Abnormal synaptic proteomes, impaired neural ensembles, and defective behaviors in autism mouse models are ameliorated by dietary intervention with nutrient mixtures

Abnormal synaptic proteomes, impaired neural ensembles, and defective behaviors in autism mouse models are ameliorated by dietary intervention with nutrient mixtures | 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 Abnormal synaptic proteomes, impaired neural ensembles, and defective behaviors in autism mouse models are ameliorated by dietary intervention with nutrient mixtures Tzyy-Nan Huang , Ming-Hui Lin , Tsan-Ting Hsu , Chen-Hsin Yu , View ORCID Profile Yi-Ping Hsueh doi: https://doi.org/10.1101/2025.05.29.656761 Tzyy-Nan Huang 1 Institute of Molecular Biology, Academia Sinica , Taipei, 11529, Taiwan , Republic of China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ming-Hui Lin 1 Institute of Molecular Biology, Academia Sinica , Taipei, 11529, Taiwan , Republic of China 2 Molecular and Cell Biology, Taiwan International Graduate Program, Institute of Molecular Biology, Academia Sinica and Graduate Institute of Life Sciences, National Defense Medical Center , Taipei 11529, Taiwan , Republic of China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tsan-Ting Hsu 1 Institute of Molecular Biology, Academia Sinica , Taipei, 11529, Taiwan , Republic of China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Chen-Hsin Yu 1 Institute of Molecular Biology, Academia Sinica , Taipei, 11529, Taiwan , Republic of China Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yi-Ping Hsueh 1 Institute of Molecular Biology, Academia Sinica , Taipei, 11529, Taiwan , Republic of China 2 Molecular and Cell Biology, Taiwan International Graduate Program, Institute of Molecular Biology, Academia Sinica and Graduate Institute of Life Sciences, National Defense Medical Center , Taipei 11529, Taiwan , Republic of China Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yi-Ping Hsueh For correspondence: yph{at}as.edu.tw yph{at}gate.sinica.edu.tw Abstract Full Text Info/History Metrics Preview PDF Abstract Autism spectrum disorders (ASD) are a group of heterogeneous, behaviorally defined neurodevelopmental conditions influenced by both genetic and environmental factors. Here, we show that nutrients—an important environmental factor—can modulate synaptic proteomes, reconfigure neural ensembles, and improve social behaviors in ASD mouse genetic models. We analyzed Tbr1 +/− mice, a well-established model of ASD, using proteomic approaches and in vivo calcium imaging. Synaptic and metabolic proteomes were found to be sensitive to Tbr1 haploinsufficiency. Our results also revealed that Tbr1 haploinsufficiency promotes hyperactivation and hyperconnectivity of basolateral amygdala (BLA) neurons, enhancing the activity correlation between individual neurons and their corresponding ensembles. Zinc, branched-chain amino acids (BCAA), and serine—all nutrients known to regulate synapse formation and activity—were then combined into supplement cocktails and administered to Tbr1 +/− mice. This treatment altered synaptic and metabolic proteomes and normalized the activity and connectivity of the BLA in Tbr1 +/− mice during social interactions. We further show that although a low dose of individual nutrients did not alter social behaviors, treatment with supplement cocktails containing low-dose individual nutrients improved social behaviors and associative memory of Tbr1 +/− mice, implying a synergistic effect of combining low-dose zinc, BCAA, and serine. Moreover, the supplement cocktails also improved social behaviors in Nf1 +/− and Cttnbp2 +/M120I mice, two additional ASD mouse models. Thus, our findings reveal aberrant neural connectivity in the BLA of Tbr1 +/− mice and indicate that dietary supplementation with zinc, BCAA, and/or serine offers a safe and accessible approach to mitigate neural connectivity and social behaviors across multiple ASD models. Introduction Autism spectrum disorder (ASD) is a group of highly prevalent neurodevelopmental conditions characterized by two core behavioral symptoms: impairments in social behavior and communication, and the presence of restricted, repetitive behaviors and sensory abnormalities.[ 1 , 2 ] ASD arises from a combination of genetic and environmental factors[ 3 , 4 ] that influence neural development—particularly synapse formation and signaling—ultimately leading to impaired neural connectivity.[ 5 , 6 ] The crosstalk between genetic variations and environmental factors and the outcomes for synaptic functions and neural ensembles are critical issues in ASD research, yet many aspects of this topic remain to be investigated. Nutrition is a significant environmental factor contributing to ASD,[ 7 ] with dietary bias and gastrointestinal disturbances being common comorbidities.[ 8 , 9 ] Accordingly, dietary interventions have been proposed as a treatment avenue.[ 8 – 11 ] Importantly, recent studies have indicated convergence of the effects of certain nutrients, including zinc, branched-chain amino acids (BCAA) and serine, on synapse formation and activity.[ 10 , 12 – 18 ] Dietary supplementation with these nutrients may improve synapse formation and maintenance, as well as promote synaptic responses, to ameliorate neuronal functions ( Fig. 1A ).[ 7 ] Download figure Open in new tab Fig. 1. Cocktail supplementation alters the total proteome of Tbr1 +/− mouse brains. ( A ) Zinc, Ser and BCAA act in concert to regulate synaptic signaling and the synaptic response. Zinc is highly concentrated at synaptic vesicles and is co-released with glutamate. At the postsynaptic site, zinc induces condensate formation of the postsynaptic proteins and maintains dendritic spine morphology. Synaptic stimulation via the action of glutamate and D-Ser on ion channels activates downstream signaling and promotes protein synthesis, which is required for the long-term synaptic response and synaptic remodeling. BCAA enhances protein synthesis via activation of the mTOR pathway. ( B )-( G ) Four groups of total mouse brain lysates—WT_water, Tbr1 +/− _water, WT_1/4 cocktail and Tbr1 +/− _1/4 cocktail—were subjected to LC-MS-MS analysis. The results were subjected to ( B ) principle component analysis (PCA) and ( C ) Python package for weighted correlation network analysis (PyWGCNA) followed by protein network analysis using STRING ( D )-( H ). In ( C ), the major GO in the Black module of PyWGCNA are shown. Specifically, zinc is highly concentrated at synaptic vesicles and co-released with glutamate upon synaptic stimulation.[ 19 , 20 ] Increased concentrations of postsynaptic zinc enhance SRC kinase activity and result in enhanced conductivity of N-Methyl-D-aspartic acid receptor (NMDAR).[ 19 ] In addition, zinc induces protein-protein interactions and condensate formation of multidomain scaffold proteins, including SHANKs and CTTNBP2, at the postsynaptic site.[ 12 , 18 , 21 ] Thus, zinc is a critical synaptic modulator of the presynapse to postsynapse signal and it facilitates synaptic signaling, remodeling and dendritic spine maintenance. Apart from synaptic molecules, long-term zinc supplementation enhances ribosomal protein expression and increases protein synthesis in neurons, consequently correcting synapse deficits in Cttnbp2 +/M120I mice.[ 22 ] Moreover, dietary zinc supplementation improves behavioral deficits of mouse models with deficiencies in the Shank , Cttnbp2 and Tbr1 genes,[ 12 – 14 , 18 , 23 – 27 ] reinforcing evidence for the crosstalk between zinc and the functions of ASD-linked genes. D-serine, a derivative of L-serine released from neurons and astrocytes,[ 28 , 29 ] enhances NMDAR conductivity by binding to the receptor’s glycine-binding site.[ 30 ] L-serine supplementation to increase intrinsic D-serine levels by providing the parent material to neurons and astrocytes was shown previously to improve the NMDAR response and alleviate the symptoms of patients harboring an NMDAR mutation.[ 31 ] Thus, L-serine supplementation ameliorated the deficiencies caused by synaptic NMDAR impairment. BCAA serves as the building material for protein synthesis. Protein synthesis is an essential downstream pathway of synaptic stimulation to control synaptic remodeling and synaptic responses via a feedback mechanism ( Fig. 1A ).[ 7 ] BCAA supplementation in the brain has been found to improve neuronal function and the autism-linked phenotypes of mice or patients carrying mutations in Branched-chain ketoacid dehydrogenase kinase ( BCKDK ), a gene essential for catabolism of BCAA, and in Solute carrier transporter 7a5 ( SLC7A5 ), a large neutral amino acid transporter essential for maintaining normal levels of BCAA in the brain.[ 11 , 32 , 33 ] In addition, BCAA also act as a triggering factor to activate the mammalian target of rapamycin (mTOR) pathway for protein synthesis.[ 34 – 37 ] Through this activity, BCAA supplementation ameliorates the impaired dendritic spine formation and synaptic responses caused by various genetic defects, including those displayed by Nf1 +/− , Cttnbp2 +/M120I , and Vcp +/R95G mice.[ 14 , 17 , 18 ] These genes exert distinct molecular functions, yet all are involved in regulating dendritic spine formation or morphology.[ 15 , 26 , 38 ] Dietary BCAA supplementation increases the density of dendritic spines in mouse brains and improves the social behaviors of several autism mouse models.[ 15 – 18 ] Based on the aforementioned studies, single nutrient supplementation seems a promising and available treatment to improve, though not cure, the ASD-related symptoms in mouse models or patients. Since the diverse array of synaptic processes always interconnect with and influence each other, we hypothesized that apart from individual nutrients, a mixture containing multiple nutrients, including zinc, BCAA and serine, would prove beneficial in abrogating ASD-associated symptoms ( Fig. 1A ). There are two advantages to using a dietary supplement mixture. The first is that lower doses may be applied, thereby reducing the side effects associated with high-dose and long-term supplementation of a specific nutrient. The second is the broadened targets of the combined supplements. Thus, as long as impaired synaptic function or formation is associated with a target, a supplement mixture containing zinc, BCAA and serine may ameliorate to a certain extent the ASD-linked deficits. In this report, we investigate the effects of nutrient cocktails containing lower doses of zinc, BCAA and serine on Tbr1 +/− mice, a well-characterized ASD model.[ 39 – 42 ] We designed three sets of experiments to characterize the effects of our nutrient supplements. First, proteomic analysis was performed to investigate altered protein expression in the brain. Second, in vivo calcium imaging was conducted to dissect the neural ensembles of the basolateral amygdala (BLA), a brain area sensitive to Tbr1 haploinsufficiency.[ 39 ] Previously, we showed that Tbr1 haploinsufficiency reduces contralateral axonal projection but increases mistargeting of ipsilateral axonal projection of the BLA to other brain regions and modulates functional connectivity at a whole-brain scale.[ 43 ] However, neural ensembles at the BLA upon social stimulation have not yet been explored. Thus, using Tbr1 +/− mice as a model, we analyzed the effect of Tbr1 haploinsufficiency on BLA neural ensembles, and then characterized if our dietary supplements could correct the defective neural ensembles in the BLA of Tbr1 +/− mice. Third, we performed behavioral assays to monitor the beneficial effects of dietary supplementation on the social behaviors of Tbr1 +/− mice. Apart from Tbr1 +/− mice, we also analyzed the social behaviors of two additional ASD mouse models, Nf1 +/− and Cttnbp2 +M120I mice. The beneficial effects of our combinatory dietary supplements for multiple mouse models support their potential broad applicability in various ASD contexts. Together, our study provides evidence for potential therapeutic treatments of ASD-linked deficiencies using dietary supplementation with multiple nutrients. Results A cocktail of dietary supplements alters total proteomes The concentrations of single supplements used to improve ASD-linked phenotypes in previous studies are equal to 2% serine, 1.8% leucine or 40 ppm zinc in drinking water (approximal 4.8 mL per day per mouse).[ 10 , 14 , 15 , 17 ] In the current study, we lowered the concentrations of individual supplements to make our cocktail. Given that L-serine has to be processed into D-serine to modulate neuronal activity, we maintained the L-serine concentration at a relatively higher level than that of BCAA. The cocktail containing 0.45% BCAA (leucine 0.225%, isoleucine 0.1125% and valine 0.1125%, i.e., Leu:Ile:Val=2:1:1), 1% serine and 20 ppm zinc is termed “1/4 cocktail”, in which the concentration of BCAA was reduced to one-quarter the original dose and the amounts of L-serine and zinc were reduced to half the original doses. The estimated total intake amounts of individual nutrients from drinking water and chow are detailed in Methods. Our previous studies have indicated that administration of either zinc or BCAA for 1 week alters the synaptic proteomes of Nf1 +/− and Cttnbp2 -deficient mice.[ 14 , 16 , 18 ] Although the concentrations of the individual supplements in our supplement cocktails were much lower than provisioned in those previous studies, the cocktail treatments may still modulate brain proteomes to some extent if the supplement cocktails have a synergistic effect on the brain. To investigate that possibility, we analyzed total lysates of whole mouse brains using label-free liquid chromatography-tandem mass spectrometry (LC-MS-MS). Four groups of animals, i.e., WT_water, Tbr1 +/− _water, WT_1/4 cocktail and Tbr1 +/− _1/4 cocktail, with three mice in each group were analyzed. We identified ∼3000 protein species from each sample ( Supplementary Table 1 ) and applied principal component analysis (PCA) to analyze the differences among the four experimental groups ( Fig. 1B ). PC1 did not strongly differentiate among the four groups of data, but the Tbr1 +/− _water group was better separated from the other three groups along PC2 ( Fig. 1B ), indicating that the total proteome of the Tbr1 +/− _water group is relatively different from those of the other three groups. This outcome also implies that cocktail supplementation renders Tbr1 +/− mice more comparable to WT mice in terms of protein expression profiles of the brain ( Fig. 1B ). To further characterize the proteomes, we performed network analysis using a Python package for weighted gene co-expression network analysis (PyWGCNA, https://github.com/mortazavilab/PyWGCNA ).[ 44 ] After removing proteins displaying low-quality results, the final 2103 proteins present in all four groups were inputted to pyWGCNA ( Supplementary Table 1 ). Sample clustering indicated that the three samples of the Tbr1 +/− _water group clustered together and were distinct from the samples of the other groups ( Supplementary Fig. 1A) , consistent with the PCA results ( Fig. 1B ). Based on topological matrix analysis, we identified seven major co-expression modules ( Supplementary Fig. 1B-1E ). The “Black” module contains the most significantly correlated proteins in response to cocktail treatment, which are highly relevant to chemical synapse and mitochondrial activity ( Fig. 1C ). The other modules are involved in translation, mitochondrial function, protein location, RNA metabolism, and signaling ( Supplementary Fig. 2A-2C, 3A-3C ). We further explored the individual gene ontology (GO) terms and protein networks of the Black module by means of STRING analysis. We noticed that the GO of chemical synaptic transmission in the Black module includes highly connective neurotransmitter receptors, their cytoplasmic adaptor molecules and ion transporters, such as glutamate receptors (GRIA1, GRIN2A, GRIN2B and GRM1), GABA receptors (GABRB1 and GABBR2) and a GABA transporter (SLC6A1, i.e., GAT-1), as well as critical pre- and post-synaptic scaffold molecules (DLG1, Homer1, LIN7A, DLGAP2 and BSN) ( Fig. 1D ). Moreover, certain protein networks in the Black module are relevant to synaptic vesicle recycling ( Fig. 1E ), membrane organization ( Fig. 1F ), and the aerobic electron transport chain ( Fig. 1G ). Thus, our proteomic and bioinformatic analyses reveal that the total proteomes of Tbr1 +/− mouse brains are different from those of WT brains and that cocktail supplementation makes the protein expression profiles of Tbr1 +/− mice more comparable to those of WT mice. In particular, the expression profiles of proteins participating in chemical synaptic transmission and mitochondrial function were altered by Tbr1 haploinsufficiency and our cocktail treatment. Alteration of neural ensembles at the BLA by Tbr1 haploinsufficiency and cocktail supplementation To further explore the impact of cocktail supplementation on neural responses in vivo, we used in vivo calcium imaging to monitor the neural activity of Tbr1 +/− mice upon social stimulation and compared it with that of WT mice, both in the presence and absence of supplement cocktail treatment. We infected the BLA with adeno-associated virus (AAV) expressing GCaMP7c and used a miniaturized fluorescence microscope to monitor BLA activity in freely moving mice ( Fig. 2A ). After recovery from surgery and habituation to handling by the experimenter and miniscope setup, the mice were subjected to an open field test followed by two sequential behavior tests separated by a one-week interval. Each behavior test comprised two sessions, i.e., inanimate object exploration (OE) and reciprocal social interaction (RSI) with an unfamiliar “stranger” mouse ( Fig. 2A ). During the one-week interval, regular drinking water was replaced by the 1/4 cocktail supplement. Thus, the first behavior test represents the control water group (i.e., OE-1 and RSI-1), and the second one is the cocktail-treated group (i.e., OE-2 and RSI-2) ( Fig. 2A ). After completing all experiments, the localizations of AAV infection and GRIN lens implantation were confirmed ( Supplementary Fig. 4A-4C ). The activity and number of recorded neurons during each session were then determined based on changes in GCaMP7c signals ( Supplementary Fig. 4D-4G ). Download figure Open in new tab Fig. 2 Neural ensembles in the BLA are influenced by Tbr1 haploinsufficiency and cocktail supplementation. ( A ) Schematic of the experimental design (WT: n = 4; Tbr1 +/− : n = 4). ( B ) Activity of neurons in the basolateral amygdala (BLA) during object exploration (OE, top) and reciprocal social interaction (RSI, bottom) tests. A set of representative results, including individual neuron activity and mean activity for each neuronal ensemble, is shown. ( C ) The correlation between the mean neuronal ensemble activity and behavior (binary vector) in the OE (top) and RSI (bottom) tests. ( D ) Correlation of the activity of all recorded neurons and their corresponding ensembles. The cumulative probabilities of the correlation coefficient of WT and Tbr1 +/− mice in OE-1, OE-2, RSI-1 and RSI-2 are shown. ( E )-( F ) Activity correlations between dual-recorded neurons and their corresponding neural ensembles. The data points represent the individual neurons. ( E ) Object exploration, n = 27 from four WT mice; n = 12 from four Tbr1 +/- mice. ( F ) Reciprocal social interaction, n = 49 from four WT mice; n = 16 from four Tbr1 +/- mice. Data in ( C ) is mean ± SEM. Statistical analysis in ( C ) by two-way ANOVA followed by Bonferroni post hoc test. The Kolmogorov–Smirnov test was used for cumulative probabilities in ( D ). * P < 0.05, ** P < 0.01, *** P < 0.001. All statistical analysis and results, including the actual P -values, are summarized in Supplementary Table 2 . We used three different methods to analyze the in vivo calcium imaging results. The first was to evaluate the effect of Tbr1 deficiency and cocktail supplementation on BLA neural ensembles. A previous study identified a paired neural ensemble in the BLA as driving social behaviors.[ 45 ] Similarly, determination of the within-cluster sum of squares from our data also revealed two neuronal ensembles in the BLA for all experimental groups (OE-1, OE-2, RSI-1 and RSI-2), whether WT or Tbr1 +/− mice were being assessed ( Fig. 2B , Supplementary Fig. 5A, 6A ). Next, we determined the correlation coefficient between behaviors and neuronal ensemble activity. For OE, there was no obvious difference in correlations between behaviors and ensembles one and two for either WT or Tbr1 +/− mice ( Fig. 2C , upper). In contrast, the correlation coefficient of ensemble one in RSI was noticeably higher than that of ensemble two for both WT and Tbr1 +/− mice ( Fig. 2C , lower). Thus, ensemble one is more relevant to RSI, no matter the genotype. Then we analyzed the correlation of individual neuron activity with its corresponding ensemble ( Supplementary Fig. 5B, 6B ), and quantified the cumulative probability of the correlation coefficients ( Fig. 2D ). All recorded neurons were subjected to this analysis. We found that no matter for OE or RSI, there were differences between genotypes (i.e., Tbr1 +/− vs WT), regardless of treatments (i.e., water vs. 1/4 cocktail) ( Fig. 2D ). The cumulative curves of Tbr1 +/− mice were shifted right related to WT mice, meaning that more Tbr1 +/− neurons were more strongly correlated with their ensembles. Tbr1 +/− and WT mice could be distinguished well based on these correlation coefficients ( Fig. 2D ). In addition to analyzing all recorded neurons ( Fig. 2D ), we analyzed dual-recorded neurons in both OE-1/OE-2 and RSI-1/RSI-2, with a view to revealing the specific response of a particular neuron. We recorded a total of 300 responsive neurons in four WT mice and 242 such neurons in four Tbr1 +/− mice: 27 (9%) and 12 (4.9%) dual-recorded neurons for OE in the WT and Tbr1 +/− mice, respectively; and 49 (16.3%) and 16 (6.6%) dual-recorded neurons for RSI in the WT and Tbr1 +/− mice, respectively. Thus, Tbr1 +/− mice had fewer dual-recorded neurons than WT mice in both the OE and RSI contexts ( Fig. 2E , 2F ). Among these dual-recorded neurons, WT neurons were positively correlated between OE-1 and OE-2, whereas Tbr1 +/− neurons were negatively correlated, although in neither case was the correlation statistically significant ( Fig. 2E , WT, p = 0.1518; Tbr1 +/− , p = 0.3883). The correlation coefficients for individual WT neurons were widely distributed from values of zero to one. However, the correlation coefficients for Tbr1 +/− neurons were enriched in the range of 0.3 to 0.8 ( Fig. 3E ). Thus, there were fewer repetitively responsive neurons in Tbr1 +/− mice in the OE condition compared to WT mice and they were less diverse. Download figure Open in new tab Fig. 3 Populations and responses of sociality-linked neurons in the BLA are influenced by Tbr1 deficiency and cocktail supplementation. ( A ) Definition of the behavior-related neurons. ( B ) Representative in vivo calcium imaging traces of behavior-related positively correlated (top), negatively correlated (middle) and irrelevant (bottom) neurons. Left, neuronal activity during the entire session. Right, comparison between the raw cosine similarity (R) and null distribution of shuffled data. ( C ) Ratio of object exploration- and sociality-linked neurons ( n = 300 from four WT mice; n = 242 from four Tbr1 +/- mice). ( D ) Mean activity of object exploration- and sociality-linked neurons during behavior tests. Only positively correlated neurons were analyzed. ( E ) Connectrograms to reveal repetitively recorded neurons across the four behavioral sessions. ( F ) Overlap between the water and cocktail experimental groups in terms of object exploration- and sociality-linked neurons. Data in ( D ) represents mean ± SEM. * P <0.05, ** P <0.01; two-way ANOVA with Bonferroni post hoc test. All statistical analysis and results, including the actual P -values, are summarized in the Supplementary Table 2 . In terms of RSI, though the correlations between the activities of individual WT neurons and their ensemble were still widely distributed from values of zero to one for both the RSI-1 and RSI-2 groups, we detected a significant positive correlation between RSI-1 and RSI-2 ( Fig. 2F , left, p = 0.0154). This outcome indicates that although the correlation is heterogeneous, the activity correlation of a particular neuron with the ensemble tended to be maintained between RSI-1 and RSI-2 in WT mice. In contrast, there was no correlation between RSI-1 and RSI-2 for Tbr1 +/− mice ( Fig. 3F , right, p = 0.4041). Moreover, the correlation coefficients of individual neurons in RSI-1 were widely distributed from values of 0.2 to one, but with coefficients enriched in the range of 0.4-0.8 for RSI-2 ( Fig. 3F , right). Thus, cocktail supplementation alters the activity correlation of repetitively responsive neurons in Tbr1 +/− but not WT mice during RSI. Consequently, Tbr1 haploinsufficiency results in a stronger correlation between individual BLA neuron activity and its corresponding ensemble. Moreover, cocktail supplementation alters the activity correlation of repetitively responsive neurons in the Tbr1 +/− BLA. Activity change of BLA neurons by Tbr1 haploinsufficiency and supplement cocktails Our second set of calcium imaging analyses aimed to investigate the responses of individual neurons during behaviors. We identified three types of neurons based on correlations of their activities with behavior,[ 46 ] i.e., positively correlated, negatively correlated, and irrelevant neurons ( Fig. 3A , 3B ). Neurons displaying a positive correlation reflected those with a higher probability of being activated during behavior. Those exhibiting a negative correlation tended to be activated between two behavioral bouts. Irrelevant neurons did not present a clear correlation (positive or negative) with behavior ( Fig. 3A , 3B ). Among a total of 300 and 242 activated neurons recorded from WT and Tbr1 +/− mice, respectively, the majority (>80%) of activated BLA neurons were irrelevant to OE and RSI for both WT and Tbr1 +/− mice ( Fig. 3C , grey area). During both the OE-1 and OE-2 tests, approximately 4% and 1% of activated cells were defined as positively or negatively correlated neurons, regardless of genotype ( Fig. 4C ), indicating that Tbr1 +/− mice do not differ from WT mice in terms of numbers of activated neurons during object exploration. Download figure Open in new tab Fig. 4 Cocktail supplementation increases the diversity of activation patterns in the sociality-linked neurons of Tbr1 +/- mice. ( A ) Representative neuronal activity patterns of RSI-positive neurons in WT and Tbr1 +/- mice. ( B ) Functional networks of WT and Tbr1 +/- mice in RSI. Links (lines) between the nodes represent significant similarity in activation patterns relative to shuffled data. ( C ) Degree centrality of neurons in WT and Tbr1 +/- mice across the RSI-1 and RSI-2 sessions. ( D ) Functional networks of WT and Tbr1 +/- mice in OE. Links (lines) between the nodes represent significant similarity in activation patterns relative to shuffled data. ( E ) Degree centrality of neurons in WT and Tbr1 +/- mice across the OE-1 and OE-2 sessions. The results of WT mouse #3 and Tbr1 +/− mouse #4 are presented as examples. Data in ( C ) and ( E ) are presented as means ± SEM. The data points of individual neurons are also shown. Two-way ANOVA with Bonferroni post hoc test was used for statistical analysis. ** P < 0.01; *** P < 0.001; **** P < 0.0001. All statistical analysis and results, including the actual P -values, are summarized in the Supplementary Table 2 . In terms of reciprocal social interaction (RSI), the percentages of positively- and negatively-correlated neurons in WT mice were 9.3% and 3% for RSI-1, respectively, which rose to 12.3% and 6.3% for RSI-2, i.e., following 1 week of cocktail treatment ( Fig. 3C ). Thus, cocktail supplementation of WT mice increased the number of both positively- and negatively-correlated neurons in the BLA. For Tbr1 +/− mice, positively correlated neurons accounted for 11.6% of total recorded neurons in RSI-1. However, we did not identify any negatively correlated neurons in the Tbr1 +/− RSI-1 group ( Fig. 3C ). In the RSI-2 group, negatively correlated neurons were present (1.2%) in Tbr1 +/− mice, but the percentage of positively correlated neurons declined to 5% ( Fig. 3C , RSI-2 group). Thus, these results suggest the differential neuronal response of Tbr1 +/− and WT mice to social stimulation as well as the differing effects of cocktail supplementation on Tbr1 +/− and WT mice. Next, we determined the mean activity of positively correlated neurons during behaviors. The amplitudes of mean activity were comparable among the OE-1 and OE-2 groups of WT and Tbr1 +/− mice ( Fig. 3D , upper). However, the mean activity of the Tbr1 +/− RSI-1 group was noticeably higher than that of the WT RSI-1 group ( Fig. 3D , lower). Moreover, cocktail supplementation reduced the mean activity of Tbr1 +/− neurons in the RSI-2 group ( Fig. 3D , lower). These results imply that Tbr1 deficiency results in hyperactivation of positively correlated neurons in the BLA during social interaction and that the cocktail treatment can correct this hyperactivity of Tbr1 +/− BLA neurons. We further determined how neurons were repetitively activated in these different behavior tests ( Fig. 3E , 3F ). First, we used concentric circles to summarize the properties of each recorded BLA neuron in WT and Tbr1 +/− mice ( Fig. 3E ). Based on behavioral tests and treatments, the concentric circles were then separated into four parts, i.e., OE-1, RSI-1, OE-2, and RSI-2 ( Fig. 3E ), with the same responsive neurons being connected by lines crossing the central area of the circles. We found that there were more connecting lines for WT mice compared to Tbr1 +/− mice ( Fig. 3E ), implying that more responsive BLA neurons were shared among the tests in WT mice, although those shared neurons still represented a minority of total BLA neurons ( Fig. 3E , 3F ). In particular, only seven neurons (i.e., 8.1% of responsive neurons) of WT mice and one neuron (i.e., 2.4% of responsive neurons) of Tbr1 +/− mice were shared by RSI-1 and RSI-2 ( Fig. 3F , right). These results indicate that different BLA neurons are used to respond to the same types of behavior at different times. In Tbr1 +/− mice, the beneficial effect of cocktail supplementation on RSI-2 is mainly mediated by neurons that differ from those that are responsive during RSI-1. Accordingly, our supplement cocktail appears to influence the responsiveness of individual neurons and consequently alters their connectivity to improve the responses of mice to social stimulation. Cocktail treatment alters the BLA neural network As a final approach to our in vivo calcium imaging analysis, we characterized the functional neural network of the BLA in our mice. When we examined the individual responses of BLA neurons, we noticed that the positively correlated neurons of the Tbr1 +/− RSI-1 group tended to display higher activity at the beginning of the RSI test and their activities seemed more correlated with each other ( Fig. 4A ). However, this property disappeared in RSI-2, i.e., after cocktail supplementation. Moreover, this synchronized activity at the beginning of the RSI-1 session was not observed for WT mice ( Fig. 4A ). To analyze this property, we measured degree centrality, which represents a given neuron’s connection with others based on the similarity of their activation patterns.[ 47 , 48 ] All recorded neurons, including positive, negative and irrelevant neurons, were subjected to this analysis. For RSI-1, all recorded neurons in Tbr1 +/− mice were tightly clustered in the respective network graph ( Fig. 4B , Supplementary Fig. 7 ) and had a higher degree centrality compared to that of WT mice ( Fig. 4C ). When we separated sociality-linked neurons (encompassing both positively- and negatively-correlated neurons) and irrelevant neurons, the difference in degree centrality between Tbr1 +/− and WT mice was more obvious for sociality-linked neurons ( Fig. 4C , middle panel) and it was absent for irrelevant neurons ( Fig. 4C , right panel). Thus, the difference observed for all neurons is mainly attributable to sociality-linked neurons. This result also indicates that Tbr1 deficiency prompts enhanced functional connectivity among BLA neurons. Then we investigated the effect of cocktail supplementation, i.e., the response of RSI-2. The degree centrality of all neurons was not affected ( Fig. 4C , left). However, the degree centrality of Tbr1 +/− sociality-linked neurons was reduced by the cocktail treatment to levels comparable to those of WT mice ( Fig. 4C , middle). Irrelevant neurons exhibited a different response, with WT irrelevant neurons displaying reduced degree centrality after cocktail supplementation, resulting in their being different to the irrelevant neurons of Tbr1 +/− mice ( Fig. 4C ). Nevertheless these results indicate that cocktail supplementation corrects the abnormal functional connectivity of sociality-linked BLA neurons in Tbr1 +/− mice. In addition to RSI, we also analyzed the BLA functional network for OE ( Supplementary Fig. 8 ). In contrast to RSI, cocktail supplementation did not alter the degree centrality of Tbr1 +/− neurons during this behavior test, no matter if all recorded neurons, neurons associated solely with object exploration, or irrelevant neurons were assessed ( Fig. 4D , 4E, Tbr1 +/− OE-1 vs. OE-2). The only noticeable differences we detected were between WT and Tbr1 +/− neurons ( Fig. 4D , 4E , all neurons of WT vs. Tbr1 +/− in OE-2 and irrelevant neurons of OE-1). These results strengthen the specific roles of TBR1 and cocktail supplementation in regulating the BLA’s functional network in response to social stimulation. Overall, the results of our suite of in vivo calcium imaging analyses indicate that Tbr1 deficiency results in hyperactivity and hyperconnectivity of BLA neurons during social interaction, consequently modulating BLA neuronal ensembles. Treatment with our supplement cocktail corrects the abnormal neuronal activity and connectivity of the BLA in Tbr1 +/− mice. Synergistic effects of dietary supplements on social behaviors Next, we investigated the effect of the cocktail supplementation on mouse behaviors. First, we confirmed the synergistic effect of the supplement cocktail on RSI. Tbr1 +/− mice were subjected to five sequential RSI tests with a one-week interval between tests starting from postnatal day 60 (P60). The first RSI test was the water control and the second to fifth tests were to investigate sequentially the effects of one-week administration with 0.45% BCAA, 1% serine, 20 ppm zinc or 1/4 cocktail ( Fig. 5A ). Supplementation with individual nutrients or 1/4 cocktail did not influence the social behaviors of WT mice ( Fig. 5B , left). For Tbr1 +/− mice, administrations of 0.45% BCAA, 1% serine or 20 ppm zinc alone did not enhance their social behaviors in RSI. However, the 1/4 cocktail treatment improved the social behaviors of the Tbr1 +/− mice in the fifth RSI test ( Fig. 5B , middle). When we compared the responses of the WT and Tbr1 +/− mice, we detected differences in the water and individual supplement assay groups, but not for the cocktail-provisioned group ( Fig. 5B , right), supporting the synergistic effect of our supplement cocktail on social behaviors. Download figure Open in new tab Fig. 5 Mixing low-dose nutrients synergistically improve social behaviors of autism mouse models. ( A ), ( C ) Experimental design of dietary supplementation and behavior assays. RSI, reciprocal social interaction. ( B ) Synergistic effects of the 1/4 cocktail on RSI of WT and Tbr1 +/− mice. Individual nutrients, including BCAA (0.45%), serine (1%) and Zn 2+ (20 ppm), and the 1/4 cocktail were sequentially applied to mice for 1 week for each supplementation assay. Five RSI tests were conducted as indicated to investigate the effect of supplements on RSI. Left: the response of WT mice in each test; Middle: the response of Tbr1 +/− mice in each test; Right: the comparison of WT and Tbr1 +/− mice in each test. ( D ) Synergistic effects of the 1/8 cocktail on Cttnbp2 +/M120I mice. Different from ( A ) and (B ), each Cttnbp2 +/M120I mouse was only subjected to two RSI tests: one is water control; the other is supplement treatment. Data are presented as data points for individual mice and/or means ± SEM. The numbers ( n ) of examined mice for each group are indicated. ( B ) Left and Middle: paired t test was performed to examine the difference between water control and other experimental groups, individually. Right: Two-way ANOVA with Bonferroni post hoc test. ( D ) Paired t test. * P <0.05, ** P <0.01, ns = non-significant. All statistical analysis and results, including the actual P -values, are summarized in Supplementary Table 2 . To further consolidate the synergistic effect of our supplement cocktail, we investigated another ASD mouse model, i.e., Cttnbp2 +/M120I mice. We have demonstrated previously that 0.45% BCAA or 40 ppm zinc supplemented in drinking water is sufficient to improve the social behaviors of Cttnbp2 +/M120I mice.[ 13 , 14 , 18 ] Therefore, we investigated the response of Cttnbp2 +/M120I mice to a “1/8 cocktail”, in which the concentration of BCAA had been further reduced to one eighth the original dose (i.e., 0.225%), the amount of serine was reduced to one-quarter of the original (i.e., 0.5%), and the amount of zinc was maintained at 20 ppm ( Fig. 5C ). Based on the results of two consecutive RSI tests (one with water, the other with nutrient supplement), we did not detect a noticeable improvement in the social behaviors of Cttnbp2 +/M120I mice that were individually supplemented with 20 ppm zinc, 0.225% BCAA or 0.5% serine ( Fig. 5D ). Importantly, supplementation with the 1/8 cocktail enhanced the social interaction of Cttnbp2 +/M120I mice with unfamiliar mice in RSI ( Fig. 5D ). Thus, mixing low-dose zinc, BCAA and serine supplements results in a synergistic effect that improves the social behaviors of multiple autism mouse models. Supplement cocktails improve ASD-associated behaviors of multiple mouse models Apart from a one-week treatment regimen, we further investigated the long-term effects of the 1/4 cocktail on Tbr1 +/− mice. Supplementation starting from weaning and it continued until all experiments had been completed. We performed a sequential series of behavioral assays, including open field, elevated plus maze, reciprocal social interaction, three-chamber test and cued fear conditioning, starting from P60 ( Fig. 6A ). Long-term supplementation of the 1/4 cocktail did not noticeably affect mouse body weight ( Fig. 6B ). Compared to the control group that drank regular water, neither Tbr1 +/− nor WT mice administered the 1/4 cocktail exhibited a difference in behavior in the open field or elevated plus maze assays ( Fig.6C -6D ), consistent with our previous observation that Tbr1 haploinsufficiency does not influence locomotion or anxiety.[ 39 ] Download figure Open in new tab Fig. 6 Cocktail supplementation improves the social behaviors of three autism mouse models. ( A ), ( H ) Experimental design of cocktail supplementation and behavior assays. OF, open field; EPM, elevated plus maze; 3C, three chamber test; RSI, reciprocal social interaction; CFC, cued fear conditioning. ( B )-( G ) The effect of long-term 1/4 cocktail treatment on Tbr1 +/− mice. ( B ) Body weight. ( C ) Open field. ( D ) Elevated plus maze. ( E ) Cued fear conditioning. ( F ) Reciprocal social interaction. ( G ) Three-chamber test. ( I ) The social behaviors of NF1 +/− , Cttnbp2 +/M120I , and Tbr1 +/− mice in the RSI assay were improved by 1/2 cocktail treatment. Data are presented as data points for individual mice and/or means ± SEM. The numbers ( n ) of examined mice for each group are indicated. ( B ), ( I ) Paired t test. ( C )-( G ) Two-way ANOVA with Bonferroni post hoc test. * P <0.05, ** P <0.01, ns = non-significant. Note there is no significant difference in ( B )-( D ), though no labeling is indicated. All statistical analysis and results, including the actual P -values, are summarized in Supplementary Table 2 . For auditory fear conditioning, similar to results reported previously,[ 39 ] the freezing response of Tbr1 +/− mice that drank regular water was lower than that of their WT littermates ( Fig. 6E ). However, the performance of Tbr1 +/− mice provisioned with the 1/4 cocktail supplement was comparable to that of their WT littermates ( Fig. 6E ). Thus, the 1/4 cocktail treatment rescued the memory performance of Tbr1 +/− mice. In terms of reciprocal social interaction, long-term 1/4 cocktail treatment also increased the interaction time of Tbr1 +/− mice with unfamiliar (stranger) mice ( Fig. 6F ). This effect was specific to the mutant mice because the 1/4 cocktail did not alter the performance of WT littermates in reciprocal social interaction ( Fig. 6F ). Similarly, the 1/4 cocktail also improved the sociability of Tbr1 +/− mice in the three-chamber test, as reflected by a longer interaction time with stranger one compared to an inanimate object, as well as the comparable preference index between cocktail-supplemented Tbr1 +/− mice and WT mice ( Fig. 6G , left). Consistent with a previous finding that Tbr1 deficiency is not involved in novelty preference of social interaction,[ 39 ] we also did not detect a difference in novelty preference regardless of genotype or treatment ( Fig. 6G , right). Thus, long-term 1/4 cocktail treatment improves the social deficits caused by Tbr1 haploinsufficiency without noticeable side effects on body weight, locomotion or anxiety. Apart from Tbr1 +/− and Cttnbp2 +/M120I mice, we further analyzed the effects of a supplement cocktail on yet another ASD mouse model, i.e., Nf1 +/− mice. Our previous study showed that 0.9% Leu in drinking water did not improve the social behavior of Nf1 +/− mice.[ 16 ] Therefore, we designed a “1/2 cocktail”, in which the concentrations of BCAA, L-serine, and zinc were all reduced to half the original dose. To monitor the behavioral changes of the same mice, we subjected them to two consecutive tests of reciprocal social interaction (RSI) with a one-week interval, providing them with the 1/2 cocktail during the interval ( Fig. 6H ). We found that the Nf1 +/− mice exhibited longer interaction times with unfamiliar mice in the second RSI compared to the first RSI ( Fig. 6I ). Tbr1 +/− mice and Cttnbp2 +/M120I mice were both included in this assay as positive controls ( Fig. 6I ). These results support that our 1/2 cocktail exerts a beneficial effect in terms of the social behavior of multiple ASD mouse models. Discussion Herein, we have demonstrated the abnormal synaptic proteomes, as well as hyperactivity and hyperconnectivity of BLA neurons, in Tbr1 +/− mice. Using this model, we have revealed the effects of a supplement cocktail containing BCAA, serine and zinc in correcting the altered proteomes and neural ensembles of Tbr1 +/− mice. We further applied mouse behavioral assays to reveal the synergistic effects of mixing low-dose individual supplements on multiple ASD mouse models, including Tbr1 +/− , Nf1 +/− and Cttnbp2 +/M120I mice. Thus, dietary supplements that enhance synaptic activity and protein synthesis can correct the abnormal neural activation and connectivity and improve the social behaviors of multiple ASD mouse models. Such supplement cocktails could represent a safe and available treatment for various ASD conditions. For unknown reasons, the BLA is the region most susceptible to Tbr1 haploinsufficiency.[ 39 ] Reduction or absence of the posterior part of the anterior commissure, a white matter structure linking the two BLA in the two brain hemispheres, is an evolutionarily conserved feature shared by humans and mice displaying monoallelic mutation or deletion in the TBR1 gene.[ 39 , 49 , 50 ] Our previous study further demonstrated that an increase in BLA activity upon treatment with D-cycloserine, an analog of D-serine, improved the social interaction behavior of Tbr1 +/− mice.[ 39 ] Recently, we performed a whole-brain analysis of C-FOS expression, revealing that Tbr1 haploinsufficiency globally enhances the neural activity of the entire brain in the absence of particular stimulation. However, the correlated neuronal activity between the BLA and other brain regions is reduced in the Tbr1 +/− mice, indicating that the degree of whole-brain synchronization, namely connectivity, of the BLA is reduced by Tbr1 haploinsufficiency.[ 43 ] Importantly, theta-burst stimulation at the BLA was found to enhance whole-brain synchronization of Tbr1 +/− brains to a level comparable to that of WT mice and improve nose-to-nose interactions (i.e., sociality) of Tbr1 +/− mice.[ 43 ] In the current study, we found that Tbr1 haploinsufficiency results in a stronger correlation among sociality-linked BLA neurons in response to social stimulation, especially at the beginning of the behavioral test. Thus, Tbr1 haploinsufficiency also induces BLA neuron hyperactivation, resulting in stronger correlations among BLA neurons upon social stimulation, which may be relevant to the alteration of synaptic proteomes caused by Tbr1 haploinsufficiency. Although the concentrations of individual supplements in our cocktails are low, mixing them elicited a beneficial effect. Our LC-MS-MS and bioinformatic analyses demonstrate that a combination of individual supplements can influence synaptic and metabolic proteomes, shifting mutant neurons toward a status comparable to WT neurons. The in vivo calcium imaging analyses also reveal that cocktail supplementation corrects the abnormal hyperactivity and synchronization of BLA neurons in Tbr1 +/− mice in response to social stimulation, indicating that the supplement cocktail has reset the connectivity of BLA neurons, thereby promoting appropriate responses to social stimulation. It would be intriguing to investigate in the future if whole-brain connectivity can also be corrected by dietary supplementation. Consistent with a previous study[ 45 ], we found that very few neurons were repetitively responsive to the first and second social stimulations. Given that no negatively correlated neuron was present in RSI-1, Tbr1 haploinsufficiency alters the cell type responding to social stimulation. This change in cell type likely contributes to the altered neural connectivity and synchronization we observed in Tbr1 +/− mouse brains. However, it remains elusive how Tbr1 haploinsufficiency changes the responsiveness of different cell types in BLA. Our observation that the supplement cocktail reduced the number of positively correlated neurons but increased the negatively correlated neurons in Tbr1 +/− mice is also interesting. Accordingly, the absolute number of responsive neurons in the BLA may not be the most critical factor in controlling social behaviors. Instead, appropriate connectivity in the BLA is likely more important. Although the three ASD-linked genes Tbr1 , Nf1 , and Cttnbp2 exert distinct molecular roles, they all influence neuronal development and synaptic functions.[ 38 , 51 – 53 ] The supplements we provisioned, i.e., zinc, BCAA, and serine, all regulate synapse formation and signaling, albeit via distinct mechanisms ( Fig. 1A ). The results of our current study support that a combination of these nutrients can indeed improve synaptic function, providing broader therapeutic effects for various ASD-linked conditions relative to single-nutrient treatments. In addition to its broader effects, our 1/4 cocktail exhibits another advantage over the application of individual nutrients in that it endows beneficial effects despite reduced doses. Lower amounts of supplements may prevent potential nutrient imbalances arising from long-term treatment. Notably, our previous studies have shown that consecutive treatments were required to maintain the beneficial effects of nutrient supplementation.[ 13 , 14 ] Constant zinc and amino acid supplementation is likely essential to improve the abnormal brain function of autism mouse models. Given that long-term supplementation is required, lower doses of individual supplements that minimize the side effects of high-dose nutrients is certainly recommended. Indeed, we have shown here that long-term 1/4 cocktail supplementation for two months improved the social behaviors of our Tbr1 +/− mice, but did not elicit obvious side effects in terms of mouse body weight or behavior. Thus, nutrient cocktails that contain reduced doses of zinc, BCAA, and serine are potentially safer treatment options for long-term applications against various ASD conditions involving impaired synaptic formation and/or signaling. Conclusion Through a combination of proteomic analysis, in vivo calcium imaging, and behavioral assays, we have demonstrated that supplementation with cocktails containing low doses of multiple nutrients can restore protein expression profiles and neural connectivity in the brains of multiple ASD mouse models, thereby improving their social behaviors. These findings have revealed a promising new avenue for dietary therapy in the treatment of ASD. Methods Animals and ethics statement The Tbr1 +/− , Nf1 +/− and Cttnbp2 M120I mutant mice had been generated and/or characterized previously.[ 14 , 18 , 26 , 39 , 54 , 55 ] Male mice were used based on previous studies.[ 14 , 18 , 26 , 39 , 54 , 55 ] All mouse lines were maintained by backcrossing to C57BL/6JNarl purchased from the National Laboratory Animal Center, Taiwan. Mice were group housed (<5 mice per cage) in the specific pathogen free animal facility of the Institute of Molecular Biology, Academia Sinica, under controlled temperature (20–23 °C) and humidity (48–55%) with free access to water and food (LabDiet #5K54 https://www.labdiet.com/getmedia/2c493c25-079b-4b38-b2b7-6e64f1313811/5K54.pdf?ext=.pdf ). One week before behavioral tests, mice were moved from the breeding room to the experimental area. Mice were further housed individually one week before conducting social behavior assays. A 12 h light / 12 h dark cycle [light (intensity 240 lx): 8 a.m. to 8 p.m.] was set in the experimental area. Temperature and humidity in the test room were also controlled. All experiments were performed during the daytime, i.e., from 10 a.m. to 5 p.m. All animal experiments were performed with the approval of the Academia Sinica Institutional Animal Care and Utilization Committee (Protocol No. 18-10-1234 and 23-03-1990) and in strict accordance with its guidelines and those of the Council of Agriculture Guidebook for the Care and Use of Laboratory Animals. Cocktail supplementation Dietary supplementation in drinking water was conducted as described previously[ 14 , 26 ] with some modifications. It was initiated one week before social tests or from weaning. Mice were regularly fed on Labdiet 5K54 containing Ile 0.74%, Leu 1.49%, Val 0.87%, Ser 0.83 %, Zinc 81 ppm, and others ( https://www.labdiet.com/getmedia/2c493c25-079b-4b38-b2b7-6e64f1313811/5K54.pdf?ext=.pdf ). The average chow intake and water drinking amount are ∼3 g and 4.8 ml per mouse per day, respectively. With supplementation of 1/2 cocktail (containing Ile 0.25%, Leu 0.45%, Val 0.25%, 1% serine and 20 ppm zinc), the total intakes of these five nutrients were similar to the dietary chow containing Ile 1.1%, Leu 2.21%, Val 1.23%, Ser 2.43 % and Zinc 113 ppm. With 1/4 cocktail (containing Ile 0.1125%, Leu 0.225%, Val 0.1125%, 1% serine and 20 ppm zinc) in drinking water, the total intakes of these five nutrients were similar to the dietary chow containing Ile 0.92%, Leu 1.85%, Val 1.05%, Ser 2.43 % and Zinc 113 ppm. Combined with 1/8 cocktail (containing Ile 0.056%, Leu 0.1125%, Val 0.056%, 0.5% serine and 20 ppm zinc), the total intakes of these five nutrients were similar to the dietary chow containing Ile 0.83%, Leu 1.67%, Val 0.96%, Ser 1.63 % and Zinc 113 ppm. Fresh cocktail was replenished every other day throughout the assay period. Proteomic analysis LC-MS-MS Whole brains of mice treated with cocktail for one week were homogenized using a tissue Dounce homogenizer with a loose pestle in 1 mL sucrose buffer [50 mM Tris-Cl pH 7.4, 320 mM sucrose, 2 mM DTT, 2 mg/ml leupeptin, 2 mg/ml pepstatin-A, 2 mg/ml aproteinin, 2 mM PMSF, 2 mg/ml MG132]. The protein concentrations of total homogenate were determined by Bradford assay (Bio-Rad Protein Assay Dye Reagent Concentrate, Cat #5000006). Five mg of protein was loaded for 4% SDS-PAGE. After the dye front had completely entered the gel (about 10 min), the gel was fixed with 50% methanol and 10% acetic acid for 10 min and stained for a further 3 min with 0.1% Brilliant Blue R (B7920, Sigma-Aldrich) in 50% methanol and 10 % acetic acid. The gel was then destained by destaining buffer [10% methanol, 7 % acetic acid] until the bands were clearly visible. Gel bands were excised and cut into small pieces for trypsin digestion. The digestion products were subjected to LC-MS-MS using a Thermo Orbitrap Fusion Lumos mass spectrometer (Thermo-Fisher Scientific, Bremen, Germany). Proteomic data were searched against the Swiss-Prot Mus musculus database (17,049 entries total) using the Mascot search engine (v.2.6.2; Matrix Science, Boston, MA, USA) through Proteome Discoverer (v 2.2.0.388; Thermo-Fisher Scientific, Waltham, MA, USA) and peak-not-found groups were removed. PyWGCNA WGCNA is an unsupervised algorithm for finding modules of highly correlated genes/proteins[ 56 ]. The adjacency matrix was measured based on co-expression pattern similarity between the nodes (i.e., genes/proteins). After processing by sample clustering and choosing the soft-thresholding power, modules were identified as clustered interconnected nodes (genes/proteins) using hierarchical clustering. The module-trait heatmap was then identified to represent correlations of the module eigengenes with differential traits. High absolute correlation values indicated that the eigengenes have a higher probability of being affected by a trait. Gene ontology (GO) enrichment using genes identified from individual modules was further analyzed to determine the biological process pathways related to these modules. Principle Component Analysis (PCA) and GO analysis using STRING STRING analysis ( https://string-db.org/ ) was employed to identify functional protein networks. Lines between nodes indicate the interactions based on experimental or STRING database evidence. PCA was conducted using the jupyter notebook editor with Python3.8. The results of LC-MS-MS were loaded using the pandas module. The principle components were analyzed using the sklearn PCA module and the plot was generated using the seaborn module. Behavior analyses and cocktail supplementation The mouse behavioral tests including an open-field test, elevated plus maze, reciprocal social interaction, three-chamber test, and cued fear conditioning were conducted as described previously.[ 14 , 17 , 57 , 58 ] Open-field test The experiment was performed based on a previous study.[ 57 ] In brief, a mouse was placed into an open box (40 x 40 x 30 cm) and allowed to freely explore the box for 10 min. The area of the central region was equal to the total area of the four corners, and the regions were marked on the bottom of the box. The total moving distance and the time spent in the four corners and the central area were quantified using the Smart Video Tracking System (Panlab, Barcelona, Spain). Total travel distance indicated horizontal locomotor activity. The time spent in the corners indicated anxiety. Elevated plus maze As described previously,[ 57 ] the maze consisted of two open arms (30 × 5 cm) and two closed arms (30 × 5 cm) enclosed by a 14-cm-high wall, which was used to analyze the anxiety of mice. Mice were placed individually into the central area facing one of the open arms and allowed to freely explore the maze for 10 min. Their movements were recorded by video-recording from above and analyzed using the Smart Video Tracking System (Panlab, Barcelona, Spain). The percentage of time spent in the open arms, the closed arms, and the central square was measured to evaluate the degree of anxiety of the test mice. Reciprocal social interaction test This experiment was performed as described previously.[ 39 ] An unfamiliar “stranger” wild-type male mouse that was 1-2 weeks younger than the test mouse was put into the home cage of the isolated test mouse. The unfamiliar mice had their backs shaved to distinguish them from the test mice. With the lid of the cage open, the social interaction of the test mouse with the unfamiliar mouse was recorded for 5 min using a digital camera. The time that the test mouse spent interacting with the unfamiliar mouse was then measured. Longer interaction times indicated better social behaviors. Three-chamber test This assay was conducted as described previously.[ 39 ] The entire test comprised three 10-min sessions with 5-min intervals between sessions. The entire three sessions were video-recorded from above. During the interval, test mice were placed back in their home cages. The first session was habituation when a test mouse was placed into the middle chamber to freely explore all three empty chambers. In the second session for testing sociability, stranger mouse 1 (S1) was placed in a wire cage on the opposite side of the test mouse’s preferred chamber. An object (O) of similar size to the mouse was put into a wire cage on the other side. In the last session for evaluating novelty preference, stranger mouse 2 (S2) was placed in a wire cage at the opposite end of the three-chamber apparatus to S1 and the test mouse was placed into the middle chamber again to freely interact with S1 and S2. The time spent interacting or sniffing each wire cage of the left and right chambers was measured using the Smart VideoTracking System (Panlab) without knowing the genotype of the mice. The values of S1/(S1+O) and S2/(S2+S1) were determined as preference indices of sociability and social novelty preference, respectively. Cued fear conditioning Fear conditioning was performed as described previously using the FreezeScan 2.0 system (CleverSys).[ 39 ] The entire task was carried out over four days. The test mouse was subjected to habitation in recording cage A for 10 min on the first two days. On the third day, the test mouse was placed in recording cage B for 4 min, before receiving a 20-sec auditory cue with an electric shock (0.6 mA for 2 sec) for the last 2 sec. This cue was provided three times with a 1-min interval between each cue. On the final day, the test mouse was placed back in recording cage A for 4 min and then the freezing response was measured for a total of 20 auditory stimulations (each of 20 sec) with 5-sec intervals. The percentage of freezing responses to the first four stimulations was averaged to represent the degree of memory. Freezing responses were videotaped and measured using the FreezeScan 2.0 system (CleverSys). In vivo calcium imaging of the BLA In vivo calcium imaging and analyses using multiple approaches were conducted as described previously.[ 45 – 48 , 59 ] Detailed information about reagents, adeno-associated virus (AAV), endominiscopy, behavioral tests for in vivo calcium imaging, and all calcium imaging analyses are also summarized below. Reagents and AAV plasmid The reagents and plasmid used were as follows: 2,2,2-Tribromoethanol (Sigma-Aldrich, #T48402); Zoletil ® 50 (Virbac, 5 mL/vial); Xylazine hydrochloride (Sigma-Aldrich, #X1251); Sevatrim (Swiss Pharmaceutical Co. LTD., 5 mL/vial); Carprofen (Zoetis, 20 mL); Super-Bond C&B kit (Sun Medical Co. Ltd., Moriyama, Shiga, Japan); pGP-AAV-syn-jGCaMP7c variant 1513-WPRE (the plasmid was a gift from Douglas Kim and the GENIE Project, Addgene plasmid #105321; http://n2t.net/addgene:105321 ; RRID:Addgene_105321).[ 60 ] Viral vector injection and GRIN lens implantation Three-month-old mice were anesthetized by intraperitoneal administration of 5 mL/kg of an anesthetic mixture (Zoletil, 4 mg/mL; Xylazine, 2 mg/mL). To record BLA neuronal activity, mice were injected with 0.3 μl of AAV8-Syn-jGCaMP7c variant 1513-WPRE (1.77 x 10 13 vg/mL) into the right BLA (AP:1.33, ML: 3.25, DV: 4.95) at 30 nl/min using the Hamilton syringe system. Two weeks later, a second surgical procedure was performed to implant the gradient index (GRIN) lens. The tissue along the path above the injection site was gently removed using a 21G sterile needle. The 0.5-mm-diameter GRIN lens (efocus Imaging Cannula Model L, Doric Lenses Inc., Québec, Canada) was implanted in a position above the jGCaMP7c injection site (AP:1.33, ML: 3.25, DV: 4.9) to observe neuronal activity. The GRIN lens was then fixed using Super-Bond (Sun Medical Co. Ltd.). Antibiotics (Sevatrim, 15 TMP/kg) and an analgesic drug (Carprofen, 5 mg/kg) were injected intravenously into mice for the following 7 days. The mice underwent four weeks of recovery following surgery before undergoing behavioral testing and recording. Behavioral tests for in vivo calcium imaging Open field test (OF) – Mice hosting a GRIN lens and miniscope (eSFMB_L_458, Doric Lenses Inc., Québec, Canada) were individually placed in a transparent plastic box (40 cm (w) x 40 cm (d) x 30 cm (h)) for free exploration for 10 min. The total area of the four corners was equal to that of the center. Mouse behaviors were recorded from above using a camera (BTC_USB3.0, Doric Lenses Inc., Québec, Canada). The behavior videos were analyzed suing the Smart Video Tracking System (Panlab, Barcelona, Spain). The total distance of movement and the ratio of time spent in the corners to that in the center were calculated to evaluate the locomotion and anxiety of mice. Object exploration (OE) – A toy (of similar size to a mouse) was put into the center of the home cage of an isolated tested mouse. A mouse hosting a GRIN lens and miniscope was free to explore the toy for 10 min. Object exploration (OE) includes approaching, sniffing and touching. The total interaction time and the time points of starting and ending object exploration were recorded for further analysis with in vivo calcium imaging results. Reciprocal social interaction (RSI) – A younger unfamiliar mouse (two-month-old) was placed into the home cage of a test mouse for 10 min. The interaction between the unfamiliar mouse and the test mouse hosting a GRIN lens and miniscope was recorded from above. Approaching, sniffing, social grooming, mounting and chasing initiated by the test mouse were all coded as social interactions. The total interaction time and the time points of starting and ending the social interactions were recorded for further analysis with in vivo calcium imaging results. Only behaviors initiated by the test mouse were counted. Aggressive behaviors (attack) and passive social interactions (unfamiliar mouse actively touching the experimental mouse) were not included in the analysis. Recording of neuronal activity and signal extraction Calcium imaging (i.e., neuronal activity) and mouse behaviors were synchronously recorded at a frame rate of 10 Hz using the efocus Fluorescence Microscope System (Doric Lenses Inc., Québec, Canada). Calcium transients were acquired in a field of view of 630 x 630 pixels (320 x 320 μm) with current 30-100 mA (76-200 μW at the objective, 465 nm) and analog gain of 1. The calcium image was then spatially downsampled by a factor of nine and cropped into 180 x 180 pixels. CaImAn (1.8.5, https://github.com/flatironinstitute/CaImAn ),[ 59 ] an open-software package, was used for motion correction and signal extraction. The non-corrected regions of interest (ROIs) were removed manually. The activity of each neuron was outputted and then normalized via z-score transformation. Confirmation of injection site and GRIN lens position After completing the entire recording, test mice were deeply anesthetized via intraperitoneal injection of 0.7-0.8 mL 2,2,2-Tribromoethanol per mouse, then transcardially perfused with phosphate buffered saline (PBS), followed by 4% paraformaldehyde in PBS. The brains were collected and post-fixed overnight at 4 ℃. After two days of dehydration in 30% sucrose in PBS, the brains were cut into slices of 60 µm thickness by cryosectioning and stored in PBS. Slices were washed in TBS (25 mM Tris-Cl pH 7.5, 0.85% NaCl) three times (10 min each) and stained with DAPI (1 μg/ml). After mounting, slices were imaged using a microscope (AxioImager-Z1; Carl Zeiss). Correlation analysis between behaviors and neuronal ensembles The relevance of behaviors to neuronal ensembles was analyzed as described previously.[ 45 ] In brief, the within-cluster sum of squares (WCSS) was used to evaluate the potential number of neuronal clusters. Neurons were then separated into different clusters via k-means clustering. Pearson correlation was used to evaluate two types of correlations. The first was the correlation between the behavior vector (binary vector; social vs non-social period or object-approaching vs non-object-approaching period) and mean neuronal ensemble activity. The second was the correlation of the activities between neurons in the same ensemble. To determine if the neurons retained ensemble membership across different sessions, the correlation between the activity of an individual neuron and mean activity of the ensemble to which it belonged was calculated.[ 45 ] The multi-session registration function in CaImAn was used to identify the same neurons across sessions.[ 59 ] Correlation analysis between behaviors and individual neurons To define behavior-relevant cells at the single-cell level, the cosine similarity between the behavior vector (binary vector; social vs non-social period or object-approaching vs non-object-approaching period) and neuronal activity greater than the 95 th percentile or lower than the 5 th percentile of randomly shuffled data (1000 permutations) was recognized as neurons positively or negatively related to specific behavior, respectively.[ 46 ] The cosine similarity of neurons lying between the 95 th and 5 th percentiles of shuffled data defined neurons irrelevant to social behavior.[ 46 ] The cosine similarity ranges from 0 to 1. The ratio of social behavior-relevant cells in WT and Tbr1 +/- mice across sessions was calculated to examine changes in population. The number was normalized against total cell number (after multi-session registration). To investigate the response of social behavior-relevant neurons during interactions, the mean activity of object exploration-related positively-correlated neurons when approaching the object and sociality-related positively-correlated cells during social interactions was calculated. To track cell identity across sessions, the same neuron was identified via multi-session registration using CaImAn[ 59 ] and connectograms (Circos) were used to represent changes in identity. Functional network analysis To evaluate neuronal activation patterns among different neurons, cosine similarity was used to calculate the correlation of neuronal activities between neurons. Phase randomization was used to randomize (10000 times) the original neuronal activity of each pair.[ 48 ] The cosine similarity between two neurons greater than the 99.17 th percentile of randomly shuffled data was recognized as highly correlated cells (significant similarity).[ 47 ] To quantify the network structures, the degree centrality of a node (neuron) was used to calculate the total number of links with other nodes using the NetworkX Python package.[ 47 ] Links represent significant similarity between two neurons. Statistical analysis All quantitative data in this report are presented as means ± SEM. The individual data points are also shown. Graphs were plotted using GraphPad Prism 7.0 or 10.0 (GraphPad software). Although no randomization was performed to allocate subjects in the study, mice were arbitrarily assigned to different treatments. No statistical method was applied to evaluate the sample size, but our sample sizes are similar to previous publications.[ 14 , 42 ] To avoid potential personal bias in behavioral analyses, the data were collected and analyzed blindly without knowing the genotype or treatment of the mice. For behavior assays, statistical analysis was performed using a two-tailed unpaired Student’s t test for two-group comparisons, and two-way ANOVA and Bonferroni’s correction was performed for two-factor four-group comparisons. A Kolmogorov–Smirnov test in the Scipy Python package was used to determine cumulative probabilities. P values of less than 0.05 were considered significant. *, P < 0.05; **, P < 0.01; ***, P <0.001. All statistical methods and results are summarized in Supplementary Table 2 . Availability of data and materials The datasets and custom codes supporting the conclusions of this article are included within the article, its supplementary files and GitHub ( https://github.com/HsuehYiPing/Tbr1Cocktail ). Author contribution Conceptualization: Tzyy-Nan Huang, Ming-Hui Lin, Yi-Ping Hsueh. Funding acquisition: Yi-Ping Hsueh. Investigation: Tzyy-Nan Huang, Ming-Hui Lin, Tsan-Ting Hsu. Methodology: Tzyy-Nan Huang, Ming-Hui Lin, Tsan-Ting Hsu, Chen-Hsin Yu. Project administration: Yi-Ping Hsueh. Supervision: Yi-Ping Hsueh. Visualization: Tzyy-Nan Huang, Ming-Hui Lin, Chen-Hsin Yu Writing – original draft: Tzyy-Nan Huang, Ming-Hui Lin, Yi-Ping Hsueh. Writing – review & editing: Tzyy-Nan Huang, Ming-Hui Lin, Tsan-Ting Hsu, Chen-Hsin Yu, and Yi-Ping Hsueh. Funding This work was supported by grants from Academia Sinica (AS-IA-111-L01 and AS-TP-114-M01) and the National Science and Technology Council (NSTC 112-2326-B-001-008 to Y.- P.H.). Competing interests The authors report no competing interests. Supporting information Supplementary Table 1. The results of the proteomic analysis. Supplementary Table 2. The statistical results Download figure Open in new tab Supplementary Fig. 1. Pre-processing workflow of the Python package for weighted correlation network analysis (PyWGCNA). ( A ) Sample clustering. The three samples of the Tbr1_Water group were closer to each other and distinct from the other samples. ( B )-( C ) Checks of the soft-thresholding power for network topology analysis. ( D ) Clustering of module eigengenes. The cutoff value of distance was set at 0.2. Thus, modules with a distance <0.2 were merged into one. ( E ) Heatmap of module-trait relationships identified by PyWGCNA. Seven modules and respective numbers of proteins (in brackets) are labeled below the heatmap. In addition to the four groups of samples, the same analyses were performed according to genotype and treatment. In each well, the upper numbers indicate the correlation and the lower numbers in brackets indicate the P value of each analysis. The analysis revealed the highest level of correlation between the “Black” module and the treatment. Download figure Open in new tab Supplementary Fig. 2. Gene ontology of the PyWGCNA results. ( A ) Dark grey, ( B ) Indian red, and ( C ) Light grey eigengenes. Download figure Open in new tab Supplementary Fig. 3. Gene ontology of the PyWGCNA results (continued). ( A ) Brown, ( B ) Gainsboro, and ( C ) Whitesmoke eigengenes. Download figure Open in new tab Supplementary Fig. 4. Confirmation of GCaMP7c expression and GRIN lens position, as well as registration of the same neurons across sessions. ( A ) Schematic of virus injection and GRIN lens implantation. ( B ) An example of a mouse brain infected with AAV and implanted with a GRIN lens. ( C ) Positioning of the GRIN lens in WT and Tbr1 +/- mice (WT: n = 4; Tbr1 +/- : n = 4). D, dorsal; V, ventral; M, medial; L, lateral. ( D ) Number of firing neurons in WT and Tbr1 +/- mice across sessions. Data is represented as mean ± SEM. Each dot represents an individual mouse. ( E - G ) Processing of calcium images using CaImAn. ( E ) Template for motion correction. ( F ) Accepted firing neurons are labeled by white circles. ( G ) The same accepted firing neurons after multi-session registration are labeled by red circles. Download figure Open in new tab Supplementary Fig. 5. Two neuronal ensembles of BLA firing neurons encode object exploration. ( A ) The firing neurons during object exploration (OE) in the WT_Water, Tbr1 +/- _Water, WT_Cocktail and Tbr1 +/- _Cocktail groups were separated into two neuronal ensembles via within cluster sum of squares (WCSS) analysis. Data is represented as mean ± SEM. ( B ) Clustermap was used to represent Pearson’s correlations among neuronal activity during object exploration (OE). Download figure Open in new tab Supplementary Fig. 6. Two neuronal ensembles of BLA firing neurons encode reciprocal social interaction. ( A ) The firing neurons during reciprocal social interaction (RSI) in the WT_Water, Tbr1 +/- _Water, WT_Cocktail and Tbr1 +/- _Cocktail groups were separated into two neuronal ensembles via within cluster sum of squares (WCSS) analysis. Data is represented as mean ± SEM. ( B ) Cluster map was used to represent Pearson’s correlations among neuronal activity during reciprocal social interaction (RSI). Download figure Open in new tab Supplementary Fig. 7. Network connectivity of BLA firing neurons during reciprocal social interaction. Functional networks of BLA firing neurons of individual mice (WT: n = 4; Tbr1 +/- : n = 4) in reciprocal social interaction. Connections (lines) between the nodes indicate a significant similarity in activation patterns relative to shuffled data (10000 permutations via phase randomization). Red, neuron positively correlated with sociality. Blue, neuron negatively correlated with sociality. Grey, neuron irrelevant to social behavior. WT mouse #3 and Tbr1 +/- mouse #4 are also shown in Figure 4B . Download figure Open in new tab Supplementary Fig. 8. Network connectivity of BLA firing neurons during objection exploration. Functional networks of BLA neurons identified during the optical exploration (OE) test. Connections (lines) between nodes indicate a significant similarity in activation patterns relative to shuffled data (10000 permutations via phase randomization). The red and blue nodes represent neurons positively or negatively associated with object exploration. The grey nodes represent neurons irrelevant to approaching behaviors. WT mouse #3 and Tbr1 +/- mouse #4 are also shown in Figure 4D . Acknowledgments We thank Academia Sinica Common Mass Spectrometry Facilities for Proteomics and Protein Modification Analysis located at the Institute of Biological Chemistry, Academia Sinica (supported by AS-CFII-108-107), the Mass Spectrometry Facility of the Genomics Core at the Institute of Molecular Biology, Dr. John O’Brien for English editing, and members of Y.-P.H.’s laboratory who relabeled samples for blind experiments. Footnotes Authors’ email addresses: Tzyy-Nan Huang: Eugene02{at}as.edu.tw , Ming-Hui Lin: aucjo{at}as.edu.tw , Tsan-Ting Hsu: tsanting{at}as.edu.tw , Chen-Hsin Yu: albertchyu{at}as.edu.tw References 1. ↵ Rosen NE , Lord C , Volkmar FR . The Diagnosis of Autism: From Kanner to DSM-III to DSM-5 and Beyond . Journal of Autism and Developmental Disorders . 2021 ; 51 ( 12 ): 4253 – 70 . doi: 10.1007/s10803-021-04904-1 . OpenUrl CrossRef PubMed 2. ↵ Lord C , Bishop SL . Recent advances in autism research as reflected in DSM-5 criteria for autism spectrum disorder . 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Share Abnormal synaptic proteomes, impaired neural ensembles, and defective behaviors in autism mouse models are ameliorated by dietary intervention with nutrient mixtures Tzyy-Nan Huang , Ming-Hui Lin , Tsan-Ting Hsu , Chen-Hsin Yu , Yi-Ping Hsueh bioRxiv 2025.05.29.656761; doi: https://doi.org/10.1101/2025.05.29.656761 Share This Article: Copy Citation Tools Abnormal synaptic proteomes, impaired neural ensembles, and defective behaviors in autism mouse models are ameliorated by dietary intervention with nutrient mixtures Tzyy-Nan Huang , Ming-Hui Lin , Tsan-Ting Hsu , Chen-Hsin Yu , Yi-Ping Hsueh bioRxiv 2025.05.29.656761; doi: https://doi.org/10.1101/2025.05.29.656761 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 (7629) Biochemistry (17660) Bioengineering (13881) Bioinformatics (41911) Biophysics (21436) Cancer Biology (18578) Cell Biology (25482) Clinical Trials (138) Developmental Biology (13371) Ecology (19887) Epidemiology (2067) Evolutionary Biology (24302) Genetics (15599) Genomics (22483) Immunology (17728) Microbiology (40364) Molecular Biology (17163) Neuroscience (88537) Paleontology (666) Pathology (2830) Pharmacology and Toxicology (4821) Physiology (7637) Plant Biology (15129) Scientific Communication and Education (2045) Synthetic Biology (4290) Systems Biology (9817) Zoology (2269)