Protein S-guanylation by the biological signal 8-nitroguanosine 3\u27,5\u27-cyclic monophosphate

The signaling pathway of nitric oxide (NO) depends mainly on guanosine 3′,5′-cyclic monophosphate (cGMP, 1). Here we report the formation and chemical biology of a nitrated derivative of cGMP, 8-nitroguanosine 3′,5′-cyclic monophosphate (8-nitro-cGMP, 2), in NO-mediated signal transduction. Immunocytochemistry demonstrated marked 8-nitro-cGMP production in various cultured cells in an NO-dependent manner. This finding was confirmed by HPLC plus electrochemical detection and tandem mass spectrometry. 8-Nitro-cGMP activated cGMP-dependent protein kinase and showed unique redox-active properties independent of cGMP activity. Formation of protein Cys-cGMP adducts by 8-nitro-cGMP was identified as a new post-translational modification, which we call protein S-guanylation. 8-Nitro-cGMP seems to regulate the redox-sensor signaling protein Keap1, via S-guanylation of the highly nucleophilic cysteine sulfhydryls of Keap1. This study reveals 8-nitro-cGMP to be a second messenger of NO and sheds light on new areas of the physiology and chemical biology of signal transduction by NO

Urinary glucuronidase and arylsulfatases in identical twins of bladder cancer patients.

Studies showing that bladder cancer patients have unusually high levels of urinary beta-glucuronidase and arylsulfatases A and B led to the suggestion that these urinary enzymes may participate in bladder cancer etiology. An alternative explanation of the high levels of these urinary enzymes in bladder cancer patients is that the disease itself causes the elevation. Since the levels of these enzymes are genetically determined, measuring these enzymes in healthy identical twins of bladder cancer patients can test whether high enzyme levels occurred prior to bladder cancer. Five healthy identical cotwins of bladder cancer patients, together with matched controls, were measured for urinary beta-glucuronidase, arylsulfatases A and B, and two other lysosomal enzymes as controls, alpha- and beta-galactosidases. The mean levels of all five enzymes were not very different in the cotwins and controls, suggesting that high levels of urinary enzymes observed in bladder cancer patients are a consequence of disease rather than occurring prior to disease and contributing to its etiology

Application of 16S rRNA Gene Sequencing To Identify Bordetella hinzii as the Causative Agent of Fatal Septicemia

We report on the first case of fatal septicemia caused by Bordetella hinzii. The causative organism exhibited a biochemical profile identical to that of Bordetella avium with three commercial identification systems (API 20E, API 20 NE, and Vitek GNI+ card). However, its cellular fatty acid profile was not typical for either B. avium or previously reported strains of B. hinzii. Presumptive identification of the patient's isolate was accomplished by traditional biochemical testing, and definitive identification was achieved by 16S rRNA gene sequence analysis. Phenotypic features useful in distinguishing B. hinzii from B. avium were production of alkali from malonate and resistance to several antimicrobial agents

Issues in Biomedical Research Data Management and Analysis: Needs and Barriers

OBJECTIVES: A. Identify the current state of data management needs of academic biomedical researchers. B. Explore their anticipated data management and analysis needs. C. Identify barriers to addressing those needs. DESIGN: A multimodal needs analysis was conducted using a combination of an online survey and in-depth one-on-one semi-structured interviews. Subjects were recruited via an e-mail list representing a wide range of academic biomedical researchers in the Pacific Northwest. MEASUREMENTS: The results from 286 survey respondents were used to provide triangulation of the qualitative analysis of data gathered from 15 semi-structured in-depth interviews. RESULTS: Three major themes were identified: 1) there continues to be widespread use of basic general-purpose applications for core data management; 2) there is broad perceived need for additional support in managing and analyzing large datasets; and 3) the barriers to acquiring currently available tools are most commonly related to financial burdens on small labs and unmet expectations of institutional support. CONCLUSION: Themes identified in this study suggest that at least some common data management needs will best be served by improving access to basic level tools such that researchers can solve their own problems. Additionally, institutions and informaticians should focus on three components: 1) facilitate and encourage the use of modern data exchange models and standards, enabling researchers to leverage a common layer of interoperability and analysis; 2) improve the ability of researchers to maintain provenance of data and models as they evolve over time though tools and the leveraging of standards; and 3) develop and support information management service cores that could assist in these previous components while providing researchers with unique data analysis and information design support within a spectrum of informatics capabilities