Biomedical subjects

Craig E Thomas

Publications and source records attributed to Craig E Thomas.

3 recordsLinked to original sources

PubMed2006

Integration of genomic and metabonomic data in systems biology--are we 'there' yet?

The measurement of genes, proteins and metabolites has gained increasing acceptance as a means by which to study the response of an organism to stimuli, whether they are environmental, genetic, pharmacological, toxicological, etc. Typically referred to as genomics, proteomics, and metabonomics or metabolomics, respectively, these methods as independent entities have undoubtedly provided new biological insight that was not attainable a decade ago. Not surprisingly, scientists continue to push the boundaries to extract knowledge from data, and it is currently recognized that the full realization of these technologies is limited by a lack of tools to enable data integration. Integration of these 'omic datasets, or integromics, is desirable as it links the individual biological elements together to provide a more complete understanding of dynamic biological processes. Accordingly, in addition to developing new data analysis methods to extract further details from each of the high-content datasets individually, effort is also being expended to create or improve statistical methods, databases, annotations and pathway mapping to maximize our learning. There are several recent examples, in both mammalian and non-mammalian systems, in which genes, proteins and/or metabolites have been integrated using either biology- or data-driven strategies. Herein, key findings are reviewed, gaps in our current tools and technologies are identified and illustrated, and perspective is provided on the potential of integromics in biological research.

Acetaminophen↗

PubMed2005

Pooling samples within microarray studies: a comparative analysis of rat liver transcription response to prototypical toxicants.

Combining or pooling individual samples when carrying out transcript profiling using microarrays is a fairly common means to reduce both the cost and complexity of data analysis. However, pooling does not allow for statistical comparison of changes between samples and can result in a loss of information. Because a rigorous comparison of the identified expression changes from the two approaches has not been reported, we compared the results for hepatic transcript profiles from pooled vs. individual samples. Hepatic transcript profiles from a single-dose time-course rat study in response to the prototypical toxicants clofibrate, diethylhexylphthalate, and valproic acid were evaluated. Approximately 50% more transcript expression changes were observed in the individual (statistical) analysis compared with the pooled analysis. While the majority of these changes were less than twofold in magnitude ( approximately 80%), a substantial number were greater than twofold (approximately 20%). Transcript changes unique to the individual analysis were confirmed by quantitative RT-PCR, while all the changes unique to the pooled analysis did not confirm. The individual analysis identified more hits per biological pathway than the pooled approach. Many of the transcripts identified by the individual analysis were novel findings and may contribute to a better understanding of molecular mechanisms of these compounds. Furthermore, having individual animal data provided the opportunity to correlate changes in transcript expression to phenotypes (i.e., histology) observed in toxicology studies. The two approaches were similar when clustering methods were used despite the large difference in the absolute number of transcripts changed. In summary, pooling reduced resource requirements substantially, but the individual approach enabled statistical analysis that identified more gene expression changes to evaluate mechanisms of toxicity. An individual animal approach becomes more valuable when the overall expression response is subtle and/or when associating expression data to variable phenotypic responses.

Animals↗

PubMedDate not supplied

A clinical flow cytometric biomarker strategy: validation of peripheral leukocyte phospholipidosis using Nile red.

Phospholipidosis, or intracellular accumulation of phospholipids, is caused by specific classes of xenobiotics. This phenomenon represents a challenge for risk assessment that could benefit from the use of biomarkers in the clinical development of new drug candidates. Flow cytometry, coupled with the lipophilic fluoroprobe Nile red, was correlated to histopathology, electron microscopy and inorganic phosphorus detection to validate the utility of this method for monitoring phospholipidosis in peripheral blood leukocytes. Replicate studies with model test compounds were conducted in which F344 rats were given 4 or 7 doses of either maprotiline hydrochloride, imipramine hydrochloride, tilorone dihydrochloride, amikacin hydrate or vehicle control. Transmission electron and light microscopy were used to examine peripheral blood smears and tissue samples for the presence of cytoplasmic vacuoles. Unstained and Nile red stained lysed peripheral blood samples were acquired for analysis using a FACScan flow cytometer. Inorganic phosphorus concentration in the liver was determined from extracted phospholipids and compared with flow cytometry and histological data. It was demonstrated that flow cytometric analysis of Nile red stained lysed whole blood can be used to detect drug-induced phospholipid accumulation in circulating peripheral leukocytes. Furthermore, clinically detectable leukocyte phospholipidosis may be a useful surrogate for coincident or premonitory detection of target organ phospholipidosis.

Animals↗