Gene Expression of an <i>Arthrobacter</i> in Surfactant-Enhanced Biodegradation of a Hydrophobic Organic Compound

Surfactants can affect the biodegradation process and the fate of hydrophobic organic compounds (HOCs) in the environment. Previous studies have shown that surfactants can enhance the biodegradation of HOCs by increasing cell surface hydrophobicity (CSH) and membrane fluidity. In this study, we took this work one step further by investigating the expression levels of three genes of <i>Arthrobacter</i> sp. SA02 in the biodegradation of phenanthrene as a typical HOC at different concentrations of sodium dodecyl benzenesulfonate (SDBS), which is a widely used surfactant. The <i>Δ9 fatty acid desaturase</i> gene codes for Δ9 fatty acid desaturase, which can convert saturated fatty acid to its unsaturated form. The ring-hydroxylating dioxygenase (<i>RHDase</i>) and the 1-hydroxyl-2-naphthoate dioxygenase (<i>1H2Nase</i>) genes code for the RHDase and 1H2Nase enzymes, respectively, which play a key role in decomposing doubly hydroxylated aromatic compounds. The results show that these three genes were upregulated in the presence of SDBS. On the basis of the genetic and physiological changes, we proposed a pathway that links the gene expression with the physiological phenomena, including CSH, membrane fluidity, and intracellular degradation. This study advances our understanding of the surfactant-enhanced biodegradation of HOCs at the gene level, and the proposed pathway should be further validated in the future

Interconversion between Methoxylated and Hydroxylated Polychlorinated Biphenyls in Rice Plants: An Important but Overlooked Metabolic Pathway

To date, there is limited knowledge on the methoxylation of polychlorinated biphenyls (PCBs) and the relationship between hydroxylated polychlorinated biphenyls (OH-PCBs) and methoxylated polychlorinated biphenyls (MeO-PCBs) in organisms. In this study, rice (Oryza sativa L.) was chosen as the model organism to determine the metabolism of PCBs in plants. Limited para-substituted 4′-OH-CB-61 (major metabolite) and 4′-MeO-CB-61 (minor metabolite) were found after a 5-day exposure to CB-61, while ortho- and meta-substituted products were not detected. Interconversion between OH-PCBs and MeO-PCBs in organisms was observed for the first time. The demethylation ratio of 4′-MeO-CB-61 was 18 times higher than the methylation ratio of 4′-OH-CB-61, indicating that formation of OH-PCBs was easier than formation of MeO-PCBs. The transformation products were generated in the roots after 24 h of exposure. The results of in vivo and in vitro exposure studies show that the rice itself played a key role in the whole transformation processes, while endophytes were jointly responsible for hydroxylation of PCBs and demethylation of MeO-PCBs. Metabolic pathways of PCBs, OH-PCBs, and MeO-PCBs in intact rice plants are proposed. The findings are important in understanding the fate of PCBs and the source of OH-PCBs in the environment

Estimating Emissions and Environmental Fate of Di-(2-ethylhexyl) Phthalate in Yangtze River Delta, China: Application of Inverse Modeling

A georeferenced multimedia model was developed for evaluating the emissions and environmental fate of di-2-ethylhexyl phthalate (DEHP) in the Yangtze River Delta (YRD), China. Due to the lack of emission inventories, the emission rates were estimated using the observed concentrations in soil as inputs for the multimedia model solved analytically in an inverse manner. The estimated emission rates were then used to evaluate the environmental fate of DEHP with the regular multimedia modeling approach. The predicted concentrations in air, surface water, and sediment were all consistent with the ranges and spatial variations of observed data. The total emission rate of DEHP in YRD was 13.9 thousand t/year (95% confidence interval: 9.4–23.6), of which urban and rural sources accounted for 47% and 53%, respectively. Soil in rural areas and sediment stored 79% and 13% of the total mass, respectively. The air received 61% of the total emissions of DEHP but was only associated with 0.2% of the total mass due to fast degradation and intensive deposition. We suggest the use of an inverse modeling approach under a tiered risk assessment framework to assist future development and refinement of DEHP emission inventories

Satellite-Based Estimates of Daily NO₂ Exposure in China Using Hybrid Random Forest and Spatiotemporal Kriging Model

A novel model named random-forest-spatiotemporal-kriging (RF-STK) was developed to estimate the daily ambient NO₂ concentrations across China during 2013–2016 based on the satellite retrievals and geographic covariates. The RF-STK model showed good prediction performance, with cross-validation <i>R</i>² = 0.62 (RMSE = 13.3 μg/m³) for daily and <i>R</i>² = 0.73 (RMSE = 6.5 μg/m³) for spatial predictions. The nationwide population-weighted multiyear average of NO₂ was predicted to be 30.9 ± 11.7 μg/m³ (mean ± standard deviation), with a slowly but significantly decreasing trend at a rate of −0.88 ± 0.38 μg/m³/year. Among the main economic zones of China, the Pearl River Delta showed the fastest decreasing rate of −1.37 μg/m³/year, while the Beijing-Tianjin Metro did not show a temporal trend (<i>P</i> = 0.32). The population-weighted NO₂ was predicted to be the highest in North China (40.3 ± 10.3 μg/m³) and lowest in Southwest China (24.9 ± 9.4 μg/m³). Approximately 25% of the population lived in nonattainment areas with annual-average NO₂ > 40 μg/m³. A piecewise linear function with an abrupt point around 100 people/km² characterized the relationship between the population density and the NO₂, indicating a threshold of aggravated NO₂ pollution due to urbanization. Leveraging the ground-level NO₂ observations, this study fills the gap of statistically modeling nationwide NO₂ in China, and provides essential data for epidemiological research and air quality management

Established Thymic Epithelial Progenitor/Stem Cell-Like Cell Lines Differentiate into Mature Thymic Epithelial Cells and Support T Cell Development

<div><p>Common thymic epithelial progenitor/stem cells (TEPCs) differentiate into cortical and medullary thymic epithelial cells (TECs), which are required for the development and selection of thymocytes. Mature TEC lines have been widely established. However, the establishment of TEPC lines is rarely reported. Here we describe the establishment of thymic epithelial stomal cell lines, named TSCs, from fetal thymus. TSCs express some of the markers present on tissue progenitor/stem cells such as Sca-1. Gene expression profiling verifies the thymic identity of TSCs. RANK stimulation of these cells induces expression of autoimmune regulator (Aire) and Aire-dependent tissue-restricted antigens (TRAs) in TSCs <i>in vitro</i>. TSCs could be differentiated into medullary thymic epithelial cell-like cells with exogenously expressed NF-κB subunits RelB and p52. Importantly, upon transplantation under the kidney capsules of nude mice, TSCs are able to differentiate into mature TEC-like cells that can support some limited development of T cells <i>in vivo</i>. These findings suggest that the TSC lines we established bear some characteristics of TEPC cells and are able to differentiate into functional TEC-like cells <i>in vitro</i> and <i>in vivo</i>. The cloned TEPC-like cell lines may provide useful tools to study the differentiation of mature TEC cells from precursors.</p> </div

TSCs display thymus identity.

<p>(a) RNAs were extracted from TSC2, 1307-6.1.7 and mTEC8 cells, and transcripts were detected by RT-PCR for the expression of indicated genes. (b) Immunoblot analysis of CBX4, delta Np63, TAp63 and DNMT3a in extracts of TSC2, mTEC1 and mTEC8 cells. GAPDH was used as a loading control.</p

Established TSC cells express markers of non-hematopoietic stem cells.

<p>(a) Representative spindle-like morphology of TSC clone 2 established from C57BL/6 E14.5 thymus repeated subculture and limiting dilution cloning.(b) Flow cytometric analysis of WT TSC with antibodies to Sca-1, CD29, CD44, CD45, CD73, CD105, CD133, CD80, MHC class I and II.</p

TSCs differentiate into Aire-expressing TECs <i>in vitro</i>.

<p>(a) Immunoblot analysis of Aire, delta Np63, DNMT3a, c-Myc, p52 and. RelB in extracts of TSCs stably overexpressed with p52 and RelB for 11 days. (b) Immunofluorescence analysis for UEA-1 and K8 in TSCs stably overexpressed with p52 and RelB for 11 days.</p

TSCs express cell surface markers of TEPCs.

<p>(a) Flow cytometry analysis of WT TSC line with anti-K5, anti-K8, anti-MTS24, anti-MTS10, anti-CDC205, anti-EpCAM1, 3T3 cells as a negative control for anti-CD205 and anti-EpCAM1. (b) Immunostaining of WT TSC line and 1307-6.1.7 cells with anti-K5 (green), anti-K8 (blue), anti-EpCAM1 (green), anti-Aire (red). (c) Immunostaining of WT TSC line with anti-K8 (blue) and anti-pan-cytokeratin (green).</p

Additional file 1: of Heterologous expression, purification and function of the extracellular domain of human RANK

DNA sequence of Pichia pastoris favored codon optimize of RANK -N(human). (DOCX 12 kb