High throughput protein-protein interaction data: clues for the architecture of protein complexes

<p>Abstract</p> <p>Background</p> <p>High-throughput techniques are becoming widely used to study protein-protein interactions and protein complexes on a proteome-wide scale. Here we have explored the potential of these techniques to accurately determine the constituent proteins of complexes and their architecture within the complex.</p> <p>Results</p> <p>Two-dimensional representations of the 19S and 20S proteasome, mediator, and SAGA complexes were generated and overlaid with high quality pairwise interaction data, core-module-attachment classifications from affinity purifications of complexes and predicted domain-domain interactions. Pairwise interaction data could accurately determine the members of each complex, but was unexpectedly poor at deciphering the topology of proteins in complexes. Core and module data from affinity purification studies were less useful for accurately defining the member proteins of these complexes. However, these data gave strong information on the spatial proximity of many proteins. Predicted domain-domain interactions provided some insight into the topology of proteins within complexes, but was affected by a lack of available structural data for the co-activator complexes and the presence of shared domains in paralogous proteins.</p> <p>Conclusion</p> <p>The constituent proteins of complexes are likely to be determined with accuracy by combining data from high-throughput techniques. The topology of some proteins in the complexes will be able to be clearly inferred. We finally suggest strategies that can be employed to use high throughput interaction data to define the membership and understand the architecture of proteins in novel complexes.</p

Identification of arginine- and lysine-methylation in the proteome of Saccharomyces cerevisiae and its functional implications

<p>Abstract</p> <p>Background</p> <p>The methylation of eukaryotic proteins has been proposed to be widespread, but this has not been conclusively shown to date. In this study, we examined 36,854 previously generated peptide mass spectra from 2,607 <it>Saccharomyces cerevisiae </it>proteins for the presence of arginine and lysine methylation. This was done using the FindMod tool and 5 filters that took advantage of the high number of replicate analysis per protein and the presence of overlapping peptides.</p> <p>Results</p> <p>A total of 83 high-confidence lysine and arginine methylation sites were found in 66 proteins. Motif analysis revealed many methylated sites were associated with M<b>K</b>, <b>R</b>GG/<b>R</b>XG/<b>R</b>GX or WXXX<b>R </b>motifs. Functionally, methylated proteins were significantly enriched for protein translation, ribosomal biogenesis and assembly and organellar organisation and were predominantly found in the cytoplasm and ribosome. Intriguingly, methylated proteins were seen to have significantly longer half-life than proteins for which no methylation was found. Some 43% of methylated lysine sites were predicted to be amenable to ubiquitination, suggesting methyl-lysine might block the action of ubiquitin ligase.</p> <p>Conclusions</p> <p>This study suggests protein methylation to be quite widespread, albeit associated with specific functions. Large-scale tandem mass spectroscopy analyses will help to further confirm the modifications reported here.</p

Comparative analyses of Campylobacter concisusstrains reveal the genome of the reference strain BAA-1457 is not representative of the species

<p>Abstract</p> <p>Background</p> <p>Several studies have shown that significant genotypic heterogeneity exists among <it>Campylobacter concisus </it>strains. Recently, the genome of <it>C. concisus </it>UNSWCD, isolated from a patient with Crohn's disease, was sequenced.</p> <p>Results</p> <p>In this study, comparative analyses were performed between strain UNSWCD and BAA-1457, isolated from a patient with acute gastroenteritis. Searches between <it>C. concisus </it>UNSWCD and BAA-1457 showed that 76% of genes were homologues, whereas those between <it>C. jejuni </it>strains showed 90-91% to be homologues, indicating substantial variation exists within these two <it>C. concisus </it>genomes. More specific bidirectional homology searches identified 1593 genes that are shared between these strains, and 115 and 281 genes unique to UNSWCD and BAA-1457, respectively. Significantly, differences in the type of flagellin glycosylation pathways between the two strains were identified and confirmed by PCR. The protein profiles of UNSWCD, BAA-1457 and a further six strains of <it>C. concisus </it>were compared and analyzed bioinformatically, and this differentiated the strains into four clades. BAA-1457 was found to be highly divergent (average similarity: 56.8%) from the other seven strains (mean average similarity ± standard deviation: 64.7 ± 1.7%). Furthermore, searches for homologues of the 1593 proteins found to be common between UNSWCD and BAA-1457 were conducted against all available bacterial genomes, and 18 proteins were found to be unique to <it>C. concisus</it>, of which 6 were predicted to be secreted, and may represent good markers for detection of this species.</p> <p>Conclusions</p> <p>This study has elucidated several features that may be responsible for the heterogeneity that exists among <it>C. concisus </it>strains, and has determined that the strain BAA-1457 is genetically atypical to other <it>C. concisus </it>strains and is not a good candidate reference strain.</p

GlycoViewer: a tool for visual summary and comparative analysis of the glycome

The GlycoViewer (http://www.systemsbiology.org.au/glycoviewer) is a web-based tool that can visualize, summarize and compare sets of glycan structures. Its input is a group of glycan structures; these can be entered as a list in IUPAC format or via a sugar structure builder. Its output is a detailed graphic, which summarizes all salient features of the glycans according to the shapes of the core structures, the nature and length of any chains, and the types of terminal epitopes. The tool can summarize up to hundreds of structures in a single figure. This allows unique, high-level views to be generated of glycans from one protein, from a cell, a tissue or a whole organism. Use of the tool is illustrated in the analysis of normal and disease-associated glycans from the human glycoproteome

The Effect of Hair Color on the Incorporation of Codeine into Human Hair

The influence of melanin on the binding of xenobiotics in hair will impact the interpretation of drug concentrations determined by hair testing. The purpose of this study was to determine if codeine, as a model compound of abused drugs, would be incorporated into black, brown, blond, or red hair as a function of melanin concentration. Such data would assist in the interpretation of codeine concentrations in hair and help elucidate the potential influence of hair color on incorporation of drugs. Male and female Caucasians with black (n = 6), brown (n = 12), blond (n = 8), or red hair (n = 6) and non-Caucasians with black hair (n = 12) aged 21-40 years were enrolled in the study. Each subject was administered oral codeine phosphate syrup in a dosage of 30 mg three times a day for five days. Twenty-four hours after the end of the treatment period, a 30-mg codeine dose was administered and the subject's plasma area under the concentration time curve (AUC) for codeine was determined. Codeine and melanin were measured in the first 3 cm of hair closest to the vertex region of the scalp prior to and 1, 4, 5, 6, and 7 weeks after dosing. The quantitative and qualitative melanin profiles were determined for each subjects hair to provide an objective measure of hair color. The plasma concentrations of codeine were measured to eliminate differences in the bioavailability and clearance of codeine as factors that might account for the differences in codeine hair concentrations. The subjects were asked not to cut their hair in the vertex region of the scalp or to use any form of chemical treatment on their hair, but otherwise normal hygienic measures were permitted. The mean (± SE) hair codeine concentrations 5 weeks after dosing were 1429 (± 249) pg/mg in black hair; 208 (± 17) pg/mg in brown hair; 99 (± 10) pg/mg in blond hair; and 69 (± 11) in red hair pg/mg. In black hair, codeine concentrations were 2564 (± 170) pg/mg for Asians and 865 (± 162) pg/mg for Caucasians. Similar concentration relationships were observed at weeks 4, 6, and 7. A strong relationship between the hair concentrations of codeine and melanin (R2 = 0.73) was observed. Normalization of the codeine concentration with the melanin concentration reduced the hair color differences observed. These data demonstrate that the interpretation and reporting of hair test results for codeine are influenced by hair color. After this dosing protocol, the proposed federal guideline cutoff of 200 pg/mg of codeine would result in 100% of subjects with black hair and 50% of subjects with brown hair being reported as positive, and subjects with blond or red hair would be reported as negative. The incorporation of these drugs into hair should be studied carefully in humans to ensure the appropriate interpretation of drug concentration

Heteroepitaxial growth of ferromagnetic MnSb(0001) films on Ge/Si(111) virtual substrates

Molecular beam epitaxial growth of ferromagnetic MnSb(0001) has been achieved on high quality, fully relaxed Ge(111)/Si(111) virtual substrates grown by reduced pressure chemical vapor deposition. The epilayers were characterized using reflection high energy electron diffraction, synchrotron hard X-ray diffraction, X-ray photoemission spectroscopy, and magnetometry. The surface reconstructions, magnetic properties, crystalline quality, and strain relaxation behavior of the MnSb films are similar to those of MnSb grown on GaAs(111). In contrast to GaAs substrates, segregation of substrate atoms through the MnSb film does not occur, and alternative polymorphs of MnSb are absent

STAT3 regulates cytotoxicity of human CD57+ CD4+ T cells in blood and lymphoid follicles

A subset of human follicular helper T cells (TFH) cells expresses CD57 for which no distinct function has been identified. We show that CD57+ TFH cells are universally PD-1hi, but compared to their CD57− PD-1hi counterparts, express little IL-21 or IL-10 among others. Instead, CD57 expression on TFH cells marks cytotoxicity transcriptional signatures that translate into only a weak cytotoxic phenotype. Similarly, circulating PD-1+ CD57+ CD4+ T cells make less cytokine than their CD57− PD-1+ counterparts, but have a prominent cytotoxic phenotype. By analysis of responses to STAT3-dependent cytokines and cells from patients with gain- or loss-of-function STAT3 mutations, we show that CD4+ T cell cytotoxicity is STAT3-dependent. TFH formation also requires STAT3, but paradoxically, once formed, PD-1hi cells become unresponsive to STAT3. These findings suggest that changes in blood and germinal center cytotoxicity might be affected by changes in STAT3 signaling, or modulation of PD-1 by therapy.This work was supported by National Health and Medical Research Council (Australia) program grants APP1016953 and APP427620 (CGV, CCG, SGT, MCC)

Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia

EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distrib- uted national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia’s capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas—Tools, Data, Standards, Platforms, Compute and Training—are described in this article