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International audience; ABSTRACT Background MicroRNAs (miRNAs) are small noncoding RNAs involved in posttranscriptional regulation. miRNAs can be secreted and found in many body fluids, and although they are particularly abundant in breastmilk, their functions remain elusive. Human milk (HM) miRNAs start to raise considerable interest, but a comprehensive understanding of the repertoire and expression profiles along lactation has not been well characterized. Objectives This study aimed to characterize the longitudinal profile of HM miRNA between the second week and third month postpartum. Methods We used a new sensitive technology to measure HM miRNAs in a cohort of 44 French mothers [mean ± SD age: 31 ± 3.5; BMI (in kg/m2) 21.8 ± 2.3] who delivered at term and provided HM samples at 3 time points (17 ± 3 d, 60 ± 3 d, and 90 ± 3 d) during follow-up visits. Results We detected 685 miRNAs, of which 35 showed a high and stable expression along the lactation period analyzed. We also described for the first time a set of 11 miRNAs with a dynamic expression profile. To gain insight into the potential functional relevance of this set of miRNAs, we selected miR-3126 and miR-3184 to treat undifferentiated Caco-2 human intestinal cells and then assessed differentially expressed genes and modulation of related biological pathways. Conclusions Overall, our study provides new insights into HM miRNA composition and, to our knowledge, the first description of its longitudinal dynamics in mothers who delivered at term. Our in vitro results obtained in undifferentiated Caco-2 human intestinal cells transfected with HM miRNAs also provide further support to the hypothesized mother-to-neonate signaling role of HM miRNAs. This trial was registered at clinicaltrials.gov as NCT01894893.

International audience; Subclinical mastitis (SCM) is an inflammatory state of the lactating mammary gland, which is asymptomatic and may have negative consequences for child growth. The objectives of this study were to: (1) test the association between the dietary inflammatory index (DII(®)) and SCM and (2) assess the differences in nutrient intakes between women without SCM and those with SCM. One hundred and seventy-seven women with available data on human milk (HM) sodium potassium ratio (Na:K) and dietary intake data were included for analysis. Multivariable logistic regression was used to examine the association between nutrient intake and the DII score in relation to SCM. Women without SCM had a lower median DII score (0.60) than women with moderate (1.12) or severe (1.74) SCM (p < 0.01). A one-unit increase in DII was associated with about 41% increased odds of having SCM, adjusting for country and mode of delivery, p = 0.001. Women with SCM had lower mean intakes of several anti-inflammatory nutrients. We show for the first time exploratory evidence that SCM may be associated with a pro-inflammatory diet and women with SCM have lower intakes of several antioxidant and anti-inflammatory nutrients.

Rationale: Human milk oligosaccharides (HMOs) vary among mothers and genetic factors contribute to this variability. We assessed changes in HMO concentrations during the first year of lactation and the relationship with FUT2 Secretor group and FUT3 Lewis group defining genetic polymorphisms.Methods: Milk samples were collected from lactating mothers participating in the LIFE Child cohort in Leipzig, Germany. The concentrations of 24 HMOs in milk samples collected at 3 months (N = 156), 6 months (N = 122), and 12 months (N = 28) were measured using liquid chromatography. Concentrations of HMOs were compared at all time-points and were tested for their associations with FUT2 and FUT3 genetic variations by sPLS regression.Results:FUT2 SNP rs601338 was found to predominantly define the Secretor status Se-: 11.8% and it was highly correlated with 2′-fucosyllactose (2′FL, p < 0.001) and lacto-N-fucosylpentaose-I (LNFP-I, p < 0.001). FUT3 SNPs rs28362459 and rs812936 were found to define Lewis status (Le-: 5.9%) and correlated with lacto-N-fucosylpentaose-II (LNFP-II, p < 0.001). A polygenic score predicted the abundance of 2′FL levels within Secretors' milk (adj. R2 = 0.58, p < 0.001). Mean concentrations of most of the individual HMOs, as well as the sums of the measured HMOs, the fucosylated HMOs, and the neutral HMOs were lower at 6 and 12 months compared to 3 months (p < 0.001).Conclusions: Secretor and Lewis status defined by specific FUT2 and FUT3 SNPs are confirmed to be good proxies for specific individual HMOs and milk group variabilities. The polygenic score developed here is an opportunity for clinicians to predict 2′FL levels in milk of future mothers. These results show opportunities to strengthen our understanding of factors controlling FUT2 and FUT3 functionality, the temporal changes and variability of HMO composition during lactation and eventually their significance for infant development.

Background: A low-calorie diet (LCD) reduces fat mass excess, improves insulin sensitivity, and alters adipose tissue (AT) gene expression, yet the relation with clinical outcomes remains unclear.Objective: We evaluated AT transcriptome alterations during an LCD and the association with weight and glycemic outcomes both at LCD termination and 6 mo after the LCD.Design: Using RNA sequencing (RNAseq), we analyzed transcriptome changes in AT from 191 obese, nondiabetic patients within a multicenter, controlled dietary intervention. Expression changes were associated with outcomes after an 8-wk LCD (800-1000 kcal/d) and 6 mo after the LCD. Results were validated by using quantitative reverse transcriptase-polymerase chain reaction in 350 subjects from the same cohort. Statistical models were constructed to classify weight maintainers or glycemic improvers.Results: With RNAseq analyses, we identified 1173 genes that were differentially expressed after the LCD, of which 350 and 33 were associated with changes in body mass index (BMI; in kg/m(2)) and Matsuda index values, respectively, whereas 29 genes were associated with both endpoints. Pathway analyses highlighted enrichment in lipid and glucose metabolism. Classification models were constructed to identify weight maintainers. A model based on clinical baseline variables could not achieve any classification (validation AUC: 0.50; 95% CI: 0.36, 0.64). However, clinical changes during the LCD yielded better performance of the model (AUC: 0.73; 95% CI: 0.60, 0.87]). Adding baseline expression to this model improved the performance significantly (AUC: 0.87; 95% CI: 0.77, 0.96; Delong's P = 0.012). Similar analyses were performed to classify subjects with good glycemic improvements. Baseline- and LCD-based clinical models yielded similar performance (best AUC: 0.73; 95% CI: 0.60, 0.86). The addition of expression changes during the LCD improved the performance substantially (AUC: 0.80; 95% CI: 0.69, 0.92; P = 0.058).Conclusions: This study investigated AT transcriptome alterations after an LCD in a large cohort of obese, nondiabetic patients. Gene expression combined with clinical variables enabled us to distinguish weight and glycemic responders from nonresponders. These potential biomarkers may help clinicians understand intersubject variability and better predict the success of dietary interventions. This trial was registered at clinicaltrials.gov as NCT00390637.

International audience; AMPK is a central regulator of energy homeostasis. AMPK not only elicits acute metabolic responses but also promotes metabolic reprogramming and adaptations in the long-term through regulation of specific transcription factors and coactivators. We performed a whole-genome transcriptome profiling in wild-type (WT) and AMPK-deficient mouse embryonic fibroblasts (MEFs) and primary hepatocytes that had been treated with 2 distinct classes of small-molecule AMPK activators. We identified unique compound-dependent gene expression signatures and several AMPK-regulated genes, including folliculin (Flcn), which encodes the tumor suppressor FLCN. Bioinformatics analysis highlighted the lysosomal pathway and the associated transcription factor EB (TFEB) as a key transcriptional mediator responsible for AMPK responses. AMPK-induced Flcn expression was abolished in MEFs lacking TFEB and transcription factor E3, 2 transcription factors with partially redundant function; additionally, the promoter activity of Flcn was profoundly reduced when its putative TFEB-binding site was mutated. The AMPK-TFEB-FLCN axis is conserved across species; swimming exercise in WT zebrafish induced Flcn expression in muscle, which was significantly reduced in AMPK-deficient zebrafish. Mechanistically, we have found that AMPK promotes dephosphorylation and nuclear localization of TFEB independently of mammalian target of rapamycin activity. Collectively, we identified the novel AMPK-TFEB-FLCN axis, which may function as a key cascade for cellular and metabolic adaptations.-Collodet, C., Foretz, M., Deak, M., Bultot, L., Metairon, S., Viollet, B., Lefebvre, G., Raymond, F., Parisi, A., Civiletto, G., Gut, P., Descombes, P., Sakamoto, K. AMPK promotes induction of the tumor suppressor FLCN through activation of TFEB independently of mTOR.

Motivation Network inference provides a global view of the relations existing between gene expression in a given transcriptomic experiment (often only for a restricted list of chosen genes). However, it is still a challenging problem: even if the cost of sequencing techniques has decreased over the last years, the number of samples in a given experiment is still (very) small compared to the number of genes. Results We propose a method to increase the reliability of the inference when RNA-seq expression data have been measured together with an auxiliary dataset that can provide external information on gene expression similarity between samples. Our statistical approach, hd-MI, is based on imputation for samples without available RNA-seq data that are considered as missing data but are observed on the secondary dataset. hd-MI can improve the reliability of the inference for missing rates up to 30% and provides more stable networks with a smaller number of false positive edges. On a biological point of view, hd-MI was also found relevant to infer networks from RNA-seq data acquired in adipose tissue during a nutritional intervention in obese individuals. In these networks, novel links between genes were highlighted, as well as an improved comparability between the two steps of the nutritional intervention. Availability and implementation Software and sample data are available as an R package, RNAseqNet, that can be downloaded from the Comprehensive R Archive Network (CRAN). Supplementary information Supplementary data are available at Bioinformatics online.

Next-generation sequencing offers an unprecedented opportunity to jointly analyze cellular and viral transcriptional activity without prerequisite knowledge of the nature of the transcripts. SupT1 cells were infected with a vesicular stomatitis virus G envelope protein (VSV-G)-pseudotyped HIV vector. At 24 h postinfection, both cellular and viral transcriptomes were analyzed by serial analysis of gene expression followed by high-throughput sequencing (SAGE-Seq). Read mapping resulted in 33 to 44 million tags aligning with the human transcriptome and 0.23 to 0.25 million tags aligning with the genome of the HIV-1 vector. Thus, at peak infection, 1 transcript in 143 is of viral origin (0.7%), including a small component of antisense viral transcription. Of the detected cellular transcripts, 826 (2.3%) were differentially expressed between mock- and HIV-infected samples. The approach also assessed whether HIV-1 infection modulates the expression of repetitive elements or endogenous retroviruses. We observed very active transcription of these elements, with 1 transcript in 237 being of such origin, corresponding on average to 123,123 reads in mock-infected samples (0.40%) and 129,149 reads in HIV-1-infected samples (0.45%) mapping to the genomic Repbase repository. This analysis highlights key details in the generation and interpretation of high-throughput data in the setting of HIV-1 cellular infection.

Background: The major histocompatibility complex (MHC) is essential for human immunity and is highly associated with common diseases, including cancer. While the genetics of the MHC has been studied intensively for many decades, very little is known about the epigenetics of this most polymorphic and disease-associated region of the genome. Methods: To facilitate comprehensive epigenetic analyses of this region, we have generated a genomic tiling array of 2 Kb resolution covering the entire 4 Mb MHC region. The array has been designed to be compatible with chromatin immunoprecipitation (ChIP), methylated DNA immunoprecipitation (MeDIP), array comparative genomic hybridization (aCGH) and expression profiling, including of non-coding RNAs. The array comprises 7832 features, consisting of two replicates of both forward and reverse strands of MHC amplicons and appropriate controls. Results: Using MeDIP, we demonstrate the application of the MHC array for DNA methylation profiling and the identification of tissue-specific differentially methylated regions (tDMRs). Based on the analysis of two tissues and two cell types, we identified 90 tDMRs within the MHC and describe their characterisation. Conclusion: A tiling array covering the MHC region was developed and validated. Its successful application for DNA methylation profiling indicates that this array represents a useful tool for molecular analyses of the MHC in the context of medical genomics. Fil: Tomazou, Eleni M. Wellcome Trust Sanger Institute; Reino Unido Fil: Rakyan, Vardhman K. Institute of Cell and Molecular Science; Reino Unido Fil: Lefebvre, Gregory. Wellcome Trust Sanger Institute; Reino Unido Fil: Andrews, Robert. Wellcome Trust Sanger Institute; Reino Unido Fil: Ellis, Peter. Wellcome Trust Sanger Institute; Reino Unido Fil: Jackson, David K. Wellcome Trust Sanger Institute; Reino Unido Fil: Langford, Cordelia. Wellcome Trust Sanger Institute; Reino Unido Fil: Francis, Matthew D. Wellcome Trust Sanger Institute; Reino Unido Fil: Bäckdahl, Liselotte. University College London; Reino Unido Fil: Miretti, Marcos Mateo. Wellcome Trust Sanger Institute; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentina Fil: Coggill, Penny. Wellcome Trust Sanger Institute; Reino Unido Fil: Ottaviani, Diego. London Research Institute; Reino Unido. London School of Medicine and Dentistry; Reino Unido Fil: Sheer, Denise. London School of Medicine and Dentistry; Reino Unido Fil: Murrell, Adele. Cambridge Research Institute; Reino Unido Fil: Beck, Stephan G.. University College London; Reino Unido

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view about chromatin structure has emerged, including its interrelationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded novel mechanistic and evolutionary insights about the functional landscape of the human genome. Together, these studies are defining a path forward to pursue a more-comprehensive characterisation of human genome function.