Mechanism of antimicrobial peptide NP-6 from Sichuan pepper seeds against E. coli and effects of different environmental factors on its activity.

A novel antimicrobial peptide named NP-6 was identified in our previous work. Here, the mechanisms of the peptide against Escherichia coli (E. coli) were further investigated, as well as the peptide's resistance to temperature, pH, salinity, and enzymes. The transmission electron microscopy (TEM), confocal laser scanning microcopy (CLSM), and flow cytometric (FCM) analysis, combined with measurement of released K+, were performed to evaluate the effect of NP-6 E. coli cell membrane. The influence of NP-6 on bacterial DNA/RNA and enzyme was also investigated. The leakage of K+ demonstrated that NP-6 could increase the permeability of E. coli cell membrane. The ATP leakage, FCM, and CLSM assays suggested that NP-6 caused the disintegration of bacterial cell membrane. The TEM observation indicated that NP-6 could cause the formation of empty cells and debris. Besides, the DNA-binding assay indicated that NP-6 could bind with bacterial genomic DNA in a way that ethidium bromide (EB) did, and suppress the migration of DNA/RNA in gel retardation. Additionally, NP-6 could also affect the activity of ß-galactosidase. Finally, the effect of different surroundings such as heating, pH, ions, and protease on the antimicrobial activity of NP-6 against E. coli was also investigated. Results showed that the peptide was heat stable in the range of 60~100 °C and performed well at pH 6.0~8.0. However, the antimicrobial activity of NP-6 decreased significantly in the presence of Mg2+/Ca2+, and after incubation with trypsin/proteinase K. The results will provide a theoretical support in the further application of NP-6.

Small RNA and degradome sequencing reveals microRNAs and their targets involved in tomato pedicel abscission.

MAIN CONCLUSION: We constructed small RNA and degradome sequencing libraries to identify miRNAs and targets involved in tomato pedicel abscission, and confirmed their roles via quantitative real-time PCR. MicroRNAs (miRNAs) are endogenous small RNAs which play crucial negatively regulatory roles at both the transcriptional and post-transcriptional levels in plants; however, limited knowledge is available on the expression profiles of miRNAs and their target genes during tomato pedicel abscission. Taking advantage of small RNA (sRNA) and degradome sequencing technology, a total of 56 known and 11 novel candidate miRNAs targeting 223 mRNA genes were confirmed during pedicel abscission. Gene ontology annotation and KEGG pathway analysis showed that these target genes were significantly enriched in intracellular, membrane-bounded organelle-related biological processes as well as in metabolic, plant-pathogen interaction and hormone signaling pathways. We screened 17 miRNA/target pairs for further analysis and performed quantitative real-time PCR to identify the roles. Cluster analysis of selected miRNAs revealed that the expression profiles of miRNAs varied in different stages of abscission and could be impacted by ethylene treatment. In the present study, the correlations between miRNAs and targets suggested a complex regulatory network of miRNA-mediated target interaction during pedicel abscission. Additionally, the expression profiles of miRNAs and their targets changed by ethylene might be a considerable reason why ethylene promotes pedicel abscission. Our study provides new insights into the expression and regulatory profiles of miRNAs during tomato pedicel abscission.

Multigene manipulation of photosynthetic carbon metabolism enhances the photosynthetic capacity and biomass yield of cucumber under low-CO2 environment.

Solar greenhouses are important in the vegetable production and widely used for the counter-season production in the world. However, the CO2 consumed by crops for photosynthesis after sunrise is not supplemented and becomes chronically deficient due to the airtight structure of solar greenhouses. Vegetable crops cannot effectively utilize light resources under low-CO2 environment, and this incapability results in reduced photosynthetic efficiency and crop yield. We used cucumber as a model plant and generated several sets of transgenic cucumber plants overexpressing individual genes, including ß-carbonic anhydrase 1 (CsßCA1), ß-carbonic anhydrase 4 (CsßCA4), and sedoheptulose-1,7-bisphosphatase (CsSBP); fructose-1,6-bisphosphate aldolase (CsFBA), and CsßCA1 co-expressing plants; CsßCA4, CsSBP, and CsFBA co-expressing plants (14SF). The results showed that the overexpression of CsßCA1, CsßCA4, and 14SF exhibited higher photosynthetic and biomass yield in transgenic cucumber plants under low-CO2 environment. Further enhancements in photosynthesis and biomass yield were observed in 14SF transgenic plants under low-CO2 environment. The net photosynthesis biomass yield and photosynthetic rate increased by 49% and 79% compared with those of the WT. However, the transgenic cucumbers of overexpressing CsFBA and CsSBP showed insignificant differences in photosynthesis and biomass yield compared with the WT under low-CO2.environment. Photosynthesis, fluorescence parameters, and enzymatic measurements indicated that CsßCA1, CsßCA4, CsSBP, and CsFBA had cumulative effects in photosynthetic carbon assimilation under low-CO2 environment. Co-expression of this four genes (CsßCA1, CsßCA4, CsSBP, and CsFBA) can increase the carboxylation activity of RuBisCO and promote the regeneration of RuBP. As a result, the 14SF transgenic plants showed a higher net photosynthetic rate and biomass yield even under low-CO2environment.These findings demonstrate the possibility of cultivating crops with high photosynthetic efficiency by manipulating genes involved in the photosynthetic carbon assimilation metabolic pathway.

Impact of various vegetation configurations on traffic fine particle pollutants in a street canyon for different wind regimes.

Vegetation establishment in urban areas is a potential solution to combat elevated particulate matter (PM) pollution, create cleaner environment for residents and enhance the sustainability of cities. However, vegetation effect at the points of interest in street-canyon on traffic pollutant from multiple interconnected factors (e.g., plant species, vegetation configurations, aerodynamic effect, deposition effect and complex wind regimes) is still not well studied. Therefore, taking roadside vegetation and street canyon as research objects, we evaluated vegetation effect (VE) for vegetation configurations (VCs) with several tree species on the dispersion, deposition, and distribution of traffic generated PM pollutant under different wind regimes. Results showed that (1) the transportation and distribution of traffic PM pollutant were different from wind regimes; (2) total VEs varied from -88.3% to 25.5%, depending on different VCs and wind regimes; perpendicular wind had the best VEs, while oblique wind had the worst VEs among the three wind directions; VEs of cypress were better than pine and poplar; VEs of one side planting were better than two sides planting. (3) the optimal VCs were found by each wind direction; two sides planting by shrub was suitable for parallel and oblique winds; for the perpendicular wind, the optimal VC was that two sides planting by cypress-shrub and increased canopy volume in the street center; and (4) VE were significantly correlated (P < 0.05) with vegetation parameters at lower wind speed, however, no correlations were found at higher wind speed under parallel wind; leeward wall VEs were significantly correlated with aerodynamic parameter (P < 0.001) while windward wall VEs and pedestrian-level VEs with deposition parameter (P < 0.05) under perpendicular wind; VEs were significantly decreased (P < 0.001) with aerodynamic parameter under oblique wind. The study highlights the impact of urban vegetation on air environment and provides insights for vegetation establishment from the viewpoint of improving air quality.

Plasma membrane-localized SlSWEET7a and SlSWEET14 regulate sugar transport and storage in tomato fruits.

Sugars, especially glucose and fructose, contribute to the taste and quality of tomato fruits. These compounds are translocated from the leaves to the fruits and then unloaded into the fruits by various sugar transporters at the plasma membrane. SWEETs, are sugar transporters that regulate sugar efflux independently of energy or pH. To date, the role of SWEETs in tomato has received very little attention. In this study, we performed functional analysis of SlSWEET7a and SlSWEET14 to gain insight into the regulation of sugar transport and storage in tomato fruits. SlSWEET7a and SlSWEET14 were mainly expressed in peduncles, vascular bundles, and seeds. Both SlSWEET7a and SlSWEET14 are plasma membrane-localized proteins that transport fructose, glucose, and sucrose. Apart from the resulting increase in mature fruit sugar content, silencing SlSWEET7a or SlSWEET14 resulted in taller plants and larger fruits (in SlSWEET7a-silenced lines). We also found that invertase activity and gene expression of some SlSWEET members increased, which was consistent with the increased availability of sucrose and hexose in the fruits. Overall, our results demonstrate that suppressing SlSWEET7a and SlSWEET14 could be a potential strategy for enhancing the sugar content of tomato fruits.

Prediction of chemical reproductive toxicity to aquatic species using a machine learning model: An application in an ecological risk assessment of the Yangtze River, China.

The endocrine disrupting chemicals (EDCs) have been at the forefront of environmental issues for over 20 years and are a principle factor considered in every ecological risk assessment, but this kind of risk assessment faces difficulties. The expense, time cost of in vivo tests, and lack of toxicity data are key limiting factors for the ability to conduct ecological risk assessments of EDCs to aquatic species. In this study, a machine learning model named the support vector machine (SVM) was used to predict the reproductive toxicity of EDCs, and the performance of the models was evaluated. The results showed that the SVM model provided more accurate toxicity prediction data compared with the interspecies correlation estimation (ICE) model developed by previous study to predict the reproductive toxicity. The application of the predicted toxicity data was an important supplement to the observed data for the ecological risk assessment of EDCs in the Yangtze River, where estrogens and phenolic compounds have been found at some sampling sites in the middle and lower reaches. The results showed that the ecological risk of estrone, 17ß-estradiol, and ethinyl estradiol were significant. This study revealed the application potential of machine learning models for the prediction of reproductive toxicity effects of EDCs. This can provide reliable alternative toxicity data for the ecological risk assessments of EDCs.

Dynamics of Soil Respiration in Alpine Wetland Meadows Exposed to Different Levels of Degradation in the Qinghai-Tibet Plateau, China.

The effects of degradation of alpine wetland meadow on soil respiration (Rs) and the sensitivity of Rs to temperature (Q10) were measured in the Napa Lake region of Shangri-La on the southeastern edge of the Qinghai-Tibet Plateau. Rs was measured for 24 h during each of three different stages of the growing season on four different degraded levels. The results showed: (1) peak Rs occurred at around 5:00 p.m., regardless of the degree of degradation and growing season stage, with the maximum Rs reaching 10.05 µmol·m-2·s-1 in non-degraded meadows rather than other meadows; (2) the daily mean Rs value was 7.14-7.86 µmol·m-2·s-1 during the mid growing season in non-degraded meadows, and declined by 48.4-62.6% when degradation increased to the severely degraded level; (3) Q10 ranged from 7.1-11.3 in non-degraded meadows during the mid growing season, 5.5-8.0 and 6.2-8.2 during the early and late growing seasons, respectively, and show a decline of about 50% from the non-degraded meadows to severely degraded meadows; (4) Rs was correlated significantly with soil temperature at a depth of 0-5 cm (p < 0.05) on the diurnal scale, but not at the seasonal scale; (5) significant correlations were found between Rs and soil organic carbon (SOC), between biomass and SOC, and between Q10 and Rs (p < 0.05), which indicates that biomass and SOC potentially impact Q10. The results suggest that vegetation degradation impact both Rs and Q10 significantly. Also, we speculated that Q10 of alpine wetland meadow is probable greater at the boundary region than inner region of the Qinghai-Tibet Plateau, and shoule be a more sensitive indicator in the studying of climate change in this zone.

Proposed conservation landscape for giant pandas in the Minshan Mountains, China.

The giant panda (Ailuropoda melanoleuca), is one of the world's most endangered species. Habitat loss and fragmentation have reduced its numbers, shrunk its distribution, and separated the population into isolated subpopulations. Such isolated, small populations are in danger of extinction due to random demographic factors and inbreeding. We used least-cost modeling as a systematic approach to incorporate satellite imagery and data on ecological and behavioral parameters of the giant panda collected during more than 10 years of field research to design a conservation landscape for giant pandas in the Minshan Mountains. We identified 8 core habitats and 4 potential linkages that would link core habitats CH3, CH4, and CH5 with core habitats CH6, CH7, and CH8. Establishing and integrating the identified habitats with existing reserves would create an efficient reserve network for giant panda conservation. The core habitats had an average density of 4.9 pandas/100 km(2) and contained approximately 76.6% of the giant panda population. About 45% of the core habitat (3245.4 km(2)) existed outside the current nature reserves network. Total estimated core habitat decreased between 30.4 and 44.5% with the addition of residential areas and road networks factored into the model. A conservation area for giant panda in the Minshan Mountains should aim to ensure habitat retention and connectivity, improve dispersal potential of corridors, and maintain the evolutionary potential of giant pandas in the face of future environmental changes.

Genome-wide identification, phylogeny, and expression analysis of the SWEET gene family in tomato.

The SWEET (Sugars Will Eventually Be Exported Transporters) gene family encodes membrane-embedded sugar transporters containing seven transmembrane helices harboring two MtN3 and saliva domain. SWEETs play important roles in diverse biological processes, including plant growth, development, and response to environmental stimuli. Here, we conducted an exhaustive search of the tomato genome, leading to the identification of 29 SWEET genes. We analyzed the structures, conserved domains, and phylogenetic relationships of these protein-coding genes in detail. We also analyzed the transcript levels of SWEET genes in various tissues, organs, and developmental stages to obtain information about their functions. Furthermore, we investigated the expression patterns of the SWEET genes in response to exogenous sugar and adverse environmental stress (high and low temperatures). Some family members exhibited tissue-specific expression, whereas others were more ubiquitously expressed. Numerous stress-responsive candidate genes were obtained. The results of this study provide insights into the characteristics of the SWEET genes in tomato and may serve as a basis for further functional studies of such genes.

Temporal variations in soil moisture for three typical vegetation types in inner Mongolia, northern China.

Drought and shortages of soil water are becoming extremely severe due to global climate change. A better understanding of the relationship between vegetation type and soil-moisture conditions is crucial for conserving soil water in forests and for maintaining a favorable hydrological balance in semiarid areas, such as the Saihanwula National Nature Reserve in Inner Mongolia, China. We investigated the temporal dynamics of soil moisture in this reserve to a depth of 40 cm under three types of vegetation during a period of rainwater recharge. Rainwater from most rainfalls recharged the soil water poorly below 40 cm, and the rainfall threshold for increasing the moisture content of surface soil for the three vegetations was in the order: artificial Larix spp. (AL) > Quercus mongolica (QM) > unused grassland (UG). QM had the highest mean soil moisture content (21.13%) during the monitoring period, followed by UG (16.52%) and AL (14.55%); and the lowest coefficient of variation (CV 9.6-12.5%), followed by UG (CV 10.9-18.7%) and AL (CV 13.9-21.0%). QM soil had a higher nutrient content and higher soil porosities, which were likely responsible for the higher ability of this cover to retain soil water. The relatively smaller QM trees were able to maintain soil moisture better in the study area.

[Ecosystem service and economic valuation in the upper reaches of Xin' an River, Anhui, China for mitigating phosphorus nonpoint source pollution].

A model of phosphorus purification in a watershed was established based on the export coefficient and purification index of phosphorus in different types of land cover. The model was employed to simulate the economic value of the ecosystem service with the expected water quality standard and marginal cost of pollutant purification of the upper reaches of Xin' an River of Anhui, China. The results revealed that from 2000 to 2010, some farmland outside the Tunxi, Jixi, Shexian, Yixian and Xiuning was converted to built-up land. The total amount of phosphorus exported to the upper Xin' an River decreased a little, and the main source of phosphorus pollution was farmland and built-up land. More than half of the exported phosphorus was efficiently purified by different types of land cover via flow accumulation. The pattern of purification and export of highly concentrated phosphorus showed the same trend which occurred in the northern part of the watershed including the Yangzhi River, Fengle River and Hengjiang River. Forestland and grassland did not efficiently purify phosphorus in the watershed owing to the irrational distribution of existing land cover. The total service value was 3.80 and 3.31 million Yuan in 2000 and 2010, respectively.

Nanoporous polymer--clay hybrid membranes for gas separation.

Nanohybrid organo-inorgano clay mineral-polydimethylsiloxane (PDMS) membranes were prepared by the reaction of pure and/or modified natural clay minerals (Sepiolite and montmorillonite) with PDMS in hexane, followed by evaporation of the solvent at 70 degrees C. The membranes were characterized by means of XRD, SEM, ATD-TG and solid state (29)Si magic angle spinning (MAS) and cross-polarization (CP) CP/MAS NMR. The morphology of the membranes depends on the content loading of clay mineral. For low content, the membrane composition is homogeneous, with well dispersed nanoparticles of clay into the polymer matrix, whereas for higher clay content, the membranes are constituted also of a mixture of well dispersed nanoparticles into the polymer, but in the presence of agglomerations of small clay particles. Quantitative (29)Si MAS NMR demonstrated a strong correlation between the clay content of the membrane and the average length of the PDMS chain, indicating that the nanohybrid material is made of clay particles covalently linked to the PDMS structure. This is particularly the case for Sepiolite with has a high density of Q(2) silanol sites. The separation performances of the prepared membranes were tested for CO(2)/CH(4) and O(2)/N(2) mixtures. The observed separation factors showed an increase of the selectivity in the case of CO(2)/CH(4) in comparison with membranes made from PDMS alone under the same conditions.