102 research outputs found
Interaction of hemojuvelin with neogenin results in iron accumulation in human embryonic kidney 293 cells
Type 2 hereditary hemochromatosis (HH) or juvenile hemochromatosis is an early onset, genetically heterogeneous, autosomal recessive disorder of iron overload. Type 2A HH is caused by mutations in the recently cloned hemojuvelin gene (HJV; also called HFE2) (Papanikolaou, G., Samuels, M. E., Ludwig, E. H., MacDonald, M. L., Franchini, P. L., Dube, M. P., Andres, L., MacFarlane, J., Sakellaropoulos, N., Politou, M., Nemeth, E., Thompson, J., Risler, J. K., Zaborowska, C., Babakaiff, R., Radomski, C. C., Pape, T. D., Davidas, O., Christakis, J., Brissot, P., Lockitch, G., Ganz, T., Hayden, M. R., and Goldberg, Y. P. (2004) Nat. Genet. 36, 77â82), whereas Type 2B HH is caused by mutations in hepcidin. HJV is highly expressed in both skeletal muscle and liver. Mutations in HJV are implicated in the majority of diagnosed juvenile hemochromatosis patients. In this study, we stably transfected HJV cDNA into human embryonic kidney 293 cells and characterized the processing of HJV and its effect on iron homeostasis. Our results indicate that HJV is a glycosylphosphatidylinositol-linked protein and undergoes a partial autocatalytic cleavage during its intracellular processing. HJV co-immunoprecipitated with neogenin, a receptor involved in a variety of cellular signaling processes. It did not interact with the closely related receptor DCC (deleted in Colon Cancer). In addition, the HJV G320V mutant implicated in Type 2A HH did not co-immunoprecipitate with neogenin. Immunoblot analysis of ferritin levels and transferrin-55Fe accumulation studies indicated that the HJV-induced increase in intracellular iron levels in human embryonic kidney 293 cells is dependent on the presence of neogenin in the cells, thus linking these two proteins to intracellular iron homeostasis
Landscape-scale forest loss as a catalyst of population and biodiversity change
The BioTIME database was supported by ERC AdG BioTIME 250189 and ERC PoC BioCHANGE 727440. We thank the ERC projects BioTIME and BioCHANGE for supporting the initial data synthesis work that led to this study, and the Leverhulme Centre for Anthropocene Biodiversity for continued funding of the database. Also supported by a Carnegie-Caledonian PhD Scholarship and NERC doctoral training partnership grant NE/L002558/1 (G.N.D.), a Leverhulme Fellowship and the Leverhulme Centre for Anthropocene Biodiversity (M.D.), Leverhulme Project Grant RPG-2019-402 (A.E.M. and M.D.), and the German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (funded by the German Research Foundation; FZT 118, S.A.B.).Global biodiversity assessments have highlighted land-use change as a key driver of biodiversity change. However, there is little empirical evidence of how habitat transformations such as forest loss and gain are reshaping biodiversity over time. We quantified how change in forest cover has influenced temporal shifts in populations and ecological assemblages from 6090 globally distributed time series across six taxonomic groups. We found that local-scale increases and decreases in abundance, species richness, and temporal species replacement (turnover) were intensified by as much as 48% after forest loss. Temporal lags in population- and assemblage-level shifts after forest loss extended up to 50 years and increased with speciesâ generation time. Our findings that forest loss catalyzes population and biodiversity change emphasize the complex biotic consequences of land-use change.PostprintPeer reviewe
The Molecular Mechanism for Receptor-Stimulated Iron Release from the Plasma Iron Transport Protein Transferrin
Human transferrin receptor 1 (TfR) binds iron-loaded transferrin (Fe-Tf) and transports it to acidic endosomes where iron is released in a TfR-facilitated process. Consistent with our hypothesis that TfR binding stimulates iron release from Fe-Tf at acidic pH by stabilizing the apo-Tf conformation, a TfR mutant (W641A/F760A-TfR) that binds Fe-Tf, but not apo-Tf, cannot stimulate iron release from Fe-Tf, and less iron is released from Fe-Tf inside cells expressing W641A/F760A-TfR than cells expressing wild-type TfR (wtTfR). Electron paramagnetic resonance spectroscopy shows that binding at acidic pH to wtTfR, but not W641A/F760A-TfR, changes the Tf iron binding site â„30 Ă
from the TfR W641/F760 patch. Mutation of Tf histidine residues predicted to interact with the W641/F760 patch eliminates TfR-dependent acceleration of iron release. Identification of TfR and Tf residues critical for TfR-facilitated iron release, yet distant from a Tf iron binding site, demonstrates that TfR transmits long-range conformational changes and stabilizes the conformation of apo-Tf to accelerate iron release from Fe-Tf
Patterns of domestication in the Ethiopian oil-seed crop noug (Guizotia abyssinica)
Noug (Guizotia abyssinica) is a semidomesticated oil-seed crop, which is primarily cultivated in Ethiopia. Unlike its closest crop relative, sunflower, noug has small seeds, small flowering heads, many branches, many flowering heads, and indeterminate flowering, and it shatters in the field. Here, we conducted common garden studies and microsatellite analyses of genetic variation to test whether high levels of cropâwild gene flow and/or unfavorable phenotypic correlations have hindered noug domestication. With the exception of one population, analyses of microsatellite variation failed to detect substantial recent admixture between noug and its wild progenitor. Likewise, only very weak correlations were found between seed mass and the number or size of flowering heads. Thus, noug's âatypicalâ domestication syndrome does not seem to be a consequence of recent introgression or unfavorable phenotypic correlations. Nonetheless, our data do reveal evidence of local adaptation of noug cultivars to different precipitation regimes, as well as high levels of phenotypic plasticity, which may permit reasonable yields under diverse environmental conditions. Why noug has not been fully domesticated remains a mystery, but perhaps early farmers selected for resilience to episodic drought or untended environments rather than larger seeds. Domestication may also have been slowed by noug's outcrossing mating syste
Plant functional trait change across a warming tundra biome
Accepted versionThe tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperatureâtrait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming
The geography of biodiversity change in marine and terrestrial assemblages
This work was supported by funding to the sChange working group through sDiv, the synthesis center of iDiv, the German Centre for Integrative Biodiversity Research Halle-Jena-Leipzig, funded by the German Research Foundation (FZT 118). S.A.B., H.B., J.M.C., J.H., and M.W. were supported by the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. S.R.S. was supported by U.S. National Science Foundation grant 1400911. LHA was supported by Fundação para a CiĂȘncia e Tecnologia, Portugal (POPH/FSE SFRH/BD/90469/2012), and by the Jane and Aatos Erkko Foundation. M.D. was supported by a Leverhulme Trust Fellowship. A.E.M., F.M., and M.D. were supported by ERC AdG BioTIME 250189 and PoC BioCHANGE 727440. A.G. is supported by the Liber Ero Chair in Biodiversity Conservation.Human activities are fundamentally altering biodiversity. Projections of declines at the global scale are contrasted by highly variable trends at local scales, suggesting that biodiversity change may be spatially structured. Here, we examined spatial variation in species richness and composition change using more than 50,000 biodiversity time series from 239 studies and found clear geographic variation in biodiversity change. Rapid compositional change is prevalent, with marine biomes exceeding and terrestrial biomes trailing the overall trend. Assemblage richness is not changing on average, although locations exhibiting increasing and decreasing trends of up to about 20% per year were found in some marine studies. At local scales, widespread compositional reorganization is most often decoupled from richness change, and biodiversity change is strongest and most variable in the oceans.PostprintPostprintPeer reviewe
Mapping human pressures on biodiversity across the planet uncovers anthropogenic threat complexes
Abstract Climate change and other anthropogenic drivers of biodiversity change are unequally distributed across the world. Overlap in the distributions of different drivers have important implications for biodiversity change attribution and the potential for interactive effects. However, the spatial relationships among different drivers and whether they differ between the terrestrial and marine realm has yet to be examined. We compiled global gridded datasets on climate change, land-use, resource exploitation, pollution, alien species potential and human population density. We used multivariate statistics to examine the spatial relationships among the drivers and to characterize the typical combinations of drivers experienced by different regions of the world. We found stronger positive correlations among drivers in the terrestrial than in the marine realm, leading to areas with high intensities of multiple drivers on land. Climate change tended to be negatively correlated with other drivers in the terrestrial realm (e.g. in the tundra and boreal forest with high climate change but low human use and pollution), whereas the opposite was true in the marine realm (e.g. in the Indo-Pacific with high climate change and high fishing). We show that different regions of the world can be defined by Anthropogenic Threat Complexes (ATCs), distinguished by different sets of drivers with varying intensities. We identify 11 ATCs that can be used to test hypotheses about patterns of biodiversity and ecosystem change, especially about the joint effects of multiple drivers. Our global analysis highlights the broad conservation priorities needed to mitigate the impacts of anthropogenic change, with different priorities emerging on land and in the ocean, and in different parts of the world.Peer reviewe
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BioTIME: A database of biodiversity time series for the Anthropocene.
MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL
Tundra Trait Team: A database of plant traits spanning the tundra biome
Published VersionMotivation:The Tundra Trait Team (TTT) database includes fieldâbased measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and tradeâoffs, traitâenvironment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters.
Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density.
Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and subâAntarctic Marion Island. More than 99% of observations are georeferenced.
Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods.Major taxa and level of measurement:Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species.
Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release
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