Stress Knowledge Map: A knowledge graph resource for systems biology analysis of plant stress responses.

Stress Knowledge Map (SKM; https://skm.nib.si) is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical, signaling, and regulatory molecular interactions in plants: a highly curated model of plant stress signaling (PSS; 543 reactions) and a large comprehensive knowledge network (488 390 interactions). Both were constructed by domain experts through systematic curation of diverse literature and database resources. SKM provides a single entry point for investigations of plant stress response and related growth trade-offs, as well as interactive explorations of current knowledge. PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin. Here, we describe the features of SKM and show, through two case studies, how it can be used for complex analyses, including systematic hypothesis generation and design of validation experiments, or to gain new insights into experimental observations in plant biology.

Chloroplast redox state changes mark cell-to-cell signaling in the hypersensitive response.

Hypersensitive response (HR)-conferred resistance is associated with induction of programmed cell death and pathogen spread restriction in its proximity. The exact role of chloroplastic reactive oxygen species and its link with salicylic acid (SA) signaling in HR remain unexplained. To unravel this, we performed a detailed spatiotemporal analysis of chloroplast redox response in palisade mesophyll and upper epidermis to potato virus Y (PVY) infection in a resistant potato genotype and its transgenic counterpart with impaired SA accumulation and compromised resistance. Besides the cells close to the cell death zone, we detected individual cells with oxidized chloroplasts further from the cell death zone. These are rare in SA-deficient plants, suggesting their role in signaling for resistance. We confirmed that chloroplast redox changes play important roles in signaling for resistance, as blocking chloroplast redox changes affected spatial responses at the transcriptional level. Through spatiotemporal study of stromule induction after PVY infection, we show that stromules are induced by cell death and also as a response to PVY multiplication at the front of infection. Overall induction of stromules is attenuated in SA-deficient plants.

Using Bacillus thuringiensis HM-311@hydroxyapatite@biochar beads to remediate Pb and Cd contaminated farmland soil.

Cadmium (Cd) and lead (Pb) have become serious soil contaminants in China. In this work, we immobilized B. thuringiensis HM-311 (a heavy metal resistant strain) using vinegar residue biochar and hydroxyapatite (HAP) to form BtHM-311@HAP@biochar calcium alginate beads. In aqueous solution, the beads respectively reduced 1000 mg/L Pb2+ to 14.59 mg/L and 200 mg/L Cd2+ to 5.40 mg/L within 20 h. Furthermore, the results of pot experiment showed that the BtHM-311@HAP@biochar beads reduced the bioavailability of Pb and Cd in soil. The accumulation of Pb2+ in rice decreased by 39.97% in shoots and 46.40% in roots, while that of Cd2+ decreased by 34.59 and 44.9%, respectively. Similarly, the accumulation of Pb2+ in corn decreased by 40.86% in shoots and 51.34% in roots, while that of Cd2+ decreased by 41.28 and 42.91%, respectively. The beads also increased the microbial community diversity in the rhizosphere soil. These findings indicate that BtHM-311@HAP@biochar beads may be applicable for the bioremediation of Cd- and Pb-contaminated farmland soil.

Evaluation of Methods and Processes for Robust Monitoring of SARS-CoV-2 in Wastewater.

The SARS-CoV-2 pandemic has accelerated the development of virus concentration and molecular-based virus detection methods, monitoring systems and overall approach to epidemiology. Early into the pandemic, wastewater-based epidemiology started to be employed as a tool for tracking the virus transmission dynamics in a given area. The complexity of wastewater coupled with a lack of standardized methods led us to evaluate each step of the analysis individually and see which approach gave the most robust results for SARS-CoV-2 monitoring in wastewater. In this article, we present a step-by-step, retrospective view on the method development and implementation for the case of a pilot monitoring performed in Slovenia. We specifically address points regarding the thermal stability of the samples during storage, screening for the appropriate sample concentration and RNA extraction procedures and real-time PCR assay selection. Here, we show that the temperature and duration of the storage of the wastewater sample can have a varying impact on the detection depending on the structural form in which the SARS-CoV-2 target is present. We found that concentration and RNA extraction using Centricon filtration units coupled with Qiagen RNA extraction kit or direct RNA capture and extraction using semi-automated kit from Promega give the most optimal results out of the seven methods tested. Lastly, we confirm the use of N1 and N2 assays developed by the CDC (USA) as the best performing assays among four tested in combination with Fast Virus 1-mastermix. Data show a realistic overall process for method implementation as well as provide valuable information in regards to how different approaches in the analysis compare to one another under the specific conditions present in Slovenia during a pilot monitoring running from the beginning of the pandemic.

Using nanomaterials to increase the efficiency of chemical production in microbial cell factories: A comprehensive review.

Microbes have proven to be robust workhorses for the large-scale production of many chemicals. Especially, high-value biochemicals (e.g., natural pigments, unsaturated fatty acids) that cannot be derived from fossil fuels, can be produced by engineered microbes. There is a growing interest in both academia and industry to find new technologies that can enhance the efficiencies of microbial cell factories and boost the circular bioeconomy. Rapid technological innovations, such as microbial genome editing and synthetic biology, have greatly advanced the production of chemicals in engineered microbes. Nanomaterial-based technologies that exploit the unique physiochemical properties of nano-scale materials (e.g., large surface area, excellent catalytic activity, tunable optical and electrical performance) have demonstrated great potential and attracted increasing attention. There are many studies showing that nanomaterials can assist microbes in the synthesis of chemicals by providing micronutrients, inducing anti-ROS responses, promoting gas-liquid mass transfer, immobilizing microbial cells and promoting electron transfer in electrosynthesis. Furthermore, the latest studies demonstrate that nanomaterials can be used to construct photocatalyst-microbe hybrids and achieve solar driven chemical production. In this review, we comprehensively summarize these advances and discuss the current gaps as well as future perspectives. With the rapid development of synthetic biology and nanotechnology, we believe more nanomaterial-based technologies will be developed and used to improve the productivity of microbial cell factories.

Poultry eggshell-derived antimicrobial materials: Current status and future perspectives.

Poultry eggs, the basic foodstuffs of human society, have been extensively consumed for domestic and industrial uses. A large amount of eggshell waste is generated and discarded every year, resulting in a waste of natural resources and a threat to the environment. In this context, the reutilization of eggshell waste has gained increasing attentions. Meanwhile, the overuse of antibiotics has led to the emergence of many drug-resistant bacteria, which greatly endangers public health. Therefore, manufacturing new materials with strong antimicrobial activities has become the focus of many researchers. Recent studies have revealed that eggshells can be applied as solid substances, the raw materials for calcium oxide, and the calcium source for synthesizing hydroxyapatite or other materials with antimicrobial activities. Herein, the preparation methods, antibacterial mechanisms and the applications of these eggshell waste-derived antibacterial materials are summarized in this review. Finally, the current challenges and future directions in this field are discussed.

From Causal Networks to Adverse Outcome Pathways: A Developmental Neurotoxicity Case Study.

The last decade has seen the adverse outcome pathways (AOP) framework become one of the most powerful tools in chemical risk assessment, but the development of new AOPs remains a slow and manually intensive process. Here, we present a faster approach for AOP generation, based on manually curated causal toxicological networks. As a case study, we took a recently published zebrafish developmental neurotoxicity network, which contains causally connected molecular events leading to neuropathologies, and developed two new adverse outcome pathways: Inhibition of Fyna (Src family tyrosine kinase A) leading to increased mortality via decreased eye size (AOP 399 on AOP-Wiki) and GSK3beta (Glycogen synthase kinase 3 beta) inactivation leading to increased mortality via defects in developing inner ear (AOP 410). The approach consists of an automatic separation of the toxicological network into candidate AOPs, filtering the AOPs according to available evidence and length as well as manual development of new AOPs and weight-of-evidence evaluation. The semiautomatic approach described here provides a new opportunity for fast and straightforward AOP development based on large network resources.

Systems Biology in ELIXIR: modelling in the spotlight.

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

Sub-Lethal Peak Exposure to Insecticides Triggers Olfaction-Mediated Avoidance in Zebrafish Larvae.

In agricultural areas, insecticides inevitably reach water bodies via leaching or run-off. While designed to be neurotoxic to insects, insecticides have adverse effects on a multitude of organisms due to the high conservation of the nervous system among phyla. To estimate the ecological effects of insecticides, it is important to investigate their impact on non-target organisms such as fish. Using zebrafish as the model, we investigated how different classes of insecticides influence fish behavior and uncovered neuronal underpinnings of the associated behavioral changes, providing an unprecedented insight into the perception of these chemicals by fish. We observed that zebrafish larvae avoid diazinon and imidacloprid while showing no response to other insecticides with the same mode of action. Moreover, ablation of olfaction abolished the aversive responses, indicating that fish smelled the insecticides. Assessment of neuronal activity in 289 brain regions showed that hypothalamic areas involved in stress response were among the regions with the largest changes, indicating that the observed behavioral response resembles reactions to stimuli that threaten homeostasis, such as changes in water chemistry. Our results contribute to the understanding of the environmental impact of insecticide exposure and can help refine acute toxicity assessment.

Systems Toxicology Approach for Assessing Developmental Neurotoxicity in Larval Zebrafish.

Adverse outcomes that result from chemical toxicity are rarely caused by dysregulation of individual proteins; rather, they are often caused by system-level perturbations in networks of molecular events. To fully understand the mechanisms of toxicity, it is necessary to recognize the interactions of molecules, pathways, and biological processes within these networks. The developing brain is a prime example of an extremely complex network, which makes developmental neurotoxicity one of the most challenging areas in toxicology. We have developed a systems toxicology method that uses a computable biological network to represent molecular interactions in the developing brain of zebrafish larvae. The network is curated from scientific literature and describes interactions between biological processes, signaling pathways, and adverse outcomes associated with neurotoxicity. This allows us to identify important signaling hubs, pathway interactions, and emergent adverse outcomes, providing a more complete understanding of neurotoxicity. Here, we describe the construction of a zebrafish developmental neurotoxicity network and its validation by integration with publicly available neurotoxicity-related transcriptomic datasets. Our network analysis identified consistent regulation of tumor suppressors p53 and retinoblastoma 1 (Rb1) as well as the oncogene Krüppel-like factor (Klf8) in response to chemically induced developmental neurotoxicity. The developed network can be used to interpret transcriptomic data in a neurotoxicological context.

Approaches to Test the Neurotoxicity of Environmental Contaminants in the Zebrafish Model: From Behavior to Molecular Mechanisms.

The occurrence of neuroactive chemicals in the aquatic environment is on the rise and poses a potential threat to aquatic biota of currently unpredictable outcome. In particular, subtle changes caused by these chemicals to an organism's sensation or behavior are difficult to tackle with current test systems that focus on rodents or with in vitro test systems that omit whole-animal responses. In recent years, the zebrafish (Danio rerio) has become a popular model organism for toxicological studies and testing strategies, such as the standardized use of zebrafish early life stages in the Organisation for Economic Co-operation and Development's guideline 236. In terms of neurotoxicity, the zebrafish provides a powerful model to investigate changes to the nervous system from several different angles, offering the ability to tackle the mechanisms of action of chemicals in detail. The mechanistic understanding gained through the analysis of this model species provides a good basic knowledge of how neuroactive chemicals might interact with a teleost nervous system. Such information can help infer potential effects occurring to other species exposed to neuroactive chemicals in their aquatic environment and predicting potential risks of a chemical for the aquatic ecosystem. In the present article, we highlight approaches ranging from behavioral to structural, functional, and molecular analysis of the larval zebrafish nervous system, providing a holistic view of potential neurotoxic outcomes. Environ Toxicol Chem 2021;40:989-1006. © 2020 SETAC.

Photocatalytic Material-Microbe Hybrids: Applications in Environmental Remediations.

Environmental pollution has become one of the most urgent global issues that we have to face now. Searching new technologies to solve environmental issues is of great significance. By intimately coupling photocatalytic materials with microbes, the emerging photocatalytic material-microbe hybrid (PMH) system takes advantages of the high-efficiency, broad-spectrum light capture capability of the photocatalytic material and the selectivity of microbial enzymatic catalysis to efficiently convert solar energy into chemical energy. The PMH system is originally applied for the solar-to-chemical production. Interestingly, recent studies demonstrate that this system also has great potential in treating environmental contaminations. The photogenerated electrons produced by the PMH system can reductively decompose organic pollutants with oxidative nature (e.g., refractory azo dyes) under anaerobic circumstances. Moreover, based on the redox reactions occurring on the surface of photocatalysts and the enzymatic reactions in microbes, the PMH system can convert the valences of multiple heavy metal ions into less toxic or even nontoxic status simultaneously. In this review, we introduce the recent advances of using the PMH system in treating environmental pollutions and compare this system with another similar system, the traditional intimately coupled photocatalysis and biodegradation (ICPB) system. Finally, the current challenges and future directions in this field are discussed as well.

Systems Toxicology Approach for Testing Chemical Cardiotoxicity in Larval Zebrafish.

Transcriptomic approaches can give insight into molecular mechanisms underlying chemical toxicity and are increasingly being used as part of toxicological assessments. To aid the interpretation of transcriptomic data, we have developed a systems toxicology method that relies on a computable biological network model. We created the first network model describing cardiotoxicity in zebrafish larvae-a valuable emerging model species in testing cardiotoxicity associated with drugs and chemicals. The network is based on scientific literature and represents hierarchical molecular pathways that lead from receptor activation to cardiac pathologies. To test the ability of our approach to detect cardiotoxic outcomes from transcriptomic data, we have selected three publicly available data sets that reported chemically induced heart pathologies in zebrafish larvae for five different chemicals. Network-based analysis detected cardiac perturbations for four out of five chemicals tested, for two of them using transcriptomic data collected up to 3 days before the onset of a visible phenotype. Additionally, we identified distinct molecular pathways that were activated by the different chemicals. The results demonstrate that the proposed integrational method can be used for evaluating the effects of chemicals on the zebrafish cardiac function and, together with observed cardiac apical end points, can provide a comprehensive method for connecting molecular events to organ toxicity. The computable network model is freely available and may be used to generate mechanistic hypotheses and quantifiable perturbation values from any zebrafish transcriptomic data.

Systems biology: current status and challenges.

We put together a special issue on current approaches in systems biology with a focus on mathematical modeling of metabolic networks. Mathematical models have increasingly been used to unravel molecular mechanisms of complex dynamic biological processes. We here provide a short introduction into the topics covered in this special issue, highlighting current developments and challenges.

Common Gene Expression Patterns in Environmental Model Organisms Exposed to Engineered Nanomaterials: A Meta-Analysis.

The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regarding common responses and toxicity pathways is currently lacking. We developed an R-scripted computational pipeline to perform reanalysis and functional analysis of relevant transcriptomic data sets using a common approach, independent from the ENM type, and across different organisms, including Arabidopsis thaliana, Caenorhabditis elegans, and Danio rerio. Using the pipeline that can semiautomatically process data from different microarray technologies, we were able to determine the most common molecular mechanisms of nanotoxicity across extremely variable data sets. As expected, we found known mechanisms, such as interference with energy generation, oxidative stress, disruption of DNA synthesis, and activation of DNA-repair but also discovered that some less-described molecular responses to ENMs, such as DNA/RNA methylation, protein folding, and interference with neurological functions, are present across the different studies. Results were visualized in radar charts to assess toxicological response patterns allowing the comparison of different organisms and ENM types. This can be helpful to retrieve ENM-related hazard information and thus fill knowledge gaps in a comprehensive way in regard to the molecular underpinnings and mechanistic understanding of nanotoxicity.

Predicting the Probability that a Chemical Causes Steatosis Using Adverse Outcome Pathway Bayesian Networks (AOPBNs).

Adverse outcome pathway Bayesian networks (AOPBNs) are a promising avenue for developing predictive toxicology and risk assessment tools based on adverse outcome pathways (AOPs). Here, we describe a process for developing AOPBNs. AOPBNs use causal networks and Bayesian statistics to integrate evidence across key events. In this article, we use our AOPBN to predict the occurrence of steatosis under different chemical exposures. Since it is an expert-driven model, we use external data (i.e., data not used for modeling) from the literature to validate predictions of the AOPBN model. The AOPBN accurately predicts steatosis for the chemicals from our external data. In addition, we demonstrate how end users can utilize the model to simulate the confidence (based on posterior probability) associated with predicting steatosis. We demonstrate how the network topology impacts predictions across the AOPBN, and how the AOPBN helps us identify the most informative key events that should be monitored for predicting steatosis. We close with a discussion of how the model can be used to predict potential effects of mixtures and how to model susceptible populations (e.g., where a mutation or stressor may change the conditional probability tables in the AOPBN). Using this approach for developing expert AOPBNs will facilitate the prediction of chemical toxicity, facilitate the identification of assay batteries, and greatly improve chemical hazard screening strategies.

Intestinal Fish Cell Barrier Model to Assess Transfer of Organic Chemicals in Vitro: An Experimental and Computational Study.

We studied the role of the fish intestine as a barrier for organic chemicals using the epithelial barrier model built on the rainbow trout (Oncorhynchus mykiss) intestinal cell line, RTgutGC and the newly developed exposure chamber, TransFEr, specifically designed to work with hydrophobic and volatile chemicals. Testing 11 chemicals with a range of physicochemical properties (logKOW: 2.2 to 6.3, logHLC: 6.1 to 2.3) and combining the data with a mechanistic kinetic model enabled the determination of dominant processes underlying the transfer experiments and the derivation of robust transfer rates. Against the current assumption in chemical uptake modeling, chemical transfer did not strictly depend on the logKOW but resulted from chemical-specific intracellular accumulation and biotransformation combined with paracellular and active transport. Modeling also identified that conducting elaborate measurements of the plastic parts, including the polystyrene insert and the PET filter, is unnecessary and that stirring in the TransFEr chamber reduced the stagnant water layers compared to theoretical predictions. Aside from providing insights into chemical uptake via the intestinal epithelium, this system can easily be transferred to other cell-based barrier systems, such as the fish gill or mammalian intestinal models and may improve in vitro-in vivo extrapolation and prediction of chemical bioaccumulation into organisms.

Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment.

An important goal in toxicology is the development of new ways to increase the speed, accuracy, and applicability of chemical hazard and risk assessment approaches. A promising route is the integration of in vitro assays with biological pathway information. We examined how the adverse outcome pathway (AOP) framework can be used to develop pathway-based quantitative models useful for regulatory chemical safety assessment. By using AOPs as initial conceptual models and the AOP knowledge base as a source of data on key event relationships, different methods can be applied to develop computational quantitative AOP models (qAOPs) relevant for decision making. A qAOP model may not necessarily have the same structure as the AOP it is based on. Useful AOP modeling methods range from statistical, Bayesian networks, regression, and ordinary differential equations to individual-based models and should be chosen according to the questions being asked and the data available. We discuss the need for toxicokinetic models to provide linkages between exposure and qAOPs, to extrapolate from in vitro to in vivo, and to extrapolate across species. Finally, we identify best practices for modeling and model building and the necessity for transparent and comprehensive documentation to gain confidence in the use of qAOP models and ultimately their use in regulatory applications. Environ Toxicol Chem 2019;38:1850-1865. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Repeatability and Reproducibility of the RTgill-W1 Cell Line Assay for Predicting Fish Acute Toxicity.

Predicting fish acute toxicity of chemicals in vitro is an attractive alternative method to the conventional approach using juvenile and adult fish. The rainbow trout (Oncorhynchus mykiss) cell line assay with RTgill-W1 cells has been designed for this purpose. It quantifies cell viability using fluorescent measurements for metabolic activity, cell- and lysosomal-membrane integrity on the same set of cells. Results from over 70 organic chemicals attest to the high predictive capacity of this test. We here report on the repeatability (intralaboratory variability) and reproducibility (interlaboratory variability) of the RTgill-W1 cell line assay in a round-robin study focusing on 6 test chemicals involving 6 laboratories from the industrial and academic sector. All participating laboratories were able to establish the assay according to preset quality criteria even though, apart from the lead laboratory, none had previously worked with the RTgill-W1 cell line. Concentration-response modeling, based on either nominal or geometric mean-derived measured concentrations, yielded effect concentrations (EC50) that spanned approximately 4 orders of magnitude over the chemical range, covering all fish acute toxicity categories. Coefficients of variation for intralaboratory and interlaboratory variability for the average of the 3 fluorescent cell viability measurements were 15.5% and 30.8%, respectively, which is comparable to other fish-derived, small-scale bioassays. This study therefore underlines the robustness of the RTgill-W1 cell line assay and its accurate performance when carried out by operators in different laboratory settings.