A class B heat shock factor selected for during soybean domestication contributes to salt tolerance by promoting flavonoid biosynthesis.

Soybean (Glycine max) production is severely affected in unfavorable environments. Identification of the regulatory factors conferring stress tolerance would facilitate soybean breeding. In this study, through coexpression network analysis of salt-tolerant wild soybeans, together with molecular and genetic approaches, we revealed a previously unidentified function of a class B heat shock factor, HSFB2b, in soybean salt stress response. We showed that HSFB2b improves salt tolerance through the promotion of flavonoid accumulation by activating one subset of flavonoid biosynthesis-related genes and by inhibiting the repressor gene GmNAC2 to release another subset of genes in the flavonoid biosynthesis pathway. Moreover, four promoter haplotypes of HSFB2b were identified from wild and cultivated soybeans. Promoter haplotype II from salt-tolerant wild soybean Y20, with high promoter activity under salt stress, is probably selected for during domestication. Another promoter haplotype, III, from salt-tolerant wild soybean Y55, had the highest promoter activity under salt stress, had a low distribution frequency and may be subjected to the next wave of selection. Together, our results revealed the mechanism of HSFB2b in soybean salt stress tolerance. Its promoter variations were identified, and the haplotype with high activity may be adopted for breeding better soybean cultivars that are adapted to stress conditions.

Application of land use regression to assess exposure and identify potential sources in PM2.5, BC, NO2 concentrations.

BACKGROUND: Understanding spatial variation of air pollution is critical for public health assessments. Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations. However, they have limited application in China due to the lack of spatially resolved data. OBJECTIVE: Based on purpose-designed monitoring networks, this study developed LUR models to predict fine particulate matter (PM2.5), black carbon (BC) and nitrogen dioxide (NO2) exposure and to identify their potential outdoor-origin sources within an urban/rural region, using Taizhou, China as a case study. METHOD: Two one-week integrated samples were collected at 30 PM2.5 (BC) sites and 45 NO2 sites in each two distinct seasons. Samples of 1/3 of the sites were collected simultaneously. Annual adjusted average was calculated and regressed against pre-selected GIS-derived predictor variables in a multivariate regression model. RESULTS: LUR explained 65% of the spatial variability in PM2.5, 78% in BC and 73% in NO2. Mean (±Standard Deviation) of predicted PM2.5, BC and NO2 exposure levels were 48.3 (±6.3) µg/m3, 7.5 (±1.4) µg/m3 and 27.3 (±8.2) µg/m3, respectively. Weak spatial corrections (Pearson r = 0.05-0.25) among three pollutants were observed, indicating the presence of different sources. Regression results showed that PM2.5, BC and NO2 levels were positively associated with traffic variables. The former two also increased with farm land use; and higher NO2 levels were associated with larger industrial land use. The three pollutants were correlated with sources at a scale of ≤5 km and even smaller scales (100-700m) were found for BC and NO2. CONCLUSION: We concluded that based on a purpose-designed monitoring network, LUR model can be applied to predict PM2.5, NO2 and BC concentrations in urban/rural settings of China. Our findings highlighted important contributors to within-city heterogeneity in outdoor-generated exposure, and indicated traffic, industry and agriculture may significantly contribute to PM2.5, NO2 and BC concentrations.

An ionic liquid-magnetic graphene composite for magnet dispersive solid-phase extraction of triazine herbicides in surface water followed by high performance liquid chromatography.

A new ionic liquid-magnetic graphene (IL-MG) composite was used as the adsorbent in magnetic dispersive solid-phase extraction to rapidly extract and isolate triazine herbicides from surface water. IL-MG was synthesized by a simple and time-saving one-pot strategy where the synthesis of magnetic Fe3O4, the modification with an IL, and the reduction of graphene oxide to graphene were conducted at the same time. An IL was applied to enrich the interaction mechanism between IL-MG and analytes (π-π, hydrophobic interaction, and electrostatic interaction). Moreover, the IL and Fe3O4 nanoparticles acted as spacers, inserting between the layers of graphene to prevent the aggregation of graphene, which improved the adsorption ability because of the large specific surface area of IL-MG. The resultant IL-MG had hierarchical flake structures and showed a high adsorption capacity (8266.0-12 324.1 µg g-1) toward triazine herbicides. Under suitable conditions, the linearity for triazine herbicides was achieved in the range of 0.55-500 ng mL-1 with a detection limit of 0.09-0.15 ng mL-1 and a quantitation limit of 0.31-0.51 ng mL-1, and the enrichment factor was 83-fold, which indicated that the proposed method could be successfully applied for the determination of triazine herbicides in surface water.

Wheat WRKY genes TaWRKY2 and TaWRKY19 regulate abiotic stress tolerance in transgenic Arabidopsis plants.

WRKY-type transcription factors are involved in multiple aspects of plant growth, development and stress response. WRKY genes have been found to be responsive to abiotic stresses; however, their roles in abiotic stress tolerance are largely unknown especially in crops. Here, we identified stress-responsive WRKY genes from wheat (Triticum aestivum L.) and studied their functions in stress tolerance. Forty-three putative TaWRKY genes were identified and two multiple stress-induced genes, TaWRKY2 and TaWRKY19, were further characterized. TaWRKY2 and TaWRKY19 are nuclear proteins, and displayed specific binding to typical cis-element W box. Transgenic Arabidopsis plants overexpressing TaWRKY2 exhibited salt and drought tolerance compared with controls. Overexpression of TaWRKY19 conferred tolerance to salt, drought and freezing stresses in transgenic plants. TaWRKY2 enhanced expressions of STZ and RD29B, and bound to their promoters. TaWRKY19 activated expressions of DREB2A, RD29A, RD29B and Cor6.6, and bound to DREB2A and Cor6.6 promoters. The two TaWRKY proteins may regulate the downstream genes through direct binding to the gene promoter or via indirect mechanism. Manipulation of TaWRKY2 and TaWRKY19 in wheat or other crops should improve their performance under various abiotic stress conditions.

Measurement of air exchange rates in different indoor environments using continuous CO2 sensors.

A new air exchange rate (AER) monitoring method using continuous CO2 sensors was developed and validated through both laboratory experiments and field studies. Controlled laboratory simulation tests were conducted in a 1-m3 environmental chamber at different AERs (0.1-10.0 hr(-1)). AERs were determined using the decay method based on box model assumptions. Field tests were conducted in classrooms, dormitories, meeting rooms and apartments during 2-5 weekdays using CO2 sensors coupled with data loggers. Indoor temperature, relative humidity (RH), and CO2 concentrations were continuously monitored while outdoor parameters combined with on-site climate conditions were recorded. Statistical results indicated that good laboratory performance was achieved: duplicate precision was within 10%, and the measured AERs were 90%-120% of the real AERs. Average AERs were 1.22, 1.37, 1.10, 1.91 and 0.73 hr(-1) in dormitories, air-conditioned classrooms, classrooms with an air circulation cooling system, reading rooms, and meeting rooms, respectively. In an elderly particulate matter exposure study, all the homes had AER values ranging from 0.29 to 3.46 hr(-1) in fall, and 0.12 to 1.39 hr(-1) in winter with a median AER of 1.15.

Inhalation cancer risk estimation of source-specific personal exposure for particulate matter-bound polycyclic aromatic hydrocarbons based on positive matrix factorization.

In previous studies, inhalation cancer risk was estimated using conventional risk assessment method, which was normally based on compound-specific analysis, and cannot provide substantial data for source-specific particulate matter concentrations and pollution control. In the present study, we applied an integrated risk analysis method, which was a synthetic combination of source apportionment receptor model and risk assessment method, to estimate cancer risks associated to individual PAHs coming from specific sources. Personal exposure particulate matter samples referring to an elderly panel were collected in a community of Tianjin, Northern China, in 2009, and 12 PAH compounds were measured using GC-MS. Positive matrix factorization (PMF) was used to extract the potential sources and quantify the source contributions to the PAH mixture. Then, the lung cancer risk of each modeled source was estimated by summing up the cancer risks of all measured PAH species according to the extracted source profile. The final results indicated that the overall cancer risk was 1.12 × 10-5, with the largest contribution from gasoline vehicle emission (44.1%). Unlike other risk estimation studies, this study was successful in combining risk analysis and source apportionment approaches, which allow estimating the potential risk of all source types and provided suitable information to select prior control strategies and mitigate the main air pollution sources that contributing to health risks.

Assessing the inhalation cancer risk of particulate matter bound polycyclic aromatic hydrocarbons (PAHs) for the elderly in a retirement community of a mega city in North China.

Assessment of the health risks resulting from exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is limited by the lack of environmental exposure data among different subpopulations. To assess the exposure cancer risk of particulate carcinogenic polycyclic aromatic hydrocarbon pollution for the elderly, this study conducted a personal exposure measurement campaign for particulate PAHs in a community of Tianjin, a city in northern China. Personal exposure samples were collected from the elderly in non-heating (August-September, 2009) and heating periods (November-December, 2009), and 12 PAHs individuals were analyzed for risk estimation. Questionnaire and time-activity log were also recorded for each person. The probabilistic risk assessment model was integrated with Toxic Equivalent Factors (TEFs). Considering that the estimation of the applied dose for a given air pollutant is dependent on the inhalation rate, the inhalation rate from both EPA exposure factor book was applied to calculate the carcinogenic risk in this study. Monte Carlo simulation was used as a probabilistic risk assessment model, and risk simulation results indicated that the inhalation-ILCR values for both male and female subjects followed a lognormal distribution with a mean of 4.81 × 10-6 and 4.57 × 10-6, respectively. Furthermore, the 95 % probability lung cancer risks were greater than the USEPA acceptable level of 10-6 for both men and women through the inhalation route, revealing that exposure to PAHs posed an unacceptable potential cancer risk for the elderly in this study. As a result, some measures should be taken to reduce PAHs pollution and the exposure level to decrease the cancer risk for the general population, especially for the elderly.

Assessment on personal exposure to particulate compounds using an empirical exposure model in an elderly community in Tianjin, China.

Using central site measurement data to predict personal exposure to particulate matter (PM) is challenging, because people spend most of their time indoors and ambient contribution to personal exposure is subject to infiltration conditions affected by many factors. Efforts in assessing and predicting exposure on the basis of associated indoor/outdoor and central site monitoring were limited in China. This study collected daily personal exposure, residential indoor/outdoor and community central site PM filter samples in an elderly community during the non-heating and heating periods in 2009 in Tianjin, China. Based on the chemical analysis results of particulate species, mass concentrations of the particulate compounds were estimated and used to reconstruct the PM mass for mass balance analysis. The infiltration factors (Finf) of particulate compounds were estimated using both robust regression and mixed effect regression methods, and further estimated the exposure factor (Fpex) according to participants' time-activity patterns. Then an empirical exposure model was developed to predict personal exposure to PM and particulate compounds as the sum of ambient and non-ambient contributions. Results showed that PM mass observed during the heating period could be well represented through chemical mass reconstruction, because unidentified mass was minimal. Excluding the high observations (>300µg/m3), this empirical exposure model performed well for PM and elemental carbon (EC) that had few indoor sources. These results support the use of Fpex as an indicator for ambient contribution predictions, and the use of empirical non-ambient contribution to assess exposure to particulate compounds.

Residential indoor and personal PM10 exposures of ambient origin based on chemical components.

Many studies have focused on the relationships of particulate matter between indoor, outdoor and personal exposure; however, considerable uncertainties remain regarding the portion of indoor particles and personal exposure of ambient origin. As part of the Particle Exposure Assessment for Community Elderly (PEACE) study in Tianjin, China, we have further interpreted the relationships between personal, residential indoor, outdoor and community PM10 (particulate matter with aerodynamic diameters of less than 10 µm). Comparisons of the chemical compositions of PM10 samples were performed using the coefficient of divergence (COD). A robust regression method, least-trimmed squared (LTS) regression, was used to estimate the infiltration factors of PM10 from residential outdoor to indoor environments based on the particulate component concentrations. Personal exposures of ambient origin were also estimated. A relatively good correlation was found between the personal and indoor PM10 samples with respect to chemical composition. The infiltration factors (Finf) of the residential indoor-outdoor PM10 were 0.74±0.31 (mean±SD) in summer and 0.44±0.22 in winter, with medians of 0.98 and 0.48, respectively. The residential outdoor contributions to the indoor environments were 87±55 µg/m(3) in summer and 80±54 µg/m(3) in winter, with medians of 75 µg/m(3) and 61 µg/m(3), respectively. The personal exposures of ambient origin were 92±44 µg/m(3) in summer and 89±47 µg/m(3) in winter, with medians of 81 µg/m(3) and 80 µg/m(3), respectively. This study indicated that the infiltrations in an urbanized area in North China exhibited a seasonal difference: the residential outdoor contributions to residential indoor environments were larger in summer due to the higher use of natural ventilation. The personal exposures of ambient origin were comparable during the different seasons, whereas those of non-ambient origin were higher in summer than in winter.

Soybean Trihelix transcription factors GmGT-2A and GmGT-2B improve plant tolerance to abiotic stresses in transgenic Arabidopsis.

BACKGROUND: Trihelix transcription factors play important roles in light-regulated responses and other developmental processes. However, their functions in abiotic stress response are largely unclear. In this study, we identified two trihelix transcription factor genes GmGT-2A and GmGT-2B from soybean and further characterized their roles in abiotic stress tolerance. FINDINGS: Both genes can be induced by various abiotic stresses, and the encoded proteins were localized in nuclear region. In yeast assay, GmGT-2B but not GmGT-2A exhibits ability of transcriptional activation and dimerization. The N-terminal peptide of 153 residues in GmGT-2B was the minimal activation domain and the middle region between the two trihelices mediated the dimerization of the GmGT-2B. Transactivation activity of the GmGT-2B was also confirmed in plant cells. DNA binding analysis using yeast one-hybrid assay revealed that GmGT-2A could bind to GT-1bx, GT-2bx, mGT-2bx-2 and D1 whereas GmGT-2B could bind to the latter three elements. Overexpression of the GmGT-2A and GmGT-2B improved plant tolerance to salt, freezing and drought stress in transgenic Arabidopsis plants. Moreover, GmGT-2B-transgenic plants had more green seedlings compared to Col-0 under ABA treatment. Many stress-responsive genes were altered in GmGT-2A- and GmGT-2B-transgenic plants. CONCLUSION: These results indicate that GmGT-2A and GmGT-2B confer stress tolerance through regulation of a common set of genes and specific sets of genes. GmGT-2B also affects ABA sensitivity.