Characteristic molecular signature for early detection and prediction of persistent organic pollutants in rat liver

Seasonal trends and retention of polycyclic aromatic compounds (PACs) in a remote sub-Arctic catchment

Atmospheric deposition is the most dominant source of polycyclic aromatic hydrocarbons (PAHs) in remote and pristine areas. Despite low bioaccumulation potential, PAHs and their persistent transformation products (PAH-derivatives) are chemicals of concern as they can harm human and animal health through chronic low dose exposure. In this study, atmospheric deposition fluxes of polycyclic aromatic compounds (PACs) were measured on a seasonal basis (3-month periods) from 2012 to 2016 in a remote subarctic forest catchment in northern Europe. The target PACs included 19 PAHs and 15 PAH-derivatives (oxygenated, nitrogenated, and methylated PAHs). The deposition fluxes of ƩPAHs and ƩPAH-derivatives were in the same range and averaged 530 and 500 ng m2 day-1, respectively. The fluxes were found to be higher with a factor of 2.5 for ƩPAHs and a factor of 3 for ƩPAH-derivatives during cold (<0 °C) in comparison to warm (>10 °C) periods. PAHs and PAH-derivatives showed similar seasonal patterns, which suggests that these two compound classes have similar sources and deposition mechanisms, and that the source strength of the PAH-derivatives in air follows that of the PAHs. The terrestrial export of PACs via the outlet of the catchment stream was estimated to be 1.1% for ƩPAHs and 1.7% for ƩPAH-derivatives in relation to the annual amounts deposited to the catchment, which suggests that boreal forests are sinks for PACs derived from the atmosphere. Some individual PACs showed higher export than others (i.e. chrysene, cyclopenta(c,d)pyrene, carbazole, quinoline, and benzo(f)quinoline), with high export PACs mostly characterized by low molecular weight and low hydrophobicity (2-3 benzene rings; log Kow<6.0).

Insights into the mechanisms of organic pollutant toxicity to earthworms: Advances and perspectives

Earthworms play positive ecological roles in soil formation, structure, and fertility, environmental protection, and terrestrial food chains. For this review, we searched the Web of Science database for articles published from 2011 to 2021 using the keywords "toxic" and "earthworm" and retrieved 632 publications. From the perspective of bibliometric analysis, we conducted a co-occurrence network analysis using the keywords "toxic" and "earthworm" to identify the most and least reported topics. "Eisenia fetida," "bioaccumulation," "heavy metals," "oxidative stress," and "pesticides" were the most common terms, and "microbial community," "bacteria," "PFOS," "bioaugmentation," "potentially toxic elements," "celomic fluid," "neurotoxicity," "joint toxicity," "apoptosis," and "nanoparticles" were uncommon terms. Additionally, in this review we highlight the main routes of organic pollutant entry into soil, and discuss the adverse effects on the soil ecosystem. We then systematically review the mechanisms underlying organic pollutant toxicity to earthworms, including oxidative stress, energy and lipid metabolism disturbances, neurological toxicity, intestinal inflammation and injury, gut microbiota dysbiosis, and reproductive toxicity. We conclude by discussing future research perspectives, focusing on environmentally relevant concentrations and conditions, novel data processing approaches, technologies, and detoxification and mitigation methods. This review has implications for soil management in the context of environmental pollution.

The Role of Spring Flood and Landscape Type in the Terrestrial Export of Polycyclic Aromatic Compounds to Streamwater

Concentrations of polycyclic aromatic compounds (PACs), including 19 polycyclic aromatic hydrocarbons (PAHs) and 15 PAH-derivatives (oxygenated and nitrogen heterocyclic PAHs), were measured in streams in a remote headwater catchment in northern Europe and in more urbanized, downstream areas. Sampling was conducted during 2014 to 2016 and included the main hydrological seasons (snow-free, snow-covered, and spring flood) at six sampling sites. Levels of the targeted PACs varied substantially over time and space and were up to 110-fold (on average 17-fold) and 7000-fold (on average 670-fold) higher for PAHs and PAH-derivatives, respectively, during spring flood compared with preceding snow-covered and snow-free seasons. Higher levels of ∑PACs were generally found in a headwater stream draining a mire than at an adjacent forested site, with up to 20 times and 150 times higher levels for ∑PAH and ∑PAH-derivatives, respectively. The particle-bound PAC levels were positively correlated to surface runoff in the mire stream (∑PAHs: p = 0.032; ∑PAH-derivatives: p = 0.040) but not in the corresponding forest stream, during snowmelt and winter base flow. In more urbanized downstream areas, particle-bound PACs were instead strongly associated with suspended particulate matter ( p < 0.05; ∑PAHs and ∑PAH-derivatives except one site). Levels of ∑PACs in the streamwater were on average 3-fold higher downstream of the most densely populated area than at the outlet of the headwater catchment. The higher PAC levels in the downstream water compared to the remote headwater were clearer when normalized to SPM amounts (instead of water volume), with a gradual downstream trend between the sites.

Levels and predictors of persistent organic pollutants in an adult population from four Spanish regions

This research aimed to assess serum concentrations of a group of persistent organic pollutants (POPs) in a sample of adults recruited in four different regions from Spain and to assess socio-demographic, dietary, and lifestyle predictors of the exposure. The study population comprised 312 healthy adults selected from among controls recruited in the MCC-Spain multicase-control study. Study variables were collected using standardized questionnaires, and pollutants were analyzed by means of gas chromatography with electron capture detection. Multivariable analyses were performed to identify predictors of log-transformed pollutant concentrations, using combined backward and forward stepwise multiple linear regression models. Detection rates ranged from 89.1% (hexachlorobenzene, HCB) to 93.6% (Polychlorinated biphenyl-153 [PCB-153]); p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) showed the highest median concentrations (1.04ng/ml), while HCB showed the lowest (0.24ng/ml). In the multivariable models, age was positively associated with HCB, p,p'-DDE, and PCB-180. BMI was associated positively with p,p'-DDE but negatively with PCB-138. Total accumulated time residing in an urban area was positively associated with PCB-153 concentrations. The women showed higher HCB and lower p,p'-DDE concentrations versus the men. Notably, POP exposure in our study population was inversely associated with the breastfeeding received by participants and with the number of pregnancies of their mothers but was not related to the participants' history of breastfeeding their children or parity. Smoking was negatively associated with HCB and PCB-153 concentrations. Consumption of fatty foods, including blue fish, was in general positively associated with POP levels. Although POP environmental levels are declining worldwide, there is a need for the continuous monitoring of human exposure in the general population. The results of the present study confirm previous findings and point to novel predictors of long-term exposure to persistent organic pollutants.

Microarray-based analysis of gene expression in lycopersicon esculentum seedling roots in response to cadmium, chromium, mercury, and lead

The effects of heavy metals in agricultural soils have received special attention due to their potential for accumulation in crops, which can affect species at all trophic levels. Therefore, there is a critical need for reliable bioassays for assessing risk levels due to heavy metals in agricultural soil. In the present study, we used microarrays to investigate changes in gene expression of Lycopersicon esculentum in response to Cd-, Cr-, Hg-, or Pb-spiked soil. Exposure to (1)/10 median lethal concentrations (LC50) of Cd, Cr, Hg, or Pb for 7 days resulted in expression changes in 29 Cd-specific, 58 Cr-specific, 192 Hg-specific and 864 Pb-specific genes as determined by microarray analysis, whereas conventional morphological and physiological bioassays did not reveal any toxicant stresses. Hierarchical clustering analysis showed that the characteristic gene expression profiles induced by Cd, Cr, Hg, and Pb were distinct from not only the control but also one another. Furthermore, a total of three genes related to "ion transport" for Cd, 14 genes related to "external encapsulating structure organization", "reproductive developmental process", "lipid metabolic process" and "response to stimulus" for Cr, 11 genes related to "cellular metabolic process" and "cellular response to stimulus" for Hg, 78 genes related to 20 biological processes (e.g., DNA metabolic process, monosaccharide catabolic process, cell division) for Pb were identified and selected as their potential biomarkers. These findings demonstrated that microarray-based analysis of Lycopersicon esculentum was a sensitive tool for the early detection of potential toxicity of heavy metals in agricultural soil, as well as an effective tool for identifying the heavy metal-specific genes, which should be useful for assessing risk levels due to heavy metals in agricultural soil.

Using combined bio-omics methods to evaluate the complicated toxic effects of mixed chemical wastewater and its treated effluent

Mixed chemical wastewaters (MCWW) from industrial park contain complex mixtures of trace contaminants, which cannot be effectively removed by wastewater treatment plants (WWTP) and have become an unignored threat to ambient environment. However, limited information is available to evaluate the complicated toxic effects of MCWW and its effluent from wastewater treatment plant (WTPE) from the perspective of bio-omics. In this study, mice were exposed to the MCWW and WTPE for 90 days and distinct differences in the hepatic transcriptome and serum metabolome were analyzed by digital gene expression (DGE) and proton nuclear magnetic resonance ((1)H-NMR) spectra, respectively. Our results indicated that disruption of lipid metabolism in liver and hepatotoxicity were induced by both MCWW and WTPE exposure. WTPE is still a health risk to the environment, which is in need of more attention. Furthermore, we demonstrated the potential ability of bio-omics approaches for evaluating toxic effects of MCWW and WTPE.

A three step network based approach (TSNBA) to finding disease molecular signature and key regulators: a case study of IL-1 and TNF-alpha stimulated inflammation

A disease molecular signature is a set of biomolecular features that are prognostic of clinical phenotypes and indicative of underlying pathology. It is of great importance to develop computational approaches for finding more relevant molecular signatures. Based upon the hypothesis that various components in a molecular signature are more likely to share similar patterns, we introduced a novel three step network based approach (TSNBA) to identify the molecular signature and key pathological regulators. Protein-protein interaction (PPI) network and ranking algorithm were integrated in the first step to find pathology related proteins with high accuracy. It was followed by the second step to further screen with co-expression patterns for better pathology enrichment. Context likelihood of relatedness (CLR) algorithm was used in the third step to infer gene regulatory networks and identify key transcription regulators. We applied this approach to study IL-1 (interleukin-1) and TNF-alpha (tumor necrosis factor-alpha) stimulated inflammation. TSNBA identified inflammatory signature with high accuracy and outperformed 5 competing methods namely fold change, degree, interconnectivity, neighborhood score and network propagation based approaches. The best molecular signature, with 80% (40/50) confirmed inflammatory genes, was used to predict inflammation related genes. As a result, 8 out of 10 predicted inflammation genes that were not included in the benchmark Entrez Gene database were validated by literature evidence. Furthermore, 23 of the 32 predicted inflammation regulators were validated by literature evidence. The rest 9 were also validated with TF (transcription factor) binding site analysis. In conclusion, we developed an efficient strategy for disease molecular signature finding and key pathological regulator identification.

Discovery of characteristic molecular signatures for the simultaneous prediction and detection of environmental pollutants

Gene expression data may be very promising for the classification of toxicant types, but the development and application of transcriptomic-based gene classifiers for environmental toxicological applications are lacking compared to the biomedical sciences. Also, simultaneous classification across a set of toxicant types has not been investigated extensively. In the present study, we determined the transcriptomic response to three types of ubiquitous toxicants exposure in two types of human cell lines (HepG2 and HL-60), which are useful in vitro human model for evaluation of toxic substances that may affect human hepatotoxicity (e.g., polycyclic aromatic hydrocarbon [PAH] and persistent organic pollutant [POP]) and human leukemic myelopoietic proliferation (e.g., volatile organic compound [VOC]). The findings demonstrate characteristic molecular signatures that facilitated discrimination and prediction of the toxicant type. To evaluate changes in gene expression levels after exposure to environmental toxicants, we utilized 18 chemical substances; nine PAH toxicants, six VOC toxicants, and three POP toxicants. Unsupervised gene expression analysis resulted in a characteristic molecular signature for each toxicant group, and combination analysis of two separate multi-classifications indicated 265 genes as surrogate markers for predicting each group of toxicants with 100 % accuracy. Our results suggest that these expression signatures can be used as predictable and discernible surrogate markers for detection and prediction of environmental toxicant exposure. Furthermore, this approach could easily be extended to screening for other types of environmental toxicants.