A possible contribution of mRNA secondary structure to translation initiation efficiency in Lactococcus lactis

Gene expression signals derived from Lactococcus lactis were linked to lacZ-fused genes with different 5'-nucleotide sequences. Computer predictions of mRNA secondary structure were combined with lacZ expression studies to direct base-substitutions that could possibly influence gene expression. Mutations were made such that the DNA sequence upstream of the ATG start codon was not changed. Moreover, care was taken that the substitutions, which were all within the first six codons, neither affected the amino acid sequence of the gene product nor introduced codons rarely used in L. lactis. The results suggest that mRNA secondary structure contributes to the efficiency of translation initiation in L. lactis.     

Statistical correlation between protein secondary structure and messenger RNA stem-loop structure

A new integrated sequence-structure database, called IADE (Integrated ASTRAL-DSSP-EMBL), incorporating matching mRNA sequence, amino acid sequence, and protein secondary structural data, is constructed. It includes 648 protein domains. Based on the IADE database, we studied the relation between RNA stem-loop frequencies and protein secondary structure. It was found that the alpha-helices and beta-strands on proteins tend to be preferably "coded" by mRNA stem region, while the coils on proteins tend to be preferably "coded" by mRNA loop region. These tendencies are more obvious if we observe the structural words (SWs). An SW is defined by a four-amino-acid-fragment that shows the pronounced secondary structural (alpha-helix or beta-strand) propensity. It is demonstrated that the deduced correlation between protein and mRNA structure can hardly be explained as the stochastic fluctuation effect.     

The presence of a common downstream box enables the simultaneous expression of multiple proteins in an E. coli extract

In our experiments to produce different combinations of recombinant proteins in a cell-free protein synthesis system derived from Escherichia coli, we found that certain pairs of ORFs were not expressed equally. Instead, only a single DNA species was expressed dominantly, while the expression of the others was almost completely repressed. This bias during the co-expression of the DNA pairs was eliminated when an identical downstream box sequence was added to the 5'-ends of the template DNA pairs. By introducing identical nucleotide sequences of the his-tag or the downstream box of chloramphenicol acetyltransferase (CAT-DB) in front of the target genes that were otherwise not expressed compatibly, both of the encoded proteins were produced at similar productivities. Moreover, in the presence of a common downstream box, multiple genes were simultaneously expressed in the same reaction mixture. We expect that the proposed approach will offer a powerful tool for the preparation of unbiased protein libraries, as well as for studying the structure and functions of interacting proteins.     

HCV NS3 protein helicase domain assists RNA structure conversion

NS3H, the helicase domain of HCV NS3, possesses RNA-stimulated ATPase and ATP hydrolysis-dependent dsRNA unwinding activities. Here, the ability of NS3H to facilitate RNA structural rearrangement is studied using relatively long RNA strands as the model substrates. NS3H promotes intermolecular annealing, resolves three-stranded RNA duplexes, and assists dsRNA and ssRNA inter-conversions to establish a steady state among RNA structures. NS3H facilitates RNA structure conversions in a mode distinct from an ATP-independent RNA chaperone. These findings expand the known function of HCV NS3 helicase and reveal a role for viral helicase in assisting RNA structure conversions during virus life cycle.     

General combinatorics of RNA secondary structure

The total number of RNA secondary structures of a given length with minimal hairpin loop length m(m>0) and with minimal stack length l(l>0) is computed, under the assumption that all base pairs can occur. Asymptotics are derived from the determination of recurrence relations of decomposition properties.     

The template RNAs of RNA polymerases can have compact secondary structure, formed by long double helices with partial violations of the complementarity

A new method of contextual analysis was used to search the long non-random inverted repeats and the complementary palindromes in the genes of E. coli and T7 RNA polymerases. These genes were found to contain from 25% to 50% of all the nucleotides involved in such helices. The 5' -and 3' -ends of mRNA can be protected by neighbouring double helices from the nuclease attack. Some double helices are competing and very similar to the attenuator of E. coli trp-operon.     

RNA chaperone activity of translation initiation factor IF1

Translation initiation factor IF1 is an indispensable protein for translation in prokaryotes. No clear function has been assigned to this factor so far. In this study we demonstrate an RNA chaperone activity of this protein both in vivo and in vitro. The chaperone assays are based on in vivo or in vitro splicing of the group I intron in the thymidylate synthase gene (td) from phage T4 and an in vitro RNA annealing assay. IF1 wild-type and mutant variants with single amino acid substitutions have been analyzed for RNA chaperone activity. Some of the IF1 mutant variants are more active as RNA chaperones than the wild-type. Furthermore, both wild-type IF1 and mutant variants bind with high affinity to RNA in a band-shift assay. It is suggested that the RNA chaperone activity of IF1 contributes to RNA rearrangements during the early phase of translation initiation.     

Revolutions in RNA secondary structure prediction

RNA structure formation is hierarchical and, therefore, secondary structure, the sum of canonical base-pairs, can generally be predicted without knowledge of the three-dimensional structure. Secondary structure prediction algorithms evolved from predicting a single, lowest free energy structure to their current state where statistics can be determined from the thermodynamic ensemble. This article reviews the free energy minimization technique and the salient revolutions in the dynamic programming algorithm methods for secondary structure prediction. Emphasis is placed on highlighting the recently developed method, which statistically samples structures from the complete Boltzmann ensemble.     

Measuring the thermodynamics of RNA secondary structure formation

The thermodynamics of RNA secondary structure formation in small model systems provides a database for predicting RNA structure from sequence. Methods for making these measurements are reviewed with emphasis on optical methods and treatment of experimental errors. Analysis of experimental results in terms of simple nearest-neighbor models is presented. Some measured sequence dependences of non-Watson-Crick motifs are discussed. © 1998 John Wiley & Sons, Inc. Biopoly 44: 309–319, 1997     

Improved free energy parameters for RNA pseudoknotted secondary structure prediction

Accurate prediction of RNA pseudoknotted secondary structures from the base sequence is a challenging computational problem. Since prediction algorithms rely on thermodynamic energy models to identify low-energy structures, prediction accuracy relies in large part on the quality of free energy change parameters. In this work, we use our earlier constraint generation and Boltzmann likelihood parameter estimation methods to obtain new energy parameters for two energy models for secondary structures with pseudoknots, namely, the Dirks–Pierce (DP) and the Cao–Chen (CC) models. To train our parameters, and also to test their accuracy, we create a large data set of both pseudoknotted and pseudoknot-free secondary structures. In addition to structural data our training data set also includes thermodynamic data, for which experimentally determined free energy changes are available for sequences and their reference structures. When incorporated into the HotKnots prediction algorithm, our new parameters result in significantly improved secondary structure prediction on our test data set. Specifically, the prediction accuracy when using our new parameters improves from 68% to 79% for the DP model, and from 70% to 77% for the CC model.     

DbpA is a region‐specific RNA helicase

DbpA is a DEAD‐box RNA helicase implicated in RNA structural rearrangements in the peptidyl transferase center. DbpA contains an RNA binding domain, responsible for tight binding of DbpA to hairpin 92 of 23S ribosomal RNA, and a RecA‐like catalytic core responsible for double‐helix unwinding. It is not known if DbpA unwinds only the RNA helices that are part of a specific RNA structure, or if DbpA unwinds any RNA helices within the catalytic core's grasp. In other words, it is not known if DbpA is a site‐specific enzyme or region‐specific enzyme. In this study, we used protein and RNA engineering to investigate if DbpA is a region‐specific or a site‐specific enzyme. Our data suggest that DbpA is a region‐specific enzyme. This conclusion has an important implication for the physiological role of DbpA. It suggests that during ribosome assembly, DbpA could bind with its C‐terminal RNA binding domain to hairpin 92, while its catalytic core may unwind any double‐helices in its vicinity. The only requirement for a double‐helix to serve as a DbpA substrate is for the double‐helix to be positioned within the catalytic core's grasp.     

An economical and highly productive cell-free protein synthesis system utilizing fructose-1,6-bisphosphate as an energy source

In this study, we describe the development of a cost effective and highly productive cell-free protein synthesis system derived from Escherichia coli. Through the use of an optimal energy source and cell extract, approximately 1.3 mg/mL of protein was generated from a single batch reaction at greatly reduced reagent costs. Compared to previously reported systems, the described method yields approximately 14-fold higher productivity per unit reagent cost making this cell-free synthesis technique a promising alternative for more efficient protein production.     

RNA secondary structure as a reusable interface to biological information resources

The dissemination of biological information has become critically dependent on the Internet and World Wide Web (WWW), which enable distributed access to information in a platform independent manner. The mode of interaction between biologists and on-line information resources, however, has been mostly limited to simple interface technologies such has hypertext links, tables and forms. The introduction of platform-independent runtime environments facilitates the development of more sophisticated WWW-based user interfaces. Until recently, most such interfaces have been tightly coupled to the underlying computation engines, and not separated as reusable components. We believe that many subdisciplines of biology have intuitive and familiar graphical representations of knowledge that can serve as multipurpose user interface elements. We call such graphical idioms “domain graphics”. In order to illustrate the power of such graphics, we have built a reusable interface based on the standard two dimensional (2D) layout of RNA secondary structure. The interface can be used to represent any pre-computed layout of RNA, and takes as a parameters the sets of actions to be performed as a user interacts with the interface. It can provide to any associated application program information about the base, helix, or subsequence selected by the user. We show the versatility of this interface by using it as a special purpose interface to BLAST, Medline and the RNA MFOLD search/compute engines. These demonstrations are available at: ir|url|http://www-smi.stanford.edu/projects/helix/pubs/ gene-combis-96/     

DEAD-box helicases as integrators of RNA,nucleotide and protein binding

DEAD-box helicases perform diverse cellular functions in virtually all steps of RNA metabolism from Bacteria to Humans. Although DEAD-box helicases share a highly conserved core domain, the enzymes catalyze a wide range of biochemical reactions. In addition to the well established RNA unwinding and corresponding ATPase activities, DEAD-box helicases promote duplex formation and displace proteins from RNA. They can also function as assembly platforms for larger ribonucleoprotein complexes, and as metabolite sensors. This review aims to provide a perspective on the diverse biochemical features of DEAD-box helicases and connections to structural information. We discuss these data in the context of a model that views the enzymes as integrators of RNA, nucleotide, and protein binding. This article is part of a Special Issue entitled: The Biology of RNA helicases — Modulation for life.     

Algorithm independent properties of RNA secondary structure predictions

Algorithms predicting RNA secondary structures based on different folding criteria – minimum free energies (mfe), kinetic folding (kin), maximum matching (mm) – and different parameter sets are studied systematically. Two base pairing alphabets were used: the binary GC and the natural four-letter AUGC alphabet. Computed structures and free energies depend strongly on both the algorithm and the parameter set. Statistical properties, such as mean number of base pairs, mean numbers of stacks, mean loop sizes, etc., are much less sensitive to the choice of parameter set and even of algorithm. Some features of RNA secondary structures, such as structure correlation functions, shape space covering and neutral networks, seem to depend only on the base pairing logic (GC or AUGC alphabet). Received: 16 May 1996 / Accepted: 10 July 1996     

Visualizing the global secondary structure of a viral RNA genome with cryo-electron microscopy

The lifecycle, and therefore the virulence, of single-stranded (ss)-RNA viruses is regulated not only by their particular protein gene products, but also by the secondary and tertiary structure of their genomes. The secondary structure of the entire genomic RNA of satellite tobacco mosaic virus (STMV) was recently determined by selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE). The SHAPE analysis suggested a single highly extended secondary structure with much less branching than occurs in the ensemble of structures predicted by purely thermodynamic algorithms. Here we examine the solution-equilibrated STMV genome by direct visualization with cryo-electron microscopy (cryo-EM), using an RNA of similar length transcribed from the yeast genome as a control. The cryo-EM data reveal an ensemble of branching patterns that are collectively consistent with the SHAPE-derived secondary structure model. Thus, our results both elucidate the statistical nature of the secondary structure of large ss-RNAs and give visual support for modern RNA structure determination methods. Additionally, this work introduces cryo-EM as a means to distinguish between competing secondary structure models if the models differ significantly in terms of the number and/or length of branches. Furthermore, with the latest advances in cryo-EM technology, we suggest the possibility of developing methods that incorporate restraints from cryo-EM into the next generation of algorithms for the determination of RNA secondary and tertiary structures.     

一种新的RNA二级结构三维图形表示及其应用

本研究提出了一种新的RNA二级结构的图形表示方法,这种方法不同于以往的表示方式。根据所提出的RNA二级结构的图形表示,将对9种病毒的RNA二级结构进行图形表示,构建系统进化树,进行序列间相似性的比较和分析。根据最终结果,可以很清晰地发现,AVII与LRMV两种病毒是最为相似的,另外,较大的距离值出现在了APMV与ALMV;PDV与AVII中,这说明这几种RNA二级结构明显不相似。这一研究结果与前人相似性分析的结果是十分相似的,同时,所采取的方法更加简单易于区分观察且得到的结果又是十分可靠的,因此,这些更加证明了该方法是有效的。     

Improved RNA secondary structure prediction by maximizing expected pair accuracy

Free energy minimization has been the most popular method for RNA secondary structure prediction for decades. It is based on a set of empirical free energy change parameters derived from experiments using a nearest-neighbor model. In this study, a program, MaxExpect, that predicts RNA secondary structure by maximizing the expected base-pair accuracy, is reported. This approach was first pioneered in the program CONTRAfold, using pair probabilities predicted with a statistical learning method. Here, a partition function calculation that utilizes the free energy change nearest-neighbor parameters is used to predict base-pair probabilities as well as probabilities of nucleotides being single-stranded. MaxExpect predicts both the optimal structure (having highest expected pair accuracy) and suboptimal structures to serve as alternative hypotheses for the structure. Tested on a large database of different types of RNA, the maximum expected accuracy structures are, on average, of higher accuracy than minimum free energy structures. Accuracy is measured by sensitivity, the percentage of known base pairs correctly predicted, and positive predictive value (PPV), the percentage of predicted pairs that are in the known structure. By favoring double-strandedness or single-strandedness, a higher sensitivity or PPV of prediction can be favored, respectively. Using MaxExpect, the average PPV of optimal structure is improved from 66% to 68% at the same sensitivity level (73%) compared with free energy minimization.