Biomedical subjects

Laura Selway

Publications and source records attributed to Laura Selway.

3 recordsLinked to original sources

PubMed2005

Proteomic changes associated with inactivation of the Candida glabrata ACE2 virulence-moderating gene.

Inactivation of the gene encoding the transcriptional activator Ace2 in the fungal pathogen Candida glabrata results in an almost 200-fold increase in virulence characterised by acute mortality and a massive over-stimulation of the pro-inflammatory arm of the innate immune system. In this study we have adopted a proteomics approach to identify cellular functions regulated by C. glabrata Ace2 that might contribute to this increase in virulence. A two-dimensional polyacrylamide gel electrophoresis map of the C. glabrata proteome was constructed. We identified a total of 123 proteins, 61 of which displayed reproducible and statistically significant alterations in their levels following inactivation of ACE2. Of these, the levels of 32 proteins were elevated, and 29 were reduced in ace2 cells. These data show that Ace2 influences metabolism, protein synthesis, folding and targeting, and aspects of cell growth and polarisation. Some of these functions are likely to contribute to the effects of Ace2 upon the virulence of C. glabrata.

Candida glabrata↗

PubMed2004

Proteomic response to amino acid starvation in Candida albicans and Saccharomyces cerevisiae.

Saccharomyces cerevisiae activates general amino acid control (GCN) in response to amino acid starvation. Some aspects of this response are known to be conserved in other fungi including Candida albicans, the major systemic fungal pathogen of humans. Here, we describe a proteomic comparison of the GCN responses in S. cerevisiae and C. albicans. We have used high-resolution two-dimensional (2-D) gel electrophoresis and peptide mass fingerprinting to develop a 2-D protein map of C. albicans. A total of 391 protein spots, representing 316 open reading frames, were identified. Fifty-five C. albicans and 65 S. cerevisiae proteins were identified that responded reproducibly to 3-aminotriazole (3AT) in a Gcn4p-dependent fashion. The changes in the S. cerevisiae proteome correlated with the response in the S. cerevisiae transcript profile to 3AT treatment (rank correlation coefficient = 0.59; Natarajan et al., Molec. Cell. Biol. 2001, 21, 4347-4368). Significant aspects of the GCN response were conserved in C. albicans and S. cerevisiae. In both fungi, amino acid biosynthetic enzymes on multiple metabolic pathways were induced by 3AT in a Gcn4p-dependent fashion. Carbon metabolism functions were also induced. However, subtle differences were observed between these fungi. For example, purine biosynthetic enzymes were induced in S. cerevisiae, but were not significantly induced in C. albicans. These differences presumably reflect the contrasting niches of these relatively benign and pathogenic yeasts, respectively.

Amino Acids↗

PubMed2003

A systematic approach to modeling, capturing, and disseminating proteomics experimental data.

Both the generation and the analysis of proteome data are becoming increasingly widespread, and the field of proteomics is moving incrementally toward high-throughput approaches. Techniques are also increasing in complexity as the relevant technologies evolve. A standard representation of both the methods used and the data generated in proteomics experiments, analogous to that of the MIAME (minimum information about a microarray experiment) guidelines for transcriptomics, and the associated MAGE (microarray gene expression) object model and XML (extensible markup language) implementation, has yet to emerge. This hinders the handling, exchange, and dissemination of proteomics data. Here, we present a UML (unified modeling language) approach to proteomics experimental data, describe XML and SQL (structured query language) implementations of that model, and discuss capture, storage, and dissemination strategies. These make explicit what data might be most usefully captured about proteomics experiments and provide complementary routes toward the implementation of a proteome repository.

Database Management Systems↗