There is something special about mRNA pseudoknots that allows them to elicit efficient levels of programmed −1 ribosomal frameshifting. Here, we present a synthesis of recent crystallographic, molecular, biochemical, and genetic studies to explain this property. Movement of 9 Å by the anticodon loop of the aminoacyl-tRNA at the accommodation step normally pulls the downstream mRNA a similar distance along with it. We suggest that the downstream mRNA pseudoknot provides resistance to this movement by becoming wedged into the entrance of the ribosomal mRNA tunnel. These two opposing forces result in the creation of a local region of tension in the mRNA between the A-site codon and the mRNA pseudoknot. This can be relieved by one of two mechanisms; unwinding the pseudoknot, allowing the downstream region to move forward, or by slippage of the proximal region of the mRNA backwards by one base. The observed result of the latter mechanism is a net shift of reading frame by one base in the 5 direction, that is, a −1 ribosomal frameshift.Keywords: Virus; ribosome; translation; genetic code; recoding; structure/function After a generation spent in the shadows, the ribosome is enjoying a renaissance. Recent breakthroughs in X-ray crystallography and cryoelectron microscopy have given us atomic-level views of this complex molecular machine Wimberly et al. 2000;Harms et al. 2001;Spahn et al. 2001;) that are bringing into focus the relationship between ribosome structure and function (Gabashvili et al. 1999;Agrawal et al. 2000;Carter et al. 2000;Frank and Agrawal 2000;Mueller et al. 2000;Nissen et al. 2000;Schluenzen et al. 2000;Beckmann et al. 2001;Nissen et al. 2001; Pioletti et al. 2001;Polacek et al. 2001;Thompson et al. 2001;Yusupova et al. 2001;Noller et al. 2002;Schmeing et al. 2002;Simonson and Lake 2002). One of the major requirements of the ribosome is to maintain translational reading frame, and an increasing number of cis-acting mRNA signals that alter this have been used to probe this essential function of the translational machinery. These translational "recoding" events (Gesteland and Atkins 1996) can take many forms, for example, "slips" of one or more bases, "hops" spanning as many as 50 nucleotides, and "shunts" around large mRNA secondary structures (for review, see Jacks 1990;Brierley 1995;Farabaugh 1996;Giedroc et al. 2000). Programmed −1 ribosomal frameshifting (−1 PRF) is the most widely used translational recoding mechanism of RNA viruses. The −1 PRF signal can be broken down into three discrete parts: the "slippery site", a linker region, and a downstream region of secondary mRNA structure, typically an mRNA pseudoknot. Mutagenesis studies from many different laboratories have demonstrated that the primary sequence of the slippery site and its placement in relation to the incoming translational reading frame is critical: It must be X XXY YYZ, where X must be a stretch of three identical nucleotides, Y is either AAA or UUU, and Z is A, C, or U. Although less is known about the linker region, ...

Increased efficiencies of programmed −1 ribosomal frameshifting in yeast cells expressing mutant forms of ribosomal protein L3 are unable to maintain the dsRNA "Killer" virus. Here we demonstrate that changes in frameshifting and virus maintenance in these mutants correlates with decreased peptidyltransferase activities. The mutants did not affect Ty1-directed programmed +1 ribosomal frameshifting or nonsense-mediated mRNA decay. Independent experiments demonstrate similar programmed −1 ribosomal frameshifting specific defects in cells lacking ribosomal protein L41, which has previously been shown to result in peptidyltransferase defects in yeast. These findings are consistent with the hypothesis that decreased peptidyltransferase activity should result in longer ribosome pause times after the accommodation step of the elongation cycle, allowing more time for ribosomal slippage at programmed −1 ribosomal frameshift signals. Keywords: Frameshifting; ribosome; virusProgrammed ribosomal frameshift (PRF) events most commonly induce translating ribosomes to slip by a single base in either the 5Ј (−1) or 3Ј (+1) direction, though examples of ribosomal "hops," "shunts," and "bypasses" have also been documented (for review, see Jacks 1990;Farabaugh 1996;Gesteland and Atkins 1996). Such translational recoding signals have been valuable in addressing questions relating to ribosome structure and function. For viruses that utilize PRF, the efficiencies of frameshift events are critical: They determine the stoichiometry of viral structural to enzymatic proteins available for virus particle assembly, and altering PRF frequencies have dire consequences for virus propagation (for review, see Dinman et al. 1998). Thus, it is important to understand how frameshifting efficiencies are controlled. The most widespread mechanisms involve inducing ribosomes to stall with their associated tRNAs positioned over specific mRNA sequences called "slippery sites" such that, in the event of slippage, the tRNAs are able to base pair with the out-of-frame codon or codons. Although the cis-acting signals are relatively well characterized, the trans-acting factors and the biophysical parameters that contribute to determine PRF efficiencies are less well understood. Genetic, biochemical, molecular, and pharmacological methods have been employed toward this end. In general, parameters that can affect PRF efficiencies include: (1) changes in the residence time of ribosomes at a particular PRF signal and the precise steps of the elongation cycle that such kinetic changes might occur; (2) changes in the stabilities of ribosome-bound tRNAs and/or ribosome catalytic function due to alterations in intrinsic ribosomal components such as ribosomal proteins, rRNAs, and codon:antidcodon interactions; and (3) defects in the abilities of the translational apparatus to recognize and correct errors (for review, see Harger et al. 2002).The genetic manipulability of the yeast Saccharomyces

a b s t r a c tA new dataset of cosmetics-related chemicals for the Threshold of Toxicological Concern (TTC) approach has been compiled, comprising 552 chemicals with 219, 40, and 293 chemicals in Cramer Classes I, II, and III, respectively. Data were integrated and curated to create a database of No-/Lowest-Observed-AdverseEffect Level (NOAEL/LOAEL) values, from which the final COSMOS TTC dataset was developed. Criteria for study inclusion and NOAEL decisions were defined, and rigorous quality control was performed for study details and assignment of Cramer classes. From the final COSMOS TTC dataset, human exposure thresholds of 42 and 7.9 mg/kg-bw/day were derived for Cramer Classes I and III, respectively. The size of Cramer Class II was insufficient for derivation of a TTC value. The COSMOS TTC dataset was then federated with the dataset of Munro and colleagues, previously published in 1996, after updating the latter using the quality control processes for this project. This federated dataset expands the chemical space and provides more robust thresholds. The 966 substances in the federated database comprise 245, 49 and 672 chemicals in Cramer Classes I, II and III, respectively. The corresponding TTC values of 46, 6.2 and 2.3 mg/kg-bw/day are broadly similar to those of the original Munro dataset.

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