Plant functional traits and community assembly along interacting gradients of productivity and fragmentation

Quantifying the association of plant functional traits to environmental gradients is a promising approach for understanding and projecting community responses to land use and climatic changes. Although habitat fragmentation and climate are expected to affect plant communities interactively, there is a lack of empirical studies addressing trait associations to fragmentation in different climatic regimes.In this study, we analyse data on the key functional traits: specific leaf area (SLA), plant height, seed mass and seed number. First, we assess the evidence for the community assembly mechanisms habitat filtering and competition at different spatial scales, using several null-models and a comprehensive set of community-level trait convergence and divergence indices. Second, we analyse the association of community-mean traits with patch area and connectivity along a south–north productivity gradient.We found clear evidence for trait convergence due to habitat filtering. In contrast, the evidence for trait divergence due to competition fundamentally depended on the null-model used. When the null-model controlled for habitat filtering, there was only evidence for trait divergence at the smallest sampling scale (0.25 m × 0.25 m). All traits varied significantly along the S–N productivity gradient. While plant height and SLA were consistently associated with fragmentation, the association of seed mass and seed number with fragmentation changed along the S–N gradient.Our findings indicate trait convergence due to drought stress in the arid sites and due to higher productivity in the mesic sites. The association of plant traits to fragmentation is likely driven by increased colonization ability in small and/or isolated patches (plant height, seed number) or increased persistence ability in isolated patches (seed mass).Our study provides the first empirical test of trait associations with fragmentation along a productivity gradient. We conclude that it is crucial to study the interactive effects of different ecological drivers on plant functional traits.     

Versatile characterization of glycosylation modification in CTLA4-Ig fusion proteins by liquid chromatography-mass spectrometry

CTLA4-Ig is a highly glycosylated therapeutic fusion protein that contains multiple N- and O-glycosylation sites. Glycosylation plays a vital role in protein solubility, stability, serum half-life, activity, and immunogenicity. For a CTLA4-Ig biosimilar development program, comparative analytical data, especially the glycosylation data, can influence decisions about the type and amount of animal and clinical data needed to establish biosimilarity. Because of the limited clinical experience with biosimilars before approval, a comprehensive level of knowledge about the biosimilar candidates is needed to achieve subsequent development. Liquid chromatography-mass spectrometry (LC–MS) is a versatile technique for characterizing N- and O-glycosylation modification of recombinant therapeutic proteins, including 3 levels: intact protein analysis, peptide mapping analysis, and released glycans analysis. In this report, an in-depth characterization of glycosylation of a candidate biosimilar was carried out using a systematic approach: N- and O-linked glycans were identified and electron-transfer dissociation was then used to pinpoint the 4 occupied O-glycosylation sites for the first time. As the results show, the approach provides a set of routine tools that combine accurate intact mass measurement, peptide mapping, and released glycan profiling. This approach can be used to comprehensively research a candidate biosimilar Fc-fusion protein and provides a basis for future studies addressing the similarity of CTLA4-Ig biosimilars.     

Sulindac modulates secreted protein expression from LIM1215 colon carcinoma cells prior to apoptosis

Colorectal cancer (CRC) is a major cause of mortality in Western populations. Growing evidence from human and rodent studies indicate that nonsteroidal anti-inflammatory drugs (NSAIDs) cause regression of existing colon tumors and act as effective chemopreventive agents in sporadic colon tumor formation. Although much is known about the action of the NSAID sulindac, especially its role in inducing apoptosis, mechanisms underlying these effects is poorly understood. In previous secretome-based proteomic studies using 2D-DIGE/MS and cytokine arrays we identified over 150 proteins released from the CRC cell line LIM1215 whose expression levels were dysregulated by treatment with 1 mM sulindac over 16 h; many of these proteins are implicated in molecular and cellular functions such as cell proliferation, differentiation, adhesion, angiogenesis and apoptosis (Ji et al., Proteomics Clin. Appl. 2009, 3, 433–451). We have extended these studies and describe here an improved protein/peptide separation strategy that facilitated the identification of 987 proteins and peptides released from LIM1215 cells following 1 mM sulindac treatment for 8 h preceding the onset of apoptosis. This peptidome separation strategy involved fractional centrifugal ultrafiltration of concentrated cell culture media (CM) using nominal molecular weight membrane filters (NMWL 30 K, 3 K and 1 K). Proteins isolated in the > 30 K and 3–30 K fractions were electrophoretically separated by SDS-PAGE and endogenous peptides in the 1–3 K membrane filter were fractioned by RP-HPLC; isolated proteins and peptides were identified by nanoLC-MS–MS. Collectively, our data show that LIM1215 cells treated with 1 mM sulindac for 8 h secrete decreased levels of proteins associated with extracellular matrix remodeling (e.g., collagens, perlecan, syndecans, filamins, dyneins, metalloproteinases and endopeptidases), cell adhesion (e.g., cadherins, integrins, laminins) and mucosal maintenance (e.g., glycoprotein 340 and mucins 5 AC, 6, and 13). A salient finding of this study was the increased proteolysis of cell surface proteins following treatment with sulindac for 8 h (40% higher than from untreated LIM1215 cells); several of these endogenous peptides contained C-terminal amino acids from transmembrane domains indicative of regulated intramembrane proteolysis (RIP). Taken together these results indicate that during the early-stage onset of sulindac-induced apoptosis (evidenced by increased annexin V binding, dephosphorylation of focal adhesion kinase (FAK), and cleavage of caspase-3), 1 mM sulindac treatment of LIM1215 cells results in decreased expression of secreted proteins implicated in ECM remodeling, mucosal maintenance and cell–cell-adhesion. This article is part of a Special Issue entitled: An Updated Secretome.     

Endangered Pinzgauer cattle subtype Jochberger Hummel are genetically distinct

Autochthonous cattle breeds are an important part of cultural heritage and reservoir of genetic diversity. Usually, such breeds have been selected over centuries and reflect adaptation to a specific local environment and human demands. However, owing to low effective population size in conjunction with increased inbreeding and genetic drift, many of these lineages are threatened with extinction. The Jochberger Hummel (‘Jochberger Bumblebee’) is such an endangered subtype of the Pinzgauer cattle originating from a single polled female calf. To evaluate the suspected uniqueness of this subtype and to assess whether it should be kept separate or managed together with the Pinzgauer cattle as one population, I examined the genetic diversity in a set of 844 cattle (Angus, Charolais, Holstein, Jochberger Hummel, Pinzgauer, Uckermaerker and Tux-Zillertaler) using principal component and biogeographical ancestry analysis. The analysis showed that the Jochberger Hummel is still a distinct subtype of Pinzgauer cattle with less than 5% admixture and a low inbreeding coefficient.     

Adjustment for exploratory cut-off selection in randomized clinical trials with survival endpoint

Defining the target population based on predictive biomarkers plays an important role during clinical development. After establishing a relationship between a biomarker candidate and response to treatment in exploratory phases, a subsequent confirmatory trial ideally involves only subjects with high potential of benefiting from the new compound. In order to identify those subjects in case of a continuous biomarker, a cut-off is needed. Usually, a cut-off is chosen that resulted in a subgroup with a large observed treatment effect in an exploratory trial. However, such a data-driven selection may lead to overoptimistic expectations for the subsequent confirmatory trial. Treatment effect estimates, probability of success, and posterior probabilities are useful measures for deciding whether or not to conduct a confirmatory trial enrolling the biomarker-defined population. These measures need to be adjusted for selection bias. We extend previously introduced Approximate Bayesian Computation techniques for adjustment of subgroup selection bias to a time-to-event setting with cut-off selection. Challenges in this setting are that treatment effects become time-dependent and that subsets are defined by the biomarker distribution. Simulation studies show that the proposed method provides adjusted statistical measures which are superior to naïve Maximum Likelihood estimators as well as simple shrinkage estimators.