Tetsuya Yomo

Constructive Approaches for Understanding the Origin of Self-Replication and Evolution

The mystery of the origin of life can be divided into two parts. The first part is the origin of biomolecules: under what physicochemical conditions did biomolecules such as amino acids, nucleotides, and their polymers arise? The second part of the mystery is the origin of life-specific functions such as the replication of genetic information, the reproduction of cellular structures, metabolism, and evolution. These functions require the coordination of many different kinds of biological molecules. A direct strategy to approach the second part of the mystery is the constructive approach, in which life-specific functions are recreated in a test tube from specific biological molecules. Using this approach, we are able to employ design principles to reproduce life-specific functions, and the knowledge gained through the reproduction process provides clues as to their origins. In this mini-review, we introduce recent insights gained using this approach, and propose important future directions for advancing our understanding of the origins of life.

Density-Dependent Recycling Promotes the Long-Term Survival of Bacterial Populations during Periods of Starvation

ABSTRACT The amount of natural resources in the Earth’s environment is in flux, which can trigger catastrophic collapses of ecosystems. How populations survive under nutrient-poor conditions is a central question in ecology. Curiously, some bacteria persist for a long time in nutrient-poor environments. Although this survival may be accomplished through cell death and the recycling of dead cells, the importance of these processes and the mechanisms underlying the survival of the populations have not been quantitated. Here, we use microbial laboratory experiments and mathematical models to demonstrate that death and recycling are essential activities for the maintenance of cell survival. We also show that the behavior of the survivors is governed by population density feedback, wherein growth is limited not only by the available resources but also by the population density. The numerical simulations suggest that population density-dependent recycling could be an advantageous behavior under starvation conditions. IMPORTANCE How organisms survive after exhaustion of resources is a central question in ecology. Starving Escherichia coli constitute a model system to understand survival mechanisms during long-term starvation. Although death and the recycling of dead cells might play a key role in the maintenance of long-term survival, their mechanisms and importance have not been quantitated. Here, we verified the significance of social recycling of dead cells for long-term survival. We also show that the survivors restrained their recycling and did not use all available nutrients released from dead cells, which may be advantageous under starvation conditions. These results indicate that not only the utilization of dead cells but also restrained recycling coordinate the effective utilization of limited resources for long-term survival under starvation. IMPORTANCE How organisms survive after exhaustion of resources is a central question in ecology. Starving Escherichia coli constitute a model system to understand survival mechanisms during long-term starvation. Although death and the recycling of dead cells might play a key role in the maintenance of long-term survival, their mechanisms and importance have not been quantitated. Here, we verified the significance of social recycling of dead cells for long-term survival. We also show that the survivors restrained their recycling and did not use all available nutrients released from dead cells, which may be advantageous under starvation conditions. These results indicate that not only the utilization of dead cells but also restrained recycling coordinate the effective utilization of limited resources for long-term survival under starvation.

Reaction dynamics analysis of a reconstituted Escherichia coli protein translation system by computational modeling

Significance Biological systems are driven by multiple components and interactions that form a complex reaction network. We developed a method to analyze their dynamics by focusing on the component in temporal plateaus, or a quasi-stationary state (QSS). The analyses, using a computational model of a minimal in vitro protein synthesis system, showed that components in a QSS form clusters that grow over time. However, the growth is not in a linear fashion: The process involved collapse and regrowth of the formed clusters, where the collapse was closely related to the phase transition in the reaction network. These observations suggest that the studies focusing on the QSS might be useful for understanding of complex reaction dynamics. To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro protein synthesis system. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand these complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure, and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion, and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale biological reactions by visualizing complex dynamics, thereby extracting the characteristics of the reaction network, including phase transitions.

De novo design and synthesis of a 30-cistron translation-factor module

Abstract Two of the many goals of synthetic biology are synthesizing large biochemical systems and simplifying their assembly. While several genes have been assembled together by modular idempotent cloning, it is unclear if such simplified strategies scale to very large constructs for expression and purification of whole pathways. Here we synthesize from oligodeoxyribonucleotides a completely de-novo-designed, 58-kb multigene DNA. This BioBrick plasmid insert encodes 30 of the 31 translation factors of the PURE translation system, each His-tagged and in separate transcription cistrons. Dividing the insert between three high-copy expression plasmids enables the bulk purification of the aminoacyl-tRNA synthetases and translation factors necessary for affordable, scalable reconstitution of an in vitro transcription and translation system, PURE 3.0.

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

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 Escherichia coli strain with one of the essential genes complemented with a plasmid. We performed the combinatorial selection using an RNA encoding serS and obtained more replicable RNA encoding functional serS 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.

A decay effect of bacterial growth rate associated with genome reduction

Bacterial growth is an important topic in microbiology and of crucial importance to better understand living cells. Bacterial growth dynamics are quantitatively examined using various methods to determine the physical, chemical or biological features of growing populations. Due to methodological differences, the exponential growth rate, which is a parameter that is representative of growth dynamics, should be differentiated. This study experimentally verified the differentiation in growth rates attributed to different methodologies, and demonstrated that the most popular method, optical turbidity, led to the determination of a lower growth rate in comparison to the methods based on colony formation and ATP abundance, due to a decay effect of reading OD600 during a population increase. Accordingly, the logistic model, which is often applied to growth data reading the OD600, was revised by introducing a new parameter: the decay rate, to compensate for the lowered estimation in growth rates. The modified logistic model not only presented an improved goodness of fit in comparison to the original model but also led to an intriguing finding of a correlation between genome reduction and the decay rate. The decay effect seemed to be partially attributed to the decrease in cell size accompanied by a population increase and was medium dependent. In summary, the present study provides not only a better theoretical tool for the high-throughput studies on bacterial growth dynamics linking with experimental data using optical turbidity to the theoretical analysis with biological importance, but also a valuable insight for understanding the genome evolution and fitness increase in microbial life.

Automated in vitro evolution of a translation-coupled RNA replication system in a droplet flow reactor

Automation is a useful strategy to make laborious evolutionary experiments faster and easier. To date, several types of continuous flow reactors have been developed for the automated evolutionary experiments of viruses and bacteria. However, the development of a flow reactor applicable to compartmentalized in vitro self-replication systems is still a challenge. In this study, we demonstrate automated in vitro evolution of a translation-coupled RNA system in a droplet flow reactor for the first time. This reactor contains approximately 1010 micro-scale droplets (average diameter is approximately 0.8 μm), which continuously fuse and divide among each other at a controllable rate. In the droplets, an RNA (artificial genomic RNA) replicate through the translation of self-encoded RNA replicase with spontaneously appearing parasitic RNA. We performed two automated replication experiments for more than 400u2009hours with different mixing intensities. We found that several mutations displayed increased frequencies in the genomic RNA populations and the dominant RNA mutants acquired the ability to replicate faster or acquired resistance to the parasitic RNA, demonstrating that Darwinian evolution occurred during the long-term replication. The droplet flow reactor we developed can be a useful tool to perform in vitro evolutionary experiments of translation-coupled systems.

Self-replication of circular DNA by a self-encoded DNA polymerase through rolling-circle replication and recombination

A major challenge in constructing artificial cells is the establishment of a recursive genome replication system coupled with gene expression from the genome itself. One of the simplest schemes of recursive DNA replication is the rolling-circle replication of a circular DNA coupled with recombination. In this study, we attempted to develop a replication system based on this scheme using self-encoded phi29 DNA polymerase and externally supplied Cre recombinase. We first identified that DNA polymerization is significantly inhibited by Cre recombinase. To overcome this problem, we performed in vitro evolution and obtained an evolved circular DNA that can replicate efficiently in the presence of the recombinase. We also showed evidence that during replication of the evolved DNA, the circular DNA was reproduced through recombination by Cre recombinase. These results demonstrate that the evolved circular DNA can reproduce itself through gene expression of a self-encoded polymerase. This study provides a step forward in developing a simple recursive DNA replication system for use in an artificial cell.

Development of an Automated UV Irradiation Device for Microbial Cell Culture

Ultraviolet (UV) mutagenesis is a widely used technique to increase bacterial mutation rates in laboratory experiments. UV mutagenesis requires fine regulation of UV dose, because the number of dead cells increases exponentially as the dose increases. Ignoring this hazard can cause extinction of UV-exposed populations. Therefore, an automated system that cooperatively conducts both growth measurement and UV irradiation is needed for efficient UV mutagenesis experiments. To address this task, we constructed an automated UV irradiation device for microbial cell culture. This device can measure cell density and irradiate the bacterial cells with UV light automatically according to the state of cell growth. We demonstrated that this growth feedback control avoided extinction and enabled accumulation of mutations in bacterial genomes at a rapid rate for a long period. Whole-genome sequencing revealed the high accumulation rate, neutrality, and spectrum of UV-induced mutations. These characteristics were all consistent with those obtained by manual UV irradiation. These results indicate that our automated device is useful in accelerating mutation accumulation over a long duration.

A decay effect of the growth rate associated with genome reduction in Escherichia coli

BackgroundBacterial growth is an important topic in microbiology and of crucial importance to better understand living cells. Bacterial growth dynamics are quantitatively examined using various methods to determine the physical, chemical or biological features of growing populations. Due to methodological differences, the exponential growth rate, which is a parameter that is representative of growth dynamics, should be differentiated. Ignoring such differentiation in the growth analysis might overlook somehow slight but significant changes in cellular features of the growing population. Both experimental and theoretical investigations are required to address these issues.ResultsThis study experimentally verified the differentiation in growth rates attributed to different methodologies, and demonstrated that the most popular method, optical turbidity, led to the determination of a lower growth rate in comparison to the methods based on colony formation and cellular adenosine triphosphate, due to a decay effect of reading OD600 during a population increase. Accordingly, the logistic model, which is commonly applied to the high-throughput growth data reading the OD600, was revised by introducing a new parameter: the decay rate, to compensate for the lowered estimation in growth rates. An improved goodness of fit in comparison to the original model was acquired due to this revision. Applying the modified logistic model to hundreds of growth data acquired from an assortment of Escherichia coli strains carrying the reduced genomes led to an intriguing finding of a correlation between the decay rate and the genome size. The decay effect seemed to be partially attributed to the decrease in cell size accompanied by a population increase and was medium dependent.ConclusionsThe present study provides not only an improved theoretical tool for the high-throughput studies on bacterial growth dynamics linking with optical turbidity to biological meaning, but also a novel insight of the genome reduction correlated decay effect, which potentially reflects the changing cellular features during population increase. It is valuable for understanding the genome evolution and the fitness increase in microbial life.