Relationship of the methylenetetrahydrofolate reductase C677T polymorphism with microsatellite instability and promoter hypermethylation in sporadic colorectal cancer

The methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism is associated with the expression of a thermolabile enzyme with decreased activity that influences the pool of methyl-donor molecules. Several studies have reported an association between C677T polymorphism and susceptibility to colorectal cancer (CRC). Considering that methylation abnormalities appear to be important for the pathogenesis of CRC, we examined the correlation between the genotype of the MTHFR C677T polymorphism, hypermethylation of the promoter region of five relevant genes (DAPK, MGMT, hMLH1, p16(INK4a), and p14(ARF)), and microsatellite instability, in 106 patients with primary CRCs in Brazil. We did not find significant differences in the genotypic frequencies of the MTHFR C677T polymorphism when one or more loci were hypermethylated. However, we did find a significant excess of 677TT individuals among patients with CRC who had microsatellite instability. This strong association was independent of the methylation status of hMLH1 and of the biogeographical genomic ancestry of the patients. Although the mechanism responsible for the link between the C677T polymorphism and microsatellite instability was not apparent, this finding may provide a clue towards a better understanding of the pathogenesis of microsatellite instability in human colorectal cancer.

Mining microorganism EST databases in the quest for new proteins

Microorganisms with large genomes are commonly the subjects of single-round partial sequencing of cDNA, generating expressed sequence tags (ESTs). Usually there is a great distance between gene discovery by EST projects and submission of amino acid sequences to public databases. We analyzed the relationship between available ESTs and protein sequences and used the sequences available in the secondary database, clusters of orthologous groups (COG), to investigate ESTs from eight microorganisms of medical and/or economic relevance, selecting for candidate ESTs that may be further pursued for protein characterization. The organisms chosen were Paracoccidioides brasiliensis, Dictyostelium discoideum, Fusarium graminearum, Plasmodium yoelii, Magnaporthe grisea, Emericella nidulans, Chlamydomonas reinhardtii and Eimeria tenella, which have more than 10,000 ESTs available in dbEST. A total of 77,114 protein sequences from COG were used, corresponding to 3,201 distinct genes. At least 212 of these were capable of identifying candidate ESTs for further studies (E. tenella). This number was extended to over 700 candidate ESTs (C. reinhardtii, F. graminearum). Remarkably, even the organism that presents the highest number of ESTs corresponding to known proteins, P. yoelii, showed a considerable number of candidate ESTs for protein characterization (477). For some organisms, such as P. brasiliensis, M. grisea and F. graminearum, bioinformatics has allowed for automatic annotation of up to about 20 of the ESTs that did not correspond to proteins already characterized in the organism. In conclusion, 4093 ESTs from these eight organisms that are homologous to COG genes were selected as candidates for protein characterization