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Background Vascular abnormalities and endothelial dysfunction are part of the spectrum of autosomal dominant polycystic kidney disease (ADPKD). The mechanisms behind these manifestations, including potential effects on the endothelial surface layer (ESL) and glycocalyx integrity, remain unknown. Methods Forty-five ambulatory adult patients with ADPKD were enrolled in this prospective, observational, cross-sectional, single-centre study. Fifty-one healthy volunteers served as a control group. All participants underwent real-time microvascular perfusion measurements of the sublingual microcirculation using sidestream dark field imaging. After image acquisition, the perfused boundary region (PBR), an inverse parameter for red blood cell (RBC) penetration into the ESL, was automatically calculated. Microvascular perfusion was assessed by RBC filling and capillary density. Concentrations of circulating glycocalyx components were determined by enzyme-linked immunosorbent assay. Results ADPKD patients showed a significantly larger PBR compared with healthy controls (2.09 ± 0.23 µm versus 1.79 ± 0.25 µm; P Conclusions Dimensions and integrity of the ESL are impaired in ADPKD patients. Increased capillary density may be a compensatory mechanism for vascular dysfunction to ensure sufficient tissue perfusion and oxygenation.

Background The identification of new biomarkers in autosomal-dominant polycystic kidney disease (ADPKD) is crucial to improve and simplify prognostic assessment as a basis for patient selection for targeted therapies. Post-Hoc-Analyses of the TEMPO 3:4 study indicated that copeptin could be one of those biomarkers. Methods Copeptin was tested in serum samples from patients of the AD(H)PKD study. Serum copeptin levels were measured using a time-resolved amplified cryptate emission (TRACE) based assay. In total, we collected 711 values from 389 patients without tolvaptan treatment and a total of 243 values (of which 64 were pre-tolvaptan) from 94 patients on tolvaptan. These were associated to rapid progression and disease-causing gene variants and their predictive capacity tested and compared to the Mayo Classification. Results As expected, copeptin levels showed a significant negative correlation with eGFR. Measurements on tolvaptan showed significantly higher copeptin levels (9.871 pmol/l vs. 23.90 pmol/l at 90/30 mg; p Conclusion Copeptin levels are associated with kidney function and independently explained future eGFR slopes. As expected, treatment with tolvaptan strongly increases copeptin levels.

Background/aim Utilising radiotherapy in the management of head and neck cancer (HNC) often results in long term toxicities. Mandibular osteoradionecrosis (ORN) represents a late toxicity associated with significant morbidity. We aim to identify a panel of common genetic variants which can predict ORN to aid development ofpersonalised radiotherapy protocols. Method Single nucleotide polymorphism (SNP) arrays were applied to DNA samples from patients who had prior HNC radiotherapy and minimum two years follow-up. A case cohort of mandibular ORN was compared to a control group of participants recruited to CRUK HOPON clinical trial. Relevant clinical parameters influencing ORN risk (e.g. smoking/alcohol) were collected. Significant associations from array data were internally validated using polymerase chain reaction (PCR) and pyrosequencing. Results Following inclusion of 141 patients in the analysis (52 cases, 89 controls), a model predictive for ORN was developed; after controlling for alcohol consumption, smoking, and age 4053 SNPs were identified as significant. This was reduced to a representative model of 18 SNPs achieving 92% accuracy. Following internal technical validation, a six SNP model (rs34798038, rs6011731, rs2348569, rs530752, rs7477958, rs1415848) was retained within multivariate regression analysis (ROC AUC 0.859). Of these, four SNPs (rs34798038 (A/G)(p 0.006), rs6011731 (C/T)(p 0.018), rs530752 (A/G)(p 0.046) and rs2348569 (G/G)(p 0.005)) were significantly associated with the absence of ORN. Conclusion This is the first genome wide association study in HNC using ORN as the endpoint and offers new insight into ORN pathogenesis. Subject to validation, these variants may guide patient selection for personalised radiotherapy strategies.

BACKGROUND Prediction of disease progression is one of the main challenges in the treatment of Autosomal-Dominant Polycystic Kidney Disease (ADPKD). In addition to already established biomarkers such as total kidney volume (TKV), further biomarkers that are feasible and easy to collect would be important to allow conclusions on prognosis as well as, in the best case, on long-term treatment response. Post-hoc analyses of the TEMPO 3:4 study showed that copeptin could serve as such a biomarker [1, 2]. In this study, we investigated copeptin over a multi-year course in participants of the AD(H)PKD study. METHOD Copeptin was measure from serum samples of 486 patients in the AD(H)PKD study at both initial and follow-up presentations. A total of 95 patients were on tolvaptan therapy at least at one of the measurement time points. We examined the measured values with respect to their distribution in different patient groups (e.g. age, Mayo class) and their changes on tolvaptan administration. Baseline eGFR values were developed using historic creatinine measurements up to 8000 days prior and 1500 days after copeptin measurements. For each patient with at least 5 creatinine measurements an eGFR slope was calculated. The models were developed using a robust linear modelling approach. Slopes were extracted to be the parameter associated to date and multiplied by 365 to retrieve an annual eGFR slope. eGFRs predicted for the specific dates at which copeptin has been measured were then calculated and used in subsequent modelling approaches. To develop a model predictive of eGFR, we used a stepwise regression approach, removing insignificant coefficients at each step. RESULTS As expected, copeptin was significantly lower in 391 tolvaptan naive patients than in 95 patients on therapy (9.95 pmol/L versus 19.78 pmol/L; P CONCLUSION Our data obtained from the real-life setting should again be reconciled with the results from the TEMPO 3:4 cohort. Our findings show that copeptin levels are both associated with kidney function and with future eGFR loss. Adding copeptin to the model of the Mayo Classification indeed improves the prediction of future eGFR. However, it is not clear yet whether this mild effect will have an impact in routine clinical care. Copeptin has the potential to facilitate prognostic assessment as a biomarker and thus could be helpful in deciding on therapy initiation and possibly more patient-specific dosing. Future analyses of outcome in relation to copeptin will provide further data and might enable implementation in clinical practice.

Motivation A fundamental problem for disease treatment is that while antibiotics are a powerful counter to bacteria, they are ineffective against viruses. Often, bacterial and viral infections are confused due to their similar symptoms and lack of rapid diagnostics. With many clinicians relying primarily on symptoms for diagnosis, overuse and misuse of modern antibiotics are rife, contributing to the growing pool of antibiotic resistance. To ensure an individual receives optimal treatment given their disease state and to reduce over-prescription of antibiotics, the host response can in theory be measured quickly to distinguish between the two states. To establish a predictive biomarker panel of disease state (viral/bacterial/no-infection), we conducted a meta-analysis of human blood infection studies using machine learning. Results We focused on publicly available gene expression data from two widely used platforms, Affymetrix and Illumina microarrays as they represented a significant proportion of the available data. We were able to develop multi-class models with high accuracies with our best model predicting 93% of bacterial and 89% viral samples correctly. To compare the selected features in each of the different technologies, we reverse-engineered the underlying molecular regulatory network and explored the neighbourhood of the selected features. The networks highlighted that although on the gene-level the models differed, they contained genes from the same areas of the network. Specifically, this convergence was to pathways including the Type I interferon Signalling Pathway, Chemotaxis, Apoptotic Processes and Inflammatory/Innate Response. Availability Data and code are available on the Gene Expression Omnibus and github. Supplementary information Supplementary data are available at Bioinformatics online.

Supplementary data related to this article: Supplementary material, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc1.docx (Word document35, 5KB)); Supplementary Data 1. These are the chemicals along with their properties and the calculated doses given for the C. elegans (Caenorhabditis elegans), available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc2.xls (spreadsheet, 68KB); Supplementary Data 2. These are the chemicals and the doses given for the trout gill cell line (Rtgill-WT1). The codes here relate to the same codes on the microarray data, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc3.xlsx (spreadsheet; 11KB); Supplementary Data 3. These are the probes found to be significantly different between exposed and unexposed C. elegans for each of the narcotic chemicals tested, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc4.xlsx (spreadsheet, 363KB); Supplementary Data 4. The file provide the metabolite composition of the three clusters identified by running a metabolic-based predictive model, available at https://ars.els-cdn.com/content/image/1-s2.0-S0048969722047647-mmc5.xlsx (spreadsheet, 10KB). Copyright © 2022 The Authors. With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical. Unilever Ltd.

To investigate whether a tailored intersectoral discharge program (TIDP) impacts on multidimensional frailty, rehospitalization days, and patient-related outcome measures in older in-patients undergoing acute care and usual rehabilitative care.Randomized controlled trial of TIDP vs usual rehabilitative care with a 6-month follow-up, 2019-2020, and historical control with a 6-month follow-up, 2016-2019.Geriatric co-managed internal medicine ward of a metropolitan university hospital. One hundred-twelve multimorbid patients older than age 60 years were consecutively assessed for eligibility and inclusion (age ≥60 years, multimorbidity, admitted for treatment of acute disease, at least 2 geriatric syndromes requiring usual rehabilitative care, and able to consent) and signed informed consent, with 110 recruited and randomized to either TIDP or usual rehabilitative care. At discharge, 104 patients were alive in the intention-to-treat group, the 6-month follow-up was completed for 91 patients. A historical control group of 468 patients was included for comparison.TIDP as intervention included contact with treating general practitioner to discuss the further treatment plan, a structured medical and lifestyle counseling to patients and caregivers at admission as well as a discharge program with internist, geriatrician, and general practitioner in shared decision making with patients.Fifty-four patients underwent TIDP, 53 patients underwent usual rehabilitative care only. Rehospitalization days at follow-up as primary endpoint; multidimensional frailty and prognosis (Multidimensional Prognostic Index, Geriatric Depression Scale, Rosenberg Self-Esteem Scale, quality of life, falls, mortality, home care service need, and need of long-term care at 1-, 3- and 6-month follow-up as secondary endpoints.TIDP (median age 76.0 years, 56% female) showed significantly improved Multidimensional Prognostic Index scores at discharge compared with usual rehabilitative care (median age 78.5 years, 58% female) (0.43 vs 0.49, P = .011). Compared with usual rehabilitative care, TIDP improved self-confidence (Rosenberg Self-Esteem Scale 13.9 vs 12.4, P = .009) and mood (Geriatric Depression Scale 4 vs 5, P = .027) at follow-up. Compared with historical control (median age 77.0 years, 39 % female), usual rehabilitative care patients showed significantly lower rehospitalization rates (53% vs 70%, P = .002) and lower mortality rates (13% vs 32%, P.001).A feasible TIDP improves frailty and mood in advanced age. In older patients undergoing potentially disabling acute treatments, usual rehabilitative care significantly reduces rehospitalization rates. Therefore, implementing geriatric treatment in general is useful to improve outcomes in older in-patients and a tailored discharge program can further increase the benefit for this frail population.

The fish acute toxicity test (TG203; OECD, 2019) is frequently used and highly embedded in hazard and risk assessment globally. The test estimates the concentration of a chemical that kills 50% of the fish (LC50) over a 96 h exposure and is considered one of the most severe scientific procedures undertaken. Over the years, discussions at the Organisation for Economic Co-operation and Development (OECD) have resulted in changes to the test which reduce the number of fish used, as well as the development of a (potential) replacement test (TG236, OECD, 2013). However, refinement of the mortality endpoint with an earlier (moribundity) endpoint was not considered feasible during the Test Guideline’s (TG) last update in 2019. Several stakeholders met at a UK-based workshop to discuss how TG203 can be refined, and identified two key opportunities to reduce fish suffering: (1) application of clinical signs that predict mortality and (2) shortening the test duration. However, several aspects need to be addressed before these refinements can be adopted. TG203 has required recording of major categories of sublethal clinical signs since its conception, with the option to record more detailed signs introduced in the 2019 update. However, in the absence of guidance, differences in identification, recording and reporting of clinical signs between technicians and laboratories is likely to have generated piecemeal data of varying quality. Harmonisation of reporting templates, and training in clinical sign recognition and recording are needed to standardise clinical sign data. This is critical to enable robust data-driven detection of clinical signs that predict mortality. Discussions suggested that the 96 h duration of TG203 cannot stand up to scientific scrutiny. Feedback and data from UK contract research organisations (CROs) conducting the test were that a substantial proportion of mortalities occur in the first 24 h. Refinement of TG203 by shortening the test duration would reduce suffering (and test failure rate) but requires a mechanism to correct new results to previous 96 h LC50 data. The actions needed to implement both refinement opportunities are summarised here within a roadmap. A shift in regulatory assessment, where the 96 h LC50 is a familiar base for decisions, will also be critical. publishedVersion

Nutritional and contaminant stressors influence organismal physiology, trophic interactions, community structure, and ecosystem-level processes; however, the interactions between toxicity and elemental imbalance in food resources have been examined in only a few ecotoxicity studies. Integrating well-developed ecological theories that cross all levels of biological organization can enhance our understanding of ecotoxicology. In the present article, we underline the opportunity to couple concepts and approaches used in the theory of ecological stoichiometry (ES) to ask ecotoxicological questions and introduce stoichiometric ecotoxicology, a subfield in ecology that examines how contaminant stress, nutrient supply, and elemental constraints interact throughout all levels of biological organization. This conceptual framework unifying ecotoxicology with ES offers potential for both empirical and theoretical studies to deepen our mechanistic understanding of the adverse outcomes of chemicals across ecological scales and improve the predictive powers of ecotoxicology.

International audience; The pyrethroid insecticide permethrin is widely used for agricultural and domestic purposes. Previous data indicated that it acts as a developmental neurotoxicant and can induce transgenerational effects in non-target organisms. However, associated underlying mechanisms remain unclear. The aim of this study was to investigate permethrin-related transgenerational effects in the zebrafish model, and to identify possible molecular mechanisms underlying inheritance. Zebrafish (F0) were exposed to permethrin during early-life (2 hours postfertilization up to 28 days). The F1 and F2 offspring generations were obtained by pairing exposed F0 males and females, and were bred unexposed. Locomotor and anxiety behavior were investigated, together with transcriptomic and epigenomic (DNA methylation) changes in brains. Permethrin exposed F0 fish were hypoactive at adulthood, while males from the F1 and F2 generations showed a specific decrease in anxiety-like behavior. In F0, transcriptomic data showed enrichment in pathways related to glutamatergic synapse activity, which may partly underlie the behavioral effects. In F1 and F2 males, dysregulation of similar pathways was observed, including a subset of differentially methylated regions that were inherited from the F0 to the F2 generation and indicated stable dysregulation of glutamatergic signaling. Altogether, the present results provide novel evidence on the transgenerational neurotoxic effects of permethrin, as well as mechanistic insight: a transient exposure induces persistent transcriptional and DNA methylation changes that may translate into transgenerational alteration of glutamatergic signaling and, thus, into behavioral alterations.

The monitoring of anthropogenic chemicals in the aquatic environment including their potential effects on aquatic organisms, is important for protecting life under water, a key sustainable development goal. In parallel with monitoring the concentrations of chemicals of concern, sentinel species are often used to investigate the biological effects of contaminants. Among these, bivalve molluscs such as mussels are filter-feeding and sessile, hence an excellent model system for measuring localized pollution.This study investigates the relationship between the metabolic state of the blue mussel (Mytilus edulis) and its physiology in different environments. We developed a computational model based on a reference site (relatively unpolluted) and integrated seasonal dynamics of metabolite relative concentrations with key physiological indicators and environmental parameters. The analysis of the model revealed that changes in metabolite levels during an annual cycle are influenced by water temperature and are linked to gonadal development. This work supports the importance of data-driven biology and its potential in environmental monitoring.

Kidney transplantation is the preferred renal replacement therapy available. Yet, long‐term transplant survival is unsatisfactory, partially due to insufficient possibilities of longitudinal monitoring and understanding of the biological processes after transplantation. Small urinary extracellular vesicles (suEVs) – as a non‐invasive source of information – were collected from 22 living donors and recipients. Unbiased proteomic analysis revealed temporal patterns of suEV protein signature and cellular processes involved in both early response and longer‐term graft adaptation. Complement activation was among the most dynamically regulated components. This unique atlas of the suEV proteome is provided through an online repository allowing dynamic interrogation by the user. Additionally, a correlative analysis identified putative prognostic markers of future allograft function. One of these markers – phosphoenol pyruvate carboxykinase (PCK2) – could be confirmed using targeted MS in an independent validation cohort of 22 additional patients. This study sheds light on the impact of kidney transplantation on urinary extracellular vesicle content and allows the first deduction of early molecular processes in transplant biology. Beyond that our data highlight the potential of suEVs as a source of biomarkers in this setting.

A fundamental problem for disease treatment is that while antibiotics are a powerful counter to bacteria, they are ineffective against viruses. To ensure a given individual receives optimal treatment given their disease state and to reduce over-prescription of antibiotics leading to antimicrobial resistance, the host response can be measured to distinguish between the two states. To establish a predictive biomarker panel of disease state we conducted a meta-analysis of human blood infection studies using Machine Learning (ML). We focused on publicly available gene expression data from two widely used platforms, Affymetrix and Illumina microarrays, and integrated over 2000 samples for each platform to develop optimal gene panels. On average our models predicted 80% of bacterial and 85% viral samples correctly by class of infection type. For our best performing model, identified with an evolutionary algorithm, 93% of bacterial and 89% of viral samples were classified correctly. To enable comparison between the two differing microarray platforms, we reverse engineered the underlying molecular regulatory network and overlay the identified models. This revealed that although the exact gene-level overlap between models generated from the two technologies was relatively low, both models contained genes in the same areas of the network, indicating that the same functional changes in host biology were being detected, providing further confidence in the robustness of our models. Specifically, this convergence was to pathways including the Type I interferon Signalling Pathway, Chemotaxis, Apoptotic Processes, and Inflammatory / Innate Response. Amongst and related to these pathways we found three genes,IFI27, LY6E, andCD177, particularly prevalent throughout our analysis.Author summaryBacterial and viral disease require specific treatments, and whilst there are various treatment options for specific infection types, rapid diagnosis and identification of the optimal treatment remains challenging. Even in wealthier countries with developed healthcare systems, unnecessary prescription of antibiotics to patients with viral infections is causing phenomena such as multi-drug resistent bacteria. One way to distinguish a viral from bacterial infection is to measure an individual’s responses, for example by measuring the expression of particular genes in a blood sample, as different types of infections trigger different types of responses. In our study we analysed thousands of previously collected data sets from human blood, where individuals had either viral, bacterial or no infection (control). We used machine learning to identify “signatures” – small sets of genes that are indicative of the type of infection (if any) carried by an individual. Within data sets we used two different technology platforms had been used to collect data. We demonstrated that their gene-level signatures do not overlap perfectly when derived from the different platforms, the biological networks from which those genes were derived, however, had a high overlap – giving confidence that our models are robust against technology artefacts or bias. We have identified a small set of genes that serve as strong biomarkers of infection status in humans.

Motivation The molecular processes regulating molluscan shell production remain relatively uncharacterized, despite the clear evolutionary and societal importance of biomineralization. Results Here we built the first computationally predicted gene regulatory network (GRN) for molluscan biomineralization using Antarctic clam (Laternula elliptica) mantle gene expression data produced over an age-categorized shell damage-repair time-course. We used previously published in vivo in situ hybridization expression data to ground truth gene interactions predicted by the GRN and show that candidate biomineralization genes from different shell layers, and hence microstructures, were connected in unique modules. We characterized two biomineralization modules of the GRN and hypothesize that one module is responsible for translating the extracellular proteins required for growing, repairing or remodelling the nacreous shell layer, whereas the second module orchestrates the transport of both ions and proteins to the shell secretion site, which are required during normal shell growth, and repair. Our findings demonstrate that unbiased computational methods are particularly valuable for studying fundamental biological processes and gene interactions in non-model species where rich sources of gene expression data exist, but annotation rates are poor and the ability to carry out true functional tests are still lacking. Availability and implementation The raw RNA-Seq data is freely available for download from NCBI SRA (Accession: PRJNA398984), the assembled and annotated transcriptome can be viewed and downloaded from molluscDB (ensembl.molluscdb.org) and in addition, the assembled transcripts, reconstructed GRN, modules and detailed annotations are all available as Supplementary Files. Supplementary information Supplementary data are available at Bioinformatics online.

Coal ash contains numerous contaminants and is the focus of regulatory actions and risk assessments due to environmental spills. We exposed Daphnia magna to a gradient of coal ash contamination under high and low food rations to assess the sublethal effects of dietary exposures. Whereas exposure to contaminants resulted in significant reductions in growth and reproduction in daphnids, low, environmentally relevant food rations had a much greater effect on these endpoints. Environ Toxicol Chem 2020;39:1998-2007. © 2020 SETAC.

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

© 2021 The Authors. Advanced treatment technologies are being assessed as a proactive measure to assist with the transformation of treated wastewater into a source of water for potable water production. We investigated the biological effects along an advanced water treatment pilot plant, using zebrafish embryos throughout early development. The study compared phenotypic observations with global transcriptome responses, enabling us to keep an open mind about the chemicals that might influence the biological activity. There was no evidence of acute toxicity at any treatment stage, but skeletal, cardiovascular and pigmentation changes occurred in a small proportion of embryos along the treatment process, and in a tap water; not detected in the aquarium water control. Reverse osmosis (RO) reduced the concentration of measured chemical contaminants in the water the most, while eliminating the occurrence of abnormalities detected in fish embryos. Conversely, advanced oxidation reversed the benefits of RO treatment by increasing the frequency of teratogenic and sub-lethal abnormalities seen. Using the molecular responses of zebrafish embryos to different IPR water, we report the bioactivity within the water at different stages of advanced treatment and associate these to perturbed biological functions. Transcriptomic analysis revealed alterations to the retinoid system, which was consistent with the observed teratogenic effects. Changes to tryptophan metabolism (associated with the production of melatonin required for the control of normal circadian rhythms) and somatolactin-beta (associated with normal pigmentation in fish) were also found. We show that underexplored forms of biological activity occur in treated wastewater effluent, and/or may be created depending on the type of advanced treatment process used. By integrating the available analytical chemistry we highlight chemical groups associated to this response. Our study shows that more detailed and in-depth characterisation of chemicals and biological pathways associated with advanced treatment water systems are needed to mitigate possible risks to downstream organisms. Thames Water Utilities Ltd.

Fundamental questions remain about the application of omics in environmental risk assessments, such as the consistency of data across laboratories. The objective of the present study was to determine the congruence of transcript data across 6 independent laboratories. Male fathead minnows were exposed to a measured concentration of 15.8 ng/L 17α‐ethinylestradiol (EE2) for 96 h. Livers were divided equally and sent to the participating laboratories for transcriptomic analysis using the same fathead minnow microarray. Each laboratory was free to apply bioinformatics pipelines of its choice. There were 12 491 transcripts that were identified by one or more of the laboratories as responsive to EE2. Of these, 587 transcripts (4.7%) were detected by all laboratories. Mean overlap for differentially expressed genes among laboratories was approximately 50%, which improved to approximately 59.0% using a standardized analysis pipeline. The dynamic range of fold change estimates was variable between laboratories, but ranking transcripts by their relative fold difference resulted in a positive relationship for comparisons between any 2 laboratories (mean R2 > 0.9, p 20‐fold; e.g., vitellogenin) to subtle (∼2‐fold; i.e., block of proliferation 1) were identified as differentially expressed, suggesting that laboratories can consistently identify transcripts that are known a priori to be perturbed by a chemical stressor. Thus, attention should turn toward identifying core transcriptional networks using focused arrays for specific chemicals. In addition, agreed‐on bioinformatics pipelines and the ranking of genes based on fold change (as opposed to p value) should be considered in environmental risk assessment. These recommendations are expected to improve comparisons across laboratories and advance the use of omics in regulations. Environ Toxicol Chem 2017;36:2593–2601. © 2017 SETAC

In recent years, decreases in fish populations have been attributed, in part, to the effect of environmental chemicals on ovarian development. To understand the underlying molecular events we developed a dynamic model of ovary development linking gene transcription to key physiological end points, such as gonadosomatic index (GSI), plasma levels of estradiol (E2) and vitellogenin (VTG), in largemouth bass ( Micropterus salmoides). We were able to identify specific clusters of genes, which are affected at different stages of ovarian development. A subnetwork was identified that closely linked gene expression and physiological end points and by interrogating the Comparative Toxicogenomic Database (CTD), quercetin and tretinoin (ATRA) were identified as two potential candidates that may perturb this system. Predictions were validated by investigation of reproductive associated transcripts using qPCR in ovary and in the liver of both male and female largemouth bass treated after a single injection of quercetin and tretinoin (10 and 100 μg/kg). Both compounds were found to significantly alter the expression of some of these genes. Our findings support the use of omics and online repositories for identification of novel, yet untested, compounds. This is the first study of a dynamic model that links gene expression patterns across stages of ovarian development.

Summary Satellite cells are adult muscle stem cells residing in a specialized niche that regulates their homeostasis. How niche-generated signals integrate to regulate gene expression in satellite cell-derived myoblasts is poorly understood. We undertook an unbiased approach to study the effect of the satellite cell niche on satellite cell-derived myoblast transcriptional regulation and identified the tumor suppressor p53 as a key player in the regulation of myoblast quiescence. After activation and proliferation, a subpopulation of myoblasts cultured in the presence of the niche upregulates p53 and fails to differentiate. When satellite cell self-renewal is modeled ex vivo in a reserve cell assay, myoblasts treated with Nutlin-3, which increases p53 levels in the cell, fail to differentiate and instead become quiescent. Since both these Nutlin-3 effects are rescued by small interfering RNA-mediated p53 knockdown, we conclude that a tight control of p53 levels in myoblasts regulates the balance between differentiation and return to quiescence., Graphical Abstract, Highlights • The satellite cell niche drives a transcriptional program that promotes self-renewal • An asymmetric increase in p53 inhibits differentiation in niche-associated myoblasts • A sustained increase in p53 promotes quiescence at the expense of differentiation, In this article, Pisconti et al. use an unbiased approach to show that the transcriptional program that drives myoblast cell fate transitions is directly regulated by the nature of the surrounding niche. The authors identify p53 as a niche-induced transcriptional regulator that increases in a subset of myoblasts upon cell-cycle exit, promoting quiescence at the expense of differentiation.

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) that link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.

Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a specific purpose in a regulatory application: (i) Membrane disruption (Narcosis) leading to respiratory failure (low confidence), (ii) Hepatocellular proliferation leading to cancer (partial pathway, moderate confidence), (iii) Covalent binding to proteins leading to skin sensitization (high confidence), and (iv) Aromatase inhibition leading to reproductive dysfunction in fish (high confidence). Partially complete AOPs with unknown molecular initiating events, such as Hepatocellular proliferation leading to cancer, were found to be valuable. We demonstrate that scientific confidence in these pathways can be increased though the use of unconventional information (eg, computational identification of potential initiators). AOPs at all levels of confidence can contribute to specific uses. A significant statistical or quantitative relationship between events and/or the adverse outcome relationships is a common characteristic of AOPs, both incomplete and complete, that have specific regulatory uses. For AOPs to be useful in a regulatory context they must be at least as useful as the tools that regulators currently possess, or the techniques currently employed by regulators.

In this article we propose a Bayesian hierarchical model for the identification of differentially expressed genes in Daphnia magna organisms exposed to chemical compounds, specifically munition pollutants in water. The model we propose constitutes one of the very first attempts at a rigorous modeling of the biological effects of water purification. We have data acquired from a purification system that comprises four consecutive purification stages, which we refer to as "ponds," of progressively more contaminated water. We model the expected expression of a gene in a pond as the sum of the mean of the same gene in the previous pond plus a gene-pond specific difference. We incorporate a variable selection mechanism for the identification of the differential expressions, with a prior distribution on the probability of a change that accounts for the available information on the concentration of chemical compounds present in the water. We carry out posterior inference via MCMC stochastic search techniques. In the application, we reduce the complexity of the data by grouping genes according to their functional characteristics, based on the KEGG pathway database. This also increases the biological interpretability of the results. Our model successfully identifies a number of pathways that show differential expression between consecutive purification stages. We also find that changes in the transcriptional response are more strongly associated to the presence of certain compounds, with the remaining contributing to a lesser extent. We discuss the sensitivity of these results to the model parameters that measure the influence of the prior information on the posterior inference.

Furan, a heat-generated food contaminant, is hepatotoxic and carcinogenic in rodents. Furan is oxidized by cytochrome P450 2E1 to cis-2-butene-1,4-dial, a chemically reactive α,β-unsaturated dialdehyde, which has been identified as the key toxic metabolite of furan based on its ability to interact with tissue nucleophiles. In addition to genotoxicity, sustained cytotoxicity mediated through covalent binding of cis-2-butene-1,4-dial to critical target proteins is thought to play a key role in furan carcinogenicity. To identify putative protein targets of reactive furan metabolites, male F344/N rats (n = 5 per dose) were administered a single dose of [3,4-(14)C]-furan (20 mCi/mmol) at doses associated with hepatotoxicity following long-term exposure (0.1 and 2 mg/kg body weight [bw]). Liver proteins were separated by two-dimensional gel electrophoresis and protein spots carrying radiolabel were located by fluorography. In total, 83 discrete protein spots containing (14)C were consistently detected in livers of animals given [3,4-(14)C]-furan at 2.0 mg/kg bw, accounting for 4-5% of the proteome covered by our analyses. Protein spots were excised and digested in gel with trypsin for identification by protein mass spectrometry. Protein database search and subsequent pathway mapping identified 61 proteins localized predominantly in the cytosol and mitochondria, including structural proteins, mitochondrial enzymes involved in glucose metabolism, mitochondrial β-oxidation, and adenosine triphosphate synthesis, and proteins that participate in the maintenance of redox homeostasis and protein folding. Collectively, our data suggest that functional loss of several individual proteins and interference with pathways, most notably mitochondrial energy production, redox regulation, and protein folding, may combine to disrupt cell homeostasis and cause hepatocyte cell death.

Tumor endothelial markers (TEMs) that are highly expressed in human tumor vasculature compared with vasculature in normal tissue hold clear therapeutic potential. We report that the C-type lectin CLEC14A is a novel TEM. Immunohistochemical and immunofluorescence staining of tissue arrays has shown that CLEC14A is strongly expressed in tumor vasculature when compared with vessels in normal tissue. CLEC14A overexpression in tumor vessels was seen in a wide range of solid tumor types. Functional studies showed that CLEC14A induces filopodia and facilitates endothelial migration, tube formation and vascular development in zebrafish that is, CLEC14A regulates pro-angiogenic phenotypes. CLEC14A antisera inhibited cell migration and tube formation, suggesting that anti-CLEC14A antibodies may have anti-angiogenic activity. Finally, in endothelial cultures, expression of CLEC14A increased at low shear stress, and we hypothesize that low shear stress due to poor blood flow in the disorganized tumor vasculature induces expression of CLEC14A on tumor vessels and pro-angiogenic phenotypes.

Understanding gene regulation and its adaptive significance requires not only a detailed knowledge of individual molecular interactions that give rise to changes in gene expression but also an overview of complete genetic networks and the ways in which components within them interact. Increasingly, such studies are being done using luminescent or fluorescent reporter proteins that enable monitoring of gene expression dynamics in real time, particularly during changes in expression. We show here that such an approach is valid for dissecting the responses of the AR2 or GAD network of Escherichia coli K-12 to changes in pH, which is one of the most complex networks known in E. coli. In addition to confirming several regulatory interactions that have been revealed by previous studies, this approach has identified new components in this system that lead to complex dynamics of gene expression following a drop in pH, including an auto-regulatory loop involving the YdeO activator protein and novel roles for the PhoP protein.

Motivation: Childhood B-precursor lymphoblastic leukaemia (ALL) is the most common paediatric malignancy. Despite the fact that 80% of ALL patients respond to anti-cancer drugs, the patho-physiology of this disease is still not fully understood. mRNA expression-profiling studies that have been performed have not yet provided novel insights into the mechanisms behind cellular response to DNA damage. More powerful data analysis techniques may be required for identifying novel functional pathways involved in the cellular responses to DNA damage. Results: In order to explore the possibility that unforeseen biological processes may be involved in the response to DNA damage, we have developed and applied a novel procedure for the identification of functional modules in ALL cells. We have discovered that the overall activity of functional modules integrating protein degradation and mRNA processing is predictive of response to DNA damage. Availability: Supplementary material including R code, additional results, experimental datasets, as well as a detailed description of the methodology are available at http://www.bip.bham.ac.uk/vivo/fumo.html. Contact: f.falciani@bham.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

The expanding diversity and ever increasing amounts of man-made chemicals discharged to the environment pose largely unknown hazards to ecosystem and human health. The concept of adverse outcome pathways (AOPs) emerged as a comprehensive framework for risk assessment. However, the limited mechanistic information available for most chemicals and a lack of biological pathway annotation in many species represent significant challenges to effective implementation of this approach. Here, a systems level, multistep modeling strategy demonstrates how to integrate information on chemical structure with mechanistic insight from genomic studies, and phenotypic effects to define a putative adverse outcome pathway. Results indicated that transcriptional changes indicative of intracellular calcium mobilization were significantly overrepresented in Daphnia magna (DM) exposed to sublethal doses of presumed narcotic chemicals with log Kow ≥ 1.8. Treatment of DM with a calcium ATPase pump inhibitor substantially recapitulated the common transcriptional changes. We hypothesize that calcium mobilization is a potential key molecular initiating event in DM basal (narcosis) toxicity. Heart beat rate analysis and metabolome analysis indicated sublethal effects consistent with perturbations of calcium preceding overt acute toxicity. Together, the results indicate that altered calcium homeostasis may be a key early event in basal toxicity or narcosis induced by lipophilic compounds.

The use of chemical flame-retardants (FR) in consumer products has steadily increased over the last 30 years. Toxicity data exist for legacy FRs such as pentabromodiphenyl ether (pentaBDE), but less is known about effects of new formulations. To address this issue, the toxicity of seven FR chemicals and formulations was assessed on the freshwater crustacean Daphnia magna. Acute 48-h nominal LC50 values for penta- and octabromodiphenyl ether (pentaBDE, octaBDE), Firemaster 550 (FM550), Firemaster BZ-54 (BZ54), bis(2-ethylhexyl) tetrabromophthalate (BEH-TEBP), triphenyl phosphate (TPhP), and nonbrominated BEH-TEBP analog bis(2-ethylhexyl) phthalate (BEHP) ranged from 0.058 mg/L (pentaBDE) to 3.96 mg/L (octaBDE). mRNA expression, (1)H NMR-based metabolomic and lipidomic profiling at 1/10 LC50 revealed distinct patterns of molecular response for each exposure, suggesting pentaPBDE affects transcription and translation, octaBDE and BEH-TEBP affect glycosphingolipid biosynthesis and BZ54 affects Wnt and Hedgehog signal pathways as well as glycosaminoglycan degradation. Brominated components of FM550 (i.e., BZ54) were significantly higher in Daphnia after 48 h following 1/10 LC50 exposure. FM550 elicited significant mRNA changes at five concentrations across a range from 1/10(6) LC50 to 1/2 LC50. Analyses suggest FM550 impairs nutrient utilization or uptake in Daphnia.

Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring. The SOLUTIONS Project is supported by the Seventh Framework Programme (FP7-ENV-2013) of the European Union under grant agreement no. 603437.