Biomedical subjects

Natasha A Karp

Publications and source records attributed to Natasha A Karp.

6 recordsLinked to original sources

PubMed2005

Analysis of calibration methodologies for solvent effects in drug discovery studies using evanescent wave biosensors.

Recent improvements in sensitivity have enabled direct binding studies of small molecules with evanescent wave biosensors, which monitor binding by measuring refractive index changes close to the sensing surface. The universal solvent for small molecules, dimethylsulfoxide has a high refractive index; consequently, on ligate addition a large non-specific solvent effect is seen which can mask the specific signal. It has been previously noted that different sensor surfaces can respond differently to the same buffer change. The difference is proposed to arise from differences in buffer space and contraction and swelling of the surface hydrogel. Within this paper, a number of calibration approaches are investigated and tested using warfarin binding to human serum albumin as a model system. A number of recommendations are made for accurate referencing for non-specific effects. Changes to the ionic strength of the running buffer had little effect, whilst changes to the charge density of the carboxylmethyl dextran significantly affected how well the control surface reflects the non-specific signal. An amended 'calibration method' can be used, however, it is an additional complex step that was found to overcorrect in the presence of non-specific binding. Matching immobilisation levels between control and active surface significantly reduces solvent differences allowing accurate correction providing solvent compositional changes are minimised in experimental design. Under these circumstances, the traditional method of simple subtraction of the control from the active response is the most appropriate method of correction.

Biosensing Techniques↗

PubMed2005

Application of partial least squares discriminant analysis to two-dimensional difference gel studies in expression proteomics.

Two-dimensional difference gel electrophoresis (DIGE) is a tool for measuring changes in protein expression between samples involving pre-electrophoretic labeling ith cyanine dyes. In multi-gel experiments, univariate statistical tests have been used to identify differential expression between sample types by looking for significant changes in spot volume. Multivariate statistical tests, which look for correlated changes between sample types, provide an alternate approach for identifying spots with differential expression. Partial least squares-discriminant analysis (PLS-DA), a multivariate statistical approach, was combined with an iterative threshold process to identify which protein spots had the greatest contribution to the model, and compared to univariate test for three datasets. This included one dataset where no biological difference was expected. The novel multivariate approach, detailed here, represents a method to complement the univariate approach in identification of differentially expressed protein spots. This new approach has the advantages of reduced risk of false-positives and the identification of spots that are significantly altered in terms of correlated expression rather than absolute expression values.

Analysis of Variance↗

PubMed2005

Maximising sensitivity for detecting changes in protein expression: experimental design using minimal CyDyes.

DIGE is a powerful tool for measuring changes in protein expression between samples. Here we assess the assumptions of normality and heterogeneity of variance that underlie the univariate statistical tests routinely used to detect proteins with expression changes. Furthermore, the technical variance experienced in a multigel experiment is assessed here and found to be reproducible within- and across-sample types. Utilising the technical variance measured, a power study is completed for several "typical" fold changes in expression commonly used as thresholds by researchers. Based on this study using DeCyder, guidance is given on the number of gel replicates that are needed for the experiment to have sufficient sensitivity to detect expression changes. A two-dye system based on utilising just Cy3 and Cy5 was found to be more reproducible than the three-dye system. A power and cost-benefit analysis performed here suggests that the traditional three-dye system would use fewer resources in studies where multiple samples are compared. Technical variance was shown to encompass both experimental and analytical noise and thus is dependent on the analytical software utilised. Data is provided as a resource to the community to assess alternative software and upgrades.

Animals↗

PubMed2004

DNA microarray normalization methods can remove bias from differential protein expression analysis of 2D difference gel electrophoresis results.

MOTIVATION: Two-dimensional Difference Gel Electrophoresis (DIGE) measures expression differences for thousands of proteins in parallel. In contrast to DNA microarray analysis, however, there have been few systematic studies on the validity of differential protein expression analysis, and the effects of normalization methods have not yet been investigated. To address this need, we assessed a series of same-same comparisons, evaluating how random experimental variance influenced differential expression analysis. RESULTS: The strong fluctuations observed were reflected in large discrepancies between the distributions of the spot intensities for different gels. Correct normalization for pooling of multiple gels for analysis is, therefore, essential. We show that both dye-specific background levels and the differences in scale of the spot intensity distributions must be accounted for. A variance stabilizing transform that had been developed for DNA microarray analysis combined with a robust Z-score allowed the determination of gel-independent signal thresholds based on the empirical distributions from same-same comparisons. In contrast, similar thresholds holding up to cross-validation could not be proposed for data normalized using methods established in the field of proteomics. AVAILABILITY: Software is available on request from the authors. SUPPLEMENTARY INFORMATION: There is supplementary material available online at http://www.flychip.org.uk/kreil/pub/2dgels/

Algorithms↗

PubMed2004

Determining a significant change in protein expression with DeCyder during a pair-wise comparison using two-dimensional difference gel electrophoresis.

Two-dimensional difference gel electrophoresis (DIGE) is a tool for measuring changes in protein expression between samples involving pre-electrophoretic labeling with cyanine dyes. Here we assess a common method to analyze DIGE data using the DeCyder software system. Experimental error was studied by a series of same sample comparisons. Aliquots of sample were labeled with N-hydroxyl succinimidyl ester-derivatives of Cy2, Cy3, and Cy5 dyes and run together on one gel. This allowed assessment of how experimental error influenced differential expression analysis. Bias in the log volume ratios was observed, which could be explained by differences in dye background. Further complications are caused by significant gel-to-gel variation in the spot volume ratio distributions. Using DeCyder alone results in an inability to define ratio thresholds for 90 or 95% confidence. An alternative normalization method was thus applied which resulted in improved data distribution and allowed greater sensitivity in analysis. When combined with a standardizing function, this allowed gel-independent thresholds for 90% confidence. The new approach, detailed here, represents a method to greatly improve the success of DIGE data analysis.

Bacterial Proteins↗

PubMedDate not supplied

Impact of replicate types on proteomic expression analysis.

In expression proteomics, the samples utilized within an experimental design may include technical, biological, or pooled replicates. This manuscript discusses various experimental designs and the conclusions that can be drawn from them. Specifically, it addresses the impact of mixing replicate types on the statistical analysis which can be performed. This study focuses on difference gel electrophoresis (DiGE), but the issues are equally applicable to all quantitative methodologies assessing relative changes in protein expression.

Analysis of Variance↗