Multiomics analysis identifies novel facilitators of human dopaminergic neuron differentiation.

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior under physiological conditions and are implicated in human diseases such as Parkinson's disease (PD). Many transcription factors (TFs) controlling human mDAN differentiation during development have been described, but much of the regulatory landscape remains undefined. Using a tyrosine hydroxylase (TH) human iPSC reporter line, we here generate time series transcriptomic and epigenomic profiles of purified mDANs during differentiation. Integrative analysis predicts novel regulators of mDAN differentiation and super-enhancers are used to identify key TFs. We find LBX1, NHLH1 and NR2F1/2 to promote mDAN differentiation and show that overexpression of either LBX1 or NHLH1 can also improve mDAN specification. A more detailed investigation of TF targets reveals that NHLH1 promotes the induction of neuronal miR-124, LBX1 regulates cholesterol biosynthesis, and NR2F1/2 controls neuronal activity.

Phagocytosis-related NADPH oxidase 2 subunit gp91phox contributes to neurodegeneration after repeated systemic challenge with lipopolysaccharides.

Repeated systemic challenge with lipopolysaccharides (LPS) can induce microglia activation and inflammatory neurodegeneration in the substantia nigra pars compacta region of mice. We now explored the role of mononuclear phagocytes associated nicotinamide adenine dinucleotide phosphate oxidase 2 (NOX-2) in inflammatory neurodegeneration. Cybb-deficient NOX-2 knock-out (KO) and control wild type (WT) mice were treated intraperitoneally daily over four consecutive days with 1 µg/gbw/day LPS. Transcriptome analysis by RNA-seq of total brain tissue indicated increased LPS-induced upregulation of genes belonging to the reactive oxygen species and reactive nitrogen species production, complement and lysosome activation as well as apoptosis and necroptosis in WT compared to NOX-2 KO mice. Validation of up-regulated gene transcripts via qRT-PCR confirmed that LPS-challenged NOX-2 KO mice expressed lower levels of the microglial phagocytosis-related genes Nos2, Cd68, Aif1/Iba1, Cyba, Itgam, and Fcer1g compared to WT mice at Day 5 after systemic inflammatory challenge, but no significant differences in the pro-inflammatory genes Tnfα and Il1b as well as microglial IBA1 and CD68 intensities were observed between both genotypes. Furthermore, loss of tyrosine hydroxylase positive (TH+) and NeuN positive neurons in the substantia nigra pars compacta upon repeated systemic LPS application were attenuated in NOX-2 KO mice. Thus, our data demonstrate that loss of dopaminergic neurons in the substantia nigra pars compacta after repeated systemic challenge with LPS is associated with a microglial phagocytosis-related gene activation profile involving the NADPH oxidase subunit Cybb/gp91phox.

Temporal enhancer profiling of parallel lineages identifies AHR and GLIS1 as regulators of mesenchymal multipotency.

Temporal data on gene expression and context-specific open chromatin states can improve identification of key transcription factors (TFs) and the gene regulatory networks (GRNs) controlling cellular differentiation. However, their integration remains challenging. Here, we delineate a general approach for data-driven and unbiased identification of key TFs and dynamic GRNs, called EPIC-DREM. We generated time-series transcriptomic and epigenomic profiles during differentiation of mouse multipotent bone marrow stromal cell line (ST2) toward adipocytes and osteoblasts. Using our novel approach we constructed time-resolved GRNs for both lineages and identifed the shared TFs involved in both differentiation processes. To take an alternative approach to prioritize the identified shared regulators, we mapped dynamic super-enhancers in both lineages and associated them to target genes with correlated expression profiles. The combination of the two approaches identified aryl hydrocarbon receptor (AHR) and Glis family zinc finger 1 (GLIS1) as mesenchymal key TFs controlled by dynamic cell type-specific super-enhancers that become repressed in both lineages. AHR and GLIS1 control differentiation-induced genes and their overexpression can inhibit the lineage commitment of the multipotent bone marrow-derived ST2 cells.

Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation.

Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.

TREM2 triggers microglial density and age-related neuronal loss.

The microglial triggering receptor expressed on myeloid cells 2 (TREM2) signals via the activatory membrane adaptor molecule TYROBP. Genetic variants or mutations of TREM2 or TYROBP have been linked to inflammatory neurodegenerative diseases associated with aging. The typical aging process goes along with microglial changes and mild neuronal loss, but the exact contribution of TREM2 is still unclear. Aged TREM2 knock-out mice showed decreased age-related neuronal loss in the substantia nigra and the hippocampus. Transcriptomic analysis of the brains of 24 months old TREM2 knock-out mice revealed 211 differentially expressed genes mostly downregulated and associated with complement activation and oxidative stress response pathways. Consistently, 24 months old TREM2 knock-out mice showed lower transcription of microglial (Aif1 and Tmem119), oxidative stress markers (Inos, Cyba, and Cybb) and complement components (C1qa, C1qb, C1qc, C3, C4b, Itgam, and Itgb2), decreased microglial numbers and expression of the microglial activation marker Cd68, as well as accumulation of oxidized lipids. Cultured microglia of TREM2 knock-out mice showed reduced phagocytosis and oxidative burst. Thus, microglial TREM2 contributes to age-related microglial changes, phagocytic oxidative burst, and loss of neurons with possible detrimental effects during physiological aging.

Analysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture.

Changes in mature microRNA (miRNA) levels that occur downstream of signaling cascades play an important role during human development and disease. However, the regulation of primary microRNA (pri-miRNA) genes remains to be dissected in detail. To address this, we followed a data-driven approach and developed a transcript identification, validation and quantification pipeline for characterizing the regulatory domains of pri-miRNAs. Integration of 92 nascent transcriptomes and multilevel data from cells arising from ecto-, endo- and mesoderm lineages reveals cell type-specific expression patterns, allows fine-resolution mapping of transcription start sites (TSS) and identification of candidate regulatory regions. We show that inter- and intragenic pri-miRNA transcripts span vast genomic regions and active TSS locations differ across cell types, exemplified by the mir-29a∼29b-1, mir-100∼let-7a-2∼125b-1 and miR-221∼222 clusters. Considering the presence of multiple TSS as an important regulatory feature at miRNA loci, we developed a strategy to quantify differential TSS usage. We demonstrate that the TSS activities associate with cell type-specific super-enhancers, differential stimulus responsiveness and higher-order chromatin structure. These results pave the way for building detailed regulatory maps of miRNA loci.

Cell type-selective disease-association of genes under high regulatory load.

We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3' UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner.

Gene-pair expression signatures reveal lineage control.

The distinct cell types of multicellular organisms arise owing to constraints imposed by gene regulatory networks on the collective change of gene expression across the genome, creating self-stabilizing expression states, or attractors. We curated human expression data comprising 166 cell types and 2,602 transcription-regulating genes and developed a data-driven method for identifying putative determinants of cell fate built around the concept of expression reversal of gene pairs, such as those participating in toggle-switch circuits. This approach allows us to organize the cell types into their ontogenic lineage relationships. Our method identifies genes in regulatory circuits that control neuronal fate, pluripotency and blood cell differentiation, and it may be useful for prioritizing candidate factors for direct conversion of cell fate.

Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network.

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraint-based modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) γ, CCAAT/enhancer binding protein (CEBP) α, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-3-phosphate acyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions.

Neurodegeneration by activation of the microglial complement-phagosome pathway.

Systemic inflammatory reactions have been postulated to exacerbate neurodegenerative diseases via microglial activation. We now demonstrate in vivo that repeated systemic challenge of mice over four consecutive days with bacterial LPS maintained an elevated microglial inflammatory phenotype and induced loss of dopaminergic neurons in the substantia nigra. The same total cumulative LPS dose given within a single application did not induce neurodegeneration. Whole-genome transcriptome analysis of the brain demonstrated that repeated systemic LPS application induced an activation pattern involving the classical complement system and its associated phagosome pathway. Loss of dopaminergic neurons induced by repeated systemic LPS application was rescued in complement C3-deficient mice, confirming the involvement of the complement system in neurodegeneration. Our data demonstrate that a phagosomal inflammatory response of microglia is leading to complement-mediated loss of dopaminergic neurons.

Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network.

BACKGROUND: The reconstruction of context-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important in research and medicine. Current reconstruction methods suffer from high computational effort and arbitrary threshold setting. Moreover, understanding the underlying epigenetic regulation might allow the identification of putative intervention points within metabolic networks. Genes under high regulatory load from multiple enhancers or super-enhancers are known key genes for disease and cell identity. However, their role in regulation of metabolism and their placement within the metabolic networks has not been studied. METHODS: Here we present FASTCORMICS, a fast and robust workflow for the creation of high-quality metabolic models from transcriptomics data. FASTCORMICS is devoid of arbitrary parameter settings and due to its low computational demand allows cross-validation assays. Applying FASTCORMICS, we have generated models for 63 primary human cell types from microarray data, revealing significant differences in their metabolic networks. RESULTS: To understand the cell type-specific regulation of the alternative metabolic pathways we built multiple models during differentiation of primary human monocytes to macrophages and performed ChIP-Seq experiments for histone H3 K27 acetylation (H3K27ac) to map the active enhancers in macrophages. Focusing on the metabolic genes under high regulatory load from multiple enhancers or super-enhancers, we found these genes to show the most cell type-restricted and abundant expression profiles within their respective pathways. Importantly, the high regulatory load genes are associated to reactions enriched for transport reactions and other pathway entry points, suggesting that they are critical regulatory control points for cell type-specific metabolism. CONCLUSIONS: By integrating metabolic modelling and epigenomic analysis we have identified high regulatory load as a common feature of metabolic genes at pathway entry points such as transporters within the macrophage metabolic network. Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming.

Combinatorial regulation of lipoprotein lipase by microRNAs during mouse adipogenesis.

MicroRNAs (miRNAs) regulate gene expression directly through base pairing to their targets or indirectly through participating in multi-scale regulatory networks. Often miRNAs take part in feed-forward motifs where a miRNA and a transcription factor act on shared targets to achieve accurate regulation of processes such as cell differentiation. Here we show that the expression levels of miR-27a and miR-29a inversely correlate with the mRNA levels of lipoprotein lipase (Lpl), their predicted combinatorial target, and its key transcriptional regulator peroxisome proliferator-activated receptor gamma (Pparg) during 3T3-L1 adipocyte differentiation. More importantly, we show that Lpl, a key lipogenic enzyme, can be negatively regulated by the two miRNA families in a combinatorial fashion on the mRNA and functional level in maturing adipocytes. This regulation is mediated through the Lpl 3'UTR as confirmed by reporter gene assays. In addition, a small mathematical model captures the dynamics of this feed-forward motif and predicts the changes in Lpl mRNA levels upon network perturbations. The obtained results might offer an explanation to the dysregulation of LPL in diabetic conditions and could be extended to quantitative modeling of regulation of other metabolic genes under similar regulatory network motifs.

Dataset integration identifies transcriptional regulation of microRNA genes by PPARγ in differentiating mouse 3T3-L1 adipocytes.

Peroxisome proliferator-activated receptor γ (PPARγ) is a key transcription factor in mammalian adipogenesis. Genome-wide approaches have identified thousands of PPARγ binding sites in mouse adipocytes and PPARγ upregulates hundreds of protein-coding genes during adipogenesis. However, no microRNA (miRNA) genes have been identified as primary PPARγ-targets. By integration of four separate datasets of genome-wide PPARγ binding sites in 3T3-L1 adipocytes we identified 98 miRNA clusters with PPARγ binding within 50 kb from miRNA transcription start sites. Nineteen mature miRNAs were upregulated ≥2-fold during adipogenesis and for six of these miRNA loci the PPARγ binding sites were confirmed by at least three datasets. The upregulation of five miRNA genes miR-103-1 (host gene Pank3), miR-148b (Copz1), miR-182/96/183, miR-205 and miR-378 (Ppargc1b) followed that of Pparg. The PPARγ-dependence of four of these miRNA loci was demonstrated by PPARγ knock-down and the loci of miR-103-1 (Pank3), miR-205 and miR-378 (Ppargc1b) were also responsive to the PPARγ ligand rosiglitazone. Finally, chromatin immunoprecipitation analysis validated in silico predicted PPARγ binding sites at all three loci and H3K27 acetylation was analyzed to confirm the activity of these enhancers. In conclusion, we identified 22 putative PPARγ target miRNA genes, showed the PPARγ dependence of four of these genes and demonstrated three as direct PPARγ target genes in mouse adipogenesis.

2-Hydroxyglutarate modulates histone methylation at specific loci and alters gene expression via Rph1 inhibition.

2-Hydroxyglutarate (2-HG) is an oncometabolite that accumulates in certain cancers. Gain-of-function mutations in isocitrate dehydrogenase lead to 2-HG accumulation at the expense of alpha-ketoglutarate. Elevated 2-HG levels inhibit histone and DNA demethylases, causing chromatin structure and gene regulation changes with tumorigenic consequences. We investigated the effects of elevated 2-HG levels in Saccharomyces cerevisiae, a yeast devoid of DNA methylation and heterochromatin-associated histone methylation. Our results demonstrate genetic background-dependent gene expression changes and altered H3K4 and H3K36 methylation at specific loci. Analysis of histone demethylase deletion strains indicated that 2-HG inhibits Rph1 sufficiently to induce extensive gene expression changes. Rph1 is the yeast homolog of human KDM4 demethylases and, among the yeast histone demethylases, was the most sensitive to the inhibitory effect of 2-HG in vitro. Interestingly, Rph1 deficiency favors gene repression and leads to further down-regulation of already silenced genes marked by low H3K4 and H3K36 trimethylation, but abundant in H3K36 dimethylation. Our results provide novel insights into the genome-wide effects of 2-HG and highlight Rph1 as its preferential demethylase target.

Metabolic modelling-based in silico drug target prediction identifies six novel repurposable drugs for melanoma.

Despite high initial response rates to targeted kinase inhibitors, the majority of patients suffering from metastatic melanoma present with high relapse rates, demanding for alternative therapeutic options. We have previously developed a drug repurposing workflow to identify metabolic drug targets that, if depleted, inhibit the growth of cancer cells without harming healthy tissues. In the current study, we have applied a refined version of the workflow to specifically predict both, common essential genes across various cancer types, and melanoma-specific essential genes that could potentially be used as drug targets for melanoma treatment. The in silico single gene deletion step was adapted to simulate the knock-out of all targets of a drug on an objective function such as growth or energy balance. Based on publicly available, and in-house, large-scale transcriptomic data metabolic models for melanoma were reconstructed enabling the prediction of 28 candidate drugs and estimating their respective efficacy. Twelve highly efficacious drugs with low half-maximal inhibitory concentration values for the treatment of other cancers, which are not yet approved for melanoma treatment, were used for in vitro validation using melanoma cell lines. Combination of the top 4 out of 6 promising candidate drugs with BRAF or MEK inhibitors, partially showed synergistic growth inhibition compared to individual BRAF/MEK inhibition. Hence, the repurposing of drugs may enable an increase in therapeutic options e.g., for non-responders or upon acquired resistance to conventional melanoma treatments.

Pyruvate dehydrogenase fuels a critical citrate pool that is essential for Th17 cell effector functions.

Pyruvate dehydrogenase (PDH) is the central enzyme connecting glycolysis and the tricarboxylic acid (TCA) cycle. The importance of PDH function in T helper 17 (Th17) cells still remains to be studied. Here, we show that PDH is essential for the generation of a glucose-derived citrate pool needed for Th17 cell proliferation, survival, and effector function. In vivo, mice harboring a T cell-specific deletion of PDH are less susceptible to developing experimental autoimmune encephalomyelitis. Mechanistically, the absence of PDH in Th17 cells increases glutaminolysis, glycolysis, and lipid uptake in a mammalian target of rapamycin (mTOR)-dependent manner. However, cellular citrate remains critically low in mutant Th17 cells, which interferes with oxidative phosphorylation (OXPHOS), lipid synthesis, and histone acetylation, crucial for transcription of Th17 signature genes. Increasing cellular citrate in PDH-deficient Th17 cells restores their metabolism and function, identifying a metabolic feedback loop within the central carbon metabolism that may offer possibilities for therapeutically targeting Th17 cell-driven autoimmunity.

Normal and Pathological NRF2 Signalling in the Central Nervous System.

The nuclear factor erythroid 2-related factor 2 (NRF2) was originally described as a master regulator of antioxidant cellular response, but in the time since, numerous important biological functions linked to cell survival, cellular detoxification, metabolism, autophagy, proteostasis, inflammation, immunity, and differentiation have been attributed to this pleiotropic transcription factor that regulates hundreds of genes. After 40 years of in-depth research and key discoveries, NRF2 is now at the center of a vast regulatory network, revealing NRF2 signalling as increasingly complex. It is widely recognized that reactive oxygen species (ROS) play a key role in human physiological and pathological processes such as ageing, obesity, diabetes, cancer, and neurodegenerative diseases. The high oxygen consumption associated with high levels of free iron and oxidizable unsaturated lipids make the brain particularly vulnerable to oxidative stress. A good stability of NRF2 activity is thus crucial to maintain the redox balance and therefore brain homeostasis. In this review, we have gathered recent data about the contribution of the NRF2 pathway in the healthy brain as well as during metabolic diseases, cancer, ageing, and ageing-related neurodegenerative diseases. We also discuss promising therapeutic strategies and the need for better understanding of cell-type-specific functions of NRF2 in these different fields.

Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases.

Brain disorders represent 32% of the global disease burden, with 169 million Europeans affected. Constraint-based metabolic modelling and other approaches have been applied to predict new treatments for these and other diseases. Many recent studies focused on enhancing, among others, drug predictions by generating generic metabolic models of brain cells and on the contextualisation of the genome-scale metabolic models with expression data. Experimental flux rates were primarily used to constrain or validate the model inputs. Bi-cellular models were reconstructed to study the interaction between different cell types. This review highlights the evolution of genome-scale models for neurodegenerative diseases and glioma. We discuss the advantages and drawbacks of each approach and propose improvements, such as building bi-cellular models, tailoring the biomass formulations for glioma and refinement of the cerebrospinal fluid composition.

Focal adhesion kinase plays a dual role in TRAIL resistance and metastatic outgrowth of malignant melanoma.

Despite remarkable advances in therapeutic interventions, malignant melanoma (MM) remains a life-threating disease. Following high initial response rates to targeted kinase-inhibition metastases quickly acquire resistance and present with enhanced tumor progression and invasion, demanding alternative treatment options. We show 2nd generation hexameric TRAIL-receptor-agonist IZI1551 (IZI) to effectively induce apoptosis in MM cells irrespective of the intrinsic BRAF/NRAS mutation status. Conditioning to the EC50 dose of IZI converted the phenotype of IZI-sensitive parental MM cells into a fast proliferating and invasive, IZI-resistant metastasis. Mechanistically, we identified focal adhesion kinase (FAK) to play a dual role in phenotype-switching. In the cytosol, activated FAK triggers survival pathways in a PI3K- and MAPK-dependent manner. In the nucleus, the FERM domain of FAK prevents activation of wtp53, as being expressed in the majority of MM, and consequently intrinsic apoptosis. Caspase-8-mediated cleavage of FAK as well as FAK knockdown, and pharmacological inhibition, respectively, reverted the metastatic phenotype-switch and restored IZI responsiveness. FAK inhibition also re-sensitized MM cells isolated from patient metastasis that had relapsed from targeted kinase inhibition to cell death, irrespective of the intrinsic BRAF/NRAS mutation status. Hence, FAK-inhibition alone or in combination with 2nd generation TRAIL-receptor agonists may be recommended for treatment of initially resistant and relapsed MM, respectively.