Mapping the spatiotemporal dynamics of de novo protein synthesis during long-term memory formation

Mapping the spatiotemporal dynamics of de novo protein synthesis during long-term memory formation | 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 Mapping the spatiotemporal dynamics of de novo protein synthesis during long-term memory formation View ORCID Profile Harrison T. Evans , View ORCID Profile Drew Adler , View ORCID Profile Maria Clara Selles , View ORCID Profile Srinidhi V. Kalavai , View ORCID Profile Astra Yu , View ORCID Profile Victor Wu , View ORCID Profile Eléa Denil , View ORCID Profile Ela N. Golhan , View ORCID Profile Ambika Polavarapu , View ORCID Profile Emma Balamoti , View ORCID Profile Moses V. Chao , View ORCID Profile Robert C. Froemke , View ORCID Profile Eric Klann doi: https://doi.org/10.1101/2025.04.17.649250 Harrison T. Evans 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Harrison T. Evans Drew Adler 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Drew Adler Maria Clara Selles 2 Department of Neuroscience, New York University Grossman School of Medicine ; New York, 10016, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Maria Clara Selles Srinidhi V. Kalavai 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Srinidhi V. Kalavai Astra Yu 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Astra Yu Victor Wu 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Victor Wu Eléa Denil 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Eléa Denil Ela N. Golhan 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ela N. Golhan Ambika Polavarapu 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ambika Polavarapu Emma Balamoti 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Emma Balamoti Moses V. Chao 2 Department of Neuroscience, New York University Grossman School of Medicine ; New York, 10016, USA 3 Department of Psychiatry, New York University Grossman School of Medicine ; New York, 10016, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Moses V. Chao Robert C. Froemke 1 Center for Neural Science, New York University , New York, NY, 10003, United States 2 Department of Neuroscience, New York University Grossman School of Medicine ; New York, 10016, USA 4 Department of Otolaryngology, New York University Grossman School of Medicine ; New York, 10016 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Robert C. Froemke Eric Klann 1 Center for Neural Science, New York University , New York, NY, 10003, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Eric Klann For correspondence: ek65{at}nyu.edu Abstract Full Text Info/History Metrics Preview PDF Abstract The formation of new associative long-term memory (LTM) following Pavlovian conditioning is dependent upon multiple, temporally distinct windows of mRNA translation. Current methods lack the temporal specificity to robustly characterize the dynamics of protein synthesis throughout the rodent brain following conditioning. Here we resolve these technological limitations and demonstrate that in awake mice, the retro-orbital (RO) injection of azidohomoalanine (AHA) enables the labelling and subsequent visualization of the brain de novo proteome, with labelling periods as short as 30 minutes. Combining this advancement in de novo proteomic labelling with tissue clearing, we identified brain region, cell-type, and neuronal sub-population specific changes in de novo protein synthesis in mice following an auditory threat conditioning paradigm. This approach also allowed us to track the changes in de novo protein synthesis over time, revealing that conditioning-induced changes in mRNA translation exhibit remarkable temporal specificity in brain regions such as the somatosensory cortex. Taken together, our findings highlight how this novel labelling technique can be used to map the highly intricate temporal and spatial dynamics of mRNA translation after behavioral conditioning. Introduction The formation of new long-term memories (LTM) is reliant upon mRNA translation. This was first established in 1963 by Flexner and colleagues who showed that intracerebral injection of puromycin, an antibiotic that inhibits protein synthesis, impaired avoidance discrimination memory in mice ( Flexner et al , 1963 ). Since then, numerous studies have utilized pharmacological, and more recently, chemogenetic techniques to identify brain regions and cell types in which protein synthesis is required for the consolidation of different forms of long-term memory ( Lima et al , 2009 ; Pedroza-Llinás et al , 2009 ; Ozawa et al , 2017 ; Shrestha et al , 2020a ; Moncada & Viola, 2007 ). Taken together, these previous findings led researchers to hypothesize that during memory consolidation, multiple spatially and temporally distinct windows of protein synthesis enable the formation of the neuronal circuits that encode memory ( Shrestha & Klann, 2022 ). Indeed, many of the proposed cellular correlates of memory, such as long-term potentiation and long-term depression, have been demonstrated to require de novo protein synthesis ( Younts et al , 2016 ; Fonseca et al , 2006 ). Furthermore, several neurodevelopmental and neurodegenerative diseases in which memory is impaired also exhibit perturbations in various aspects of translational control, resulting in either exaggerated or deficient de novo protein synthesis ( Mohamed & Klann, 2023 ; Evans et al , 2019 ; Elder et al , 2021 ; Oliveira et al , 2021 ; Evans et al , 2021b ; Koren et al , 2019 ). Thus, it is clear that mRNA translation plays a causal and critical role in the formation of new long-term memories. Given the requirement of de novo protein synthesis for memory consolidation, identifying which proteins are newly synthesized, in which brain regions and cell types these proteins are synthesized, and during which stages of consolidation this synthesis occurs, is vital to understanding the spatial-temporal dynamics of memory. Unfortunately, technical limitations have prevented researchers from visualizing de novo protein synthesis during memory formation in the rodent brain. The current gold-standard for labelling, visualizing, and identifying newly synthesized proteins is non-canonical amino acid (NCAA) tagging ( Evans et al , 2021a ) where newly synthesized proteins are labeled with azide-bearing NCAAs such as azidohomoalanine (AHA), which incorporates into the nascent polypeptide chain in the place of methionine ( Fig. 1A ). Unlike other de novo proteomic techniques, such as puromycin labeling, AHA labeling has minimal effects on protein structure or function ( McClatchy et al , 2020 ). The azide group of AHA can be used to covalently bond labeled newly synthesized proteins to a variety of tags via the azide-alkyne cycloaddition. As a result, newly synthesized proteins can be either visualized via FUNCAT (fluorescent non-canonical amino acid tagging) or isolated using BONCAT (bio-orthogonal non-canonical amino acid tagging) and subsequently identified via mass spectrometry ( Carlisle et al , 2023 ; Dieterich et al , 2006 ). Download figure Open in new tab Figure 1: Retro-orbital injection of AHA allows for rapid labelling of the brain de novo proteome. (A) Newly synthesized proteins can be labeled by the methionine surrogate AHA and then be covalently bonded to a fluorescent tag using FUNCAT. (B) Retro-orbital delivery of AHA results in significantly higher brain de novo proteome labelling after 2 hours of treatment compared to i.p. and i.v. (intra tail-vein) injection as measured by FUNCAT-WB (one-way ANOVA, Tukey’s MCT, n=3 animals). (C) AHA labeling of de novo synthesized proteins can be detected as little as 30 minutes post retro-orbital (R.O.) injection, with FUNCAT signal peaking 8 hours post injection (one-way ANOVA, Tukey’s MCT, n=3 animals). (D) Treating mice with dosage of AHA higher than 50 mg/kg does not increase de novo proteomic labelling, as measured via FUNCAT-WB (one-way ANOVA, Tukey’s MCT, n=6 animals). (E) Co-injection of the protein synthesis inhibitor cycloheximide (CHX) significantly reduces AHA labeling as measured by FUNCAT-IHC (Students T.Test, n=3 animals, ≥3 sections per animal). Scale bar = 50μm. Error bars = S.E.M. *= p≤ 0.05, **= p≤ 0.01, ***= p≤ 0.001, ****= p≤ 0.001 Labeling newly synthesized proteins with NCAAs offers several distinct advantages over other de novo proteomic analysis techniques. Unlike techniques that rely upon isotopically labeled amino acids such as SILAC (stable isotype labeling with amino acids in cell culture), newly synthesized proteins labelled with NCAAs can be either visualized or purified from the rest of the proteome ( Hinz et al , 2013 ). In addition, the labelling of newly synthesized proteins with NCAAs has minimal effects on protein structure and function in contrast to techniques such as SUnSET (surface sense of translation), which utilize the tRNA analogue puromycin, resulting in truncation of the polypeptide chain ( Schmidt et al , 2009 ). NCAA labelling has been utilized to study the de novo proteome in a wide range of animal models, including Drosophila melanogaster ( Erdmann et al , 2015 ), Caenorhabditis elegans ( Liang et al , 2014 ), and rodents, and has even been proposed for use in human patients ( McBride et al , 2014 ). In mice, it has been used to study how protein synthesis is altered by environmental enrichment ( Alvarez-Castelao et al , 2019 ) and impaired in models of frontotemporal dementia ( Evans et al , 2019 ). NCAAs like AHA have typically been delivered to the brain via either dietary supplementation ( McClatchy et al , 2015 ) or intraperitoneal (i.p.) injection ( Evans et al , 2019 , Evans et al 2021b ), resulting in long minimum labelling periods of upwards of 16 hours. As such, until now AHA labelling has been unable to be used to robustly study the spatial and temporal dynamics of learning-induced protein synthesis. Here, we overcome these technical limitations by delivering AHA to the brain via the retro-orbital (R.O.) sinus. We report that retro-orbital injection of AHA into awake mice results in rapid labeling of the de novo proteome in time periods as short as 30 minutes. By combining FUNCAT with tissue clearing and light sheet microscopy, we reveal that this new technique rapidly labels the de novo proteome throughout the mouse brain. Harnessing this technique, we characterize the spatial and temporal dynamics of protein synthesis induced by training in an auditory threat conditioning paradigm. We found that immediately following training, conditioning-induced protein synthesis occurs predominately in the amygdala, before becoming more pronounced in the hippocampus and somatosensory cortex six hours later. Together, our findings show that NCAA labelling can be used to dissect the spatio-temporal complexities of conditioning-induced protein synthesis in the rodent brain. Results Rapid labeling of the brain de novo proteome enabled by retro-orbital injection of AHA We first sought to determine whether retro-orbital delivery improved the temporal resolution of AHA labeling compared to other delivery techniques. To address this issue, we utilized FUNCAT-western blot (FUNCAT-WB) analysis to quantify the amount of de novo proteomic labelling in the hippocampal tissue of mice after two hours of labeling. Mice were administered 50 mg/kg of AHA either via intraperitoneal, intravenous (tail-vein), or retro-orbital injection. 50 mg/kg was administered as this was previously shown to be the optimal dosage of AHA when delivered via i.p. injection. A treatment period of two hours was selected as these previous studies that utilized i.p. injection observed very limited AHA labeling at this time. FUNCAT-WB quantification revealed that with two hours of labeling, retro-orbital injection of AHA resulted in nearly a 4-fold increase in de novo proteomic labeling compared to i.p injection, and nearly double the labeling achieved via tail-vein injection ( Fig. 1B ). We next determined the temporal dynamics of AHA labeling following retro-orbital delivery. Using FUNCAT-WB we were able to detect significant AHA labeling as little as 30 minutes post-injection, with the amount of AHA labeling peaking at eight hours post injection ( Fig. 1C ). Following this, we determined that 50 mg/kg of AHA is the optimal dosage for retro-orbital injection, with higher doses not increasing the amount of de novo proteomic labeling two hours post-injection ( Fig. 1D ). Finally, we used FUNCAT-IHC to demonstrate that the observed AHA labeling is protein synthesis-dependent as co-injection of the protein synthesis inhibitor cycloheximide (CHX) significantly reduced the FUNCAT signal ( Fig. 1E ). Brain wide visualization of protein synthesis by Fun-DISCO Immunohistochemistry with FUNCAT labeling in slices is limited by the spatial resolution of individual slices and inherently adds bias to an analysis of region-specific changes in protein synthesis tied to a behavioral task. To spatially resolve region-specific changes in protein synthesis tied to conditioning in unbiased manner we developed Fun-DISCO, which leverages Click-3D ( Tamura et al , 2024 ) paired with FUNCAT labeling, brain clearing ( Friedmann et al , 2020 ), and light sheet microscopy to visualize the nascent proteome brain-wide ( Fig. 2A ). Download figure Open in new tab Figure 2: Fun-DISCO enables brain wide visualization of conditioning induced protein synthesis. (A) FUNCAT staining was combined with a modified version of iDISCO to visualize protein synthesis in the brains of mice which were administered AHA for two hours via retro-orbital injection, immediately after contextual fear conditioning. (B) Compared to home-cage controls, these trained mice appear to exhibit increased FUNCAT staining in brain regions typically associated with contextual memory, such as the dentate gyrus and entorhinal cortex, as well as other brains regions such as the periaqueductal gray (PAG) and cuneiform nucleus (CfN) not typically associated with conditioning induced plasticity. Scale bar = 200μm As a proof of principle, we conducted FUNCAT-iDISCO (Fun-DISCO) on brains perfused 2 hours after retro-orbital delivery of AHA following a contextual fear conditioning paradigm ( Fig. 2 ). Compared to mice injected with AHA after resting in their home cage, AHA injected conditioned animals showed robust region-specific intensities of protein synthesis including in the dentate gyrus and the entorhinal cortex ( Fig. 2B ), two regions that have previously been implicated in threat memory formation ( Feng et al , 2021 ; Bernier et al , 2017 ). In addition, we noticed increased FUNCAT staining intensity in a number of thalamic and midbrain nuclei in trained mice ( Fig. 2B ). Thus, Fun-DISCO has the capacity to discover novel regions involved in learning-induced plasticity in an unbiased way that may be missed through conventional sectioning approaches. Rapid changes in protein synthesis in the amygdala occur immediately following auditory threat conditioning Next, we sought to leverage the vast improvement in temporal resolution enabled by the retro-orbital delivery of AHA to explore the spatial and temporal dynamics of learning-induced de novo protein synthesis immediately following training in a different behavioral paradigm, namely auditory threat conditioning. Here, mice were trained to associate hearing a tone (conditioned stimulus, CS) with receiving a foot shock (unconditioned stimulus, US), and were compared to mice which did not receive foot shocks, as well as mice where the foot shock and tone were unpaired ( Fig. 3 ). FUNCAT-IHC analysis revealed that neuronal de novo protein synthesis was significantly increased in the amygdala in the two hours immediately following conditioning ( Fig. 3 ). This is consistent with previous studies that have shown memory consolidation following this associative conditioning paradigm to be dependent upon neuronal protein synthesis the amygdala ( Shrestha et al , 2020a ). We also observed that hippocampal neuronal protein synthesis was increased in both our paired and unpaired groups compared to non-shock controls, with this increase being significantly higher in the paired mice ( Fig. 3 ). Our analysis also revealed that protein synthesis levels in the somatosensory cortex remained unchanged in the two hours immediately following training ( Fig. 3 ). Download figure Open in new tab Figure 3: Auditory threat conditioning elevates neuronal protein synthesis in the hippocampus and amygdala immediately following training. Trained mice were conditioned to associate receiving a foot shock (unconditioned stimulus; US) upon hearing an auditory cue (conditioned stimulus; CS) within a specific context. Immediately following training, mice were administered 50 mg/kg AHA via RO injection before being perfused 2 hours later. These mice were compared to an unpaired control group, where mice received the foot shock independently from the CS, as well as non-shock control group, where mice were exposed to the context but not the US or CS. FUNCAT-IHC analysis revealed that neuronal protein synthesis was signifcantly increased in amygdala and the CA1 region of the hippocampus of mice trained via the ACFC compared to non-shock and unpaired controls, with NeuN immunoreactivity being used to identify neurons. FUNCAT signal remained unchanged in the somatosensory cortex (one-way ANOVA, Tukey’s MCT, n=4 animals, ≥3 sections per animal). Scale bar = 100 μm. Error bars = S.E.M. *= p≤ 0.05, **= p≤ 0.01, ***= p≤ 0.001, ****= p≤ 0.001. Auditory threat conditioning induces multiple temporally shifted windows of protein synthesis across different brain regions Given our improvements made to the temporal resolution of de novo proteomic labelling in vivo , we next determined how learning-induced protein synthesis changes throughout the process of memory consolidation. The consensus in the field is that the neuronal changes associated with memory consolidation occur at different time points, with some changes immediately following training, and others occurring hours or even days later. We therefore chose to examine neuronal protein synthesis between five and seven hours following auditory threat conditioning ( Fig. 4 ). Although FUNCAT-IHC analysis revealed that neuronal protein synthesis in the amygdala and hippocampus was still significantly elevated ( Fig. 4 ), more robust differences were observed in the somatosensory cortex at this later timepoint. Unlike immediately following training, at 5-7 hours post training, both the paired and unpaired mice exhibited a large increase in de novo protein synthesis in the layer 2/3 neurons of the somatosensory cortex compared to no shock controls. These findings suggest that de novo protein synthesis in this brain region may be involved in later processes of memory consolidation compared to the amygdala and hippocampus. Download figure Open in new tab Figure 4: A secondary wave of conditioning-induced protein synthesis occurs in layer 2/3 somatosensory neurons five hours after auditory threat conditioning. Mice in the trained, unpaired, and non-shock groups were administered 50 mg/kg AHA via RO injection 5 hours after their respective behavioral paradigms and perfused 2 hours later. FUNCAT-IHC analysis revealed that neuronal protein synthesis remained significantly elevated in amygdala in trained mice compared to non-shock controls. Interestingly at this later time point, protein synthesis was significantly increased in the CA1 neurons of the hippocampus and layer 2/3 neurons of the somatosensory cortex in both trained and unpaired mice when compared to the non-shock controls, with this effect being more pronounced in trained mice (one-way ANOVA, Tukey’s MCT, n=4 animals, ≥3 sections per animal). Scale bar = 50μm. Error bars = S.E.M. *= p≤ 0.05, **= p≤ 0.01, ***= p≤ 0.001, ****= p≤ 0.001 Discussion For over 60 years it has been known that the formation of LTM is dependent upon protein synthesis, but the temporal and spatial landscape of conditioning-induced de novo protein synthesis remains relatively underexplored. Herein, through combining the retro-orbital delivery of AHA with Fun-DISCO, we have significantly improved the spatial and temporal resolution of de novo proteomic labeling in vivo , allowing for the visualization of multiple windows of conditioning-induced protein synthesis throughout the mouse brain for the first time. These advancements enabled us to demonstrate that protein synthesis occurs predominately in the amygdala and hippocampus during the initial stages of auditory threat memory consolidation, before becoming more pronounced in the somatosensory cortex at later time points. Delivering AHA via retro-orbital injection allowed us to gain greater insights into the spatiotemporal dynamics of conditioning-induced protein synthesis compared to previous studies that have used AHA labeling in the context of memory. In the first of these studies, the authors delivered AHA to mice trained using a modified active place avoidance paradigm, where they observed increased protein synthesis in the hippocampus but not in the somatosensory cortex ( Evans et al , 2020 ). However, as this study relied upon i.p. injection, the authors were forced to label the de novo proteome over a period of 16 hours. Our findings suggest that this extended labeling period would have prevented the observation of the multiple, distinct windows of conditioning-induced protein synthesis that occur during this timeframe, meaning that FUNCAT signal was only found to be increased in areas of the brain where protein synthesis was constantly upregulated. A more recent study showed that dietary depletion of methionine can increase AHA labeling efficiency in mice ( Sharma et al , 2023 ). The authors in this study used AHA to examine astrocytic protein synthesis in mice following viral-mediated modulation of eIF2α (eukaryotic initiation factor 2α) phosphorylation. By depleting methionine for one week, the authors were able to observe de novo protein labelling three hours after i.p. injection of AHA. When designing our approach for examining learning-induced protein synthesis we opted to avoid methionine depletion, reasoning that it may interfere with metabolically sensitive processes involved in memory formation. Methionine is an essential amino acid found in nearly all proteins ( Lim et al , 2019 ) and as such any prolonged dietary restriction may lead to hypomethoninemia, which can result in a host of neurological symptoms ( Kripps et al , 2022 ). As such, any behavioral task or memory-related readout paired with methionine depletion should be interpreted with caution. This is especially the case in models of neurodegenerative and neurodevelopment disease where metabolism is already impacted ( Gruss, 2004 ; Griffin & Bradshaw, 2017 ; Cunnane et al , 2020 ). By improving the temporal specificity of AHA labelling, we were able to reveal that protein synthesis is elevated in the amygdala and hippocampus immediately following auditory threat conditioning and remains elevated during later stages of memory consolidation ( Fig. 3 & 4 ). These findings add further support to the plethora of evidence demonstrating that protein synthesis in these two brain regions are critically involved in the processing of threat memory, with the amygdala thought to enable long-term association between the administration of the CS (the tone) and the US (the foot shock), whereas the hippocampus is thought to allow long-term association between the foot shock and the spatial context ( Phillips & LeDoux, 1992 ). Notably, we observed that in the somatosensory cortex, neuronal de novo protein synthesis is unchanged immediately following auditory threat conditioning but becomes significantly elevated five hours later ( Fig. 3 & 4 ). In the auditory threat conditioning paradigm, lesioning of the somatosensory cortex in rats does not prevent the formation of a conditioned response (freezing) to the CS (tone) or the context in which the CS is presented ( Phillips & LeDoux, 1992 ). Instead, during auditory threat conditioning it is thought that these cortical regions are required for the long-term storage of these memories ( Bergstrom, 2016 ). It is possible that the delayed window of neuronal protein synthesis that we observed in the somatosensory cortex may help facilitate this storage. When seeking to identify the brain regions and cell types in which protein synthesis is required to facilitate memory formation, the field has done so using candidate approaches. In these studies, various pharmacological, genetic, and chemogenetic techniques have been leveraged to block protein synthesis in brain regions and specific cell types already thought to be involved in the particular form of memory being tested ( Shrestha et al , 2020a , 2020b ; Ozawa et al , 2017 ). Here, by combining retro-orbital delivery of AHA with Fun-DISCO, we have enabled the rapid labeling and visualization of the de novo proteome throughout the entirety of the mouse brain. This technological advancement will enable researchers to, in a non-biased manner, identify both where and when protein synthesis is altered during the different stages of memory consolidation. Although the reliance of LTM upon protein synthesis was first described in 1963, researchers are yet to identify which proteins need to be synthesized, in which cells, and at what timepoint in order to facilitate memory consolidation. Here, by significantly advancing the spatial and temporal resolution of AHA labeling in vivo , we hope to enable researchers to more accurately map changes in the de novo proteomic landscape that underlies long-term changes in complex behaviors. Methods Animal Care Wild-type C57/bl6J male and female mice of 3-5 months of age were provided with both food and water ad libitum and were maintained on a 12h/12h light/dark cycle at a stable temperature (78°F) and humidity (40–50%). All procedures involving the use of animals were performed in accordance with the guidelines of the National Institutes of Health and were approved by the Institutional Animal Care and Use Committee (IACUC, protocols 221-1143 and 221-1145). Contextual and cued-threat conditioning Rodent behavioral training and analysis was performed during the light cycle of the mice, with an even distribution of male and female mice across groups. For contextual fear conditioning, mice were placed into fear conditioning chamber (Coulbourn instruments) for 270 seconds before receiving a 2 second, 0.5mA foot-shock. This foot-shock (conditioned stimulus-CS) was repeated 100 and 200 seconds later, with the mouse being removed from the chamber 150 seconds after the administration of the final shock, spending a total of 12 minutes in the chamber. For cued-threat conditioning, all mice were first habituated to the fear conditioning chamber for 15 minutes, one-day prior to training. On day two, trained mice were placed into the chamber for 270 seconds, before being presented with a 5kHz, 85 dB pure tone for 30s, culminating with the administration of a 2 second, 0.5mA foot-shock. This paired-tone presentation (conditioned stimulus-CS) was repeated 100 and 200 seconds later, with the mouse being removed from the chamber 150 seconds after the administration of the final shock, spending a total of 12 minutes in the chamber. For the unpaired controls, mice spent a total of 12 minutes in the chamber. Mice were administered a 2 second, 0.5mA foot-shock 300, 430 and 530 seconds after being placed in the chamber. These mice were presented with a 5kHz, 85 dB pure tone for 30s at 100, 350 and 600 seconds after being placed in the chamber. Non-shock controls were placed in the chamber for a total of 12 minutes and were not administered a foot shock or presented with the audio cue. Freezing behavior was automatically measured by Freeze Frame 4 software (ActiMetrics). Mice were then administered AHA via RO injection either immediately after being removed from the chamber, or 5 hours later. Delivery of azidohomoalanine to awake mice Azidohomoalanine (Vector Laboratories, CCT-1106) was dissolved in phosphate-buffered saline (PBS) prior to delivery to awake via either intraperitoneal (IP), intravenous (tail-vein), or retro-orbital (RO) injection. A total injection volume of 50uL was used for all three delivery methods. For delivery of AHA via RO injection, a 0.5% proparacaine hydrochloride ophthalmic solution (Covetrus, 2963726) was administered to the eye 2 minutes prior to injection. RO injection in awake mice was then performed by two researchers, with the first restraining the mouse’s head before subsequently drawing back the skin below the eye and second researcher using a 27G needle to inject into the retro-bulbar sinus. For experiments requiring the inhibition of protein synthesis using the protein synthesis inhibitor cycloheximide (CHX, Millipore Sigma, 01810), 10 mg/kg CHX was delivered alongside AHA via RO injection. Mice were then deeply anesthetized with isoflurane before being intracardially perfused with 20 mL of PBS. For FUCNAT-WB analysis, the hippocampus was then dissected before being snap-frozen. Mice which underwent subsequent FUNCAT/IHC analysis were then intracardially perfused with 20 mL of 4% paraformaldehyde (PFA, ThermoFisher, 50-980-494). FUNCAT-Western Blot analysis Snap-frozen samples were lysed via sonication in radioimmunoprecipitation assay (RIPA) buffer (Cell Signaling, 9806) with Halt protein inhibitor cocktail (ThermoFisher, 78,438) and 1 mM phenylmethylsulfonyl fluoride (ThermoFisher, 36,978), with the EZQ protein quantification assay (Invitrogen, R33200) being used to determine protein concentration. Newly synthesized proteins were then labelled with IRDye® 800CW Alkyne Infrared Dye (LI-COR, 929-60002) using the Click-&-Go® Protein Reaction Buffer Kit (Vector Laboratories, CCT-1262) as per the manufacturer’s instructions. Briefly, newly synthesized proteins contained within 100 μg of sample were labelled with 20 μM 800CW Alkyne at RT for 30 minutes prior to undergoing chloroform-methanol precipitation as previously described ( Evans et al , 2024 ). Samples were then resuspended in 100uL of RIPA buffer with 2.5% SDS, before being denatured by boiling at 95°C for 5 minutes in 1X Laemmli sample buffer (Bio-Rad-1610747) with 5% 2-Mercaptoethanol (Millipore-Sigma, M6250). Samples were then separated via SDS-PAGE using a 4-20% Tris-Glycine gel (Invitrogen, XP04205BOX) before being transferred to a PVDF membrane (Invitrogen, IB24002) using the iBlot semidry transfer system (Invitrogen, IB2100). The total protein stain REVERT (LI-COR, 926– 10,011) was used for normalization. Immunohistochemistry, FUNCAT and Fun-DISCO For IHC and FUNCAT staining, brains fixed with 4% PFA were submerged in PBS with 30% w/v sucrose for 48 hours prior to being sectioned at 40 μM thickness using a vibratome (Leica, VT1200). Samples were then blocked and permeabilized for 1h at RT under constant agitation in 5% bovine serum albumin, 5% normal goat serum, and 0.5% triton-x in PBS. Newly synthesized proteins were then labelled with 5μM Alexa 647 alkyne (Vector Laboratories, CCT-1301) using the Click-&-Go® Cell Reaction Buffer Kit (Vector Laboratories, CCT-1263) as per the manufacturer’s instructions. Neurons were visualized using a guinea pig IgG anti-NeuN primary antibody (Synaptic Systems, 266 004, 1:1000) and Alexa-488 labeled goat anti-Guinea Pig IgG (H+L) (Invitrogen, A-11073). DAPI was used to stain cell nuclei and samples were mounted in ProLong Gold mounting media (ThermoFisher, P10144). For Fun-DISCO, brains were transcardially perfused with heparinized (.01%) PBS followed by 4%PFA. Brains were then post-fixed overnight in 4% PFA while rotating on an orbital shaker at 4oC. Following post-fixation, brains were washed 3x (for 2hrs, 4hrs, and overnight) in PBS and transferred to 5mL Eppendorf tubes. Brains were dehydrated in increasing concentrations MeOH (20%, 40%, 60%, and 80% 1hr each) diluted in B1N solution without sodium azide (2% glycine, .1% tritonX-100, and .01% 10N NaOH) at room temperature (RT) on an orbital shaker. Brains were then further dehydrated 4x in 100% MeOH for 1hr at RT. To delipidate the samples, a 2:1 solution of dichloromethane (DCM, Sigma 270997) and MeOH overnight (ON). The next day brains were further depilated in 100% DCM 3x for 1hr at RT with shaking. Samples were then washed 2x 1hr in 100% MeOH followed by rehydration in a MeOH/B1n series (60%, 40%, 20%) for 1 hr each at RT with shaking, followed by 100% B1N ON. The next day samples were begun on an adapted Click 3D protocol ( Tamura et al., 2024 ): Brains were incubated in 4mL of Click3D-C solution (10mM Hepes (pH 7.3), 900mM NaCl, 10% w/v DMSO, 4mM THPTA (Vector Labs CCT-1010, 2mM CuSO4 added to sterile H2O with vertexing after each addition) for 2 days at 370 on a 3600 vertical rotator. The Click3D-C solution was exchanged with new Click3D-C and rotated ON at 370 on a 3600 vertical rotator. The next day Click3D-C solution was exchanged for Click3D-R solution (10mM Hepes, 900mM NaCl, 10% w/v DMSO, 2mM CuSO4, 15 μM Alexa 647 alkyne (Vector Laboratories, CCT-1301), and freshly prepared 100mM NaAsc (Sigma, PHR1279), added to sterile H2O and vortexed after each addition) and rotated 2x ON at 370 on a 3600 vertical rotator with a fresh exchange after the first night. The Click3D-R solution was exchanged 1 more time and incubated at 370 on a 3600 vertical rotator for 2 hrs. Then the solution was exchanged for Click3D-W (0.1M EDTA (pH 8), .2% Triton x-100 in sterile H2O) and incubated for 2 hrs 4x at 370 on a 3600 vertical rotation with an exchange of solution after each period followed by 1x incubation ON. The following day the brains were washed 3x 1hr in PBS followed by dehydration in a MeOH series (20%, 40%, 60%, 80%, 100%, 100%, 100%) 1hr each diluted in H2O on an orbital shaker at RT. The brains were further delipidated ON in a 2:1 DCM/MeOH ON at RT on an orbital shaker. The next day the brains were incubated 2x 1hr in 100% DCM. Finally the brains were transferred to a 5mL amber borosilicate vial filled with benzyl ether (Sigma, 108014) for refractive index matching and stored until imaging. Imaging and image analysis For FUNCAT-Western blot analysis, membranes were imaged using a LI-COR Odessey M Scanner with the LI-COR Emperia Studio software being used for quantification. For FUNCAT-IHC analysis, 15 μm thick Z-stack images were taken using a Leica SP8 Confocal microscope with maximum intensity projections being created in ImageJ. Image analysis was performed blinded in ImageJ with NeuN immunoreactivity being used to generate a mask. Mean gray value was then measured within this neuronal mask for each image, with no significant difference being detected between the area of these masks across groups. A minimum of 3 sections per animal were analyzed, with each data point representing an average of these sections. For Fun-DISCO, cleared whole brains were imaged in benzyl ether using a Zeiss Z1 light sheet microscope at 5× magnification with the Zeiss Zen Black software. Image stitching and generation of orthogonal views were performed using Zeiss Zen Blue. Statistical analysis GraphPad Prism 10.1.2 was used for statistical analysis, with a one-way ANOVA with Tukey’s multiple comparison test (MCT), or Student’s T.Test being used as appropriate. All values are given as mean ± standard error of the mean. Significance was defined as *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Author Information Funding Sources This work was supported with funding from the Leon Levy Foundation, Alzheimer’s Association, Rainwater foundation, the National Institutes of Health (NS121786 and NS122316 to E.K.). Acknowledgement The authors would like to acknowledge the contributions Maggie Donohue and Jenesha Rawlani to this work. Funding National Institutes of Health, https://ror.org/01cwqze88 , NS121786 , NS122316 Alzheimer's Association, https://ror.org/0375f4d26 , Rainwater Charitable Foundation, https://ror.org/003q4qk22 , Leon Levy Foundation, https://ror.org/033hnyq61 , Footnotes ↵ # Co-first authors References ↵ Alvarez-Castelao B , Schanzenbächer CT , Langer JD & Schuman EM ( 2019 ) Cell-type-specific metabolic labeling, detection and identification of nascent proteomes in vivo . Nat Protoc 14 : 556 – 575 OpenUrl CrossRef PubMed ↵ Bergstrom HC ( 2016 ) The neurocircuitry of remote cued fear memory . 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