Effect of ribosome shielding on mRNA stability

Less is more: slow-codon windows enhance eGFP mRNA resilience against RNA interference

Extensive efforts have been devoted to enhancing the translation efficiency of mRNA delivered to mammalian cells via codon optimization. However, the impact of codon choice on mRNA stability remains underexplored. In this study, we investigated the influence of codon usage on mRNA degradation kinetics in cultured human cell lines using live-cell imaging on single-cell arrays. By measuring mRNA lifetimes at the single-cell level for synthetic mRNA constructs, we confirmed that mRNAs containing slowly translated codon windows have shorter lifetimes. Unexpectedly, these mRNAs did not exhibit decreased stability in the presence of small interfering RNA (siRNA) compared with the unmutated sequence, suggesting an interference of different concurrent degradation mechanisms. We employed stochastic simulations to predict ribosome density along the open reading frame, revealing that the ribosome densities correlated with mRNA stability in a cell-type- and codon-position-specific manner. In summary, our results suggest that the effect of codon choice and its influence on mRNA lifetime is context-dependent with respect to cell type, codon position and RNA interference.

The contribution of mRNA targeting to spatial protein localization in bacteria

About 30% of all bacterial proteins execute their function outside of the cytosol and must be inserted into or translocated across the cytoplasmic membrane. This requires efficient targeting systems that recognize N-terminal signal sequences in client proteins and deliver them to protein transport complexes in the membrane. While the importance of these protein transport machineries for the spatial organization of the bacterial cell is well documented in multiple studies, the contribution of mRNA targeting and localized translation to protein transport is only beginning to emerge. mRNAs can exhibit diverse subcellular localizations in the bacterial cell and can accumulate at sites where new protein is required. This is frequently observed for mRNAs encoding membrane proteins, but the physiological importance of membrane enrichment of mRNAs and the consequences it has for the insertion of the encoded protein have not been explored in detail. Here, we briefly highlight some basic concepts of signal sequence-based protein targeting and describe in more detail strategies that enable the monitoring of mRNA localization in bacterial cells and potential mechanisms that route mRNAs to particular positions within the cell. Finally, we summarize some recent developments that demonstrate that mRNA targeting and localized translation can sustain membrane protein insertion under stress conditions when the protein-targeting machinery is compromised. Thus, mRNA targeting likely acts as a back-up strategy and complements the canonical signal sequence-based protein targeting.

The missing part: the Archaeoglobus fulgidus Argonaute forms a functional heterodimer with an N-L1-L2 domain protein

Argonaute (Ago) proteins are present in all three domains of life (bacteria, archaea and eukaryotes). They use small (15-30 nucleotides) oligonucleotide guides to bind complementary nucleic acid targets and are responsible for gene expression regulation, mobile genome element silencing, and defence against viruses or plasmids. According to their domain organization, Agos are divided into long and short Agos. Long Agos found in prokaryotes (long-A and long-B pAgos) and eukaryotes (eAgos) comprise four major functional domains (N, PAZ, MID and PIWI) and two structural linker domains L1 and L2. The majority (∼60%) of pAgos are short pAgos, containing only the MID and inactive PIWI domains. Here we focus on the prokaryotic Argonaute AfAgo from Archaeoglobus fulgidus DSM4304. Although phylogenetically classified as a long-B pAgo, AfAgo contains only MID and catalytically inactive PIWI domains, akin to short pAgos. We show that AfAgo forms a heterodimeric complex with a protein encoded upstream in the same operon, which is a structural equivalent of the N-L1-L2 domains of long pAgos. This complex, structurally equivalent to a long PAZ-less pAgo, outperforms standalone AfAgo in guide RNA-mediated target DNA binding. Our findings provide a missing piece to one of the first and the most studied pAgos.

Physical modeling of ribosomes along messenger RNA: Estimating kinetic parameters from ribosome profiling experiments using a ballistic model

Gene expression is the synthesis of proteins from the information encoded on DNA. One of the two main steps of gene expression is the translation of messenger RNA (mRNA) into polypeptide sequences of amino acids. Here, by taking into account mRNA degradation, we model the motion of ribosomes along mRNA with a ballistic model where particles advance along a filament without excluded volume interactions. Unidirectional models of transport have previously been used to fit the average density of ribosomes obtained by the experimental ribo-sequencing (Ribo-seq) technique in order to obtain the kinetic rates. The degradation rate is not, however, accounted for and experimental data from different experiments are needed to have enough parameters for the fit. Here, we propose an entirely novel experimental setup and theoretical framework consisting in splitting the mRNAs into categories depending on the number of ribosomes from one to four. We solve analytically the ballistic model for a fixed number of ribosomes per mRNA, study the different regimes of degradation, and propose a criterion for the quality of the inverse fit. The proposed method provides a high sensitivity to the mRNA degradation rate. The additional equations coming from using the monosome (single ribosome) and polysome (arbitrary number) ribo-seq profiles enable us to determine all the kinetic rates in terms of the experimentally accessible mRNA degradation rate.

The essential role of mRNA degradation in understanding and engineering E. coli metabolism

Metabolic engineering strategies are crucial for the development of bacterial cell factories with improved performance. Until now, optimal metabolic networks have been designed based on systems biology approaches integrating large-scale data on the steady-state concentrations of mRNA, protein and metabolites, sometimes with dynamic data on fluxes, but rarely with any information on mRNA degradation. In this review, we compile growing evidence that mRNA degradation is a key regulatory level in E. coli that metabolic engineering strategies should take into account. We first discuss how mRNA degradation interacts with transcription and translation, two other gene expression processes, to balance transcription regulation and remove poorly translated mRNAs. The many reciprocal interactions between mRNA degradation and metabolism are also highlighted: metabolic activity can be controlled by changes in mRNA degradation and in return, the activity of the mRNA degradation machinery is controlled by metabolic factors. The mathematical models of the crosstalk between mRNA degradation dynamics and other cellular processes are presented and discussed with a view towards novel mRNA degradation-based metabolic engineering strategies. We show finally that mRNA degradation-based strategies have already successfully been applied to improve heterologous protein synthesis. Overall, this review underlines how important mRNA degradation is in regulating E. coli metabolism and identifies mRNA degradation as a key target for innovative metabolic engineering strategies in biotechnology.

Translational autoregulation of RF2 protein in E. coli through programmed frameshifting

Various feedback mechanisms regulate the expression of different genes to ensure the required protein levels inside a cell. In this paper, we develop a kinetic model for one such mechanism that autoregulates RF2 protein synthesis in E. coli through programmed frameshifting. The model finds that the programmed frameshifting autoregulates RF2 protein synthesis by two independent mechanisms. First, it increases the rate of RF2 synthesis from each mRNA transcript at low RF2 concentration. Second, programmed frameshifting can dramatically increase the lifetime of RF2 transcripts when RF2 protein levels are lower than a threshold. This sharp increase in mRNA lifetime is caused by a first-order phase transition from a low to a high ribosome density on an RF2 transcript. The high ribosome density prevents the transcript's degradation by shielding it from nucleases, which increases its average lifetime and hence RF2 protein levels. Our study identifies this quality control mechanism that regulates the cellular protein levels by breaking the hierarchy of processes involved in gene expression.

Coupled Transcription-Translation in Prokaryotes: An Old Couple With New Surprises

Coupled transcription-translation (CTT) is a hallmark of prokaryotic gene expression. CTT occurs when ribosomes associate with and initiate translation of mRNAs whose transcription has not yet concluded, therefore forming "RNAP.mRNA.ribosome" complexes. CTT is a well-documented phenomenon that is involved in important gene regulation processes, such as attenuation and operon polarity. Despite the progress in our understanding of the cellular signals that coordinate CTT, certain aspects of its molecular architecture remain controversial. Additionally, new information on the spatial segregation between the transcriptional and the translational machineries in certain species, and on the capability of certain mRNAs to localize translation-independently, questions the unanimous occurrence of CTT. Furthermore, studies where transcription and translation were artificially uncoupled showed that transcription elongation can proceed in a translation-independent manner. Here, we review studies supporting the occurrence of CTT and findings questioning its extent, as well as discuss mechanisms that may explain both coupling and uncoupling, e.g., chromosome relocation and the involvement of cis- or trans-acting elements, such as small RNAs and RNA-binding proteins. These mechanisms impact RNA localization, stability, and translation. Understanding the two options by which genes can be expressed and their consequences should shed light on a new layer of control of bacterial transcripts fate.

Hfq-Assisted RsmA Regulation Is Central to Pseudomonas aeruginosa Biofilm Polysaccharide PEL Expression

To appropriately switch between sessile and motile lifestyles, bacteria control expression of biofilm-associated genes through multiple regulatory elements. In Pseudomonas aeruginosa, the post-transcriptional regulator RsmA has been implicated in the control of various genes including those related to biofilms, but much of the evidence for these links is limited to transcriptomic and phenotypic studies. RsmA binds to target mRNAs to modulate translation by affecting ribosomal access and/or mRNA stability. Here, we trace a global regulatory role of RsmA to inhibition of the expression of Vfr—a transcription factor that inhibits transcriptional regulator FleQ. FleQ directly controls biofilm-associated genes that encode the PEL polysaccharide biosynthesis machinery. Furthermore, we show that RsmA alone cannot bind vfr mRNA but requires the assistance of RNA chaperone protein Hfq. This is the first example where a RsmA protein family member requires another protein for binding to its target RNA.

Competitive effects in bacterial mRNA decay

In living organisms, the same enzyme catalyses the degradation of thousands of different mRNAs, but the possible influence of competing substrates has been largely ignored so far. We develop a simple mechanistic model of the coupled degradation of all cell mRNAs using the total quasi-steady-state approximation of the Michaelis-Menten framework. Numerical simulations of the model using carefully chosen parameters and analyses of rate sensitivity coefficients show how substrate competition alters mRNA decay. The model predictions reproduce and explain a number of experimental observations on mRNA decay following transcription arrest, such as delays before the onset of degradation, the occurrence of variable degradation profiles with increased non linearities and the negative correlation between mRNA half-life and concentration. The competition acts at different levels, through the initial concentration of cell mRNAs and by modifying the enzyme affinity for its targets. The consequence is a global slow down of mRNA decay due to enzyme titration and the amplification of its apparent affinity. Competition happens to stabilize weakly affine mRNAs and to destabilize the most affine ones. We believe that this mechanistic model is an interesting alternative to the exponential models commonly used for the determination of mRNA half-lives. It allows analysing regulatory mechanisms of mRNA degradation and its predictions are directly comparable to experimental data.

Computational discovery and modeling of novel gene expression rules encoded in the mRNA

The transcript is populated with numerous overlapping codes that regulate all steps of gene expression. Deciphering these codes is very challenging due to the large number of variables involved, the non-modular nature of the codes, biases and limitations in current experimental approaches, our limited knowledge in gene expression regulation across the tree of life, and other factors. In recent years, it has been shown that computational modeling and algorithms can significantly accelerate the discovery of novel gene expression codes. Here, we briefly summarize the latest developments and different approaches in the field.

RNA localization in prokaryotes: Where, when, how, and why

Only recently has it been recognized that the transcriptome of bacteria and archaea can be spatiotemporally regulated. All types of prokaryotic transcripts-rRNAs, tRNAs, mRNAs, and regulatory RNAs-may acquire specific localization and these patterns can be temporally regulated. In some cases bacterial RNAs reside in the vicinity of the transcription site, but in many others, transcripts show distinct localizations to the cytoplasm, the inner membrane, or the pole of rod-shaped species. This localization, which often overlaps with that of the encoded proteins, can be achieved either in a translation-dependent or translation-independent fashion. The latter implies that RNAs carry sequence-level features that determine their final localization with the aid of RNA-targeting factors. Localization of transcripts regulates their posttranscriptional fate by affecting their degradation and processing, translation efficiency, sRNA-mediated regulation, and/or propensity to undergo RNA modifications. By facilitating complex assembly and liquid-liquid phase separation, RNA localization is not only a consequence but also a driver of subcellular spatiotemporal complexity. We foresee that in the coming years the study of RNA localization in prokaryotes will produce important novel insights regarding the fundamental understanding of membrane-less subcellular organization and lead to practical outputs with biotechnological and therapeutic implications. This article is categorized under: RNA Export and Localization > RNA Localization Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

Marcksb plays a key role in the secretory pathway of zebrafish Bmp2b

During vertebrate early embryogenesis, the ventral development is directed by the ventral-to-dorsal activity gradient of the bone morphogenetic protein (BMP) signaling. As secreted ligands, the extracellular traffic of BMP has been extensively studied. However, it remains poorly understood that how BMP ligands are secreted from BMP-producing cells. In this work, we show the dominant role of Marcksb controlling the secretory process of Bmp2b via interaction with Hsp70 in vivo. We firstly carefully characterized the role of Marcksb in promoting BMP signaling during dorsoventral axis formation through knockdown approach. We then showed that Marcksb cell autonomously regulates the trafficking of Bmp2b from producing cell to the extracellular space and both the total and the extracellular Bmp2b was decreased in Marcksb-deficient embryos. However, neither the zygotic mutant of marcksb (Zmarcksb) nor the maternal zygotic mutant of marcksb (MZmarcksb) showed any defects of dorsalization. In contrast, the MZmarcksb embryos even showed increased BMP signaling activity as measured by expression of BMP targets, phosphorylated Smad1/5/9 levels and imaging of Bmp2b, suggesting that a phenomenon of “genetic over-compensation” arose. Finally, we revealed that the over-compensation effects of BMP signaling in MZmarcksb was achieved through a sequential up-regulation of MARCKS-family members Marcksa, Marcksl1a and Marcksl1b, and MARCKS-interacting protein Hsp70.3. We concluded that the Marcksb modulates BMP signaling through regulating the secretory pathway of Bmp2b.

Bone morphogenetic proteins (BMPs) are extracellular proteins which belong to the transforming growth factor-β (TGF-β) superfamily. BMP signaling is essential for embryonic development, organogenesis, and tissue regeneration and homeostasis, and tightly linked to various diseases and tumorigenesis. However, as secreted proteins, how BMPs are transported and secreted from BMP-producing cells remains poorly understood. In this study, we showed that Marcksb interacts with a molecular chaperon–Hsp70.3 to mediate the secretory pathway of BMP ligands during early development of zebrafish. Moreover, we discovered a novel phenomenon of “genetic over-compensation” in the genetic knock-out mutants of marcksb. To our knowledge, this is the first report that reveals the molecules and their related trafficking system mediating the secretion of BMPs. Considering the wide distribution of BMP and MARCKS within the human body, our work may shed light on the studies of BMPs secretion in organogenesis and adult tissue homeostasis. The finding of MARCKS in controlling BMP secretion may provide potential therapeutic targets for modulating the activity of BMP signaling and thus will be of interest to clinical research.

Inverted translational control of eukaryotic gene expression by ribosome collisions

The canonical model of eukaryotic translation posits that efficient translation initiation increases protein expression and mRNA stability. Contrary to this model, we find that increasing initiation rate can decrease both protein expression and stability of certain mRNAs in the budding yeast Saccharomyces cerevisiae. These mRNAs encode a stretch of polybasic residues that cause ribosome stalling. Our computational modeling predicts that the observed decrease in gene expression at high initiation rates occurs when ribosome collisions at stalls stimulate abortive termination of the leading ribosome or cause endonucleolytic mRNA cleavage. Consistent with this prediction, the collision-associated quality-control factors Asc1 and Hel2 (orthologs of human RACK1 and ZNF598, respectively) decrease gene expression from stall-containing mRNAs only at high initiation rates. Remarkably, hundreds of S. cerevisiae mRNAs that contain ribosome stall sequences also exhibit lower translation efficiency. We propose that inefficient translation initiation allows these stall-containing endogenous mRNAs to escape collision-stimulated reduction in gene expression.

Higher rates of translation counterintuitively lead to lower protein levels from eukaryotic mRNAs that encode ribosome stalls; modelling suggests that this occurs when ribosome collisions at stalls trigger abortive termination of the leading ribosome or cause endonucleolytic mRNA cleavage.

Optimizing the dynamics of protein expression

Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences.

Networks of ribosome flow models for modeling and analyzing intracellular traffic

The ribosome flow model with input and output (RFMIO) is a deterministic dynamical system that has been used to study the flow of ribosomes during mRNA translation. The input of the RFMIO controls its initiation rate and the output represents the ribosome exit rate (and thus the protein production rate) at the 3′ end of the mRNA molecule. The RFMIO and its variants encapsulate important properties that are relevant to modeling ribosome flow such as the possible evolution of “traffic jams” and non-homogeneous elongation rates along the mRNA molecule, and can also be used for studying additional intracellular processes such as transcription, transport, and more. Here we consider networks of interconnected RFMIOs as a fundamental tool for modeling, analyzing and re-engineering the complex mechanisms of protein production. In these networks, the output of each RFMIO may be divided, using connection weights, between several inputs of other RFMIOs. We show that under quite general feedback connections the network has two important properties: (1) it admits a unique steady-state and every trajectory converges to this steady-state; and (2) the problem of how to determine the connection weights so that the network steady-state output is maximized is a convex optimization problem. These mathematical properties make these networks highly suitable as models of various phenomena: property (1) means that the behavior is predictable and ordered, and property (2) means that determining the optimal weights is numerically tractable even for large-scale networks. For the specific case of a feed-forward network of RFMIOs we prove an additional useful property, namely, that there exists a spectral representation for the network steady-state, and thus it can be determined without any numerical simulations of the dynamics. We describe the implications of these results to several fundamental biological phenomena and biotechnological objectives.

AU-Rich Long 3' Untranslated Region Regulates Gene Expression in Bacteria

3′ untranslated regions (3′ UTRs) and particularly long 3′ UTRs have been shown to act as a new class of post-transcriptional regulatory element. We previously reported that hmsT mRNA stability is negatively regulated by the 3′ UTR of hmsT in Yersinia pestis. To investigate more general effects of 3′ UTRs in Y. pestis, we selected 15 genes potentially possessing long 3′ UTRs with different AU content and constructed their 3′ UTR deletion mutants. Deletion of AU-rich 3′ UTRs increased mRNA levels, whereas deletion of 3′ UTRs with normal AU content resulted in slight or no changes in the mRNA level. In addition, we found that PNPase was important for 3′ UTR-mediated mRNA decay when the transcriptional terminator was Rho-dependent. Finally, we showed that ribosomes promote mRNA stability when bound to a 3′ UTR. Our findings suggest that functional 3′ UTRs might be broadly distributed in bacteria and their novel regulatory mechanisms require further investigation.

Controllability Analysis and Control Synthesis for the Ribosome Flow Model

The ribosomal density along different parts of the coding regions of the mRNA molecule affects various fundamental intracellular phenomena including: protein production rates, global ribosome allocation and organismal fitness, ribosomal drop off, co-translational protein folding, mRNA degradation, and more. Thus, regulating translation in order to obtain a desired ribosomal profile along the mRNA molecule is an important biological problem. We study this problem by using a dynamical model for mRNA translation, called the ribosome flow model (RFM). In the RFM, the mRNA molecule is modeled as an ordered chain of $n$ sites. The RFM includes $n$ state-variables describing the ribosomal density profile along the mRNA molecule, and the transition rates from each site to the next are controlled by $n+1$ positive constants. To study the problem of controlling the density profile, we consider some or all of the transition rates as time-varying controls. We consider the following problem: given an initial and a desired ribosomal density profile in the RFM, determine the time-varying values of the transition rates that steer the system to the desired density profile, if they exist. More specifically, we consider two control problems. In the first, all transition rates can be regulated separately, and the goal is to steer the ribosomal density profile and the protein production rate from a given initial value to a desired value. In the second problem, one or more transition rates are jointly regulated by a single scalar control, and the goal is to steer the production rate to a desired value within a certain set of feasible values. In the first case, we show that the system is controllable, i.e., the control is powerful enough to steer the system to any desired value in finite time, and provide simple closed-form expressions for constant positive control functions (or transition rates) that asymptotically steer the system to the desired value. In the second case, we show that the system is controllable, and provide a simple algorithm for determining the constant positive control value that asymptotically steers the system to the desired value. We discuss some of the biological implications of these results.

Bacterial regulatory RNAs: complexity, function, and putative drug targeting

Over the past decade, RNA-deep sequencing has uncovered copious non-protein coding RNAs (npcRNAs) in bacteria. Many of them are key players in the regulation of gene expression, taking part in various regulatory circuits, such as metabolic responses to different environmental stresses, virulence, antibiotic resistance, and host-pathogen interactions. This has contributed to the high adaptability of bacteria to changing or even hostile environments. Their mechanisms include the regulation of transcriptional termination, modulation of translation, and alteration of messenger RNA (mRNA) stability, as well as protein sequestration. Here, the mechanisms of gene expression by regulatory bacterial npcRNAs are comprehensively reviewed and supplemented with well-characterized examples. This class of molecules and their mechanisms of action might be useful targets for the development of novel antibiotics.

The Chemical Fluctuation Theorem governing gene expression

Gene expression is a complex stochastic process composed of numerous enzymatic reactions with rates coupled to hidden cell-state variables. Despite advances in single-cell technologies, the lack of a theory accurately describing the gene expression process has restricted a robust, quantitative understanding of gene expression variability among cells. Here we present the Chemical Fluctuation Theorem (CFT), providing an accurate relationship between the environment-coupled chemical dynamics of gene expression and gene expression variability. Combined with a general, accurate model of environment-coupled transcription processes, the CFT provides a unified explanation of mRNA variability for various experimental systems. From this analysis, we construct a quantitative model of transcription dynamics enabling analytic predictions for the dependence of mRNA noise on the mRNA lifetime distribution, confirmed against stochastic simulation. This work suggests promising new directions for quantitative investigation into cellular control over biological functions by making complex dynamics of intracellular reactions accessible to rigorous mathematical deductions.

A unified framework to understand gene expression noise is still lacking. Here the authors derive a universal theorem relating the biological noise with dynamics of birth and death processes and present a model of transcription dynamics, allowing analytical prediction of the dependence of mRNA noise on mRNA lifetime variability.

Ribosome flow model with extended objects

We study a deterministic mechanistic model for the flow of ribosomes along the mRNA molecule, called the ribosome flow model with extended objects (RFMEO). This model encapsulates many realistic features of translation including non-homogeneous transition rates along mRNA, the fact that every ribosome covers several codons, and the fact that ribosomes cannot overtake one another. The RFMEO is a mean-field approximation of an important model from statistical mechanics called the totally asymmetric simple exclusion process with extended objects (TASEPEO). We demonstrate that the RFMEO describes biophysical aspects of translation better than previous mean-field approximations, and that its predictions correlate well with those of TASEPEO. However, unlike TASEPEO, the RFMEO is amenable to rigorous analysis using tools from systems and control theory. We show that the ribosome density profile along the mRNA in the RFMEO converges to a unique steady-state density that depends on the length of the mRNA, the transition rates along it, and the number of codons covered by every ribosome, but not on the initial density of ribosomes along the mRNA. In particular, the protein production rate also converges to a unique steady state. Furthermore, if the transition rates along the mRNA are periodic with a common period T then the ribosome density along the mRNA and the protein production rate converge to a unique periodic pattern with period T, that is, the model entrains to periodic excitations in the transition rates. Analysis and simulations of the RFMEO demonstrate several counterintuitive results. For example, increasing the ribosome footprint may sometimes lead to an increase in the production rate. Also, for large values of the footprint the steady-state density along the mRNA may be quite complex (e.g. with quasi-periodic patterns) even for relatively simple (and non-periodic) transition rates along the mRNA. This implies that inferring the transition rates from the ribosome density may be non-trivial. We believe that the RFMEO could be useful for modelling, understanding and re-engineering translation as well as other important biological processes.

Optimal Translation Along a Circular mRNA

The ribosome flow model on a ring (RFMR) is a deterministic model for ribosome flow along a circularized mRNA. We derive a new spectral representation for the optimal steady-state production rate and the corresponding optimal steady-state ribosomal density in the RFMR. This representation has several important advantages. First, it provides a simple and numerically stable algorithm for determining the optimal values even in very long rings. Second, it enables efficient computation of the sensitivity of the optimal production rate to small changes in the transition rates along the mRNA. Third, it implies that the optimal steady-state production rate is a strictly concave function of the transition rates. Maximizing the optimal steady-state production rate with respect to the rates under an affine constraint on the rates thus becomes a convex optimization problem that admits a unique solution. This solution can be determined numerically using highly efficient algorithms. This optimization problem is important, for example, when re-engineering heterologous genes in a host organism. We describe the implications of our results to this and other aspects of translation.

Regulatory 3' Untranslated Regions of Bacterial mRNAs

The untranslated regions (UTRs) of mRNA contain important features that are relevant to the post-transcriptional and translational regulation of gene expression. Most studies of bacterial UTRs have focused on the 5′regions; however, 3′UTRs have recently emerged as a new class of post-transcriptional regulatory elements. 3′UTRs were found to regulate the decay and translation initiation in their own mRNAs. In addition, 3′UTRs constitute a rich reservoir of small regulatory RNAs, regulating target gene expression. In the current review, we describe several recently discovered examples of bacterial regulatory 3′UTRs, discuss their modes of action, and illustrate how they facilitate gene regulation in various environments.

On the Ribosomal Density that Maximizes Protein Translation Rate

During mRNA translation, several ribosomes attach to the same mRNA molecule simultaneously translating it into a protein. This pipelining increases the protein translation rate. A natural and important question is what ribosomal density maximizes the protein translation rate. Using mathematical models of ribosome flow along both a linear and a circular mRNA molecules we prove that typically the steady-state protein translation rate is maximized when the ribosomal density is one half of the maximal possible density. We discuss the implications of our results to endogenous genes under natural cellular conditions and also to synthetic biology.

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.

Degradation Parameters from Pulse-Chase Experiments

Pulse-chase experiments are often used to study the degradation of macromolecules such as proteins or mRNA. Considerations for the choice of pulse length include the toxicity of the pulse to the cell and maximization of labeling. In the general case of non-exponential decay, varying the length of the pulse results in decay patterns that look different. Analysis of these patterns without consideration to pulse length would yield incorrect degradation parameters. Here we propose a method that constructively includes pulse length in the analysis of decay patterns and extracts the parameters of the underlying degradation process. We also show how to extract decay parameters reliably from measurements taken during the pulse phase.

The Meaning of NMD: Translate or Perish

Premature translation termination leads to a reduced mRNA level in all types of organisms. In eukaryotes, the phenomenon is known as nonsense-mediated mRNA decay (NMD). This is commonly regarded as the output of a specific surveillance and destruction mechanism that is activated by the presence of a premature translation termination codon (PTC) in an atypical sequence context. Despite two decades of research, it is still unclear how NMD discriminates between PTCs and normal stop codons. We suggest that cells do not possess any such mechanism and instead propose a new model in which this mRNA depletion is a consequence of the appearance of long tracts of mRNA that are unprotected by scanning ribosomes.

Length-dependent translation initiation benefits the functional proteome of human cells

We previously found that shorter mRNAs are preferably translated in various eukaryotic cells. However, the theoretical basis of this phenomenon is unclear. We hypothesize that shorter mRNA length correlates to the decreased translational error rate to reduce the energy consumption on defective protein degradation. In this study, we established a computational model to explain the length-dependent translation initiation efficiency. We provided mathematical evidence that this translational preference, rather than the protein degradation, is a major factor to shape the genome-wide length-dependent protein abundance. As deducted, we simulated that shorter mRNA length is a determinant of initiation circularization time. Furthermore, our model unveiled that preferentially translating shorter mRNAs benefits the energy efficiency on the proteome functionality. We proposed that cancer cells tend to hijack this evolutionary mechanism by counteracting the higher translational error rate. In conclusion, our model provides insights into the nature of the global length-dependent translational control and its biological significance.

Netrin-1 induces local translation of down syndrome cell adhesion molecule in axonal growth cones

Down syndrome cell adhesion molecule (DSCAM) plays an important role in many neurodevelopmental processes such as axon guidance, dendrite arborization, and synapse formation. DSCAM is located in the Down syndrome trisomic region of human chromosome 21 and may contribute to the Down syndrome brain phenotype, which includes a reduction in the formation of long-distance connectivity. The local translation of a select group of mRNA transcripts within growth cones is necessary for the formation of appropriate neuronal connectivity. Interestingly, we have found that Dscam mRNA is localized to growth cones of mouse hippocampal neurons, and is dynamically regulated in response to the axon guidance molecule, netrin-1. Furthermore, netrin-1 stimulation results in an increase in locally translated DSCAM protein in growth cones. Deleted in colorectal cancer (DCC), a netrin-1 receptor, is required for the netrin-1-induced increase in Dscam mRNA local translation. We also find that two RNA-binding proteins-fragile X mental retardation protein (FMRP) and cytoplasmic polyadenylation element binding protein (CPEB)-colocalize with Dscam mRNA in growth cones, suggesting their regulation of Dscam mRNA localization and translation. Finally, overexpression of DSCAM in mouse cortical neurons results in a severe stunting of axon outgrowth and branching, suggesting that an increase in DSCAM protein results in a structural change having functional consequences. Taken together, these results suggest that netrin-1-induced local translation of Dscam mRNA during embryonic development may be an important mechanism to regulate axon growth and guidance in the developing nervous system. © 2015 Wiley Periodicals, Inc. Develop Neurobiol 76: 799-816, 2016.

The membrane: transertion as an organizing principle in membrane heterogeneity

The bacterial membrane exhibits a significantly heterogeneous distribution of lipids and proteins. This heterogeneity results mainly from lipid-lipid, protein-protein, and lipid-protein associations which are orchestrated by the coupled transcription, translation and insertion of nascent proteins into and through membrane (transertion). Transertion is central not only to the individual assembly and disassembly of large physically linked groups of macromolecules (alias hyperstructures) but also to the interactions between these hyperstructures. We review here these interactions in the context of the processes in Bacillus subtilis and Escherichia coli of nutrient sensing, membrane synthesis, cytoskeletal dynamics, DNA replication, chromosome segregation, and cell division.

Regulation of bacterial virulence by Csr (Rsm) systems

Most bacterial pathogens have the remarkable ability to flourish in the external environment and in specialized host niches. This ability requires their metabolism, physiology, and virulence factors to be responsive to changes in their surroundings. It is no surprise that the underlying genetic circuitry that supports this adaptability is multilayered and exceedingly complex. Studies over the past 2 decades have established that the CsrA/RsmA proteins, global regulators of posttranscriptional gene expression, play important roles in the expression of virulence factors of numerous proteobacterial pathogens. To accomplish these tasks, CsrA binds to the 5' untranslated and/or early coding regions of mRNAs and alters translation, mRNA turnover, and/or transcript elongation. CsrA activity is regulated by noncoding small RNAs (sRNAs) that contain multiple CsrA binding sites, which permit them to sequester multiple CsrA homodimers away from mRNA targets. Environmental cues sensed by two-component signal transduction systems and other regulatory factors govern the expression of the CsrA-binding sRNAs and, ultimately, the effects of CsrA on secretion systems, surface molecules and biofilm formation, quorum sensing, motility, pigmentation, siderophore production, and phagocytic avoidance. This review presents the workings of the Csr system, the paradigm shift that it generated for understanding posttranscriptional regulation, and its roles in virulence networks of animal and plant pathogens.

Maximizing protein translation rate in the non-homogeneous ribosome flow model: a convex optimization approach

Translation is an important stage in gene expression. During this stage, macro-molecules called ribosomes travel along the mRNA strand linking amino acids together in a specific order to create a functioning protein. An important question, related to many biomedical disciplines, is how to maximize protein production. Indeed, translation is known to be one of the most energy-consuming processes in the cell, and it is natural to assume that evolution shaped this process so that it maximizes the protein production rate. If this is indeed so then one can estimate various parameters of the translation machinery by solving an appropriate mathematical optimization problem. The same problem also arises in the context of synthetic biology, namely, re-engineer heterologous genes in order to maximize their translation rate in a host organism. We consider the problem of maximizing the protein production rate using a computational model for translation-elongation called the ribosome flow model (RFM). This model describes the flow of the ribosomes along an mRNA chain of length n using a set of n first-order nonlinear ordinary differential equations. It also includes n + 1 positive parameters: the ribosomal initiation rate into the mRNA chain, and n elongation rates along the chain sites. We show that the steady-state translation rate in the RFM is a strictly concave function of its parameters. This means that the problem of maximizing the translation rate under a suitable constraint always admits a unique solution, and that this solution can be determined using highly efficient algorithms for solving convex optimization problems even for large values of n. Furthermore, our analysis shows that the optimal translation rate can be computed based only on the optimal initiation rate and the elongation rate of the codons near the beginning of the ORF. We discuss some applications of the theoretical results to synthetic biology, molecular evolution, and functional genomics.

Why do bacteria divide?

The problem of not only how but also why cells divide can be tackled using recent ideas. One idea from the origins of life – Life as independent of its constituents – is that a living entity like a cell is a particular pattern of connectivity between its constituents. This means that if the growing cell were just to get bigger the average connectivity between its constituents per unit mass – its cellular connectivity – would decrease and the cell would lose its identity. The solution is division which restores connectivity. The corollary is that the cell senses decreasing cellular connectivity and uses this information to trigger division. A second idea from phenotypic diversity – Life on the Scales of Equilibria – is that a bacterium must find strategies that allow it to both survive and grow. This means that it has learnt to reconcile the opposing constraints that these strategies impose. The solution is that the cell cycle generates daughter cells with different phenotypes based on sufficiently complex equilibrium (E) and non-equilibrium (NE) cellular compounds and structures appropriate for survival and growth, respectively, alias ‘hyperstructures.’ The corollary is that the cell senses both the quantity of E material and the intensity of use of NE material and then uses this information to trigger the cell cycle. A third idea from artificial intelligence – Competitive Coherence – is that a cell selects the active subset of elements that actively determine its phenotype from a much larger set of available elements. This means that the selection of an active subset of a specific size and composition must be done so as to generate both a coherent cell state, in which the cell’s contents work together harmoniously, and a coherent sequence of cell states, each coherent with respect to itself and to an unpredictable environment. The solution is the use of a range of mechanisms ranging from hyperstructure dynamics to the cell cycle itself.

Trade-offs between tRNA abundance and mRNA secondary structure support smoothing of translation elongation rate

Translation of protein from mRNA is a complex multi-step process that occurs at a non-uniform rate. Variability in ribosome speed along an mRNA enables refinement of the proteome and plays a critical role in protein biogenesis. Detailed single protein studies have found both tRNA abundance and mRNA secondary structure as key modulators of translation elongation rate, but recent genome-wide ribosome profiling experiments have not observed significant influence of either on translation efficiency. Here we provide evidence that this results from an inherent trade-off between these factors. We find codons pairing to high-abundance tRNAs are preferentially used in regions of high secondary structure content, while codons read by significantly less abundant tRNAs are located in lowly structured regions. By considering long stretches of high and low mRNA secondary structure in Saccharomyces cerevisiae and Escherichia coli and comparing them to randomized-gene models and experimental expression data, we were able to distinguish clear selective pressures and increased protein expression for specific codon choices. The trade-off between secondary structure and tRNA-concentration based codon choice allows for compensation of their independent effects on translation, helping to smooth overall translational speed and reducing the chance of potentially detrimental points of excessively slow or fast ribosome movement.

Genome-wide study of mRNA degradation and transcript elongation in Escherichia coli

An essential part of gene expression is the coordination of RNA synthesis and degradation, which occurs in the same cellular compartment in bacteria. Here, we report a genome-wide RNA degradation study in Escherichia coli using RNA-seq, and present evidence that the stereotypical exponential RNA decay curve obtained using initiation inhibitor, rifampicin, consists of two phases: residual RNA synthesis, a delay in the interruption of steady state that is dependent on distance relative to the mRNA's 5′ end, and the exponential decay. This gives a more accurate RNA lifetime and RNA polymerase elongation rate simultaneously genome-wide. Transcripts typically have a single RNA decay constant along all positions, which is distinct between different operons, indicating that RNA stability is unlikely determined by local sequences. These measurements allowed us to establish a model for RNA processing involving co-transcriptional degradation, providing quantitative description of the macromolecular coordination in gene expression in bacteria on a system-wide level.

Time-dependent effects of transcription- and translation-halting drugs on the spatial distributions of the Escherichia coli chromosome and ribosomes

Previously observed effects of rifampicin and chloramphenicol indicate that transcription and translation activity strongly affect the coarse spatial organization of the bacterial cytoplasm. Single-cell, time-resolved, quantitative imaging of chromosome and ribosome spatial distributions and ribosome diffusion in live Escherichia coli provides insight into the underlying mechanisms. Monte Carlo simulations of model DNA-ribosome mixtures support a novel nucleoid-ribosome mixing hypothesis. In normal conditions, 70S-polysomes and the chromosomal DNA segregate, while 30S and 50S ribosomal subunits are able to penetrate the nucleoids. Growth conditions and drug treatments determine the partitioning of ribosomes into 70S-polysomes versus free 30S and 50S subunits. Entropic and excluded volume effects then dictate the resulting chromosome and ribosome spatial distributions. Direct observation of radial contraction of the nucleoids 0-5 min after treatment with either transcription- or translation-halting drugs supports the hypothesis that simultaneous transcription, translation, and insertion of proteins into the membrane ('transertion') exerts an expanding force on the chromosomal DNA. Breaking of the DNA-RNA polymerase-mRNA-ribosome-membrane chain in either of two ways causes similar nucleoid contraction on a similar timescale. We suggest that chromosomal expansion due to transertion enables co-transcriptional translation throughout the nucleoids.

Entrainment to periodic initiation and transition rates in a computational model for gene translation

Periodic oscillations play an important role in many biomedical systems. Proper functioning of biological systems that respond to periodic signals requires the ability to synchronize with the periodic excitation. For example, the sleep/wake cycle is a manifestation of an internal timing system that synchronizes to the solar day. In the terminology of systems theory, the biological system must entrain or phase-lock to the periodic excitation. Entrainment is also important in synthetic biology. For example, connecting several artificial biological systems that entrain to a common clock may lead to a well-functioning modular system. The cell-cycle is a periodic program that regulates DNA synthesis and cell division. Recent biological studies suggest that cell-cycle related genes entrain to this periodic program at the gene translation level, leading to periodically-varying protein levels of these genes. The ribosome flow model (RFM) is a deterministic model obtained via a mean-field approximation of a stochastic model from statistical physics that has been used to model numerous processes including ribosome flow along the mRNA. Here we analyze the RFM under the assumption that the initiation and/or transition rates vary periodically with a common period . We show that the ribosome distribution profile in the RFM entrains to this periodic excitation. In particular, the protein synthesis pattern converges to a unique periodic solution with period . To the best of our knowledge, this is the first proof of entrainment in a mathematical model for translation that encapsulates aspects such as initiation and termination rates, ribosomal movement and interactions, and non-homogeneous elongation speeds along the mRNA. Our results support the conjecture that periodic oscillations in tRNA levels and other factors related to the translation process can induce periodic oscillations in protein levels, and may suggest a new approach for re-engineering genetic systems to obtain a desired, periodic, protein synthesis rate.

Global effects of the DEAD-box RNA helicase DeaD (CsdA) on gene expression over a broad range of temperatures

In Escherichia coli, activity of the global regulatory RNA binding protein CsrA is antagonized by two non-coding sRNAs, CsrB and CsrC, which sequester it away from its lower affinity mRNA targets. Transcription of csrB/C requires the BarA-UvrY two component signal transduction system, which responds to short chain carboxylates. We show that two DEAD-box RNA helicases, DeaD and SrmB, activate csrB/C expression by different pathways. DeaD facilitates uvrY translation by counteracting the inhibitory effect of long distance base-pairing between the uvrY mRNA leader and coding region, while SrmB does not affect UvrY or UvrY-phosphate levels. Contrary to the prevailing notion that these helicases act primarily at low temperatures, DeaD and SrmB activated csrB expression over a wide temperature range. High-throughput sequencing of RNA isolated by cross-linking immunoprecipitation (HITS-CLIP) revealed in vivo interactions of DeaD with 39 mRNAs, including those of uvrY and 9 other regulatory genes. Studies on the expression of several of the identified genes revealed regulatory effects of DeaD in all cases and diverse temperature response patterns. Our findings uncover an expanded regulatory role for DeaD, which is mediated through novel mRNA targets, important global regulators and under physiological conditions that were considered to be incompatible with its function.