Current aspects of DNA damage and repair in ecotoxicology: a mini-review

Deficiency of the Arabidopsis mismatch repair MSH6 attenuates Pseudomonas syringae invasion

The MutS homolog 6 (MSH6) is a nuclear DNA mismatch repair (MMR) gene that encodes the MSH6 protein. MSH6 interacts with MSH2 to form the MutSα heterodimer. MutSα corrects DNA mismatches and unpaired nucleotides arising during DNA replication, deamination of 5-methylcytosine, and recombination between non-identical DNA sequences. In addition to correcting DNA biosynthetic errors, MutSα also recognizes chemically damaged DNA bases. Here, we show that inactivation of MSH6 affects the basal susceptibility of Arabidopsis thaliana to Pseudomonas syringae pv tomato DC3000. The msh6 T-DNA insertional mutant exhibited a reduced susceptibility to the bacterial invasion. This heightened basal resistance of msh6 mutants appears to be dependent on an increased stomatal closure, an accumulation of H₂O₂ and double-strand breaks (DSBs) and a constitutive expression of pathogenesis-related (NPR1 and PR1) and DNA damage response (RAD51D and SOG1) genes. Complementation of this mutant with the MSH6 wild type allele under the control of its own promoter resulted in reversal of the basal bacterial resistance phenotype and the stomatal closure back to wild type levels. Taken together, these results demonstrate that inactivation of MSH6 increases Arabidopsis basal susceptibility to the bacterial pathogen and suggests a link between DNA repair and stress signaling in plants.

Ecotoxicological effects of soil lithium on earthworm Eisenia fetida: Lethality, bioaccumulation, biomarker responses, and histopathological changes

Lithium is an emerging environmental contaminant in the current low-carbon economy, but little is known about its influences on soil invertebrates. In this work, earthworm Eisenia fetida was exposed to soils treated with different levels of lithium for 7 d, and multiple ecotoxicological parameters were evaluated. The results showed that mortality was dose-dependent and lithium's median lethal content (LC₅₀) to earthworm was respectively 865.08, 361.01, 139.36, and 94.95 mg/kg after 1 d, 2 d, 4 d, and 7 d exposure. The bioaccumulation factor based on measured exogenous lithium content (BF_exog) respectively reached 0.79, 1.01, 1.57, and 1.27 with the increasing lithium levels, suggesting that lithium accumulation was averagely 1.16-fold to the exogenous content, and 74.42%∼81.19%, 14.54%∼18.23%, and 2.26%∼8.02% of the lithium in exposed earthworms were respectively retained in the cytosol, debris, and granule. Then, lithium stress stimulated the activity of superoxide dismutase, peroxidase, catalase, acetylcholinesterase, and glutathione S-transferase as well as the content of 8-hydroxy-2-deoxyguanosine and metallothionein, indicating the generation of oxidative damage, while the content of reactive oxygen species and malondialdehyde decreased. Finally, lithium introduced histopathological changes, including the degenerated seminal vesicle and muscle hyperplasia, as well as high or extreme nuclear DNA damage. This study confirmed the obvious bioaccumulation and toxic effects caused by soil lithium via ecotoxicological data, providing new theoretical insights into understanding the ecological risks of lithium to soil invertebrates.

In situ detection of the genotoxic potential as one of the lines of evidence in the weight-of-evidence approach-the Joint Danube Survey 4 Case Study

Environmental studies which aim to assess the ecological impact of chemical and other types of pollution should employ a complex weight-of-evidence approach with multiple lines of evidence (LoEs). This study focused on in situ genotoxicological methods such as the comet and micronucleus assays and randomly amplified polymorphic DNA analysis as one of the multiple LoEs (LoE3) on the fish species Alburnus alburnus (bleak) as a bioindicator. The study was carried out within the Joint Danube Survey 4 (JDS4) at nine sites in the Danube River Basin in the Republic of Serbia. Out of nine sampling sites, two were situated at the Tisa, Sava, and Velika Morava rivers, and three sites were at the Danube River. The three additionally employed LoEs were: SumTUwater calculated based on the monitoring data in the database of the Serbian Environmental Protection Agency (SEPA) (LoE1); in vitro analyses of JDS4 water extracts employing genotoxicological methods (LoE2); assessment of the ecological status/potential by SEPA and indication of the ecological status for the sites performed within the JDS4 (LoE4). The analyzed biomarker responses in the bleak were integrated into the unique integrated biomarker response index which was used to rank the sites. The highest pollution pressure was recorded at JDS4 39 and JDS4 36, while the lowest was at JDS4 35. The impact of pollution was confirmed at three sites, JDS4 33, 40, and 41, by all four LoEs. At other sampling sites, a difference was observed regarding the pollution depending on the employed LoEs. This indicates the importance of implementing a comprehensive weight-of-evidence approach to ensure the impact of pollution is not overlooked when using only one LoE as is often the case in environmental studies.

After a Century of Research into Environmental Mutagens and Carcinogens, Where Do We Stand?

Cancer is one of the longest-known human diseases, yet only in recent times have we begun to perceive that the percentage of neoplasms caused by environmental factors, lifestyle and chemicals, is likely underestimated. The first medical reports associating cancer with pollutants like tars appeared by the early 20th century, but despite initial evidence relating oncogenesis and chromosomal alterations, only after the structure of DNA had been elucidated in the 1950s have genetic disorders been fully perceived as cause. This led to a growing interest in genotoxic and mutagenic pollutants. Even though we are now familiar with a range of environmental carcinogens spanning between aromatic hydrocarbons and asbestos to radionuclides and forms of carbon nanomaterials, establishing causal networks between pollutants and cancer remains cumbersome. In most part, this is due to the complexity of toxicant matrices, unknown modes-of-action of chemicals or their mixtures, the widening array of novel pollutants plus difficulties in subtracting background effects from true aetiology of disease. Recent advances in analytical chemistry, high-throughput toxicology, next-generation sequencing, computational biology and databases that allocate whole normal and cancer genomes, all indicate that we are on the verge of a new age of research into mechanistic 'oncotoxicology', but how can it impact risk assessment and prevention?

Adverse Outcome Pathways and Linkages to Transcriptomic Effects Relevant to Ionizing Radiation Injury

BACKGROUND

In the past three decades, a large body of data on the effects of exposure to ionizing radiation and the ensuing changes in gene expression has been generated. These data have allowed for an understanding of molecular-level events and shown a level of consistency in response despite the vast formats and experimental procedures being used across institutions. However, clarity on how this information may inform strategies for health risk assessment needs to be explored. An approach to bridge this gap is the adverse outcome pathway (AOP) framework. AOPs represent an illustrative framework characterizing a stressor associated with a sequential set of causally linked key events (KEs) at different levels of biological organization, beginning with a molecular initiating event (MIE) and culminating in an adverse outcome (AO). Here, we demonstrate the interpretation of transcriptomic datasets in the context of the AOP framework within the field of ionizing radiation by using a lung cancer AOP (AOP 272: https://www.aopwiki.org/aops/272) as a case example.

METHODS

Through the mining of the literature, radiation exposure-related transcriptomic studies in line with AOP 272 related to lung cancer, DNA damage response, and repair were identified. The differentially expressed genes within relevant studies were collated and subjected to the pathway and network analysis using Reactome and GeneMANIA platforms. Identified pathways were filtered (p < 0.001, ≥ 3 genes) and categorized based on relevance to KEs in the AOP. Gene connectivities were identified and further grouped by gene expression-informed associated events (AEs). Relevant quantitative dose-response data were used to inform the directionality in the expression of the genes in the network across AEs.

RESULTS

Reactome analyses identified 7 high-level biological processes with multiple pathways and associated genes that mapped to potential KEs in AOP 272. The gene connectivities were further represented as a network of AEs with associated expression profiles that highlighted patterns of gene expression levels.

CONCLUSIONS

This study demonstrates the application of transcriptomics data in AOP development and provides information on potential data gaps. Although the approach is new and anticipated to evolve, it shows promise for improving the understanding of underlying mechanisms of disease progression with a long-term vision to be predictive of adverse outcomes.

Environmental induced transgenerational inheritance impacts systems epigenetics in disease etiology

Environmental toxicants have been shown to promote the epigenetic transgenerational inheritance of disease through exposure specific epigenetic alterations in the germline. The current study examines the actions of hydrocarbon jet fuel, dioxin, pesticides (permethrin and methoxychlor), plastics, and herbicides (glyphosate and atrazine) in the promotion of transgenerational disease in the great grand-offspring rats that correlates with specific disease associated differential DNA methylation regions (DMRs). The transgenerational disease observed was similar for all exposures and includes pathologies of the kidney, prostate, and testis, pubertal abnormalities, and obesity. The disease specific DMRs in sperm were exposure specific for each pathology with negligible overlap. Therefore, for each disease the DMRs and associated genes were distinct for each exposure generational lineage. Observations suggest a large number of DMRs and associated genes are involved in a specific pathology, and various environmental exposures influence unique subsets of DMRs and genes to promote the transgenerational developmental origins of disease susceptibility later in life. A novel multiscale systems biology basis of disease etiology is proposed involving an integration of environmental epigenetics, genetics and generational toxicology.