Adaptive Evolution of an Artificial RNA Genome to a Reduced Ribosome Environment

The reconstitution of an artificial system that has the same evolutionary ability as a living thing is a major challenge in the <i>in vitro</i> synthetic biology. In this study, we tested the adaptive evolutionary ability of an artificial RNA genome replication system, termed the translation-coupled RNA replication (TcRR) system. In a previous work, we performed a study of the long-term evolution of the genome with an excess amount of ribosome. In this study, we continued the evolution experiment in a reduced-ribosome environment and observed that the mutant genome compensated for the reduced ribosome concentration. This result demonstrated the ability of the TcRR system to adapt and may be a step toward generating living things with evolutionary ability

Effects of Compartment Size on the Kinetics of Intracompartmental Multimeric Protein Synthesis

The cell contents are encapsulated within a compartment, the volume of which is a fundamental physical parameter that may affect intracompartmental reactions. However, there have been few studies to elucidate whether and how volume changes alone can affect the reaction kinetics. It is difficult to address these questions <i>in vivo</i>, because forced cell volume changes, e.g., by osmotic inflation/deflation, globally alters the internal state. Here, we prepared artificial cell-like compartments with different volumes but with identical constituents, which is not possible with living cells, and synthesized two tetrameric enzymes, β-glucuronidase (GUS) and β-galactosidase (GAL), by cell-free protein synthesis. Tetrameric GUS but not GAL was synthesized more quickly in smaller compartments. The difference between the two was dependent on the rate-limiting step and the reaction order. The observed acceleration mechanism would be applicable to living cells as multimeric protein synthesis in a microcompartment is ubiquitous <i>in vivo</i>

Combinatorial selection for replicable RNA by Qβ replicase while maintaining encoded gene function

<div><p>Construction of a complex artificial self-replication system is challenging in the field of in vitro synthetic biology. Recently, we developed a translation-coupled RNA replication system, wherein an artificial genomic RNA replicates with the Qβ RNA replicase gene encoded on itself. The challenge is to introduce additional genes into the RNA to develop a complex system that mimics natural living systems. However, most RNA sequence encoding genes are not replicable by the Qβ replicase owing to its requirement for strong secondary structures throughout the RNA sequence that are absent in most genes. In this study, we establish a new combinatorial selection method to find an RNA sequence with secondary structures and functional amino acid sequences of the encoded gene. We selected RNA sequences based on their in vitro replication and in vivo gene functions. First, we used the α-domain gene of β-galactosidase as a model-encoding gene, with functional selection based on blue-white screening. Through the combinatorial selection, we developed more replicable RNAs while maintaining the function of the encoded α-domain. The selected sequence improved the affinity between the minus strand RNA and Qβ replicase. Second, we established an in vivo selection method applicable to a broader range of genes by using an <i>Escherichia coli</i> strain with one of the essential genes complemented with a plasmid. We performed the combinatorial selection using an RNA encoding <i>serS</i> and obtained more replicable RNA encoding functional <i>serS</i> gene. These results suggest that combinatorial selection methods are useful for the development of RNA sequences replicable by Qβ replicase while maintaining the encoded gene function.</p></div