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.

Absolute values of protein expression levels in cells are crucial information for understanding cellular biological systems. Precise quantification of proteins can be achieved by liquid chromatography (LC)–mass spectrometry (MS) analysis of enzymatic digests of proteins in the presence of isotope-labeled internal standards. Thus, development of a simple and easy way for the preparation of internal standards is advantageous for the analyses of multiple target proteins, which will allow systems-level studies. Here we describe a method, termed MS-based Quantification By isotope-labeled Cell-free products (MS-QBiC), which provides the simple and high-throughput preparation of internal standards by using a reconstituted cell-free protein synthesis system, and thereby facilitates both multiplexed and sensitive quantification of absolute amounts of target proteins. This method was applied to a systems-level dynamic analysis of mammalian circadian clock proteins, which consist of transcription factors and protein kinases that govern central and peripheral circadian clocks in mammals. Sixteen proteins from 20 selected circadian clock proteins were successfully quantified from mouse liver over a 24-h time series, and 14 proteins had circadian variations. Quantified values were applied to detect internal body time using a previously developed molecular timetable method. The analyses showed that single time-point data from wild-type mice can predict the endogenous state of the circadian clock, whereas data from clock mutant mice are not applicable because of the disappearance of circadian variation.

During translation in Escherichia coli, the ribosome rescue factor YaeJ and the alternative ribosome rescue factor (ArfA, previously called YhdL) can release stalled ribosomes from mRNA. Here, I used a reconstituted cell-free protein synthesis system to examine YaeJ- and ArfA-dependent recycling of stalled ribosomes, in which mRNA lacks in-frame stop codons. It is shown that YaeJ alone could recycle the ribosome but that ArfA required the presence of release factor 2 (RF2). Furthermore, I show that RF2 binds to stalled ribosomes only in the presence of ArfA, demonstrating that ArfA recruits RF2 into the A site of the ribosome to facilitate peptidyl-tRNA hydrolysis. It is also demonstrated that the efficiency of the ArfA-dependent process decreases rapidly with an increase in mRNA length downstream of the A site of the ribosome whereas YaeJ function is maintained on mRNA with sufficient length. From the results, I discuss differences of in vivo roles of these two systems in addition to the well-known tmRNA-dependent trans-translation system.Graphical AbstractDownload high-res image (114KB)Download full-size imageHighlights► YaeJ- and ArfA-dependent ribosome rescue processes were analyzed. ► YaeJ alone can facilitate several cycles of ribosomal turnover. ► ArfA requires RF2 for the stalled ribosome recycling. ► RF2 can bind to the ribosome dependently on the presence of ArfA. ► Difference between YaeJ- and ArfA-dependent ribosome rescue systems was clarified.