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Chronic high-fat feeding triggers widespread metabolic dysfunction including obesity, insulin resistance, and diabetes. While these ultimate pathological states are relatively well understood, we have a limited understanding of how high-fat intake first triggers physiological changes. Here, we identify an acute microglial metabolic response that rapidly translates intake of high-fat diet (HFD) to a surprisingly beneficial effect on spatial and learning memory. Acute high-fat intake increases palmitate levels in cerebrospinal fluid and triggers a wave of microglial metabolic activation characterized by mitochondrial membrane activation, fission and metabolic skewing towards aerobic glycolysis. These effects are generalized, detectable in the hypothalamus, hippocampus, and cortex all within 1-3 days of HFD exposure. In vivo microglial ablation and conditional DRP1 deletion experiments show that the microglial metabolic response is necessary for the acute effects of HFD.13C-tracing experiments reveal that in addition to processing via β-oxidation, microglia shunt a substantial fraction of palmitate towards anaplerosis and re-release of bioenergetic carbons into the extracellular milieu in the form of lactate, glutamate, succinate, and intriguingly, the neuro-protective metabolite itaconate. Together, these data identify microglial cells as a critical nutrient regulatory node in the brain, metabolizing away harmful fatty acids and liberating the same carbons instead as alternate bioenergetic and protective substrates. The data identify a surprisingly beneficial effect of short-term HFD on learning and memory.

SummaryDespite the recent explosion in surveys of cell-type heterogeneity, the mechanisms that specify and stabilize highly related cell subtypes remain poorly understood. Here, focusing initially on exploring quantitative histone mark heterogeneity, we identify two major sub-types of pancreatic β-cells (βHIand βLO). βHIand βLOcells differ in their size, morphology, cytosolic and nuclear ultrastructure, transcriptional output, epigenomes, cell surface marker, and function. Importantly, βHIand βLOcells can be FACS separated live into CD24+(βHI) and CD24-(βLO) fractions. From an epigenetic viewpoint, βHI-cells exhibit ∼4-fold higher levels of H3K27me3, more compacted chromatin, and distinct chromatin organization that associates with a specific pattern of transcriptional output. Functionally, βHIcells have increased mitochondrial mass, activity, and insulin secretion bothin vivoandex vivo. Critically,EedandJmjd3loss-of-function studies demonstrate that H3K27me3 dosage is a significant regulator of βHI/ βLOcell ratioin vivo,yielding some of the first-ever specific models of β-cell sub-type distortion. βHIand βLOsub-types are conserved in humans with βHI-cells enriched in human Type-2 diabetes. These data identify two novel and fundamentally distinct β-cell subtypes and identify epigenetic dosage as a novel regulator of β-cell subtype specification and heterogeneity.HighlightsQuantitative H3K27me3 heterogeneity reveals 2 common β-cell subtypesβHIand βLOcells are stably distinct by 7 independent sets of parametersH3K27me3 dosage controls βHI/ βLOratio in vivoβHIand βLOcells are conserved in humans and enriched in Type-2 diabetes

PIWI-interacting RNAs (piRNAs) are small noncoding RNAs that silence transposons in the animal germline. PiRNAs are produced from long single-stranded non-coding transcripts, from protein-coding transcripts, as well as from transposons. While some sites that produce piRNAs are in deeply conserved syntenic regions, in general, piRNAs and piRNA-producing loci turnover faster than other functional parts of the genome. To learn about the sequence changes that contribute to the fast evolution of piRNAs, we set out to analyse piRNA expression between genetically different mice. Here we report the sequencing and analysis of small RNAs from the mouse male germline of four classical inbred strains, one inbred wild-derived strain and one outbred strain. We find that genetic differences between individuals underlie variation in piRNA expression. We report significant differences in piRNA production at loci with endogenous retrovirus insertions. Strain-specific piRNA-producing loci include protein-coding genes. Our findings provide evidence that transposable elements contribute to inter-individual differences in expression, and potentially to the fast evolution of piRNA-producing loci in mammals.

Obesity is a complex disease influenced by genetics, epigenetics, the environment, and their interactions. Mature adipocytes represent the major cell type in white adipose tissue. Understanding how adipocytes function and respond to (epi)genetic and environmental signals is essential for identifying the cause(s) of obesity. RNA and chromatin have previously been isolated from adipocytes using enzymatic digestion. In addition, protocols have been developed for nuclear isolation, where purification is achieved by fluorescence-activated cell sorting (FACS) of adipocyte-specific transgenic reporters. One of the greatest challenges to achieving high yield and quality during such protocols is the substantial amount of lipid contained in adipose tissue. The present protocol describes an optimized procedure for isolating mature adipocytes that leverages heptane to separate lipids from the targets of interest (RNA/chromatin). The resulting RNA has high integrity and generates high-quality RNA-seq results. Likewise, the procedure improves nuclei yield rate and generates reproducible ChIP-seq results across samples. Therefore, the current study provides a reliable and universal murine adipocyte isolation protocol suitable for whole-genome transcriptome and epigenome studies.

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. Current barcoding strategies aim to improve assay throughput and scalability but intense sample handling and lack of standardization over cell types, cell numbers and epitopes hinder wide-spread use in the field. Here, we present a barcoding method to enable high-throughput ChIP-seq using common molecular biology techniques. The method, called RELACS (restriction enzyme-based labeling of chromatin in situ) relies on standardized nuclei extraction from any source and employs chromatin cutting and barcoding within intact nuclei. Barcoded nuclei are pooled and processed within the same ChIP reaction, for maximal comparability and workload reduction. The innovative barcoding concept is particularly user-friendly and suitable for implementation to standardized large-scale clinical studies and scarce samples. Aiming to maximize universality and scalability, RELACS can generate ChIP-seq libraries for transcription factors and histone modifications from hundreds of samples within three days., Laura Arrigoni et al. present RELACS, a method enabling high-throughput ChIP-seq which involves barcoding and processing intact nuclei in the same ChIP reaction. The method is useful for broad cell types and epitopes, robust to experimental conditions, and drastically decreases workload.

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. However, sample preparation is still a largely individual and labor-intensive process that hinders assay throughput and comparability. Here, we present a novel method for ultra-parallelized high-throughput ChIP-seq that addresses the aforementioned problems. The method, called RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ), employs barcoding of chromatin within intact nuclei extracted from different sources (e.g. tissues, treatments, time points). Barcoded nuclei are pooled and processed within the same ChIP, for maximal comparability and significant workload reduction. The choice of user-friendly, straightforward, enzymatic steps for chromatin fragmentation and barcoding makes RELACS particularly suitable for implementation large-scale clinical studies and scarce samples. RELACS can generate ChIP-seq libraries from hundreds of samples within three days and with less than 1000 cells per sample.

Summary Tumor-infiltrating regulatory T lymphocytes (Treg) can suppress effector T cells specific for tumor antigens. Deeper molecular definitions of tumor-infiltrating-lymphocytes could thus offer therapeutic opportunities. Transcriptomes of T helper 1 (Th1), Th17, and Treg cells infiltrating colorectal or non-small-cell lung cancers were compared to transcriptomes of the same subsets from normal tissues and validated at the single-cell level. We found that tumor-infiltrating Treg cells were highly suppressive, upregulated several immune-checkpoints, and expressed on the cell surfaces specific signature molecules such as interleukin-1 receptor 2 (IL1R2), programmed death (PD)-1 Ligand1, PD-1 Ligand2, and CCR8 chemokine, which were not previously described on Treg cells. Remarkably, high expression in whole-tumor samples of Treg cell signature genes, such as LAYN, MAGEH1, or CCR8, correlated with poor prognosis. Our findings provide insights into the molecular identity and functions of human tumor-infiltrating Treg cells and define potential targets for tumor immunotherapy., Highlights • Transcriptome analysis performed on tumor-resident CD4+ Th1, Th17, and Treg cells • Tumor-infiltrating Treg cells are defined by the expression of signature genes • Treg-specific signature genes correlate with patients’ survival in both CRC and NSCLC, Tumor-infiltrating regulatory T cells can suppress effector T cells specific for tumor antigens. De Simone et al. (2016) demonstrate that tumor-infiltrating Treg cells display specific gene signatures that were also validated at the single-cell level. These data can contribute to dissect the molecular networks underlying the biology of tumor-infiltrating Treg cells. As part of the IHEC consortium, this study integrates genetic, epigenetic, and transcriptomic profiling in three immune cell types from nearly 200 people to characterize the distinct and cooperative contributions of diverse genomic inputs to transcriptional variation. Explore the Cell Press IHEC webportal at www.cell.com/consortium/IHEC.

Next-generation sequencing approaches, in particular RNA-seq, provide a genome-wide expression profiling allowing the identification of novel and rare transcripts such as long noncoding RNAs (lncRNA). Many RNA-seq studies have now been performed aimed at the characterization of lncRNAs and their possible involvement in cell development and differentiation in different organisms, cell types, and tissues. The adaptive immune system is an extraordinary context for the study of the role of lncRNAs in differentiation. Indeed lncRNAs seem to be key drivers in governing flexibility and plasticity of both CD8+ and CD4+ T cell, together with lineage-specific transcription factors and cytokines, acting as fine-tuners of fate choices in T cell differentiation.We describe here a pipeline for the identification of lncRNAs starting from RNA-Seq raw data.

Next-generation sequencing approaches, in particular RNA-seq, provide a genome-wide expression profiling allowing the identification of novel and rare transcripts such as long noncoding RNAs (lncRNA). Many RNA-seq studies have now been performed aimed at the characterization of lncRNAs and their possible involvement in cell development and differentiation in different organisms, cell types, and tissues. The adaptive immune system is an extraordinary context for the study of the role of lncRNAs in differentiation. Indeed lncRNAs seem to be key drivers in governing flexibility and plasticity of both CD8

RNA-Seq is an approach to transcriptome profiling that uses deep-sequencing technologies to detect and accurately quantify RNA molecules originating from a genome at a given moment in time. In recent years, the advent of RNA-Seq has facilitated genome-wide expression profiling, including the identification of novel and rare transcripts like noncoding RNAs and novel alternative splicing isoforms.Here, we describe the analytical steps required for the identification and characterization of noncoding RNAs starting from RNA-Seq raw samples, with a particular emphasis on long noncoding RNAs (lncRNAs).

The majority of our genome is pervasively transcribed, but not translated into proteins. These highly heterogeneous noncoding transcripts proved to have key cellular functions. One of the major features described for noncoding RNAs is their ability to create tridimensional structures that serve as scaffold, guide, or decoy for proteins and other transcripts. Recent data support the notion of a prominent role of these interactions in the epigenetic modulation of gene expression mediated by chromatin remodelers and histone modifiers that act converging environmental signals to DNA. These epigenetic marks have the peculiarity to be maintained throughout generations, even when the cue is no longer present without altering DNA sequence. Given the key importance of noncoding RNAs (ncRNAs) in cell physiology, therapeutic approaches based on ncRNAs targeting via diverse tools are now under development and offer many advantages over classical protein-targeting therapies. Understanding the basis of ncRNAs’ interaction with the epigenetic machinery is therefore of key interest in order to expand our knowledge on the molecular mechanisms driving epigenetic modifications and to guide the development of novel and more specific therapeutic approaches. Noncoding transcripts not only act within the cell in which they are transcribed but also can be actively or passively released to body fluids where pathological alterations in the expression of noncoding genes can be detected. These pathology-related signatures can be easily exploited as biomarkers for disease onset and progression.

RNA-Seq is an approach to transcriptome profiling that uses deep-sequencing technologies to detect and accurately quantify RNA molecules originating from a genome at a given moment in time. In recent years, the advent of RNA-Seq has facilitated genome-wide expression profiling, including the identification of novel and rare transcripts like noncoding RNAs and novel alternative splicing isoforms.Here, we describe the analytical steps required for the identification and characterization of noncoding RNAs starting from RNA-Seq raw samples, with a particular emphasis on long noncoding RNAs (lncRNAs).

To help better understand the role of long noncoding RNAs in the human immune system, we recently generated a comprehensive RNA-seq data set using 63 RNA samples from 13 subsets of T (CD4+ naive, CD4+ TH1, CD4+ TH2, CD4+ TH17, CD4+ Treg, CD4+ TCM, CD4+ TEM, CD8+ TCM, CD8+ TEM, CD8+ naive) and B (B naive, B memory, B CD5+) lymphocytes. There were five biological replicates for each subset except for CD8+ TCM and B CD5+ populations that included 4 replicates. RNA-Seq data were generated by an Illumina HiScanSQ sequencer using the TruSeq v3 Cluster kit. 2.192 billion of paired-ends reads, 2×100 bp, were sequenced and after filtering a total of about 1.7 billion reads were mapped. Using different de novo transcriptome reconstruction techniques over 500 previously unknown lincRNAs were identified. The current data set could be exploited to drive the functional characterization of lincRNAs, identify novel genes and regulatory networks associated with specific cells subsets of the human immune system.

Long noncoding RNAs are emerging as important regulators of cellular functions, but little is known of their role in the human immune system. Here we investigated long intergenic noncoding RNAs (lincRNAs) in 13 subsets of T lymphocytes and B lymphocytes by next-generation sequencing-based RNA sequencing (RNA-seq analysis) and de novo transcriptome reconstruction. We identified over 500 previously unknown lincRNAs and described lincRNA signatures. Expression of linc-MAF-4, a chromatin-associated lincRNA specific to the TH1 subset of helper T cells, was inversely correlated with expression of MAF, a TH2-associated transcription factor. Downregulation of linc-MAF-4 skewed T cell differentiation toward the TH2 phenotype. We identified a long-distance interaction between the genomic regions of the gene encoding linc-MAF-4 and MAF, where linc-MAF-4 associated with the chromatin modifiers LSD1 and EZH2; this suggested that linc-MAF-4 regulated MAF transcription through the recruitment of chromatin modifiers. Our results demonstrate a key role for lincRNA in T lymphocyte differentiation.

CD4+ T lymphocytes orchestrate adaptive immune responses by differentiating into various subsets of effector T cells such as T-helper 1 (Th1), Th2, Th17, and regulatory T cells. These subsets have been generally described by master transcription factors that dictate the expression of cytokines and receptors, which ultimately define lymphocyte effector functions. However, the view of T-lymphocyte subsets as stable and terminally differentiated lineages has been challenged by increasing evidence of functional plasticity within CD4+ T-cell subsets, which implies flexible programming of effector functions depending on time and space of T-cell activation. An outstanding question with broad basic and traslational implications relates to the mechanisms, besides transcriptional regulation, which define the plasticity of effector functions. In this study, we discuss the emerging role of regulatory non-coding RNAs in T-cell differentiation and plasticity. Not only microRNAs have been proven to be important for CD4+ T-cell differentiation, but it is also likely that the overall T-cell functioning is the result of a multilayered network composed by coding RNAs as well as by short and long non-coding RNAs. The integrated study of all the nodes of this network will provide a comprehensive view of the molecular mechanisms underlying T-cell functions in health and disease. © 2013 John Wiley & Sons A/S.