Yeast has evolved to minimize protein resource cost for synthesizing amino acids.

Proteins, as essential biomolecules, account for a large fraction of cell mass, and thus the synthesis of the complete set of proteins (i.e., the proteome) represents a substantial part of the cellular resource budget. Therefore, cells might be under selective pressures to optimize the resource costs for protein synthesis, particularly the biosynthesis of the 20 proteinogenic amino acids. Previous studies showed that less energetically costly amino acids are more abundant in the proteomes of bacteria that survive under energy-limited conditions, but the energy cost of synthesizing amino acids was reported to be weakly associated with the amino acid usage in Saccharomyces cerevisiae Here we present a modeling framework to estimate the protein cost of synthesizing each amino acid (i.e., the protein mass required for supporting one unit of amino acid biosynthetic flux) and the glucose cost (i.e., the glucose consumed per amino acid synthesized). We show that the logarithms of the relative abundances of amino acids in S. cerevisiae's proteome correlate well with the protein costs of synthesizing amino acids (Pearson's r = -0.89), which is better than that with the glucose costs (Pearson's r = -0.5). Therefore, we demonstrate that S. cerevisiae tends to minimize protein resource, rather than glucose or energy, for synthesizing amino acids.

Central dogma rates and the trade-off between precision and economy in gene expression.

Steady-state protein abundance is set by four rates: transcription, translation, mRNA decay and protein decay. A given protein abundance can be obtained from infinitely many combinations of these rates. This raises the question of whether the natural rates for each gene result from historical accidents, or are there rules that give certain combinations a selective advantage? We address this question using high-throughput measurements in rapidly growing cells from diverse organisms to find that about half of the rate combinations do not exist: genes that combine high transcription with low translation are strongly depleted. This depletion is due to a trade-off between precision and economy: high transcription decreases stochastic fluctuations but increases transcription costs. Our theory quantitatively explains which rate combinations are missing, and predicts the curvature of the fitness function for each gene. It may guide the design of gene circuits with desired expression levels and noise.

High Cooperativity in Negative Feedback can Amplify Noisy Gene Expression.

Burst-like synthesis of protein is a significant source of cell-to-cell variability in protein levels. Negative feedback is a common example of a regulatory mechanism by which such stochasticity can be controlled. Here we consider a specific kind of negative feedback, which makes bursts smaller in the excess of protein. Increasing the strength of the feedback may lead to dramatically different outcomes depending on a key parameter, the noise load, which is defined as the squared coefficient of variation the protein exhibits in the absence of feedback. Combining stochastic simulation with asymptotic analysis, we identify a critical value of noise load: for noise loads smaller than critical, the coefficient of variation remains bounded with increasing feedback strength; contrastingly, if the noise load is larger than critical, the coefficient of variation diverges to infinity in the limit of ever greater feedback strengths. Interestingly, feedbacks with lower cooperativities have higher critical noise loads, suggesting that they can be preferable for controlling noisy proteins.

Comparison of whole animal costs of protein synthesis among polar and temperate populations of the same species of gammarid amphipod.

Protein synthesis can account for a substantial proportion of metabolic rate. Energetic costs of protein synthesis, should in theory, be the same in marine invertebrates from a range of thermal habitats, and yet direct measurements using inhibitors produce widely differing values, especially in the cold. The present study aimed to remove any potential confounding interspecific effects by determining costs of protein synthesis in two latitudinally separated populations of the same species (amphipod, Gammarus oceanicus) living in two different thermal regimes; polar vs cold-temperate. Costs of protein synthesis were determined in summer acclimatised G. oceanicus from Svalbard (79°N) at 5°C and from Scotland (58°N) at 13°C. Amphipods were injected with the protein synthesis inhibitor, cycloheximide (CHX), at 9mmoll-1 in crab saline to give a tissue concentration of 0.05mgCHXg-1FW and left for 60min before the injection of [3H] phenylalanine. After incubation for 120min (180min in total from initial injection), both whole-animal rates of oxygen uptake and absolute rates of protein synthesis were significantly reduced in CHX-treated amphipods vs controls injected with saline. Both populations exhibited similar costs of protein synthesis of ~7µmolO2mg-1protein which is close to the estimated theoretical minimum for peptide bond formation, and similar to the values obtained in cell-free systems. The study demonstrates that in G. oceanicus, costs of protein synthesis rates were not elevated in the cold but were fixed among polar and cold-temperate populations.

A stochastic analysis of autoregulation of gene expression.

This paper analyzes, in the context of a prokaryotic cell, the stochastic variability of the number of proteins when there is a control of gene expression by an autoregulation scheme. The goal of this work is to estimate the efficiency of the regulation to limit the fluctuations of the number of copies of a given protein. The autoregulation considered in this paper relies mainly on a negative feedback: the proteins are repressors of their own gene expression. The efficiency of a production process without feedback control is compared to a production process with an autoregulation of the gene expression assuming that both of them produce the same average number of proteins. The main characteristic used for the comparison is the standard deviation of the number of proteins at equilibrium. With a Markovian representation and a simple model of repression, we prove that, under a scaling regime, the repression mechanism follows a Hill repression scheme with an hyperbolic control. An explicit asymptotic expression of the variance of the number of proteins under this regulation mechanism is obtained. Simulations are used to study other aspects of autoregulation such as the rate of convergence to equilibrium of the production process and the case where the control of the production process of proteins is achieved via the inhibition of mRNAs.

Rapid Assessment of Resistance to Antibiotic Inhibitors of Protein Synthesis in the Gram-Positive Pathogens, Enterococcus faecalis and Streptococcus pneumoniae, Based on Evaluation of the Lytic Response.

A novel assay for rapid determination of resistance to antibiotic inhibitors of protein synthesis was developed for the gram-positive pathogens, Enterococcus faecalis and Streptococcus pneumoniae. To this purpose, a lytic response was obtained by a brief incubation with lysozyme or a mixture of lysozyme, Triton X-100, and EDTA for E. faecalis (n = 82) and S. pneumoniae (n = 51), respectively. Lysis was quantified by visualizing the released nucleoids. Antibiotic-susceptible bacteria treated with Clinical and Laboratory Standards Institute (CLSI) breakpoint doses of erythromycin, azithromycin, or doxycycline that inhibited protein synthesis demonstrated a large reduction of lysed cells with respect to the control, that is, without antibiotics. However, cell lysis prevention was much lower in nonsusceptible strains, with unsuccessful inhibition of protein synthesis. ROC analysis showed that a reduction value of ≥35.6% and ≥40.4% discriminates susceptible and nonsusceptible strains for erythromycin and for doxycycline, respectively, in E. faecalis, whereas ≥20.0% is adequate for both macrolides and doxycycline in S. pneumoniae. Resistant stains were identified in 90-120 min with sensitivity and specificity between 91.7% and 100%. This is a proof of concept that evaluation of the lytic response may be a rapid and efficient test for determination of resistance to antibiotic inhibitors of protein synthesis.

Genomic charting of ribosomally synthesized natural product chemical space facilitates targeted mining.

Microbial natural products are an evolved resource of bioactive small molecules, which form the foundation of many modern therapeutic regimes. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) represent a class of natural products which have attracted extensive interest for their diverse chemical structures and potent biological activities. Genome sequencing has revealed that the vast majority of genetically encoded natural products remain unknown. Many bioinformatic resources have therefore been developed to predict the chemical structures of natural products, particularly nonribosomal peptides and polyketides, from sequence data. However, the diversity and complexity of RiPPs have challenged systematic investigation of RiPP diversity, and consequently the vast majority of genetically encoded RiPPs remain chemical "dark matter." Here, we introduce an algorithm to catalog RiPP biosynthetic gene clusters and chart genetically encoded RiPP chemical space. A global analysis of 65,421 prokaryotic genomes revealed 30,261 RiPP clusters, encoding 2,231 unique products. We further leverage the structure predictions generated by our algorithm to facilitate the genome-guided discovery of a molecule from a rare family of RiPPs. Our results provide the systematic investigation of RiPP genetic and chemical space, revealing the widespread distribution of RiPP biosynthesis throughout the prokaryotic tree of life, and provide a platform for the targeted discovery of RiPPs based on genome sequencing.

Selection for reduced translation costs at the intronic 5' end in fungi.

It is generally believed that introns are not translated; therefore, the potential intronic features that may be related to the translation step (occurring after splicing) have yet to be thoroughly studied. Here, focusing on four fungi, we performed for the first time a comprehensive study aimed at characterizing how translation efficiency is encoded in introns and affects their evolution. By analysing their intronome we provide evidence of selection for STOP codons close to the intronic 5' end, and show that the beginning of introns are selected for significantly high translation, presumably to reduce translation and metabolic costs in cases of non-spliced introns. Ribosomal profiling data analysis in Saccharomyces cerevisiae supports the conjecture that in this organism intron retention frequently occurs, introns are partially translated, and their translation efficiency affects organismal fitness. We show that the reported results are more significant in highly translated and highly spliced genes, but are not associated only with genes with a specific function. We also discuss the potential relation of the reported signals to efficient nonsense-mediated decay due to splicing errors. These new discoveries are supported by population-genetics considerations. In addition, they are contributory steps towards a broader understanding of intron evolution and the effect of silent mutations on gene expression and organismal fitness.

Compensating the Fitness Costs of Synonymous Mutations.

Synonymous mutations do not change the sequence of the polypeptide but they may still influence fitness. We investigated in Salmonella enterica how four synonymous mutations in the rpsT gene (encoding ribosomal protein S20) reduce fitness (i.e., growth rate) and the mechanisms by which this cost can be genetically compensated. The reduced growth rates of the synonymous mutants were correlated with reduced levels of the rpsT transcript and S20 protein. In an adaptive evolution experiment, these fitness impairments could be compensated by mutations that either caused up-regulation of S20 through increased gene dosage (due to duplications), increased transcription of the rpsT gene (due to an rpoD mutation or mutations in rpsT), or increased translation from the rpsT transcript (due to rpsT mutations). We suggest that the reduced levels of S20 in the synonymous mutants result in production of a defective subpopulation of 30S subunits lacking S20 that reduce protein synthesis and bacterial growth and that the compensatory mutations restore S20 levels and the number of functional ribosomes. Our results demonstrate how specific synonymous mutations can cause substantial fitness reductions and that many different types of intra- and extragenic compensatory mutations can efficiently restore fitness. Furthermore, this study highlights that also synonymous sites can be under strong selection, which may have implications for the use of dN/dS ratios as signature for selection.

Assessment of global proteome dynamics in carp: a model for investigating environmental stress.

Fish have to respond to a range of natural and man-made environmental stressors, which can lead to molecular changes within their tissues. Many studies focused on environmental stress in fish have examined the change in protein abundance or mRNA level. However, it is well-known that there is a disconnect between mRNA and protein expression. In order to bridge this gap, protein turnover must also be considered. We have developed an experimental strategy to determine the synthesis rates of individual proteins in the tissues of fish on a proteome-wide scale. This approach has been applied to the common carp ( Cyprinus carpio ), a key model species for investigating environmentally induced physiological plasticity. We have calculated the rates of protein synthesis for over a thousand individual proteins from the skeletal muscle and liver of carp. The median synthesis rate of proteins from liver was higher than that of skeletal muscle. The analysis further revealed that the same protein can have a different rate of synthesis depending on the tissue type. Our strategy permits a full investigation of proteome dynamics in fish and will have relevance to the fields of integrative biology and ecotoxicology.

Assessment of mitochondrial biogenesis and mTORC1 signaling during chronic rapamycin feeding in male and female mice.

Chronic inhibition of the protein synthesis regulator mTORC1 through rapamycin extends life span in mice, with longer extension in females than in males. Whether rapamycin treatment inhibits protein synthesis or whether it does so differently between sexes has not been examined. UM-HET3 mice were fed a control or rapamycin-supplemented (Rap) diet for 12 weeks. Protein synthesis in mixed, cytosolic (cyto), and mitochondrial (mito) fractions and DNA synthesis and mTORC1 signaling were determined in skeletal muscle, heart, and liver. In both sexes, mito protein synthesis was maintained in skeletal muscle from Rap despite decreases in mixed and cyto fractions, DNA synthesis, and rpS6 phosphorylation. In the heart, no change in protein synthesis occurred despite the decreased DNA synthesis. In the heart and liver, Rap males were more sensitive to mTORC1 inhibition than Rap females. In conclusion, we show changes in protein synthesis and mTORC1 signaling that differ by sex and tissue.

Type of noise defines global attractors in bistable molecular regulatory systems.

The aim of this study is to demonstrate that in molecular dynamical systems with the underlying bi- or multistability, the type of noise determines the most strongly attracting steady state or stochastic attractor. As an example we consider a simple stochastic model of autoregulatory gene with a nonlinear positive feedback, which in the deterministic approximation has two stable steady state solutions. Three types of noise are considered: transcriptional and translational - due to the small number of gene product molecules and the gene switching noise - due to gene activation and inactivation transitions. We demonstrate that the type of noise in addition to the noise magnitude dictates the allocation of probability mass between the two stable steady states. In particular, we found that when the gene switching noise dominates over the transcriptional and translational noise (which is characteristic of eukaryotes), the gene preferentially activates, while in the opposite case, when the transcriptional noise dominates (which is characteristic of prokaryotes) the gene preferentially remains inactive. Moreover, even in the zero-noise limit, when the probability mass generically concentrates in the vicinity of one of two steady states, the choice of the most strongly attracting steady state is noise type-dependent. Although the epigenetic attractors are defined with the aid of the deterministic approximation of the stochastic regulatory process, their relative attractivity is controlled by the type of noise, in addition to noise magnitude. Since noise characteristics vary during the cell cycle and development, such mode of regulation can be potentially employed by cells to switch between alternative epigenetic attractors.

Robust model matching design methodology for a stochastic synthetic gene network.

Synthetic biology has shown its potential and promising applications in the last decade. However, many synthetic gene networks cannot work properly and maintain their desired behaviors due to intrinsic parameter variations and extrinsic disturbances. In this study, the intrinsic parameter uncertainties and external disturbances are modeled in a non-linear stochastic gene network to mimic the real environment in the host cell. Then a non-linear stochastic robust matching design methodology is introduced to withstand the intrinsic parameter fluctuations and to attenuate the extrinsic disturbances in order to achieve a desired reference matching purpose. To avoid solving the Hamilton-Jacobi inequality (HJI) in the non-linear stochastic robust matching design, global linearization technique is used to simplify the design procedure by solving a set of linear matrix inequalities (LMIs). As a result, the proposed matching design methodology of the robust synthetic gene network can be efficiently designed with the help of LMI toolbox in Matlab. Finally, two in silico design examples of the robust synthetic gene network are given to illustrate the design procedure and to confirm the robust model matching performance to achieve the desired behavior in spite of stochastic parameter fluctuations and environmental disturbances in the host cell.

Unique cost dynamics elucidate the role of frameshifting errors in promoting translational robustness.

There is now considerable evidence supporting the view that codon usage is frequently under selection for translational accuracy. There are, however, multiple forms of inaccuracy (missense, premature termination, and frameshifting errors) and pinpointing a particular error process behind apparently adaptive mRNA anatomy is rarely straightforward. Understanding differences in the fitness costs associated with different types of translational error can help us devise critical tests that can implicate one error process to the exclusion of others. To this end, we present a model that captures distinct features of frameshifting cost and apply this to 641 prokaryotic genomes. We demonstrate that, although it is commonly assumed that the ribosome encounters an off-frame stop codon soon after the frameshift and costs of mis-elongation are therefore limited, genomes with high GC content typically incur much larger per-error costs. We go on to derive the prediction, unique to frameshifting errors, that differences in translational robustness between the 5' and 3' ends of genes should be less pronounced in genomes with higher GC content. This prediction we show to be correct. Surprisingly, this does not mean that GC-rich organisms necessarily carry a greater fitness burden as a consequence of accidental frameshifting. Indeed, increased per-error costs are often more than counterbalanced by lower predicted error rates owing to more diverse anticodon repertoires in GC-rich genomes. We therefore propose that selection on tRNA repertoires may operate to reduce frameshifting errors.

Lack of adequate appreciation of physical exercise's complexities can pre-empt appropriate design and interpretation in scientific discovery.

Two major issues are presented. First, a challenge is made by us that a misunderstanding of physiology has led to incomplete or wrong functional designations of genes in some cases. Normal physiological processes are dynamic, integrated and periodic, and, therefore, it is difficult to define normal physiological function by looking at a single time point or single process in a non-stressed subject. The ability of the organism to successfully respond to homeostatic disruptions defines normal physiology. Genes were selected for survival and to appropriately respond to stresses, such as physical activity. Omitting gene functions by restricting them to non-stressful conditions could lead to less than optimal primary preventions, treatments and cures for diseases. Physical exercise, as a stressor, should be used to better demonstrate the complete functional classifications of some genes. Second, the challenge from others of an 'exercise pill' as a mimetic of natural physical activity will be shown to be lacking a scientific basis. The concept of an 'exercise pill'/'exercise mimetic' demonstrates an inadequate appreciation of the complexities in integrating cell, tissue, organ and systems during both acute disruptions in homeostasis by a single bout of exercise, and longer-term chronic adaptations to different types of exercise such as resistance and endurance. It is our opinion that those promoting drugs targeting a single or few molecules should not redefine the term 'exercise' and exercise concepts in an attempt to sensationalize findings. Additionally, the scientific criteria that the authors demand to be met to legitimately use the terms 'exercise pill' and 'exercise mimetic' are presented.

Cost minimization of ribosomal frameshifts.

Properties of mRNA leading regions that modulate protein synthesis are little known (besides effects of their secondary structure). Here I explore how coding properties of leading regions may account for their disparate efficiencies. Trinucleotides that form off frame stop codons decrease costs of ribosomal slippages during protein synthesis: protein activity (as a proxy of gene expression, and as measured in experiments using artificial variants of 5' leading sequences of beta galactosidase in Escherichia coli) increases proportionally to the number of stop motifs in any frame in the 5' leading region. This suggests that stop codons in the 5' leading region, upstream of the recognized coding sequence, terminate eventual translations that sometimes start before ribosomes reach the mRNA's recognized start codon, increasing efficiency. This hypothesis is confirmed by further analyses: mRNAs with 5' leading regions containing in the same frame a start preceding a stop codon (in any frame) produce less enzymatic activity than those with the stop preceding the start. Hence coding properties, in addition to other properties, such as the secondary structure of the 5' leading region, regulate translation. This experimentally (a) confirms that within coding regions, off frame stops increase protein synthesis efficiency by early stopping frameshifted translation; (b) suggests that this occurs for all frames also in 5' leading regions and that (c) several alternative start codons that function at different probabilities should routinely be considered for all genes in the region of the recognized initiation codon. An unknown number of short peptides might be translated from coding and non-coding regions of RNAs.

Rate, accuracy and cost of ribosomes in bacterial cells.

Recent biochemical data on the rate of peptidyl-transfer and missense error levels associated with the E. coli ribosome in conjunction with direct measurements of diffusion constants for proteins in the E. coli cell have been used to discuss protein synthesis in the living E. coli cell in the perspective of a previously developed maximal fitness theory. With these improved experimental parameters, i.e. kcat approximately 50 s(-1) for protein elongation and kcat/KM approximately 4 microM(-1) s(-1) for cognate ternary complex binding to the ribosomal A site, theory predicts the experimentally observed variations in protein elongation rate, ribosome and ternary complex concentrations with varying quality of the growth medium. The theoretically predicted average missense error level is close the error levels estimated in vitro for special isoacceptor combinations, i.e. error levels about 1 per million. The future prospect of extensive integration of biochemistry, cell physiology and population genetics is discussed in the light of the maximal fitness theory and other, similar, theoretical approaches.

Markov encoding for detecting signals in genomic sequences.

We present a technique to encode the inputs to neural networks for the detection of signals in genomic sequences. The encoding is based on lower-order Markov models which incorporate known biological characteristics in genomic sequences. The neural networks then learn intrinsic higher-order dependencies of nucleotides at the signal sites. We demonstrate the efficacy of the Markov encoding method in the detection of three genomic signals, namely, splice sites, transcription start sites, and translation initiation sites.

Accurate multiplex gene synthesis from programmable DNA microchips.

Testing the many hypotheses from genomics and systems biology experiments demands accurate and cost-effective gene and genome synthesis. Here we describe a microchip-based technology for multiplex gene synthesis. Pools of thousands of 'construction' oligonucleotides and tagged complementary 'selection' oligonucleotides are synthesized on photo-programmable microfluidic chips, released, amplified and selected by hybridization to reduce synthesis errors ninefold. A one-step polymerase assembly multiplexing reaction assembles these into multiple genes. This technology enabled us to synthesize all 21 genes that encode the proteins of the Escherichia coli 30S ribosomal subunit, and to optimize their translation efficiency in vitro through alteration of codon bias. This is a significant step towards the synthesis of ribosomes in vitro and should have utility for synthetic biology in general.

STOCKS: STOChastic Kinetic Simulations of biochemical systems with Gillespie algorithm.

MOTIVATION: The availability of a huge amount of molecular data concerning various biochemical reactions provoked numerous attempts to study the dynamics of cellular processes by means of kinetic models and computer simulations. Biochemical processes frequently involve small numbers of molecules (e.g. a few molecules of a transcriptional regulator binding to one 'molecule' of a DNA regulatory region). Such reactions are subject to significant stochastic fluctuations. Monte Carlo methods must be employed to study the functional consequences of the fluctuations and simulate processes that cannot be modelled by continuous fluxes of matter. This provides the motivation to develop software dedicated to Monte Carlo simulations of cellular processes with the rigorously proven Gillespie algorithm. RESULTS: STOCKS, software for the stochastic kinetic simulation of biochemical processes is presented. The program uses a rigorously derived Gillespie algorithm that has been shown to be applicable to the study of prokaryotic gene expression. Features dedicated to the study of cellular processes are implemented, such as the possibility to study a process in the range of several cell generations with the application of a simple cell division model. Taking expression of Escherichia coli beta-galactosidase as an example, it is shown that the program is able to simulate systems composed of reactions varying in several orders of magnitude by means of reaction rates and the numbers of molecules involved. AVAILABILITY: The software is available at ftp://ibbrain.ibb.waw.pl/stocksand http://www.ibb.waw.pl/stocks. SUPPLEMENTARY INFORMATION: Parameters of the model of prokaryotic gene expression are available in example files of software distribution.