Grazing tolerance of Gentianella amarella and other monocarpic herbs: why is tolerance highest at low damage levels?

Plants have adapted to compensate for the loss of vegetative biomass and reproductive potential caused by grazing. Shoot damage breaks down the correlative inhibition maintained by apical dominance. The consequent increased branching may lead to increased production of flowers and fruits in damaged plants, provided that enough resources, both in terms of meristems and nutrients, are available. In Gentianella amarella, the removal of the apex of the main stem (10% clipping) had no pronounced effect on branching and plant performance. In one of the two study populations, however, apically damaged plants produced more fruits than undamaged control plants. The plants also fully compensated for 50% removal of the main stem in terms of above-ground biomass, but their fruit production was reduced compared to control and apically damaged plants. After 75% clipping, fruit production was not significantly reduced compared to 50% clipping. Consequently, G. amarella showed highest tolerance in the presence of minor shoot damage. The pattern is qualitatively similar in some other monocarpic species (Gentianella campestris, Erysimum strictum and Rhinanthus minor). Multiple constraints as well as selective forces may shape these compensatory responses: (1) A lack of basal meristems may constrain tolerance of high damage levels. (2) Species with basal meristems may have a potential to tolerate major damage, but a shortage of resources or otherwise unfavourable growth conditions may constrain their compensatory ability. (3) It may be adaptive to have maximum tolerance of low and moderate damage levels if chemical defences reduce the risk of extensive shoot damage as well as the risk of repeated grazing. (4) The compensatory ability of monocarpic species may be affected by selective forces that favour fast vertical growth early in the season and unbranched architecture in undamaged conditions. Therefore, it is not the mere grazing history, but also other factors associated with growth conditions that are required to explain the variation in grazing tolerance.     

Multispectral canopy reflectance improves spatial distribution models of Amazonian understory species

Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin-wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty-nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species’ prevalence or abundance. Adding Landsat-based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate-only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management.     

Correspondence of vegetation boundaries to redox barriers in a Northern European moraine plain

Little attention has been devoted to the investigation of the formation and functioning of ecotones at the interfaces between the upland and riparian zones. The margins of riparian mires act as redox geochemical barriers. Such biogeochemical hot spots retain elements that have leached from upland soils, favouring the growth of mesomorphic plants in hydromorphic soils. This paper aims to clarify the correspondence of vegetation borders to horizontal redox barriers of a Northern European moraine plain in Estonia.24 random transects were surveyed on the moraine plain, sampled across sharp soil moisture boundaries as proxies of redox barriers. The shifts in vegetation perpendicular to the boundaries were investigated. Curves of Euclidean distance were computed by moving a 20 m split-window along transects. The curves showed peaks of high dissimilarity a few metres below the redox barriers in the sites of natural soil moisture. In artificially drained sites, the relict redox barriers poorly corresponded to the vegetation borders. We conclude that in the studied moraine plain, the vegetation boundaries between riparian mires and uplands correspond to the redox barriers. The same can be set as a hypothesis for Northern European moraine plains. Related ecotones can be observed on the footslopes, revealing redox barrier in the landscape and related hot spots in cultural landscapes. In field margins, the redox barriers and corresponding ecotones occur below cultivation terraces. The ecotones may represent functional boundaries for delineating wetlands. Man-made drainage removes soil redox barriers and corresponding vegetation boundaries, making the landscape uniform and therefore vulnerable to disturbances. As a management implication, footslope ecotones should be preserved in their natural condition.     

Using remote sensing to model tree species distribution in Peruvian lowland Amazonia

Species distribution models for Amazonian trees have mostly been produced at scales and resolutions that are too broad and coarse for practical use in either conservation or forestry. On the other hand, several studies have shown that elevation and the medium‐resolution remote sensing data available via Landsat imagery can be successfully used to detect differences in plant species composition in Amazonia. Therefore, it seems likely that the same data can also be used to predict geographical distributions of individual taxa. Here we use remotely sensed data and a maximum entropy algorithm (MaxEnt) to generate landscape‐scale distribution models at 30‐m‐resolution for five economically important timber tree genera (Apuleia, Amburana, Crepidospermum, Dipteryx, and Manilkara). Individual Landsat Thematic Mapper bands and normalized difference vegetation index yielded acceptable model performance, and the use of averaging filters (3 × 3 and 5 × 5 pixel low‐pass filters) improved model performance further. Including elevation as a predictor also improved model performance for all the genera. Our results suggest that it is possible to use Landsat bands and elevation as predictors for modeling the potential distribution of tree species in lowland Amazonia at a fine enough resolution to facilitate the practical management of forest resources.     

C-terminal Peptides of Tissue Factor Pathway Inhibitor Are Novel Host Defense Molecules

Tissue factor pathway inhibitor (TFPI) inhibits tissue factor-induced coagulation, but may, via its C terminus, also modulate cell surface, heparin, and lipopolysaccharide interactions as well as participate in growth inhibition. Here we show that C-terminal TFPI peptide sequences are antimicrobial against the Gram-negative bacteria Escherichia coli and Pseudomonas aeruginosa, Gram-positive Bacillus subtilis and Staphylococcus aureus, as well as the fungi Candida albicans and Candida parapsilosis. Fluorescence studies of peptide-treated bacteria, paired with analysis of peptide effects on liposomes, showed that the peptides exerted membrane-breaking effects similar to those seen for the “classic” human antimicrobial peptide LL-37. The killing of E. coli, but not P. aeruginosa, by the C-terminal peptide GGLIKTKRKRKKQRVKIAYEEIFVKNM (GGL27), was enhanced in human plasma and largely abolished in heat-inactivated plasma, a phenomenon linked to generation of antimicrobial C3a and activation of the classic pathway of complement activation. Furthermore, GGL27 displayed anti-endotoxic effects in vitro and in vivo in a mouse model of LPS shock. Importantly, TFPI was found to be expressed in the basal layers of normal epidermis, and was markedly up-regulated in acute skin wounds as well as wound edges of chronic leg ulcers. Furthermore, C-terminal fragments of TFPI were associated with bacteria present in human chronic leg ulcers. These findings suggest a new role for TFPI in cutaneous defense against infections.     

An interaction map of endoplasmic reticulum chaperones and foldases

Chaperones and foldases in the endoplasmic reticulum (ER) ensure correct protein folding. Extensive protein-protein interaction maps have defined the organization and function of many cellular complexes, but ER complexes are under-represented. Consequently, chaperone and foldase networks in the ER are largely uncharacterized. Using complementary ER-specific methods, we have mapped interactions between ER-lumenal chaperones and foldases and describe their organization in multiprotein complexes. We identify new functional chaperone modules, including interactions between protein-disulfide isomerases and peptidyl-prolyl cis-trans-isomerases. We have examined in detail a novel ERp72-cyclophilin B complex that enhances the rate of folding of immunoglobulin G. Deletion analysis and NMR reveal a conserved surface of cyclophilin B that interacts with polyacidic stretches of ERp72 and GRp94. Mutagenesis within this highly charged surface region abrogates interactions with its chaperone partners and reveals a new mechanism of ER protein-protein interaction. This ability of cyclophilin B to interact with different partners using the same molecular surface suggests that ER-chaperone/foldase partnerships may switch depending on the needs of different substrates, illustrating the flexibility of multichaperone complexes of the ER folding machinery.     

Modified hyaluronan hydrogels support the maintenance of mouse embryonic stem cells and human induced pluripotent stem cells

These studies provide evidence for the ability of a commercially available, defined, hyaluronan-gelatin hydrogel, HyStem-C?, to maintain both mouse embryonic stem cells (mESCs) and human induced pluripotent stem cells (hiPSCs) in culture while retaining their growth and pluripotent characteristics. Growth curve and doubling time analysis show that mESCs and hiPSCs grow at similar rates on HyStem-C? hydrogels and mouse embryonic fibroblasts and Matrigel?, respectively. Immunocytochemistry, flow cytometry, gene expression and karyotyping reveal that both human and murine pluripotent cells retain a high level of pluripotency on the hydrogels after multiple passages. The addition of fibronectin to HyStem-C? enabled the attachment of hiPSCs in a xeno-free, fully defined medium.     

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets

Background

Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type (‘outlier genes’), a hallmark of potential oncogenes.

Methodology

A new statistical method (the gene tissue index, GTI) was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29) of these genes, and 17 of these 19 genes (90%) showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target.

Conclusions/Significance

Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is implemented in an R package (Text S1).