Utilization of tmRNA sequences for bacterial identification

In recent years, molecular approaches based on nucleotide sequences of ribosomal RNA (rRNA) have become widely used tools for identification of bacteria [1-4]. The high degree of evolutionary conservation makes 16S and 23S rRNA molecules very suitable for phylogenetic studies above the species level [3-5]. More than 16,000 sequences of 16S rRNA are presently available in public databases [4,6]. The 16S rRNA sequences are commonly used to design fluorescently labeled oligonucleotide probes. Fluorescence in situ hybridization (FISH) with these probes followed by observation with epifluorescence microscopy allows the identification of a specific microorganism in a mixture with other bacteria [2-4]. By shifting probe target sites from conservative to increasingly variable regions of rRNA, it is possible to adjust the probe specificity from kingdom to species level. Nevertheless, 16S rRNA sequences of closely related strains, subspecies, or even of different species are often identical and therefore can not be used as differentiating markers [3]. Another restriction concerns the accessibility of target sites to the probe in FISH experiments. The presence of secondary structures, or protection of rRNA segments by ribosomal proteins in fixed cells can limit the choice of variable regions as in situ targets for oligonucleotide probes [7,8]. One way to overcome the limitations of in situ identification of bacteria is to use molecules other than rRNA for phylogenetic identification of bacteria, for which nucleotide sequences would be sufficiently divergent to design species specific probes, and which would be more accessible to oligonucleotide probes. For this purpose we investigated the possibility of using tmRNA (also known as 10Sa RNA; [9-11]). This molecule was discovered in E. coli and described as small stable RNA, present at ~1,000 copies per cell [9,11]. The high copy number is an important prerequisite for FISH, which works best with naturally amplified target molecules. In E. coli, tmRNA is encoded by the ssrA gene, is 363 nucleotides long and has properties of tRNA and mRNA [12,13]. tmRNA was shown to be involved in the degradation of truncated proteins: the tmRNA associates with ribosomes stalled on mRNAs lacking stop codons, finally resulting in the addition of a C-terminal peptide tag to the truncated protein. The peptide tag directs the abnormal protein to proteolysis [14,15]. 165 tmRNA sequences have so far (August 2001; The tmRNA Website: http://www.indiana.edu/~tmrna/) been determined [16,17]. The tmRNA is likely to be present in all bacteria and has also been found in algae chloroplasts, the cyanelle of Cyanophora paradoxa and the mitochondrion of the flagellate Reclinomonas americana[10,17,18]

Recognition of vitamin B metabolites by mucosal-associated invariant T cells

The mucosal-associated invariant T-cell antigen receptor (MAIT TCR) recognizes MR1 presenting vitamin B metabolites. Here we describe the structures of a human MAIT TCR in complex with human MR1 presenting a non-stimulatory ligand derived from folic acid and an agonist ligand derived from a riboflavin metabolite. For both vitamin B antigens, the MAIT TCR docks in a conserved manner above MR1, thus acting as an innate-like pattern recognition receptor. The invariant MAIT TCR a-chain usage is attributable to MR1-mediated interactions that prise open the MR1 cleft to allow contact with the vitamin B metabolite. Although the non-stimulatory antigen does not contact the MAIT TCR, the stimulatory antigen does. This results in a higher affinity of the MAIT TCR for a stimulatory antigen in comparison with a non-stimulatory antigen. We formally demonstrate a structural basis for MAIT TCR recognition of vitamin B metabolites, while illuminating how TCRs recognize microbial metabolic signatures

Assessing Communities of Practice in health policy : A conceptual framework as a first step towards empirical research

Peer reviewe

Logical Development of the Cell Ontology

<p>Abstract</p> <p>Background</p> <p>The Cell Ontology (CL) is an ontology for the representation of <it>in vivo </it>cell types. As biological ontologies such as the CL grow in complexity, they become increasingly difficult to use and maintain. By making the information in the ontology computable, we can use automated reasoners to detect errors and assist with classification. Here we report on the generation of computable definitions for the hematopoietic cell types in the CL.</p> <p>Results</p> <p>Computable definitions for over 340 CL classes have been created using a genus-differentia approach. These define cell types according to multiple axes of classification such as the protein complexes found on the surface of a cell type, the biological processes participated in by a cell type, or the phenotypic characteristics associated with a cell type. We employed automated reasoners to verify the ontology and to reveal mistakes in manual curation. The implementation of this process exposed areas in the ontology where new cell type classes were needed to accommodate species-specific expression of cellular markers. Our use of reasoners also inferred new relationships within the CL, and between the CL and the contributing ontologies. This restructured ontology can be used to identify immune cells by flow cytometry, supports sophisticated biological queries involving cells, and helps generate new hypotheses about cell function based on similarities to other cell types.</p> <p>Conclusion</p> <p>Use of computable definitions enhances the development of the CL and supports the interoperability of OBO ontologies.</p

Measurement of the Isolated Photon Cross Section in p-pbar Collisions at sqrt{s}=1.96 TeV

The cross section for the inclusive production of isolated photons has been measured in p anti-p collisions at sqrt{s}=1.96 TeV with the D0 detector at the Fermilab Tevatron Collider. The photons span transverse momenta 23 to 300 GeV and have pseudorapidity |eta|<0.9. The cross section is compared with the results from two next-to-leading order perturbative QCD calculations. The theoretical predictions agree with the measurement within uncertainties.Comment: 7 pages, 5 figures, submitted to Phys.Lett.

Measurement of isolated photon production in pp and PbPb collisions at sqrt(sNN) = 2.76 TeV

Isolated photon production is measured in proton-proton and lead-lead collisions at nucleon-nucleon centre-of-mass energies of 2.76 TeV in the pseudorapidity range |eta|<1.44 and transverse energies ET between 20 and 80 GeV with the CMS detector at the LHC. The measured ET spectra are found to be in good agreement with next-to-leading-order perturbative QCD predictions. The ratio of PbPb to pp isolated photon ET-differential yields, scaled by the number of incoherent nucleon-nucleon collisions, is consistent with unity for all PbPb reaction centralities.Comment: Submitted to Physics Letters

The normal breast microenvironment of premenopausal women differentially influences the behavior of breast cancer cells in vitro and in vivo

<p>Abstract</p> <p>Background</p> <p>Breast cancer studies frequently focus on the role of the tumor microenvironment in the promotion of cancer; however, the influence of the normal breast microenvironment on cancer cells remains relatively unknown. To investigate the role of the normal breast microenvironment on breast cancer cell tumorigenicity, we examined whether extracellular matrix molecules (ECM) derived from premenopausal African-American (AA) or Caucasian-American (CAU) breast tissue would affect the tumorigenicity of cancer cells <it>in vitro </it>and <it>in vivo</it>. We chose these two populations because of the well documented predisposition of AA women to develop aggressive, highly metastatic breast cancer compared to CAU women.</p> <p>Methods</p> <p>The effects of primary breast fibroblasts on tumorigenicity were analyzed via real-time PCR arrays and mouse xenograft models. Whole breast ECM was isolated, analyzed via zymography, and its effects on breast cancer cell aggressiveness were tested <it>in vitro </it>via soft agar and invasion assays, and <it>in vivo </it>via xenograft models. Breast ECM and hormone metabolites were analyzed via mass spectrometry.</p> <p>Results</p> <p>Mouse mammary glands humanized with premenopausal CAU fibroblasts and injected with primary breast cancer cells developed significantly larger tumors compared to AA humanized glands. Examination of 164 ECM molecules and cytokines from CAU-derived fibroblasts demonstrated a differentially regulated set of ECM proteins and increased cytokine expression. Whole breast ECM was isolated; invasion and soft agar assays demonstrated that estrogen receptor (ER)^-, progesterone receptor (PR)/PR^-cells were significantly more aggressive when in contact with AA ECM, as were ER⁺/PR⁺cells with CAU ECM. Using zymography, protease activity was comparatively upregulated in CAU ECM. In xenograft models, CAU ECM significantly increased the tumorigenicity of ER⁺/PR⁺cells and enhanced metastases. Mass spectrometry analysis of ECM proteins showed that only 1,759 of approximately 8,000 identified were in common. In the AA dataset, proteins associated with breast cancer were primarily related to tumorigenesis/neoplasia, while CAU unique proteins were involved with growth/metastasis. Using a novel mass spectrometry method, 17 biologically active hormones were measured; estradiol, estriol and 2-methoxyestrone were significantly higher in CAU breast tissue.</p> <p>Conclusions</p> <p>This study details normal premenopausal breast tissue composition, delineates potential mechanisms for breast cancer development, and provides data for further investigation into the role of the microenvironment in cancer disparities.</p

Structure of a Classical MHC Class I Molecule That Binds “Non-Classical” Ligands

The chicken MHC YF1*7.1 X-ray structures reveal that this protein binds lipids and thus represents a "hybrid" class I complex with features of classical as well as non-classical MHC molecules