A Federated Database for Obesity Research: An IMI-SOPHIA Study.

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.

BALDR: A Web-based platform for informed comparison and prioritization of biomarker candidates for type 2 diabetes mellitus.

Novel biomarkers are key to addressing the ongoing pandemic of type 2 diabetes mellitus. While new technologies have improved the potential of identifying such biomarkers, at the same time there is an increasing need for informed prioritization to ensure efficient downstream verification. We have built BALDR, an automated pipeline for biomarker comparison and prioritization in the context of diabetes. BALDR includes protein, gene, and disease data from major public repositories, text-mining data, and human and mouse experimental data from the IMI2 RHAPSODY consortium. These data are provided as easy-to-read figures and tables enabling direct comparison of up to 20 biomarker candidates for diabetes through the public website https://baldr.cpr.ku.dk.

Identification of biomarkers for glycaemic deterioration in type 2 diabetes.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles.

Extracellular vesicles (EV) are membranous particles secreted by all cells and found in body fluids. Established EV contents include a variety of RNA species, proteins, lipids and metabolites that are considered to reflect the physiological status of their parental cells. However, to date, little is known about cell-type enriched EV cargo in complex EV mixtures, especially in urine. To test whether EV secretion from distinct human kidney cells in culture differ and can recapitulate findings in normal urine, we comprehensively analysed EV components, (particularly miRNAs, long RNAs and protein) from conditionally immortalised human kidney cell lines (podocyte, glomerular endothelial, mesangial and proximal tubular cells) and compared to EV secreted in human urine. EV from cell culture media derived from immortalised kidney cells were isolated by hydrostatic filtration dialysis (HFD) and characterised by electron microscopy (EM), nanoparticle tracking analysis (NTA) and Western blotting (WB). RNA was isolated from EV and subjected to miRNA and RNA sequencing and proteins were profiled by tandem mass tag proteomics. Representative sets of EV miRNAs, RNAs and proteins were detected in each cell type and compared to human urinary EV isolates (uEV), EV cargo database, kidney biopsy bulk RNA sequencing and proteomics, and single-cell transcriptomics. This revealed that a high proportion of the in vitro EV signatures were also found in in vivo datasets. Thus, highlighting the robustness of our in vitro model and showing that this approach enables the dissection of cell type specific EV cargo in biofluids and the potential identification of cell-type specific EV biomarkers of kidney disease.

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes.

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.

Vacuolins and myosin VII are required for phagocytic uptake and phagosomal membrane recycling in Dictyostelium discoideum.

Flotillins are lipid raft residents involved in membrane trafficking and recycling of plasma membrane proteins. Dictyostelium discoideum uses phagocytosis to kill, digest and feed on bacteria. It possesses three flotillin-like vacuolins that are strongly associated with membranes and that gradually accumulate on maturing phagosomes. Absence of vacuolins reduced adhesion and particle recognition resulting in a drastic reduction in the uptake of various types of particles. This was caused by a block in the recycling of plasma membrane components and the absence of their specific cortex-associated proteins. In addition, absence of vacuolins also impaired phagolysosome biogenesis, without significantly impacting killing and digestion of a range of bacteria. Strikingly, both absence and overexpression of vacuolins induced a strong downregulation of myosin VII (also known as MyoI) expression, as well as its binding partner talin A. Episomal expression of myosin VII fully rescued defects in uptake and adhesion but not in phagosome maturation. These results suggest a dual role for vacuolins: a novel mechanism involving membrane microdomains and myosin VII-talin A in clustering phagosomal receptors and adhesion molecules at the plasma membrane, and a role in phagolysosomal biogenesis.

Transcriptional Responses of Dictyostelium discoideum Exposed to Different Classes of Bacteria.

Dictyostelium discoideum amoebae feed by ingesting bacteria, then killing them in phagosomes. Ingestion and killing of different bacteria have been shown to rely on largely different molecular mechanisms. One would thus expect that D. discoideum adapts its ingestion and killing machinery when encountering different bacteria. In this study, we investigated by RNA sequencing if and how D. discoideum amoebae respond to the presence of different bacteria by modifying their gene expression patterns. Each bacterial species analyzed induced a specific modification of the transcriptome. Bacteria such as Bacillus subtilis, Klebsiella pneumoniae, or Mycobacterium marinum induced a specific and different transcriptional response, while Micrococcus luteus did not trigger a significant gene regulation. Although folate has been proposed to be one of the key molecules secreted by bacteria and recognized by hunting amoebae, it elicited a very specific and restricted transcriptional signature, distinct from that triggered by any bacteria analyzed here. Our results indicate that D. discoideum amoebae respond in a highly specific, almost non-overlapping manner to different species of bacteria. We additionally identify specific sets of genes that can be used as reporters of the response of D. discoideum to different bacteria.

Molecular Biomarkers of Neovascular Age-Related Macular Degeneration With Incomplete Response to Anti-Vascular Endothelial Growth Factor Treatment.

The standard treatment for neovascular age-related macular degeneration (nAMD) consists of intravitreal anti-vascular endothelial growth factors (VEGF). However, for some patients, even maximal anti-VEGF treatment does not entirely suppress exudative activity. The goal of this study was to identify molecular biomarkers in nAMD with incomplete response to anti-VEGF treatment. Aqueous humor (AH) samples were collected from three groups of patients: 17 patients with nAMD responding incompletely to anti-VEGF (18 eyes), 17 patients affected by nAMD with normal treatment response (21 eyes), and 16 control patients without any retinopathy (16 eyes). Proteomic and multiplex analyses were performed on these samples. Proteomic analyses showed that nAMD patients with incomplete anti-VEGF response displayed an increased inflammatory response, complement activation, cytolysis, protein-lipid complex, and vasculature development pathways. Multiplex analyses revealed a significant increase of soluble vascular cell adhesion molecule-1 (sVCAM-1) [ p = 0.001], interleukin-6 (IL-6) [ p = 0.009], bioactive interleukin-12 (IL-12p40) [ p = 0.03], plasminogen activator inhibitor type 1 (PAI-1) [ p = 0.004], and hepatocyte growth factor (HGF) [ p = 0.004] levels in incomplete responders in comparison to normal responders. Interestingly, the same biomarkers showed a high intercorrelation with r2 values between 0.58 and 0.94. In addition, we confirmed by AlphaLISA the increase of sVCAM-1 [ p < 0.0001] and IL-6 [ p = 0.043] in the incomplete responder group. Incomplete responders in nAMD are associated with activated angiogenic and inflammatory pathways. The residual exudative activity of nAMD despite maximal anti-VEGF treatment may be related to both angiogenic and inflammatory responses requiring specific adjuvant therapy. Data are available via ProteomeXchange with identifier PXD02247.

Inferring gene expression networks with hubs using a degree weighted Lasso approach.

MOTIVATION: Genome-scale gene networks contain regulatory genes called hubs that have many interaction partners. These genes usually play an essential role in gene regulation and cellular processes. Despite recent advancements in high-throughput technology, inferring gene networks with hub genes from high-dimensional data still remains a challenging problem. Novel statistical network inference methods are needed for efficient and accurate reconstruction of hub networks from high-dimensional data. RESULTS: To address this challenge we propose DW-Lasso, a degree weighted Lasso (least absolute shrinkage and selection operator) method which infers gene networks with hubs efficiently under the low sample size setting. Our network reconstruction approach is formulated as a two stage procedure: first, the degree of networks is estimated iteratively, and second, the gene regulatory network is reconstructed using degree information. A useful property of the proposed method is that it naturally favors the accumulation of neighbors around hub genes and thereby helps in accurate modeling of the high-throughput data under the assumption that the underlying network exhibits hub structure. In a simulation study, we demonstrate good predictive performance of the proposed method in comparison to traditional Lasso type methods in inferring hub and scale-free graphs. We show the effectiveness of our method in an application to microarray data of Escherichia coli and RNA sequencing data of Kidney Clear Cell Carcinoma from The Cancer Genome Atlas datasets. AVAILABILITY AND IMPLEMENTATION: Under the GNU General Public Licence at https://cran.r-project.org/package=DWLasso. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The mitophagy activator urolithin A is safe and induces a molecular signature of improved mitochondrial and cellular health in humans.

Urolithin A (UA) is a natural dietary, microflora-derived metabolite shown to stimulate mitophagy and improve muscle health in old animals and in preclinical models of aging1. Here, we report the results of a first-in-human clinical trial in which we administered UA, either as a single dose or as multiple doses over a 4-week period, to healthy, sedentary elderly individuals. We show that UA has a favourable safety profile (primary outcome). UA was bioavailable in plasma at all doses tested, and 4 weeks of treatment with UA at doses of 500 mg and 1,000 mg modulated plasma acylcarnitines and skeletal muscle mitochondrial gene expression in elderly individuals (secondary outcomes). These observed effects on mitochondrial biomarkers show that UA induces a molecular signature of improved mitochondrial and cellular health following regular oral consumption in humans.

A systems genetics resource and analysis of sleep regulation in the mouse.

Sleep is essential for optimal brain functioning and health, but the biological substrates through which sleep delivers these beneficial effects remain largely unknown. We used a systems genetics approach in the BXD genetic reference population (GRP) of mice and assembled a comprehensive experimental knowledge base comprising a deep "sleep-wake" phenome, central and peripheral transcriptomes, and plasma metabolome data, collected under undisturbed baseline conditions and after sleep deprivation (SD). We present analytical tools to interactively interrogate the database, visualize the molecular networks altered by sleep loss, and prioritize candidate genes. We found that a one-time, short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%-78% of the transcriptomes and the metabolome, with numerous genetic loci affecting the magnitude and direction of change. Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep. Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported.

Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes.

AIMS/HYPOTHESIS: Pancreatic islet beta cell failure causes type 2 diabetes in humans. To identify transcriptomic changes in type 2 diabetic islets, the Innovative Medicines Initiative for Diabetes: Improving beta-cell function and identification of diagnostic biomarkers for treatment monitoring in Diabetes (IMIDIA) consortium ( www.imidia.org ) established a comprehensive, unique multicentre biobank of human islets and pancreas tissues from organ donors and metabolically phenotyped pancreatectomised patients (PPP). METHODS: Affymetrix microarrays were used to assess the islet transcriptome of islets isolated either by enzymatic digestion from 103 organ donors (OD), including 84 non-diabetic and 19 type 2 diabetic individuals, or by laser capture microdissection (LCM) from surgical specimens of 103 PPP, including 32 non-diabetic, 36 with type 2 diabetes, 15 with impaired glucose tolerance (IGT) and 20 with recent-onset diabetes (<1 year), conceivably secondary to the pancreatic disorder leading to surgery (type 3c diabetes). Bioinformatics tools were used to (1) compare the islet transcriptome of type 2 diabetic vs non-diabetic OD and PPP as well as vs IGT and type 3c diabetes within the PPP group; and (2) identify transcription factors driving gene co-expression modules correlated with insulin secretion ex vivo and glucose tolerance in vivo. Selected genes of interest were validated for their expression and function in beta cells. RESULTS: Comparative transcriptomic analysis identified 19 genes differentially expressed (false discovery rate ≤0.05, fold change ≥1.5) in type 2 diabetic vs non-diabetic islets from OD and PPP. Nine out of these 19 dysregulated genes were not previously reported to be dysregulated in type 2 diabetic islets. Signature genes included TMEM37, which inhibited Ca2+-influx and insulin secretion in beta cells, and ARG2 and PPP1R1A, which promoted insulin secretion. Systems biology approaches identified HNF1A, PDX1 and REST as drivers of gene co-expression modules correlated with impaired insulin secretion or glucose tolerance, and 14 out of 19 differentially expressed type 2 diabetic islet signature genes were enriched in these modules. None of these signature genes was significantly dysregulated in islets of PPP with impaired glucose tolerance or type 3c diabetes. CONCLUSIONS/INTERPRETATION: These studies enabled the stringent definition of a novel transcriptomic signature of type 2 diabetic islets, regardless of islet source and isolation procedure. Lack of this signature in islets from PPP with IGT or type 3c diabetes indicates differences possibly due to peculiarities of these hyperglycaemic conditions and/or a role for duration and severity of hyperglycaemia. Alternatively, these transcriptomic changes capture, but may not precede, beta cell failure.

A transcribed enhancer dictates mesendoderm specification in pluripotency.

Enhancers and long noncoding RNAs (lncRNAs) are key determinants of lineage specification during development. Here, we evaluate remodeling of the enhancer landscape and modulation of the lncRNA transcriptome during mesendoderm specification. We sort mesendodermal progenitors from differentiating embryonic stem cells (ESCs) according to Eomes expression, and find that enhancer usage is coordinated with mesendoderm-specific expression of key lineage-determining transcription factors. Many of these enhancers are associated with the expression of lncRNAs. Examination of ESC-specific enhancers interacting in three-dimensional space with mesendoderm-specifying transcription factor loci identifies MesEndoderm Transcriptional Enhancer Organizing Region (Meteor). Genetic and epigenetic manipulation of the Meteor enhancer reveal its indispensable role during mesendoderm specification and subsequent cardiogenic differentiation via transcription-independent and -dependent mechanisms. Interestingly, Meteor-deleted ESCs are epigenetically redirected towards neuroectodermal lineages. Loci, topologically associating a transcribed enhancer and its cognate protein coding gene, appear to represent therefore a class of genomic elements controlling developmental competence in pluripotency.

Identification of islet-enriched long non-coding RNAs contributing to ß-cell failure in type 2 diabetes.

OBJECTIVE: Non-coding RNAs constitute a major fraction of the ß-cell transcriptome. While the involvement of microRNAs is well established, the contribution of long non-coding RNAs (lncRNAs) in the regulation of ß-cell functions and in diabetes development remains poorly understood. The aim of this study was to identify novel islet lncRNAs differently expressed in type 2 diabetes models and to investigate their role in ß-cell failure and in the development of the disease. METHODS: Novel transcripts dysregulated in the islets of diet-induced obese mice were identified by high throughput RNA-sequencing coupled with de novo annotation. Changes in the level of the lncRNAs were assessed by real-time PCR. The functional role of the selected lncRNAs was determined by modifying their expression in MIN6 cells and primary islet cells. RESULTS: We identified about 1500 novel lncRNAs, a number of which were differentially expressed in obese mice. The expression of two lncRNAs highly enriched in ß-cells, ßlinc2, and ßlinc3, correlated to body weight gain and glycemia levels in obese mice and was also modified in diabetic db/db mice. The expression of both lncRNAs was also modulated in vitro in isolated islet cells by glucolipotoxic conditions. Moreover, the expression of the human orthologue of ßlinc3 was altered in the islets of type 2 diabetic patients and was associated to the BMI of the donors. Modulation of the level of ßlinc2 and ßlinc3 by overexpression or downregulation in MIN6 and mouse islet cells did not affect insulin secretion but increased ß-cell apoptosis. CONCLUSIONS: Taken together, the data show that lncRNAs are modulated in a model of obesity-associated type 2 diabetes and that variations in the expression of some of them may contribute to ß-cell failure during the development of the disease.

Molecular phenotyping of multiple mouse strains under metabolic challenge uncovers a role for Elovl2 in glucose-induced insulin secretion.

OBJECTIVE: In type 2 diabetes (T2D), pancreatic ß cells become progressively dysfunctional, leading to a decline in insulin secretion over time. In this study, we aimed to identify key genes involved in pancreatic beta cell dysfunction by analyzing multiple mouse strains in parallel under metabolic stress. METHODS: Male mice from six commonly used non-diabetic mouse strains were fed a high fat or regular chow diet for three months. Pancreatic islets were extracted and phenotypic measurements were recorded at 2 days, 10 days, 30 days, and 90 days to assess diabetes progression. RNA-Seq was performed on islet tissue at each time-point and integrated with the phenotypic data in a network-based analysis. RESULTS: A module of co-expressed genes was selected for further investigation as it showed the strongest correlation to insulin secretion and oral glucose tolerance phenotypes. One of the predicted network hub genes was Elovl2, encoding Elongase of very long chain fatty acids 2. Elovl2 silencing decreased glucose-stimulated insulin secretion in mouse and human ß cell lines. CONCLUSION: Our results suggest a role for Elovl2 in ensuring normal insulin secretory responses to glucose. Moreover, the large comprehensive dataset and integrative network-based approach provides a new resource to dissect the molecular etiology of ß cell failure under metabolic stress.

Vps13F links bacterial recognition and intracellular killing in Dictyostelium.

Bacterial sensing, ingestion, and killing by phagocytic cells are essential processes to protect the human body from infectious microorganisms. The cellular mechanisms involved in intracellular killing, their relative importance, and their specificity towards different bacteria are however poorly defined. In this study, we used Dictyostelium discoideum, a phagocytic cell model amenable to genetic analysis, to identify new gene products involved in intracellular killing. A random genetic screen led us to identify the role of Vps13F in intracellular killing of Klebsiella pneumoniae. Vps13F knock-out (KO) cells exhibited a delayed intracellular killing of K. pneumoniae, although the general organization of the phagocytic and endocytic pathway appeared largely unaffected. Transcriptomic analysis revealed that vps13F KO cells may be functionally similar to previously characterized fspA KO cells, shown to be defective in folate sensing. Indeed, vps13F KO cells showed a decreased chemokinetic response to various stimulants, suggesting a direct or indirect role of Vps13F in intracellular signaling. Overstimulation with excess folate restored efficient killing in vps13F KO cells. Finally, genetic inactivation of Far1, the folate receptor, resulted in inefficient intracellular killing of K. pneumoniae. Together, these observations show that stimulation of Dictyostelium by bacterial folate is necessary for rapid intracellular killing of K. pneumoniae.

A Genetic Screen Identifies Hypothalamic Fgf15 as a Regulator of Glucagon Secretion.

The counterregulatory response to hypoglycemia, which restores normal blood glucose levels to ensure sufficient provision of glucose to the brain, is critical for survival. To discover underlying brain regulatory systems, we performed a genetic screen in recombinant inbred mice for quantitative trait loci (QTL) controlling glucagon secretion in response to neuroglucopenia. We identified a QTL on the distal part of chromosome 7 and combined this genetic information with transcriptomic analysis of hypothalami. This revealed Fgf15 as the strongest candidate to control the glucagon response. Fgf15 was expressed by neurons of the dorsomedial hypothalamus and the perifornical area. Intracerebroventricular injection of FGF19, the human ortholog of Fgf15, reduced activation by neuroglucopenia of dorsal vagal complex neurons, of the parasympathetic nerve, and lowered glucagon secretion. In contrast, silencing Fgf15 in the dorsomedial hypothalamus increased neuroglucopenia-induced glucagon secretion. These data identify hypothalamic Fgf15 as a regulator of glucagon secretion.

Discovery and functional characterization of cardiovascular long noncoding RNAs.

Recent advances in sequencing and genomic technologies have resulted in the discovery of thousands of previously unannotated long noncoding RNAs (lncRNAs). However, their function in the cardiovascular system remains elusive. Here we review and discuss considerations for cardiovascular lncRNA discovery, annotation and functional characterization. Although we primarily focus on the heart, the proposed pipeline should foster functional and mechanistic exploration of these transcripts in various cardiovascular pathologies. Moreover, these insights could ultimately lead to novel therapeutic approaches targeting lncRNAs for the amelioration of cardiovascular diseases including heart failure.

Genome-wide profiling of the cardiac transcriptome after myocardial infarction identifies novel heart-specific long non-coding RNAs.

AIM: Heart disease is recognized as a consequence of dysregulation of cardiac gene regulatory networks. Previously, unappreciated components of such networks are the long non-coding RNAs (lncRNAs). Their roles in the heart remain to be elucidated. Thus, this study aimed to systematically characterize the cardiac long non-coding transcriptome post-myocardial infarction and to elucidate their potential roles in cardiac homoeostasis. METHODS AND RESULTS: We annotated the mouse transcriptome after myocardial infarction via RNA sequencing and ab initio transcript reconstruction, and integrated genome-wide approaches to associate specific lncRNAs with developmental processes and physiological parameters. Expression of specific lncRNAs strongly correlated with defined parameters of cardiac dimensions and function. Using chromatin maps to infer lncRNA function, we identified many with potential roles in cardiogenesis and pathological remodelling. The vast majority was associated with active cardiac-specific enhancers. Importantly, oligonucleotide-mediated knockdown implicated novel lncRNAs in controlling expression of key regulatory proteins involved in cardiogenesis. Finally, we identified hundreds of human orthologues and demonstrate that particular candidates were differentially modulated in human heart disease. CONCLUSION: These findings reveal hundreds of novel heart-specific lncRNAs with unique regulatory and functional characteristics relevant to maladaptive remodelling, cardiac function and possibly cardiac regeneration. This new class of molecules represents potential therapeutic targets for cardiac disease. Furthermore, their exquisite correlation with cardiac physiology renders them attractive candidate biomarkers to be used in the clinic.

Endogenous RNAs modulate microRNA sorting to exosomes and transfer to acceptor cells.

MicroRNA (miRNA) transfer via exosomes may mediate cell-to-cell communication. Interestingly, specific miRNAs are enriched in exosomes in a cell-type-dependent fashion. However, the mechanisms whereby miRNAs are sorted to exosomes and the significance of miRNA transfer to acceptor cells are unclear. We used macrophages and endothelial cells (ECs) as a model of heterotypic cell communication in order to investigate both processes. RNA profiling of macrophages and their exosomes shows that miRNA sorting to exosomes is modulated by cell-activation-dependent changes of miRNA target levels in the producer cells. Genetically perturbing the expression of individual miRNAs or their targeted transcripts promotes bidirectional miRNA relocation from the cell cytoplasm/P bodies (sites of miRNA activity) to multivesicular bodies (sites of exosome biogenesis) and controls miRNA sorting to exosomes. Furthermore, the use of Dicer-deficient cells and reporter lentiviral vectors (LVs) for miRNA activity shows that exosomal miRNAs are transferred from macrophages to ECs to detectably repress targeted sequences.