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Background: BCN02 was a pilot kick-and-kill clinical trial that combined therapeutic vaccination (MVA.HIVconsv) with the latency reversing agent romidepsin (RMD) followed by a monitored antiretroviral pause (MAP) in 15 early-treated HIV+ individuals (NCT02616874). Out of 12 evaluable participants for an omics sub-analysis, 8 participants showed early (pVL > 2000 copies/mL < 4 weeks) and 4 a more delayed viral rebound (pVL > 2000 copies/mL > 4 weeks) in MAP. Systems biology analyses identified epigenetic and molecular mechanisms associated with response to vaccination and RMD and viral rebound kinetics. Methods: Genome-wide gene expression (Ilumina HiSeq2500) and DNA Methylation (Infinium HumanMethylation450 BeadChip) were assessed in frozen PBMC-pellets at baseline, 1 week after vaccination and 1 week after the 3rd RMD infusion (post-RMD). After pre-processing and normalization steps we applied principal component analyses (PCA) and differential expression/methylation analyses (limma-R/Biocondcutor). GSEA was used for functional analysis, and sPLS-DA (MixOmics-R/Bioconductor), to identify pathways explicative of differential viral rebound kinetics. Results: The largest impact on host transcriptional and DNA methylation (DNAm) profiles was observed after the combined effect of vaccination and RMD, with 733 differentially expressed genes and 5695 differentially methylated positions being detected between baseline and post-RMD (adjusted p < 0.1). Modulated pathways at gene expression and/or DNAm level, were mainly associated with processes including cell cycle, DNA repair or metabolism and HIV, innate and adaptive immunity (GSEA q-value < 0.15). Of note, PCA revealed that only DNAm levels after the combined intervention segregated participants by their early or late viral rebound kinetics in MAP. We summarized the therapy-modulated pathways with eigenvectors of DNAm at post-RMD, and identified HIV, innate immunity and T-cell pathways among the most relevant to discriminate the two viral rebound profiles in MAP. Interestingly, 3 CpG positions in the HIV category, 37 in the innate immunity group and 10 in the T cell category were differentially methylated between individuals with different viral rebound profile (adjusted p < 0.1). Conclusions: Host transcription and epigenetic programs provide a deeper understanding of the molecular mechanisms induced during HIV cure therapies. While DNAm after a kick-and-kill strategy could be used to predict viral rebound kinetics after ART interruption, further study is warranted in future controlled studies.

Background: Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. Results: An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. Conclusions: We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

The epigenomic landscape of Parkinson's disease (PD) remains unknown. We performed a genomewide DNA methylation and a transcriptome studies in induced pluripotent stem cell (iPSC)‐derived dopaminergic neurons (DAn) generated by cell reprogramming of somatic skin cells from patients with monogenic LRRK2‐associated PD (L2PD) or sporadic PD (sPD), and healthy subjects. We observed extensive DNA methylation changes in PD DAn, and of RNA expression, which were common in L2PD and sPD. No significant methylation differences were present in parental skin cells, undifferentiated iPSCs nor iPSC‐derived neural cultures not‐enriched‐in‐DAn. These findings suggest the presence of molecular defects in PD somatic cells which manifest only upon differentiation into the DAn cells targeted in PD. The methylation profile from PD DAn, but not from controls, resembled that of neural cultures not‐enriched‐in‐DAn indicating a failure to fully acquire the epigenetic identity own to healthy DAn in PD. The PD‐associated hypermethylation was prominent in gene regulatory regions such as enhancers and was related to the RNA and/or protein downregulation of a network of transcription factors relevant to PD (FOXA1, NR3C1, HNF4A, and FOSL2). Using a patient‐specific iPSC‐based DAn model, our study provides the first evidence that epigenetic deregulation is associated with monogenic and sporadic PD. Synopsis This is the first proof‐of‐principle that induced pluripotent stem cell (iPSC)‐derived dopaminergic neurons (DAn) from sporadic and monogenetic Parkinson's disease (PD) patients show the same epigenomic changes as compared to healthy controls. For a video version of this synopsis, see: http://embopress.org/video_EMM-2015-05439 . Epigenomic changes are common in patients with sporadic PD and patients with a monogenic form of PD associated with mutations in the gene LRRK2. PD‐associated methylation changes are latent in parental somatic cells or undifferentiated iPSCs and become uncovered upon differentiation into DAn (cells targeted in PD) but not into other neural types. PD‐associated methylation changes correlate with gene expression, target functionally‐ active sequences (enhancers), and are related to the aberrant down‐regulation of a network of transcription factors relevant to PD. Graphical Abstract This is the first proof‐of‐principle that induced pluripotent stem cell (iPSC)‐derived dopaminergic neurons (DAn) from sporadic and monogenetic Parkinson's disease (PD) patients show the same epigenomic changes as compared to healthy controls.

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively.

GWAS, immune analyses and biomarker screenings have identified host factors associated with in vivo HIV-1 control. However, there is a gap in the knowledge about the mechanisms that regulate the expression of such host factors. Here, we aimed to assess DNA methylation impact on host genome in natural HIV-1 control. To this end, whole DNA methylome in 70 untreated HIV-1 infected individuals with either high (>50,000 HIV-1-RNA copies/ml, n = 29) or low (<10,000 HIV-1-RNA copies/ml, n = 41) plasma viral load (pVL) levels were compared and identified 2,649 differentially methylated positions (DMPs). Of these, a classification random forest model selected 55 DMPs that correlated with virologic (pVL and proviral levels) and HIV-1 specific adaptive immunity parameters (IFNg-T cell responses and neutralizing antibodies capacity). Then, cluster and functional analyses identified two DMP clusters: cluster 1 contained hypo-methylated genes involved in antiviral and interferon response (e.g. PARP9, MX1, and USP18) in individuals with high viral loads while in cluster 2, genes related to T follicular helper cell (Tfh) commitment (e.g. CXCR5 and TCF7) were hyper-methylated in the same group of individuals with uncontrolled infection. For selected genes, mRNA levels negatively correlated with DNA methylation, confirming an epigenetic regulation of gene expression. Further, these gene expression signatures were also confirmed in early and chronic stages of infection, including untreated, cART treated and elite controllers HIV-1 infected individuals (n = 37). These data provide the first evidence that host genes critically involved in immune control of the virus are under methylation regulation in HIV-1 infection. These insights may offer new opportunities to identify novel mechanisms of in vivo virus control and may prove crucial for the development of future therapeutic interventions aimed at HIV-1 cure.

The North Atlantic Oscillation (NAO) is the major atmospheric mode that controls winter European climate variability because its strength and phase determine regional temperature, precipitation and storm tracks. The NAO spatial structure and associated climatic impacts over Europe are not stationary making it crucial to understanding its past evolution in order to improve the predictability of future scenarios. In this regard, there has been a dramatic increase in the number of studies aimed at reconstructing past NAO variability, but the information related to decadal-scale NAO evolution beyond the last millennium is scarce and inconclusive. We present a new 2,000-year multi-annual, proxy-based reconstruction of local NAO impact, with associated uncertainties, obtained by a Bayesian approach. This new local NAO reconstruction is obtained from a mountain lacustrine sedimentary archive of the Iberian Peninsula. This geographical area is not included in previous NAO reconstructions despite being a widely used region for instrumental-based NAO measurements. We assess the main external forcings (i.e., volcanic eruptions and solar activity) on NAO variability which, on a decadal scale, show that a low number of sunspots correlate to low NAO values. By comparison with other previously published NAO reconstructions in our analyses we can test the stationarity of the solar influence on the NAO signal across a latitudinal gradient based on the position of the employed archives for each NAO reconstruction. Inconclusive results on the volcanic forcing on NAO variability over decadal time-scales indicates the need for further studies. Moreover, we highlight the potential role of other North Atlantic modes of variability (i.e., East Atlantic pattern) on the non-stationary behaviour of the NAO throughout the Common Era, likely via solar forcing.

Mutations in GDAP1, which encodes protein located in the mitochondrial outer membrane, cause axonal recessive (AR-CMT2), axonal dominant (CMT2K) and demyelinating recessive (CMT4A) forms of Charcot-Marie-Tooth (CMT) neuropathy. Loss of function recessive mutations in GDAP1 are associated with decreased mitochondrial fission activity, while dominant mutations result in impairment of mitochondrial fusion with increased production of reactive oxygen species and susceptibility to apoptotic stimuli. GDAP1 silencing in vitro reduces Ca2+ inflow through store-operated Ca2+ entry (SOCE) upon mobilization of endoplasmic reticulum (ER) Ca2+, likely in association with an abnormal distribution of the mitochondrial network. To investigate the functional consequences of lack of GDAP1 in vivo, we generated a Gdap1 knockout mouse. The affected animals presented abnormal motor behavior starting at the age of 3 months. Electrophysiological and biochemical studies confirmed the axonal nature of the neuropathy whereas histopathological studies over time showed progressive loss of motor neurons (MNs) in the anterior horn of the spinal cord and defects in neuromuscular junctions. Analyses of cultured embryonic MNs and adult dorsal root ganglia neurons from affected animals demonstrated large and defective mitochondria, changes in the ER cisternae, reduced acetylation of cytoskeletal α-tubulin and increased autophagy vesicles. Importantly, MNs showed reduced cytosolic calcium and SOCE response. The development and characterization of the GDAP1 neuropathy mice model thus revealed that some of the pathophysiological changes present in axonal recessive form of the GDAP1-related CMT might be the consequence of changes in the mitochondrial network biology and mitochondria-endoplasmic reticulum interaction leading to abnormalities in calcium homeostasis.

Background In integrative bioinformatic analyses, it is of great interest to stablish the equivalence between gene or (more in general) feature lists, up to a given level and in terms of their annotations in the Gene Ontology. The aim of this article is to present an equivalence test based on the proportion of GO terms which are declared as enriched in both lists simultaneously. Results On the basis of these data, the dissimilarity between gene lists is measured by means of the Sorensen–Dice index. We present two flavours of the same test: One of them based on the asymptotic normality of the test statistic and the other based on the bootstrap method. Conclusions The accuracy of these tests is studied by means of simulation and their possible interest is illustrated by using them over two real datasets: A collection of gene lists related to cancer and a collection of gene lists related to kidney rejection after transplantation.

Abstract The incidence of syphilis has risen worldwide in the last decade in spite of being an easily treated infection. The causative agent of this sexually transmitted disease is the bacterium Treponema pallidum subspecies pallidum (TPA), very closely related to subsp. pertenue (TPE) and endemicum (TEN), responsible for the human treponematoses yaws and bejel, respectively. Although much focus has been placed on the question of the spatial and temporary origins of TPA, the processes driving the evolution and epidemiological spread of TPA since its divergence from TPE and TEN are not well understood. Here, we investigate the effects of recombination and selection as forces of genetic diversity and differentiation acting during the evolution of T. pallidum subspecies. Using a custom-tailored procedure, named phylogenetic incongruence method, with 75 complete genome sequences, we found strong evidence for recombination among the T. pallidum subspecies, involving 12 genes and 21 events. In most cases, only one recombination event per gene was detected and all but one event corresponded to intersubspecies transfers, from TPE/TEN to TPA. We found a clear signal of natural selection acting on the recombinant genes, which is more intense in their recombinant regions. The phylogenetic location of the recombination events detected and the functional role of the genes with signals of positive selection suggest that these evolutionary processes had a key role in the evolution and recent expansion of the syphilis bacteria and significant implications for the selection of vaccine candidates and the design of a broadly protective syphilis vaccine.

Stroke is a major cause of death and disability. A better comprehension of stroke pathophysiology is fundamental to reduce its dramatic outcome. The use of high-throughput unbiased omics approaches and the integration of these data might deepen the knowledge of stroke at the molecular level, depicting the interaction between different molecular units. We aimed to identify protein and gene expression changes in the human brain after ischemia through an integrative approach to join the information of both omics analyses. The translational potential of our results was explored in a pilot study with blood samples from ischemic stroke patients. Proteomics and transcriptomics discovery studies were performed in human brain samples from six deceased stroke patients, comparing the infarct core with the corresponding contralateral brain region, unveiling 128 proteins and 2716 genes significantly dysregulated after stroke. Integrative bioinformatics analyses joining both datasets exposed canonical pathways altered in the ischemic area, highlighting the most influential molecules. Among the molecules with the highest fold-change, 28 genes and 9 proteins were selected to be validated in five independent human brain samples using orthogonal techniques. Our results were confirmed for NCDN, RAB3C, ST4A1, DNM1L, A1AG1, A1AT, JAM3, VTDB, ANXA1 , ANXA2 , and IL8 . Finally, circulating levels of the validated proteins were explored in ischemic stroke patients. Fluctuations of A1AG1 and A1AT, both up-regulated in the ischemic brain, were detected in blood along the first week after onset. In summary, our results expand the knowledge of ischemic stroke pathology, revealing key molecules to be further explored as biomarkers and/or therapeutic targets. Graphical abstract