nArgBP2-SAPAP-SHANK, the core postsynaptic triad associated with psychiatric disorders

nArgBP2 together with GKAP and SHANK3 forms a dynamic layered structure

nArgBP2, a protein whose disruption is implicated in intellectual disability, concentrates in excitatory spine-synapses. By forming a triad with GKAP and SHANK, it regulates spine structural rearrangement. We here find that GKAP and SHANK3 concentrate close to the synaptic contact, whereas nArgBP2 concentrates more centrally in the spine. The three proteins collaboratively form biomolecular condensates in living fibroblasts, exhibiting distinctive layered localizations. nArgBP2 concentrates in the inner phase, SHANK3 in the outer phase, and GKAP partially in both. Upon co-expression of GKAP and nArgBP2, they evenly distribute within condensates, with a notable peripheral localization of SHANK3 persisting when co-expressed with either GKAP or nArgBP2. Co-expression of SHANK3 and GKAP with CaMKIIα results in phase-in-phase condensates, with CaMKIIα at the central locus and SHANK3 and GKAP exhibiting peripheral localization. Additional co-expression of nArgBP2 maintains the layered organizational structure within condensates. Subsequent CaMKIIα activation disperses a majority of the condensates, with an even distribution of all proteins within the extant deformed condensates. Our findings suggest that protein segregation via phase separation may contribute to establishing layered organization in dendritic spines.

Systematic detection of functional proteoform groups from bottom-up proteomic datasets

To a large extent functional diversity in cells is achieved by the expansion of molecular complexity beyond that of the coding genome. Various processes create multiple distinct but related proteins per coding gene - so-called proteoforms - that expand the functional capacity of a cell. Evaluating proteoforms from classical bottom-up proteomics datasets, where peptides instead of intact proteoforms are measured, has remained difficult. Here we present COPF, a tool for COrrelation-based functional ProteoForm assessment in bottom-up proteomics data. It leverages the concept of peptide correlation analysis to systematically assign peptides to co-varying proteoform groups. We show applications of COPF to protein complex co-fractionation data as well as to more typical protein abundance vs. sample data matrices, demonstrating the systematic detection of assembly- and tissue-specific proteoform groups, respectively, in either dataset. We envision that the presented approach lays the foundation for a systematic assessment of proteoforms and their functional implications directly from bottom-up proteomic datasets.

Molecular architecture of postsynaptic Interactomes

The postsynaptic density (PSD) plays an essential role in the organization of the synaptic signaling machinery. It contains a set of core scaffolding proteins that provide the backbone to PSD protein-protein interaction networks (PINs). These core scaffolding proteins can be seen as three principal layers classified by protein family, with DLG proteins being at the top, SHANKs along the bottom, and DLGAPs connecting the two layers. Early studies utilizing yeast two hybrid enabled the identification of direct protein-protein interactions (PPIs) within the multiple layers of scaffolding proteins. More recently, mass-spectrometry has allowed the characterization of whole interactomes within the PSD. This expansion of knowledge has further solidified the centrality of core scaffolding family members within synaptic PINs and provided context for their role in neuronal development and synaptic function. Here, we discuss the scaffolding machinery of the PSD, their essential functions in the organization of synaptic PINs, along with their relationship to neuronal processes found to be impaired in complex brain disorders.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

Genome-wide profiling of DNA methylome and transcriptome in peripheral blood monocytes for major depression: A Monozygotic Discordant Twin Study

DNA methylation plays an important role in major depressive disorder (MDD), but the specific genes and genomic regions associated with MDD remain largely unknown. Here we conducted genome-wide profiling of DNA methylation (Infinium MethylationEPIC BeadChip) and gene expression (RNA-seq) in peripheral blood monocytes from 79 monozygotic twin pairs (mean age 38.2 ± 15.6 years) discordant on lifetime history of MDD to identify differentially methylated regions (DMRs) and differentially expressed genes (DEGs) associated with MDD, followed by replication in brain tissue samples. Integrative DNA methylome and transcriptome analysis and network analysis was performed to identify potential functional epigenetic determinants for MDD. We identified 39 DMRs and 30 DEGs associated with lifetime history of MDD. Some genes were replicated in postmortem brain tissue. Integrative DNA methylome and transcriptome analysis revealed both negative and positive correlations between DNA methylation and gene expression, but the correlation pattern varies greatly by genomic locations. Network analysis revealed distinct gene modules enriched in signaling pathways related to stress responses, neuron apoptosis, insulin receptor signaling, mTOR signaling, and nerve growth factor receptor signaling, suggesting potential functional relevance to MDD. These results demonstrated that altered DNA methylation and gene expression in peripheral blood monocytes are associated with MDD. Our results highlight the utility of using peripheral blood epigenetic markers and demonstrate that a monozygotic discordant co-twin control design can aid in the discovery of novel genes associated with MDD. If validated, the newly identified genes may serve as novel biomarkers or druggable targets for MDD and related disorders.

Cannabis use is associated with potentially heritable widespread changes in autism candidate gene DLGAP2 DNA methylation in sperm

Parental cannabis use has been associated with adverse neurodevelopmental outcomes in offspring, but how such phenotypes are transmitted is largely unknown. Using reduced representation bisulphite sequencing (RRBS), we recently demonstrated that cannabis use is associated with widespread DNA methylation changes in human and rat sperm. Discs-Large Associated Protein 2 (DLGAP2), involved in synapse organization, neuronal signaling, and strongly implicated in autism, exhibited significant hypomethylation (p < 0.05) at 17 CpG sites in human sperm. We successfully validated the differential methylation present in DLGAP2 for nine CpG sites located in intron seven (p < 0.05) using quantitative bisulphite pyrosequencing. Intron 7 DNA methylation and DLGAP2 expression in human conceptal brain tissue were inversely correlated (p < 0.01). Adult male rats exposed to delta-9-tetrahydrocannabinol (THC) showed differential DNA methylation at Dlgap2 in sperm (p < 0.03), as did the nucleus accumbens of rats whose fathers were exposed to THC prior to conception (p < 0.05). Altogether, these results warrant further investigation into the effects of preconception cannabis use in males and the potential effects on subsequent generations.