Biomedical subjects

Donatella Sarti

Publications and source records attributed to Donatella Sarti.

4 recordsLinked to original sources

PubMed2005

Over-expression of hTERT in CHO K1 results in decreased apoptosis and reduced serum dependency.

The enzyme telomerase plays a crucial role in cellular proliferation. By adding hexameric repeats to the chromosome ends, it prevents telomeric loss and, thus entry into senescence of limited life span cells. It is unclear, however, what would be the effect of over-expressing telomerase in an immortalised cell line, characterised by unlimited life span and high levels of apoptosis under sub-optimal growth conditions. In order to address this question, we have transfected the immortal cell line CHO K1 with the human telomerase reverse transcriptase (hTERT) catalytic subunit. Differences in the growth profile and apoptosis levels between the cells over-expressing hTERT (Telo) and the cells containing mock vector were found under standard growth conditions. Similarly, the Telo cells showed lower levels of apoptosis, greater attachment tendency and higher viable cell density under serum-deprived conditions compared to the control cell line, suggesting a major role for hTERT over-expression in stressed cultures. Using a mouse cDNA microarray, the collagen type III and V genes were shown to have at least a 10-fold higher expression in the Telo cells than the control cells, suggesting a role of hTERT in the cell attachment pathways.

Animals↗

PubMed2005

Analysis of host response to bacterial infection using error model based gene expression microarray experiments.

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples.

Bacterial Infections↗

PubMed2004

Regulators encoded in the Escherichia coli type III secretion system 2 gene cluster influence expression of genes within the locus for enterocyte effacement in enterohemorrhagic E. coli O157:H7.

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 subverts host cells through a type III secretion system encoded by the locus for enterocyte effacement (LEE). Genome sequencing of this pathotype revealed the existence of a gene cluster encoding components of a second cryptic type III secretion system, E. coli type III secretion system 2 (ETT2). Recently, we showed that the ETT2 gene cluster is present in whole or in part in the majority of E. coli strains but is unable to encode a functional secretion system in most strains, including EHEC O157:H7. However, here we show that mutational inhibition of two regulatory genes (ECs3720 or etrA and ECs3734 or eivF) from the ETT2 cluster in EHEC O157:H7 leads to greatly increased secretion of proteins encoded by the LEE and to increased adhesion to human intestinal cells. Studies in which transcriptional fusions and microarrays were used indicated that EtrA and EivF exert profound negative effects on gene transcription within the LEE. Consistent with these observations, expression of these regulators in an EHEC O26:H- strain led to suppression of protein secretion under LEE-inducing conditions. These findings provide fresh examples of the influence of mobile genetic elements on regulation of the LEE and of cross talk between type III secretion system gene clusters. In addition, they provide a cautionary tale because they show that the effects of regulatory genes can outlive widespread decay of other genes in a functionally coherent gene cluster, a phenomenon that we have named the "Cheshire cat effect." It also seems likely that variations in the ETT2 regulator repertoire might account for strain-to-strain variation in secretion of LEE-encoded proteins.

Bacterial Adhesion↗

PubMed2004

Making sense of molecular signatures in the immune system.

The development of Functional Genomics technologies has opened new avenues to investigate the complexity of the immune system. Microarray technology has been particularly successful because of its relatively low cost and high genome coverage. Consequently to our ability to monitor the expression of a significant proportion of an organism genome, our understanding of the molecular dynamics behind cell differentiation and cell response has greatly improved. Molecular signatures associated to immune cells have provided important tools to investigate the molecular basis of diseases and have been often associated to diagnostic and prognostic markers. The availability of such large collection of data has stimulated the application of complex machine learning techniques in the attempt to link molecular signatures and cell physiology. Here we review the most recent developments in the analysis of molecular signatures in the immune system.

Animals↗