Synaptic Targets of Circadian Clock Neurons Influence Core Clock Parameters

Synaptic Targets of Circadian Clock Neurons Influence Core Clock Parameters | 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 Synaptic Targets of Circadian Clock Neurons Influence Core Clock Parameters View ORCID Profile Eva Scholz-Carlson , View ORCID Profile Aishwarya Ramakrishnan Iyer , View ORCID Profile Aljoscha Nern , View ORCID Profile John Ewer , View ORCID Profile Maria P. Fernandez doi: https://doi.org/10.1101/2025.01.30.635801 Eva Scholz-Carlson 1 Department of Biology, Indiana University Bloomington. Bloomington , 47401 IN 2 Department of Neuroscience and Behavior, Barnard College. New York City , 10027 NY Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Eva Scholz-Carlson Aishwarya Ramakrishnan Iyer 1 Department of Biology, Indiana University Bloomington. Bloomington , 47401 IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Aishwarya Ramakrishnan Iyer Aljoscha Nern 3 Janelia Research Campus, Howard Hughes Medical Institute , Ashburn VA 20147 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Aljoscha Nern John Ewer 4 Instituto de Neurociencia, Universidad de Valparaíso , Valparaíso 2360102, Chile 5 Centro Interdisciplinario de Neurociencias de Valparaíso, Universidad de Valparaíso , Valparaíso 2360102, Chile Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for John Ewer Maria P. Fernandez 1 Department of Biology, Indiana University Bloomington. Bloomington , 47401 IN 2 Department of Neuroscience and Behavior, Barnard College. New York City , 10027 NY Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Maria P. Fernandez For correspondence: fernanm{at}iu.edu Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Neuronal connectivity in the circadian clock network is essential for robust endogenous timekeeping. In the Drosophila circadian clock network, four pairs of small ventral lateral neurons (sLN v s) serve as critical pacemakers. Peptidergic communication via sLN v release of the key output neuropeptide Pigment Dispersing Factor (PDF) has been well characterized. In contrast, little is known about the role of the synaptic connections that sLN v s form with downstream neurons. Connectomic analyses revealed that the sLN v s form strong synaptic connections with a group of previously uncharacterized neurons, SLP316. Here, we show that silencing synaptic output in the SLP316 neurons via tetanus toxin (TNT) expression shortens the free-running period, whereas hyper-exciting them by expressing the Na[+] channel NaChBac results in period lengthening. Under light-dark cycles, silencing SLP316 neurons also causes lower daytime activity and higher daytime sleep. Our results revealed that the main postsynaptic partners of the Drosophila pacemaker neurons are a non-clock neuronal cell type that regulates the timing of sleep and activity. Introduction Circadian rhythms, which allow animals to adapt to day-night changes in their environment, are generated by small groups of neurons in the brain that contain molecular clocks ( 1 ). These neurons form a network with synchronized molecular oscillations ( 2 , 3 ). The maintenance of robust and coherent behavioral circadian rhythms depends on connectivity within the clock network, which controls the timing of key behavioral outputs like rhythms in feeding, mating, and sleep ( 3 ). In both mammals and flies, connectivity in the clock network is mediated by peptide and transmitter outputs ( 4 – 7 ). Although the molecular mechanisms driving endogenous oscillations in clock neurons are well described, the pathways through which these neurons communicate with each other and with downstream targets to propagate oscillations throughout the brain remain poorly understood. Drosophila melanogaster is an ideal model for studying connectivity in the clock network. The fly circadian network consists of ∼240 neurons (( 8 ), reviewed in ( 9 )) and is the functional equivalent of the mammalian suprachiasmatic nuclei, the principal clock in the vertebrate brain ( 10 , 11 ). Each clock neuron within this network has an intracellular molecular timekeeping mechanism based on a transcriptional‒translational feedback loop ( 12 ). Clock neurons can be organized into seven main groups based on their anatomical location ( 11 , 13 – 16 ). Whereas the molecular oscillations of most of these groups are in phase, some major clock groups become active at specific times of day, which correlates with their roles in behavioral outputs ( 17 ). Among these cells, the small lateral ventral neurons (sLN v s) are key for maintaining rhythmicity under conditions of constant darkness and temperature (DD) and are considered the dominant circadian pacemakers under these conditions ( 18 – 21 ). Despite the importance of these cells for sustaining physiological and behavioral rhythms, very little is known about their connectivity with target neurons. Indeed, an analysis of their synaptic connectivity revealed that they form very few monosynaptic connections with other clock neurons ( 16 ). Peptidergic signaling is essential for clock network intercommunication and output ( 6 ). The neuropeptide Pigment Dispersing Factor (PDF), which is secreted by the sLN v s, is required for synchronizing molecular oscillations within the network, setting the phase of neural activity in other groups of clock neurons, and maintaining activity-rest rhythms under constant conditions ( 18 , 22 – 24 ). Expression of PDF undergoes daily and circadian oscillations in the sLN v dorsal terminals ( 19 ), and the loss of PDF or of the PDF receptor (PDFR) results in arrhythmicity under free-running conditions ( 25 – 27 ). In addition to PDF, the sLN v s express the neuropeptide, short Neuropeptide F (sNPF) ( 28 ), which promotes sleep and is involved in feeding regulation ( 28 – 30 ), and the inhibitory neurotransmitter glycine ( 31 ). Interestingly, downregulation of bruchpilot ( brp ) and of other synaptic active zone proteins expressed by the sLN v s does not affect rhythmicity, and dense-core vesicle release profiles of the sLN v s in the Full Adult Fly Brain (FAFB) do not show spatial overlap with BRP-labeled active zones ( 32 ). This finding is consistent with the observation that neuropeptide release takes place from sites located all along the sLN v , including the soma ( 33 ), and with the persistence of robust behavioral rhythmicity upon silencing of synaptic transmission ( 34 ) in Pdf + neurons ( 35 , 36 ) Although the circadian clock provides predictability, it must also be flexible to adapt to varying environmental conditions. Distinct subsets of neurons control the morning and evening bouts of activity that produce the bimodal pattern that flies show under light-dark cycles. The sLN v s, which are active around dawn ( 17 ), are associated with the morning peak of activity ( 18 , 20 , 21 ) and are called morning (M) cells. The PDFR-expressing lateral neurons dorsal (LN d s) and the PDF-negative 5 th LN v are associated with the evening peak activity ( 20 , 21 , 37 ) and their neural activity peaks before dusk ( 17 ). Some dorsal neurons (DNs) also contribute to the timing and amount of activity and sleep via the modulation of M and E cells ( 38 – 41 ). The phase of the morning and evening activity bouts adjusts to environmental light and temperature ( 42 – 47 ), allowing flies to adjust their activity patterns according to the season. The four sLN v s form few direct synaptic connections with other clock neurons or with other neurons outside the clock network, yet they form strong connections with a previously uncharacterized group of neurons named SLP316. The SLP316 cells synapse onto the DN1pA class of dorsal clock neurons, which are associated with the reorganization of sleep/wake cycles (reviewed in ( 40 )). Here, we show that despite not being clock neurons themselves, silencing SLP316 neuronal activity resulted in a shortening of the free-running period of activity, whereas their excitation resulted in the opposite phenotype. Neither manipulation led to the loss of rhythmicity. Under light-dark cycles (LD), manipulations of the SLP316 activity led to a reduction in evening activity and an increase in sleep, both under ambient temperature of 25°C, and under cold, winter-like days. Under both LD and DD, the behavioral phenotypes observed were different from those caused by the loss of PDF. In conclusion, our data reveal a role for a previously unknown neuronal population that connects two classes of clock neurons but is not itself part of the circadian clock network, in regulating the timing of sleep/wake cycles. Results 1 Connectomics datasets identify SLP316 neurons as primary post-synaptic partners of sLN v s Based on the Drosophila hemibrain connectome ( 48 ), the sLN v s form much stronger connections with an uncharacterized neuronal cell type than with any other neurons, including other clock neurons ( 16 ) ( Fig. 1A ). This cell type, SLP316, consists of three neurons with somas in the dorsal-most region of the Superior Lateral Protocerebrum (SLP) ( 48 ). Interestingly, the sLN v s are in turn the main presynaptic inputs to SLP316 neurons ( Fig 1A , B). Most inputs to SLP316 cells from their top ten presynaptic partners are located along the ventromedial projections, whereas their output synapses are concentrated along the dorsal arborizations ( Fig. 1C ). Download figure Open in new tab Fig. 1: SLP316 neurons are the main postsynaptic partner of the sLN v s. (A-B) Connectomic mapping from the hemibrain dataset. (A) Map of top input/output neuronal groups to/from the SLP316s and from the sLN v s. The number of neurons in each group are indicated in parenthesis if greater than one and reflected by circle size. Connection strength between cell types is represented by arrow width and decreases in a clockwise direction for each connection type (input/output). SLP232 likely corresponds to DN3s. (B) Strong shared inputs to, and (B’) outputs of the SLP316s (>10 synapses to/from at least two SLP316 neurons) with neuronal morphology shown above or below. (C) Input synapses to, and output synapses of, the three SLP316 neurons (SLP316_R_1, SLP316_R_2 and SLP316_R_3) shown in green, excluding synapses from neuron segments. Synapse color corresponds to neuron color in (A) and (B) and all other synapses are shown in grey. The synapses formed by the sLN v s onto the SLP316 neurons represent 70% of the synapses by all groups that form strong connections with these cells (weight >10) ( Fig 1A , B). Many of the synapses that the sLN v s form onto the SLP316s (∼20%) are located below the point at which the sLN v s extend and ramify their dorsal termini (Suppl. Fig. 1A), the region long thought to be the location of sLN v output synapses. The other main inputs to SLP316 are from two neurons that belong to the SLP364 cell type and from ventroposterior (VP) antennal lobe glomeruli neurons. The SLP316s are innervated largely by neurons in the SLP neuropil but also from the superior medial (SMP) and posterior lateral (SLP) protocerebrum (Suppl. Fig. 1B). The SLP316 neurons are largely homogeneous in their connectivity patterns with upstream neurons, but their outputs are more varied ( Fig 1B ’). These cells form some of the strongest connections with another group of clock neurons, posterior dorsal neurons (DN1p). The DN1pA class of clock neurons is the top output of the SLP316 cells. The main neuropil innervated by SLP316s is the SLP, followed by the SMP and PLP with a much smaller number of connections (Suppl. Fig. 1B). We next examined the connectivity patterns of the sLN v s in the FlyWire Drosophila connectome ( 49 ) to determine whether cells similar in morphology to the SLP316s were among their top post-synaptic partners. We found that in both hemispheres, the sLN v s form most of their output synapses with cells highly similar in location and morphology (Suppl. Fig. 1C). Computational predictions based on synapse architecture for both the hemibrain and FAFB-Flywire datasets ( 50 ) indicate that SLP316 cells are likely glutamatergic. 2 The SLP316 neurons are non-clock neurons that extend along the sLN v projection tract To further study the SLP316 neurons, we generated a Split-Gal4 line that targets these cells (#SS76489, see Methods) (Suppl. Fig. 2A). Since both the hemibrain and FAFB/FlyWire connectomes correspond to an adult female ( 48 ), we dissected brains from both SLP316>mCD8-GFP males and females to determine if there were sex differences in the number of cells or their morphology. The projections from the SLP316 neurons extend toward the ventral brain along the same tract as the projections of the sLN v s, which extend from the ventral to the dorsal brain ( Fig. 2A-B ). We did not find expression in additional neurons in the central brain or the ventral nerve cord, or sex differences in the number of cells ( Fig. 2C ). The number of cells remains similar in older flies (Suppl. Fig. 2B). Therefore, we conclude that the driver is likely specifically expressed in SLP316 neurons in adults and that the expression pattern is similar in males and females. Download figure Open in new tab Fig. 2: The SLP316 driver labels non-clock neurons that share functional synapses with the sLN v s. (A-B) Representative confocal images of a brain from a 7-day old male fly ( SLP316>GFP) stained with antibodies against GFP (green) and PDF (magenta). (A) Whole brain, (B) Superior Lateral Protocerebrum z-stack, and anterior (B’) and posterior (B”) single optical slices (step size 0.9 μm). (C) Quantification of cell body count on the left hemisphere labelled by the SLP316 driver in 7-day and 1-day old male and female flies from three replicate experiments (n > 21 for each age/sex). (D) Representative confocal images of a brain hemisphere of 6–7-day old male brains ( SLP316>GFP ) stained with antibodies against GFP (green) and PER (magenta). (E-F) Representative confocal images of SLP316-Gal4 and Pdf-LexA driving expression of BAcTrace components. RFP signal can only be detected in the sLNvs. (E’) sLN v dorsal termini show PDF and RFP expression. (E’’) Cell bodies of sLN v s and lLN v s. (E’’’) sLN v cell bodies plus dorsal projections show RFP signal, whereas the lLN v s do not. (F) syb-GFP expression in the small and large LN v s in experimental brains. (G-H) Representative confocal images of Pdf-LexA driving expression of BATrace components, without the SLP316-Gal4 driver. All scale bars are 50 µm. The SLP316 neurons are in the dorsoposterior area of the brain, where the DN1ps are located. To determine if these cells were yet unidentified clock neurons, we co-stained with a PER antibody. Adult SLP316>mCD8-GFP flies were entrained to a 12h:12h light-dark cycle (LD) for 5 days, and brains were dissected at the end of the night (ZT23), when PER nuclear signal is strongest ( 51 ). We did not detect PER nuclear signal in the somas of any of the SLP316 cells ( Fig. 2D ). Therefore, we conclude that the SLP316 neurons are not circadian clock neurons. To determine if there were daily changes in excitability in these cells, we used a transcriptional reporter in which the Hr38 regulatory DNA is upstream of a nuclear-localized fluorescent Tomato reporter ( 52 ). In the sLN v s, the Hr38-Tomato reporter gene shows higher expression around ZT2, consistent with a previous study ( 53 ). In contrast, SLP316 cells showed consistently low signal, and the presence of physiological rhythms cannot be excluded based on these data (Suppl. Fig. 2C-D). Next, we assessed connectivity between the cells labeled by the SLP316 split-GAL4 line and the sLN v s via BAcTrace. This is a retrograde synaptic tracing technique in which Clostridium botulinum neurotoxin A1 (BoNT/A) is transferred from a postsynaptic donor cell (driven by Gal4 components) to a presynaptic receiver cell (driven by LexA components) by targeting the interior of a synaptic vesicle ( 54 ). In the receiver cell, the toxin releases a membrane-localized transcription factor, inducing Tomato expression. When a vesicle is recycled, the toxin is internalized into the cell. We combined flies expressing the BAcTrace transgenes (see the methods section) with flies carrying both the SLP316 split Gal4 and the Pdf-LexA transgenes and stained brains with antibodies against PDF, RFP, and GFP ( Fig 2E-H ). Experimental flies showed RFP signal in the sLN v s but not the lLN v s, whereas PDF-immunoreactivity was detected in both groups of LN v s ( Fig. 2E ). Control flies without the SLP316 split Gal4 driver did not express RFP ( Fig. 2G ). As expected, GFP signal could be detected in both the sLN v s and lLN v s in control flies, reflecting the expression pattern of the Pdf-LexA driver present in both lines ( Fig. 2F and H ). We did not observe sex differences in expression pattern in experimental or control flies. These results support the notion that the SLP316 neurons are post-synaptic partners of the sLN v s, which is consistent with connectomics data. 3 Altering the activity of SLP316 neurons changes the free-running period Elimination of the LN v s via expression of the pro-apoptotic gene hid leads to severe loss of rhythmicity and shortening of the free running period, similar to the behavioral phenotypes of the Pdf null mutation, Pdf 01 ( 18 ). Whereas inhibiting synaptic transmission in Pdf neurons via tetanus toxin (TNT) does not affect the ability of the flies to maintain rhythmicity in DD, it leads to changes in free-running period, as Pdf >TNT flies show longer periods than their parental controls ( 35 , 36 ). Since the SLP316s are the main cell type downstream of the clock pacemaker neurons, we asked how manipulations of these cells would affect behavioral rhythms. The bacterial voltage-gated sodium channel NaChBac is used to increase neuronal excitability (reviewed in ( 55 )). Expression of NaChBac in Pdf + expressing neurons results in complex rhythms, with multiple superimposed period components under free-running conditions ( 56 ). NaChBac expression in the SLP316 cells resulted in lengthening of the free-running period without affecting overall rhythmicity ( Fig. 3A-C and Table 1 ), similar to the phenotype observed upon silencing activity of the Pdf + neurons via TNT. After eight days in DD, experimental flies showed a 3.3-hour phase delay in their activity peak ( Fig. 3D-E ). Under a light dark-dark cycle, SLP316>NaChBac flies showed a significant reduction in daytime activity (Suppl. Fig. 3A-D). Download figure Open in new tab Fig. 3: Manipulation of the SLP316s modulates free-running period length (A) Representative double-plotted actograms, (B) free-running period calculated using the Chi-square periodogram, and (C) percentage of rhythmic flies for control ( SLP316 split Gal4 and UAS-NaChBac ) and experimental ( SLP316>NaChBac ) flies. (D) Activity plot on the eighth day of free running, indicated in (A) with yellow box. (E) Phase of activity from (D), calculated using a sine-fit of the waveform of activity in CLOCKLAB. (F) Representative actograms, (G) free-running period and (H) percentage of rhythmic flies for control (w ;UAS-hid;UAS-GFP and w ;pUAS-tetx-LC-TNT; ) and experimental ( SLP316 >hid+GFP or SLP316>tetx-LC-TNT ) flies. (I) Free-running period, and (J) percentage of rhythmic flies for control ( SLP316 split Gal4 and ;pUAS-tetx-LC-TNT; ) and experimental (SLP316>tetx-LC-TNT ) flies. (K) Activity plot and (L) phase of activity on the eighth day of free-running for control ( SLP316 split Gal4 and ;pUAS-tetx-LC-TNT; ) and experimental (SLP316 >tetx-LC-TNT ) flies. Actograms show 5 days of LD followed by 9 days of DD. Flies were raised and activity-rest behavior recorded at 25°C. Rhythmic power was calculated using the Chi-square periodogram in ClockLab using 30-minute activity bins, and flies with a rhythmic power of 10 or greater were classified as rhythmic. Free-running period was calculated for rhythmic flies using the Chi-square periodogram routine of ClockLab using 1-minute activity bins. Statistical comparisons were conducted using the Kruskal-Wallis test followed by Dunn’s multiple comparisons test for free-running period and phase of activity, and using Fischer’s exact test for the number of rhythmic and arrhythmic flies. Data are plotted from three replicate experiments for each genotype. View this table: View inline View popup Download powerpoint Table 1. Summary of free running activity rhythms. Activity analysis of the above genotypes at either 25°C or 18°C. Light conditions for each experiment were 12:12 LD-DD. For each genotype the number of flies (n) is listed above. All flies were raised at 25°C. ClockLab’s χ-square periodogram analysis was used to analyze rhythmicity, rhythmic power, and free-running period for each genotype. The percent rhythmicity, along with the number of rhythmic flies (nR), the period in hours with the SEM, and the rhythmic power with the SEM are indicated. Arrhythmic flies were not considered in the analysis. Statistical analysis is included in Table S1. Next, we expressed hid under the SLP316 driver. Under DD conditions, SLP316 > hid flies had a short free running period ( Fig 3F-G ). The overall number of rhythmic flies and their rhythmic power were not affected ( Fig 3H and Table 1 ). A phase advance in activity can be detected on day 8 under DD conditions (Suppl. Fig. 3P-Q). SLP316>hid females also show a shortening in free-running period and no effect on the overall number of rhythmic flies (Suppl. Fig. 4A-B and E). Therefore, elimination of most SLP316 cells and NaChBac -mediated hyperexcitation of these cells led to opposite phenotypes in free-running period of activity rhythms. To determine whether synaptic activity of the SLP316 cells mediates the effects on period we expressed TNT ( 34 ). This manipulation led to a shortened period ( Fig 3F , I and Table 1 ). We also observed a small but significant reduction in the percentage of rhythmic flies and a phase advance at DD 8 of ∼3.2 hours ( Fig. 3J-L ). In SLP316>TNT females, the reduction in free-running period was not significantly different from that of controls (Suppl. Fig. 4C-E). Under LD, both hid and TNT expression in SLP neurons resulted in a reduction in daytime activity (Suppl. Fig. 3G, L). Shortening of free-running period is typically associated with an early phase of the evening peak of activity under a light-dark cycle (LD), such as in Pdf 01 mutants or flies in which Shaggy or Doubletime (DBT S ) are expressed in the sLN v s ( 57 , 58 ). However, LD activity profiles of SLP316>hid and SLP316>TNT flies indicate that these flies could still anticipate the lights-on transition and did not have an early phase of the evening peak (Suppl. Fig. 3F,I,K and N). The evening peak area in experimental SLP316>hid and SLP316>TNT males was significantly lower than the controls, indicating lower activity at this time of day (Suppl. Fig.3J,O). The only behavioral rhythm that is mediated by the LN v s but does not rely on PDF is adult emergence from the pupal case (eclosion) ( 59 , 60 ). The larval LNs, which survive metamorphosis and become the adult sLN v s ( 61 ), communicate with the PTTH neurons to regulate eclosion rhythms ( 59 ). In pharate adults, the sLN v s inhibit PTTH neuron Ca 2+ activity via short neuropeptide F (sNPF), not PDF, and the PTTH neurons appear to be post-synaptic targets of the sLN v s based on transsynaptic tracing experiments ( 59 ). In addition, PTTH neurons express sNPF and not PDF receptors ( 59 ). To determine if manipulations of SLP316 neurons affected eclosion rhythms, we conducted population experiments in which these cells were eliminated via expression of hid . We did not detect eclosion rhythm phenotypes in experimental SLP316>hid flies ( Fig. 4A-B ). Taken together, these results show that manipulations of the SLP316 neurons affect free-running rhythms in activity but not eclosion rhythms. Download figure Open in new tab Fig. 4: Silencing or eliminating SLP316 neurons does not affect the eclosion rhythm. (A) Records showing the time course of emergence of flies under DD conditions (left), their corresponding autocorrelation analysis (middle), and periodicities (right). (B) Period of eclosion of populations of flies of the indicated genotypes. 4. Organization of activity under cold days is disrupted upon SLP316 silencing Since a subset of the DN1p class of clock neurons are major postsynaptic partners of the SLP316 cells, we investigated the effect of manipulating these cells under low temperature light-dark (LD) conditions, where the DN1ps appear to play a more prominent role in shaping activity ( 45 ). Only under conditions with low light intensity, low temperature, or low or absent PDF can rescuing the molecular clock in a subset of glutamatergic DN1ps promote an evening peak of activity ( 44 , 45 ). Low temperatures lead to a reorganization of activity in wild-type flies as they adapt to the shorter days of winter. Under low temperature conditions (18°C) and light-dark cycles, the distance between the morning and evening peaks is reduced, primarily due to a substantially earlier phase of the evening peak, which decreases the phase angle of entrainment ( 42 ). We exposed flies in which we eliminated or silenced SLP316 cells to LD cycles under cold temperatures. SLP316>hid flies show significantly reduced daytime activity and increased daytime sleep compared to controls ( Fig. 5A-D ). Similar phenotypes, both in terms of daytime activity and daytime sleep, were observed in experimental SLP316>TNT flies ( Fig. 5E-H ). Neither nocturnal activity nor sleep were affected (Suppl. Fig. 5A-D). Download figure Open in new tab Fig. 5: Pdf and SLP316 disruption have opposite effects on daytime activity and sleep quantities under cold temperature. (A-D) Activity and sleep phenotypes of SLP316 >hid+GFP flies during three days of 12:12 LD at 18°C. Representative activity (A) and sleep (C) plots averaged for ( SLP316 split Gal4 and w;UAS-hid;UAS-GFP ) and experimental ( SLP316 >hid+GFP ) flies. Daytime (ZT0-12) (B) activity counts and total sleep amount (D). (E-H) Activity and sleep phenotypes of SLP316 >;tetx-LC-TNT flies and parental controls. Representative activity (E) and sleep (G) plots, and their respective quantifications (F, H). (I-l) Activity and sleep phenotypes of for wild-type w 1118 and pdf 01 flies. Representative activity (I) and sleep (K) plots, and total daytime activity counts (J) and sleep amount (L). Flies were raised at 25°C and activity-rest behavior was recorded at 18°C. Statistical comparisons were conducted using the Kruskal-Wallis test followed by Dunn’s multiple comparisons test for comparisons between three genotypes in (B), (D), (F) and (H), and using the Mann-Whitney test for comparisons between two genotypes in (J) and (L). Data plotted are from two replicate experiments for (B), (D), (F) and (H), and three replicate experiments for each genotype in (J) and (L). Under free-running conditions, manipulations of SLP316 neuron activity and the loss of Pdf result in distinct phenotypes. The Pdf 01 mutant is predominantly arrhythmic ( 18 ). However, the Pdf 01 flies that remained rhythmic exhibited a shortened free-running period, similar to the effect observed after silencing SLP316 neurons ( 18 ). Under light-dark (LD) conditions, manipulations of SLP316 neurons did not cause the expression of the classic phenotypes associated with the loss of Pdf , such as a lack of morning anticipation or an advanced evening peak (Suppl. Fig. 3). The advanced evening peak is thought to result from a phase-delay effect of PDF on evening cells: in the absence of PDF, neuronal activity in the evening cells show a large phase advance ( 24 ). PDF levels are temperature-sensitive, increasing during hot, summer-like days and decreasing under colder conditions ( 62 ). We exposed Pdf 01 flies to the same LD 18°C cycles and observed a significant advance in the evening peak and a 1.5-fold increase in daytime activity ( Fig. 5I-J ). This indicates that the early peak observed in wild-type flies under LD ( 42 ) is not solely attributable to the reduction in PDF under lower temperatures, since flies that lack PDF show a pronounced shift in evening activity. Pdf mutants show higher levels of daytime sleep in 12:12 LD cycles at 25°C ( 63 ); however, the pronounced increase in evening activity under LD 18°C is accompanied by an overall decrease in daytime sleep ( Fig. 5K-L ). The onset of activity was earlier, and activity levels remained high until the lights-off transition. After the lights-off transition, activity and sleep levels between control and Pdf 01 flies converge ( Fig. 5I,K and Suppl. Fig. 6E-F). These findings indicate that under cold-day conditions, the loss of Pdf and the silencing or elimination of SLP316 neurons results in the expression of opposite behavioral phenotypes. 5. Silencing SLP316 neurons increases daytime sleep Under standard light-dark conditions at 25°C, Pdf mutants show increased sleep during the day, as well as during the subjective day under constant conditions ( 63 ). However, the effect of Pdf loss on sleep appears to be dependent on temperature: indeed, these flies show increased sleep at 25°C and decreased sleep at 18°C ( Fig. 5L ). We analyzed the sleep profiles of flies expressing hid in the SLP316 cells under a LD cycle at 25°C and observed a significant increase in daytime sleep ( Fig. 6A-B ). (These results were obtained using the standard quantification based on periods of 5 minutes of inactivity ( 64 , 65 )). A similar phenotype was observed in SLP316 > TNT flies ( Fig. 6E-F ). Neither of those manipulations affected nighttime sleep (Suppl. Fig 6). These findings allow us to conclude that the effects on sleep are not unique to low temperature cycles but, in contrast to PDF’s temperature dependent roles, reflect a feature of the SLP316 neurons at both low and high temperature. Download figure Open in new tab Fig. 6: Silencing or eliminating SLP316 neurons increases the amount of daytime sleep (A) Representative sleep plot averaged from three days of 12:12 LD at 25°C for control ( SLP316 split Gal4 and ;UAS-hid;UAS-GFP ) and experimental ( SLP316 >;hid;GFP ) flies. (B) Total daytime sleep over three days for each genotype. (C) Representative sleep plot and (D) total daytime sleep for control ( SLP316-Gal4 and ;pUAS-tetx-LC-TNT; ) and experimental ( SLP316 >tetx-LC-TNT ) flies. (E) P(doze) from the same three days of LD, plotted in three-hour for either control shown for controls, SLP316 split Gal4 and ;UAS-hid;UAS-GFP ), and experimental ( SLP316 >;hid;GFP ) flies. (F) Average P(doze) throughout entire 3-day period. (G) P(doze) plot and (H) average P(doze) for control ( SLP316-Gal4 and ;pUAS-tetx-LC-TNT; ) and experimental ( SLP316 >tetx-LC-TNT ) flies under same conditions. Sleep was quantified in PHASE based on periods of inactivity of 5 minutes or more and plotted in (A) and (C) as minutes of sleep per 30-minute bin. P(doze) was quantified in R using routines from the Griffith Laboratory ( 66 ). Statistical comparisons were conducted using the Kruskal-Wallis test followed by Dunn’s multiple comparisons test. Data is plotted from four replicate experiments. To determine the underlying cause for this increase in sleep, we analyzed P(doze) and P(wake), the probabilities that an inactive fly will start moving or an active fly will stop moving, respectively, between 1-minute activity bins. P(doze) corresponds to sleep pressure, and P(wake) corresponds to sleep depth; thus, these conditional probabilities can offer insight into the biological processes driving changes in sleep ( 66 ). P(doze) was higher throughout most of the day and night for both SLP316>hid and SLP316>TNT animals, especially during the evening (ZT6-12) and morning (ZT18-3), when flies are most active ( Fig. 6 C,D and G,H). The average P(wake) was not significantly affected in either manipulation, although SLP316>hid flies showed a minor reduction in P(wake) from ZT9-12 (Suppl. Fig. 7A-D). This increase in P(doze) suggests that the increased sleep observed when the SLP316s are silenced was due to increased sleep pressure, especially at times when flies should be most active. We conclude that silencing SLP316 neurons leads to an increase in daytime sleep under both 25°C and low temperature conditions, and that this phenotype is not dependent on PDF since Pdf manipulations lead to opposite effects. Discussion The recent availability of connectomics data allows the identification of neuronal connections that have not been described using other approaches. We used openly available Drosophila connectomes to identify the SLP316 neurons, which are the main post-synaptic partners of the sLN v s, the key pacemaker neurons in the Drosophila clock network. We found that genetic manipulations of the SLP316 neurons led to changes in free-running rhythms: silencing their activity via TNT or eliminating them via hid leads to a period shortening, whereas hyperexciting them via NaChBac led to a period lengthening. Another important behavioral output of the sLN v s, eclosion rhythm, was not affected by genetic elimination of SLP316 neurons. Under light dark cycles, silencing SLP316s resulted in a reduction in daytime activity and an increase in sleep, under both 25°C and low temperature conditions. Neither the free-running nor the light-dark (LD) phenotypes observed following SLP316 manipulations resembled those caused by the loss of PDF, a well-known output of the sLN v s, which facilitates communication with the rest of the circadian clock network. Our study identified a non-clock group of neurons that affects circadian rhythms and contributes to our understanding of neuronal connectivity within the clock network. To date, the best characterized output of the sLN v s is PDF ( 18 , 67 ), a neuropeptide that accumulates--and is also released ( 33 )-rhythmically from their dorsal termini and soma, likely independently of classical transmitter release from these cells ( 32 ). The sLN v s also express sNPF ( 28 ), and there is evidence that they also use glycine to communicate with postsynaptic targets ( 31 ). Based on the availability of neurotransmitter use information, the flywire EM prediction for the sLN v s is acetylcholine ( 50 ), but the likelihood is relatively low. If the sLN v s contact the SLPs via glycine, they would likely inhibit them, which is consistent with the observation that inhibiting synaptic release from Pdf neurons via TNT and exciting the SLP316 neurons via NaChBac both lead to period lengthening. Functional connectivity experiments between the sLN v s and the SLPs would be needed to determine the nature of this connection. Given their prominent role in the clock network, several studies have examined neuronal targets of the sLN v s that would contribute to the propagation of rhythmic signals throughout the brain. PDF receptors ( PdfR ) are expressed by a wide range of neurons distributed throughout the brain, including much of the clock network ( 6 ), and PDFR-expressing cells respond to sLN v stimulation ( 68 ). PTTH neurons, which are downstream of sLN v s, express sNPF receptors, are inhibited by the sLN v s via sNPF to regulate eclosion rhythms ( 59 ). Connections between Pdf + cells and non-clock cells that regulate rhythm amplitude were detected via GRASP ( 69 ). More recently, the Blau laboratory used the transsynaptic tracer trans-tango to identify neuronal populations downstream of the sLN v s and reported that they form connections with a subset of DN1p clock neurons that express the neuropeptide CNMa and with mushroom body Kenyon cells ( 70 ). Strong monosynaptic connections between the sLN v s and the DN1ps cannot be detected in the connectomes ( 16 , 49 ), but it is possible that those synapses were missed because the sLN v s show daily structural plasticity rhythms ( 71 ), as do the VIP expressing neurons in the SCN ( 72 ). Truncation of the dorsal termini of the sLN v s, which are the sites of synaptic output and undergo clock-controlled plasticity, does not affect free-running rhythms ( 38 , 73 ), suggesting that PDF release is independent of the arborization rhythms. In addition, silencing synaptic transmission in Pdf + neurons via TNT does not lead to the loss of behavioral rhythms ( 36 ), nor does downregulation of bruchpilot ( brp ) or other active zone proteins ( 32 ). Taken together, these results suggest that unlike PDF release, the synaptic connections that the sLN v s form with downstream neurons are not required for maintaining activity-rest rhythms under free running conditions. However, those connections play a role in regulating the free-running period of those rhythms. The sLN v s appear to contact the DN1p clock neurons both via PDF release ( 58 ) and synaptically through the SLP316s ( Fig. 1 ). A functional clock in CRY-positive DN1ps, along with the presence of PDF, is sufficient for morning anticipation ( 44 , 45 , 74 ). Neither inhibition of synaptic transmission from sLN v nor manipulation of the SLP316 cells appeared to affect morning anticipation, suggesting that this feature depends on only PDF signaling from the sLN v s. Rescuing the molecular clock in a glutamatergic subset of DN1ps can promote an evening peak of activity when PDF is reduced or absent ( 44 , 62 ). The pronounced and very early peak of activity we observed in Pdf 01 flies under cold temperatures may at least in part be due to increased prominence of the activity of evening DN1ps in the absence of PDF ( 75 ). Another clock subset, DN1a, which is inhibited by cold temperature, is connected reciprocally to the sLN v s through the neuropeptides CCHamide1 and PDF ( 76 , 77 ). Thus, a cold-temperature induced change in sLN v activity could alter evening DN1p activity via the SLP316s, while simultaneous loss of PDF eliminates suppression of the DN1p-induced effects. These glutamatergic DN1ps are also sleep-promoting; activating them increases daytime sleep and arousal threshold at ZT6 and 10, whereas inhibiting them decreases both daytime and nighttime sleep ( 78 ). If the SLP316 neurons are glutamatergic as predicted in Flywire ( 49 ) and inhibitory, silencing them would be expected to increase the neuronal activity of the DN1ps and thus daytime sleep levels, in agreement with our results. Studying how neurons use different signals to communicate with downstream targets is essential for understanding how networks of neurons produce behavior. The Drosophila sLN v s are an excellent model for studying neuronal basis of behavior given their well characterized role as key circadian pacemakers. This role relies on their release of the neuropeptide PDF as a critical output signal for synchrony within the network. Our study is the first to examine the role on rhythmic behavior of direct synaptic targets of the sLN v s based on connectomics data, a connection that is likely independent of PDF. Our results reveal that manipulations of the SLP316 cells, the primary postsynaptic partners of the sLNvs in the connectome, can affect a core circadian parameter, free-running period. This finding indicates that a non-clock neuronal cell type can modulate circadian timekeeping. We show that manipulations of the SLP316 cells and loss of PDF lead to different behavioral phenotypes, both under free running conditions and under standard and low temperature light-dark cycles. These two pathways of clock neuron output may add plasticity to the system and allow the circadian network to adjust to changing environmental conditions. Materials and Methods Fly lines and husbandry Flies were reared on cornmeal-sucrose-yeast media under a 12hr:12hr Light:Dark (LD) cycle at 25 °C. The fly lines used in this study were: SLP316 split-Gal4 (SS76489: w; 38E08-p65ADZp in attP40; 36B07-ZpGdbd in attP2), w ; Pdf-Red, Pdf-Gal4; w;;UAS-NaChBac, yw;UAS-hid/cyo;UAS-mCD8-GFP, w;UAS-TeTxLC;, w 1118 , w;;Pdf 01 , and w; LexAop2-Syb.GFPN146I.TEVT173V LexAop2-QF2.V5.hSNAP25.HIVNES.Syx1A/CyO,20XUAS-B3R.PEST-UAS(B3RT.B2)BoNTA QUAS-mtdTomato-3xHA/TM6B, Tb1 (see Fly Lines and Reagents table for details). We identified the SLP316 split-GAL4 line (SS76489) by screening candidate hemidriver combinations selected by comparing GAL4 driver expression patterns and the hemibrain reconstructions of SLP316. This work was done in collaboration with the Janelia Fly Light Project Team using established methods and the driver line is included in a recently published split-GAL4 collection ( 79 ). Immunohistochemistry Flies were entrained to 12:12 LD cycles at 25°C and dissected at the specified times in cold Schneider’s Drosophila Medium. For all experiments, dissections were completed within 30 minutes. For anti-PER staining ( Fig. 2D ), brains were dissected at ZT23 on the fifth day under LD. Brains were fixed in 2% paraformaldehyde prepared in Schneider’s Drosophila Medium for 30 minutes at room temperature. Blocking was performed using 5% normal goat serum in PBS containing 0.3% Triton (PBS-TX) for 1 hour at room temperature. Samples were incubated with primary antibodies for 24 to 48 hours at 4°C, followed by several washes with PBS-TX under agitation. Secondary antibody cocktails were applied for 24 to 48 hours at 4°C, after which samples were washed again with PBS-TX. Antibodies (see table) were diluted in PBS-TX supplemented with 5% normal goat serum. Brains were mounted between coverslips and imaged at the Advanced Science Research Center (GC-CUNY) using an Olympus Fluoview 3000 laser-scanning confocal microscope (Olympus, Center Valley, PA). Brains for the BacTrace experiments were imaged using an Olympus/Evident Fluoview 4000 laser-scanning confocal microscope (Fernández lab, Indiana University Bloomington). The LM images in Figure S2 are based on confocal stacks previously reported ( 79 ) and the original images are available online ( https://splitgal4.janelia.org/cgi-bin/view_splitgal4_imagery.cgi?line=SS76489 ). The EM-LM overlay was generated using VVDviewer ( https://zenodo.org/records/14468001 ). The other images show maximum intensity projections produced using Fiji ( https://imagej.net/software/fiji/ ). Connectome analysis The Drosophila Hemibrain (release v2.1) was accessed via neuprint ( https://neuprint.janelia.org/ ). FlyWire data are based on FAFB version 783 ( https://flywire.ai/ )( 49 , 80 ). Hemibrain reconstructions are identified by their instance names in neuprint (e.g. ‘SLP316_R’) with individual cells distinguished here by an additional number (‘SLP316_R_1’). Behavior recording and analysis Locomotor activity rhythms of adult male and virgin female flies were recorded using DAM2 Drosophila Activity Monitors. Three- to six-day old flies were placed individually in TriKinetics capillary tubes containing 2% agar-4% sucrose food at one end sealed with a cap, plugged with a small length of yarn, and loaded into the DAM2 monitors for locomotor activity recording. Flies were entrained to 12:12 LD cycles for at least five days and then released into constant darkness (DD) for at least nine days at a constant temperature of 18 or 25°C (as indicated in the figure legend for each experiment). Free-running activity rhythms were analyzed with ClockLab software. ClockLab’s Chi-square periodogram function was used to analyze rhythmicity and rhythmic power in individual flies using 30-minute bins for activity and a confidence level of 0.01. The “Rhythmic Power” for each designated rhythmic fly was determined by subtracting the “Significance” value from the “Power” value associated with the predominant peak. Flies that did not exhibit a Rhythmic Power of 10 were categorized as “arrhythmic,” and their period and rhythmic power were not included in the analysis ( 81 ). ClockLab periodogram analysis was repeated for rhythmic flies using 1-minute bins to quantify free-running period. For each of the genotypes tested, only periodicities falling within the 14 to 34-hour range were taken into consideration. Phases on the eighth day of free-running were calculated using 1-minute bins and applying a Least Squares sine-wave fit in the ClockLab activity profile, excluding any phases with P>0.05. All relevant information about statistical analyses is included in Table S1. Activity counts were collected in 1-minute bins, and averaged across the population and profiles of specific genotypes under LD were generated using PHASE ( 82 ). First, individual fly activity levels were normalized by establishing the average activity across all 30-minute bins over days 2-4 under LD. Population averages of this normalized activity were computed for each 30-minute bin and averaged into a single representative 24-hour day. Total daytime (ZT0-12) and nighttime (ZT12-24) activity counts from days 2-4 of LD were recorded. Representative sleep plots and amounts were similarly generated for LD days 2-4 by classifying 5-minute periods of inactivity as sleep, unless otherwise specified. Total daytime and nighttime sleep over the three-day period were also recorded. Morning and evening phase were quantified in PHASE using a filter frame length of 481 minutes and filter order of 2. P(wake) and P(doze) values ( 66 ). were averaged for the entire duration of LD days 2-4, or in three-hour windows and averaged across the same days. Adult emergence monitoring Flies were raised at 25°C for 5 days, then transferred to 20°C and entrained under a LD 12:12 light:dark cycle. Resulting pupae were collected and fixed on eclosion plates with Elmer’s glue and mounted on Trikinetics eclosion monitors (Trikinetics, MA, USA). Emergence was then monitored for 7 days at 20°C under DD conditions and analyzed as previously described ( 83 ). Rhythmicity of eclosion profiles was analyzed using MATLAB (MathWorks, Inc., Natick) and the appropriate MATLAB toolbox ( 84 ). Using autocorrelation analyses, records were considered rhythmic if the rhythmicity index (RI) was 0.3, weakly rhythmic if 0.1<0.3, and arrhythmic if RI<0.1 ( 20 ). Fly lines and reagents View this table: View inline View popup Conflict of interest statement Authors declare that they have no competing interests. Acknowledgments We are grateful to Patrick Emery and members of the Fernández lab for helpful discussions and to Orie Shafer for comments on the manuscript, assistance on imaging, and providing access to the FV3000 microscope. We also thank the Janelia FlyLight Project Team for help with split-GAL4 screening and imaging, Justin Blau, Paul Taghert, and Cahir O’Kane for sharing fly lines, and Abhilash Lakshman for the code to obtain P(wake) and P(doze) values. Stocks obtained from the Bloomington Drosophila Stock Center (NIH P40OD018537) were used in this study. The mouse anti-PDF antibody was obtained from the Developmental Studies Hybridoma Bank, created by the NICHD of the NIH and maintained at The University of Iowa, Department of Biology, Iowa City, IA 52242, and the rat anti-PER antibody was donated by O. Shafer. This work was supported by a Beckman Foundation Scholarship to E.S-C, an NSF CAREER award (IOS-2239994) to M.P.F. and an NIH (R01NS118012) grant. Footnotes Table 1 and Suppl. Table 1 (statistical analyses) had not been included in the previous versions. One of the references was cited multiple times with a different number. https://figshare.com/account/home#/projects/230804 References 1. ↵ E. D. Herzog , Neurons and networks in daily rhythms . Nat Rev Neurosci 8 , 790 – 802 ( 2007 ). OpenUrl CrossRef PubMed Web of Science 2. ↵ D. K. Welsh , J. S. Takahashi , S. A. Kay , Suprachiasmatic nucleus: cell autonomy and network properties . Annu Rev Physiol 72 , 551 – 577 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 3. ↵ M. H. Hastings , M. Brancaccio , E. S. Maywood , Circadian pacemaking in cells and circuits of the suprachiasmatic nucleus . J Neuroendocrinol 26 , 2 – 10 ( 2014 ). OpenUrl CrossRef PubMed Web of Science 4. ↵ E. S. Maywood , J. E. Chesham , J. A. O’Brien , M. H. Hastings , A diversity of paracrine signals sustains molecular circadian cycling in suprachiasmatic nucleus circuits . Proceedings of the National Academy of Sciences 108 , 14306 – 14311 ( 2011 ). OpenUrl Abstract / FREE Full Text 5. B. Ananthasubramaniam , E. D. Herzog , H. Herzel , Timing of neuropeptide coupling determines synchrony and entrainment in the mammalian circadian clock . PLoS Comput Biol 10 , e1003565 ( 2014 ). OpenUrl CrossRef PubMed 6. ↵ P. H. Taghert , M. N. Nitabach , Peptide neuromodulation in invertebrate model systems . Neuron 76 , 82 – 97 ( 2012 ). OpenUrl CrossRef PubMed Web of Science 7. ↵ D. R. Nässel , M. Zandawala , Recent advances in neuropeptide signaling in Drosophila, from genes to physiology and behavior . Prog Neurobiol 179 , 101607 ( 2019 ). OpenUrl CrossRef PubMed 8. ↵ N. Reinhard et al. , Synaptic connectome of the Drosophila circadian clock . Nature Communications 15 , 10392 ( 2024 ). OpenUrl CrossRef PubMed 9. ↵ C. Helfrich-Förster , N. Reinhard , Mutual coupling of neurons in the circadian master clock: what we can learn from fruit flies . Neurobiology of Sleep and Circadian Rhythms doi: 10.1016/j.nbscr.2025.100112 , 100112 ( 2025 ). OpenUrl CrossRef 10. ↵ C. Helfrich-Forster , The neuroarchitecture of the circadian clock in the brain of Drosophila melanogaster . Microsc Res Tech 62 , 94 – 102 ( 2003 ). OpenUrl CrossRef PubMed Web of Science 11. ↵ F. K. Schubert , N. Hagedorn , T. Yoshii , C. Helfrich-Forster , D. Rieger , Neuroanatomical details of the lateral neurons of Drosophila melanogaster support their functional role in the circadian system . J Comp Neurol 526 , 1209 – 1231 ( 2018 ). OpenUrl CrossRef PubMed 12. ↵ C. Dubowy , A. Sehgal , Circadian Rhythms and Sleep in Drosophila melanogaster . Genetics 205 , 1373 – 1397 ( 2017 ). OpenUrl Abstract / FREE Full Text 13. ↵ C. Helfrich-Forster , Organization of endogenous clocks in insects . Biochem Soc Trans 33 , 957 – 961 ( 2005 ). OpenUrl Abstract / FREE Full Text 14. D. Ma et al. , A transcriptomic taxonomy of Drosophila circadian neurons around the clock . eLife 10 , e63056 ( 2021 ). OpenUrl CrossRef PubMed 15. O. T. Shafer , C. Helfrich-Forster , S. C. Renn , P. H. Taghert , Reevaluation of Drosophila melanogaster’s neuronal circadian pacemakers reveals new neuronal classes . J Comp Neurol 498 , 180 – 193 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 16. ↵ O. T. Shafer et al. , Connectomic analysis of the Drosophila lateral neuron clock cells reveals the synaptic basis of functional pacemaker classes . Elife 11 ( 2022 ). 17. ↵ X. Liang , T. E. Holy , P. H. Taghert , Synchronous Drosophila circadian pacemakers display nonsynchronous Ca(2)(+) rhythms in vivo . Science 351 , 976 – 981 ( 2016 ). OpenUrl Abstract / FREE Full Text 18. ↵ S. C. Renn , J. H. Park , M. Rosbash , J. C. Hall , P. H. Taghert , A pdf neuropeptide gene mutation and ablation of PDF neurons each cause severe abnormalities of behavioral circadian rhythms in Drosophila . Cell 99 , 791 – 802 ( 1999 ). OpenUrl CrossRef PubMed Web of Science 19. ↵ J. H. Park et al. , Differential regulation of circadian pacemaker output by separate clock genes in Drosophila . Proc Natl Acad Sci U S A 97 , 3608 – 3613 ( 2000 ). OpenUrl Abstract / FREE Full Text 20. ↵ B. Grima , E. Chelot , R. Xia , F. Rouyer , Morning and evening peaks of activity rely on different clock neurons of the Drosophila brain . Nature 431 , 869 – 873 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 21. ↵ D. Stoleru , Y. Peng , J. Agosto , M. Rosbash , Coupled oscillators control morning and evening locomotor behaviour of Drosophila . Nature 431 , 862 – 868 ( 2004 ). OpenUrl CrossRef PubMed Web of Science 22. ↵ T. Yoshii et al. , The neuropeptide pigment-dispersing factor adjusts period and phase of Drosophila’s clock . J Neurosci 29 , 2597 – 2610 ( 2009 ). OpenUrl Abstract / FREE Full Text 23. Y. Peng , D. Stoleru , J. D. Levine , J. C. Hall , M. Rosbash , Drosophila free-running rhythms require intercellular communication . PLoS Biol 1 , E13 ( 2003 ). OpenUrl CrossRef PubMed 24. ↵ X. Liang , T. E. Holy , P. H. Taghert , A Series of Suppressive Signals within the Drosophila Circadian Neural Circuit Generates Sequential Daily Outputs . Neuron 94 , 1173 – 1189 e1174 ( 2017 ). OpenUrl CrossRef PubMed 25. ↵ I. Mertens et al. , PDF receptor signaling in Drosophila contributes to both circadian and geotactic behaviors . Neuron 48 , 213 – 219 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 26. S. Hyun et al. , Drosophila GPCR Han is a receptor for the circadian clock neuropeptide PDF . Neuron 48 , 267 – 278 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 27. ↵ B. C. Lear et al. , A G protein-coupled receptor, groom-of-PDF, is required for PDF neuron action in circadian behavior . Neuron 48 , 221 – 227 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 28. ↵ H. A. D. Johard et al. , Peptidergic clock neurons in Drosophila: Ion transport peptide and short neuropeptide F in subsets of dorsal and ventral lateral neurons . Journal of Comparative Neurology 516 , 59 – 73 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 29. C. G. Vecsey , N. Pirez , L. C. Griffith , The Drosophila neuropeptides PDF and sNPF have opposing electrophysiological and molecular effects on central neurons . J Neurophysiol 111 , 1033 – 1045 ( 2014 ). OpenUrl CrossRef PubMed Web of Science 30. ↵ Y. Shang et al. , Short neuropeptide F is a sleep-promoting inhibitory modulator . Neuron 80 , 171 – 183 ( 2013 ). OpenUrl CrossRef PubMed Web of Science 31. ↵ L. Frenkel et al. , Organization of Circadian Behavior Relies on Glycinergic Transmission . Cell Rep 19 , 72 – 85 ( 2017 ). OpenUrl CrossRef PubMed 32. ↵ B. Hofbauer et al. , The neuropeptide pigment-dispersing factor signals independently of Bruchpilot-labelled active zones in daily remodelled terminals of Drosophila clock neurons . Eur J Neurosci 59 , 2665 – 2685 ( 2024 ). OpenUrl CrossRef PubMed 33. ↵ M. K. Klose , M. P. Bruchez , D. L. Deitcher , E. S. Levitan , Temporally and spatially partitioned neuropeptide release from individual clock neurons . Proc Natl Acad Sci U S A 118 ( 2021 ). 34. ↵ S. T. Sweeney , K. Broadie , J. Keane , H. Niemann , C. J. O’Kane , Targeted expression of tetanus toxin light chain in Drosophila specifically eliminates synaptic transmission and causes behavioral defects . Neuron 14 , 341 – 351 ( 1995 ). OpenUrl CrossRef PubMed Web of Science 35. ↵ A. R. Iyer et al. , The Circadian Neuropeptide PDF has Sexually Dimorphic Effects on Activity Rhythms . bioRxiv doi: 10.1101/2024.01.31.578273 ( 2024 ). OpenUrl Abstract / FREE Full Text 36. ↵ M. Kaneko , J. H. Park , Y. Cheng , P. E. Hardin , J. C. Hall , Disruption of synaptic transmission or clock-gene-product oscillations in circadian pacemaker cells of Drosophila cause abnormal behavioral rhythms . J Neurobiol 43 , 207 – 233 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 37. ↵ M. P. Brown et al. , A subclass of evening cells promotes the switch from arousal to sleep at dusk . bioRxiv doi: 10.1101/2023.08.28.555147 ( 2023 ). OpenUrl Abstract / FREE Full Text 38. ↵ M. P. Fernandez et al. , Sites of Circadian Clock Neuron Plasticity Mediate Sensory Integration and Entrainment . Curr Biol 30 , 2225 – 2237 e2225 ( 2020 ). OpenUrl CrossRef PubMed 39. F. Guo , X. Chen , M. Rosbash , Temporal calcium profiling of specific circadian neurons in freely moving flies . Proc Natl Acad Sci U S A 114 , E8780 – E8787 ( 2017 ). OpenUrl Abstract / FREE Full Text 40. ↵ A. Lamaze , R. Stanewsky , DN1p or the “Fluffy” Cerberus of Clock Outputs . Front Physiol 10 , 1540 ( 2019 ). OpenUrl CrossRef PubMed 41. ↵ B. Collins , Elizabeth A. Kane , David C. Reeves , Myles H. Akabas , J. Blau , Balance of Activity between LNvs and Glutamatergic Dorsal Clock Neurons Promotes Robust Circadian Rhythms in Drosophila . Neuron 74 , 706 – 718 ( 2012 ). OpenUrl CrossRef PubMed Web of Science 42. ↵ J. Majercak , D. Sidote , P. E. Hardin , I. Edery , How a circadian clock adapts to seasonal decreases in temperature and day length . Neuron 24 , 219 – 230 ( 1999 ). OpenUrl CrossRef PubMed Web of Science 43. P. Lamba , L. E. Foley , P. Emery , Neural network interactions modulate CRY-dependent photoresponses in Drosophila . The Journal of Neuroscience doi: 10.1523/jneurosci.2259-17.2018 , 2259 – 2217 ( 2018 ). OpenUrl CrossRef 44. ↵ A. Chatterjee et al. , Reconfiguration of a Multi-oscillator Network by Light in the Drosophila Circadian Clock . Curr Biol 28 , 2007 – 2017 e2004 ( 2018 ). OpenUrl CrossRef PubMed 45. ↵ Y. Zhang , Y. Liu , D. Bilodeau-Wentworth , P. E. Hardin , P. Emery , Light and temperature control the contribution of specific DN1 neurons to Drosophila circadian behavior . Curr Biol 20 , 600 – 605 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 46. K. M. Parisky , J. L. Agosto Rivera , N. C. Donelson , S. Kotecha , L. C. Griffith , Reorganization of Sleep by Temperature in Drosophila Requires Light, the Homeostat, and the Circadian Clock . Curr Biol 26 , 882 – 892 ( 2016 ). OpenUrl CrossRef PubMed 47. ↵ C. Kistenpfennig et al. , A New Rhodopsin Influences Light-dependent Daily Activity Patterns of Fruit Flies . J Biol Rhythms 32 , 406 – 422 ( 2017 ). OpenUrl CrossRef PubMed 48. ↵ L. K. Scheffer et al. , A connectome and analysis of the adult Drosophila central brain . Elife 9 ( 2020 ). 49. ↵ S. Dorkenwald et al. , Neuronal wiring diagram of an adult brain . Nature 634 , 124 – 138 ( 2024 ). OpenUrl CrossRef PubMed 50. ↵ N. Eckstein et al. , Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster . Cell 187 , 2574 – 2594 .e2523 ( 2024 ). OpenUrl CrossRef PubMed 51. ↵ O. T. Shafer , M. Rosbash , J. W. Truman , Sequential nuclear accumulation of the clock proteins period and timeless in the pacemaker neurons of Drosophila melanogaster . J Neurosci 22 , 5946 – 5954 ( 2002 ). OpenUrl Abstract / FREE Full Text 52. ↵ Z. Zhu et al. , A gene expression program activated by neuronal inactivity . bioRxiv doi: 10.1101/636878 , 636878 ( 2024 ). OpenUrl Abstract / FREE Full Text 53. ↵ D. G. Gundermann , S. Lymer , J. Blau , A rapid and dynamic role for FMRP in the plasticity of adult neurons . bioRxiv doi: 10.1101/2023.09.01.555985 ( 2023 ). OpenUrl Abstract / FREE Full Text 54. ↵ S. Cachero et al. , BAcTrace, a tool for retrograde tracing of neuronal circuits in Drosophila . Nature Methods 17 , 1254 – 1261 ( 2020 ). OpenUrl CrossRef PubMed 55. ↵ F. Lehmann-Horn , K. Jurkat-Rott , Voltage-gated ion channels and hereditary disease . Physiol Rev 79 , 1317 – 1372 ( 1999 ). OpenUrl CrossRef PubMed Web of Science 56. ↵ M. N. Nitabach et al. , Electrical hyperexcitation of lateral ventral pacemaker neurons desynchronizes downstream circadian oscillators in the fly circadian circuit and induces multiple behavioral periods . J Neurosci 26 , 479 – 489 ( 2006 ). OpenUrl Abstract / FREE Full Text 57. ↵ D. Stoleru , Y. Peng , P. Nawathean , M. Rosbash , A resetting signal between Drosophila pacemakers synchronizes morning and evening activity . Nature 438 , 238 – 242 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 58. ↵ Z. Yao , A. J. Bennett , J. L. Clem , O. T. Shafer , The Drosophila Clock Neuron Network Features Diverse Coupling Modes and Requires Network-wide Coherence for Robust Circadian Rhythms . Cell Rep 17 , 2873 – 2881 ( 2016 ). OpenUrl CrossRef PubMed 59. ↵ M. Selcho et al. , Central and peripheral clocks are coupled by a neuropeptide pathway in Drosophila . Nature Communications 8 , 15563 ( 2017 ). OpenUrl CrossRef PubMed 60. ↵ C. Wegener , E. Amini , J. Cavieres-Lepe , J. Ewer , Neuronal and endocrine mechanisms underlying the circadian gating of eclosion: insights from Drosophila . Curr Opin Insect Sci 66 , 101286 ( 2024 ). OpenUrl CrossRef PubMed 61. ↵ C. Helfrich-Forster , Development of pigment-dispersing hormone-immunoreactive neurons in the nervous system of Drosophila melanogaster . J Comp Neurol 380 , 335 – 354 ( 1997 ). OpenUrl CrossRef PubMed Web of Science 62. ↵ S. Hidalgo , M. Anguiano , C. A. Tabuloc , J. C. Chiu , Seasonal cues act through the circadian clock and pigment-dispersing factor to control EYES ABSENT and downstream physiological changes . Curr Biol 33 , 675 – 687 e675 ( 2023 ). OpenUrl CrossRef PubMed 63. ↵ K. M. Parisky et al. , PDF cells are a GABA-responsive wake-promoting component of the Drosophila sleep circuit . Neuron 60 , 672 – 682 ( 2008 ). OpenUrl CrossRef PubMed Web of Science 64. ↵ P. J. Shaw , C. Cirelli , R. J. Greenspan , G. Tononi , Correlates of sleep and waking in Drosophila melanogaster . Science 287 , 1834 – 1837 ( 2000 ). OpenUrl Abstract / FREE Full Text 65. ↵ J. C. Hendricks et al. , Rest in Drosophila is a sleep-like state . Neuron 25 , 129 – 138 ( 2000 ). OpenUrl CrossRef PubMed Web of Science 66. ↵ T. D. Wiggin et al. , Covert sleep-related biological processes are revealed by probabilistic analysis in Drosophila . Proc Natl Acad Sci U S A 117 , 10024 – 10034 ( 2020 ). OpenUrl Abstract / FREE Full Text 67. ↵ P. H. Taghert , O. T. Shafer , Mechanisms of clock output in the Drosophila circadian pacemaker system . J Biol Rhythms 21 , 445 – 457 ( 2006 ). OpenUrl CrossRef PubMed Web of Science 68. ↵ O. T. Shafer et al. , Widespread receptivity to neuropeptide PDF throughout the neuronal circadian clock network of Drosophila revealed by real-time cyclic AMP imaging . Neuron 58 , 223 – 237 ( 2008 ). OpenUrl CrossRef PubMed Web of Science 69. ↵ N. Pirez , S. G. Bernabei-Cornejo , M. Fernandez-Acosta , J. M. Duhart , M. F. Ceriani , Contribution of non-circadian neurons to the temporal organization of locomotor activity . Biol Open 8 ( 2019 ). 70. ↵ A. Ehrlich , et al. , Tango-seq: overlaying transcriptomics on connectomics to identify neurons downstream of Drosophila clock neurons . bioRxiv doi: 10.1101/2024.05.22.595372 ( 2024 ). OpenUrl Abstract / FREE Full Text 71. ↵ M. P. Fernandez , J. Berni , M. F. Ceriani , Circadian remodeling of neuronal circuits involved in rhythmic behavior . PLoS Biol 6 , e69 ( 2008 ). OpenUrl CrossRef PubMed 72. ↵ A. F. Neitz , B. M. Carter , M. F. Ceriani , M. H. Ellisman , H. O. de la Iglesia , Suprachiasmatic nucleus VIPergic fibers show a circadian rhythm of expansion and retraction . Current Biology 34 , 4056 – 4061 .e4052 ( 2024 ). OpenUrl CrossRef PubMed 73. ↵ A. Sivachenko , Y. Li , K. C. Abruzzi , M. Rosbash , The transcription factor Mef2 links the Drosophila core clock to Fas2, neuronal morphology, and circadian behavior . Neuron 79 , 281 – 292 ( 2013 ). OpenUrl CrossRef PubMed Web of Science 74. ↵ M. Sekiguchi et al. , A Detailed Re-Examination of the Period Gene Rescue Experiments Shows That Four to Six Cryptochrome-Positive Posterior Dorsal Clock Neurons (DN(1p)) of Drosophila melanogaster Can Control Morning and Evening Activity . J Biol Rhythms 39 , 463 – 483 ( 2024 ). OpenUrl CrossRef PubMed 75. ↵ A. Chatterjee , J. De , B. Martin , E. Chélot , F. Rouyer , Neuropeptide Dynamics Coordinate Layered Plasticity Mechanisms Adapting Drosophila Circadian Behavior to Changing Environment . bioRxiv doi: 10.1101/2024.10.15.618497 , 2024.2010.2015.618497 ( 2024 ). OpenUrl Abstract / FREE Full Text 76. ↵ Y. Fujiwara et al. , The CCHamide1 Neuropeptide Expressed in the Anterior Dorsal Neuron 1 Conveys a Circadian Signal to the Ventral Lateral Neurons in Drosophila melanogaster . Front Physiol 9 , 1276 ( 2018 ). OpenUrl CrossRef PubMed 77. ↵ M. H. Alpert et al. , A Circuit Encoding Absolute Cold Temperature in Drosophila . Curr Biol 30 , 2275 – 2288 e2275 ( 2020 ). OpenUrl CrossRef PubMed 78. ↵ F. Guo et al. , Circadian neuron feedback controls the Drosophila sleep--activity profile . Nature 536 , 292 – 297 ( 2016 ). OpenUrl CrossRef PubMed 79. ↵ G. W. Meissner , et al. ( 2025 ) A split-GAL4 driver line resource for Drosophila neuron types . ( eLife Sciences Publications, Ltd ). 80. ↵ P. Schlegel et al. , Whole-brain annotation and multi-connectome cell typing of Drosophila . Nature 634 , 139 – 152 ( 2024 ). OpenUrl CrossRef PubMed 81. ↵ C. Pfeiffenberger , B. C. Lear , K. P. Keegan , R. Allada , Processing circadian data collected from the Drosophila Activity Monitoring (DAM) System . Cold Spring Harb Protoc 2010 , pdb prot5519 ( 2010 ). OpenUrl CrossRef 82. ↵ J. L. Persons et al. , PHASE: An Open-Source Program for the Analysis of DrosophilaPhase, Activity, and Sleep Under Entrainment . J Biol Rhythms 37 , 455 – 467 ( 2022 ). OpenUrl CrossRef PubMed 83. ↵ J. Cavieres-Lepe et al. , Timed receptor tyrosine kinase signaling couples the central and a peripheral circadian clock in Drosophila . Proc Natl Acad Sci U S A 121 , e2308067121 ( 2024 ). OpenUrl CrossRef PubMed 84. ↵ J. D. Levine , P. Funes , H. B. Dowse , J. C. Hall , Signal analysis of behavioral and molecular cycles . BMC Neuroscience 3 , 1 ( 2002 ). 85. M. Ruben , M. D. Drapeau , D. Mizrak , J. Blau , A mechanism for circadian control of pacemaker neuron excitability . J Biol Rhythms 27 , 353 – 364 ( 2012 ). OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted February 06, 2025. Download PDF Supplementary Material Data/Code 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 Synaptic Targets of Circadian Clock Neurons Influence Core Clock Parameters 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 Synaptic Targets of Circadian Clock Neurons Influence Core Clock Parameters Eva Scholz-Carlson , Aishwarya Ramakrishnan Iyer , Aljoscha Nern , John Ewer , Maria P. Fernandez bioRxiv 2025.01.30.635801; doi: https://doi.org/10.1101/2025.01.30.635801 Share This Article: Copy Citation Tools Synaptic Targets of Circadian Clock Neurons Influence Core Clock Parameters Eva Scholz-Carlson , Aishwarya Ramakrishnan Iyer , Aljoscha Nern , John Ewer , Maria P. Fernandez bioRxiv 2025.01.30.635801; doi: https://doi.org/10.1101/2025.01.30.635801 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 (7622) Biochemistry (17648) Bioengineering (13871) Bioinformatics (41880) Biophysics (21423) Cancer Biology (18561) Cell Biology (25461) Clinical Trials (138) Developmental Biology (13364) Ecology (19866) Epidemiology (2067) Evolutionary Biology (24290) Genetics (15590) Genomics (22475) Immunology (17713) Microbiology (40328) Molecular Biology (17148) Neuroscience (88473) Paleontology (666) Pathology (2827) Pharmacology and Toxicology (4816) Physiology (7635) Plant Biology (15114) Scientific Communication and Education (2044) Synthetic Biology (4286) Systems Biology (9815) Zoology (2268)