Genome size, GC percentage and 5mC level in the Indonesian coelacanth Latimeria menadoensis

The living fossil Latimeria menadoensis is important to understand sarcopterygian evolution. To gain further insights into this fish species we studied its genome size, GC% and 5mC level. The genome size and the GC% of the Indonesian coelacanth seem to be very similar to those of the African coelacanth. Moreover the GC%, the CpG frequency and the 5mC level of L. menadoensis are more similar to those of fish and amphibians than to those of mammals, birds and reptiles and this is in line with the hypothesis that two different DNA methylation and CpG shortage equilibria arose during vertebrate evolution. Our results suggest that the genome of L. menadoensis has remained unchanged for several million years, maybe since the origin of the lineage which from lobe-finned fish led to tetrapods. These data fit a conservative evolutionary landscape and suggest that the genome of the extant crossopterygians may be a sort of evolutionarily frozen genome.     

Expression of MAGE-C1/CT7 and MAGE-C2/CT10 predicts lymph node metastasis in melanoma patients

MAGE-C1/CT7 and MAGE-C2/CT10 are members of the large MAGE family of cancer-testis (CT) antigens. CT antigens are promising targets for immunotherapy in cancer because their expression is restricted to cancer and germ line cells and a proportion of cancer patients presents with immune responses against CT antigens, which clearly demonstrates their immunogenicity. This study investigates the expression of MAGE-C1/CT7 and MAGE-C2/CT10 in primary and metastatic melanoma. Immunohistochemical staining of tissue microarrays that consisted of 59 primary malignant melanomas of the skin, 163 lymph node and distant melanoma metastases and 68 melanoma cell lines was performed. We found MAGE-C1/CT7 expression in 15 out of 50 (24%) primary melanomas and 15 out of 50 (24%) cell lines, whereas MAGE-C2/CT10 was detected in 17 out of 51 (33%) primary melanomas and 14 out of 68 (17%) cell lines. MAGE-C1/CT7 and MAGE-C2/CT10 were both detected in 40% of melanoma metastases. Patients with MAGE-C1/CT7 or MAGE-C2/CT10 positive primary melanoma had significantly more lymph node metastases (p = 0.005 and p<0.001, resp.). Prediction of lymph node metastasis by MAGE-C1/CT7 and MAGE-C2/CT10 was independent of tumor cell proliferation rate (Ki67 labeling index) in a multivariate analysis (p = 0.01). Our results suggest that the expression of MAGE-C1/CT7 and MAGE-C2/CT10 in primary melanoma is a potent predictor of sentinel lymph node metastasis.     

Mammalian frataxin: an essential function for cellular viability through an interaction with a preformed ISCU/NFS1/ISD11 iron-sulfur assembly complex

Background

Frataxin, the mitochondrial protein deficient in Friedreich ataxia, a rare autosomal recessive neurodegenerative disorder, is thought to be involved in multiple iron-dependent mitochondrial pathways. In particular, frataxin plays an important role in the formation of iron-sulfur (Fe-S) clusters biogenesis.

Methodology/Principal Findings

We present data providing new insights into the interactions of mammalian frataxin with the Fe-S assembly complex by combining in vitro and in vivo approaches. Through immunoprecipitation experiments, we show that the main endogenous interactors of a recombinant mature human frataxin are ISCU, NFS1 and ISD11, the components of the core Fe-S assembly complex. Furthemore, using a heterologous expression system, we demonstrate that mammalian frataxin interacts with the preformed core complex, rather than with the individual components. The quaternary complex can be isolated in a stable form and has a molecular mass of ≈190 kDa. Finally, we demonstrate that the mature human FXN_81–210 form of frataxin is the essential functional form in vivo.

Conclusions/Significance

Our results suggest that the interaction of frataxin with the core ISCU/NFS1/ISD11 complex most likely defines the essential function of frataxin. Our results provide new elements important for further understanding the early steps of de novo Fe-S cluster biosynthesis.     

Miniaturized bacterial biosensor system for arsenic detection holds great promise for making integrated measurement device

Combining bacterial bioreporters with microfluidics systems holds great promise for in-field detection of chemical or toxicity targets. Recently we showed how Escherichia coli cells engineered to produce a variant of green fluorescent protein after contact to arsenite and arsenate can be encapsulated in agarose beads and incorporated into a microfluidic chip to create a device for in-field detection of arsenic, a contaminant of well known toxicity and carcinogenicity in potable water both in industrialized and developing countries. Cell-beads stored in the microfluidics chip at -20°C retained inducibility up to one month and we were able to reproducibly discriminate concentrations of 10 and 50 μg arsenite per L (the drinking water standards for European countries and the United States, and for the developing countries, respectively) from the blank in less than 200 minutes. We discuss here the reasons for decreasing bioreporter signal development upon increased storage of cell beads but also show how this decrease can be reduced, leading to a faster detection and a longer lifetime of the device.     

Differential development of human brain white matter tracts

Neuroscience is increasingly focusing on developmental factors related to human structural and functional connectivity. Unfortunately, to date, diffusion-based imaging approaches have only contributed modestly to these broad objectives, despite the promise of diffusion-based tractography. Here, we report a novel data-driven approach to detect similarities and differences among white matter tracts with respect to their developmental trajectories, using 64-direction diffusion tensor imaging. Specifically, using a cross-sectional sample comprising 144 healthy individuals (7 to 48 years old), we applied k-means cluster analysis to separate white matter voxels based on their age-related trajectories of fractional anisotropy. Optimal solutions included 5-, 9- and 14-clusters. Our results recapitulate well-established tracts (e.g., internal and external capsule, optic radiations, corpus callosum, cingulum bundle, cerebral peduncles) and subdivisions within tracts (e.g., corpus callosum, internal capsule). For all but one tract identified, age-related trajectories were curvilinear (i.e., inverted 'U-shape'), with age-related increases during childhood and adolescence followed by decreases in middle adulthood. Identification of peaks in the trajectories suggests that age-related losses in fractional anisotropy occur as early as 23 years of age, with mean onset at 30 years of age. Our findings demonstrate that data-driven analytic techniques may be fruitfully applied to extant diffusion tensor imaging datasets in normative and neuropsychiatric samples.     

Functional connectivity analyses in imaging genetics: considerations on methods and data interpretation

Functional magnetic resonance imaging (fMRI) can be combined with genotype assessment to identify brain systems that mediate genetic vulnerability to mental disorders ("imaging genetics"). A data analysis approach that is widely applied is "functional connectivity". In this approach, the temporal correlation between the fMRI signal from a pre-defined brain region (the so-called "seed point") and other brain voxels is determined. In this technical note, we show how the choice of freely selectable data analysis parameters strongly influences the assessment of the genetic modulation of connectivity features. In our data analysis we exemplarily focus on three methodological parameters: (i) seed voxel selection, (ii) noise reduction algorithms, and (iii) use of additional second level covariates. Our results show that even small variations in the implementation of a functional connectivity analysis can have an impact on the connectivity pattern that is as strong as the potential modulation by genetic allele variants. Some effects of genetic variation can only be found for one specific implementation of the connectivity analysis. A reoccurring difficulty in the field of psychiatric genetics is the non-replication of initially promising findings, partly caused by the small effects of single genes. The replication of imaging genetic results is therefore crucial for the long-term assessment of genetic effects on neural connectivity parameters. For a meaningful comparison of imaging genetics studies however, it is therefore necessary to provide more details on specific methodological parameters (e.g., seed voxel distribution) and to give information how robust effects are across the choice of methodological parameters.