Biomedical subjects

Claire L Wilson

Publications and source records attributed to Claire L Wilson.

6 recordsLinked to original sources

PubMed2006

Quantitative proteomics reveals posttranslational control as a regulatory factor in primary hematopoietic stem cells.

The proteome is determined by rates of transcription, translation, and protein turnover. Definition of stem cell populations therefore requires a stem cell proteome signature. However, the limit to the number of primary cells available has restricted extensive proteomic analysis. We present a mass spectrometric method using an isobaric covalent modification of peptides for relative quantification (iTRAQ), which was employed to compare the proteomes of approximately 1 million long-term reconstituting hematopoietic stem cells (Lin(-)Sca(+)Kit(+); LSK(+)) and non-long-term reconstituting progenitor cells (Lin(-)Sca(+)Kit(-); LSK(-)), respectively. Extensive 2-dimensional liquid chromatography (LC) peptide separation prior to mass spectrometry (MS) enabled enhanced proteome coverage with relative quantification of 948 proteins. Of the 145 changes in the proteome, 54% were not seen in the transcriptome. Hypoxia-related changes in proteins controlling metabolism and oxidative protection were observed, indicating that LSK(+) cells are adapted for anaerobic environments. This approach can define proteomic changes in primary samples, thereby characterizing the molecular signature of stem cells and their progeny.

Animals↗

PubMed2005

Simpleaffy: a BioConductor package for Affymetrix Quality Control and data analysis.

UNLABELLED: Quality Control is a fundamental aspect of successful microarray data analysis. Simpleaffy is a BioConductor package that provides access to a variety of QC metrics for assessing the quality of RNA samples and of the intermediate stages of sample preparation and hybridization. Simpleaffy also offers fast implementations of popular algorithms for generating expression summaries and detection calls. AVAILABILITY: Simpleaffy can be downloaded from http://www.bioconductor.org. SUPPLEMENTARY INFORMATION: Additional information can be found on the supplementary website located at http://bioinformatics.picr.man.ac.uk.

Computational Biology↗

PubMed2004

Improved prediction for N-termini of alpha-helices using empirical information.

The prediction of the secondary structure of proteins from their amino acid sequences remains a key component of many approaches to the protein folding problem. The most abundant form of regular secondary structure in proteins is the alpha-helix, in which specific residue preferences exist at the N-terminal locations. Propensities derived from these observed amino acid frequencies in the Protein Data Bank (PDB) database correlate well with experimental free energies measured for residues at different N-terminal positions in alanine-based peptides. We report a novel method to exploit this data to improve protein secondary structure prediction through identification of the correct N-terminal sequences in alpha-helices, based on existing popular methods for secondary structure prediction. With this algorithm, the number of correctly predicted alpha-helix start positions was improved from 30% to 38%, while the overall prediction accuracy (Q3) remained the same, using cross-validated testing. Although the algorithm was developed and tested on multiple sequence alignment-based secondary structure predictions, it was also able to improve the predictions of start locations by methods that use single sequences to make their predictions. Furthermore, the residue frequencies at N-terminal positions of the improved predictions better reflect those seen at the N-terminal positions of alpha-helices in proteins. This has implications for areas such as comparative modeling, where a more accurate prediction of the N-terminal regions of alpha-helices should benefit attempts to model adjacent loop regions. The algorithm is available as a Web tool, located at http://rocky.bms.umist.ac.uk/elephant.

Databases, Protein↗

PubMed2004

Amplification protocols introduce systematic but reproducible errors into gene expression studies.

The desire to perform microarray experiments with small starting amounts of RNA has led to the development of a variety of protocols for preparing and amplifying mRNA. This has consequences not only for the standardization of experimental design, but also for reproducibility and comparability between experiments. Here we investigate the differences between the Affymetrix standard and small sample protocols and address the data analysis issues that arise when comparing samples and experiments that have been processed in different ways. We show that data generated on the same platform using different protocols are not directly comparable. Further, protocols introduce systematic biases that can be largely accounted for by using the correct data analysis techniques.

Data Interpretation, Statistical↗

PubMed2002

Extracellular peptidases of imaginal discs of Drosophila melanogaster.

The imaginal discs of Drosophila melanogaster give rise to the adult epidermis during metamorphosis. During this developmental period several peptidase genes are expressed in disc cells, but there is a paucity of biochemical information regarding substrate specificity. We have used peptides and peptidyl 7-amino-4-methylcoumarin (AMC) substrates to detect several peptidases either positioned on the surface of wing discs or secreted by the imaginal cells. Using [Leu(5)]enkephalin as a substrate, a captopril sensitive dipeptidyl carboxypeptidase (angiotensin I-converting enzyme) and an amastatin-sensitive aminopeptidase were detected as prominent activities associated with intact discs. The formation of [Leu(5)]enkephalin-derived Phe was attributed to the concerted action of the D. melanogaster angiotensin I-converting enzyme (Ance) and a dipeptidase. The disc Ance also showed endopeptidic activity towards locust tachykinin-1 (LomTK-I) by cleaving the Gly-Val peptide bond, but this enzyme was not the sole endopeptidase activity associated with discs. Complete inhibition of the endopeptidic hydrolysis of the LomTK-1 by a disc homogenate required a combination of captopril and the neprilysin inhibitor, phosphoramidon, providing biochemical evidence for a neprilysin-like peptidase, in addition to Ance, in imaginal discs of D. melanogaster. Peptidyl AMC substrates for furin, prohormone convertase and tryptase provided evidence for trypsin-like serine endopeptidases in addition to the metalloendopeptidases. We conclude that imaginal discs are endowed with a variety of peptidases from different families that together are capable of hydrolyzing a broad range of peptides and proteins. Some of these peptidases might be responsible for the metabolic activation/inactivation of signaling peptides, as well as being involved in the production of dipeptides and free amino acids required for protein synthesis and osmotic balance during adult morphogenesis.

Animals↗

PubMed2002

A critical assessment of the secondary structure alpha-helices and their termini in proteins.

Secondary structure prediction from amino acid sequence is a key component of protein structure prediction, with current accuracy at approximately 75%. We analysed two state-of-the-art secondary structure prediction methods, PHD and JPRED, comparing predictions with secondary structure assigned by the algorithms DSSP and STRIDE. The specific focus of our study was alpha-helix N-termini, as empirical free energy scales are available for residue preferences at N-terminal positions. Although these prediction methods perform well in general at predicting the alpha-helical locations and length distributions in proteins, they perform less well at predicting the correct helical termini. For example, although most predicted alpha-helices overlap a real alpha-helix (with relatively few completely missed or extra predicted helices), only one-third of JPRED and PHD predictions correctly identify the N-terminus. Analysis of neighbouring N-terminal sequences to predicted helical N-termini shows that the correct N-terminus is often within one or two residues. More importantly, the true N-terminal motif is, on average, more favourable as judged by our experimentally measured free energies. This suggests a simple, but powerful, strategy to improve secondary structure prediction using empirically derived energies to adjust the predicted output to a more favourable N-terminal sequence.

Algorithms↗