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The thermogenic activity of brown adipose tissue (BAT) and browning of white adipose tissue are important components of energy expenditure. Here we show that GPR120, a receptor for polyunsaturated fatty acids, promotes brown fat activation. Using RNA-seq to analyse mouse BAT transcriptome, we find that the gene encoding GPR120 is induced by thermogenic activation. We further show that GPR120 activation induces BAT activity and promotes the browning of white fat in mice, whereas GRP120-null mice show impaired cold-induced browning. Omega-3 polyunsaturated fatty acids induce brown and beige adipocyte differentiation and thermogenic activation, and these effects require GPR120. GPR120 activation induces the release of fibroblast growth factor-21 (FGF21) by brown and beige adipocytes, and increases blood FGF21 levels. The effects of GPR120 activation on BAT activation and browning are impaired in FGF21-null mice and cells. Thus, the lipid sensor GPR120 activates brown fat via a mechanism that involves induction of FGF21. GPR120 is a G-protein-coupled receptor that binds polyunsaturated fatty acids. Here, the authors show that GPR120 is upregulated in brown fat in cold-exposed mice, and mediates thermogenic activation of brown fat via a mechanism that, at least in part, depends on the release of the adipokine FGF21.

Alteration of epigenetic modifications plays an important role in human cancer. Notably, the dysregulation of histone post-translational modifications (PTMs) has been associated with several cancers including colorectal cancer (CRC). However, the signature of histone PTMs on circulating nucleosomes is still not well described. We have developed a fast and robust enrichment method to isolate circulating nucleosomes from plasma for further downstream proteomic analysis. This method enabled us to quantify the global alterations of histone PTMs from 9 CRC patients and 9 healthy donors. Among 54 histone proteoforms identified and quantified in plasma samples, 13 histone PTMs were distinctive in CRC. Notably, methylation of histone H3K9 and H3K27, acetylation of histone H3 and citrullination of histone H2A1R3 were upregulated in plasma of CRC patients. A comparative analysis of paired samples identified 3 common histone PTMs in plasma and tumor tissue including the methylation and acetylation state of lysine 27 of histone H3. Moreover, we highlight for the first time that histone H2A1R3 citrulline is a modification upregulated in CRC patients. This new method presented herein allows the detection and quantification of histone variants and histone PTMs from circulating nucleosomes in plasma samples and could be used for biomarker discovery of cancer.

Interferon-α (IFNα), a type I interferon, is expressed in the islets of type 1 diabetic individuals, and its expression and signaling are regulated by T1D genetic risk variants and viral infections associated with T1D. We presently characterize human beta cell responses to IFNα by combining ATAC-seq, RNA-seq and proteomics assays. The initial response to IFNα is characterized by chromatin remodeling, followed by changes in transcriptional and translational regulation. IFNα induces changes in alternative splicing (AS) and first exon usage, increasing the diversity of transcripts expressed by the beta cells. This, combined with changes observed on protein modification/degradation, ER stress and MHC class I, may expand antigens presented by beta cells to the immune system. Beta cells also up-regulate the checkpoint proteins PDL1 and HLA-E that may exert a protective role against the autoimmune assault. Data mining of the present multi-omics analysis identifies two compound classes that antagonize IFNα effects on human beta cells. The cytokine IFNα is expressed in the islets of individuals with type 1 diabetes and contributes to local inflammation and destruction of beta cells. Here, the authors provide a global multiomics view of IFNα-induced changes in human beta cells at the level of chromatin, mRNA and protein expression.

Background Altered circulating cell-free DNA (cfDNA) fragmentation patterns serve as cancer biomarkers, yet standard short-read sequencing fails to capture the full fragment-length spectrum. Although cancer patients often exhibit elevated cfDNA, the relationship between high cfDNA concentration and altered fragmentation remains poorly defined. To address this question, we leverage Oxford Nanopore (ONT) sequencing, which captures the full fragment-length spectrum and enables cell type inference via DNA methylation markers. Results We perform ONT whole-genome sequencing on a pan-cancer cohort and a neuroendocrine cancer cohort, both with elevated cfDNA levels. In both cohorts, the highest cfDNA levels are characterized by either hypofragmentation or hyperfragmentation. Hypofragmented samples (characterized by 1–4 kb fragments) exhibit hallmarks of DNASE1L3-mediated fragmentation due to blood-derived DNA release during delayed blood processing, while samples with ultra-long fragments (> 7.5 kb) indicate release due to cell lysis during plasma processing. In contrast, the short (<145 bp) fragments of hyperfragmented cancer samples are not artifactual, and they are characterized by elevated levels of both cancer- and blood-derived DNA, suggesting an inflammatory or other systemic response as opposed to a cancer-specific fragmentation mechanism. Conclusions These findings differentiate biological from artifactual fragmentation, broaden our understanding of high cfDNA levels and hyperfragmentation in cancer, and establish long-read sequencing as a robust tool for biomarker discovery.

Hematopoietic malignancies are extremely common in pet dogs and represent nearly 30% of the malignancies diagnosed in this population each year. Clinicians commonly use existing tools such as physical exam findings, radiographs, ultrasound and baseline blood work to monitor these patients for treatment response and remission. Circulating biomarkers, such as prostate specific antigen or carcinoembryonic antigen, can be useful tools for monitoring treatment response and remission status in human cancer patients. To date, there has a been a lack of useful circulating biomarkers available to veterinary oncology patients. Circulating plasma nucleosome concentrations were evaluated at diagnosis, throughout treatment and during remission monitoring for 40 dogs with lymphoma, acute myelogenous leukemia and multiple myeloma. Additionally, C-reactive protein and thymidine kinase-1 levels were recorded. Plasma nucleosome concentrations were significantly higher at diagnosis and progressive disease than they were when dogs were in remission. All but two dogs had plasma nucleosome concentrations that returned to the low range during treatment. These two dogs had the shortest progression free and overall survival times. Dogs with the highest plasma nucleosome concentrations had a significantly shorter first progression free survival than dogs with lower plasma nucleosome concentrations at diagnosis. Plasma nucleosome concentrations correlated better with disease response and progression than either thymidine kinase or C reactive protein. Plasma nucleosome concentrations can be a useful tool for treatment monitoring and disease progression in dogs with hematopoietic malignancies.

There are presently no reliable ways to quantify endocrine cell mass (ECM) in vivo , which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. To address this unmet need, we coupled RNA sequencing of human pancreatic islets to a systems biology approach to identify new biomarkers of the endocrine pancreas. Dipeptidyl-Peptidase 6 (DPP6) was identified as a target whose mRNA expression is at least 25-fold higher in human pancreatic islets as compared to surrounding tissues and is not changed by proinflammatory cytokines. At the protein level, DPP6 localizes only in beta and alpha cells within the pancreas. We next generated a high-affinity camelid single-domain antibody (nanobody) targeting human DPP6. The nanobody was radiolabelled and in vivo SPECT/CT imaging and biodistribution studies were performed in immunodeficient mice that were either transplanted with DPP6-expressing Kelly neuroblastoma cells or insulin-producing human EndoC-βH1 cells. The human DPP6-expressing cells were clearly visualized in both models. In conclusion, we have identified a novel beta and alpha cell biomarker and developed a tracer for in vivo imaging of human insulin secreting cells. This provides a useful tool to non-invasively follow up intramuscularly implanted insulin secreting cells.

The autoimmune-mediated beta-cell death in type 1 diabetes (T1DM) is associated with local inflammation (insulitis). We examined the role of MCPIP1 (monocyte chemotactic protein–induced protein 1), a novel cytokine-induced antiinflammatory protein, in this process. Basal MCPIP1 expression was lower in rat vs. human islets and beta-cells. Proinflammatory cytokines stimulated MCPIP1 expression in rat and human islets and in insulin-secreting cells. Moderate overexpression of MCPIP1 protected insulin-secreting INS1E cells against cytokine toxicity by a mechanism dependent on the presence of the PIN/DUB domain in MCPIP1. It also reduced cytokine-induced Chop and C/ebpβ expression and maintained MCL-1 expression. The shRNA-mediated suppression of MCPIP1 led to the potentiation of cytokine-mediated NFκB activation and cytokine toxicity in human EndoC-βH1 beta-cells. MCPIP1 expression was very high in infiltrated beta-cells before and after diabetes manifestation in the LEW.1AR1-iddm rat model of human T1DM. The extremely high expression of MCPIP1 in clonal beta-cells was associated with a failure of the regulatory feedback-loop mechanism, ER stress induction and high cytokine toxicity. In conclusion, our data indicate that the expression level of MCPIP1 affects the susceptibility of insulin-secreting cells to cytokines and regulates the mechanism of beta-cell death in T1DM.

Background Identification of islet β cell death prior to the onset of type 1 diabetes (T1D) or type 2 diabetes (T2D) might allow for interventions to protect β cells and reduce diabetes risk. Circulating unmethylated DNA fragments arising from the human INS gene have been proposed as biomarkers of β cell death, but this gene alone may not be sufficiently specific to report β cell death. Results To identify new candidate genes whose CpG sites may show greater specificity for β cells, we performed unbiased DNA methylation analysis using the Infinium HumanMethylation 450 array on 64 human islet preparations and 27 non-islet human tissues. For verification of array results, bisulfite DNA sequencing of human β cells and 11 non-β cell tissues was performed on 5 of the top 10 CpG sites that were found to be differentially methylated. We identified the CHTOP gene as a candidate whose CpGs show a greater frequency of unmethylation in human islets. A digital PCR strategy was used to determine the methylation pattern of CHTOP and INS CpG sites in primary human tissues. Although both INS and CHTOP contained unmethylated CpG sites in non-islet tissues, they occurred in a non-overlapping pattern. Based on Naïve Bayes classifier analysis, the two genes together report 100% specificity for islet damage. Digital PCR was then performed on cell-free DNA from serum from human subjects. Compared to healthy controls ( N = 10), differentially methylated CHTOP and INS levels were higher in youth with new onset T1D ( N = 43) and, unexpectedly, in healthy autoantibody-negative youth who have first-degree relatives with T1D ( N = 23). When tested in lean ( N = 32) and obese ( N = 118) youth, increased levels of unmethylated INS and CHTOP were observed in obese individuals. Conclusion Our data suggest that concurrent measurement of circulating unmethylated INS and CHTOP has the potential to detect islet death in youth at risk for both T1D and T2D. Our data also support the use of multiple parameters to increase the confidence of detecting islet damage in individuals at risk for developing diabetes.

The early stages of type 1 diabetes (T1D) are characterized by local autoimmune inflammation and progressive loss of insulin-producing pancreatic β cells. Here we show that exposure to proinflammatory cytokines reveals a marked plasticity of the β-cell regulatory landscape. We expand the repertoire of human islet regulatory elements by mapping stimulus-responsive enhancers linked to changes in the β-cell transcriptome, proteome and three-dimensional chromatin structure. Our data indicate that the β-cell response to cytokines is mediated by the induction of new regulatory regions as well as the activation of primed regulatory elements prebound by islet-specific transcription factors. We find that T1D-associated loci are enriched with newly mapped cis -regulatory regions and identify T1D-associated variants disrupting cytokine-responsive enhancer activity in human β cells. Our study illustrates how β cells respond to a proinflammatory environment and implicate a role for stimulus response islet enhancers in T1D. Cytokine-induced regulatory changes in human pancreatic islets illustrate the β-cell chromatin dynamics in response to a proinflammatory environment and implicate a role for islet enhancers in type 1 diabetes.

This protocol shows how to detect putative cis -regulatory elements and regions enriched in such elements with the regulatory sequence analysis tools (RSAT) web server ( http://rsat.ulb.ac.be/rsat/ ). The approach applies to known transcription factors, whose binding specificity is represented by position-specific scoring matrices, using the program matrix-scan . The detection of individual binding sites is known to return many false predictions. However, results can be strongly improved by estimating P value, and by searching for combinations of sites (homotypic and heterotypic models). We illustrate the detection of sites and enriched regions with a study case, the upstream sequence of the Drosophila melanogaster gene even-skipped . This protocol is also tested on random control sequences to evaluate the reliability of the predictions. Each task requires a few minutes of computation time on the server. The complete protocol can be executed in about one hour.