Regulation of Nitrogen Fixation in Azotobacter vinelandii OP and in an Apparently Partially Constitutive Mutant

Methylamine and 2-methylalanine appeared to act as co-repressors of nitrogenase in Azotobacter vinelandii OP. They inhibited the growth of this organism on molecular nitrogen but not on nitrate, ammonia, or Casamino Acids; they prevented the formation of nitrogenase by cells transferred from repression to induction conditions; and they did not inhibit the activity of nitrogenase in vitro. A mutant of strain OP, selected on the basis of its relative resistance to methylalanine, appeared partially constitutive because nitrogenase in this strain was less sensitive to repressors than was the enzyme in the wild-type strain.     

T cell receptor junctional regions and the MHC molecule affect the recognition of antigenic peptides by T cell clones.

Nine independent pigeon cytochrome c-specific T cell clones were analyzed by using a panel of antigenic peptide analogs presented in association with three allelic IE-encoded MHC glycoproteins. Eight of the T cell clones expressed a TCR composed of a unique alpha- and beta-chain amino acid sequence, and concordantly, each of these T cell clones exhibited a unique Ag specificity. This was true for several clones which differed only in TCR V-J junctional regions. Interestingly, for a given clone, the response to some of the peptide analogs depended to a large extent on the allelic form of the presenting MHC molecule. A simple interpretation of these data would suggest that certain positions of the peptide Ag are most important for Ag-MHC molecule interactions, and that these specific interactions can influence the antigenic epitope recognized by the TCR. We suggest that an antigenic peptide binds to an MHC glycoprotein in a distinct way, but may retain a measure of flexibility.     

A predicted consensus structure for the protein kinase C2 homology (C2H) domain,the repeating unit of synaptotagmin

A secondary structure has been predicted for the protein kinase C2 regulatory domain found in homologous form in synaptotagmin, some phospholipases, and some GTP activated proteins. The proposed structure is built from seven consecutive beta strands followed by a terminal alpha helix. Considerations of overall surface exposure of individual secondary structural elements suggest that these are packed into a 2-sheet beta sandwich structure, with one of only three of the many possible folds being preferred. © 1995 Wiley-Liss, Inc.     

Reticulum Cell Sarcoma of the Central Nervous System

One variety of sarcoma of the central nervous system (CNS) has been referred to under such synonyms as perithelial sarcoma, microglioma, and reticulum cell sarcoma. A case of diffuse involvement of the CNS is reported and the author believes that the tumour is a reticulum cell sarcoma because: (1) in addition to involvement of the CNS, lesions characteristic of a diffuse lymphomatous process were present in extraneural sites; (2) silver carbonate impregnation of the tumour cells was demonstrated. This tinctorial property has been reported as characteristic of microgliomas but has been shown to be an unreliable criterion for the differentiation of the cells of microglial from those of reticulum cell sarcomas. It is concluded that in such cases the CNS is the initial and major focus of a multicentric malignant lymphoma which has the histologic characteristics of a reticulum cell sarcoma.     

Phylogenetic and structural analysis of centromeric DNA and kinetochore proteins

Background  

Kinetochores are large multi-protein structures that assemble on centromeric DNA (CEN DNA) and mediate the binding of chromosomes to microtubules. Comprising 125 base-pairs of CEN DNA and 70 or more protein components, Saccharomyces cerevisiae kinetochores are among the best understood. In contrast, most fungal, plant and animal cells assemble kinetochores on CENs that are longer and more complex, raising the question of whether kinetochore architecture has been conserved through evolution, despite considerable divergence in CEN sequence.     

A Highlights from MBoC Selection: Cells surviving fractional killing by TRAIL exhibit transient but sustainable resistance and inflammatory phenotypes

When clonal populations of human cells are exposed to apoptosis-inducing agents, some cells die and others survive. This fractional killing arises not from mutation but from preexisting, stochastic differences in the levels and activities of proteins regulating apoptosis. Here we examine the properties of cells that survive treatment with agonists of two distinct death receptors, tumor necrosis factor–related apoptosis-inducing ligand (TRAIL) and anti-FasR antibodies. We find that “survivor” cells are highly resistant to a second ligand dose applied 1 d later. Resistance is reversible, resetting after several days of culture in the absence of death ligand. “Reset” cells appear identical to drug-naive cells with respect to death ligand sensitivity and gene expression profiles. TRAIL survivors are cross-resistant to activators of FasR and vice versa and exhibit an NF-κB–dependent inflammatory phenotype. Remarkably, reversible resistance is induced in the absence of cell death when caspase inhibitors are present and can be sustained for 1 wk or more, also without cell death, by periodic ligand exposure. Thus stochastic differences in cell state can have sustained consequences for sen­sitivity to prodeath ligands and acquisition of proinflammatory phenotypes. The important role played by periodicity in TRAIL exposure for induction of opposing apoptosis and survival mechanisms has implications for the design of optimal therapeutic agents and protocols.     

The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging

The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.