An astrocytic AMPK clock drives circadian behaviour

An astrocytic AMPK clock drives circadian behaviour | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results An astrocytic AMPK clock drives circadian behaviour María Luengo-Mateos , Antía González-Vila , María Silveira-Loureiro , Daniela Sofía Abreu , Mikel Azkargorta , Ali Mohammad Ibrahim-Alasoufi , Victor Pardo-García , Hugo Lopez-Goldar , Helena Covelo Molares , Nathalia R.V. Dragano , Paola Fernández-Sanmartín , Ánxela M Estévez-Salguero , Mariana Astiz , View ORCID Profile Cláudia Cavadas , Carlos Diéguez , Miguel Fidalgo , Diana Guallar , Félix Elortza , Joao Filipe Oliveira , Miguel López , View ORCID Profile Olga Barca-Mayo doi: https://doi.org/10.1101/2025.08.14.670385 María Luengo-Mateos 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Antía González-Vila 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site María Silveira-Loureiro 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain 2 NeurObesity Lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Daniela Sofía Abreu 3 Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho , 4710-057 Braga, Portugal Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mikel Azkargorta 4 Proteomics Platform, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA) , Derio, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ali Mohammad Ibrahim-Alasoufi 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Victor Pardo-García 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hugo Lopez-Goldar 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Helena Covelo Molares 5 Epitranscriptomics and Ageing Lab, Biochemistry Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain 6 Stem cells and human diseases lab. Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Nathalia R.V. Dragano 2 NeurObesity Lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Paola Fernández-Sanmartín 2 NeurObesity Lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ánxela M Estévez-Salguero 2 NeurObesity Lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mariana Astiz 7 Achucarro Basque Center for Neuroscience, Leioa, Spain. IKERBASQUE, Basque Foundation for Science , Bilbao, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cláudia Cavadas 8 Center for Neuroscience and Cell Biology (CNC-UC), Centre for Innovation in Biomedicine and Biotechnology (CIBB), Faculty of Pharmacy, University of Coimbra , Coimbra, Portugal Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Cláudia Cavadas Carlos Diéguez 9 Functional Obesomics lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Miguel Fidalgo 5 Epitranscriptomics and Ageing Lab, Biochemistry Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Diana Guallar 6 Stem cells and human diseases lab. Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Félix Elortza 4 Proteomics Platform, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA) , Derio, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joao Filipe Oliveira 3 Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho , 4710-057 Braga, Portugal Find this author on Google Scholar Find this author on PubMed Search for this author on this site Miguel López 2 NeurObesity Lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site Olga Barca-Mayo 1 Circadian and glial biology lab, Physiology Department, Molecular Medicine and Chronic Diseases Research Centre (CiMUS), Instituto de Investigación Sanitaria (IDIS), University of Santiago de Compostela , Santiago de Compostela, Spain Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Olga Barca-Mayo For correspondence: olga.barca.mayo{at}usc.es m.lopez{at}usc.es Abstract Full Text Info/History Metrics Supplementary material Preview PDF Summary Circadian clocks coordinate behaviour and physiology with daily cycles of light and nutrient availability, yet how metabolic signals tune brain timing remains unclear. Astrocytes integrate metabolic and hormonal cues and sustain cell-autonomous rhythms, implicating them as candidate links between energy state and central circadian control. Here we show that AMP-activated protein kinase (AMPK) in hypothalamic astrocytes exhibits intrinsic, calcium-dependent rhythmicity that persists under constant darkness and without feeding cues. This glial rhythm sustains time-of-day phosphorylation programmes in the hypothalamus and stabilises the clock protein PER2 via phosphorylation at a conserved serine residue, thereby linking metabolic state to period control beyond the canonical transcription-translation feedback loops. In the ventromedial hypothalamus, astrocytic AMPK-PER2 signalling is required for food-anticipatory activity, identifying a glial node within the food-entrainable timing system. Disrupting astrocytic AMPK rhythmicity alters circadian behaviour and energy homeostasis and shortens lifespan in a sex-dependent manner. These findings recast AMPK as a metabolically adaptive glial timekeeper that connects calcium signalling and phosphorylation rhythms to behaviour and metabolism. They also reveal a phosphorylation-based timing layer in central metabolic circuits, with implications for circadian-metabolic misalignment in contexts such as shift work and metabolic disorders. Introduction Temporal coordination of behaviour and physiology is essential for maintaining organismal homeostasis 1 . In mammals, this is controlled by a distributed network of cellular clocks present in nearly all tissues and hierarchically synchronized by the suprachiasmatic nucleus (SCN), a hypothalamic pacemaker entrained by light 2 . However, not all circadian rhythms are light dependent. Scheduled feeding, for example, induces food-anticipatory activity (FAA), a surge in locomotion prior to mealtime that persists even after SCN ablation, implying the existence of a distributed food-entrainable oscillator (FEO) 3 , 4 . Despite decades of behavioural evidence, the anatomical, cellular and molecular identity of the FEO remains elusive, with emerging models proposing a network of food-sensitive clocks across brain and periphery 3 , 4 . At the molecular level, circadian clocks rely on transcription-translation feedback loops (TTFLs) in which positive (CLOCK, BMAL1) and negative (PER, CRY) regulators generate self-sustained 24-h rhythms in gene expression 2 , 5 – 7 . Beyond transcription, clocks also regulate rhythmic translation and protein turnover through post-translational modifications (PTMs) that control protein stability, activity, interactions, and localisation 8 – 10 . Among these, phosphorylation is a key driver of circadian rhythm generation across species 11 , 12 . In mammals, phosphoproteomic studies, conducted largely in peripheral tissues, show that phosphorylation rhythms outnumber those of transcripts or total proteins, highlighting its importance as a metabolically efficient and evolutionarily conserved layer of circadian regulation 9 , 10 , 13 . Astrocytes, once viewed as passive support cells, are now recognized as active components of the circadian system. In the SCN, they harbour autonomous clocks, modulate neuronal synchrony and drive both behavioural and physiological outputs 14 – 23 . Beyond the SCN, astrocytes integrate hormonal, synaptic and metabolic cues 24 , 25 , raising the possibility that they link internal energy state to central circadian timing. AMP-activated protein kinase (AMPK), a conserved energy sensor activated by low cellular ATP and abundantly expressed in astrocytes 26 – 28 , is a prime candidate for such coupling. While AMPK has been implicated in circadian regulation in peripheral tissues 29 – 31 , its role in astrocyte-mediated central timekeeping is unknown. Here we show that AMPK activity in hypothalamic astrocytes exhibits intrinsic rhythmicity via Ca²⁺ signalling and is required to maintain the circadian phosphoproteome. Disrupting this rhythmicity alters the intrinsic period of locomotor behaviour, leads to sex-specific metabolic dysfunction, and shortens lifespan. We further identify AMPK-PER2 signalling in ventromedial hypothalamic astrocytes as essential for FAA, thereby positioning astrocytic AMPK as a Ca²⁺-gated clock component that links metabolic state to circadian behaviour and systemic homeostasis. Results Astrocytes regulate intrinsic circadian period via AMPK We examined AMPK activity in the SCN using phosphorylated acetyl-CoA carboxylase (pACCα), a canonical downstream target, and found enrichment of pACCα signal in the vasoactive intestinal polypeptide (VIP)-expressing SCN core ( Fig. 1a ) , a region critical for network synchrony and circadian rhythm amplitude 32 . Although AMPK is classically activated by elevated AMP/ATP ratios during energy depletion 28 , hypothalamic AMPK displayed robust circadian variation, peaking in the active phase 31 despite stable ATP levels in the brain 33 , suggesting regulation beyond energetic state. To test whether astrocytic AMPK contributes to circadian regulation, we generated two inducible astrocyte-specific knockouts using Glast CreERT 2 -mediated recombination 19 , 20 , 23 , 34 , 35 . Deletion of the catalytic α1 subunit ( α1cKO ) abolished AMPK kinase activity, whereas deletion of the regulatory γ2 subunit ( γ2cKO ) impaired AMP sensing and functionally mimicked constitutive activation 36 – 38 . Immunoblotting confirmed strong reductions in AMPKα1, phosphorylated AMPKα (pAMPKα) and pACCα in α1cKO hypothalamus ( Fig. 1b and Extended Data Fig. 1a ) . Download figure Open in new tab Fig. 1. Astrocytic AMPKα1 constrains SCN neuropeptide output and shortens circadian period. a, Representative immunofluorescence images showing pACCα in the SCN at ZT4 following overnight fasting. DAPI staining (left) delineates SCN structure; middle and right panels show pACCα signal, with inset highlighting the ventrolateral SCN domain. b, Western blot analysis of AMPK signalling components in hypothalamic lysates from control and α1cKO mice at ZT8. c, Locomotor activity rhythms of control and α1cKO mice under 12:12 hours LD and DD conditions (upper panels). Lomb-Scargle periodogram analysis of rhythmic period under LD and DD (lower panels) (n = 5-13). d, Representative double-plotted actograms from control and α1cKO mice under LD and DD. e, Levels of clock proteins (PER2, CRY1) and neuropeptides (VIP, AVP) in hypothalamic tissue from control and α1cKO mice at ZT8. Western blot quantification (left) (n = 3-5) and representative immunoblots (right). Data are presented as mean ± s.e.m. * P < 0.05, ** P < 0.01, **** P < 0.0001 (unpaired two-tailed t-test or two-way ANOVA). Male α1cKO mice showed increased wheel-running activity under both light-dark (LD) and constant darkness (DD) conditions, with a shortened free-running period and higher rhythm amplitude ( Fig. 1c, d and Extended Data Fig. 1b ) . At the molecular level ( Fig. 1e ) , α1cKO hypothalamus exhibited elevated arginine vasopressin (AVP) and a trend toward increased VIP (p = 0.06), consistent with enhanced rhythm amplitude. Whereas in peripheral tissues AMPK promotes CRY1 and PER2 degradation 29 , 31 , 39 , in α1cKO hypothalamus only PER2 was reduced, indicating a central mechanism in which astrocytic AMPK stabilises PER2. Notably, astrocyte-specific deletion of Per2 has been shown to shorten the free-running period in DD 40 , consistent with the accelerated behavioural rhythms observed in α1cKO mice. The resemblance to the global AMPKα1 -knockout 31 phenotype supports a cell-autonomous role for AMPKα1 within SCN astrocytes. Together, these findings identify astrocytic AMPKα1 as a regulator of circadian period and output strength via PER2 stability and SCN neuropeptide control. Astrocytic AMPK stabilises PER2 and rewires hypothalamic phosphoproteome To test whether sustained AMPK activity in astrocytes has effects opposite to AMPKα1 loss, we generated an inducible astrocyte-specific knockout of the regulatory γ2 subunit ( Prkag2 ; γ2cKO ), whose loss disrupts AMP sensing and functionally mimics chronic AMPK activation 36 – 38 . Reanalysis of published circadian transcriptome data from CBA/CaJ mice 41 showed that Prkag2 was rhythmic in the SCN, peaking at night, but not in other brain regions (Extended Data Fig. 2a ) . In control animals, hypothalamic pAMPK rose at ZT20, consistent with nocturnal circadian AMPK activation 31 . This temporal pattern was abolished in γ2cKO mice, which showed comparable levels of pAMPK at ZT8 and ZT20 (Extended Data Fig. 2b ) . In controls, pACCα levels remained relatively stable across time points, indicating a temporal lag between AMPK activation and ACCα phosphorylation, as described in liver 10 . By contrast, γ2cKO mice exhibited elevated pACCα at ZT8 (Extended Data Fig. 2b ) , consistent with persistent and mistimed AMPK activity. In γ2cKO tdTomato reporter mice, pACCα immunoreactivity was increased in Tomato⁺ VMH astrocytes at ZT0 (Extended Data Fig. 2c ) , confirming cell-autonomous AMPK activation. Expression of AMPKγ1, previously proposed to compensate for AMPKγ2 loss 42 , was reduced at ZT8 and unchanged at ZT20 (Extended Data Fig. 2b ) , arguing against compensatory upregulation. These findings validate the γ2cKO model and demonstrate persistent, temporally misaligned AMPK signalling across the circadian cycle. Behaviourally, γ2cKO mice exhibited reduced nocturnal activity and dampened circadian amplitude, with a lengthened free-running period under DD, in contrast to the shortened period (∼12 min difference) and enhanced amplitude in α1cKO mice. Total daily activity was unchanged, excluding hypoactivity as a cause ( Fig. 2a, b and Extended Data Fig. 2d ) . Molecularly, γ2cKO hypothalami showed elevated day-time PER2 and reduced SCN VIP (Extended Data Fig. 3a and Fig. 2c ) . Thus, α1cKO and γ2cKO mice display opposing circadian phenotypes at both behavioural and molecular levels, consistent with a bidirectional role for astrocytic AMPK in circadian timing: loss of activity accelerates rhythms, whereas persistent activation decelerates them, including modulation of SCN neuropeptide output. Download figure Open in new tab Fig. 2. Astrocytic AMPKγ2 coordinates circadian timing and phospho-signalling dynamics. a, Locomotor activity rhythms of control and γ2cKO mice under LD and DD conditions (upper panels). Lomb-Scargle periodogram analysis of rhythm amplitude and free-running period (lower panels) (n = 6-7). b, Representative double-plotted actograms from control and γ2cKO mice under LD and DD. c, VIP immunoreactivity in the SCN of control and γ2cKO mice at ZT2. Quantification of VIP immunofluorescence intensity (left) and representative confocal images (right) (n = 10). d, Heatmap showing time-of-day-dependent phosphoproteins in control but not γ2cKO hypothalami at ZT6 and ZT18 (n = 3-4). e, Venn diagrams showing the number of time-of-day-dependent phosphoproteins unique to or shared between genotypes at each time point. f, KEGG pathway enrichment and g, Gene Ontology analysis of time-of-day-dependent phosphoproteins in control hypothalami. Bubble size reflects -log10 ( P -value); position indicates fold enrichment; colour denotes peak phase (ZT6, yellow; ZT18, gray). Data are presented as mean ± s.e.m. *** P < 0.001, **** P < 0.0001 (unpaired two-tailed t-test or two-way ANOVA). Given the elevated daytime PER2 in γ2cKO hypothalami, we next asked whether its stability is regulated via phosphorylation at Ser659, a conserved residue homologous to human Ser662, whose mutation causes familial advanced sleep phase syndrome (FASPS) 43 . This site lies within a serine-rich domain targeted by Casein Kinase I (CKI)ε and matches the AMPK consensus motif [ϕ-X-(R/K)-X-X-S/T] 44 , suggesting it could be directly phosphorylated by AMPK (Extended Data Fig. 3b ) . Consistent with the importance of astrocytic CKIε in circadian period control, selective manipulation of CK1ε Tau in SCN astrocytes lengthens the free-running period of locomotor rhythms in vivo to a degree comparable to neuronal manipulations 15 , 16 . Together, these observations support a model in which AMPK regulation of PER2 at Ser659/662 converges with CK1ε-dependent pacemaking in astrocytes. In control hypothalami, total PER2 and Ser659-phosphorylated PER2 (pPER2) peaked at ZT20, coinciding with the nocturnal rise in AMPK signalling. In γ2cKO mice, both were prematurely elevated at ZT8, consistent with persistent AMPK activation and impaired phase-dependent degradation (Extended Data Fig. 3a ). Previous work in peripheral tissues showed that AMPK can promote PER2 degradation indirectly by phosphorylating CK1ε at Ser389, thereby enhancing CK1ε activity towards PER2 39 . By contrast, our astrocyte data indicate that AMPK correlates with PER2 stabilisation and delayed turnover, in association with changes at the Ser659/662 site, whose phosphorylation has been shown to stabilise PER2 in heterologous systems 45 . To test this directly, we treated primary hypothalamic astrocytes with the AMPK activator AICAR under high-or low-glucose conditions, with or without the protein synthesis inhibitor cycloheximide (CHX) (Extended Data Fig. 3c ) . Without CHX, AICAR robustly increased pAMPK under both glucose conditions. Under high glucose, pPER2 transiently decreased at 2-4 h and rebounded by 8 h, indicating dynamic phosphorylation-dephosphorylation. Total PER2 remained stable, consistent with balanced synthesis and degradation. Under low glucose, pPER2 and PER2 tracked pAMPK, rising over time and falling at 8 h, recapitulating the nutrient-sensitive AMPK-PER2 axis observed in vivo (Extended Data Fig. 3d ) . In the presence of CHX, pAMPK, pPER2, and total PER2 all declined upon AICAR treatment, indicating that PER2 stability requires both AMPK-dependent phosphorylation and ongoing protein synthesis. Although our data do not distinguish whether AMPK phosphorylates PER2 directly or via upstream activation of CK1ε at the Ser659/662 site, the nutrient- and AMPK-dependent changes in pPER2 and total PER2 support Ser659/662 as a metabolically gated stability switch in astrocytes. To assess whether this mechanism is under circadian control in vivo , we examined PER2 and pPER2 in hypothalamic tissue collected at ZT8 and ZT20 under DD. Both forms peaked at ZT20, matching AMPK activation, whereas pACCα peaked during the day (Extended Data Fig. 3e ) , indicating a phase lag between AMPK activation and substrate phosphorylation, as also observed in LD (Extended Data Fig. 2b ) and as reported in liver 10 . These findings identify Ser659 as a metabolically gated phospho-switch through which astrocytic AMPK stabilises PER2, linking nutrient state to circadian timing, in a TTFL-independent manner. In contrast to males, female γ2cKO mice showed no overt behavioural phenotype: free-running period, nocturnal activity and total locomotion were indistinguishable from controls (Extended Data Fig. 4a, b ) . Nevertheless, pAMPK and pACCα failed to exhibit day-night variation in γ2cKO female hypothalami (Extended Data Fig. 4c ) , indicating disrupted AMPK signalling. This disconnect between molecular and behavioural outputs may reflect compensatory mechanisms (e.g., SCN plasticity or oestrogen-mediated clock robustness) that preserve circadian behaviour despite upstream perturbations 23 , 34 , 46 – 49 . To determine how astrocytic AMPKγ2 shapes circadian signalling at the systems level, we profiled the hypothalamic phosphoproteome of control and γ2cKO males at two circadian phases (ZT6 and ZT18). In controls, phosphorylation showed marked day-night differences, with over 350 phosphoproteins varying significantly between ZT6 and ZT18. In γ2cKO hypothalami, more than 95% of these rhythms were lost ( Fig. 2d, e ) , revealing that astrocytic AMPK is essential for temporal organisation of hypothalamic phosphorylation. Although circadian phosphoregulation is well characterized in peripheral tissues, its role in the brain has remained unclear. Here, gene ontology and KEGG analyses linked rhythmic phosphoproteins in controls to circadian entrainment, ion transport, synaptic and insulin signalling ( Fig. 2f, g ) , highlighting the integration of timekeeping with neuronal and metabolic pathways. Phase-specific comparisons at ZT6 and ZT18 revealed broad network disruption in γ2cKO mice that was largely independent of phase (Extended Data Fig. 5a, b). At ZT6, dysregulated processes included neurotransmitter and ion (calcium and potassium) transport and biological rhythms. At ZT18, enrichment shifted toward mRNA processing, ER-Golgi transport and cell cycle regulation. These divergences suggest that astrocytic AMPK normally partitions hypothalamic functions across the day, engaging neuronal signalling and ion homeostasis during the light phase and biosynthetic/trafficking programmes at night, whereas chronic AMPK activation erodes this partitioning, reducing phase specificity and phospho-signalling coherence. Together, these data position astrocytic AMPK as a temporal integrator that gates hypothalamic phosphorylation across neuronal and metabolic pathways. Astrocytic AMPKγ2 shapes sex-specific metabolism and lifespan Astrocytic disruption of clock or nutrient-sensing pathways alters circadian behaviour and systemic metabolism in a sex-dependent manner 19 , 20 , 23 , 34 . Persistent AMPK activation, caused by mutations in PRKAG2 (AMPKγ2), is associated with obesity, hyperphagia and systemic metabolic dysfunction in both animal models and humans, including Wolff-Parkinson-White syndrome 36 – 38 . Whether astrocyte-specific loss of AMPKγ2 is sufficient to perturb whole-body homeostasis, and whether such effects differ between sexes, remains unknown. In females, γ2cKO mice exhibited progressive weight gain accompanied by increased fat mass, lean mass and extracellular fluid, without alterations in food intake, locomotor activity or respiratory exchange ratio (RER) ( Fig. 3a and Extended Data Fig 6a-c ) . Reduced energy expenditure and impaired thermogenesis, evidenced by lower rectal and brown adipose tissue (BAT) temperatures and decreased BAT UCP1 expression, emerged as primary drivers ( Fig. 3b-d and Extended Data Fig. 6d, e ) . Fasting glucose remained normal, but glucose and insulin tolerance tests revealed modest impairments ( Fig. 3e, f and Extended Data Fig. 6f ) . Thus, persistent astrocytic AMPK activation in females uncouples behavioural rhythmicity from metabolic homeostasis, selectively disrupting thermogenic regulation, glycaemic control, and overall energy balance. Download figure Open in new tab Fig. 3. Sex-specific metabolic and lifespan effects in γ2cKO mice. a , g , Body weight trajectories and composition (fat, lean mass, and free fluid) in control and γ2cKO females (n = 11-18) and males (n = 15-18), respectively. b, Energy expenditure (EE) profiles over 72 h (left) and quantification of average day-time, night-time, and total EE (right) in females (n = 5-7). c, Rectal temperature (left), thermographic BAT temperature (middle), and representative infrared images (right) in females (n = 11-20). d, UCP1 protein levels in BAT from females (n = 5-7). Representative immunoblots (upper panels) and Western blot quantification (lower panels). e, Glucose tolerance test (left) and area under the curve (AUC, right) in females (n = 15-19). f, Insulin tolerance test (ITT, left) and AUC (right) in females (n = 9-25). h, Food intake during light and dark phases in males (n = 7-8). i, Quantification of average day-time, night-time, and total EE in males (n = 5-8). j, Quantification of average day-time, night-time, and total RER in males (n = 5-8). k, ITT (left) and AUC (right) in males (n = 13-16). l, Kaplan-Meier survival curves for control and γ2cKO males (n = 18). Panels a (right) to f and g (right) to k were assessed 20 weeks after tamoxifen induction. Data are mean ± s.e.m. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001 (unpaired two-tailed t-test or two-way ANOVA). In males, γ2cKO mice developed a parallel but more severe phenotype, with progressive weight gain, increased adiposity, hyperphagia, reduced dark-phase activity, decreased energy expenditure, elevated RER and marked insulin resistance, despite preserved fasting glucose and glucose tolerance ( Fig. 3g-k and Extended Data Fig. 6h-j ) . Strikingly, only males exhibited a significant reduction in lifespan ( Fig. 3l and Extended Data Fig. 6g ) , revealing a male-specific vulnerability to chronic AMPK activation. This decline was more pronounced and accelerated than that reported for astrocytic Bmal1 knockout 19 . Whereas BMAL1 functions as a transcriptional driver of the TTFL, AMPK operates as a bidirectional integrator of metabolic and temporal cues. Although AMPK activation is often associated with improved metabolic health and longevity 50 , our findings indicate that these require precise temporal control. In γ2cKO mice, persistent, phase-independent AMPK activation disrupts hypothalamic timing and drives chronic peripheral metabolic stress. This dual burden accelerates physiological decline selectively in males, underscoring that the timing, rather than the magnitude, of AMPK activation is critical for organismal health. Female resilience may reflect sex-hormone-dependent enhancement of SCN adaptability, which could buffer both central and peripheral systems against chronic circadian and metabolic stress 23 , 34 , 46 – 48 . VMH astrocytic AMPK-PER2 signalling gates food anticipation Regularly scheduled feeding elicits food-anticipatory activity (FAA), a preprandial surge in locomotion that persists after SCN ablation 3 , 4 . The molecular clocks driving FAA, and their coupling to metabolic state, remain unknown, but evidence suggests they emerge from a distributed network of central and peripheral food-entrainable oscillators (FEOs) 3 , 4 . Because astrocytes and AMPK are established nutrient and energy sensors 24 – 28 , we hypothesised that astrocytic AMPK could be a critical driver of FAA. To test this, control, γ2cKO , and α1cKO mice were subjected to restricted feeding during the light phase ( ZT4-10 for six days, then ZT4-8 for four days 23 , 34 , 46 ) ( Fig. 4a ) . Controls exhibited robust FAA, with activity redistributed into the feeding window. In γ2cKO males, FAA was markedly blunted despite preserved total locomotion, whereas α1cKO mice showed exaggerated FAA, accompanied by reduced nocturnal activity ( Fig. 4b, c and Extended Data Fig. 7a, b, d, e ) . These opposing behavioural phenotypes were mirrored by distinct metabolic adaptations: γ2cKO males maintained elevated body weight despite reduced food intake, whereas α1cKO mice were hyperphagic and lost substantial weight (Extended Data Fig. 7c, f ) . Together, these bidirectional effects indicate that AMPK dynamics, rather than tonic levels, shape FAA expression. Download figure Open in new tab Fig. 4. AMPK-PER2 signalling in VMH astrocytes gates food-anticipatory behaviour. a, Diagram of the restricted-feeding (RF) schedule ( 6 h/day, ZT4-10 for 6 days; then 4 h/day, ZT4-8 for 4 days ) and experimental design for VMH-targeted AAV manipulations . b, Representative double-plotted actograms of locomotor activity during RF in γ2cKO , control, and α1cKO mice. c, Average locomotor activity profiles (left) and FAA quantification (right) in γ2cKO (upper panel, n = 9) and α1cKO mice (lower panel, n = 6-12) during RF4h. d, Immunoblot (left) and quantification of pAMPK and AMPK (right) in VMH from AMPKγ2 f/f mice injected with either AAV-GFAP-GFP or AAV-GFAP-Cre (n = 4). e, Locomotor activity profiles (left) and FAA quantification (right) following VMH-specific deletion of AMPKγ2 (n = 6-9). f, Representative VMH sections from Glast Cre-TdTomato mice showing astrocyte ablation after AAV-flex-taCASP3-TEVp injection. g, Locomotor activity profiles (left) and FAA quantification (right) following VMH astrocyte ablation (n = 4-5). h, PER2 knockdown in VMH astrocytes using AAV-shPER2. Representative immunoblot (left) and quantification of PER2 protein levels (right) (n = 6-7). i, Locomotor activity profiles (left) and FAA quantification (right) in shPER2-injected mice (n = 7). All activity data (panels c, e, g, i ) correspond to the RF4h phase conducted after 6 days of RF6h adaptation. Data are mean ± s.e.m. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001 (unpaired two-tailed t-test or two-way ANOVA). Given the pronounced FAA deficit in γ2cKO males, we examined this genotype in detail. Indirect calorimetry revealed persistently lower total energy expenditure (EE), resembling ad libitum profiles (Extended Data Fig. 7g ) . In both controls and γ2cKO mice, EE rhythms shifted toward the feeding window, consistent with partial alignment to mealtime 51 , but the day-time EE rise upon food availability was markedly attenuated in γ2cKO mice, despite similar nocturnal values. Under restricted feeding, their EE rhythms also displayed a lengthened circadian period (Extended Data Fig. 7g ) , indicating weaker FEO entrainment and impaired coupling to metabolic timing cues. At the molecular level, hypothalamic AMPK and ACCα phosphorylation in controls was higher at ZT4 (meal onset) than at ZT6, reflecting nutrient-responsive, phase-appropriate activation. This temporal adjustment was absent in γ2cKO males, which maintained elevated AMPK phosphorylation postprandially (Extended Data Fig. 7h ) , consistent with defective transduction of metabolic timing cues. These molecular deficits may underlie the blunted FAA observed in γ2cKO males. By contrast, α1cKO mice exhibited exaggerated FAA, suggesting that suppression of AMPK activity, rather than acute activation at meal onset, may be important for normal FAA expression, potentially via recruitment of AMPKα2 or other astrocytic nutrient-sensing pathways. γ2cKO females, however, retained FAA and behavioural rhythmicity under RF despite progressive weight gain (Extended Data Fig. 8 a-d) , indicating that FAA can persist despite marked metabolic dysregulation, potentially via sex-specific buffering within the FEO network. The ventromedial hypothalamus (VMH) senses feeding-fasting state and integrates metabolic and circadian signals 51 . Lesion studies have shown that VMH ablation suppresses FAA 52 , 53 although whether it harbours a bona fide FEO or participates in a distributed network remains debated 54 – 56 . This controversy stems partly from neuronal mapping studies, such as c-Fos immunoreactivity or electrophysiological recordings, that have not consistently detected food-entrainable neuronal involvement in the VMH 54 – 57 , methods that are inherently neuron-centric and overlook astrocytic dynamics. We therefore tested whether VMH astrocytes are required for FAA. Targeted deletion of AMPKγ2 in VMH astrocytes (AAV-GFAP-Cre in Prkag f/f mice) suppressed local pAMPK and abolished FAA ( Fig. 4d, e and Extended Data Fig. 8e ) , phenocopying the whole-brain γ2cKO phenotype. Selective astrocyte-specific ablation in the VMH (AAV-Caspase-3 in Glast Cre-TdTomato mice) produced the same outcome, eliminating FAA without affecting baseline locomotion ( Fig. 4f, g and Extended Data Fig. 8f ) . Similarly, knockdown of Per2 in VMH astrocytes (AAV-shPER2) again abolished FAA ( Fig. 4h, i and Extended Data Fig. 8g ) , identifying PER2 as a necessary downstream effector of astrocytic AMPK. This aligns with prior evidence that global, but not neuron-specific, Per2 deletion abolishes FAA 58 , 59 , implicating non-neuronal PER2 as essential for food-entrainable rhythms. Together, these results establish an AMPK-PER2 module in VMH astrocytes as essential for FAA. AMPK is a calcium-dependent circadian effector in the hypothalamus Although AMPK is canonically described as an energy sensor activated by elevated AMP/ATP ratios 28 , previous work, including our own (Extended Data Fig. 2b ) , has shown that hypothalamic AMPK activity exhibits robust circadian variation, peaking in the active phase 31 despite stable ATP levels in the brain 33 . This dissociation from energetic state indicates that AMPK activation is not solely a consequence of feeding-fasting cycles but is also under clock-dependent control. To directly separate nutrient-driven from circadian inputs, we performed time-resolved hypothalamic phosphoproteomics in mice fasted for 24 h, with sampling across the circadian cycle. Even in the absence of feeding cues, 347 phosphoproteins exhibited robust circadian oscillations ( Fig. 5a, b ) , revealing intrinsically generated phosphorylation rhythms. Unsupervised clustering identified two phosphorylation “rush hours” at ZT0 and ZT13, corresponding to the rest-activity transitions, and a prominent nocturnal module, absent under ad libitum -fed animals. This module was enriched for predicted upstream kinases, with AMPKα1 and AMPKα2 ranking among the top hits ( Fig. 5c ). These findings indicate that hypothalamic AMPK is rhythmically engaged under nutrient-deprived conditions, reinforcing its role as a circadian-gated metabolic integrator. Download figure Open in new tab Fig. 5. Circadian AMPK activation in the hypothalamus is gated by Ca²⁺ signalling. a, Heatmap of rhythmic hypothalamic phosphoproteins after 24-h fasting (left) or ad libitum feeding (right) across four circadian time points (n = 3-4 per group). b, Polar plot showing phase distribution of the 347 rhythmic phosphoproteins detected under fasting, highlighting “rush hours” of phosphorylation at ZT0 and ZT13. c, Kinase-substrate enrichment analysis showing the top predicted upstream kinases for daytime (yellow) and night-time (grey) phosphorylation profiles; red text indicates AMPK subunits. d, KEGG pathway enrichment analysis of differentially phosphorylated proteins at ZT0 (daytime, yellow) and ZT13 (night-time, grey). Bubble size represents -log₁₀ (p value), position indicates fold enrichment, and colour denotes peak phase. e, Quantification (left) and representative immunoblots (right) of pAMPK and pACCα in hypothalamic extracts from wild-type and IP₃R2KO mice under ad libitum feeding at ZT0 and ZT12 (n = 4-6 per group). f, Schematic model of night-time Ca²⁺-dependent AMPK activation in astrocytes. During the night, IP₃R2-mediated Ca²⁺ release activates CaMKK2, leading to AMPK phosphorylation. During the day, reduced Ca²⁺ flux limits AMPK activation. Data are mean ± s.e.m. * P < 0.05, **** P < 0.0001 (unpaired two-tailed t-test). Pathway enrichment analysis revealed a marked temporal segregation of phosphoproteins under fasting ( Fig. 5d ) . Day-time phosphoproteins mapped to GABAergic synapses and tight junctions, indicating predominant engagement of inhibitory and intercellular communication programmes, alongside metabolic pathways such as autophagy, cAMP signalling, and endocrine resistance. By contrast, the night-time module was enriched for neuroendocrine and metabolic coordination pathways, including neurotrophin, glucagon, vasopressin, and insulin signalling, indicating a shift in functional priorities between rest and active phases. Gene ontology analysis (Extended Data Fig. 9a ) reinforced this KEGG-based temporal partitioning: day-time phosphoproteins were dominated by glycolysis, translational regulation, and solute symport, whereas night-time targets were enriched for large-scale transport processes (protein and ion, including potassium), mRNA and rRNA processing, and ribosome biogenesis. This night-time profile under fasting likely reflects an adaptive increase in neurosecretory and biosynthetic capacity, positioning AMPK as a coordinator of hypothalamic circadian-metabolic alignment. Ca²⁺/calmodulin-dependent protein kinase 2 (CaMKK2) is highly expressed in hypothalamic circuits controlling energy balance and can phosphorylate AMPK independently of the AMP/ATP ratio 60 . Given that SCN astrocytes and neurons exhibit circadian Ca²⁺ dynamics 16 – 21 , we hypothesised that CaMKK2 could act as a Ca²⁺-dependent gatekeeper of the fasting-specific nocturnal AMPK programme. To test Ca²⁺ dependence in vivo , we examined IP₃R2KO mice, which lack astrocytic intracellular Ca²⁺ release 61 , 62 . In these mice, phosphorylation of AMPK and its downstream target ACCα did not follow the normal day-night variation from ZT0 to ZT12 ( Fig. 5e and Extended data Fig. 9b) . Importantly, these changes occurred under ad libitum feeding, indicating that astrocytic Ca²⁺-driven AMPK activation can occur independently of feeding-fasting cycles. Consistent with this, phosphoproteomics revealed higher CaMKK2 phosphorylation at Ser495 during the night-time in controls, whereas γ2cKO mice displayed elevated Ser495 phosphorylation at ZT6, flattening its normal temporal profile (Extended Data Fig. 9c ) . This effect was specific to CaMKK2, as no comparable day-night variation or genotype-dependent change was observed for CaMKK1. These findings indicate that constitutive activation of astrocytic AMPK alters the circadian regulation of CaMKK2 activity, potentially uncoupling Ca²⁺-sensitive kinase networks from their normal phase-dependent engagement. Together, these findings establish CaMKK2 as the Ca²⁺-dependent mediator linking circadian Ca²⁺ dynamics to the rhythmic activation of hypothalamic AMPK. This phase-dependent coupling operates independently of feeding cues and likely drives the fasting-associated night-time phosphorylation programme. More broadly, it extends Ca²⁺-based circadian signalling beyond the SCN and recasts AMPK as a dual-mode integrator of metabolic demand and circadian phase. Discussion We identify astrocytic AMPK as an intrinsically rhythmic, Ca²⁺-gated circadian effector that links metabolic state to time-of-day-specific hypothalamic signalling. Functioning outside canonical TTFLs, it orchestrates both molecular and behavioural timing, extending astrocyte-based timekeeping from the SCN 14 – 23 into hypothalamic circuits via a PER2-dependent pathway. At the mechanistic core, our data support a metabolically gated phospho-switch in which astrocytic AMPK activity promotes PER2 stability via phosphorylation at a conserved serine (Ser659/662). This framework aligns with the bidirectional period changes we observe in vivo : constitutive activation lengthens the free-running period, whereas deletion shortens it. This behaviour is consistent with the phospho-switch mechanism described for CK1ε, where phosphorylation of specific PER2 residues modulates its stability and circadian period 15 , 16 , 39 , 45 , while leaving open whether AMPK phosphorylates PER2 directly or acts indirectly via CK1 kinases. Traditionally viewed as an energy sensor triggered by low ATP 28 , AMPK here assumes a noncanonical role: it displays autonomous circadian rhythmicity under DD and remains independent of feeding cues, indicating intrinsic clock regulation. In this context, AMPK activation is predominantly driven by circadian Ca²⁺ dynamics, with CaMKK2 acting as the upstream conduit that links astrocytic Ca²⁺ rhythms to the core clockwork and its metabolic outputs. At the systems level, AMPK imposes temporal structure on the hypothalamic phospho-signalling networks. Under fasting, these networks segregate into complementary day- and night-time programmes, while rhythmicity in the phosphoproteome collapses when astrocytic AMPK signalling is chronically mistimed. Such chronic, phase-independent activation elicits metabolic dysfunction, with sex-dependent severity, and shortens lifespan in males. These outcomes highlight a general principle: for nutrient-sensing pathways, the timing of activation can be as critical as its magnitude 34 . The role of AMPK varies across tissues, reflecting differences in upstream inputs and downstream targets. This temporal dependency may help reconcile these differences and suggests a role for sex-dependent buffering of central-peripheral coupling under chronic circadian or metabolic stress 23 , 34 , 46 – 49 . Functionally, AMPK-PER2 signalling in VMH astrocytes is necessary for FAA, serving as a cellular and molecular entry point into the FEO and indicating that the temporal pattern, rather than tonic levels, of AMPK activity is the relevant timekeeping signal. Rodents can anticipate multiple daily meals, including those scheduled under different zeitgeber periods (e.g., non-24-h T-cycles) 3 , 4 , 63 , 64 , features generally attributed to distributed, flexibly coupled FEOs. In this context, gap-junction-coupled astrocyte networks that interconnect hypothalamic nuclei 65 provide a plausible substrate for coordinating phases across sites, allowing local VMH timing to align with distal FEO nodes. In parallel, given the rapid and reversible nutrient sensitivity of the AMPK-PER2 axis, a single VMH astrocyte population could, in principle, support “multiphase” anticipation via phase-staggered bouts of AMPK activity for distinct meals. This work have broad implications. First, they establish AMPK as an astrocytic clock component that meets canonical criteria, including rhythmic activation, intrinsic timing, and regulation of circadian outputs, while operating independently of the core TTFL. Second, they delineate a glial AMPK-PER2 axis that gates food-anticipatory behaviour from the VMH. Third, they bridge metabolic and circadian systems through a Ca²⁺-gated mechanism that integrates internal state with temporal architecture. Finally, they point to disease-relevant convergence: AMPK and PER2 are linked to metabolic and circadian disorders, including Wolff-Parkinson-White syndrome and FASP 36 – 38 , 44 , respectively. Notably, AMPK phosphorylates PER2 at the same serine residue mutated in FASP, suggesting that their intersection in astrocytes may represent a therapeutically targetable axis in metabolic and circadian disorders. Together, these findings provide a conceptual bridge between glial biology, central metabolism, and circadian behaviour. Methods Animals All mice were bred and maintained at the animal facilities of the University of Santiago de Compostela in strict accordance with Spanish and European Union legislation on animal care. All procedures were approved by the University of Santiago de Compostela Ethics Committee, in compliance with Directive 2010/63/EU (Projects IDs 15012/2020/010 and 15012/2021/011). Mice were housed under standard conditions (12-h light/dark cycle, ZT0 = lights on at 08:00), in a temperature- and humidity-controlled environment, with ad libitum access to standard chow (Teklad-7913, Envigo) and water. To generate conditional knockout ( cKO ) mice, AMPKγ2 f/f (B6N.Cg- Prkag2 tm1.1Rto/J, The Jackson Laboratory, #030979) and AMPKα1 f/f ( Prkaa1 tm1.1Sjm/J, The Jackson Laboratory, #014141) lines were crossed with the Glast CreERT 2 mice 35 (kind gift from M. Götz, Ludwig-Maximilians-University, Germany). In some experiments, these mice were further crossed with the tdTomato reporter strain (B6. Cg-Gt (ROSA)26Sor tm14(CAG-tdTomato) Hze/J, The Jackson Laboratory, #007914). γ2cKO , α1cKO , and littermate controls ( AMPKγ2 f/f or AMPKα1 f/f ) aged 12-16 weeks received oral gavage of tamoxifen (5 mg/day; Sigma-Aldrich, T-5648) dissolved in corn oil (Sigma-Aldrich, C-8267) for two consecutive days to induce recombination 19 , 20 , 23 , 34 , 35 , 66 . Mice were allowed to recover, and experiments commenced after a two-month tamoxifen washout, according to the timelines specified for each assay. Hypothalamic samples from IP 3 R2 knockout mice were obtained by João Filipe Oliveira from mice originally shared by Prof. Alfonso Araque (Minneapolis, MN, USA), under an agreement with Prof. Ju Chen (University of California, San Diego, CA, USA). Adult male C57BL/6J mice (12-16 weeks old) were obtained from the institutional facility. Postnatal day 1-3 Sprague Dawley rats (crl:SD 400; Charles River Laboratories, Spain) of both sexes were used for primary astrocyte cultures. Pups were housed with their dams under a 12:12 h light-dark cycle in a temperature- and humidity-controlled room, with ad libitum access to food and water. Circadian locomotor activity Circadian activity rhythms were assessed in 4-to 5-month-old γ2cKO , α1cKO , and control mice using running wheel assays. Mice were single-housed in ventilated cages equipped with low-profile wireless running wheels (ENV-044; Med Associates Inc.). Males and females were housed separately on independent ventilated racks to prevent sex-related olfactory or social interference. All cages were maintained under uniform lighting conditions in the same room to ensure consistent light exposure across groups (14-16, 18, 19, 38). Animals were acclimated to the wheels for 3 days under a 12-h light/12-h dark (LD) cycle, followed by 7-10 days of LD recording. Mice were then transferred to fully blacked-out cages (Tecniplast) and maintained in constant darkness (DD) for 3-4 weeks 19 , 20 , 23 , 34 , 46 . Wheel-running activity was recorded in 5-min bins using Wheel Manager software (SOF-860; Med Associates Inc.) and analyzed with ActogramJ. LD activity was plotted using zeitgeber time (ZT), with ZT0 defined as lights on. For DD conditions, data were plotted using circadian time (CT), adjusted to each animal’s endogenous period. Mean activity profiles were generated by averaging 5-min binned activity over 7-10 consecutive stable days. Free-running period and rhythm amplitude were estimated with Lomb-Scargle periodograms. Female data were collected across multiple estrous cycles to account for intra-individual variability 19 , 20 , 23 , 34 , 46 Metabolic and physiological assessments Body weight and food intake were recorded weekly. Whole-body composition was determined by nuclear magnetic resonance (NMR) using an EchoMRI analyzer (EchoMRI, Houston, TX) 23 , 34 , 46 , 67 – 69 . Skin temperature over the interscapular brown adipose tissue (BAT) was assessed via infrared thermography (FLIR B335 camera; FLIR Systems) and analyzed with FLIR Tools software. For each animal, three dorsal images were acquired, and average BAT surface temperature was calculated 23 , 34 , 46 , 67 – 69 . Measurements were performed at a fixed Zeitgeber time (ZT8) to control for circadian variation. Rectal temperature was measured with a digital thermistor probe immediately before imaging. Food restriction experiments Food-entrainable circadian rhythms were assessed in control, γ2cKO , and α1cKO mice (14 weeks after tamoxifen-induced recombination), as well as mice subjected to stereotaxic VMH injections of AAV-Cre ( AMPKγ2 f/f ), AAV-flex-taCasp3-TEVp ( Glast CreERT 2 ), or shRNA targeting Per2 (AAV [miR30]-GFAP-EGFP) and respective controls. All mice were single-housed in cages equipped with running wheels (ENV-044; Med Associates Inc.) under 12-h: 12-h LD conditions. Water was available ad libitum throughout RF. Prior to restricted feeding (RF), baseline wheel-running activity was recorded for 7 days under ad libitum feeding. Body weight and food intake were measured at zeitgeber time 4 (ZT4). Mice were then subjected to a 10-day RF schedule: during the first 6 days, food access was limited to ZT4-ZT10; for the remaining 4 days, it was further restricted to ZT4-ZT8 23 , 34 , 46 . Standard chow (Envigo) was provided during these windows. Food consumption was monitored daily by weighing pellets at the beginning (ZT4) and end (ZT10 or ZT8) of each feeding period, with values corrected for spillage. Locomotor activity was recorded in 5-min bins using Wheel Manager software (SOF-860; Med Associates Inc.) and analyzed with ActogramJ 23 , 34 , 46 . Indirect calorimetry Energy expenditure, respiratory exchange ratio (RER), and locomotor activity were measured using an open-circuit indirect calorimetry system (LabMaster; TSE Systems). Mice were acclimated to metabolic cages for 24 h, prior to data acquisition over the following 48- 72 h 23,34,46,67–69. Glucose and insulin tolerance test For glucose tolerance tests (GTT), mice were fasted for 6 h and injected intraperitoneally with D-glucose (2 g/kg; Sigma-Aldrich, G8270). For insulin tolerance tests (ITT), human insulin (Actrapid; Novo Nordisk) was administered at 0.75 IU/kg for males and 0.35 IU/kg for females. Blood glucose levels were measured at designated time points using a handheld glucometer 19,23,34,46,67–69. Western blotting Protein expression analyses were performed on tissue samples from the hypothalamus, mediobasal hypothalamus (MBH), brown adipose tissue (BAT), and on primary hypothalamic astrocytes derived from neonatal rats. Samples were homogenized in ice-cold lysis buffer containing 0.05 M Tris-HCl, 0.01 M EGTA, 0.001 M EDTA, 0.016 M Triton X-100, 0.001 M sodium orthovanadate, 0.05 M sodium fluoride, 0.01 M sodium pyrophosphate, and 0.25 M sucrose (all from Sigma-Aldrich), adjusted to pH 7.5. Protease inhibitor cocktail (Roche Diagnostics) was added fresh prior to homogenization 19 – 21 , 23 , 34 , 46 , 67 – 69 . Protein concentration was determined using the Bradford assay (Bio-Rad). Equal amounts of protein were separated by SDS-PAGE and transferred to nitrocellulose membranes (Protran, Schleicher & Schuell). Membranes were blocked in 5% non-fat dry milk in TBS-T (20 mM Tris-HCl, 150 mM NaCl, 0.1% Tween-20) for 1 h at room temperature. Membranes were incubated with primary antibodies against: PER2 (1:1000, Invitrogen PA5-89045), phospho-PER2 (Ser662) (1:1000, Invitrogen PA538901); CRY1 (1:1000, Invitrogen PA5-89349), UCP1 (1:1000, Abcam ab10983), phospho-AMPK (1:1000, Cell Signaling #2535S), total AMPK (1:1000, Cell Signaling #2532), AMPKγ1 (1:1000, Thermo Fisher PA5-27471), VIP (1:500, Invitrogen PA5-78224), AVP (1:1000, Santa Cruz Biotechnology sc-390723), phospho-ACC (pACC) (1:1000, Cell Signaling #3661S), and total ACC (1:1000, Cell Signaling #3662S). HRP-conjugated secondary antibodies (sc-2357 and sc-525408; Santa Cruz Biotechnology) were used at 1:2000. After detection, membranes were stripped (Thermo Fisher, #46430) and re-probed with loading control antibodies: GAPDH (1:5000, Santa Cruz Biotechnology sc-25778), β-actin (1:5000, Sigma-Aldrich A5316), or α-tubulin (1:5000, Sigma-Aldrich AB_330337), depending on tissue source. Immunoreactive bands were visualized using enhanced chemiluminescence (ECL; GE Healthcare) and exposed to autoradiographic film (Fujifilm). Band intensity was quantified by densitometry using ImageJ 1.33 (NIH). Signals were normalized to GAPDH (primary astrocytes), β-actin (hypothalamus), or α-tubulin (BAT). Representative images are shown for each target protein; for loading controls, one representative gel is displayed, though each target was internally normalized. All bands shown originate from the same gel, with digital repositioning applied when necessary for clarity 19 – 21 , 23 , 34 , 46 , 67 – 69 . Immunofluorescence Mice were deeply anesthetized with ketamine/xylazine (150 mg/kg and 10 mg/kg, i.p.) and transcardially perfused with ice-cold phosphate-buffered saline (PBS), followed by 4% paraformaldehyde (PFA; Fisher 10342243) in PBS. Brains were post-fixed overnight in 4% PFA at 4 °C, then coronally sectioned at 30 μm using a cryostat (Leica Microsystems). Free-floating sections were permeabilized with 0.3% Triton X-100 in PBS, blocked with 10% goat serum for 1 h at room temperature, and incubated overnight at 4 °C with rabbit anti-VIP (1:500, Invitrogen PA5-78224) and phospho-ACC (pACC; 1:50, Cell Signaling #3661S). The next day, sections were washed and incubated for 2 h at room temperature with Alexa Fluor™ conjugated secondary antibodies (Alexa Fluor™ 647 and Alexa Fluor™ 488) (goat anti-rabbit or anti-mouse, Alpaca anti-Human IgG/Rabbit IgG VHH, Nano-Secondaries™, SRBAF647-1-100 and SRBAF488-1-100; ChromoTek). Slices were mounted using ProLong Gold Antifade Mountant (Thermo Fisher Scientific, P36934) and imaged with a Leica TCS SP5 inverted laser scanning confocal microscope equipped with 20× and 40× objectives. Quantification was performed using ImageJ (NIH). Regions of interest (ROIs), including the SCN, VMH, and ARC, were delineated based on DAPI nuclear staining, and average fluorescence intensity of the target signal (e.g., VIP) was measured. For each animal, the mean value from consecutive sections was used as a single biological replicate 19 – 23 , 34 , 46 , 66 . Immunohistochemistry Brown adipose tissue samples were fixed in 10% neutral-buffered formalin for 24 h, dehydrated, and embedded in paraffin using standard procedures. Serial sections (3 μm thick) were obtained with a rotary microtome. For immunohistochemical detection of UCP1, sections were incubated with a rabbit anti-UCP1 primary antibody (1:2000; Abcam ab10983) followed by appropriate secondary detection. UCP1-positive cells were visualized and quantified using ImageJ, based on thresholded staining intensity 23 , 34 , 67 – 69 . Primary hypothalamic astrocytes cultures Primary monolayer cultures of astrocytes were established from the hypothalamus of neonatal (P1-P3) Sprague Dawley rats 20 – 22 , 34 , 70 – 74 . Neonatal rat pups were decapitated using sharp scissors. Astrocyte cultures were maintained at 37 °C in a humidified 5% CO₂ atmosphere for 1 week. After that, cells were trypsinized and subcultured for experiments. These astrocyte-enriched cultures contained >96% astrocytes, as indicated by immunofluorescence with a monoclonal anti-GFAP antibody (clone 6F2, Dako; 1:1000 dilution) (15-19, 48-54). Astrocytes were treated with AICAR (1 mM; Thermo Scientific, CAS: 2627-69-2) and/or cycloheximide (CHX, 50 μg/mL; Thermo Scientific, CAS: 66-81-9) in medium containing either low (1000 mg/L) or high (4500 mg/L) glucose. Phosphoproteomic sample preparation Hypothalamic tissues were homogenized using a FastPrep-24™ 5G instrument (MP Biomedicals) in lysis buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 200 mM DTT, and phosphatase inhibitor cocktail. Following sonication and centrifugation, proteins were precipitated with acetone overnight; this precipitation step was repeated three times. After the final precipitation, protein pellets were resuspended in lysis buffer lacking phosphatase inhibitors and quantified. Proteins were digested following a modified filter-aided sample preparation (FASP) protocol as described by Wiśniewski et al., with minor modifications 75 . Trypsin was added at a 1:20 enzyme-to-substrate ratio and incubated overnight at 37 °C. Resulting peptides were dried in a vacuum concentrator (RVC2 25, Christ) and resuspended in 0.1% formic acid. Phosphopeptides were enriched using the High-Select™ TiO₂ Phosphopeptide Enrichment Kit (Thermo Fisher Scientific) according to the manufacturer’s instructions (∼500 µg input per sample). Eluted phosphopeptides were directly subjected to LC-MS/MS analysis. Phosphopeptide mass spectrometry and data analysis Phosphopeptide samples (∼20% of enriched material) were loaded onto an Evosep One system (Evosep) coupled online to a timsTOF Pro mass spectrometer using PASEF acquisition (Bruker Daltonics). Separation was performed using the 30 samples-per-day Evosep protocol. Raw data were processed using FragPipe ( https://fragpipe.nesvilab.org/ ) against the Mus musculus UniProt/Swiss-Prot database, with precursor and fragment mass tolerances of 20 ppm and 0.05 Da, respectively. Carbamidomethylation of cysteine was set as a fixed modification; methionine oxidation and phosphorylation of serine, threonine, and tyrosine were specified as variable modifications. Peptide identifications were filtered at 1% FDR. Quantitative values from FragPipe were log₂-transformed and analyzed in Perseus 76 . Phosphopeptides present in ≥70% of samples in any experimental group were retained. Missing values were imputed based on a normal distribution of the lowest 10% of signal intensities within each sample. In silico analysis In silico analyses were performed on hypothalamic phosphoproteomic datasets obtained from mice subjected to 24 h of food deprivation. Animals were sacrificed at four circadian time points (ZT0, ZT6, ZT12, and ZT18) to capture temporal phosphorylation dynamics across the light-dark cycle. Additionally, phosphoproteomic profiles were generated from the hypothalami of control and γ2cKO mice, collected at ZT6 and ZT18, to assess genotype-specific effects on circadian phosphorylation. To identify circadian rhythmic phosphorylation events, data from starved wild-type mice were analyzed using BIO_CYCLE via the CircadiOmics web portal ( https://circadiomics.igb.uci.edu/biocycle ), which fits cosine curves assuming a ∼24 h periodicity 77 , 78 . Phosphopeptides were considered rhythmic if they exhibited significant fits (q < 0.05, Benjamini-Hochberg). When multiple peptides mapped to the same protein, the one with the highest rhythmic amplitude was retained for downstream analysis. Rhythmic phosphopeptides were grouped by peak phase and clustered based on z-scored intensity profiles across time points 34 . The number of temporal clusters was determined by minimizing the the Bayesian Information Criterion (BIC). Functional enrichment analysis was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations via the DAVID Bioinformatics Resource ( https://david.ncifcrf.gov/ ), applying default parameters for GO Biological Process (BP_FAT) terms to prioritize specific over broad categories 34 . Kinase-substrate enrichment analysis was conducted using KEA3 (Kinase Enrichment Analysis 3; https://maayanlab.cloud/kea3/ ), which predicts upstream kinase activity based on the overrepresentation of known kinase-substrate relationships in the input phosphopeptide set. Default settings were used throughout. Statistical analysis Data are presented as mean ± s.e.m. and were analyzed using GraphPad Prism 10 (GraphPad Software, San Diego, CA, USA). Exact n values, statistical tests, and measures of variability are reported in the figure legends. Statistical significance was assessed using multiple approaches depending on the experimental design. For paired or unpaired comparisons, two-tailed Student’s t-tests were used as appropriate. Two-way repeated-measures ANOVA with Bonferroni post hoc correction was used for time-course and repeated-measures data. All datasets were tested for normality and homogeneity of variance prior to analysis. Rhythmicity in gene or protein expression was evaluated using Cosinor analysis, and circadian parameters (period, phase, mesor, amplitude) were extracted accordingly 19 – 23 , 34 , 46 , 66 . Outlier samples were excluded based on pre-established criteria: values exceeding ±2 standard deviations from the group mean. In food-restriction experiments, food anticipatory activity (FAA) was quantified as the duration (in hours) of wheel-running activity during the pre-feeding period. The FAA ratio was calculated as the fold change in activity during the 4 h preceding food availability relative to the rest of the day. Similarly, the nocturnal activity ratio was defined as the fold change in activity during the dark phase compared to total daily activity 23 , 34 , 46 . Author contributions O.B.-M. conceptualized the study, designed the experimental framework and supervised the overall project. M.L. generated and provided the γ2cKO and α1cKO mouse lines. M.L.-M. and A.G.-V. performed most of the experiments. O.B.-M., M.L.-M. and A.G.-V. analysed and interpreted the data. M.S.-L. carried out the metabolic characterization of the mouse models. A.M.I.-A., V.P.-G., H.L.-G., H.C.M., N.R.V.D., P.F.-S. and A.M.E.-S. provided technical support and assisted in sample collection and western blot analyses. J.F.O. and D.S.A. contributed IP₃R2KO hypothalamic samples. F.E. and M.Az. conducted the phosphoproteomic experiments and bioinformatic analyses. O.B.-M. wrote the manuscript with input from all authors. M.L., M.As., C.C., C.D., M.F. and D.G. contributed to manuscript editing and refinement. Data and materials availability All data supporting the findings of this study are available from the corresponding authors upon request. Competing interests M.L. serves as Scientific Director of Gazella Biotech ( https://gazellabiotech.com/ ). The rest of the authors have no other conflicts of interest. Acknowledgments We thank Dr. M. Götz (Physiological Genomics, Biomedical Center, Ludwig-Maximilians-University Munich, Germany) for providing the Glast CreERT 2 mouse line. We also thank Prof. Michael Hastings and Dr. Andrew Patton (MRC Laboratory of Molecular Biology, Cambridge, UK), and Prof. Rubén Nogueiras (CiMUS, University of Santiago de Compostela, Spain) for scientific discussions. We thank the technical staff at CiMUS for support, and the USC Animal Facility (CEBEGA) for assistance with animal care and experimentation. Some figures were created using BioRender.com (2025) and adapted from templates available at https://app.biorender.com/biorender-templates . This research was supported by the Xunta de Galicia (ED431F 2020/009 and ED431C 2023/28 to O.B.-M.; ED431G/05, 2020-2023, institutional support to CiMUS); the Agencia Estatal de Investigación (AEI), Spain (PID2019-109556RB-I00 and PID2022-138436OB-I00 to O.B.-M.; PID2021-128145NB-I00 and PDC2022-133958-I00 to M.L.); the la Caixa Foundation (LCF/PR/HR19/52160022 and LCF/PR/HR20/52400013 to M.L.; LCF/PR/HR21/52410024 to J.F.O.); the Fundación AECC (PRYGN234908LOPE to M.L.); the Fundação para a Ciência e a Tecnologia (FCT), Portugal (CEECINST/00018/2021, UIDB/50026/2020, UIDP/50026/2020 and LA/P/0050/2020 to J.F.O.); and the Bial Foundation (156/24 to J.F.O.). M.L.-M. and A.G.-V. are supported by the Ministerio de Ciencia, Innovación y Universidades, Spain (PRE2020-093614 and PID2022-138436OB-I00, respectively). D.S.A. is supported by a Foundation for Science and Technology (FCT) fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funder Information Declared Xunta de Galicia, https://ror.org/0181xnw06 , ED431F 2020/009 , ED431C 2023/28 , ED431G/05, 2020-2023 Agencia Estatal de Investigación , PID2019-109556RB-I00 , PID2022-138436OB-I00 , PID2021-128145NB-I00 , PDC2022-133958-I00 La Caixa Foundation , LCF/PR/HR19/52160022 , LCF/PR/HR20/52400013 , LCF/PR/HR21/52410024 Fundación AECC , PRYGN234908LOPE Fundação para a Ciência e Tecnologia , CEECINST/00018/2021 , UIDB/50026/2020 , UIDP/50026/2020 , LA/P/0050/2020 Bial Foundation , 156/24 Ministerio de Ciencia, Innovación y Universidades , PRE2020-093614 , PID2022-138436OB-I00 Footnotes ↵ † Co-senior authors References 1. ↵ Koronowski , K. B. & Sassone-Corsi , P . Communicating clocks shape circadian homeostasis . Science 371 , 1 – 9 ( 2021 ). OpenUrl CrossRef 2. ↵ Hastings , M. H. , Maywood , E. S. & Brancaccio , M . The mammalian circadian timing system and the suprachiasmatic nucleus as its pacemaker . Biology (Basel ) 8 , 13 ( 2019 ). 3. ↵ Mistlberger , R. E . Food as circadian time cue for appetitive behavior . F1000Research 9 , 1 – 12 ( 2020 ). OpenUrl 4. ↵ Petersen , C. C. , Cao , F. , Stinchcombe , A. R. & Mistlberger , R. E . Multiple entrained oscillator model of food anticipatory circadian rhythms . Sci. Rep . 12 , 1 – 15 ( 2022 ). OpenUrl CrossRef PubMed 5. ↵ Herzog , E. D. , Hermanstyne , T. , Smyllie , N. J. & Hastings , M. H . Regulating the suprachiasmatic nucleus (SCN) circadian clockwork: interplay between cell-autonomous and circuit-level mechanisms . Cold Spring Harb. Perspect. Biol . 9 , a027706 ( 2017 ). OpenUrl Abstract / FREE Full Text 6. Welsh , D. K. , Takahashi , J. S. & Kay , S. A . Suprachiasmatic nucleus: cell autonomy and network properties . Annu. Rev. Physiol . 72 , 551 – 577 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 7. ↵ Dibner , C. , Schibler , U. & Albrecht , U . The mammalian circadian timing system: organization and coordination of central and peripheral clocks . Annu. Rev. Physiol . 72 , 517 – 549 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 8. ↵ Mehra , A. , Baker , C. L. , Loros , J. J. & Dunlap , J. C . Post-translational modifications in circadian rhythms . Trends Biochem. Sci . 34 , 483 – 490 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 9. ↵ Brenna , A. & Albrecht , U. Phosphorylation and circadian molecular timing . Front. Physiol. 11 , 612510 ( 2020 ). OpenUrl CrossRef PubMed 10. ↵ Robles , M. S. , Humphrey , S. J. & Mann , M . Phosphorylation is a central mechanism for circadian control of metabolism and physiology . Cell Metab . 25 , 118 – 127 ( 2017 ). OpenUrl CrossRef PubMed 11. ↵ Larrondo , L. F. , Olivares-Yañez , C. , Baker , C. L. , Loros , J. J. & Dunlap , J. C . Decoupling circadian clock protein turnover from circadian period determination . Science 347 , 1257277 ( 2015 ). OpenUrl Abstract / FREE Full Text 12. ↵ Nakajima , M. et al. Reconstitution of circadian oscillation of cyanobacterial KaiC phosphorylation in vitro . Science 308 , 414 – 415 ( 2005 ). OpenUrl Abstract / FREE Full Text 13. ↵ Robles , M. S. , Cox , J. & Mann , M . In vivo quantitative proteomics reveals a key contribution of post-transcriptional mechanisms to the circadian regulation of liver metabolism . PLoS Genet . 10 , e1004047 ( 2014 ). OpenUrl CrossRef PubMed 14. ↵ Prolo , L. M. , Takahashi , J. S. & Herzog , E. D . Circadian rhythm generation and entrainment in astrocytes . J. Neurosci . 25 , 404 – 408 ( 2005 ). OpenUrl Abstract / FREE Full Text 15. ↵ Tso , C. F. et al. Astrocytes regulate daily rhythms in the suprachiasmatic nucleus and behavior . Curr. Biol . 27 , 1055 – 1061 ( 2017 ). OpenUrl CrossRef PubMed 16. ↵ Brancaccio , M. , Patton , A. P. , Chesham , J. E. , Maywood , E. S. & Hastings , M. H . Astrocytes control circadian timekeeping in the suprachiasmatic nucleus via glutamatergic signaling . Neuron 93 , 1420 – 1435 .e5 ( 2017 ). OpenUrl PubMed 17. Brancaccio , M. et al. Cell-autonomous clock of astrocytes drives circadian behavior in mammals . Science 363 , 187 – 192 ( 2019 ). OpenUrl Abstract / FREE Full Text 18. Patton , A. P. et al. Astrocytic control of extracellular GABA drives circadian timekeeping in the suprachiasmatic nucleus . Proc. Natl. Acad. Sci. U.S.A . 120 , e2303138120 ( 2023 ). OpenUrl 19. ↵ Barca-Mayo , O. , Boender , A. J. , Armirotti , A. & De Pietri Tonelli , D . Deletion of astrocytic BMAL1 results in metabolic imbalance and shorter lifespan in mice . Glia 68 , 1131 – 1147 ( 2020 ). OpenUrl CrossRef PubMed 20. ↵ Barca-Mayo , O. et al. Astrocyte deletion of Bmal1 alters daily locomotor activity and cognitive functions via GABA signalling . Nat. Commun . 8 , 14336 ( 2017 ). 21. ↵ Giantomasi , L. et al. Astrocytes actively support long-range molecular clock synchronization of segregated neuronal populations . Sci. Rep . 13 , 4815 ( 2023 ). OpenUrl PubMed 22. ↵ Barca-Mayo , O. , Berdondini , L. & De Pietri Tonelli , D . Astrocytes and circadian rhythms: An emerging astrocyte-neuron synergy in the timekeeping system . Methods Mol. Biol . 1938 , 183 – 197 ( 2019 ). OpenUrl 23. ↵ Luengo-Mateos , M. et al. Hypothalamic astrocytic-BMAL1 regulates energy homeostasis in a sex-dependent manner . Cell Rep . 42 , 112949 ( 2023 ). 24. ↵ Barca-Mayo , O. & López , M. Astrocyte clocks and glucose homeostasis . Front. Endocrinol. (Lausanne) 12 , 662594 ( 2021 ). OpenUrl 25. ↵ García-Cáceres , C. et al. Role of astrocytes, microglia, and tanycytes in brain control of systemic metabolism . Nat. Neurosci . 22 , 7 – 14 ( 2019 ). OpenUrl CrossRef PubMed 26. ↵ Bolaños , J. P . Bioenergetics and redox adaptations of astrocytes to neuronal activity . J. Neurochem . 139 Suppl. 2 , 115 – 125 ( 2016 ). OpenUrl CrossRef PubMed 27. Almeida , A. , Moncada , S. & Bolaños , J. P . Nitric oxide switches on glycolysis through the AMP protein kinase and 6-phosphofructo-2-kinase pathway . Nat. Cell Biol . 6 , 45 – 51 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 28. ↵ López , M. , Nogueiras , R. , Tena-Sempere , M. & Diéguez , C . Hypothalamic AMPK: a canonical regulator of whole-body energy balance . Nat. Rev. Endocrinol . 12 , 421 – 432 ( 2016 ). OpenUrl CrossRef PubMed 29. ↵ Lamia , K. A. et al. AMPK regulates the circadian clock by cryptochrome phosphorylation and degradation . Science 326 , 437 – 440 ( 2009 ). OpenUrl Abstract / FREE Full Text 30. Lee , Y. & Kim , E. K . AMP-activated protein kinase as a key molecular link between metabolism and clockwork . Exp. Mol. Med . 45 , e33 ( 2013 ). OpenUrl CrossRef PubMed 31. ↵ Um , J. H. et al. AMPK regulates circadian rhythms in a tissue- and isoform-specific manner . PLoS One 6 , e18450 ( 2011 ). OpenUrl CrossRef PubMed 32. ↵ Aton , S. J. et al. Vasoactive intestinal polypeptide mediates circadian rhythmicity and synchrony in mammalian clock neurons . Nat. Neurosci . 8 , 476 – 483 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 33. ↵ Dworak , M. , McCarley , R. W. , Kim , T. , Kalinchuk , A. V. & Basheer , R . Sleep and brain energy levels: ATP changes during sleep . J. Neurosci . 30 , 9007 – 9016 ( 2010 ). OpenUrl Abstract / FREE Full Text 34. ↵ González-Vila , A. et al. Astrocytic insulin receptor controls circadian behavior via dopamine signaling in a sexually dimorphic manner . Nat. Commun . 14 , 1 – 21 ( 2023 ). OpenUrl CrossRef PubMed 35. ↵ Mori , T. et al. Inducible gene deletion in astroglia and radial glia: a valuable tool for functional and lineage analysis . Glia 54 , 21 – 34 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 36. ↵ Yavari , A. , Sarma , D. & Sternick , E. B . Human γ2-AMPK mutations . Methods Mol. Biol . 1732, 581-619 ( 2018 ). 37. Yavari , A. et al. Chronic activation of γ2 AMPK induces obesity and reduces β cell function . Cell Metab . 23 , 821 – 832 ( 2016 ). OpenUrl CrossRef PubMed 38. ↵ Hu , D. et al. Identification, clinical manifestation and structural mechanisms of mutations in AMPK associated cardiac glycogen storage disease . EBioMedicine 54 , 102721 ( 2020 ). 39. ↵ Jee , H. U. et al. Activation of 5′-AMP-activated kinase with diabetes drug metformin induces casein kinase Iε-dependent degradation of clock protein mPER2 . J. Biol. Chem . 282 , 20794 – 20798 ( 2007 ). OpenUrl Abstract / FREE Full Text 40. ↵ Hassan , S. A. , Wendrich , K. S. & Albrecht , U . Deletion of clock gene Period 2 ( Per2 ) in astrocytes shortens clock period but does not affect light-mediated phase shifts in mice . Clocks Sleep 7 , 37 ( 2025 ). 41. ↵ van Rosmalen , L. et al. Energy balance drives diurnal and nocturnal brain transcriptome rhythms . Cell Rep . 43 , 113951 ( 2024 ). 42. ↵ Cao , Y. et al. Activation of γ2-AMPK suppresses ribosome biogenesis and protects against myocardial ischemia/reperfusion injury . Circ. Res . 121 , 1182 – 1191 ( 2017 ). OpenUrl Abstract / FREE Full Text 43. ↵ Toh , K. L. et al. An hPer2 phosphorylation site mutation in familial advanced sleep phase syndrome . Science 291 , 1040 – 1043 ( 2001 ). OpenUrl Abstract / FREE Full Text 44. ↵ Jordan , S. D. & Lamia , K. A . AMPK at the crossroads of circadian clocks and metabolism . Mol. Cell. Endocrinol . 366 , 163 – 169 ( 2013 ). OpenUrl CrossRef PubMed 45. ↵ Vanselow , K. et al. Differential effects of PER2 phosphorylation: molecular basis for the human familial advanced sleep phase syndrome . Genes Dev . 20 , 2660 – 2672 ( 2006 ). OpenUrl Abstract / FREE Full Text 46. ↵ González-Vila , A. et al. IL-6 decodes sex- and diet-dependent circadian and metabolic rhythms . Mol. Metab . 97 , 102171 ( 2025 ). 47. Anderson , S. T. & Fitzgerald , G. A . Sexual dimorphism in body clocks . Science 369 , 1164 – 1165 ( 2020 ). OpenUrl Abstract / FREE Full Text 48. ↵ Morris , A . Sex differences in circadian misalignment . Nat. Rev. Endocrinol . 16 , 68 – 69 ( 2020 ). OpenUrl 49. ↵ Schlaeger , L. et al. Estrogen-mediated coupling via gap junctions in the suprachiasmatic nucleus . Eur. J. Neurosci . 59 , 1723 – 1742 ( 2024 ). OpenUrl PubMed 50. ↵ Burkewitz , K. , Zhang , Y. & Mair , W. B . AMPK at the nexus of energetics and aging . Cell Metab . 20 , 10 – 25 ( 2014 ). OpenUrl CrossRef PubMed 51. ↵ Orozco-Solis , R. et al. The circadian clock in the ventromedial hypothalamus controls cyclic energy expenditure . Cell Metab . 23 , 1 – 12 ( 2016 ). OpenUrl PubMed 52. ↵ Mistlberger , R. E. & Rechtschaffen , A . Recovery of anticipatory activity to restricted feeding in rats with ventromedial hypothalamic lesions . Physiol. Behav . 33 , 227 – 235 ( 1984 ). OpenUrl CrossRef PubMed 53. ↵ Inouye , S. I. T . Ventromedial hypothalamic lesions eliminate anticipatory activities of restricted daily feeding schedules in the rat . Brain Res . 250 , 183 – 187 ( 1982 ). OpenUrl CrossRef PubMed Web of Science 54. ↵ Choi , S. J. , Wong , L. S. , Yamat , C. & Dallman , M. F . Hypothalamic ventromedial nuclei amplify circadian rhythms: do they contain a food-entrained endogenous oscillator? J. Neurosci . 18 , 3843 – 3852 ( 1998 ). OpenUrl Abstract / FREE Full Text 55. Ribeiro , A. C. , Lesauter , J. , Dupré , C. & Pfaff , D. W . Relationship of arousal to circadian anticipatory behavior: ventromedial hypothalamus, one node in a hunger/arousal network . Eur. J. Neurosci . 30 , 1730 – 1738 ( 2009 ). OpenUrl CrossRef PubMed 56. ↵ Inouye , S. I. T . Does the ventromedial hypothalamic nucleus contain a self-sustained circadian oscillator associated with periodic feedings? Brain Res . 279 , 53 – 63 ( 1983 ). OpenUrl CrossRef PubMed Web of Science 57. ↵ Angeles-Castellanos , M. , Aguilar-Roblero , R. & Escobar, C. c-Fos expression in hypothalamic nuclei of food-entrained rats . Am. J. Physiol. Regul. Integr. Comp. Physiol . 286 , R158 – R165 ( 2004 ). OpenUrl PubMed 58. ↵ Chavan , R. et al. Liver-derived ketone bodies are necessary for food anticipation . Nat. Commun . 7 , 10580 ( 2016 ). OpenUrl CrossRef PubMed 59. ↵ Feillet , C. A. et al. Lack of food anticipation in Per2 mutant mice . Curr. Biol . 16 , 2016 – 2022 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 60. ↵ McAloon , L. M. et al. CaMKK2: bridging the gap between Ca²⁺ signaling and energy sensing . Essays Biochem . 68 , 309 – 320 ( 2024 ). OpenUrl CrossRef PubMed 61. ↵ de Oliveira Figueiredo , E. C. , Calì , C. , Petrelli , F. & Bezzi , P. Emerging evidence for astrocyte dysfunction in schizophrenia . Glia 70 , 1585 – 1604 ( 2022 ). OpenUrl CrossRef PubMed 62. ↵ Veiga , A. et al. Calcium-dependent signaling in astrocytes: downstream mechanisms and implications for cognition . J. Neurochem . 169 , e70019 ( 2025 ). OpenUrl CrossRef PubMed 63. ↵ Power , S. C. & Mistlberger , R. E . Food anticipatory circadian rhythms in mice entrained to long or short day photoperiods . Physiol. Behav . 222 , 112926 ( 2020 ). 64. ↵ Marchant , E. G. & Mistlberger , R. E . Anticipation and entrainment to feeding time in intact and SCN-ablated C57BL/6J mice . Brain Res . 765 , 273 – 282 ( 1997 ). OpenUrl CrossRef PubMed Web of Science 65. ↵ Cooper , M. L. et al. Astrocytes connect specific brain regions through plastic gap junctional networks . bioRxiv 2025.07.18.665573 ( 2025 ). 66. ↵ Riccitelli , S. et al. Glial BMAL1 role in mammalian retina daily changes . Sci. Rep . 12 , 20123 ( 2022 ). OpenUrl PubMed 67. ↵ Rial-Pensado , E. et al. Temperature modulates systemic and central actions of thyroid hormones on BAT thermogenesis . Front. Physiol . 13 , 974345 ( 2022 ). OpenUrl 68. Fernández-González , I. et al. JNK1 in SF1 neurons regulates the central action of thyroid hormones on hepatic lipid metabolism . Mol. Metab . 102 , 102170 ( 2025 ). OpenUrl 69. ↵ Dragano , N. R. V. et al. Hypothalamic free fatty acid receptor-1 regulates whole-body energy balance . Mol. Metab . 79 , 101568 ( 2024 ). 70. ↵ Barca , O. , Seoane , M. , Señarís , M. R. & Arce , V. M . Fas/CD95 ligation induces proliferation of primary fetal astrocytes through a mechanism involving caspase 8-mediated ERK activation . Cell. Physiol. Biochem . 32 , 111 – 120 ( 2013 ). OpenUrl CrossRef 71. Barca , O. , Costoya , J. A. , Señarís , R. M. & Arce , V. M . Interferon-β protects astrocytes against tumour necrosis factor-induced apoptosis via activation of p38 mitogen-activated protein kinase . Exp. Cell Res . 314 , 2231 – 2237 ( 2008 ). OpenUrl CrossRef PubMed Web of Science 72. Barca , O. , Carneiro , C. , Costoya , J. A. , Señarís , R. M. & Arce , V. M . Resistance of neonatal primary astrocytes against Fas-induced apoptosis depends on silencing of caspase 8 . Neurosci. Lett . 479 , 206 – 210 ( 2010 ). OpenUrl PubMed 73. Barca , O. , Devesa-Peleteiro , P. , Seoane , M. , Señarís , R. M. & Arce , V. M . Bimodal effect of interferon-β on astrocyte proliferation and survival: importance of nuclear factor-κB . J. Neuroimmunol . 226 , 73 – 80 ( 2010 ). OpenUrl PubMed 74. ↵ Barca , O. et al. Mechanisms of interferon-β-induced survival in fetal and neonatal primary astrocytes . Neuroimmunomodulation 14 , 39 – 45 ( 2007 ). OpenUrl CrossRef PubMed 75. ↵ Wiśniewski , J. R. , Zougman , A. , Nagaraj , N. & Mann , M . Universal sample preparation method for proteome analysis . Nat. Methods 6 , 359 – 362 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 76. ↵ Tyanova , S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data . Nat. Methods 13 , 731 – 740 ( 2016 ) OpenUrl CrossRef PubMed 77. ↵ Samad , M. , Agostinelli , F. , Sato , T. , Shimaji , K. & Baldi , P . CircadiOmics: circadian omic web portal . Nucleic Acids Res . 50 , W183 – W190 ( 2022 ). OpenUrl PubMed 78. ↵ Patel , V. R. , Eckel-Mahan , K. , Sassone-Corsi , P. & Baldi , P . CircadiOmics: integrating circadian genomics, transcriptomics, proteomics and metabolomics . Nat. Methods 9 , 772 – 773 ( 2012 ). OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted August 15, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following An astrocytic AMPK clock drives circadian behaviour Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share An astrocytic AMPK clock drives circadian behaviour María Luengo-Mateos , Antía González-Vila , María Silveira-Loureiro , Daniela Sofía Abreu , Mikel Azkargorta , Ali Mohammad Ibrahim-Alasoufi , Victor Pardo-García , Hugo Lopez-Goldar , Helena Covelo Molares , Nathalia R.V. Dragano , Paola Fernández-Sanmartín , Ánxela M Estévez-Salguero , Mariana Astiz , Cláudia Cavadas , Carlos Diéguez , Miguel Fidalgo , Diana Guallar , Félix Elortza , Joao Filipe Oliveira , Miguel López , Olga Barca-Mayo bioRxiv 2025.08.14.670385; doi: https://doi.org/10.1101/2025.08.14.670385 Share This Article: Copy Citation Tools An astrocytic AMPK clock drives circadian behaviour María Luengo-Mateos , Antía González-Vila , María Silveira-Loureiro , Daniela Sofía Abreu , Mikel Azkargorta , Ali Mohammad Ibrahim-Alasoufi , Victor Pardo-García , Hugo Lopez-Goldar , Helena Covelo Molares , Nathalia R.V. Dragano , Paola Fernández-Sanmartín , Ánxela M Estévez-Salguero , Mariana Astiz , Cláudia Cavadas , Carlos Diéguez , Miguel Fidalgo , Diana Guallar , Félix Elortza , Joao Filipe Oliveira , Miguel López , Olga Barca-Mayo bioRxiv 2025.08.14.670385; doi: https://doi.org/10.1101/2025.08.14.670385 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Neuroscience Subject Areas All Articles Animal Behavior and Cognition (7616) Biochemistry (17627) Bioengineering (13856) Bioinformatics (41836) Biophysics (21398) Cancer Biology (18529) Cell Biology (25421) Clinical Trials (138) Developmental Biology (13352) Ecology (19859) Epidemiology (2067) Evolutionary Biology (24280) Genetics (15581) Genomics (22460) Immunology (17700) Microbiology (40281) Molecular Biology (17138) Neuroscience (88412) Paleontology (666) Pathology (2823) Pharmacology and Toxicology (4813) Physiology (7632) Plant Biology (15107) Scientific Communication and Education (2042) Synthetic Biology (4281) Systems Biology (9807) Zoology (2267)