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[Preprint]. 2023 Aug 2:2023.07.31.551324. [Version 1] doi: 10.1101/2023.07.31.551324

CCT and Cullin1 regulate the TORC1 pathway to promote dendritic arborization in health and disease

Erin N Lottes 1, Feyza H Ciger 1, Shatabdi Bhattacharjee 1, Emily A Timmins-Wilde 1, Benoit Tete 1, Tommy Tran 1, Jais Matta 1, Atit A Patel 1, Daniel N Cox 1,*
PMCID: PMC10418059  PMID: 37577581

Abstract

The development of cell-type-specific dendritic arbors is integral to the proper functioning of neurons within their circuit networks. In this study, we examine the regulatory relationship between the cytosolic chaperonin CCT, key insulin pathway genes, and an E3 ubiquitin ligase (Cullin1) in homeostatic dendritic development. CCT loss of function (LOF) results in dendritic hypotrophy in Drosophila Class IV (CIV) multidendritic larval sensory neurons, and CCT has recently been shown to fold components of the TOR (Target of Rapamycin) complex 1 (TORC1), in vitro. Through targeted genetic manipulations, we have confirmed that LOF of CCT and the TORC1 pathway reduces dendritic complexity, while overexpression of key TORC1 pathway genes increases dendritic complexity in CIV neurons. Both CCT and TORC1 LOF significantly reduce microtubule (MT) stability. CCT has been previously implicated in regulating proteinopathic aggregation, thus we examined CIV dendritic development in disease conditions as well. Expression of mutant Huntingtin leads to dendritic hypotrophy in a repeat-length-dependent manner, which can be rescued by TORC1 disinhibition via Cullin1 LOF. Together, our data suggest that Cullin1 and CCT influence dendritic arborization through regulation of TORC1 in both health and disease.

INTRODUCTION

It was once thought that the brain was isolated from the effects of starvation: at the start of the 20th century, Edward H. Dewey, M.D. asserted, “The brain is not only a self-feeding organ when necessary, but it is also a self-charging dynamo, regaining its exhausted energies entirely through rest and sleep” (Dewey, 1900). Cognitive symptoms were repeatedly connected to diabetes (Miles and Root, 1922; Moheet et al., 2015), but it wasn’t until the discovery of neuronal insulin that the idea of the metabolically insulated brain was retired (Raizada, 1983; Weyhenmeyer and Fellows, 1983; Pardridge et al., 1985; Craft, 2009). Research linking neurodegenerative disorders to insulin resistance have since highlighted the necessity of understanding how the insulin pathway modulates the brain in health and disease (Schulingkamp et al., 2000; Wu et al., 2017; Kellar and Craft, 2020; Burillo et al., 2021). In this study, we examine putative connections among three cytosolic mechanisms – the insulin pathway, chaperone activity, and ubiquitin ligase activity – which each coordinate dendritic arborization through the regulation of the cytoskeleton.

In Drosophila melanogaster, the chaperonin CCT (Complex Containing Tailless Complex Polypeptide 1 [TCP-1], also known as TRiC) is required for dendritic development of Class IV (CIV) multidendritic (md) sensory neurons of the larval peripheral nervous system (Das et al., 2017; Wang et al., 2020). CCT is a chaperonin – an ATP-dependent chaperone – and has the canonical chaperonin “barrel” shape, composed of two repeating rings of eight subunits each: CCT1–8 (Fig 1A) (Liou and Willison, 1997; Jin et al., 2019). Estimated to fold from 1–15% of cellular proteins, two of CCT’s most notable clients are cytoskeletal monomeric subunits actin and tubulin (Thulasiraman et al., 1999; Grantham et al., 2006; Brackley and Grantham, 2009; Willison, 2018; Gestaut et al., 2022).

Figure 1: CCT and the TORC1 pathway promote dendritic arborization.

Figure 1:

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(A) Schematic diagram of regulatory relationships between the insulin pathway, SCF complex, CCT, and TORC1 pathway with the insulin pathway indicated by teal arrows. TORC1 is negatively regulated by Cullin1 and positively regulated by CCT. The upstream insulin pathway in green is displayed for context but was not examined in this study. Individual components of the SCF and TORC1 complexes examined in this study are outlined in white. (B) Representative images of CIV neurons for key CCT and TORC1 pathway manipulations, with RNAi-mediated knockdown indicated with -IR and UAS-mediated overexpression with -OE. Scale bars = 100 μm (C) Total dendritic length of CCT and TORC1 pathway manipulations shown in comparison to a WT control, * indicates a significant change from control (p < 0.05). (D) Number of Sholl intersections mapped by color at increasing radial distances from soma (μm). Significant changes in Sholl maximum intersections and radius are indicated by an asterisk. Arrows indicate genotypes where the radius of maximum intersections has shifted significantly from WT. The white dashed line is to reference the radius of maximum intersections for WT neurons. In all panels * = p < 0.05, see Supplementary Table S2 for detailed statistics.

CCT physically interacts with proteins in the TORC1 pathway and folds Raptor, the regulatory component of TORC1 (Cuéllar et al., 2019; Kim and Choi, 2019). TORC1 is a part of the insulin pathway, operating downstream of Phosphatidylinositol-3 kinase (PI3K) and Akt kinase (Fig 1A), and has been long known to control cell size (Fingar et al., 2002; Kumar et al., 2005) as well as dendritic development in many organisms (Jaworski et al., 2005; Kumar et al., 2005; Lee and Chung, 2007; Urbanska et al., 2012; Thomanetz et al., 2013; Shimono et al., 2014; Skalecka et al., 2016; Kosillo et al., 2019, 2022).

In this study, we investigate the regulatory roles of CCT, TORC1, and the SCF complex in both conditions of homeostatic development and proteinopathic disease states. Cullin1 is the scaffolding component of the Skp, Cullin, F-box (SCF) E3-ubiquitin ligase – previously shown to regulate TORC1 in dendritic pruning in Drosophila (Wong et al., 2013). In homeostasis, via in vivo analyses of CIV neurons, we establish that dendritic arborization is mediated by a chaperonin (CCT) and E3 ubiquitin ligase component (Cullin1), both of which partially mediate dendritic complexity through regulation of TORC1. TORC1 inhibition leads to dendritic hypotrophy whereas TORC1 activation leads to dendritic hypertrophy.

CCT and TORC1 have also been examined as endogenous mediators of the cellular effects of Huntington’s Disease (HD), a neurodegenerative disease caused by a polyglutamine expansion mutation. Targeted manipulations of CCT and TORC1 have been found to reduce aggregates and enhance cell viability in multiple model systems of HD (Sontag et al., 2013; Lee et al., 2015; Noormohammadi et al., 2016; Shen et al., 2016). TORC1 inhibition, via application of rapamycin and similar drugs, has been shown to be neuroprotective in cell culture models of HD, as well as in both Drosophila and zebrafish photoreceptors with mutant Huntingtin (Ravikumar et al., 2004; Berger et al., 2006; King et al., 2008; Williams et al., 2008). However, the role of TORC1 and CCT in regulating dendritic development in HD conditions was previously unexplored. In CIV neurons, although high repeat mHTT expression results in dendritic hypotrophy and loss of underlying microtubule signal like that of TORC1 and CCT LOF, we do not find evidence that mHTT disrupts the TORC1-CCT dendritic arborization pathway in HD conditions.

METHODS

Drosophila husbandry and stocks

The Drosophila melanogaster stocks used in this study were reared on a standard recipe of cornmeal, molasses, and agar media and maintained at 25°C. Genetic crosses for live imaging and immunohistochemistry were reared at 29°C. In all experiments, larvae were randomized for sex. A complete list of stocks and genetic lines for this study is provided in Supplementary Table S1.

Immunohistochemical analysis

Larval dissection, mounting, and staining were performed as previously described (Grueber et al., 2002; Sulkowski et al., 2011). Larvae stained for CCT, acetylated α-tubulin, and Raptor were dissected and muscles removed as previously described (Tenenbaum and Gavis, 2016), and fixed samples were imaged with a Zeiss LSM780 Confocal microscope under 63X magnification using an oil-immersion objective. Primary antibodies used include: chicken anti-GFP (1:1000 dilution, Aves Labs), rabbit anti-phosphorylated S6k (1:300 dilution, Cell Signaling Technology), rabbit anti-Raptor (1:200 dilution, Cell Signaling Technology), mouse anti-acetylated α-tubulin (1:100 dilution, Santa Cruz Biotechnology), mouse anti-Futsch (1:100 dilution, Developmental Studies Hybridoma Bank), rabbit anti-Huntingtin (1:200 dilution, Cell Signaling Technology), rabbit anti-HA (1:500 dilution, Cell Signaling Technology), rat anti-CCT1 (1:200 dilution, Origene), mouse anti-CCT5 (1:200 dilution, GeneTex), mouse anti-S6k (1:200 dilution, Proteintech), rabbit anti-phosphorylated Akt (1:200 dilution, Cell Signaling Technology), rabbit anti-Cullin1 (1:200 dilution, Invitrogen), mouse anti-β-tubulin IIA (1:500 dilution, Novus Biologicals). Secondary antibodies used include: donkey anti-chicken 488 (1:2000 dilution, Jackson Immunoresearch), donkey anti-mouse 555 (1:200 dilution, Life Technologies), donkey anti-mouse 568 (1:200 dilution, Life Technologies), donkey anti-mouse 647 (1:200 dilution, Life Technologies), donkey anti-rabbit 568 (1:200 dilution, Life Technologies), donkey anti-rabbit 647 (1:200 dilution, Life Technologies), donkey anti-rat Cy3 (1:200 dilution, Jackson Immunoresearch).

Live confocal imaging, neural reconstructions, and morphometric analyses

Live imaging was performed using the Zeiss LSM780 Confocal as previously described (Iyer et al., 2013a, 2013b). Multiple gene-specific RNAi lines were examined for each genotype and validated using IHC and mutant analysis when possible. MARCM analysis was performed as previously described (Sulkowski et al., 2011; Iyer et al., 2013b). To generate CIV neuron MARCM clones GAL5−40 UAS-Venus:pm SOP-FLP#42;tubP-GAL80FRT40A (2L MARCM) flies were crossed to CCT4KG09280,FRT40A mutant flies. Maximum intensity projections of dendritic z-stacks were processed and neurons reconstructed as previously described (Clark et al., 2018). Quantitative morphological data (including total dendritic length and Sholl analysis) were compiled using the Simple Neurite Tracer (SNT) plugin for FIJI (Ferreira et al., 2014; Arshadi et al., 2021). Batch processing was completed using a custom FIJI macro and Rstudio script created by Dr. Atit A. Patel (Cox Lab) and the resulting data was exported to Excel (Microsoft).

Live multichannel neural reconstructions

Multichannel cytoskeletal reconstructions and related quantitative analyses were performed using the method described in (Nanda et al., 2021) and implemented in (Bhattacharjee et al., 2022) for CIV cytoskeletal analysis. In brief, one primary branch and all connected distal branches in the same posterior quadrant were reconstructed for each neuron using Neutube (Feng et al., 2015), then microtubule (MT) fluorescence was measured at distinct points along the dendritic arbor, averaged in 20 or 40 μm bins, and then normalized to 1 for comparison to controls. Displayed Jupiter::mCherry fluorescence is shown as a ratio of normalized fluorescence over the total path length within each bin, and can be understood as the average normalized fluorescence along a single branch.

Co-localization analysis

Colocalization was performed on samples prepared via immunohistochemistry and imaged at 63X resolution under an oil immersion lens. A theoretical point spread function (PSF) was created for each measured wavelength using FIJI’s PSF Generator and the Born and Wolf 3D optical model and images were deconvolved with the FIJI DeconvolutionLab2 plugin using the Richardson-Lucy algorithm (Sage et al., 2017). Cytosolic compartments of interest were traced and regions of interest created using FIJI, then analyzed with BIOP JacoP to produce Pearson’s Correlation and Mander’s Coefficients (Bolte and Cordelières, 2006). Automatic thresholding based on percentile was used for Mander’s Coefficients for CCT and wild-type (WT) HTT signal. Manual thresholding for mHTT120-HA signal was based on the maximum intensity of off-target rabbit anti-HA signal in matched controls.

Temperature-induced mHTT expression

mHTT overexpression lines were made by crossing ppkEGFP,tsGAL80;ppkGAL4 with UAS-mHTTQ120-HA overexpression lines. tsGAL80 binds GAL4 at temperatures <29°C and prevents transcription of UAS-driven mHTT misexpression (McGuire et al., 2004). However, at temperatures ≥29°C, tsGAL80 cannot bind GAL4 which allows mHTTQ120-HA overexpression. ppkEGFP,tsGAL80;ppkGAL4 was crossed to Oregon R (WT) and UAS-mHTTQ120-HA at RT (25°C) and allowed to lay eggs for three hours. Larvae were raised in two conditions: 96 hours at 25C (GAL4 “off”) then stained for HTT (WT HTT), or 48 hours at 25°C followed by 48 hours at 30°C (GAL4 “on”) and stained for HA (HTT120). Larvae were dissected 96 hours after egg laying (AEL) as described above. Dissected larvae were stained for HTT and CCT1 or HA and CCT1 and prepared and imaged as described above for all other immunohistochemical analyses.

mHTT aggregate inclusion body analysis

Inclusion body aggregates of mHTT were manually quantified using Zen Blue Lite software in neurons expressing mHTTQ96-Cerulean imaged live at 20X magnification. Neuron labels were coded for analysis to ensure blind conditions. Inclusion bodies were outlined using the “Draw Spline Contour” tool and average area compared across genotypes.

Experimental design and statistical analyses

Statistical analyses were performed using GraphPad Prism 10. Error bars in the figures represent standard error of the mean (SEM). All data were tested for normality using the Shapiro-Wilk normality test. Statistical tests performed include: unpaired t-test; one-way ANOVA with Dunnett’s, Šídák’s, or Tukey’s multiple comparison test (multiple comparison tests chosen based on Prism 10 recommendations); two-way ANOVA with Tukey’s multiple comparison test; Mann-Whitney U test; Kruskal Wallis test using Dunn’s multiple comparison test. Data points lying greater than two standard deviations above or below the mean were removed. A single asterisk is used in all graphs to denote significance (p ≤ 0.05), and detailed statistical results are available in Supplementary Table S2.

RESULTS

CCT LOF and of disruption of TORC1 pathway genes results in dendritic hypotrophy

CCT is required for complex dendritic arbor formation in Drosophila melanogaster CIV md neurons (Das et al., 2017; Wang et al., 2020), as we have independently confirmed in this study via RNAi and MARCM (Fig 1B–D, S1A–D). LOF of CCT3 and CCT5 both result in significant dendritic hypotrophy and will be used throughout this study to disrupt the CCT complex. LOF of single CCT subunits has previously been found to reduce expression of other CCT subunits (Freund et al., 2014; Chen et al., 2018; Kim and Choi, 2019), and we have independently found via immunohistochemistry (IHC) that CCT4 LOF results in significant reductions in CCT5 expression (Fig S1E). Additionally, simultaneous RNAi knockdown of CCT4 and CCT5 results in significantly lower CCT5 expression than CCT4-IR or CCT5-IR knockdowns alone (Fig S1E). Developmental time course analyses reveal that CIV dendritic hypotrophy with CCT3 or CCT5 knockdowns first manifests at 72 hours after egg laying (AEL) – as indicated by reductions in total dendritic length (TDL) that plateau later in larval development (Fig S1F).

Though many clients of CCT have been identified, few have been examined alongside CCT in dendritic development. There is evidence that CCT folds components of TORC1 in vitro and co-operates with the insulin pathway to regulate organ size in Drosophila (Cuéllar et al., 2019; Kim and Choi, 2019). Using RNAi, we knocked down key insulin pathway effector genes: Akt, Raptor, and S6k – an activator, a component, and a downstream effector of TORC1, respectively (Fig 1A). Efficacy of various RNAi knockdowns was confirmed by quantifying fluorescence of each protein of interest in the wild-type (WT) control and RNAi knockdown conditions. Raptor RNAi results in significant reductions in Raptor fluorescence relative to control (Fig S2A). S6k RNAi (S6k-IR) likewise results in significant decreases in S6k (Fig S2B), and phosphorylated S6k (P-S6k) expression, the active form of S6k (Fig 2A). Akt-IR also results in a significant decrease of phosphorylated Akt expression (Fig S2C). Akt, Raptor, and S6k LOF all result in significant dendritic hypotrophy, as measured by total dendritic length (TDL) (Fig 1B–C). Furthermore, the maximum number of Sholl intersections is significantly decreased in Akt and CCT3 knockdown conditions (Fig 1D), indicative of decreased branch complexity; additionally, CCT5 knockdown leads to a significant shift in maximum radius toward the soma (Fig 1D). Collectively, these data demonstrate both CCT and the TORC1 pathway are required for CIV dendritic development.

Figure 2: CCT and Cullin1 regulate the TORC1 pathway in vivo.

Figure 2:

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(A) Heat map showing the percent change in P-S6k fluorescence for each genetic manipulation as compared to its proper control. (B) Raptor fluorescence is significantly decreased in CCT5 LOF conditions and is not rescued by overexpression of Raptor. (C) P-S6k fluorescence levels are significantly decreased in CCT5 LOF and are not rescued by overexpression of S6k. (D) Representative images of combined TORC1 genetic manipulations. Scale bars = 100 μm. (E) Total dendritic length in microns for WT and combined TORC1 genetic manipulations. In all panels * = p < 0.05, see Supplementary Table S2 for detailed statistics.

TORC1 hyperactivation results in dendritic hypertrophy

There is evidence in multiple model organisms that TORC1 over-activation can result in increases in dendritic complexity (Diaz-Ruiz et al., 2009; Kosillo et al., 2019; Kanaoka et al., 2023). In CIV neurons, overexpression (OE) of key components of the TORC1 pathway result in increased complexity of dendritic arbors (Fig 1B–D). S6k OE and Akt OE both result in significantly increased TDL, a significantly higher Sholl maximum, and a significantly, distally shifted Sholl maximum radius relative to controls (Fig 1B–D). In contrast, overexpression of individual subunits of CCT does not produce any significant change in dendritic TDL (Fig S1G), consistent with prior studies (Das et al., 2017). Overexpression of single CCT subunits has been found to be insufficient to increase levels of other CCT subunits in the complex (Tam et al., 2006; Noormohammadi et al., 2016).

Cullin1, a scaffolding component of the SCF complex, has previously been shown to regulate TORC1 activity in CIV dendrite pruning (Wong et al., 2013) through inhibition of Akt (Fig 1A). Another component of SCF, SkpA, was also previously reported to produce dendritic hypertrophy under LOF conditions (Das et al., 2017). We find that as in SkpA LOF and Akt OE, Cullin1 LOF results in significantly increased TDL in CIV neurons (Fig 1B–C). Efficacy of Cullin1 RNAi was confirmed via IHC as Cullin1 LOF leads to a significant reduction in Cullin1 fluorescence in CIV neurons (Fig S2D).

To validate activation or inhibition of TORC1 through genetic manipulations of pathway components and cytosolic interactors, we stained for the downstream product of TORC1: phosphorylated S6k (P-S6k) (Fig 1A, 2A). LOF of Raptor and CCT5 significantly decrease P-S6k levels, confirming disruption of TORC1 (Fig 2A). Cullin1 LOF significantly increases levels of P-S6k (Fig 2A) indicating that knockdown of Cullin1 disinhibits TORC1 to phosphorylate S6k.

CCT regulates Raptor levels in vivo

CCT was recently demonstrated to fold Raptor, the regulatory component of TORC1 (Cuéllar et al., 2019). We confirm that this regulatory relationship is conserved in Drosophila melanogaster larval sensory neurons. First, we find that CCT5 knockdown significantly decreases levels of Raptor in CIV neurons from both WT and Raptor overexpression (Fig 2B, S2A). Though overexpression of Raptor via UAS-Raptor-HA significantly increases Raptor fluorescence over WT levels (Fig S2A), it is insufficient to increase Raptor fluorescence levels significantly in a CCT5 LOF background, as measured via IHC (Fig 2B).

To further confirm the requirement of CCT to sustain the TORC1 pathway, we overexpress S6k in the CCT5-IR background (Fig 2 C–E). We hypothesized that if CCT were required for TORC1-mediated phosphorylation of S6k, then overexpression of S6k would not be sufficient to rescue either P-S6k levels or dendritic arborization. Indeed, overexpression of S6k could not return levels of P-S6k fluorescence to WT conditions in a CCT5-IR background (Fig 2C). Likewise, overexpression of S6k in CCT5-IR neurons was unable to rescue CCT5 LOF-induced dendritic hypotrophy (Fig 2D–E) revealing CCT is necessary for S6k OE-induced dendritic hypertrophy. These data indicate that CCT is required for Raptor expression and subsequent S6k phosphorylation through TORC1.

Cullin1 regulates dendritic arborization through TORC1

Cullin1 knockdown significantly increases levels of P-S6k fluorescence as measured through IHC (Fig. 2A). Cullin1 LOF and S6k overexpression both lead to dendritic hypertrophy (Fig 1 B–D). However, combining Cullin1 knockdown and S6k overexpression in the same neurons does not further increase dendritic complexity, and there is no significant difference in TDL between the individual manipulations and the combined phenotype (Fig 2D–E).

We hypothesized that if Cullin1 LOF were causing dendritic hypertrophy through regulation of TORC1, then it would be unable to recover any of the lost complexity in CCT LOF neurons, as we have established CCT is essential for TORC1 activity (Fig 2B–C). Cullin1 knockdown does not significantly change TDL in a CCT3 LOF background compared to CCT3 knockdown alone (Fig 2E), indicating that CCT function is required for the observed hypertrophy in Cullin1 knockdown neurons (Fig 2E).

TORC1 pathway disruption results in loss of stable microtubules

CCT has been demonstrated to directly fold both α- and β-tubulin (Llorca, 2000; Gestaut et al., 2022) and regulate stable microtubule (MT) levels in CIV dendrites (Das et al., 2017; Wang et al., 2020). We have independently confirmed that CCT LOF leads to significant reductions in underlying levels of stable MTs through several measures (Figs. 3A–C, S2E). Since inhibition of the TORC1 pathway caused significant dendritic hypotrophy, and TORC1 has been previously linked to cytoskeletal phenotypes (Swiech et al., 2011), we predicted that there would be underlying cytoskeletal changes accompanying the loss of complexity.

Figure 3: TORC1 pathway manipulations alter underlying stable MT signal.

Figure 3:

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(A) Heat map showing percent change from control in acetylated α-tubulin and Futsch levels for each genetic manipulation. Each experimental condition was compared to WT control and appropriate statistical comparisons were performed (detailed in Supplementary Table S2). (B) Representative reconstructions of branches from WT and TORC1 genetic manipulations – normalized mCherry::Jupiter fluorescence is coded with the rainbow spectrum shown (A.U.). Scaled axes are provided in μm. (C) Heat map representing the average normalized, binned mCherry::Jupiter fluorescence along dendrites at increasing distances from the soma for each genotype. TORC1 inhibitions are marked in purple and TORC1 activations in green. Genotypes found to be significantly different along the dendritic arbor are marked with an asterisk. In all panels * = p < 0.05, see Supplementary Table S2 for detailed statistics.

We examined the levels of Futsch – a microtubule-associated protein (MAP), acetylated α-tubulin, and βtubulin IIA in the soma of CIV neurons. Both Futsch and acetylated α-tubulin serve as markers of stable MTs (Hummel et al., 2000; Pawson et al., 2008; Weiner et al., 2016; Eshun-Wilson et al., 2019), and β-tubulin IIA is a MT subunit known to be specifically folded by CCT (Llorca, 2000).

In CIV neurons, basal levels of acetylated α-tubulin are significantly reduced in CCT3-IR, CCT5-IR, Raptor-IR, S6k-IR, and Akt-IR, but are not significantly changed in Cullin1-IR, S6k OE, or Akt OE (Fig 3A). Futsch is significantly decreased in TORC1 inhibition conditions: LOF of CCT3, CCT5, S6k, Raptor, or Akt leads to significant reductions of Futsch fluorescence (Fig 3A). In contrast, Akt and S6k overexpression leads to significant increases in Futsch signal (Fig 3A); however, Cullin1-IR does not show a significant change from control.

CCT3 and CCT5 LOF lead to significant decreases in β-tubulin IIA, as CCT LOF does for measures of MT stability (Fig 3A, S2E). Although Akt and Raptor LOF also significantly reduce β-tubulin IIA fluorescence, surprisingly, S6k LOF significantly increases overall levels of β-tubulin IIA compared to WT neurons. Interestingly, Cullin1 also significantly decreases β-tubulin IIA fluorescence (Fig S2F).

We further confirm that TORC1 LOF reduces stable MT levels throughout the dendritic arbor through the use of a fluorescent line marking the MT-associated protein Jupiter (UAS-Jupiter::mCherry) (Das et al., 2017). CCT LOF (1-, 3-, and 5-IR) results in the steepest decline in Jupiter::mCherry signal (Fig 3B–C). Similar to the effects on acetylated α-tubulin and Futsch, loss of Raptor, S6k, and Akt also significantly decrease Jupiter::mCherry signal; however, Akt OE and S6k OE do not significantly alter Jupiter::mCherry signal. Interestingly, Cullin1 knockdown significantly decreases Jupiter::mCherry signal despite also resulting in hyper-arborization (Fig 3B–C). In general, we find that TORC1 inhibition significantly decreases MT signal along the dendritic arbor, and that TORC1 hyperactivation results in varied MT signal along the arbor depending on the measured marker of MT stability.

Mutant Huntingtin expression leads to repeat length-dependent reduction in branch complexity and underlying microtubule losses

Though CCT and TORC1 clearly regulate dendritic arborization during development in homeostatic conditions, there is also great interest in examining the putative relationships of these complexes to proteinopathic disease. Several studies have connected CCT to the regulation of mutant Huntingtin (mHTT) protein, and there is some evidence that loss of wild-type HTT disrupts neuron formation (McKinstry et al., 2014; Barnat et al., 2017). Drosophila melanogaster has been used to model many HD-related phenomena, such as motor deficits, circadian rhythm changes, metabolic precursors of disease, mHTT aggregate spreading in the brain, and more (Krench and Littleton, 2013; Bertrand et al., 2020; Vernizzi et al., 2020; Khyati et al., 2021; Subhan and Siddique, 2021). Using UAS-mediated constructs of mutant Huntingtin (see Supplementary Table S1), we expressed human mHTT in CIV neurons and quantified gross morphology of the resultant dendritic arbors. Shorter repeats of mHTTQ20 and mHTTQ50 do not significantly alter arbor complexity, but expression of mHTTQ93 and mHTTQ120 significantly reduce TDL from WT (Fig S3A–B). We also examined HTT distribution in CIV neurons and identified somatic and dendritic expression (Fig 4A). Consistent with WT HTT expression, induced expression of mHTT120HA and mHTT96Cer show clear expression in soma and dendrites (Fig 4B, S3E). Though mHTT misexpression lines have significantly higher overall HTT expression than WT (Fig S3G), neurons expressing UAS-mHTTQ25-Cerulean do not display apparent puncta (Fig 4B). In contrast, misexpression of UAS-mHTTQ96-Cerulean or UAS-mHTTQ120-HA results in aggregate inclusion bodies (IBs) of mHTT forming in the dendritic arbor (Fig 4B, S3E).

Figure 4: Expression of mHTT leads to dendritic hypotrophy parallel to TORC1 pathway.

Figure 4:

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(A) Representative image of WT HTT staining in CIV neuron – dendrite marked by dashed white lines, axon by solid lines. Scale bar = 3 μm. (B) Representative images of mHTT25-Cerulean and mHTT96-Cerulean shown with aggregate inclusion bodies marked by white arrows for mHTT96-Cerulean. Scale bar = 10 μm. (C) Representative reconstructions of branches from WT and TORC1 genetic manipulations – normalized mCherry::Jupiter fluorescence is coded with the rainbow spectrum shown (A.U.) (D) Heat map representing the average normalized, binned mCherry::Jupiter fluorescence along dendrites at increasing distances from the soma for overexpressions of mHTT 20, 50, and 93 repeats. Genotypes found to be significantly different along the dendritic arbor are marked with an asterisk. (E) Pearson’s correlation Coefficient (r) is near-zero for CCT1 and HTT co-expression in soma cytosol, however, r for CCT1-mHTT120HA is significantly higher than CCT1-WT HTT and HA-stained Gal4 “off” controls. (F) Thresholded Mander’s Coefficient M2 signifying overlap of two signals is significantly higher in CCT1-mHTT120HA conditions than CCT1-WT HTT conditions. (G) TDL of Cullin1-IR and CCT5-IR in both mHTTQ25 and mHTTQ96 backgrounds displayed as percent change from WT control. CCT5-IR decreases both mHTTQ96 and mHTTQ25 neurons to far lower than WT, while Cullin1-IR rescues mHTT96 hypotrophy to WT levels. (H) Representative images of CIV dendritic morphology in combined HTT and CCT5-IR or Cullin1-IR combinations. Scale bars = 100 μm. In all panels * = p < 0.05, see Supplementary Table S2 for detailed statistics.

WT HTT is thought to be involved in cellular trafficking, and there is evidence that mHTT expression can destabilize MTs (Trushina et al., 2003; Subhan and Siddique, 2021). We predicted that there would be underlying cytoskeletal deficits in these neurons similar to the phenotypes we observe in CCT and TORC1 LOF neurons. Expression of mHTTQ96 significantly decreases Futsch fluorescence levels in the soma as measured via IHC (Fig S3C). Live imaging of Jupiter::mCherry, reveals that expression of mHTTQ50 does not significantly reduce stable MT signal, but expression of mHTTQ93 significantly reduces stable MT signal across the arbor (Fig 4C–D) as compared to the non-phenotypic mHTTQ20. Overall, expression of high repeats of mHTT results in dendritic hypotrophy and underlying losses of stable MTs in CIV neurons.

mHTT induction of dendritic hypotrophy may involve CCT and TORC1

A large number of previous studies implicate CCT in direct regulation of mHTT (Tam et al., 2006; Shahmoradian et al., 2013; Sontag et al., 2013; Noormohammadi et al., 2016; Shen et al., 2016; Zhao et al., 2016); therefore, we first sought to answer whether CCT regulates wild-type Huntingtin. We found that CCT5 knockdown led to a significant decrease in soma levels of wild-type Drosophila Huntingtin, as measured through IHC (Fig S3D).

CCT has been shown to reduce aggregation of mutant Huntingtin (mHTT) through physical interaction in vitro (Tam et al., 2006; Shahmoradian et al., 2013), thus we predicted that subunits of CCT would co-localize with HTT and mHTT in the cytosol. To test this prediction, we examined the correlation of expression between CCT1 and HTT, as well as between CCT1 and mHTTQ120-HA (Fig 4E–F, S3E). The use of the temperature-sensitive Gal4 inhibitor, ts-Gal80, allowed us to measure HA and HTT levels in WT neurons and those with mHTTQ120-HA expressed (Gal4 “on”) as well as those with mHTTQ120-HA suppressed (Gal4 “off”) (See Methods for details) (Fig S3E).

Analyses of CIV neuron soma from these genetic backgrounds reveal near-zero Pearson’s correlation Coefficients (PC) between CCT1 and WT HTT as well as between CCT1 and mHTTQ120-HA (Fig 4E). PC is a measurement of the linear relationship between two fluorescent labels in an area of interest that ranges from −1 (perfect exclusion) to 1 (perfect colocalization) (Cordelières and Bolte, 2014). We find a small, but significant increase in the correlation for mHTT120HA from its positive genetic control but no difference between mHTT120HA and WT HTT (Fig 4E). Since PC is sensitive to noise and non-linear relationships between labels, we also analyzed the images using Mander’s correlation Coefficient, with strict predetermined thresholds (see Methods for details). The M2 statistic, which describes the fraction of the CCT1 signal overlapping with HTT, was high in both WT and mHTT conditions (Fig 4F). There was a small, but significant increase in the M2 statistic between WT and mHTT conditions in both soma and dendrites (Fig 4F, S3F). In sum, CCT1 and both WT HTT and mHTT120-HA are clearly present in the cytoplasm of CIV soma and dendrites, and though they display high overlap, we find no linear relationship between the two signals at the current resolution.

As CCT appears to be necessary for WT HTT expression, and the two proteins show high co-expression in the cytoplasm, we predicted that they might operate within the same pathway to regulate dendritic arborization. After knocking down CCT5 in neurons expressing either subclinical mHTTQ25-Cerulean or mHTTQ96-Cerulean, we find the combination does not show potentiation of the two phenotypes. CCT5-IR appears to strongly drive the hypotrophy phenotype in both mHTTQ25 and mHTTQ96 backgrounds (Fig 4G–H).

Previous in vitro evidence suggests that CCT may work to clear mHTT aggregates (Kitamura et al., 2006; Tam et al., 2006; Shahmoradian et al., 2013; Sontag et al., 2013; Sergeeva et al., 2014; Shen et al., 2016), thus we predicted that CCT LOF may lead to higher aggregate load in dendrites in vivo. However, CCT LOF in the UAS-mHTTQ96-Cerulean background does not lead to a significant change in IB number or size (Fig S3H–I). Additionally, CCT5-IR in a mHTT96 background does not potentiate the loss of Futsch signal, which is already significantly reduced in mHTTQ96 neurons (Fig S3C). Though CCT is required for WT HTT expression and shows high co-expression with both WT HTT and mHTT in the cytosol, CCT LOF does not appear to exacerbate IB appearance at the current resolution.

TORC1 activity has also been explored as an avenue for mHTT clearance, mainly through inhibition via the application of rapamycin (Sarkar et al., 2008; Pryor et al., 2014; Lee et al., 2015). Given HTT’s many connections to both CCT and TORC1, we predicted that expression of mHTT may influence dendritic arborization through disruption of the insulin pathway and cytosolic interactors CCT and Cullin1. Interestingly, knockdown of Cullin1 in the mHTTQ96 background increases TDL significantly from mHTT96 alone, returning it to WT levels (Fig 4G–H). Despite rescue of the dendritic hypotrophy, when Cullin1 is knocked down in a UAS-mHTTQ96-Cerulean background, neither the median number, nor aggregate size, of mHTT IBs changes (Fig S3H–I). Overall, though we find that CCT5 is required for WT HTT levels, and that CCT1 and HTT, as well as mHTT, are both co-expressed in the cytoplasm of CIV soma and dendrites, we did not find that CCT LOF and mHTT expression resulted in an additive phenotype. Interestingly, we did find that Cullin1 LOF was sufficient to rescue mHTTQ96-mediated defects in TDL, though it did not significantly affect the appearance of mHTT dendritic IBs.

DISCUSSION

A TORC1 cytosolic network regulates dendritic development and the underlying MT cytoskeleton

The TORC1 pathway has many cytosolic interactors; we have illuminated the roles of two, CCT and Cullin1, in dendritic development. Previous work established that CCT subunits are required for CIV dendritic arbor formation (Das et al., 2017; Wang et al., 2020), and we have confirmed that CCT LOF results in dendritic hypotrophy with underlying stable MT deficits. Though CCT directly folds actin and tubulin monomers, we predicted that its contribution to dendritic arborization may also extend to secondary regulators of the dendritic arbor, such as TORC1. TORC1 has been found to regulate dendritic arbors in mammalian dopaminergic neurons (Diaz-Ruiz et al., 2009; Kosillo et al., 2019, 2022), and was recently found to be regulated by CCT in both Drosophila and human cell cultures (Vinayagram et al., 2016; Cuéllar et al., 2019; Kim and Choi, 2019). We confirmed, in vivo, that CCT is required for WT levels of Raptor and P-S6k in Drosophila CIV neurons. CCT5 knockdown significantly reduces Raptor expression levels and cannot be rescued by Raptor overexpression, indicating that CCT is required for WT levels of Raptor (Fig 2B). Additionally, S6k overexpression could not rescue P-S6k levels in CCT5 knockdown neurons, indicating that CCT is required for WT levels of P-S6k (Fig 2C).

Furthermore, we found TORC1 LOF results in dendritic hypotrophy while TORC1 hyperactivation results in dendritic hypertrophy (Fig 1B–D). The hypotrophy resulting from both LOF of TORC1 and CCT is mirrored by underlying losses of stable MT markers in the soma such as Futsch and acetylated α-tubulin as well as Jupiter::mCherry signal throughout the dendritic arbor (Fig 3A–C). A notable difference is that CCT, Raptor, and Akt LOF significantly reduce β-tubulin IIA signal in the soma, while S6k LOF significantly increases β-tubulin IIA signal (Fig S2E). The β-tubulin IIA antibody used in our experiments is not specific to either free or incorporated β-tubulin IIA, so the production of free β-tubulin IIA could create increased fluorescence even in a cell with reduced stable MTs.

Our gross morphological findings of TORC1 LOF coincide tightly with those of a recent study demonstrating that changes in nutrition result in CIV dendritic hyper-arborization and subsequent changes in cell sensitivity and larval behavior (Kanaoka et al., 2023). Akt, TOR, and S6k were all found to be required for hyper-arborization induced by a low-yeast diet. Levels of phosphorylated Akt were increased in low-yeast diet conditions, and overexpression of Akt increased dendritic complexity. Akt LOF and OE have been established to decrease and increase CIV dendritic coverage, respectively (Parrish et al., 2009). In our work, LOF of Akt and S6k produce dendritic hypotrophy (Fig 1B–D), and while we have found that there are underlying MT deficits in TORC1 LOF conditions (Fig 3A–C), it remains to be seen if the cytoskeletal phenotypes are inducible through diet changes.

Manipulations inducing TORC1 hyperactivity or disinhibition of TORC1 all result in hypertrophy but have variable effects on MT markers. In our experiments, inhibition of TORC1 pathway genes reduces levels of acetylated α-tubulin while TORC1 hyperactivity leads to increases in acetylated α-tubulin by 15–22% (Fig 3A). S6k has previously been found necessary for stress-evoked acetylation of α-tubulin in mouse embryonic fibroblasts (Hać et al., 2021), but the mechanism connecting S6k to tubulin acetylation is still unclear. TORC1 hyperactivation through S6k OE and Akt OE also increases Futsch levels; however, Cullin1-IR-mediated disinhibition of TORC1 does not show the same MT phenotypes despite similar dendritic hypertrophy (Fig 3A–C). Although Cullin1-IR results in a 22% increase in acetylated α-tubulin, it results in a mild decrease in Futsch and a significant decrease in Jupiter signal. It may be that loss of Cullin1 reduces the expression or attachment of MAPs to MTs without affecting underlying MT stability. Together, our data suggest that CCT and Cullin1 partially influence dendritic arborization and development of the neuronal cytoskeleton through regulation of TORC1.

TORC1 cytosolic network and mHTT interact in the regulation of dendritic arbors

Although important to understand the role of TORC1 in homeostatic dendritic development, TORC1 has also been extensively investigated with respect to proteinopathies, including Huntington’s Disease (for recent review see (Querfurth and Lee, 2021)) as has CCT (Tam et al., 2006; Shahmoradian et al., 2013; Sergeeva et al., 2014; Noormohammadi et al., 2016; Shen et al., 2016; Zhao et al., 2016; Chen et al., 2018). Similar to TORC1 and CCT LOF phenotypes, expression of high repeat human mHTT in CIV neurons reduces dendritic complexity and underlying stable MT signal (Fig S3 A–B, 4C–D, G–H). We observed both WT and mutant HTT in multiple neuronal compartments; furthermore, expression of mHTTQ96-Cerulean and mHTTQ120-HA produced large aggregate IBs in dendritic arbors, similar to those previously reported in (Krench and Littleton, 2013) (Fig 4A–B, S3E).

Although CCT appears to be required for WT levels of HTT, we found mixed colocalization results for CCT1 and HTT (Fig 4E–F, S3F). Based on the current level of resolution, we find no linear relationship between CCT1 and HTT signal in the cytoplasm despite a high degree of co-expression in both soma and dendritic compartments (Fig 4E–F, S3F). The correlation between CCT1 and mHTT120HA was significantly higher than the correlation between CCT1 and HTT; however, as all conditions are still far closer to zero than one, we do not assert that there is any meaningful correlation between CCT1 and WT HTT or mHTT120-HA signal within the cytoplasm. Given the differences between the two statistics we examined (PC and Mander’s), it is possible that HTT and CCT1 have a non-linear co-expression relationship in the cytoplasm (e.g. CCT1 signal could increase near mHTT aggregates but not at the rate of mHTT signal increase).

We also carried out genetic interaction studies between CCT and mHTT expression. When combined, CCT5 LOF and mHTTQ96 expression do not display an additive dendritic phenotype: arbor complexity in the mHTT96 background is reduced to the same level as that in neurons with both mHTT25 and CCT5-IR (Fig 4G–H). Furthermore, CCT5-IR did not induce a change in size or number of mHTT dendritic puncta in the mHTTQ96-Cerulean background (Fig S3H–I). This is in contrast with previously published iPSC data, which found LOF of individual CCT subunits triggered aggregation of mHTT (Noormohammadi et al., 2016). CIV neurons form IBs upon expression of high repeat mHTT, whereas iPSCs expressing mHTT require heat or proteostatic stress to induce IB formation, which may explain the discrepancy. There may also be changes in the IBs that are not evident at our current experimental parameters, such as organization of mHTT within the IB, or changes to temporal dynamics of IB formation.

Cullin1, the cytosolic inhibitor of TORC1, does show genetic interaction with mHTT expression: when we knocked down Cullin1 in mHTTQ96 neurons, there was a significant increase in dendritic complexity, restoring TDL to WT levels (Fig 4G–H). Unexpectedly, in this same genetic background, we did not observe any change to dendritic IB size or number (Fig S3H–I). We had predicted Cullin-IR would lead to an increase in IB number or size for two reasons. First, Cullin1, as part of an E3 ubiquitin ligase, helps to ubiquitinate proteins for degradation (Gerez et al., 2019), and Cullin1 LOF has been linked to increased protein aggregate load (Bhutani et al., 2012; Chen et al., 2019). Second, Cullin1-IR leads to TORC1 disinhibition, which reduces autophagic activity (Switon et al., 2017). Previous studies have shown that rapamycin application – inhibition of TORC1 – reduces mHTT aggregation in Drosophila ommatidia and mammalian cells (Ravikumar et al., 2004; Berger et al., 2006), and other studies have shown that inhibition of mTORC1 ameliorates mHTT pathology through increased autophagic activity (Berger et al., 2006; Roscic et al., 2011; Vernizzi et al., 2020; Querfurth and Lee, 2021). However, we find in CIV neurons, Cullin1 knockdown increases dendritic complexity while the dendritic IB load remains unchanged. There is evidence that the SCF complex is down-regulated in Parkinson’s Disease, Huntington’s Disease, and Spinal-Cerebellar Ataxia Type 3, and that further Cullin1 LOF exacerbates aggregate phenotypes (Bhutani et al., 2012; Mandel et al., 2012a, 2012b; Chen et al., 2019). Therefore, it is possible that the role of Cullin1 in suppression of complex dendritic development and its role in promoting degradation of protein aggregates are carried out through distinct cellular pathways. There are undoubtedly several mechanisms by which complexes like TORC1, CCT, and SCF could interact with protein aggregates, providing fertile ground for future studies.

In summary, our study shows that CCT regulates TORC1 in vivo to promote dendritic arborization in homeostatic development. We further demonstrate that Cullin1 inhibits TORC1 in vivo to suppress dendritic arborization. At the cytoskeletal level, TORC1 hypo-activation leads to underlying stable MT deficits, while hyper-activation and disinhibition through Cullin1 knockdown have distinct MT phenotypes. In proteinopathic disease conditions, high repeats of mHTT lead to dendritic hypotrophy, and Cullin1 LOF can rescue mHTT-induced hypotrophy, though neither Cullin1 LOF nor CCT LOF significantly alters mHTT aggregate IB expression. Our data, together with previous literature, demonstrate conserved roles of TORC1, CCT, and Cullin1 in dendritic regulation in healthy and diseased neurons.

Supplementary Material

1

SIGNIFICANCE.

The insulin pathway has become an increasingly attractive target for researchers interested in understanding the intersection of metabolism and brain health. We have found connections between the insulin pathway and cytosolic protein maintenance in the development of neuronal dendrites. These pathways converge on the dendritic cytoskeleton, particularly microtubules. Neurons expressing mutant Huntingtin also show defects in dendritic development and the underlying cytoskeleton, and we find that disinhibition of the insulin pathway can rescue dendritic hypotrophy in these neurons. This work advances our understanding of the molecular interactions between the insulin pathway and neuronal development in both health and Huntington’s Disease conditions.

ACKNOWLEDGEMENTS

This work is supported by NIH R01 NS086082 to DNC. ENL was supported by an NIH F31 NS130970-01, a GSU Brains and Behavior (B&B) Fellowship, a GSU 2CI Neurogenomics Fellowship, and a Kenneth W. and Georganne F. Honeycutt Fellowship. FHC was supported by a GSU 2CI Neurogenomics Fellowship. EAT-W and TT were supported by NIH Maximizing Access to Research Careers (MARC) fellowships (T34 GM131939-01). BT was supported by a GSU B&B summer fellowship. AAP was supported by a GSU 2CI Neurogenomics Fellowship, a Kenneth W. and Georganne F. Honeycutt Fellowship, and a B&B Fellowship. We thank Dr. Kwang-Wook Choi at KAIST, South Korea for the UAS-dCCT4 transgenic line. The authors gratefully acknowledge the Imaging Core Facility at Georgia State University for their support and assistance in this work.

ENL and DNC designed the research. ENL, FHC, SB, and EAT-W performed the research. ENL, FHC, SB, EAT-W, BT, TT, and JM analyzed the data. AAP contributed analytic tools. ENL wrote the manuscript, which was revised by FHC, SB, and DNC. ENL and DNC were responsible for funding acquisition and DNC for project supervision.

Footnotes

CONFLICT OF INTEREST

The authors declare no competing financial interests.

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