mRNA composition and control of bacterial gene expression

Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation

Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200 E. coli proteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis.

How total mRNA influences cell growth

Experimental observations tracing back to the 1960s imply that ribosome quantities play a prominent role in determining a cell's growth. Nevertheless, in biologically relevant scenarios, growth can also be influenced by the levels of mRNA and RNA polymerase. Here, we construct a quantitative model of biosynthesis providing testable scenarios for these situations. The model explores a theoretically motivated regime where RNA polymerases compete for genes and ribosomes for transcripts and gives general expressions relating growth rate, mRNA concentrations, ribosome, and RNA polymerase levels. On general grounds, the model predicts how the fraction of ribosomes in the proteome depends on total mRNA concentration and inspects an underexplored regime in which the trade-off between transcript levels and ribosome abundances sets the cellular growth rate. In particular, we show that the model predicts and clarifies three important experimental observations, in budding yeast and Escherichia coli bacteria: i) that the growth-rate cost of unneeded protein expression can be affected by mRNA levels, ii) that resource optimization leads to decreasing trends in mRNA levels at slow growth, and iii) that ribosome allocation may increase, stay constant, or decrease, in response to transcription-inhibiting antibiotics. Since the data indicate that a regime of joint limitation may apply in physiological conditions and not only to perturbations, we speculate that this regime is likely self-imposed.

Multiomics data integration, limitations, and prospects to reveal the metabolic activity of the coral holobiont

Since their radiation in the Middle Triassic period ∼240 million years ago, stony corals have survived past climate fluctuations and five mass extinctions. Their long-term survival underscores the inherent resilience of corals, particularly when considering the nutrient-poor marine environments in which they have thrived. However, coral bleaching has emerged as a global threat to coral survival, requiring rapid advancements in coral research to understand holobiont stress responses and allow for interventions before extensive bleaching occurs. This review encompasses the potential, as well as the limits, of multiomics data applications when applied to the coral holobiont. Synopses for how different omics tools have been applied to date and their current restrictions are discussed, in addition to ways these restrictions may be overcome, such as recruiting new technology to studies, utilizing novel bioinformatics approaches, and generally integrating omics data. Lastly, this review presents considerations for the design of holobiont multiomics studies to support lab-to-field advancements of coral stress marker monitoring systems. Although much of the bleaching mechanism has eluded investigation to date, multiomic studies have already produced key findings regarding the holobiont's stress response, and have the potential to advance the field further.

Elongation Factor P Is Important for Sporulation Initiation

The universally conserved protein elongation factor P (EF-P) facilitates translation at amino acids that form peptide bonds with low efficiency, particularly polyproline tracts. Despite its wide conservation, it is not essential in most bacteria and its physiological role remains unclear. Here, we show that EF-P affects the process of sporulation initiation in the bacterium Bacillus subtilis. We observe that the lack of EF-P delays expression of sporulation-specific genes. Using ribosome profiling, we observe that expression of spo0A, encoding a transcription factor that functions as the master regulator of sporulation, is lower in a Δefp strain than the wild type. Ectopic expression of Spo0A rescues the sporulation initiation phenotype, indicating that reduced spo0A expression explains the sporulation defect in Δefp cells. Since Spo0A is the earliest sporulation transcription factor, these data suggest that sporulation initiation can be delayed when protein synthesis is impaired. IMPORTANCE Elongation factor P (EF-P) is a universally conserved translation factor that prevents ribosome stalling at amino acids that form peptide bonds with low efficiency, particularly polyproline tracts. Phenotypes associated with EF-P deletion are pleiotropic, and the mechanistic basis underlying many of these phenotypes is unclear. Here, we show that the absence of EF-P affects the ability of B. subtilis to initiate sporulation by preventing normal expression of Spo0A, the key transcriptional regulator of this process. These data illustrate a mechanism that accounts for the sporulation delay and further suggest that cells are capable of sensing translation stress before committing to sporulation.

N-region of Cry1Ia: A novel fusion tag for Escherichia coli and Pichia pastoris

Secretory signal peptides (SPs) can increase enhanced green fluorescent protein (eGFP) expression in cytosol. In this study, SPs Iasp (Cry1Ia), Vasp (Vip3A), and their local sequences were used as fusion tags to compare their effects on eGFP expression in Escherichia coli MC4100 and Pichia pastoris GS115. In E coli, the solubility was almost opposite between the proteins encoded by Vegfp and Iegfp. This may be because the overall hydrophobicity of the SPs differed. When the hydrophobic H-region and C-region were removed, the negative effects on eGFP solubility of the N-regions of both SPs (IaN and VN) were significantly reduced without compromise on the expression level. IaN promotes eGFP protein yield 7.1-fold more than Iasp, and using this peptide in tandem (Ia3N) further enhanced fluorescent fusion protein solubility with an efficacy similar to that of a polycationic tag. Furthermore, the GS-IaNeGFP strain produced the highest fluorescent signal intensity when these fusion proteins were expressed in P. pastoris, and the expression was higher than in other strains, including eGFP. In conclusion, we revealed the potential of the N-region of Iasp as a fusion tag in both prokaryotic and eukaryotic cells and further demonstrated the value of the N-regions of abundant SPs.

Microbiota and Ocular Diseases

Recent advances have identified significant associations between the composition and function of the gut microbiota and various disorders in organ systems other than the digestive tract. Utilizing next-generation sequencing and multiomics approaches, the microbial community that possibly impacts ocular disease has been identified. This review provides an overview of the literature on approaches to microbiota analysis and the roles of commensal microbes in ophthalmic diseases, including autoimmune uveitis, age-related macular degeneration, glaucoma, and other ocular disorders. In addition, this review discusses the hypothesis of the "gut-eye axis" and evaluates the therapeutic potential of targeting commensal microbiota to alleviate ocular inflammation.

Real-time measurements of aminoglycoside effects on protein synthesis in live cells

The spread of antibiotic resistance is turning many of the currently used antibiotics less effective against common infections. To address this public health challenge, it is critical to enhance our understanding of the mechanisms of action of these compounds. Aminoglycoside drugs bind the bacterial ribosome, and decades of results from in vitro biochemical and structural approaches suggest that these drugs disrupt protein synthesis by inhibiting the ribosome's translocation on the messenger RNA, as well as by inducing miscoding errors. So far, however, we have sparse information about the dynamic effects of these compounds on protein synthesis inside the cell. In the present study, we measured the effect of the aminoglycosides apramycin, gentamicin, and paromomycin on ongoing protein synthesis directly in live Escherichia coli cells by tracking the binding of dye-labeled transfer RNAs to ribosomes. Our results suggest that the drugs slow down translation elongation two- to fourfold in general, and the number of elongation cycles per initiation event seems to decrease to the same extent. Hence, our results imply that none of the drugs used in this study cause severe inhibition of translocation.

Direct Measurements of Erythromycin's Effect on Protein Synthesis Kinetics in Living Bacterial Cells

Macrolide antibiotics, such as erythromycin, bind to the nascent peptide exit tunnel (NPET) of the bacterial ribosome and modulate protein synthesis depending on the nascent peptide sequence. Whereas in vitro biochemical and structural methods have been instrumental in dissecting and explaining the molecular details of macrolide-induced peptidyl-tRNA drop-off and ribosome stalling, the dynamic effects of the drugs on ongoing protein synthesis inside live bacterial cells are far less explored. In the present study, we used single-particle tracking of dye-labeled tRNAs to study the kinetics of mRNA translation in the presence of erythromycin, directly inside live Escherichia coli cells. In erythromycin-treated cells, we find that the dwells of elongator tRNA^Phe on ribosomes extend significantly, but they occur much more seldom. In contrast, the drug barely affects the ribosome binding events of the initiator tRNA^fMet. By overexpressing specific short peptides, we further find context-specific ribosome binding dynamics of tRNA^Phe, underscoring the complexity of erythromycin's effect on protein synthesis in bacterial cells.

Challenges and Perspective in Integrated Multi-Omics in Gut Microbiota Studies

The advent of omic technology has made it possible to identify viable but unculturable micro-organisms in the gut. Therefore, application of multi-omic technologies in gut microbiome studies has become invaluable for unveiling a comprehensive interaction between these commensals in health and disease. Meanwhile, despite the successful identification of many microbial and host-microbial cometabolites that have been reported so far, it remains difficult to clearly identify the origin and function of some proteins and metabolites that are detected in gut samples. However, the application of single omic techniques for studying the gut microbiome comes with its own challenges which may be overcome if a number of different omics techniques are combined. In this review, we discuss our current knowledge about multi-omic techniques, their challenges and future perspective in this field of gut microbiome studies.

Translation elongation factor P (EF-P)

Translation elongation factor P (EF-P) is conserved in all three domains of life (called eIF5A and aIF5A in eukaryotes and archaea, respectively) and functions to alleviate ribosome pausing during the translation of specific sequences, including consecutive proline residues. EF-P was identified in 1975 as a factor that stimulated the peptidyltransferase reaction in vitro but its involvement in the translation of tandem proline residues was not uncovered until 2013. Throughout the four decades of EF-P research, perceptions of EF-P function have changed dramatically. In particular, while EF-P was thought to potentiate the formation of the first peptide bond in a protein, it is now broadly accepted to act throughout translation elongation. Further, EF-P was initially reported to be essential, but recent work has shown that the requirement of EF-P for growth is conditional. Finally, it is thought that post-translational modification of EF-P is strictly required for its function but recent studies suggest that EF-P modification may play a more nuanced role in EF-P activity. Here, we review the history of EF-P research, with an emphasis on its initial isolation and characterization as well as the discoveries that altered our perceptions of its function.

Algorithms for ribosome traffic engineering and their potential in improving host cells' titer and growth rate

mRNA translation is a fundamental cellular process consuming most of the intracellular energy; thus, it is under extensive evolutionary selection for optimization, and its efficiency can affect the host's growth rate. We describe a generic approach for improving the growth rate (fitness) of any organism by introducing synonymous mutations based on comprehensive computational models. The algorithms introduce silent mutations that may improve the allocation of ribosomes in the cells via the decreasing of their traffic jams during translation respectively. As a result, resources availability in the cell changes leading to improved growth-rate. We demonstrate experimentally the implementation of the method on Saccharomyces cerevisiae: we show that by introducing a few mutations in two computationally selected genes the mutant's titer increased. Our approach can be employed for improving the growth rate of any organism providing the existence of data for inferring models, and with the relevant genomic engineering tools; thus, it is expected to be extremely useful in biotechnology, medicine, and agriculture.

Delivery of Heterologous Proteins, Enzymes, and Antigens via the Bacterial Type III Secretion System

The Type III Secretion System (T3SS) is a multimeric protein complex composed of over 20 different proteins, utilized by Gram-negative bacteria to infect eukaryotic host cells. The T3SS has been implicated as a virulence factor by which pathogens cause infection and has recently been characterized as a communication tool between bacteria and plant cells in the rhizosphere. The T3SS has been repurposed to be used as a tool for the delivery of non-native or heterologous proteins to eukaryotic cells or the extracellular space for a variety of purposes, including drug discovery and drug delivery. This review covers the methodology of heterologous protein secretion as well as multiple cases of utilizing the T3SS to deliver heterologous proteins or artificial materials. The research covered in this review will serve to outline the scope and limitations of utilizing the T3SS as a tool for protein delivery.

Bacterial growth physiology and RNA metabolism

Bacteria are sophisticated systems with high capacity and flexibility to adapt to various environmental conditions. Each prokaryote however possesses a defined metabolic network, which sets its overall metabolic capacity, and therefore the maximal growth rate that can be reached. To achieve optimal growth, bacteria adopt various molecular strategies to optimally adjust gene expression and optimize resource allocation according to the nutrient availability. The resulting physiological changes are often accompanied by changes in the growth rate, and by global regulation of gene expression. The growth-rate-dependent variation of the abundances in the cellular machineries, together with condition-specific regulatory mechanisms, affect RNA metabolism and fate and pose a challenge for rational gene expression reengineering of synthetic circuits. This article is part of a Special Issue entitled: RNA and gene control in bacteria, edited by Dr. M. Guillier and F. Repoila.

A stochastic model for simulating ribosome kinetics in vivo

Computational modelling of in vivo protein synthesis is highly complicated, as it requires the simulation of ribosomal movement over the entire transcriptome, as well as consideration of the concentration effects from 40+ different types of tRNAs and numerous other protein factors. Here I report on the development of a stochastic model for protein translation that is capable of simulating the dynamical process of in vivo protein synthesis in a prokaryotic cell containing several thousand unique mRNA sequences, with explicit nucleotide information for each, and report on a number of biological predictions which are beyond the scope of existing models. In particular, I show that, when the complex network of concentration dependent interactions between elongation factors, tRNAs, ribosomes, and other factors required for protein synthesis are included in full detail, several biological phenomena, such as the increasing peptide elongation rate with bacterial growth rate, are predicted as emergent properties of the model. The stochastic model presented here demonstrates the importance of considering the translational process at this level of detail, and provides a platform to interrogate various aspects of translation that are difficult to study in more coarse-grained models.

Efficiency of protein synthesis inhibition depends on tRNA and codon compositions

Regulation and maintenance of protein synthesis are vital to all organisms and are thus key targets of attack and defense at the cellular level. Here, we mathematically analyze protein synthesis for its sensitivity to the inhibition of elongation factor EF-Tu and/or ribosomes in dependence of the system’s tRNA and codon compositions. We find that protein synthesis reacts ultrasensitively to a decrease in the elongation factor’s concentration for systems with an imbalance between codon usages and tRNA concentrations. For well-balanced tRNA/codon compositions, protein synthesis is impeded more effectively by the inhibition of ribosomes instead of EF-Tu. Our predictions are supported by re-evaluated experimental data as well as by independent computer simulations. Not only does the described ultrasensitivity render EF-Tu a distinguished target of protein synthesis inhibiting antibiotics. It may also enable persister cell formation mediated by toxin-antitoxin systems. The strong impact of the tRNA/codon composition provides a basis for tissue-specificities of disorders caused by mutations of human mitochondrial EF-Tu as well as for the potential use of EF-Tu targeting drugs for tissue-specific treatments.

We predict and analyze the response of differently composed protein synthesis systems to the inhibition of elongation factor EF-Tu and/or ribosomes. The study reveals a strong interdependency of a protein synthesis system’s composition and its susceptibility to inhibition. This interdependency defines a generic mechanism that provides a common basis for a variety of seemingly unrelated phenomena including, for example, persister cell formation and tissue-specificity of certain mitochondrial diseases. The described mechanism applies to simple artificial translation systems as well as to complex protein synthesis in vivo.

Kinetics of d-Amino Acid Incorporation in Translation

Despite the stereospecificity of translation for l-amino acids (l-AAs) in vivo, synthetic biologists have enabled ribosomal incorporation of d-AAs in vitro toward encoding polypeptides with pharmacologically desirable properties. However, the steps in translation limiting d-AA incorporation need clarification. In this work, we compared d- and l-Phe incorporation in translation by quench-flow kinetics, measuring 250-fold slower incorporation into the dipeptide for the d isomer from a tRNA^Phe-based adaptor (tRNA^PheB). Incorporation was moderately hastened by tRNA body swaps and higher EF-Tu concentrations, indicating that binding by EF-Tu can be rate-limiting. However, from tRNA^AlaB with a saturating concentration of EF-Tu, the slow d-Phe incorporation was unexpectedly very efficient in competition with incorporation of the l isomer, indicating fast binding to EF-Tu, fast binding of the resulting complex to the ribosome, and rate-limiting accommodation/peptide bond formation. Subsequent elongation with an l-AA was confirmed to be very slow and inefficient. This understanding helps rationalize incorporation efficiencies in vitro and stereospecific mechanisms in vivo and suggests approaches for improving incorporation.

Single-Molecule Tracking Approaches to Protein Synthesis Kinetics in Living Cells

Decades of traditional biochemistry, structural approaches, and, more recently, single-molecule-based in vitro techniques have provided us with an astonishingly detailed understanding of the molecular mechanism of ribosome-catalyzed protein synthesis. However, in order to understand these details in the context of cell physiology and population biology, new techniques to probe the dynamics of molecular processes inside the cell are needed. Recent years' development in super-resolved fluorescence microscopy has revolutionized imaging of intracellular processes, and we now have the possibility to directly peek into the microcosm of biomolecules in their native environment. In this Perspective, we discuss how these methods are currently being applied and further developed to study the kinetics of protein synthesis directly inside living cells.

Co-adaption of tRNA gene copy number and amino acid usage influences translation rates in three life domains

Although more and more entangled participants of translation process were realized, how they cooperate and co-determine the final translation efficiency still lacks details. Here, we reasoned that the basic translation components, tRNAs and amino acids should be consistent to maximize the efficiency and minimize the cost. We firstly revealed that 310 out of 410 investigated genomes of three domains had significant co-adaptions between the tRNA gene copy numbers and amino acid compositions, indicating that maximum efficiency constitutes ubiquitous selection pressure on protein translation. Furthermore, fast-growing and larger bacteria are found to have significantly better co-adaption and confirmed the effect of this pressure. Within organism, highly expressed proteins and those connected to acute responses have higher co-adaption intensity. Thus, the better co-adaption probably speeds up the growing of cells through accelerating the translation of special proteins. Experimentally, manipulating the tRNA gene copy number to optimize co-adaption between enhanced green fluorescent protein (EGFP) and tRNA gene set of Escherichia coli indeed lifted the translation rate (speed). Finally, as a newly confirmed translation rate regulating mechanism, the co-adaption reflecting translation rate not only deepens our understanding on translation process but also provides an easy and practicable method to improve protein translation rates and productivity.

tRNA tracking for direct measurements of protein synthesis kinetics in live cells

Our ability to directly relate results from test tube biochemical experiments to the kinetics in living cells is very limited. Here we present experimental and analytical tools to directly study the kinetics of fast biochemical reactions in live cells. Dye-labeled molecules are electroporated into bacterial cells and tracked using super-resolved single-molecule microscopy. Trajectories are analyzed by machine-learning algorithms to directly monitor transitions between bound and free states. In particular, we measure the dwell-time of tRNAs on ribosomes, and hence achieve direct measurements of translation rates inside living cells at codon resolution. We find elongation rates with tRNA^Phe in perfect agreement with previous indirect estimates, and that once fMet-tRNA^fMet has bound to the 30S ribosomal subunit, initiation of translation is surprisingly fast and does not limit the overall rate of protein synthesis. The experimental and analytical tools for direct kinetics measurements in live cells have applications far beyond bacterial protein synthesis.

Genetic toggle switch controlled by bacterial growth rate

Background

In favorable conditions bacterial doubling time is less than 20 min, shorter than DNA replication time. In E. coli a single round of genome replication lasts about 40 min and it must be accomplished about 20 min before cell division. To achieve such fast growth rates bacteria perform multiple replication rounds simultaneously. As a result, when the division time is as short as 20 min E. coli has about 8 copies of origin of replication (ori) and the average copy number of the genes situated close to ori can be 4 times larger than those near the terminus of replication (ter). It implies that shortening of cell cycle may influence dynamics of regulatory pathways involving genes placed at distant loci.

Results

We analyze this effect in a model of a genetic toggle switch, i.e. a system of two mutually repressing genes, one localized in the vicinity of ori and the other localized in the vicinity of ter. Using a stochastic model that accounts for cell growth and divisions we demonstrate that shortening of the cell cycle can induce switching of the toggle to the state in which expression of the gene placed near ter is suppressed. The toggle bistability causes that the ratio of expression of the competing genes changes more than two orders of magnitude for a two-fold change of the doubling time. The increasing stability of the two toggle states enhances system sensitivity but also its reaction time.

Conclusions

By fusing the competing genes with fluorescent tags this mechanism could be tested and employed to create an indicator of the doubling time. By manipulating copy numbers of the competing genes and locus of the gene situated near ter, one can obtain equal average expression of both genes for any doubling time T between 20 and 120 min. Such a toggle would accurately report departures of the doubling time from T.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0483-4) contains supplementary material, which is available to authorized users.

Analysis of Translation Elongation Dynamics in the Context of an Escherichia coli Cell

Understanding the mechanisms behind translation and its rate-limiting steps is crucial for both the development of drug targets and improvement of heterologous protein production with many biotechnological applications, such as in pharmaceutical and biofuel industries. Despite many advances in the knowledge of the ribosome structure and function, there is still much discussion around the determinants of translation elongation with experiments and computational studies pointing in different directions. Here, we use a stochastic framework to simulate the process of translation in the context of an Escherichia coli cell by gathering the available biochemical data into a ribosome kinetics description. Our results from the study of translation in E. coli at different growth rates contradict the increase of mean elongation rate with growth rate established in the literature. We show that both the level of tRNA competition and the type of cognate binding interaction contribute to the modulation of elongation rate, and that optimization of a heterologous transcript for faster elongation rate is achieved by combining the two. We derive an equation that can accurately predict codon elongation rates based on the abundances of free tRNA in the cell, and can be used to assist transcript design. Finally, we show that non-cognate tRNA-ribosome binding has an important weight in translation, and plays an active role in the modulation of mean elongation rate as shown by our amino-acid starvation/surplus studies.

Elongation Factor P and the Control of Translation Elongation

Elongation factor P (EF-P) binds to ribosomes requiring assistance with the formation of oligo-prolines. In order for EF-P to associate with paused ribosomes, certain tRNAs with specific d-arm residues must be present in the peptidyl site, e.g., tRNA^Pro. Once EF-P is accommodated into the ribosome and bound to Pro-tRNA^Pro, productive synthesis of the peptide bond occurs. The underlying mechanism by which EF-P facilitates this reaction seems to have entropic origins. Maximal activity of EF-P requires a posttranslational modification in Escherichia coli, Pseudomonas aeruginosa, and Bacillus subtilis. Each of these modifications is distinct and ligated onto its respective EF-P through entirely convergent means. Here we review the facets of translation elongation that are controlled by EF-P, with a particular focus on the purpose behind the many different modifications of EF-P.

Translation elicits a growth rate-dependent, genome-wide, differential protein production in Bacillus subtilis

Complex regulatory programs control cell adaptation to environmental changes by setting condition-specific proteomes. In balanced growth, bacterial protein abundances depend on the dilution rate, transcript abundances and transcript-specific translation efficiencies. We revisited the current theory claiming the invariance of bacterial translation efficiency. By integrating genome-wide transcriptome datasets and datasets from a library of synthetic gfp-reporter fusions, we demonstrated that translation efficiencies in Bacillus subtilis decreased up to fourfold from slow to fast growth. The translation initiation regions elicited a growth rate-dependent, differential production of proteins without regulators, hence revealing a unique, hard-coded, growth rate-dependent mode of regulation. We combined model-based data analyses of transcript and protein abundances genome-wide and revealed that this global regulation is extensively used in B. subtilis We eventually developed a knowledge-based, three-step translation initiation model, experimentally challenged the model predictions and proposed that a growth rate-dependent drop in free ribosome abundance accounted for the differential protein production.

Structural characterization of the interaction of α-synuclein nascent chains with the ribosomal surface and trigger factor

The ribosome is increasingly becoming recognized as a key hub for integrating quality control processes associated with protein biosynthesis and cotranslational folding (CTF). The molecular mechanisms by which these processes take place, however, remain largely unknown, in particular in the case of intrinsically disordered proteins (IDPs). To address this question, we studied at a residue-specific level the structure and dynamics of ribosome-nascent chain complexes (RNCs) of α-synuclein (αSyn), an IDP associated with Parkinson's disease (PD). Using solution-state nuclear magnetic resonance (NMR) spectroscopy and coarse-grained molecular dynamics (MD) simulations, we find that, although the nascent chain (NC) has a highly disordered conformation, its N-terminal region shows resonance broadening consistent with interactions involving specific regions of the ribosome surface. We also investigated the effects of the ribosome-associated molecular chaperone trigger factor (TF) on αSyn structure and dynamics using resonance broadening to define a footprint of the TF-RNC interactions. We have used these data to construct structural models that suggest specific ways by which emerging NCs can interact with the biosynthesis and quality control machinery.

Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally--a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process.

Protein Synthesis in E. coli: Dependence of Codon-Specific Elongation on tRNA Concentration and Codon Usage

To synthesize a protein, a ribosome moves along a messenger RNA (mRNA), reads it codon by codon, and takes up the corresponding ternary complexes which consist of aminoacylated transfer RNAs (aa-tRNAs), elongation factor Tu (EF-Tu), and GTP. During this process of translation elongation, the ribosome proceeds with a codon-specific rate. Here, we present a general theoretical framework to calculate codon-specific elongation rates and error frequencies based on tRNA concentrations and codon usages. Our theory takes three important aspects of in-vivo translation elongation into account. First, non-cognate, near-cognate and cognate ternary complexes compete for the binding sites on the ribosomes. Second, the corresponding binding rates are determined by the concentrations of free ternary complexes, which must be distinguished from the total tRNA concentrations as measured in vivo. Third, for each tRNA species, the difference between total tRNA and ternary complex concentration depends on the codon usages of the corresponding cognate and near-cognate codons. Furthermore, we apply our theory to two alternative pathways for tRNA release from the ribosomal E site and show how the mechanism of tRNA release influences the concentrations of free ternary complexes and thus the codon-specific elongation rates. Using a recently introduced method to determine kinetic rates of in-vivo translation from in-vitro data, we compute elongation rates for all codons in Escherichia coli. We show that for some tRNA species only a few tRNA molecules are part of ternary complexes and, thus, available for the translating ribosomes. In addition, we find that codon-specific elongation rates strongly depend on the overall codon usage in the cell, which could be altered experimentally by overexpression of individual genes.

Microbial biofilm as a smart material

Microbial biofilm colonies will in many cases form a smart material capable of responding to external threats dependent on their size and internal state. The microbial community accordingly switches between passive, protective, or attack modes of action. In order to decide which strategy to employ, it is essential for the biofilm community to be able to sense its own size. The sensor designed to perform this task is termed a quorum sensor, since it only permits collective behaviour once a sufficiently large assembly of microbes have been established. The generic quorum sensor construct involves two genes, one coding for the production of a diffusible signal molecule and one coding for a regulator protein dedicated to sensing the signal molecules. A positive feedback in the signal molecule production sets a well-defined condition for switching into the collective mode. The activation of the regulator involves a slow dimerization, which allows low-pass filtering of the activation of the collective mode. Here, we review and combine the model components that form the basic quorum sensor in a number of Gram-negative bacteria, e.g., Pseudomonas aeruginosa.

Division time-based amplifiers for stochastic gene expression

While cell-to-cell variability is a phenotypic consequence of gene expression noise, sources of this noise may be complex – apart from intrinsic sources such as the random birth/death of mRNA and stochastic switching between promoter states, there are also extrinsic sources of noise such as cell division where division times are either constant or random.

Deducing the kinetics of protein synthesis in vivo from the transition rates measured in vitro

The molecular machinery of life relies on complex multistep processes that involve numerous individual transitions, such as molecular association and dissociation steps, chemical reactions, and mechanical movements. The corresponding transition rates can be typically measured in vitro but not in vivo. Here, we develop a general method to deduce the in-vivo rates from their in-vitro values. The method has two basic components. First, we introduce the kinetic distance, a new concept by which we can quantitatively compare the kinetics of a multistep process in different environments. The kinetic distance depends logarithmically on the transition rates and can be interpreted in terms of the underlying free energy barriers. Second, we minimize the kinetic distance between the in-vitro and the in-vivo process, imposing the constraint that the deduced rates reproduce a known global property such as the overall in-vivo speed. In order to demonstrate the predictive power of our method, we apply it to protein synthesis by ribosomes, a key process of gene expression. We describe the latter process by a codon-specific Markov model with three reaction pathways, corresponding to the initial binding of cognate, near-cognate, and non-cognate tRNA, for which we determine all individual transition rates in vitro. We then predict the in-vivo rates by the constrained minimization procedure and validate these rates by three independent sets of in-vivo data, obtained for codon-dependent translation speeds, codon-specific translation dynamics, and missense error frequencies. In all cases, we find good agreement between theory and experiment without adjusting any fit parameter. The deduced in-vivo rates lead to smaller error frequencies than the known in-vitro rates, primarily by an improved initial selection of tRNA. The method introduced here is relatively simple from a computational point of view and can be applied to any biomolecular process, for which we have detailed information about the in-vitro kinetics.

The proverb ‘life is motion’ also applies to the molecular scale. Indeed, if we looked into any living cell with molecular resolution, we would observe a large variety of highly dynamic processes. One particularly striking aspect of these dynamics is that all macromolecules within the cell are continuously synthesized, modified, and degraded by complex biomolecular machines. These ‘nanorobots’ follow intricate reaction pathways that form networks of molecular transitions or transformation steps. Each of these steps is stochastic and takes, on average, a certain amount of time. A fundamentally important question is how these individual step times or the corresponding transition rates determine the overall speed of the process in the cell. This question is difficult to answer, however, because the step times can only be measured in vitro but not in vivo. Here, we develop a general computational method by which one can deduce the individual step times in vivo from their in-vitro values. In order to demonstrate the predictive power of our method, we apply it to protein synthesis by ribosomes, a key process of gene expression, and validate the deduced step times by three independent sets of in-vivo data.

A 'resource allocator' for transcription based on a highly fragmented T7 RNA polymerase

Synthetic genetic systems share resources with the host, including machinery for transcription and translation. Phage RNA polymerases (RNAPs) decouple transcription from the host and generate high expression. However, they can exhibit toxicity and lack accessory proteins (σ factors and activators) that enable switching between different promoters and modulation of activity. Here, we show that T7 RNAP (883 amino acids) can be divided into four fragments that have to be co-expressed to function. The DNA-binding loop is encoded in a C-terminal 285-aa ‘σ fragment’, and fragments with different specificity can direct the remaining 601-aa ‘core fragment’ to different promoters. Using these parts, we have built a resource allocator that sets the core fragment concentration, which is then shared by multiple σ fragments. Adjusting the concentration of the core fragment sets the maximum transcriptional capacity available to a synthetic system. Further, positive and negative regulation is implemented using a 67-aa N-terminal ‘α fragment’ and a null (inactivated) σ fragment, respectively. The α fragment can be fused to recombinant proteins to make promoters responsive to their levels. These parts provide a toolbox to allocate transcriptional resources via different schemes, which we demonstrate by building a system which adjusts promoter activity to compensate for the difference in copy number of two plasmids.

Size of quorum sensing communities

Ensembles of bacteria are able to coordinate their phenotypic behavior in accordance with the size, density, and growth state of the ensemble. This is achieved through production and exchange of diffusible signal molecules in a cell-cell regulatory system termed quorum sensing. In the generic quorum sensor a positive feedback in the production of signal molecules defines the conditions at which the collective behavior switches on. In spite of its conceptual simplicity, a proper measure of biofilm colony "size" appears to be lacking. We establish that the cell density multiplied by a geometric factor which incorporates the boundary conditions constitutes an appropriate size measure. The geometric factor is the square of the radius for a spherical colony or a hemisphere attached to a reflecting surface. If surrounded by a rapidly exchanged medium, the geometric factor is divided by three. For a disk-shaped biofilm the geometric factor is the horizontal dimension multiplied by the height, and the square of the height of the biofilm if there is significant flow above the biofilm. A remarkably simple factorized expression for the size is obtained, which separates the all-or-none ignition caused by the positive feedback from the smoother activation outside the switching region.

Understanding the influence of codon translation rates on cotranslational protein folding

Protein domains can fold into stable tertiary structures while they are synthesized by the ribosome in a process known as cotranslational folding. If a protein does not fold cotranslationally, however, it has the opportunity to do so post-translationally, that is, after the nascent chain has been fully synthesized and released from the ribosome. The rate at which a ribosome adds an amino acid encoded by a particular codon to the elongating nascent chain can vary significantly and is called the codon translation rate. Recent experiments have illustrated the profound impact that codon translation rates can have on the cotranslational folding process and the acquisition of function by nascent proteins. Synonymous codon mutations in an mRNA molecule change the chemical identity of a codon and its translation rate without changing the sequence of the synthesized protein. This change in codon translation rate can, however, cause a nascent protein to malfunction as a result of cotranslational misfolding. In some situations, such dysfunction can have profound implications; for example, it can alter the substrate specificity of an ABC transporter protein, resulting in patients who are nonresponsive to chemotherapy treatment. Thus, codon translation rates are crucial in coordinating protein folding in a cellular environment and can affect downstream cellular processes that depend on the proper functioning of newly synthesized proteins. As the importance of codon translation rates makes clear, a necessary aspect of fully understanding cotranslational folding lies in considering the kinetics of the process in addition to its thermodynamics. In this Account, we examine the contributions that have been made to elucidating the mechanisms of cotranslational folding by using the theoretical and computational tools of chemical kinetics, molecular simulations, and systems biology. These efforts have extended our ability to understand, model, and predict the influence of codon translation rates on cotranslational protein folding and misfolding. The application of such approaches to this important problem is creating a framework for making quantitative predictions of the impact of synonymous codon substitutions on cotranslational folding that has led to a novel hypothesis regarding the role of fast-translating codons in coordinating cotranslational folding. In addition, it is providing new insights into proteome-wide cotranslational folding behavior and making it possible to identify potential molecular mechanisms by which molecular chaperones can influence such behavior during protein synthesis. As we discuss in this Account, bringing together these theoretical developments with experimental approaches is increasingly helping answer fundamental questions about the nature of nascent protein folding on the ribosome.

DnaA dynamics could be linked with fitness cost in bacteria

Fitness cost is the measure of the metabolic burden of unneeded gene expression. It is defined as the lag in bacterial cells growth harboring unneeded genes relative to unburdened cells. Separate cells can concurrently adapt to the burden, demonstrating a decrease in or even a disappearance of the lag. The precise mechanisms of this adaptation are not clearly understood. One possibility is that an increased amount of free ribosomes "absorb" the unnecessary burden. In this work, the mechanism by which an increased concentration of ribosomes could result in faster growth and mask the unneeded gene expression burden is discussed. The initiation time of chromosome replication by the initiator protein DnaA, for which the accumulation speed depends on the ribosomes amount, is taken into account.

Stability of bacterial toggle switches is enhanced by cell-cycle lengthening by several orders of magnitude

Bistable regulatory elements are important for nongenetic inheritance, increase of cell-to-cell heterogeneity allowing adaptation, and robust responses at the population level. Here, we study computationally the bistable genetic toggle switch-a small regulatory network consisting of a pair of mutual repressors-in growing and dividing bacteria. We show that as cells with an inhibited growth exhibit high stability of toggle states, cell growth and divisions lead to a dramatic increase of toggling rates. The toggling rates were found to increase with rate of cell growth, and can be up to six orders of magnitude larger for fast growing cells than for cells with the inhibited growth. The effect is caused mainly by the increase of protein and mRNA burst sizes associated with the faster growth. The observation that fast growth dramatically destabilizes toggle states implies that rapidly growing cells may vigorously explore the epigenetic landscape enabling nongenetic evolution, while cells with inhibited growth adhere to the local optima. This can be a clever population strategy that allows the slow growing (but stress resistant) cells to survive long periods of unfavorable conditions. Simultaneously, at favorable conditions, this stress resistant (but slowly growing-or not growing) subpopulation may be replenished due to a high switching rate from the fast growing population.

Co-translational mechanisms of protein maturation

Protein biogenesis integrates multiple finely regulated mechanisms, ensuring nascent polypeptide chains are correctly enzymatically processed, targeted to membranes and folded to native structure. Recent studies show that the cellular translation machinery serves as hub that coordinates the maturation events in space and time at various levels. The ribosome itself serves as docking site for a multitude of nascent chain-interacting factors. The movement of ribosomes along open reading frames is non-uniformous and includes pausing sites, which facilitates nascent chain folding and perhaps factor engagement. Here we summarize current knowledge and discuss emerging concepts underlying the critical interplay between translation and protein maturation in E. coli.

The significance of translation regulation in the stress response

Background

The stress response in bacteria involves the multistage control of gene expression but is not entirely understood. To identify the translational response of bacteria in stress conditions and assess its contribution to the regulation of gene expression, the translational states of all mRNAs were compared under optimal growth condition and during nutrient (isoleucine) starvation.

Results

A genome-scale study of the translational response to nutritional limitation was performed in the model bacterium Lactococcus lactis. Two measures were used to assess the translational status of each individual mRNA: the fraction engaged in translation (ribosome occupancy) and ribosome density (number of ribosomes per 100 nucleotides). Under isoleucine starvation, half of the mRNAs considered were translationally down-regulated mainly due to decreased ribosome density. This pattern concerned genes involved in growth-related functions such as translation, transcription, and the metabolism of fatty acids, phospholipids and bases, contributing to the slowdown of growth. Only 4% of the mRNAs were translationally up-regulated, mostly related to prophagic expression in response to stress. The remaining genes exhibited antagonistic regulations of the two markers of translation. Ribosome occupancy increased significantly for all the genes involved in the biosynthesis of isoleucine, although their ribosome density had decreased. The results revealed complex translational regulation of this pathway, essential to cope with isoleucine starvation.

To elucidate the regulation of global gene expression more generally, translational regulation was compared to transcriptional regulation under isoleucine starvation and to other post-transcriptional regulations related to mRNA degradation and mRNA dilution by growth. Translational regulation appeared to accentuate the effects of transcriptional changes for down-regulated growth-related functions under isoleucine starvation although mRNA stabilization and lower dilution by growth counterbalanced this effect.

Conclusions

We show that the contribution of translational regulation to the control of gene expression is significant in the stress response. Post-transcriptional regulation is complex and not systematically co-directional with transcription regulation. Post-transcriptional regulation is important to the understanding of gene expression control.

In vivo biochemistry in bacterial cells using FRAP: insight into the translation cycle

In vivo measurements of the mobility and binding kinetics of cellular components are essential to fully understand the biochemical processes occurring inside cells. Here, we describe a fluorescence recovery after photobleaching-based method that can be easily implemented to the study of reaction-diffusion processes in live bacteria despite their small size. We apply this method to provide new, to our knowledge, quantitative insight into multiple aspects of the bacterial translation cycle by measuring the binding kinetics and the micrometer-scale diffusive properties of the 50S ribosomal subunit in live Caulobacter cells. From our measurements, we infer that 70% of 50S subunits are engaged in translation and display, on average, limited motion on the micrometer scale, consistent with little mixing of transcripts undergoing translation. We also extract the average rate constants for the binding of 50S subunits to 30S initiation complexes during initiation and for their release from mRNAs when translation is completed. From this, we estimate the average time of protein synthesis and the average search time of 50S subunits before they engage in the next initiation event. Additionally, our experiments suggest that so-called free 50S subunits do not diffuse freely; instead their mobility is significantly slowed down, possibly through transient associations with mRNA.

N-terminal domains in two-domain proteins are biased to be shorter and predicted to fold faster than their C-terminal counterparts

Computational analysis of proteomes in all kingdoms of life reveals a strong tendency for N-terminal domains in two-domain proteins to have shorter sequences than their neighboring C-terminal domains. Given that folding rates are affected by chain length, we asked whether the tendency for N-terminal domains to be shorter than their neighboring C-terminal domains reflects selection for faster-folding N-terminal domains. Calculations of absolute contact order, another predictor of folding rate, provide additional evidence that N-terminal domains tend to fold faster than their neighboring C-terminal domains. A possible explanation for this bias, which is more pronounced in prokaryotes than in eukaryotes, is that faster folding of N-terminal domains reduces the risk for protein aggregation during folding by preventing formation of nonnative interdomain interactions. This explanation is supported by our finding that two-domain proteins with a shorter N-terminal domain are much more abundant than those with a shorter C-terminal domain.

Dissecting specific and global transcriptional regulation of bacterial gene expression

Gene expression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional--but often neglected--layer of complexity in gene expression. Here, we develop an experimental-computational approach to dissect specific and global regulation in the bacterium Escherichia coli. By using fluorescent promoter reporters, we show that global regulation is growth rate dependent not only during steady state but also during dynamic changes in growth rate and can be quantified through two promoter-specific parameters. By applying our approach to arginine biosynthesis, we obtain a quantitative understanding of both specific and global regulation that allows accurate prediction of the temporal response to simultaneous perturbations in arginine availability and growth rate. We thereby uncover two principles of joint regulation: (i) specific regulation by repression dominates the transcriptional response during metabolic steady states, largely repressing the biosynthesis genes even when biosynthesis is required and (ii) global regulation sets the maximum promoter activity that is exploited during the transition between steady states.

In vivo translation rates can substantially delay the cotranslational folding of the Escherichia coli cytosolic proteome

A question of fundamental importance concerning protein folding in vivo is whether the kinetics of translation or the thermodynamics of the ribosome nascent chain (RNC) complex is the major determinant of cotranslational folding behavior. This is because translation rates can reduce the probability of cotranslational folding below that associated with arrested ribosomes, whose behavior is determined by the equilibrium thermodynamics of the RNC complex. Here, we combine a chemical kinetic equation with genomic and proteomic data to predict domain folding probabilities as a function of nascent chain length for Escherichia coli cytosolic proteins synthesized on both arrested and continuously translating ribosomes. Our results indicate that, at in vivo translation rates, about one-third of the Escherichia coli cytosolic proteins exhibit cotranslational folding, with at least one domain in each of these proteins folding into its stable native structure before the full-length protein is released from the ribosome. The majority of these cotranslational folding domains are influenced by translation kinetics which reduces their probability of cotranslational folding and consequently increases the nascent chain length at which they fold into their native structures. For about 20% of all cytosolic proteins this delay in folding can exceed the length of the completely synthesized protein, causing one or more of their domains to switch from co- to posttranslational folding solely as a result of the in vivo translation rates. These kinetic effects arise from the difference in time scales of folding and amino-acid addition, and they represent a source of metastability in Escherichia coli's proteome.

Trigger factor slows co-translational folding through kinetic trapping while sterically protecting the nascent chain from aberrant cytosolic interactions

The E. coli chaperone trigger factor (TF) interacts directly with nascent polypeptide chains as they emerge from the ribosome exit tunnel. Small protein domains can fold under the cradle created by TF, but the co-translational folding of larger proteins is slowed down by its presence. Because of the great experimental challenges in achieving high spatial and time resolution, it is not yet known whether or not TF alters the folding properties of small proteins and if the reduced rate of folding of larger proteins is the result of kinetic or thermodynamic effects. We show, by molecular simulations employing a coarse-grained model of a series of ribosome nascent-chain complexes, that TF does not alter significantly the co-translational folding process of a small protein G domain but delays that of a large β-galactosidase domain as a result of kinetic trapping of its unfolded ensemble. We demonstrate that this trapping occurs through a combination of three distinct mechanisms: a decrease in the rate of structural rearrangements within the nascent chain, an increase in the effective exit tunnel length due to folding outside the cradle, and entanglement of the nascent chain with TF. We present evidence that this TF-induced trapping represents a trade-off between promoting co-translational folding and sterically shielding the nascent chain from aberrant cytosolic interactions that could lead to its aggregation or degradation.