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.

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.

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 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.

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.

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.

Modeling and gene knockdown to assess the contribution of nonsense-mediated decay, premature termination, and selenocysteine insertion to the selenoprotein hierarchy.

The expression of selenoproteins, a specific group of proteins that incorporates selenocysteine, is hierarchically regulated by the availability of Se, with some, but not all selenoprotein mRNA transcripts decreasing in abundance with decreasing Se. Selenocysteine insertion into the peptide chain occurs during translation following recoding of an internal UGA stop codon. There is increasing evidence that this UGA recoding competes with premature translation termination, which is followed by nonsense-mediated decay (NMD) of the transcript. In this study, we tested the hypothesis that the susceptibility of different selenoprotein mRNAs to premature termination during translation and differential sensitivity of selenoprotein transcripts to NMD are major factors in the selenoprotein hierarchy. Selenoprotein transcript abundance was measured in Caco-2 cells using real-time PCR under different Se conditions and the data obtained fitted to mathematical models of selenoprotein translation. A calibrated model that included a combination of differential sensitivity of selenoprotein transcripts to NMD and different frequency of non-NMD related premature translation termination was able to fit all the measurements. The model predictions were tested using SiRNA to knock down expression of the crucial NMD factor UPF1 (up-frameshift protein 1) and selenoprotein mRNA expression. The calibrated model was able to predict the effect of UPF1 knockdown on gene expression for all tested selenoproteins, except SPS2 (selenophosphate synthetase), which itself is essential for selenoprotein synthesis. These results indicate an important role for NMD in the hierarchical regulation of selenoprotein mRNAs, with the exception of SPS2 whose expression is likely regulated by a different mechanism.

Transcriptomics and proteomics show that selenium affects inflammation, cytoskeleton, and cancer pathways in human rectal biopsies.

Epidemiologic studies highlight the potential role of dietary selenium (Se) in colorectal cancer prevention. Our goal was to elucidate whether expression of factors crucial for colorectal homoeostasis is affected by physiologic differences in Se status. Using transcriptomics and proteomics followed by pathway analysis, we identified pathways affected by Se status in rectal biopsies from 22 healthy adults, including 11 controls with optimal status (mean plasma Se = 1.43 µM) and 11 subjects with suboptimal status (mean plasma Se = 0.86 µM). We observed that 254 genes and 26 proteins implicated in cancer (80%), immune function and inflammatory response (40%), cell growth and proliferation (70%), cellular movement, and cell death (50%) were differentially expressed between the 2 groups. Expression of 69 genes, including selenoproteins W1 and K, which are genes involved in cytoskeleton remodelling and transcription factor NFκB signaling, correlated significantly with Se status. Integrating proteomics and transcriptomics datasets revealed reduced inflammatory and immune responses and cytoskeleton remodelling in the suboptimal Se status group. This is the first study combining omics technologies to describe the impact of differences in Se status on colorectal expression patterns, revealing that suboptimal Se status could alter inflammatory signaling and cytoskeleton in human rectal mucosa and so influence cancer risk.-Méplan, C., Johnson, I. T., Polley, A. C. J., Cockell, S., Bradburn, D. M., Commane, D. M., Arasaradnam, R. P., Mulholland, F., Zupanic, A., Mathers, J. C., Hesketh, J. Transcriptomics and proteomics show that selenium affects inflammation, cytoskeleton, and cancer pathways in human rectal biopsies.

Detecting translational regulation by change point analysis of ribosome profiling data sets.

Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While during normal translation, ribosome density is constant along the length of the mRNA coding region, this can be altered in response to translational regulatory events. In the present study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modeling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq data set obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artifacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and gene isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g., premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new transcript isoforms.

Integrated Stochastic Model of DNA Damage Repair by Non-homologous End Joining and p53/p21-Mediated Early Senescence Signalling.

Unrepaired or inaccurately repaired DNA damage can lead to a range of cell fates, such as apoptosis, cellular senescence or cancer, depending on the efficiency and accuracy of DNA damage repair and on the downstream DNA damage signalling. DNA damage repair and signalling have been studied and modelled in detail separately, but it is not yet clear how they integrate with one another to control cell fate. In this study, we have created an integrated stochastic model of DNA damage repair by non-homologous end joining and of gamma irradiation-induced cellular senescence in human cells that are not apoptosis-prone. The integrated model successfully explains the changes that occur in the dynamics of DNA damage repair after irradiation. Simulations of p53/p21 dynamics after irradiation agree well with previously published experimental studies, further validating the model. Additionally, the model predicts, and we offer some experimental support, that low-dose fractionated irradiation of cells leads to temporal patterns in p53/p21 that lead to significant cellular senescence. The integrated model is valuable for studying the processes of DNA damage induced cell fate and predicting the effectiveness of DNA damage related medical interventions at the cellular level.

Selenium Uptake and Methylation by the Microalga Chlamydomonas reinhardtii.

Biogenic selenium (Se) emissions play a major role in the biogeochemical cycle of this essential micronutrient. Microalgae may be responsible for a large portion of these emissions via production of methylated Se compounds that volatilize into the atmosphere. However, the biochemical mechanisms underlying Se methylation in microalgae are poorly understood. Here, we study Se methylation by Chlamydomonas reinhardtii, a model freshwater alga, as a function of uptake and intracellular Se concentrations and present a biochemical model that quantitatively describes Se uptake and methylation. Both selenite and selenate, two major inorganic forms of Se, are readily internalized by C. reinhardtii, but selenite is accumulated around ten times more efficiently than selenate due to different membrane transporters. With either selenite or selenate as substrates, Se methylation was highly efficient (up to 89% of intracellular Se) and directly coupled to intracellular Se levels (R(2) > 0.92) over an intracellular concentration range exceeding an order of magnitude. At intracellular concentrations exceeding 10 mM, intracellular zerovalent Se was formed. The relationship between uptake, intracellular accumulation, and methylation was used by the biochemical model to successfully predict measured concentrations of methylated Se in natural waters. Therefore, biological Se methylation by microalgae could significantly contribute to environmental Se cycling.

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.

Planning of electroporation-based treatments using Web-based treatment-planning software.

Electroporation-based treatment combining high-voltage electric pulses and poorly permanent cytotoxic drugs, i.e., electrochemotherapy (ECT), is currently used for treating superficial tumor nodules by following standard operating procedures. Besides ECT, another electroporation-based treatment, nonthermal irreversible electroporation (N-TIRE), is also efficient at ablating deep-seated tumors. To perform ECT or N-TIRE of deep-seated tumors, following standard operating procedures is not sufficient and patient-specific treatment planning is required for successful treatment. Treatment planning is required because of the use of individual long-needle electrodes and the diverse shape, size and location of deep-seated tumors. Many institutions that already perform ECT of superficial metastases could benefit from treatment-planning software that would enable the preparation of patient-specific treatment plans. To this end, we have developed a Web-based treatment-planning software for planning electroporation-based treatments that does not require prior engineering knowledge from the user (e.g., the clinician). The software includes algorithms for automatic tissue segmentation and, after segmentation, generation of a 3D model of the tissue. The procedure allows the user to define how the electrodes will be inserted. Finally, electric field distribution is computed, the position of electrodes and the voltage to be applied are optimized using the 3D model and a downloadable treatment plan is made available to the user.

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.

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.

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.