Analysis of genome instability in breast cancer

Breast cancer is a heterogeneous disease, previously associated with genomic instability. Our aim was to analyze microsatellite markers in order to determine patterns and levels of instability, as well as possible correlations with histopathological parameters. Polymerase chain reaction was used to characterize microsatellite instability (MSI) and loss of heterozygosity (LOH) in 107 breast carcinomas at twelve microsatellite loci. Some of the markers were selected because of their relation to steroid hormone metabolism, which seems to be related to sporadic breast cancer risk. D5S346 and D17S250 markers showed a statistically significant frequency of MSI. LOH in D3S1611, D17S250, AR and ER-β were associated with some parameters of worse prognosis. Marker group analysis showed that CYP19, AR and ER-β were related to histological grade III, ER-negative and PR-negative cases. Our results suggest that marker group analysis may be preferred to the single marker strategy, being predictive of worst prognosis when single markers are unable to provide such information. A further evaluation of steroid metabolism genes and their association with low penetrance genes in breast cancer may be useful.     

Cloning and characterization of the phosphoglucomutase of Trypanosoma cruzi and functional complementation of a Saccharomyces cerevisiae PGM null mutant

Trypanosoma cruzi is the etiological agent of Chagas' disease, a chronic illness characterized by progressive cardiomyopathy and/or denervation of the digestive tract. The parasite surface is covered with glycoconjugates, such as mucin-type glycoproteins and glycoinositolphospholipids (GIPLs), whose glycans are rich in galactopyranose (Galp) and/or galactofuranose (Galf) residues. These molecules have been implicated in attachment of the parasite to and invasion of mammalian cells and in modulation of the host immune responses during infection. In T. cruzi, galactose (Gal) biosynthesis depends on the conversion of uridine diphosphate (UDP)-glucose (UDP-Glc) into UDP-Gal by an NAD-dependent reduction catalyzed by UDP-Gal 4-epimerase. Phosphoglucomutase (PGM) is a key enzyme in this metabolic pathway catalyzing the interconversion of Glc-6-phosphate (Glc-6-P) and Glc-1-P which is then converted into UDP-Glc. We here report the cloning of T. cruzi PGM, encoding T. cruzi PGM, and the heterologous expression of a functional enzyme in Saccharomyces cerevisiae. T. cruzi PGM is a single copy gene encoding a predicted protein sharing 61% amino acid identity with Leishmania major PGM and 43% with the yeast enzyme. The 59-trans-splicing site of PGM RNA was mapped to a region located at 18 base pairs upstream of the start codon. Expression of T. cruzi PGM in a S. cerevisiae null mutant-lacking genes encoding both isoforms of PGM (pgm1Delta/pgm2Delta) rescued the lethal phenotype induced upon cell growth on Gal as sole carbon source.     

<Emphasis Type="Italic">Scoredist</Emphasis>: A simple and robust protein sequence distance estimator

Background  

Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used.     

Improved profile HMM performance by assessment of critical algorithmic features in SAM and HMMER

Background  

Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling are not fully known. In the present work we approached this by using two of the most popular HMM packages: SAM and HMMER. The programs' abilities to build models and score sequences were compared on a SCOP/Pfam based test set. The comparison was done separately for local and global HMM scoring.     

Assessment of gastroenteric viruses frequency in a children's day care center in Rio De Janeiro, Brazil: a fifteen year study (1994-2008)

This 15-year study aimed to determine the role of the main viruses responsible for acute infantile gastroenteritis cases in a day care center in the city of Rio de Janeiro, Brazil. From 1994 to 2008, 539 fecal samples were obtained from 23 outbreaks as well as sporadic cases that occurred in this period. The detection of Rotavirus group A (RVA), norovirus (NoV) and astrovirus (AstV) was investigated both by classical and molecular methods of viral detection. RVA was detected by enzymatic immune assay and/or polyacrylamide gel electrophoresis and genotyped by using semi-nested multiplex PCR. NoV and AstV were subsequently tested by real time PCR in all RVA-negative samples and genotyped throughout genome sequencing. Three protocols for molecular characterization of NoV nucleotide sequencing were performed with the partial nucleotide sequencing of genomic regions known as region B (polymerase gen), C and D (capsid gen).Viruses were identified in 47.7% (257/539) of the cases, and the detection rates of RVA, NoV and AstV in16.1% (87/539), 33.4% (151/452), and 6.3% (19/301), respectively. Most gastroenteritis cases were reported in autumn and winter, although NoV presented a broader monthly distribution. Viruses' detection rates were significantly higher among children aged less than 24 months old, although NoV cases were detected in all age groups. RVA genotypes as G1P[8], G9P[8], G2P[4], G3P[8] and G1+G3P[8] and RVA was no longer detected after 2005. NoV characterization revealed genotypes variability circulating in the period as GI.2, GI.3, GI.8 GII.2, GII.3, GII.4, GII.4 variants 2001 and 2006b, GII.6, GII.7, GII.12 and GII.17. AstV genotypes 1, 2, 4 and 5 were also characterized. Those data demonstrate the impact of NoV infection in cases of infantile gastroenteritis, surpassing RVA infection responsible for high morbidity rate in children under five years old.