Symbiotic and saprophytic survival of three unmarked Rhizobium leguminosarum biovar trifolii strains introduced into the field

The symbiotic and saprophytic persistence of three unmarked Rhizobium leguminosarum biovar trifolii (Rlt) strains introduced into a field site in Iceland were followed. This site was free of clover cultivation and initially devoid of clover-nodulating rhizobia as tested by nodulation studies. Nodule occupancy by strains was identified based on their distinct ERIC-polymerase chain reaction (PCR) DNA fingerprint patterns. The survival and persistence of the individual strains in soil were monitored by the quantitative real-time PCR (qRT-PCR) assay, targeting the host-specific nodE gene. The most dominant strain in the nodule population, Rlt 20-15, showed relatively less saprophytic survival ability and maintained high numbers only in the presence of the appropriate host plant. Conversely, the minor nodule occupant, Rlt 32-28, persisted in soil at a relatively higher abundance both in the presence of its host legumes and in the presence of a non-host grass. The qRT-PCR assay was successfully applied to quantify rhizobial strains directly in soil without culturing or nodulation. However, the assay demonstrated less sensitivity compared with the plant infection most-probable-number (MPN) method for estimating the population size of rhizobia in soil. The quantitative detection limit of our qRT-PCR assays was 1 x 10(3) cells per gram of soil, as opposed to the MPN test which has a detection limit of 10 cells per gram of soil.     

Overcoming residual frustration in domain-swapping: the roles of disulfide bonds in dimerization and aggregation

The prevalence of domain-swapping in nature is a manifestation of the principle of minimal frustration in that the interactions designed by evolution to stabilize the protein are also involved in this mode of binding. We previously demonstrated that the Symmetrized-Go potential accurately predicts the experimentally observed domain-swapped structure of Eps8 based solely on the structure of the monomer. There can be, however, multiple modes of domain-swapping, reflecting a higher level of frustration, which is a consequence of symmetry. The human prion and cyanovirin-N are too frustrated to form unique domain-swapped structures on the basis of the Symmetrized-Go potential. However, supplementing the completely symmetric model with intermolecular and intramolecular disulfide bonds in the prion and cyanovirin-N proteins, respectively, yielded unique domain-swapped structures with a remarkable similarity to the experimentally observed ones. These results suggest that the disulfide bonds may sometimes be critical in overcoming the intrinsic frustration of the symmetrized energy landscapes for domain-swapping. We also discuss the implications of intermolecular disulfide bonds in the formation of mammalian prion aggregates.     

Using a histone yellow fluorescent protein fusion for tagging and tracking endothelial cells in ES cells and mice

We report the first endothelial lineage-specific transgenic mouse allowing live imaging at subcellular resolution. We generated an H2B-EYFP fusion protein which can be used for fluorescent labeling of nucleosomes and used it to specifically label endothelial cells in mice and in differentiating embryonic stem (ES) cells. A fusion cDNA encoding a human histone H2B tagged at its C-terminus with enhanced yellow fluorescent protein (EYFP) was expressed under the control of an Flk1 promoter and intronic enhancer. The Flk1::H2B-EYFP transgenic mice are viable and high levels of chromatin-localized reporter expression are maintained in endothelial cells of developing embryos and in adult animals upon breeding. The onset of fluorescence in differentiating ES cells and in embryos corresponds with the beginning of endothelial cell specification. These transgenic lines permit real-time imaging in normal and pathological vasculogenesis and angiogenesis to track individual cells and mitotic events at a level of detail that is unprecedented in the mouse.     

Structure determination and characterization of carbendazim hydrochloride dihydrate

The objective of this study was to synthesize and characterize the hydrochloride salt of carbendazim with the aim of improving the intrinsic solubility of the parent compound. Carbendazim hydrochloride dihydrate was synthesized for the purpose of increasing the aqueous solubility of the parent drug, carbendazim. This was done with the commonly used saturation and cooling method. The structure was determined by single crystal radiograph crystallography, and the hydrochloride salt was found to be a dihydrate. The salt crystallized in a P 2₁ 2₁ 2₁ (#19) space group, which is typical for nonplanar, achiral, and noncentrosymmetric molecules. The asymmetric unit is comprised of 1 molecule each of carbendazim and chloride and 2 water molecules. The carbendazim molecules arrange themselves in a helical structure, with the waters and the chloride molecules in the channel linking the helix. The crystal lattice is held together by numerous hydrogen bonds, as well as van der Waals interactions. The melting point of the salt is 125.6°C. The solubility of the salt is 6.08 mg/mL, which is a thousand-fold increase from the intrinsic solubility (6.11 μg/mL) of the free base. Published: September 20, 2005     

Conceival,a novel noncontraceptive vaginal vehicle for lipophilic microbicides

The objective of this study was to develop a nontoxic and noncontraceptive vaginal drug delivery vehicle for lipophilic anti-human immunodeficiency virus (HIV) microbicides. Three representative poorly water-soluble novel broad-spectrum anti-HIV microbicides, PHI-113, PHI-346, and PHI-443, were evaluated in 11 different solvent systems. Based on their solubility profiles, a novel non-spermicidal self-emulsifying gel (viz Conceival) composed of pharmaceutical excipients, sorbitol, polyethylene glycol 400, polysorbate 80, microcrystalline cellulose, xanthan gum, and water was optimized. Conceival enhanced the solubility of these poorly water-soluble (<0.001 mg/mL) anti-HIV drugs by at least 150- to 270-fold. Conceival was evaluated in vivo in the New Zealand white rabbit model for the preservation of sperm function based on pregnancy outcome and the potential for vaginal irritation following single and multiple intravaginal applications, respectively. Conceival administered intravaginally immediately prior to artificial insemination with semen had no adverse effects on subsequent reproductive performance, neonatal survival, or pup development when compared with untreated control group. Histologic evaluation of vaginal tissues of rabbits exposed intravaginally to Conceival for 14 consecutive days revealed lack of epithelial, submucosal, and vascular changes at the gel application site (total irritation score <3 out of a possible 16). These findings indicate that Conceival has potential to become a clinically useful, safe noncontraceptive vaginal vehicle for lipophilic microbicides. Published: September 20, 2005     

Protein name tagging guidelines: lessons learned

Interest in information extraction from the biomedical literature is motivated by the need to speed up the creation of structured databases representing the latest scientific knowledge about specific objects, such as proteins and genes. This paper addresses the issue of a lack of standard definition of the problem of protein name tagging. We describe the lessons learned in developing a set of guidelines and present the first set of inter-coder results, viewed as an upper bound on system performance. Problems coders face include: (a) the ambiguity of names that can refer to either genes or proteins; (b) the difficulty of getting the exact extents of long protein names; and (c) the complexity of the guidelines. These problems have been addressed in two ways: (a) defining the tagging targets as protein named entities used in the literature to describe proteins or protein-associated or -related objects, such as domains, pathways, expression or genes, and (b) using two types of tags, protein tags and long-form tags, with the latter being used to optionally extend the boundaries of the protein tag when the name boundary is difficult to determine. Inter-coder consistency across three annotators on protein tags on 300 MEDLINE abstracts is 0.868 F-measure. The guidelines and annotated datasets, along with automatic tools, are available for research use.     

Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach

We have developed two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) and 18O proteolytic labeling strategies to identify and compare levels of secretory proteins with low abundance in the conditioned medium of rat adipose cells without or with insulin stimulation. Culture medium was concentrated and secreted proteins were separated on a RP-HPLC followed by LC-MS/MS analysis. For 18O proteolytic labeling, 16O- to 18O-exchange in the digested peptides from eight individual fractions was carried out in parallel in H2(16)O and H(2)18O with immobilized trypsin, and the ratios of isotopically distinct peptides were measured by mass spectrometry. A total of 84 proteins was identified as secreted adipokines. This large number of secretory proteins comprise multiple functional categories. Comparative proteomics of 18O proteolytic labeling allows the detection of different levels of many secreted proteins as exemplified here by the difference between basal and insulin treatment of adipose cells. Taken together, our proteomic approach is able to identify and quantify the comprehensive secretory proteome of adipose cells. Thus, our data support the endocrine role of adipose cells in pathophysiological states through the secretion of signaling molecules.     

Associative clustering for exploring dependencies between functional genomics data sets

High-throughput genomic measurements, interpreted as cooccurring data samples from multiple sources, open up a fresh problem for machine learning: What is in common in the different data sets, that is, what kind of statistical dependencies are there between the paired samples from the different sets? We introduce a clustering algorithm for exploring the dependencies. Samples within each data set are grouped such that the dependencies between groups of different sets capture as much of pairwise dependencies between the samples as possible. We formalize this problem in a novel probabilistic way, as optimization of a Bayes factor. The method is applied to reveal commonalities and exceptions in gene expression between organisms and to suggest regulatory interactions in the form of dependencies between gene expression profiles and regulator binding patterns.