WNT signalling control by KDM5C during development affects cognition.

Although KDM5C is one of the most frequently mutated genes in X-linked intellectual disability1, the exact mechanisms that lead to cognitive impairment remain unknown. Here we use human patient-derived induced pluripotent stem cells and Kdm5c knockout mice to conduct cellular, transcriptomic, chromatin and behavioural studies. KDM5C is identified as a safeguard to ensure that neurodevelopment occurs at an appropriate timescale, the disruption of which leads to intellectual disability. Specifically, there is a developmental window during which KDM5C directly controls WNT output to regulate the timely transition of primary to intermediate progenitor cells and consequently neurogenesis. Treatment with WNT signalling modulators at specific times reveal that only a transient alteration of the canonical WNT signalling pathway is sufficient to rescue the transcriptomic and chromatin landscapes in patient-derived cells and to induce these changes in wild-type cells. Notably, WNT inhibition during this developmental period also rescues behavioural changes of Kdm5c knockout mice. Conversely, a single injection of WNT3A into the brains of wild-type embryonic mice cause anxiety and memory alterations. Our work identifies KDM5C as a crucial sentinel for neurodevelopment and sheds new light on KDM5C mutation-associated intellectual disability. The results also increase our general understanding of memory and anxiety formation, with the identification of WNT functioning in a transient nature to affect long-lasting cognitive function.

A Chemically Defined Feeder-free System for the Establishment and Maintenance of the Human Naive Pluripotent State.

The distinct states of pluripotency in the pre- and post-implantation embryo can be captured in vitro as naive and primed pluripotent stem cell cultures, respectively. The study and application of the naive state remains hampered, particularly in humans, partially due to current culture protocols relying on extraneous undefined factors such as feeders. Here we performed a small-molecule screen to identify compounds that facilitate chemically defined establishment and maintenance of human feeder-independent naive embryonic (FINE) stem cells. The expression profile in genic and repetitive elements of FINE cells resembles the 8-cell-to-morula stage in vivo, and only differs from feeder-dependent naive cells in genes involved in cell-cell/cell-matrix interactions. FINE cells offer several technical advantages, such as increased amenability to transfection and a longer period of genomic stability, compared with feeder-dependent cells. Thus, FINE cells will serve as an accessible and useful system for scientific and translational applications of naïve pluripotent stem cells.

A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters.

Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. However, while a global change in transcription is recognized as a defining feature of cancer, the contribution of alternative promoters still remains largely unexplored. Here, we infer active promoters using RNA-seq data from 18,468 cancer and normal samples, demonstrating that alternative promoters are a major contributor to context-specific regulation of transcription. We find that promoters are deregulated across tissues, cancer types, and patients, affecting known cancer genes and novel candidates. For genes with independently regulated promoters, we demonstrate that promoter activity provides a more accurate predictor of patient survival than gene expression. Our study suggests that a dynamic landscape of active promoters shapes the cancer transcriptome, opening new diagnostic avenues and opportunities to further explore the interplay of regulatory mechanisms with transcriptional aberrations in cancer.

Tumor-associated B cells and humoral immune response in head and neck squamous cell carcinoma.

B lymphocytes are important players in immune responses to cancer. However, their composition and function in head and neck squamous cell carcinoma (HNSCC) has not been well described. Here, we analyzed B cell subsets in HNSCC (n = 38), non-cancerous mucosa (n = 14) and peripheral blood from HNSCC patients (n = 38) and healthy controls (n = 20) by flow cytometry. Intratumoral B cells contained high percentages of activated (CD86+), antigen-presenting (CD86+/CD21-) and memory B cells (IgD-/CD27+). T follicular helper cells (CD4+/CXCR5+/CD45RA-/CCR7-) as key components of tertiary lymphoid structures and plasma cells made up high percentages of the lymphocyte infiltrate. Percentages of regulatory B cell varied depending on the regulatory phenotype. Analysis of humoral immune responses against 23 tumor-associated antigens (TAA) showed reactivity against at least one antigen in 56% of HNSCC patients. Reactivity was less frequent in human papillomavirus associated (HPV+) patients and healthy controls compared to HPV negative (HPV-) HNSCC. Likewise, patients with early stage HNSCC or MHC-I loss on tumor cells had low TAA responses. Patients with TAA responses showed CD4+ dominated T cell infiltration compared to mainly CD8+ T cells in tumors without detected TAA response. To summarize, our data demonstrates different immune infiltration patterns in relation to serological TAA response detection and the presence of B cell subpopulations in HNSCC that can engage in tumor promoting and antitumor activity. In view of increasing use of immunotherapeutic approaches, it will be important to include B cells into comprehensive phenotypic and functional analyses of tumor-associated lymphocytes.

B cells in esophago-gastric adenocarcinoma are highly differentiated, organize in tertiary lymphoid structures and produce tumor-specific antibodies.

Tumor-infiltrating lymphocytes (TILs) are correlated to prognosis of several kinds of cancer. Most studies focused on T cells, while the role of tumor-associated B cells (TABs) has only recently gained more attention. TABs contain subpopulations with distinct functions, potentially promoting or inhibiting immune responses. This study provides a detailed analysis of TABs in gastro-esophageal adenocarcinoma (EAC). Flow cytometric analyses of single cell suspensions of tumor samples, mucosa, lymph nodes and peripheral blood mononuclear cells (PBMC) of EAC patients and healthy controls revealed a distinct B cell compartment in cancer patients. B cells were increased in tumor samples and subset-analyses of TILs showed increased proportions of differentiated and activated B cells and an enrichment for follicular T helper cells. Confocal microscopy demonstrated that TABs were mainly organized in tertiary lymphoid structures (TLS), which resemble lymphoid follicles in secondary lymphoid organs. A panel of 34 tumor-associated antigens (TAAs) expressed in EAC was identified based on public databases and TCGA data to analyze tumor-specific B cell responses using a LUMINEXTM bead assay and flow cytometry. Structural analyses of TLS and the detection of tumor-specific antibodies against one or more TAAs in 48.1% of analyzed serum samples underline presence of anti-tumor B cell responses in EAC. Interestingly, B cells were decreased in tumors with expression of Programmed Death Ligand 1 or impaired HLA-I expression. These data demonstrate that anti-tumor B cell responses are an additional and underestimated aspect of EAC. Our results are of immediate translational relevance to emerging immunotherapies.

An ontology-based method for assessing batch effect adjustment approaches in heterogeneous datasets.

Motivation: International consortia such as the Genotype-Tissue Expression (GTEx) project, The Cancer Genome Atlas (TCGA) or the International Human Epigenetics Consortium (IHEC) have produced a wealth of genomic datasets with the goal of advancing our understanding of cell differentiation and disease mechanisms. However, utilizing all of these data effectively through integrative analysis is hampered by batch effects, large cell type heterogeneity and low replicate numbers. To study if batch effects across datasets can be observed and adjusted for, we analyze RNA-seq data of 215 samples from ENCODE, Roadmap, BLUEPRINT and DEEP as well as 1336 samples from GTEx and TCGA. While batch effects are a considerable issue, it is non-trivial to determine if batch adjustment leads to an improvement in data quality, especially in cases of low replicate numbers. Results: We present a novel method for assessing the performance of batch effect adjustment methods on heterogeneous data. Our method borrows information from the Cell Ontology to establish if batch adjustment leads to a better agreement between observed pairwise similarity and similarity of cell types inferred from the ontology. A comparison of state-of-the art batch effect adjustment methods suggests that batch effects in heterogeneous datasets with low replicate numbers cannot be adequately adjusted. Better methods need to be developed, which can be assessed objectively in the framework presented here. Availability and implementation: Our method is available online at https://github.com/SchulzLab/OntologyEval. Supplementary information: Supplementary data are available at Bioinformatics online.

SRSF3 maintains transcriptome integrity in oocytes by regulation of alternative splicing and transposable elements.

The RNA-binding protein SRSF3 (also known as SRp20) has critical roles in the regulation of pre-mRNA splicing. Zygotic knockout of Srsf3 results in embryo arrest at the blastocyst stage. However, SRSF3 is also present in oocytes, suggesting that it might be critical as a maternally inherited factor. Here we identify SRSF3 as an essential regulator of alternative splicing and of transposable elements to maintain transcriptome integrity in mouse oocyte. Using 3D time-lapse confocal live imaging, we show that conditional deletion of Srsf3 in fully grown germinal vesicle oocytes substantially compromises the capacity of germinal vesicle breakdown (GVBD), and consequently entry into meiosis. By combining single cell RNA-seq, and oocyte micromanipulation with steric blocking antisense oligonucleotides and RNAse-H inducing gapmers, we found that the GVBD defect in mutant oocytes is due to both aberrant alternative splicing and derepression of B2 SINE transposable elements. Together, our study highlights how control of transcriptional identity of the maternal transcriptome by the RNA-binding protein SRSF3 is essential to the development of fertilized-competent oocytes.

Enriching Traditional Protein-protein Interaction Networks with Alternative Conformations of Proteins.

Traditional Protein-Protein Interaction (PPI) networks, which use a node and edge representation, lack some valuable information about the mechanistic details of biological processes. Mapping protein structures to these PPI networks not only provides structural details of each interaction but also helps us to find the mutual exclusive interactions. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different interactions, functions, and downstream signalling. In this study, we proposed a new representation for structural PPI networks inspecting the alternative conformations of proteins. We performed a large-scale study by creating breast cancer metastasis network and equipped it with different conformers of proteins. Our results showed that although 88% of proteins in our network has at least two structures in Protein Data Bank (PDB), only 22% of them have alternative conformations and the remaining proteins have different regions saved in PDB. However, using even this small set of alternative conformations we observed a considerable increase in our protein docking predictions. Our protein-protein interaction predictions increased from 54% to 76% using the alternative conformations. We also showed the benefits of investigating structural data and alternative conformations of proteins through three case studies.

Disrupting Interactions Between ß-Catenin and Activating TCFs Reconstitutes Ground State Pluripotency in Mouse Embryonic Stem Cells.

The 2i-media, composed of two small molecule inhibitors (PD0325901 and CHIR99021) against MEK and GSK3-kinases, respectively, is known to establish naïve ground state pluripotency in mouse embryonic stem cells (mESCs). These inhibitors block MEK-mediated differentiation, while driving ß-catenin dependent de-repression of pluripotency promoting targets. However, accumulating evidence suggest that ß-catenin's association with activating TCFs (TCF7 and TCF7L2) can induce expression of several lineage-specific prodifferentiation genes. We posited that CHIR-induced upregulation of ß-catenin levels could therefore compromise the stability of the naïve state in long-term cultures. Here, we investigated whether replacing CHIR with iCRT3, a small molecule that abrogates ß-catenin-TCF interaction, can still retain ground state pluripotency in mESCs. Our data suggests that iCRT3 + PD mediated coinhibition of MEK and ß-catenin/TCF-dependent transcriptional activity over multiple passages significantly reduces expression of differentiation markers, as compared to 2i. Furthermore, the ability to efficiently contribute toward chimera generation and germline transmission suggests that the inhibition of ß-catenin's TCF-dependent transcriptional activity, independent of its protein expression level, retains the naïve ground state pluripotency in mESCs. Additionally, growth medium containing iCRT3 + PD can provide an alternative to 2i as a stable culture method. Stem Cells 2017;35:1924-1933.

Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons.

Recent advances in 3D culture systems have led to the generation of brain organoids that resemble different human brain regions; however, a 3D organoid model of the midbrain containing functional midbrain dopaminergic (mDA) neurons has not been reported. We developed a method to differentiate human pluripotent stem cells into a large multicellular organoid-like structure that contains distinct layers of neuronal cells expressing characteristic markers of human midbrain. Importantly, we detected electrically active and functionally mature mDA neurons and dopamine production in our 3D midbrain-like organoids (MLOs). In contrast to human mDA neurons generated using 2D methods or MLOs generated from mouse embryonic stem cells, our human MLOs produced neuromelanin-like granules that were structurally similar to those isolated from human substantia nigra tissues. Thus our MLOs bearing features of the human midbrain may provide a tractable in vitro system to study the human midbrain and its related diseases.

Histone modifications and p53 binding poise the p21 promoter for activation in human embryonic stem cells.

The high proliferation rate of embryonic stem cells (ESCs) is thought to arise partly from very low expression of p21. However, how p21 is suppressed in ESCs has been unclear. We found that p53 binds to the p21 promoter in human ESCs (hESCs) as efficiently as in differentiated human mesenchymal stem cells, however it does not promote p21 transcription in hESCs. We observed an enrichment for both the repressive histone H3K27me3 and activating histone H3K4me3 chromatin marks at the p21 locus in hESCs, suggesting it is a suppressed, bivalent domain which overrides activation by p53. Reducing H3K27me3 methylation in hESCs rescued p21 expression, and ectopic expression of p21 in hESCs triggered their differentiation. Further, we uncovered a subset of bivalent promoters bound by p53 in hESCs that are similarly induced upon differentiation in a p53-dependent manner, whereas p53 promotes the transcription of other target genes which do not show an enrichment of H3K27me3 in ESCs. Our studies reveal a unique epigenetic strategy used by ESCs to poise undesired p53 target genes, thus balancing the maintenance of pluripotency in the undifferentiated state with a robust response to differentiation signals, while utilizing p53 activity to maintain genomic stability and homeostasis in ESCs.

Molecular Features Underlying Neurodegeneration Identified through In Vitro Modeling of Genetically Diverse Parkinson's Disease Patients.

The fact that Parkinson's disease (PD) can arise from numerous genetic mutations suggests a unifying molecular pathology underlying the various genetic backgrounds. To address this hypothesis, we took an integrated approach utilizing in vitro disease modeling and comprehensive transcriptome profiling to advance our understanding of PD progression and the concordant downstream signaling pathways across divergent genetic predispositions. To model PD in vitro, we generated neurons harboring disease-causing mutations from patient-specific, induced pluripotent stem cells (iPSCs). We observed signs of degeneration in midbrain dopaminergic neurons, reflecting the cardinal feature of PD. Gene expression signatures of PD neurons provided molecular insights into disease phenotypes observed in vitro, including oxidative stress vulnerability and altered neuronal activity. Notably, PD neurons show that elevated RBFOX1, a gene previously linked to neurodevelopmental diseases, underlies a pattern of alternative RNA-processing associated with PD-specific phenotypes.

Hot spots in protein-protein interfaces: towards drug discovery.

Identification of drug-like small molecules that alter protein-protein interactions might be a key step in drug discovery. However, it is very challenging to find such molecules that target interface regions in protein complexes. Recent findings indicate that such molecules usually target specifically energetically favored residues (hot spots) in protein-protein interfaces. These residues contribute to the stability of protein-protein complexes. Computational prediction of hot spots on bound and unbound structures might be useful to find druggable sites on target interfaces. We review the recent advances in computational hot spot prediction methods in the first part of the review and then provide examples on how hot spots might be crucial in drug design.

PRISM: a web server and repository for prediction of protein-protein interactions and modeling their 3D complexes.

The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs). The prediction algorithm is knowledge-based. It combines structural similarity and accounts for evolutionary conservation in the template interfaces. The predicted models are stored in its repository. Given two protein structures, PRISM will provide a structural model of their complex if a matching template interface is available. Users can download the complex structure, retrieve the interface residues and visualize the complex model. The PRISM web server is user friendly, free and open to all users at http://cosbi.ku.edu.tr/prism.

Non-redundant unique interface structures as templates for modeling protein interactions.

Improvements in experimental techniques increasingly provide structural data relating to protein-protein interactions. Classification of structural details of protein-protein interactions can provide valuable insights for modeling and abstracting design principles. Here, we aim to cluster protein-protein interactions by their interface structures, and to exploit these clusters to obtain and study shared and distinct protein binding sites. We find that there are 22604 unique interface structures in the PDB. These unique interfaces, which provide a rich resource of structural data of protein-protein interactions, can be used for template-based docking. We test the specificity of these non-redundant unique interface structures by finding protein pairs which have multiple binding sites. We suggest that residues with more than 40% relative accessible surface area should be considered as surface residues in template-based docking studies. This comprehensive study of protein interface structures can serve as a resource for the community. The dataset can be accessed at http://prism.ccbb.ku.edu.tr/piface.

HotRegion: a database of predicted hot spot clusters.

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

Analysis of hot region organization in hub proteins.

Protein interaction maps constructed from binary interactions reveal that some proteins are highly connected to others (acting as hub proteins), whereas some others have a few interactions (at the edges of the map). This paper addresses hub proteins from a structural point: interfaces. It investigates how hot spots are organized in hub proteins (hot regions). We annotate interfaces as the ones between two date-hubs (DD), two party hubs (PP), and two non-hubs (NN). We investigate the physico-chemical properties of these three types of interfaces focusing on the accessible surface area distribution, hot region organization, and amino acid composition differences. Results reveal that there are significant differences between DD and PP interfaces. More of the hot spots are organized into the hot regions in DD interfaces compared to PP ones. A high fraction of the interfaces are covered by hot regions in DD interfaces. There are more distinct hot regions in DDs. Since the same (or overlapping) DD interfaces should be used repeatedly, different hot regions can be used to bind to different partners. Further, these hot region characteristics can be used to predict whether a given hub interface is involved in a DD or a PP interface type with 80% accuracy.