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Small-molecule G-quadruplex stabilizers reveal a novel pathway of autophagy regulation in neurons

  1. Jose F Moruno-Manchon
  2. Pauline Lejault
  3. Yaoxuan Wang
  4. Brenna McCauley
  5. Pedram Honarpisheh
  6. Diego A Morales Scheihing
  7. Shivani Singh
  8. Weiwei Dang
  9. Nayun Kim
  10. Akihiko Urayama
  11. Liang Zhu
  12. David Monchaud
  13. Louise D McCullough
  14. Andrey S Tsvetkov  Is a corresponding author
  1. The University of Texas McGovern Medical School at Houston, United States
  2. Institut de Chimie Moléculaire (ICMUB), UBFC Dijon, CNRS UMR6302, France
  3. Baylor College of Medicine, United States
  4. The University of Texas Graduate School of Biomedical Sciences, United States
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Cite this article as: eLife 2020;9:e52283 doi: 10.7554/eLife.52283

Abstract

Guanine-rich DNA sequences can fold into four-stranded G-quadruplex (G4-DNA) structures. G4-DNA regulates replication and transcription, at least in cancer cells. Here, we demonstrate that, in neurons, pharmacologically stabilizing G4-DNA with G4 ligands strongly downregulates the Atg7 gene. Atg7 is a critical gene for the initiation of autophagy that exhibits decreased transcription with aging. Using an in vitro assay, we show that a putative G-quadruplex-forming sequence (PQFS) in the first intron of the Atg7 gene folds into a G4. An antibody specific to G4-DNA and the G4-DNA-binding protein PC4 bind to the Atg7 PQFS. Mice treated with a G4 stabilizer develop memory deficits. Brain samples from aged mice contain G4-DNA structures that are absent in brain samples from young mice. Overexpressing the G4-DNA helicase Pif1 in neurons exposed to the G4 stabilizer improves phenotypes associated with G4-DNA stabilization. Our findings indicate that G4-DNA is a novel pathway for regulating autophagy in neurons.

Introduction

G-quadruplex-DNA (G4-DNA) is a higher-order nucleic acid structure formed by guanine (G)-rich sequences. Co-planar associations of four guanines into G-quartets self-stack to form highly thermodynamically stable G4-DNA complexes, which are further stabilized by potassium cations. These structures are important in DNA replication, telomere maintenance, and regulation of transcription, at least in cancer cells (Rhodes and Lipps, 2015; Maizels and Gray, 2013). Putative G4-DNA forming sequences (PQFSes) are ubiquitous in the human genome: more than 300,000 PQFSes have been identified in silico and more than 700,000 G4-DNA sequences by G4-seq (Chambers et al., 2015). These sequences are frequent in oncogenes and regulatory and homeostatic genes (Eddy and Maizels, 2006; Huppert and Balasubramanian, 2007). Intriguingly, the number of the G4-DNA structures varies between cancerous cell lines, indicating that ‘active’ G4-DNA structures and G4-DNA landscapes might be cell-type dependent (Hänsel-Hertsch et al., 2016).

The importance of G4-DNA in cellular homeostasis has been further supported by the discovery of G4-DNA binding proteins. Various proteins, including G4-DNA unwinding helicases (Sauer and Paeschke, 2017) (e.g., Pif1 Paeschke et al., 2013) and several transcription factors (Lopez et al., 2017; Gao et al., 2015; Kumar et al., 2011), bind to the G4-DNA structures and, therefore, may regulate transcription of specific genes. G4-DNA downregulates gene expression by preventing transcription factor binding to the gene promoter or stalling RNA polymerase. Stabilized G4-DNA must be unfolded for transcription to occur. In contrast, the G4-DNA structures may enhance the expression of certain genes by facilitating transcription factor binding to these genes or their promoters (Bochman et al., 2012; Kumar et al., 2008; Smestad and Maher, 2015) or by keeping the gene ‘open’ and, thus, enabling re-initiation of transcription (Bochman et al., 2012; Smestad and Maher, 2015; Du et al., 2008; David et al., 2016).

Recently, we demonstrated that PQFSes are located in the promoter region of the Brca1 gene and in the Brca1 gene itself and that pharmacologically stabilizing G4-DNA downregulates Brca1 gene and promotes DNA damage in neurons (Moruno-Manchon et al., 2017). However, whether G4-DNA regulates gene expression of other genes in highly transcriptionally active neurons is not known. Additionally, G4-DNA was recently implicated in neurodegenerative disorders, such as frontotemporal dementia and amyotrophic lateral sclerosis (Haeusler et al., 2016). In aged cells, intriguingly, guanines within DNA are often oxidized, and oxidation stabilizes G-quadruplexes (Gros et al., 2007), therefore making these non-canonical structures an attractive research target in neurodegeneration and brain aging research.

Macroautophagy (referred to as autophagy hereafter) is a fundamental cellular process by which cells sequester and degrade proteins, damaged or unwanted organelles, and parasites (Galluzzi et al., 2017). Thus, autophagy is critical for cell survival and maintenance, development, inflammation and immune responses, DNA repair, proteostasis, organelle quality control, and prevention of cellular senescence and aging (Galluzzi et al., 2017). Mice with enhanced basal autophagy exhibit increased healthspan and lifespan (Fernández et al., 2018), but those with defective autophagy develop neurodegenerative disease–like symptoms, indicating that autophagy plays a vital role in neural maintenance and survival (Komatsu et al., 2006). To sequester cytoplasmic content, autophagy involves the use of autophagosomes, double-membrane vesicles, which subsequently fuse to lysosomes for degradation (Galluzzi et al., 2017). Autophagy is orchestrated by the autophagy-related (ATG) evolutionarily conserved genes that nucleate the autophagosomal precursor phagophore and elongate the autophagosome, engulf cytoplasmic cargo, and fuse the autophagosome with the lysosome (Galluzzi et al., 2017). Autophagy is regulated by transcription and translation, as well as by protein post-translational modifications and autophagic proteins’ half-lives (He and Klionsky, 2009; Lubas et al., 2018). A decrease in autophagic activity with aging leads to the accumulation of damaged and senescent cellular components in all cell types of aging organisms (Cuervo, 2008). The expression of many critical autophagic genes, such as Atg5 and Atg7, decreases with aging (Lipinski et al., 2010; Lu et al., 2004), which can also be epigenetically regulated, at least in part (Lapierre et al., 2015; Füllgrabe et al., 2014). Intriguingly, G4 ligands stimulate autophagy in cancer cells (Beauvarlet et al., 2019; Orlotti et al., 2012; Zhou et al., 2009). Whether G4-DNA structures can regulate autophagy in neurons or are altered with aging is not known.

ATG7, an E1-like enzyme, critical for the initiation of autophagy, couples LC3-I to the E2-like enzyme ATG3 leading to the E3-like complex of ATG16L1/ATG5-ATG12 to conjugate LC3-I to phosphatidylethanolamine in phagophore membranes (Galluzzi et al., 2017). Mice deficient in genes involved in the ATG conjugation system, including Atg7, die within 1 day after birth because autophagy is strongly upregulated immediately after birth as an adaptation mechanism (Kuma et al., 2017). Models of neurodegeneration, such as alpha-synucleinopathy and brain samples from patients with Lewy Body disease, show that ATG7 is downregulated, reflecting reduced and defective autophagy, and endogenously raising ATG7 by a lentiviral delivery decreases the levels of alpha-synuclein and mitigates neurodegeneration (Crews et al., 2010). Atg7-deficient neurons in the midbrain of conditional Atg7 knock-out mice degenerate and are accompanied by the formation of ubiquitinated inclusion bodies (Friedman et al., 2012). Importantly, the expression of Atg7 goes down in the human brain during normal aging (Lipinski et al., 2010). It is not clear what mechanisms regulate Atg7 expression.

In this study, we investigated whether G4-DNA regulates neuronal autophagy. We discovered that stabilizing G4-DNA with two distinct G4-DNA-binding ligands, pyridostatin (PDS) and BRACO19, downregulates the ATG7 protein, lowers Atg7 mRNA, and inhibits autophagy in cultured primary neurons. We also found that, in an in vitro gel-shift assay, an antibody specific to the G4-DNA binds to a synthetic oligonucleotide, which corresponds to a G4-forming sequence in the first intron of the Atg7 gene. The G4-DNA-binding protein PC4 also binds to this oligonucleotide from the Atg7 gene. We discovered that mice treated with PDS exhibit memory deficits and accumulate lipofuscin, a hallmark of aged brains. Brain samples from aged mice contained G4-DNA structures that are not present in brain samples from young mice. In cultured primary neurons exposed to PDS, overexpressing the G4-DNA helicase Pif1, a G4-DNA helicase that unwinds the G-quadruplex structures even in the presence of G4-DNA-binding drugs (Zhou et al., 2014), improves autophagic phenotypes induced by PDS treatment. Our findings suggest that the G4-DNA structures might be an important pathway during brain aging and neurodegeneration.

Results

Autophagic genes contain PQFSes

We hypothesized that many autophagy genes can be regulated by G4-DNA. First, we investigated whether the ATG genes contain putative G4-DNA motifs. We used the QGRS mapper (http://bioinformatics.ramapo.edu/QGRS/index.php) to identify the PQFSes in these genes (mouse, rat and human). Analyses revealed that all these genes contain PQFSes, suggesting that G4-DNA may be involved in the regulation of their expression (Figure 1).

PQFS in the gene and the promoter sequence of autophagy genes.

The number of PQFS in the listed genes and their promoter were analyzed by using the QGRS mapper (http://bioinformatics.ramapo.edu/QGRS/index.php). * 5000 nucleotides upstream the gene were considered as the promoter sequence; ** Data not available.

PDS and BRACO19 downregulate Atg7 in neurons

ATG7 is important for autophagosome biogenesis (Galluzzi et al., 2017). The rat Atg7 gene contains 27 putative sequences that can arrange into G4-DNA. There are no PQFSes in the Atg7 gene promoter (upstream, 5 kb) (Figure 2a). We first determined if PDS alters Atg7’s mRNA levels in primary cultured neurons (Figure 2b). After PDS treatment, mRNA was extracted and analyzed by qRT-PCR. We found that the levels of Atg7’s mRNA were sevenfold lower in neurons exposed to the G4 ligand than in neurons treated with a vehicle. Tbp (TATA-binding protein) mRNA was used as loading control as neither Tbp nor its promoter contains a PQFS (Moruno-Manchon et al., 2017). We next tested if the levels of the ATG7 protein are changed in neuronal cells treated with PDS. Cultured neurons were treated with PDS, and cellular extracts were analyzed by western blotting. The levels of the ATG7 protein in PDS-treated neurons were half those of control neurons (Figure 2c,d). We confirmed these findings with another well-established G4 ligand, BRACO-19 (Haider et al., 2011). Similarly, BRACO-19 reduced the levels of Atg7 mRNA and ATG7 by twofold in neurons (Figure 2e,f,g).

PDS downregulates ATG7 levels in primary neurons.

(a) A scheme of the rat Atg7 gene and its promoter showing putative G4-DNA locations. (b–d) Cultured primary neurons were treated with a vehicle (control, cont) or with PDS (2 μM) overnight. Neurons were collected and processed to measure mRNA (b) and levels of ATG7 (c,d). (b) Expression levels of Atg7 and Tbp (housekeeping protein as control) were determined by qRT-PCR. ***p(Atg7)=0.0001 (t-test). n.s., non-significant, p(Tbp)=0.426. Results were pooled from three independent experiments. (c) The protein levels of ATG7 were determined by western blotting. Actin was used as a loading control. (d) Quantification of ATG7 protein levels normalized to actin from (c). ***p=0.0001 (t-test). Results were pooled from four independent experiments. (e–g) Cultured primary neurons were treated with a vehicle (control, cont) or with BRACO19 (2 μM) overnight. Neurons were collected and processed to measure mRNA (e) and levels of ATG7 (f,g). (e) The expression of Atg7 and Tbp was determined by qRT-PCR. ***p(Atg7)=0.0001 (t-test). n.s., non-significant, p(Tbp)=0.662. Results were pooled from three independent experiments. (f) Levels of ATG7 were determined by western blotting. Actin was used as a loading control. (g) Quantification of ATG7 protein was normalized to actin from (f). ***p=0.0001 (t-test). Results were pooled from four independent experiments.

A PQFS in the Atg7 gene folds into a G4 motif in vitro and in vivo

G4-DNA sequences have been extensively studied in vitro. We examined whether the sequence discovered in the Atg7 gene folds into a G4 structure in vitro. We first identified a 32-nt sequence with the highest QGRS score (G-score = 67; see Materials and methods) in the Atg7 gene (Figure 3a). Whether this sequence, named Atg7-32 (d[5’G3GCTGG3TC3T2GG3A2CTGTAT2G33’]), is able to fold into a G4 structure (Figure 3b) was investigated by circular dichroism (CD) and thermal difference spectra (TDS) (Mergny et al., 2005). CD and TDS signatures clearly indicated that Atg7-32 indeed folds into a mixture of different topological quadruplex structures (Figure 3c,d). These signatures were expected in view of the nature of the intervening sequences between the guanine-runs (from 2-nt to 9-nt loops), which might also form duplex stems. The variety of the Atg7-32 G4-DNA structures can be reduced by dehydrating conditions with PEG200 and CH3CN (Buscaglia et al., 2013), leading to the typical CD (negative at 242 nm and positive at 264 nm) and TDS (positive at 273 nm and negative at 296 nm) signatures of a G4-DNA structure (Figure 3c,d). Similar experiments were performed with a modified Atg7-32 sequence (named mutAtg7-32) that cannot fold into a G4-DNA structures because of seven G-to-C replacements (underlined) within the four G-runs of the Atg7-32 sequence (d[5′GCGCCTGCGCTC3T2GCGCA2CTGTAT2GCG3′]). We found that mutAtg7-32 display signatures typical of a GC-rich duplex (CD signals at 255 (negative) and 285 nm (positive); TDS signals at 240 and 276 nm), thus confirming the G4 topological unicity of Atg7-32 (Figure 3c,d). We further investigated the higher-order structure of both Atg7-32 and mutAtg7-32 by nuclear magnetic resonance (NMR). Both displayed 1H-NMR signals in the 12–14 ppm region, which corresponds to duplex stems (providing a rationale for the complicated CD/TDS signature of the former), but only Atg7-32 had 1H-NMR signals in the 10–12 ppm region, characteristic of a G4-DNA structure (poorly defined here, demonstrating a mixture of G4 topologies) (Figure 3e). These signals indicate that Atg7-32 may fold into a variety of G4-DNA topologies, including both 3- and 4-G-quartet G4s with both short (2-nt) and long (9-nt) hairpin-forming loops (Figure 3b), which were also detected earlier in non-neuronal cells (Chambers et al., 2015; Puig Lombardi et al., 2019) or computationally predicted (Bedrat et al., 2016; Puig Lombardi and Londoño-Vallejo, 2020). An equilibrium among all these various topologies is illustrated by the complex signatures generated with CD, TDS and NMR.

A PQFS in the Atg7 gene folds into a G4 structure in vitro.

(a) Scheme of the rat Atg7 gene and its promoter showing the sequence of the Atg7-32 and ATG2700 oligonucleotides that corresponds to a putative G4-forming sequence. (b) Scheme of the G-rich sequence under its unfolded (left) and folded structures (G4-DNA, right); guanines are shown as gray squares, with detailed chemical structures of guanine (left) and G-quartets (right). Atg7-32 may fold into multiple conformations that include both 3- and 4-G-quartet G4s with both short (2-nt) and long (9-nt) hairpin-forming loops. An equilibrium between all these various topologies is illustrated by the complex signatures generated with CD, TDS and NMR (see c–e). (c) Circular dichroism (CD) generated from 3 μM Atg7-32 (plain lines) and mutAtg7-32 (dotted lines) in 10 mM lithium cacodylate buffer plus 10 mM KCl and 90 mM LiCl (Caco.K10) in absence (black lines) or presence dehydrating agent (PEG200, 20% v/v, brown line, or acetonitrile, 50% v/v, red plain line and gray dotted line for Atg7-32 and mutAtg7-32, respectively). (d) Thermal difference spectra (TDS) generated from 3 μM Atg7-32 (plain lines) and mutAtg7-32 (dotted lines) in Caco.K10 in absence (black lines) or presence of acetonitrile (50% v/v, red plain line and gray dotted line for Atg7-32 and mutAtg7-32, respectively). (e) Nuclear magnetic resonance (NMR) of 200 μM Atg7-32 (upper panel) and mutAtg7-32 (lower panel) in Caco.K10. (f) Chemical structures of PDS and BRACO19. (g–h) FRET-melting curves (g) and results (h) for experiments performed with 0.2 μM fam-Atg7-32-tamra (g,h) and fam-mutAtg7-32-tamra (h) in absence (black line) or presence of increasing concentrations of PDS (0.2–1.0 μM, blue lines), (g,h) and BRACO19 (h) in CacoK.10.

We next investigated whether and how PDS and BRACO-19 (Figure 3f) interact with Atg7-32 and mutAtg7-32 in vitro. We found that both ligands strongly stabilize the Atg7-32 G4 structure against thermal denaturation (via a FRET-melting assay, using doubly labeled Atg7-32 and mutAtg7-32 sequences, see Methods), delaying melting by 22°C and 14°C for PDS and BRACO-19, respectively, while interacting only moderately with the mutAtg7-32 hairpin structure, delaying its melting by 3°C and 4°C only for PDS and BRACO-19, respectively (Figure 3g,h). Overall, these data confirm that Atg7-32 folds into a G4-DNA structure in vitro that can be stabilized by G4-ligands.

A longer version of the Atg7-32 motif, with 6-nt extensions on both its 5′- and 3′-ends, named ATG2700 (d[5′AT2CT2G3GCTGG3TC3T2GG3A2CTGTAT2G3TGA2C23′]), was used to assess whether it can be recognized by the G4-specific antibody HF2 (Figure 4a). We synthesized both Cy5-labeled ATG2700 and SS-DNA, a control that cannot fold into a G4 structure. The HF2 antibody was incubated with ATG2700 and SS-DNA in buffers with either K+, which favors G4, or Li+, which prevents G4 formation (Figure 4a,b). We found that HF2 interacts with ATG2700 only in K+-rich conditions (Figure 4a), without binding to the control SS-DNA. Our data thus indicate that the PQFS identified in the Atg7 gene indeed adopts a G4 structure in vitro. These findings were further confirmed with a well-established G4-binding protein, PC4. Yeast PC4 (Sub1) and human PC4 (hPC4) were overexpressed in yeast and lysates were incubated with ATG2700 and SS-DNA, immobilized on beads. Yeast and human PC4 only interact with ATG2700 (Figure 4c,d), further demonstrating the G4 nature of the Atg7’s G4.

Figure 4 with 1 supplement see all
The HF2 antibody and PC4 bind to the ATG2700 oligonucleotide in vitro, and the N-TASQ probe detects G4-DNA in vivo.

(a–b) Cy5-conjugated ATG2700 and SS-DNA (a negative control) oligonucleotides were heat-denatured and then slow-cooled in the presence of K+ (KCl) or Li+ (LiCl) to allow the formation of a secondary structure. 1.5 pmoles of each oligonucleotides (oligo) and 0 (a buffer alone), 10 or 20 ng of the HF2 antibody were incubated in a buffer, which contained 100 mM KCl (a) or 100 mM LiCl (b). Note in (a) that the bands at the top of the gel correspond to the ATG2700 oligonucleotide bound to the HF2 antibody in samples incubated with a buffer containing KCl. However, note in (b) that the gel lacks of bands at the top. (c–d) Yeast were transformed with a DNA construct that express yeast Sub1-FLAG (c) or with a DNA construct that express human PC4-HIS (d). Yeast were collected and lysed, and extracts were incubated with ATG2700 or SS-DNA (negative control) oligonucleotides. Immunoprecipitates were immobilized with agarose beads, and protein complexes were then run in a gel and analyzed by western blotting with antibodies against FLAG (c) or antibodies against HIS (d). (e) Cultured primary neurons were treated with a vehicle (control, cont) or with PDS (2 μM) overnight. Cells were fixed and stained with N-TASQ (50 μM), with antibodies against MAP2c, and with the nuclear dye Hoechst (DAPI). White arrows depict N-TASQ-positive puncta. Scale bar, 10 µm (f) N-TASQ fluorescence intensities were analyzed from (e). ***p(cont vs PDS)=0.0001 (t-test). For each experiment, 200 neurons were analyzed, and results were pooled from three independent experiments.

Finally, to confirm that the G4s can be detected in vivo, cultured primary neurons were treated with a vehicle or PDS or BRACO19 and then stained with N-TASQ, a G4-DNA-selective fluorophore that has been used to gauge the changes in a G4 landscape in cancer cells treated with G4 ligands (Laguerre et al., 2015; Laguerre et al., 2016; Yang et al., 2017). We discovered that PDS- and BRCAO19-treated neurons exhibit higher levels of N-TASQ fluorescence than control cells (Figure 4e,f, and Figure 4—figure supplement 1). These data indicate that G4 ligands modulate a G4 landscape in cultured primary neurons, suggesting a mechanism of how G4 stabilization downregulates Atg7.

PDS inhibits neuronal autophagy

To confirm that autophagy is downregulated by PDS, we measured autophagic flux in live neurons. We used an optical pulse-chase labeling method based on the photoswitchable protein Dendra2 and longitudinal imaging (Tsvetkov et al., 2013a; Barmada et al., 2014; Tsvetkov et al., 2013b). Brief irradiation with short wavelength visible light (‘photoswitch’) irreversibly changes the conformation of ‘green’ Dendra2 and its fluorescence to the ‘red’ form (Figure 5a). The Dendra2-based optical pulse-chase labeling has been applied to study autophagic flux (Barmada et al., 2014; Moruno Manchon et al., 2015), protein degradation (e.g., wild-type and mutant huntingtin) (Tsvetkov et al., 2013b), the dynamics and turnover of synaptic proteins (Wang et al., 2009), and mitochondrial dynamics (Pham et al., 2012). Cultured cortical neurons were transfected with Dendra2-LC3 (LC3 is a marker of autophagy Klionsky et al., 2016; Mizushima et al., 2010), photoswitched, treated with PDS or vehicle, and followed with an automated microscope for several days. The red fluorescence intensities from individual cells were measured at different time points. Decay of the red fluorescence were plotted against time, transformed into log values; the half-lives from individual neurons were analyzed and normalized. Expectedly, the half-life of Dendra2-LC3 (e.g., the decay of photoswitched ‘red’ Dendra2 signal) was prolonged by PDS by 1.7-fold, indicating slowed flux through autophagy (Figure 5b). Beclin1 (Zhong et al., 2009), a constitutive protein within the pre-autophagosomal complex used as a positive control, reduced the Dendra2-LC3 half-life by twofold, indicating that the flux through autophagy was increased, as expected (Figure 5b).

Figure 5 with 3 supplements see all
PDS inhibits autophagy in cultured primary neurons.

(a) The photoswitchable protein Dendra2 is commonly used to measure the half-life of a protein of interest. A brief irradiation with short-wavelength visible light induces an irreversible conformational change (‘photoswitch’, indicated by a blue arrow) in Dendra2. Photoswitched Dendra2 emits red fluorescence that can be tracked overtime with an automated microscope. Scale bar, 10 µm. (b) Dendra2 was fused to LC3, an autophagy marker, to measure autophagy flux. Two cohorts of primary neurons were co-transfected with Dendra2-LC3 and an empty plasmid, or with Dendra2-LC3 and untagged beclin1 (Becn1, as a positive control). Neurons co-transfected with Dendra2-LC3 and an empty plasmid were treated with a vehicle (control, cont), or with 0.1 µM PDS overnight. After treatment, neurons were longitudinally imaged, and the decay of the red fluorescence over time was used to calculate the half-life of Dendra2-LC3. The half-life of Dendra2-LC3 is normalized to one with respect to control neurons. *p(cont vs Becn1)=0.02, **p(cont vs PDS)=0.001, **p(Becn1 vs PDS)=0.001 (one-way ANOVA). One hundred neurons per group were analyzed from two independent experiments. (c) Cultured primary neurons were treated with a vehicle or with PDS (2 µM), in combination with the autophagy enhancer 10-NCP (NCP, 1 µM) overnight. Neurons were collected, and pellets were lysed and analyzed by western blotting with antibodies against LC3-II and against actin. (d) Quantification of LC3-II levels normalized to actin from (c). **p(cont vs NCP+PDS)=0.008, ***p(cont vs NCP)=0.0001, ***p(NCP vs NCP+PDS)=0.0002 (one-way ANOVA). Results were pooled from four independent experiments. (e) Dendra2 was fused to Httex1-Q46, an autophagy substrate, to measure autophagy flux. Two cohorts of primary neurons were transfected with Dendra2- Httex1-Q46. 24 hr after transfection, neurons were treated with a vehicle (control, cont), or with PDS (0.1 µM), and longitudinally imaged. The decay of the red fluorescence over time was used to calculate the half-life of Dendra2- Httex1-Q46. The half-life of Dendra2- Httex1-Q46 is normalized to one with respect to control neurons. **p(cont vs PDS)=0.0064 (t-test). Fifty neurons per group were analyzed from two independent experiments. (f) Fluorescence images of a neuron co-transfected with the DNA constructs TagBFP and mito-Keima. Keima is a fluorescent pH-sensitive protein used as a reporter of subcellular acidic environments. Keima emits green fluorescence in neutral environments, and emits red light in acidic environments, such as lysosomes or autolysosomes. Targeting Keima to mitochondria has been used to study a specific form of autophagy, mitophagy. Note that a white arrow depicts mitochondria in acidic compartment (red channel). (g) Two cohorts of primary neurons were transfected with mito-Keima. 24 hr after transfection, neurons were treated with a vehicle (control, cont) or with 0.1 µM PDS, and imaged 48 hr after treatment. Quantification of red fluorescence intensity of mito-Keima indicates that mitophagy is reduced in PDS-treated neurons. ***p(cont vs PDS)=0.0001, (t-test). One hundred neurons per group were analyzed from three independent experiments.

We previously discovered a series of small molecules that induce autophagy in primary neurons (Tsvetkov et al., 2010). Among them, the benzoxazine derivative 10-NCP promotes neuronal autophagy and protects neurons from misfolded proteins (Moruno Manchon et al., 2015; Tsvetkov et al., 2010; Moruno-Manchon et al., 2018). This compound enhances the formation of autophagosomes and stimulates the lipidation of LC3-I to LC3-II, reflecting enhanced autophagy (Tsvetkov et al., 2010; Moruno-Manchon et al., 2018). We, therefore, wondered if G4 ligands could reduce and/or prevent 10-NCP-induced lipidation of LC3-I. Primary cortical neurons were treated with PDS, with or without 10-NCP (Figure 5c,d). We discovered that PDS completely prevented 10-NCP-mediated formation of LC3-II. In addition, we used BRACO19 alone or in combination with 10-NCP to confirm if lipidation of LC3-II is also inhibited in neurons by an alternative G4 ligand (Figure 5—figure supplement 1a,b). BRACO19 reduced the LC3-II levels by 0.8-fold, leading to the conclusion that the initial stages of autophagy are inhibited by G4 ligand treatment, which likely arise from downregulated levels of ATG7, at least in part.

10-NCP, as an autophagy enhancer, regulates the degradation of mutant huntingtin (mHtt) (Tsvetkov et al., 2010) in neurons, the protein that causes Huntington’s disease. To confirm that PDS modulates autophagic substrates, we transfected neurons with the exon-1 fragment of polyQ-expanded mHtt (mHttex1) tagged with Dendra2 and treated them with PDS or vehicle. Importantly, we confirmed that neither the plasmid promoter (pGW1 Arrasate et al., 2004) nor the mHttex1 contain putative G4s with QGRS mapper analyses. We found that the half-life of mHttex1-Dendra2 was increased in neurons exposed to PDS by 1.4-fold (Figure 5e). We then used the BACHD mouse model to confirm that PDS affects the degradation of an autophagy substrate, mHtt. BACHD mice express the full-length human mHtt gene and recapitulate multiple features of Huntington disease (Gray et al., 2008). We cultured primary cortical neurons from BACHD mouse pups and treated them with a vehicle or PDS. mHtt levels were measured with western blotting. As expected, PDS treatment increased the levels of mHtt by twofold, indicating that degradation of mHtt is inhibited (Figure 5—figure supplement 2a,b). Actin was used as a loading control, as we previously found that the levels of the actin protein in neurons are not significantly affected by PDS (Moruno-Manchon et al., 2017).

Next, we assessed whether G4 ligands regulate a specific form of autophagy, mitophagy, the autophagic degradation of mitochondria that depends on ATG7 (Vincow et al., 2013). To measure mitophagy in live neurons, we used an optical method that combines a pH-sensitive protein Keima with automated imaging. Keima is a fluorescent protein that changes both its excitation and emission spectra in response to environmental pH changes, emitting green light at neutral pH and red light at acidic pH. Mitochondrially targeted Keima has been successfully used to study mitophagy (Katayama et al., 2011; Proikas-Cezanne and Codogno, 2011). Primary cortical neurons were transfected with mito-Keima and BFP, treated with a vehicle, PDS or BRACO19, and the red fluorescence intensity of mito-Keima was analyzed in individual neurons (Figure 5f,g and Figure 5—figure supplement 1c). Similar to previous studies (Cai et al., 2012), we found that basal mitophagy is a relatively slow process, with first mitochondria appearing in the lysosomes ~ 2 days after mito-Keima transfection, and that mitophagy is primarily localized to the neuronal soma (Figure 5f,g). In neurons treated with PDS, mitophagy efficiency was reduced by 0.6-fold compared to neurons treated with a vehicle (Figure 5g). Interestingly, the BRACO19 treatment reduced mitophagy by 0.8-fold, indicating that PDS and BRACO19 affect neuronal homeostasis differently. Thus, we conclude that, in primary cultured neurons, G4 stabilization downregulates autophagy, including mitophagy.

Finally, we wondered whether ectopic expression of ATG7 mitigates neurotoxicity and autophagy deficits induced by PDS. p62 or sequestosome-1 is a scaffolding protein that acts as an adaptor to identify and deliver cargo to the autophagosome for degradation (Liu et al., 2017; Katsuragi et al., 2015). p62 is degraded together with the cargo, making p62 a commonly used autophagy marker. Two cohorts of cultured neurons were transfected with p62-GFP and mApple. The third neuronal cohort was transfected with p62-GFP and ATG7-mApple. mApple-expressing neurons were treated with a vehicle (control) or with PDS, neurons transfected with p62-GFP, and ATG7-mApple were treated with PDS (PDS+ATG7). We analyzed fluorescence intensity of p62-GFP and discovered that PDS-treated mApple-expressing neurons exhibited a 1.7-fold increase of p62-GFP fluorescence intensity over control neurons. Interestingly, ATG7-overexpressing neurons treated with PDS displayed 0.7-fold reduction of p62-GFP fluorescence intensity, indicating that overexpressing ATG7 mitigates the inhibitory effects of PDS on neuronal autophagy (Figure 5—figure supplement 3a,b). Similarly, ATG7 overexpression mitigates PDS-induced neurotoxicity (Figure 5—figure supplement 3c). These data further highlight the importance of ATG7 in neuronal autophagy and survival.

Mice treated with PDS develop memory deficits

We then wondered if PDS would have any effect on the brain in mice. Stabilizers of G4-DNA are being investigated as an anti-cancer therapy. In a prior in vivo study, a G4-binding small molecule (MM41) was used as an anti-cancer therapy with a dosage and schedule that was tolerated (Ohnmacht et al., 2015). In our studies, we used a comparable dosage and schedule of PDS. In these experiments, we used old male and female mice (25 months). Mice were randomized and injected weekly with a vehicle or PDS for 8 weeks (4 mg/kg/week), and thereafter, these mice completed the novel object recognition (NOR) test, a standard test for recognition memory that assesses both hippocampal and cortical cognitive function (Antunes and Biala, 2012). The discrimination index measures the ability of the tested animal to differentiate a novel object from the familiar object, which was previously presented to the animal. Thus, higher discrimination index indicates if the animal is able to recognize the novel object. Male and female mice treated with PDS exhibited a reduced discrimination index, compared to vehicle-treated mice (Figure 6a). These were old mice and even vehicle-treated mice were expected to exhibit significant age-associated neuropathology. We analyzed one of the hallmarks of aging and downregulated autophagy—the levels of lipofuscin—in male and female mice. Lipofuscin is a mixture of accumulated oxidized proteins and lipids found in aged brains (Brunk and Terman, 2002). Brains from PDS-treated mice contained more lipofuscin than vehicle-treated mice (Figure 6b,c), demonstrating that the treatment with PDS promotes aging phenotypes in the mouse brains. Our data also suggest that anticancer drugs that target G4-DNA may accelerate brain aging and lead to early dementia.

Mice treated with PDS develop memory deficits and aged-related symptoms.

(a) 25-month-old male and female mice were intraperitoneally injected with a solution of a vehicle in PBS (control, cont) or with a solution of PDS in PBS (5 mg/kg, PDS) once a week for 8 weeks. After treatment, mice were tested for short-term memory in the novel object recognition test and discrimination index (DI) was calculated. *p-value(male-cont vs PDS)=0.0265, *p-value(female-cont vs PDS)=0.0382, p-value(male vs female)=0.1029 (two-way ANOVA). Six mice per group were analyzed. (b) Mice were sacrificed, and their brains were analyzed for the lipofuscin autofluorescent age pigment. (c) Quantification of autofluorescence from (c). **p-value(male-cont vs PDS)=0.0043, ***p-value(female-cont vs PDS)=0.0007, p-value(male vs female)=0.2121 (two-way ANOVA). Six mice per group were analyzed.

Brain samples from old mice contain stable G4-DNA

Transcription of many genes is altered in the aged brain (Lu et al., 2004), and many of these gene bodies or promoters contain PQFSes. For example, expression of Atg7 decreases in the human brain during normal aging (Lipinski et al., 2010). In yeast, flies, worms, and human immune and cancer cells, histone and chromatin modifications regulate Atg7 expression (Settembre et al., 2011; Eisenberg et al., 2009; Eisenberg et al., 2014). We first analyzed the mRNA levels of Atg7 in young and aged mice and observed that Atg7 mRNA is downregulated by 25% in the aged brains compared to brain samples from young mice (Figure 7a). Second, we hypothesized that aged brains contain stable G4-DNA. To test that, we used the BG4 antibody, which recognizes G4 structures in fixed cytological samples (Biffi et al., 2013). Young (3 months old) and old (25 months old) mice were sacrificed, and their brains were analyzed by immunohistochemistry with the BG4 antibody. BG4-positive puncta were seen in aged mice and were very rarely seen in young mice (Figure 7b,c). These data suggest that the G4 landscape is modulated by aging in vivo, which opens new avenues for aging research.

Brain samples from aged mice exhibit elevated levels of G4-DNA.

3-month-old (young) and 25-month-old (old) mice were sacrificed, and their brains were processed for RT-qPCR and immunohistochemistry analysis. (a) Cortical brain samples from young and old mice were lysed, and mRNA was extracted. mRNA samples were retro-transcribed and analyzed for expression of the Atg7 gene. **p(young vs old)=0.0011 (t-test). Six mice per group were analyzed. (b) Brain samples from young and old mice were stained with antibodies against BG4 (green channel) and the Hoechst dye (nuclei marker, blue channel), and imaged with a fluorescent microscope. In the zoomed image, white arrows depict some G-quadruplex-positive structures in the nuclei. (c) Quantification of BG4 fluorescence intensity in the hippocampus (hip) and the cortex (cort) of young and old mice. ***p(hip-young vs old)=0.0001; ***p(cor-young vs old)=0.0001. n.s., non-significant, p(young-hip vs cor)=0.35 (one-way ANOVA). Six mice per group were analyzed.

Pif1 rescues PDS-induced phenotypes in cultured primary neurons

More than 20 G4 helicases unwind G4-DNA, among which Pif1 is one of the most potent and studied (Paeschke et al., 2013). Pif1 unwinds G4 structures even in the presence of G4 ligands (Zhou et al., 2014). Thus, we wondered whether Pif1 could rescue PDS-induced phenotypes in cultured primary neurons. Primary neurons were transfected either with GFP and mApple (a marker of viability and morphology) or with Pif1-GFP and mApple (Figure 8a–d). Loss of the mApple fluorescence is a sensitive marker of neuronal death (Tsvetkov et al., 2013a; Tsvetkov et al., 2010; Arrasate and Finkbeiner, 2005). Therefore, by analyzing when each neuron lost its fluorescence, we can measure neuronal survival with cumulative hazard statistics (Figure 8e). Transfected neurons were tracked longitudinally for several days. Surprisingly, Pif1-GFP was somewhat toxic for primary cortical neurons, in comparison with control GFP-expressing neurons (Figure 8e). Nevertheless, Pif1-GFP partially rescued PDS-associated neurotoxicity. Next, we tested if Pif1-GFP rescues autophagic deficits in cultured neurons exposed to PDS. Remarkably, Pif1-GFP reduced the half-life of Dendra2-LC3 by 0.6-fold in neurons treated with PDS (Figure 8f). We then used a mutant form of Pif1 without ATPase/helicase activity as a control. Expectedly, mutant Pif1 could not rescue PDS-associated autophagy reduction (Figure 8f). These data indicate that Pif1 likely activates coping mechanisms in degenerating neurons, leading to better autophagy.

The helicase Pif1 restores autophagy in PDS-treated neurons.

(a) An example of survival analysis. Cultured primary neurons were transfected with the red fluorescent protein mApple as a marker of cell morphology and viability. Neurons were longitudinally imaged each 24 hr for 6 days with an automated microscope. Each image is a montage of 25 individual non-overlapping images. Scale bar is 400 µm. (b) Zoomed images from (a) at each time point. Images demonstrate the ability to track the same group of neurons over time, and they show the progression of neuron development (note how neurites grow in the top-left neuron), and neurodegeneration (two neurons to the right side of the images gradually lose their neurites until they die). Scale bar is 40 µm. (c) Zoomed image that shows the complex neurite arborization of a depicted neuron from (b) 144 hr after transfection. Scale bar is 20 µm. (d) An example of a neuron co-transfected with mApple (red) and Pif1-GFP (green). Note that Pif1-GFP is mostly nuclear. (e) Two cohorts of cultured primary neurons were co-transfected with mApple (as a morphology and survival marker) and GFP (as a control construct), and other two cohorts of neurons were co-transfected with mApple and Pif1-GFP. One cohort of neurons co-transfected with mApple and GFP was treated with a vehicle (Apple), and the second one with 0.5 μM PDS. Another cohort of neurons co-transfected with mApple and Pif1-GFP was treated with a vehicle (Pif1), and the second one with 0.5 μM PDS (Pif1+PDS). Neurons were longitudinally imaged during 4 days, and risks of death were analyzed. ***p=0.0001 (log-rank test). Results were pooled from three independent experiments. (f) Two cohorts of cultured primary neurons were co-transfected with Dendra2-LC3 and GFP (as a control construct), and other two cohorts of neurons were co-transfected with Dendra2-LC3 and Pif1-GFP. One cohort of neurons co-transfected with Dendra2-LC3 and GFP was treated with a vehicle (control, cont), and the second one with 0.1 μM PDS (PDS). Also, one cohort of neurons co-transfected with mApple and Pif1-GFP was treated with a vehicle (Pif1), and the second one with 0.1 μM PDS (Pif1+PDS). One last cohort of neurons was transfected with mApple and mutant Pif1-GFP and treated with PDS (mPif1+PDS). Neurons were longitudinally imaged, and the half-life of Dendra2-LC3 of each group was analyzed, and normalized to one with respect to the control group. **p(cont vs PDS)=0.001, **p(PDS vs Pif1+PDS)=0.001, p(Pif1 vs Pif1+PDS)=0.001. n.s., non-significant, p(cont vs Pif1)=0.1726, p(cont vs Pif1+PDS)=0.3239, p(PDS vs mPif+PDS)=0.4267 (one-way ANOVA). One hundred neurons per group were analyzed from two independent experiments.

Discussion

In this study, we demonstrated that the levels of Atg7 and, therefore, neuronal autophagy are downregulated by the G4-ligands PDS and BRACO19. We showed that a PQFS identified in the Atg7 gene can fold into a G4 structure, as demonstrated by spectroscopy (CD, TDS and NMR), which interacts with PDS and BRACO-19, the HF2 antibody, and the G4-binding protein PC4. Mice treated with PDS exhibited memory deficits and accumulation of lipofuscin. Importantly, we discovered that aged mouse brains contain numerous G4-DNA, while young brains have very few. Our data suggest that an age-associated change in DNA conformation could be a novel epigenetic-like mechanism of gene expression in aging neurons (Kim, 2019).

There is a good consensus in the autophagy field that autophagy plays a positive role in slowing aging and increasing longevity (Hansen et al., 2018). Autophagy-related genes are critical for longer healthspan and lifespan extension in worms, flies, and mice (Hansen et al., 2018). Mice with enhanced basal autophagy have increased healthspan and lifespan (Fernández et al., 2018). A decrease in autophagic activity leads to the accumulation of damaged and senescent cellular components in almost all cell types of aging organisms (Cuervo, 2008). Transcription factors, such as TFEB and FOXO, regulate the expression of many autophagy genes involved in the healthspan and lifespan (Lapierre et al., 2015). We previously demonstrated that transcription factors Nrf2 and TFEB positively regulate neuronal autophagy and promote basal neuronal survival and survival of neurons under stress (Tsvetkov et al., 2013b; Moruno-Manchon et al., 2016). Epigenetic histone and chromatin modifications also regulate autophagy during aging (Lapierre et al., 2015; Baek and Kim, 2017). For example, autophagy genes can be epigenetically silenced (Baek and Kim, 2017; Artal-Martinez de Narvajas et al., 2013). Conversely, pharmacologic inhibition or genetic downregulation of histone methyltransferase G9a leads to the activation of autophagy in cancer cells and in fibroblasts (Artal-Martinez de Narvajas et al., 2013). The expression of many critical autophagic genes, such as Atg5 and Atg7, decreases with aging (Lipinski et al., 2010; Lu et al., 2004). Many of these genes contain PQFS motifs in their introns, exons or promoters. Our findings indicate that G4-DNA may play crucial roles in transcription of autophagic genes in aged neurons.

A link between G4-DNA ligands and autophagy has already been demonstrated in cancer cells. Мelanoma cells stop dividing and upregulate autophagy when treated with the G4 ligand Ant1,5 (Orlotti et al., 2012). In agreement with this study, a G4 agent, SYUIQ-5, inhibits proliferation, damages G4-DNA enriched telomeres, and upregulates autophagy in CNE2 and HeLa cancer cells (Zhou et al., 2009). The G4 ligand 20A causes cell growth arrest and upregulates autophagy in HeLa cells (Beauvarlet et al., 2019). In our work, however, we found that, in neurons, G4-ligands trigger opposite effects, downregulating autophagy in post-mitotic neurons, which comes with no surprise as the autophagic pathways in neurons differ from those in other cell types (Kulkarni et al., 2018).

G4-DNA-associated regulation of transcription extends well beyond the autophagy genes. We recently demonstrated that PDS and BRACO19 downregulate the Brca1 gene in cultured primary neurons—the Brca1 gene and gene’s promoter contain G4-DNA motifs—leading to DNA damage (Moruno-Manchon et al., 2017). Ectopically increasing BRCA1 levels attenuates DNA damage associated with PDS treatment, indicating that Brca1 downregulation impedes DNA damage repair and DNA double strand breaks accumulate as a result. Age-dependent accumulation of stabilized G4-DNA structures in diverse genes may lead to neuronal senescence and, eventually, to neurodegeneration. In some neurodegenerative diseases and in advanced aging, neurons exhibit various DNA/chromatin abnormalities, including aneuploidy and transposable element dysregulation (Mosch et al., 2007; Fischer et al., 2012; Sun et al., 2018). Our findings suggest that age-dependent changes in DNA conformation and accumulation of G4-DNA could represent a novel mechanism of senescence that includes the autophagic and non-autophagic genes in general. Future studies will determine the exact G4-DNA loci in neurons, how these loci differ between neuronal cell types (e.g., cortical versus granular cerebellar), and how these loci change as neurons develop and age.

G4-DNA structures fold spontaneously within single-stranded DNA (ssDNA) transiently formed during DNA replication, and helicases (including Pif1) unfold them (Rhodes and Lipps, 2015). A similar process occurs during transcription on ssDNA in a transcriptional bubble, and Pif1 dismantles these G4-DNA structures as well (Rhodes and Lipps, 2015). G4-RNA structures being mostly protein bound form only transiently in living cells (Fay et al., 2017; Yang et al., 2018). Post-mitotic neurons do not divide, and so, G4 ligands may have a strong effect on co-transcriptionally formed G4-DNA and G4-RNA. In our current and previous studies (Moruno-Manchon et al., 2017), we observed no significant accumulation of mRNA (Atg7 and Brca1 Moruno-Manchon et al., 2017) in PDS-treated neurons (e.g., G4-RNA), suggesting that mRNA stability is not considerably affected by G4 ligands. Therefore, in post-mitotic neurons, the primary target of G4-ligands would likely be transcription. Nevertheless, we cannot exclude a possibility that PDS may affect RNA metabolism by stabilizing G4-RNA. Intriguingly, we found that PDS downregulates Atg7 stronger than BRACO19, indicating that these two ligands have different affinities towards the G4 structures in living neurons or/and bind to different G4-DNA conformations. As neurons are highly specialized cells, they may have their own, unique G4-DNA pathways, which may be drastically different from G4-DNA mechanisms in non-neuronal cells.

Pif1 is a class of nuclear and mitochondrial 5'−3' DNA helicases present in all eukaryotes (Mendoza et al., 2016). Originally identified in yeast as an important factor for maintaining mitochondrial DNA (Lahaye et al., 1991), Pif1’s functions now include the regulation of telomere length, replication, and resolving G4-DNA (Byrd and Raney, 2017). Among G4-DNA helicases, Pif1 is one of the most potent and can unwind G4-DNA stabilized by G4-DNA-interacting small molecules (Paeschke et al., 2013; Zhou et al., 2014). We demonstrate that Pif1 rescues phenotypes associated with PDS treatment. Intriguingly, expression of Pif1 itself somewhat upregulates autophagy. Therefore, in addition to histone acetyltransferases facilitating chromatin decondensation and promoting the expression of autophagy-related genes (Lapierre et al., 2015; Baek and Kim, 2017), Pif1 may also help to sterically allow the transcriptional machinery to transcribe DNA, including autophagic and non-autophagic genes. Nevertheless, we cannot fully exclude a possibility that Pif1 is protective in our experiments with PDS due to unknown functions besides being a G4-DNA helicase. Intriguingly, prior in vitro studies found that Pif1’s G4-DNA unwinding activity is diminished by G4 ligands (e.g., PDS), which appears to contradict to our in vivo findings. Nevertheless, the relevance of these data to our study is not straightforward since a G4-DNA forming sequence was used without its complementary sequence in the in vitro studies. Adding the complementary DNA sequence unfolds the G4-DNA/ligand complexes (Mendoza et al., 2016). In addition, the in vitro experiments assayed the activity of Pif1 using an excess of G4 ligands (Mendoza et al., 2016), and therefore, the data are not easy to extrapolate to our neuronal in vivo model. Also, in our studies with living neurons, Pif1 was overexpressed before PDS was added to the media, and thus, the kinetics of Pif1-G4-DNA-PDS interactions may be overly complex for a direct comparison to the in vitro conditions.

Our findings have important ramifications for aging and neurodegeneration research. We and others previously demonstrated that neuronal autophagy can be targeted therapeutically to mitigate or potentially stop neuronal aging and neurodegeneration. In this study, we demonstrate that there is a novel layer of autophagy regulation – G4-DNA. Our data suggest that G4-DNA and G4-DNA-regulating proteins might be promising therapeutic targets for developing therapies against age-associated neurodegenerative disorders.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional
information
Gene (Rattus norvegicus)ATG7N/AGene-NCBI: ID: NC_005103.4
Strain, strain background (Mus musculus)C57BL/6Jackson Laboratoy664female and male
Strain, strain background (Rattus norvegicus)Long EvansCharles River6N/A
Cell line (Rattus norvegicus)primary cortical neuronsNeurons isolated from Long-Evans rat embryos (E17–18) cortices
Antibodyanti-microubule-associated protein 1 light chain three alpha (LC3; rabbit polyclonal)MBL#PD014(1:1000), overnight 4°C
Antibodyanti-atg7 (clone D12B11; rabbit monoclonal)Cell Signaling#8558(1:1000), overnight 4°C
Antibodyanti-beta actin (clone 8H10D10; mouse monoclonal)Cell Signaling#3700(1:2000), overnight 4°C
Antibodyanti-DYKDDDDK Tag (FLAG; clone D6W5B; rabbit polyclonal)Cell Signaling#2368(1:500), overnight 4°C
Antibodyanti-microtubule-associated protein-2 (MAP-2; clone A-4; mouse monoclonal)Santa Cruz Biotechnology#sc-74421(1:500), overnight 4°C
Antibodyanti-rabbit-HRPEMD Millipore#AP307P(1:2000), overnight 4°C
Antibodyanti-mouse-HRPEMD Millipore#AP308P(1:2000), overnight 4°C
Antibodyanti-mouse Alexa Fluor-488Life Technologies#A11001(1:500), overnight 4°C
Antibodyanti-Huntingtin protein (Htt; clone mEM48; mouse monoclonal)EMD Millipore#MAB5374(1:1000), overnight 4°C
Antibodyanti-rabbit Alexa Fluor-546Life Technologies#A11010(1:500), overnight 4°C
Antibodyanti-HF2(Lopez et al., 2017)(1:100), overnight 4°C, prepared in Nayun Kim’s lab
Antibodyanti-BG4 (Biffi et al., 2013)(1:100), overnight 4°C, prepared in Nayun Kim’s lab
Recombinant DNA reagentlipofectamine 2000Thermo Fisher Scientific12566014
Recombinant DNA reagentpCAG-TagBFPVectorBuilderpRP[Exp]-CAG > TagBFP
Recombinant DNA reagentpCAG-EGFP-hPIF1VectorBuilderpRP[Exp]-CAG > EGFP(ns): hPIF1[ORF026999]
Recombinant DNA reagentpCAG-EGFP-mutant hPIF1VectorBuilderpRP[Exp]-CAG > EGFP(ns):{hPIF1[ORF026999]*(E307Q)}
Recombinant DNA reagentEF1A-mApple-ATG7VectorBuilderpRFP[Exp]-EF1A > mApple(ns):mAtg7[NM_001253717.1]
Recombinant DNA reagentpSANG10-3F-BG4Addgene#55756; deposited by Dr. Shankar Balasubramanian, the University of Cambridge
Recombinant DNA reagentpGW1-Dendra2-LC3(Tsvetkov et al., 2013b)
Recombinant DNA reagentHttex1-Q46-Dendra2(Tsvetkov et al., 2013b)
Recombinant DNA reagentpGW1-mito-KeimaotherIt was cloned from the mt-mKeima/pIND(SP1) construct that we kindly received from Dr. Atsushi Miyawaki (RIKEN Brain Science Institute, Japan)
Sequence-based reagentATG7, forwardLone Star laboratories5’-TCCTGAGAGCATCCCTCTAATC-3’
Sequence-based reagentATG7, reverseLone Star laboratories5’- CTTCAGTTCGACACAGGTCATC-3’
Sequence-based reagentTBP, forwardLone Star laboratories5’-AGTGCCCAGCATCACTGTTT-3’
Sequence-based reagentTBP, reverseLone Star laboratories5’-GGTCCATGACTCTCACTTTCTT-3’
Sequence-based reagentATG2700Dr. Monchaud lab.ATTCTTGGGGCTGGGGTCCCT TGGGGAACTGTATTGGGTGAACC
Sequence-based reagentSS-DNADr. Monchaud lab.GCACGCGTATCTTTTTGGCGCAGGTG
Commercial assay or kitRNeasy Mini kitQiagen74104
Commercial assay or kitiScript Reverse Transcription SuperMixBioRad1708840
Chemical compound, drugPyridostatin (PDS)Cayman Chemical18013
Chemical
compound, drug
10-(4′-(N-diethylamino)butyl)−2-chlorophenoxazine (10-NCP)EMD Millipore925681–41
Chemical compound, drugN-TASQ (Laguerre et al., 2015; Laguerre et al., 2016)synthesized by Dr. David Monchaud
Software, algorithmJMP softwareSAS Institute, Houston, TX
OtherHoechst dyeSanta Cruz Biotechnologysc-394039
Otherpoly-D-lysineMilliporeA-003-E
OtherNeurobasal MediumLife Technologies21103–049
OtherB-27Life Technologies17504–044
OtherGlutaMAXLife Technologies35050–061
Otherpenicillin-streptomycinLife Technologies15240.062
OtherHisPur Ni-NTA resinThermo Scientific88221
OtherDynabeadsThermoFisher Scientific10002D

Chemicals and plasmids

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PDS was from Cayman Chemical (#18013). 10-NCP (10-(4′-(N-diethylamino)butyl)−2-chlorophenoxazine) was from EMD Millipore ((#925681–41). Hoechst dye was from Santa Cruz Biotechnology (#sc-394039). N-TASQ was synthesized as described (Laguerre et al., 2015; Laguerre et al., 2016; Yang et al., 2017). Antibodies against LC3 were from MBL (#PD014). Antibodies against ATG7 (D12B11; #8558), β-actin (8H10D10; #3700), and the Anti-FLAG DYKDDDDK M2 tag (D6W5B; #2368) were from Cell Signaling. Mouse antibodies against MAP2c (A-4, #sc-74421) were from Santa Cruz Biotechnology. Antibodies against Htt (mEM48), rabbit IgG(H+L) conjugated with horseradish peroxidase (HRP) (#AP307P), and mouse IgG(H+L) conjugated with HRP (#AP308P) were from EMD Millipore. Anti-mouse Alexa Fluor 488-labeled (#A11001) and anti-rabbit Alexa Fluor 546-labeled (#A11010) secondary antibodies were from Life Technologies. A single-chain BG4 antibody that recognizes G4 structures (Biffi et al., 2013) was purified in the lab of Dr. Nayun Kim. pGW1-Dendra2-LC3 was described (Tsvetkov et al., 2013b). pGW1-mito-Keima was cloned from the mt-mKeima/pIND(SP1) construct that was received from Dr. Atsushi Miyawaki (RIKEN Brain Science Institute, Japan). pCAG-TagBFP, pCAG-EGFP-PIF1, pCAG-EGFP-mPIF1 (E307Q George et al., 2009), and pEF1A-mApple-ATG7 were cloned by VectorBuilder.

Cell cultures and transfection

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Cortices from rat embryos (E17–18) were dissected, dissociated, and plated on 24-well tissue-culture plates (4 × 105/well) coated with poly-D-lysine (BD Biosciences, San Jose, CA), as described (Moruno-Manchon et al., 2017; Moruno Manchon et al., 2015; Moruno-Manchon et al., 2018). Primary cortical neurons were grown in Neurobasal Medium (Life Technologies, Carlsbad, CA) supplemented with B-27 (Life Technologies), GlutaMAX (Life Technologies) and penicillin-streptomycin (Life Technologies). Primary cultures were transfected with Lipofectamine2000 (Thermo Fisher Scientific) and a total of 1–2 μg of plasmid DNA per well, as described (Moruno-Manchon et al., 2017; Moruno Manchon et al., 2015; Moruno-Manchon et al., 2018).

Survival analysis

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We used automated microscopy and longitudinal analysis to determine neuronal survival. This method allows us to track large cellular cohorts and to sensitively measure their survival with the statistical analyses used in clinical medicine (Moruno Manchon et al., 2015; Tsvetkov et al., 2010; Arrasate and Finkbeiner, 2005). For tracking the same group of cells over time, an image of the fiduciary field on the plate was collected at the first time-point and used as a reference image. Each time the same plate was imaged, the fiduciary image was aligned with the reference image. Neurons that died during the imaging interval were assigned a survival time. These events were transformed into log values and plotted in risk of death curves and analyzed for statistical significance (log-rank test). JMP software (SAS Institute, Houston, TX) was used to analyze data and generate survival curves (Tsvetkov et al., 2013a; Tsvetkov et al., 2013b).

Optical pulse-chase

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Photoswitching of Dendra2-LC3 and Httex1-Q46-Dendra2 was performed as described (Barmada et al., 2014; Tsvetkov et al., 2013b; Moruno Manchon et al., 2015). Upon brief irradiation with short-wave visible light, Dendra2 undergoes an irreversible conformational change (‘photoswitch’). The spectral properties of Dendra2 then change from that of a protein that absorbs blue light and emits green fluorescence to that of one that absorbs green light and emits red fluorescence (Barmada et al., 2014). Photoswitched Dendra2 maintains these spectral properties until the cell degrades the protein. The red fluorescence intensities from a region of interest in individual cells were measured at different time points. Fluorescence of non-photoswitched ‘green’ molecules served as a guide for drawing the region of interest. The decays of red fluorescence were plotted against time, transformed into log values, and individual half-life (t1/2) was analyzed (Barmada et al., 2014; Tsvetkov et al., 2013b). The half-lives (H1/2) of Dendra2-LC3 was calculated using the formula: H1/2 = (24xLn(2))/(Ln(A/A°). A = final fluorescence; A°=initial fluorescence.

Immunoblotting

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Neuronal cultures were lysed in RIPA buffer (150 mM NaCl, 1% Nonidet P40, 0.5% sodium deoxycholate, 0.1% SDS and 50 mM Tris/HCl (pH 8.0), with phosphatase and protease inhibitors cocktail) on ice. Lysates were vortexed and cleared by centrifugation (14000 g, 10 min, 4°C). Supernatants were collected, and protein concentrations were determined by the Bicinchoninic Acid Protein Assay Kit (Thermo Scientific). Samples were analyzed by SDS/PAGE (4–12% gradient gels), and proteins were transferred on to nitrocellulose membranes using the iBlot2 system (Life Technologies). Membranes were blocked with 5% skimmed milk for 1 hr at room temperature, and they were incubated with the primary antibodies (anti-LC3, Htt, anti-actin or anti-ATG7) overnight at 4°C. Membranes were then washed with TBS (Tris-buffered saline; 10 mM Tris/HCl and 150 mM NaCl (pH 7.4)) and incubated with anti-rabbit-HRP or anti-mouse-HRP for 1 hr at room temperature. Chemiluminescent signal was visualized with Prometheus ProSignal Pico (Genesee Scientific) on Blue Devil autoradiography films (Genesee Scientific).

G4-DNA analyses

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The QGRS mapper (http://bioinformatics.ramapo.edu/QGRS/index.php) was used to determine the potential G4-DNA structures contained in genes of interest and their G-scores. Search parameters: maximal length: 45; minimal G-group size: 3; loop size: from 0 to 102.

RNA extraction and qRT-PCR

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Total RNA was extracted from primary culture using the RNeasy Mini kit (#74104, Qiagen), and then reverse transcribed using iScript Reverse Transcription SuperMix (#1708840, Bio-Rad), according to the manufacturer’s protocol and as described (Moruno-Manchon et al., 2017). RT-qPCR was performed using a Bio-Rad CFX96 Touch machine using SSoAdvanced Universal SYBR Green (#1725275, Bio-Rad) for visualization and quantification according to the manufacturer’s instructions. Primer sequences were: ATG7 (Atg7), forward: 5′-TCCTGAGAGCATCCCTCTAATC-3′, reverse: 5′- CTTCAGTTCGACACAGGTCATC-3′; TBP (Tbp), forward: 5′-AGTGCCCAGCATCACTGTTT-3′, reverse: 5′-GGTCCATGACTCTCACTTTCTT-3′. The PCR conditions were: 95°C for 3 min, followed by 40 cycles of 95°C for 10 s and 55°C for 30 s. Relative expression levels were calculated from the average threshold cycle number using the delta-delta Ct method.

Oligonucleotides

The sequences of oligonucleotides used herein were: Atg7-32, 5′-GGGGCTGGGGTCCCTTGGGGAACTGTATTGGG-3′; mutAtg7-32, 5′-GCGCCTGCGCTCCCTTGCGCAACTGTATTGCG-3′; fam-Atg7-32-tamra, 5′-fam-GGGGCTGGGGTCCCTTGGGGAACTGTATTGGG-tamra-3′; fam-mutAtg7-32-tamra: 5′-fam-GCGCCTGCGCTCCCTTGCGCAACTGTATTGCG-tamra-3′. The lyophilized DNA strands purchased from Eurogentec (Seraing, Belgium) were firstly diluted at 500 µM in deionized water (18.2 MΩ.cm resistivity). DNA samples were prepared in a Caco.K10 buffer, composed of 10 mM lithium cacodylate buffer (pH 7.2) plus 10 mM KCl/90 mM LiCl. Samples were prepared by mixing 40 µL of the constitutive strand (500 µM) with 8 µL of a lithium cacodylate buffer solution (100 mM, pH 7.2), plus 8 µL of a KCl/LiCl solution (100 mM/900 mM) and 24 µL of water. The actual concentration of each sample was determined through a dilution to 1 µM theoretical concentration via a UV spectral analysis at 260 nm (after 5 min at 90°C) with the following molar extinction coefficient (ε) values: 302000 (Atg7-32), 276500 (mutAtg7-32), 355300 (fam-Atg7-32-tamra) and 329800 l.mol−1.cm−1 (fam-mutAtg7-32-tamra). The G4 structures were folded heating the solutions at 90°C for 5 min, and then cooling them on ice (for 7 hr) before being stored overnight at 4°C.

CD and TDS experiments

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CD and UV-Vis spectra were recorded on the JASCO J-815 spectropolarimeter and the JASCO V630Bio spectrophotometer, respectively, in a 10 mm path-length quartz semi-micro cuvette (Starna). CD spectra of 3 μM of Atg7-32 and mutAtg7-32 (Eurogentec) were recorded over a range of 220–340 nm (bandwidth = 1 nm, 1 nm data pitch, 1 s response, scan speed = 500 nm.min−1, averaged over five scans) without and with dehydrating agent (PEG200, 20% v/v; acetonitrile, 50% v/v) in 600 μL (final volume) of in 10 mM lithium cacodylate buffer (pH 7.2) plus 10 mM KCl and 90 mM LiCl (Caco.K10). Final data were treated with OriginPro8, zeroing CD spectra at 340 nm. TDS experiments were performed with Atg7-32 and mutAtg7-32 (3 μM) recording the optical over a range of 220–340 nm at 20°C and 80°C in 600 μL (final volume) of Caco.K10. Final data were treated with Excel (Microsoft Corp.) and OriginPro9.1 (OriginLab Corp.). TDS signature were calculated subtracting the spectra collected at 20°C from the spectra collected at 80°C, normalized (0 to 1) and zeroed at 340 nm.

FRET-melting experiments

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Experiments were performed in a 96-well format using a Mx3005P qPCR machine (Agilent) equipped with FAM filters (λex = 492 nm; λem = 516 nm) in 100 μL (final volume) of Caco.K10 with 0.2 μM of Fam-Atg7-32-Tamra or Fam-mutAtg7-32-Tamra (Eurogentec) with 0, 1, 2 and 5 molar equivalents of PDS and BRACO-19 (i.e., 0, 0.2, 0.4 and 1.0 μM ligand). After a first equilibration step (25°C, 30 s), a stepwise increase of 1°C every 30 s for 65 cycles to reach 90°C was performed, and measurements were made after each cycle. Final data were analyzed with Excel (Microsoft Corp.) and OriginPro9.1 (OriginLab Corp.). The emission of FAM was normalized (0 to 1), and T1/2 was defined as the temperature for which the normalized emission is 0.5; ΔT1/2 values, calculated as follows: ΔT1/2 = [T1/2(DNA+ligand)-(T1/2(DNA alone)], and are means of three experiments.

NMR experiments

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Atg7-32 and mutAtg7-32 (Eurogentec) were annealed at 200 μM in a Caco.K10 by heating at 95°C for 10 min. The samples were cooled to 4°C (ice bath) and equilibrated at 4°C for at least 24 hr. 1H-NMR spectra (250 μL final volume) were acquired after the addition of DSS (4,4-dimethyl-4-silapentane-1-sulfonic acid) as internal calibration standard. NMR spectra were recorded at 298 K (4248 scans) using a 600 MHz Bruker Avance III HD spectrometer equipped with a cryogenic probe. Water suppression was achieved using excitation sculpting (pulse program: zgesgp). Final data were analyzed with TopSpin v4.0.6 (Bruker).

HF2 binding assay

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HF2 antibody expression and purification were carried out as described (Fernando et al., 2008). The expression of the HF2 single–chain antibody was then induced by 100 mM isopropyl β-D-1-thiogalactopyranosid in E. coli. Cells were pelleted and resuspended in a lysis buffer (25 mM Tris-HCl, 100 mM NaCl, 10% glycerol, 1% NP-40 and 10 mM imidazole) and sonicated using the QSONICA sonicator. Purification of the 6XHis-tagged HF2 antibody was carried out using HisPur Ni-NTA resin according to the manufacturer’s instruction (Thermo Scientific). The eluted protein was concentrated with the Amicon Ultra-4 Centrifugal Filter and stored at −20°C in 50% glycerol. For the binding assay, 5′- Cy5-labeled oligonucleotides (Sigma) were resuspended in 10 mM Tris-Cl containing 100 mM LiCl or KCl and denatured at 95°C for 5 min and then slowly cooled overnight to allow secondary structure formation. Annealed oligonucleotides were mixed with the purified HF2 antibody in 100 mM LiCl or KCl, 20 mM HEPES pH 7.5, 0.01% NP40, 5% glycerol, 5 mM MgCl2, and incubated at room temperature for 15 min before running on a 10% non-denaturing TBE-polyacrylamide gel with 0.5X TBE. Gel images were captured using the BioRad Chemidoc imager. Sequences of the oligonucleotides were:

  • ATG2700, ATTCTTGGGGCTGGGGTCCCTTGGGGAACTGTATTGGGTGAACC

  • SS-DNA, GCACGCGTATCTTTTTGGCGCAGGTG

DNA-dynabeads affinity purification of proteins

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DNA-Dynabeads affinity purification of proteins was carried out as described (Gao et al., 2015) with several modifications. For DNA-conjugated Dynabeads preparation, biotinylated oligonucleotides ATG-2700 and SS-DNA were ordered from Sigma. The oligonucleotides were incubated at 60°C overnight in the presence of 10 mM Tris pH 7.5 and 100 mM KCl and then conjugated to Streptavidin-Coupled M-280 Dynabeads (Life Technologies) as per the manufacturer’s instructions. Yeast extract was made by glass bead-mediated cell disruption in 2 ml of lysis buffer (50 mM HEPES–NaOH, pH 7.5, 300 mM KCl, 1 mM EDTA, 10% glycerol, 0.05% NP-40, 1 mM DTT, 1 mM PMSF, 1X protease inhibitor cocktail (Roche)). After mechanical lysis of cells with Biospec Mini-bead-beater, the cell lysate was collected in a 15 ml tube and sonicated. DNA-conjugated Dynabeads were washed once with the lysis buffer and incubated overnight with gentle inversion with the remaining yeast extract at 4°C. The beads were washed with the lysis buffer five times and then eluted by boiling in 1XSDS-PAGE loading buffer followed by immunoblotting analysis with the anti-FLAG (Sigma; # A8592) or anti-His (Sigma; # H1029) antibodies.

Fluorescence microscopy

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Live cell and fixed cell imaging was performed with the EVOS FL Auto Imaging System (Thermo Fisher Scientific). Lipofuscin was measured in the brain samples acquired from the aged female and male mice treated with a vehicle or with PDS (5 mg/kg). Brain samples were mounted on the glass slides and stained with the nuclear Hoechst dye. Samples were then imaged using the green GFP filter for autofluorescent lipofuscin and the blue DAPI filter with the EVOS microscopy system.

Immunocytochemistry

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Cultured primary cortical neurons on coverslips were treated with a vehicle or with PDS overnight, fixed with 4% paraformaldehyde, permeabilized with a 0.5% Triton X-100/PBS solution, and blocked with a 5% bovine serum albumin/PBS solution. Neurons were then stained with antibodies against MAP2c and with the G4-selective fluorophore N-TASQ overnight. Neurons were incubated with secondary antibodies, stained with Hoechst dye, and imaged with the EVOS microscopy system.

Immunohistochemistry

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To determine and analyze G4 quadruples in brain samples from young and aged mice, frozen floating brain sections were incubated with antibodies against G4 (BG4) overnight. Samples were then incubated with antibodies against FLAG for 1 hr at room temperature, and then with secondary antibodies conjugated with a fluorochrome for 1 hr at room temperature. Nuclei were stained with Hoechst dye. Brain sections were mounted on glass slides, and imaged with a Leica DM8i SPE confocal microscope or the EVOS microscope.

Novel object recognition test (NORT)

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The test is a standard test for recognition memory that is sensitive to aging. For this test, we used old male and female mice (25 months). During the test, two identical objects were presented to each mouse in an arena, and the mice allowed to explore the objects for 10 min. The objects and their position in the arena will be pseudo-randomized between the different mice. After 1 hr interval, one of these objects was replaced with a novel object; again, the mouse was allowed to explore the objects for 10 min. We video recorded the behavior of mice and evaluated the differences in the exploration time with novel and familiar objects. The discrimination index (DI) was calculated as: DI=(TN*100)/(TN+TF). TN is the time mouse spent exploring the novel object. TF is the time mouse spent exploring the familiar object. All test were performed by an investigator blinded to treatment group.

Statistical analysis

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For longitudinal survival analysis, neurons that died during the imaging interval were assigned a survival time (the period between transfection and their disappearance from an image). These event times were used to generate exponential cumulative survival curves in JMP statistical software. Survival curves describe the risk of death for single cells in the group being longitudinally imaged. To determine differences in the survival curves, they were then analyzed for statistical significance by the log-rank test as described (Moruno-Manchon et al., 2017; Moruno Manchon et al., 2015; Moruno-Manchon et al., 2018). To compare differences across two groups, the groups were analyzed with Student’s t-test. Differences across multiple groups were analyzed with one-way ANOVA.

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    574. G Fabrias
    575. C Fabrizi
    576. A Facchiano
    577. NJ Færgeman
    578. A Faggioni
    579. WD Fairlie
    580. C Fan
    581. D Fan
    582. J Fan
    583. S Fang
    584. M Fanto
    585. A Fanzani
    586. T Farkas
    587. M Faure
    588. FB Favier
    589. H Fearnhead
    590. M Federici
    591. E Fei
    592. TC Felizardo
    593. H Feng
    594. Y Feng
    595. Y Feng
    596. TA Ferguson
    597. ÁF Fernández
    598. MG Fernandez-Barrena
    599. JC Fernandez-Checa
    600. A Fernández-López
    601. ME Fernandez-Zapico
    602. O Feron
    603. E Ferraro
    604. CV Ferreira-Halder
    605. L Fesus
    606. R Feuer
    607. FC Fiesel
    608. EC Filippi-Chiela
    609. G Filomeni
    610. GM Fimia
    611. JH Fingert
    612. S Finkbeiner
    613. T Finkel
    614. F Fiorito
    615. PB Fisher
    616. M Flajolet
    617. F Flamigni
    618. O Florey
    619. S Florio
    620. RA Floto
    621. M Folini
    622. C Follo
    623. EA Fon
    624. F Fornai
    625. F Fortunato
    626. A Fraldi
    627. R Franco
    628. A Francois
    629. A François
    630. LB Frankel
    631. ID Fraser
    632. N Frey
    633. DG Freyssenet
    634. C Frezza
    635. SL Friedman
    636. DE Frigo
    637. D Fu
    638. JM Fuentes
    639. J Fueyo
    640. Y Fujitani
    641. Y Fujiwara
    642. M Fujiya
    643. M Fukuda
    644. S Fulda
    645. C Fusco
    646. B Gabryel
    647. M Gaestel
    648. P Gailly
    649. M Gajewska
    650. S Galadari
    651. G Galili
    652. I Galindo
    653. MF Galindo
    654. G Galliciotti
    655. L Galluzzi
    656. L Galluzzi
    657. V Galy
    658. N Gammoh
    659. S Gandy
    660. AK Ganesan
    661. S Ganesan
    662. IG Ganley
    663. M Gannagé
    664. FB Gao
    665. F Gao
    666. JX Gao
    667. L García Nannig
    668. E García Véscovi
    669. M Garcia-Macía
    670. C Garcia-Ruiz
    671. AD Garg
    672. PK Garg
    673. R Gargini
    674. NC Gassen
    675. D Gatica
    676. E Gatti
    677. J Gavard
    678. E Gavathiotis
    679. L Ge
    680. P Ge
    681. S Ge
    682. PW Gean
    683. V Gelmetti
    684. AA Genazzani
    685. J Geng
    686. P Genschik
    687. L Gerner
    688. JE Gestwicki
    689. DA Gewirtz
    690. S Ghavami
    691. E Ghigo
    692. D Ghosh
    693. AM Giammarioli
    694. F Giampieri
    695. C Giampietri
    696. A Giatromanolaki
    697. DJ Gibbings
    698. L Gibellini
    699. SB Gibson
    700. V Ginet
    701. A Giordano
    702. F Giorgini
    703. E Giovannetti
    704. SE Girardin
    705. S Gispert
    706. S Giuliano
    707. CL Gladson
    708. A Glavic
    709. M Gleave
    710. N Godefroy
    711. RM Gogal
    712. K Gokulan
    713. GH Goldman
    714. D Goletti
    715. MS Goligorsky
    716. AV Gomes
    717. LC Gomes
    718. H Gomez
    719. C Gomez-Manzano
    720. R Gómez-Sánchez
    721. DA Gonçalves
    722. E Goncu
    723. Q Gong
    724. C Gongora
    725. CB Gonzalez
    726. P Gonzalez-Alegre
    727. P Gonzalez-Cabo
    728. RA González-Polo
    729. IS Goping
    730. C Gorbea
    731. NV Gorbunov
    732. DR Goring
    733. AM Gorman
    734. SM Gorski
    735. S Goruppi
    736. S Goto-Yamada
    737. C Gotor
    738. RA Gottlieb
    739. I Gozes
    740. D Gozuacik
    741. Y Graba
    742. M Graef
    743. GE Granato
    744. GD Grant
    745. S Grant
    746. GL Gravina
    747. DR Green
    748. A Greenhough
    749. MT Greenwood
    750. B Grimaldi
    751. F Gros
    752. C Grose
    753. JF Groulx
    754. F Gruber
    755. P Grumati
    756. T Grune
    757. JL Guan
    758. KL Guan
    759. B Guerra
    760. C Guillen
    761. K Gulshan
    762. J Gunst
    763. C Guo
    764. L Guo
    765. M Guo
    766. W Guo
    767. XG Guo
    768. AA Gust
    769. ÅB Gustafsson
    770. E Gutierrez
    771. MG Gutierrez
    772. HS Gwak
    773. A Haas
    774. JE Haber
    775. S Hadano
    776. M Hagedorn
    777. DR Hahn
    778. AJ Halayko
    779. A Hamacher-Brady
    780. K Hamada
    781. A Hamai
    782. A Hamann
    783. M Hamasaki
    784. I Hamer
    785. Q Hamid
    786. EM Hammond
    787. F Han
    788. W Han
    789. JT Handa
    790. JA Hanover
    791. M Hansen
    792. M Harada
    793. L Harhaji-Trajkovic
    794. JW Harper
    795. AH Harrath
    796. AL Harris
    797. J Harris
    798. U Hasler
    799. P Hasselblatt
    800. K Hasui
    801. RG Hawley
    802. TS Hawley
    803. C He
    804. CY He
    805. F He
    806. G He
    807. RR He
    808. XH He
    809. YW He
    810. YY He
    811. JK Heath
    812. MJ Hébert
    813. RA Heinzen
    814. GV Helgason
    815. M Hensel
    816. EP Henske
    817. C Her
    818. PK Herman
    819. A Hernández
    820. C Hernandez
    821. S Hernández-Tiedra
    822. C Hetz
    823. PR Hiesinger
    824. K Higaki
    825. S Hilfiker
    826. BG Hill
    827. JA Hill
    828. WD Hill
    829. K Hino
    830. D Hofius
    831. P Hofman
    832. GU Höglinger
    833. J Höhfeld
    834. MK Holz
    835. Y Hong
    836. DA Hood
    837. JJ Hoozemans
    838. T Hoppe
    839. C Hsu
    840. CY Hsu
    841. LC Hsu
    842. D Hu
    843. G Hu
    844. HM Hu
    845. H Hu
    846. MC Hu
    847. YC Hu
    848. ZW Hu
    849. F Hua
    850. Y Hua
    851. C Huang
    852. HL Huang
    853. KH Huang
    854. KY Huang
    855. S Huang
    856. S Huang
    857. WP Huang
    858. YR Huang
    859. Y Huang
    860. Y Huang
    861. TB Huber
    862. P Huebbe
    863. WK Huh
    864. JJ Hulmi
    865. GM Hur
    866. JH Hurley
    867. Z Husak
    868. SN Hussain
    869. S Hussain
    870. JJ Hwang
    871. S Hwang
    872. TI Hwang
    873. A Ichihara
    874. Y Imai
    875. C Imbriano
    876. M Inomata
    877. T Into
    878. V Iovane
    879. JL Iovanna
    880. RV Iozzo
    881. NY Ip
    882. JE Irazoqui
    883. P Iribarren
    884. Y Isaka
    885. AJ Isakovic
    886. H Ischiropoulos
    887. JS Isenberg
    888. M Ishaq
    889. H Ishida
    890. I Ishii
    891. JE Ishmael
    892. C Isidoro
    893. K Isobe
    894. E Isono
    895. S Issazadeh-Navikas
    896. K Itahana
    897. E Itakura
    898. AI Ivanov
    899. AK Iyer
    900. JM Izquierdo
    901. Y Izumi
    902. V Izzo
    903. M Jäättelä
    904. N Jaber
    905. DJ Jackson
    906. WT Jackson
    907. TG Jacob
    908. TS Jacques
    909. C Jagannath
    910. A Jain
    911. NR Jana
    912. BK Jang
    913. A Jani
    914. B Janji
    915. PR Jannig
    916. PJ Jansson
    917. S Jean
    918. M Jendrach
    919. JH Jeon
    920. N Jessen
    921. EB Jeung
    922. K Jia
    923. L Jia
    924. H Jiang
    925. H Jiang
    926. L Jiang
    927. T Jiang
    928. X Jiang
    929. X Jiang
    930. X Jiang
    931. Y Jiang
    932. Y Jiang
    933. A Jiménez
    934. C Jin
    935. H Jin
    936. L Jin
    937. M Jin
    938. S Jin
    939. UK Jinwal
    940. EK Jo
    941. T Johansen
    942. DE Johnson
    943. GV Johnson
    944. JD Johnson
    945. E Jonasch
    946. C Jones
    947. LA Joosten
    948. J Jordan
    949. AM Joseph
    950. B Joseph
    951. AM Joubert
    952. D Ju
    953. J Ju
    954. HF Juan
    955. K Juenemann
    956. G Juhász
    957. HS Jung
    958. JU Jung
    959. YK Jung
    960. H Jungbluth
    961. MJ Justice
    962. B Jutten
    963. NO Kaakoush
    964. K Kaarniranta
    965. A Kaasik
    966. T Kabuta
    967. B Kaeffer
    968. K Kågedal
    969. A Kahana
    970. S Kajimura
    971. O Kakhlon
    972. M Kalia
    973. DV Kalvakolanu
    974. Y Kamada
    975. K Kambas
    976. VO Kaminskyy
    977. HH Kampinga
    978. M Kandouz
    979. C Kang
    980. R Kang
    981. TC Kang
    982. T Kanki
    983. TD Kanneganti
    984. H Kanno
    985. AG Kanthasamy
    986. M Kantorow
    987. M Kaparakis-Liaskos
    988. O Kapuy
    989. V Karantza
    990. MR Karim
    991. P Karmakar
    992. A Kaser
    993. S Kaushik
    994. T Kawula
    995. AM Kaynar
    996. PY Ke
    997. ZJ Ke
    998. JH Kehrl
    999. KE Keller
    1000. JK Kemper
    1001. AK Kenworthy
    1002. O Kepp
    1003. A Kern
    1004. S Kesari
    1005. D Kessel
    1006. R Ketteler
    1007. IC Kettelhut
    1008. B Khambu
    1009. MM Khan
    1010. VK Khandelwal
    1011. S Khare
    1012. JG Kiang
    1013. AA Kiger
    1014. A Kihara
    1015. AL Kim
    1016. CH Kim
    1017. DR Kim
    1018. DH Kim
    1019. EK Kim
    1020. HY Kim
    1021. HR Kim
    1022. JS Kim
    1023. JH Kim
    1024. JC Kim
    1025. JH Kim
    1026. KW Kim
    1027. MD Kim
    1028. MM Kim
    1029. PK Kim
    1030. SW Kim
    1031. SY Kim
    1032. YS Kim
    1033. Y Kim
    1034. A Kimchi
    1035. AC Kimmelman
    1036. T Kimura
    1037. JS King
    1038. K Kirkegaard
    1039. V Kirkin
    1040. LA Kirshenbaum
    1041. S Kishi
    1042. Y Kitajima
    1043. K Kitamoto
    1044. Y Kitaoka
    1045. K Kitazato
    1046. RA Kley
    1047. WT Klimecki
    1048. M Klinkenberg
    1049. J Klucken
    1050. H Knævelsrud
    1051. E Knecht
    1052. L Knuppertz
    1053. JL Ko
    1054. S Kobayashi
    1055. JC Koch
    1056. C Koechlin-Ramonatxo
    1057. U Koenig
    1058. YH Koh
    1059. K Köhler
    1060. SD Kohlwein
    1061. M Koike
    1062. M Komatsu
    1063. E Kominami
    1064. D Kong
    1065. HJ Kong
    1066. EG Konstantakou
    1067. BT Kopp
    1068. T Korcsmaros
    1069. L Korhonen
    1070. VI Korolchuk
    1071. NV Koshkina
    1072. Y Kou
    1073. MI Koukourakis
    1074. C Koumenis
    1075. AL Kovács
    1076. T Kovács
    1077. WJ Kovacs
    1078. D Koya
    1079. C Kraft
    1080. D Krainc
    1081. H Kramer
    1082. T Kravic-Stevovic
    1083. W Krek
    1084. C Kretz-Remy
    1085. R Krick
    1086. M Krishnamurthy
    1087. J Kriston-Vizi
    1088. G Kroemer
    1089. MC Kruer
    1090. R Kruger
    1091. NT Ktistakis
    1092. K Kuchitsu
    1093. C Kuhn
    1094. AP Kumar
    1095. A Kumar
    1096. A Kumar
    1097. D Kumar
    1098. D Kumar
    1099. R Kumar
    1100. S Kumar
    1101. M Kundu
    1102. HJ Kung
    1103. A Kuno
    1104. SH Kuo
    1105. J Kuret
    1106. T Kurz
    1107. T Kwok
    1108. TK Kwon
    1109. YT Kwon
    1110. I Kyrmizi
    1111. AR La Spada
    1112. F Lafont
    1113. T Lahm
    1114. A Lakkaraju
    1115. T Lam
    1116. T Lamark
    1117. S Lancel
    1118. TH Landowski
    1119. DJ Lane
    1120. JD Lane
    1121. C Lanzi
    1122. P Lapaquette
    1123. LR Lapierre
    1124. J Laporte
    1125. J Laukkarinen
    1126. GW Laurie
    1127. S Lavandero
    1128. L Lavie
    1129. MJ LaVoie
    1130. BY Law
    1131. HK Law
    1132. KB Law
    1133. R Layfield
    1134. PA Lazo
    1135. L Le Cam
    1136. KG Le Roch
    1137. H Le Stunff
    1138. V Leardkamolkarn
    1139. M Lecuit
    1140. BH Lee
    1141. CH Lee
    1142. EF Lee
    1143. GM Lee
    1144. HJ Lee
    1145. H Lee
    1146. JK Lee
    1147. J Lee
    1148. JH Lee
    1149. JH Lee
    1150. M Lee
    1151. MS Lee
    1152. PJ Lee
    1153. SW Lee
    1154. SJ Lee
    1155. SJ Lee
    1156. SY Lee
    1157. SH Lee
    1158. SS Lee
    1159. SJ Lee
    1160. S Lee
    1161. YR Lee
    1162. YJ Lee
    1163. YH Lee
    1164. C Leeuwenburgh
    1165. S Lefort
    1166. R Legouis
    1167. J Lei
    1168. QY Lei
    1169. DA Leib
    1170. G Leibowitz
    1171. I Lekli
    1172. SD Lemaire
    1173. JJ Lemasters
    1174. MK Lemberg
    1175. A Lemoine
    1176. S Leng
    1177. G Lenz
    1178. P Lenzi
    1179. LO Lerman
    1180. D Lettieri Barbato
    1181. JI Leu
    1182. HY Leung
    1183. B Levine
    1184. PA Lewis
    1185. F Lezoualc'h
    1186. C Li
    1187. F Li
    1188. FJ Li
    1189. J Li
    1190. K Li
    1191. L Li
    1192. M Li
    1193. M Li
    1194. Q Li
    1195. R Li
    1196. S Li
    1197. W Li
    1198. W Li
    1199. X Li
    1200. Y Li
    1201. J Lian
    1202. C Liang
    1203. Q Liang
    1204. Y Liao
    1205. J Liberal
    1206. PP Liberski
    1207. P Lie
    1208. AP Lieberman
    1209. HJ Lim
    1210. KL Lim
    1211. K Lim
    1212. RT Lima
    1213. CS Lin
    1214. CF Lin
    1215. F Lin
    1216. F Lin
    1217. FC Lin
    1218. K Lin
    1219. KH Lin
    1220. PH Lin
    1221. T Lin
    1222. WW Lin
    1223. YS Lin
    1224. Y Lin
    1225. R Linden
    1226. D Lindholm
    1227. LM Lindqvist
    1228. P Lingor
    1229. A Linkermann
    1230. LA Liotta
    1231. MM Lipinski
    1232. VA Lira
    1233. MP Lisanti
    1234. PB Liton
    1235. B Liu
    1236. C Liu
    1237. CF Liu
    1238. F Liu
    1239. HJ Liu
    1240. J Liu
    1241. JJ Liu
    1242. JL Liu
    1243. K Liu
    1244. L Liu
    1245. L Liu
    1246. Q Liu
    1247. RY Liu
    1248. S Liu
    1249. S Liu
    1250. W Liu
    1251. XD Liu
    1252. X Liu
    1253. XH Liu
    1254. X Liu
    1255. X Liu
    1256. X Liu
    1257. Y Liu
    1258. Y Liu
    1259. Z Liu
    1260. Z Liu
    1261. JP Liuzzi
    1262. G Lizard
    1263. M Ljujic
    1264. IJ Lodhi
    1265. SE Logue
    1266. BL Lokeshwar
    1267. YC Long
    1268. S Lonial
    1269. B Loos
    1270. C López-Otín
    1271. C López-Vicario
    1272. M Lorente
    1273. PL Lorenzi
    1274. P Lõrincz
    1275. M Los
    1276. MT Lotze
    1277. PE Lovat
    1278. B Lu
    1279. B Lu
    1280. J Lu
    1281. Q Lu
    1282. SM Lu
    1283. S Lu
    1284. Y Lu
    1285. F Luciano
    1286. S Luckhart
    1287. JM Lucocq
    1288. P Ludovico
    1289. A Lugea
    1290. NW Lukacs
    1291. JJ Lum
    1292. AH Lund
    1293. H Luo
    1294. J Luo
    1295. S Luo
    1296. C Luparello
    1297. T Lyons
    1298. J Ma
    1299. Y Ma
    1300. Y Ma
    1301. Z Ma
    1302. J Machado
    1303. GM Machado-Santelli
    1304. F Macian
    1305. GC MacIntosh
    1306. JP MacKeigan
    1307. KF Macleod
    1308. JD MacMicking
    1309. LA MacMillan-Crow
    1310. F Madeo
    1311. M Madesh
    1312. J Madrigal-Matute
    1313. A Maeda
    1314. T Maeda
    1315. G Maegawa
    1316. E Maellaro
    1317. H Maes
    1318. M Magariños
    1319. K Maiese
    1320. TK Maiti
    1321. L Maiuri
    1322. MC Maiuri
    1323. CG Maki
    1324. R Malli
    1325. W Malorni
    1326. A Maloyan
    1327. F Mami-Chouaib
    1328. N Man
    1329. JD Mancias
    1330. EM Mandelkow
    1331. MA Mandell
    1332. AA Manfredi
    1333. SN Manié
    1334. C Manzoni
    1335. K Mao
    1336. Z Mao
    1337. ZW Mao
    1338. P Marambaud
    1339. AM Marconi
    1340. Z Marelja
    1341. G Marfe
    1342. M Margeta
    1343. E Margittai
    1344. M Mari
    1345. FV Mariani
    1346. C Marin
    1347. S Marinelli
    1348. G Mariño
    1349. I Markovic
    1350. R Marquez
    1351. AM Martelli
    1352. S Martens
    1353. KR Martin
    1354. SJ Martin
    1355. S Martin
    1356. MA Martin-Acebes
    1357. P Martín-Sanz
    1358. C Martinand-Mari
    1359. W Martinet
    1360. J Martinez
    1361. N Martinez-Lopez
    1362. U Martinez-Outschoorn
    1363. M Martínez-Velázquez
    1364. M Martinez-Vicente
    1365. WK Martins
    1366. H Mashima
    1367. JA Mastrianni
    1368. G Matarese
    1369. P Matarrese
    1370. R Mateo
    1371. S Matoba
    1372. N Matsumoto
    1373. T Matsushita
    1374. A Matsuura
    1375. T Matsuzawa
    1376. MP Mattson
    1377. S Matus
    1378. N Maugeri
    1379. C Mauvezin
    1380. A Mayer
    1381. D Maysinger
    1382. GD Mazzolini
    1383. MK McBrayer
    1384. K McCall
    1385. C McCormick
    1386. GM McInerney
    1387. SC McIver
    1388. S McKenna
    1389. JJ McMahon
    1390. IA McNeish
    1391. F Mechta-Grigoriou
    1392. JP Medema
    1393. DL Medina
    1394. K Megyeri
    1395. M Mehrpour
    1396. JL Mehta
    1397. Y Mei
    1398. UC Meier
    1399. AJ Meijer
    1400. A Meléndez
    1401. G Melino
    1402. S Melino
    1403. EJ de Melo
    1404. MA Mena
    1405. MD Meneghini
    1406. JA Menendez
    1407. R Menezes
    1408. L Meng
    1409. LH Meng
    1410. S Meng
    1411. R Menghini
    1412. AS Menko
    1413. RF Menna-Barreto
    1414. MB Menon
    1415. MA Meraz-Ríos
    1416. G Merla
    1417. L Merlini
    1418. AM Merlot
    1419. A Meryk
    1420. S Meschini
    1421. JN Meyer
    1422. MT Mi
    1423. CY Miao
    1424. L Micale
    1425. S Michaeli
    1426. C Michiels
    1427. AR Migliaccio
    1428. AS Mihailidou
    1429. D Mijaljica
    1430. K Mikoshiba
    1431. E Milan
    1432. L Miller-Fleming
    1433. GB Mills
    1434. IG Mills
    1435. G Minakaki
    1436. BA Minassian
    1437. XF Ming
    1438. F Minibayeva
    1439. EA Minina
    1440. JD Mintern
    1441. S Minucci
    1442. A Miranda-Vizuete
    1443. CH Mitchell
    1444. S Miyamoto
    1445. K Miyazawa
    1446. N Mizushima
    1447. K Mnich
    1448. B Mograbi
    1449. S Mohseni
    1450. LF Moita
    1451. M Molinari
    1452. M Molinari
    1453. AB Møller
    1454. B Mollereau
    1455. F Mollinedo
    1456. M Mongillo
    1457. MM Monick
    1458. S Montagnaro
    1459. C Montell
    1460. DJ Moore
    1461. MN Moore
    1462. R Mora-Rodriguez
    1463. PI Moreira
    1464. E Morel
    1465. MB Morelli
    1466. S Moreno
    1467. MJ Morgan
    1468. A Moris
    1469. Y Moriyasu
    1470. JL Morrison
    1471. LA Morrison
    1472. E Morselli
    1473. J Moscat
    1474. PL Moseley
    1475. S Mostowy
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    1477. D Mottet
    1478. JC Mottram
    1479. CE Moussa
    1480. VE Mpakou
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    1482. JM Mulcahy Levy
    1483. S Muller
    1484. R Muñoz-Moreno
    1485. C Muñoz-Pinedo
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    1490. IU Mysorekar
    1491. IR Nabi
    1492. M Nabissi
    1493. GA Nader
    1494. Y Nagahara
    1495. Y Nagai
    1496. K Nagata
    1497. A Nagelkerke
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    1502. H Nakatogawa
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    1505. NI Naqvi
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    1508. M Narita
    1509. AC Nascimbeni
    1510. R Natarajan
    1511. LC Navegantes
    1512. ST Nawrocki
    1513. TY Nazarko
    1514. VY Nazarko
    1515. T Neill
    1516. LM Neri
    1517. MG Netea
    1518. RT Netea-Maier
    1519. BM Neves
    1520. PA Ney
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    1524. AS Nicot
    1525. H Nilsen
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    1527. M Nishimura
    1528. I Nishino
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    1530. H Niu
    1531. RA Nixon
    1532. VC Njar
    1533. T Noda
    1534. AA Noegel
    1535. EM Nolte
    1536. E Norberg
    1537. KK Norga
    1538. SK Noureini
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    1544. VB O'Donnell
    1545. T O'Donovan
    1546. PJ O'Dwyer
    1547. I Oehme
    1548. CL Oeste
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    1555. R Ojha
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    1563. I Orhon
    1564. L Orosz
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    1567. AL Ortega
    1568. E Ortona
    1569. LD Osellame
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    1572. HD Osiewacz
    1573. T Otomo
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    1576. TF Outeiro
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    1579. M Overholtzer
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Decision letter

  1. Andrés Aguilera
    Reviewing Editor; CABIMER, Universidad de Sevilla, Spain
  2. Michael B Eisen
    Senior Editor; HHMI, University of California, Berkeley, United States
  3. Sherif El-Khamisy
    Reviewer; University of Sheffield, United Kingdom

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

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting your work entitled "A small molecule G-quadruplex stabilizer reveals a novel pathway of autophagy regulation in neurons" for consideration by eLife. Your article has been reviewed by a Senior Editor, a Reviewing Editor, and three reviewers. The reviewers have opted to remain anonymous.

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered at this moment for publication in eLife. However, we believe that this is a very interesting study that after further work would be appropriate for eLife. It reveals that G4 may represent a new putative intervention point to interfere with autophagy-related neurodegeneration represents an important discovery and that the implication of G4-DNA in autophagy and age-related neurological deficit is novel and will be of interest to a broad readership and of interest for eLife. We would invite to resubmit a properly revised version attending the comments of the three reviewers accompanying your submission with a rebuttal explaining point-by-point the comments of the reviewers.

Reviewer #1:

Summary:

The G-quadruplex (G4) ligand pyridostatin (PDS) was found to downregulate expression of the Atg7 gene in neurons. The first intron of the Atg7 gene contains predicted G4-forming sequence that was indeed shown to form G4 and interact with PDS. Consistent with these findings, in vitro a G4 antibody and G4-binding protein bind to the Atg7 intron G4-sequence. In vivo, mice treated with PDS were found to develop memory deficits and accumulation of lipofuscin, a mixture of oxidized lipids and proteins previously observed to accumulate in aged brains. Brain samples from aged mice, but not young mice, contained G4 DNA, as evidenced by staining with G4-selective reagent. Overexpression of the G4-resolving helicase Pif1 in neurons improved phenotypes associated with PDS treatment, i.e., neuronal death. Based on their findings, the authors conclude that G4 DNA is involved in regulating autophagy in neurons.

Critical Comments:

- The narrative of the Results section is noticeably deficient in making quantitative statements relating to the experimental data. This issue should be addressed throughout the Results section.

- A useful control in the Pif1 rescue experiments would have been to test if a site-directed ATPase/helicase-dead mutant version of Pif1 failed to affect PDS-induced phenotypes in cultured primary neurons.

- Please define/explain Dendra2-LC3 half-life and how it is a reliable indicator of autophagy. It is mentioned in Figure 4 that LC3 is an autophagy marker. This should be better described in Results section and reference(s) provided.

- Aside from short-term memory as assayed by novel object recognition test, are there any other effects on mice treated with PDS in terms of development of memory deficits or neurological function/capacity? Were there any sex-specific effects?

- The authors briefly mention in the Introduction the recently published paper by Beauvarlet et al., (April 2019) suggesting that G4 DNA in autophagic genes regulates autophagy in cancer cells. As cite in that work, there were several other previously published papers suggesting a connection of autophagy to G4 nucleic acid metabolism as probed by G4 ligands: Orlotti et al., (2012); Zhou et al., (2009); Zhou et al., (2009). While all these papers delved more into the relationships of G4 and autophagy in cancer, it would be useful to discuss these works in a single paragraph in the Discussion and place the current work in light of those findings.

- In the Introduction, references should be provided for the statement that G4 has been implicated in neurodegenerative disorders frontotemporal dementia and ALS.

- In previous work by the authors, they reported that PDS promotes DNA damage and downregulates transcription of BRCA1 in neurons (Aging (2017)). The showed that overexpressed BRCA1 mitigates PDS-induced DNA damage. Similarly, in the current work does overexpression of ATG7 enzyme modulate the PDS-related phenotypes observed? Is DNA damage accumulation in neurons also observed in the current work? How are the results and findings from the two studies related, if at all?

Reviewer #2:

In this paper, the authors rather convincingly show that the ATG7 gene, which is critical for the initiation of autophagy and whose transcription decreases with aging, does contain a bona fide G-quadruplex (G4) in its first intron and that stabilization of G4 using pyridostatin (PDS), a well-known benchmark G4 ligand, downregulates this ATG7 gene. All this suggest that stabilization of ATG7 G4 does interfere with the transcription of this gene, thereby inhibiting induction of autophagy. In good agreement, the authors found that mice treated with PDS develop memory deficits and accumulation of lipofuscin, suggesting premature aging and deficient autophagy. Moreover, brain samples from aged mice contain G4-DNA which are absent in brain samples from young mice. Finally, the authors showed that overexpressing the helicase Pif1, which is known to resolve G4, in neurons exposed to PDS improves the various phenotypes associated with PDS treatment, thereby suggesting that G4-DNA may represent an interesting and relevant intervention point for boosting autophagy and thereby interfering with neurodegeneration.

In general, I think this is a very interesting study based on well-designed and well-conducted experiments that deserves to be published in eLife. In particular, revealing that G4 may represent a new putative intervention point to interfere with autophagy-related neurodegeneration represents an important discovery. Also, the idea that G4-ligands may induce/accelerate neurodegeneration is highly important, especially with respect to their putative development to the clinics in other field like cancerology. However, I have a few comments that need to be addressed before this paper could be deemed for publication in eLife.

- Figure 1: the search for PQFS in the gene and promoter sequences of autophagy genes. The analysis performed by the authors indicates that all the autophagy genes contain putative G4-DNA. It would be important to precise the percentage of total genes that contain, or not putative G4-DNA to assess how specific is this correlation.

- Figure 2: 2 µM PDS has a much stronger negative effect than 2 µM BRACO19 on the level of the ATG7 transcript. However, the effect on ATG7 protein level is similar for both compounds suggesting that BRACO19 could also interfere with translation of ATG7 mRNA or on ATG7 protein stability. The authors should comment on this. As for BRACO19, although it is very important to use another GA-ligand than PDS to support the authors' main conclusions, it is somehow surprising that BRACO19 is used only in this experiment and also that its putative stabilizing effect on ATG7 G4-DNA is not properly assessed (see below).

- Figure 3: The CD signature of the ATG7 gene in the classical conditions is not fully convincing and could correspond to a mix of several structures (not only G4). The authors argue that the presence of dehydrating agents (PEG, CH3CN) reduces the polymorphism and indeed the CD looks better but this effect has been reported only for telomeric sequences and is not fully admitted. Therefore, the salt effect (Li+ to K+) should preferably been tested using the HF2 antibodies. In line with what I discussed just above, BRACO19 should also be tested in the UV-melting experiments performed in panel c to determine if it also stabilizes, or not, the most probable ATG7 G4 and also in the experiments performed with N-TASQ on neurons in panels I & J. The TDS spectrum without dehydrating agents should also be shown. TDS and CD spectra should be shown on different panels and the CD in K+ conditions should not be termed "cont" (for control?) as it is misleading. Also, another classical control for CD which is missing is the use of scrambled G runs. Another important point is that the in vitro experiments presented in panels e to h should be repeated in presence, or not, of PDS or of BRACO19 to determine if these two G4 ligands may, or not, interfere with the binding of the HF2 antibody and/or of G4-binding proteins. This point looks important to me as the general assumption is that G4-ligands stabilize G4 structures but, in principle they could also destabilize them, and/or even prevent the binding of various factors such as antibodies or G4-binding proteins by direct competition. Finally, as for the experiments with N-TASQ, I have some problem to understand them because, as this fluorescent molecule is also a G4-ligand, one may imagine a competition between this compound and PDS for the binding on G4. And, indeed, in the original paper on N-TASQ (Laguerre et al., 2016), this problem is discussed and addressed (by using BRACO19 instead of PDS) and the authors concluded that at high concentration (100 µM) N-TASQ provides high resolution images but does not allow to visualize significant differences between BRACO19-treated and -untreated cells and that the only conditions that allowed to visualize an increase in N-TASQ stained nuclear foci was a low dose of N-TASQ (2.5 µM) and of BRACO19, and that a higher dose of BRACO19 leads to a BRACO19 dose-dependent decrease in N-TASQ staining, presumably because of a competition between these two G4-ligands for binding on G4. Hence it is hard for me to understand why and how PDS treatment should lead to an increase in N-TASQ staining (used at 50 µM here) as shown in panel i and j. Of note such a competition with PDS has been described for DAOTA-M2, another G4-specific fluorescent probe (Shivalingam et al., 2015). All this should be discussed and the effect of BRACO19 on N-TASQ staining should also be tested.

- Figure 4: BRACO19 should also be tested in at least one of the experiments presented here as there are at the basis of the main conclusion of the paper, destabilization of DNA-G4 represents a relevant and interesting intervention point ATG7 to interfere with neurodegeneration associated with aging-related decline in induction of autophagy.

- In the Discussion section, my suggestion is that the authors should discuss about the ability of G4-ligand to stabilize DNA-G4. Is it a general property of all the G4-ligands or is it specific to a subset of G4-ligands (that includes PDS and BRACO19)? Should a compound that efficiently bind G4 without any effect on their stability exist, then it would represent an ideal control to further validate their findings. Also the possibility that the PDS-related phenotypes may involve its effect on RNA-G4 should be mentioned and discussed.

To finish, and importantly, in my view the main message of this manuscript is that G4-DNA may represent an interesting and relevant intervention point for boosting autophagy and thereby interfering with neurodegeneration, rather than the discovery of a novel pathway that regulates autophagy in neurons, as stated by the authors already in the title. Indeed, if the authors want to state that their findings do reveal a novel pathway for regulating autophagy, than they need to find physiological situations where the stability of DNA-G4 present in autophagy genes (in particular in ATG7) may be tuned by various cellular pathway(s)/component(s) which, this way, regulate autophagy. As for now, they essentially showed that stabilizing G4 using PDS downregulates ATG7 and that PDS induces memory deficits and autophagy in mice and that, on the contrary, overexpressing the G4-DNA helicase Pif1 in neurons exposed to PDS suppresses PDS-associated phentotype. Not to mention that this G4 stabilization/PDS effect may also be at the level of G4-RNA. Therefore, I suggest that the authors down tune their message, especially in the Title but also in the discussion. I guess that revealing a new and relevant intervention point for modulating autophagy in neurons is per se sufficiently interesting in addition to be of biomedical relevance.

Reviewer #3:

The authors used the G4 stabilizer pyridostatin (PDS) in cultured neurons and in mice to unravel a role for G4-DNA structures during Atg7-mediated autophagy. They used biophysical methods to demonstrate accumulation of G4-DNA in the Atg7 gene and immunostaining methods to illustrate an age-dependent global increase of G4-DNA. The authors further show that the majority of phenotypes induced by PDS were partially rescued by overexpression of fhe Pif1 helicase.

The manuscript is clearly written, and data are well presented. The implication of G4-DNA in autophagy and age-related neurological deficit is novel and will be of interest to a broad readership. It is not, however, clear if the effects reported here are direct consequences of G4-DNA in the Atg7 gene or indirect global perturbations of G4-DNA homeostasis. PDS is a blunt tool potentially impacting over 600,000 putative G4-DNA structures. Also, Pif1, as acknowledged by the authors, impacts telomere length, so how can the authors be sure that the reported partial improvements of neuronal phenotypes are solely due to resolving G4-DNA structures? Is the partial rescue specific to G4s in the Atfg7 gene? Performing a classical epistasis experiments is critical in this manuscript. For example, repeating key experiments in presence and absence of Atg7 will confirm that the reported phenotypes are due to direct modulation of G4-DNA in the Atg7 gene, hence supports the conclusion of a novel pathway as stated in the Title.

For the huntingtin experiments in Figure 4, I suggest using patient derived fibroblasts or iPS-derived striatal neurons instead of ectopic expression of the exon-1 fragment of the poly-Q huntingtin. Although, in silico predictions using the QGRS mapper rule out G4-DNA, it is important to experimentally rule it out in the native genomic environment.

The protein p62 is a known hallmark of perturbed autophagy. Is p62 aggregation also modulated by PDS in an Atg7 dependent manner? This is important since this hallmark protein aggregation is a common phenomenon in a number of age-associated neurological disorders including Huntington's and ALS/FTD. In the opinion of this reviewer, this is a better hallmark of perturbed autophagy given its clinical relevance.

Overall, the concept is novel and exciting but the data in its present form do not support the main conclusion.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Small-molecule G-quadruplex stabilizers reveal a novel pathway of autophagy regulation in neurons" for consideration by eLife. Your article has been reviewed by Michael Eisen as the Senior Editor, a Reviewing Editor, and two reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Sherif El-Khamisy (Reviewer #1).

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

Summary:

This manuscript is a resubmission of a previous one in which authors show that the G-quadruplex (G4) ligand pyridostatin (PDS) was found to downregulate expression of the Atg7 gene in neurons. The first intron of the Atg7 gene contains predicted G4-forming sequences that seem to form G4 and interact with PDS. Mice treated with PDS develop memory deficits and accumulation of lipids and proteins previously observed to accumulate in aged brains. Brain samples from aged mice, but not young mice, contained G4 DNA, and overexpression of the G4-resolving helicase Pif1 in neurons improved the phenotypes associated with PDS treatment. Based on their findings, the authors conclude that G4 DNA is involved in regulating autophagy in neurons. The authors have satisfactorily responded to the concerns raised by the referees, but q few points need to be taken before the manuscript can be accepted.

Essential revisions:

- The 3 quartet structure shown in Figure 3 has a low probability of formation due to the presence of 3 long loops (5-nt, 7-nt, 9-nt) which drastically reduce its stability (see various methods of the G4 score calculation in Bedrat et al., 2016; Puig-Lombardi et al., 2019). Hence it follows that the Atg7-32 sequence is most probably highly dynamic and may form several secondary structures that exist in equilibrium (various G4, hairpins etc.), which is good agreement with the very broad profile of the NMR spectra. Hence this analysis does not allow the authors to firmly conclude the existence of a stable G4. Therefore, the authors should down-tune, or at least modulate their G4 hypothesis.

- The fact that Pif1 rescues PDS-induced phenotypes in cultured primary neurons (Figure 8). This observation is interesting but somehow a bit surprising and rather counter-intuitive as it is not fully consistent with numerous studies reported in the literature that show that the G4 unwinding activity of most of the G4 helicases is indeed prevented by G4 ligands. This has been shown in particular for Pif1 (see Mendoza et al., 2016; Mergny et al., 2015; Balasubramanian et al., 2015 plus references cited therein). Therefore, the assumption that Pif1 rescues PDS-induced phenotype by unwinding G4 in the Atg7 is unclear. The authors should discuss the results of their experiment with Pif1 in light of all the published data indicating that Pif1 G4 unwinding activity is inhibited by various G4 ligands that include PDS, or alternatively they could test their hypothesis by performing a functional in vitro assay (e.g.: unwinding assay with or without PDS).

https://doi.org/10.7554/eLife.52283.sa1

Author response

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the first round of review.]

Reviewer #1:

Summary:

The G-quadruplex (G4) ligand pyridostatin (PDS) was found to downregulate expression of the Atg7 gene in neurons. The first intron of the Atg7 gene contains predicted G4-forming sequence that was indeed shown to form G4 and interact with PDS. Consistent with these findings, in vitro a G4 antibody and G4-binding protein bind to the Atg7 intron G4-sequence. In vivo, mice treated with PDS were found to develop memory deficits and accumulation of lipofuscin, a mixture of oxidized lipids and proteins previously observed to accumulate in aged brains. Brain samples from aged mice, but not young mice, contained G4 DNA, as evidenced by staining with G4-selective reagent. Overexpression of the G4-resolving helicase Pif1 in neurons improved phenotypes associated with PDS treatment, i.e., neuronal death. Based on their findings, the authors conclude that G4 DNA is involved in regulating autophagy in neurons.

Critical Comments:

- The narrative of the Results section is noticeably deficient in making quantitative statements relating to the experimental data. This issue should be addressed throughout the Results section.

We thank the reviewer for this comment. We revised the manuscript to describe the results in greater detail, including quantitative statements for all of the results in the revised Results section.

- A useful control in the Pif1 rescue experiments would have been to test if a site-directed ATPase/helicase-dead mutant version of Pif1 failed to affect PDS-induced phenotypes in cultured primary neurons.

We thought this was an excellent suggestion, and we collected new data, which were added to the revised manuscript, to address this issue (Figure 8F). We cloned a site-directed ATPase/helicase-dead mutant version of Pif1 (E307Q) (George et al., 2009) and expressed it in primary neurons. Indeed, the mutant Pif1 failed to affect PDS-associated neuronal phenotypes—strong evidence that wild-type Pif1 activates coping mechanisms in PDS-treated degenerating neurons, leading to improved neuronal phenotypes, such as enhanced autophagy.

- Please define/explain Dendra2-LC3 half-life and how it is a reliable indicator of autophagy. It is mentioned in Figure 4 that LC3 is an autophagy marker. This should be better described in Results section and reference(s) provided.

The referee correctly points out that we only briefly described how protein (or organelle) half-life is measured with photoswitchable proteins and optical pulse-chase labeling (OPL). A number of studies used Dendra2 or other photoswitchable proteins, such as EOS2, and the OPL method to study protein or organelle dynamics in live cells. For example, mouse cell lines that express a mitochondrially localized Dendra2 (mito-Dendra2) were created to study mitochondrial dynamics and mitophagy (Pham, McCaffery and Chan, 2012). Another group created Dendra2-based PhOTO zebrafish for studying development and regeneration (Dempsey, Fraser and Pantazis, 2012). Dendra2-based OPL has been applied to study autophagy with Dendra2LC3 (Barmada et al., 2014; Moruno Manchon et al., 2015; Moruno Manchon et al., 2016); Tsvetkov et al., 2013) (LC3 is a marker of autophagy (Klionsky et al., 2016; Mizushima, Yoshimori and Levine, 2010), protein degradation (Barmada et al., 2014; Fernando, Rodriguez and Balasubramanian, 2008; Kwok and Merrick, 2017; Tsvetkov et al., 2013; Skibinski et al., 2017), and the dynamics of synaptic proteins (Wang et al., 2009). The journal Autophagy published a review paper, which recommended using Dendra2-LC3 to study autophagic flux in neurons (Klionsky et al., 2016). To measure autophagic flux in live neurons, we used the OPL method and longitudinal imaging (Barmada et al., 2014; Tsvetkov et al., 2013). Brief irradiation with short wavelength visible light irreversibly changes the conformation of “green” Dendra2 (“photoswitch”) and its fluorescence to red. We can then track how the red signal (e.g., “red” Dendra2-LC3) is “cleared” over time and measure the half-life of Dendra2-LC3. This information and references have been added to the manuscript, thereby directly addressing the reviewer’s concern.

- Aside from short-term memory as assayed by novel object recognition test, are there any other effects on mice treated with PDS in terms of development of memory deficits or neurological function/capacity? Were there any sex-specific effects?

We thank the reviewer for these questions. It took nearly 6 months to execute the requested experiments and revise the manuscript, primarily because the mice needed to reach a certain age to perform the requested task assays (we age our animals in house to control for diet/housing/microbiome effects). We apologize for this delay.

Regarding sex differences, we only used male mice in the original submission. This is a very important point and thus we prepared new cohorts of male and female mice that were injected with PDS. Previously, a G4-binding small molecule (MM41) was used as an anti-cancer therapy (Kulkarni, Chen and Maday, 2018); we therefore used a comparable dosage and schedule of PDS. We also used old male and female mice (25 months) with a leaky blood brain barrier (BBB) (Haeusle, Donnelly and Rothstein, 2016). All test were performed by an investigator blinded to treatment group. We examined these mice in (1) the novel object recognition test (NORT), (2) a fear conditioning test. We worked in collaboration with Dr. McCullough, who routinely uses animal models of stroke and has extensive expertise with behavior studies (https://med.uth.edu/neurology/faculty/louise-d-mccullough-md-phd/). First, we found that male and female mice injected with PDS performed significantly worse in the NORT (Figure 6A; *p-value(male-cont vs PDS)=0.0265, *pvalue(female-cont vs PDS)=0.0382, p-value(male vs female)=0.1029 (two-way ANOVA)). Second, mice were tested in the fear conditioning assay. The latter proved extremely stressful for old mice: they would frequently not move, making it difficult to analyze the data. Nevertheless, male mice performed worse in the fear conditioning assay. There was also a trend showing worse performance in the female cohort, although the data did not achieve statistical significance (see Author response image 1). Due to the lack of mobility in the aged mice (which could be mistaken for “freezing”), we did not include these data into the manuscript.

Author response image 1