Pred-O3, a web server to predict molecules, olfactory receptors and odor relationships.

The sense of smell is a biological process involving volatile molecules that interact with proteins called olfactory receptors to transmit a nervous message that allows the recognition of a perceived odor. However, the relationships between odorant molecules, olfactory receptors and odors (O3) are far from being well understood due to the combinatorial olfactory codes and large family of olfactory receptors. This is the reason why, based on 5802 odorant molecules and their annotations to 863 olfactory receptors (human) and 7029 odors and flavors annotations, a web server called Pred-O3 has been designed to provide insights into olfaction. Predictive models based on Artificial Intelligence have been developed allowing to suggest olfactory receptors and odors associated with a new molecule. In addition, based on the encoding of the odorant molecule's structure, physicochemical features related to odors and/or olfactory receptors are proposed. Finally, based on the structural models of the 98 olfactory receptors a systematic docking protocol can be applied and suggest if a molecule can bind or not to an olfactory receptor. Therefore, Pred-O3 is well suited to aid in the design of new odorant molecules and assist in fragrance research and sensory neuroscience. Pred-O3 is accessible at ' https://odor.rpbs.univ-paris-diderot.fr/'.

AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development.

MOTIVATION: Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome. RESULTS: Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment. AVAILABILITY AND IMPLEMENTATION: AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

NMR metabolomics study of chronic low-dose exposure to a cocktail of persistent organic pollutants.

Nowadays, exposure to endocrine-disrupting chemicals (EDCs), including persistent organic pollutants (POPs), is one of the most critical threats to public health. EDCs are chemicals that mimic, block, or interfere with hormones in the body's endocrine system and have been associated with a wide range of health issues. This innovative, untargeted metabolomics study investigates chronic low-dose internal exposure to a cocktail of POPs on multiple tissues that are known to accumulate these lipophilic compounds. Interestingly, the metabolic response differs among selected tissues/organs in mice. In the liver, we observed a dynamic effect according to the exposure time and the doses of POPs. In the brain tissue, the situation is the opposite, leading to the conclusion that the presence of POPs immediately gives a saturated effect that is independent of the dose and the duration of exposure studied. By contrast, for the adipose tissues, nearly no effect is observed. This metabolic profiling leads to a holistic and dynamic overview of the main metabolic pathways impacted in lipophilic tissues by a cocktail of POPs.

Integrating -omics approaches into population-based studies of endocrine disrupting chemicals: A scoping review.

Health effects of endocrine disrupting chemicals (EDCs) are challenging to detect in the general population. Omics technologies become increasingly common to identify early biological changes before the apparition of clinical symptoms, to explore toxic mechanisms and to increase biological plausibility of epidemiological associations. This scoping review systematically summarises the application of omics in epidemiological studies assessing EDCs-associated biological effects to identify potential gaps and priorities for future research. Ninety-eight human studies (2004-2021) were identified through database searches (PubMed, Scopus) and citation chaining and focused on phthalates (34 studies), phenols (19) and PFASs (17), while PAHs (12) and recently-used pesticides (3) were less studied. The sample sizes ranged from 10 to 12,476 (median = 159), involving non-pregnant adults (38), pregnant women (11), children/adolescents (15) or both latter populations studied together (23). Several studies included occupational workers (10) and/or highly exposed groups (11) focusing on PAHs, PFASs and pesticides, while studies on phenols and phthalates were performed in the general population only. Analysed omics layers included metabolic profiles (30, including 14 targeted analyses), miRNA (13), gene expression (11), DNA methylation (8), microbiome (5) and proteins (3). Twenty-one studies implemented targeted multi-assays focusing on clinical routine blood lipid traits, oxidative stress or hormones. Overall, DNA methylation and gene expression associations with EDCs did not overlap across studies, while some EDC-associated metabolite groups, such as carnitines, nucleotides and amino acids in untargeted metabolomic studies, and oxidative stress markers in targeted studies, were consistent across studies. Studies had common limitations such as small sample sizes, cross-sectional designs and single sampling for exposure biomonitoring. In conclusion, there is a growing body of evidence evaluating the early biological responses to exposure to EDCs. This review points to a need for larger longitudinal studies, wider coverage of exposures and biomarkers, replication studies and standardisation of research methods and reporting.

Gene-environment interactions in the associations of PFAS exposure with insulin sensitivity and beta-cell function in a Faroese cohort followed from birth to adulthood.

BACKGROUND: Exposure to perfluoroalkyl substances (PFAS) has been associated with changes in insulin sensitivity and pancreatic beta-cell function in humans. Genetic predisposition to diabetes may modify these associations; however, this hypothesis has not been yet studied. OBJECTIVES: To evaluate genetic heterogeneity as a modifier in the PFAS association with insulin sensitivity and pancreatic beta-cell function, using a targeted gene-environment (GxE) approach. METHODS: We studied 85 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes, in 665 Faroese adults born in 1986-1987. Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were measured in cord whole blood at birth and in participants' serum from age 28 years. We calculated the Matsuda-insulin sensitivity index (ISI) and the insulinogenic index (IGI) based on a 2 h-oral glucose tolerance test performed at age 28. Effect modification was evaluated in linear regression models adjusted for cross-product terms (PFAS*SNP) and important covariates. RESULTS: Prenatal and adult PFOS exposures were significantly associated with decreased insulin sensitivity and increased beta-cell function. PFOA associations were in the same direction but attenuated compared to PFOS. A total of 58 SNPs were associated with at least one PFAS exposure variable and/or Matsuda-ISI or IGI in the Faroese population and were subsequently tested as modifiers in the PFAS-clinical outcome associations. Eighteen SNPs showed interaction p-values (PGxE) < 0.05 in at least one PFAS-clinical outcome association, five of which passed False Discovery Rate (FDR) correction (PGxE-FDR<0.20). SNPs for which we found stronger evidence for GxE interactions included ABCA1 rs3890182, FTO rs9939609, FTO rs3751812, PPARG rs170036314 and SLC12A3 rs2289116 and were more clearly shown to modify the PFAS associations with insulin sensitivity, rather than with beta-cell function. DISCUSSION: Findings from this study suggest that PFAS-associated changes in insulin sensitivity could vary between individuals as a result of genetic predisposition and warrant replication in independent larger populations.

Application of AOPs to assist regulatory assessment of chemical risks - Case studies, needs and recommendations.

While human regulatory risk assessment (RA) still largely relies on animal studies, new approach methodologies (NAMs) based on in vitro, in silico or non-mammalian alternative models are increasingly used to evaluate chemical hazards. Moreover, human epidemiological studies with biomarkers of effect (BoE) also play an invaluable role in identifying health effects associated with chemical exposures. To move towards the next generation risk assessment (NGRA), it is therefore crucial to establish bridges between NAMs and standard approaches, and to establish processes for increasing mechanistically-based biological plausibility in human studies. The Adverse Outcome Pathway (AOP) framework constitutes an important tool to address these needs but, despite a significant increase in knowledge and awareness, the use of AOPs in chemical RA remains limited. The objective of this paper is to address issues related to using AOPs in a regulatory context from various perspectives as it was discussed in a workshop organized within the European Union partnerships HBM4EU and PARC in spring 2022. The paper presents examples where the AOP framework has been proven useful for the human RA process, particularly in hazard prioritization and characterization, in integrated approaches to testing and assessment (IATA), and in the identification and validation of BoE in epidemiological studies. Nevertheless, several limitations were identified that hinder the optimal usability and acceptance of AOPs by the regulatory community including the lack of quantitative information on response-response relationships and of efficient ways to map chemical data (exposure and toxicity) onto AOPs. The paper summarizes suggestions, ongoing initiatives and third-party tools that may help to overcome these obstacles and thus assure better implementation of AOPs in the NGRA.

Combining the Classification and Pharmacophore Approaches to Understand Homogeneous Olfactory Perceptions at Peripheral Level: Focus on Two Aroma Mixtures.

The mechanisms involved in the homogeneous perception of odorant mixtures remain largely unknown. With the aim of enhancing knowledge about blending and masking mixture perceptions, we focused on structure-odor relationships by combining the classification and pharmacophore approaches. We built a dataset of about 5000 molecules and their related odors and reduced the multidimensional space defined by 1014 fingerprints representing the structures to a tridimensional 3D space using uniform manifold approximation and projection (UMAP). The self-organizing map (SOM) classification was then performed using the 3D coordinates in the UMAP space that defined specific clusters. We explored the allocating in these clusters of the components of two aroma mixtures: a blended mixture (red cordial (RC) mixture, 6 molecules) and a masking binary mixture (isoamyl acetate/whiskey-lactone [IA/WL]). Focusing on clusters containing the components of the mixtures, we looked at the odor notes carried by the molecules belonging to these clusters and also at their structural features by pharmacophore modeling (PHASE). The obtained pharmacophore models suggest that WL and IA could have a common binding site(s) at the peripheral level, but that would be excluded for the components of RC. In vitro experiments will soon be carried out to assess these hypotheses.

AOP4EUpest: mapping of pesticides in adverse outcome pathways using a text mining tool.

MOTIVATION: Exposure to pesticides may lead to adverse health effects in human populations, in particular vulnerable groups. The main long-term health concerns are neurodevelopmental disorders, carcinogenicity as well as endocrine disruption possibly leading to reproductive and metabolic disorders. Adverse outcome pathways (AOP) consist in linear representations of mechanistic perturbations at different levels of the biological organization. Although AOPs are chemical-agnostic, they can provide a better understanding of the Mode of Action of pesticides and can support a rational identification of effect markers. RESULTS: With the increasing amount of scientific literature and the development of biological databases, investigation of putative links between pesticides, from various chemical groups and AOPs using the biological events present in the AOP-Wiki database is now feasible. To identify co-occurrence between a specific pesticide and a biological event in scientific abstracts from the PubMed database, we used an updated version of the artificial intelligence-based AOP-helpFinder tool. This allowed us to decipher multiple links between the studied substances and molecular initiating events, key events and adverse outcomes. These results were collected, structured and presented in a web application named AOP4EUpest that can support regulatory assessment of the prioritized pesticides and trigger new epidemiological and experimental studies. AVAILABILITY AND IMPLEMENTATION: http://www.biomedicale.parisdescartes.fr/aop4EUpest/home.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Endocrine Disrupting Chemicals: Current Understanding, New Testing Strategies and Future Research Needs.

Endocrine disrupting chemicals (EDCs) are exogenous chemicals which can disrupt any action of the endocrine system, and are an important class of substances which play a role in the Developmental Origins of Health and Disease (DOHaD) [...].

sAOP: linking chemical stressors to adverse outcomes pathway networks.

MOTIVATION: Adverse outcome pathway (AOP) is a toxicological concept proposed to provide a mechanistic representation of biological perturbation over different layers of biological organization. Although AOPs are by definition chemical-agnostic, many chemical stressors can putatively interfere with one or several AOPs and such information would be relevant for regulatory decision-making. RESULTS: With the recent development of AOPs networks aiming to facilitate the identification of interactions among AOPs, we developed a stressor-AOP network (sAOP). Using the 'cytotoxitiy burst' (CTB) approach, we mapped bioactive compounds from the ToxCast data to a list of AOPs reported in AOP-Wiki database. With this analysis, a variety of relevant connections between chemicals and AOP components can be identified suggesting multiple effects not observed in the simplified 'one-biological perturbation to one-adverse outcome' model. The results may assist in the prioritization of chemicals to assess risk-based evaluations in the context of human health. AVAILABILITY AND IMPLEMENTATION: sAOP is available at http://saop.cpr.ku.dk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrative systems toxicology to predict human biological systems affected by exposure to environmental chemicals.

Biological systems are disturbed by several factors that are defined by the exposome. Environmental substances, including endocrine disruptors (EDs), represent the chemical exposome. These stressors may alter biological systems, that could lead to toxic health effects. Even if scientific evidence provide links between diverse environmental substances and disorders, innovative approaches, including alternative methods to animal testing, are still needed to address the complexity of the chemical mechanisms of action. Network science appears to be a valuable approach for helping to decipher a comprehensive assessment of the chemical exposome. A computational protein system-system association network (pS-SAN), based on various data sources such as chemical-protein interactions, chemical-system links, and protein-tissue associations was developed. The integrative systems toxicological model was applied to three EDs, to predict potential biological systems they may perturb. The results revealed that several systems may be disturbed by theses EDs, such as the kidney, liver and endocrine systems. The presented network-based approach highlights an opportunity to shift the paradigm of chemical risk assessment towards a better understanding of chemical toxicology mechanisms.

Integrative Strategy of Testing Systems for Identification of Endocrine Disruptors Inducing Metabolic Disorders-An Introduction to the OBERON Project.

Exposure to chemical substances that can produce endocrine disrupting effects represents one of the most critical public health threats nowadays. In line with the regulatory framework implemented within the European Union (EU) to reduce the levels of endocrine disruptors (EDs) for consumers, new and effective methods for ED testing are needed. The OBERON project will build an integrated testing strategy (ITS) to detect ED-related metabolic disorders by developing, improving and validating a battery of test systems. It will be based on the concept of an integrated approach for testing and assessment (IATA). OBERON will combine (1) experimental methods (in vitro, e.g., using 2D and 3D human-derived cells and tissues, and in vivo, i.e., using zebrafish at different stages), (2) high throughput omics technologies, (3) epidemiology and human biomonitoring studies and (4) advanced computational models (in silico and systems biology) on functional endpoints related to metabolism. Such interdisciplinary framework will help in deciphering EDs based on a mechanistic understanding of toxicity by providing and making available more effective alternative test methods relevant for human health that are in line with regulatory needs. Data generated in OBERON will also allow the development of novel adverse outcome pathways (AOPs). The assays will be pre-validated in order to select the test systems that will show acceptable performance in terms of relevance for the second step of the validation process, i.e., the inter-laboratory validation as ring tests. Therefore, the aim of the OBERON project is to support the organization for economic co-operation and development (OECD) conceptual framework for testing and assessment of single and/or mixture of EDs by developing specific assays not covered by the current tests, and to propose an IATA for ED-related metabolic disorder detection, which will be submitted to the Joint Research Center (JRC) and OECD community.

Exploring the Characteristics of an Aroma-Blending Mixture by Investigating the Network of Shared Odors and the Molecular Features of Their Related Odorants.

The perception of aroma mixtures is based on interactions beginning at the peripheral olfactory system, but the process remains poorly understood. The perception of a mixture of ethyl isobutyrate (Et-iB, strawberry-like odor) and ethyl maltol (Et-M, caramel-like odor) was investigated previously in both human and animal studies. In those studies, the binary mixture of Et-iB and Et-M was found to be configurally processed. In humans, the mixture was judged as more typical of a pineapple odor, similar to allyl hexanoate (Al-H, pineapple-like odor), than the odors of the individual components. To explore the key features of this aroma blend, we developed an in silico approach based on molecules having at least one of the odors-strawberry, caramel or pineapple. A dataset of 293 molecules and their related odors was built. We applied the notion of a "social network" to describe the network of the odors. Additionally, we explored the structural properties of the molecules in this dataset. The network of the odors revealed peculiar links between odors, while the structural study emphasized key characteristics of the molecules. The association between "strawberry" and "caramel" notes, as well as the structural diversity of the "strawberry" molecules, were notable. Such elements would be key to identifying potential odors/odorants to form aroma blends.

A systems biology approach to predictive developmental neurotoxicity of a larvicide used in the prevention of Zika virus transmission.

The need to prevent developmental brain disorders has led to an increased interest in efficient neurotoxicity testing. When an epidemic of microcephaly occurred in Brazil, Zika virus infection was soon identified as the likely culprit. However, the pathogenesis appeared to be complex, and a larvicide used to control mosquitoes responsible for transmission of the virus was soon suggested as an important causative factor. Yet, it is challenging to identify relevant and efficient tests that are also in line with ethical research defined by the 3Rs rule (Replacement, Reduction and Refinement). Especially in an acute situation like the microcephaly epidemic, where little toxicity documentation is available, new and innovative alternative methods, whether in vitro or in silico, must be considered. We have developed a network-based model using an integrative systems biology approach to explore the potential developmental neurotoxicity, and we applied this method to examine the larvicide pyriproxyfen widely used in the prevention of Zika virus transmission. Our computational model covered a wide range of possible pathways providing mechanistic hypotheses between pyriproxyfen and neurological disorders via protein complexes, thus adding to the plausibility of pyriproxyfen neurotoxicity. Although providing only tentative evidence and comparisons with retinoic acid, our computational systems biology approach is rapid and inexpensive. The case study of pyriproxyfen illustrates its usefulness as an initial or screening step in the assessment of toxicity potentials of chemicals with incompletely known toxic properties.

Proteomic analysis of cAMP-mediated signaling during differentiation of 3 T3-L1 preadipocytes.

Initiation of adipocyte differentiation is promoted by the synergistic action of insulin/insulin-like growth factor, glucocorticoids, and agents activating cAMP-dependent signaling. The action of cAMP is mediated via PKA and Epac, where at least part of the PKA function relates to strong repression of Rho kinase activity, whereas Epac counteracts the reduction in insulin/insulin-like growth factor signaling associated with complete repression of Rho kinase activity. However, detailed knowledge of the Epac-dependent branch and the interplay with PKA is still limited. In the present study, we present a comprehensive evaluation of Epac-mediated processes and their interplay with PKA during the initiation of 3 T3-L1 preadipocyte differentiation using a combination of proteomics, molecular approaches, and bioinformatics. Proteomic analyses revealed 7 proteins specifically regulated in response to Epac activation, 4 in response to PKA activation, and 11 in response to the combined activation of Epac and PKA during the initial phase of differentiation. Network analyses indicated that the identified proteins are involved in pathways of importance for glucose metabolism, inositol metabolism, and calcium-dependent signaling thereby adding a novel facet to our understanding of cAMP-mediated potentiation of adipocyte differentiation.

Transcriptome profiling of brown adipose tissue during cold exposure reveals extensive regulation of glucose metabolism.

We applied digital gene expression profiling to determine the transcriptome of brown and white adipose tissues (BAT and WAT, respectively) during cold exposure. Male C57BL/6J mice were exposed to cold for 2 or 4 days. A notable induction of genes related to glucose uptake, glycolysis, glycogen metabolism, and the pentose phosphate pathway was observed in BAT from cold-exposed animals. In addition, glycerol-3-phosphate dehydrogenase 1 expression was induced in BAT from cold-challenged mice, suggesting increased synthesis of glycerol from glucose. Similarly, expression of lactate dehydrogenases was induced by cold in BAT. Pyruvate dehydrogenase kinase 2 (Pdk2) and Pdk4 were expressed at significantly higher levels in BAT than in WAT, and Pdk2 was induced in BAT by cold. Of notice, only a subset of the changes detected in BAT was observed in WAT. Based on changes in gene expression during cold exposure, we propose a model for the intermediary glucose metabolism in activated BAT: 1) fluxes through glycolysis and the pentose phosphate pathway are induced, the latter providing reducing equivalents for de novo fatty acid synthesis; 2) glycerol synthesis from glucose is increased, facilitating triacylglycerol synthesis/fatty acid re-esterification; 3) glycogen turnover and lactate production are increased; and 4) entry of glucose carbon into the tricarboxylic acid cycle is restricted by PDK2 and PDK4. In summary, our results demonstrate extensive and diverse gene expression changes related to glucose handling in activated BAT.

Chemical biology databases: from aggregation, curation to representation.

Systems chemical biology offers a novel way of approaching drug discovery by developing models that consider the global physiological environment of protein targets and their perturbations by drugs. However, the integration of all these data needs curation and standardization with an appropriate representation in order to get relevant interpretations. In this mini review, we present some databases and services, which integrated together with computational tools and data standardization, could assist scientists in decision making during the different drug development process.

ChemProt-2.0: visual navigation in a disease chemical biology database.

ChemProt-2.0 (http://www.cbs.dtu.dk/services/ChemProt-2.0) is a public available compilation of multiple chemical-protein annotation resources integrated with diseases and clinical outcomes information. The database has been updated to >1.15 million compounds with 5.32 millions bioactivity measurements for 15 290 proteins. Each protein is linked to quality-scored human protein-protein interactions data based on more than half a million interactions, for studying diseases and biological outcomes (diseases, pathways and GO terms) through protein complexes. In ChemProt-2.0, therapeutic effects as well as adverse drug reactions have been integrated allowing for suggesting proteins associated to clinical outcomes. New chemical structure fingerprints were computed based on the similarity ensemble approach. Protein sequence similarity search was also integrated to evaluate the promiscuity of proteins, which can help in the prediction of off-target effects. Finally, the database was integrated into a visual interface that enables navigation of the pharmacological space for small molecules. Filtering options were included in order to facilitate and to guide dynamic search of specific queries.

HExpoChem: a systems biology resource to explore human exposure to chemicals.

SUMMARY: Humans are exposed to diverse hazardous chemicals daily. Although an exposure to these chemicals is suspected to have adverse effects on human health, mechanistic insights into how they interact with the human body are still limited. Therefore, acquisition of curated data and development of computational biology approaches are needed to assess the health risks of chemical exposure. Here we present HExpoChem, a tool based on environmental chemicals and their bioactivities on human proteins with the objective of aiding the qualitative exploration of human exposure to chemicals. The chemical-protein interactions have been enriched with a quality-scored human protein-protein interaction network, a protein-protein association network and a chemical-chemical interaction network, thus allowing the study of environmental chemicals through formation of protein complexes and phenotypic outcomes enrichment. AVAILABILITY: HExpoChem is available at http://www.cbs.dtu.dk/services/HExpoChem-1.0/.

Polychlorinated dibenzo-p-dioxins, furans, and biphenyls (PCDDs/PCDFs and PCBs) in breast milk and early childhood growth and IGF1.

Experimental studies have shown that dioxin-like chemicals may interfere with aspects of the endocrine system including growth. However, human background population studies are, however, scarce. We aimed to investigate whether early exposure of healthy infants to dioxin-like chemicals was associated with changes in early childhood growth and serum IGF1. In 418 maternal breast milk samples of Danish children (born 1997-2001) from a longitudinal cohort, we measured polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, and polychlorinated biphenyls (pg or ng/g lipid) and calculated total toxic equivalent (total TEQ). SDS and SDS changes over time (ΔSDS) were calculated for height, weight, BMI, and skinfold fat percentage at 0, 3, 18, and 36 months of age. Serum IGF1 was measured at 3 months. We adjusted for confounders using multivariate regression analysis. Estimates (in parentheses) correspond to a fivefold increase in total TEQ. TEQ levels in breast milk increased significantly with maternal age and fish consumption and decreased with maternal birth year, parity, and smoking. Total TEQ was associated with lower fat percentage (-0.45 s.d., CI: -0.89; -0.04), non-significantly with lower weight and length at 0 months, accelerated early height growth (increased ΔSDS) (ΔSDS 0-18 months: +0.77 s.d., CI: 0.34; 1.19) and early weight increase (ΔSDS 0-18: +0.52 s.d., CI: 0.03; 1.00), and increased IGF1 serum levels at 3 months (+13.9 ng/ml, CI: 2.3; 25.5). Environmental exposure to dioxin-like chemicals was associated with being skinny at birth and with higher infant levels of circulating IGF1 as well as accelerated early childhood growth (rapid catch-up growth).