Peri/nuclear localization of intact insulin-like growth factor binding protein-2 and a distinct carboxyl-terminal IGFBP-2 fragment in vivo

Insulin-like growth factor binding protein-2 (IGFBP-2) as one of the most important IGFBPs has never been assessed in the intracellular compartment in vivo. Since there is evidence for novel intracellular functions of distinct IGFBPs, we investigated the presence of IGFBP-2 inside the cell. In peri/nuclear fractions of various tissues isolated from IGFBP-2 transgenic and non-transgenic mice we were able to show the presence of intact IGFBP-2. In addition, we demonstrate the presence of a highly conserved carboxyl-terminal IGFBP-2 fragment in the peri/nuclear fraction by using different peptide-induced antibodies. In pancreatic sections, confocal microscopy revealed the presence of IGFBP-2 on the nuclear surface but not within the nucleus. Our findings suggest novel functions of intact IGFBP-2 and IGFBP-2 fragments within the cell.     

Semiquantitative analysis of ECM molecules in the different cartilage layers in early and advanced osteoarthritis of the knee joint

The study was conducted to examine the expression of collagen type I and II in the different cartilage layers in relation to other ECM molecules during the progression of early osteoarthritic degeneration in human articular cartilage (AC). Quantitative real-time (RT)-PCR and colorimetrical techniques were used for calibration of Photoshop-based image analysis in detecting such lesions. Immunohistochemistry and histology were performed with 40 cartilage tissue samples showing mild (ICRS grade 1b) respectively moderate/advanced (ICRS grade 3a or 3b) (20 each) osteoarthritis compared with 15 healthy biopsies. Furthermore, we quantified our results on the gene expression of collagen type I and II and aggrecan with the help of real-time (RT)-PCR. Proteoglycan content was measured colorimetrically. The digitized images of histology and immunohistochemistry stains were analyzed with Photoshop software. T-test and Spearman correlation analysis were used for statistical analysis. In the earliest stages of AC deterioration the loss of collagen type II was associated with the appearance of collagen type I, shown by increasing amounts of collagen type I mRNA. During subsequent stages, a progressive loss of structural integrity was associated with increasing deposition of collagen type I as part of a natural healing response. A decrease of collagen type II is visible especially in the upper fibrillated area of the advanced osteoarthritic samples, which then leads to an overall decrease. Analysis of proteoglycan showed losses of the overall content and a loss of the classical zonal formation. Correlation analysis of the proteoglycan Photoshop measurements with the RT-PCR revealed strong correlation for Safranin O and collagen type I, medium for collagen type II, alcian blue and glycoprotein but weak correlation with PCR aggrecan results. Photoshop based image analysis might become a valuable supplement for well known histopathological grading systems of lesioned articular cartilage. The evidence of collagen type I production early in the OA disease process coupled with the ability of chondrocytes to up-regulate collagen type II production suggests that therapeutic agents that suppress collagen type I production and increase collagen type II production may enable chondrocytes to generate a more effective repair response.     

Differential screening of phage-ab libraries by oligonucleotide microarray technology

A novel and efficient tagArray technology was developed that allows rapid identification of antibodies which bind to receptors with a specific expression profile, in the absence of biological information. This method is based on the cloning of a specific, short nucleotide sequence (tag) in the phagemid coding for each phage-displayed antibody fragment (phage-Ab) present in a library. In order to set up and validate the method we identified about 10,000 different phage-Abs binding to receptors expressed in their native form on the cell surface (10 k Membranome collection) and tagged each individual phage-Ab. The frequency of each phage-Ab in a given population can at this point be inferred by measuring the frequency of its associated tag sequence through standard DNA hybridization methods. Using tiny amounts of biological samples we identified phage-Abs binding to receptors preferentially expressed on primary tumor cells rather than on cells obtained from matched normal tissues. These antibodies inhibited cell proliferation in vitro and tumor development in vivo, thus representing therapeutic lead candidates.     

Consistent associations with beneficial bacteria in the seed endosphere of barley (Hordeum vulgare L.)

The importance of the plant microbiome for host fitness has led to the concept of the “plant holobiont”. Seeds are reservoirs and vectors for beneficial microbes, which are very intimate partners of higher plants with the potential to connect plant generations. In this study, the endophytic seed microbiota of numerous barley samples, representing different cultivars, geographical sites and harvest years, was investigated. Cultivation-dependent and -independent analyses, microscopy, functional plate assays, greenhouse assays and functional prediction were used, with the aim of assessing the composition, stability and function of the barley seed endophytic bacterial microbiota. Associations were consistently detected in the seed endosphere with Paenibacillus, Pantoea and Pseudomonas spp., which were able to colonize the root with a notable rhizocompetence after seed germination. In greenhouse assays, enrichment with these bacteria promoted barley growth, improved mineral nutrition and induced resistance against the fungal pathogen Blumeria graminis. We demonstrated here that barley, an important crop plant, was consistently associated with beneficial bacteria inside the seeds. The results have relevant implications for plant microbiome ecology and for the holobiont concept, as well as opening up new possibilities for research and application of seed endophytes as bioinoculants in sustainable agriculture.     

Recognition of single-stranded DNA by nuclease P1: High resolution crystal structures of complexes with substrate analogs

The reaction mechanism of nuclease P1 from Penicillium citrinum has been investigated using single-stranded dithiophosphorylated di-, tetra-, and hexanucleotides as substrate analogs. The complexes crystallize in tetragonal and orthorhombic space groups and have been solved by molecular replacement. The high resolution structures give a clear picture of base recognition by P1 nuclease at its two nucleotide-binding sites, especially the 1.8 Å structure of a P1-tetranucleotide complex which can be considered a P1-product complex. The observed binding modes are in agreement with a catalytic mechanism where the two closely spaced zinc ions activate the attacking water while the third, more exposed zinc ion stabilizes the leaving 03' oxyanion. Stacking as well as hydrogen bonding interactions with the base 5' to the cleaved phosphodiester bond are important elements of substrate binding and recognition. Modelling of a productive P1-substrate complex based on the solved structures suggests steric hindrance as the likely reason for the resistance of Rp-phosphorothioates and phosphorodithioates. Differences with the highly homologous nuclease S1 from Aspargillus oryzae are discussed. Proteins 32:414–424, 1998. © 1998 Wiley-Liss, Inc.     

Large Scale Application of Neural Network Based Semantic Role Labeling for Automated Relation Extraction from Biomedical Texts

To reduce the increasing amount of time spent on literature search in the life sciences, several methods for automated knowledge extraction have been developed. Co-occurrence based approaches can deal with large text corpora like MEDLINE in an acceptable time but are not able to extract any specific type of semantic relation. Semantic relation extraction methods based on syntax trees, on the other hand, are computationally expensive and the interpretation of the generated trees is difficult. Several natural language processing (NLP) approaches for the biomedical domain exist focusing specifically on the detection of a limited set of relation types. For systems biology, generic approaches for the detection of a multitude of relation types which in addition are able to process large text corpora are needed but the number of systems meeting both requirements is very limited. We introduce the use of SENNA (“Semantic Extraction using a Neural Network Architecture”), a fast and accurate neural network based Semantic Role Labeling (SRL) program, for the large scale extraction of semantic relations from the biomedical literature. A comparison of processing times of SENNA and other SRL systems or syntactical parsers used in the biomedical domain revealed that SENNA is the fastest Proposition Bank (PropBank) conforming SRL program currently available. 89 million biomedical sentences were tagged with SENNA on a 100 node cluster within three days. The accuracy of the presented relation extraction approach was evaluated on two test sets of annotated sentences resulting in precision/recall values of 0.71/0.43. We show that the accuracy as well as processing speed of the proposed semantic relation extraction approach is sufficient for its large scale application on biomedical text. The proposed approach is highly generalizable regarding the supported relation types and appears to be especially suited for general-purpose, broad-scale text mining systems. The presented approach bridges the gap between fast, cooccurrence-based approaches lacking semantic relations and highly specialized and computationally demanding NLP approaches.