Biomedical subjects

David P Kreil

Publications and source records attributed to David P Kreil.

11 recordsLinked to original sources

PubMed2006

Expansins are involved in the formation of nematode-induced syncytia in roots of Arabidopsis thaliana.

Parasitism of the cyst nematode Heterodera schachtii is characterized by the formation of syncytial feeding structures in the host root. Syncytia are formed by the fusion of root cells, accompanied by local cell wall degradation, fusion of protoplasts and hypertrophy. Expansins are cell wall-loosening proteins involved in growth and cell wall disassembly. In this study, we analysed whether members of the expansin gene family are specifically and developmentally regulated during syncytium formation in the roots of Arabidopsis thaliana. We used PCR to screen a cDNA library of 5-7-day-old syncytia for expansin transcripts with primers differentiating between 26 alpha- and three beta-expansin cDNAs. AtEXPA1, AtEXPA3, AtEXPA4, AtEXPA6, AtEXPA8, AtEXPA10, AtEXPA15, AtEXPA16, AtEXPA20 and AtEXPB3 could be amplified from the library. In a semi-quantitative RT-PCR and a Genechip analysis AtEXPA3, AtEXPA6, AtEXPA8, AtEXPA10 and AtEXPA16 were found to be upregulated specifically in syncytia, but not to be transcribed in surrounding root tissue. Histological analyses were performed with the aid of promoter::GUS lines and in situ RT-PCR. Results from both approaches supported the specific expression pattern. Among the specifically expressed genes, AtEXPA3 and AtEXPA16 turned out to be of special interest as they are shoot-specific in uninfected plants. We conclude that syncytium formation involves the specific regulation of expansin genes, indicating that the encoded expansins take part in cell growth and cell wall disassembly during syncytium formation.

Animals↗

PubMed2006

Microarray oligonucleotide probes.

Oligonucleotide probes are increasingly the method of choice for many modern DNA microarray applications. They provide higher target specificity, probe selection gives improved experimental control of hybridization properties, and targeting of specific gene subsequences allows better discrimination of highly similar targets such as splice variants or gene families. Only recently has there been substantial progress in dealing with the complexities of probe set design and probe-specific signal interpretation. After a discussion of advantages and disadvantages of oligonucleotide probes in comparison to amplicons, this chapter focuses on recent advances and remaining key challenges in probe design and computational data analysis for spotted and in situ-synthesized oligonucleotide microarray technologies. Both experimental questions and computational aspects are addressed. Experimental issues discussed include the choice of an optimal number of probes per target and probe lengths and their influence on bias and random measurement noise, effects of different probe or substrate modifications, and laboratory protocols on signal specificity and sensitivity. Computational topics include practical considerations and a case study in probe sequence design, the exploitation of probing multiple target regions, and the modeling of probe sequence-specific signals. The current state of the art of the field is examined, and principled thermodynamic probe design criteria are proposed that are based on the free energy of the probe-target complex at the hybridization temperature rather than its melting temperature. Finally, this chapter notes and discusses an emerging trend in recent computational work toward a focus on signal interpretation rather than probe sequence design.

Animals↗

PubMed2005

Atypical RNA polymerase subunits required for RNA-directed DNA methylation.

RNA-directed DNA methylation, one of several RNA interference-mediated pathways in the nucleus, has been documented in plants and in human cells. Despite progress in identifying the DNA methyltransferases, histone-modifying enzymes and RNA interference proteins needed for RNA-directed DNA methylation, the mechanism remains incompletely understood. We screened for mutants defective in RNA-directed DNA methylation and silencing of a transgene promoter in Arabidopsis thaliana and identified three drd complementation groups. DRD1 is a SNF2-like protein required for RNA-directed de novo methylation. We report here that DRD2 and DRD3 correspond to the second-largest subunit and largest subunit, respectively, of a fourth class of DNA-dependent RNA polymerase (polymerase IV) that is unique to plants. DRD3 is a functionally diversified homolog of NRPD1a or SDE4, identified in a separate screen for mutants defective in post-transcriptional gene silencing. The identical DNA methylation patterns observed in all three drd mutants suggest that DRD proteins cooperate to create a substrate for RNA-directed de novo methylation.

Arabidopsis↗

PubMed2005

Conservation of unique cell-surface CD antigen mosaics in HIV-1-infected individuals.

Cluster of differentiation (CD) antigens are expressed on cells of myeloid and lymphoid lineages. As most disease processes involve immune system activation or suppression, these antigens offer unique opportunities for monitoring host responses. Immunophenotyping using limited numbers of CD antigens enables differentiation states of immune system cells to be determined. Extended phenotyping involving parallel measurement of multiple CD antigens may help identify expression pattern signatures associated with specific disease states. To explore this possibility we have made a CD monoclonal antibody array and scanner, enabling the parallel immunophenotyping of leukocyte cell suspensions in a single and rapid analysis. To demonstrate this approach, we used the specific example of patients infected with human immunodeficiency virus type-1 (HIV-1). An invariant HIV-induced CD antigen signature has been defined that is both robust and independent of clinical outcome, composed of a unique profile of CD antigen expression levels that are both increased and decreased relative to internal controls. The results indicate that HIV-induced changes in CD antigen expression are disease specific and independent of outcome. Their invariant nature indicates an irreversible component to retroviral infection and suggests the utility of CD antigen expression patterns in other disease settings.

Antibodies, Monoclonal↗

PubMed2005

Robotic spotting of cDNA and oligonucleotide microarrays.

DNA microarrays are a uniquely efficient method for simultaneously assessing the expression levels of thousands of genes. Owing to their flexibility and value, mechanically spotted microarrays remain the most popular platform. Here, we review recent technological advances with a focus on spotted arrays. Robotic spotting still poses numerous technical challenges. To reduce artefacts, many laboratories have recently investigated ways of improving the spotting process. We compare alternative options and discuss implications for next-generation systems. Together with modern approaches to data analysis, such developments bring greatly improved reliability to individual microarray experiments. Advancing towards the ultimate goal of delivering calibrated, truly quantitative gene-expression measurements on a genomic scale, microarray technology remains at the forefront of post-genomic systems biology.

DNA Probes↗

PubMed2005

There is no silver bullet--a guide to low-level data transforms and normalisation methods for microarray data.

To overcome random experimental variation, even for simple screens, data from multiple microarrays have to be combined. There are, however, systematic differences between arrays, and any bias remaining after experimental measures to ensure consistency needs to be controlled for. It is often difficult to make the right choice of data transformation and normalisation methods to achieve this end. In this tutorial paper we review the problem and a selection of solutions, explaining the basic principles behind normalisation procedures and providing guidance for their application.

Algorithms↗

PubMed2004

Independent component analysis of microarray data in the study of endometrial cancer.

Gene microarray technology is highly effective in screening for differential gene expression and has hence become a popular tool in the molecular investigation of cancer. When applied to tumours, molecular characteristics may be correlated with clinical features such as response to chemotherapy. Exploitation of the huge amount of data generated by microarrays is difficult, however, and constitutes a major challenge in the advancement of this methodology. Independent component analysis (ICA), a modern statistical method, allows us to better understand data in such complex and noisy measurement environments. The technique has the potential to significantly increase the quality of the resulting data and improve the biological validity of subsequent analysis. We performed microarray experiments on 31 postmenopausal endometrial biopsies, comprising 11 benign and 20 malignant samples. We compared ICA to the established methods of principal component analysis (PCA), Cyber-T, and SAM. We show that ICA generated patterns that clearly characterized the malignant samples studied, in contrast to PCA. Moreover, ICA improved the biological validity of the genes identified as differentially expressed in endometrial carcinoma, compared to those found by Cyber-T and SAM. In particular, several genes involved in lipid metabolism that are differentially expressed in endometrial carcinoma were only found using this method. This report highlights the potential of ICA in the analysis of microarray data.

Endometrial Neoplasms↗

PubMed2004

Involvement of putative SNF2 chromatin remodeling protein DRD1 in RNA-directed DNA methylation.

In plants, the mechanism by which RNA can induce de novo cytosine methylation of homologous DNA is poorly understood. Cytosines in all sequence contexts become modified in response to RNA signals. Recent work has implicated the de novo DNA methyltransferases (DMTases), DRM1 and DRM2, in establishing RNA-directed methylation of the constitutive nopaline synthase promoter, as well as the DMTase MET1 and the putative histone deacetylase HDA6 in maintaining or enhancing CpG methylation induced by RNA. Despite the identification of enzymes that catalyze epigenetic modifications in response to RNA signals, it is unclear how RNA targets DNA for methylation. A screen for mutants defective in RNA-directed DNA methylation identified a novel putative chromatin-remodeling protein, DRD1. This protein belongs to a previously undefined, plant-specific subfamily of SWI2/SNF2-like proteins most similar to the RAD54/ATRX subfamily. In drd1 mutants, RNA-induced non-CpG methylation is almost eliminated at a target promoter, resulting in reactivation, whereas methylation of centromeric and rDNA repeats is unaffected. Thus, unlike the SNF2-like proteins DDM1/Lsh1 and ATRX, which regulate methylation of repetitive sequences, DRD1 is not a global regulator of cytosine methylation. DRD1 is the first SNF2-like protein implicated in an RNA-guided, epigenetic modification of the genome.

Amino Acid Sequence↗

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↗

PubMed2003

Comparison of sequence masking algorithms and the detection of biased protein sequence regions.

MOTIVATION: Separation of protein sequence regions according to their local information complexity and subsequent masking of low complexity regions has greatly enhanced the reliability of function prediction by sequence similarity. Comparisons with alternative methods that focus on compositional sequence bias rather than information complexity measures have shown that removal of compositional bias yields at least as sensitive and much more specific results. Besides the application of sequence masking algorithms to sequence similarity searches, the study of the masked regions themselves is of great interest. Traditionally, however, these have been neglected despite evidence of their functional relevance. RESULTS: Here we demonstrate that compositional bias seems to be a more effective measure for the detection of biologically meaningful signals. Typical results on proteins are compared to results for sequences that have been randomized in various ways, conserving composition and local correlations for individual proteins or the entire set. It is remarkable that low-complexity regions have the same form of distribution in proteins as in randomized sequences, and that the signal from randomized sequences with conserved local correlations and amino acid composition almost matches the signal from proteins. This is not the case for sequence bias, which hence seems to be a genuinely biological phenomenon in contrast to patches of low complexity.

Aeropyrum↗