Skip to main content

Main menu

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Blog
    • Collections
    • Podcast
  • TOPICS
    • Cognition and Behavior
    • Development
    • Disorders of the Nervous System
    • History, Teaching and Public Awareness
    • Integrative Systems
    • Neuronal Excitability
    • Novel Tools and Methods
    • Sensory and Motor Systems
  • ALERTS
  • FOR AUTHORS
  • ABOUT
    • Overview
    • Editorial Board
    • For the Media
    • Privacy Policy
    • Contact Us
    • Feedback
  • SUBMIT

User menu

Search

  • Advanced search
eNeuro

eNeuro

Advanced Search

 

  • HOME
  • CONTENT
    • Early Release
    • Featured
    • Current Issue
    • Issue Archive
    • Blog
    • Collections
    • Podcast
  • TOPICS
    • Cognition and Behavior
    • Development
    • Disorders of the Nervous System
    • History, Teaching and Public Awareness
    • Integrative Systems
    • Neuronal Excitability
    • Novel Tools and Methods
    • Sensory and Motor Systems
  • ALERTS
  • FOR AUTHORS
  • ABOUT
    • Overview
    • Editorial Board
    • For the Media
    • Privacy Policy
    • Contact Us
    • Feedback
  • SUBMIT
PreviousNext
Research ArticleNew Research, Disorders of the Nervous System

Morphine-Induced Modulation of Endolysosomal Iron Mediates Upregulation of Ferritin Heavy Chain in Cortical Neurons

Bradley Nash, Kevin Tarn, Elena Irollo, Jared Luchetta, Lindsay Festa, Peter Halcrow, Gaurav Datta, Jonathan D. Geiger and Olimpia Meucci
eNeuro 12 July 2019, 6 (4) ENEURO.0237-19.2019; DOI: https://doi.org/10.1523/ENEURO.0237-19.2019
Bradley Nash
1Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA 19102
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kevin Tarn
1Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA 19102
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Elena Irollo
1Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA 19102
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jared Luchetta
1Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA 19102
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lindsay Festa
1Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA 19102
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter Halcrow
2Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND 58203
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gaurav Datta
2Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND 58203
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jonathan D. Geiger
2Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND 58203
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Olimpia Meucci
1Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA 19102
3Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA 19102
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Olimpia Meucci
  • Article
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    Morphine upregulates FHC protein without altering transcript levels. A, Morphine dose dependently upregulates neuronal FHC. Neurobasal cultures were treated with morphine (0.01, 0.1, 1, or 10 µM) or vehicle for 24 h. Morphine significantly increased FHC protein level at every dose, and 1 µM produced a peak effect. Positive control cultures were iron-loaded with FAC (50 µM, 24 h), and negative control cultures were iron-chelated with DFO (100 µM, 24 h). Iron loading significantly increased FHC protein levels, while iron chelation did not alter FHC protein levels, showing that neurobasal cultures could predictably respond to altered iron levels through FHC synthesis; F(6,14) = 52.697, p < 0.0001. B, Blocking Gαi signaling inhibits morphine-mediated FHC upregulation in bilaminar cultures. Cultures were pre-treated with PTX (200 ng/ml) or vehicle for 2 h, followed by addition of morphine (1 µM, 24 h). Morphine alone significantly increased FHC protein levels, but pre-treatment with PTX completely blocked FHC upregulation by morphine; F(3,8) = 6.2933, p = 0.0168. C, Morphine does not change FHC transcript expression in neurobasal cultures. Cultures were treated with morphine (1 µM) for 30 min, 6 h, or 24 h before collection of total RNA. Morphine had no effect on FHC transcript expression as assessed by qPCR. Positive control cultures either iron loaded with a high concentration of FAC (100 µM) for 24 h or treated with TNFα (10 ng/ml) for 3 h significantly upregulated FHC transcripts, showing that the cultures were capable of increasing FHC gene expression; F(7,16) = 94.711, p < 0.0001. D, Morphine does not change FHC transcript expression in bilaminar cultures. As before, cultures were treated with morphine (1 µM) for 30 min, 6 h, or 24 h before collection of total RNA. Again, morphine had no effect on neuronal FHC transcript levels, even in the presence of a glial feeder layer; N = 4 experiments, F(3,42) = 0.38357, p = 0.7654. In both C, D, FHC transcripts were quantified using the ΔΔCT method, and data are presented relative to GAPDH. All experiments analyzed by one-way ANOVA and Dunnett post hoc.

  • Figure 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2.

    Morphine upregulates FHC protein in the neuronal cytoplasm. A, FHC is expressed in the soma and processes of morphine-treated neurons. Neurobasal cultures were treated with morphine (1 µM, 24 h) or vehicle before fixation and immunostaining. Cultures were immunostained for FHC (green) and the neuronal marker β-III Tubulin (red), and counterstained with the nuclear marker Hoechst (blue). Images were acquired with 20× and 60× objectives. Morphine treatment visibly increased FHC staining in the soma and processes. One group of neurons was immunostained without both primary antibodies, showing that non-specific staining was negligible. B, Morphine upregulates FHC in cytoplasmic extracts of neurobasal cultures. Cultures were treated with morphine (1 µM, 3, 6, or 24 h) or vehicle, and separated into cytosolic and nuclear extracts. Morphine dose dependently increased FHC protein levels in cytoplasmic extracts, and 6-h and 24-h treatments reached significance; F(3,8) = 24.28, p = 0.0002. Conversely, morphine did not significantly alter FHC expression in nuclear extracts at any time; F(3,8) = 1.644, p = 0.2549. Both experiments were analyzed by one-way ANOVA and Dunnett post hoc.

  • Figure 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3.

    Morphine dose dependently reduces dendritic spine density and mature spine types through µOR and Gαi signaling. A, Morphine reduced several dendritic spine types in neurobasal cultures. Cultures (20 DIV) were treated with morphine (1 µM, 24 h), followed by fixation and staining with antibodies against MAP2 and with phalloidin 488 counterstain to visualize dendritic spines in MAP2-positive neurons; scale bar = 5 µm. Morphine significantly reduced overall dendritic spine density (t(16) = 9.372) and specifically reduced the density of thin, stubby, and mushroom spines. Dendritic spine density data were analyzed by two-tailed Student’s t test, while dendritic spine morphology data were analyzed by two-way ANOVA with Sidak’s multiple comparisons test (treatment F(3,64) = 151.9, p < 0.0001; morphology F(1,64) = 81.83, p < 0.0001). B, Morphine decreases dendritic spine density in a dose-dependent manner. Neurobasal cultures (20 DIV) were treated with morphine (0.01, 0.1, 1, or 10 µM) or vehicle for 24 h before fixation. As in A, treated cultures were stained with antibodies against MAP2, and counterstained with phalloidin 488 to visualize dendritic spines in MAP2-positive neurons. Morphine reduced overall dendritic spine density dose dependently, and each dose up to 1 µM reduced spine density significantly more than the previous dose; F(4,40) = 50.32, p < 0.0001. Spine morphology analysis showed the same dose-dependent reduction of thin and mushroom spines. All morphine doses significantly reduced thin spine density, while only 0.1, 1, and 10 µM morphine significantly reduced mushroom spine density; treatment F(4,160) = 42.9, p < 0.0001; spine morphology F(3,160) = 956.9, p < 0.0001. C, Morphine’s actions on dendritic spines depend on µOR and Gαi protein activation. Neurobasal cultures (20 DIV) were either treated with morphine (1 µM, 24 h) alone or pre-treated with the µOR antagonist CTAP (1 µM) or the Gαi protein inhibitor PTX (200 ng/ml) for 30 min/2 h before morphine treatment, respectively. Morphine alone significantly reduced dendritic spine density, which was blocked by cotreatment with both CTAP and PTX; F(5,42) = 15.29, p < 0.0001. Spine morphology analysis revealed a similar pattern where morphine significantly reduced thin and mushroom spine density, which was rescued by PTX and CTAP pre-treatment; treatment F(5,168) = 17.39, p < 0.0001; spine morphology F(3,168) = 1448, p < 0.0001. N = 3 experiments for all panels. Spine density data were analyzed by one-way ANOVA and Tukey post hoc, while spine morphology data were analyzed by two-way ANOVA and Tukey post hoc.

  • Figure 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 4.

    Morphine upregulates FHC and decreases mature dendritic spines in layer 2/3 neurons of the rat medial prefrontal cortex. A, Morphine upregulates FHC in cortical neurons in vivo. Three-week-old Holtzman rats were treated with extended-release morphine pellets (25 mg) or placebo for 96 h as detailed in the methods, followed by perfusion and brain tissue collection. Brain sections were stained with antibodies against FHC (green) and the neuronal marker NeuN (red), and images were acquired with a 20× objective. Images were analyzed by measuring the staining intensity of FHC in NeuN-positive areas of the layer 2/3 prelimbic cortex of the mPFC. FHC staining intensity values from individual neurons were averaged to one value per rat, represented as one dot in the graph. FHC staining was significantly higher in neurons of morphine-treated rats; N = 4 rats per treatment group. Data analyzed by Student’s t test; t(6) = 2.717. B, Morphine reduced thin and mushroom dendritic spine density in PFC neurons. A different group of three-week-old Holtzman rats treated with morphine or placebo pellets were used for dendritic spine analysis. PFC-containing tissue slices were stained with DiI to visualize dendritic spines, as shown in the micrograph; scale bar = 5 µm. Morphine decreased the overall spine density of layer 2/3 prelimbic cortex neurons (t(10) = 8.482), and specifically reduced the density of thin and mushroom spines. Stubby spines and filopodia were not significantly changed by morphine; N = 6 rats per treatment group. Spine density data were analyzed by Student’s t test, and morphology data were analyzed by two-way ANOVA with Sidak’s multiple comparisons test (treatment F(1,40) = 44.5, p < 0.0001; morphology F(3,40) = 114, p < 0.0001).

  • Figure 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 5.

    Morphine and iron upregulate FHC and FLC in cortical neurons. A, Iron-loading upregulates FHC and FLC in neurobasal cultures. Cultures were iron-loaded with FAC (25 µM) for 30 min, 6 h, or 24 h before lysis. Additionally, a negative control culture was iron-chelated with DFO (100 µM, 24 h) before lysis. Iron loading with FAC significantly increased FHC and FLC but only after 24 h. FHC and FLC expression were not significantly different at any time after treatment; N = 3 experiments; treatment F(4,20) = 12.94, p < 0.0001; FHC/FLC expression F(1,20) = 0.0029, p = 0.9576. B, Morphine upregulates FHC and FLC in neurobasal cultures. Cultures were treated with morphine (1 µM) or vehicle and lysed 30 min, 6 h, or 24 h after treatment. Morphine upregulated both FHC and FLC, but FHC was significantly upregulated at 6 h, while FLC reached significance at 24 h. However, the overall expression of FHC was not significantly different from FLC at each time point; N = 4 experiments; treatment F(3,24) = 22.94, p < 0.0001; FHC/FLC expression F(1,24) = 9.252, p = 0.0056. C, Morphine-treated rats upregulate FHC and FLC in frontal cortex tissue. Three-week-old Holtzman rats were treated with extended-release morphine or placebo pellets for 96 h as described in Figure 4 and the Materials and Methods. After the treatment, rats were killed and frontal cortex tissue was dissected, homogenized, and analyzed by Western blotting. Morphine significantly increased FHC and FLC expression in vivo, similarly to the in vitro experiment in panel B; N = 4 rats per treatment group; each column contains a homogenate from a different rat; treatment F(1,12) = 43.94, p < 0.0001; FHC/FLC expression F(1,12) = 3.814, p = 0.0745. All data were analyzed by two-way ANOVA and Tukey post hoc.

  • Figure 6.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 6.

    Morphine induces endolysosomal iron efflux to the cytoplasm. Visualization (A) and quantification (B) of endolysosomal iron levels in morphine-treated cortical neurons. Neurobasal cultures were transfected with LAMP1-GFP to visualize endolysosomes and loaded with the endolysosome/Golgi localized iron sensor FeRhoNox-1 (10 µM, 1 h). FeRhoNox-1 fluorescence, which is increased by iron, was measured from LAMP1-GFP-positive areas. Morphine reduced endolysosomal iron levels dose dependently, achieving statistical significance at all doses from 1 to 100 µM; F(4,8) = 112, p < 0.0001. Visualization (C) and quantification (D) of cytosolic iron levels in morphine-treated cortical neurons. A different group of neurons was transfected with LAMP1-RFP and loaded with the cytoplasmically localized iron sensor phen green SK (1 µM, 30 min). Phen green fluorescence, which is quenched by iron, was measured outside of LAMP1-RFP-positive areas. Morphine increased cytosolic iron levels dose dependently, and statistical significance was achieved at all doses from 1 to 100 µM in direct agreement with endolysosomal iron studies; F(4,13) = 47.98, p < 0.0001. E, Morphine dose dependently de-acidifies cortical neuron endolysosomes. Neurobasal cultures were transfected with LAMP1-GFP to visualize lysosomes and loaded with pH-sensitive pHrodo dextran and pH-insensitive Alexa Fluor 647 dextran the night before drug treatments. Endolysosomal pH was calculated from the ratio of dextran emission in LAMP1-GFP-positive areas. Morphine treatment (0.1–10 µM, 30 min) increased endolysosome pH dose dependently (shown in top graph), reaching statistical significance at 1 and 10 µM doses; F(3,8) = 180.2, p < 0.0001. Additionally, naloxone (50 µM) cotreatment with morphine (10 µM, 30 min) completely blocked morphine’s actions on endolysosomal pH, while naloxone alone had no effect on endolysosomal pH (shown in bottom graph); F(3,8) = 127.2, p < 0.0001. All cortical neuron data were analyzed by one-way ANOVA and Dunnett post hoc. Iron visualization (F) and quantification (G) in morphine-treated hippocampal neurons. Hippocampal neurons were labeled with LysoTracker and FeRhoNox-1 to visualize endolysosomal iron, as shown in the micrograph. Morphine treatment (10 µM, 30 min) significantly reduced endolysosomal iron levels (t(4) = 7.036), and increased cytoplasmic iron levels as measured by phen green SK (t(4) = 16.86). Data analyzed by Student’s t test. H, Iron quantification in morphine-treated U87MG cells. Endolysosomal and cytoplasmic iron levels in U87MG cells were measured with the same approach used for hippocampal neurons. Morphine (10 µM, 30 min) significantly reduced endolysosomal iron levels, which was blocked by cotreatment with naloxone (50 µM); F(3,8) = 541.2, p < 0.0001. The same morphine treatment significantly increased cytoplasmic iron levels as measured by phen green SK, which was blocked by chelating endolysosomal iron with DFO (100 µM); F(3,8) = 26.27, p = 0.0002. I, Morphine de-acidifies endolysosomes in U87MG cells. U87MG cells were loaded with the ratiometric pH sensor Lysosensor DND-160 (1 µM, 30 min) before treatments. Morphine (10 µM, 30 min) significantly increased endolysosomal pH, which was blocked by cotreatment with naloxone; F(3,8) = 45.05, p < 0.0001. U87MG data analyzed by one-way ANOVA with Tukey post hoc.

  • Figure 7.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 7.

    Endolysosomal iron is required for morphine-mediated FHC upregulation and reduction of mature types of dendritic spines. A, Morphine increases cytoplasmic labile iron levels over 24 h in cultured neurons. Neurobasal cultures were treated with morphine (1 µM) for 30 min, 3, 6, or 24 h before loading with the cytoplasmically localized fluorescent iron sensor calcein-AM (200 nM, 30 min). Morphine treatment significantly increased cytoplasmic iron from 30 min to at least 24 h. Negative control cultures pre-treated with the iron chelator phenanthroline (10 µM, 30 min) blocked morphine's ability to increase iron levels. Positive control cultures loaded with FAC (100 µM, 24 h) significantly increased neuronal iron levels, as expected; F(8,18) = 166.5, p < 0.0001. B, Chelation of endolysosomal iron blocks morphine-mediated FHC upregulation. Neuronal cultures were treated with the extracellular and endolysosomal iron chelator DFO (100 µM), the cell-impermeable iron chelator DTPA (100 µM), or vehicle in combination with morphine (1 µM) and lysed 24 h later. Morphine alone significantly upregulated FHC, but DFO blocked morphine-mediated FHC upregulation. The extracellular iron chelator DTPA had no effect on morphine-mediated FHC upregulation, indicating that only intracellular iron is required for this pathway; F(5,14) = 13.72, p < 0.0001. Data in A, B were analyzed by one-way ANOVA and Dunnett post hoc. C, Morphine-mediated reduction of mature dendritic spines requires endolysosomal iron. Neuronal cultures (20 DIV) were treated with morphine and various iron modulators for 24 h, followed by analysis of dendritic spine density and morphology. Morphine (1 µM) and FAC (50 µM) both significantly reduced overall dendritic spine density by the same amount. Morphine’s ability to reduce dendritic spine density was blocked by chelation of endolysosomal iron with DFO, but not affected by extracellular iron chelation with DTPA, demonstrating the importance of endolysosomal iron for this pathway; F(6,56) = 24.21, p < 0.0001. Spine morphology analysis showed that morphine and FAC significantly reduced thin and mushroom spines, and this effect was similarly blocked by DFO, but not DTPA; treatment F(6,224) = 31.61, p < 0.0001; spine morphology F(3,224) = 1991, p < 0.0001. Spine density data were analyzed by one-way ANOVA and Tukey post hoc, while spine morphology data were analyzed by two-way ANOVA and Tukey post hoc. N = 3 experiments for all panels.

  • Figure 8.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 8.

    Working model of opioid regulation of FHC. Morphine-mediated activation of the µOR Gαi-protein pathway resulted in endolysosomal iron flux to the cytoplasm and a corresponding de-acidification of endolysosomes. This may be caused by µOR activation of two-pore channels (TPC), TRPML1, or DMT-1. Increased labile iron levels in the cytoplasm results in neurons producing additional FHC protein without altering FHC transcript levels. As FHC translation is controlled by IRPs that bind to FHC transcripts and prevent translation in low-iron conditions, endolysosomal iron flux may release IRPs from FHC transcripts, allowing FHC translation. FHC protein then directly interacts with the CXCR4 signaling complex and inhibits its homeostatic signaling pathways. Notably, this results in reduced dendritic spine density and reduced resilience to excitotoxicity. This pathway may be implicated in HAND with comorbid opioid use, as well as other neurologic disorders where neuronal iron levels are pathologically altered.

Tables

  • Figures
    • View popup
    Table 1.

    Statistics table

    FiguresData structureType of testStatistical information
    Figure 1ANormal distributionOne-way ANOVAF(6,14) = 52.697, p < 0.0001
    Vehicle vs 0.01 μMDunnett's multiple comparisons testCI: –1.8649 to –0.17292
    Vehicle vs 0.1 μMDunnett's multiple comparisons testCI: –3.6802 to –1.9882
    Vehicle vs 1 μMDunnett's multiple comparisons testCI: –3.9667 to –2.2748
    Vehicle vs 10 μMDunnett's multiple comparisons testCI: –3.5352 to –1.8432
    Vehicle vs FACDunnett's multiple comparisons testCI: –4.198 to –2.5061
    Vehicle vs DFODunnett's multiple comparisons testCI: –0.77749 to 0.91446
    Figure 1BNormal distributionOne-way ANOVAF(3,8) = 6.2933, p = 0.0168
    Vehicle vs morphineDunnett's multiple comparisons testCI: –1.9825 to –0.01226
    Vehicle vs PTXDunnett's multiple comparisons testCI: –1.0416 to 0.92856
    Vehicle vs PTX + MorDunnett's multiple comparisons testCI: –0.53893 to 1.4313
    Figure 1CNormal distributionOne-way ANOVAF(7,16) = 94.711, p < 0.0001
    Vehicle vs 30 m MorDunnett's multiple comparisons testCI: –0.49618 to 1.6318
    Vehicle vs 6 h MorDunnett's multiple comparisons testCI: –1.2963 to 0.8317
    Vehicle vs 24 h MorDunnett's multiple comparisons testCI: –1.6376 to 0.49035
    Vehicle vs 24 h FACDunnett's multiple comparisons testCI: –6.7161 to –4.5881
    Vehicle vs 1 h TNFDunnett's multiple comparisons testCI: –2.109 to 0.019
    Vehicle vs 3 h TNFDunnett's multiple comparisons testCI: –6.4336 to –4.3057
    Vehicle vs 24 h TNFDunnett's multiple comparisons testCI: –0.98676 to 1.1412
    Figure 1DNormal distributionOne-way ANOVAF(3,42) = 0.38357, p = 0.7654
    Vehicle vs 30 m MorDunnett's multiple comparisons testCI: –0.23702 to 0.11747
    Vehicle vs 6 h MorDunnett's multiple comparisons testCI: –0.24894 to 0.10556
    Vehicle vs 24 h MorDunnett's multiple comparisons testCI: –0.21279 to 0.14933
    Figure 2B, cytoplasmicNormal distributionOne-way ANOVAF(3,8) = 24.28, p = 0.0002
    Vehicle vs 3 h MorDunnett's multiple comparisons testCI: –1.002 to 0.4371
    Vehicle vs 6 h MorDunnett's multiple comparisons testCI: –1.629 to –0.1897
    Vehicle vs 24 h MorDunnett's multiple comparisons testCI: –2.684 to –1.245
    Figure 2B, nuclearNormal distributionOne-way ANOVAF(3,8) = 1.644, p = 0.2549
    Vehicle vs 3 h MorDunnett's multiple comparisons testCI: –0.6596 to 0.767
    Vehicle vs 6 h MorDunnett's multiple comparisons testCI: –0.7541 to 0.6725
    Vehicle vs 24 h MorDunnett's multiple comparisons testCI: –1.151 to 0.2751
    Figure 3A, spine densityNormal distributionTwo-tailed, unpaired t testt(16) = 9.372, CI: –2.825 to –1.783
    Figure 3A, spine morphologyNormal distributionTwo-way ANOVAInteraction F(3,64) = 13.9, p < 0.0001Treatment F(3,64) = 151.9, p < 0.0001Morphology F(1,64) = 81.83, p < 0.0001
    Vehicle, morphine
    ThinSidak's multiple comparisons testCI: 0.7779 to 1.428
    StubbySidak's multiple comparisons testCI: 0.007506 to 0.6573
    MushroomSidak's multiple comparisons testCI: 0.4853 to 1.135
    FilopodiaSidak's multiple comparisons testCI: –0.2768 to 0.373
    Figure 3B, spine densityNormal distributionOne-way ANOVAF(4,40) = 50.32, p < 0.0001
    Vehicle vs 0.01 μMTukey's multiple comparisons testCI: 0.0951 to 1.616
    Vehicle vs 0.1 μMTukey's multiple comparisons testCI: 1.048 to 2.569
    Vehicle vs 1 μMTukey's multiple comparisons testCI: 2.003 to 3.524
    Vehicle vs 10 μMTukey's multiple comparisons testCI: 2.487 to 4.008
    0.01 vs 0.1 μMTukey's multiple comparisons testCI: 0.1923 to 1.713
    0.1 vs 1 μMTukey's multiple comparisons testCI: 0.1951 to 1.716
    1 vs 10 μMTukey's multiple comparisons testCI: –0.2771 to 1.244
    Figure 3B, spine morphologyNormal distributionTwo-way ANOVAInteraction F(12,160) = 21.58, p < 0.0001Morphology F(3,160) = 956.9, p < 0.0001Treatment F(4,160) = 42.9, p < 0.0001
    Filopodia
    Vehicle vs 0.01 μMTukey's multiple comparisons testCI: –0.4073 to 0.3795
    Vehicle vs 0.1 μMTukey's multiple comparisons testCI: –0.1906 to 0.5962
    Vehicle vs 1 μMTukey's multiple comparisons testCI: –0.3156 to 0.4712
    Vehicle vs 10 μMTukey's multiple comparisons testCI: –0.2767 to 0.5101
    Mushroom
    Vehicle vs 0.01 μMTukey's multiple comparisons testCI: –0.1934 to 0.5934
    Vehicle vs 0.1 μMTukey's multiple comparisons testCI: 0.006604 to 0.7934
    Vehicle vs 1 μMTukey's multiple comparisons testCI: 0.08438 to 0.8712
    Vehicle vs 10 μMTukey's multiple comparisons testCI: 0.1983 to 0.9851
    Stubby
    Vehicle vs 0.01 μMTukey's multiple comparisons testCI: –0.3934 to 0.3934
    Vehicle vs 0.1 μMTukey's multiple comparisons testCI: –0.4378 to 0.349
    Vehicle vs 1 μMTukey's multiple comparisons testCI: –0.3434 to 0.4434
    Vehicle vs 10 μMTukey's multiple comparisons testCI: –0.3295 to 0.4573
    Thin
    Vehicle vs 0.01 μMTukey's multiple comparisons testCI: 0.4372 to 1.224
    Vehicle vs 0.1 μMTukey's multiple comparisons testCI: 0.803 to 1.59
    Vehicle vs 1 μMTukey's multiple comparisons testCI: 1.77 to 2.557
    Vehicle vs 10 μMTukey's multiple comparisons testCI: 2.114 to 2.9
    0.01 vs 0.1 μMTukey's multiple comparisons testCI: –0.02756 to 0.7592
    0.1 vs 1 μMTukey's multiple comparisons testCI: 0.5741 to 1.361
    1 vs 10 μMTukey's multiple comparisons testCI: –0.05034 to 0.7365
    Figure 3C, spine densityNormal distributionOne-way ANOVAF(5,42) = 15.29, p < 0.0001
    Vehicle vs morphineTukey's multiple comparisons testCI: 1.608 to 3.41
    Vehicle vs PTXTukey's multiple comparisons testCI: 0.0146 to 1.817
    Vehicle vs PTX + MorTukey's multiple comparisons testCI: –0.3166 to 1.485
    Vehicle vs CTAPTukey's multiple comparisons testCI: 0.2709 to 2.073
    Vehicle vs CTAP + MorTukey's multiple comparisons testCI: 0.09273 to 1.895
    PTX vs PTX + MorTukey's multiple comparisons testCI: –1.232 to 0.5698
    CTAP vs CTAP + MorTukey's multiple comparisons testCI: –1.079 to 0.7229
    Figure 3C, spine morphologyNormal distributionTwo-way ANOVAInteraction F(15,168) = 9.193, p < 0.0001Morphology F(3,168) = 1448, p < 0.0001Treatment F(5,168) = 17.39, p < 0.0001
    Filopodia
    Vehicle vs morphineTukey's multiple comparisons testCI: –0.3425 to 0.4612
    Vehicle vs PTXTukey's multiple comparisons testCI: –0.3894 to 0.4144
    Vehicle vs PTX + MorTukey's multiple comparisons testCI: –0.4519 to 0.3519
    Vehicle vs CTAPTukey's multiple comparisons testCI: –0.3675 to 0.4362
    Vehicle vs CTAP + MorTukey's multiple comparisons testCI: –0.3487 to 0.455
    Mushroom
    Vehicle vs morphineTukey's multiple comparisons testCI: 0.1544 to 0.9581
    Vehicle vs PTXTukey's multiple comparisons testCI: –0.2019 to 0.6019
    Vehicle vs PTX + MorTukey's multiple comparisons testCI: –0.2956 to 0.5081
    Vehicle vs CTAPTukey's multiple comparisons testCI: –0.08937 to 0.7144
    Vehicle vs CTAP + MorTukey's multiple comparisons testCI: –0.1081 to 0.6956
    PTX vs PTX + MorTukey's multiple comparisons testCI: –0.4956 to 0.3081
    CTAP vs CTAP + MorTukey's multiple comparisons testCI: –0.4206 to 0.3831
    Stubby
    Vehicle vs morphineTukey's multiple comparisons testCI: –0.4644 to 0.3394
    Vehicle vs PTXTukey's multiple comparisons testCI: –0.5612 to 0.2425
    Vehicle vs PTX + MorTukey's multiple comparisons testCI: –0.4206 to 0.3831
    Vehicle vs CTAPTukey's multiple comparisons testCI: –0.4144 to 0.3894
    Vehicle vs CTAP + MorTukey's multiple comparisons testCI: –0.38 to 0.4237
    Thin
    Vehicle vs morphineTukey's multiple comparisons testCI: 1.404 to 2.208
    Vehicle vs PTXTukey's multiple comparisons testCI: 0.1481 to 0.9519
    Vehicle vs PTX + MorTukey's multiple comparisons testCI: –0.03 to 0.7737
    Vehicle vs CTAPTukey's multiple comparisons testCI: 0.4544 to 1.258
    Vehicle vs CTAP + MorTukey's multiple comparisons testCI: –0.03625 to 0.7675
    PTX vs PTX + MorTukey's multiple comparisons testCI: –0.58 to 0.2237
    CTAP vs CTAP + MorTukey's multiple comparisons testCI: –0.8925 to –0.08875
    Figure 4ANormal distributionTwo-tailed, unpaired t testt(6) = 2.717, CI: 0.6332 to 12.11
    Figure 4B, spine densityNormal distributionTwo-tailed, unpaired t testt(10) = 8.482, CI: –7.026 to –4.103
    Figure 4B, spine morphologyNormal distributionTwo-way ANOVAInteraction F(3,40) = 7.579, p = 0.0004Morphology F(3,40) = 114, p < 0.0001Treatment F(1,40) = 44.5, p < 0.0001
    Vehicle, morphine
    ThinSidak's multiple comparisons testCI: 1.922 to 4.195
    StubbySidak's multiple comparisons testCI: –0.2348 to 2.038
    MushroomSidak's multiple comparisons testCI: 0.4543 to 2.727
    FilopodiaSidak's multiple comparisons testCI: –0.8738 to 1.399
    Figure 5ANormal distributionTwo-way ANOVAInteraction F(4,20) = 0.1919, p = 0.9398Treatment F(4,20) = 12.94, p < 0.0001Expression F(1,20) = 0.002895, p = 0.9576
    Vehicle:FHC vs 30 m FAC:FHCTukey's multiple comparisons testCI: –1.704 to 1.063
    Vehicle:FHC vs 6 h FAC:FHCTukey's multiple comparisons testCI: –1.8 to 0.9668
    Vehicle:FHC vs 24 h FAC:FHCTukey's multiple comparisons testCI: –2.94 to –0.1729
    Vehicle:FHC vs DFO:FHCTukey's multiple comparisons testCI: –1.299 to 1.468
    Vehicle:FLC vs 30 m FAC:FLCTukey's multiple comparisons testCI: –1.433 to 1.334
    Vehicle:FLC vs 6 h FAC:FLCTukey's multiple comparisons testCI: –1.762 to 1.005
    Vehicle:FLC vs 24 h FAC:FLCTukey's multiple comparisons testCI: –3.136 to –0.3684
    Vehicle:FLC vs DFO:FLCTukey's multiple comparisons testCI: –1.365 to 1.402
    24 h FAC:FHC vs 24 h FAC:FLCTukey's multiple comparisons testCI: –1.579 to 1.188
    Figure 5BNormal distributionTwo-way ANOVAInteraction F(3,24) = 1.244, p = 0.3157Treatment F(3,24) = 22.94, p < 0.0001Expression F(1,24) = 9.252, p = 0.0056
    Vehicle:FHC vs 30 m Mor:FHCSidak's multiple comparisons testCI: –1.581 to 0.5878
    Vehicle:FHC vs 6 h Mor:FHCSidak's multiple comparisons testCI: –2.202 to –0.03317
    Vehicle:FHC vs 24 h Mor:FHCSidak's multiple comparisons testCI: –3.17 to –1.001
    Vehicle:FLC vs 30 m Mor:FLCSidak's multiple comparisons testCI: –1.118 to 1.051
    Vehicle:FLC vs 6 h Mor:FLCSidak's multiple comparisons testCI: –1.596 to 0.5731
    Vehicle:FLC vs 24 h Mor:FLCSidak's multiple comparisons testCI: –2.356 to –0.1869
    30 m Mor:FHC vs 30 m Mor:FLCSidak's multiple comparisons testCI: –0.6212 to 1.548
    6 h Mor:FHC vs 6 h Mor:FLCSidak's multiple comparisons testCI: –0.4783 to 1.691
    24 h Mor:FHC vs 24 h Mor:FLCSidak's multiple comparisons testCI: –0.2706 to 1.899
    Figure 5CNormal distributionTwo-way ANOVAInteraction F(1,12) = 3.823, p = 0.0742Treatment F(1,12) = 43.94, p < 0.0001Expression F(1,12) = 3.814, p = 0.0745
    Vehicle:FHC vs morphine:FHCTukey's multiple comparisons testCI: –1.358 to –0.4659
    Vehicle:FLC vs morphine:FHCTukey's multiple comparisons testCI: –1.358 to –0.4657
    Morphine:FHC vs morphine:FLCTukey's multiple comparisons testCI: –0.03085 to 0.8613
    Figure 6BNormal distributionOne-way ANOVAF(4,8) = 112, p < 0.0001
    Vehicle vs 0.1 μMDunnett's multiple comparisons testCI: –1.472 to 2.722
    Vehicle vs 1 μMDunnett's multiple comparisons testCI: 1.293 to 5.487
    Vehicle vs 10 μMDunnett's multiple comparisons testCI: 8.804 to 13.49
    Vehicle vs 100 μMDunnett's multiple comparisons testCI: 10.07 to 14.76
    Figure 6DNormal distributionOne-way ANOVAF(4,13) = 47.98, p < 0.0001
    Vehicle vs 0.1 μMDunnett's multiple comparisons testCI: –26.25 to 4.68
    Vehicle vs 1 μMDunnett's multiple comparisons testCI: –34.28 to –6.624
    Vehicle vs 10 μMDunnett's multiple comparisons testCI: –60.4 to –35.66
    Vehicle vs 100 μMDunnett's multiple comparisons testCI: –61.63 to –36.89
    Figure 6E, topNormal distributionOne-way ANOVAF(3,8) = 180.2, p < 0.0001
    Vehicle vs 0.1 μMDunnett's multiple comparisons testCI: –0.2068 to 0.0702
    Vehicle vs 1 μMDunnett's multiple comparisons testCI: –0.6368 to –0.3598
    Vehicle vs 10 μMDunnett's multiple comparisons testCI: –1.127 to –0.8498
    Figure 6E, bottomNormal distributionOne-way ANOVAF(3,8) = 127.2, p < 0.0001
    Vehicle vs morphineDunnett's multiple comparisons testCI: –1.17 to –0.8066
    Vehicle vs naloxoneDunnett's multiple comparisons testCI: –0.11 to 0.2534
    Vehicle vs Nal + MorDunnett's multiple comparisons testCI: –0.21 to 0.1534
    Figure 6G, ELNormal distributionTwo-tailed, unpaired t testt(4) = 7.036, CI: –27.35 to –11.87
    Figure 6G, cytosolNormal distributionTwo-tailed, unpaired t testt(4) = 16.86, CI: 11.13 to 15.52
    Figure 6H, ELNormal distributionOne-way ANOVAF(3,8) = 541.2, p < 0.0001
    Vehicle vs morphineTukey's multiple comparisons testCI: 30.67 to 36.88
    Vehicle vs naloxoneTukey's multiple comparisons testCI: –2.663 to 3.55
    Vehicle vs Nal + MorTukey's multiple comparisons testCI: 4.1 to 10.31
    Morphine vs Nal + MorTukey's multiple comparisons testCI: –29.68 to –23.46
    Figure 6H, cytosolNormal distributionOne-way ANOVAF(3,8) = 26.27, p = 0.0002
    Vehicle vs morphineTukey's multiple comparisons testCI: –14.9 to –5.351
    Vehicle vs DFOTukey's multiple comparisons testCI: –4.623 to 4.929
    Vehicle vs DFO + MorTukey's multiple comparisons testCI: –3.169 to 6.383
    Morphine vs DFO + MorTukey's multiple comparisons testCI: 6.957 to 16.51
    Figure 6INormal distributionOne-way ANOVAF(3,8) = 45.05, p < 0.0001
    Vehicle vs morphineTukey's multiple comparisons testCI: –0.249 to –0.131
    Vehicle vs naloxoneTukey's multiple comparisons testCI: –0.06895 to 0.04895
    Vehicle vs Nal + MorTukey's multiple comparisons testCI: –0.119 to –0.001048
    Morphine vs Nal + MorTukey's multiple comparisons testCI: 0.07105 to 0.189
    Figure 7ANormal distributionOne-way ANOVAF(7,16) = 87.91, p < 0.0001
    Vehicle vs 30 m MorDunnett's multiple comparisons testCI: –678.2 to –19.94
    Vehicle vs 3 h MorDunnett's multiple comparisons testCI: –1010 to –351.8
    Vehicle vs 6 h MorDunnett's multiple comparisons testCI: –1033 to –374.9
    Vehicle vs 24 h MorDunnett's multiple comparisons testCI: –741.5 to –83.21
    Vehicle vs PhenDunnett's multiple comparisons testCI: –27.91 to 630.4
    Vehicle vs Phen + 24 h MorDunnett's multiple comparisons testCI: –208.3 to 449.9
    Vehicle vs FACDunnett's multiple comparisons testCI: –2417 to –1759
    Figure 7BNormal distributionOne-way ANOVAF(5,14) = 13.72, p < 0.0001
    Vehicle vs morphineDunnett's multiple comparisons testCI: –0.954 to –0.06
    Vehicle vs DFODunnett's multiple comparisons testCI: –0.06606 to 0.8279
    Vehicle vs Mor + DFODunnett's multiple comparisons testCI: –0.009428 to 0.8182
    Vehicle vs DTPADunnett's multiple comparisons testCI: –0.1879 to 0.7061
    Vehicle vs Mor + DTPADunnett's multiple comparisons testCI: –0.9824 to –0.08839
    Figure 7C, spine densityNormal distributionOne-way ANOVAF(6,56) = 24.21, p < 0.0001
    Vehicle vs morphineTukey's multiple comparisons testCI: 1.869 to 3.642
    Vehicle vs FACTukey's multiple comparisons testCI: 1.494 to 3.267
    Vehicle vs DFOTukey's multiple comparisons testCI: 0.1525 to 1.925
    Vehicle vs DFO + MorTukey's multiple comparisons testCI: 0.1108 to 1.884
    Vehicle vs DTPATukey's multiple comparisons testCI: –0.3058 to 1.467
    Vehicle vs DTPA + MorTukey's multiple comparisons testCI: 1.13 to 2.903
    Morphine vs FACTukey's multiple comparisons testCI: –1.261 to 0.5114
    DFO vs DFO + MorTukey's multiple comparisons testCI: –0.928 to 0.8447
    DTPA vs DTPA + MorTukey's multiple comparisons testCI: 0.5497 to 2.322
    Figure 7C, spine morphologyNormal distributionTwo-way ANOVAInteraction F(18,224) = 17.58Morphology F(3,224) = 1991, p < 0.0001Treatment F(6,224) = 31.61, p < 0.0001
    Filopodia
    Vehicle vs morphineTukey's multiple comparisons testCI: –0.254 to 0.504
    Vehicle vs FACTukey's multiple comparisons testCI: –0.2623 to 0.4956
    Vehicle vs DFOTukey's multiple comparisons testCI: –0.2984 to 0.4595
    Vehicle vs DFO + MorTukey's multiple comparisons testCI: –0.3355 to 0.4225
    Vehicle vs DTPATukey's multiple comparisons testCI: –0.2568 to 0.5012
    Vehicle vs DTPA + MorTukey's multiple comparisons testCI: –0.2512 to 0.5068
    Mushroom
    Vehicle vs morphineTukey's multiple comparisons testCI: 0.1044 to 0.8623
    Vehicle vs FACTukey's multiple comparisons testCI: 0.07103 to 0.829
    Vehicle vs DFOTukey's multiple comparisons testCI: –0.1206 to 0.6373
    Vehicle vs DFO + MorTukey's multiple comparisons testCI: –0.05953 to 0.6984
    Vehicle vs DTPATukey's multiple comparisons testCI: –0.2068 to 0.5512
    Vehicle vs DTPA + MorTukey's multiple comparisons testCI: 0.03769 to 0.7956
    Morphine vs FACTukey's multiple comparisons testCI: –0.4123 to 0.3456
    DFO vs DFO + MorTukey's multiple comparisons testCI: –0.3179 to 0.4401
    DTPA vs DTPA + MorTukey's multiple comparisons testCI: –0.1345 to 0.6234
    Stubby
    Vehicle vs morphineTukey's multiple comparisons testCI: –0.3845 to 0.3734
    Vehicle vs FACTukey's multiple comparisons testCI: –0.3706 to 0.3873
    Vehicle vs DFOTukey's multiple comparisons testCI: –0.4429 to 0.3151
    Vehicle vs DFO + MorTukey's multiple comparisons testCI: –0.3956 to 0.3623
    Vehicle vs DTPATukey's multiple comparisons testCI: –0.3956 to 0.3623
    Vehicle vs DTPA + MorTukey's multiple comparisons testCI: –0.3929 to 0.3651
    Thin
    Vehicle vs morphineTukey's multiple comparisons testCI: 1.788 to 2.546
    Vehicle vs FACTukey's multiple comparisons testCI: 1.457 to 2.215
    Vehicle vs DFOTukey's multiple comparisons testCI: 0.4081 to 1.166
    Vehicle vs DFO + MorTukey's multiple comparisons testCI: 0.3432 to 1.101
    Vehicle vs DTPATukey's multiple comparisons testCI: –0.07897 to 0.679
    Vehicle vs DTPA + MorTukey's multiple comparisons testCI: 1.121 to 1.879
    Morphine vs FACTukey's multiple comparisons testCI: –0.7095 to 0.04842
    DFO vs DFO + MorTukey's multiple comparisons testCI: –0.4438 to 0.3142
    DTPA vs DTPA + MorTukey's multiple comparisons testCI: 0.821 to 1.579
Back to top

In this issue

eneuro: 6 (4)
eNeuro
Vol. 6, Issue 4
July/August 2019
  • Table of Contents
  • Index by author
  • Ed Board (PDF)
Email

Thank you for sharing this eNeuro article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Morphine-Induced Modulation of Endolysosomal Iron Mediates Upregulation of Ferritin Heavy Chain in Cortical Neurons
(Your Name) has forwarded a page to you from eNeuro
(Your Name) thought you would be interested in this article in eNeuro.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
View Full Page PDF
Citation Tools
Morphine-Induced Modulation of Endolysosomal Iron Mediates Upregulation of Ferritin Heavy Chain in Cortical Neurons
Bradley Nash, Kevin Tarn, Elena Irollo, Jared Luchetta, Lindsay Festa, Peter Halcrow, Gaurav Datta, Jonathan D. Geiger, Olimpia Meucci
eNeuro 12 July 2019, 6 (4) ENEURO.0237-19.2019; DOI: 10.1523/ENEURO.0237-19.2019

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Share
Morphine-Induced Modulation of Endolysosomal Iron Mediates Upregulation of Ferritin Heavy Chain in Cortical Neurons
Bradley Nash, Kevin Tarn, Elena Irollo, Jared Luchetta, Lindsay Festa, Peter Halcrow, Gaurav Datta, Jonathan D. Geiger, Olimpia Meucci
eNeuro 12 July 2019, 6 (4) ENEURO.0237-19.2019; DOI: 10.1523/ENEURO.0237-19.2019
del.icio.us logo Digg logo Reddit logo Twitter logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Significance Statement
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgments
    • Footnotes
    • References
    • Synthesis
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

Keywords

  • dendritic spine
  • endolysosome
  • ferritin
  • morphine
  • neuroHIV
  • NEURON

Responses to this article

Respond to this article

Jump to comment:

No eLetters have been published for this article.

Related Articles

Cited By...

More in this TOC Section

New Research

  • Long-term effects of preterm birth on children’s brain structure: an analysis of the Adolescent Brain Cognitive Development (ABCD) Study
  • Target-distractor competition modulates saccade trajectories in space and object-space
  • Modulation of visual contrast sensitivity with tRNS across the visual system, evidence from stimulation and simulation
Show more New Research

Disorders of the Nervous System

  • Sex and Estrous Cycle Stage Shape Left-Right Asymmetry in Chronic Hippocampal Seizures in Mice
  • β2 nAChR Activation on VTA DA Neurons Is Sufficient for Nicotine Reinforcement in Rats
  • Understanding Glaucoma One Synapse at a Time
Show more Disorders of the Nervous System

Subjects

  • Disorders of the Nervous System

  • Home
  • Alerts
  • Visit Society for Neuroscience on Facebook
  • Follow Society for Neuroscience on Twitter
  • Follow Society for Neuroscience on LinkedIn
  • Visit Society for Neuroscience on Youtube
  • Follow our RSS feeds

Content

  • Early Release
  • Current Issue
  • Latest Articles
  • Issue Archive
  • Blog
  • Browse by Topic

Information

  • For Authors
  • For the Media

About

  • About the Journal
  • Editorial Board
  • Privacy Policy
  • Contact
  • Feedback
(eNeuro logo)
(SfN logo)

Copyright © 2023 by the Society for Neuroscience.
eNeuro eISSN: 2373-2822

The ideas and opinions expressed in eNeuro do not necessarily reflect those of SfN or the eNeuro Editorial Board. Publication of an advertisement or other product mention in eNeuro should not be construed as an endorsement of the manufacturer’s claims. SfN does not assume any responsibility for any injury and/or damage to persons or property arising from or related to any use of any material contained in eNeuro.