Establishment of a Transgenic Mouse Model Specifically Expressing Human Serum Amyloid A in Adipose Tissue

Obesity and obesity co-morbidities are associated with a low grade inflammation and elevated serum levels of acute phase proteins, including serum amyloid A (SAA). In the non-acute phase in humans, adipocytes are major producers of SAA but the function of adipocyte-derived SAA is unknown. To clarify the role of adipocyte-derived SAA, a transgenic mouse model expressing human SAA1 (hSAA) in adipocytes was established. hSAA expression was analysed using real-time PCR analysis. Male animals were challenged with a high fat (HF) diet. Plasma samples were subjected to fast protein liquid chromatography (FPLC) separation. hSAA, cholesterol and triglyceride content were measured in plasma and in FPLC fractions. Real-time PCR analysis confirmed an adipose tissue-specific hSAA gene expression. Moreover, the hSAA gene expression was not influenced by HF diet. However, hSAA plasma levels in HF fed animals (37.7±4.0 µg/mL, n = 7) were increased compared to those in normal chow fed animals (4.8±0.5 µg/mL, n = 10; p<0.001), and plasma levels in the two groups were in the same ranges as in obese and lean human subjects, respectively. In FPLC separated plasma samples, the concentration of hSAA peaked in high-density lipoprotein (HDL) containing fractions. In addition, cholesterol distribution over the different lipoprotein subfractions as assessed by FPLC analysis was similar within the two experimental groups. The established transgenic mouse model demonstrates that adipose tissue produced hSAA enters the circulation, resulting in elevated plasma levels of hSAA. This new model will enable further studies of metabolic effects of adipose tissue-derived SAA

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification

Connexin channels and phospholipids: association and modulation

<p>Abstract</p> <p>Background</p> <p>For membrane proteins, lipids provide a structural framework and means to modulate function. Paired connexin hemichannels form the intercellular channels that compose gap junction plaques while unpaired hemichannels have regulated functions in non-junctional plasma membrane. The importance of interactions between connexin channels and phospholipids is poorly understood.</p> <p>Results</p> <p>Endogenous phospholipids most tightly associated with purified connexin26 or connexin32 hemichannels or with junctional plaques in cell membranes, those likely to have structural and/or modulatory effects, were identified by tandem electrospray ionization-mass spectrometry using class-specific interpretative methods. Phospholipids were characterized by headgroup class, charge, glycerol-alkyl chain linkage and by acyl chain length and saturation. The results indicate that specific endogenous phospholipids are uniquely associated with either connexin26 or connexin32 channels, and some phospholipids are associated with both. Functional effects of the major phospholipid classes on connexin channel activity were assessed by molecular permeability of hemichannels reconstituted into liposomes. Changes to phospholipid composition(s) of the liposome membrane altered the activity of connexin channels in a manner reflecting changes to the surface charge/potential of the membrane and, secondarily, to cholesterol content. Together, the data show that connexin26 and connexin32 channels have a preference for tight association with unique anionic phospholipids, and that these, independent of headgroup, have a positive effect on the activity of both connexin26 and connexin32 channels. Additionally, the data suggest that the likely in vivo phospholipid modulators of connexin channel structure-function that are connexin isoform-specific are found in the cytoplasmic leaflet. A modulatory role for phospholipids that promote negative curvature is also inferred.</p> <p>Conclusion</p> <p>This study is the first to identify (endogenous) phospholipids that tightly associate with connexin channels. The finding that specific phospholipids are associated with different connexin isoforms suggests connexin-specific regulatory and/or structural interactions with lipid membranes. The results are interpreted in light of connexin channel function and cell biology, as informed by current knowledge of lipid-protein interactions and membrane biophysics. The intimate involvement of distinct phospholipids with different connexins contributes to channel structure and/or function, as well as plaque integrity, and to modulation of connexin channels by lipophilic agents.</p

Diel and seasonal patterns in activity and home range size of green turtles on their foraging grounds revealed by extended Fastloc-GPS tracking

An animal’s home range is driven by a range of factors including top-down (predation risk) and bottom-up (habitat quality) processes, which often vary in both space and time. We assessed the role of these processes in driving spatiotemporal patterns in the home range of the green turtle (Chelonia mydas), an important marine megaherbivore. We satellite tracked adult green turtles using Fastloc-GPS telemetry in the Chagos Archipelago and tracked their fine-scale movement in different foraging areas in the Indian Ocean. Using this extensive data set (5,081 locations over 1,675 tracking days for 8 individuals) we showed that green turtles exhibit both diel and seasonal patterns in activity and home range size. At night, turtles had smaller home ranges and lower activity levels, suggesting they were resting. In the daytime, home ranges were larger and activity levels higher, indicating that turtles were actively feeding. The transit distance between diurnal and nocturnal sites varied considerably between individuals. Further, some turtles changed resting and foraging sites seasonally. These structured movements indicate that turtles had a good understanding of their foraging grounds in regards to suitable areas for foraging and sheltered areas for resting. The clear diel patterns and the restricted size of nocturnal sites could be caused by spatiotemporal variations in predation risk, although other factors (e.g. depth, tides and currents) could also be important. The diurnal and seasonal pattern in home range sizes could similarly be driven by spatiotemporal variations in habitat (e.g. seagrass or algae) quality, although this could not be confirmed

Generic ecological impact assessments of alien species in Norway: a semi-quantitative set of criteria

The ecological impact assessment scheme that has been developed to classify alien species in Norway is presented. The underlying set of criteria enables a generic and semi-quantitative impact assessment of alien species. The criteria produce a classification of alien species that is testable, transparent and easily adjustable to novel evidence or environmental change. This gives a high scientific and political legitimacy to the end product and enables an effective prioritization of management efforts, while at the same time paying attention to the precautionary principle. The criteria chosen are applicable to all species regardless of taxonomic position. This makes the assessment scheme comparable to the Red List criteria used to classify threatened species. The impact of alien species is expressed along two independent axes, one measuring invasion potential, the other ecological effects. Using this two-dimensional approach, the categorization captures the ecological impact of alien species, which is the product rather than the sum of spread and effect. Invasion potential is assessed using three criteria, including expected population lifetime and expansion rate. Ecological effects are evaluated using six criteria, including interactions with native species, changes in landscape types, and the potential to transmit genes or parasites. Effects on threatened species or landscape types receive greater weightings