RUES2 hESCs exhibit MGE-biased neuronal differentiation and muHTT-dependent defective specification hinting at SP1.

RUES2 cell lines represent the first collection of isogenic human embryonic stem cells (hESCs) carrying different pathological CAG lengths in the HTT gene. However, their neuronal differentiation potential has yet to be thoroughly evaluated. Here, we report that RUES2 during ventral telencephalic differentiation is biased towards medial ganglionic eminence (MGE). We also show that HD-RUES2 cells exhibit an altered MGE transcriptional signature in addition to recapitulating known HD phenotypes, with reduced expression of the neurodevelopmental regulators NEUROD1 and BDNF and increased cleavage of synaptically enriched N-cadherin. Finally, we identified the transcription factor SP1 as a common potential detrimental co-partner of muHTT by de novo motif discovery analysis on the LGE, MGE, and cortical genes differentially expressed in HD human pluripotent stem cells in our and additional datasets. Taken together, these observations suggest a broad deleterious effect of muHTT in the early phases of neuronal development that may unfold through its altered interaction with SP1.

Experimental and Computational Analysis of Newly Identified Pathogenic Mutations in the Creatine Transporter SLC6A8.

Creatine is an essential metabolite for the storage and rapid supply of energy in muscle and nerve cells. In humans, impaired metabolism, transport, and distribution of creatine throughout tissues can cause varying forms of mental disability, also known as creatine deficiency syndrome (CDS). So far, 80 mutations in the creatine transporter (SLC6A8) have been associated to CDS. To better understand the effect of human genetic variants on the physiology of SLC6A8 and their possible impact on CDS, we studied 30 missense variants including 15 variants of unknown significance, two of which are reported here for the first time. We expressed these variants in HEK293 cells and explored their subcellular localization and transport activity. We also applied computational methods to predict variant effect and estimate site-specific changes in thermodynamic stability. To explore variants that might have a differential effect on the transporter's conformers along the transport cycle, we constructed homology models of the inward facing, and outward facing conformations. In addition, we used mass-spectrometry to study proteins that interact with wild type SLC6A8 and five selected variants in HEK293 cells. In silico models of the protein complexes revealed how two variants impact the interaction interface of SLC6A8 with other proteins and how pathogenic variants lead to an enrichment of ER protein partners. Overall, our integrated analysis disambiguates the pathogenicity of 15 variants of unknown significance revealing diverse mechanisms of pathogenicity, including two previously unreported variants obtained from patients suffering from the creatine deficiency syndrome.

ProteoMutaMetrics: machine learning approaches for solute carrier family 6 mutation pathogenicity prediction.

The solute carrier transporter family 6 (SLC6) is of key interest for their critical role in the transport of small amino acids or amino acid-like molecules. Their dysfunction is strongly associated with human diseases such as including schizophrenia, depression, and Parkinson's disease. Linking single point mutations to disease may support insights into the structure-function relationship of these transporters. This work aimed to develop a computational model for predicting the potential pathogenic effect of single point mutations in the SLC6 family. Missense mutation data was retrieved from UniProt, LitVar, and ClinVar, covering multiple protein-coding transcripts. As encoding approach, amino acid descriptors were used to calculate the average sequence properties for both original and mutated sequences. In addition to the full-sequence calculation, the sequences were cut into twelve domains. The domains are defined according to the transmembrane domains of the SLC6 transporters to analyse the regions' contributions to the pathogenicity prediction. Subsequently, several classification models, namely Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) with the hyperparameters optimized through grid search were built. For estimation of model performance, repeated stratified k-fold cross-validation was used. The accuracy values of the generated models are in the range of 0.72 to 0.80. Analysis of feature importance indicates that mutations in distinct regions of SLC6 transporters are associated with an increased risk for pathogenicity. When applying the model on an independent validation set, the performance in accuracy dropped to averagely 0.6 with high precision but low sensitivity scores.

Differentiation of hPSCs to Study PRC2 Role in Cell-Fate Specification and Neurodevelopment.

Several studies highlighted the importance of the polycomb repressive complex 2 (PRC2) already at the beginning of development. Although the crucial function of PRC2 in regulating lineage commitment and cell-fate specification has been well-established, the in vitro study of the exact mechanisms for which H3K27me3 is indispensable for proper differentiation is still challenging. In this chapter, we report a well-established and reproducible differentiation protocol to generate striatal medium spiny neurons as a tool to explore PRC2 role in brain development.

Superactive mutants of thromboxane prostanoid receptor: functional and computational analysis of an active form alternative to constitutively active mutants.

In class A GPCRs the E/DRY motif is critical for receptor activation and function. According to experimental and computational data, R3.50 forms a double salt bridge with the adjacent E/D3.49 and E/D6.30 in helix 6, constraining the receptor in an inactive state. The disruption of this network of interactions facilitates conformational transitions that generate a signal or constitutive activity. Here we demonstrate that non-conservative substitution of either E129((3.49)) or E240((6.30)) of thromboxane prostanoid receptor (TP) resulted in mutants characterized by agonist-induced more efficient signaling properties, regardless of the G protein coupling. Results of computational modeling suggested a more effective interaction between G(q) and the agonist-bound forms of the TP mutants, compared to the wild type. Yet, none of the mutants examined revealed any increase in basal activity, precluding their classification as constitutively active mutants. Here, we propose that these alternative active conformations might be identified as superactive mutants or SAM.