Biomedical subjects

Carlotta De Filippo

Publications and source records attributed to Carlotta De Filippo.

5 recordsLinked to original sources

PubMed2005

Red wine polyphenols influence carcinogenesis, intestinal microflora, oxidative damage and gene expression profiles of colonic mucosa in F344 rats.

Polyphenols from tea and other beverages such as red wine have been regarded with interest as possible chemopreventive agents against cancer. Here we report that red wine polyphenols (50 mg/kg) administered with the diet to F344 rats for 16 weeks inhibited colon carcinogenesis induced by azoxymethane (AOM, 7.4 mg/kg, total dose 74 mg/kg) or dimethylhydrazine (DMH, 30 mg/kg, total dose, 300 mg/kg). Polyphenol-treated animals had a consistently lower tumour yield compared to controls. In polyphenol-treated rats, the main bacterial strains in the faeces at sacrifice were Bacteroides, Lactobacillus and Bifidobacterium spp., whereas microorganisms predominantly identified in control-fed rats were Bacteroides, Clostridium and Propionibacterium spp. Wine polyphenols (57 mg/kg for 10 days, by gavage), administered to rats not treated with carcinogens, produced a significant decrease in the basal level of DNA oxidative damage of the colon mucosa as measured with the comet assay (average pyrimidine oxidation was reduced by 62% and purine oxidation by 57%, p<0.05). To further explore the molecular effects of wine polyphenols we used the microarray technology to study gene expression profiles: rats were treated with 50 mg/kg wine polyphenols for 14 days, mixed in the diet. Global expression analysis of 5707 genes revealed an extensive down-regulation of genes involved in a wide range of physiological functions, such as metabolism, transport, signal transduction and intercellular signalling. By analysing metabolic pathways with the GenMAPP software program we observed that two major regulatory pathways were down-regulated in the colon mucosa of polyphenols-treated rats: inflammatory response and steroid metabolism. We also found a down-regulation of many genes regulating cell surface antigens, metabolic enzymes and cellular response to oxidative stress. In conclusion, reduction of oxidative damage, modulation of colonic flora and variation in gene expression may all concur in the modulation of intestinal function and carcinogenesis by wine polyphenols.

1,2-Dimethylhydrazine↗

PubMed2005

Large-scale genetic variation of the symbiosis-required megaplasmid pSymA revealed by comparative genomic analysis of Sinorhizobium meliloti natural strains.

BACKGROUND: Sinorhizobium meliloti is a soil bacterium that forms nitrogen-fixing nodules on the roots of leguminous plants such as alfalfa (Medicago sativa). This species occupies different ecological niches, being present as a free-living soil bacterium and as a symbiont of plant root nodules. The genome of the type strain Rm 1021 contains one chromosome and two megaplasmids for a total genome size of 6 Mb. We applied comparative genomic hybridisation (CGH) on an oligonucleotide microarrays to estimate genetic variation at the genomic level in four natural strains, two isolated from Italian agricultural soil and two from desert soil in the Aral Sea region. RESULTS: From 4.6 to 5.7 percent of the genes showed a pattern of hybridisation concordant with deletion, nucleotide divergence or ORF duplication when compared to the type strain Rm 1021. A large number of these polymorphisms were confirmed by sequencing and Southern blot. A statistically significant fraction of these variable genes was found on the pSymA megaplasmid and grouped in clusters. These variable genes were found to be mainly transposases or genes with unknown function. CONCLUSION: The obtained results allow to conclude that the symbiosis-required megaplasmid pSymA can be considered the major hot-spot for intra-specific differentiation in S. meliloti.

Blotting, Southern↗

PubMed2005

Bioinformatic methods for integrating whole-genome expression results into cellular networks.

Extracting a comprehensive overview from the huge amount of information arising from whole-genome analyses is a significant challenge. This review critically surveys the state of the art methods that are used to connect information from functional genomic studies to biological function. Cluster analysis methods for inferring the correlation between genes are discussed, as are the methods for integrating gene expression information with existing information on biological pathways and the methods that combine cluster analysis with biological information to reconstruct novel biological networks.

Cluster Analysis↗

PubMed2005

Defining best practice for microarray analyses in nutrigenomic studies.

Microarrays represent a powerful tool for studies of diet-gene interactions. Their use is, however, associated with a number of technical challenges and potential pitfalls. The cost of microarrays continues to drop but is still comparatively high. This, coupled with the complex logistical issues associated with performing nutritional microarray studies, often means that compromises have to be made in the number and type of samples analysed. Additionally, technical variations between array platforms and analytical procedures will almost inevitably lead to differences in the transcriptional responses observed. Consequently, conflicting data may be produced, important effects may be missed and/or false leads generated (e.g. apparent patterns of differential gene regulation that ultimately prove to be incorrect or not significant). This is likely to be particularly true in the field of nutrition, in which we expect that many dietary bioactive agents at nutritionally relevant concentrations will elicit subtle changes in gene transcription that may be critically important in biological terms but will be difficult to detect reliably. Thus, great care should always be taken in designing and executing microarray studies. This article seeks to provide an overview of both the main practical and theoretical considerations in microarray use that represent potential sources of technical variation and error. Wherever possible, recommendations are made on what we propose to be the best approach. The overall aims are to provide a basic framework of advice for researchers who are new to the use of microarrays and to promote a discussion of standardisation and best practice in the field.

Animals↗

PubMed2005

Extremely low-frequency electromagnetic fields do not affect DNA damage and gene expression profiles of yeast and human lymphocytes.

We studied the effects of extremely low-frequency (50 Hz) electromagnetic fields (EMFs) on peripheral human blood lymphocytes and DBY747 Saccharomyces cerevisiae. Graded exposure to 50 Hz magnetic flux density was obtained with a Helmholtz coil system set at 1, 10 or 100 microT for 18 h. The effects of EMFs on DNA damage were studied with the single-cell gel electrophoresis assay (comet assay) in lymphocytes. Gene expression profiles of EMF-exposed human and yeast cells were evaluated with DNA microarrays containing 13,971 and 6,212 oligonucleotides, respectively. After exposure to the EMF, we did not observe an increase in the amount of strand breaks or oxidated DNA bases relative to controls or a variation in gene expression profiles. The results suggest that extremely low-frequency EMFs do not induce DNA damage or affect gene expression in these two different eukaryotic cell systems.

Blood Proteins↗