The Arabidopsis COBRA Protein Facilitates Cellulose Crystallization at the Plasma Membrane

Mutations in the Arabidopsis COBRA gene lead to defects in cellulose synthesis but the function of COBRA is unknown. Here we present evidence that COBRA localizes to discrete particles in the plasma membrane and is sensitive to inhibitors of cellulose synthesis, suggesting that COBRA and the cellulose synthase complex reside in close proximity on the plasma membrane. Live-cell imaging of cellulose synthesis indicated that, once initiated, cellulose synthesis appeared to proceed normally in the cobra mutant. Using isothermal calorimetry, COBRA was found to bind individual β1–4-linked glucan chains with a K_D of 3.2 μm. Competition assays suggests that COBRA binds individual β1–4-linked glucan chains with higher affinity than crystalline cellulose. Solid-state nuclear magnetic resonance studies of the cell wall of the cobra mutant also indicated that, in addition to decreases in cellulose amount, the properties of the cellulose fibrils and other cell wall polymers differed from wild type by being less crystalline and having an increased number of reducing ends. We interpret the available evidence as suggesting that COBRA facilitates cellulose crystallization from the emerging β1–4-glucan chains by acting as a “polysaccharide chaperone.”     

BNTagger: improved tagging SNP selection using Bayesian networks

Genetic variation analysis holds much promise as a basis for disease-gene association. However, due to the tremendous number of candidate single nucleotide polymorphisms (SNPs), there is a clear need to expedite genotyping by selecting and considering only a subset of all SNPs. This process is known as tagging SNP selection. Several methods for tagging SNP selection have been proposed, and have shown promising results. However, most of them rely on strong assumptions such as prior block-partitioning, bi-allelic SNPs, or a fixed number or location of tagging SNPs. We introduce BNTagger, a new method for tagging SNP selection, based on conditional independence among SNPs. Using the formalism of Bayesian networks (BNs), our system aims to select a subset of independent and highly predictive SNPs. Similar to previous prediction-based methods, we aim to maximize the prediction accuracy of tagging SNPs, but unlike them, we neither fix the number nor the location of predictive tagging SNPs, nor require SNPs to be bi-allelic. In addition, for newly-genotyped samples, BNTagger directly uses genotype data as input, while producing as output haplotype data of all SNPs. Using three public data sets, we compare the prediction performance of our method to that of three state-of-the-art tagging SNP selection methods. The results demonstrate that our method consistently improves upon previous methods in terms of prediction accuracy. Moreover, our method retains its good performance even when a very small number of tagging SNPs are used.     

Integrating image data into biomedical text categorization

Categorization of biomedical articles is a central task for supporting various curation efforts. It can also form the basis for effective biomedical text mining. Automatic text classification in the biomedical domain is thus an active research area. Contests organized by the KDD Cup (2002) and the TREC Genomics track (since 2003) defined several annotation tasks that involved document classification, and provided training and test data sets. So far, these efforts focused on analyzing only the text content of documents. However, as was noted in the KDD'02 text mining contest-where figure-captions proved to be an invaluable feature for identifying documents of interest-images often provide curators with critical information. We examine the possibility of using information derived directly from image data, and of integrating it with text-based classification, for biomedical document categorization. We present a method for obtaining features from images and for using them-both alone and in combination with text-to perform the triage task introduced in the TREC Genomics track 2004. The task was to determine which documents are relevant to a given annotation task performed by the Mouse Genome Database curators. We show preliminary results, demonstrating that the method has a strong potential to enhance and complement traditional text-based categorization methods.     

New directions in biomedical text annotation: definitions, guidelines and corpus construction

Background  

While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined.     

New insights into the autoinhibition mechanism of glycogen synthase kinase-3beta

It has been suggested that phosphorylation at serine 9 near the N-terminus of glycogen synthase kinase-3β (GSK-3β) mimics the prephosphorylation of its substrate and, therefore, the N-terminus functions as a pseudosubstrate. The molecular basis for the pseudosubstrate's binding to the catalytic core and autoinhibition has not been fully defined. Here, we combined biochemical and computational analyses to identify the potential residues within the N-terminus and the catalytic core engaged in autoinhibition of GSK-3β. Bioinformatic analysis found Arg4, Arg6, and Ser9 in the pseudosubstrate sequence to be extremely conserved through evolution. Mutations at Arg4 and Arg6 to alanine enhanced GSK-3β kinase activity and impaired its ability to autophosphorylate at Ser9. In addition, and unlike wild-type GSK-3β, these mutants were unable to undergo autoinhibition by phosphorylated Ser9. We further show that Gln89 and Asn95, located within the catalytic core, interact with the pseudosubstrate. Mutation at these sites prevented inhibition by phosphorylated Ser9. Furthermore, the respective mutants were not inhibited by a phosphorylated pseudosubstrate peptide inhibitor. Finally, computational docking of the pseudosubstrate into the catalytic active site of the kinase suggested specific interactions between Arg6 and Asn95 and of Arg4 to Asp181 (apart from the interaction of phosphorylated serine 9 with the “phosphate binding pocket”). Altogether, our study supports a model of GSK-3-pseudosubstrate autoregulation that involves phosphorylated Ser9, Arg4, and Arg6 within the N-terminus and identified the specific contact sites within the catalytic core.     

Activity of short segments of Type I antifreeze protein

In this work, we present a study on the antifreeze activity of short segments of a Type I antifreeze protein, instead of the whole protein. This approach simplifies the correlation between antifreeze protein characteristics, such as hydrophilicity/hydrophobicity, and the effect of these characteristics on the antifreeze mechanism. Three short polypeptides of Type I AFP have been synthesized. Their antifreeze activity and interactions with water and ice crystals have been analyzed by various techniques such as circular dichroism spectroscopy, X-ray diffraction, differential scanning calorimetry, and osmometry. It is shown that one short segment of Type I AFP has an antifreeze activity of about 60% of the native protein activity. In this work, we demonstrate that short segments of Type I AFPs possess nonzero thermal hysteresis and result in modifications in the growth habits and growth rates of ice. This approach enables the preparation of large quantities of short AFP segments at low cost with high antifreeze activity, and opens the possibility of developing the commercial potential of AFPs.     

Glycogen synthase kinase 3: an emerging therapeutic target

Glycogen synthase kinase 3 (GSK-3) is a serine/threonine protein kinase that has recently emerged as a key target in drug discovery. It has been implicated in multiple cellular processes and linked with the pathogenesis of several diseases. GSK-3 inhibitors might prove useful as therapeutic compounds in the treatment of conditions associated with elevated levels of enzyme activity, such as type 2 diabetes and Alzheimer's disease. The pro-apoptotic feature of GSK-3 activity suggests a potential role for its inhibitors in protection against neuronal cell death, and in the treatment of traumatic head injury and stroke. Finally, selective inhibitors of GSK-3 could mimic the action of mood stabilizers such as lithium and valproic acid and be used in the treatment of bipolar mood disorders.     

BAF-1 mobility is regulated by environmental stresses

Barrier to autointegration factor (BAF) is an essential component of the nuclear lamina that binds lamins, LEM-domain proteins, histones, and DNA. Under normal conditions, BAF protein is highly mobile when assayed by fluorescence recovery after photobleaching and fluorescence loss in photobleaching. We report that Caenorhabditis elegans BAF-1 mobility is regulated by caloric restriction, food deprivation, and heat shock. This was not a general response of chromatin-associated proteins, as food deprivation did not affect the mobility of heterochromatin protein HPL-1 or HPL-2. Heat shock also increased the level of BAF-1 Ser-4 phosphorylation. By using missense mutations that affect BAF-1 binding to different partners we find that, overall, the ability of BAF-1 mutants to be immobilized by heat shock in intestinal cells correlated with normal or increased affinity for emerin in vitro. These results show BAF-1 localization and mobility at the nuclear lamina are regulated by stress and unexpectedly reveal BAF-1 immobilization as a specific response to caloric restriction in C. elegans intestinal cells.     

Activation of Tm-22 resistance is mediated by a conserved cysteine essential for tobacco mosaic virus movement

The tomato Tm-2² gene was considered to be one of the most durable resistance genes in agriculture, protecting against viruses of the Tobamovirus genus, such as tomato mosaic virus (ToMV) and tobacco mosaic virus (TMV). However, an emerging tobamovirus, tomato brown rugose fruit virus (ToBRFV), has overcome Tm-2², damaging tomato production worldwide. Tm-2² encodes a nucleotide-binding leucine-rich repeat (NLR) class immune receptor that recognizes its effector, the tobamovirus movement protein (MP). Previously, we found that ToBRFV MP (MP^ToBRFV) enabled the virus to overcome Tm-2²-mediated resistance. Yet, it was unknown how Tm-2² remained durable against other tobamoviruses, such as TMV and ToMV, for over 60 years. Here, we show that a conserved cysteine (C68) in the MP of TMV (MP^TMV) plays a dual role in Tm-2² activation and viral movement. Substitution of MP^ToBRFV amino acid H67 with the corresponding amino acid in MP^TMV (C68) activated Tm-2²-mediated resistance. However, replacement of C68 in TMV and ToMV disabled the infectivity of both viruses. Phylogenetic and structural prediction analysis revealed that C68 is conserved among all Solanaceae-infecting tobamoviruses except ToBRFV and localizes to a predicted jelly-roll fold common to various MPs. Cell-to-cell and subcellular movement analysis showed that C68 is required for the movement of TMV by regulating the MP interaction with the endoplasmic reticulum and targeting it to plasmodesmata. The dual role of C68 in viral movement and Tm-2² immune activation could explain how TMV was unable to overcome this resistance for such a long period.