Laser-induced Precession of Magnetization in GaMnAs

We report on the photo-induced precession of the ferromagnetically coupled Mn spins in (Ga,Mn)As, which is observed even with no external magnetic field applied. We concentrate on various experimental aspects of the time-resolved magneto-optical Kerr effect (TR-MOKE) technique that can be used to clarify the origin of the detected signals. We show that the measured data typically consist of several different contributions, among which only the oscillatory signal is directly connected with the ferromagnetic order in the sample.Comment: 4 pages, 5 figure

tRNAdb 2009: compilation of tRNA sequences and tRNA genes

One of the first specialized collections of nucleic acid sequences in life sciences was the ‘compilation of tRNA sequences and sequences of tRNA genes’ (http://www.trna.uni-bayreuth.de). Here, an updated and completely restructured version of this compilation is presented (http://trnadb.bioinf.uni-leipzig.de). The new database, tRNAdb, is hosted and maintained in cooperation between the universities of Leipzig, Marburg, and Strasbourg. Reimplemented as a relational database, tRNAdb will be updated periodically and is searchable in a highly flexible and user-friendly way. Currently, it contains more than 12 000 tRNA genes, classified into families according to amino acid specificity. Furthermore, the implementation of the NCBI taxonomy tree facilitates phylogeny-related queries. The database provides various services including graphical representations of tRNA secondary structures, a customizable output of aligned or un-aligned sequences with a variety of individual and combinable search criteria, as well as the construction of consensus sequences for any selected set of tRNAs

A unique tRNA recognition mechanism of Caenorhabditis elegans mitochondrial EF-Tu2

Nematode mitochondria expresses two types of extremely truncated tRNAs that are specifically recognized by two distinct elongation factor Tu (EF-Tu) species named EF-Tu1 and EF-Tu2. This is unlike the canonical EF-Tu molecule that participates in the standard protein biosynthesis systems, which basically recognizes all elongator tRNAs. EF-Tu2 specifically recognizes Ser-tRNA(Ser) that lacks a D arm but has a short T arm. Our previous study led us to speculate the lack of the D arm may be essential for the tRNA recognition of EF-Tu2. However, here, we showed that the EF-Tu2 can bind to D arm-bearing Ser-tRNAs, in which the D–T arm interaction was weakened by the mutations. The ethylnitrosourea-modification interference assay showed that EF-Tu2 is unique, in that it interacts with the phosphate groups on the T stem on the side that is opposite to where canonical EF-Tu binds. The hydrolysis protection assay using several EF-Tu2 mutants then strongly suggests that seven C-terminal amino acid residues of EF-Tu2 are essential for its aminoacyl-tRNA-binding activity. Our results indicate that the formation of the nematode mitochondrial (mt) EF-Tu2/GTP/aminoacyl-tRNA ternary complex is probably supported by a unique interaction between the C-terminal extension of EF-Tu2 and the tRNA

Light-induced magnetization precession in GaMnAs

We report dynamics of the transient polar Kerr rotation (KR) and of the transient reflectivity induced by femtosecond laser pulses in ferromagnetic (Ga,Mn)As with no external magnetic field applied. It is shown that the measured KR signal consist of several different contributions, among which only the oscillatory signal is directly connected with the ferromagnetic order in (Ga,Mn)As. The origin of the light-induced magnetization precession is discussed and the magnetization precession damping (Gilbert damping) is found to be strongly influenced by annealing of the sample.Comment: 6 pages, 4 figures. accepted in Applied Physics Letter

Tissue-Specific Differences in Human Transfer RNA Expression

Over 450 transfer RNA (tRNA) genes have been annotated in the human genome. Reliable quantitation of tRNA levels in human samples using microarray methods presents a technical challenge. We have developed a microarray method to quantify tRNAs based on a fluorescent dye-labeling technique. The first-generation tRNA microarray consists of 42 probes for nuclear encoded tRNAs and 21 probes for mitochondrial encoded tRNAs. These probes cover tRNAs for all 20 amino acids and 11 isoacceptor families. Using this array, we report that the amounts of tRNA within the total cellular RNA vary widely among eight different human tissues. The brain expresses higher overall levels of nuclear encoded tRNAs than every tissue examined but one and higher levels of mitochondrial encoded tRNAs than every tissue examined. We found tissue-specific differences in the expression of individual tRNA species, and tRNAs decoding amino acids with similar chemical properties exhibited coordinated expression in distinct tissue types. Relative tRNA abundance exhibits a statistically significant correlation to the codon usage of a collection of highly expressed, tissue-specific genes in a subset of tissues or tRNA isoacceptors. Our findings demonstrate the existence of tissue-specific expression of tRNA species that strongly implicates a role for tRNA heterogeneity in regulating translation and possibly additional processes in vertebrate organisms

Diversity of tRNA genes in eukaryotes

We compare the diversity of chromosomal-encoded transfer RNA (tRNA) genes from 11 eukaryotes as identified by tRNAScan-SE of their respective genomes. They include the budding and fission yeast, worm, fruit fly, fugu, chicken, dog, rat, mouse, chimp and human. The number of tRNA genes are between 170 and 570 and the number of tRNA isoacceptors range from 41 to 55. Unexpectedly, the number of tRNA genes having the same anticodon but different sequences elsewhere in the tRNA body (defined here as tRNA isodecoder genes) varies significantly (10–246). tRNA isodecoder genes allow up to 274 different tRNA species to be produced from 446 genes in humans, but only up to 51 from 275 genes in the budding yeast. The fraction of tRNA isodecoder genes among all tRNA genes increases across the phylogenetic spectrum. A large number of sequence differences in human tRNA isodecoder genes occurs in the internal promoter regions for RNA polymerase III. We also describe a systematic, ligation-based method to detect and quantify tRNA isodecoder molecules in human samples, and show differential expression of three tRNA isodecoders in six human tissues. The large number of tRNA isodecoder genes in eukaryotes suggests that tRNA function may be more diverse than previously appreciated

Early virological response may predict treatment response in sofosbuvir-based combination therapy of chronic hepatitis c in a multi-center “real-life” cohort

Background: The combination of sofosbuvir (SOF), ribavirin (RBV) and peg-interferon-alfa-2a (peg-IFN-alfa-2a) as well as the combination of SOF and RBV for the treatment of patients infected with hepatitis c virus (HCV) has improved rates of sustained virological response (SVR) considerably in recent trials. However, there is only limited data concerning the efficacy and safety in a “real-life” cohort. Methods: We analyzed a cohort of 119 patients with chronic HCV infection treated at four investigational sites in Germany. All patients received either a combination treatment of SOF, RBV and peg-IFN-alfa-2a or SOF and RBV. Results: The rates of SVR at 12 weeks after end of treatment (SVR 12) were as follows: Among 76 patients with genotype 1 infection the SVR 12 rate was 74 % (n = 56), among 14 patients with genotype 2 infection the SVR 12 rate was 79 % (n = 11), among 24 patients with genotype 3 infection the SVR 12 rate was 92 % (n = 22) and among 5 patients with genotype 4 infection the SVR 12 rate was 80 % (n = 4). Of all 26 patients with a relapse in our cohort, 69 % (n = 18) of these patients presented with liver cirrhosis and 58 % (n = 15) were treatment experienced. Notably, the level of HCV-RNA after 4 weeks of treatment was a significant predictor of treatment response in genotype 1 patients. Patients with HCV-RNA levels ≥ 12 IU ml-1 after 4 weeks of treatment achieved SVR 12 only in 30 % (n = 17/56, p < 0.0001) of cases and treatment response was even lower with SVR 12 of 25 % (n = 5/20, p = 0.0016) in the subgroup of patients with cirrhosis. Conclusion: We observed a high rate of SVR 12 with SOF-based treatment regimes, however probably due to the high number of patients with liver cirrhosis and prior treatment experience, treatment response rates were lower than in previously published trials. In genotype 1 patients the analysis of early virological response may predict treatment response in SOF-based combination therapies

Can Clustal-style progressive pairwise alignment of multiple sequences be used in RNA secondary structure prediction?

<p>Abstract</p> <p>Background</p> <p>In ribonucleic acid (RNA) molecules whose function depends on their final, folded three-dimensional shape (such as those in ribosomes or spliceosome complexes), the secondary structure, defined by the set of internal basepair interactions, is more consistently conserved than the primary structure, defined by the sequence of nucleotides.</p> <p>Results</p> <p>The research presented here investigates the possibility of applying a progressive, pairwise approach to the alignment of multiple RNA sequences by simultaneously predicting an energy-optimized consensus secondary structure. We take an existing algorithm for finding the secondary structure common to two RNA sequences, Dynalign, and alter it to align profiles of multiple sequences. We then explore the relative successes of different approaches to designing the tree that will guide progressive alignments of sequence profiles to create a multiple alignment and prediction of conserved structure.</p> <p>Conclusion</p> <p>We have found that applying a progressive, pairwise approach to the alignment of multiple ribonucleic acid sequences produces highly reliable predictions of conserved basepairs, and we have shown how these predictions can be used as constraints to improve the results of a single-sequence structure prediction algorithm. However, we have also discovered that the amount of detail included in a consensus structure prediction is highly dependent on the order in which sequences are added to the alignment (the guide tree), and that if a consensus structure does not have sufficient detail, it is less likely to provide useful constraints for the single-sequence method.</p