Computational design of orthogonal ribosomes

Nucleic Acids Research, Jul 2008

Orthogonal ribosomes (o-ribosomes), also known as specialized ribosomes, are able to selectively translate mRNA not recognized by host ribosomes. As a result, they are powerful tools for investigating translational regulation and probing ribosome structure. To date, efforts directed towards engineering o-ribosomes have involved random mutagenesis-based approaches. As an alternative, we present here a computational method for rationally designing o-ribosomes in bacteria. Working under the assumption that base-pair interactions between the 16S rRNA and mRNA serve as the primary mode for ribosome binding and translational initiation, the algorithm enumerates all possible extended recognition sequences for 16S rRNA and then chooses those candidates that: (i) have a similar binding strength to their target mRNA as the canonical, wild-type ribosome/mRNA pair; (ii) do not bind mRNA with the wild-type, canonical Shine-Dalgarno (SD) sequence and (iii) minimally interact with host mRNA irrespective of whether a recognizable SD sequence is present. In order to test the algorithm, we experimentally characterized a number of computationally designed o-ribosomes in Escherichia coli.

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Computational design of orthogonal ribosomes

Lon M. Chubiz 0 Christopher V. Rao 0 0 Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign , 600 S. Mathews Ave, Urbana, IL 61801, USA Orthogonal ribosomes (o-ribosomes), also known as specialized ribosomes, are able to selectively translate mRNA not recognized by host ribosomes. As a result, they are powerful tools for investigating translational regulation and probing ribosome structure. To date, efforts directed towards engineering o-ribosomes have involved random mutagenesisbased approaches. As an alternative, we present here a computational method for rationally designing o-ribosomes in bacteria. Working under the assumption that base-pair interactions between the 16S rRNA and mRNA serve as the primary mode for ribosome binding and translational initiation, the algorithm enumerates all possible extended recognition sequences for 16S rRNA and then chooses those candidates that: (i) have a similar binding strength to their target mRNA as the canonical, wild-type ribosome/mRNA pair; (ii) do not bind mRNA with the wild-type, canonical ShineDalgarno (SD) sequence and (iii) minimally interact with host mRNA irrespective of whether a recognizable SD sequence is present. In order to test the algorithm, we experimentally characterized a number of computationally designed o-ribosomes in Escherichia coli. - INTRODUCTION Gene expression involves two steps, transcription and translation. While a number of genetic tools exist for reprograming transcription in cells, far fewer tools exist for translation. Of the tools available in bacteria, the most popular are riboregulators, both cis- and trans-activating (14), and orthogonal ribosomes (o-ribosomes), also known as specialized ribosomes (59). In terms of reprograming translation, o-ribosomes are especially powerful as they enable one to partially decouple translation from the native protein synthesis machinery. In particular, o-ribosomes can translate genes with altered ShineDalgarno (SD) sequences not recognized by host ribosomes. Because of this fact, o-ribosomes can be used to explore translational regulatory mechanisms such as coupling (10,11) and to probe ribosome structure (6,1215). Furthermore, o-ribosomes can be used to explore gene expression dynamics as they potentially provide a method for tuning translation rates. Finally, o-ribosomes may have application in synthetic biology as they introduce new functionality within cells (8,1619). O-ribosomes are duplicated ribosomes with mutations in the 30 end of 16S rRNA that alter their specificity for mRNA (59) (Figure 1). In bacteria, translation initiation is primarily mediated by interactions between the 30S ribosomal subunit and the 50 untranslated region of mRNA. Although many factors control this process, the most recognizable signal for translation is the SD sequence located approximately 612 bp upstream of the start codon (2022). Complementary base-pair interactions between the SD sequence and the 30 end of the 16S ribosomal RNA (rRNA), known as the anti-ShineDalgarno (ASD) sequence, serve to correctly position the 30S ribosomal subunit during the initiation process (2224). The strength of this interaction is thought to influence translational efficiency as mutations in either the SD or ASD sequence that weaken the interaction reduce the amount of protein made (5,25). In the case of o-ribosomes, mutations are introduced into the ASD region such that they can base pair with complementary, noncanonical SD sequences not recognized by host ribosomes (59). Initial efforts devoted towards engineering o-ribosomes in Escherichia coli involved changing two bases in the SD and ASD sequences (5,6). While these mutant ribosomes were sufficient for translating genes not recognized by host ribosomes, translation was inefficient (26). Furthermore, a number of researchers discovered that the o-ribosomes could be toxic to the cell (7,27). More recently, researchers have employed random mutagenesis and directed evolution to improve the functionality of o-ribosomes (7,8). Of notable significance is the recent work of Rackham and Chin, who proposed a novel dual-selection strategy for engineering o-ribosomes in E. coli. Unlike work in the past, their designs bypass many of the limitations associated with earlier ones, in particular toxicity. Figure 1. Comparison of canonical and orthogonal translation. (a) Translation of canonical mRNAs is performed solely by the native ribosome and not the o-ribosome. (b) Orthogonal translation is specific only to cognate o-mRNAs. The native ribosomes are unable to translate the o-mRNA. To date, o-ribosome design has either involved ad hoc or random mutagenesis-based approaches. While these approaches have clearly been successful, one question is whether a rational, computational-based strategy could be employed in design. In particular, a computational approach would enable one to explicitly explore the different elements and associated hypotheses that factor into o-ribosome design. In this work, we propose a computational strategy for designing o-ribosomes in bacteria. The basic approach in our algorithm involves enumerating all possible ASDSD pairs and then selecting those that minimally interfere with the translation of native mRNA. To demonstrate the utility of our algorithm, we experimentally tested a number of computationally designed o-ribosomes in E. coli. In the process, we were able to test a number of hypotheses regarding o-ribosome functionality. These findings should complement existing approaches based on random mutagenesis and screening. MATERIALS AND METHODS Bacterial strains, media and growth conditions All cloning steps were performed in E. coli strain DH5aZ1 (F deoR supE44 recA1 endA1 relA1 gyrA96 thi-1 ( lacZargF)U169 80 (lacZDM15) hsdR17 attB ::[PN25-tetR lacIq spcR]) (28). Subsequent experiments were conducted in E. coli strain LC100 (F ilvG rfb-50 rph-1 attB ::[PN25tetR lacIq spcR]). LC100 was constructed by P1vir transduction of the chromosomally integrated TetR/LacI expression cassette from DH5aZ1 into strain MG1655 (29). Cultures were grown in Luria-Bertani (LB) liquid media for all experiments. All media were supplemented with 20 mg/ml chloramphenicol and 100 mg/ml ampicillin. Inducers anhydrotetracycline (aTc) and isopropyl-bD-galactopyranoside (IPTG) were used at concentrations of 200 ng/ml and 1 mM, respectively, unless otherwise specified. All cultures were grown at 378C. O-ribosome expression systems For ribosomal expression in E. coli, the rRNA operon rrnB was amplified by PCR using pKK3535 (a gift from H. Noller, UCSC) (30) using primers ATAGCGGGT ACCGCCGCTGAGAAAAAGCGAAGC and ATACT GCAGTGTTCGTCTTCGGCACATAC bearing KpnI and PstI restriction sites (underlined). The resulting rrnB PCR fragment was cloned into the plasmid pZA31 (p15A origin, chloramphenicol resistance) under control of the aTc-inducible promoter PLtetO-1 (28), resulting in the plasmid pZA31-WT. Derivat (...truncated)


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Lon M. Chubiz, Christopher V. Rao. Computational design of orthogonal ribosomes, Nucleic Acids Research, 2008, pp. 4038-4046, 36/12, DOI: 10.1093/nar/gkn354