From pots to plots: Hierarchical trait-based prediction of plant performance in a mesic grassland

Traits are powerful predictors of ecosystem functions pointing to underlying physiological and ecological processes. Plant individual performance results from the coordinated operation of many processes, ranging from nutrient uptake over organ turnover to photosynthesis, thus requiring a large set of traits for its prediction. For plant performance on higher hierarchical levels, e.g. populations, additional traits important for plant-plant and trophic interactions may be required which should even enlarge the spectrum of relevant predictor traits.(2)The goal of this study was to assess the importance of plant functional traits to predict individual and population performance of grassland species with particular focus on the significance of root traits. We tested this for 59 grassland species using 35 traits divided into three trait clusters: leaf traits (16), stature traits (8) and root traits (11), using individual biomass of mesocosm plants as a measure of individual performance and population biomass of monocultures as a measure of population performance. We applied structural equation models to disentangle direct effects of single traits on population biomass and indirect effects via individual plant biomass or shoot density.We tested multivariate trait effects on individual and population biomass to analyze whether the importance of different trait clusters shifts with increasing hierarchical integration from individuals to populations.(3)Traits of all three clusters significantly correlated with individual and population biomass. However, in spite of a number of significant correlations, above-below-ground linkages were generally week, with few exceptions like N content.(4)Stature traits exclusively affected population biomass indirectly via their effect on individual biomass, whereas root and leaf traits showed also direct effects and partly indirect effects via density.(5)The inclusion of root traits in multiple regression models improved the prediction of individual biomass compared to models with only above-ground information only slightly (95% vs. 93% of variance prediction with and without root traits, respectively) but was crucial for the prediction of population biomass (77% and 49%, respectively). Root traits were more important for plant performance than leaf traits and were even the most important predictors at the population level(6)Synthesis: Upscaling from the individual to the population level reflects an increasing number of processes requiring traits from different trait clusters for their prediction. Our results emphasize the importance of root traits for trait-based studies especially at higher organizational levels. Our approach provides a comprehensive framework acknowledging the hierarchical nature of trait influences. This is one step towards a more process-oriented assessment of trait-based approache

PDZ domain-mediated interactions of G protein-coupled receptors with postsynaptic density protein 95: Quantitative characterization of interactions.

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome. Their signaling is regulated by scaffold proteins containing PDZ domains, but although these interactions are important for GPCR function, they are still poorly understood. We here present a quantitative characterization of the kinetics and affinity of interactions between GPCRs and one of the best characterized PDZ scaffold proteins, postsynaptic density protein 95 (PSD-95), using fluorescence polarization (FP) and surface plasmon resonance (SPR). By comparing these in vitro findings with colocalization of the full-length proteins in cells and with previous studies, we suggest that the range of relevant interactions might extend to interactions with K-i = 450 mu M in the in vitro assays. Within this range, we identify novel PSD-95 interactions with the chemokine receptor CXCR2, the neuropeptide Y receptor Y-2, and four of the somatostatin receptors (SSTRs). The interaction with SSTR1 was further investigated in mouse hippocampal neurons, where we found a clear colocalization between the endogenously expressed proteins, indicating a potential for further investigation of the role of this interaction. The approach can easily be transferred to other receptors and scaffold proteins and this could help accelerate the discovery and quantitative characterization of GPCR-PDZ interactions

Supplementary Material for: HCC Immune Surveillance and Antiviral Therapy of Hepatitis C Virus Infection

<b><i>Objective:</i></b> HCV clearance by current antiviral therapies improves clinical outcomes but falls short in eliminating the risk for hepatocellular carcinoma (HCC) emergence. As the HCC immune surveillance establishment is vital for the control of neoplastic development and growth, we investigated its correlation with on-/post-treatment HCC emergence, and further analyzed the influence of viral eradication on this setup in patients with HCV-related liver cirrhosis. <b><i>Design:</i></b> PBMC isolated at baseline and longitudinally during therapy were analyzed for tumor-associated antigen (TAA)-specific CD8+ T cell responses against glypican-3 overlapping peptides in vitro using high-definition flow cytometry. Multianalyte profiling of fifty soluble inflammatory mediators (SIM) in the plasma was also performed using Luminex-based multiplex technology. <b><i>Results:</i></b> Cirrhosis patients were characterized by an altered profile of distinct SIMs at baseline. At this time point, immune-surveilling T cells targeting specific HCC-associated antigens were readily detectable in HCV-free cirrhosis patients whilst being rather weak in such patients who further developed HCC upon virus eradication. Therapy-induced cure of HCV infection analogously reduced the strength of the prevailing HCC immune surveillance machinery, particularly by CD8+ T cells in cirrhosis patients. These results were further validated by T cell reactivities to six immuno-dominant HCC-associated HLA-A2-restricted epi­topes. Further, we demonstrated that this phenomenon was likely orchestrated by alterations in SIMs – with evidence of IL-12 being a major culprit. <b><i>Conclusion:</i></b> Given the relationship between the baseline HCC-specific immune surveilling T cell responses and therapy-associated HCC emergence, and the impact of HCV clearance on its strength and magnitude, we recommend a continued HCC screening in cirrhotic HCV patients despite HCV resolution

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

Leaf dark respiration (R-dark) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of R-dark and associated leaf traits. Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in R-dark. Area-based R-dark at the prevailing average daily growth temperature (T) of each siteincreased only twofold from the Arctic to the tropics, despite a 20 degrees C increase in growing T (8-28 degrees C). By contrast, R-dark at a standard T (25 degrees C, R-dark(25)) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher R-dark(25) at a given photosynthetic capacity (V-cmax(25)) or leaf nitrogen concentration ([N]) than species at warmer sites. R-dark(25) values at any given V-cmax(25) or [N] were higher in herbs than in woody plants. The results highlight variation in R-dark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of R-dark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs)