Quantitative Proteomics of Chromochloris zofingiensis Reveals the Key Proteins Involved in Cell Growth and Bioactive Compound Biosynthesis

Glucose metabolism regulates cell growth and affects astaxanthin accumulation in the green algae Chromochloris zofingiensis. Hub gene functioning in this bioactive compound has been illustrated at the genome, transcriptome and metabolome level, but is rather limited from a proteome aspect. Microalgal cell produce an enhanced biomass (8-fold higher) but decreased lipid and astaxanthin content (~20% less) in the glucose condition compared to the control. Here, we investigate the proteomic response of C. zofingiensis grown with and without glucose using an LC-MS/MS-based Tandem Mass Tag (TMT) approach. The proteomic analysis demonstrated that glucose supplementation triggers the upregulation of 105 proteins and downregulation of 151 proteins. Thus, the carbon and energy flux might flow to cell growth, which increased the associated protein abundance, including DNA polymerase, translation initiation factor, 26S proteasome regulatory subunits, and the marker enzyme of the TCA cycle ribosomal protein. Moreover, the glucose supplement triggered the downregulation of proteins mainly involved in photosynthesis, chloroplasts, valine, leucine and isoleucine biosynthesis, 2-oxocarboxylic acid metabolism, and pantothenate and CoA biosynthesis pathways. This proteomic analysis is likely to provide new insights into algal growth and lipid or astaxanthin accumulation upon glucose supplementation, providing a foundation for further development of C. zofingiensis as oleaginous microalga for bioengineering applications

Stability and Mechanical Properties of w1-X Mox b4.2 (X=0.0-1.0) From First Principles

Heavy transition-metal tetraborides (e.g., tungsten tetraboride, molybdenum tetraboride, and molybdenum-doped tungsten tetraboride) exhibit superior mechanical properties, but solving their complex crystal structures has been a long-standing challenge. Recent experimental x-ray and neutron diffraction measurements combined with first-principles structural searches have identified a complex structure model for tungsten tetraboride that contains a boron trimer as an unusual structural unit with a stoichiometry of 1:4.2. In this paper, we expand the study to binary MoB4.2 and ternary W1-xMoxB4.2 (x=0.0-1.0) compounds to assess their thermodynamic stability and mechanical properties using a tailor-designed crystal structure search method in conjunction with first-principles energetic calculations. Our results reveal that an orthorhombic MoB4.2 structure in Cmcm symmetry matches well the experimental x-ray diffraction patterns. For the synthesized ternary Mo-doped tungsten tetraborides, a series of W1-xMoxB4.2 structures are theoretically designed using a random substitution approach by replacing the W to Mo atoms in the Cmcm binary crystal structure. This approach leads to the discovery of several W1-xMoxB4.2 structures that are energetically superior and stable against decomposition into binary WB4.2 and MoB4.2. The structural and mechanical properties of these low-energy W1-xMoxB4.2 structures largely follow the Vegard\u27s law. Under changing composition parameter x=0.0-1.0, the superior mechanical properties of W1-xMoxB4.2 stay in a narrow range. This unusual phenomenon stems from the strong covalent network with directional bonding configurations formed by boron atoms to resist elastic deformation. The findings offer insights into the fundamental structural and physical properties of ternary W1-xMoxB4.2 in relation to the binary WB4.2/MoB4.2 compounds, which open a promising avenue for further rational optimization of the functional performance of transition-metal borides that can be synthesized under favorable experimental conditions for wide applications

Geographic and Climatic Attributions of Autumn Land Surface Phenology Spatial Patterns in the Temperate Deciduous Broadleaf Forest of China

Autumn vegetation phenology plays a critical role in identifying the end of the growing season and its response to climate change. Using the six vegetation indices retrieved from moderate resolution imaging spectroradiometer data, we extracted an end date of the growing season (EOS) in the temperate deciduous broadleaf forest (TDBF) area of China. Then, we validated EOS with the ground-observed leaf fall date (LF) of dominant tree species at 27 sites and selected the best vegetation index. Moreover, we analyzed the spatial pattern of EOS based on the best vegetation index and its dependency on geo-location indicators and seasonal temperature/precipitation. Results show that the plant senescence reflectance index-based EOS agrees most closely with LF. Multi-year averaged EOS display latitudinal, longitudinal and altitudinal gradients. The altitudinal sensitivity of EOS became weaker from 2000 to 2012. Temperature-based spatial phenology modeling indicated that a 1 K spatial shift in seasonal mean temperature can cause a spatial shift of 2.4–3.6 days in EOS. The models explain between 54% and 73% of the variance in the EOS timing. However, the influence of seasonal precipitation on spatial variations of EOS was much weaker. Thus, spatial temperature variation controls the spatial patterns of EOS in TDBF of China, and future temperature increase might lead to more uniform autumn phenology across elevations

Novel sulfamoylamino-containing cephalosporin derivatives, and their in vitro antibacterial properties

Purpose: To prepare and develop new antibacterial agents with novel molecular structures. Method: A series of novel sulfamoylamino-containing cephalosporin derivatives were synthesized. The in vitro antibacterial effects of the derivatives against Gram-positive bacteria (S. aureus, S. pneumonia and S. epidermidis), and Gram-negative bacteria (E. coli, P. aeruginosa, and K. pneumonia) were investigated. Results: Compounds 13a and 13b exhibited excellent antibacterial effects against all the Gram-positive and Gram-negative bacteria tested, when compared with other cephalosporin derivatives. Conclusion: Of these new cephalosporin derivatives, compounds 13a and 13b show the most potent antibacterial activity and would need to be further investigated

In Vitro Study on Apoptosis Induced by Strontium-89 in Human Breast Carcinoma Cell Line

Many radiopharmaceuticals used for medical diagnosis and therapy are beta emitters; however, the mechanism of the cell death caused by beta-irradiation is not well understood. The objective of this study was to investigate the apoptosis of human breast carcinoma MCF-7 cell lines induced by Strontium-89 (89Sr) and its regulation and control mechanism. High-metastatic Breast Carcinoma MCF-7 cells were cultured in vitro using 89Sr with different radioactive concentration. The inhibition rate of cell proliferation was measured by MTT color matching method. The cell cycle retardation, apoptosis conditions, mitochondrion transmembrane potential difference and Fas expression were tested and analyzed. The genes P53 and bcl-2 expressions was also analyzed using immunity histochemical analysis. After being induced by 89Sr with various of radioactive concentration, it was found that the inhibition of cell proliferation of MCF-7 cells was obviously, the retardation of cell cycle occurred mainly in G2-M. It was also found that the obvious apoptosis occurred after being induced by 89Sr, the highest apoptosis rate reached 46.28%. The expressions of Fas acceptor and P53 gene increased, while bcl-2 gene expression decreasesd. These findings demonstrate that in the ranges of a certain radioactive concentration, the inhibition rate of MCF-7 cell proliferation and retardation of cell cycle had positive correlation with the concentration of 89Sr. And the mitochondrion transmembrane potential decrease would induce the apoptosis of MCF-7 cell notably, which were controlled by P53 and bcl-2 genes, involved with the Fas acceptor

Sustainable protected cropping : a case study of seasonal impacts on greenhouse energy consumption during capsicum production

Sustainable food production in protected cropping is increasing rapidly in response to global climate change and population growth. However, there are significant knowledge gaps regarding energy consumption while achieving optimum environmental conditions for greenhouse crop production. A capsicum crop cultivated in a high-tech greenhouse facility in Australia was analysed in terms of relationships between key environmental variables and the comparative analysis of energy consumption during different seasons. We showed that daily energy consumption varied due to the seasonal nature of the external environment and maintenance of optimal growing temperatures. Total power consumption reported throughout the entire crop cycle for heating (gas hot water system) and cooling (pad and fan) was 12,503 and 5183 kWh, respectively; hence, heating consumed ca. 70% of the total energy requirement over the 8-month growing period (early spring to late autumn) in the greenhouse facility. Regressions of daily energy consumption within each season, designated either predominantly for heating or cooling, indicated that energy consumption was 14.62 kWh per 1 °C heating and 2.23 kWh per 1 °C cooling. Therefore, changing the planting date to late spring is likely to significantly reduce heating energy costs for greenhouse capsicum growers in Australia. The findings will provide useful guidelines to maximise the greenhouse production of capsicum with better economic return by taking into consideration the potential optimal energy saving strategy during different external environment conditions and seasons

Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast

Drought is part of natural climate variability and ranks the first natural disaster in the world. Drought forecasting plays an important role in mitigating impacts on agriculture and water resources. In this study, a drought forecast model based on the random forest method is proposed to predict the time series of monthly standardized precipitation index SPI . We demonstrate model application by four stations in the Haihe river basin, China. The random-forest-RF-based forecast model has consistently shown better predictive skills than the ARIMA model for both long and short drought forecasting. The confidence intervals derived from the proposed model generally have good coverage, but still tend to be conservative to predict some extreme drought events