- Research article
- Open Access
MicroRNA miR-29 controls a compensatory response to limit neuronal iron accumulation during adult life and aging
© Cellerino et al. 2017
- Received: 25 October 2016
- Accepted: 25 January 2017
- Published: 13 February 2017
A widespread modulation of gene expression occurs in the aging brain, but little is known as to the upstream drivers of these changes. MicroRNAs emerged as fine regulators of gene expression in many biological contexts and they are modulated by age. MicroRNAs may therefore be part of the upstream drivers of the global gene expression modulation correlated with aging and aging-related phenotypes.
Here, we show that microRNA-29 (miR-29) is induced during aging in short-lived turquoise killifish brain and genetic antagonism of its function induces a gene-expression signature typical of aging. Mechanicistically, we identified Ireb2 (a master gene for intracellular iron delivery that encodes for IRP2 protein), as a novel miR-29 target. MiR-29 is induced by iron loading and, in turn, it reduces IRP2 expression in vivo, therefore limiting intracellular iron delivery in neurons. Genetically modified fish with neuro-specific miR-29 deficiency exhibit increased levels of IRP2 and transferrin receptor, increased iron content, and oxidative stress.
Our results demonstrate that age-dependent miR-29 upregulation is an adaptive mechanism that counteracts the expression of some aging-related phenotypes and its anti-aging activity is primarily exerted by regulating intracellular iron homeostasis limiting excessive iron-exposure in neurons.
- Iron Homeostasis
- Iron Accumulation
- KEGG Pathway Analysis
- Multisite Gateway
- Dietary Iron Supplementation
MicroRNAs (miRNAs) are a class of small non-coding RNAs frequently present as small clusters spanning some kilobases in the genome, that negatively regulate gene expression by targeting mRNAs due to sequence complementarity, thereby inducing transcript degradation and/or translational inhibition . A single miRNA shows complementarity to hundreds or thousands of different transcripts, an ability which gives miRNAs the potential to act as central regulatory nodes in gene co-expression networks , thereby modulating and providing stability to complex biological processes involving several interconnected signaling pathways such as aging. In recent years, specific miRNAs that regulate different aspects of the aging process were identified . Several miRNAs were described to be significantly up- or down-regulated with age, both in invertebrate and vertebrate species [4, 5], some microRNAs influence lifespan and/or predict longevity in invertebrate models [6–9] and one of these (miR-34) regulates functional heart aging in mammals . MicroRNA-29 family members (miR-29a, miR-29b and miR-29c) were shown to be upregulated during normal aging in the central nervous system (CNS) of different vertebrate species such as fish , mice [12–14], monkeys  and humans [5, 15]. Moreover, miR-29 appears upregulated in klotho-deficient mice , a model of premature aging, and progeroid mouse model Zmpste24 –/– .
In mammals, the miR-29 family is present as two distinct genomic clusters that are both ubiquitously expressed and are particularly enriched in the CNS , specifically in mature neurons . Mutant mice lacking both clusters do not present evident abnormalities at birth, but they rapidly accumulate defects during post-natal development and die within 6 weeks . Mice lacking only one cluster (the miR-29b/a-1 locus), thus retaining residual miR-29 activity, reach adulthood, display an ataxic phenotype, a mild loss of Purkinje cells in the cerebellum, and die around 9 months of age . A similar cerebellar phenotype is induced by knock-down of miR-29 in adult rodents . On the other hand, up-regulation of miR-29 protects neurons against apoptosis during neuronal maturation, forebrain cerebral ischemia and stroke by targeting pro-apoptotic members of the BCL-2 family [20–22]. Interestingly, the miR-29 family was found to target Beta-Site APP-Cleaving Enzyme (BACE1) mRNA and to be downregulated in sporadic Alzheimer’s disease . All these data indicate that miR-29 plays a protective role in neurons and reduced miR-29 activity in adult life has detrimental effects.
Iron is an element required for multiple fundamental biological processes such as mitochondrial ATP generation, DNA replication and synthesis of heme, myelin and dopamine . While iron is an essential micronutrient, it also represents one of the most powerful sources of oxidative damage. Indeed, intermediates of oxygen reduction, including H2O2 and superoxide, are potent oxidants in the presence of Fe2+ and their reactions with Fe2+ form hydroxyl radicals, which cause cytotoxicity primarily due to lipid peroxidation . This, along with the evidence that iron accumulates in several tissues with age [26–29], supports the prevailing opinion that age-dependent iron accumulation contributes to the aging process by increasing oxygen reactive species production, which over time causes extensive mitochondrial and cellular dysfunction . Consistently, dietary iron supplementation reduces lifespan and accelerates age-dependent protein aggregation in C. elegans . Instead, reduced iron absorption increases longevity in flies  and iron chelant therapy reduces oxidative stress in worms .
Iron responsive proteins (IRP1 and IRP2) and their binding sites in mRNAs (iron responsive elements, IREs) constitute an iron sensing system that tightly regulates intracellular iron homeostasis by post-transcriptional regulation of key genes involved in iron uptake, storage, export and utilization , thus strongly influencing the energy production and redox status of cells. IRP2 is particularly enriched in the CNS and it appears to play a preeminent role in the regulation of intracellular iron homeostasis within the CNS . Indeed, alteration of IRP2 alone, but not of IRP1 alone, induces iron imbalance and iron-mediated toxicity in neurons [35, 36]. Despite the central role of IRPs in regulating iron homeostasis, little is known as to their regulation during aging and whether their altered expression contributes to the age-related decline. It is known, however, that downregulation of transferring receptor, a direct target of IRPs, is among the most robust transcriptional markers of aging  (and personal unpublished observations).
Here, we investigated the role of miR-29 during adult life in the short-lived turquoise killifish Nothobranchius furzeri (turquoise killifish). This is the shortest-lived vertebrate that can be cultured in captivity and has emerged as model organism to study vertebrate aging. Its aging is characterized by an exceptionally short lifespan of 4–12 months (depending on genetic background), age-dependent cognitive decline, and expression of age-related phenotypes at the molecular, cellular, and integrated level [38–44] (for a review see ). In particular, genome-wide transcript regulation patterns during aging are similar in N. furzeri and humans  and miR-29 is upregulated during N. furzeri aging . It therefore represents an ideal model to investigate how a perturbation of miR-29 expression affects aging. We generated a transgenic line with neuronal specific mir-29 loss of function and analyzed genome-wide transcript regulation by RNA-seq to compare the perturbations induced by miR-29 loss with those induced by aging.
MiR-29 is up-regulated with age in neurons and is negatively-correlated with expression of its targets
Genetic repression of mir-29
MiR-29 antagonism mimics aging-induced gene regulation in N. furzeri brain
Mir-29 affects iron homeostasis via regulation of IRP2
Overall, these data strongly indicate that miR-29 is responsible for age-dependent downregulation of IRP2 in neurons that, in turn, reduces TFR1A expression. As a proof of principle that miR-29 could exhibit a conserved regulation of iron homeostasis also in mammals, we evaluated the expression of miR-29 and iron management genes during post-natal development in the mouse brain. A dramatic up-regulation of mature miR-29 members during the first 2 months of postnatal life was already described [16, 23]. We tested whether miR-29 increase correlates with Ireb2 and Tfr1a downregulation. Using RT-qPCR, we quantified the expression of both miR-29 primary transcripts in postnatal day 0 (P0) and P60 mouse cerebral cortex. Both increased their expression more than 30 times (Additional file 9a) while Ireb2, Tfr1a, and Scl11a2/DMT1 were significantly downregulated (Additional file 9b). In addition, during the preparation of this manuscript, Papadopulous et al.  reported that mice lacking one locus for miR-29 show up-regulation of Ireb2, lending further support to a direct regulation of IRP2 expression by miR-29 in vivo.
Neuronal-specific overexpression of IRP2 leads to mitochondria damage and pervasive oxidative stress . Therefore, we assessed iron content and histochemical markers of damage in the sponge-29 transgenic line. Non-heme iron content was significantly increased as compared to wild-types at age 12 weeks (Fig. 5g). To assess whether increased iron induced oxidative stress we analyzed lipofuscin, an autofluorescent pigment that is primarily composed of cross-linked protein residues, generated by iron-catalyzed oxidative processes . Lipofuscin deposition was quantified in the periventricular grey zone of the optic tectum, a brain region composed by tightly packed neuronal somata and that shows a strong expression of miR-29 (Fig. 1d) and was significantly increased in the sponge-29 line as compared to wild-type (Fig. 5h). Finally, gliosis was assessed as a nonspecific reactive change of glial cells in response to neuronal damage. Increased immunoreactivity for the glial markers GFAP and S100β was observed (Additional file 10).
Our data indicate that miR-29 upregulation with age reduces IRP2-TFR1A axis in neurons thereby reducing intracellular iron delivery and limiting iron-mediated neuronal damage.
Iron loading induces miR-29 in neurons
Our results suggest that iron amount affects mir-29 expression; however, since the delay between mir-29 increases and iron-overload, we consider that intracellular events triggered by iron increase and not iron directly are responsible for up-regulation of miR-29.
Here, we report the first case of modulation of neuronal aging by a miRNA in a vertebrate species. Neuronal-specific miR-29 loss of function induces accelerated expression of aging phenotypes both at the global gene expression level and the histological level. Age-dependent up-regulation of miR-29 is conserved among different vertebrate species and different tissues. With our work, we show that, in fish, (1) miR-29 is expressed in mature neurons as previously shown in mice, (2) a robust negative correlation between expression of miR-29 and its targets is observed during adult life, as previously shown in primates , and (3) miR-29 loss of function has detrimental effects, as previously observed in mammals both in physiological [17, 18] and pathological contexts such as ischemia , cancer , thymus involution , and inflammatory response [66, 67]. Therefore, miR-29 upregulation appears to be an evolutionary conserved aging signature that provides an advantage in opposing aging-induced dysfunctions. This hypothesis is further supported by the observation that miR-29 is upregulated in a mouse model of progeria . In addition, during killifish aging, miR-29 is upregulated also in liver, skin , and heart (own published data). Consistently, miR-29 is reported to be upregulated in several tissues in aging mammals as well [5, 12–15]. Thus, miR-29 upregulation appears to be a common aging mechanism across different tissues.
These data also lead to the general concept that part of age-dependent gene regulation is adaptive and protective. Indeed, a recent study showed that out of 29 conserved genes that are down-regulated with age in nematode worms, fish, and mice, 15 cause life extension when experimentally down-regulated in the worm  and it was previously shown that miR-34 is upregulated with age in fruit fly and its overexpression is life-extending while the knock-out is life-shortening .
Although we did not investigate the molecular mechanism underlying age-dependent miR-29 upregulation, here we observed that miR-29 loss of function leads to increased iron deposition in the adult killifish brain and that, in turn, acute iron loading induces miR-29 upregulation in brain, liver, and muscle. In this respect, it should be noticed that age-dependent iron accumulation was observed in several organisms such us C. elegans, D. melanogaster , mice , primates [70, 71], and humans . In mammals, iron increase is observed in several tissues, such as brain, heart, muscle, liver, skin, kidney, and spleen, and it appears to be a robust aging hallmark. However, our data also demonstrate that miR-29 does not respond immediately to an acute increase iron concentrations, but with a delay of 2 days. We therefore speculate that age-dependent accumulation of iron-mediated damage might represent the stimulus that triggers miR-29 upregulation during aging.
Further, we report that miR-29 regulates IRP2 expression directly and antagonism of miR-29 abrogates age-dependent repression of IRP2 in neurons, which is very likely the cause of increased iron accumulation in the brain of the sponge-29 line. In fact, IRP2 is an RNA-binding protein that acts as master regulator of intracellular iron availability in the brain, influencing both the energy production and the redox status of the cell. Similarly to miR-29, IRP2 in enriched in the CNS. Within the CNS, different cell types (neurons, astrocytes, oligodendrocytes, and microglia) express iron management genes at different levels due to differences in their iron requirement and utilization. For instance, neurons express high levels of TFR1A and low levels of ferritin which, on the other hand, is strongly expressed in astrocytes and microglia . Indeed, the neuronal-specific expression of TFR1A reflects their high-energy metabolic rate, while the relative low ferritin expression suggests that, as opposed to astrocytes, iron storage is negligible as compared to iron usage by mitochondria and other metabolic processes. Moreover, neuronal restricted expression of mitochondrial ferritin in the mammalian brain further supports this consideration . In addition, in rodents, the highest neuronal iron consumption seems to occur during perinatal development and coincides with neuronal maturation and myelin synthesis [74, 75]; subsequently, neuronal iron demand decreases along with Tfr1a mRNA expression. Due to the low cytosolic iron storage capacity of neurons, a small increase in iron loading may result in mitochondrial iron accumulation and significant changes in the mitochondrial redox status. Thus, modulation of TFR1A expression is crucial for redox status homeostasis in neurons. In fact, our work revealed that miR-29 increases in aging reduce IRP2 and TFR1A levels, therefore limiting excessive intracellular iron delivery and protecting neurons from iron-mediated toxicity. Although IRP2 simultaneously regulates several iron-management genes, neuron-specific loss-of-function of miR-29 results in a significant modulation of Tfr1a, but not of cytosolic Fth1a nor of Scl40a2, suggesting that neurons might regulate iron homeostasis primarily through modulation of TFR1A. Since expressions of Fth1a, Scl40a2, and FBXL5 – all linked to cytosolic iron – were stable during aging, we speculate that iron might accumulate primarily in the mitochondria causing mitochondrial dysfunction and that this effect is exacerbated by mR-29 knockdown. Our hypothesis is supported by the up-regulation of energy production pathways such as oxidative phosphorylation and TCA cycle in the sponge-29 line and by the direct demonstration that IRP2 upregulation induces mitochondrial iron accumulation in human lung cells . Moreover, La Vaute et al.  showed that IRP2-deficient mice exhibit neurodegeneration linked to cytosolic iron accumulation in gray and white matter. Deficiency of IRP2 increases the expression of the iron storage protein ferritin and reduces the expression of the transferrin receptor leading to functional iron deficiency and therefore neuronal death. The same team reported a markedly reduced activity of mitochondria complex I and II as a consequence of iron starvation , and Galy et al.  reported that correct mitochondria iron supply requires IRP2 in mouse liver. All these data indicate that an important function of IRP2 is to control mitochondrial iron homoeostasis, thereby preventing iron starvation. Our work integrates this view, identifying a novel mechanism of IRP2 regulation, mediated by miR-29 that contributes to the prevention of iron-induced mitochondrial dysfunction.
A direct relation between aging and iron homeostasis was reported also by Klang et al. , showing that dietary iron supplementation significantly accelerates the onset of aging-related phenotypes, reduces the lifespan expectancy and increases the age-dependent protein aggregation in C. elegans. Strikingly, TCA cycle and oxidative phosphorylation proteins are the most enriched proteins in the iron-induced aggregates. Conversely, the sponge-29 lines exhibited up-regulation of the same categories at the transcript level. Overall, these data suggest two important considerations: (1) the transcriptional up-regulation of TCA cycle and oxidative phosphorylation proteins in response to miR-29 loss-of-function represents a compensatory response to iron-induced damage of mitochondrial protein. Up-regulation of these categories is therefore a marker of compromised mitochondrial functionality and of accelerated aging. Consistently, Baumgart et al.  showed that increased expression of oxidative phosphorylation genes (in particular those of complex I) negatively correlates with killifish lifespan. (2) Iron accumulation compromises mitochondrial activity, corroborating the observation that age-dependent iron accumulation occurs primarily in the mitochondria and that miR-29 might promote mitochondrial integrity through regulation of iron homeostasis.
All experiments were performed on group-house N. furzeri of the MZM-04/10 strain. The fish used were raised in 35-L tanks at 25 °C and were fed two to three times a day with frozen Chironomus larvae or living nauplii of Artemia salina, depending on size. Eggs were collected by sieving the sand with a plastic net and kept in wet peat moss during developmental processes and diapauses. Embryos were hatched by flushing the peat with tap water at 16–18 °C. Embryos were scooped with a cut plastic pipette and transferred to a clean vessel. Fry were fed with newly hatched Artemia nauplii for the first 2 weeks and then weaned with finely chopped Chironomus larvae.
All experiments were performed on the Ab strain. Fish were maintained at 28 °C under continuous flow in zebrafish facility with automatic control for a 14-hour light and 10-hour dark cycle (Zebtech system). To generate embryos for injection, male and female fish were placed the night before injection in a 1-L fish tank with the inner mesh and divider. Zebrafish embryos were obtained from natural spawning by removing the divider and light stimulation.
Vector design and generation of transgenic lines
For the generation of all transgenesis vectors, we used multisite gateway technology. Design of vector kif5aa:eGFP-sponge-29: mir-29 sponge consisted of seven repetitions of mir-29 complementary sequences with a mismatch of four nucleotides immediately after the seed sequence. The sponge sequence was previously chemically synthetized by Eurofin (Milan) then cloned in the 3′ entry p3E-polyA using the restriction site BamHI. A 3,094 kb zebrafish kif5aa promoter region (Source: ZFIN; Acc:ZDB-GENE-070912-141) was amplified by PCR from genomic DNA (from –2969 to +125 bp including a small portion of the first exon, before the ATG), using primers Kif5aa-SalI f: (5′-gtcgacGTTGTCCAGCACGGATGTATAGGTA-3′) and Kif5aa-XmaI r:(5′-cccggg-ATAGCGGGGCAGAGGACGGCAG-3′) and cloned into gateway 5′-entry p5E-MCS. Then, the multisite gateway recombination reaction was performed as described in the Invitrogen Multi-Site Gateway Manual, an equimolar amount of entry vectors (20 fg of each; p5E-kif5aa, pEM-EGFPCAAX, and p3E-sponge-20-SV40pa) and destination vector (pDESTol2CG2) were combined with LR Clonase II Plus enzyme mix. For the generation of actb2:eGFP-sponge-29 vector was used as 5′entry p5-bactin2 (from Tol2kit v1.2) together with the other plasmids following the protocol mentioned above. All these vectors also contain the eGFP reporter gene driven by the zebrafish cardiac myosin light chain (cmlc2) promoter. All vectors generated were extracted and purified using Qiagen plasmid midi kit (toxin free). Eggs were harvested and injected at zygote stage as described in the following protocols ( and  for N. furzeri and D. rerio microinjections, respectively). For microinjection borosilicate microcapillaries were used. Capillaries were pulled with a micropipette puller (P97, Sutter Instrument). The needles were filled with 2 μL of water solution containing 20–30 ng/μL of plasmid DNA, 20–30 ng/μL of Tol2 transposase mRNA, 0.4 M KCl, and 1% phenol red as visual control of successful injections. Embryos were injected with approximately 2 nL of mix solution and the drop volume was estimated under a microscope using a calibrated slide. Injections were performed under the Nikon C-PS stereoscope. F0 fishes were screened under fluorescence microscope at 3–4 days after hatching (N. furzeri) and at 24 hpf for zebrafish larvae. Three different founders were selected for line establishment.
Ireb2 3′-UTR vectors assembly and mir-29 targeting validation
In order to experimentally validate Ireb2 as direct mir-29 target in fishes, 671 and 633 bp from Ireb2 3′-UTR of N. furzeri and D. rerio, respectively, were amplified by PCR from cDNA of both species (N. furzeri reference: Nofu_GRZ_cDNA_3_0193494, D. rerio reference: ZFIN; Acc:ZDB-GENE-051205-1) using the primers nfIreb2-3′UTR-BamH-F: (5′-ttcgggggatccCATGTTTGACTCTGAGAAGGAC-3′) and nfIreb2-3′UTR-BamH-R: (5′-ttcgggggatccGTTCTGTGCCCAGTTTGCCC-3′) for N. furzeri and DrIreb2-3′UTR-BamH-F: (5′-gtcacgC-GGATCCTCACATGGACCTCTGAACACC-3′) and DrIreb2-3′UTR-BamH-R: (5′-gatcggc-GGATCCCACAGCGAAAGTATCACAGCC-3′) for D. rerio and cloned in the 3′ entry p3E-polyA. Then p5E-CMV/SP6, pME-EGFPCAAX, p3E-Ireb2-3′UTR-polyA, and pDESTol2CG2 were combined using multisite gateway (see above). Finally, the plasmid producing fluorescence standard control was assembled combining p5E-CMV/SP6, pME-RFP, p3E-polyA and pDESTol2CG2. We renamed these plasmids as N.f CMV/SP6: eGFP-Ireb2-pA, D.r CMV/SP6: eGFP-Ireb2-pA and CMV/SP6: RFP-pA. For all of these reporters, in vitro transcription was carried out as described below. About 2 nL of solution containing 100 pg of egfp-Ireb2 sensor mRNA, 100 pg of RFP standard, 100 pg of Dre-mir-29a mimic or 100 pg of Dre-mir-29b mimic (Qiagen) was microinjected in the zygote stage embryos (for the control embryos the same mix was assembled without microRNA mimic). At 24 hpf, 30–40 embryos were collected from each experimental condition, dechorionated and dissociated according to Gallardo et al. . Dissociated cells were diluted in PBS 1×, loaded in the flow cytometer machine (FacsCalibur, Becton-Dickinson) and the eGFP/RFP fluorescence ratio was analyzed and quantified. For mmu-Ireb2 3′-UTR validation we used dual luciferase reporter assay system (Promega). Mmu-Ireb2 3′utr (transcript ID: ENSMUST00000034843) containing the putative mir-29 binding site was cloned in pMIR-REPORT™ luciferase reporter system (Termo Fisher) using the restriction enzymes SpeI and MluI. Mmu-mir-29b1/a precursor was cloned in CMV/SP6: RFP-Pa vector, downstream of RFP using the restriction enzyme MluI. Transfection on Hek293 was performed using lipofectamine 2000 (Invitrogen). CMV:RFP-mir-29b/c precursor-polyA-tail was co-transfected with pMIR-report and Renilla control vector following the manufacturer’s instructions. In the control experiment the same vector was co-transfected without the mir-29a/b1 precursor sequence. At 24 hours post transfection both Renilla and Firefly luciferase activity were measured using the luminometer (GloMax 96 microplate Luminometer w/dual injectors). Mutant vectors were generated using the QuikChange II XL Site-Directed Mutagenesis kit (Stratagene) according to the manufacturer’s protocol.
In vitro RNA and DIG-labeled probes synthesis
The Tol2 mRNA was transcribed from the pCS-TP plasmid whereas eGFP-Ireb2-3′utr and standard fluorescence control mRNAs were transcribed from plasmids: N.f CMV/SP6: eGFP-Ireb2-pA, D.r CMV/SP6: eGFP-Ireb2-pA and CMV/SP6: RFP-pA, respectively. All were previously linearized using NotI and purified with Wizard® SV Gel and PCR Clean-Up System (Promega). Then, 1 μg of each linearized plasmid was transcribed using the mMESSAGE mMACHINE SP6 kit (Ambion) according to the manufacturer’s protocol. For DIG-labeled probe synthesis, initially sequences were amplified by PCR from cDNA using a reverse primer carrying a T7 promoter sequence on its 5′ end; 200 ng of PCR product, previously purified with Wizard® SV Gel and PCR Clean-Up System (Promega), were directly transcribed using T7 enzyme (Fermentas) and digoxygenated RNTP mix (Roche) for 2 hours at 37 °C. The in vitro transcription mix was precipitated with 1/10 of volume of LiCl (5 M) and 2.5 volumes of isopropanol, than washed with 70% ethanol and finally resuspended in nuclease-free water and stored at –80 °C.
Total RNA extraction and RT-qPCR
Dissected tissues were immediately put in 500 μL of Qiazol lysis reagent and manually homogenized with pounder. Total RNA was extracted using miRneasy mini kit (Qiagen) according to the manufacturer’s protocol; 200 ng of each RNA extraction was retrotranscribed for cDNA synthesis using miScript II RT kit (Qiagen). qPCR was performed using Rotorgene 6000 (Corbet). PCR mix solutions were prepared using SsoAdvanced™ Universal SYBR® Green Supermix (Biorad) and 4 ng of cDNA for each sample as template. The relative gene quantification was calculated using the ΔΔCt method, as reference genes were used TBP, ACTB2, and GAPDH for N. furzeri, D. rerio, and mouse, respectively.
Histology and histochemistry
All the immunohistochemical procedures were performed on frozen tissue sections. Animals were killed with overdose of MS-222, brains were dissected and fixed in PFA 4%, washed in PBS 1× twice then equilibrated in sucrose 30% and embedded in Tissue-Tek OCT (Leica). Frozen tissues were cut with cryostat (Leica), 12- to 14-μm thick sections were immediately put on superfrost plus slides (Thermo Scientific) and dried in the oven at 55 °C for 1 hour. Sections were rehydrated in PBS 1× permeabilized with tritonX 0.3% and blocked in BSA 5%, goat serum 1%. Primary antibodies were all incubated overnight at 4 °C according to the following dilutions: Anti-HuC/D (1:50, Thermo Fisher Scientific Cat# A-21271 RRID:AB_221448), Anti-GFP (1:1000, Abcam Cat# ab32146 RRID:AB_732717), Anti-GFAP (1:400, Millipore Cat# MAB5324 RRID:AB_95211), Anti-S100 (1:400, Dako, zo311). Secondary antibodies coupled to Alexa Fluor dye (488, Molecular Probes Cat# A-11008 also A11008 RRID:AB_143165, 633, Molecular Probes Cat# A-21052 also A21052 RRID:AB_141459) were incubated for 2 hours at room temperature (RT) (1:500).
In situ hybridizations were performed according to  with minor modifications. Slides were incubated with proteinase K for 10 minutes at RT (1:80000; Fermentas, 20 mg/mL), post-fixed with PFA 4% for 20 minutes at RT, and then incubated with a digoxigenin (DIG)-labeled probes (60 °C, ON). Immediately before incubation probes were put in hybridization solution denaturated at 98 °C for 3 min. Sections were washed with SSC-2× twice at 60 °C for 15 min each, then with SSC-0.5× three times for 10 min each time at RT and incubated with anti-Dig AP Fab (Roche; 1/2000 4 °C ON) in blocking solution (Roche). The day after, slides were placed for 20 min RT in TMN solution (Tris-MgCl2-NaCl buffer) with the addition of levamisole 1 mM (Sigma) in order to inhibit endogenous alkaline phosphatase and transferred in Fast red solution (Roche tablets). The staining was constantly monitored under epiflourescence microscope and blocked by washing in PBS 1×. Images were acquired using epifluorescence microscope (Nikon, Eclipse600) or confocal microscope (Leica DMIRE2).
For lipofuscin detection, unstained sections were deparaffinized and mounted using a water-based medium within DAPI (Invitrogen). An important property of lipofuscin is its broad autofluorescence, which was acquired using a Zeiss apotome(2) at an excitation wavelength of 488 and 550 nm as well as under UV excitation following DAPI staining. Images were analyzed using ImageJ, thresholds were determined by operator and applied to images to discriminate lipofuscin granules from background signal. The area occupied by granules was expressed as a percentage of total image area analyzed.
Iron staining (Perls staining)
Iron staining was performed according to  with minor modifications. Briefly, brains were dissected and fixed in PFA 4% and embedded in paraffin. After this, 5- to 7-μm thick sections were deparaffinized and immersed in 4% ferrocyanide and 2% HCl for 1 hour at 37 °C, then immersed in methanol containing 0.5% H2O2 and 0.01 NaN3 for 30 min at RT, and finally immersed in 0.1 M phosphate buffer containing DAB 0.05% and 0.005% H2O2 for 30 min. Sections were counterstained with hematoxylin, dehydrated and mounted.
Non-heme iron quantification
Iron quantification was performed according to the protocol published by . Extracted tissues were placed in an empty 1.5 mL tube, previously weighed, and were weighed again in order to precisely determine wet tissue weight. Homogenates were prepared in high-purity water. Briefly, 100 μL of homogenate tissues were combined in a new 1.5 mL tube with an equal volume of protein precipitation solution (1 N HCl, 10% trichloroacetic acid) and placed in thermoblock at 95 °C for 1 hour. Tubes were cooled to RT for 10 min and were then centrifuged for 20 min at 4 °C; 100 μL of the supernatant was collected from each tube sample and combined with an equal volume of chromogenic solution (Ferrozine 0.5 mM, ammonium acetate 1.5 M and Tioglicolic acid 0.1%). After 30 min, absorbance was measured at 562 nm using a spectrophotometer. Standard curves were prepared using 0, 0.5, 1, 2, 4, 8, 10, and 20 μg/mL of iron standard solution (Sigma).
Iron and drug delivery
Fish were previously anesthetized with Trichaine methanesulfonate and weighed. A single dose respectively of 350 μg/g body weight iron dextran (Sigma, 100 mg/mL), 30 μg/g body weight deferoxamine (DFO, Novartis), and 50 μ/g body weight 4-OH-Tempol (Sigma) was injected intraperitonealy. Injections were performed under a stereomicroscope (Leica) using Amilton 10-μL syringes, control animals were sham-injected with saline solution. At 4, 8, 12, 24, 48, and 72 hours after injection brains were removed from anesthetized animals and put in a previously weighed tube for iron measurement or immediately frozen in liquid nitrogen for the following RNA extraction.
Samples were lysed in RIPA-buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, 1% Triton X-100, 0.1% SDS, 0.5% deoxycolic acid) containing protease inhibitor (Complete Protease Inhibitor Cocktail Tablets, Roche Diagnostics) and centrifuged at 12,300 rpm for 10 min at 4 °C and supernatants were collected. Total protein concentration was determined by BCA protein assay (Pierce). Aliquots of homogenate with equal protein concentrations were separated in 10% acrylamide gel and transferred to nitrocellulose membranes by mini trans-blot (Bio-Rad). The membranes were blocked with milk (5% w/v) and probed with appropriate primary and secondary IgG-HRP conjugated antibodies (Millipore). Enhanced chemiluminescence detection system (GE Healthcare) was used for developing on autoradiography-films (GE Healthcare). Densitometric quantification was performed using ImageJ and normalized to the relative amount of α-Tubulin and expressed as n-fold of control samples. In this study the following antibodies were used: Anti-IRP2 (1:1000, Abcam, ab181153), Anti-TFRC (1:500, Abcam Cat# ab84036 RRID:AB_10673794), Anti-FBXL5 (1:500, Abcam Cat# ab68069 RRID:AB_1140312), α-TUB (1:20000, Sigma-Aldrich Cat# T5168 RRID:AB_477579); secondary HRP antibodies: goat-anti rabbit (1:2000, Santa Cruz Biotechnology Cat# sc-2004 RRID:AB_631746), goat-anti mouse (1:2000, Santa Cruz Biotechnology Cat# sc-2005 RRID:AB_631736).
Cell culture and iron exposure
Following a previously published protocol , murine ES cell line E14Tg2A was differentiated into cortical neurons. In brief, mouse embryonic stem cells (mESC) were cultured in a chemically defined medium on laminin-coated culture dishes for 20 days. mESC-derived neurons were then treated with iron dextran (50, 100, and 200 μg/mL) and Iron(II) sulfate (25, 50 and 100 μM) in Neurobasal Medium (Thermo Fisher Scientific) supplemented with B27 (Thermo Fisher Scientific) for 72 h, medium was changed daily. Subsequently, two wells of a six-well plate were pooled for each thesis; RNA extraction and PCR analysis were carried out from three biological replicates.
RNA-sequencing and analysis
RNA was extracted using Quaziol (Qiagen). Library preparation using Illumina’s TruSeq RNA sample prep kit v2 and sequenced on Illumina HiSeq2500, 50 bp single-read mode in multiplexing obtaining approximately 50–40 mio reads per sample. Read mapping was performed using Tophat 2.0.6  and featureCounts v1.4.3-p1  using the N. furzeri genome  or Zv9.73 as references. Differential gene expression analysis was performed using R software, for DEGs identification was used the statistical test of edgeR package . For multiple testing correction a FDR of < 0.05 was chosen. KEGG pathway analysis was performed using the software Web-based gene set analysis tool kit (WebGestalt)  using an FDR < 0.05.
Annotation of small RNAs
The processing and annotation of small RNA-Seq raw data was performed using an R 3.0.2 and ShortRead Bioconductor package .
Quality filtering: eliminated all the reads containing an “N”;
Adapter trimming: used function trimLRPatterns(), allowing up to two mismatches and using as adapter sequence “TGGAATTCTCGGGTGCCAAGGAACTCCAGTCAC”;
Size filtering: removed all the reads with length < 18 and > 33 nucleotides.
Alignment against the reference (miRBase 20; ) with up to two mismatches. In this step the reference used was the mature sequence of microRNAs for the analyzed organism (except for N. furzeri, for which D. rerio reference was used). Each read was aligned using these criteria with Bowtie 1.0.0 (settings:-q --best –norc);
The remaining reads, which could not align in the previous step, were used as reference for a second alignment step. In this case, the annotated mature microRNAs were aligned against the reads;
The information obtained in the two alignment phases was conveyed in one single table, containing a list of all the retrieved sequences and their relative counts.
Enrichment analysis of miR-29 binding sites
Target predictions were obtained using MiRanda (version: august 2010) with default parameters .
Enrichment analysis was performed to test the overrepresentation of specific microRNA targets in the identified transcript clusters of genes with different expression profiles with age . For this purpose, three different tests were used: Binomial test, Fisher’s test and Hypergeometric test. Only microRNAs having a Hochberg’s corrected P value < 0.05 in the three tests were considered as having their targets overrepresented in one cluster.
We thank Matthias Platzer for access to the sequencing facility and support through this project, Letizia Pitto for access to the zebrafish fishroom, Uwe Menzel for help in analysis, Mirko Mutalipassi for technical assistance in the fishroom, Marco Matteucci for access to the histology facility, and Nicola Carucci, Giovanna Testa and Caterina Rizzi for sharing mouse samples.
This work was supported by internal grant of Scuola Normale Superiore and a grant of the Bundesamt für Bildung und Forschung (JenAge; BMBF, support codes: 0315581A).
Availability of data and materials
Data from  are deposited in NCBI’s Gene Expression Omnibus (GEO) under the accession number GSE52462. RNA-seq data generated for this study were deposited under the accession number GSE79825. Raw PCR data are included in Additional file 11.
RR and AC designed the experiments; RR, LD, VA, and ETT performed the experiments; MG performed the RNA-seq; RR, MT, LP, MB, MG, and AS analyzed the data; RR and AC wrote the paper with contributions from all other authors. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
Procedure for animal husbandry and breeding were authorized by the Italian Ministry of Health (Aut N. 96/2003-A and n°297/2012-A). Animal experiment procedures were specifically approved by the local ethical committee and the Italian Ministry of Health (Aut. N. 1314/2015-PR). Moreover, all researchers who took care of the animals and performed the experiments were appropriately trained by attending specific courses.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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