Regulation of Translation by the Redox State of Elongation Factor G in the Cyanobacterium Synechocystis sp. PCC 6803

Elongation factor G (EF-G), a key protein in translational elongation, was identified as a primary target of inactivation by reactive oxygen species within the translational machinery of the cyanobacterium Synechocystis sp. PCC 6803 (Kojima, K., Oshita, M., Nanjo, Y., Kasai, K., Tozawa, Y., Hayashi, H., and Nishiyama, Y. (2007) Mol. Microbiol. 65, 936–947). In the present study, we found that inactivation of EF-G (Slr1463) by H₂O₂ was attributable to the oxidation of two specific cysteine residues and formation of a disulfide bond. Substitution of these cysteine residues by serine residues protected EF-G from inactivation by H₂O₂ and allowed the EF-G to mediate translation in a translation system in vitro that had been prepared from Synechocystis. The disulfide bond in oxidized EF-G was reduced by thioredoxin, and the resultant reduced form of EF-G regained the activity to mediate translation in vitro. Western blotting analysis showed that levels of the oxidized form of EF-G increased under strong light in a mutant that lacked NADPH-thioredoxin reductase, indicating that EF-G is reduced by thioredoxin in vivo. These observations suggest that the translational machinery is regulated by the redox state of EF-G, which is oxidized by reactive oxygen species and reduced by thioredoxin, a transmitter of reducing signals generated by the photosynthetic transport of electrons.Reactive oxygen species (ROS)² are produced as inevitable by-products of the light-driven reactions of photosynthesis. The superoxide radical, hydrogen peroxide (H₂O₂), and the hydroxyl radical are produced as a result of the photosynthetic transport of electrons, whereas singlet state oxygen (singlet oxygen) is produced by the transfer of excitation energy (1). Exposure of the photosynthetic machinery to strong light promotes the production of ROS and gives rise to oxidative stress (1).Strong light rapidly inactivates photosystem II (PSII). This phenomenon is referred to as photoinhibition (2–4), and it occurs when the rate of photodamage to PSII exceeds the rate of the repair of photodamaged PSII (5). The actions of ROS in the photoinhibition of PSII have been studied extensively, and several mechanisms for photoinhibition have been proposed (5). Recent studies of the effects of ROS on photodamage and repair have revealed that ROS act primarily by inhibiting the repair of photodamaged PSII and not by damaging PSII directly (5–9). Such studies have also shown that photodamage to PSII is an exclusively light-dependent event; photodamage is initiated by disruption of the manganese cluster of the oxygen-evolving complex upon absorption of light, in particular UV and blue light, with subsequent damage to the reaction center upon absorption of visible light by chlorophylls (10–12).Inhibition of the repair of PSII has been attributed to the suppression, by ROS, of the synthesis de novo of proteins that are required for the repair of PSII, such as the D1 protein, which forms a heterodimer with the D2 protein in the reaction center, in the cyanobacterium Synechocystis sp. PCC 6803 (hereafter referred to as Synechocystis) (6, 7), in Chlamydomonas (13), and in plants (14, 15). Analysis of polysomes in Synechocystis has demonstrated that ROS inhibit the synthesis de novo of proteins primarily at the elongation step of translation, suggesting that some proteins involved in translational elongation might be the targets of inactivation by ROS (6, 7).A translation system in vitro was successfully prepared from Synechocystis, and biochemical investigations using this translation system have revealed that elongation factor G (EF-G), a GTP-binding protein that catalyzes the translocation of peptidyl-tRNA (16), is a primary target of inactivation by ROS (17). EF-G is reversibly inactivated by ROS in a redox-dependent manner; it is inactive in the oxidized form and active in the reduced form (17). Moreover, it has been proposed that changes in the activity of EF-G might depend on and be regulated by the redox states of cysteine residues within EF-G (17). However, the specific cysteine residues within EF-G that might be the targets of ROS and might be responsible for redox regulation remain to be determined.In the present study, we investigated the redox state of Slr1463, the EF-G that is phylogenetically closest to chloroplast EF-G among three homologs of EF-G in Synechocystis (17). We determined that two specific cysteine residues in the EF-G of Synechocystis were targets of oxidation by ROS. The resultant disulfide bond between the two cysteine residues was efficiently reduced by thioredoxin. In addition, we observed that EF-G was reduced by thioredoxin in vivo. Our findings revealed the mechanism of the ROS-induced inactivation of EF-G and suggested a mechanism for the redox regulation of translation by electrons generated during photosynthesis.     

Systematically Ranking the Tightness of Membrane Association for Peripheral Membrane Proteins (PMPs)

Large-scale quantitative evaluation of the tightness of membrane association for nontransmembrane proteins is important for identifying true peripheral membrane proteins with functional significance. Herein, we simultaneously ranked more than 1000 proteins of the photosynthetic model organism Synechocystis sp. PCC 6803 for their relative tightness of membrane association using a proteomic approach. Using multiple precisely ranked and experimentally verified peripheral subunits of photosynthetic protein complexes as the landmarks, we found that proteins involved in two-component signal transduction systems and transporters are overall tightly associated with the membranes, whereas the associations of ribosomal proteins are much weaker. Moreover, we found that hypothetical proteins containing the same domains generally have similar tightness. This work provided a global view of the structural organization of the membrane proteome with respect to divergent functions, and built the foundation for future investigation of the dynamic membrane proteome reorganization in response to different environmental or internal stimuli.The cells of living organisms contain different types of membranes performing uniquely specific functions that are largely dictated by their protein compositions. Membrane proteome typically contains integral membrane proteins (IMPs)¹ with one or more transmembrane domains (TM) and peripheral membrane proteins (PMPs) without TM. PMPs usually interact with IMPs and function together as protein complexes, as typically demonstrated by the peripheral subunits of the membrane protein complexes such as photosystem (PS) I, PSII, the F₁F₀-ATP synthase, and ABC type transporters (1–6). Identification of the PMPs is important for the understanding of the underlying mechanism of various membrane related functions, and could help to discover novel functionally important membrane protein complexes.Large-scale identification of PMPs were typically performed by identification of the total proteins from the isolated whole membranes from which PMPs were predicted by the absence of TM using topology prediction software such as TMHMM (7), or by identification of the proteins extracted from the intact whole membranes with chaotropic reagents such as high concentration salts, urea, or high pH solution (8–13). These methods can identify some non-TM containing proteins uniquely from the membrane fraction. However, in most cases the majority of the non-TM containing proteins identified with such methods can also be identified from the soluble fraction that is expected to consist of mainly cytoplasmic proteins. Therefore, it is necessary to evaluate whether the non-TM containing proteins identified from the membranes are true PMPs or just some carry-over contaminant from the soluble fraction during sample fractionation. Unfortunately, the high throughput method to perform such an evaluation is still lacking, and such a method is a pressing need considering the ever-increasing number of identified proteins from a single proteomic study.The unicellular photosynthetic cyanobacterium Synechocystis sp. PCC 6803 (hereafter referred to as Synechocystis) is an ideal organism for studies in membrane proteomics. Synechocystis is the first cyanobacterium with a completely sequenced genome and contains large numbers of membrane structures (12–14). The organism can naturally take up foreign DNA from environment and integrate it into its genome through homologous recombination, making it simple to perform target mutagenesis for the validation of functional significance of proteins screened from high throughput approaches. The autotrophic growth ability allows Synechocystis to emerge as a potential cost-effective cell factory for producing clean and renewable biofuels to deal with the world-wide crisis of energy shortage and environmental pollution (15–18). Functional proteomics have great potential in the identification of novel target proteins and for discovering and optimizing novel protein networks for the generation of biofuel-producing strains with higher efficiency and less cost.We separated Synechocystis whole cell lysates into membrane and soluble fractions, and identified the proteins in each fraction with unprecedented coverage using high-resolution MS. We present a novel method and its rationale for evaluating the tightness of membrane association for all non-TM containing proteins identified in both fractions. This built a foundation for the large-scale identification of bona fide peripheral membrane proteins, particularly for the hypothetical and unknown proteins that are not known to be physically or functionally associated with the membranes.     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]