Mouse models of the GM2 gangliosidoses [Tay-Sachs, late onset Tay-Sachs (LOTS), Sandhoff] and GM1 gangliosidosis have been studied to determine whether there is a common neuro-inflammatory component to these disorders. During the disease course, we have: (i) examined the expression of a number of inflammatory markers in the CNS, including MHC class II, CD68, CD11b (CR3), 7/4, F4/80, nitrotyrosine, CD4 and CD8; (ii) profiled cytokine production [tumour necrosis factor alpha (TNF alpha), transforming growth factor (TGF beta 1) and interleukin 1 beta (IL1 beta)]; and (iii) studied blood-brain barrier (BBB) integrity. The kinetics of apoptosis and the expression of Fas and TNF-R1 were also assessed. In all symptomatic mouse models, a progressive increase in local microglial activation/expansion and infiltration of inflammatory cells was noted. Altered BBB permeability was evident in Sandhoff and GM1 mice, but absent in LOTS mice. Progressive CNS inflammation coincided with the onset of clinical signs in these mouse models. Substrate reduction therapy in the Sandhoff mouse model slowed the rate of accumulation of glycosphingolipids in the CNS, thus delaying the onset of the inflammatory process and disease pathogenesis. These data suggest that inflammation may play an important role in the pathogenesis of the gangliosidoses.

Oxidative stress is a central part of innate-immune induced neurodegeneration. However, the transcriptomic landscape of the central nervous system (CNS) innate immune cells contributing to oxidative stress is unknown, and therapies to target their neurotoxic functions are not widely available. Here, we provide the oxidative stress innate immune cell atlas in neuroinflammatory disease, and report the discovery of new druggable pathways. Transcriptional profiling of oxidative stress-producing CNS innate immune cells (Tox-seq) identified a core oxidative stress gene signature coupled to coagulation and glutathione pathway genes shared between a microglia cluster and infiltrating macrophages. Tox-seq followed by a microglia high-throughput screen (HTS) and oxidative stress gene network analysis, identified the glutathione regulating compound acivicin with potent therapeutic effects decreasing oxidative stress and axonal damage in chronic and relapsing multiple sclerosis (MS) models. Thus, oxidative stress transcriptomics identified neurotoxic CNS innate immune populations and may enable the discovery of selective neuroprotective strategies.

BackgroundBenzene, an established cause of acute myeloid leukemia (AML), may also cause one or more lymphoid malignancies in humans. Previously, we identified genes and pathways associated with exposure to high (> 10 ppm) levels of benzene through transcriptomic analyses of blood cells from a small number of occupationally exposed workers.ObjectivesThe goals of this study were to identify potential biomarkers of benzene exposure and/or early effects and to elucidate mechanisms relevant to risk of hematotoxicity, leukemia, and lymphoid malignancy in occupationally exposed individuals, many of whom were exposed to benzene levels < 1 ppm, the current U.S. occupational standard.MethodsWe analyzed global gene expression in the peripheral blood mononuclear cells of 125 workers exposed to benzene levels ranging from < 1 ppm to > 10 ppm. Study design and analysis with a mixed-effects model minimized potential confounding and experimental variability.ResultsWe observed highly significant widespread perturbation of gene expression at all exposure levels. The AML pathway was among the pathways most significantly associated with benzene exposure. Immune response pathways were associated with most exposure levels, potentially providing biological plausibility for an association between lymphoma and benzene exposure. We identified a 16-gene expression signature associated with all levels of benzene exposure.ConclusionsOur findings suggest that chronic benzene exposure, even at levels below the current U.S. occupational standard, perturbs many genes, biological processes, and pathways. These findings expand our understanding of the mechanisms by which benzene may induce hematotoxicity, leukemia, and lymphoma and reveal relevant potential biomarkers associated with a range of exposures.

Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in eleven anatomically-defined regions of the developing human telencephalon, including upper and deep layers of the prefrontal cortex. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These region-specific predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across regions and developmental stages and harbor distinct sequence motifs that suggest potential upstream regulators of regional and temporal transcription. We leverage this atlas to identify regulators of genes associated with autism spectrum disorder (ASD) including an enhancer of BCL11A , validated in mouse, and two functional de novo mutations in individuals with ASD in an enhancer of SLC6A1 , validated in neuroblastoma cells. These applications demonstrate the utility of this atlas for decoding neurodevelopmental gene regulation in health and disease.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an important tool for studying gene regulatory proteins, such as transcription factors and histones. Peak calling is one of the first steps in the analysis of these data. Peak calling consists of two sub-problems: identifying candidate peaks and testing candidate peaks for statistical significance. We surveyed 30 methods and identified 12 features of the two sub-problems that distinguish methods from each other. We picked six methods GEM, MACS2, MUSIC, BCP, Threshold-based method (TM) and ZINBA] that span this feature space and used a combination of 300 simulated ChIP-seq data sets, 3 real data sets and mathematical analyses to identify features of methods that allow some to perform better than the others. We prove that methods that explicitly combine the signals from ChIP and input samples are less powerful than methods that do not. Methods that use windows of different sizes are more powerful than the ones that do not. For statistical testing of candidate peaks, methods that use a Poisson test to rank their candidate peaks are more powerful than those that use a Binomial test. BCP and MACS2 have the best operating characteristics on simulated transcription factor binding data. GEM has the highest fraction of the top 500 peaks containing the binding motif of the immunoprecipitated factor, with 50% of its peaks within 10 base pairs of a motif. BCP and MUSIC perform best on histone data. These findings provide guidance and rationale for selecting the best peak caller for a given application.

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical–molecular–biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics.

Microglial surveillance is a key feature of brain physiology and disease. We found that Gi-dependent microglial dynamics prevent neuronal network hyperexcitability. By generating Mg PTX mice to genetically inhibit Gi in microglia, we showed that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony upon physiologically evoked neuronal activity in awake adult mice. Thus, Gi-dependent microglia dynamics may prevent hyperexcitability in neurological diseases.

Highlights d Integrated scRNA-, ATAC-, and ChIP-seq analyses to interrogate cardiac reprogramming d Gata4, Mef2c, and Tbx5 both facilitate and limit one another's ability to bind to DNA d Mef2c and Tbx5 bind to inaccessible chromatin and promote its remodeling d Context-specific cooperative mechanisms guide cardiac reprogramming