Gene Expression Analyzed by High-resolution State Array Analysis and Quantitative Proteomics

The TCF4 Gene Regulates Apoptosis of Corneal Endothelial Cells in Fuchs Endothelial Corneal Dystrophy

Purpose

Fuchs endothelial corneal dystrophy (FECD) is a progressive corneal disorder characterized by excessive extracellular matrix (ECM) accumulation and corneal endothelial cell death. CTG trinucleotide repeat expansion in the transcription factor 4 (TCF4) gene represents the most significant genetic risk factor. This study aimed to elucidate the role of TCF4 in FECD pathogenesis through comprehensive proteomic analysis.

Methods

Corneal endothelial cells isolated from patients with FECD harboring TCF4 trinucleotide repeat expansion were immortalized to establish an FECD cell model (iFECD). CRISPR/Cas9-mediated genome editing was employed to generate TCF4-knockout iFECD cells. Whole-cell proteome analysis was performed using liquid chromatography-mass spectrometry, followed by pathway enrichment analysis of differentially expressed proteins (DEPs). The effects of TCF4 deletion on TGF-β-mediated protein aggregation and cell death were evaluated using Western blot analysis, flow cytometry, and aggresome detection assays.

Results

Proteomic analysis identified 88 DEPs among 6510 detected proteins. Pathway analysis revealed significant enrichment in ECM-associated pathways, oxidative stress responses, and cellular motility. TCF4 deletion attenuated TGF-β-induced cell death in iFECD cells. Concordantly, Western blot analysis demonstrated that TCF4 deletion suppressed TGF-β2-mediated cleavage of caspase-3 and poly (ADP-ribose) polymerase. Flow cytometric analysis of Annexin V-positive cells confirmed reduced apoptosis in TCF4-deleted cells following TGF-β2 treatment. Additionally, aggresome detection assays revealed that TCF4 deletion diminished TGF-β2-induced protein aggregation.

Conclusions

This study demonstrates a crucial role for TCF4 in FECD pathogenesis, particularly in ECM regulation and protein aggregation-induced cell death.

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will be maintained only if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74%-94% of the variance in aneuploid strains' growth rates is explained by the cumulative cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of small nucleolar RNAs (snoRNAs) and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains' growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

Engineered cell differentiation and sexual reproduction in probiotic and mating yeasts

G protein-coupled receptors (GPCRs) enable cells to sense environmental cues and are indispensable for coordinating vital processes including quorum sensing, proliferation, and sexual reproduction. GPCRs comprise the largest class of cell surface receptors in eukaryotes, and for more than three decades the pheromone-induced mating pathway in baker's yeast Saccharomyces cerevisiae has served as a model for studying heterologous GPCRs (hGPCRs). Here we report transcriptome profiles following mating pathway activation in native and hGPCR-signaling yeast and use a model-guided approach to correlate gene expression to morphological changes. From this we demonstrate mating between haploid cells armed with hGPCRs and endogenous biosynthesis of their cognate ligands. Furthermore, we devise a ligand-free screening strategy for hGPCR compatibility with the yeast mating pathway and enable hGPCR-signaling in the probiotic yeast Saccharomyces boulardii. Combined, our findings enable new means to study mating, hGPCR-signaling, and cell-cell communication in a model eukaryote and yeast probiotics.

Peptide-Dependent Growth in Yeast via Fine-Tuned Peptide/GPCR-Activated Essential Gene Expression

Building multicellular microbial consortia that communicate with each other and perform programmed functionalities is the next milestone for synthetic biology. Achieving cell-cell communication within these communities requires programming of the transduction of an extracellular signal into a customized intracellular response. G-protein-coupled receptors (GPCRs) are attractive candidates for engineering signal transduction as they can sense extracellular events with high sensitivity and specificity and transduce them into complex intracellular programs. We recently developed a scalable cell-cell communication language based on fungal mating GPCRs and their secreted peptide ligands. This language allows the assembly of engineered yeast strains into multicellular communication networks and allows them to be made interdependent by peptide signaling. In peptide signaling, one cell secretes a peptide that supports the growth of another cell at nanomolar concentrations, a scalable approach for engineering interdependence. Here we address the challenge of correlating the doubling time of Saccharomyces cerevisiae cells with an increasing external peptide concentration by linking GPCR activation to the expression of an essential gene. The required fine-tuning of downstream signaling is achieved via the transcriptional titration of a set of orthogonal GPCR-activated transcription factors, a series of corresponding promoters with different output dynamics, and the use of chemically recoded peptide ligands with varying activation potentials. As such, our work establishes three control points that allow the tuning of the basal and maximal activation of the GPCR response, fold change activation, and response sensitivity. The presented results enable the implementation of peptide-dependent and peptide-tunable growth but could also facilitate the design and calibration of more complex GPCR-controlled synthetic functionality in the future.

Chemotaxis and Shorter O-Antigen Chain Length Contribute to the Strong Desiccation Tolerance of a Food-Isolated Cronobacter sakazakii Strain

Cronobacter sakazakii is an opportunistic pathogen causing a lethality rate as high as 80% in infants. Desiccation tolerance ensures its survival in powdered infant formula (PIF) and contributes to the increased exposure to neonates, resulting in neonatal meningitis, septicemia, and necrotizing enterocolitis. This study showed that a food-isolated C. sakazakii G4023 strain exhibited a stronger desiccation tolerance than C. sakazakii ATCC 29544 strain. Considering the proven pathogenicity of G4023, it could be a big threat to infants. Transcriptome and proteome were performed to provide new insights into the desiccation adaptation mechanisms of G4023. Integrated analyses of these omics suggested that 331 genes were found regulated at both transcriptional and protein levels (≥2.0- and ≥1.5-fold, respectively). Deletion of chemotaxis system encoded genes cheA and cheW resulted in decreased tolerance in both short- and long-term desiccation. Reduced O-antigen chain length contributed to the biofilm formation and desiccation tolerance in the short term rather than the long term. In addition, biosynthesis of flagella, arginine and its transport system, and Fe/S cluster were also observed regulated in desiccated G4023. A better understanding of desiccation adaptation mechanisms of G4023 could in turn guide the operations during production and preservation of PIF or other food to reduce survival odds of G4023 and lower its exposure to get to infants.

Inhibition of the norepinephrine transporter rescues vascular hyporeactivity to catecholamine in obstructive jaundice

In patients with obstructive jaundice, the cardiovascular system exhibits hypotension and vascular hyporeactivity. Most norepinephrine is taken up through the neuronal norepinephrine transporter (NET), which is implicated in cardiovascular diseases. A previous study demonstrated that pharmacological NET inhibition could increase resting blood pressure. However, the role of NETs in vascular hyporeactivity induced by obstructive jaundice is poorly understood. This study used the NET inhibitor nisoxetine and a rat model of bile duct ligation (BDL) to investigate whether NET is associated with BDL-induced vascular hyporeactivity. Rats were injected with nisoxetine via the tail vein for 7 consecutive days after BDL. Samples of the superior cervical sympathetic ganglion (SCG) and thoracic aortic rings were processed for investigations. Our results showed that NET expression in the SCG was significantly increased after BDL. Nisoxetine prevented the augmentation of NET expression, increased α₁-adrenoceptor activation, and enhanced the weakened contractile responses of thoracic aortic rings after BDL. Our study demonstrates that nisoxetine plays a protective role in BDL-induced vascular hyporeactivity through increased α₁-adrenoceptor activation in rats.

Modelling the effect of ribosome mobility on the rate of protein synthesis

Translation is one of the main steps in the synthesis of proteins. It consists of ribosomes that translate sequences of nucleotides encoded on mRNA into polypeptide sequences of amino acids. Ribosomes bound to mRNA move unidirectionally, while unbound ribosomes diffuse in the cytoplasm. It has been hypothesized that finite diffusion of ribosomes plays an important role in ribosome recycling and that mRNA circularization enhances the efficiency of translation, see e.g. Lodish et al. (Molecular cell biology, 8th edn, W.H. Freeman and Company, San Francisco, 2016). In order to estimate the effect of cytoplasmic diffusion on the rate of translation, we consider a totally asymmetric simple exclusion process coupled to a finite diffusive reservoir, which we call the ribosome transport model with diffusion. In this model, we derive an analytical expression for the rate of protein synthesis as a function of the diffusion constant of ribosomes, which is corroborated with results from continuous-time Monte Carlo simulations. Using a wide range of biological relevant parameters, we conclude that diffusion is not a rate limiting factor in translation initiation because diffusion is fast enough in biological cells.

Reciprocal relation between reporter gene transcription and translation efficiency in fission yeast

The fission yeast, Schizosaccharomyces pombe, is an excellent model for basic research but is not useful for commercial scale protein expression due to lack of strong expression vectors. Earlier, we showed that the lsd90 promoter elicited significantly greater GFP expression level than the adh1 and nmt1 promoters, albeit in different vector backbones. Here, we have systematically investigated the contribution of selectable markers, LEU2 and URA3m to GFP expression: while LEU2 elicited very low expression, the URA3m gene, with truncated promoter, elicited much greater GFP expression level with all promoters. Paradoxically, an inverse correlation was observed between the GFP transcription and translation efficiency. This system can be useful for understanding the factors governing recombinant gene expression and optimization of protein production.

Inferring efficiency of translation initiation and elongation from ribosome profiling

One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosome’s stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$50\%$\end{document}. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.

Migration inhibitory factor in spinal tuberculosis: -173G/C polymorphisms, and transcript and protein levels in a northern province of China

The aim of this study was to elucidate the possible association between migration inhibitory factor (MIF)-173G/C gene polymorphisms and transcript and plasma levels of MIF in spinal tuberculosis (TB) patients. Clinical data were collected from 254 spinal TB patients and 262 healthy controls participating in the study. The genotype of the MIF-173G/C gene was amplified by polymerase chain reaction and genotyped by DNA sequencing technology. The level of mRNA expression was determined by real-time polymerase chain reaction and MIF plasma levels were measured by a solid-phase enzyme-linked immunosorbent assay. The frequency of the C allele and GC+CC genotype in MIF-173G/C was over-represented in spinal TB patients. The mean MIF mRNA level in spinal TB patients and patients with the GG and GC+CC genotype were significantly lower than controls; however, our study also indicated that the MIF concentration in spinal TB patients and patients with the GG and GC+CC genotypes were significantly higher than controls. Spinal TB patients with the GG genotype had higher MIF plasma levels than patients with the GC+CC genotype. The C-reactive protein level and erythrocyte sedimentation rate was correlated with the MIF plasma level. In summary, the association between the MIF-173G/C genetic polymorphism, reduced transcript and increased plasma levels of MIF in spinal TB patients, and MIF may play an important role in the occurrence, development, and damage of spinal TB in the northern Province population of China.

Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.

The Key Parameters that Govern Translation Efficiency

Translation of mRNA into protein is a fundamental yet complex biological process with multiple factors that can potentially affect its efficiency. Here, we study a stochastic model describing the traffic flow of ribosomes along the mRNA and identify the key parameters that govern the overall rate of protein synthesis, sensitivity to initiation rate changes, and efficiency of ribosome usage. By analyzing a continuum limit of the model, we obtain closed-form expressions for stationary currents and ribosomal densities, which agree well with Monte Carlo simulations. Furthermore, we completely characterize the phase transitions in the system, and by applying our theoretical results, we formulate design principles that detail how to tune the key parameters we identified to optimize translation efficiency. Using ribosome profiling data from S. cerevisiae, we show that its translation system is generally consistent with these principles. Our theoretical results have implications for evolutionary biology, as well as for synthetic biology.

Power series method for solving TASEP-based models of mRNA translation

We develop a method for solving mathematical models of messenger RNA (mRNA) translation based on the totally asymmetric simple exclusion process (TASEP). Our main goal is to demonstrate that the method is versatile and applicable to realistic models of translation. To this end we consider the TASEP with codon-dependent elongation rates, premature termination due to ribosome drop-off and translation reinitiation due to circularisation of the mRNA. We apply the method to the model organism Saccharomyces cerevisiae under physiological conditions and find an excellent agreement with the results of stochastic simulations. Our findings suggest that the common view on translation as being rate-limited by initiation is oversimplistic. Instead we find theoretical evidence for ribosome interference and also theoretical support for the ramp hypothesis which argues that codons at the beginning of genes have slower elongation rates in order to reduce ribosome density and jamming.

Translation can affect the antisense activity of RNase H1-dependent oligonucleotides targeting mRNAs

RNase H1-dependent antisense oligonucleotides (ASOs) can degrade complementary RNAs in both the nucleus and the cytoplasm. Since cytoplasmic mRNAs are actively engaged in translation, ASO activity may thus be affected by translating ribosomes that scan the mRNAs. Here we show that mRNAs associated with ribosomes can be cleaved using ASOs and that translation can alter ASO activity. Translation inhibition tends to increase ASO activity when targeting the coding regions of efficiently translated mRNAs, but not nuclear non-coding RNAs or less efficiently translated mRNAs. Increasing the level of RNase H1 protein eliminated the enhancing effects of translation inhibition on ASO activity, suggesting that RNase H1 recruitment to ASO/mRNA heteroduplexes is a rate limiting step and that translating ribosomes can inhibit RNase H1 recruitment. Consistently, ASO activity was not increased by translation inhibition when targeting the 3′ UTRs, independent of the translation efficiency of the mRNAs. Contrarily, the activity of 3′ UTR-targeting ASOs tended to be reduced upon translation inhibition, likely due to decreased accessibility. These results indicate that ASO activity can be affected by the translation process, and the findings also provide important information toward helping better ASO drug design.

A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data

Analysis methods based on simulations and optimization have been previously developed to estimate relative translation rates from next-generation sequencing data. Translation involves molecules and chemical reactions, hence bioinformatics methods consistent with the laws of chemistry and physics are more likely to produce accurate results. Here, we derive simple equations based on chemical kinetic principles to measure the translation-initiation rate, transcriptome-wide elongation rate, and individual codon translation rates from ribosome profiling experiments. Our methods reproduce the known rates from ribosome profiles generated from detailed simulations of translation. By applying our methods to data from S. cerevisiae and mouse embryonic stem cells, we find that the extracted rates reproduce expected correlations with various molecular properties, and we also find that mouse embryonic stem cells have a global translation speed of 5.2 AA/s, in agreement with previous reports that used other approaches. Our analysis further reveals that a codon can exhibit up to 26-fold variability in its translation rate depending upon its context within a transcript. This broad distribution means that the average translation rate of a codon is not representative of the rate at which most instances of that codon are translated, and it suggests that translational regulation might be used by cells to a greater degree than previously thought.

Enhancing co-translational folding of heterologous protein by deleting non-essential ribosomal proteins in Pichia pastoris

BACKGROUND

Translational regulation played an important role in the correct folding of heterologous proteins to form bioactive conformations during biogenesis. Translational pausing coordinates protein translation and co-translational folding. Decelerating translation elongation speed has been shown to improve the soluble protein yield when expressing heterologous proteins in industrial expression hosts. However, rational redesign of translational pausing via synonymous mutations may not be feasible in many cases. Our goal was to develop a general and convenient strategy to improve heterologous protein synthesis in Pichia pastoris without mutating the expressed genes.

RESULTS

Here, a large-scale deletion library of ribosomal protein (RP) genes was constructed for heterologous protein expression in Pichia pastoris, and 59% (16/27) RP deletants have significantly increased heterologous protein yield. This is due to the delay of 60S subunit assembly by deleting non-essential ribosomal protein genes or 60S subunit processing factors, thus globally decreased the translation elongation speed and improved the co-translational folding, without perturbing the relative transcription level and translation initiation.

CONCLUSION

Global decrease in the translation elongation speed by RP deletion enhanced co-translational folding efficiency of nascent chains and decreased protein aggregates to improve heterologous protein yield. A potential expression platform for efficient pharmaceutical proteins and industrial enzymes production was provided without synonymous mutation.

Bioinformatics and Translation Elongation

Codon usage depends on mutation bias, tRNA-mediated selection, and the need for high efficiency and accuracy in translation. One codon in a synonymous codon family is often strongly over-used, especially in highly expressed genes, which often leads to a high dN/dS ratio because dS is very small. Many different codon usage indices have been proposed to measure codon usage and codon adaptation. Sense codon could be misread by release factors and stop codons misread by tRNAs, which also contribute to codon usage in rare cases. This chapter outlines the conceptual framework on codon evolution, illustrates codon-specific and gene-specific codon usage indices, and presents their applications. A new index for codon adaptation that accounts for background mutation bias (Index of Translation Elongation) is presented and contrasted with codon adaptation index (CAI) which does not consider background mutation bias. They are used to re-analyze data from a recent paper claiming that translation elongation efficiency matters little in protein production. The reanalysis disproves the claim.

Determinants of translation speed are randomly distributed across transcripts resulting in a universal scaling of protein synthesis times

Ribosome profiling experiments have found greater than 100-fold variation in ribosome density along mRNA transcripts, indicating that individual codon elongation rates can vary to a similar degree. This wide range of elongation times, coupled with differences in codon usage between transcripts, suggests that the average codon translation-rate per gene can vary widely. Yet, ribosome run-off experiments have found that the average codon translation rate for different groups of transcripts in mouse stem cells is constant at 5.6 AA/s. How these seemingly contradictory results can be reconciled is the focus of this study. Here, we combine knowledge of the molecular factors shown to influence translation speed with genomic information from Escherichia coli, Saccharomyces cerevisiae and Homo sapiens to simulate the synthesis of cytosolic proteins in these organisms. The model recapitulates a near constant average translation rate, which we demonstrate arises because the molecular determinants of translation speed are distributed nearly randomly amongst most of the transcripts. Consequently, codon translation rates are also randomly distributed and fast-translating segments of a transcript are likely to be offset by equally probable slow-translating segments, resulting in similar average elongation rates for most transcripts. We also show that the codon usage bias does not significantly affect the near random distribution of codon translation rates because only about 10% of the total transcripts in an organism have high codon usage bias while the rest have little to no bias. Analysis of Ribo-Seq data and an in vivo fluorescent assay supports these conclusions.

The impact of ribosomal interference, codon usage, and exit tunnel interactions on translation elongation rate variation

Previous studies have shown that translation elongation is regulated by multiple factors, but the observed heterogeneity remains only partially explained. To dissect quantitatively the different determinants of elongation speed, we use probabilistic modeling to estimate initiation and local elongation rates from ribosome profiling data. This model-based approach allows us to quantify the extent of interference between ribosomes on the same transcript. We show that neither interference nor the distribution of slow codons is sufficient to explain the observed heterogeneity. Instead, we find that electrostatic interactions between the ribosomal exit tunnel and specific parts of the nascent polypeptide govern the elongation rate variation as the polypeptide makes its initial pass through the tunnel. Once the N-terminus has escaped the tunnel, the hydropathy of the nascent polypeptide within the ribosome plays a major role in modulating the speed. We show that our results are consistent with the biophysical properties of the tunnel.

Gene length as a regulator for ribosome recruitment and protein synthesis: theoretical insights

Protein synthesis rates are determined, at the translational level, by properties of the transcript’s sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. According to our results, the proximity of the 3′ end to the ribosomal recruitment site of the mRNA could induce a feedback in the translation process that would favour the recycling of ribosomes. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.

ARSDA: A New Approach for Storing, Transmitting and Analyzing Transcriptomic Data

Two major stumbling blocks exist in high-throughput sequencing (HTS) data analysis. The first is the sheer file size, typically in gigabytes when uncompressed, causing problems in storage, transmission, and analysis. However, these files do not need to be so large, and can be reduced without loss of information. Each HTS file, either in compressed .SRA or plain text .fastq format, contains numerous identical reads stored as separate entries. For example, among 44,603,541 forward reads in the SRR4011234.sra file (from a Bacillus subtilis transcriptomic study) deposited at NCBI’s SRA database, one read has 497,027 identical copies. Instead of storing them as separate entries, one can and should store them as a single entry with the SeqID_NumCopy format (which I dub as FASTA+ format). The second is the proper allocation of reads that map equally well to paralogous genes. I illustrate in detail a new method for such allocation. I have developed ARSDA software that implement these new approaches. A number of HTS files for model species are in the process of being processed and deposited at http://coevol.rdc.uottawa.ca to demonstrate that this approach not only saves a huge amount of storage space and transmission bandwidth, but also dramatically reduces time in downstream data analysis. Instead of matching the 497,027 identical reads separately against the B. subtilis genome, one only needs to match it once. ARSDA includes functions to take advantage of HTS data in the new sequence format for downstream data analysis such as gene expression characterization. I contrasted gene expression results between ARSDA and Cufflinks so readers can better appreciate the strength of ARSDA. ARSDA is freely available for Windows, Linux. and Macintosh computers at http://dambe.bio.uottawa.ca/ARSDA/ARSDA.aspx.

Effect of MT3 on Retinal and Choroidal TGF-β2 and HAS2 Expressions in Form Deprivation Myopia of Guinea Pig

Purpose

To confirm its dose-dependent effect on form deprivation myopia and evaluate the effect of MT3 at different tissue concentrations on changes in mRNA and protein expression for TGF-β2 and HAS2.

Methods

MT3 was intravitreally injected into deprived eyes at two-day intervals. Refraction was measured by streak retinoscopy after cycloplegia. The axial dimensions were measured by A-scan ultrasound. The quantitative RT-PCR and Western blot were used to detect the changes of TGF-β2 and HAS2 expressions in the retina and choroid of guinea pigs.

Results

MT3 treatment produced a significant dose-dependent reduction in relative myopia compared to FD group (both p < 0.001). There were statistically significant increases in retinal and choroidal mRNA levels for both TGF-β2 and HAS2 after injections of 10 μM of MT3, when compared to the FD group. There were no significant differences in retinal and choroidal TGF-β2 protein expression levels between the MT3 treatment groups and FD group (all p > 0.05). The injections of 10 μM of MT3 caused a marked decrease in retinal HAS2 protein expression level, when compared to the FD group (p = 0.001).

Conclusion

MT3 can inhibit form deprivation myopia, and MT3 treatment can result in changes of retinal and choroidal TGF-β2 and HAS2 mRNA and protein expressions.

Positive Detection of GPCR Antagonists Using a System for Inverted Expression of a Fluorescent Reporter Gene

The yeast Saccharomyces cerevisiae is a useful eukaryotic host organism for studying GPCRs as monomolecular models. Fluorescent reporter gene assays for GPCRs provide a convenient assay for measuring receptor activity using fluorometric instruments. Generally, these assays detect receptor activation by agonistic ligands as the induction of fluorescent reporter expression, whereas antagonistic activities are detected by competition with agonistic ligands, resulting in decreases in fluorescence intensity. In the current study, we established a system for inverted expression of a fluorescent reporter by incorporating a PEST-tag and finding out a promoter inhibited by activation of the GPCR signaling pathway from yeast endogenous promoters. Because agonists prevent fluorescent reporter expression in this system, antagonists compete with agonists and yield increased fluorescence intensity. We used the yeast endogenous pheromone receptor as a model GPCR to demonstrate the feasibility of our system for positive detection targeted at antagonists. Compared to results when only agonists were added to yeast cells, more than 10-fold higher fluorescence intensity was observed when antagonists were added in combination with agonists. The approach described here has the potential to markedly accelerate the identification of GPCR antagonists by providing rapid and straightforward responses.

Inhibiting function of human fetal dermal mesenchymal stem cells on bioactivities of keloid fibroblasts

BACKGROUND

Keloid is one kind of benign skin disease caused by hyperplasia of fibroblasts and collagen fibrils. It is refractory due to the lack of an effective treatment at present, which puts pressure on seeking a new therapeutic regimen. Mesenchymal stem cells (MSCs) from fetal skin are considered to play a crucial role in scarless healing. Nevertheless, the efficacy of them in keloid disorders remains poorly understood.

METHODS

Keloid fibroblasts (KFs), human adult dermal fibroblasts (ADFs), and human fetal dermal mesenchymal stem cells (FDMSCs) were isolated to single cells and cultured in Dulbecco's modified Eagle's medium (DMEM). ADFs and FDMSCs were used to generate ADF-conditioned medium (A-CM) and FDMSC-conditioned medium (F-CM). The effects of A-CM and F-CM on KFs were tested using MTT assay, BrdU assay, TUNEL assay, quantitative polymerase chain reaction, Western blot, and annexin V-FITC/PI binding assay,.

RESULTS

FDMSCs inhibited the bioactivity of KFs, downregulated the expression of the antiapoptotic protein BCL-2, and upregulated the expression of the proapoptotic protein BAX of KFs by secreting some soluble substances, thus accelerating the apoptosis of KFs.

CONCLUSION

F-CM induces apoptosis of KFs, providing a novel treatment strategy for keloid disorders.

Ribosome reinitiation can explain length-dependent translation of messenger RNA

Models of mRNA translation usually presume that transcripts are linear; upon reaching the end of a transcript each terminating ribosome returns to the cytoplasmic pool before initiating anew on a different transcript. A consequence of linear models is that faster translation of a given mRNA is unlikely to generate more of the encoded protein, particularly at low ribosome availability. Recent evidence indicates that eukaryotic mRNAs are circularized, potentially allowing terminating ribosomes to preferentially reinitiate on the same transcript. Here we model the effect of ribosome reinitiation on translation and show that, at high levels of reinitiation, protein synthesis rates are dominated by the time required to translate a given transcript. Our model provides a simple mechanistic explanation for many previously enigmatic features of eukaryotic translation, including the negative correlation of both ribosome densities and protein abundance on transcript length, the importance of codon usage in determining protein synthesis rates, and the negative correlation between transcript length and both codon adaptation and 5' mRNA folding energies. In contrast to linear models where translation is largely limited by initiation rates, our model reveals that all three stages of translation-initiation, elongation, and termination/reinitiation-determine protein synthesis rates even at low ribosome availability.

Novel mRNA-specific effects of ribosome drop-off on translation rate and polysome profile

The well established phenomenon of ribosome drop-off plays crucial roles in translational accuracy and nutrient starvation responses during protein translation. When cells are under stress conditions, such as amino acid starvation or aminoacyl-tRNA depletion due to a high level of recombinant protein expression, ribosome drop-off can substantially affect the efficiency of protein expression. Here we introduce a mathematical model that describes the effects of ribosome drop-off on the ribosome density along the mRNA and on the concomitant protein synthesis rate. Our results show that ribosome premature termination may lead to non-intuitive ribosome density profiles, such as a ribosome density which increases from the 5' to the 3' end. Importantly, the model predicts that the effects of ribosome drop-off on the translation rate are mRNA-specific, and we quantify their resilience to drop-off, showing that the mRNAs which present ribosome queues are much less affected by ribosome drop-off than those which do not. Moreover, among those mRNAs that do not present ribosome queues, resilience to drop-off correlates positively with the elongation rate, so that sequences using fast codons are expected to be less affected by ribosome drop-off. This result is consistent with a genome-wide analysis of S. cerevisiae, which reveals that under favourable growth conditions mRNAs coding for proteins involved in the translation machinery, known to be highly codon biased and using preferentially fast codons, are highly resilient to ribosome drop-off. Moreover, in physiological conditions, the translation rate of mRNAs coding for regulatory, stress-related proteins, is less resilient to ribosome drop-off. This model therefore allows analysis of variations in the translational efficiency of individual mRNAs by accounting for the full range of known ribosome behaviours, as well as explaining mRNA-specific variations in ribosome density emerging from ribosome profiling studies.

Bioinformatics and Drug Discovery

Bioinformatic analysis can not only accelerate drug target identification and drug candidate screening and refinement, but also facilitate characterization of side effects and predict drug resistance. High-throughput data such as genomic, epigenetic, genome architecture, cistromic, transcriptomic, proteomic, and ribosome profiling data have all made significant contribution to mechanismbased drug discovery and drug repurposing. Accumulation of protein and RNA structures, as well as development of homology modeling and protein structure simulation, coupled with large structure databases of small molecules and metabolites, paved the way for more realistic protein-ligand docking experiments and more informative virtual screening. I present the conceptual framework that drives the collection of these high-throughput data, summarize the utility and potential of mining these data in drug discovery, outline a few inherent limitations in data and software mining these data, point out news ways to refine analysis of these diverse types of data, and highlight commonly used software and databases relevant to drug discovery.

Snf1-Dependent Transcription Confers Glucose-Induced Decay upon the mRNA Product

In the yeast Saccharomyces cerevisiae, the switch from respiratory metabolism to fermentation causes rapid decay of transcripts encoding proteins uniquely required for aerobic metabolism. Snf1, the yeast ortholog of AMP-activated protein kinase, has been implicated in this process because inhibiting Snf1 mimics the addition of glucose. In this study, we show that the SNF1-dependent ADH2 promoter, or just the major transcription factor binding site, is sufficient to confer glucose-induced mRNA decay upon heterologous transcripts. SNF1-independent expression from the ADH2 promoter prevented glucose-induced mRNA decay without altering the start site of transcription. SNF1-dependent transcripts are enriched for the binding motif of the RNA binding protein Vts1, an important mediator of mRNA decay and mRNA repression whose expression is correlated with decreased abundance of SNF1-dependent transcripts during the yeast metabolic cycle. However, deletion of VTS1 did not slow the rate of glucose-induced mRNA decay. ADH2 mRNA rapidly dissociated from polysomes after glucose repletion, and sequences bound by RNA binding proteins were enriched in the transcripts from repressed cells. Inhibiting the protein kinase A pathway did not affect glucose-induced decay of ADH2 mRNA. Our results suggest that Snf1 may influence mRNA stability by altering the recruitment activity of the transcription factor Adr1.

LUCID: A Quantitative Assay of ESCRT-Mediated Cargo Sorting into Multivesicular Bodies

Endosomes are transportation nodes, mediating selective transport of soluble and transmembrane cargos to and from the Golgi apparatus, plasma membrane and lysosomes. As endosomes mature to become multivesicular bodies (MVBs), Endosomal Sorting Complexes Required for Transport (ESCRTs) selectively incorporate transmembrane cargos into vesicles that bud into the endosome lumen. Luminal vesicles and their cargoes are targeted for destruction when MVBs fuse with lysosomes. Common assays of endosomal luminal targeting, including fluorescence microscopy and monitoring of proteolytic cargo maturation, possess significant limitations. We present a quantitative assay system called LUCID (LUCiferase reporter of Intraluminal Deposition) that monitors exposure of chimeric luciferase-cargo reporters to cytosol. Luciferase-chimera signal increases when sorting to the endosome lumen is disrupted, and silencing of signal from the chimera depends upon luminal delivery of the reporter rather than proteolytic degradation. The system presents several advantages, including rapidity, microscale operation and a high degree of reproducibility that enables detection of subtle phenotypic differences. Luciferase reporters provide linear signal over an extremely broad dynamic range, allowing analysis of reporter traffic even at anemic levels of expression. Furthermore, LUCID reports transport kinetics when applied to inducible trafficking reporters.

A Comprehensive Analysis of Replicative Lifespan in 4,698 Single-Gene Deletion Strains Uncovers Conserved Mechanisms of Aging

Many genes that affect replicative lifespan (RLS) in the budding yeast Saccharomyces cerevisiae also affect aging in other organisms such as C. elegans and M. musculus. We performed a systematic analysis of yeast RLS in a set of 4,698 viable single-gene deletion strains. Multiple functional gene clusters were identified, and full genome-to-genome comparison demonstrated a significant conservation in longevity pathways between yeast and C. elegans. Among the mechanisms of aging identified, deletion of tRNA exporter LOS1 robustly extended lifespan. Dietary restriction (DR) and inhibition of mechanistic Target of Rapamycin (mTOR) exclude Los1 from the nucleus in a Rad53-dependent manner. Moreover, lifespan extension from deletion of LOS1 is nonadditive with DR or mTOR inhibition, and results in Gcn4 transcription factor activation. Thus, the DNA damage response and mTOR converge on Los1-mediated nuclear tRNA export to regulate Gcn4 activity and aging.

Ty3 Retrotransposon Hijacks Mating Yeast RNA Processing Bodies to Infect New Genomes

Retrotransposition of the budding yeast long terminal repeat retrotransposon Ty3 is activated during mating. In this study, proteins that associate with Ty3 Gag3 capsid protein during virus-like particle (VLP) assembly were identified by mass spectrometry and screened for roles in mating-stimulated retrotransposition. Components of RNA processing bodies including DEAD box helicases Dhh1/DDX6 and Ded1/DDX3, Sm-like protein Lsm1, decapping protein Dcp2, and 5' to 3' exonuclease Xrn1 were among the proteins identified. These proteins associated with Ty3 proteins and RNA, and were required for formation of Ty3 VLP retrosome assembly factories and for retrotransposition. Specifically, Dhh1/DDX6 was required for normal levels of Ty3 genomic RNA, and Lsm1 and Xrn1 were required for association of Ty3 protein and RNA into retrosomes. This role for components of RNA processing bodies in promoting VLP assembly and retrotransposition during mating in a yeast that lacks RNA interference, contrasts with roles proposed for orthologous components in animal germ cell ribonucleoprotein granules in turnover and epigenetic suppression of retrotransposon RNAs.

RiboAbacus: a model trained on polyribosome images predicts ribosome density and translational efficiency from mammalian transcriptomes

Fluctuations in mRNA levels only partially contribute to determine variations in mRNA availability for translation, producing the well-known poor correlation between transcriptome and proteome data. Recent advances in microscopy now enable researchers to obtain high resolution images of ribosomes on transcripts, providing precious snapshots of translation in vivo. Here we propose RiboAbacus, a mathematical model that for the first time incorporates imaging data in a predictive model of transcript-specific ribosome densities and translational efficiencies. RiboAbacus uses a mechanistic model of ribosome dynamics, enabling the quantification of the relative importance of different features (such as codon usage and the 5′ ramp effect) in determining the accuracy of predictions. The model has been optimized in the human Hek-293 cell line to fit thousands of images of human polysomes obtained by atomic force microscopy, from which we could get a reference distribution of the number of ribosomes per mRNA with unmatched resolution. After validation, we applied RiboAbacus to three case studies of known transcriptome-proteome datasets for estimating the translational efficiencies, resulting in an increased correlation with corresponding proteomes. RiboAbacus is an intuitive tool that allows an immediate estimation of crucial translation properties for entire transcriptomes, based on easily obtainable transcript expression levels.

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

Estimating a structured covariance matrix from multi-lab measurements in high-throughput biology

We consider the problem of quantifying the degree of coordination between transcription and translation, in yeast. Several studies have reported a surprising lack of coordination over the years, in organisms as different as yeast and human, using diverse technologies. However, a close look at this literature suggests that the lack of reported correlation may not reflect the biology of regulation. These reports do not control for between-study biases and structure in the measurement errors, ignore key aspects of how the data connect to the estimand, and systematically underestimate the correlation as a consequence. Here, we design a careful meta-analysis of 27 yeast data sets, supported by a multilevel model, full uncertainty quantification, a suite of sensitivity analyses and novel theory, to produce a more accurate estimate of the correlation between mRNA and protein levels-a proxy for coordination. From a statistical perspective, this problem motivates new theory on the impact of noise, model mis-specifications and non-ignorable missing data on estimates of the correlation between high dimensional responses. We find that the correlation between mRNA and protein levels is quite high under the studied conditions, in yeast, suggesting that post-transcriptional regulation plays a less prominent role than previously thought.

Ribosome recycling induces optimal translation rate at low ribosomal availability

During eukaryotic cellular protein synthesis, ribosomal translation is made more efficient through interaction between the two ends of the messenger RNA (mRNA). Ribosomes reaching the 3′ end of the mRNA can thus recycle and begin translation again on the same mRNA, the so-called ‘closed-loop’ model. Using a driven diffusion lattice model of translation, we study the effects of ribosome recycling on the dynamics of ribosome flow and density on the mRNA. We show that ribosome recycling induces a substantial increase in ribosome current. Furthermore, for sufficiently large values of the recycling rate, the lattice does not transition directly from low to high ribosome density, as seen in lattice models without recycling. Instead, a maximal current phase becomes accessible for much lower values of the initiation rate, and multiple phase transitions occur over a wide region of the phase plane. Crucially, we show that in the presence of ribosome recycling, mRNAs can exhibit a peak in protein production at low values of the initiation rate, beyond which translation rate decreases. This has important implications for translation of certain mRNAs, suggesting that there is an optimal concentration of ribosomes at which protein synthesis is maximal, and beyond which translational efficiency is impaired.

Mathematical model of the Tat-Rev regulation of HIV-1 replication in an activated cell predicts the existence of oscillatory dynamics in the synthesis of viral components

Background

The life cycle of human immunodeficiency virus type-1 (HIV-1) makes possible the realization of regulatory strategies that can lead to complex dynamical behavior of the system. We analyze the strategy which is based on two feedback mechanisms, one mediating a positive regulation of the virus replication by Tat protein via the antitermination of the genomic RNAs transcription on TAR (transactivation responsive) element of the proviral DNA and the second mechanism providing a negative regulation of the splicing of the full-length (9 kb) RNAs and incompletely spliced (4 kb) RNAs via their transport from the nucleus to the cytoplasm. Although the existence of these two regulatory feedback loops has been considered in other mathematical models, none of them examined the conditions for the emergence of complex oscillatory patterns in the intracellular dynamics of viral components.

Results

We developed a mechanistic mathematical model for the Tat-Rev mediated regulation of HIV-1 replication, which considers the activation of proviral DNA transcription, the Tat-specific antitermination of transcription on TAR-element, resulting in the synthesis of the full-length 9 kb RNA, the splicing of the 9 kb RNA down to the 4 kb RNA and the 4 kb RNA to 2 kb RNA, the transport of 2 kb mRNAs from the nucleus to the cytoplasm by the intracellular mechanisms, the multiple binding of the Rev protein to RRE (Rev Response Element) sites on 9 kb and 4 kb RNA resulting in their export to the cytoplasm and the synthesis of Tat and Rev proteins in the cytoplasm followed by their transport into the nucleus. The degradation of all viral proteins and RNAs both in the cytoplasm and the nucleus is described. The model parameters values were derived from the published literature data. The model was used to examine the dynamics of the synthesis of the viral proteins Tat and Rev, the mRNAs under the intracellular conditions specific for activated HIV-1 infected macrophages. In addition, we analyzed alternative hypotheses for the re-cycling of the Rev proteins both in the cytoplasm and the nuclear pore complex.

Conclusions

The quantitative mathematical model of the Tat-Rev regulation of HIV-1 replication predicts the existence of oscillatory dynamics which depends on the efficacy of the Tat and TAR interaction as well as on the Rev-mediated transport processes. The biological relevance of the oscillatory regimes for the HIV-1 life cycle is discussed.

Genetic influences on translation in yeast

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.

Individuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic—it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called “ribosome profiling” to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.

A competitive chemiluminescence enzyme immunoassay method for β-defensin-2 detection in transgenic mice

A competitive chemiluminescence enzyme immunoassay (CLEIA) method for porcine β-defensin-2 (pBD-2) detection in transgenic mice was established. Several factors that affect detection, including luminol, p-iodophenol and hydrogen peroxide concentrations, as well as pH, were studied and optimized. The linear range of the proposed method for pBD-2 detection under optimal conditions was 0.05-80 ng/mL with a correlation coefficient of 0.9960. Eleven detections of a 30 ng/mL pBD-2 standard sample were performed. Reproducible results were obtained with a relative standard deviation of 3.94%. The limit of detection of the method for pBD-2 was 3.5 pg/mL (3σ). The proposed method was applied to determine pBD-2 expression levels in the tissues of pBD-2 transgenic mice, and compared with LC-MS/MS and quantitative real-time reverse-transcriptase polymerase chain reaction. This suggests that the CLEIA can be used as a valuable method to detect and quantify pBD-2.

The translational landscape of fission-yeast meiosis and sporulation

Sexual development in the fission yeast Schizosaccharomyces pombe culminates in meiosis and sporulation. We used ribosome profiling to investigate the translational landscape of this process. We show that the translation efficiency of hundreds of genes is regulated in complex patterns, often correlating with changes in RNA levels. Ribosome-protected fragments show a three-nucleotide periodicity that identifies translated sequences and their reading frame. Using this property, we identified 46 novel translated genes and found that 24% of non-coding RNAs are actively translated. We also detected 19 nested antisense genes, in which both DNA strands encode translated mRNAs. Finally, we identified 1,735 translated upstream ORFs in leader sequences. In contrast with Saccharomyces cerevisiae, sexual development in S. pombe is not accompanied by large increases in upstream ORF use, suggesting that this is an organism-specific adaptation and not a general feature of developmental processes.

Comparative proteome analysis of two Streptococcus agalactiae strains from cultured tilapia with different virulence

Streptococcus agalactiae is a major piscine pathogen, which causes significant morbidity and mortality among numerous fish species, and results in huge economic losses to aquaculture. Many S. agalactiae strains showing different virulence characteristics have been isolated from infected tilapia in different geographical regions throughout South China in the recent years, including natural attenuated S. agalactiae strain TFJ0901 and virulent S. agalactiae strain THN0901. In the present study, survival of tilapia challenged with S. agalactiae strain TFJ0901 and THN0901 (10(7)CFU/fish) were 93.3% and 13.3%, respectively. Moreover, there are severe lesions of the examined tissues in tilapia infected with strain THN0901, but no significant histopathological changes were observed in tilapia infected with the strain TFJ0901. In order to elucidate the factors responsible for the invasive potential of S. agalactiae between two strains TFJ0901 and THN0901, a comparative proteome analysis was applied to identify the different protein expression profiles between the two strains. 506 and 508 cellular protein spots of S. agalactiae TFJ0901 and THN0901 were separated by two dimensional electrophoresis, respectively. And 34 strain-specific spots, corresponding to 27 proteins, were identified successfully by MALDI-TOF mass spectrometry. Among them, 23 proteins presented exclusively in S. agalactiae TFJ0901 or THN0901, and the other 4 proteins presented in different isomeric forms between TFJ0901 and THN0901. Most of the strain-specific proteins were just involved in metabolic pathways, while 7 of them were presumed to be responsible for the virulence differences of S. agalactiae strain TFJ0901 and THN0901, including molecular chaperone DnaJ, dihydrolipoamide dehydrogenase, thioredoxin, manganese-dependent inorganic pyrophosphatase, elongation factor Tu, bleomycin resistance protein and cell division protein DivIVA. These virulence-associated proteins may contribute to identify new diagnostic markers and help to understand the pathogenesis of S. agalactiae.

Differential expression of tyrosine hydroxylase and transporters in the right and left stellate ganglion of socially isolated rats

Chronic isolation stress of adult rat males acted increasing gene expression of tyrosine hydroxylase (TH) and neuronal norepinephrine transporter (NET) in the right stellate ganglia, while vesicular monoamine transporter 2 (VMAT2) level remained unchanged. The stress decreased protein level of TH, as well as mRNA levels for NET and VMAT2 in the left stellate ganglia, but expressed no effect on protein levels of these two transporters. These results demonstrate asymmetry in noradrenergic genes in the right and left stellate ganglia during stress and provide molecular evidence to help explain the difference in response to the stress.

Cytological and comparative proteomic analyses on male sterility in Brassica napus L. induced by the chemical hybridization agent monosulphuron ester sodium

Male sterility induced by a chemical hybridization agent (CHA) is an important tool for utilizing crop heterosis. Monosulphuron ester sodium (MES), a new acetolactate synthase-inhibitor herbicide belonging to the sulphonylurea family, has been developed as an effective CHA to induce male sterility in rapeseed (Brassica napus L.). To understand MES-induced male sterility in rapeseed better, comparative cytological and proteomic analyses were conducted in this study. Cytological analysis indicated that defective tapetal cells and abnormal microspores were gradually generated in the developing anthers of MES-treated plants at various development stages, resulting in unviable microspores and male sterility. A total of 141 differentially expressed proteins between the MES-treated and control plants were revealed, and 131 of them were further identified by MALDI-TOF/TOF MS. Most of these proteins decreased in abundance in tissues of MES-treated rapeseed plants, and only a few increased. Notably, some proteins were absent or induced in developing anthers after MES treatment. These proteins were involved in several processes that may be crucial for tapetum and microspore development. Down-regulation of these proteins may disrupt the coordination of developmental and metabolic processes, resulting in defective tapetum and abnormal microspores that lead to male sterility in MES-treated plants. Accordingly, a simple model of CHA-MES-induced male sterility in rapeseed was established. This study is the first cytological and dynamic proteomic investigation on CHA-MES-induced male sterility in rapeseed, and the results provide new insights into the molecular events of male sterility.

A decade of plant proteomics and mass spectrometry: translation of technical advancements to food security and safety issues

Tremendous progress in plant proteomics driven by mass spectrometry (MS) techniques has been made since 2000 when few proteomics reports were published and plant proteomics was in its infancy. These achievements include the refinement of existing techniques and the search for new techniques to address food security, safety, and health issues. It is projected that in 2050, the world's population will reach 9-12 billion people demanding a food production increase of 34-70% (FAO, 2009) from today's food production. Provision of food in a sustainable and environmentally committed manner for such a demand without threatening natural resources, requires that agricultural production increases significantly and that postharvest handling and food manufacturing systems become more efficient requiring lower energy expenditure, a decrease in postharvest losses, less waste generation and food with longer shelf life. There is also a need to look for alternative protein sources to animal based (i.e., plant based) to be able to fulfill the increase in protein demands by 2050. Thus, plant biology has a critical role to play as a science capable of addressing such challenges. In this review, we discuss proteomics especially MS, as a platform, being utilized in plant biology research for the past 10 years having the potential to expedite the process of understanding plant biology for human benefits. The increasing application of proteomics technologies in food security, analysis, and safety is emphasized in this review. But, we are aware that no unique approach/technology is capable to address the global food issues. Proteomics-generated information/resources must be integrated and correlated with other omics-based approaches, information, and conventional programs to ensure sufficient food and resources for human development now and in the future.

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.