Iwona A. Cymerman

The memory of fear extinction is context dependent: fear that is suppressed in one context readily renews in another. Understanding of the underlying neuronal circuits is, therefore, of considerable clinical relevance for anxiety disorders. Prefrontal cortical and hippocampal inputs to the amygdala have recently been shown to regulate the retrieval of fear memories, but the cellular organization of these projections remains unclear. By using anterograde tracing in a transgenic rat in which neurons express a dendritically-targeted PSD-95:Venus fusion protein under the control of a c-fos promoter, we found that, during the retrieval of extinction memory, the dominant input to active neurons in the lateral amygdala was from the infralimbic cortex, whereas the retrieval of fear memory was associated with greater hippocampal and prelimbic inputs. This pattern of retrieval-related afferent input was absent in the central nucleus of the amygdala. Our data show functional anatomy of neural circuits regulating fear and extinction, providing a framework for therapeutic manipulations of these circuits.

BACKGROUND: Various drugs of abuse activate intracellular pathways in the brain reward system. These pathways regulate the expression of genes that are essential to the development of addiction. To reveal genes common and distinct for different classes of drugs of abuse, we compared the effects of nicotine, ethanol, cocaine, morphine, heroin and methamphetamine on gene expression profiles in the mouse striatum. RESULTS: We applied whole-genome microarray profiling to evaluate detailed time-courses (1, 2, 4 and 8 hours) of transcriptome alterations following acute drug administration in mice. We identified 42 drug-responsive genes that were segregated into two main transcriptional modules. The first module consisted of activity-dependent transcripts (including Fos and Npas4), which are induced by psychostimulants and opioids. The second group of genes (including Fkbp5 and S3-12), which are controlled, in part, by the release of steroid hormones, was strongly activated by ethanol and opioids. Using pharmacological tools, we were able to inhibit the induction of particular modules of drug-related genomic profiles. We selected a subset of genes for validation by in situ hybridization and quantitative PCR. We also showed that knockdown of the drug-responsive genes Sgk1 and Tsc22d3 resulted in alterations to dendritic spines in mice, possibly reflecting an altered potential for plastic changes. CONCLUSIONS: Our study identified modules of drug-induced genes that share functional relationships. These genes may play a critical role in the early stages of addiction.

The 5' cap of human messenger RNA consists of an inverted 7-methylguanosine linked to the first transcribed nucleotide by a unique 5'-5' triphosphate bond followed by 2'-O-ribose methylation of the first and often the second transcribed nucleotides, likely serving to modify efficiency of transcript processing, translation and stability. We report the validation of a human enzyme that methylates the ribose of the second transcribed nucleotide encoded by FTSJD1, henceforth renamed HMTR2 to reflect function. Purified recombinant hMTr2 protein transfers a methyl group from S-adenosylmethionine to the 2'-O-ribose of the second nucleotide of messenger RNA and small nuclear RNA. Neither N(7) methylation of the guanosine cap nor 2'-O-ribose methylation of the first transcribed nucleotide are required for hMTr2, but the presence of cap1 methylation increases hMTr2 activity. The hMTr2 protein is distributed throughout the nucleus and cytosol, in contrast to the nuclear hMTr1. The details of how and why specific transcripts undergo modification with these ribose methylations remains to be elucidated. The 2'-O-ribose RNA cap methyltransferases are present in varying combinations in most eukaryotic and many viral genomes. With the capping enzymes in hand their biological purpose can be ascertained.

We applied a new multi-step protocol to predict the structures of all targets during CASP5, regardless of their potential category. 1) We used diverse fold-recognition (FR) methods to generate initial target-template alignments, which were converted into preliminary full-atom models by comparative modeling. All preliminary models were evaluated (scored) by VERIFY3D to identify well- and poorly-folded fragments. 2) Preliminary models with similar 3D folds were superimposed, poorly-scoring regions were deleted and the "average model" structure was created by merging the remaining segments. All template structures reported by FR were superimposed and a composite multiple-structure template was created from the most conserved fragments. 3). The average model was superimposed onto the composite template and the structure-based target-template alignment was inferred. This alignment was used to build a new (intermediate) comparative model of the target, again scored with VERIFY3D. 4) For all poorly scoring regions series of alternative alignments were generated by progressively shifting the "unfit" sequence fragment in either direction. Here, we considered additional information, such as secondary structure, placement of insertions and deletions in loops, conservation of putative catalytic residues, and the necessity to obtain a compact, well-folded structure. For all alternative alignments, new models were built and evaluated. 5) All models were superimposed and the "FRankenstein's monster" (FR, fold recognition) model was built from best-scoring segments. The final model was obtained after limited energy minimization to remove steric clashes between sidechains from different fragments. The novelty of this approach is in the focus on "vertical" recombination of structure fragments, typical for the ab initio field, rather than "horizontal" sequence alignment typical for comparative modeling. We tested the usefulness of the "FRankenstein" approach for non-expert predictors: only the leader of our team had considerable experience in protein modeling - he registered as a separate group (020) and submitted models built only by himself. At the onset of CASP5, the other five members of the team (students) had very little or no experience with modeling. They followed the same protocol in a deliberately naïve way. In the fourth step they used solely the VERIFY3D criterion to compare their models and the leader's model (the latter regarded only as one of the many alternatives) and generated the hybrid or selected only one model for submission (group 517). In order to compare our protocol with the traditional "one target-one template-one alignment" approach, we submitted (as a separate group 242) models selected from those automatically generated by all CAFASP servers (i.e. obtained without any human intervention). Here, we compare the results obtained by the three "groups", describe successes and failures of the "FRankenstein" approach and discuss future developments of comparative modeling. The automatic version of our multi-step protocol is being developed as a meta-server; the prototype is freely available at http://genesilico.pl/meta/.

Dextran is widely exploited in medical products and as a component of drug-delivering nanoparticles (NPs). Here, we tested whether dextran can serve as the main substrate of NPs and form a stable backbone. We tested dextrans with several molecular masses under several synthesis conditions to optimize NP stability. The analysis of the obtained nanoparticles showed that dextran NPs that were synthesized from 70 kDa dextran with a 5% degree of oxidation of the polysaccharide chain and 50% substitution with dodecylamine formed a NP backbone composed of modified dextran subunits, the mean diameter of which in an aqueous environment was around 100 nm. Dextran NPs could be stored in a dry state and reassembled in water. Moreover, we found that different chemical moieties (e.g., drugs such as doxorubicin) can be attached to the dextran NPs via a pH-dependent bond that allows release of the drug with lowering pH. We conclude that dextran NPs are a promising nano drug carrier.