Low “penetrance” of phylogenetic knowledge in mitochondrial disease studies

An up-to-date view of the worldwide mitochondrial DNA (mtDNA) phylogeny together with an evaluation of the conservation of each site is a reliable tool for detecting errors in mtDNA studies and assessing the functional importance of alleged pathogenic mutations. However, most of the published studies on mitochondrial diseases make very little use of the phylogenetic knowledge that is currently available. This drawback has two inadvertent consequences: first, there is no sufficient a posteriori quality assessment of complete mtDNA sequencing efforts; and second, no feedback is provided for the general mtDNA database when apparently new mtDNA lineages are discovered. We demonstrate, by way of example, these issues by reanalysing three mtDNA sequencing attempts, two from Europe and another one from East Asia. To further validate our phylogenetic deductions, we completely sequenced two mtDNAs from healthy subjects that nearly match the mtDNAs of two patients, whose sequences gave problematic results. (c) 2005 Elsevier Inc. All rights reserved.

Phantom mutation hotspots in human mitochondrial DNA

Phantom mutations are systematic artifacts generated in the course of the sequencing process. Contra common belief these artificial mutations are nearly ubiquitous in sequencing results, albeit at frequencies that may vary dramatically. The amount of artifacts depends not only on the sort of automated sequencer and sequencing chemistry employed, but also on other lab-specific factors. An experimental study executed on four samples under various combinations of sequencing conditions revealed a number of phantom mutations occurring at the same sites of mitochondrial DNA (mtDNA) repeatedly. To confirm these and identify further hotspots for artifacts, > 5000 mtDNA electropherograms were screened for artificial patterns. Further, > 30000 published hypervariable segment 1 sequences were compared at potential hotspots for phantom mutations, especially for variation at positions 16085 and 16197. Resequencing of several samples confirmed the artificial nature of these and other polymorphisms in the original publications. Single-strand sequencing, as typically executed in medical and anthropological studies, is thus highly vulnerable to this kind of artifacts. In particular, phantom mutation hotspots could easily lead to misidentification of somatic mutations and to misinterpretations in all kinds of clinical mtDNA studies.

Environmental signals: Synthetic humic substances act as xeno-estrogen and affect the thyroid system of Xenopus laevis

According to outdated paradigms humic substances (HS) are considered to be refractory or inert that do not directly interact with aquatic organisms. However, they are taken up and induce biotransformation activities and may act as hormone-like substances. In the present study, we tested whether HS can interfere with endocrine regulation in the amphibian Xenopus laevis. In order to exclude contamination with phyto-hormones, which may occur in environmental isolates, the artificial HS 1500 was applied. The in vivo results showed that HS 1500 causes significant estrogenic effects on X. laevis during its larval development and results of semi-quantitative RT-PCR revealed a marked increase of the estrogenic biomarker estrogen receptor mRNA (ER-mRNA). Furthermore, preliminary RT-PCR results showed that the thyroid-stimulating hormone (TSH beta-mRNA) is enhanced after exposure to HS1500, indicating a weak adverse effect on T3/T4 availability. Hence, HS may have estrogenic and anti-thyroidal effects on aquatic animals, and therefore may influence the structure of aquatic communities and they may be considered environmental signaling chemicals. (c) 2005 Elsevier Ltd. All rights reserved.

Discrimination of Type 2 diabetic patients from healthy controls by using metabonomics method based on their serum fatty acid profiles

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields, including work in cardiovascular research and drug toxicology. In this study, metabonomics method was employed to the diagnosis of Type 2 diabetes mellitus (DM2) based on serum lipid metabolites. The results suggested that serum fatty acid profiles determined by capillary gas chromatography combined with pattern recognition analysis of the data might provide an effective approach to the discrimination of Type 2 diabetic patients from healthy controls. And the applications of pattern recognition methods have improved the sensitivity and specificity greatly. (C) 2004 Elsevier B.V. All rights reserved.