Phospholipid-derived fatty acids and quinones as markers for bacterial biomass and community structure in marine sediments.

Phospholipid-derived fatty acids (PLFA) and respiratory quinones (RQ) are microbial compounds that have been utilized as biomarkers to quantify bacterial biomass and to characterize microbial community structure in sediments, waters, and soils. While PLFAs have been widely used as quantitative bacterial biomarkers in marine sediments, applications of quinone analysis in marine sediments are very limited. In this study, we investigated the relation between both groups of bacterial biomarkers in a broad range of marine sediments from the intertidal zone to the deep sea. We found a good log-log correlation between concentrations of bacterial PLFA and RQ over several orders of magnitude. This relationship is probably due to metabolic variation in quinone concentrations in bacterial cells in different environments, whereas PLFA concentrations are relatively stable under different conditions. We also found a good agreement in the community structure classifications based on the bacterial PLFAs and RQs. These results strengthen the application of both compounds as quantitative bacterial biomarkers. Moreover, the bacterial PLFA- and RQ profiles revealed a comparable dissimilarity pattern of the sampled sediments, but with a higher level of dissimilarity for the RQs. This means that the quinone method has a higher resolution for resolving differences in bacterial community composition. Combining PLFA and quinone analysis as a complementary method is a good strategy to yield higher resolving power in bacterial community structure.

First trimester screening for trisomy 21 in gestational week 8-10 by ADAM12-S as a maternal serum marker.

BACKGROUND: A disintegrin and metalloprotease 12 (ADAM12-S) has previously been reported to be significantly reduced in maternal serum from women with fetal aneuploidy early in the first trimester and to significantly improve the quality of risk assessment for fetal trisomy 21 in prenatal screening. The aim of this study was to determine whether ADAM12-S is a useful serum marker for fetal trisomy 21 using the mixture model. METHOD: In this case control study ADAM12-S was measured by KRYPTOR ADAM12-S immunoassay in maternal serum from gestational weeks 8 to 11 in 46 samples of fetal trisomy 21 and in 645 controls. Comparison of sensitivity and specificity of first trimester screening for fetal trisomy 21 with or without ADAM12-S included in the risk assessment using the mixture model. RESULTS: The concentration of ADAM12-S increased from week 8 to 11 and was negatively correlated with maternal weight. Log MoM ADAM12-S was positively correlated with log MoM PAPP-A (r = 0.39, P < 0.001), and with log MoM free beta hCG (r = 0.21, P < 0.001). The median ADAM12-S MoM in cases of fetal trisomy 21 in gestational week 8 was 0.66 increasing to approx. 0.9 MoM in week 9 and 10. The use of ADAM12-S along with biochemical markers from the combined test (PAPP-A, free beta hCG) with or without nuchal translucency measurement did not affect the detection rate or false positive rate of fetal aneuploidy as compared to routine screening using PAPP-A and free ß-hCG with or without nuchal translucency. CONCLUSION: The data show moderately decreased levels of ADAM12-S in cases of fetal aneuploidy in gestational weeks 8-11. However, including ADAM12-S in the routine risk does not improve the performance of first trimester screening for fetal trisomy 21.

High frequency of phenotypic deviations in Physcomitrella patens plants transformed with a gene-disruption library.

BACKGROUND: The moss Physcomitrella patens is an attractive model system for plant biology and functional genome analysis. It shares many biological features with higher plants but has the unique advantage of an efficient homologous recombination system for its nuclear DNA. This allows precise genetic manipulations and targeted knockouts to study gene function, an approach that due to the very low frequency of targeted recombination events is not routinely possible in any higher plant. RESULTS: As an important prerequisite for a large-scale gene/function correlation study in this plant, we are establishing a collection of Physcomitrella patens transformants with insertion mutations in most expressed genes. A low-redundancy moss cDNA library was mutagenised in E. coli using a derivative of the transposon Tn1000. The resulting gene-disruption library was then used to transform Physcomitrella. Homologous recombination of the mutagenised cDNA with genomic coding sequences is expected to target insertion events preferentially to expressed genes. An immediate phenotypic analysis of transformants is made possible by the predominance of the haploid gametophytic state in the life cycle of the moss. Among the first 16,203 transformants analysed so far, we observed 2636 plants (= 16.2%) that differed from the wild-type in a variety of developmental, morphological and physiological characteristics. CONCLUSIONS: The high proportion of phenotypic deviations and the wide range of abnormalities observed among the transformants suggests that mutagenesis by gene-disruption library transformation is a useful strategy to establish a highly diverse population of Physcomitrella patens mutants for functional genome analysis.

Plant functional genomics.

Functional genome analysis of plants has entered the high-throughput stage. The complete genome information from key species such as Arabidopsis thaliana and rice is now available and will further boost the application of a range of new technologies to functional plant gene analysis. To broadly assign functions to unknown genes, different fast and multiparallel approaches are currently used and developed. These new technologies are based on known methods but are adapted and improved to accommodate for comprehensive, large-scale gene analysis, i.e. such techniques are novel in the sense that their design allows researchers to analyse many genes at the same time and at an unprecedented pace. Such methods allow analysis of the different constituents of the cell that help to deduce gene function, namely the transcripts, proteins and metabolites. Similarly the phenotypic variations of entire mutant collections can now be analysed in a much faster and more efficient way than before. The different methodologies have developed to form their own fields within the functional genomics technological platform and are termed transcriptomics, proteomics, metabolomics and phenomics. Gene function, however, cannot solely be inferred by using only one such approach. Rather, it is only by bringing together all the information collected by different functional genomic tools that one will be able to unequivocally assign functions to unknown plant genes. This review focuses on current technical developments and their impact on the field of plant functional genomics. The lower plant Physcomitrella is introduced as a new model system for gene function analysis, owing to its high rate of homologous recombination.