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Letter↗
Biomedical subjects
Dmitri D Pervouchine
Publications and source records attributed to Dmitri D Pervouchine.
RNAKinetics: a web server that models secondary structure kinetics of an elongating RNA.
The RNAKinetics server (http://www.ig-msk.ru/RNA/kinetics) is a web interface for the newly developed RNAKinetics software. The software models the dynamics of RNA secondary structure by the means of kinetic analysis of folding transitions of a growing RNA molecule. The result of the modeling is a kinetic ensemble, i.e. a collection of RNA structures that are endowed with probabilities, which depend on time. This approach gives comprehensive probabilistic description of RNA folding pathways, revealing important kinetic details that are not captured by the traditional structure prediction methods. The access to the RNAKinetics server is free.
Base Sequence↗
Low-dimensional maps encoding dynamics in entorhinal cortex and hippocampus.
Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I(h). In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I(h). The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework.
Action Potentials↗
Slow and fast inhibition and an H-current interact to create a theta rhythm in a model of CA1 interneuron network.
The oriens-lacunosum moleculare (O-LM) subtype of interneuron is a key component in the formation of the theta rhythm (8-12 Hz) in the hippocampus. It is known that the CA1 region of the hippocampus can produce theta rhythms in vitro with all ionotropic excitation blocked, but the mechanisms by which this rhythmicity happens were previously unknown. Here we present a model suggesting that individual O-LM cells, by themselves, are capable of producing a single-cell theta-frequency firing, but coupled O-LM cells are not capable of producing a coherent population theta. By including in the model fast-spiking (FS) interneurons, which give rise to IPSPs that decay faster than those of the O-LM cells, coherent theta rhythms are produced. The inhibition to O-LM cells from the FS cells synchronizes the O-LM cells, but only when the FS cells themselves fire at a theta frequency. Reciprocal connections from the O-LM cells to the FS cells serve to parse the FS cell firing into theta bursts, which can then synchronize the O-LM cells. A component of the model O-LM cell critical to the synchronization mechanism is the hyperpolarization-activated h-current. The model can robustly reproduce relative phases of theta frequency activity in O-LM and FS cells.
Animals↗
Engineered riboregulators enable post-transcriptional control of gene expression.
Recent studies have demonstrated the important enzymatic, structural and regulatory roles of RNA in the cell. Here we present a post-transcriptional regulation system in Escherichia coli that uses RNA to both silence and activate gene expression. We inserted a complementary cis sequence directly upstream of the ribosome binding site in a target gene. Upon transcription, this cis-repressive sequence causes a stem-loop structure to form at the 5'-untranslated region of the mRNA. The stem-loop structure interferes with ribosome binding, silencing gene expression. A small noncoding RNA that is expressed in trans targets the cis-repressed RNA with high specificity, causing an alteration in the stem-loop structure that activates expression. Such engineered riboregulators may lend insight into mechanistic actions of endogenous RNA-based processes and could serve as scalable components of biological networks, able to function with any promoter or gene to directly control gene expression.
5' Untranslated Regions↗
IRIS: intermolecular RNA interaction search.
Here we present IRIS, a method for prediction of RNA-RNA interactions that is based on dynamic programming and extends current RNA secondary structure prediction approaches. Using this method we have found a number of interesting refinements to the structures of RNA-RNA complexes that have been studied previously and predicted novel targets for several known regulatory RNAs in E. coli. The computational time and memory usage of IRIS are O(n(3)m(3)) and O(n(2)m(2)), respectively, where n and m are the lengths of the input sequences. IRIS can be used for analysis of antisense regulatory systems in sequenced organisms and for the design of artificial riboregulators such as antisense drugs.
Base Sequence↗
On the normalization of RNA equilibrium free energy to the length of the sequence.
There is no universal definition of stability for RNA secondary structures. Here we present an approach that is based on normalization of the equilibrium free energy to the length of the sequence: a segment of RNA is said to be stable if the ratio of the equilibrium free energy to the length of the segment is greater than a certain threshold value. Discarding the segments whose normalized equilibrium free energies are smaller than the threshold allows us to view the secondary structure at different levels of stability. Confined to only highly stable structures, the algorithm for secondary structure prediction admits a number of simplifications that make it computationally tractable for large sequences and advantageous over most other methods on a genome-wide scale. This method was applied to the Caenorhabditis elegans genome to localize the regions that encode stable secondary structures. In particular, 36 of 56 previously reported micro-RNAs were localized to 4% of the genome. A fraction of long (>or=400 nt) stable inverted repeats in the genomic sequence of C.elegans was found. Their distribution is very uneven, and skewed towards the ends of chromosomes. This method can be used for genome-wide detection of transcription termination signals, putative micro-RNAs, and other regulatory elements that involve stable RNA secondary structures.
Algorithms↗