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Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

Little is known about the impact of metabolic stimuli on brain tissue at a molecular level. The ketone body beta-hydroxybutyrate (BHB) can be a signaling molecule regulating gene transcription. Thus, we assessed lysine beta-hydroxybutyrylation (K-bhb) levels in proteins extracted from the cerebral cortex of mice undergoing a ketogenic metabolic challenge (48 h fasting). We found that fasting enhanced K-bhb in a variety of proteins including histone H3. ChIP-seq experiments showed that K9 beta-hydroxybutyrylation of H3 (H3K9-bhb) was significantly enriched by fasting on more than 8000 DNA loci. Transcriptomic analysis showed that H3K9-bhb on enhancers and promoters correlated with active gene expression. One of the most enriched functional annotations both at the epigenetic and transcriptional level was "circadian rhythms''. Indeed, we found that the diurnal oscillation of specific transcripts was modulated by fasting at distinct zeitgeber times both in the cortex and suprachiasmatic nucleus. Moreover, specific changes in locomotor activity daily features were observed during re-feeding after 48-h fasting. Thus, our results suggest that fasting remarkably impinges on the cerebral cortex transcriptional and epigenetic landscape, and BHB acts as a powerful epigenetic molecule in the brain through direct and specific histone marks remodeling in neural tissue cells.

Background & aimsLiver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples.MethodsWe collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools.ResultsUtilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes.ConclusionsOur machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases.Lay summaryDistinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases.

Naturally occurring and recombinant protein-based materials are frequently employed for the study of fundamental biological processes and are often leveraged for applications in areas as diverse as electronics, optics, bioengineering, medicine, and even fashion. Within this context, unique structural proteins known as reflectins have recently attracted substantial attention due to their key roles in the fascinating color-changing capabilities of cephalopods and their technological potential as biophotonic and bioelectronic materials. However, progress toward understanding reflectins has been hindered by their atypical aromatic and charged residue-enriched sequences, extreme sensitivities to subtle changes in environmental conditions, and well-known propensities for aggregation. Herein, we elucidate the structure of a reflectin variant at the molecular level, demonstrate a straightforward mechanical agitation-based methodology for controlling this variant's hierarchical assembly, and establish a direct correlation between the protein's structural characteristics and intrinsic optical properties. Altogether, our findings address multiple challenges associated with the development of reflectins as materials, furnish molecular-level insight into the mechanistic underpinnings of cephalopod skin cells' color-changing functionalities, and may inform new research directions across biochemistry, cellular biology, bioengineering, and optics.

The use of evolutionary profiles to predict protein secondary structure, as well as other protein structural features, has been standard practice since the 1990s. Using profiles in the input of such predictors, in place or in addition to the sequence itself, leads to significantly more accurate predictions. While profiles can enhance structural signals, their role remains somewhat surprising as proteins do not use profiles when folding in vivo. Furthermore, the same sequence-based redundancy reduction protocols initially derived to train and evaluate sequence-based predictors, have been applied to train and evaluate profile-based predictors. This can lead to unfair comparisons since profiles may facilitate the bleeding of information between training and test sets. Here we use the extensively studied problem of secondary structure prediction to better evaluate the role of profiles and show that: (1) high levels of profile similarity between training and test proteins are observed when using standard sequence-based redundancy protocols; (2) the gain in accuracy for profile-based predictors, over sequence-based predictors, strongly relies on these high levels of profile similarity between training and test proteins; and (3) the overall accuracy of a profile-based predictor on a given protein dataset provides a biased measure when trying to estimate the actual accuracy of the predictor, or when comparing it to other predictors. We show, however, that this bias can be mitigated by implementing a new protocol (EVALpro) which evaluates the accuracy of profile-based predictors as a function of the profile similarity between training and test proteins. Such a protocol not only allows for a fair comparison of the predictors on equally hard or easy examples, but also reduces the impact of choosing a given similarity cutoff when selecting test proteins. The EVALpro program is available in the SCRATCH suite ( www.scratch.proteomics.ics.uci.edu) and can be downloaded at: www.download.igb.uci.edu/#evalpro.

Retroelement integration into host genomes affects chromosome structure and function. A goal of a considerable number of investigations is to elucidate features influencing insertion site selection. The Saccharomyces cerevisiae Ty3 retrotransposon inserts proximal to the transcription start sites (TSS) of genes transcribed by RNA polymerase III (RNAP3). In this study, differential patterns of insertion were profiled genome-wide using a random barcode-tagged Ty3. Saturation transposition showed that tRNA genes (tDNAs) are targeted at widely different frequencies even within isoacceptor families. Ectopic expression of Ty3 integrase (IN) showed that it localized to targets independent of other Ty3 proteins and cDNA. IN, RNAP3, and transcription factor Brf1 were enriched at tDNA targets with high frequencies of transposition. To examine potential effects of cis-acting DNA features on transposition, targeting was tested on high-copy plasmids with restricted amounts of 5' flanking sequence plus tDNA. Relative activity of targets was reconstituted in these constructions. Weighting of genomic insertions according to frequency identified an A/T-rich sequence followed by C as the dominant site of strand transfer. This site lies immediately adjacent to the adenines previously implicated in the RNAP3 TSS motif (CAA). In silico DNA structural analysis upstream of this motif showed that targets with elevated DNA curvature coincide with reduced integration. We propose that integration mediated by the Ty3 intasome complex (IN and cDNA) is subject to inputs from a combination of host factor occupancy and insertion site architecture, and that this results in the wide range of Ty3 targeting frequencies.

Mammals rely on a network of circadian clocks to control daily systemic metabolism and physiology. The central pacemaker in the suprachiasmatic nucleus (SCN) is considered hierarchically dominant over peripheral clocks, whose degree of independence, or tissue-level autonomy, has never been ascertained in vivo. Using arrhythmic Bmal1-null mice, we generated animals with reconstituted circadian expression of BMAL1 exclusively in the liver (Liver-RE). High-throughput transcriptomics and metabolomics show that the liver has independent circadian functions specific for metabolic processes such as the NAD+ salvage pathway and glycogen turnover. However, although BMAL1 occupies chromatin at most genomic targets in Liver-RE mice, circadian expression is restricted to ∼10% of normally rhythmic transcripts. Finally, rhythmic clock gene expression is lost in Liver-RE mice under constant darkness. Hence, full circadian function in the liver depends on signals emanating from other clocks, and light contributes to tissue-autonomous clock function.

DNA modification is known to regulate experience-dependent gene expression. However, beyond cytosine methylation and its oxidated derivatives, very little is known about the functional importance of chemical modifications on other nucleobases in the brain. Here we report that in adult mice trained in fear extinction, the DNA modification N6-methyl-2'-deoxyadenosine (m6dA) accumulates along promoters and coding sequences in activated prefrontal cortical neurons. The deposition of m6dA is associated with increased genome-wide occupancy of the mammalian m6dA methyltransferase, N6amt1, and this correlates with extinction-induced gene expression. The accumulation of m6dA is associated with transcriptional activation at the brain-derived neurotrophic factor (Bdnf) P4 promoter, which is required for Bdnf exon IV messenger RNA expression and for the extinction of conditioned fear. These results expand the scope of DNA modifications in the adult brain and highlight changes in m6dA as an epigenetic mechanism associated with activity-induced gene expression and the formation of fear extinction memory.

The circadian clock operates as intrinsic time-keeping machinery to preserve homeostasis in response to the changing environment. While food is a known zeitgeber for clocks in peripheral tissues, it remains unclear how lack of food influences clock function. We demonstrate that the transcriptional response to fasting operates through molecular mechanisms that are distinct from time-restricted feeding regimens. First, fasting affects core clock genes and proteins, resulting in blunted rhythmicity of BMAL1 and REV-ERBα both in liver and skeletal muscle. Second, fasting induces a switch in temporal gene expression through dedicated fasting-sensitive transcription factors such as GR, CREB, FOXO, TFEB, and PPARs. Third, the rhythmic genomic response to fasting is sustainable by prolonged fasting and reversible by refeeding. Thus, fasting imposes specialized dynamics of transcriptional coordination between the clock and nutrient-sensitive pathways, thereby achieving a switch to fasting-specific temporal gene regulation.

Aging is accompanied by impairments in both circadian rhythmicity and long-term memory. Although it is clear that memory performance is affected by circadian cycling, it is unknown whether age-related disruption of the circadian clock causes impaired hippocampal memory. Here, we show that the repressive histone deacetylase HDAC3 restricts long-term memory, synaptic plasticity, and experience-induced expression of the circadian gene Per1 in the aging hippocampus without affecting rhythmic circadian activity patterns. We also demonstrate that hippocampal Per1 is critical for long-term memory formation. Together, our data challenge the traditional idea that alterations in the core circadian clock drive circadian-related changes in memory formation and instead argue for a more autonomous role for circadian clock gene function in hippocampal cells to gate the likelihood of long-term memory formation.

ClusterCAD is a web-based toolkit designed to leverage the collinear structure and deterministic logic of type I modular polyketide synthases (PKSs) for synthetic biology applications. The unique organization of these megasynthases, combined with the diversity of their catalytic domain building blocks, has fueled an interest in harnessing the biosynthetic potential of PKSs for the microbial production of both novel natural product analogs and industrially relevant small molecules. However, a limited theoretical understanding of the determinants of PKS fold and function poses a substantial barrier to the design of active variants, and identifying strategies to reliably construct functional PKS chimeras remains an active area of research. In this work, we formalize a paradigm for the design of PKS chimeras and introduce ClusterCAD as a computational platform to streamline and simplify the process of designing experiments to test strategies for engineering PKS variants. ClusterCAD provides chemical structures with stereochemistry for the intermediates generated by each PKS module, as well as sequence- and structure-based search tools that allow users to identify modules based either on amino acid sequence or on the chemical structure of the cognate polyketide intermediate. ClusterCAD can be accessed at https://clustercad.jbei.org and at http://clustercad.igb.uci.edu.

Recent human exome-sequencing studies have implicated polymorphic Brg1-associated factor (BAF) complexes (mammalian SWI/SNF chromatin remodeling complexes) in several intellectual disabilities and cognitive disorders, including autism. However, it remains unclear how mutations in BAF complexes result in impaired cognitive function. Post-mitotic neurons express a neuron-specific assembly, nBAF, characterized by the neuron-specific subunit BAF53b. Subdomain 2 of BAF53b is essential for the differentiation of neuronal precursor cells into neurons. We generated transgenic mice lacking subdomain 2 of Baf53b (BAF53bΔSB2). Long-term synaptic potentiation (LTP) and long-term memory, both of which are associated with phosphorylation of the actin severing protein cofilin, were assessed in these animals. A phosphorylation mimic of cofilin was stereotaxically delivered into the hippocampus of BAF53bΔSB2 mice in an effort to rescue LTP and memory. BAF53bΔSB2 mutant mice show impairments in phosphorylation of synaptic cofilin, LTP, and memory. Both the synaptic plasticity and memory deficits are rescued by overexpression of a phosphorylation mimetic of cofilin. Baseline physiology and behavior were not affected by the mutation or the experimental treatment. This study suggests a potential link between nBAF function, actin cytoskeletal remodeling at the dendritic spine, and memory formation. This work shows that a targeted manipulation of synaptic function can rescue adult plasticity and memory deficits caused by manipulations of nBAF, and thereby provides potential novel avenues for therapeutic development for multiple intellectual disability disorders.

MicroRNAs (miRNAs) are known to mediate post-transcriptional gene regulation, but their role in postnatal brain development is still poorly explored. We show that the expression of many miRNAs is dramatically regulated during functional maturation of the mouse visual cortex with miR-132/212 family being one of the top upregulated miRNAs. Age-downregulated transcripts are significantly enriched in miR-132/miR-212 putative targets and in genes upregulated in miR-132/212 null mice. At a functional level, miR-132/212 deletion affects development of receptive fields of cortical neurons determining a specific impairment of binocular matching of orientation preference, but leaving orientation and direction selectivity unaltered. This deficit is associated with reduced depth perception in the visual cliff test. Deletion of miR-132/212 from forebrain excitatory neurons replicates the binocular matching deficits. Thus, miR-132/212 family shapes the age-dependent transcriptome of the visual cortex during a specific developmental window resulting in maturation of binocular cortical cells and depth perception.

The reinforcing and motivational aspects of food are tied to the release of the dopamine in the mesolimbic system (ML). Free fatty acids from triglyceride (TG)-rich particles are released upon action of TG-lipases found at high levels in peripheral oxidative tissue (muscle, heart), but also in the ML. This suggests that local TG-hydrolysis in the ML might regulate food seeking and reward. Indeed, evidence now suggests that dietary TG directly target the ML to regulate amphetamine-induced locomotion and reward seeking behavior. Though the cellular mechanisms of TG action are unresolved, TG act in part through ML lipoprotein lipase, upstream of dopamine 2 receptor (D2R), and show desensitization in conditions of chronically elevated plasma TG as occur in obesity. TG sensing in the ML therefore represents a new mechanism by which chronic consumption of dietary fat might lead to adaptations in the ML and dysregulated feeding behaviors.

MotivationNot only sequence data continue to outpace annotation information, but also the problem is further exacerbated when organisms are underrepresented in the annotation databases. This is the case with non-human-pathogenic viruses which occur frequently in metagenomic projects. Thus, there is a need for tools capable of detecting and classifying viral sequences.ResultsWe describe VIRALpro a new effective tool for identifying capsid and tail protein sequences, which are the cornerstones toward viral sequence annotation and viral genome classification.Availability and implementationThe data, software and corresponding web server are available from http://scratch.proteomics.ics.uci.edu as part of the SCRATCH suite.Contactclovis.galiez@inria.fr or pfbaldi@uci.eduSupplementary informationSupplementary data are available at Bioinformatics online.

Yarrowia lipolytica, an oleaginous yeast, is capable of accumulating significant cellular mass in lipid making it an important source of biosustainable hydrocarbon-based chemicals. In spite of a similar number of protein-coding genes to that in other Hemiascomycetes, the Y. lipolytica genome is almost double that of model yeasts. Despite its economic importance and several distinct strains in common use, an independent genome assembly exists for only one strain. We report here a de novo annotated assembly of the chromosomal genome of an industrially-relevant strain, W29/CLIB89, determined by hybrid next-generation sequencing. For the first time, each Y. lipolytica chromosome is represented by a single contig. The telomeric rDNA repeats were localized by Irys long-range genome mapping and one complete copy of the rDNA sequence is reported. Two large structural variants and retroelement differences with reference strain CLIB122 including a full-length, novel Ty3/Gypsy long terminal repeat (LTR) retrotransposon and multiple LTR-like sequences are described. Strikingly, several of these are adjacent to RNA polymerase III-transcribed genes, which are almost double in number in Y. lipolytica compared to other Hemiascomycetes. In addition to previously-reported dimeric RNA polymerase III-transcribed genes, tRNA pseudogenes were identified. Multiple full-length and truncated LINE elements are also present. Therefore, although identified transposons do not constitute a significant fraction of the Y. lipolytica genome, they could have played an active role in its evolution. Differences between the sequence of this strain and of the existing reference strain underscore the utility of an additional independent genome assembly for this economically important organism.

Feeding behavior is exquisitely regulated by homeostatic and hedonic neural substrates that integrate energy demand as well as the reinforcing and rewarding aspects of food. Understanding the net contribution of homeostatic and reward-driven feeding has become critical because of the ubiquitous source of energy-dense foods and the consequent obesity epidemic. Hypothalamic agouti-related peptide-secreting neurons (AgRP neurons) provide the primary orexigenic drive of homeostatic feeding. Using models of neuronal inhibition or ablation, we demonstrate that the feeding response to a fast ghrelin or serotonin receptor agonist relies on AgRP neurons. However, when palatable food is provided, AgRP neurons are dispensable for an appropriate feeding response. In addition, AgRP-ablated mice present exacerbated stress-induced anorexia and palatable food intake--a hallmark of comfort feeding. These results suggest that, when AgRP neuron activity is impaired, neural circuits sensitive to emotion and stress are engaged and modulated by food palatability and dopamine signaling.

A considerable body of evidence supports the role of mitochondrial dysfunction in psychiatric disorders and mitochondrial DNA (mtDNA) mutations are known to alter brain energy metabolism, neurotransmission, and cause neurodegenerative disorders. Genetic studies focusing on common nuclear genome variants associated with these disorders have produced genome wide significant results but those studies have not directly studied mtDNA variants. The purpose of this study is to investigate, using next generation sequencing, the involvement of mtDNA variation in bipolar disorder, schizophrenia, major depressive disorder, and methamphetamine use. MtDNA extracted from multiple brain regions and blood were sequenced (121 mtDNA samples with an average of 8,800x coverage) and compared to an electronic database containing 26,850 mtDNA genomes. We confirmed novel and rare variants, and confirmed next generation sequencing error hotspots by traditional sequencing and genotyping methods. We observed a significant increase of non-synonymous mutations found in individuals with schizophrenia. Novel and rare non-synonymous mutations were found in psychiatric cases in mtDNA genes: ND6, ATP6, CYTB, and ND2. We also observed mtDNA heteroplasmy in brain at a locus previously associated with schizophrenia (T16519C). Large differences in heteroplasmy levels across brain regions within subjects suggest that somatic mutations accumulate differentially in brain regions. Finally, multiplasmy, a heteroplasmic measure of repeat length, was observed in brain from selective cases at a higher frequency than controls. These results offer support for increased rates of mtDNA substitutions in schizophrenia shown in our prior results. The variable levels of heteroplasmic/multiplasmic somatic mutations that occur in brain may be indicators of genetic instability in mtDNA.

MotivationAccurately predicting protein secondary structure and relative solvent accessibility is important for the study of protein evolution, structure and function and as a component of protein 3D structure prediction pipelines. Most predictors use a combination of machine learning and profiles, and thus must be retrained and assessed periodically as the number of available protein sequences and structures continues to grow.ResultsWe present newly trained modular versions of the SSpro and ACCpro predictors of secondary structure and relative solvent accessibility together with their multi-class variants SSpro8 and ACCpro20. We introduce a sharp distinction between the use of sequence similarity alone, typically in the form of sequence profiles at the input level, and the additional use of sequence-based structural similarity, which uses similarity to sequences in the Protein Data Bank to infer annotations at the output level, and study their relative contributions to modern predictors. Using sequence similarity alone, SSpro's accuracy is between 79 and 80% (79% for ACCpro) and no other predictor seems to exceed 82%. However, when sequence-based structural similarity is added, the accuracy of SSpro rises to 92.9% (90% for ACCpro). Thus, by combining both approaches, these problems appear now to be essentially solved, as an accuracy of 100% cannot be expected for several well-known reasons. These results point also to several open technical challenges, including (i) achieving on the order of ≥ 80% accuracy, without using any similarity with known proteins and (ii) achieving on the order of ≥ 85% accuracy, using sequence similarity alone.Availability and implementationSSpro, SSpro8, ACCpro and ACCpro20 programs, data and web servers are available through the SCRATCH suite of protein structure predictors at http://scratch.proteomics.ics.uci.edu.

Long-chain n -3 PUFA (LC n -3 PUFA) prevent, in rodents, insulin resistance (IR) induced by a high-fat and/or fructose diet but not IR induced by glucocorticoids. In humans, contrasting effects have also been reported. We investigated their effects on insulin sensitivity, feed intake (FI) and body weight gain in genetically insulin resistant male obese (fa/fa) Zucker (ZO) rats during the development of obesity. ZO rats were fed a diet supplemented with 7 % fish oil (FO) + 1 % corn oil (CO) (wt/wt) (ZOFO), while the control group was fed a diet containing 8 % fat from CO (wt/wt) (ZOCO). Male lean Zucker (ZL) rats fed either FO (ZLFO) or CO (ZLCO) diet were used as controls. FO was a marine-derived TAG oil containing EPA 90 mg/g + DHA 430 mg/g. During an oral glucose tolerance test, glucose tolerance remained unaltered by FO while insulin response was reduced in ZOFO only. Liver insulin sensitivity (euglycaemic–hyperinsulinaemic clamp + 2 deoxyglucose) was improved in ZOFO rats, linked to changes in phosphoenolpyruvate carboxykinase expression, activity and glucose-6-phosphatase activity. FI in response to intra-carotid insulin/glucose infusion was decreased similarly in ZOFO and ZOCO. Hypothalamic ceramides levels were lower in ZOFO than in ZOCO. Our study demonstrates that LC n -3 PUFA can minimise weight gain, possibly by alleviating hypothalamic lipotoxicity, and liver IR in genetically obese Zucker rats. [ABSTRACT FROM AUTHOR]

Recent human exome-sequencing studies have implicated polymorphic Brg1-associated factor (BAF) complexes (mammalian SWI/SNF chromatin remodeling complexes) in several intellectual disabilities and cognitive disorders, including autism. However, it remains unclear how mutations in BAF complexes result in impaired cognitive function. Post-mitotic neurons express a neuron-specific assembly, nBAF, characterized by the neuron-specific subunit BAF53b. Subdomain 2 of BAF53b is essential for the differentiation of neuronal precursor cells into neurons. We generated transgenic mice lacking subdomain 2 of Baf53b (BAF53b?SB2). Long-term synaptic potentiation (LTP) and long-term memory, both of which are associated with phosphorylation of the actin severing protein cofilin, were assessed in these animals. A phosphorylation mimic of cofilin was stereotaxically delivered into the hippocampus of BAF53b?SB2 mice in an effort to rescue LTP and memory. BAF53b?SB2 mutant mice show impairments in phosphorylation of synaptic cofilin, LTP, and memory. Both the synaptic plasticity and memory deficits are rescued by overexpression of a phosphorylation mimetic of cofilin. Baseline physiology and behavior were not affected by the mutation or the experimental treatment. This study suggests a potential link between nBAF function, actin cytoskeletal remodeling at the dendritic spine, and memory formation. This work shows that a targeted manipulation of synaptic function can rescue adult plasticity and memory deficits caused by manipulations of nBAF, and thereby provides potential novel avenues for therapeutic development for multiple intellectual disability disorders.

Recent exome sequencing studies have implicated polymorphic Brg1-associated factor (BAF) complexes (mammalian SWI/SNF chromatin remodeling complexes) in several human intellectual disabilities and cognitive disorders. However, it is currently unknown how mutations in BAF complexes result in impaired cognitive function. Postmitotic neurons express a neuron-specific assembly, nBAF, characterized by the neuron-specific subunit BAF53b. Mice harboring selective genetic manipulations of BAF53b have severe defects in long-term memory and long-lasting forms of hippocampal synaptic plasticity. We rescued memory impairments in BAF53b mutant mice by reintroducing BAF53b in the adult hippocampus, which suggests a role for BAF53b beyond neuronal development. The defects in BAF53b mutant mice appeared to derive from alterations in gene expression that produce abnormal postsynaptic components, such as spine structure and function, and ultimately lead to deficits in synaptic plasticity. Our results provide new insight into the role of dominant mutations in subunits of BAF complexes in human intellectual and cognitive disorders.