Pharmacological modulation of developmental and synaptic phenotypes in human SHANK3 deficient stem cell-derived neuronal models.

Phelan-McDermid syndrome (PMDS) arises from mutations in the terminal region of chromosome 22q13, impacting the SHANK3 gene. The resulting deficiency of the postsynaptic density scaffolding protein SHANK3 is associated with autism spectrum disorder (ASD). We examined 12 different PMDS patient and CRISPR-engineered stem cell-derived neuronal models and controls and found that reduced expression of SHANK3 leads to neuronal hyperdifferentiation, increased synapse formation, and decreased neuronal activity. We performed automated imaging-based screening of 7,120 target-annotated small molecules and identified three compounds that rescued SHANK3-dependent neuronal hyperdifferentiation. One compound, Benproperine, rescued the decreased colocalization of Actin Related Protein 2/3 Complex Subunit 2 (ARPC2) with ß-actin and rescued increased synapse formation in SHANK3 deficient neurons when administered early during differentiation. Neuronal activity was only mildly affected, highlighting Benproperine's effects as a neurodevelopmental modulator. This study demonstrates that small molecular compounds that reverse developmental phenotypes can be identified in human neuronal PMDS models.

Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls.

Parkinson's disease (PD) is the second most common neurodegenerative disease and is characterized by the loss of midbrain dopaminergic neurons. Endocrine disrupting chemicals (EDCs) are active substances that interfere with hormonal signaling. Among EDCs, bisphenols (BPs) and perfluoroalkyls (PFs) are chemicals leached from plastics and other household products, and humans are unavoidably exposed to these xenobiotics. Data from animal studies suggest that EDCs exposure may play a role in PD, but data about the effect of BPs and PFs on human models of the nervous system are lacking. Previous studies demonstrated that machine learning (ML) applied to microscopy data can classify different cell phenotypes based on image features. In this study, the effect of BPs and PFs at different concentrations within the real-life exposure range (0.01, 0.1, 1, and 2 µM) on the phenotypic profile of human stem cell-derived midbrain dopaminergic neurons (mDANs) was analyzed. Cells exposed for 72 h to the xenobiotics were stained with neuronal markers and evaluated using high content microscopy yielding 126 different phenotypic features. Three different ML models (LDA, XGBoost and LightGBM) were trained to classify EDC-treated versus control mDANs. EDC treated mDANs were identified with high accuracies (0.88-0.96). Assessment of the phenotypic feature contribution to the classification showed that EDCs induced a significant increase of alpha-synuclein (αSyn) and tyrosine hydroxylase (TH) staining intensity within the neurons. Moreover, microtubule-associated protein 2 (MAP2) neurite length and branching were significantly diminished in treated neurons. Our study shows that human mDANs are adversely impacted by exposure to EDCs, causing their phenotype to shift and exhibit more characteristics of PD. Importantly, ML-supported high-content imaging can identify concrete but subtle subcellular phenotypic changes that can be easily overlooked by visual inspection alone and that define EDCs effects in mDANs, thus enabling further pathological characterization in the future.

Phenotypic Profiling of Human Stem Cell-Derived Midbrain Dopaminergic Neurons.

Parkinson's disease (PD) is linked to a range of cell biological processes that cause midbrain dopaminergic (mDA) neuron loss. Many current in vitro PD cellular models lack complexity and do not take multiple phenotypes into account. Phenotypic profiling in human induced pluripotent stem cell (iPSC)-derived mDA neurons can address these shortcomings by simultaneously measuring a range of neuronal phenotypes in a PD-relevant cell type in parallel. Here, we describe a protocol to obtain and analyze phenotypic profiles from commercially available human mDA neurons. A neuron-specific fluorescent staining panel is used to visualize the nuclear, α-synuclein, Tyrosine hydroxylase (TH), and Microtubule-associated protein 2 (MAP2) related phenotypes. The described phenotypic profiling protocol is scalable as it uses 384-well plates, automatic liquid handling and high-throughput microscopy. The utility of the protocol is exemplified using healthy donor mDA neurons and mDA neurons carrying the PD-linked G2019S mutation in the Leucine-rich repeat kinase 2 (LRRK2) gene. Both cell lines were treated with the LRRK2 kinase inhibitor PFE-360 and phenotypic changes were measured. Additionally, we demonstrate how multidimensional phenotypic profiles can be analyzed using clustering or machine learning-driven supervised classification methods. The described protocol will particularly interest researchers working on neuronal disease modeling or studying chemical compound effects in human neurons.

High-content phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons using machine learning classification.

Combining multiple Parkinson's disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic neuron (mDAN) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control, and genetically unrelated iPSCs into mDANs. Using automated fluorescence microscopy in 384-well-plate format, we identified elevated levels of α-synuclein (αSyn) and serine 129 phosphorylation, reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDANs according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or αSyn levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient-derived SNCA gene triplication mDAN model which overexpresses αSyn. This phenotyping and classification strategy improves the practical exploitability of mDANs for disease modeling and the identification of novel LRRK2-associated drug targets.

Time-resolved FRET screening identifies small molecular modifiers of mutant Huntingtin conformational inflexibility in patient-derived cells.

Huntington's disease (HD) is the most common monogenic neurodegenerative disease and is fatal. CAG repeat expansions in mutant Huntingtin (mHTT) exon 1 encode for polyglutamine (polyQ) stretches and influence age of onset and disease severity, depending on their length. mHTT is more structured compared to wild-type (wt) HTT, resulting in a decreased N-terminal conformational flexibility. mHTT inflexibility may contribute to both gain of function toxicity, due to increased mHTT aggregation propensity, but also to loss of function phenotypes, due to decreased interactions with binding partners. High-throughput-screening techniques to identify mHTT flexibility states and potential flexibility modifying small molecules are currently lacking. Here, we propose a novel approach for identifying small molecules that restore mHTT's conformational flexibility in human patient fibroblasts. We have applied a well-established antibody-based time-resolved Förster resonance energy transfer (TR-FRET) immunoassay, which measures endogenous HTT flexibility using two validated HTT-specific antibodies, to a high-throughput screening platform. By performing a small-scale compound screen, we identified several small molecules that can partially rescue mHTT inflexibility, presumably by altering HTT post-translational modifications. Thus, we demonstrated that the HTT TR-FRET immunoassay can be miniaturized and applied to a compound screening workflow in patient cells. This automated assay can now be used in large screening campaigns to identify previously unknown HD drugs and drug targets.

Author Correction: CPSF3-dependent pre-mRNA processing as a druggable node in AML and Ewing's sarcoma.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

CPSF3-dependent pre-mRNA processing as a druggable node in AML and Ewing's sarcoma.

The post-genomic era has seen many advances in our understanding of cancer pathways, yet resistance and tumor heterogeneity necessitate multiple approaches to target even monogenic tumors. Here, we combine phenotypic screening with chemical genetics to identify pre-messenger RNA endonuclease cleavage and polyadenylation specificity factor 3 (CPSF3) as the target of JTE-607, a small molecule with previously unknown target. We show that CPSF3 represents a synthetic lethal node in a subset of acute myeloid leukemia (AML) and Ewing's sarcoma cancer cell lines. Inhibition of CPSF3 by JTE-607 alters expression of known downstream effectors in AML and Ewing's sarcoma lines, upregulates apoptosis and causes tumor-selective stasis in mouse xenografts. Mechanistically, it prevents the release of newly synthesized pre-mRNAs, resulting in read-through transcription and the formation of DNA-RNA hybrid R-loop structures. This study implicates pre-mRNA processing, and specifically CPSF3, as a druggable target providing an avenue to therapeutic intervention in cancer.

Single-Molecule Imaging of mRNA Localization and Regulation during the Integrated Stress Response.

Biological phase transitions form membrane-less organelles that generate distinct cellular environments. How molecules are partitioned between these compartments and the surrounding cellular space and the functional consequence of this localization is not well understood. Here, we report the localization of mRNA to stress granules (SGs) and processing bodies (PBs) and its effect on translation and degradation during the integrated stress response. Using single mRNA imaging in living human cells, we find that the interactions of mRNAs with SGs and PBs have different dynamics, very few mRNAs directly move between SGs and PBs, and that specific RNA-binding proteins can anchor mRNAs within these compartments. During recovery from stress, we show that mRNAs that were within SGs and PBs are translated and degraded at similar rates as their cytosolic counterparts. Our work provides a framework for using single-molecule measurements to directly investigate the molecular mechanisms of phase-separated compartments within their cellular environment.

Exchange between Escherichia coli polymerases II and III on a processivity clamp.

Escherichia coli has three DNA polymerases implicated in the bypass of DNA damage, a process called translesion synthesis (TLS) that alleviates replication stalling. Although these polymerases are specialized for different DNA lesions, it is unclear if they interact differently with the replication machinery. Of the three, DNA polymerase (Pol) II remains the most enigmatic. Here we report a stable ternary complex of Pol II, the replicative polymerase Pol III core complex and the dimeric processivity clamp, ß. Single-molecule experiments reveal that the interactions of Pol II and Pol III with ß allow for rapid exchange during DNA synthesis. As with another TLS polymerase, Pol IV, increasing concentrations of Pol II displace the Pol III core during DNA synthesis in a minimal reconstitution of primer extension. However, in contrast to Pol IV, Pol II is inefficient at disrupting rolling-circle synthesis by the fully reconstituted Pol III replisome. Together, these data suggest a ß-mediated mechanism of exchange between Pol II and Pol III that occurs outside the replication fork.

Translation. An RNA biosensor for imaging the first round of translation from single cells to living animals.

Analysis of single molecules in living cells has provided quantitative insights into the kinetics of fundamental biological processes; however, the dynamics of messenger RNA (mRNA) translation have yet to be addressed. We have developed a fluorescence microscopy technique that reports on the first translation events of individual mRNA molecules. This allowed us to examine the spatiotemporal regulation of translation during normal growth and stress and during Drosophila oocyte development. We have shown that mRNAs are not translated in the nucleus but translate within minutes after export, that sequestration within P-bodies regulates translation, and that oskar mRNA is not translated until it reaches the posterior pole of the oocyte. This methodology provides a framework for studying initiation of protein synthesis on single mRNAs in living cells.