Unidirectional crosstalk between Bcl-xL and Bcl-2 enhances the angiogenic phenotype of endothelial cells

Expression of Bcl-x(L) correlates with the clinical outcomes of patients with cancer. While the role of Bcl-2 in angiogenesis is becoming increasingly evident, the function of Bcl-x(L) in angiogenesis is unclear. Here, we showed that epidermal growth factor (EGF) induces in vitro capillary sprouting and Bcl-x(L) expression in primary endothelial cells. Bcl-x(L)-transduced human dermal microvascular endothelial cells (HDMEC-Bcl-x(L)), but not empty vector control cells, spontaneously organize into capillary-like sprouts. Searching for a mechanism to explain these responses, we observed that Bcl-x(L) induced expression of the pro-angiogenic chemokines CXC ligand-1 (CXCL1) and CXC ligand-8 (CXCL8), and that blockade of CXC receptor-2 (CXCR2) signaling inhibited spontaneous sprouting of HDMEC-Bcl-x(L). Bcl-x(L) led to Bcl-2 upregulation, but Bcl-2 did not upregulate Bcl-x(L), suggesting the existence of a unidirectional crosstalk from Bcl-x(L) to Bcl-2. EGF and Bcl-x(L) activate the mitogen-activated protein kinase/ERK pathway resulting in upregulation of vascular endothelial growth factor (VEGF), a known inducer of Bcl-2 in endothelial cells. Inhibition of VEGF receptor signaling in HDMEC-Bcl-x(L) prevented Bcl-2 upregulation and demonstrated the function of a VEGF-mediated autocrine loop. Bcl-2 downregulation by RNAi blocked CXCL1 and CXCL8 expression downstream of Bcl-x(L), and markedly decreased angiogenesis in vivo. We conclude that Bcl-x(L) functions as a pro-angiogenic signaling molecule controlling Bcl-2 and VEGF expression. These results emphasize a complex interplay between Bcl-2 family members beyond their classical roles in apoptosis.     

An analysis of the DOCA-salt model of hypertension in HO-1-/- mice and the Gunn rat

Heme oxygenase-1 (HO-1) is induced in the vasculature in the DOCA-salt model of hypertension in rats. Whereas the HO system and its products may exert vasodilator effects, recent studies have suggested that the HO system may predispose to hypertension. The present study examined the effects of selected components of the HO system, specifically, the HO-1 isozyme and the product bilirubin in the DOCA-salt model of systemic hypertension; the experimental approach employed mutant rodent models, namely, the HO-1(-/-) mouse and the hyperbilirubinemic Gunn rat. DOCA-salt induced HO-1 protein in the aorta in HO-1(+/+) mice and provoked a significant rise in systolic arterial pressure in HO-1(-/-) mice but not in HO-1(+/+) mice; this effect could not be ascribed to impaired urinary sodium excretion or impaired glomerular filtration rate in the DOCA-salt-treated HO-1(-/-) mice. The administration of DOCA salt to uninephrectomized rats significantly increased systolic arterial pressure in wild-type rats, an effect that was attenuated in the mutant Gunn rat; this reduction in systemic hypertension in the DOCA-salt-treated Gunn rat was not due to a greater induction of HO-1 in the vasculature or to a more avid urinary sodium excretion. DOCA-salt impaired endothelium-dependent and endothelium-independent vasorelaxation in wild-type rats but not in Gunn rats; prior exposure to bilirubin repaired the defect in endothelium-dependent vasorelaxation in aortic rings in DOCA-salt-treated rats. DOCA salt stimulated vascular production of superoxide anion in wild-type but not in Gunn rats. We suggest that HO-1 and the product bilirubin may exert a countervailing effect in the DOCA-salt model of systemic hypertension.     

Quantitation of Guggenheimella bovis and treponemes in bovine tissues related to digital dermatitis

Digital dermatitis is an inflammation of uncertain aetiology in the skin of the foot of cattle. In 2005, a novel microorganism, Guggenheimella bovis, was isolated from the advancing front of digital dermatitis lesions, suggesting a possible role in pathogenesis. In the present study, tissue samples of 20 affected cows were examined by quantitative PCR for G. bovis, treponemes and the total eubacterial load. High numbers of eubacteria and treponemes were found in most lesions, whereas only a few lesions contained Guggenheimella, and only at low concentrations. The results argue against the relevance of G. bovis in the aetiology of digital dermatitis in cattle, but are consistent with a role for treponemes.     

Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework

Species abundance distributions (SADs) follow one of ecology's oldest and most universal laws – every community shows a hollow curve or hyperbolic shape on a histogram with many rare species and just a few common species. Here, we review theoretical, empirical and statistical developments in the study of SADs. Several key points emerge. (i) Literally dozens of models have been proposed to explain the hollow curve. Unfortunately, very few models are ever rejected, primarily because few theories make any predictions beyond the hollow-curve SAD itself. (ii) Interesting work has been performed both empirically and theoretically, which goes beyond the hollow-curve prediction to provide a rich variety of information about how SADs behave. These include the study of SADs along environmental gradients and theories that integrate SADs with other biodiversity patterns. Central to this body of work is an effort to move beyond treating the SAD in isolation and to integrate the SAD into its ecological context to enable making many predictions. (iii) Moving forward will entail understanding how sampling and scale affect SADs and developing statistical tools for describing and comparing SADs. We are optimistic that SADs can provide significant insights into basic and applied ecological science.     

Geographic Tools for Eradication Programs of Insular Non-native Mammals

Non-native mammals are major drivers of ecosystem change and biodiversity loss; this is especially apparent on islands. However, techniques exist to remove non-native mammals, providing a powerful conservation tool. Conservation practitioners are now targeting larger islands for restoration. Leveraging existing and developing new techniques and technologies will prove critical to successful eradications on large islands. Using the removal of introduced goats (Capra hircus) from Santiago Island, Galápagos as a case study, we present a suite of Geographic Information System (GIS) tools that aid island conservation actions. GIS tools were incorporated into the three phases of the eradication campaign: planning, hunting, and monitoring. Further, these tools were adopted for three eradication techniques: ground-based hunting, aerial hunting by helicopter, and Judas goats. These geographic approaches provide a foundation for statistical, spatial, and economic analyses that should increase the capability and efficiency of removal campaigns. Given limited conservation funds and the dire status of many insular species, efficiently removing non-native mammals from islands is of paramount global conservation importance.     

Alternative profiling platform based on MELDI and its applicability in clinical proteomics

The presence of numerous proteomics data and their results in literature reveal the importance and influence of proteins and peptides on human cell cycle. For instance, the proteomic profiling of biological samples, such as serum, plasma or cells, and their organelles, carried out by surface-enhanced laser desorption/ionization mass spectrometry, has led to the discovery of numerous key proteins involved in many biological disease processes. However, questions still remain regarding the reproducibility, bioinformatic artifacts and cross-validations of such experimental set-ups. The authors have developed a material-based approach, termed material-enhanced laser desorption/ionization mass spectrometry (MELDI-MS), to facilitate and improve the robustness of large-scale proteomic experiments. MELDI-MS includes a fully automated protein-profiling platform, from sample preparation and analysis to data processing involving state-of-the-art methods, which can be further improved. Multiplexed protein pattern analysis, based on material morphology, physical characteristics and chemical functionalities provides a multitude of protein patterns and allows prostate cancer samples to be distinguished from non-prostate cancer samples. Furthermore, MELDI-MS enables not only the analysis of protein signatures, but also the identification of potential discriminating peaks via capillary liquid chromatography mass spectrometry. The optimized MELDI approach offers a complete proteomics platform with improved sensitivity, selectivity and short sample preparation times.     

Seasonal habitat use of three predatory fishes in a freshwater ecosystem

Hydrobiologia - To understand the spatiotemporal overlap in the habitat use of sympatric predators, we studied longitudinal activity and reservoir section and depth use of pike (Esox lucius),...     

Genome-Wide Association of Carbon and Nitrogen Metabolism in the Maize Nested Association Mapping Population

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C₄ metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.Carbon (C) and nitrogen (N) metabolism are the basis for life on Earth. The production, balance, and tradeoffs of C and N metabolism are critical to all plant growth, yield, and local adaptation (Coruzzi and Bush, 2001; Coruzzi et al., 2007). In plants, there is a critical balance between the tissues that are producing energy (sources) and those using it (sinks), as the identities and locations of these vary through time and developmental stage (Smith et al., 2004). While a great deal of research has focused on the key genes and proteins involved in these processes (Wang et al., 1993; Kim et al., 2000; Takahashi et al., 2009), relatively little is known about the natural variation within a species that fine-tunes these processes in individual plants.In addition, a key aspect of core C metabolism involves the nature of plant photosynthesis. While the majority of plants use standard C₃ photosynthetic pathways, some, including maize (Zea mays) and many other grasses, use C₄ photosynthesis to concentrate CO₂ in bundle sheath cells to avoid wasteful photorespiration (Sage, 2004). Under some conditions (such as drought or high temperatures), C₄ photosynthesis is much more efficient than C₃ photosynthesis. Since these conditions are expected to become more prevalent in the near future due to climate change, various research groups are working to convert C₃ crop species to C₄ metabolism in order to boost crop production and food security (Sage and Zhu, 2011). Beyond this, better understanding of both C₃ and C₄ metabolic pathways will aid efforts to breed crops for superior yield, N-use efficiency, and other traits important for global food production.In the last two decades, quantitative trait locus (QTL) mapping, first with linkage analysis and later with association mapping, has been used to dissect C and N metabolism in several species, including Arabidopsis (Arabidopsis thaliana; Mitchell-Olds and Pedersen, 1998; Keurentjes et al., 2008; Lisec et al., 2008; Sulpice et al., 2009), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Hirel et al., 2001; Limami et al., 2002; Zhang et al., 2006, 2010a, 2010b). These studies identified key genetic regions underlying variation in core C and N metabolism, many of which include candidate genes known to be involved in these processes.Previous studies of genetic variation for C and N metabolism are limited by the fact that they identified trait loci only through linkage mapping in artificial families or through association mapping across populations of unrelated individuals. Linkage mapping benefits from high statistical power due to many individuals sharing the same genotype at any given location, but it suffers from low resolution due to the limited number of generations (and hence recombination events) since the initial founders. Association mapping, in turn, enjoys high resolution due to the long recombination histories of natural populations but suffers from low power, since most genotypes occur in only a few individuals. In addition, many of these studies focused on C and N in artificial settings (e.g. greenhouses or growth chambers) instead of field conditions, running the risk that important genetic loci could be missed if the conditions do not include important (and potentially unknown) natural environmental variables.To address these issues and improve our understanding of C and N metabolism in maize, we used a massive and diverse germplasm resource, the maize nested association mapping (NAM) population (Buckler et al., 2009; McMullen et al., 2009), to evaluate genetic variation underlying the accumulation of 12 targeted metabolites in maize leaf tissue under field conditions. This population was formed by mating 25 diverse maize lines to the reference line, B73, and creating a 200-member biparental family from each of these crosses. The entire 5,000-member NAM population thus combines the strengths of both linkage and association mapping (McMullen et al., 2009), and it has been used to identify QTLs for important traits such as flowering time (Buckler et al., 2009), disease resistance (Kump et al., 2011; Poland et al., 2011), and plant architecture (Tian et al., 2011; Peiffer et al., 2013). Most importantly, this combination of power and resolution frequently resolves associations down to the single-gene level, even when using field-based data.The metabolites we profiled are key indicators of photosynthesis, respiration, glycolysis, and protein and sugar metabolism in the plant (Sulpice et al., 2009). By taking advantage of a robotized metabolic phenotyping platform (Gibon et al., 2004), we performed more than 100,000 assays across 12,000 samples, with two independent samples per experimental plot. Raw data and the best linear unbiased predictors (BLUPs) of these data were included as part of a study of general functional variation in maize (Wallace et al., 2014), but, to our knowledge, this is the first in-depth analysis of these metabolic data. We find strong correlations among several of the metabolites, and we also find extensive pleiotropy among the different traits. Many of the top QTLs are also near or within candidate genes relating to C and N metabolism, thus identifying targets for future breeding and selection. These results provide a powerful resource for those working with core C and N metabolism in plants and for improving maize performance in particular.