Damages Caused by Irradiation in the Presence of NaCl in Macromolecular Components of E. coli

Damages in macromolecular components and in their functions of E. coli produced by gamma irradiation in the presence of higher concentration of NaCl were determined with reference to the basic mechanism for NaCl radiosensitization. As the results, inhibitions of DNA repair, of DNA degradation, of macromolecular syntheses and of RNA species formation were found in DNA repair proficient strains. The number of radiation-induced DNA-strand breaks was not increased by the presence of 1 m NaCl during irradiation. It was suggested that inhibition of DNA repair may be of primary importance among these lesions for NaCl radiosensitization.     

High‐resolution prediction of leaf onset date in Japan in the 21st century under the IPCC A1B scenario

Reports indicate that leaf onset (leaf flush) of deciduous trees in cool‐temperate ecosystems is occurring earlier in the spring in response to global warming. In this study, we created two types of phenology models, one driven only by warmth (spring warming [SW] model) and another driven by both warmth and winter chilling (parallel chill [PC] model), to predict such phenomena in the Japanese Islands at high spatial resolution (500 m). We calibrated these models using leaf onset dates derived from satellite data (Terra/MODIS) and in situ temperature data derived from a dense network of ground stations Automated Meteorological Data Acquisition System. We ran the model using future climate predictions created by the Japanese Meteorological Agency's MRI‐AGCM3.1S model. In comparison to the first decade of the 2000s, our results predict that the date of leaf onset in the 2030s will advance by an average of 12 days under the SW model and 7 days under the PC model throughout the study area. The date of onset in the 2090s will advance by 26 days under the SW model and by 15 days under the PC model. The greatest impact will occur on Hokkaido (the northernmost island) and in the central mountains.     

Multispectral image analysis for algal biomass quantification

This article reports a novel multispectral image processing technique for rapid, noninvasive quantification of biomass concentration in attached and suspended algae cultures. Monitoring the biomass concentration is critical for efficient production of biofuel feedstocks, food supplements, and bioactive chemicals. Particularly, noninvasive and rapid detection techniques can significantly aid in providing delay‐free process control feedback in large‐scale cultivation platforms. In this technique, three‐band spectral images of Anabaena variabilis cultures were acquired and separated into their red, green, and blue components. A correlation between the magnitude of the green component and the areal biomass concentration was generated. The correlation predicted the biomass concentrations of independently prepared attached and suspended cultures with errors of 7 and 15%, respectively, and the effect of varying lighting conditions and background color were investigated. This method can provide necessary feedback for dilution and harvesting strategies to maximize photosynthetic conversion efficiency in large‐scale operation. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:808–816, 2013     

Functional diversity of potassium channel voltage-sensing domains

Voltage-gated potassium channels or Kv's are membrane proteins with fundamental physiological roles. They are composed of 2 main functional protein domains, the pore domain, which regulates ion permeation, and the voltage-sensing domain, which is in charge of sensing voltage and undergoing a conformational change that is later transduced into pore opening. The voltage-sensing domain or VSD is a highly conserved structural motif found in all voltage-gated ion channels and can also exist as an independent feature, giving rise to voltage sensitive enzymes and also sustaining proton fluxes in proton-permeable channels. In spite of the structural conservation of VSDs in potassium channels, there are several differences in the details of VSD function found across variants of Kvs. These differences are mainly reflected in variations in the electrostatic energy needed to open different potassium channels. In turn, the differences in detailed VSD functioning among voltage-gated potassium channels might have physiological consequences that have not been explored and which might reflect evolutionary adaptations to the different roles played by Kv channels in cell physiology.     

Bacterial biofilms and quorum sensing: fidelity in bioremediation technology

Increased contamination of the environment with toxic pollutants has paved the way for efficient strategies which can be implemented for environmental restoration. The major problem with conventional methods used for cleaning of pollutants is inefficiency and high economic costs. Bioremediation is a growing technology having advanced potential of cleaning pollutants. Biofilm formed by various micro-organisms potentially provide a suitable microenvironment for efficient bioremediation processes. High cell density and stress resistance properties of the biofilm environment provide opportunities for efficient metabolism of number of hydrophobic and toxic compounds. Bacterial biofilm formation is often regulated by quorum sensing (QS) which is a population density-based cell–cell communication process via signaling molecules. Numerous signaling molecules such as acyl homoserine lactones, peptides, autoinducer-2, diffusion signaling factors, and α-hydroxyketones have been studied in bacteria. Genetic alteration of QS machinery can be useful to modulate vital characters valuable for environmental applications such as biofilm formation, biosurfactant production, exopolysaccharide synthesis, horizontal gene transfer, catabolic gene expression, motility, and chemotaxis. These qualities are imperative for bacteria during degradation or detoxification of any pollutant. QS signals can be used for the fabrication of engineered biofilms with enhanced degradation kinetics. This review discusses the connection between QS and biofilm formation by bacteria in relation to bioremediation technology.     

Comparative regional-scale soil salinity assessment with near-ground apparent electrical conductivity and remote sensing canopy reflectance

Soil salinity is recognized worldwide as a major threat to agriculture, particularly in arid and semi-arid regions. Producers and decision makers need updated and accurate maps of salinity in agronomically and environmentally relevant ranges (i.e., <20 dS m⁻¹, when salinity is measured as electrical conductivity of the saturation extract, EC_e). State-of-the-art approaches for creating accurate EC_e maps beyond field scale (i.e., 1 km²) include: (i) Analysis Of Covariance (ANOCOVA) of near-ground measurements of apparent soil electrical conductivity (EC_a) and (ii) regression modeling of multi-year remote sensing canopy reflectance and other co-variates (e.g., crop type, annual rainfall). This study presents a comparison of the two approaches to establish their viability and utility. The approaches were tested using 22 fields (total 542 ha) located in California’s western San Joaquin Valley. In 2013 EC_a-directed soil sampling resulted in the collection of 267 soil samples across the 22 fields, which were analyzed for EC_e, ranging from 0 to 38.6 dS m⁻¹. The ANOCOVA EC_a-EC_e model returned a coefficient of determination (R²) of 0.87 and root mean square prediction error (RMSPE) of 3.05 dS m⁻¹. For the remote sensing approach seven years (2007–2013) of Landsat 7 reflectance were considered. The remote sensing salinity model had R² = 0.73 and RMSPE = 3.63 dS m⁻¹. The robustness of the models was tested with a leave-one-field-out (lofo) cross-validation to assure maximum independence between training and validation datasets. For the ANOCOVA model, lofo cross-validation provided a range of scenarios in terms of RMSPE. The worst, median, and best fit scenarios provided global cross-validation R² of 0.52, 0.80, and 0.81, respectively. The lofo cross-validation for the remote sensing approach returned a R² of 0.65. The ANOCOVA approach performs particularly well at EC_e values <10 dS m⁻¹, but requires extensive field work. Field work is reduced considerably with the remote sensing approach, but due to the larger errors at low EC_e values, the methodology is less suitable for crop selection, and other practices that require accurate knowledge of salinity variation within a field, making it more useful for assessing trends in salinity across a regional scale. The two models proved to be viable solutions at large spatial scales, with the ANOCOVA approach more appropriate for multiple-field to landscape scales (1–10 km²) and the remote sensing approach best for landscape to regional scales (>10 km²).