Volker A. Erdmann

Differentiating the functional role of hypoxia-inducible factor (HIF)-1α and HIF-2α (EPAS-1) by the use of RNA interference: erythropoietin is a HIF-2α target gene in Hep3B and Kelly cells

Activation of the hypoxia‐inducible factor α‐subunits, HIF‐1α and HIF‐2α, seems to be subject to similar regulatory mechanisms, and transgene approaches suggested partial functional redundancy. Here, we used RNA interference to determine the contribution of HIF‐1α vs. HIF‐2α to the hypoxic gene induction. Surprisingly, most genes tested were responsive only to the HIF‐1α siRNA, showing no effect by HIF‐2α knock‐down. The same was found for the activation of reporter genes driven by hypoxia‐responsive elements (HREs) from the erythropoietin (EPO), vascular endothelial growth factor, or phosphoglycerate kinase gene. Interestingly, EPO was the only gene investigated that showed responsiveness only to HIF‐2α knock‐down, as observed in Hep3B and Kelly cells. In contrast to the EPO‐HRE reporter, the complete EPO enhancer displayed dependency on HIF‐2α regulation, indicating that additional cis‐acting elements confer HIF‐2α specificity within this region. In 786‐0 cells lacking HIF‐1α protein, the identified HIF‐1α target genes were regulated by HIF‐2α. Overexpression of the HIFα subunits in different cell lines also led to a loss of target gene specificity. In conclusion, we found a remarkably restricted target gene specificity of the HIFα subunits, which can be overcome in cells with perturbations in the pVHL/HIF system and under forced expression.

Long-term cardiac-targeted RNA interference for the treatment of heart failure restores cardiac function and reduces pathological hypertrophy.

Background— RNA interference (RNAi) has the potential to be a novel therapeutic strategy in diverse areas of medicine. Here, we report on targeted RNAi for the treatment of heart failure, an important disorder in humans that results from multiple causes. Successful treatment of heart failure is demonstrated in a rat model of transaortic banding by RNAi targeting of phospholamban, a key regulator of cardiac Ca2+ homeostasis. Whereas gene therapy rests on recombinant protein expression as its basic principle, RNAi therapy uses regulatory RNAs to achieve its effect. Methods and Results— We describe structural requirements to obtain high RNAi activity from adenoviral and adeno-associated virus (AAV9) vectors and show that an adenoviral short hairpin RNA vector (AdV-shRNA) silenced phospholamban in cardiomyocytes (primary neonatal rat cardiomyocytes) and improved hemodynamics in heart-failure rats 1 month after aortic root injection. For simplified long-term therapy, we developed a dimeric cardiotropic adeno-associated virus vector (rAAV9-shPLB) to deliver RNAi activity to the heart via intravenous injection. Cardiac phospholamban protein was reduced to 25%, and suppression of sacroplasmic reticulum Ca2+ ATPase in the HF groups was rescued. In contrast to traditional vectors, rAAV9 showed high affinity for myocardium but low affinity for liver and other organs. rAAV9-shPLB therapy restored diastolic (left ventricular end-diastolic pressure, dp/dtmin, and &tgr;) and systolic (fractional shortening) functional parameters to normal ranges. The massive cardiac dilation was normalized, and cardiac hypertrophy, cardiomyocyte diameter, and cardiac fibrosis were reduced significantly. Importantly, no evidence was found of microRNA deregulation or hepatotoxicity during these RNAi therapies. Conclusions— Our data show for the first time the high efficacy of an RNAi therapeutic strategy in a cardiac disease.

5S Ribosomal RNA Database

Ribosomal 5S RNA (5S rRNA) is an integral component of the large ribosomal subunit in all known organisms with the exception only of mitochondrial ribosomes of fungi and animals. It is thought to enhance protein synthesis by stabilization of a ribosome structure. This paper presents the updated database of 5S rRNA and their genes (5S rDNA). Its short characteristics are presented in the Introduction. The database contains 2280 primary structures of 5S rRNA and 5S rRNA genes. These include 536 eubacterial, 61 archaebacterial, 1611 eukaryotic and 72 organelle sequences. The database is available on line through the World Wide Web at http://biobases.ibch.poznan.pl/5SData/.

The non-coding RNAs as riboregulators

The non-coding RNAs database (http://biobases.ibch.poznan.pl/ncRNA/) contains currently available data on RNAs, which do not have long open reading frames and act as riboregulators. Non-coding RNAs are involved in the specific recognition of cellular nucleic acid targets through complementary base pairing to control cell growth and differentiation. Some of them are connected with several well known developmental and neuro-behavioral disorders. We have divided them into four groups. This paper is a short introduction to the database and presents its latest, updated edition.

The Translational Apparatus

Robin Ray Gutell MCDBiology Campus Box 347 University of Colorado Boulder, Colorado 80309-0347 USA email: rgutell@boulder.colorado.edu The elucidation of 16S and 23S rRNA Higher-Order Structure has been addressed by Comparative Sequence Methods for more than a decade. During these years our comparative methods have evolved as the number of complete 16S and 23S rRNA sequences have increased significantly, resulting in the maturation of the higher-order structure models for 16S and 23S rRNA. With over 1000 16S (and 16S-like) and 200 23S (and 23S-like) sequences at this time, we have strong comparative evidence for the vast majority of all secondary structure base pairings, and are thus quite confident of the majority of the proposed Escherichia coli 16S and 23S rRNA secondary structure. Within the past few years additional rRNA Higher-Order structure constraints have been elucidated; constraints that reveal various RNA structural forms, including lone canonical pairings, pseudoknots, non-canonical pairings, tetra loops, canonical and non-canonical pairings that together forms a parallel (vs. the usual antiparallel) stranded structural element, and suggestive evidence for coaxial stacking of adjacent helices. At this time we question what additional RNA structural constraints can be deciphered with comparative structure methods. To answer such questions, the rRNA sequence collection will need to continue to grow in both number and diversity, and our comparative structure algorithms need to evolve to a more sophisticated level. In an effort to establish the limits for structural similarity, we need to address how different two higher-order structures can be and still be considered analogous. Introductory Statements Since the flrstcomplete 16S (Brosius et al. 1978) and 23S (Brosius et al. 1980) rRNA sequences were determined, comparative analyds of these molecules has progressed in a variety of ways. Maybe foremost for the majority (especially for this audience) is the resulting higher-order structures, which ribosome-ologists utilize to map andlor design their experiments onto. While there is a wealth of information that can and should be elucidated from the sequences that make up the 16S and 23S rRNA datasets, this article will focus on the most obvious and probably experimentally meaningful structural features, namely secondary structure helices, tertiary interactions, and a few interesting examples of other comparatively derived structural constraints. And since much has already been written on comparatively derived rRNA structure [and most recently for an upcoming book on ribosomal RNA (Gutell et al. 1993), this article will only briefly touch on some of the emerging RNA structural features and new The Translational Apparatus, Edited by K.H. Nierhaus et al., Plenum Press, New York, 1993 477 structural possibilities that have been uncovered within the past year or so, leaving the interested reader to investigate elsewhere for a more encompassing perspective of the details of the comparatively derived rRNA structures. Comparative Structure Analysis What is the basis of this method? What might we expect to decipher? This method is rooted in the simple concept that similar or analogous three-dimensional structure can be composed of different primary structures, or in other words many different primary structures can fold into the same isomorphic 3-dimensional structure. Thus natural selection can maintain and act on the higher-order structures of RNA while the primary structure is free to change, although constrained in its divergence. The ribosomal RNA is an ideal molecule to apply such methodology to due to its structural and functional role in the ribosome, and the ribosomes position in protein synthesis and the evolution of the cell (Woese 1980). Underlying this method are a number of key questions that cannot be answered a priori. How much and what types of variance can be tolerated in higher-order structure before these structures are not considered isomorphic? How much overall similarity should we expect to fmd for any RNA molecule? How much overall variance should we expect to find for any RNA molecule (i.e., tRNA: type I vs. type II)? To what extent can these methods identify general folding patterns and to what extent can these methods identify and distinguish subtle and detailed RNA structure (i.e., elucidate the generalized three-dimensional structure for tRNAs; elucidate the detailed features recognized by each of the aminoacyl synthetases for their cognate tRNA)? Will all RNA structural motifs be identified with such methods, or will only a subset of these structural elements be amenable to such methods, i.e., should we expect secondary and all tertiary interactions to be equally decipherable? And lastly, should we anticipate the same overall and/or detailed structural (and even biological) constraints within phylogenetic ally related vs. distant structures? A quick glimpse at the progression of our rRNA structure models Although these questions are not (yet) answerable, the comparative analysis of the rRNAs (and all RNAs for that matter) has advanced in stages, in part so the results from each stage with their underlying assumptions can be evalulated before moving on to the next stage, and in part due to the significant increase in the number of sequences, development of the underlying correlation analysis algorithms, and the fact that we believe there is more structural detail to be found at the completion of each stage. This analysis started with basic assumptions that were congruent with principles elucidated with experimental methods. Initially the comparative structure searched for the helices that compose the overall secondary structure [For 16S rRNA: (Woese et al. 1980, Stiegler et al. 1980, Zwieb et al. 1981), and 23S rRNA: (Nolier et al. 1981, Glotz et al. 1981, and Branlant et al. 1981) rRNAs]. These methods specifically searched for canonical base pairings (ie. A-U and G-C) arranged contiguously and in an antiparallel orientation. These structures were tested and evaluated with each new rRNA sequence, resulting in numerous refmements in the secondary structures [Many references not noted here]. The specific search for helical elements gave way to a more generalized, non-structure based method. This method (Gutell et al. 1985) transformed the pattern of nucleotides at each column in the sequence alignment to a number pattern, which was based on the pattern of conservation and variance at every position in the molecule. Similar number patterns were subsequently grouped and analyzed, resulting in refmements in the secondary structure, and several proposed tertiary interactions (Gutell et al. 1985, 1986). Equally significant this simple algorithm uncovered a few basic principles of RNA structure, namely canonical pairings, and contiguous and antiparallel arrangement of such pairings [It should be noted that this method searched for columns (nucleotide positions) with similar patterns of variation or covariance, regardless of the nucleotide and pairing types. It so happened that the underlying pairs

Probing the SELEX Process with Next-Generation Sequencing

Background SELEX is an iterative process in which highly diverse synthetic nucleic acid libraries are selected over many rounds to finally identify aptamers with desired properties. However, little is understood as how binders are enriched during the selection course. Next-generation sequencing offers the opportunity to open the black box and observe a large part of the population dynamics during the selection process. Methodology We have performed a semi-automated SELEX procedure on the model target streptavidin starting with a synthetic DNA oligonucleotide library and compared results obtained by the conventional analysis via cloning and Sanger sequencing with next-generation sequencing. In order to follow the population dynamics during the selection, pools from all selection rounds were barcoded and sequenced in parallel. Conclusions High affinity aptamers can be readily identified simply by copy number enrichment in the first selection rounds. Based on our results, we suggest a new selection scheme that avoids a high number of iterative selection rounds while reducing time, PCR bias, and artifacts.

The product of the imprinted H19 gene is an oncofetal RNA.

AIMS/BACKGROUND: The H19 gene is an imprinted, maternally expressed gene in humans. It is tightly linked and coregulated with the imprinted, paternally expressed gene of insulin-like growth factor 2. The H19 gene product is not translated into protein and functions as an RNA molecule. Although its role has been investigated for more than a decade, its biological function is still not understood fully. H19 is abundantly expressed in many tissues from early stages of embryogenesis through fetal life, and is down regulated postnatally. It is also expressed in certain childhood and adult tumours. This study was designed to screen the expression of H19 in human cancer and its relation to the expression of H19 in the fetus. METHODS: Using in situ hybridisation with a [35S] labelled probe, H19 mRNA was detected in paraffin wax sections of fetal tissues from the first and second trimesters of pregnancy and of a large array of human adult and childhood tumours arising from these tissues. RESULTS: The H19 gene is expressed in tumours arising from tissues which express this gene in fetal life. Its expression in the fetus and in cancer is closely linked with tissue differentiation. CONCLUSIONS: Based on these and previous data, H19 is neither a tumour suppressor gene nor an oncogene. Its product is an oncofetal RNA. The potential use of this RNA as a tumour marker should be evaluated.

Non-coding, mRNA-like RNAs database Y2K

In last few years much data has accumulated on various non-translatable RNA transcripts that are synthesised in different cells. They are lacking in protein coding capacity and it seems that they work mainly or exclusively at the RNA level. All known non-coding RNA transcripts are collected in the database: http://www. man.poznan.pl/5SData/ncRNA/index.html

Sequence Requirements in the Catalytic Core of the “10-23” DNA Enzyme

A systematic mutagenesis study of the “10-23” DNA enzyme was performed to analyze the sequence requirements of its catalytic domain. Therefore, each of the 15 core nucleotides was substituted separately by the remaining three naturally occurring nucleotides. Changes at the borders of the catalytic domain led to a dramatic loss of enzymatic activity, whereas several nucleotides in between could be exchanged without severe effects. Thymidine at position 8 had the lowest degree of conservation and its substitution by any of the other three nucleotides caused only a minor loss of activity. In addition to the standard nucleotides (adenosine, guanosine, thymidine, or cytidine) modified nucleotides were used to gain further information about the role of individual functional groups. Again, thymidine at position 8 as well as some other nucleotides could be substituted by inosine without severe effects on the catalytic activity. For two positions, additional experiments with 2-aminopurine and deoxypurine, respectively, were performed to obtain information about the specific role of functional groups. In addition to sequence-function relationships of the DNA enzyme, this study provides information about suitable sites to introduce modified nucleotides for further functional studies or for internal stabilization of the DNA enzyme against endonucleolytic attack.

5 S rRNA: structure and interactions.

5 S rRNA is an integral component of the large ribosomal subunit in all known organisms. Despite many years of intensive study, the function of 5 S rRNA in the ribosome remains unknown. Advances in the analysis of ribosome structure that have revealed the crystal structures of large ribosomal subunits and of the complete ribosome from various organisms put the results of studies on 5 S rRNA in a new perspective. This paper summarizes recently published data on the structure and function of 5 S rRNA and its interactions in complexes with proteins, within and outside the ribosome.