Mark E. Dalphin

MIFlowCyt: The Minimum Information About a Flow Cytometry Experiment

A fundamental tenet of scientific research is that published results are open to independent validation and refutation. Minimum data standards aid data providers, users, and publishers by providing a specification of what is required to unambiguously interpret experimental findings. Here, we present the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard, stating the minimum information required to report flow cytometry (FCM) experiments. We brought together a cross‐disciplinary international collaborative group of bioinformaticians, computational statisticians, software developers, instrument manufacturers, and clinical and basic research scientists to develop the standard. The standard was subsequently vetted by the International Society for Advancement of Cytometry (ISAC) Data Standards Task Force, Standards Committee, membership, and Council. The MIFlowCyt standard includes recommendations about descriptions of the specimens and reagents included in the FCM experiment, the configuration of the instrument used to perform the assays, and the data processing approaches used to interpret the primary output data. MIFlowCyt has been adopted as a standard by ISAC, representing the FCM scientific community including scientists as well as software and hardware manufacturers. Adoptionof MIFlowCyt by the scientific and publishing communities will facilitate third‐party understanding and reuse of FCM data.

The translational termination signal database

The Translational Termination Database (TransTerm) consists of the immediate context sequences around the natural termination codons from 45 organisms, and summary tables. The influence of termination codon context on their effectivness as stop signals has been widely documented. The SPECIES--TRI.DAT table shows trinucleotide stop codon usage in each organism and for comparison the occurrence of these sequences in the noncoding region. The SPECIES--TETRA.DAT table contains is a similar table of tetranucleotide stop signal usage. The database is available from EMBL.

A Multigene Urine Test for the Detection and Stratification of Bladder Cancer in Patients Presenting with Hematuria

PURPOSE We investigated whether the RNA assay uRNA® and its derivative Cxbladder® have greater sensitivity for the detection of bladder cancer than cytology, NMP22™ BladderChek™ and NMP22™ ELISA, and whether they are useful in risk stratification. MATERIALS AND METHODS A total of 485 patients presenting with gross hematuria but without a history of urothelial cancer were recruited prospectively from 11 urology clinics in Australasia. Voided urine samples were obtained before cystoscopy. The sensitivity and specificity of the RNA tests were compared to cytology and the NMP22 assays using cystoscopy as the reference. The ability of Cxbladder to distinguish between low grade, stage Ta urothelial carcinoma and more advanced urothelial carcinoma was also determined. RESULTS uRNA detected 41 of 66 urothelial carcinoma cases (62.1% sensitivity, 95% CI 49.3-73.8) compared with NMP22 ELISA (50.0%, 95% CI 37.4-62.6), BladderChek (37.9%, 95% CI 26.2-50.7) and cytology (56.1%, 95% CI 43.8-68.3). Cxbladder, which was developed on the study data, detected 82%, including 97% of the high grade tumors and 100% of tumors stage 1 or greater. The cutoffs for uRNA and Cxbladder were prespecified to give a specificity of 85%. The specificity of cytology was 94.5% (95% CI 91.9-96.5), NMP22 ELISA 88.0%, (95% CI 84.6-91.0) and BladderChek 96.4% (95% CI 94.2-98.0). Cxbladder distinguished between low grade Ta tumors and other detected urothelial carcinoma with a sensitivity of 91% and a specificity of 90%. CONCLUSIONS uRNA and Cxbladder showed improved sensitivity for the detection of urothelial carcinoma compared to the NMP22 assays. Stratification with Cxbladder provides a potential method to prioritize patients for the management of waiting lists.

The translational stop signal: codon with a context, or extended factor recognition element?

Wide ranging studies of the readthrough of translational stop codons within the last 25 years have suggested that the stop codon might be only part of the molecular signature for recognition of the termination signal. Such studies do not distinguish between effects on suppression and effects on termination, and so we have used a number of different approaches to deduce whether the stop signal is a codon with a context or an extended factor recognition element. A data base of natural termination sites from a wide range of organisms (148 organisms, approximately 40,000 sequences) shows a very marked bias in the bases surrounding the stop codon in the genes for all organisms examined, with the most dramatic bias in the base following the codon (+4). The nature of this base determines the efficiency of the stop signal in vivo, and in Escherichia coli this is reinforced by overexpressing the stimulatory factor, release factor 3. Strong signals, defined by their high relative rates of selecting the decoding release factors, are enhanced whereas weak signals respond relatively poorly. Site-directed cross-linking from the +1, and bases up to +6 but not beyond make close contact with the bacterial release factor-2. The translational stop signal is deduced to be an extended factor recognition sequence with a core element, rather than simply a factor recognition triplet codon influenced by context.

TransTerm, the translational signal database, extended to include full coding sequences and untranslated regions.

TransTerm is a database of mRNA sequences and parameters useful for detecting translational control signals in general. TransTerm-98 has been expanded beyond previous years to include full coding sequences and UTRs, while retaining the original small contexts about the coding sequence start- and stop-codons. The database contains more than 130 000 non-redundant coding sequences with associated untranslated regions (UTRs) from over 450 species. This includes the complete genomes of 12 prokaryotic and one eukaryotic organism. Several coding sequence parameters are available: coding sequence length, Nc, GC3 and, when it is computable, Codon Adaptation Index (CAI). Codon usage tables and summaries of start- and stop-codon contexts are also included. TransTerm-98 has both a relational database form with a WWW interface and a flatfile format, also available by Internet browser. TransTerm is available at: http://biochem.otago.ac.nz:800/Transterm/homepage.h tml

The translational signal database, TransTerm: more organisms, complete genomes

TransTerm is a database of initiation and termination sequence contexts from more than 250 organisms listed in GenBank, including the four complete genomes:Haemophilus influenzae, Methanococcus jannaschii, Mycoplasma genitalium,and Saccharomyces cerevisiae. For the current release, more than 60 000 coding sequences were analysed. The tabulated data include initiation and termination contexts organised by species along with quantitative parameters about individual coding sequences (length, %GC, GC3, Nc and CAI). There are also tables of initiation- and termination-region nucleotide-frequencies, codon usage tables and summaries of stop signal usage. TransTerm is available on the World Wide Web at: http://biochem.otago.ac.nz:800/Transterm/homepage.h tml

Defining dose-response relationships in the therapeutic blockade of B7RP-1-dependent immune responses

The ICOS (Inducible T cell Co-Stimulator)/B7RP-1 (B7-related protein 1) interaction is critical for the proper activation of a T lymphocyte. In this manuscript we describe a systematic in vivo approach to determine the level of blockade required to impair the generation of a T cell-dependent antibody response. We have developed an overall strategy for correlating drug exposure, target saturation, and efficacy in a biological response that can be generalized for most protein therapeutics. Using this strategy, we determined that low levels of B7RP-1 blockade are still sufficient to inhibit the immune response. These data suggest that contact between the T cell and the antigen-presenting cell during antigen presentation is much more sensitive to inhibition than previously believed and that ICOS/B7RP-1 blockade may be efficacious in the treatment of autoimmune diseases.

THE STOP SIGNAL CONTROLS THE EFFICIENCY OF RELEASE FACTOR­ MEDIATED TRANSLATIONAL TERMINATION

There are three important steps in protein synthesis where signals in the mRNA are critical for a successful outcome, namely the production of a functional protein. First the information in the nucleic acid which is to be translated into an amino acid sequence is signalled by successive triplet sense codons, second the frame is set by one sense codon, the initiation codon, which acts as the start of translation of the encoded information, and third the end of the information frame also has to be marked by a specific signal. The use of a range of different signals to mark each of these steps allows for differences in the efficiency with which different proteins are produced. In this review the focus is on the signal that marks the end of the frame, the translational termination signal. For a long time it was thought that termination would be the least interesting phase of protein synthesis but it has subsequently been found to have unexpected dimensions, providing a substratum of cellular regulation. The translational stop signal should now be thought of as a full stop in the large majority of cases, but as a pause in a fundamentally important minority of cases where alternative genetic events can occur.

Translational Stop Signals: Evolution, Decoding for Protein Synthesis and Recoding for Alternative Events

Termination or translational stopping involves a close relationship between the ribosome, the mRNA, and the polypeptide chain release factors. The discovery of an array of alternative events occurring at stop codons in the mRNA has focussed attention on how the decoding mechanism discriminates between simple ‘stop’ signals and alternative events outside the normal constraints of the genetic code (Tate and Brown, 1992). This latter phenomenon has been recently called ‘recoding’ and the signals ‘recoding signals’ (Gesteland et al., 1992). Is the normal role of the stop codon merely overriden by the recoding signals or does the stop component of such a signal contribute to a finely tuned regulation at sites where the alternative events occur? These questions demand a re-examination of how a stop signal recognition mechanism might have evolved, first for its function in translational stopping, and second for a possible role in gene regulation.