Explore the vast range of titles available.

Exposure of cells or organisms to chemicals can trigger a series of effects at the regulatory pathway level, which involve changes of levels, interactions, and feedback loops of biomolecules of different types. A single-omics technique, e.g., transcriptomics, will detect biomolecules of one type and thus can only capture changes in a small subset of the biological cascade. Therefore, although applying single-omics analyses can lead to the identification of biomarkers for certain exposures, they cannot provide a systemic understanding of toxicity pathways or adverse outcome pathways. Integration of multiple omics data sets promises a substantial improvement in detecting this pathway response to a toxicant, by an increase of information as such and especially by a systemic understanding. Here, we report the findings of a thorough evaluation of the prospects and challenges of multi-omics data integration in toxicological research. We review the availability of such data, discuss options for experimental design, evaluate methods for integration and analysis of multi-omics data, discuss best practices, and identify knowledge gaps. Re-analyzing published data, we demonstrate that multi-omics data integration can considerably improve the confidence in detecting a pathway response. Finally, we argue that more data need to be generated from studies with a multi-omics-focused design, to define which omics layers contribute most to the identification of a pathway response to a toxicant.

Significant fractions of eukaryotic genomes give rise to RNA, much of which is unannotated and has reduced protein-coding potential. The genomic origins and the associations of human nuclear and cytosolic polyadenylated RNAs longer than 200 nucleotides (nt) and whole-cell RNAs less than 200 nt were investigated in this genome-wide study. Subcellular addresses for nucleotides present in detected RNAs were assigned, and their potential processing into short RNAs was investigated. Taken together, these observations suggest a novel role for some unannotated RNAs as primary transcripts for the production of short RNAs. Three potentially functional classes of RNAs have been identified, two of which are syntenically conserved and correlate with the expression state of protein-coding genes. These data support a highly interleaved organization of the human transcriptome.

Genome sequencing of Helicobacter pylori has revealed the potential proteins and genetic diversity of this prevalent human pathogen, yet little is known about its transcriptional organization and noncoding RNA output. Massively parallel cDNA sequencing (RNA-seq) has been revolutionizing global transcriptomic analysis. Here, using a novel differential approach (dRNA-seq) selective for the 5′ end of primary transcripts, we present a genome-wide map of H. pylori transcriptional start sites and operons. We discovered hundreds of transcriptional start sites within operons, and opposite to annotated genes, indicating that complexity of gene expression from the small H. pylori genome is increased by uncoupling of polycistrons and by genome-wide antisense transcription. We also discovered an unexpected number of ∼60 small RNAs including the ε-subdivision counterpart of the regulatory 6S RNA and associated RNA products, and potential regulators of cis - and trans -encoded target messenger RNAs. Our approach establishes a paradigm for mapping and annotating the primary transcriptomes of many living species. The Helicobacter pylori transcriptome The bacterium Helicobacter pylori infects about half the human population, thriving in the acid conditions of the stomach. Most carriers are asymptomatic, but some suffer inflammation, ulcers and gastric cancer. Now, using a novel approach that selects for the 5' ends of primary transcripts, the 'primary transcriptome' — predominantly the unprocessed messenger RNAs and small non-coding RNAs — has been determined for H. pylori in a variety of growth conditions. With the genome sequence and protein interactome previously published, this work provides the third global reference data set for the widely used Helicobacter strain 26695. The transcriptome of Helicobacter pylori , an important human pathogen involved in gastric ulcers and cancer, is presented. The approach establishes a model for mapping and annotating the primary transcriptomes of many living species.

Alzheimerʼs disease (AD) is a neurodegenerative disorder of unknown cause with complex genetic and environmental traits. While AD is extremely prevalent in human elderly, it hardly occurs in non-primate mammals and even non-human-primates develop only an incomplete form of the disease. This specificity of AD to human clearly implies a phylogenetic aspect. Still, the evolutionary dimension of AD pathomechanism remains difficult to prove and has not been established so far. To analyze the evolutionary age and dynamics of AD-associated-genes, we established the AD-associated genome-wide RNA-profile comprising both protein-coding and non-protein-coding transcripts. We than applied a systematic analysis on the conservation of splice-sites as a measure of gene-structure based on multiple alignments across vertebrates of homologs of AD-associated-genes. Here, we show that nearly all AD-associated-genes are evolutionarily old and did not originate later in evolution than not-AD-associated-genes. However, the gene-structures of loci, that exhibit AD-associated changes in their expression, evolve faster than the genome at large. While protein-coding-loci exhibit an enhanced rate of small changes in gene structure, non-coding loci show even much larger changes. The accelerated evolution of AD-associated-genes indicates a more rapid functional adaptation of these genes. In particular AD-associated non-coding-genes play an important, as yet largely unexplored, role in AD. This phylogenetic trait indicates that recent adaptive evolution of human brain is causally involved in basic principles of neurodegeneration. It highlights the necessity for a paradigmatic change of our disease-concepts and to reconsider the appropriateness of current animal-models to develop disease-modifying strategies that can be translated to human.

Human organoids could facilitate research of complex and currently incurable neuropathologies, such as age-related macular degeneration (AMD) which causes blindness. Here, we establish a human retinal organoid system reproducing several parameters of the human retina, including some within the macula, to model a complex combination of photoreceptor and glial pathologies. We show that combined application of TNF and HBEGF, factors associated with neuropathologies, is sufficient to induce photoreceptor degeneration, glial pathologies, dyslamination, and scar formation: These develop simultaneously and progressively as one complex phenotype. Histologic, transcriptome, live-imaging, and mechanistic studies reveal a previously unknown pathomechanism: Photoreceptor neurodegeneration via cell extrusion. This could be relevant for aging, AMD, and some inherited diseases. Pharmacological inhibitors of the mechanosensor PIEZO1, MAPK, and actomyosin each avert pathogenesis; a PIEZO1 activator induces photoreceptor extrusion. Our model offers mechanistic insights, hypotheses for neuropathologies, and it could be used to develop therapies to prevent vision loss or to regenerate the retina in patients suffering from AMD and other diseases. Complex neuropathologies, like macular degeneration, are common but incompletely understood. Here the authors report a complex human retina pathology organoid model induced by HBEGF-TNF, causing PIEZO1-mediated photoreceptor degeneration by cell extrusion.

Environmental factors contribute to the risk for adverse health outcomes against a background of genetic predisposition. Among these factors, chemical exposures may substantially contribute to disease risk and adverse outcomes. In fact, epidemiological cohort studies have established associations between exposure against individual chemicals and adverse health effects. Yet, in daily life individuals are exposed to complex mixtures in varying compositions. To capture the totality of environmental exposures the concept of the exposome has been developed. Here, we undertake an overview of major exposome projects, which pioneered the field of exposomics and explored the links between chemical exposure and health outcomes using cohort studies. We seek to reflect their achievements with regard to (i) capturing a comprehensive picture of the environmental chemical exposome, (ii) aggregating internal exposures using chemical and bioanalytical means of detection, and (iii) identifying associations that provide novel options for risk assessment and intervention. Various complementary approaches can be distinguished in addressing relevant exposure routes and it emerges that individual exposure histories may not easily be grouped. The number of chemicals for which human exposure can be detected is substantial and highlights the reality of mixture exposures. Yet, to a large extent it depends on targeted chemical analysis with the specific challenges to capture all relevant exposure routes and assess the chemical concentrations occurring in humans. The currently used approaches imply prior knowledge or hypotheses about relevant exposures. Typically, the number of chemicals considered in exposome projects is counted in dozens—in contrast to the several thousands of chemicals for which occurrence have been reported in human serum and urine. Furthermore, health outcomes are often still compared to single chemicals only. Moreover, explicit consideration of mixture effects and the interrelations between different outcomes to support causal relationships and identify risk drivers in complex mixtures remain underdeveloped and call for specifically designed exposome-cohort studies.

Chemicals in the aquatic environment can be harmful to organisms and ecosystems. Knowledge on effect concentrations as well as on mechanisms and modes of interaction with biological molecules and signaling pathways is necessary to perform chemical risk assessment and identify toxic compounds. To this end, we developed criteria and a pipeline for harvesting and summarizing effect concentrations from the US ECOTOX database for the three aquatic species groups algae, crustaceans, and fish and researched the modes of action of more than 3,300 environmentally relevant chemicals in literature and databases. We provide a curated dataset ready to be used for risk assessment based on monitoring data and the first comprehensive collection and categorization of modes of action of environmental chemicals. Authorities, regulators, and scientists can use this data for the grouping of chemicals, the establishment of meaningful assessment groups, and the development of in vitro and in silico approaches for chemical testing and assessment.

The RNA-binding proteins Roquin-1 and Roquin-2 redundantly control gene expression and cell-fate decisions. Here, we show that Roquin not only interacts with stem–loop structures, but also with a linear sequence element present in about half of its targets. Comprehensive analysis of a minimal response element of the Nfkbid 3′-UTR shows that six stem–loop structures cooperate to exert robust and profound post-transcriptional regulation. Only binding of multiple Roquin proteins to several stem–loops exerts full repression, which redundantly involved deadenylation and decapping, but also translational inhibition. Globally, most Roquin targets are regulated by mRNA decay, whereas a small subset, including the Nfat5 mRNA, with more binding sites in their 3′-UTRs, are also subject to translational inhibition. These findings provide insights into how the robustness and magnitude of Roquin-mediated regulation is encoded in complex cis -elements. Roquin targets are known to contain two types of sequence-structure motifs, the constitutive and the alternative decay elements (CDE and ADE). Here, the authors describe a linear Roquin binding element (LBE) also involved in target recognition, and show that Roquin binding affects the translation of a subset of targeted mRNAs.

Background A lack of reproducibility has been repeatedly criticized in computational research. High throughput sequencing (HTS) data analysis is a complex multi-step process. For most of the steps a range of bioinformatic tools is available and for most tools manifold parameters need to be set. Due to this complexity, HTS data analysis is particularly prone to reproducibility and consistency issues. We have defined four criteria that in our opinion ensure a minimal degree of reproducible research for HTS data analysis. A series of workflow management systems is available for assisting complex multi-step data analyses. However, to the best of our knowledge, none of the currently available work flow management systems satisfies all four criteria for reproducible HTS analysis. Results Here we present uap , a workflow management system dedicated to robust, consistent, and reproducible HTS data analysis. uap is optimized for the application to omics data, but can be easily extended to other complex analyses. It is available under the GNU GPL v3 license at https://github.com/yigbt/uap . Conclusions uap is a freely available tool that enables researchers to easily adhere to reproducible research principles for HTS data analyses.

The function of mucosal-associated invariant T (MAIT) cells highly depends on the mode of activation, either by recognition of bacterial metabolites via their T cell receptor (TCR) or in a TCR-independent manner via cytokines. The underlying molecular mechanisms are not entirely understood. To define the activation of MAIT cells on the molecular level, we applied a multi-omics approach with untargeted transcriptomics, proteomics and metabolomics. Transcriptomic analysis of E. coli - and TCR-activated MAIT cells showed a distinct transcriptional reprogramming, including altered pathways, transcription factors and effector molecules. We validated the consequences of this reprogramming on the phenotype by proteomics and metabolomics. Thus, and to distinguish between TCR-dependent and -independent activation, MAIT cells were stimulated with IL12/IL18, anti-CD3/CD28 or both. Only a combination of both led to full activation of MAIT cells, comparable to activation by E. coli . Using an integrated network-based approach, we identified key drivers of the distinct modes of activation, including cytokines and transcription factors, as well as negative feedback regulators like TWIST1 or LAG3. Taken together, we present novel insights into the biological function of MAIT cells, which may represent a basis for therapeutic approaches to target MAIT cells in pathological conditions.