An integrative analysis of DNA methylation and RNA-Seq data for human heart, kidney and liver

<p>Abstract</p> <p>Background</p> <p>Many groups, including our own, have proposed the use of DNA methylation profiles as biomarkers for various disease states. While much research has been done identifying DNA methylation signatures in cancer vs. normal etc., we still lack sufficient knowledge of the role that differential methylation plays during normal cellular differentiation and tissue specification. We also need thorough, genome level studies to determine the meaning of methylation of individual CpG dinucleotides in terms of gene expression.</p> <p>Results</p> <p>In this study, we have used (insert statistical method here) to compile unique DNA methylation signatures from normal human heart, lung, and kidney using the Illumina Infinium 27 K methylation arraysand compared those to gene expression by RNA sequencing. We have identified unique signatures of global DNA methylation for human heart, kidney and liver, and showed that DNA methylation data can be used to correctly classify various tissues. It indicates that DNA methylation reflects tissue specificity and may play an important role in tissue differentiation. The integrative analysis of methylation and RNA-Seq data showed that gene methylation and its transcriptional levels were comprehensively correlated. The location of methylation markers in terms of distance to transcription start site and CpG island showed no effects on the regulation of gene expression by DNA methylation in normal tissues.</p> <p>Conclusions</p> <p>This study showed that an integrative analysis of methylation array and RNA-Seq data can be utilized to discover the global regulation of gene expression by DNA methylation and suggests that DNA methylation plays an important role in normal tissue differentiation via modulation of gene expression.</p

Evaluation of macrophage plasticity in brown and white adipose tissue

There are still questions about whether macrophage differentiation is predetermined or is induced in response to tissue microenvironments. C2D macrophage cells reside early in the macrophage lineage in vitro, but differentiate to a more mature phenotype after adoptive transfer to the peritoneal cavity (PEC-C2D). Since C2D macrophage cells also traffic to adipose tissue after adoptive transfer, we explored the impact of white adipose tissue (WAT), brown adipose tissue (BAT) and in vitro cultured adipocytes on C2D macrophage cells. When PEC-C2D macrophage cells were cultured with preadipocytes the cells stretched out and CD11b and Mac-2 expression was lower compared to PEC-C2D macrophage cells placed in vitro alone. In contrast, PEC-C2D cells co-cultured with adipocytes maintained smaller, round morphology and more cells expressed Mac-2 compared to PEC-C2D co-cultured with preadipocytes. After intraperitoneal injection, C2D macrophage cells migrated into both WAT and BAT. A higher percentage of C2D macrophage cells isolated from WAT (WAT-C2D) expressed Ly-6C (33%), CD11b (11%), Mac-2 (11%) and F4/80 (29%) compared to C2D macrophage cells isolated from BAT (BAT-C2D). Overall, BAT-C2D macrophage cells had reduced expression of many cytokine, chemokine and receptor gene transcripts when compared to in vitro grown C2D macrophages, while WAT-C2D macrophage cells and PEC-C2D up-regulated many of these gene transcripts. These data suggest that the C2D macrophage phenotype can change rapidly and distinct phenotypes are induced by different microenvironments

A hidden Markov model-based algorithm for identifying tumour subtype using array CGH data

<p>Abstract</p> <p>Background</p> <p>The recent advancement in array CGH (aCGH) research has significantly improved tumor identification using DNA copy number data. A number of unsupervised learning methods have been proposed for clustering aCGH samples. Two of the major challenges for developing aCGH sample clustering are the high spatial correlation between aCGH markers and the low computing efficiency. A mixture hidden Markov model based algorithm was developed to address these two challenges.</p> <p>Results</p> <p>The hidden Markov model (HMM) was used to model the spatial correlation between aCGH markers. A fast clustering algorithm was implemented and real data analysis on glioma aCGH data has shown that it converges to the optimal cluster rapidly and the computation time is proportional to the sample size. Simulation results showed that this HMM based clustering (HMMC) method has a substantially lower error rate than NMF clustering. The HMMC results for glioma data were significantly associated with clinical outcomes.</p> <p>Conclusions</p> <p>We have developed a fast clustering algorithm to identify tumor subtypes based on DNA copy number aberrations. The performance of the proposed HMMC method has been evaluated using both simulated and real aCGH data. The software for HMMC in both R and C++ is available in ND INBRE website <url>http://ndinbre.org/programs/bioinformatics.php.</url></p

Intracellular trafficking and secretion of adiponectin is dependent on GGA coated vesicles

Adiponectin (Acrp30) is an insulin-sensitizing hormone produced and secreted exclusively by adipose tissue. Confocal fluorescent microscopy demonstrated the colocalization of adiponectin with the Golgi membrane markers p115, β-COP, and the trans-Golgi network marker, syntaxin 6. Treatment of cells with brefeldin A redistributed adiponectin to the endoplasmic reticulum where it colocalized with the chaperone protein BIP and inhibited secretion of adiponectin demonstrating a requirement for a functional Golgi apparatus for adiponectin release. Confocal fluorescent microscopy also demonstrated a colocalization of endogenous adiponectin with that of expressed GGA1myc (Golgi-localizing γ-adaptin ear homology ARF-binding protein) but with no significant overlap between adiponectin and the GGA2myc or GGA3myc isoforms. Consistent with confocal fluorescent microscopy, transmission electron microscopy demonstrated the colocalization of GGA1 with adiponectin. Although GGA1 did not directly interact with the adiponectin protein, the adiponectin enriched membrane compartments of adipocyte were precipitated by a GST-GGA1 cargo binding domain (VHS) fusion protein but not with a GST-GGA2 VHS or GST-GGA3 VHS fusion proteins. Moreover, co-expression of adiponectin with a GGA1 dominant-interfering mutant (GGA1-VHS GAT domain) resulted in a marked inhibition of adiponectin secretion in both 3T3L1 adipocytes and HEK293 cells, whereas no inhibition was detected with the truncated mutants GGA2-VHSGAT or GGA3-VHSGAT. Moreover, co-expression of wild type GGA1 with adiponectin enhanced secretion of adiponectin. Interestingly, leptin secretion was unaffected by neither the wild type form or GGA1 mutant. Taken together these data demonstrate that the trafficking of adiponectin through its secretory pathway is dependent on GGA-coated vesicles

The influence of cultural attitudes to nut exposure on reported nut allergy: A pilot cross sectional study

Food allergies in children have become a common management and diagnostic concern and have a significant influence on general health-related quality of life. We investigated the prevalence of reported nut allergy between populations with different cultural attitudes to nuts during pregnancy and infancy. We conducted a survey to investigate the relationship between cultural differences in the consumption of nuts during pregnancy, breastfeeding and exposure to nuts in early childhood against the reported prevalence of nut allergy between three populations: Libyan, UK Libyan and a general UK population. The survey was administered to a representative sample of UK and Libyan parents with children aged between 3 and 16 years who were asked to report prevalence of nut allergy and to describe the factors that might affect this such as cultural behaviours and diet. A total of 1,123 parents responded. Nut allergy was defined as an allergic reaction that required medical treatment. The reported rates of nut allergy showed a significant difference in nut allergy between the Libyan populations and the general UK population with an increased odds ratio of nut allergy of ~10 when comparing the Native Libyan population to the UK population. The UK Libyan population reported the same low rate of allergic reactions as the Libyan population which were both significantly lower than the UK population (p < .0001). The Libyan populations showed significant differences from the UK population in exposure to nuts during pregnancy, breastfeeding and early infancy. The development of peanut and almond allergy through tolerance induction could be prevented by frequent and early ingestion of a moderate quantity of nuts during infancy and by maternal ingestion during pregnancy or lactation

Maternal Diet Intervention Before Pregnancy Primes Offspring Lipid Metabolism in Liver

Nonalcoholic fatty liver disease (NAFLD) has a developmental origin and is influenced in utero. We aimed to evaluate if maternal diet intervention before pregnancy would be beneficial to reduce the risk of offspring NAFLD. In our study, female mice were either on a normal-fat diet (NF group), or a high-fat diet for 12 weeks and continued on this diet throughout pregnancy and lactation (HF group), or switched from HF-to-NF diet 1 week (H1N group), or 9 weeks (H9N group) before pregnancy. Compared with the NF offspring, the H1N and HF, but not the H9N offspring, displayed more severe hepatic steatosis and glucose intolerance. More specifically, an abnormal blood lipid panel was seen in the H1N offspring and abnormal hepatic free fatty acid composition was present in both the HF and H1N offspring, while the H9N offspring displayed both at normal levels. These physiological changes were associated with desensitized hepatic insulin/AKT signaling, increased expression of genes and proteins for de novo lipogenesis and cholesterol synthesis, decreased expression of genes and proteins for fatty acid oxidation, increased Pcsk9 expression, and hypoactivation of 5' AMP-activated protein kinase (AMPK) signaling in the HF and H1N offspring. However, these effects were completely or partially rescued in the H9N offspring. In summary, we found that early maternal diet intervention is effective in reducing the risk of offspring NAFLD caused by maternal HF diet. These findings provide significant support to develop effective diet intervention strategies and policies for prevention of obesity and NAFLD to promote optimal health outcomes for mothers and children

Effects of prenatal low protein and postnatal high fat diets on visceral adipose tissue macrophage phenotypes and IL-6 expression in Sprague Dawley rat offspring

Adipose tissue macrophages (ATM) are implicated in adipose tissue inflammation and obesity-related insulin resistance. Maternal low protein models result in fetal programming of obesity. The study aims to answer whether maternal undernutrition by protein restriction affects the ATM M1 or M2 phenotype under postnatal high fat diet in F1 offspring. Using a rat model of prenatal low protein (LP, 8% protein) diet followed by a postnatal high fat energy diet (HE, 45% fat) or low fat normal energy diet (NE, 10% fat) for 12 weeks, we investigated the effects of these diets on adiposity, programming of the offspring ATM phenotype, and the associated inflammatory response in adipose tissue. Fat mass in newborn and 12-week old LP fed offspring was lower than that of normal protein (20%; NP) fed offspring; however, the adipose tissue growth rate was higher compared to the NP fed offspring. While LP did not affect the number of CD68+ or CD206+ cells in adipose tissue of NE offspring, it attenuated the number of these cells in offspring fed HE. In offspring fed HE, LP offspring had a lower percentage of CD11c+CD206+ ATMs, whose abundancy was correlated with the size of the adipocytes. Noteworthy, similar to HE treatment, LP increased gene expression of IL-6 within ATMs. Two-way ANOVA showed an interaction of prenatal LP and postnatal HE on IL-6 and IL-1β transcription. Overall, both LP and HE diets impact ATM phenotype by affecting the ratio of CD11c+CD206+ ATMs and the expression of IL-6

Overexpression of IL-10 in C2D macrophages promotes a macrophage phenotypic switch in adipose tissue environments

Adipose tissue macrophages are a heterogeneous collection of classically activated (M1) and alternatively activated (M2) macrophages. Interleukin 10 (IL-10) is an anti-inflammatory cytokine, secreted by a variety of cell types including M2 macrophages. We generated a macrophage cell line stably overexpressing IL-10 (C2D-IL10) and analyzed the C2D-IL10 cells for several macrophage markers after exposure to adipocytes compared to C2D cells transfected with an empty vector (C2D-vector). C2D-IL10 macrophage cells expressed more CD206 when co-cultured with adipocytes than C2D-vector cells; while the co-cultured cell mixture also expressed higher levels of Il4, Il10, Il1β and Tnf. Since regular C2D cells traffic to adipose tissue after adoptive transfer, we explored the impact of constitutive IL-10 expression on C2D-IL10 macrophages in adipose tissue in vivo. Adipose tissue-isolated C2D-IL10 cells increased the percentage of CD206+, CD301+, CD11c−CD206+ (M2) and CD11c+CD206+ (M1b) on their cell surface, compared to isolated C2D-vector cells. These data suggest that the expression of IL-10 remains stable, alters the C2D-IL10 macrophage cell surface phenotype and may play a role in regulating macrophage interactions with the adipose tissue

Label-free spatially maintained measurements of metabolic phenotypes in cells

Metabolic reprogramming at a cellular level contributes to many diseases including cancer, yet few assays are capable of measuring metabolic pathway usage by individual cells within living samples. Here, autofluorescence lifetime imaging is combined with single-cell segmentation and machine-learning models to predict the metabolic pathway usage of cancer cells. The metabolic activities of MCF7 breast cancer cells and HepG2 liver cancer cells were controlled by growing the cells in culture media with specific substrates and metabolic inhibitors. Fluorescence lifetime images of two endogenous metabolic coenzymes, reduced nicotinamide adenine dinucleotide (NADH) and oxidized flavin adenine dinucleotide (FAD), were acquired by a multi-photon fluorescence lifetime microscope and analyzed at the cellular level. Quantitative changes of NADH and FAD lifetime components were observed for cells using glycolysis, oxidative phosphorylation, and glutaminolysis. Conventional machine learning models trained with the autofluorescence features classified cells as dependent on glycolytic or oxidative metabolism with 90%–92% accuracy. Furthermore, adapting convolutional neural networks to predict cancer cell metabolic perturbations from the autofluorescence lifetime images provided improved performance, 95% accuracy, over traditional models trained via extracted features. Additionally, the model trained with the lifetime features of cancer cells could be transferred to autofluorescence lifetime images of T cells, with a prediction that 80% of activated T cells were glycolytic, and 97% of quiescent T cells were oxidative. In summary, autofluorescence lifetime imaging combined with machine learning models can detect metabolic perturbations between glycolysis and oxidative metabolism of living samples at a cellular level, providing a label-free technology to study cellular metabolism and metabolic heterogeneity

Understanding adipokine secretion and adipocyte-macrophage cellular interactions, in search for the molecular basis of insulin sensitivity and resistance

Doctor of PhilosophyDepartment of BiologyStephen K. ChapesSilvia Mora FayosMy work focused on understanding adipocyte function and regulation because of the importance to diabetes. In addition to being a fat storage depot, adipose tissue is an endocrine tissue. Adiponectin and leptin are two adipokines that control insulin sensitivity and energy balance. In spite of their importance, there are still questions about their secretion. I hypothesized that leptin and adiponectin follow different secretory routes. I found adiponectin localized in Golgi and the trans Golgi Network, while leptin mostly localized in ER during basal metabolisms. Common requirements for their secretion were the presence of class III Arf proteins and an intact Golgi apparatus, since BFA treatment inhibited secretion of both adiponectin and leptin. I found that trafficking of adiponectin is dependent on GGA1 coated vesicles. Endosomal inactivation significantly reduced adiponectin, but not leptin, secretion in both 3T3L1 and isolated rat adipocytes. Also, adiponectin, but not leptin, secretion was reduced in cells expressing non- functional form of Rab11 and Rab5 proteins. However, secretion of leptin, but not adiponectin was inhibited in cells expressing mutants of Protein Kinase D1. These results suggest that leptin and adiponectin secretion involve distinct intracellular compartments and pathways. Insulin resistance is associated with macrophage infiltration into adipose tissue and elevated levels of IL-6, TNF-alpha and IL-1beta Therefore, the second part of my dissertation tested the hypothesis that the interaction of macrophages and adipocytes causes insulin resistance. To test this hypothesis, I co-cultured macrophages and adipocytes. I found that mouse elicited peritoneal macrophages significantly decreased insulin-stimulated GLUT4 translocation to the plasma membrane in a contact-independent manner. IL-6 was the most inhibitory cytokine in reducing GLUT4 translocation, GLUT4 expression, Akt phsphorylation and reducing adipocyte differentiation compared to TNF-alpha and IL-1beta. These data suggest that IL-6 is the most effective cytokine secreted by macrophages involved in insulin resistance. Lastly, I tested the impact of adipocytes on macrophage differentiation in vitro and in vivo. I found that C2D macrophages isolated from the peritoneal cavity had increased IL-6 transcript levels after co-culture with 3T3L1 adipocytes in vitro. After i.p. injection, C2D macrophages isolated from WAT increased expression of mature macrophage surface markers and transcript levels of proinflammatory cytokines compared to C2D cells in vitro. However, macrophages isolated from BAT expressed low levels of cytokines and macrophage surface markers