Characterization of the heme pocket structure and ligand binding kinetics of non-symbiotic hemoglobins from the model legume lotus japonicus

Plant hemoglobins (Hbs) are found in nodules of legumes and actinorhizal plants but also in non-symbiotic organs of monocots and dicots. Non-symbiotic Hbs (nsHbs) have been classified into two phylogenetic groups. Class 1 nsHbs show an extremely high O2 affinity and are induced by hypoxia and nitric oxide (NO), whereas class 2 nsHbs have moderate O2 affinity and are induced by cold and cytokinins. The functions of nsHbs are still unclear, but some of them rely on the capacity of hemes to bind diatomic ligands and catalyze the NO dioxygenase (NOD) reaction (oxyferrous Hb + NO ? ferric Hb + nitrate). Moreover, NO may nitrosylate Cys residues of proteins. It is therefore important to determine the ligand binding properties of the hemes and the role of Cys residues. Here, we have addressed these issues with the two class 1 nsHbs (LjGlb1-1 and LjGlb1-2) and the single class 2 nsHb (LjGlb2) of Lotus japonicus, which is a model legume used to facilitate the transfer of genetic and biochemical information into crops. We have employed carbon monoxide (CO) as a model ligand and resonance Raman, laser flash photolysis, and stopped-flow spectroscopies to unveil major differences in the heme environments and ligand binding kinetics of the three proteins, which suggest non-redundant functions. In the deoxyferrous state, LjGlb1-1 is partially hexacoordinate, whereas LjGlb1-2 shows complete hexacoordination (behaving like class 2 nsHbs) and LjGlb2 is mostly pentacoordinate (unlike other class 2 nsHbs). LjGlb1-1 binds CO very strongly by stabilizing it through hydrogen bonding, but LjGlb1-2 and LjGlb2 show lower CO stabilization. The changes in CO stabilization would explain the different affinities of the three proteins for gaseous ligands. These affinities are determined by the dissociation rates and follow the order LjGlb1-1 > LjGlb1-2 > LjGlb2. Mutations LjGlb1-1 C78S and LjGlb1-2 C79S caused important alterations in protein dynamics and stability, indicating a structural role of those Cys residues, whereas mutation LjGlb1-1 C8S had a smaller effect. The three proteins and their mutant derivatives exhibited similarly high rates of NO consumption, which were due to NOD activity of the hemes and not to nitrosylation of Cys residues

Control of style-of-faulting on spatial pattern of earthquake-triggered landslides

Predictive mapping of susceptibility to earthquake-triggered landslides (ETLs) commonly uses distance to fault as spatial predictor, regardless of style-of-faulting. Here, we examined the hypothesis that the spatial pattern of ETLs is influenced by style-of-faulting based on distance distribution analysis and Fry analysis. The Yingxiu–Beichuan fault (YBF) in China and a huge number of landslides that ruptured and occurred, respectively, during the 2008 Wenchuan earthquake permitted this study because the style-of-faulting along the YBF varied from its southern to northern parts (i.e. mainly thrust-slip in the southern part, oblique-slip in the central part and mainly strike-slip in the northern part). On the YBF hanging-wall, ETLs at 4.4–4.7 and 10.3–11.5 km from the YBF are likely associated with strike- and thrust-slips, respectively. On the southern and central parts of the hanging-wall, ETLs at 7.5–8 km from the YBF are likely associated with oblique-slips. These findings indicate that the spatial pattern of ETLs is influenced by style-of-faulting. Based on knowledge about the style-of-faulting and by using evidential belief functions to create a predictor map based on proximity to faults, we obtained higher landslide prediction accuracy than by using unclassified faults. When distance from unclassified parts of the YBF is used as predictor, the prediction accuracy is 80%; when distance from parts of the YBF, classified according to style-of-faulting, is used as predictor, the prediction accuracy is 93%. Therefore, mapping and classification of faults and proper spatial representation of fault control on occurrence of ETLs are important in predictive mapping of susceptibility to ETLs

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts

Modelling the initiation and runout of rainfall induced debris flows in the Cardoso basin (Apuan Alps, Italy)

A GIS based mass flow model was used to simulate debris flow triggering and evolution: a saturated/unsaturated soil water model was used to simulate the distribution of soil water and the generation of excess pore pressure leading to slope instability during a rainfall event. The model is able to detect potential instability due both to the development of a perched watertable at the colluvium/bedrock interface, and to the development of a saturated top layer because of the direct infiltration of rainfall during an intense event. Stability conditions are evaluated at the bottom of the saturated zones, i.e. at the wetting front and at the soil-rock contact. The safety factor, ratio of stabilizing forces or shear strength to destabilizing forces or shear stress, is calculated assuming the infinite slope model. The geotechnical parameters c' and phi can be introduced with uncertainty (mean value and variance); confidence intervals are calculated using a first order second moment (FOSM) method. This also allows to the estimate the failure probabilities. A flow routing model is then used to simulate the spreading and deposition of the mud/debris mixture on the hillslopes: once a landslide has been predicted, the location and released volume are used as inputs to a second model to simulate the spreading of the debris on the hillslope. The dynamic model has been built with PCRaster Software, based on the Bingham rheological expression. This model is applied to simulate the debris flow triggering and evolution in the Cardoso Torrent basin (Upper Versilia, NW Tuscany - Italy), where an extremely heavy rainstorm (about 500 mm within 12 hours) hit some restricted areas on June 19th, 1996, involving a few basins of the Versilia and Garfagnana areas and inducing various effects on the slopes (soil slips and debris flows). A large number of data is available thanks to detailed surveys, which provided the characterization of the main factors (pluviometric, hydrogeological, geological, geomorphological and geotechnical) contributing to the landslide triggering. In particular, some factors were recurrent in the landslide sites: bedrock features (impermeable bedrock, discontinuity dipping downslope), slope morphology (hollow shape), geotechnical characteristics (fine, scarcely permeable cover material)