Nup214 protein level in larval brains at 0, 2, 4, and 6 hr post-injury or controls. (Q) Quantification of Nup214 protein levels in larval brains of trauma and control at 0, 2, 4, and 6 hr (n = 3). (R) Western blot of Nup214 protein level in adult brains at 0, 2, 4, 24, and 72 hr post-injury or controls. (S) Quantification of Nup214 level levels in adult brains of trauma and control at 0, 2, 4, 24, and 72 hr (n = 3). All qRT-PCR and western blot analysis were done in triplicate using biological replicates. One-tailed t-test was used in panels F–L and O. One-way ANOVA with Tukey’s multiple comparisons tested was used for panel N. All quantification represents mean ± s.e.m.

NPC is a large multi-protein complex that spans the nuclear envelope and mediates NCT. In vertebrates, NPC comprises multiple copies of ~30 proteins called nucleoporins (Nups) with highly conserved function between species (Nofrini et al., 2016). Our proteomics analysis revealed that several Nups were upregulated in response to TBI in Drosophila brains (Figure 1D and E). Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) analysis of these Nups confirmed that TBI significantly upregulated Nup93-2 (p < 0.01), Nup54 (p < 0.001), Nup62 (p < 0.01), Nup44A (p < 0.05), and Nup214 (p < 0.05) mRNA levels in Drosophila larval (Figure 1F–I andFigure 1 − Figure Supplement 1G) and adult brains (Figure 1J–L; Nup62, p < 0.01; Nup214, p < 0.01; Nup54, p < 0.001). In addition, mRNA levels of nuclear export gene Emb (Exportin) were significantly increased post-TBI (Figure 1M, p < 0.001), while the microtubule-associated protein Futsch showed no change in mRNA levels compared to controls (Figure 1 − Figure Supplement 1H), consistent with proteomics analysis. Western blotting further confirmed a TBI-dependent increase in Drosophila Nup214 protein levels in larval brains (Figure 1N and O).

We next asked if trauma alter endogenous nucleoporin protein levels overtime. To address this, we measured Nup214 protein levels in trauma and control larval and adult brains. We performed time-course analysis on larval (0, 2, 4, and 6 hr) or adult (0, 2, 4, 24, and 72 hr) animals’ post-injury to assess Nup214 protein level by Western blot analysis. Interestingly, we found that Nup214 protein level remains upregulated in both larval and adult brains over the time point examined (Figure 1P,Q,R,S), suggesting that trauma probably disrupts Nup214 levels and possibly turnover in vivo.

TBI disrupts NPC and RanGAP1 distribution and leads to TBPH/NPC coaggregation

To test whether repeated trauma disrupts NPC, we examined the distribution on the nuclear membrane of TBI Drosophila brains. Using the NPC marker Mab414, which recognizes the FG domains of several Nups including Nup62, we found a predominantly homogenous rim-like labeling of the nuclear membrane in non-TBI control Drosophila brains. NPC staining in the ventral nerve cord (VNC) in non-TBI control brains appeared distributed evenly. In contrast, nuclear membrane NPC staining in VNCs exposed to TBI was irregular and revealed a disturbed nuclear morphology. We observed gaps in the nuclear membrane and the appearance of aggregation (Mab414 clumps) in brains post-TBI (Figure 2A). Quantitatively, the percentage of cells with abnormal Mab414 staining was significantly higher in TBI brains than non-TBI controls (Figure 2B, p < 0.001), suggesting that traumatic injury disrupts NPC morphology. Next, we asked whether Tbph aggregation identified in our Drosophila larval and adult model of trauma (Anderson et al., 2018) co-aggregate with NPC (Mab414). We found perinuclear and cytoplasmic coaggregation of Tbph and Mab414 in TBI-exposed VNCs, while control brains showed little to no coaggregation (Figure 2C). Quantification showed that the percentage of Mab414–Tbph-positive cells with coaggregation was significantly higher in TBI-exposed VNCs compared to controls (Figure 2D, p < 0.001).

Figure 2 with 2 supplements see all
Nuclear pore complex morphology and RanGAP1 distribution defects as well as TBPH/NPC coaggregation after traumatic injury in vivo.

(A) Immunofluorescence images of the ventral nerve cord (VNC) of trauma brain injury (Trauma) and non-TBI control w1118 Drosophila larvae stained with the nuclear pore complex (NPC) marker (Mab414, red) marker and nuclei (DAPI, blue). TBI NPCs show gaps in membranes (arrows) with signs of aggregation (arrow heads). Scale bar = 15 µM. (B) Quantification of percentage of VNC cells with abnormal (Gaps and aggregation) Mab414 staining after TBI compared to non-TBI controls (n = 7–9 larval VNCs, ***p < 0.001). (C) Representative images of larval VNCs in TBI and control brains stained for the Drosophila homolog of TDP-43, TAR DNA-binding protein-43 homolog (Tbph, red), and Mab414 (green), showing perinuclear as well as cytoplasmic coaggregation (arrows, yellow). Scale bar = 20 µM. (D) Percentage of cells with Tbph/Mab414 coaggregation in the VNCs of TBI and control brains (n = 8 larval VNCs, ***p< 0.001). (E) Immunofluorescence of RanGAP1 (gray) and Lamin (red) in TBI and control VNCs shows aberrant RanGAP1 staining in TBI brains (intense nuclear and cytoplasmic staining, arrows). Scale bar = 15 µM. (F) Percentage of cells with abnormal RanGAP1 staining in TBI VNCs compared to controls (n = 6 larval VNCs, ***p < 0.001). (G) Schematic of control cortical impact (CCI) model of TBI (adopted from Xiong et al., 2013). (H) Immunohistochemical staining of RanGAP1 in rat hippocampal region (granule cell layer and subgranular zone) underlying the cortex in TBI animals or controls shows intense nuclear staining (arrow heads) and cytoplasmic aggregation (arrows). Inset box shows ×40 magnification (scale bar = 50 µM). (I) Percentage of cells with RanGAP1 pathology (cytoplasmic/nuclear aggregate or intense nuclear/cytoplasmic mislocalization) in TBI brains and controls (n = 4, **p < 0. 01). (J) Immunohistochemical staining of Nup62 in rat hippocampal regions shows intense nuclear staining (arrow heads) and cytoplasmic aggregation (arrows). Inset box shows ×40 magnification (scale bar = 50 µM). (K) Percentage of cells with Nup62 pathology (cytoplasmic/nuclear aggregate or intense nuclear/cytoplasmic mislocalization) in TBI brains and controls (n = 4, **p < 0.01). One-tailed t-tested was used in panel B, D, F, I, and K. Data represent mean ± s.e.m.

Ran GTPase-activating protein 1 (RanGAP1), which is located on cytoplasmic filaments of the NPC, is required for Ran-dependent nuclear import and export (Bischoff et al., 1995). GTP hydrolysis of Ran-GTP by RanGAP1 is essential for cargo release into the cytoplasm during nuclear export (Floch et al., 2014). RanGAP1 maintains the nuclear/cytoplasmic Ran gradient, and its loss causes cell death (Hetzer et al., 2002). Intriguingly, RanGAP1 gradient is disrupted in neurodegenerative diseases including ALS (Zhang et al., 2015) and HD (Grima et al., 2017). Therefore, we examined whether repeated trauma influences RanGAP1 distribution in the VNCs of Drosophila larvae. RanGAP1 in non-TBI control brains appeared mostly uniform in distribution within the nuclear membrane, with few cells showing intense nuclear signals. However, TBI-exposed brains had aberrant distribution of RanGAP1 staining, with intense nuclear and cytoplasmic intensity (Figure 2E, arrows). The percentage of cells with abnormal RanGAP1 distribution was significantly higher in brains post-TBI compared to controls (Figure 2F, p < 0.001), suggesting that repeated traumatic injury disturbs RanGAP1 localization in the brain. TBI-mediated disruption in NPCs or RanGAP1 was not due to apoptosis, as TUNEL assays showed no elevation in cell death immediately after injury (Figure 2—figure supplement 1A,B).

To further determine whether RanGAP1 and Nup mislocalization and/or aggregation occurs in mammals, we assessed distribution in a control cortical impact (CCI) rat model of TBI (Xiong et al., 2013; Figure 2G). Brain cells in hippocampal regions underlying the injured cortex (ipsilateral hemisphere) of rats with TBI exhibited either mislocalization and/or aggregation (arrows) or intense nuclear staining (arrow heads) of RanGAP1, compared to predominantly smooth perinuclear staining in sham controls (Figure 2H). Quantitatively, the percentage of cells with mislocalization and/or aggregation of RanGAP1 was significantly higher in TBI brains than controls (Figure 2I, p < 0.01). In contrast, RanGAP1 pathology in the contralateral hemisphere of trauma brains showed a mild increase that was not significant compared to controls (Figure 2—figure supplement 2A,B).

We also evaluated whether nucleoporins exhibited mislocalization and/or aggregation by staining for NUP62. Although we did not detect many instances of NUP62 aggregation, NUP62 showed dramatic cytoplasmic (arrows) and nuclear (arrow heads) mislocalization in TBI rats compared to sham controls, which showed few instances of cytoplasmic but no nuclear mislocalization (Figure 2J). Quantitatively, the percentage of cells with NUP62 pathology was significantly higher in TBI brains compared to sham controls (Figure 2K, p < 0.01). Similarly, the percentage of cells with NUP62 pathology contralateral to the injury site was significantly higher in TBI brains compared to controls (Figure 2—figure supplement 2C,D, p < 0.05).

TBI-mediated NCT defects and lethality are suppressed by nuclear export inhibitors in vivo

To determine whether TBI impairs nucleocytoplasmic transport in vivo, we overexpressed a GFP protein tagged with a nuclear localization sequence (NLS) and nuclear export sequence (NES) (NLS-NES-GFP) (Kusano et al., 2001) in Drosophila motor neurons (OK371-gal4). GFP signals in NLS-NES-GFP-expressing brains appeared distributed in both the nucleus and cytoplasm (Figure 3A). However, quantitative analysis showed that the percentage of cells with reduced nuclear GFP signals in NLS-NES-GFP-expressing VNCs exposed to TBI was significantly increased while nuclear GFP intensity was significantly reduced (Figure 3B and C, p < 0.001), suggesting that nuclear import of GFP was inhibited and/or nuclear export of GFP was increased. We next expressed a GFP protein tagged with an NLS and mutated NES (ΔNES) without nuclear export activity (Kusano et al., 2001) in motor neurons. Brain cells of non-TBI animals expressing NLS-ΔNES-GFP showed robust GFP localization to the nucleus (Figure 3A), whereas TBI animal VNCs showed significantly increased number of cells with reduced nuclear GFP (p < 0.01) and decreased nuclear GFP intensity (p < 0.001) (Figure 3B and C). Together, these data strongly suggest that traumatic injury impair nuclear import.

Figure 3 with 1 supplement see all
Pharmacological suppression of nuclear export rescues trauma-mediated nucleocytoplasmic transport defects and lethality in vivo.

(A) Representative immunofluorescence images of larval ventral nerve cord (VNC) cells expressing NLS-NES-GFP or NLS-ΔNES-GFP in motor neurons (OK371-gal4) exposed to traumatic brain injury (TBI) or controls (non-TBI) were co-stained for anti-GFP (green) and nuclear envelope marker Lamin (red). Scale bar = 15 µM. (B) Percentage of cells with reduced nuclear GFP signal in animals expressing NLS-NES-GFP (n = 10–11) or NLS-ΔNES-GFP GFP (n = 6–10) exposed to TBI or non-TBI controls (**p < 0.01, ***p < 0.001). (C) Quantification of nuclear GFP signal intensity in TBI and non-TBI NLS-NES-GFP (n = 15) or NLS-ΔNES-GFP (n = 6) expressing animals (***p < 0.001). (D, E) Quantification of eclosion assay of trauma Drosophila larvae treated with DMSO only compared to those treated with (D) KPT-350 (0.05, 0.1, or 0.5 mM) or (E) KPT-276 (50, 200, or 1000 nM). Treatment with KPT-350 or KPT-276 shows a dose-dependent rescue of trauma-mediated lethality (n = 3; *p < 0.05, **p < 0.01). Results indicate one-way ANOVA with Tukey’s multiple comparisons. All quantifications represent mean ± s.e.m. (n = 15 animals per experiment). (F) Representative immunofluorescence confocal images of Drosophila VNCs expressing NLS-NES-GFP or NLS-ΔNES-GFP in motor neurons exposed to TBI and fed KPT-350 (0.5 mM) or DMSO alone for 24 hr show that KPT-350 protects against trauma-mediated depletion of nuclear GFP signal. Scale bar = 15 µM. (G) Quantification of nuclear GFP signal intensity in animals expressing NLS-NES-GFP or NLS-ΔNES-GFP exposed to TBI or non-TBI controls (n = 5–6, ***p < 0.001).

Previously, we showed that repeated trauma in Drosophila larvae leads to lethality (Anderson et al., 2018). To assess whether pharmacological inhibition of trauma-mediated NCT defects protects against lethality, we fed selective inhibitors of nuclear export (SINE) compounds KPT-350 or KPT-276 to Drosophila larvae post-injury. KPT-350 and KPT-276 show neuroprotection in C9orf72 mediated ALS neurons and Drosophila models Tamir et al., 2017; Zhang et al., 2015; KPT-350 reduce cell death in rodent primary cortical neurons expressing HD protein Grima et al., 2017; and KPT-350 protect cortical circuit function and survival of inhibitory interneurons as well as reduce TBI-induced behavioral and histological deficits in a CCI model of TBI (Cantu et al., 2016; Tajiri et al., 2016). Drosophila larvae were exposed to TBI and raised on either DMSO alone, KPT-350 (0.05, 0.1, or 0.5 mM), or KPT-276 (50, 200, or 1000 nM). Eclosion assays on Drosophila larvae that experienced TBI showed a significant dose-dependent suppression of lethality in animals treated with KPT-350 (Figure 3D, **p < 0.01) or KPT-276 (Figure 3E, *p < 0.05, ***p < 0.001). Because KPT-350 and KPT-276 rescue aberrant NCT in Drosophila models of C9 ALS/FTD (Tamir et al., 2017), we examined whether administration of these compounds also protected Drosophila against TBI-mediated NCT defects. Drosophila larvae expressing NLS-NES-GFP or NLS-ΔNES-GFP in motor neurons, exposed to TBI, and fed KPT-350 (0.5 mM) for 24 hr showed strong nuclear GFP intensity compared to DMSO-treated controls (Figure 3F, ***p < 0.001). Quantitatively, nuclear GFP signals in KPT-350-treated flies were significantly higher than DMSO-treated controls (Figure 3G, p < 0.001). KPT-350 treatment in adult Drosophila exposed to TBI showed a dose-dependent suppression of Tbph puncta post-trauma (Figure 3—figure supplement 1A,B, p < 0.05). Taken together, these results suggest that suppression of trauma mediated NCT defects and/or Tbph cytoplasmic puncta via inhibition of nuclear export correlate with increased survival.

NUPs upregulation causes TDP-43/TBPH mislocalization and aggregation in vivo and in vitro

Upregulation of Nups in our proteomics analysis and TDP-43 aggregation post-TBI (Anderson et al., 2018) prompted us to investigate whether Nup upregulation can directly lead to TDP-43 mislocalization. Previous studies report TDP-43 pathology in postmortem brain tissues of patients who experience repeated trauma (Mckee et al., 2018; McKee et al., 2010) as well as in animal models of TBI (Huang et al., 2017; Tan et al., 2018; Wiesner et al., 2018). Consistent with this, we recently showed that repeated traumatic injury in larval and adult Drosophila leads to stress granule induction, ubiquitin, p62 (Ref2(P)), and Tbph pathology (Anderson et al., 2018). Moreover, TDP-43 droplets were recently shown to recruit NUP62 and induce mislocalization of RanGAP1 and Nup107 (Gasset-Rosa et al., 2019), suggesting that NUPs might be important modulators of TDP-43 proteinopathy. To test the impact of Nup upregulation on Tbph (Drosophila TDP-43) pathology, we generated a site-specific Nup62 overexpression (Nup62 OE) fly line and stained for endogenous Tbph. The distribution of Tbph in eGFP control (henceforth referred to as control) expressing Drosophila larval VNC appeared predominantly nuclear, while Nup62 OE larval VNC had dramatically altered Tbph localization with cytoplasmic aggregation (Figure 4A). Quantitative analysis revealed a significant increase in Tbph puncta in Nup62 OE Drosophila larvae or adult brains compared to controls (Figure 4B, p < 0.001; Figure 4—figure supplement 1A,B, p < 0.001). The Tbph puncta in Nup62 OE VNCs congregated with NPC/Mab414 (Figure 4—figure supplement 2A). We further showed that nuclear Tbph intensity in Nup62 OE VNCs was significantly reduced compared to controls (Figure 4C, p < 0.01). Moreover, nuclear-cytoplasmic (N/C) fractionation further confirmed a significantly reduced Tbph N/C ratio in Nup62 OE animals compared to controls (Figure 4D and E, p < 0.01), suggesting that Nup62 upregulation alters the subcellular localization of Tbph in vivo. Mislocalization and aggregation of Tbph caused by Nup62 expression also led us to examine if Tbph solubility was affected by Nup62 expression. Soluble-insoluble fractionation of Nup62 OE or control Drosophila brains showed that upregulation of Nup62 expression in motor neurons shifted Tbph solubility by significantly increasing insolubility compared to controls (Figure 4F and G, p < 0.01), suggesting that Nup62 levels are an important determinant of Tbph solubility. Overexpression of Nup62 was confirmed by qPCR (Figure 4H, p < 0.001).

Figure 4 with 6 supplements see all
Nup62 expression promotes TDP-43 mislocalization and aggregation in vivo and in vitro.

(A) Drosophila larval brain overexpressing Nup62 (Nup62 OE) in motor neurons (Ok371-gal4) and controls (eGFP) stained for the Drosophila homolog of TDP-43, TAR DNA-binding protein-43 homolog (Tbph), and the nuclear envelope marker Lamin, showing Tbph accumulation. Scale bar = 25 µM. Zoom image represents inset box. (B) Quantification of the number of Tbph puncta in Nup62 OE flies compared to controls (n = 5–7, ***p< 0.001). (C) Nuclear Tbph intensity in Nup62 OE flies compared to controls (n = 5–7 brains, **p < 0.01). (D) Western blots of cytoplasmic (C) and nuclear (N) fractions from Drosophila expressing Nup62 OE in motor neurons and control probed for Tbph, lamin, and tubulin. (E) Nuclear-cytoplasmic (N/C) ratio quantification of Tbph in Nup62 OE and control animals (n = 3 blots, **p < 0.01). (F) Western blots of soluble (S) and insoluble (I/S) fractions Drosophila expressing Nup62 OE in motor neurons and controls probed for Tbph and tubulin. (G) Percentage of Tbph solubility in Nup62 OE and control motor neurons (n = 3 blots, **p < 0.01). (H) qRT-PCR analysis of Nup62 mRNA in Nup62 OE animals compared to controls (n = 3, ***p < 0.001). (I) Representative immunofluorescence images of human embryonic kidney 293T (HEK293T) cells transfected with mRuby alone (red) and NUP62-mRuby show endogenous TDP-43 (green) coaggregation with NUP62. NUP62-mRuby co-localizes with endogenous TDP-43 (merge, yellow). Scale bar = 25 µM. (J) Western blots of soluble and insoluble fractions from HEK293T cells transfected with mRuby alone or NUP62-mRuby probed for TDP-43 and tubulin. (K) Quantification of TDP-43 solubility in HEK293T cells transfected with mRuby alone or NUP62-mRuby (n = 3 blots, **p < 0.01). (L) Representative immunofluorescence images of HEK293T cells transfected with NUP62 show phosphorylated TDP-43 accumulation (green) that co-localizes with NUP62 (merged, yellow). Scale bar = 25 µM. qRT-PCR and western blot analysis were done in triplicate using biological replicates. One-tailed t-test was used in panel B, C, E, G, H, and K. All quantification represent mean ± s.e.m.

We further evaluated the impact of Nup62 overexpression on human TDP-43 protein in Drosophila. We crossed Nup62 OE flies to a previously published line made using CRISPR/Cas9 genome editing that removed the endogenous Tbph gene and replaced it with FLAG-tagged wild-type human TDP43 (hTDP-43WT) (Chang and Morton, 2017). FLAG staining in CRISPR hTDP-43WT control Drosophila brains appeared nuclear, with few puncta. However, Nup62 OE; CRISPR hTDP-43WT brains had significantly increased FLAG puncta (p < 0.01) and reduced nuclear TDP-43 intensity (p < 0.05) compared to controls (Figure 4—figure supplement 1C,D,E), further suggesting that Nup62 overexpression disrupts TDP-43 subcellular localization.

We also expressed four additional Nups that were upregulated in our proteomic analysis, EP (Enhancer-promoter) overexpression Nup93-2 and Nup44A lines, Nup214 OE, and HA-tagged Nup43 OE, to determine the contribution of other Nups on Tbph subcellular distribution. There was a significant increase in Tbph puncta in flies overexpressing Nup93-2 (p < 0.001) but not Nup44A (Figure 4—figure supplement 3A,B). Further, Nup93-2 and Nup44A overexpressing flies showed a trend of decreasing nuclear Tbph intensity that was not significant (Figure 4—figure supplement 3C). qPCR analysis validated that flies significantly overexpressed Nup93-2 and Nup44A mRNA (Figure 4—figure supplement 3D,E, p < 0.001). Nup214 or Nup43 overexpression led to Tbph aggregation (Figure 4—figure supplement 4A,B, p < 0.001) and decreased N/C Tbph ratio (Figure 4—figure supplement 4C,D, p < 0.05), although the Tbph aggregates in Nup214 and Nup43-expressing animals did not localize with Mab414 (Nup214) or Anti-HA (Nup43) (Figure 4—figure supplement 2A,B). qPCR analysis showed significant increase Nup214 and Nup43 mRNA levels (Figure 4—figure supplement 4E,F, p < 0.001). Together, these data suggest that alteration in multiple Nups may contribute to Tbph mislocalization and/or aggregation, albeit with a more pronounced effect by Nup62.

We next assessed the effects of NUP62 expression on endogenous TDP-43 localization and aggregation in human embryonic kidney cells (HEK293T). HEK293T cells were transfected with mRuby alone or mRuby tagged NUP62 (Nup62-mRuby). Expression of NUP62 in HEK293T led to aggregation of the mRuby reporter (Figure 4I). FG-Nups such as NUP62, NUP214, and NUP54 are predicted to contain prion-like domain and a low complexity domain, which is suggested to mediate cytoplasmic coaggregation with the C-terminal fragment of TDP-43 (TDP-CTF) (Chou et al., 2018). Interestingly, NUP62 co-aggregated with endogenous TDP-43 (Figure 4I). Moreover, expression of NUP62 in HEK293T cells led to a significant shift in TDP-43 solubility compared to mRuby alone (Figure 4J and K, p < 0.01), similar to the Drosophila Nup62 overexpression model. TDP-43 aggregates are phosphorylated and are toxic in vitro and in vivo (Arai et al., 2009; Choksi et al., 2014; Zhang et al., 2009),. Therefore, we assessed whether NUP62-mediated TDP-43 aggregates were phosphorylated in HEK293T cells. Endogenous TDP-43 aggregates that co-localized with NUP62-mRuby were phosphorylated (Figure 4L), suggesting that TDP-43 aggregates might be pathological and toxic. Interestingly, expression of NUP54 in HEK293T cells did not show endogenous TDP-43 aggregation (Figure 4—figure supplement 5), although proteomic analysis showed an increase in Drosophila Nup54 protein levels, suggesting that TDP-43 localization and/or aggregation may be influenced by a subset of Nups, specifically NUP62. Expression of human NME1 [Drosophila Awd], HSPB2 [Drosophila heat shock protein 27 (HSP27)], FKBP1A (Drosophila Fkbp12), and SRSF1 (Drosophila SF2), which were upregulated as part of the microtubule cytoskeleton, protein folding, and spliceosome component post-TBI (Supplementary file 1), in HEK293T cells did not alter TDP-43 localization (Figure 4—figure supplement 6A,B,C,D), suggesting that expression of a subset of proteins within the top four upregulated pathways does not disrupt TDP-43 distribution.

Nucleoporin’s expression leads to motor dysfunction and reduced lifespan in Drosophila that is partially rescued by nucleoporins knockdown

To determine whether Nup upregulation, which leads to Tbph aggregation and mislocalization, is toxic in Drosophila, we assessed the effect of Nup62, Nup214, and Nup43 expression on motor function and lifespan. Overexpression of Nup62, Nup214, or Nup43 in motor neurons significantly reduced motor function and climbing velocity (Figure 5A and B, p < 0.01; p < 0.001, and p < 0.05, respectively) in Drosophila compared to controls, suggesting that genetic upregulation of Nups alters motor function. Further, Nup62 OE, Nup214 OE, and Nup43 OE animals had a significantly reduced lifespan compared to control animals—controls had a median survival of 55 days when raised at 29°C, while Nup62 OE, Nup214 OE, and Nup43 animals had a median survival of 33, 40, and 43 days respectively. Overexpression of Nup62 and Nup214 or Nup62 and Nup43 together was further shown to significantly reduce lifespan compared to their respective Nup controls or control animals - Nup62/Nup214 OE and Nup62/Nup43 OE median survival was 23 days and 21 days, respectively (Figure 5C, p < 0.0001, Figure 5—figure supplement 1D).

Figure 5 with 1 supplement see all
Nups expression reduces motor function and lifespan, and knockdown partially rescues trauma-mediated motor dysfunction in Drosophila.

(A) Percentage of flies that climbed 4 cm in 20 seconds for Nup62, Nup214, and Nup43-overexpressing (Nup62 OE, Nup214 OE and Nup43 OE) animals compared to eGFP control (n = 3 trials, 10 animals per trials; ***p < 0.001, *p < 0.01, *p < 0.05). (B) Quantification of climbing velocity (cm/s) of Nup62 OE, Nup214 OE, and Nup43 OE flies compared to eGFP controls (n = 3 trials, 10 animals per trials, ***p < 0.001, **p < 0.01, *p < 0.05). (C) Kaplan-Meier survival curve of flies expressing Nup62 OE, Nup214 OE, Nup43 OE, Nup62/Nup214 OE, Nup62/Nup43 OE or eGFP control in motor neurons. (n = 60–80, ****p < 0.0001). (D, E) qPCR analysis of Nup62 and Nup214 mRNA levels in flies expressing Nup62 RNAi, Nup214 RNAi or eGFP controls (n = 3, **p < 0.01, ***p < 0.001). (F, G) Adult Drosophila expressing Nup62 RNAi or Nup214 RNAi in neuronal cells exposed to repeated traumatic brain injury (TBI) were raised on RU486 (+ RU486) or ethanol (-RU486) treated food for 20 days before motor assays. Quantification of (F) percentage of flies that climbed 4 cm in 20 s (n = 3 trials, **p < 0.01, ***p < 0.001) and (G) climbing velocity (cm/s) (n = 3 trials, *p < 0.05, **p < 0.01). Log-rank with Grehan-Breslow-Wilcoxon tests were performed to determine significance for panel C, while one-tailed t-tested was used in panel D, E, F, and G. All quantifications represent mean ± s.e.m.

Enhanced Nup levels post-TBI coupled with Nup-mediated alteration in motor function in Drosophila prompted us to evaluate whether RNAi-mediated knockdown of Nups post-trauma was protective in vivo. We used the Elav-GeneSwitch (ElavGS) system to conditionally express Nup62 RNAi or Nup214 RNAi in neuronal cells by feeding adult flies RU486, as reported (Anderson et al., 2018; Osterwalder et al., 2001). Adult RNAi (Nup62 or Nup214) flies were exposed to repeated traumatic injuries and motor function as well as lifespan were examined. Nup62 mRNA (p < 0.01) and Nup214 mRNA (p < 0.001) levels were significantly reduced in Nup62 and Nup214 RNAi-treated animals compared to controls (Figure 5D and E). Interestingly, Nup62 RNAi and Nup214 RNAi animals treated with RU486 post-trauma had a significant improvement in climbing (Figure 5E, p < 0.01 and p < 0.001, respectively) and velocity (Figure 5F, p < 0.05 and p < 0.01, respectively) compared to ethanol-treated animals, suggesting that genetically modulating Nup62 and Nup214 levels post-TBI may partially improve motor function in Drosophila. Knockdown of Nup62 or Nup214 individually did not significantly extend life-span post-injury (Figure 5—figure supplement 1A,B, P = NS). However, RNAi knockdown Nup62/Nup214 together significantly increase lifespan of trauma animals (Figure 5—figure supplement 1C,p < 0.001).

Nuclear pore pathology is present in repetitive TBI patient brain tissues and co-aggregates with TDP-43 pathology

TBI can be categorized as mild, moderate, or severe based on clinical factors such as duration and severity, amnesia and neurological symptoms, and structural brain imaging (Management of Concussion/mTBI Management of Concussion/mTBI Working Group, 2009). We examined postmortem brain tissue from patients with mild (nine cases) and severe CTE (nine cases) and aged-matched controls (eight control cases) without neurodegenerative disease for NUP62 pathology in the frontal cortex (Supplementary file 2). All mild and severe CTE subjects were involved in sports, specifically American Football with one severe case played Hockey, and control cases played no sports. The mild subjects played an average of 12.222 ± 6.438 years (mean ± SD), while severe subject played an average of 18.333 ± 4.610 (mean ± SD). Interestingly, tissues from mild and severe CTE but not age-matched controls showed widespread and intense NUP62 immunoreactivity (Figure 6A,B,C and Figure 6—figure supplement 1). Brain tissues from mild and severe CTE cases also showed cytoplasmic and nuclear mislocalization of Nup62 as well as perinuclear accumulation. Cytoplasmic NUP62 aggregates were present in brain tissue from patients with severe CTE, suggesting increased NUP62 aggregation with more severe CTE neuropathology. Enzyme-linked immunosorbent assay (ELISA) on postmortem brain tissues from eleven subjects with mild CTE showed an increasing trend in NUP62 levels, although they were not significantly different from controls cases. However, NUP62 levels in twenty-one severe CTE patient brain tissues were significantly higher than controls (Figure 6D, p < 0.05), suggesting that repetitive TBI is associated with altered NUP62 in CTE.

Figure 6 with 1 supplement see all
NUP62 pathology is present in brain tissue of patients with mild and severe CTE and coaggregates with pTDP-43 inclusion.

(A) NUP62 immunohistochemical staining in human frontal cortex tissue from a control individual without neurodegenerative disease, showing faint perinuclear staining for NUP62 (arrow). (B) NUP62 immunohistochemical staining in human frontal cortex tissue from a participant with mild CTE (mCTE), showing more neurons with diffuse cytoplasmic staining as well as perinuclear aggregates of NUP62 (arrowhead). (C) NUP62 immunohistochemical staining in human frontal cortex tissue from a participant with severe CTE (sCTE), showing more intense Nup62 staining in the nucleus and cytoplasm (arrowheads). Scale bar = 20 µm. (D) Quantification of enzyme-linked immunosorbent assay (ELISA) results for human NUP62 in control (n = 6), mCTE (n = 11), and sCTE (n = 21) subjects (*p < 0.05, n.s. = not significant). (E) Representative immunofluorescence images of a control, and two mCTE and sCTE cases stained for NUP62 (green) and phosphorylated TDP-43 (red) in the frontal cortex (Scale bar = 25 µm), showing pTDP-43 co-localization with NUP62 (arrows head, merge) in two patients. DAPI was used as a nuclear marker. One-way ANOVA with Tukey’s multiple comparisons tested was used for panel D. All quantification represent mean ± s.e.m.

To investigate the connection between Nups and TDP-43 pathology in CTE, we stained the dorsolateral prefrontal cortex at the depth of the cortical sulcus (approximately Broadman area 9) from two subject with mild and severe CTE as well as an aged-matched control. CTE brain tissue exhibited abnormal NUP62 staining in the prefrontal cortex. Interestingly, we found that mild CTE cases showed limited NUP62 coaggregation with pTDP-43, whereas the severe CTE cases showed a more pronounced coaggregation (arrows) of NUP62 and pTDP-43-positive inclusions in the frontal cortex (Figure 6E).

Discussion

Evidence suggests that TBI is a predisposing factor for the development of neurodegenerative diseases (Chen et al., 2007; Gardner and Yaffe, 2015; Goldman et al., 2006; Lye and Shores, 2000; Peters et al., 2013; Sivanandam and Thakur, 2012; Taylor et al., 2016; Vanacore et al., 2006), and repeated trauma to the head is also associated with CTE (McKee et al., 2013; Omalu et al., 2010; Omalu et al., 2005; Stern et al., 2011). Further, CTE postmortem brain tissues and animal models of TBI show TDP-43 and TAU pathology (Blennow et al., 2012; Huang et al., 2017; Mckee et al., 2018; McKee et al., 2010; Tan et al., 2018; Wang et al., 2015),, although the underlying mechanism that promotes this pathology has remained unexplored. Interestingly, although TBI causes nuclear dysfunction (Tajiri et al., 2016), it has remained unknown whether TBI leads to NCT defects that might be linked to TDP-43 pathology in CTE. Here, we uncovered that TBI disrupts NPC proteins and NCT in models of trauma, postmortem brain tissues form CTE patients, and leads to TDP-43/Tbph coaggregation with components of the NPC. Of note, our study provides evidence of alteration in nucleoporins proteins, defects in NPC morphology and RanGAP1 distributions, coaggregation of NPC components with TDP-43/Tbph, overexpression of nucleoporins lead to TDP-43 mislocalization and/or aggregation, alter motor function and lifespan, and pharmacological inhibition of nuclear export or modulating nucleoporins post-injury is protective. Taken together, these results suggest that TBI can disrupt NCT machinery. These defects may account for the nuclear depletion and cytoplasmic accumulation of TDP-43 widely seen in CTE and/or TBI-related conditions.

Trafficking of protein and RNA between the nucleus and cytoplasm is important for proper cellular function—NCT of macromolecules is essential for signaling, neuronal plasticity, and overall cellular survival (Dickmanns et al., 2015; Schachtrup et al., 2015). NCT dysfunction has been reported in AD (Eftekharzadeh et al., 2018), HD (Gasset-Rosa et al., 2017; Grima et al., 2017), and ALS/FTD (Chou et al., 2018; Zhang et al., 2015), and mutation in NUP62 causes autosomal recessive infantile bilateral striatal necrosis (Basel-Vanagaite et al., 2006), suggesting a common disrupted pathway. Our study provides evidence that TBI directly alters NPC and NCT components in vivo. Nups mRNA and protein levels were increased post-TBI (Figure 1) and NUP62 protein levels were elevated in postmortem brain tissues from CTE patients (Figure 6). Nups that were significantly upregulated include cytoplasmic FG Nups and filaments (Nup214), central channel FG Nups (Nup62 and Nup54), nuclear FG Nups and basket (TPR), linker Nups (Nup93), and outer ring Nups (Nup44A/SEH1, Nup43, and Nup75). In mammals, NUP93 forms an adaptor complex with NUP155, NUP35, NUP205, and NUP188, while NUP214 and other Nups constitute NPC cytoplasmic filaments that provide key interaction sites for NCT machinery (Lin and Hoelz, 2019; Solmaz et al., 2011). On the other hand, NUP62 and NUP54, in addition to NUP58, are suggested to constitute the channel (termed channel Nups) that undergoes large-scale reversible expansions to regulate NCT (Dickmanns et al., 2015; Lin and Hoelz, 2019) suggesting that alteration in these components by TBI might impact NCT of critical components in and out of the nucleus.

It is tempting to speculate that upregulation in Nups protein post-trauma (Figure 1) may be linked to post-transcriptional modifications. NPC components are extensively modified by nucleocytoplasmically disposed N-acetyglucosamine (GlcNAc) residues O-linked to serine and threonine residues (O-GlcNAc) (Holt et al., 1987; Li and Kohler, 2014). Indeed, 18 of the 30 Nups are modified by O-GlcNAc, and FG-Nups in the central scaffold of the NPC are heavily O-GlcNAcylated (Zhu et al., 2016). Nups such as Nup62, Nup153, Nup214, Nup93, and Nup358 as well as scaffold Nups are targeted by O-GlcNAc (Boyce et al., 2011; Gloster et al., 2011; Zhu et al., 2016). Further, genetic and pharmacological reduction of O-GlcNAc levels lead to decreased Nup levels and accelerated degradation, suggesting that O-GlcNAc might modulate Nup stability (Zhu et al., 2016). Collectively, these studies imply that repeated trauma can directly or indirectly upregulate components of the NPC and that O-GlcNAcylation may have an important role in this process. However, further studies are needed to assess the role of trauma in modulating Nup O-GlcNacylation. Alternatively, Nups protein upregulation post-trauma may occur at the transcriptional level. Our results showed significant upregulation in Nups mRNA (Figure 1). It is plausible that both transcriptional and translational events may contribute to Nups upregulation in traumatic injury, but the exact sequence of events and factors involve require additional work. Intriguingly, Nups such as Pom121 and Nup107 are long-lived proteins in post-mitotic cells and are susceptible to oxidative damage. The slow turnover of damaged Nups and aged-associated reduction of nuclear protein import and NPC may result in neuronal dysfunction and death (D’Angelo et al., 2009; Pujol et al., 2002). In support, our data showed the Nup214 protein levels remains elevated overtime in larval and adult brains. It is possible that the slow turnover of Nup214 protein might be due to dysfunction in protein clearance pathways. Our lab and others have shown that traumatic brain injury impaired autophagy (Anderson et al., 2018; Sarkar et al., 2014; Zeng et al., 2018) and ubiquitin proteosome components (Tylicka et al., 2014; Yao et al., 2008), suggesting that the impairments in these pathways might be important in mediating Nups slow turnover which potentially contribute to neurodegeneration.

Although strong evidence exists for NCT dysfunction in neurodegenerative disease, this evidence is centered around how pathological mutations in disease proteins influence this process, while many neurodegenerative diseases are mostly sporadic. Factors such as heavy metal exposure, pesticides, smoking, and head trauma have been link to development of neurodegenerative disease. Repeated head trauma is one of the most consistent risk factors for developing diseases such as ALS (Peters et al., 2013) and AD (Fann et al., 2018). However, the role of repeated head trauma in NCT dysfunction and its relation to neurodegeneration are unknown. To address this question, we used a well-characterized Drosophila trauma model (Katzenberger et al., 2015; Katzenberger et al., 2013) that shows a strong correlation between the amount of trauma and lethality as well as pathology in larval and adult Drosophila (Anderson et al., 2018). Our results show that repeated trauma altered several molecular pathways including NPC and NCT. The NPC tightly regulates transport in and out of the nucleus, suggesting that trauma-mediated alteration in NPC components may disrupt NCT. Indeed, trauma disrupt the NPC morphology resulting in gaps and/or aggregation of nucleoporins on the membrane (Figure 2). Trauma was shown to disrupt RanGAP1 distribution, Ran-dependent nuclear import and export regulator (Bischoff et al., 1995), as well as nuclear import of GFP containing a classic NLS and NES in vivo (Figure 3). Studies in multiple model systems of neurodegenerative diseases suggest that defects in the NCT pathway can manifest as ‘leaky pores’, impaired NCT, reduced NPC density, and irregular nuclear envelope morphology (Hutten and Dormann, 2020). Studies also show that overexpression of NUP214 leads to NCT defects (Boer et al., 1998). Conversely, depletion of NUP214 in mouse embryonic stem cells is reported to impair NLS-mediated protein import and lead to nuclear accumulation of polyadenylated RNA (van Deursen et al., 1996), while knockout of NUP98 in mice disrupts nuclear import of proteins with an NLS (Wu et al., 2002). Together, these data implicate repeated traumatic injury as a disruptor of the NPC and suggest that altering nucleoporins might possibly disrupt NCT by either disrupting the NPC morphology or creating ‘leaky pores’ but further work is needed to address this.

Our data further support a role for Nup62 upregulation in transport defects of NLS-containing protein, TDP-43. Targeted upregulation of Nup62 in Drosophila and in HEK293T cells caused nuclear depletion of TDP-43. In addition, expression Nup214, Nup43, and Nup93 also caused TDP-43 mislocalization, albeit to a lesser extent. Our in vivo and in vitro data further support that Nup62 upregulation leads to TDP-43 cytoplasmic aggregation and phosphorylation as well as increased levels of insoluble TDP-43. TDP-43 contains a classic NLS sequence, and its aggregation and phosphorylation are reported to be toxic (Johnson et al., 2009; Zhang et al., 2009). TDP-43 is considered a pathological hallmark of ALS/FTD (Lattante et al., 2013) and is also found in CTE postmortem brain tissues (McKee et al., 2010). Further, our results show that mild and severe CTE cases also have NUP62 pathology that coaggregated with pTDP-43, and its extent is related to disease severity. Importantly, repeated trauma in Drosophila led to TDP-43/Tbph accumulation with NPC components in the brain and this is recapitulated by overexpressing Nup62 but not Nup214 or Nup43 in Drosophila. We speculate that the TDP-43 pathology observed post-trauma is likely due to NPC dysfunction via upregulated NPC proteins. Our recent work have demonstrated that cytoplasmic Nup62 droplets exhibit characteristics of proteins that undergo liquid-liquid phase separation, and it is likely that these interaction through the classical NLS promotes deleterious phase transition of cytoplasmic TDP-43 causing it to mature into insoluble inclusions (Gleixner et al., 2021 PREPRINT), providing a mechanism for how Nups might promote TDP-43 pathology in traumatic injury. On the other hand, evidence in vitro and in vivo demonstrate that TDP-43 aggregation/demixing promotes NPC deficits that sequesters NPC components with TDP-43 aggregates (Chou et al., 2018; Cook et al., 2020; Gasset-Rosa et al., 2019; Zhang et al., 2018), suggesting that the TBI-mediated NCT deficits could be a consequence of cytoplasmic TDP-43 pathology. However, further research is needed to address whether NPC dysfunction is a cause or consequence of TDP-43 pathology in trauma-related conditions to fully decipher the exact mechanism. Moreover, the synergistic effects of both mechanisms cannot be ruled out as cause of neurodegeneration in traumatic injury.

Here, we also show that overexpression of Nups is toxic in Drosophila. Overexpression of Nup62, Nup214, or Nup43 reduces motor function and lifespan of Drosophila (Figure 5), suggesting that altered NPC proteins may mediate toxicity. Interestingly, RNAi-mediated knockdown of Nup62 or Nup214 partially rescued the motor dysfunction but not lifespan in adult Drosophila exposed to TBI. However, knockdown of Nup62 and Nup214 together post-trauma partially extend lifespan. Importantly, pharmacological inhibition of nuclear export via administration of KPT compounds rescued the trauma-mediated NCT defect of GFP-tagged NLS-NES and Tbph aggregation, which correlates with rescue of trauma-mediated lethality (Figure 3). Similarly, KPT-350 and KPT-276 are protective in models of ALS/FTD (Tamir et al., 2017; Zhang et al., 2015) and TBI (Cantu et al., 2016; Tajiri et al., 2016), suggesting a potential therapeutic application in TBI cases. While we did not observe a complete rescue of lifespan by RNAi knockdown of Nups post-injury, we speculate that it might be due to upregulation of multiple Nups post-trauma that might contribute to the overall phenotypes. We cannot exclude the possibility that Nups upregulation or a combination of other upregulated Nups might mediate toxicity by altering NCT balance, leading to NLS-containing proteins such as TDP-43 mislocalization and aggregation. Thus, further work is needed to assess whether modulating the levels of multiple Nups post-trauma or in conjunction with NCT inhibitors might be protective. In all cases, modulating Nups and/or nuclear export post-injury might provide some level of protection following repeated head trauma.

Taken together, our data suggest that disruption of NPC and NCT function may be a common pathogenesis in repetitive TBI diseases such as CTE. Based on our findings, we propose that trauma-mediated cytoplasmic aggregation of NLS-containing proteins such as TDP-43 is potentially caused by NCT defects and that cytoplasmic aggregation of NPC components such as Nup62 may sequester TDP-43 in aggregates that lead to toxicity. Further understanding of the role of repeated trauma in NCT and TDP-43 pathology will help develop therapeutic strategies for CTE and trauma-related diseases.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (D. melanogaster)w1118Bloomington Drosophila Stock CenterBDSC:3605; FLYB: FBst000360; RRID:BDSC_3605w[1,118]
Genetic reagent (D. melanogaster)w1118; P{UAS-NLS-NES+-GFP}5ABloomington Drosophila Stock CenterBDSC:7032; FLYB: FBst0007032; RRID:BDSC_7032w[1,118]; P{w[+ mC] = UAS-NLS-NES[+]-GFP}5A
Genetic reagent (D. melanogaster)y1 w*; P{UAS-NLS-NESP12-GFP}2ABloomington Drosophila Stock CenterBDSC:7033; FLYB: FBst0007033; RRID:BDSC_7033y (Amador-Ortiz et al., 2007) w[*]; P{w[+ mC] = UAS-NLS-NES[P12]-GFP}2A
Genetic reagent (D. melanogaster)w1118; P{EP}Nup44AEP2417Bloomington Drosophila Stock CenterBDSC:17053; FLYB: FBst0017053; RRID:BDSC_17053w[1,118]; P{w[+ mC] = EP}Nup44A[EP2417]
Genetic reagent (D. melanogaster)w1118; P{EPg}Nup93-2HP35056Bloomington Drosophila Stock CenterBDSC:21975; FLYB: FBst0021975; RRID:BDSC_21975w[1,118]; P{w[+ mC] = EPg}Nup93-2[HP35056]
Genetic reagent (D. melanogaster)P{VSH330104}attP40Vienna Drosophila Resource CenterVDRC:v330104; FLYB: FBst0491076; RRID:FlyBase_FBst0491076P{VSH330104}attP40
Genetic reagent (D. melanogaster)P{KK108318}VIE-260BVienna Drosophila Resource CenterVDRC: v100588; FLYB: FBst0472461; RRID:FlyBase_FBst0472461P{KK108318}VIE-260B
Genetic reagent (D. melanogaster)UAS-Nup62This paperCreated at BestGene
Genetic reagent (D. melanogaster)M{UAS-Nup214.ORF}ZH-86FbFLYORFFLYORF: F001467; FLYB: FBst0500182; RRID:FlyBase_FBst0500182M{UAS-Nup214.ORF}ZH-86Fb
Genetic reagent (D. melanogaster)M{UAS-Nup43.ORF.3xHA.GW}ZH-86FbFLYORFFLYORF: F003133; FLYB: FBst0502466; RRID:FlyBase_FBst050246M{UAS-Nup43.ORF.3xHA.GW}ZH-86Fb
Genetic reagent (D. melanogaster)CRISPR/Cas9 hTDP43-WTGift from David B. Morton Chang and Morton, 2017
Cell line (Homo sapiens)Human Embryonic Kidney cells (HEK 293T)ATCCRRID:CVCL_0063
Transfected construct (human)mRFP-FKBP1A PlasmidAddgene(Cat #: 67514); RRID:Addgene_67514transfected construct (human)
Transfected construct (human)Frt-V5-HspB2 PlasmidAddgene(Cat #: 63103); RRID:Addgene_63103transfected construct (human)
Transfected construct (human)FLAG NM23-H1/NME1 PlasmidAddgene(Cat #: 25000); RRID:Addgene_25000transfected construct (human)
Transfected construct (human)pEGFP SF2/SRSF1 PlasmidAddgene(Cat #: 17990); RRID:Addgene_17990transfected construct (human)
Transfected construct (human)Nup54-HA-eGFP PlasmidVectorBuilderThis papertransfected construct (human)
Transfected construct (human)HA-eGFP PlasmidVectorBuilderThis papertransfected construct (human)
Transfected construct (human)mRuby PlasmidGift from Dr. Christopher DonnellyThis papertransfected construct (human)
Transfected construct (human)NUP62-mRuby PlasmidGift from Dr. Christopher DonnellyThis papertransfected construct (human)
Antibodyanti-Nup214 (Guinea Pig polyclonal)Gift from Dr. Christos Samakovlis Roth et al., 2003WB (1:5000)
AntibodyAnti-Lamin Dm0 (Mouse monoclonal)DSHBCat# ADL84.12; RRID:AB_528338IF(1:200)WB (1:1000)
Antibodyanti-α-Tubulin (Mouse monoclonal)Sigma-AldrichCat#: T5168; RRID:AB_477579WB (1:10,000)
Antibodyanti-Tbph (Rabbit polyclonal)Gift from Dr. Frank Hirth Diaper et al., 2013IF (1:1500)WB (1:3000)
Antibodyanti-FLAG (Mouse monoclonal)Sigma-AldrichCat#: F1804; RRID:AB_259529IF (1:1000)
Antibodyanti-GFP (Chicken polyclonal)AbcamCat#: ab13970; RRID:AB_300798IF (1:1000)
Antibodyanti-TDP43 (Rabbit polyclonal)ProteintechCat#: 10782–2-AP; RRID:AB_615042IF (1:1000)
Antibodyanti-phospho-TDP43 (Rat monoclonal)Millipore SIGMACat#: MABN14; RRID:AB_11212279IF (1:1000)
Antibodyanti-Mab414 (Mouse monoclonal)AbcamCat#: ab24609; RRID:AB_448181IF (1:1000)
Antibodyanti-RanGAP1 (Rabbit polyclonal)Millipore SIGMACat#: ABN1674IF (1:200)
Antibodyanti-Nup62 (Mouse polyclonal)BD Transduction LaboratoriesCat#: 610497; RRID:AB_397863IHC/IF (1:500)
Antibodyanti-pTDP-43 (Rabbit polyclonal)Cosmo BioCat#:NC0877946; RRID:AB_1961899IF (1:1000)
Antibodyanti-Nup62 (Mouse polyclonal)Roche Applied ScienceCat#: 610497; RRID:AB_397863IHC (1:400)
Antibodyanti-RanGAP1 (Rabbit polyclonal)Santa Cruz BiotechnologyCat#: sc-28322; RRID:AB_2176987IHC (1:1000)
Sequence-based reagentFutschThis paperPCR primers (5'–3'):Forward: CAAAGCCCACTCACCTTTCReverse: CTGCTCCTGCCAACATCTProbe: AGTCTCTGGAAATGCAGCACCACT
Sequenced-based reagentdNup93-2This paperPCR primers (5'–3'):Forward: ACACCGTCCGCGAAATACReverse: ACTCAACCGCCACCTTAACProbe: ATGGCCGCTGGTTTACTACGGATT
Sequenced-based reagentdNup214This paperPCR primers (5'–3'):Forward: CCTAAGTGAGGACAAGGATGAGReverse: GGCATAGTCTGCAGCTTCTTProbe: TGCCTTCGACACTTCTACAACGCA
Sequenced-based reagentdNup54This paperPCR primers (5'–3'):Forward: GAGTGAGCTGACAGAACTCAAGReverse: CTCGGCCAGTTTCCGTTTATProbe: CCACTGCCACAGCGAAGATACTTGA
Sequenced-based reagentdNup44AThis paperPCR primers (5'–3'):Forward: AAGGTATCCTCCACCAATACCCReverse: TTGGGTGCAAACTCCACATCProbe: TTGTAGACTCGCGGACCAGTGTCA
Sequenced-based reagentdNup62This paperPCR primers (5'–3'):Forward: CTTGCTGTTGTCTGCATCTCReverse: CAGCACCAGCTTCAGGAProbe: ACATTCTCTTTCGGAACACCGGCA
Sequenced-based reagentEmb (Exportin)This paperPCR primers (5'–3'):Forward: GGTCACGCGTATGTCATTCAReverse: GTTCACATTGACGCCATTCACProbe: AGCATGTCCAGATATATGCGGCCC
Sequenced-based reagentdNup43This paperPCR primers (5'–3'):Forward: TTGCATCTGATCCTCCTCCACReverse: ACCGCCATGGAGTTCGTProbe: TGGACGTTAAACACGCTGAGATGACC
Sequenced-based reagentdGapdhThis paperPCR primers (5'–3'):Forward: CAACAGTGATTCCCGACCAGReverse: TTCGTCAAGCTAATCTCGTGGProbe: CCAAAACTATCGTACAAACCCGGCG
Commercial assay or kit3,3'-diaminobenzidine (DAB)Vector LaboratoriesCat: #SK-4100; RRID:AB_2336382
Commercial assay or kitNE-PER nuclear-cytoplasmic extraction kitThermoFisher ScientificCat #: 78,833
Commercial assay or kitNup62 ELISALSBioCat #: LS-F22196
Chemical compound, drugKPT-350Karyopharm
Chemical compound, drugKPT-276Selleck ChemCat #: S7251
Software, algorithmGraphPad Prism 6GraphPad Prism 6RRID:SCR_002798

Drosophila

Fly lines

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w1118, P{EP}Nup44AEP2417, P{EPg}Nup93-2HP35056, P{UAS-NLS-NES-GFP}, P{UAS-NLS-ΔNES-GFP}, Ok371-gal4, and UAS-eGFP were obtained from the Bloomington Drosophila stock center (http://www.flystocks.bio.indiana.edu). UAS-Nup214 (F001467) and UAS-Nup43 (F003133) were obtained from FlyORF. Nup62 RNAi (100588) and Nup214 RNAi (41964) were obtained from Vienna Drosophila Resource Center. The previously described CRISPR/Cas9 human TDP-43 wild-type (hTDP-43WT) was a kind gift from David B. Morton (Oregon Health and Science University) (Chang and Morton, 2017). UAS-Nup62 overexpression lines (UAS-Nup62 OE) were generated through site-specific integration of the transgene at BestGene Inc To generate UAS-Nup62 OE lines, we used the pUAST-attB vector. We subcloned the Nup62 cDNA (Drosophila Genomic Research Center) into the pUAST-attB vector.

Proteomics of Drosophila brains

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Larvae (three biological replicate) that were subjected to repeated whole-body trauma, 8 hits @ 50° angles with 20 s interval between hits (Anderson et al., 2018), and non-TBI controls brains were extracted immediately following trauma and flash-frozen. For protein extraction, frozen brains were thawed on ice with 50 µL of chilled MS lysis buffer (6 M urea, 0.4 M NaCl, 20 mM HEPES [pH 7.9], 5 % glycerol, 0.2 mM EDTA, 0.5 mM DTT) with 1 X protease inhibitors. Brains were crushed by 20 strokes with a plastic pestle and centrifuged at 19,000 g for 30 min to pellet debris. Supernatants was passed through a 0.45 µm microcentrifuge filter and quantified for mass spectrometry by BCA assay. Filtered protein was reduced and alkylated with 10 mM TCEP and 40 mM chloroacetamide, respectively. Lysates were digested into tryptic peptides using the filter-aided sample prep (FASP) method (Wisniewski et al., 2009) by diluting to 4 M urea, adding LysC (Wako), and rocking at ambient temperature for 4 hr. Lysates were further diluted to ~1 M urea for trypsin digestion (Pierce), rocking overnight at ambient temperature. Digested peptides were desalted using an Oasis HLB cartridge (Waters) according to the manufacturer’s instructions.

Samples were suspended in 7 µL of 3 % (v/v) acetonitrile/0.1 % (v/v) trifluoroacetic acid, and 1 µL was directly injected on a C18 1.7 µm, 130 Å, 75 µm X 250 mm M-class column (Waters), using a Waters M-class UPLC. Tryptic peptides were eluted at 300 nL/min using a gradient from 3–20% acetonitrile over 100 min into an Orbitrap Fusion mass spectrometer (Thermo Scientific). Precursor mass spectra (MS1) were acquired at a resolution of 120,000 from 380 to 1500 m/z with an AGC target of 4.0 × 105 and a maximum injection time of 60 ms. Dynamics exclusion was set for 30 s with a mass tolerance of ±10 ppm. Precursor peptide ion isolation width for MS2 fragment scans was 1.6 Da using the quadrupole, and the most intense ions were sequenced using Top Speed with a 3 s cycle time. All MS2 sequencing was performed using higher energy collision dissociation (HCD) at 35 % collision energy and scanning in the linear ion trap. An AGC target of 1.0 × 104 and 35 s maximum injection time was used. Raw files were searched against the Uniprot Drosophila database using Maxquant version 1.6.0.16 with cysteine carbamidomethylation as a fixed modification (Bateman, 2019Old et al., 2005; Tyanova et al., 2015). Methionine oxidation and protein N-terminal acetylation were searched as variable modifications. All peptides and proteins were thresholded at a 1% false discovery rate (FDR).

Quantification of AE-MS data and gene ontology

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Of the 4696 Drosophila proteins detected, the top 2000 ranking proteins were selected for further analysis with >4 label-free quantified (LFQ) values averaged across all samples and biological replicates. The average fold-change between TBI samples and controls (n = 2 or 6 biological replicates, respectively) was determined, and significance was determined by student’s t-test. Proteins were selected for GO analysis if they had a log-2 fold-change after TBI of ≥0.7 or ≤–0.7. The 361 proteins are just those whose p-value between TBI and non-TBI is ≤0.05. When we did both >1.6 fold up or down and p ≤ 0.05, there were 246 proteins (Supplementary files 1 and 3) that were altered and present “TBI Proteome”. The GO analysis accepted all genes changed >1.6 fold and p ≤ 0.1 to get enough genes to do GO analysis on. These proteins were consistently observed in all replicates. GO analysis was performed using Cytoscape v.3.7.1 and the BiNGO tool set v.3.0.3 (Saito et al., 2012). Associated GO terms were determined with the hypergeometric test with Benjamini and Hochberg FDR correction. Volcano plots were generated using all proteins associated with the selected GO terms and in the top 2000 ranked proteins detected. Additional proteins were included in volcano plots by manual curation and indicated in recent literature to associate with factors listed under the GO term (e.g. nuclear pore proteins).

Western blotting

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Fly heads were collected from each genetic cross and snap-frozen on dry ice. Heads were crushed on dry ice and incubated in RIPA buffer (150 mM NaCl, 1% NP40, 0.1% SDS, 1% sodium deoxycholate, 50 mM NaF, 2 mM EDTA, 2 mM DTT, 0.2 mM Na orthovanadate, 1 X Roche protease inhibitor #11836170001). Lysates were sonicated and centrifuged to remove debris. Supernatants were boiled in Laemmli buffer (Boston Bioproducts, #BP-111R) for 5 min and loaded onto 4%–12% Nupage Bis-Tris gels (Novex/Life Technologies). Proteins were transferred using the iBlot2 (Life Technologies, #13120134) onto nitrocellulose (iBlot 2 NC regular Stacks, Invitrogen, #IB23001). Western blots were blocked with milk solution (BLOT-QuickBlocker reagent, EMB Millipore, #WB57-175GM) and incubated with primary antibody overnight: guinea pig DNup214, 1:5000 (a kind gift from Christos Samakovlis [Roth et al., 2003]); anti-lamin Dm0 (ADL84.12), 1:1000 (Developmental Studies Hybridoma Bank); mouse anti-tubulin, 1:10,000 (Sigma-Aldrich); rabbit GAPDH, 1:1000 (GeneTex). Blots were washed and incubated in secondary antibody for one hour [anti-mouse IRDye 680D, 1:10,000 (LI-COR Biosciences); anti-rabbit DYLight 800, 1:10,000 (Invitrogen)] and imaged on a Licor imager (Odyssey CLx). All western blots were run in triplicate using biological replicates. Protein levels were quantified using NIH Image J software, and statistical analysis was performed with GraphPad Prism six software.

Soluble-insoluble fractionation

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Ten adult fly heads were collected for each genotype, crushed on dry ice, incubated in NP40 lysis buffer (10 mM Tris HCl pH 7.8, 10 mM EDTA, 150 mM NaCl, protease inhibitor cocktail, 0.5% NP40), sonicated, and centrifuged (21,000 g for 20 min), and supernatants (soluble fractions) were collected. Pellets were washed in 1 mL washing buffer (50 mM Tris HCl pH 7.4, 150 mM NaCl), vortexed, and centrifuged (21,000 g for 5 min). Supernatants were discarded, and pellets were resuspended in resolubilization buffer (50 mM Tris HCl pH 6.8, 5% SDS, 10% glycerol) and sonicated. Similarly, transfected HEK293T cells were harvested 24 h after transfection, and the above protocol was followed. Western blotting was performed as described above.

Nuclear-cytoplasmic fractionation

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A total of 50 adult fly heads were harvested, and nuclear-cytoplasmic fractionation was done using a NE-PER Nuclear-Cytoplasmic extraction kit per manufacturer’s protocol (Thermo Fisher Scientific).

Larval preparations, immunohistochemistry, and quantification

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Third instar larvae or adult Drosophila brains were dissected, fixed, and immunostained as previously described (Anderson et al., 2018). Briefly, animals were dissected in ice-cold phosphate buffered saline (PBS) (Lonza, #17–516 F), fixed in 4% formaldehyde, washed three times in PBS, incubated in 5% Triton X-100/PBS for 20 min, washed three times in 0.1% PBST (0.1 % Triton X-100/PBS), and incubated overnight with primary antibodies: mouse anti-Lamin Dm0, 1:200 (Developmental Studies Hybridoma Bank); rabbit anti-Tbph, 1:3000 generous gift from Dr. Frank Hirth Diaper et al., 2013; mouse anti-FLAG, 1:1,000 (Sigma-Aldrich); chicken anti-GFP, 1:1000 (Abcam); Rabbit Anti-RanGAP1, 1:200 (Millipore Sigma) or mouse anti-nuclear pore complex (Mab414), 1:1000 (Abcam). Larvae were washed three times in 0.1% PBST and incubated with secondary antibodies: anti-rabbit Alexa Flour 568, 1:100 (Invitrogen, #651727); anti-mouse Alexa Flour 647, 1:100 (Invitrogen, #28181); anti-rabbit Alexa Flour 405, 1:100 (Invitrogen, #157554); anti-rabbit Alexa Flour 647, 1:100 (Invitrogen, #1660844); or anti-chicken Alexa Flour 647, 1:100 (Invitrogen, #2010133). Stained larvae were mounted using DAPI Fluoroshield (Sigma-Aldrich, #F6182). Images were collected on a Nikon A1 eclipse Ti confocal microscope. Relative Tbph puncta and staining intensity were quantified in 100–150 VNC cells from four to seven animals using the Image J threshold function, and average intensity (subtracted from background) was used for analysis. All IF image quantification were done single-blinded.

Eclosion assay

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For eclosion percentages, a total of 15 w1118 larvae were subjected to trauma, 8hits @ 50° angles with 20 sec interval between hits, as previously described (Anderson et al., 2018). Briefly, larvae were exposed to trauma and directly transferred to food vials supplemented with DMSO only, KPT-350 (0.05, 0.1, or 0.5 mM; Karyopharm), or KPT-276 (50, 200, or 1,000 nM; Selleck Chem). Eclosion percentages were calculated as: (total number of eclosed adults) / (total number of pupal cases) x 100. Each condition was analyzed in triplicate using biological replicates. Statistical analysis was performed with GraphPad Prism six software.

Climbing assay

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OK371-gal4 (motor neuron specific driver) was used to overexpress Nups (Nup62 OE, Nup214 OE, Nup43 OE) or eGFP (control), and climbing assays were performed as previously described (Anderson et al., 2018). Additionally, Elav-GeneSwitch (ElavGS) was used to conditionally express Nup62 RNAi or Nup214 RNAi in neuronal cells on normal cornmeal food. Adult progeny were subjected to repeated trauma as described (Anderson et al., 2018), and flies that survived after 24 hr were placed on food treated with ethanol (-RU486) or RU486 (+ RU486, Cayman Chemical) for 20 days before motor assay. Adult flies were anesthetized with CO2 after 20 days, transferred to vials, and allowed to recover for 30 min. Flies were knocked to the bottom of vials by tapping against the bench three times, and a video camera was used to record flies climbing up the walls. The percentage of flies that climbed 4 cm in 20 s as well as the velocity (cm/s) of each individual fly was quantified and analyzed using GraphPad Prism six software. Three experimental replicates were performed for each group.

Lifespan assay

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Nup62 OE, Nup214 RNAi or Nup43 RNAi or eGFP adult 2-day-old flies (20 flies per vial, 60–80 flies) were collected for each experimental group. Flies were transferred to fresh food twice a week. Number of dead flies was counted every day, and survival functions were calculated and plotted as Kaplan-Meier survival curves. Log-rank with Grehan-Breslow-Wilcoxon tests were performed to determine significance of differences in survival data between samples using GraphPad Prism six software.

Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR)

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RNA was extracted in triplicate from TBI or non-TBI w1118 larval brains (10 brains per extraction) as well as Nup62 RNAi, Nup214 RNAi, Nup62 RNAi, eGFP, Nup214 OE, Nup43 OE, or Nup62 OE, flies using Trizol (Ambion, #15596026) in 1-bromo-3-chloropropane (BCP; Sigma-Aldrich, #MKCB0830V), as previously described (Jensen et al., 2013). Brains were dissected from larvae, snap frozen on dry ice, ground in Trizol, and centrifuged to pellet. BCP was added, and samples were centrifuged again. The upper aqueous layer was used to precipitate RNA with isopropanol, followed by pelleting RNA through centrifugation. RNA pellets were washed with 70% ethanol and allowed to air-dry prior to resuspending in RNase-free water. RNA samples were quantified on a NanoDrop ND-1000 spectrophotometer, and purity was assessed using 260/280 and 260/230 ratios. Samples were run on a 1% agarose gel with ethidium bromide to rule out RNA degradation. cDNA was then generated from RNA samples with the BioRad iScript Select cDNA Synthesis Kit (#170–8897) in a Thermo Hybaid Omn-E PCR machine. All cDNA samples were run on a 96-well plate (Applied Biosystems, #4306737) on an Applied Biosystems 7,300 Real-Time PCR system with BioRad iQ Supermix (#170–8862). cDNA-specific PrimeTime qPCR Assay primers (Integrated DNA Technologies) were used for qPCR reactions (http://www.idtdna.com). Drosophila GAPDH (dGapdh) was used as a housekeeping control. The comparative C(T) method was used to analyze results, as previously described (Schmittgen and Livak, 2008). GraphPad Prism six software was used for statistical analyses.

Primers (5'–3'):

Futsch

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  • Forward: CAAAGCCCACTCACCTTTC

  • Reverse: CTGCTCCTGCCAACATCT

  • Probe: AGTCTCTGGAAATGCAGCACCACT

dNup93-2

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  • Forward: ACACCGTCCGCGAAATAC

  • Reverse: ACTCAACCGCCACCTTAAC

  • Probe: ATGGCCGCTGGTTTACTACGGATT

dNup214

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  • Forward: CCTAAGTGAGGACAAGGATGAG

  • Reverse: GGCATAGTCTGCAGCTTCTT

  • Probe: TGCCTTCGACACTTCTACAACGCA

dNup54

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  • Forward: GAGTGAGCTGACAGAACTCAAG

  • Reverse: CTCGGCCAGTTTCCGTTTAT

  • Probe: CCACTGCCACAGCGAAGATACTTGA

dNup44A

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  • Forward: AAGGTATCCTCCACCAATACCC

  • Reverse: TTGGGTGCAAACTCCACATC

  • Probe: TTGTAGACTCGCGGACCAGTGTCA

dNup62

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  • Forward: CTTGCTGTTGTCTGCATCTC

  • Reverse: CAGCACCAGCTTCAGGA

  • Probe: ACATTCTCTTTCGGAACACCGGCA

Emb (Exportin)

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  • Forward: GGTCACGCGTATGTCATTCA

  • Reverse: GTTCACATTGACGCCATTCAC

  • Probe: AGCATGTCCAGATATATGCGGCCC

dNup43

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  • Forward: TTGCATCTGATCCTCCTCCAC

  • Reverse: ACCGCCATGGAGTTCGT

  • Probe: TGGACGTTAAACACGCTGAGATGACC

dGapdh

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  • Forward: CAACAGTGATTCCCGACCAG

  • Reverse: TTCGTCAAGCTAATCTCGTGG

  • Probe: CCAAAACTATCGTACAAACCCGGCG

Rat CCI TBI model

Subjects and presurgical procedures

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Ten adult male Sprague-Dawley rats (Envigo RMS) were pair-housed in standard rat individual ventilated cages under a 12 hr light/dark cycle and maintained at a temperature of 21°C ± 1°C with ad libitum access to food and water. All experimental procedures were approved by the Institutional Animal Care and Use Committee at the University of Pittsburgh. Every attempt was made to limit the number of rats used and to minimize suffering.

Surgery

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TBI was conducted on rats weighing 300–325 g, as previously described (Sozda et al., 2010). Briefly, following induction of surgical anesthesia with 4% isoflurane and 2:1 N2O:O2, rats were intubated, maintained on 2% isoflurane, and mechanically ventilated. A controlled cortical impact (CCI) of moderate severity (2.8 mm tissue deformation at a velocity of 4 m/s) was produced. Immediately after CCI, anesthesia was removed, and the incision was promptly sutured. Rats were returned to home cages, where they remained until being euthanized at 24 hr post-injury.

Immunohistochemistry

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CCI and sham rats were anesthetized intraperitoneally with Fatal-Plus (0.25 mL) and perfused transcardially with 200 mL 0.1 M PBS (pH 7.4), followed by 300 mL 4% paraformaldehyde (PFA) 24 h post-injury. Calvaria were immersion-fixed an additional 24 h in 4% PFA, and brains were subsequently extracted and post-fixed in 4% PFA until dehydration for immunohistochemical staining. Serial dehydrations (increasing concentrations of ethanol, then embedded in paraffin wax) were performed on all brain tissues. After embedding, 5-mm-thick tissues were sectioned at ~1 mm interval.

Slides were selected based on region of interest (ROI), deparaffinized, and rehydrated. ROIs were determined a priori as hippocampal regions underlying the injured cortex. Endogenous peroxide was blocked with 3% H2O2, and slides were subjected to an antigen retrieval step with 1 X Decloaking solution (BioCare Medical, #CB910M). Primary antibody incubation was then performed on all sections for 12 hr at 4°C using mouse anti-Nup62 (IgG), 1:400 (Roche Applied Sciences) or rabbit anti-RanGAP1 (IgG), 1:1000 (Santa Cruz Biotechnology). Slides were washed in 1 X TBS automation buffer (BioCare Medical, #TWB945M) and incubated for 2 hr with secondary goat anti-mouse IgG (1:750, Vector Laboratories, #PK-6102) or anti-rabbit IgG (1:750, Vector Laboratories, #PK-6101). Immunostaining was visualized using a 3,3'-diaminobenzidine (DAB) staining kits (Vector Laboratories, #SK-4100) for ~5 min. Slides were counterstained with aqueous Hematoxylin QS (Vector Laboratories, #H-3404), dehydrated, and cover-slipped using Permount mounting medium (Thermo Fisher Scientific, #SP15-500). Sections were imaged on a Nikon i90 microscope with NS-elements software (Nikon). Nup62 and RanGAP1 pathology was quantified as previously described (Grima et al., 2017).

Human neuropathology

Subjects

Cases were ascertained from the VA-BU-CLF Brain Bank at Boston University. Detailed inclusion criteria have been described previously (Mez et al., 2015). An authorized legal representative provided written consent from brain donation. IRB approval for the brain donation program was obtained through Boston University Alzheimer’s Disease & CTE Center and the Edith Nourse Rogers Memorial Veterans Hospital. Neuropathologic evaluation has been described previously (Cherry et al., 2017). CTE neuropathologic stage was determined using McKee staging criteria (McKee et al., 2016). CTE Stage I or II cases were grouped as mild CTE, and Stage III or IV cases were grouped as severe CTE, as previously published (Cherry et al., 2016).

ELISA

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Frozen tissue was collected from identical regions in Broadman area 8/9, as previously described (Cherry et al., 2016). Briefly, freshly prepared, ice-cold 5 M guanidine hydrochloride in Tris-buffered saline (20 mM Tris-HCl, 150 mM NaCl, pH 7.4 TBS) containing 1:100 Halt protease inhibitor cocktail (Thermo Fisher Scientific) and 1:100 phosphatase inhibitor cocktail 2 and 3 (Sigma-Aldrich) were added to brain tissues at a 5:1 ratio and homogenized with Qiagen Tissue Lyser LT at 50 Hz for 5 min. Lysates were diluted according to the manufacturer’s protocol and centrifuged at 17,000 g at 4°C for 15 min. Supernatant was analyzed using a Nup62 ELISA (LSBio, #LS-F22196) according to the manufacturer’s protocol. Results are reported as ng/mL.

Histology

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Staining was performed as previously described (Cherry et al., 2016). Briefly, tissue blocks of cortical samples were taken from Broadman area 8/9 for all cases. Tissues were embedded in paraffin and cut into 20-µm-thick sections. For chromogenic staining, sections were incubated overnight at 4°C with anti-NUP62 antibody. Sections were treated with biotinylated secondary antibodies and labeled with a 3-amino-9-ethylcarbazol HRP substrate kit (Vector Laboratories). Sections were counterstained with Gill’s hematoxylin (Vector Laboratories, #H-3401). For multiplex immunofluorescent images, sections were incubated overnight at 4°C with anti-NUP62 (BD Transduction Laboratories, #610497) and or anti-pTDP43 (Cosmo Bio, #NC0877946) antibodies. Fluorescent labeling was carried out using the PerkinElmer Opal 7-Color Automation IHC kit (#NEL801001KT), per manufacturer’s instructions. Sections were counterstained with DAPI.

Cell culture, transfection, and immunohistochemistry

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HEK293T (#CRL-3216) cells were acquired from ATCC, was authenticated and tested negative for mycoplasma contamination. H293T cells were cultured on coverslips coated with poly-L-lysine (Sigma-Aldrich). Cells were transfected with either mRuby, NUP62-mRuby, HA-eGFP, Nup54-HA-eGFP, pEGFP-SF2/SRSF1 (Addgene, #17990), FLAG-NM23-H1/NME1 (Addgene, #25000), Frt-V5-HspB2 (Addgene, #63103), or mRFP-FKBP1A (Addgene, #67514) expression plasmids using TurboFect (Thermo Fisher Scientific), following the manufacturer’s instructions. Cells were washed and incubated with primary antibodies overnight: rabbit anti-TDP-43 (10782–2-AP), 1:1000 (Proteintech); or rat anti-phospho TDP-43 (MABN14), 1:1000 (Millipore, Sigma-Aldrich). Cells were washed and incubated with secondary antibodies: anti-rabbit Alexa Flour 647, 1:100 (Life Technologies, #1660844); anti-rat Alexa Flour 568 (Invitrogen, Cat # A-11077). Coverslips were mounted onto slides using Fluoroshield with DAPI (Sigma-Aldrich, #F6057). Cells were imaged with a NIKON A1 eclipse Ti confocal microscope.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

References

    1. Cantu D
    2. Croker D
    3. Tamir S
    4. Shacham S
    5. Dulla C
    (2016)
    Using the selective inhibitor of nuclear export (SINE) compound KPT-350 to reduce cortical circuit hyperexcitability and interneuron cell loss in the controlled cortical impact (CCI) model of traumatic brain injury (TBI
    Neurology 86:5–23.
    1. Zaninotto ALC
    2. Costa BT
    3. Ferreira IS
    4. French M
    5. Paiva WS
    6. Fregni F
    (2018)
    Traumatic brain injury
    Neuromethods 139:1–3.

Decision letter

  1. Patrik Verstreken
    Reviewing Editor; KU Leuven, Belgium
  2. Huda Y Zoghbi
    Senior Editor; Texas Children's Hospital, United States
  3. Shinya Yamamoto
    Reviewer; Baylor College of Medicine, United States

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

Acceptance summary:

Anderson and colleagues use a traumatic brain injury (TBI) model fruit fly to understand the molecular pathogenesis of this disease. They identify proteins that are altered upon TBI, including that Nucleoporins (Nups) are upregulated and this is associated with the aggregation of TDP-43, a protein implicated in neurodegeneration. These findings were confirmed in a TBI rat model and in samples from patients who suffered from TBI. The findings provide molecular insight into TBI pathogenesis and identify a promising therapeutic pathway.

Decision letter after peer review:

Thank you for submitting your article "Traumatic injury results in functional impairments in nucleocytoplasmic transport and leads to TDP-43 pathology" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Huda Zoghbi as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Shinya Yamamoto (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

As you will see from the reviews below, and from our subsequent discussion, we were enthusiastic about the paper. The reviewers ask a number of questions that are listed below, but there are two items we all agreed on that we hope you will be able to address, possibly by including new experiments or by textual changes:

1. You currently do not directly demonstrate the stability of Nups. We suggest to either reword the text or include a pulse-chase experiment to study the stability of Nups;

2. Clearly discuss the two possible models i.e. TDP-43 aggregation leads to Nup alterations or vice versa; or include experiments that clarify this relationship.

Reviewer #2:

Anderson and colleagues investigated the mechanisms underlying toxicity during traumatic brain injury (TBI), which is emerging as a risk factor in several neurodegenerative diseases including Alzheimer's disease, amyotrophic lateral sclerosis (ALS) and chronic traumatic encephalopathy (CTE). They propose deficits in nucleocytoplasmic transport accompanied by TDP-43 pathology to be critical to TBI-induced damage. Starting from a proteomic analysis of brains from a TBI Drosophila model previously reported by the team (Anderson et al., 2018 HMG), the authors identify that the majority of the proteins with altered expression (361 proteins) are significantly upregulated, among which nearly half of the 30 known components of the nucleopore complex (NPC) -which the study focuses on. The authors report that repeated trauma provokes aberrant localization and aggregation of specific components of the NPC (including Nup62) in multiple TBI models including Drosophila, human cell line, rats, and ultimately in postmortem autopsied brains from CTE patients. Using a functional GFP-reporter assay they demonstrate that TBI impairs active nucleocytoplasmic transport and that pharmacological inhibition of nuclear export improves nuclear/cytoplasmic transport the GFP reporter as well as the fly eclosion deficits caused by TBI.

The team had previously reported that TBI recapitulates TDP-43 pathology in Drosophila (Anderson et al., 2018 HMG). Here, the authors report that increased expression of nucleoporins (Nups) including Nup62 in a human cell line (Hek) and in flies induces TDP-43 mislocalization/aggregation, motor impairments and reduced survival, thus leading to the proposal that TBI induced-NPC deficits may provoke TDP-43 pathology.

The authors convincingly demonstrate that TBI provokes morphological and functional alterations in NPC and nucleocytoplasmic transport, which can be partially improved by pharmacological inhibition of nuclear export thus providing mechanistic insight with potential therapeutic avenue. That being said, there are some aspects that need to be clarified to fully support all claims.

1. In figure 1 the authors conclude that trauma increases stability of Nup214, as increased accumulation of Nup214 is observed (by WB) with time of post-traumatic injury. However, the authors also report that mRNA levels are increased and the time course provided does not allow to fully exclude that Nup enhanced levels may occur predominantly at the transcriptional level (rather than at the protein level due to reduced turnover and/or increased stability as claimed by the authors). To substantiate the authors' conclusion on the effects of enhanced stability, pulse-chase/cycloheximide experiments should be considered.

Strengthening such evidence on stability is even more critical given this is in contrast with previously published studies describing a loss (or reduction) rather than increase of NPC components during neurodegenerative processes (Coyne et al., 2020 Neuron; Chou et al. 2017 Nat Neurosc) or aging (D'Angelo et al., 2009 Cell).

2. In their original study describing the TBI Drosophila model (Anderson et al. 2018 HMG) the authors had proposed that repetitive trauma induces TDP-43 mislocalization and stress granule formation. Here the authors suggest that TDP-43 pathology may be caused by TBI-induced NPC deficits as cautiously stated "TBI leads to NCT defects, which potentially mediate the TDP-43 pathology in CTE". Given the ample evidence demonstrating that TDP-43 demixing/aggregation induces (in vitro and in vivo) NPC deficits with possible sequestration of some NPC components together with TDP-43 aggregates (Chou et al., 2017 Nat Neuros, Ditsworth et al. 2017 Acta Neuropath, Zhang et al., 2018 Cell, Gasset-Rosa et al. 2019 Neuron), nucleocytoplasmic transport deficits could thus be a consequence of cytoplasmic TDP-43 pathology, rather than the cause. It would be of interest to test whether targeting the NPC rescues/prevents TDP-43 pathology using siRNA-mediated silencing of Nups or pharmacological inhibition, as the authors did to show modest improvement in survival or eclosion, respectively. Providing such evidence could help convincingly determine whether NPC deficits cause TDP-43 pathology in CTE.

3. Line 123: 361 proteins were significantly found to be associated with TBI. Were these consistently found to be impaired with all replicates? The criteria used to select those 361 should be described. This would ascertain their relevance.

4. Figure 2: The sophisticated TBI rat model where trauma seems to be induced unilaterally and provokes TDP-43 pathology in the ipsilateral hemisphere could provide a unique system to test whether TDP-43 aggregates spread with time within the nervous system. It would be of interest to analyze the contralateral side and assess where TDP-43 pathology is also eventually recapitulated.

5. Figure 3 provides elegant evidence for functional rescue of NPT deficits using pharmacological inhibition (using KPT-compound derivatives). Was survival or TDP-43 pathology also improved?

6. There are differences between images shown in Figure 2A: not all cells (stained with Dapi) are Nup positive in the control flies (while it appears to be the case in the TBI larvae). What could be the reason? Are there different cell types represented in control versus TBI?

7. Figure 2B: NPC signal is not consistent between figure 2A and figure 2B (which appears very dotty in the latter), albeit it should be similar: can the authors clarify this discrepancy?

8. Figure 6: the increased intensity of Nup62 IHC signal reported in TBE patients is not fully consistent with that shown by immunofluorescence. Hence the overall IHC background signal is much higher in the patient tissues compared to the single control shown. Including additional controls would strengthen the data.

9, There are some problems with the references. For example: reference 45 (line 121) is not correct here, it should be reference 47. Similarly, on page 134, the references stating that "NPC associated with neurodegenerative" are not correctly cited. They should include Chou et al., 2018; Ditsworth et al. 2017, Zhang et al., Coyne et al., 2020 Neuron, Gasset-Rosa et al., 2019…

10. Figure 2H: the main section of the text refers to arrows/arrowheads that should point at RanGAP1 abnormal staining but they are missing in the figure itself.

11. Line 235: figure citation is not correct. It should be figure 3G (and not Figure 5G).

Reviewer #3:

In this study, Anderson and colleagues present data showing that traumatic brain injury (TBI) in Drosophila upregulates expression of Nucleoporins (Nups) that in turn impacts nucleocytoplasmic transport (NCT) by taking an untargeted proteomics approach. The authors further explore the effect of Nup upregulation on the aggregation of TDP-43 (TDPH), a protein whose aggregates are a hallmark of several neurodegenerative diseases; importantly chronic traumatic encephalopathy (CTE), a disease that affects those who play high contact sports such as American football. The authors provide convincing data showing that TBI increases Nup expression and affects (likely-pathological) TDP43 aggregation not just in Drosophila but consistently in a rat model. They also include data from patient samples to show that increased expression of NUP62 and TDP-43.

Overall, the data presented are very compelling and demonstrative of the power of a multi-species approach (Drosophila, rat and human) to explore disease related biology that is translatable and consistent across multiple systems.

1. Line 150 and 414: Here, the authors claim they measured the "Nup214 protein stability". Also in the discussion, they state "In support, our data showed the Nup214 stability and turnover is impaired by repeated traumatic injury in fly brains. It is possible that the slow turnover of Nup214 might be due to dysfunction in protein clearance pathways (e.g. autophagy)." However, what they are doing here is a simple western blot at different time points post-TBI, and it is difficult to tease out differences in protein stability from mRNA/protein synthesis using this strategy. If the authors really want to claim that this is altering protein turnover, one should perform a western upon stopping translation (e.g. cycloheximide application) to claim that the changes that they see are indeed due to alterations in protein stability (not sure how feasible this is in their experimental setting in vivo). Otherwise, they need to do some sort of pulse labeling and tracing experiment. Note that they show that mRNA level of Nup214 (shown as Nup-214 in Fig1I) does increase in adults and larva (Fig1I, K). Hence, both increase in transcription and translation or mRNA stability may all contribute to the increase in Nup214 protein in addition to increased protein stability. If it is difficult to perform these experiments to concretely say that there is a defect in protein stability, the authors should reword their text to say they observe an alteration in "Nup214 protein levels" and not strongly state there is a defect in proteostasis of Nup214 since they don't have direct evidence.

2. Based on the authors model, TBI causes upregulation of certain Nups, which in turn causes TDP-43 aggregation, which then causes neurodegeneration. While the data presented in this paper supports this model, it is also possible that TBI first causes TDP-43 aggregation, which then causes upregulation/aggregation of Nups which then leads to neurodegeneration. I feel the second model is not discussed here and cannot be ruled out since certain experiments are lacking to prefer the first model over the second model. The difference of the two model is whether TDP-43 is upstream or downstream of Nup. For example, if one over-expresses TDP-43 in the absence of TBI, what happens to Nup expression and localization? Can one suppress the short lifespan and motor phenotype caused by over-expressing certain Nup by simultaneously knocking down TDP-43? It is possible both Model 1 and 2 are both correct, and in this case this may suggest that TDP-43 and Nups can regulate each other, causing a vicious cycle in TBI pathogenesis.

https://doi.org/10.7554/eLife.67587.sa1

Author response

Essential revisions:

As you will see from the reviews below, and from our subsequent discussion, we were enthusiastic about the paper. The reviewers ask a number of questions that are listed below, but there are two items we all agreed on that we hope you will be able to address, possibly by including new experiments or by textual changes:

1. You currently do not directly demonstrate the stability of Nups. We suggest to either reword the text or include a pulse-chase experiment to study the stability of Nups;

The reviewer made a great point, and we fully agree that a pulse-chase assay would help in clarifying the stability of Nups. We thought about doing a pulse-chase experiment in our fly model of traumatic brain injury (TBI). However, Cycloheximide treatment in Drosophila at larval or adult stages leads to lethality (Marco et al., Toxicology Letters, 1982). Moreover, the animal’s post-traumatic injury become symptomatic (Anderson et al., HMG 2018) and we suspect that treating them with cycloheximide would make their phenotypes obviously worst (even lethal) as reported previously, making it difficult to perform this assay in vivo. Therefore, we are rewording our statement about the stability of Nups.

This section now reads “We next asked if trauma alters endogenous nucleoporin protein levels overtime. To address this, we measured Nup214 protein levels in trauma and control larval and adult brains. We performed time-course analysis on larval (0, 2, 4, and 6 hours) or adult (0, 2, 4, 24, and 72 hours) animals’ post-injury to assess Nup214 protein level by Western blot analysis. Interestingly, we found that Nup214 protein levels remain upregulated in both larval and adult brains over the time point examined (Figure 1P-S), suggesting that trauma probably disrupts Nup214 levels and possibly turnover in vivo.”

2. Clearly discuss the two possible models i.e. TDP-43 aggregation leads to Nup alterations or vice versa; or include experiments that clarify this relationship.

This is another great point that the reviewer 3 made. In collaboration with Dr. Christopher Donnelly (senior author), we have a manuscript under review that defined the relationship between TDP-43 aggregation and Nup62 sequestration in iPSC motor neurons, HEK293T cells, and ALS patient postmortem tissues. In order to publicly share our unpublished data while under review, we uploaded our collaborative manuscript titled “Nup62 is recruited to pathological condensates and promotes TDP-43 insolubility in C9orf72 and sporadic ALS/FTLD” on Research Square site (Gleixner et al.,). Here is a link. https://www.researchsquare.com/article/rs-144654/v1

Briefly, in our collaborative manuscript (Gleixner et al., 2021 PREPRINT), we report how TDP43 promotes nuclear depletion and cytoplasmic sequestration of Nup62 in ALS/FTD patient iPSC neurons. We found that formation of TDP-43 containing stress granules promotes the nuclear loss and sequestration of Nup62 in vitro and in vivo. Our data suggests that cytoplasmic Nup62 and TDP-43 interactions are pathological in nature and result in insoluble assemblies in both familial and sporadic ALS/FTD postmortem brain tissues (Gleixner et al., 2021 preprint). More importantly, cytoplasmic Nup62 droplets interaction through the NLS likely alter cytoplasmic TDP-43 phase transition resulting in insoluble inclusions. In addition to this, a recent study has shown that aggregated and pathogenic mutations in TDP-43 promote the sequestration and mislocalization of nucleoporins in mouse primary cortical neurons, human fibroblasts and induced pluripotent stem cell–derived neurons (Chou et al., 2018 Nature Neuroscience). Importantly, nuclear pore pathology has been observed in brain tissue in cases of sporadic ALS and those carrying pathogenic mutations in TDP-43 and C9orf72 (Chou et al., 2018; Cook et al., 2020).

Altogether, the abovementioned studies demonstrate the role of TDP-43 in sequestering nucleoporins in sporadic and familial forms of human neurodegenerative diseases. We are including details about both papers in the Discussion section of our manuscript. This section the discussion now reads:

“Recent data from our and Dr. Donnelly’s lab have demonstrated that cytoplasmic Nup62 droplets exhibit characteristics of proteins that undergo liquid-liquid phase separation, and it is likely that these interaction through the classical NLS promotes deleterious phase transition of cytoplasmic TDP-43 causing it to mature into insoluble inclusions (Gleixner et al., 2021 PREPRINT), providing a mechanism for how Nups might promote TDP-43 pathology in traumatic injury. […] Moreover, the synergistic effects of both mechanisms cannot be ruled out as cause of neurodegeneration in traumatic injury.”

Reviewer #2:

[…] The authors convincingly demonstrate that TBI provokes morphological and functional alterations in NPC and nucleocytoplasmic transport, which can be partially improved by pharmacological inhibition of nuclear export thus providing mechanistic insight with potential therapeutic avenue. That being said, there are some aspects that need to be clarified to fully support all claims.

1. In figure 1 the authors conclude that trauma increases stability of Nup214, as increased accumulation of Nup214 is observed (by WB) with time of post-traumatic injury. However, the authors also report that mRNA levels are increased and the time course provided does not allow to fully exclude that Nup enhanced levels may occur predominantly at the transcriptional level (rather than at the protein level due to reduced turnover and/or increased stability as claimed by the authors). To substantiate the authors' conclusion on the effects of enhanced stability, pulse-chase/cycloheximide experiments should be considered.

Strengthening such evidence on stability is even more critical given this is in contrast with previously published studies describing a loss (or reduction) rather than increase of NPC components during neurodegenerative processes (Coyne et al., 2020 Neuron; Chou et al. 2017 Nat Neurosc) or aging (D'Angelo et al., 2009 Cell).

Please see our response (1 and 2) to the essential comments where we addressed these issues.

2. In their original study describing the TBI Drosophila model (Anderson et al. 2018 HMG) the authors had proposed that repetitive trauma induces TDP-43 mislocalization and stress granule formation. Here the authors suggest that TDP-43 pathology may be caused by TBI-induced NPC deficits as cautiously stated "TBI leads to NCT defects, which potentially mediate the TDP-43 pathology in CTE". Given the ample evidence demonstrating that TDP-43 demixing/aggregation induces (in vitro and in vivo) NPC deficits with possible sequestration of some NPC components together with TDP-43 aggregates (Chou et al., 2017 Nat Neuros, Ditsworth et al. 2017 Acta Neuropath, Zhang et al., 2018 Cell, Gasset-Rosa et al. 2019 Neuron), nucleocytoplasmic transport deficits could thus be a consequence of cytoplasmic TDP-43 pathology, rather than the cause. It would be of interest to test whether targeting the NPC rescues/prevents TDP-43 pathology using siRNA-mediated silencing of Nups or pharmacological inhibition, as the authors did to show modest improvement in survival or eclosion, respectively. Providing such evidence could help convincingly determine whether NPC deficits cause TDP-43 pathology in CTE.

As suggested by the reviewer, we fed adult Drosophila KPT-350 (0.05mM and 0.5mM or DMSO) for 10 days and found dose-dependent reduction in Tbph aggregation and have incorporate this new data in (Supplementary Figure 4).

3. Line 123: 361 proteins were significantly found to be associated with TBI. Were these consistently found to be impaired with all replicates? The criteria used to select those 361 should be described. This would ascertain their relevance.

The 361 genes are just those whose p-value between TBI and non-TBI is ≤ 0.05. When we did both >1.6-fold up or down and p≤0.05, there were 246 genes that were altered and present “TBI Proteome”. The GO analysis accepted all genes changed >1.6-fold and p ≤ 0.1 to get enough genes to do GO analysis on. These genes were consistently observed in all replicates. We are including these details in the methodology section.

4. Figure 2: The sophisticated TBI rat model where trauma seems to be induced unilaterally and provokes TDP-43 pathology in the ipsilateral hemisphere could provide a unique system to test whether TDP-43 aggregates spread with time within the nervous system. It would be of interest to analyze the contralateral side and assess where TDP-43 pathology is also eventually recapitulated.

We agree with the reviewer. Further studies in the TBI rat model are ongoing and we plan to examine propagation, aggregation and spreading of TDP-43 pathology in different parts of the rat brain over time. It is going to take us several months to perform and analyze these assays in a rodent model. This is beyond the scope of our current manuscript.

5. Figure 3 provides elegant evidence for functional rescue of NPT deficits using pharmacological inhibition (using KPT-compound derivatives). Was survival or TDP-43 pathology also improved?

We agree with the reviewer. Further studies in the TBI rat model are ongoing and we plan to examine propagation, aggregation and spreading of TDP-43 pathology in different parts of the rat brain over time. It is going to take us several months to perform and analyze these assays in a rodent model. This is beyond the scope of our current manuscript.

6. There are differences between images shown in Figure 2A: not all cells (stained with Dapi) are Nup positive in the control flies (while it appears to be the case in the TBI larvae). What could be the reason? Are there different cell types represented in control versus TBI?

All cells stained with DAPI are Nup positive in Figure 2A. Careful analysis of Figure 2A control image will show that the DAPI signals are surrounded by Nup staining albeit the signal is lower in some of the cells. This might be because of antibody penetration issues (technical). We hope the reviewer can appreciate the effort in acquiring these images, as it is difficult to get Nup antibody that stain Drosophila tissues uniformly. Furthermore, even within the same Drosophila brain tissue there can be some level of variation in the staining pattern of NPC. Hence, we quantify abnormal NPC staining pattern (Figure 2B) in cells located specifically along the midline of the VNC because these cells showed robust and consistent NPC staining.

7. Figure 2B: NPC signal is not consistent between figure 2A and figure 2B (which appears very dotty in the latter), albeit it should be similar: can the authors clarify this discrepancy?

We believe that the reviewer is referring to Figure 2A and 2C. The two images are different in that Figure 2A is only stained with NPC marker Mab414 (imaged in the 568 channel), while Figure 2C is stained with both Mab414 (488 channel, green) and Tbph (568 channel, red) which seems to cause minor alteration in the NPC signal. We hope the reviewer can appreciate that although there was minor effect on the signal when double labeling with Mab414 and Tbph antibodies was done, the abnormal NPC morphology are consistent and still present in Figure 2B

(inset).

8. Figure 6: the increased intensity of Nup62 IHC signal reported in TBE patients is not fully consistent with that shown by immunofluorescence. Hence the overall IHC background signal is much higher in the patient tissues compared to the single control shown. Including additional controls would strengthen the data.

We are including additional high quality IHC images of two controls in our revised manuscript (please see Supplementary Figure 12).

9, There are some problems with the references. For example: reference 45 (line 121) is not correct here, it should be reference 47. Similarly, on page 134, the references stating that "NPC associated with neurodegenerative" are not correctly cited. They should include Chou et al., 2018; Ditsworth et al. 2017, Zhang et al., Coyne et al., 2020 Neuron, Gasset-Rosa et al., 2019…

We apologize for this error. We have checked every reference carefully and corrected them.

10. Figure 2H: the main section of the text refers to arrows/arrowheads that should point at RanGAP1 abnormal staining but they are missing in the figure itself.

We have added the arrows/arrowheads in the figure. Thanks for pointing out this mistake.

11. Line 235: figure citation is not correct. It should be figure 3G (and not Figure 5G).

We have corrected the figure citation.

Reviewer #3:

[…] 1. Line 150 and 414: Here, the authors claim they measured the "Nup214 protein stability". Also in the discussion, they state "In support, our data showed the Nup214 stability and turnover is impaired by repeated traumatic injury in fly brains. It is possible that the slow turnover of Nup214 might be due to dysfunction in protein clearance pathways (e.g. autophagy)." However, what they are doing here is a simple western blot at different time points post-TBI, and it is difficult to tease out differences in protein stability from mRNA/protein synthesis using this strategy. If the authors really want to claim that this is altering protein turnover, one should perform a western upon stopping translation (e.g. cycloheximide application) to claim that the changes that they see are indeed due to alterations in protein stability (not sure how feasible this is in their experimental setting in vivo). Otherwise, they need to do some sort of pulse labeling and tracing experiment. Note that they show that mRNA level of Nup214 (shown as Nup-214 in Fig1I) does increase in adults and larva (Fig1I, K). Hence, both increase in transcription and translation or mRNA stability may all contribute to the increase in Nup214 protein in addition to increased protein stability. If it is difficult to perform these experiments to concretely say that there is a defect in protein stability, the authors should reword their text to say they observe an alteration in "Nup214 protein levels" and not strongly state there is a defect in proteostasis of Nup214 since they don't have direct evidence.

We have addressed this issue in more details in the “essential comment” section

(comment 1). We agree with the reviewer and we are re-wording our statement about the Nup62 protein stability and toning it down. Specifically, we have removed the word “stability” and replaced it with “Nup214 protein levels” as suggested by the reviewer.

Due to technological obstacles, we are unable to perform a pulse chase experiment in vivo. We agree that the Nup214 mRNA levels are also increased suggesting that both TBI impacts nucleoporins at transcription and translational levels. We have added a statement addressing both possibilities in the discussion (see response to comment #15).

2. Based on the authors model, TBI causes upregulation of certain Nups, which in turn causes TDP-43 aggregation, which then causes neurodegeneration. While the data presented in this paper supports this model, it is also possible that TBI first causes TDP-43 aggregation, which then causes upregulation/aggregation of Nups which then leads to neurodegeneration. I feel the second model is not discussed here and cannot be ruled out since certain experiments are lacking to prefer the first model over the second model. The difference of the two model is whether TDP-43 is upstream or downstream of Nup. For example, if one over-expresses TDP-43 in the absence of TBI, what happens to Nup expression and localization? Can one suppress the short lifespan and motor phenotype caused by over-expressing certain Nup by simultaneously knocking down TDP-43? It is possible both Model 1 and 2 are both correct, and in this case this may suggest that TDP-43 and Nups can regulate each other, causing a vicious cycle in TBI pathogenesis.

The reviewer made a valid point. We remain unbiased and open about both models.

It has been previously reported that overexpression of a C-terminal fragment of TDP-43 (TDP43-CTF) itself in primary cortical neurons perturbed Nup98 localization and distribution. This is further evident from mAb414 staining showing that TDP43-CTF overexpression is sufficient to cause FG Nup pathology (Chou et al., 2018). These findings suggesting a cascade of events due to defects in nucleocytoplasmic transport processes. We plan to follow up on the experiments that the reviewer suggested to directly assess which mechanism(s) are involved and which model is more relevant to TBI-mediated neurodegeneration. We are including statements about both models in the Discussion section (see response to essential comment #2).

https://doi.org/10.7554/eLife.67587.sa2

Article and author information

Author details

  1. Eric N Anderson

    Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
  2. Andrés A Morera

    Department of Chemistry and Biochemistry, University of Arizona, Tucson, United States
    Contribution
    Formal analysis, Methodology
    Competing interests
    No competing interests declared
  3. Sukhleen Kour

    Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Writing – review and editing
    Competing interests
    No competing interests declared
  4. Jonathan D Cherry

    1. Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, United States
    2. Boston VA Healthcare System, Boston, United States
    Contribution
    Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – review and editing
    Competing interests
    No competing interests declared
  5. Nandini Ramesh

    Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, United States
    Contribution
    Formal analysis
    Competing interests
    No competing interests declared
  6. Amanda Gleixner

    1. Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. LiveLike Lou Center for ALS Research, Brain Institute, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation
    Competing interests
    No competing interests declared
  7. Jacob C Schwartz

    Department of Chemistry and Biochemistry, University of Arizona, Tucson, United States
    Contribution
    Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – review and editing
    Competing interests
    No competing interests declared
  8. Christopher Ebmeier

    Molecular, Cellular & Developmental Biology, University of Colorado, Boulder, United States
    Contribution
    Formal analysis, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7940-6190
  9. William Old

    Molecular, Cellular & Developmental Biology, University of Colorado, Boulder, United States
    Contribution
    Formal analysis, Methodology
    Competing interests
    No competing interests declared
  10. Christopher J Donnelly

    1. Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. LiveLike Lou Center for ALS Research, Brain Institute, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Conceptualization, Data curation, Funding acquisition, Project administration, Resources, Supervision, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2383-9015
  11. Jeffrey P Cheng

    Physical Medicine & Rehabilitation; Safar Center for Resuscitation Research, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Formal analysis, Investigation, Methodology, Validation
    Competing interests
    No competing interests declared
  12. Anthony E Kline

    1. Physical Medicine & Rehabilitation; Safar Center for Resuscitation Research, University of Pittsburgh, Pittsburgh, United States
    2. Center for Neuroscience; Center for the Neural Basis of Cognition; Critical Care Medicine, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Funding acquisition, Project administration, Resources
    Competing interests
    No competing interests declared
  13. Julia Kofler

    Department of Pathology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – review and editing
    Competing interests
    No competing interests declared
  14. Thor D Stein

    1. Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, United States
    2. Boston VA Healthcare System, Boston, United States
    Contribution
    Data curation, Formal analysis, Funding acquisition, Methodology, Resources, Supervision, Validation, Writing – review and editing
    Competing interests
    No competing interests declared
  15. Udai Bhan Pandey

    1. Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, United States
    2. Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, United States
    Contribution
    Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review and editing
    For correspondence
    udai@pitt.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6267-0179

Funding

National Institute of Neurological Disorders and Stroke (R21 AG064940)

  • Christopher J Donnelly
  • Udai Bhan Pandey

National Institute of Neurological Disorders and Stroke (R01 NS081303)

  • Udai Bhan Pandey

National Institute of Neurological Disorders and Stroke (R21 NS098379)

  • Christopher J Donnelly
  • Udai Bhan Pandey

National Institute of Neurological Disorders and Stroke (U54 NS115266)

  • Thor Stein

National Institute of Neurological Disorders and Stroke (R01 NS084967)

  • Anthony E Kline

National Institute of Neurological Disorders and Stroke (R56 NS113810)

  • Anthony E Kline

National Institute of Neurological Disorders and Stroke (1R00 NS082376)

  • Jacob Schwartz

Robert Packard Center for ALS Research, Johns Hopkins University

  • Udai Bhan Pandey

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

Ethics

All of the animals were handled according to approved institutional animal care and using the approved protocol #21049041 by the University of Pittsburgh.

Senior Editor

  1. Huda Y Zoghbi, Texas Children's Hospital, United States

Reviewing Editor

  1. Patrik Verstreken, KU Leuven, Belgium

Reviewer

  1. Shinya Yamamoto, Baylor College of Medicine, United States

Publication history

  1. Received: February 16, 2021
  2. Accepted: May 14, 2021
  3. Version of Record published: June 1, 2021 (version 1)

Copyright

© 2021, Anderson et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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