Preparation of tRNAArg for Arginylation Assay by In Vitro Transcription.

This chapter describes the preparation of tRNAArg by in vitro transcription. tRNA produced by this method can be efficiently utilized for in vitro arginylation assays, following aminoacylation with Arg-tRNA synthetase, either directly during the arginylation reaction or separately to produce the purified preparation of Arg-tRNAArg. tRNA charging is described in other chapters of this book.

Preparation of an Enriched tRNAArg Fraction for Arginylation by Expression in E. coli.

The method described here provides a fast and efficient way to obtain an enriched preparation of tRNA of interest, which is also posttranscriptionally modified by the intracellular machinery of the host cells, E. coli. While this preparation also contains a mixture of total E. coli tRNA, the enriched tRNA of interest is obtained in high yields (milligram) and is highly efficient for biochemical assays in vitro. It is routinely used in our lab for arginylation.

Enzymatic Aminoacylation of tRNAArg Using Recombinant Arg-tRNA Synthetase.

This chapter describes the preparation of pre-charged Arg-tRNA that can be used in arginylation reaction. While in a typical arginylation reaction arginyl-tRNA synthetase (RARS) is normally included as a component of the reaction and continually charges tRNA during arginylation, it is sometimes necessary to separate the charging and the arginylation step, in order to perform each reaction under controlled conditions, e.g., for measuring the kinetics or determining the effect of different compounds and chemicals on the reaction. In such cases, tRNAArg can be pre-charged with Arg and purified away from the RARS enzyme prior to arginylation.

Functional Interplay between Arginyl-tRNA Synthetases and Arginyltransferase.

Protein arginylation, mediated by arginyltransferase ATE1, is a post-translational modification of emerging biological importance that consists of transfer of the amino acid Arg to protein and peptide substrates. ATE1 utilizes charged tRNAArg as the donor of the arginyl group, which depends on the activity of Arg-tRNA synthetases (RARS) and is also utilized in translation. The mechanisms that regulate the functional balance among ATE1, RARS and translation are unknown. Here, we addressed the question of how these two enzymes can partition Arg-tRNAArg to functionally distinct pathways using an intracellular arginylation sensor in cell lines with overexpression or deletion of ATE1 and RARS isoforms. We found that arginylation levels depend on the physiological state of the cells but are not directly affected by translation activity or the availability of RARS isoforms. However, displacement of RARS from the multi-synthetase complex leads to an increase in intracellular arginylation independently of RARS enzymatic activity. This effect is accompanied by ATE1's redistribution into the cytosol. Our results provide the first comprehensive analysis of the interdependence among translation, arginyl-tRNA synthesis and arginylation.

Availability of Arg, but Not tRNA, Is a Rate-Limiting Factor for Intracellular Arginylation.

Protein arginylation, mediated by arginyltransferase ATE1, is a posttranslational modification of emerging biological importance that consists of transfer of the amino acid Arg from tRNA to protein and peptide targets. ATE1 can bind tRNA and exhibits specificity toward particular tRNA types, but its dependence on the availability of the major components of the arginylation reaction has never been explored. Here we investigated key intracellular factors that can potentially regulate arginylation in vivo, including several tRNA types that show strong binding to ATE1, as well as availability of free Arg, in an attempt to identify intracellular rate limiting steps for this enzyme. Our results demonstrate that, while modulation of tRNA levels in cells does not lead to any changes in intracellular arginylation efficiency, availability of free Arg is a potentially rate-limiting factor that facilitates arginylation if added to the cultured cells. Our results broadly outline global pathways that may be involved in the regulation of arginylation in vivo.

Purification and Use of tRNA for Enzymatic Post-translational Addition of Amino Acids to Proteins.

Post-translational addition of amino acids to proteins by enzymes using aminoacyl-tRNA is an emerging regulatory mechanism. Examples include Arg transfer in eukaryotes, Leu/Phe transfer in bacteria, and tRNA-synthetase-mediated addition of amino acids to Lys side chains. Here, we present a method of purification and use of tRNA for such reactions, focusing on tRNAArg and its use for arginylation. This method can also be used for other tRNA-mediated reactions. For complete details on the use and execution of this protocol, please refer to Avcilar-Kucukgoze et al. (2020).

tRNAArg-Derived Fragments Can Serve as Arginine Donors for Protein Arginylation.

Arginyltransferase ATE1 mediates posttranslational arginylation and plays key roles in multiple physiological processes. ATE1 utilizes arginyl (Arg)-tRNAArg as the donor of Arg, putting this reaction into a direct competition with the protein synthesis machinery. Here, we address the question of ATE1- Arg-tRNAArg specificity as a potential mechanism enabling this competition in vivo. Using in vitro arginylation assays and Ate1 knockout models, we find that, in addition to full-length tRNA, ATE1 is also able to utilize short tRNAArg fragments that bear structural resemblance to tRNA-derived fragments (tRF), a recently discovered class of small regulatory non-coding RNAs with global emerging biological role. Ate1 knockout cells show a decrease in tRFArg generation and a significant increase in the ratio of tRNAArg:tRFArg compared with wild type, suggesting a functional link between tRFArg and arginylation. We propose that generation of physiologically important tRFs can serve as a switch between translation and protein arginylation.

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology.

Transfer tRNAs (tRNAs) are small non-coding RNAs that are highly conserved in all kingdoms of life. Originally discovered as the molecules that deliver amino acids to the growing polypeptide chain during protein synthesis, tRNAs have been believed for a long time to play exclusive role in translation. However, recent studies have identified key roles for tRNAs and tRNA-derived small RNAs in multiple other processes, including regulation of transcription and translation, posttranslational modifications, stress response, and disease. These emerging roles suggest that tRNAs may be central players in the complex machinery of biological regulatory pathways. Here we overview these non-canonical roles of tRNA in normal physiology and disease, focusing largely on eukaryotic and mammalian systems.

Rewiring host activities for synthetic circuit production: a translation view.

The expression of synthetic circuits in host organisms, or chassis, is a key aspect of synthetic biology. Design adjustments made for maximal production may negatively affect the central metabolism and biosynthetic activities of the chassis host. Here, we review recent attempts to modulate synthetic circuit design for optimal production and present models that precisely capture the trade-off between circuit production and chassis growth. We also present emerging concepts for full orthogonalization of synthetic productivity and its decoupling from the endogenous biosynthetic activities of the cell, opening new routes towards robust synthetic circuit expression.

Discharging tRNAs: a tug of war between translation and detoxification in Escherichia coli.

Translation is a central cellular process and is optimized for speed and fidelity. The speed of translation of a single codon depends on the concentration of aminoacyl-tRNAs. Here, we used microarray-based approaches to analyze the charging levels of tRNAs in Escherichia coli growing at different growth rates. Strikingly, we observed a non-uniform aminoacylation of tRNAs in complex media. In contrast, in minimal medium, the level of aminoacyl-tRNAs is more uniform and rises to approximately 60%. Particularly, the charging level of tRNA(Ser), tRNA(Cys), tRNA(Thr) and tRNA(His) is below 50% in complex medium and their aminoacylation levels mirror the degree that amino acids inhibit growth when individually added to minimal medium. Serine is among the most toxic amino acids for bacteria and tRNAs(Ser) exhibit the lowest charging levels, below 10%, at high growth rate although intracellular serine concentration is plentiful. As a result some serine codons are among the most slowly translated codons. A large fraction of the serine is most likely degraded by L-serine-deaminase, which competes with the seryl-tRNA-synthetase that charges the tRNAs(Ser) These results indicate that the level of aminoacylation in complex media might be a competition between charging for translation and degradation of amino acids that inhibit growth.

A Minimal Model of Ribosome Allocation Dynamics Captures Trade-offs in Expression between Endogenous and Synthetic Genes.

Cells contain a finite set of resources that must be distributed across many processes to ensure survival. Among them, the largest proportion of cellular resources is dedicated to protein translation. Synthetic biology often exploits these resources in executing orthogonal genetic circuits, yet the burden this places on the cell is rarely considered. Here, we develop a minimal model of ribosome allocation dynamics capturing the demands on translation when expressing a synthetic construct together with endogenous genes required for the maintenance of cell physiology. Critically, it contains three key variables related to design parameters of the synthetic construct covering transcript abundance, translation initiation rate, and elongation time. We show that model-predicted changes in ribosome allocation closely match experimental shifts in synthetic protein expression rate and cellular growth. Intriguingly, the model is also able to accurately infer transcript levels and translation times after further exposure to additional ambient stress. Our results demonstrate that a simple model of resource allocation faithfully captures the redistribution of protein synthesis resources when faced with the burden of synthetic gene expression and environmental stress. The tractable nature of the model makes it a versatile tool for exploring the guiding principles of efficient heterologous expression and the indirect interactions that can arise between synthetic circuits and their host chassis because of competition for shared translational resources.