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The liver and the kidney are the most common targets of chemical toxicity, due to their major metabolic and excretory functions. However, since the liver is directly involved in biotransformation, compounds in many currently and normally used drugs could affect it adversely. Most chemical compounds are already labeled according to FDA-approved labels using DILI-concern scale. Drug Induced Liver Injury (DILI) scale refers to an adverse drug reaction. Many compounds do not exhibit hepatotoxicity at early stages of development, so it is important to detect anomalies at gene expression level that could predict adverse reactions in later stages. In this study, a large collection of microarray data is used to investigate gene expression changes associated with hepatotoxicity. Using TG-GATEs a large-scale toxicogenomics database, we present a computational strategy to classify compounds by toxicity levels in human and animal models through patterns of gene expression. We combined machine learning algorithms with time series analysis to identify genes capable of classifying compounds by FDA-approved labeling as DILI-concern toxic. The goal is to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. The study illustrates that expression profiling can be used to classify compounds according to different hepatotoxic levels; to label those that are currently labeled as undertemined; and to determine if at the molecular level, animal models are a good proxy to predict hepatotoxicity in humans.

Background Obesity is a well-recognized risk factor for insulin resistance and type 2 diabetes (T2D), although the precise mechanisms underlying the relationship remain unknown. In this study we identified alterations of DNA methylation influencing T2D pathogenesis, in subcutaneous and visceral adipose tissues, liver, and blood from individuals with obesity. Methods The study included individuals with obesity, with and without T2D. From these patients, we obtained samples of liver tissue ( n  = 16), visceral and subcutaneous adipose tissues ( n  = 30), and peripheral blood ( n  = 38). We analyzed DNA methylation using Illumina Infinium Human Methylation arrays, and gene expression profiles using HumanHT-12 Expression BeadChip Arrays. Results Analysis of DNA methylation profiles revealed several loci with differential methylation between individuals with and without T2D, in all tissues. Aberrant DNA methylation was mainly found in the liver and visceral adipose tissue. Gene ontology analysis of genes with altered DNA methylation revealed enriched terms related to glucose metabolism, lipid metabolism, cell cycle regulation, and response to wounding. An inverse correlation between altered methylation and gene expression in the four tissues was found in a subset of genes, which were related to insulin resistance, adipogenesis, fat storage, and inflammation. Conclusions Our present findings provide additional evidence that aberrant DNA methylation may be a relevant mechanism involved in T2D pathogenesis among individuals with obesity.

An important NK-cell inhibition with reduced TNF-α, IFN-γ and TLR2 expression had previously been identified in patients with diffuse cutaneous leishmaniasis (DCL) infected with Leishmania mexicana. In an attempt to pinpoint alterations in the signaling pathways responsible for the NK-cell dysfunction in patients with DCL, this study aimed at identifying differences in the NK-cell response towards Leishmania mexicana lipophosphoglycan (LPG) between patients with localized and diffuse cutaneous leishmaniasis through gene expression profiling. Our results indicate that important genes involved in the innate immune response to Leishmania are down-regulated in NK cells from DCL patients, particularly TLR and JAK/STAT signaling pathways. This down-regulation showed to be independent of LPG stimulation. The study sheds new light for understanding the mechanisms that undermine the correct effector functions of NK cells in patients with diffuse cutaneous leishmaniasis contributing to a better understanding of the pathobiology of leishmaniasis.

Formation of the three primary germ layers during gastrulation is an essential step in the establishment of the vertebrate body plan and is associated with major transcriptional changes 1 – 5 . Global epigenetic reprogramming accompanies these changes 6 – 8 , but the role of the epigenome in regulating early cell-fate choice remains unresolved, and the coordination between different molecular layers is unclear. Here we describe a single-cell multi-omics map of chromatin accessibility, DNA methylation and RNA expression during the onset of gastrulation in mouse embryos. The initial exit from pluripotency coincides with the establishment of a global repressive epigenetic landscape, followed by the emergence of lineage-specific epigenetic patterns during gastrulation. Notably, cells committed to mesoderm and endoderm undergo widespread coordinated epigenetic rearrangements at enhancer marks, driven by ten-eleven translocation (TET)-mediated demethylation and a concomitant increase of accessibility. By contrast, the methylation and accessibility landscape of ectodermal cells is already established in the early epiblast. Hence, regulatory elements associated with each germ layer are either epigenetically primed or remodelled before cell-fate decisions, providing the molecular framework for a hierarchical emergence of the primary germ layers. Single-cell mapping of chromatin accessibility, DNA methylation and RNA expression during gastrulation in mouse embryos shows characteristic epigenetic changes that accompany formation of the primary germ layers.

Background Single-cell technologies are transforming biomedical research, including the recent demonstration that unspliced pre-mRNA present in single-cell RNA-Seq permits prediction of future expression states. Here we apply this RNA velocity concept to an extended timecourse dataset covering mouse gastrulation and early organogenesis. Results Intriguingly, RNA velocity correctly identifies epiblast cells as the starting point, but several trajectory predictions at later stages are inconsistent with both real-time ordering and existing knowledge. The most striking discrepancy concerns red blood cell maturation, with velocity-inferred trajectories opposing the true differentiation path. Investigating the underlying causes reveals a group of genes with a coordinated step-change in transcription, thus violating the assumptions behind current velocity analysis suites, which do not accommodate time-dependent changes in expression dynamics. Using scRNA-Seq analysis of chimeric mouse embryos lacking the major erythroid regulator Gata1, we show that genes with the step-changes in expression dynamics during erythroid differentiation fail to be upregulated in the mutant cells, thus underscoring the coordination of modulating transcription rate along a differentiation trajectory. In addition to the expected block in erythroid maturation, the Gata1-chimera dataset reveals induction of PU.1 and expansion of megakaryocyte progenitors. Finally, we show that erythropoiesis in human fetal liver is similarly characterized by a coordinated step-change in gene expression. Conclusions By identifying a limitation of the current velocity framework coupled with in vivo analysis of mutant cells, we reveal a coordinated step-change in gene expression kinetics during erythropoiesis, with likely implications for many other differentiation processes.

To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88, CARD11, EZH2, and CREBBP. We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO, and TNFRSF14. Further, we show that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase–mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.

Since the emergence of the pandemic H1N1pdm09 virus in Mexico and California, biannual increases in the number of cases have been detected in Mexico. As observed in previous seasons, pandemic A/H1N1 09 virus was detected in severe cases during the 2011-2012 winter season and finally, during the 2013-2014 winter season it became the most prevalent influenza virus. Molecular and phylogenetic analyses of the whole viral genome are necessary to determine the antigenic and pathogenic characteristics of influenza viruses that cause severe outcomes of the disease. In this paper, we analyzed the evolution, antigenic and genetic drift of Mexican isolates from 2009, at the beginning of the pandemic, to 2014. We found a clear variation of the virus in Mexico from the 2011-2014 season due to different markers and in accordance with previous reports. In this study, we identified 13 novel substitutions with important biological effects, including virulence, T cell epitope presented by MHC and host specificity shift and some others substitutions might have more than one biological function. The systematic monitoring of mutations on whole genome of influenza A pH1N1 (2009) virus circulating at INER in Mexico City might provide valuable information to predict the emergence of new pathogenic influenza virus.

Background Human central memory CD4 T cells are characterized by their capacity of proliferation and differentiation into effector memory CD4 T cells. Homeostasis of central memory CD4 T cells is considered a key factor sustaining the asymptomatic stage of Human Immunodeficiency Virus type 1 (HIV-1) infection, while progression to acquired immunodeficiency syndrome is imputed to central memory CD4 T cells homeostatic failure. We investigated if central memory CD4 T cells from patients with HIV-1 infection have a gene expression profile impeding proliferation and survival, despite their activated state. Methods Using gene expression microarrays, we analyzed mRNA expression patterns in naive, central memory, and effector memory CD4 T cells from healthy controls, and naive and central memory CD4 T cells from patients with HIV-1 infection. Differentially expressed genes, defined by Log 2 Fold Change (FC) ≥ |0.5| and Log (odds) > 0, were used in pathway enrichment analyses. Results Central memory CD4 T cells from patients and controls showed comparable expression of differentiation-related genes, ruling out an effector-like differentiation of central memory CD4 T cells in HIV infection. However, 210 genes were differentially expressed in central memory CD4 T cells from patients compared with those from controls. Expression of 75 of these genes was validated by semi quantitative RT-PCR, and independently reproduced enrichment results from this gene expression signature. The results of functional enrichment analysis indicated movement to cell cycle phases G1 and S (increased CCNE1, MKI67, IL12RB2, ADAM9, decreased FGF9, etc.), but also arrest in G2/M (increased CHK1, RBBP8, KIF11, etc.). Unexpectedly, the results also suggested decreased apoptosis (increased CSTA, NFKBIA, decreased RNASEL, etc.). Results also suggested increased IL-1β, IFN-γ, TNF, and RANTES (CCR5) activity upstream of the central memory CD4 T cells signature, consistent with the demonstrated milieu in HIV infection. Conclusions Our findings support a model where progressive loss of central memory CD4 T cells in chronic HIV-1 infection is driven by increased cell cycle entry followed by mitotic arrest, leading to a non-apoptotic death pathway without actual proliferation, possibly contributing to increased turnover.

Extra-embryonic mesoderm (ExM)—composed of the earliest cells that traverse the primitive streak—gives rise to the endothelium as well as haematopoietic progenitors in the developing yolk sac. How a specific subset of ExM becomes committed to a haematopoietic fate remains unclear. Here we demonstrate using an embryonic stem cell model that transient expression of the T-box transcription factor Eomesodermin (Eomes) governs haemogenic competency of ExM. Eomes regulates the accessibility of enhancers that the transcription factor stem cell leukaemia (SCL) normally utilizes to specify primitive erythrocytes and is essential for the normal development of Runx1 + haemogenic endothelium. Single-cell RNA sequencing suggests that Eomes loss of function profoundly blocks the formation of blood progenitors but not specification of Flk-1 + haematoendothelial progenitors. Our findings place Eomes at the top of the transcriptional hierarchy regulating early blood formation and suggest that haemogenic competence is endowed earlier during embryonic development than was previously appreciated. Analysing the extra-embryonic mesoderm, Harland et al. show that Eomes influences chromatin accessibility at SCL-bound enhancers for erythropoiesis and enhancers that drive Runx1 expression in the haemogenic endothelium.

The combination of signals from the T-cell receptor (TCR) and co-stimulatory molecules triggers transcriptional programs that lead to proliferation, cytokine secretion, and effector functions. We compared the impact of engaging the TCR with CD28 and/or CD43 at different time points relative to TCR engagement on T-cell function. TCR and CD43 simultaneous engagement resulted in higher CD69 and PD-1 expression levels than in TCR and CD28-stimulated cells, with a cytokine signature of mostly effector, inflammatory, and regulatory cytokines, while TCR and CD28-activated cells secreted all categories of cytokines, including stimulatory cytokines. Furthermore, the timing of CD43 engagement relative to TCR ligation, and to a lesser degree that of CD28, resulted in distinct patterns of expression of cytokines, chemokines, and growth factors. Complete cell activation was observed when CD28 or CD43 were engaged simultaneously with or before the TCR, but ligating the TCR before CD43 or CD28 failed to complete a cell activation program regarding cytokine secretion. As the order in which CD43 or CD28 and the TCR were engaged resulted in different combinations of cytokines that shape distinct T-cell immune programs, we analyzed their upstream sequences to assess whether the combinations of cytokines were associated with different sets of regulatory elements. We found that the order in which the TCR and CD28 or CD43 are engaged predicts the recruitment of specific sets of chromatin remodelers and TFSS, which ultimately regulate T-cell polarization and plasticity. Our data underscore that the combination of co-stimulatory molecules and the time when they are engaged relative to the TCR can change the cell differentiation program.