Like the charge process of capacitor, the N‐doped carbon can capture the photogenerated electron of CISe, and the strong interfacial coupling between CISe and N‐doped carbon can modulate the charge migration and separation. The optimized the CISe/N‐C photoanode achieves a maximum photocurrent of 4.28 mA cm−2 at 1.23 V versus reversible hydrogen electrode (RHE) in neutral electrolyte solution under AM 1.5 G simulated sunlight (100 mW cm‐2), which is 8.4 times higher than that of the CuInSe2 photoanode (0.51 mA cm‐2). And a benefit of the strong electronic coupling between CISe and N‐doped carbon, the charge transfer rate is increased to 1.3–13 times higher than that of CISe in the range of 0.6–1.1 V versus RHE. The interfacial coupling effects on modulating the carrier transfer dynamics are investigated by Kelvin probe force microscopy analysis and density functional theory calculation. This work provides new insights into bulk phase carrier modulation to improve the performance of photoanode for PEC water splitting.Regulating the charge migration and separation in photoactive materials is a great challenge for developing photoelectrochemical (PEC) applications. Herein, inspired by capacitors, well‐defined CuInSe 2/N‐doped carbon nanorod arrays are designed as the reservoirs to capture and store the photogenerated electrons of CuInSe2 by the N‐doped carbon, and the strong interface coupling can pave a specific “bridge” between components to promote carrier migration and separation for PEC water splitting.Inspired by capacitors, well‐defined CuInSe The construction of heterojunctions by coupling different materials with diverse energy level structure including type II heterojunction, Z‐type heterojunction, and S‐type heterojunction have been regarded as one of the most promising strategy to improve the electron‐hole separation, and affording a specific redox potential for the catalytic reaction.  However, it is still faces serious challenges originating from the unreasonable energy band structure, and large interface energy resistance, which inhibit the spontaneous migration and separation of photogenerated carriers. Accordingly, it is highly desirable to design a suitable interface structure with spontaneous carrier migration for efficient solar water splitting.Photoelectrochemical (PEC) water splitting for hydrogen generation is of great significance in the field of carbon‐neutral technology for zero‐emission renewable energy evolution. 1, 22S4, CuInSe2 have emerged as one of the most promising candidates for photocatalytic water splitting. CuInSe2 (CISe) is a typical n‐type semiconductor with adjustable bandgap of 1.0–2.0 eV. The maximum value of the conduction band position is as high as about ‐1.0 eV, which endows the strong reducing capacity for the photogenerated electrons. The bulk carrier recombination in CISe seriously limits its photo‐to‐electric conversion efficiency. The strategy of coupling suitable materials with CISe to build the interfacial heterojunction is thought to be a feasible way to regulate the carrier spontaneous migration. Carbon material with π‐conjugated structure presents an attractive electron mobility, tunable electronic local structure, and good catalytic economical applicability. Some pioneer composites including activated Carbon‐TiO2 carbon spheres‐BiVO4, N‐C/In2O3‐CuO, In2Se3@N‐C  have been proposed for improving their photocatalytic performances. As electron acceptor, the carbon material could capture the photoinduced electrons, whereas, the lack of a tight interaction between the carbon material and the semiconductor interface can weaken the ability to capture electrons due to the high energy barriers at the interface. The continuous distribution of carbon in the composite and their interface contact are the current big questions. The poor interfacial contact is like stacking a “wall” between the composites, seriously preventing the trajection of charge flow. The intimate interface combination, such as in strong chemical bonds, could pave a specific “bridge” to promote carrier migration between components, and facilitate modulating the interface electronic structure and space charge density distribution. We also have reported that engineering the heterogeneous interfaces via in‐situ reaction protocols could largely decrease the phase boundary thermal resistance for the migration and separation of electron and holes. To this end, constructing carbon continuous distribution in CISe with intimate interfacial contact might be an effective approach to regulate the charge spontaneous migration and separation for highly efficient PEC water splitting.Ternary metal selenide or chalcogenide semiconductors, such as ZnInlectrons.7, 8 It works as follows: the carbon electrode adsorbs electrons in the charging stage, and then release electrons in the discharging stage. Inspired by this, we reported the CuInSe2/N‐doped carbon (CISe/N‐C) nanorod arrays by using the N‐doped carbon as the reservoirs to capture and store the photogenerated electrons of CISe. The strong interfacial coupling between CISe and N‐doped carbon could facilitate the migration and separation of electrons and holes. The typical CISe/N‐C photoanode shows a maximum photocurrent density of 4.28 mA cm‐2 at 1.23 V versus reversible hydrogen electrode (RHE) in neutral electrolyte solution under AM 1.5 G simulated sunlight (100 mW cm‐2), an 8.4 times enhancement relative to that of the CISe sample. In addition, the photo‐stability is also greatly improved in the redox electrolyte solution, 98.11% initial value is maintained even after 3600 s continuous light illumination at an applied potential of 1.0 V versus RHE. As compared to the similar photoelectrodes, the activity of the CISe/N‐C sample is superior to the most reports in recent literature. The prominent performances of the CISe/N‐C photoanode can be ascribed to the high carrier separation efficiency, low interfacial resistance driven by the berried continuous electrons reservoirs, and the strong interfacial coupling interactions, the charge separation mechanism of which is understood from the electrochemical analysis and the density functional theory (DFT) simulation. This work might be important for understanding the interfacial charge migration within nanostructured photoelectrodes boosting the high PEC applications.Electric double‐layer capacitor is an efficient energy storage device for the uneven power demand in sustainable energy systems.22 It 2Figure From TEM images . The Raman spectra . As shown in Figure s Figure , it can s Figure , a clears Figure  indicated Figure  exhibit Figure2 (JCPDS 40‐1487). In Cu 2p spectra  and Se  in CISe/N‐C also exhibit a slight positive shift. It might be aroused by the carbon component, which adsorbs the electron cloud of CISe to its surface, and resulting in the adjacent atoms shift to a high binding energy position. The high resolution C 1s spectra  in CISe/N‐C implies a strong interfacial coupling effect between CISe and N‐doped carbon.The microstructures of CISe, CISe‐C, and CISe/N‐C samples are characterized by X‐ray diffraction (XRD), X‐ray photoelectron spectroscopy (XPS) analysis. As shown in a Figure , the Cu a Figure  are compa Figure  can be a2SO4 electrolyte under 1.5G illumination with a standard three‐electrode system. As shown in Figurein‐situ formed carbon layer, the photocurrent density is only about 1.66 mA cm‐2 at 1.23 V versus RHE . However, for the typical CISe/N‐C photoanode, the value gets to as high as 4.28 mA cm‐2 at 1.23 V versus RHE and the onset potential also negatively shifted, the value is 8.4 times higher than that of the pure CISe photoanode. Meanwhile, the current density of CISe/N‐C photoanode is also higher than that of CISe in dark  is calculated by the open‐circuit photovoltage measurements in dark as shown in Figure τ value of the CISe/N‐C photoanode is significantly prolonged than those samples, indicating that the interfacial coupling interactions promote the carrier transfer. The stability curves are also used to evaluated the activity of the as‐prepared photoanodes. As seen from Figure ‐2) test, further demonstrating that the interfacial coupling protocol is a promising way to improve the stability. In addition, CISe/N‐C photoanode still maintains a current retention rate of about 88% even prolonging to 3 h . The ctR values can be calculated from the equivalent circuit model based on the EIS data  spectra is performed as shown in absJ obtained from 1.5 G solar spectrum integration:absJ is the photon adsorption rate, and q is the charge of an electron, h is the Plank constant, c is the light speed, λϕ is the photon flux of the AM 1.5 G solar spectrum, and absη is the light absorption efficiency. As shown in Figure sepη) of the CISe is only 29.4% at 1.23 V versus RHE, whereas, the value is as high as 72.21% for the CISe/N–C photoanode. It confirms that the N‐doped carbon as electron reservoir and the strong interfacial coupling effect plays a key role in the migration and separation of charge carriers. The surface injection efficiency of the electrodes also has been evaluated as displayed in Figure injη) of the CISe/N–C electrode can reach 92.12% at 1.23 V versus RHE, which is 3.4 times as compared to the pure CISe electrode (26.97%). Cyclic voltammetry (CV) tests are further used to confirm that the N‐doped carbon possesses the ability to extract electrons as displayed in Figure ‐1), and is obviously larger than that of pure CISe electrode in the potential region, indicating that higher capacitance can be obtained in CISe/N–C than in CISe under light irradiation. Furthermore, the capacity of the photoelectrode can be calculated based on the following equation:I is the current density of cyclic voltammetry, ψ is the potential range, S is the working area of photoelectrode, v is the scan rate, ΔV is the potential window. The photocapacitance of CISe/N‐C is 0.57 mF cm2 at 0.03 V s‐1, which is 14.6 times higher than that of the CISe (0.039 mF cm2). The large capacitance means that the N‐doped carbon can capture more photoinduced electrons from CISe. Under dark conditions, the capacitance of CISe/N‐C is obvious higher than that of CISe, which reflects that the electron spontaneously migrate to the N‐doped carbon layer  curves of the electrodes at different potentials is shown in Figure transk value of CISe/N‐C electrode is 1.3‐13 times higher than that of CISe electrode at the potential range of 0.6–1.1 V versus RHE, indicating significantly promoting the bulk charge transport kinetics by the strong interfacial coupling between CISe and N‐doped carbon. The recombination rate constant (reck) curves  as shown in s Figure  graduallFigure2 with chalcopyrite structure is shown in Figure  Three situations of substitution sites are predicted: surface Se atoms  calculation as e Figure  confirmsFigure It can be seen that the degradation efficiency of DOX for CISe/N‐C sample is as high as 94.2% within 90 min under visible light illumination  value of rate‐determining step (RDS) for the naked CISe from OOH* to O2 is as high as 1.85 V, which inhibits the release of oxygen. After the introduction of N‐doped carbon layer, the RDS of CISe/N‐C changes from OH* to O*, indicating that it is favorable for O2 production. And the η value is obviously reduced to 1.31 V, further indicating that the strong interfacial coupling effect promotes the OER activity of photoanode. The catalytic reaction mechanism is proposed as shown in Figure The antibiotic contaminant Adriamycin hydrochloride (DOX) is used as a model pollutant to evaluated the photoactivity of CISe/N‐C sample as shown in n Figure . Howevern Figure , the ints Figure  and the s Figure  further l Figure . The O2 3‐2 at 1.23 V versus RHE in neutral electrolyte solution under AM 1.5 G illumination. DFT calculations suggest that interfacial Cu‐N bonds between CISe and N‐doped carbon efficiently suppress carrier recombination for PEC water splitting. This work provides a rational protocol to modulate the bulk charge migration and separation by interfacial coupling for obtaining highly efficient photoelectrodes.In summary, well‐defined CISe/N‐C nanorod arrays have been successfully synthesized via a two‐step method. Like capacitor, the photogenerated electrons of CISe can be stored by the adjacent N‐doped carbon, and the strong interfacial coupling creates direct charge transfer channels between CISe and N‐doped carbon for the charge migration and separation. The optimized CISe/N‐C sample exhibits a maximum photocurrent of 4.28 mA cm4 First, 0.193 g Cu(NO3)2·3H2O, 0.481 g In(NO3)3·xH2O, 0.3 g PVP, and 0.185 g PTA were dissolved in a mixed solvent (DMF: EG: H2O=2: 2: 1) and stirred for 30 min. Then, 530 µL HNO3 was slowly added to the solution. The obtained solution was transferred into a 100 mL Teflon‐lined stainless‐steel autoclave with a piece of clean FTO and maintained at 120 °C for 12 h. After cooling down to the room temperature, the samples were washed with deionized water and ethanol for several times, and dried at 60 °C overnight in air.Cu/In‐MOF were prepared with some modifications.35 Fir‐1 in Ar atmospheres. The synthesized samples were labeled as CISe/N‐C(x), x represents the time. Specially, CISe/N‐C(6) are recorded as CISe/N‐C.The obtained Cu/In‐MOF nanoarray and 0.1 g Se powder were placed in the tube furnace with the Se powder in the atmosphere inlet. The temperature was set to 500 °C for 4‐7 h with the increasing rate of 2 °C·min3)3·xH2O, 0.024 g Cu(NO3)2·3H2O, and 0.0158 g Se powder were dissolved in 20 mL ethylenediamine and 20 mL anhydrous ethanol, then stirring for 60 min. The obtained solution was transferred into a 50 mL Teflon‐lined stainless‐steel autoclave and maintained at 200 °C for 24 h. After cooling down to the room temperature, the samples were washed with deionized water and ethanol for several times, and dried at 60 °C overnight in air. The samples were heat‐treated in argon at 500 °C for 6 h. Specifically, the obtained sample was dispersed in ethanol to form a solution of 10 mg mL‐1. Then 0.15 mL was coated on the conductive surface of the glass slide, with a deposition area of about 1 cm × 1 cm. Spin coating speed 800 rpm min‐1, spin coating time 30 s, then dry in vacuum at 60 °C. The obtained porous CISe film was exhibited in Figure 0.03 g In. AM 1.5 G simulated sunlight illumination (100 mW cm‐2), which was provided by a solar simulator. Electrochemical impedance spectroscopy (EIS), and intensity‐modulated photocurrent spectroscopy (IMPS) were all measured by Zahner IM6 , in which IMPS was excited by monochromatic light at the excitation wavelength of 455 nm. The stability test was measured at 0.25 m Na2S and 0.35 m Na2SO3 (pH 12.8).The performance of PEC was measured on the electrochemical workstation CHI 660E  using a three‐electrode system . The electrolyte was 0.5 2SO4 and a 300 W Xe lamp (100 mW cm‐2) at an applied bias of 1.2 V versus RHE. The electrolyte was previously purged with Ar for 30 min to remove any dissolved oxygen and cooling system maintained a 4 °C temperature in the reaction device. The PEC rate was determined by measuring the O2 created at 30 min intervals.Oxygen evolution on photoanodes was measured using a sealed quartz reactor equipped with a typical three‐electrode cell connected to an Ar cycle and a cooling device. In this cell, 0.5 M NaThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


Many mechanisms have been proposed to explain acute antidepressantdrug-induced activation of TrkB neurotrophin receptors, but severalquestions remain. In a series of pharmacological experiments, we observedthat TrkB activation induced by antidepressants and several otherdrugs correlated with sedation, and most importantly, coinciding hypothermia.Untargeted metabolomics of pharmacologically dissimilar TrkB activatingtreatments revealed effects on shared bioenergetic targets involvedin adenosine triphosphate (ATP) breakdown and synthesis, demonstratinga common perturbation in metabolic activity. Both activation of TrkBsignaling and hypothermia were recapitulated by administration ofinhibitors of glucose and lipid metabolism, supporting a close relationshipbetween metabolic inhibition and neurotrophic signaling. Drug-inducedTrkB phosphorylation was independent of electroencephalography slow-waveactivity and remained unaltered in knock-in mice with the brain-derivedneurotrophic factor (BDNF) Val66Met allele, which have impaired activity-dependentBDNF release, alluding to an activation mechanism independent fromBDNF and neuronal activity. Instead, we demonstrated that the activemaintenance of body temperature prevents activation of TrkB and othertargets associated with antidepressants, including p70S6 kinase downstreamof the mammalian target of rapamycin (mTOR) and glycogen synthasekinase 3β (GSK3β). Increased TrkB, GSK3β, and p70S6Kphosphorylation was also observed during recovery sleep followingsleep deprivation, when a physiological temperature drop is knownto occur. Our results suggest that the changes in bioenergetics andthermoregulation are causally connected to TrkB activation and mayact as physiological regulators of signaling processes involved inneuronal plasticity. A core molecular mechanism of plasticity is the signaling oftropomyosin-related kinase B (TrkB), which acts as the cognate receptorfor the brain-derived neurotrophic factor (BDNF).6 Subsequent research suggested thatketamine induces rapid BDNF translation and release.7 Certain drugs, like amitriptyline and 7,8-dihydroxyflavone, havealso been proposed to act as direct agonists of TrkB.9 However, as many in vitro studies have proven unreliable in demonstratingconvincing pharmacodynamic interaction of the drugs and TrkB receptor,there have been calls to reevaluate whether these drugs actually bindto the receptor in vivo at all and whether the observed downstreamsignaling is initiated in a canonical manner.12 Another morerecent hypothesis suggests that antidepressants facilitate neuronalresponsiveness to BDNF by binding to a novel transmembrane site ofTrkB.13 Casarotto and colleagues proposethat rapid-acting antidepressants bind to TrkB more readily than traditionalantidepressants, which require chronic administration and accumulationin the brain tissue in order to reach TrkB signaling-promoting concentrations.However, earlier findings demonstrate that the intraperitoneal administrationof conventional antidepressants prominently activates brain TrkB receptorsrapidly within an hour5 and without any involvement ofBDNF.12Several mechanisms have been proposedto govern the antidepressant-inducedTrkB activation. Initially, chronic administration of conventionalantidepressants was shown to enhance BDNF expression in several brainareas.2O, “laughing gas”)14 and flurothyl—considered “a chemical electroconvulsivetherapy” (ECT),15 as it producesepileptiform activity and significant electroencephalography (EEG)slowing during the subsequent postictal state—converge in activatingTrkB signaling only after their acute pharmacological effects havedissipated.16 Although both flurothyl andN2O are eliminated from the body within minutes and haveno active metabolites, TrkB becomes and remains phosphorylated longafter the drug delivery.16 These findingssuggest that the treatments render TrkB active through a mechanismthat does not involve activity-dependent BDNF release and/or directbinding of the drug ligand to TrkB.To complicate the interpretationof past research further, theeffects of some clinically effective antidepressants are problematicto explain using the principles of conventional receptor pharmacology.For example, according to our recent findings, nitrous oxide ,16 a neurophysiological signature of deep sleep17 and reduced brain energy utilization18 and a biomarker associated with therapeuticefficacy of ECT.20 Notably, sleep deprivation (SD)—anothernonpharmacological rapid-acting antidepressant21—also increases SWA during the following bout ofsleep.22 Furthermore, there appears tobe a strong association with activation of TrkB signaling and thepotency of EEG suppression produced by several anesthetic agents,including putative rapid-acting antidepressant isoflurane25 and subanesthetic ketamine.26 Similarto earlier findings on NMDA receptor antagonists,27 we have observed in rodents how EEG slowing—inducedby subanesthetic ketamine, N2O, and flurothyl—emergesgradually after their acute effects begin to fade out.16 Therefore, these findings have raised the possibilityof an association between reduced electrophysiological activity andneurotrophic signaling.30TrkB activation inducedby flurothyl and N31 This response, besides beingcharacterized by EEG slowing and neurotrophic signaling, co-associateswith other physiological changes connected with deep slow-wave sleep:behavioral immobility,32 attenuated brainenergy expenditure,33 and reduced bodytemperature.34 Here, we present evidencefrom molecular studies in mice showing that a range of pharmacologicalagents possessing sedative properties can activate neurotrophic signalingirrespective of their primary pharmacological target. We further demonstratethat similar mechanisms may be associated with physiological processessuch as sleep, metabolism, and thermoregulation. This work providesnew insights into the physiological changes underlying TrkB activationand urges to examine the antidepressant signaling from the perspectiveof brain physiology instead of being solely a conventional ligand-receptorinteraction.Collectively, emergingevidence suggests that antidepressant-inducedTrkB activation may not involve a straightforward ligand release and/orreceptor binding mechanism but could instead be associated with somecomponents of the physiological state evoked by the pharmacologicaltreatment.35 Tothis end, we administered mice drugs commonly classified as stimulants,antidepressants, sedatives, and volatile anesthetics, in dosages commonlyutilized in the available literature. At 30 min after administrationor continuous inhalation anesthesia, we collected samples from themedial prefrontal cortex (mPFC) for western blot (A receptor modulator), medetomidine(α2-adrenergic agonist), hydroxyzine (H1 receptor inverse agonist), isoflurane (volatile anesthetic), gamma-hydroxybutyrate, and antipsychotics suchas clozapine  and chlorpromazine  activated TrkB signaling . Several drugsclassified as antidepressants also increased TrkB signaling or had a trend for increase (mirtazapine).However, antidepressants paroxetine and duloxetine, or stimulantssuch as amphetamine (dopaminergic stimulant) or atipamezole (α2-adrenergic antagonist) had no acute effect on TrkB signalingat the selected dose and time point. Notably, selective serotoninreuptake inhibitors (SSRIs) like fluoxetine are often considered nonsedativein the clinical context, but high acute doses commonly used in rodentantidepressant literature have shown to significantly reduce locomotoractivity.36 Moreover, tricyclic antidepressantslike amitriptyline are known to be sedatives.37 To screen for an association between sedation and TrkB phosphorylation,we tested selected compounds for their effects on locomotor activity andGSK3β.ern blot 1A. We foignaling 1A and it16 whereas isofluranedose-dependently suppresses neuronal activity, resulting in anesthesia.25 TrkB signaling was observed to be unaffectedin brain samples collected immediately after the flurothyl-inducedseizure, suggesting that the acute convulsive activity and the precedingexcitation, during which there should conceivably be more activity-dependentrelease of BDNF, do not have an immediate effect on the phosphorylationlevels of TrkB 45 or inhibiting complex IV46 andincreasing energy-consuming cellular processes47 (ketamine). The metabolomic profile after flurothyl seizure,on the other hand, suggests that the decrease in the metabolic rateis a result of homeostatic inhibition of the complex II (succinatedehydrogenase) in response to the preceding excitatory insult. A similarinhibitory mechanism has been recently described during mammalianhibernation.48To further understand the mechanism behind TrkB activation, we analyzedthe molecular signaling events after treatment with two volatile drugssharing a similar chemical structure but opposite pharmacologicaleffect: flurothyl and isoflurane. Inhalation of flurothyl vapor overa period of few minutes evokes a generalized seizure by progressiveexcitation of the brain, of TrkB 2A. Howev of TrkB 2A. Our p49 and a combination of metabolic inhibitors 2-deoxy-d-glucoseand mercaptoacetate (2DG + MA).50 Systemicdelivery of ATP slows down the TCA cycle through allosteric inhibitionof pyruvate hydrogenase,51 producing astate characterized by immobility52 andincreased slow EEG activity , after which a subsetof animals was allowed to enter recovery sleep in their home cage,monitored remotely for behavioral immobility and a sleeping posture.As expected, recovery sleep after SD increased the spectral powerof the slowest EEG bands, most notably in the SWA range . This suggests that the mere presence ofcortical SWA is not sufficient to explain the observed TrkB phosphorylation,and we continued to investigate whether the sedation-activated TrkBsignaling could be prevented by reversing other physiological changesassociated with deep sleep or sedation. To this end, we used medetomidine,an alpha-2 receptor agonist, due to its ability to induce a sleeplikestate coinciding with SWA and TrkB signaling,56 and amphetamine, which is known to augment EEG activity,57 wakefulness,58 andthermogenesis.59 We replicated the previouslyobserved medetomidine-induced upregulation of TrkBY816,GSK3βS9, and p70SK6T421/S424 in samplescollected from the PFC and hippocampus.16 Furthermore, we detected comparable signaling changes in both thesynaptosome preparations and total homogenates of the samples, suggestingthat the observed response is not isolated to the synaptic fraction. Pre-treatment with amphetamineabolished the medetomidine-induced increase in EEG delta power butdid not significantly affect TrkB phosphorylation in the mPFC , which were collectedto illustrate the occurrence of sedation-induced TrkB signaling throughoutthe brain in different structures. Together, these results furthersupport the hypothesis that SWA is not causally connected with TrkBphosphorylation. However, body temperature measurements recorded duringthe experiment suggested that while the effect on EEG was abolishedwith amphetamine pre-treatment, it had only a small effect on themedetomidine-induced decrease in the rectally measured core body temperature or an incubator maintained at an elevatedtemperature (37 ± 1 °C). Core body temperature was measuredrectally at 10 min intervals, and the mice were terminated for biochemicalanalyses at 30 min after administration. Again, medetomidine induceda progressive reduction in body temperature of the animals at roomtemperature, which was not seen in the heated animals . Remarkably, prevention of the medetomidine-induceddecrease in body temperature also reduced the phosphorylation of TrkBY816, GSK3βS9, and p70SK6T421/S424 .Homeothermic animals maintain a relatively constant body temperaturein a wide range of ambient temperatures by altering their metabolicrate. Consequently, the cerebral metabolic rate, for example, changeslinearly with the surrounding temperature and energy-consuming functionalactivity of the neurons.8 Westudied the acute effects of amitriptyline using a dose  used in previous preclinical antidepressant research.64 The treatment produced marked sedation and hypothermia in mice atroom temperature, accompanied by phosphorylation of TrkBY816, GSK3βS9, and p70SK6T421/S424 in themPFC samples . Thus, we screened selected drugs and treatments that have previouslydemonstrated robust TrkB activation, including 2DG + MA, chlorpromazine,isoflurane, and flurothyl, for their effects on the body temperatureand found that they all induced prominent decrease in either rectalor skin temperature when administered to animals housed at room temperature. We also repeated the experimentwith isoflurane anesthesia in a temperature-controlled setting andobserved a similar pattern of abolished TrkB phosphorylation whenthe body temperature was maintained . These observations question the widely accepted claims, accordingto which the effects of amitriptyline and various other antidepressantsor sedative-anesthetic drugs are mediated by direct pharmacodynamicaction with the TrkB receptor, suggesting instead a causal effectfrom their ability to impair energy metabolism, and consequently,lower body temperature.Next, we set to investigatethe role of temperature and metabolic rate in the antidepressant-inducedTrkB signaling. We decided to use the tricyclic antidepressant amitriptyline,as it has been claimed to be—among many other drugs—adirect agonist of the TrkB receptor. samples 4A. Akin  samples 4A, with 24 alluding insteadto a BDNF-independent transactivation mechanism. To test this notionfurther, we administered an acute dose of amitriptyline to adult micecarrying Met66Met mutation in the Bdnf gene, whichimpairs activity-dependent BDNF release.66 The magnitude of the TrkB signaling and thermoregulatory responsesinduced by amitriptyline were indistinguishable between the met66metBdnf and control mice   4B.67 as wellas mediating temperature-associated changes in the metabolic rate,68 we assessed the active phosphorylation of Srcin brain homogenates that showed increased TrkB phosphorylation. Indeed,SrcY416 phosphorylation was rapidly induced by amitriptyline,isoflurane, metabolic inhibitors 2-DG + MA, and during recovery fromSD and flurothyl seizure (S7). Conversely, thekinase phosphorylation in medetomidine- and amitriptyline-treatedanimals was reduced by warm ambient temperature, although the changewas not statistically significant with amitriptyline , whichis a well-established downstream target of BDNF-induced TrkB activation.69Finally, considering the role of Src familykinases in the neurotrophin-independentTrk receptor transactivation, seizure 4A and S7iptyline 4A. A non5 yet the underlyingmechanisms have remained enigmatic. Attempts to explain the effectsof antidepressants on TrkB signaling have revolved around canonicalprinciples of receptor pharmacology, with some studies suggestingthat all antidepressants, including structurally different amitriptyline,9 fluoxetine,13 and ketamine,13 directly bind to the receptor. Rodent studieshave also indicated that antidepressant-like effects and their associatedmolecular and structural changes are coupled to TrkB downstream signalingpathways, most notably the activation of mTOR and its effector P70S6Kand the inhibition of GSK3β.35 In this study, we show that the phosphorylation ofTrkB, P70S6K, and GSK3β is regulated in mice by various classicalantidepressants, as well as numerous sedative-anesthetic drugs lackingany established clinical value in the treatment of depression. Moreover,we demonstrate that the activation of neurotrophic signaling cascadeoccurs independently of any direct pharmacodynamic action during recoveryfrom a convulsion or in physiological sleep following sleep deprivation.The ability of antidepressants to acutelyactivate neurotrophicfactor receptor TrkB in rodents was established in the seminal observationsby Saarelainen et al.,71As suggested by the four key findings of this report, the TrkB-activatinginterventions appear to be connected by their capability of producingsedation and decreasing metabolic rate. First, a range of pharmacodynamicallydistinct sedative agents were found to activate TrkB irrespectiveof the drugs known for the clinical antidepressant effect. Second,flurothyl and isoflurane, despite their distinct mechanism of actionand timeframe of activating TrkB, led to a similar metabolomic profilethat suggested perturbed bioenergetics. Third, activation of TrkBsignaling was observed during a sedative-hypothermic state inducedby specific metabolic inhibitors, which are routinely used to modelhypothermia. Fourth, the activation of TrkB can be prevented by controllingthe ambient temperature to reverse the drug-induced hypothermia. Thisnovel hypothesis of a noncanonical drug-induced activation mechanismis reinforced by our results, showing that the antidepressant-inducedTrkB signaling is not compromised in animals with impaired activity-dependentBDNF release but instead can be readily prevented through the manipulationof ambient temperature, conceivably by its effect on body temperature,which is determined by the metabolic activity.72 and locomotor activity in rodents,36 conceivably reflecting its effect on bioenergetics.Small laboratory rodents spend a considerably higher proportion oftheir basal metabolic rate to maintain their body temperature, incomparison to humans; thus, clinically insignificant perturbationsto central and peripheral thermoregulatory mechanisms can have a considerablydifferent effect in preclinical studies,75 which are conductedat an ambient temperature far below the animals’ thermoneutrality.Since our screening was limited to a single dose of each drug andwas designed to address TrkB phosphorylation, rather than sedationand other complex interactions of physiology and environment, subsequentdose–response studies in a controlled experimental settingare warranted. Nevertheless, we found that the sedation induced byclozapine and amitriptyline, as measured by a decrease in locomotoractivity, was reflected in increased TrkB phosphorylation, whereasstimulants amphetamine and atipamezole did not alter the signaling.Similarly, increased TrkB signaling and decreased locomotor activityand body temperature were observed after the administration of metabolicinhibitors 2DG and MA. These findings are in line with previous studiesassociating TrkB activation induced by medetomidine, nitrous oxide,and ketamine with increased SWA in mice.26 Strikingly, we have not observed acute activation of TrkB signalingusing subanesthetic doses of ketamine, commonly used in antidepressantresearch, but instead with anesthetic doses that have been shown toelicit hypothermia.77From a pharmacological perspective, drugs that produced consistentTrkB activation belonged to the general categories of either sedative-anesthetics,metabolic inhibitors, or antidepressants and antipsychotics that havesedating properties at high doses. Out of drugs categorized as antidepressants,fluoxetine, mirtazapine, amitriptyline, and mianserin increased TrkB,p70S6K, and GSK3β phosphorylation, while duloxetine and paroxetinedid not. Mirtazapine, amitriptyline, and mianserin are generally consideredto have pronounced sedative properties and are sometimes used to treatinsomnia, while the SSRIs fluoxetine and paroxetine, and the selectiveserotonin and noradrenaline reuptake inhibitor (SNRI) duloxetine,are generally considered to be nonsedative. However, high acute dosesof fluoxetine have been shown to significantly reduce body temperature78 further research on the thermal dynamics of TrkB signaling and sleepcould perchance shed light on the putative physiological role of temperatureregulation in neuroplasticity and possibly in producing antidepressanteffects. Notably, recent studies have shown that brief therapeutichyperthermia can elicit antidepressant effects in depressed patients,79 which have been associated with the subsequentfacilitation of thermoregulatory cooling.80 Temperature-induced antidepressant-like effects have also been observedin rodents.81 As a limitation of this study,we used naïve mice and focused solely on characterizing thetemperature-dependent signaling phenomena. Future studies investigatingthe functional significance of the observed phenomena in animal modelsof depression, and in producing antidepressant-like behavioral outcomes,are warranted.While the functional roleof the observed phenomenon remains unclear,our findings implicate that TrkB activation occurs during naturaldeep slow-wave sleep, known to coincide with decreasing body temperature,as evidenced by our experiment using sleep deprivation. By using amphetamineto block medetomidine-induced increase in SWA and atropine to inducerobust cortical SWA, we demonstrated that SWA is not, however, inand of itself a sufficient causal explanation for the increased signaling.Instead, TrkB signaling induced by the antidepressant amitriptylineand sedative-anesthetics medetomidine and isoflurane was specificallyabolished by the active maintenance of body temperature. Given thatthe depth of sedation is dependent on ambient temperature and NREMsleep is accompanied by brain cooling,82 has been shown to rescue the brain from various insultsand is associated with significant physiological structural plasticity.84 The therapeutic effects of hypothermia are widely considered tobe mediated through attenuated energy expenditure, oxidative stress,and inflammation, with recent studies also highlighting the involvementof TrkB signaling. In particular, Peretti and colleagues have shownthat RNA-binding motif 3 (RBM3)—a major inducer of cold-inducedstructural plasticity and neuroprotection85—controls the phospholipase-Cγ signaling downstreamof TrkB.86 The authors used a combinationof pharmacological (adenosine monophosphate [5′-AMP]) and environmental(low ambient temperature) means to induce and maintain hypothermia,respectively, observing upregulated BDNF release and TrkB signalingboth in vivo and in vitro. In contrast to the considerably longer,up to 24 h-long time frames used in the previous experiments, ourfindings demonstrate that even an acute decrease in body temperaturecan upregulate TrkB signaling within minutes.The findings of this study may also provide furtherinsight intothe neurobiological mechanisms of therapeutic hypothermia. Hypothermia,among the oldest known neuroprotective treatments,87 Furthermore, we observed a concomitant reduction—rather thanan increase—of ERK phosphorylation, distinguishing the currentphenomenon from canonical BDNF-mediated activation of TrkB.89 This report therefore extendsour previous observations that support the hypothesis of BDNF-independentactivation of TrkB by antidepressants.24 While theprecise mechanism of the activation remains to be fully elucidated,one possibility is the involvement of Src family kinases, which havebeen previously associated with transactivation of the TrkB.67 Previous studies have shown that Src, as wellas several other targets associated with TrkB signaling (most notablyGSK3β), are indeed regulated by the metabolic milieu throughmechanisms such as oxidative stress and altered neuronal lipid environment.91This report contradictswith previous hypotheses, according towhich the acute effects of antidepressants on TrkB signaling are mediatedby a direct receptor-ligand interaction, or via BDNF release, dueto two major reasons. (1) The effect of amitriptyline on TrkB signalingis abolished if the hypothermic reaction is prevented by adjustingambient temperature. (2) There is an identical signaling responseseen in animals with genetically abated BDNF release or function.TA of 22 °C.92 Thus, themice grown and experimented with in a constant cold environment differin their phenotype, metabolism, and thermal responses from those raised,akin to humans, closer to their thermoneutral zone (∼30 °C).93 Further variability is introduced by the nonstandardizedtiming of experiments, as the thermoneutrality of laboratory rodentsundergoes circadian variation. Thus, it is conceivable that the availableliterature on TrkB signaling is significantly affected by varyingconditions related to animal housing group sizes, thermal, and aircirculation conditions.94 Moreover, previousstudies have demonstrated that chronic stress, used to study depression-likebehavior in rodents, modulates thermoregulatory cooling mechanisms,95 which may further influence drug effects. Currently,the reporting of these fundamental experimental factors is lackingin the pharmacological literature, and data regarding the thermalresponses produced by common psychopharmacological agents are verylimited.Beyond the implications to therapeutic mechanisms of variousdrugs,the findings of this report raise crucial questions regarding thereproducibility and translational value of the neuropharmacologicalresearch. Over a third of the energy expenditure of a mouse goes tomaintenance of body temperature at a standard laboratory In conclusion, by studying various antidepressantsand sedative-anestheticdrugs, we found that their propensity to activate TrkB receptor signalingis coupled to their ability to alter the thermal physiology in mice.Maintaining the animals at elevated temperatures during acute drugeffects was found to completely abolish the signaling previously associatedwith the drugs’ pharmacological action. Moreover, our preliminaryfindings suggest that analogous TrkB activation is observed duringphysiological sleep, uncoupling the effect from solely a pharmacologicaldomain. Most importantly, this report proposes a new hypothesis foracute antidepressant-induced TrkB activation by highlighting the roleof bioenergetics and thermoregulation in the modulation of neurochemicalsignaling. This notion raises critical questions about the mechanisticaspects of TrkB signaling and calls for more carefully controlledexperimental settings to re-evaluate the established understandingof drug-induced TrkB signaling by antidepressants and other treatments.Further study of these physiological processes may uncover novel waysto utilize such physiological adaptations in the treatment of neuropsychiatricconditions and recovery from brain insults.ad libitum. BDNF Val66Metmice were generated as previously described.66 Briefly, BDNF Val/Met mice were interbred, and the offspring weregenotyped by polymerase chain reaction (PCR) analysis of tail tip-derivedgenomic DNA. The experiment involving BDNF Val66Met mice was conductedin female BDNFVal/Val and BDNFMet/Met mice.The animal experiments were carried out in compliance with the EuropeanCommunities Council Directive of 22 September 2010 (Directive 2010/63/EU),according to the guidelines of the Society for Neuroscience and approvedby the County Administrative Board of Southern Finland (Licenses ESAVI/9793/04.10.07/2016and ESAVI/5844/2019).Unless otherwise stated, 10–16-week-oldC57BL/6JRccHsd mice  were used. Animalswere maintained under standard housing conditions  in filtered plastic cages, with wood shavings and accessto food and water available d-glucose , adenosine triphosphate ,amitriptyline-HCl , (S)-amphetamine-HCl, atipamezole-HCl , atropine sulfate chlorpromazine-HCl , (S)-duloxetine-HCl , fluoxetine-HCl , gamma-hydroxybutyrate sodium , hydroxyzine-HCl ,medetomidine-HCl , mercaptoacetate, mianserin-HCl , mirtazapine-HCl , paroxetine-HCl, and urethane . Clozapine  was dissolved in 0.1 M hydrochloric acid,adjusted to pH ∼7 with 0.1 M sodium hydroxide, and then dilutedto a concentration of 1.2 mg/mL with sterile saline. An equivalentvehicle solution was prepared without the active drug for clozapinecontrol animals.The following drugs were dilutedin isotonic saline and administered intraperitoneally (i.p.) in avolume of 10 mL/kg: 2-deoxy-24 Briefly, isoflurane anesthesia was induced using 2% isoflurane  and maintained under constant flow of 1.5% isoflurane.24 Sevoflurane anesthesia was induced using 6%sevoflurane  and maintainedunder 4.5%.96 Volatile anesthetics wereadministered in an induction chamber of a small-animal anesthesiasystem  containinga preheated pad to prevent hypothermia. Sham-treated control animalsreceived pressurized room air. Seizure was induced by injecting 10%flurothyl (in 90% ethanol) at a steady rate into a cotton pad placedinside the lid of an airtight Plexiglass chamber (13 × 13 ×13 cm) until the animals went into a myoclonic seizure. The lid wasremoved to terminate the seizure, after which the animals were movedto recover in their home cages. For control animals, 90% ethanol withoutflurothyl was injected to the pad as a sham treatment. All treatmentswere administered 3–7 h after the light onset (6 A.M.) in standardlaboratory conditions, with animals brought to the room to habituatefor at least 30 min before experiments.Isoflurane, sevoflurane, and flurothyl ether; Sigma-Aldrich) were administered as previously described.The locomotor activityof a group of animals was recorded after administration of amitriptyline–HCl,amphetamine–HCl, clozapine, or atipamezole–HCl. Controlanimals were injected with isotonic sterile saline or clozapine vehiclesolution. The treatments were selected from the array of pharmacologicalagents previously tested for their effects on TrkB signaling 1, and do16 Briefly, electrodes were implanted under isofluraneanesthesia using lidocaine (10 mg/mL) for local anesthesia and buprenorphine and carprofen  for postoperativepain care. Two epidural screw EEG electrodes were placed above thefronto-parietal cortex. A third screw was installed as the mountingsupport. Two silver wire electrodes were implanted in the nuchal musclesto monitor electromyographic activity (EMG). After a recovery period(5–7 days), animals were connected to flexible counterbalancedcables for EEG/EMG recording and habituated to recording cables forthree days. Recordings were conducted in the home-cages of the animals.The EEG and EMG signals were amplified (gain 5/10 K) and filtered with a 16-channelAC amplifier , sampled at 254 Hz or 70 Hzwith 1401 interface , and recorded and processed using Spike2 software . EEG power spectra were calculatedwithin the 1–50 Hz frequency range by fast Fourier transform. Oscillation powerin each bandwidth  was computed in 30–300-secondepochs from spectrograms (FFT size = 1024 points) for each animal.Representative sonograms were computed using a Hanning window witha block size of 512.EEG-recordings were performed as described.Animals were kept awake in theirhome cages at standard housing conditions for 6 h starting from lightonset (9 A.M.) by introducing novel objects or gentle handling wheneverthe animals began to display signs of sleepiness. Animals for biochemicalanalyses were euthanized using rapid cervical dislocation either immediatelyfollowing the sleep deprivation or after 15 min of recovery sleep.The entry to recovery sleep was determined for each animal individuallyusing a remote infrared camera based on their immobility and crouchedposture typical for sleep. For EEG studies of SD, the power spectrumof the wake baseline was continuously recorded for 24 h to establisha baseline, followed by a 6 h SD and 1.5 h long recovery sleep period.Corebody temperature was measured using small-animal rectal probe thermometers. The temperaturemeasurements, lasting less than 10 s, were performed by experiencedpersonnel in order to minimize the impact of handling stress on bodytemperature. For longitudinal analysis of body temperature, whole-bodythermal imaging was used to assess the surface temperature of theanimals. Thermal images were acquired using a forward-looking infrared(FLIR) P640 thermal camera , with a reported thermalsensitivity of 0.06 °C at 30 ° C and a reading accuracyof ±2%. The camera was equipped with a 45° field of view,19 mm focal length lens, and positioned perpendicular to the imagedplane above the recording chambers. Thermal data were acquired ata rate of one image per 30 s, for 3–5 min before and followingtimes after treatment initiation; 2-DG + MA receiving animals wererecorded for 50 min after injection; animals recovering from flurothyl-inducedseizure were recorded for 45 min after the end of convulsing; andanimals subjected to 1 and 20 min of isoflurane anesthesia were recordedfor 7 and 10 min, respectively. Images were analyzed using eitherFLIR Tools software (version 6.4.18039.1003), where the highest radiometricpixel temperature was manually acquired for each rodent cage/imageusing the rectangle tool or ThermaCAM Researcher Pro (version 2.10),where the rectangle tool was used to automatically acquire the highestpixel temperatures for each rodent cage/image.75 to account for sedation-associated hypothermia.An external thermometer placed on the incubator floor was used toconfirm the chamber temperature, recording TA range of 33–34 °C during the experiments. Controlanimals were placed in empty plastic containers of roughly the samesize as the incubator, kept at TA of 22°C. The temporary conditions did not include other mice or woodshavings affecting the microenvironment of the animals. Core temperaturemeasurements at the time of termination were acquired using rectalprobes as described above.In the experimentsinvolving controlled ambient temperature, animals were heated usinga ventilated incubator  set to maintain the temperature of the chamber at the upperlimit of animals’ thermoneutral zone (35 °C)2O, Pierce Protease Inhibitor Mini Tablet , Pierce Phosphatase Inhibitor Mini Tablet). After ∼15 min incubationon ice, samples were centrifuged , and the resulting supernatant was collected forwestern blot analysis.Animalswere euthanized at indicated times by a rapid cervical dislocationfollowed by decapitation and removal of the brain. Bilateral mPFC was rapidly dissectedon a cooled dish and stored at −80 °C until further processing.For some experiments, hippocampal (HC), cerebellar (CB), and/or midbrain(MB) samples were collected and processed with the same protocol.For the analysis of crude brain homogenates, the samples were homogenizedin lysis buffer  ice-cold buffer containing 0.32 M sucrose,20 mM HEPES pH 7.4, 1 mM EDTA, 1× protease inhibitor cocktail, 5 mM NaF, 1 mM Na3VO4, and 5 mM Na2HPO4. After centrifugation , the supernatant was further centrifugedat 15,300×g for 10 min. The supernatant (cytosolicfraction) was removed and the remaining pellets, corresponding tothe crude synaptosomal fraction, were resuspended in a lysis buffer.Crude synaptosomes were prepared as previouslydescribed.24 Membranes were incubated overnightin +4 °C with following primary phosphoprotein antibodies: anti-p-TrkAY785/p-TrkBY816 , anti-p-GSK3βS9 , anti-p-p70S6KT421/S424 , anti-p-ERK1/2T202/Y204 ,and anti-p-SrcY416 .For normalization, the following total protein antibodies were used:anti-TrkB , anti-mTrkB , anti-GSK3β , anti-p70S6K , anti-ERK1/2, anti-β-Actin , and anti-GAPDH .The membranes were washed with TBS containing 0.1% Tween (TBST) andincubated with horseradish peroxidase conjugated secondary antibodies. Secondary antibodies were visualized using enhancedchemiluminescence  fordetection using the Biorad ChemiDoc MP camera (Bio-Rad Laboratories).Sample protein concentrations were measuredusing the Bio-Rad DC protein assay . Proteins (40 μg) were separated with SDS-PAGE under reducingand denaturing conditions and blotted to a PVDF membrane as previouslydescribed.97 Briefly, weighed tissue samples were extracted using 100 μLof 80% methanol  per 10 mg of tissue under sonication. After vortexing and centrifugation, the supernatant was collected andfiltered to HPLC bottles through an Acrodisc CR 4 mm (0.45 μm)filter. Samples were analyzed with a UHPLC-qTOF-MS system (AgilentTechnologies) using two different chromatographic techniques, i.e.,reversed phase (RP) and hydrophilic interaction (HILIC) chromatographyand acquired data in both positive and negative polarity. Welch’sANOVA was used for statistical analysis. Principal component analysis(PCA) was used for metabolite profiling data to analyze the overallvariance between all the samples, and partial least sum of squaresdiscriminant analysis (PLS-DA) was used to calculate VIP values, identifyingmolecular features explaining the variance between the study groups.Fifteen principal components were needed to explain 95% of the variancein the metabolomics data; therefore, the α level was adjustedto 0.0033 to account for multiple testing. Cohen’s d effect sizes were calculated between the treatment andcontrol groups. MassHunter Acquisition was used for data acquisition, Profinder was used for feature extraction and peak alignment, the Mass ProfilerProfessional  for statistics, SIMCA to perform multivariate analyses, and MS-DIAL(ver.2.90) for metabolite identification.The nontargeted metabolomicsmethod has been described in detail before.t-test and one- ortwo-way analysis of variance (ANOVA) with Tukey’s post hoctest using Graphpad Prism . Comparisonsof groups with unequal variances were corrected using Welch’s,Dunnett’s, or Dunnett’s T3 tests, depending on the numberof groups and comparisons. When multiple individual pairwise comparisonsto their respective control treatments were performed, for examplein p values are described in figure legends, and details of statisticaltests and n numbers are presented in Table S1.The data were primarily analyzedwith Student’s unpaired The animal experiments were carriedout in compliance with theEuropean Communities Council Directive of 22 September 2010 (Directive2010/63/EU), according to the guidelines of the Society for Neuroscience,and approved by the County Administrative Board of Southern Finland(Licenses ESAVI/9793/04.10.07/2016 and ESAVI/5844/2019).


Drosophila of inducible, glial cell type-specific TDP-43 overexpression, a model that causes TDP-43 protein pathology including loss of nuclear TDP-43 and accumulation of cytoplasmic inclusions. We report that TDP-43 pathology in Drosophila is sufficient to cause progressive loss of each of the 5 glial sub-types. But the effects on organismal survival were most pronounced when TDP-43 pathology was induced in the perineural glia (PNG) or astrocytes. In the case of PNG, this effect is not attributable to loss of the glial population, because ablation of these glia by expression of pro-apoptotic reaper expression has relatively little impact on survival. To uncover underlying mechanisms, we used cell-type-specific nuclear RNA sequencing to characterize the transcriptional changes induced by pathological TDP-43 expression. We identified numerous glial cell-type specific transcriptional changes. Notably, SF2/SRSF1 levels were found to be decreased in both PNG and in astrocytes. We found that further knockdown of SF2/SRSF1 in either PNG or astrocytes lessens the detrimental effects of TDP-43 pathology on lifespan, but extends survival of the glial cells. Thus TDP-43 pathology in astrocytes or PNG causes systemic effects that shorten lifespan and SF2/SRSF1 knockdown rescues the loss of these glia, and also reduces their systemic toxicity to the organism.Accumulation of cytoplasmic inclusions of TAR-DNA binding protein 43 (TDP-43) is seen in both neurons and glia in a range of neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) and Alzheimer’s disease (AD). Disease progression involves non-cell autonomous interactions among multiple cell types, including neurons, microglia and astrocytes. We investigated the effects in  Neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD) and Alzheimer’s disease (AD) involve dysfunction in both neuronal and non-neuronal cells in the brain. Each of these disorders involves abnormal accumulation of a protein called TDP-43, which is thought to cause toxic effects that ultimately lead to cell death. We used cell type specific sequencing to characterize the effects of inducing pathological TDP-43 within each of the non-neuronal cell types in Drosophila. This identified changes in expression of a gene called SF2/SRSF1, which has previously been implicated in mediating toxic effects. We found that knocking down the expression of this gene within individual glial cell types was sufficient to prevent the loss of nearby neurons. Pathological cytoplasmic inclusions of TDP-43 are seen in post-mortem brain tissues from >90% of patients with ALS, ~45% of FTD cases, and nearly 50% of AD cases –8. TDP-4Under pathological conditions, TDP-43 is lost from the nucleus and becomes sequestered into cytoplasmic inclusions, which removes this autoregulatory mechanism –17. ThisThe loss of nuclear function is in fact a shared feature of over-expression and knock out models, but the over-expression approach also has the potential to model impacts from presence of cytoplasmic inclusions . Over-exDrosophila TDP-43 model are convergent with this literature, implicating a variety of non-neuronal cells in toxicity to neurons [Drosophila glial cells is sufficient to cause severe motor deficits, drive TDP-43 pathology in nearby neurons, cause neuronal cell death, and greatly reduce lifespan [Such astrocyte toxicity has also been observed in in vivo rodent and fly models –37. Acti neurons . We havelifespan ,37,42.Drosophila have five major glial cell types in the adult central brain, whose functional roles and anatomical features bear many similarities to non-neuronal cells (including glia) in the mammalian brain [an brain ,44. The an brain . Althougan brain . In addian brain –47. We pan brain ,42.SF2/SRSF1, a known suppressor of C9orf72 ALS/FTD models [SF2/SRSF1.Here, we used cell-type-specific nuclear RNA-seq both to better characterize the baseline transcriptional profiles of the 5 major glial cell types and to investigate mechanisms underlying glial cell type specific impacts of TDP-43 pathology. We identified numerous glial cell-type-specific transcriptional changes in response to induced TDP-43 expression. Notably, these included D models  that we D models . We obseDrosophila, pan-glial over-expression of TDP-43 causes loss of nuclear localization and accumulation of cytoplasmic hyperphosphorylated TDP-43 [Drosophila model also triggers pathological cytoplasmic accumulation of TDP-43 in nearby neurons where TDP-43 is not over-expressed [ts) approach, we induced post development over-expression of TDP-43 in each of the 5 individual glial cell types. This temperature switch expression system allowed us to avoid effects on development from over-expressing TDP-43 during glial specification, and also permitted us to determine the time-course of lethality after induction on the first day of adult life  differential intracellular sensitivity of a given cell type to TDP-43 toxicity, (2) differences in severity of effects on brain homeostasis from loss of each glial cell type, or (3) from cell-type specificity in non-cell autonomous toxic effects from TDP-43 proteinopathy ,42. We fWith each cell type, we observed a progressive loss in the numbers of labeled nuclei over time. With PNG, ALG, EG and CG, we see a similar time-course of cell loss . With earpr). In order to quantify effects on PNG cell loss, we co-expressed a UAS-nuclear-GFP. In each case, we used the same Gal-80ts approach to induce post development expression of GFP and either TDP-43 or rpr. As above, animals were reared at 21°C and then shifted to 29°C after eclosion (Day 0) in order to induce expression. We then quantified the effects on lifespan and PNG cell loss  ,51. HereUsing this method, we generated nuclear RNA sequencing libraries from each of the 5 cell types and compared expression 2 days after induction of either the GFP tag alone (baseline), or the GFP tag plus TDP-43 (N = 3 libraries per group). Because each of the cell types are comprised of different numbers of cells per brain , we adjuWhen comparing the baseline expression profiles across each of the five glial cell types, several things are of note. First, we found that the CG and EG show higher correlation in gene expression with each other than with the other cell types . SimilarThe transcriptional responses to TDP-43 pathology within each glial cell type included significant differential expression of many genes from cellular pathways that previously have been implicated in TDP-43 related neurodegeneration. These included genes involved in neuroinflammation ,53, DNA The differential expression analysis identified numerous cell type specific responses to TDP-43, as well as responses that were found to be in common across several cell types . Among tts method, to induce TDP-43 together with either a control shRNA against mCherry or the shRNA that targets the SF2/SRSF1 gene55. We used the same Gal80ts induction conditions described in previous experiments to turn on expression after development . We found that SF2/SRSF1 knockdown significantly suppressed the lifespan defects caused by TDP-43 induction in either PNG or ALG  , and lieDrosophila do not have a clear microglial cell type, they do have an astrocyte like cell type. And expression of pathological TDP-43 in Drosophila astrocytes drives non-cell autonomous toxicity to neurons [A sizeable literature supports the idea that release of factors from disease-activated glial cells is sufficient to promote toxicity to other cells including neurons ,31,62. T neurons . The finDrosophila SPG, PNG and astrocytes is sufficient to trigger loss of nearby neurons. Although mechanisms that mediate non-cell autonomous toxic effects in TDP-43 related and other neurodegenerative disorders are not fully understood, there is evidence implicating inflammatory effects [Drosophila model that TDP-43 pathology drives expression of the mdg4-ERV, and that mdg4 contributes to the non-cell autonomous effects on neuronal survival [Our prior work has demonstrated that TDP-43 proteinopathy in  effects , movemen effects –66 and e effects ,67. We hsurvival ,42. IndeDrosophila, and potentially to the non-cell autonomous effects of TDP-43. Although several prior publications have reported baseline expression profiling of several glial-cell-types during larval development, and adult stages in Drosophila, this is the first direct comparison of RNA expression profiles across all five major glial subtypes in the adult, using a single platform. This dataset supports the idea that CG and EG are functionally most similar, and that PNG and SPG also are more similar to each other than to the other glial cell types , our laboratory wild-type strain, for at least five generations. Female flies were utilized throughout the study. Strains used are shown in Flies were reared at 21°C and maintained on standard propionic acid food for all experiments in this study. A list of transgenic lines used in this study can be found in the table below. All were backcrossed to Canton-S derivative wts repression, allowing Gal4 mediated expression. Each lifespan experiments included 20 female flies per vial of a single genotype, with at least 60 flies total per genotype in each experiment. Flies were counted and flipped onto fresh food every other day. The Log-Rank (Mantel-Cox) test and the Gehan-Breslow-Wilcoxon test were used to compare the survival curves.All flies were reared at 21°C and shifted to 29°C upon eclosion, in order to relieve the Gal80Genotypes used in Figs Brains from adult drosophila were dissected in phosphate-buffered-saline (PBS) on days 2, 5, and 10. After dissection flies were transferred to 4% paraformaldehyde (PFA) solution  and fixed for one hour in a vacuum to remove air from trachea. Brains were then washed 3 times in 1XPBST for 10 minutes each prior to either (1) being mounted directly for imaging; or (2) transferred to a blocking solution  overnight at 4°C on a nutator in preparation for staining. After blocking brains were washed once in 1X PBST for 10 minutes and transferred to primary antibodies against Repo  and Elav  in 1XPBST and incubated overnight at 4°C on a nutator. Following primary antibody incubation brains were washed 4 times for 15 minutes each in a 3% salt solution (in 1X PBST) and transferred to secondary antibodies  in 1XPBST and incubated overnight at 4°C on a nutator. After secondary incubation brains were washed 4 times for 15 minutes each in a 3% salt solution (in 1X PBST) and mounted in FocusClear (CelExplorer).Brains were imaged within 24 hours of mounting using a Zeiss LSM 800 confocal microscope at 20X. All images were processed by Zeiss Zen software package. A single standard anterior section, defined by anatomy, was chosen for analysis for all cell quantification. Images were analyzed using FIJI (ImageJ). Mixed-effect analysis and two-way ANOVA were used to compare cell counts.2 and flash frozen in liquid nitrogen before being stored at -80°C until an appropriate number of flies were collected for each group . Fly heads were separated, homogenized, and incubated with an antibody against GFP (ThermoFisher: G10362) before being bound to protein A beads, cleaved, and rebound to protein G beads. Twice purified TAPIN-tagged nuclei were then burst and nuclear RNA was collected and stored at -80°C.Methods are described in detail in prior studies ,51. BrieTAPIN-generated nuclear RNA was treated with DNase and purified by the Arcturus PicoPure system. Purified RNA was amplified to cDNA via Nugen Ovation v2 system (Nugen: 7102–32) and was then fragmented with a Covaris s-series to 200bp. Fragmented cDNA was repaired and underwent second strand synthesis before being ligated to barcoded linkers . Libraries were quantified via KAPA qPCR before being sequenced on Illumina NextSeq to 76bp read length.98 using the DESeq normalization strategy and negative binomial modeling. B-H corrected FDR P-value threshold of p< 0.05 was used to determine significance. For correlation plots, Pearson correlation was calculated using normalized count values from DESeq2. For heatmap visualization, counts were normalized using a variance stabilizing transformation in DESeq2Reads were aligned to the dm6 genome using STAR v2.7.6a , allowinWith the exception of the TAPINseq expression analysis, all statistical analyses were performed in GraphPad Prism v9.2. Specific statistical analyses are listed under each methods description and include mixed-effect analysis, two-way ANOVA, Log-rank (Mantel-Cox) test, and Gehan-Breslow-Wilcoxon test.S1 FigFlies expressing UAS-TDP-43 and the INTACT reporter (5XUAS-unc84-2XGFP) under control of a temperatures sensitive Gal80 plus a glial cell-type-specific Gal4 (methods) were (A) reared at 21°C and shifted to 29°C upon eclosion (day 0). Heads were collected for sequencing on day 2 and stored at -80°C until use. (B) schematic of the INTACT nuclear tag used to purify nuclei and schematic of the tandem affinity purification process.(PDF)Click here for additional data file.S2 FigGene expression profiles generated from (A) Pearson correlation analysis demonstrating EG and CG more closely resemble each other at baseline than they do their own cell type with TDP-43 expression (B) principle component analysis plot demonstrating PNG and SPG separate from other glial cell types. (C) upregulated and downregulated genes (p < .05) in a given glial cell type and their overlap with other glial cell types.(PDF)Click here for additional data file.S3 FigThe PNG-Gal4 and Gal80ts were used to induce post development expression of hTDP-43 and UAS- Watermelon (WM), a dual reporter module that encodes both a myristylated GFP that tethers to the membrane (myr-GFP-V5) and nuclear localized mCherry (H2B-mCherry-HA). As in other figures, flies were reared at 21°C and shifted to 29°C upon eclosion (day 0). To quantify effects on neuron number, brains were dissected at day 10 (D10) post temperature shift. PNG glia were visualized using the mCherry nuclear reporter, and neuronal nulei were visualized using the Elav antibody. The numbers of Elav-labeled neuronal nuclei were quantified in A 4.68 μm stack  of ventral, posterior brain region as depicted with a yellow box in the image at left. This reveals a statistically significant  reduction in numbers of neurons in TDP-43 expressing  vs controls . Means and SEM are shown.(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(PDF)Click here for additional data file. 29 May 2023Dear Dr Dubnau,Thank you very much for submitting your Research Article entitled 'TDP-43 pathology in Drosophila induces glial-cell type specific toxicity that can be ameliorated by knock-down of SF2/SRSF1.' to PLOS Genetics.The manuscript was fully evaluated at the editorial level and by independent peer reviewers. 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You will be contacted if needed following the screening process.PLOS has incorporated To resubmit, you will need to go to the link below and 'Revise Submission' in the 'Submissions Needing Revision' folder.Please let us know if you have any questions while making these revisions.Yours sincerely,Fengwei YuAcademic EditorPLOS GeneticsGregory P. CopenhaverEditor-in-ChiefPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: Krupp et al. described the effect of SF2/SRSF1 knockdown in glia-induced TDP-43 pathology in Drosophila. Overall the study is interesting, of interest, and well conducted. I have some major concerns prior to publication:1. How physiologically relevant is glial-specific TDP-43 overexpression? TDP-43 accumulation occurs in both glia and neurons, but is TDP-43 expressed in both cell types? If it’s dominantly expressed in neurons, overexpressing TDP-43 in glia does not recapitulate the situation under normal physiological condition.2. For all experiments in the study, does the control have similar GAL4:UAS ratio as the experimental group? As titration effect of gene expression might occur when using one GAL4 for two UAS, it will be best to compare all effects with similar number of UAS transgenes for the same GAL4.3. Did the authors try overexpressing SF2/SRSF1 in the presence of TDP-43 in glia? It is a bit counter-intuitive to learn that knockdown of SF2/SRSF1 ameliorate TDP-43 pathology in glia, as RNA-sequencing results suggest that this gene is downregulated when TDP-43 is overexpressed. One would imagine that by overexpressing SF2/SRSF1 TDP-43 pathology will be rescued.4. The discussion on the non-cell-autonomous toxicity from glia to neurons is a bit hard to understand. It will help if the author can revise and add in more discussion to make things more clear.5. There is a typo in Figure 1A, the genotype is unc8402xGFP?Reviewer #2: Understanding how TDP-43 related pathology and aggregation can underlie neurodegenerative diseases like ALS, FTD, and AD is a critical current goal for the field. Important recent work highlighted that not only neurons play a role in the pathological process, but that non-cell autonomous interactions with glia are important. Krupp and colleagues examine such interactions in more depth in this manuscript, to determine the effects of TDP-43 overexpression in specific subpopulations of glia on TDP-43 pathology. They show that organismal survival is most severely impacted following TDP-43 overexpression in perineurial glia or astrocytes; for perineurial glia, this is not due to cell ablation, but likely non-cell autonomous defects. Further, they observe that TDP-43 overexpression in each glial cell type leads to varying degrees of age-dependent cell loss. The authors conduct TAPIN-seq to determine how TDP-43 overexpression affects the transcriptome of each subpopulation of glial cells and show that SF2/SRSF1 is reduced in perineurial glia and astrocytes, consistent with previous broad cell-type findings in ALS models. Further knockdown of SF2/SRSF1 in either perineurial glia or astrocytes reduces TDP-43 pathology including cell loss and lifespan.This paper represents a strong and important contribution to the field for two main reasons: 1) it demonstrates a fascinating biological finding that glial subtypes are not equally susceptible / causative in TDP-43 pathology and 2) it establishes a valuable resource in the nuclear RNA sequencing databases of different glial subtypes under normal conditions and TDP-43 overexpression conditions. Both aspects are notable advances in the field. Moreover, the paper is well-written, with the experimental logic clearly laid out and the results straightforward and easy to follow. My criticisms are minor and largely restricted to issues of data presentation and the need for additional discussion on the roles of glial subtypes and the mechanism of SF2/SRSF1 function. With these minor additions, the paper will be suitable for publication.Experimental Point - Though consistent with data from the field, the knockdown of SF2/SRSF1 that rescues TDP-43 pathology when TDP-43 pathology already results in a reduction of SF2/SRSF1 is counterintuitive. If the two were causative / genetically linked, I expect SF2/SRSF1 overexpression would rescue the pathology. Can you instead overexpress SF2/SRSF1 and see altered TDP-43 pathology? Further, the authors posit that SF2/SRSF1 “rescue” results in “a reduction in the non-cell autonomous toxicity of the glia to surrounding neurons.” Can this be demonstrated and quantified? It would help strengthen the existing data. It would also be helpful for the authors to include further discussion of the role / mechanism of SF2/SRSF1.Discussion Point - There is little discussion of the role that astrocytes are playing in TDP-43 overexpression pathology. The roles of subperineurial glia and perineurial glia are well discussed, but additional discussion / speculation on the role of astrocytes would be very helpful here.Data Presentation Points - My biggest issue with this paper is in data presentation. In its current state, it is very challenging to discern labels and interpret the results of figures and graphs throughout the paper. Though the issue is present in all figures, it is most distinctly so with Figure 2. For all figures, can the authors adjust font size and clarity? In Figure 2, even at very high magnification, it’s still challenging to tell what the labels are showing. Additionally, larger graphs  would be very helpful in conveying the important points as with the rest of the figures. In all figures, larger image labels would be helpful.In Figure 1, it is also difficult to tell the difference in the curve genotypes due to the size of the shapes. Can you color the TDP-43 containing curves so it’s easier to see? Also, can you denote significance on the graph? There is no significance in the figure despite noting it in the text and a p value in the figure legend.Finally, in Figure 4, the letter labeling is inconsistent with the rest of the paper. Also, the pink bar denoting the Tg_TDP43 genotype is difficult to see. Can it be changed to aid in visibility?Reviewer #3: TDP43 pathology plays a central role in the pathogenesis of ALS and FTD, and may be also involved in AD as well. Thus, it has been under intense investigation in the field. Over the years, Dr. Josh Dubnau and his colleagues have investigated the effects of TDP43 pathology in Drosophila by overexpressing it in different cell types and have made a series of important discoveries (such as DNA damage and retrotransposon activation). In the current study, the authors made an interesting observation that TDP43 expression in the perineural glia (PNG) and astrocytes had most pronounced effect on organismal survival compared with other types of glia. Because genetic ablation of PNG did not have the same effect, these findings suggest that some unknown factors released by TDP43-expressing PNG cause systematic toxicity and neurodegeneration. This is important, because they are now in an excellent position to perform genetic studies to identify the nature of these factors released by PNG. Of course, their work here would be much more significant and novel if they could report what these factors are. Then they went on to perform cell-type specific nuclear RNA-seq and found that SF2/SRSF1 is downregulated in PNG expressing TDP-43. Further KD of SF2/SRSF1 in PNG rescued loss of these glia and reduced systematic toxicity of TDP43. Although the beneficial effects of SF2/SRSF1 KD in TDP-43 or C9 models are already known, their RNA-seq datasets will be useful for the field.The authors can consider the following suggestions for minor revisions to further improve their manuscript.1. The strength of different glial subtype-specific Gal4 drivers may be different. Is it possible different levels of TDP43 are expressed in different glial subtypes to cause different effects on organismal survival? Western blot analysis will not help address this question because the numbers and location of glia in different subtypes are different. Or immunostaining of different flies is good enough to tell the difference. At a minimal, the authors can discuss more in detail the number and location of glial subtypes, and potentially differential strengths of different Gal4 drivers.2. As mentioned above, SF2/SRSF1 is already known to be a modifier in TDP43 and C9 models . If not too much work, the authors can include another novel modifier identified from their RNA-seq analysis to enhance the novelty of the study. Alternatively, they can perform a few more mechanistic studies to understand further how SF2/SRSF1 modifies TDP-43 toxicity. For instance, is SF2/SRSF1 required to export TDP43 mRNA from the nucleus to the cytoplasm as it does for C9 repeats as reported? Does SF2/SRSF1 overexpression enhance the phenotype? And so on.3. Maybe the authors published this in their earlier papers. In several places, the authors talk about toxicity of glial TDP43 on neurons, but they never showed any data. Is that possible to include neuron survival data at least in one figure?4. In Figure 1 legend, it is stated that p<0.0001 for all panels. Is that true? This reviewer is a little bit surprised, because in Panel C, the small difference is largely due to the second data point and death occurred only few days after the experiment started. So the authors should carefully perform statistical analyses again and state in the legend what statistical methods were used. The number of flies for each panel should be stated and it is better to list p values in each panel of the figure as well.5. In Figure 2 and Figure 3 legends, *p<0.5 must be an error. Is it *p<0.05? Also, please state the values are S.D. or S.E.M., what are n numbers, and by what statistical analysis in all figure legends.6. In Figure 3B, the number of PNG cells at day 2 is >200, but the image does not show that many cells as in Figure 2. Please explain.7. In Figure 4 legend, they say “upregulated (blue) and downregulated (red) genes”. But in the figure, upregulated genes are in red and downregulated genes are in blue.8. Figure 5 can be reorganized to better utilize the empty spaces. Panels D and E can be new Panels A and B, and Panels A-C can be new Panels C-E.9. Please increase font size in all figures.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: None**********what does this mean?). If published, this will include your full peer review and any attached files.PLOS authors have the option to publish the peer review history of their article , and click on the Fetch/Validate link next to the ORCID field.  This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager.In the meantime, please log into Editorial Manager at If you have a press-related query, or would like to know about making your underlying data available , please see the end of this email. If your institution or institutions have a press office, please notify them about your upcoming article at this point, to enable them to help maximise its impact. Inform journal staff as soon as possible if you are preparing a press release for your article and need a publication date.Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Genetics!Yours sincerely,Fengwei YuAcademic EditorPLOS GeneticsGregory P. CopenhaverEditor-in-ChiefPLOS Geneticswww.plosgenetics.orgTwitter: @PLOSGenetics----------------------------------------------------Comments from the reviewers (if applicable):Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: The reviewer has no further questions and the manuscript is ready for publication in its current formReviewer #2: I thank the authors for their thoughtful replies to my comments, for the addition of new data in Figure S3, and especially the changes to data presentation which greatly improved the figures. This was very helpful. The authors have appropriately addressed all of my comments and I can support publication. Thank you!Though I'd like to cast my vote  for overexpressing SF2/SRSF1 in the next paper!Reviewer #3: The authors have satisfactorily addressed most of my comments. Some suggested experiments were not performed, such as SF2/SRSF1 overexpression, which was also proposed by another reviewer. I understand their reasoning why it is more important to focus on down-regulation.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: NoneReviewer #2: YesReviewer #3: Yes**********what does this mean?). 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PLOS Genetics may also choose to issue a press release for your article. If there's anything the journal should know or you'd like more information, please get in touch via  20 Sep 2023PGENETICS-D-23-00514R1 TDP-43 pathology in Drosophila induces glial-cell type specific toxicity that can be ameliorated by knock-down of SF2/SRSF1. Dear Dr Dubnau, We are pleased to inform you that your manuscript entitled "TDP-43 pathology in Drosophila induces glial-cell type specific toxicity that can be ameliorated by knock-down of SF2/SRSF1." has been formally accepted for publication in PLOS Genetics! Your manuscript is now with our production department and you will be notified of the publication date in due course.The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any errors. 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