Gene regulatory mechanisms in the oligodendrocyte lineage in development and disease

Oligodendrocytes are the myelinating cells of the central nervous system (CNS). They contribute to the neuronal network through the insulation of neuronal axons, facilitating communication between neurons and providing metabolic support. In multiple sclerosis (MS), oligodendrocytes are attacked by the immune system leading to a wide variety of symptoms. Remyelination is necessary for functional recovery, which can occur through the recruitment and differentiation of oligodendrocyte precursor cells (OPCs) that reside in the adult CNS. During development and in disease, oligodendrocytes and OPCs (oligodendroglia) undergo significant changes at the transcriptional level. However, the genomes remain the same within these cells, so how do these transcriptional changes occur? In this thesis, we investigate gene regulatory mechanisms in the oligodendrocyte lineage in development and disease. In Paper I we investigate the role of citrullination in the differentiation of oligodendrocytes. We identify peptidylarginine deiminase 2 (PAD2) as the major citrullinating enzyme in oligodendrocytes, promoting oligodendrocyte differentiation through the upregulation of myelin genes. Interestingly, the main targets of PAD2 are proteins involved in transcriptional and posttranscriptional regulation. Other PAD2 targets are myelin proteins, which might explain the motor and cognitive deficits and the decrease in myelinated axons we observe upon loss of PAD2. In Paper II we characterize how the oligodendrocyte lineage is affected in disease, using single-cell transcriptomics in the MS mouse model experimental autoimmune encephalomyelitis (EAE). Oligodendroglia in EAE mice show an increase in immune pathway genes including major histocompatibility complex (MHC) class-I and -II genes involved in antigen processing and presentation. Furthermore, OPCs stimulated with interferon-gamma interact with and activate CD4 positive T cells. Thus, oligodendroglia might have a more active role in mediating the inflammatory response in MS than previously thought. In Paper III we investigate how oligodendroglia transition to the immune state, using single- cell ATAC-seq in EAE mice. We find that immune genes are primed and increase their expression in an inflammatory environment through changes in the histone modification landscape, in chromatin interactions, and in transcription factor binding. Overall, we identify gene regulatory mechanisms of the immune program in oligodendroglia that could be possible therapeutic targets for MS. In Paper IV we develop an extension of the method genome architecture mapping (immunoGAM), which we apply to study genome-wide chromatin interactions in intact brain tissue. We find interactions and mechanisms that are specific for different brain cell types. Long neuronal genes that are active, often show decondensation or ‘melting’. Furthermore, topologically associating domains and A/B compartments reorganize extensively upon differentiation, and cell type-specific interactions form mediated by specific transcription factor pairs. To conclude, this thesis examines different layers of gene regulation including chromatin accessibility, histone modifications, genome interactions, and transcription factor binding. More specifically, we investigate how these different layers are involved in the transitioning of oligodendroglia during differentiation or to disease states. The findings in this thesis will hopefully contribute to the development of improved treatment strategies for MS

A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

Background and Purpose: Diffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes. Materials and Methods: Twenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADCmean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics. Results: The median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56–1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63–1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising. Conclusions: The SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts.</p

A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

Background and Purpose: Diffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes. Materials and Methods: Twenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADCmean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics. Results: The median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56–1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63–1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising. Conclusions: The SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts.</p

A human in vitro neuronal model for studying homeostatic plasticity at the network level

Mechanisms that underlie homeostatic plasticity have been extensively investigated at single-cell levels in animal models, but are less well understood at the network level. Here, we used microelectrode arrays to characterize neuronal networks following induction of homeostatic plasticity in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons co-cultured with rat astrocytes. Chronic suppression of neuronal activity through tetrodotoxin (TTX) elicited a time-dependent network re-arrangement. Increased expression of AMPA receptors and the elongation of axon initial segments were associated with increased network excitability following TTX treatment. Transcriptomic profiling of TTX-treated neurons revealed up-regulated genes related to extracellular matrix organization, while down-regulated genes related to cell communication; also astrocytic gene expression was found altered. Overall, our study shows that hiPSC-derived neuronal networks provide a reliable in vitro platform to measure and characterize homeostatic plasticity at network and single-cell levels; this platform can be extended to investigate altered homeostatic plasticity in brain disorders.The work was supported by funding from the European Community’s Horizon 2020 Programme (H2020/2014–2020) under grant agreement no. 728018 (Eat2beNICE) (to B.F.); ERA-NET NEURON-102 SYNSCHIZ grant (NWO) 013-17-003 4538 (to D.S.); China Scholarship Council 201906100038 (to X.Y.); ISCIII /MINECO (PT17/0009/0019) and FEDER (to A.E.C.); and M.M. was supported by an internal grant from the Donders Centre for Medical Neurosciences of the Radboud University Medical Center

A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

BACKGROUND AND PURPOSE: Diffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes. MATERIALS AND METHODS: Twenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADC mean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics. RESULTS: The median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56-1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63-1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising. CONCLUSIONS: The SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts

The diabetes gene Zfp69 modulates hepatic insulin sensitivity in mice

AIMS/HYPOTHESIS: Zfp69 was previously identified by positional cloning as a candidate gene for obesity-associated diabetes. C57BL/6J and New Zealand obese (NZO) mice carry a loss-of-function mutation due to the integration of a retrotransposon. On the NZO background, the Zfp69 locus caused severe hyperglycaemia and loss of beta cells. To provide direct evidence for a causal role of Zfp69, we investigated the effects of its overexpression on both a lean [B6-Tg(Zfp69)] and an obese [NZO/B6-Tg(Zfp69)] background. METHODS: Zfp69 transgenic mice were generated by integrating the cDNA into the ROSA locus of the C57BL/6 genome and characterised. RESULTS: B6-Tg(Zfp69) mice were normoglycaemic, developed hyperinsulinaemia, and exhibited increased expression of G6pc and Pck1 and slightly reduced phospho-Akt levels in the liver. During OGTTs, glucose clearance was normal but insulin levels were significantly higher in the B6-Tg(Zfp69) than in control mice. The liver fat content and plasma triacylglycerol levels were significantly increased in B6-Tg(Zfp69) and NZO/B6-Tg(Zfp69) mice on a high-fat diet compared with controls. Liver transcriptome analysis of B6-Tg(Zfp69) mice revealed a downregulation of genes involved in glucose and lipid metabolism. Specifically, expression of Nampt, Lpin2, Map2k6, Gys2, Bnip3, Fitm2, Slc2a2, Ppargc1α and Insr was significantly decreased in the liver of B6-Tg(Zfp69) mice compared with wild-type animals. However, overexpression of Zfp69 did not induce overt diabetes with hyperglycaemia and beta cell loss. CONCLUSIONS/INTERPRETATION: Zfp69 mediates hyperlipidaemia, liver fat accumulation and mild insulin resistance. However, it does not induce type 2 diabetes, suggesting that the diabetogenic effect of the Zfp69 locus requires synergy with other as yet unidentified genes

The Genome of a Pathogenic Rhodococcus: Cooptive Virulence Underpinned by Key Gene Acquisitions

We report the genome of the facultative intracellular parasite Rhodococcus equi, the only animal pathogen within the biotechnologically important actinobacterial genus Rhodococcus. The 5.0-Mb R. equi 103S genome is significantly smaller than those of environmental rhodococci. This is due to genome expansion in nonpathogenic species, via a linear gain of paralogous genes and an accelerated genetic flux, rather than reductive evolution in R. equi. The 103S genome lacks the extensive catabolic and secondary metabolic complement of environmental rhodococci, and it displays unique adaptations for host colonization and competition in the short-chain fatty acid–rich intestine and manure of herbivores—two main R. equi reservoirs. Except for a few horizontally acquired (HGT) pathogenicity loci, including a cytoadhesive pilus determinant (rpl) and the virulence plasmid vap pathogenicity island (PAI) required for intramacrophage survival, most of the potential virulence-associated genes identified in R. equi are conserved in environmental rhodococci or have homologs in nonpathogenic Actinobacteria. This suggests a mechanism of virulence evolution based on the cooption of existing core actinobacterial traits, triggered by key host niche–adaptive HGT events. We tested this hypothesis by investigating R. equi virulence plasmid-chromosome crosstalk, by global transcription profiling and expression network analysis. Two chromosomal genes conserved in environmental rhodococci, encoding putative chorismate mutase and anthranilate synthase enzymes involved in aromatic amino acid biosynthesis, were strongly coregulated with vap PAI virulence genes and required for optimal proliferation in macrophages. The regulatory integration of chromosomal metabolic genes under the control of the HGT–acquired plasmid PAI is thus an important element in the cooptive virulence of R. equi

DNA methylation signatures of aggression and closely related constructs : A meta-analysis of epigenome-wide studies across the lifespan

DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 x 10(-7); Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.Peer reviewe

Disease-specific oligodendrocyte lineage cells arise in multiple sclerosis

Multiple sclerosis (MS) is characterized by an immune system attack targeting myelin, which is produced by oligodendrocytes (OLs). We performed single-cell transcriptomic analysis of OL lineage cells from the spinal cord of mice induced with experimental autoimmune encephalomyelitis (EAE), which mimics several aspects of MS. We found unique OLs and OL precursor cells (OPCs) in EAE and uncovered several genes specifically alternatively spliced in these cells. Surprisingly, EAE-specific OL lineage populations expressed genes involved in antigen processing and presentation via major histocompatibility complex class I and II (MHC-I and -II), and in immunoprotection, suggesting alternative functions of these cells in a disease context. Importantly, we found that disease-specific oligodendroglia are also present in human MS brains and that a substantial number of genes known to be susceptibility genes for MS, so far mainly associated with immune cells, are expressed in the OL lineage cells. Finally, we demonstrate that OPCs can phagocytose and that MHC-II-expressing OPCs can activate memory and effector CD4-positive T cells. Our results suggest that OLs and OPCs are not passive targets but instead active immunomodulators in MS. The disease-specific OL lineage cells, for which we identify several biomarkers, may represent novel direct targets for immunomodulatory therapeutic approaches in MS