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1.  Comparing Protein and mRNA Abundances to Protein Expression Regulation 
Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady-state protein concentrations in multi-cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two-thirds of protein abundance variation. mRNA sequence lengths, amino-acid properties, upstream open reading frames and secondary structures in the 5' untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3'UTR explained a larger proportion of protein abundance variation than characteristics of the 5'UTR. Further, we used data from human and six other organisms (bacteria, yeast, worm, fly, and plant) and established that steady-state abundances of proteins show significantly higher correlation across these diverse phylogenetic taxa than the abundances of their corresponding mRNAs (p=0.0008, paired Wilcoxon). These data suggest strong selective pressure to maintain protein abundances during evolution, even when mRNA abundances diverge. The absolute protein and mRNA concentration measurements for >1000 human genes and for other organisms represent one of the largest datasets currently available, and reveal both general trends and specific examples of post-transcriptional regulation.
PMCID: PMC3186639
2.  Concordant Regulation of Translation and mRNA Abundance for Hundreds of Targets of a Human microRNA 
PLoS Biology  2009;7(11):e1000238.
A specific microRNA reduces the synthesis of hundreds of proteins via concordant effects on the abundance and translation of the mRNAs that encode them.
MicroRNAs (miRNAs) regulate gene expression posttranscriptionally by interfering with a target mRNA's translation, stability, or both. We sought to dissect the respective contributions of translational inhibition and mRNA decay to microRNA regulation. We identified direct targets of a specific miRNA, miR-124, by virtue of their association with Argonaute proteins, core components of miRNA effector complexes, in response to miR-124 transfection in human tissue culture cells. In parallel, we assessed mRNA levels and obtained translation profiles using a novel global approach to analyze polysomes separated on sucrose gradients. Analysis of translation profiles for ∼8,000 genes in these proliferative human cells revealed that basic features of translation are similar to those previously observed in rapidly growing Saccharomyces cerevisiae. For ∼600 mRNAs specifically recruited to Argonaute proteins by miR-124, we found reductions in both the mRNA abundance and inferred translation rate spanning a large dynamic range. The changes in mRNA levels of these miR-124 targets were larger than the changes in translation, with average decreases of 35% and 12%, respectively. Further, there was no identifiable subgroup of mRNA targets for which the translational response was dominant. Both ribosome occupancy (the fraction of a given gene's transcripts associated with ribosomes) and ribosome density (the average number of ribosomes bound per unit length of coding sequence) were selectively reduced for hundreds of miR-124 targets by the presence of miR-124. Changes in protein abundance inferred from the observed changes in mRNA abundance and translation profiles closely matched changes directly determined by Western analysis for 11 of 12 proteins, suggesting that our assays captured most of miR-124–mediated regulation. These results suggest that miRNAs inhibit translation initiation or stimulate ribosome drop-off preferentially near the start site and are not consistent with inhibition of polypeptide elongation, or nascent polypeptide degradation contributing significantly to miRNA-mediated regulation in proliferating HEK293T cells. The observation of concordant changes in mRNA abundance and translational rate for hundreds of miR-124 targets is consistent with a functional link between these two regulatory outcomes of miRNA targeting, and the well-documented interrelationship between translation and mRNA decay.
Author Summary
The human genome contains directions to regulate the timing and magnitude of expression of its thousands of genes. MicroRNAs are important regulatory RNAs that tune the expression levels of tens to hundreds of specific genes by pairing to complimentary stretches in the messenger RNAs from these genes, thereby reducing their stability and their translation into protein. Although the importance of microRNAs is appreciated, little is known about the relative contributions of degradation or repression of translation of the cognate mRNAs to the overall effects on protein synthesis, or the links between these two regulatory mechanisms. We devised a simple, economical method to systematically measure mRNA translation profiles, then applied this method, in combination with gene expression analysis, to measure the effects of the human microRNA miR-124 on the abundance and apparent translation rate of its mRNA targets. We found that for the ∼600 mRNA targets of miR-124 that were identified by their association with microRNA effector complexes, around three quarters of the reduction in estimated protein synthesis was explained by changes in mRNA abundance. Although the apparent changes in translation efficiencies of the targeted mRNAs were smaller in magnitude, they were highly correlated with changes in the abundance of those RNAs, suggesting a functional link between microRNA-mediated repression of translation and mRNA decay.
doi:10.1371/journal.pbio.1000238
PMCID: PMC2766070  PMID: 19901979
3.  mRNA turnover rate limits siRNA and microRNA efficacy 
Based on a simple model of the mRNA life cycle, we predict that mRNAs with high turnover rates in the cell are more difficult to perturb with RNAi.We test this hypothesis using a luciferase reporter system and obtain additional evidence from a variety of large-scale data sets, including microRNA overexpression experiments and RT–qPCR-based efficacy measurements for thousands of siRNAs.Our results suggest that mRNA half-lives will influence how mRNAs are differentially perturbed whenever small RNA levels change in the cell, not only after transfection but also during differentiation, pathogenesis and normal cell physiology.
What determines how strongly an mRNA responds to a microRNA or an siRNA? We know that properties of the sequence match between the small RNA and the mRNA are crucial. However, large-scale validations of siRNA efficacies have shown that certain transcripts remain recalcitrant to perturbation even after repeated redesign of the siRNA (Krueger et al, 2007). Weak response to RNAi may thus be an inherent property of the mRNA, but the underlying factors have proven difficult to uncover.
siRNAs induce degradation by sequence-specific cleavage of their target mRNAs (Elbashir et al, 2001). MicroRNAs, too, induce mRNA degradation, and ∼80% of their effect on protein levels can be explained by changes in transcript abundance (Hendrickson et al, 2009; Guo et al, 2010). Given that multiple factors act simultaneously to degrade individual mRNAs, we here consider whether variable responses to micro/siRNA regulation may, in part, be explained simply by the basic dynamics of mRNA turnover. If a transcript is already under strong destabilizing regulation, it is theoretically possible that the relative change in abundance after the addition of a novel degrading factor would be less pronounced compared with a stable transcript (Figure 1). mRNA turnover is achieved by a multitude of factors, and the influence of such factors on targetability can be explored. However, their combined action, including yet unknown factors, is summarized into a single property: the mRNA decay rate.
First, we explored the theoretical relationship between the pre-existing turnover rate of an mRNA, and its expected susceptibility to perturbation by a small RNA. We assumed a basic model of the mRNA life cycle, in which the rate of transcription is constant and the rate of degradation is described by first-order kinetics. Under this model, the relative change in steady-state expression level will become smaller as the pre-existing decay rate grows larger, independent of the transcription rate. This relationship persists also if we assume various degrees of synergy and antagonism between the pre-existing factors and the external factor, with increasing synergism leading to transcripts being more equally targetable, regardless of their pre-existing decay rate.
We next generated a series of four luciferase reporter constructs with destabilizing AU-rich elements (AREs) of various strengths incorporated into their 3′ UTRs. To evaluate how the different constructs would respond to perturbation, we performed co-transfections with an siRNA targeted at the coding region of the luciferase gene. This reduced the signal of the non-destabilized construct to 26% compared with a control siRNA. In contrast, the most destabilized construct showed 42% remaining reporter activity, and we could observe a dose–response relationship across the series.
The reporter experiment encouraged an investigation of this effect on real-world mRNAs. We analyzed a set of 2622 siRNAs, for which individual efficacies were determined using RT–qPCR 48 h post-transfection in HeLa cells (www.appliedbiosystems.com). Of these, 1778 could be associated with an experimentally determined decay rate (Figure 4A). Although the overall correlation between the two variables was modest (Spearman's rank correlation rs=0.22, P<1e−20), we found that siRNAs directed at high-turnover (t1/2<200 min) and medium-turnover (2001000 min) transcripts (P<8e−11 and 4e−9, respectively, two-tailed KS-test, Figure 4B). While 41.6% (498/1196) of the siRNAs directed at low-turnover transcripts reached 10% remaining expression or better, only 16.7% (31/186) of the siRNAs that targeted high-turnover mRNAs reached this high degree of silencing (Figure 4B). Reduced targetability (25.2%, 100/396) was also seen for transcripts with medium-turnover rate.
Our results based on siRNA data suggested that turnover rates could also influence microRNA targeting. By assembling genome-wide mRNA expression data from 20 published microRNA transfections in HeLa cells, we found that predicted target mRNAs with short and medium half-life were significantly less repressed after transfection than their long-lived counterparts (P<8e−5 and P<0.03, respectively, two-tailed KS-test). Specifically, 10.2% (293/2874) of long-lived targets versus 4.4% (41/942) of short-lived targets were strongly (z-score <−3) repressed. siRNAs are known to cause off-target effects that are mediated, in part, by microRNA-like seed complementarity (Jackson et al, 2006). We analyzed changes in transcript levels after transfection of seven different siRNAs, each with a unique seed region (Jackson et al, 2006). Putative ‘off-targets' were identified by mapping of non-conserved seed matches in 3′ UTRs. We found that low-turnover mRNAs (t1/2 >1000 min) were more affected by seed-mediated off-target silencing than high-turnover mRNAs (t1/2 <200 min), with twice as many long-lived seed-containing transcripts (3.8 versus 1.9%) being strongly (z-score <−3) repressed.
In summary, mRNA turnover rates have an important influence on the changes exerted by small RNAs on mRNA levels. It can be assumed that mRNA half-lives will influence how mRNAs are differentially perturbed whenever small RNA levels change in the cell, not only after transfection but also during differentiation, pathogenesis and normal cell physiology.
The microRNA pathway participates in basic cellular processes and its discovery has enabled the development of si/shRNAs as powerful investigational tools and potential therapeutics. Based on a simple kinetic model of the mRNA life cycle, we hypothesized that mRNAs with high turnover rates may be more resistant to RNAi-mediated silencing. The results of a simple reporter experiment strongly supported this hypothesis. We followed this with a genome-wide scale analysis of a rich corpus of experiments, including RT–qPCR validation data for thousands of siRNAs, siRNA/microRNA overexpression data and mRNA stability data. We find that short-lived transcripts are less affected by microRNA overexpression, suggesting that microRNA target prediction would be improved if mRNA turnover rates were considered. Similarly, short-lived transcripts are more difficult to silence using siRNAs, and our results may explain why certain transcripts are inherently recalcitrant to perturbation by small RNAs.
doi:10.1038/msb.2010.89
PMCID: PMC3010119  PMID: 21081925
microRNA; mRNA decay; RNAi; siRNA
4.  A dynamic model of proteome changes reveals new roles for transcript alteration in yeast 
By characterizing dynamic changes in yeast protein abundance following osmotic shock, this study shows that the correlation between protein and mRNA differs for transcripts that increase versus decrease in abundance, and reveals physiological reasons for these differences.
The correlation between protein and mRNA change is very high at transcripts that increase in abundance, but negligible at reduced transcripts following NaCl shock.Modeling and experimental data suggest that reducing levels of high-abundance transcripts helps to direct translational machinery to newly made transcripts.The transient burst of transcript increase serves to accelerate changes in protein abundance.Post-transcriptional regulation of protein abundance is pervasive, although most of the variance in protein change is explained by changes in mRNA abundance.
Natural microenvironments change rapidly, and living creatures must respond quickly and efficiently to thrive within this flux. At all cellular levels—signaling, transcription, translation, metabolism, cell growth, and division—the response is dynamic and coordinated. Some aspects of this response, such as dynamic changes of the transcriptome, are well understood. But other aspects, like the response of the proteome, have remained obscured primarily because of previous limitations in technology. Without coordinated time-course data, it has remained impossible to correctly characterize the correlations and dependencies between these two essential levels of cell biology.
This work presents an extended picture of the coordinated response of the transcriptome and proteome as cells respond to an abrupt environmental change. To assay proteomic dynamics, we developed a strategy for large-scale, multiplexed quantitation using isobaric tags and high mass accuracy mass spectrometry. This sensitive yet efficient platform allows for the expedient collection of quantitative time-course proteomic data at six time points, sufficiently reproducible to permit meaningful interpretation of variation across biological replicates. Time-course transcriptome data were generated from paired biological samples, allowing us to examine the relationships between changes in mRNA and protein for each gene in terms of direction and intensity, as well as the characteristics of the temporal profiles for each gene.
It was immediately obvious that a single measure of correlation across the entire data set was a meaningless metric. We therefore analyzed relationships between mRNA and protein for different subsets of data. In response to osmotic shock, hundreds of transcripts are highly induced, and their temporal pattern reveals a transient peak of maximal induction, which resolves into a new elevated level as cells acclimate (Figure 2). For this group of genes, there is extremely high correlation between peak mRNA change and protein change (R2∼0.8). But the dynamics of the molecules differ: while mRNA levels transiently overshoot their final levels, proteins gradually rise in abundance toward their new, elevated state. We observed, however, that a measure of efficiency connects the two profiles. The time it takes for a protein to acclimate to its new state correlates with the magnitude of the excess mRNA induction. Thus, the cell imparts an urgency to protein induction by transiently producing excess transcript.
The most surprising result, however, involves transcripts that decrease in abundance. In response to osmotic shock, the cell transiently reduces over 600 transcripts, many of which are among the most highly expressed in unstressed cells. But protein levels for these genes remain, for the most part, almost completely unchanged. The stark absence of protein repression is independent of basal protein abundance, independent of reported protein half-lives, reproducible across biological replicates, and validated by quantitative western blots. Furthermore, since we do detect a handful of proteins whose abundance is significantly reduced, our technology is capable of identifying protein loss. Thus, we conclude that transcript reduction serves another purpose besides reducing protein levels.
To explore alternate interpretations of the consequence of transcriptional repression, we devised a mass-action kinetic model, which describes protein changes based on mRNA dynamics in the context of transient changes in the rates of cell division. The model successfully recapitulated the observed data, allowing us to alter modeling parameters to test various hypotheses.
In response to osmotic shock, overall rates of translation temporarily decrease and cell growth transiently arrests before resuming at a slower rate. We reasoned that mRNA reduction might lower the rate of new protein synthesis, but that retarded production is balanced by reduced cell division. We explored both aspects of this logic with our model.
As expected, removing cell division from our model led to a calculated decrease of protein levels, indicating that reduced growth is necessary for maintaining protein levels. However, when we computationally held mRNA levels stable and calculated protein levels in the absence of mRNA repression, we did not find the expected increase in protein abundance.
We then considered the possibility that one function of the regulated repression of these highly abundant transcripts was to liberate proteins essential for translation, such as ribosomes or translation initiation factors. To explore this, we examined a mutant lacking the Dot6p/Tod6p transcriptional repressors, which fails to properly repress ∼250 genes in response to osmotic shock. In the wild type, the mRNA for a Dot6p/Tod6p target (ARX1) decreased seven-fold, and the remaining transcript was generally unassociated with poly-ribosomes. In the mutant, however, the mRNA levels were reduced only two-fold, while the remaining transcript continued to bind ribosomes. Therefore, failure to reduce transcript levels led to a persistent association with poly-ribosomes, thereby consuming translational machinery.
Our hypothesis is, therefore, that widespread changes in the transcriptome promote efficient translation of new proteins. Transcript increase serves to increase abundance of the encoded proteins, while reduction of some of the most abundant and highly translated mRNAs supports this project by liberating translational capacity. While it is not clear what factors are the limiting elements, it is clear that a full picture of cellular biology requires exploring the dynamics of the cellular response.
The transcriptome and proteome change dynamically as cells respond to environmental stress; however, prior proteomic studies reported poor correlation between mRNA and protein, rendering their relationships unclear. To address this, we combined high mass accuracy mass spectrometry with isobaric tagging to quantify dynamic changes in ∼2500 Saccharomyces cerevisiae proteins, in biological triplicate and with paired mRNA samples, as cells acclimated to high osmolarity. Surprisingly, while transcript induction correlated extremely well with protein increase, transcript reduction produced little to no change in the corresponding proteins. We constructed a mathematical model of dynamic protein changes and propose that the lack of protein reduction is explained by cell-division arrest, while transcript reduction supports redistribution of translational machinery. Furthermore, the transient ‘burst' of mRNA induction after stress serves to accelerate change in the corresponding protein levels. We identified several classes of post-transcriptional regulation, but show that most of the variance in protein changes is explained by mRNA. Our results present a picture of the coordinated physiological responses at the levels of mRNA, protein, protein-synthetic capacity, and cellular growth.
doi:10.1038/msb.2011.48
PMCID: PMC3159980  PMID: 21772262
dynamics; modeling; proteomics; stress; transcriptomics
5.  Quantification of mRNA and protein and integration with protein turnover in a bacterium 
Determination of the average cellular copy number of 400 proteins under different growth conditions and integration with protein turnover and absolute mRNA levels reveals the dynamics of protein expression in the genome-reduced bacterium Mycoplasma pneumoniae.
Our study provides a fine-grained, quantitative picture to unprecedented detail in an established model organism for systems-wide studies.Our integrative approach reveals a novel, dynamic view on the processes, interactions and regulations underlying the central dogma pathway and the composition of protein complexes.Simulations using our quantitative data on mRNA, protein and turnover show how an organism copes with stochastic noise in gene expression in vivo.Our data serve as an important resource for colleagues both within our field of research and in related disciplines.
A hallmark of Systems Biology is the integration of diverse, large quantitative data sets with the aim to gain novel insights into how biological processes work. We measured individual mRNA and protein abundances as well as protein turnover in the bacterium Mycoplasma pneumoniae. This human pathogen is an ideal model organism for organism-wide studies. It can be readily cultured under laboratory conditions and it has a very small genome with only 690 protein-coding genes. This comparably low complexity allows for the exhaustive analysis of major cellular biomolecules avoiding constrains introduced by limitations of available analysis techniques.
Using a recently developed mass spectrometry-based approach, we determined the average cellular copy number for over 400 individual proteins under different growth and stress conditions. The 20 most abundant proteins, including Elongation factor Tu, cellular chaperones, and proteins involved in metabolizing glucose, the major energy source of M. pneumoniae account for nearly 44% of the total cellular protein mass. We observed abundance changes of many expected and several unexpected proteins in response to cellular stress, such as heat shock, DNA damage and osmotic stress, as well as along batch culture growth over 4 days.
Integration of the protein abundance data with quantitative mRNA measurements revealed a modest correlation between these two classes of biomolecules. However, for several classical stress-induced proteins, we observed a correlated induction of mRNA and protein in response to heat shock. A focused analysis of mRNA–protein abundance dynamics during batch culture growth suggested that the regulation of gene expression is largely decoupled from protein dynamics in M. pneumoniae, indicating extensive post-transcriptional and post-translational regulation influencing the cellular mRNA–protein ratios.
To investigate the factors influencing the cellular protein abundance, we measured individual protein turnover rates by mass spectrometry using a label-chase approach involving stable isotope-labelled amino acids. The average half-life of a protein in M. pneumoniae is 23 h. Based on the measured quantitative mRNA data, the protein abundances and their half-lives, we established an ordinary differential equations model for the estimation of individual in vivo protein degradation and translation efficiency rates. We found out that translation efficiency rather than protein turnover is the dominating factor influencing protein abundance. Using our abundance and turnover data, we additionally performed stochastic simulations of gene expression. We observed that long protein half-life and low translational efficiency buffers gene expression noise propagating from low cellular mRNA levels in vivo.
We compared the abundance ratios of proteins associating into complexes in vivo with their expected functional stoichiometries. We observed that for stable protein complexes, such as the GroEL/ES chaperonin or DNA gyrase, our measured abundance ratios reflected the expected subunit stoichiometries. More dynamic protein complexes, such as the DnaK/J/GrpE chaperone system or RNA polymerase, showed several unusual subunit ratios, pointing towards transient interaction of sub-stoichiometric subunits for function. A detailed, quantitative analysis of the ribosome, the largest cellular protein complex, revealed large abundance differences of the 51 subunits. This observation indicates a multi-functionality for several, abundant ribosomal proteins.
Finally, a comparison of the determined average cellular protein abundances with a different pathogenic bacterium, Leptospira interrogans, revealed that cellular protein abundances closely reflect their respective lifestyles.
Our study represents an organism-wide, quantitative analysis of cellular protein abundances. Integrating our proteomics data with determined mRNA levels and protein turnover rates reveals insights into the dynamic interplay and regulation of mRNA and proteins, the central biomolecules of a cell.
Biological function and cellular responses to environmental perturbations are regulated by a complex interplay of DNA, RNA, proteins and metabolites inside cells. To understand these central processes in living systems at the molecular level, we integrated experimentally determined abundance data for mRNA, proteins, as well as individual protein half-lives from the genome-reduced bacterium Mycoplasma pneumoniae. We provide a fine-grained, quantitative analysis of basic intracellular processes under various external conditions. Proteome composition changes in response to cellular perturbations reveal specific stress response strategies. The regulation of gene expression is largely decoupled from protein dynamics and translation efficiency has a higher regulatory impact on protein abundance than protein turnover. Stochastic simulations using in vivo data show how low translation efficiency and long protein half-lives effectively reduce biological noise in gene expression. Protein abundances are regulated in functional units, such as complexes or pathways, and reflect cellular lifestyles. Our study provides a detailed integrative analysis of average cellular protein abundances and the dynamic interplay of mRNA and proteins, the central biomolecules of a cell.
doi:10.1038/msb.2011.38
PMCID: PMC3159969  PMID: 21772259
mRNA–protein; Mycoplasma pneumoniae; protein homeostasis; protein turnover; quantitative proteomics
6.  Teasing Apart Translational and Transcriptional Components of Stochastic Variations in Eukaryotic Gene Expression 
PLoS Computational Biology  2012;8(8):e1002644.
The intrinsic stochasticity of gene expression leads to cell-to-cell variations, noise, in protein abundance. Several processes, including transcription, translation, and degradation of mRNA and proteins, can contribute to these variations. Recent single cell analyses of gene expression in yeast have uncovered a general trend where expression noise scales with protein abundance. This trend is consistent with a stochastic model of gene expression where mRNA copy number follows the random birth and death process. However, some deviations from this basic trend have also been observed, prompting questions about the contribution of gene-specific features to such deviations. For example, recent studies have pointed to the TATA box as a sequence feature that can influence expression noise by facilitating expression bursts. Transcription-originated noise can be potentially further amplified in translation. Therefore, we asked the question of to what extent sequence features known or postulated to accompany translation efficiency can also be associated with increase in noise strength and, on average, how such increase compares to the amplification associated with the TATA box. Untangling different components of expression noise is highly nontrivial, as they may be gene or gene-module specific. In particular, focusing on codon usage as one of the sequence features associated with efficient translation, we found that ribosomal genes display a different relationship between expression noise and codon usage as compared to other genes. Within nonribosomal genes we found that sequence high codon usage is correlated with increased noise relative to the average noise of proteins with the same abundance. Interestingly, by projecting the data on a theoretical model of gene expression, we found that the amplification of noise strength associated with codon usage is comparable to that of the TATA box, suggesting that the effect of translation on noise in eukaryotic gene expression might be more prominent than previously appreciated.
Author Summary
The stochastic nature of gene expression leads to cell-to-cell differences in protein level referred to as noise. Expression noise can be disadvantageous, by affecting the precision of biological functions, but it may also be advantageous by enabling heterogeneous stress-response programs to environmental changes. Therefore various genes and gene groups might display various levels of expression noise. Importantly, gene expression is a multi-step process and the stochasticity of its individual steps, including transcription and translation, contributes to the resulting variability. Recent single cell analyses of gene expression in yeast have confirmed the theoretically predicted general trend where expression noise scales with protein abundance. However, some deviations from this basic trend have also been observed, prompting questions about the contribution of gene-specific features to such deviations. Accounting for noise heterogeneity in different gene groups, we revealed a clear relationship between noise and translation-related genomic features, specifically codon usage and 5′ UTR secondary structure. Our results suggest that the effect of translation on these deviations might be more prominent than previously appreciated, and provide important clues towards understanding expression stochasticity in yeast.
doi:10.1371/journal.pcbi.1002644
PMCID: PMC3431295  PMID: 22956896
7.  A model of yeast cell-cycle regulation based on multisite phosphorylation 
Multisite phosphorylation of CDK target proteins provides the requisite nonlinearity for cell cycle modeling using elementary reaction mechanisms.Stochastic simulations, based on Gillespie's algorithm and using realistic numbers of protein and mRNA molecules, compare favorably with single-cell measurements in budding yeast.The role of transcription–translation coupling is critical in the robust operation of protein regulatory networks in yeast cells.
Progression through the eukaryotic cell cycle is governed by the activation and inactivation of a family of cyclin-dependent kinases (CDKs) and auxiliary proteins that regulate CDK activities (Morgan, 2007). The many components of this protein regulatory network are interconnected by positive and negative feedback loops that create bistable switches and transient pulses (Tyson and Novak, 2008). The network must ensure that cell-cycle events proceed in the correct order, that cell division is balanced with respect to cell growth, and that any problems encountered (in replicating the genome or partitioning chromosomes to daughter cells) are corrected before the cell proceeds to the next phase of the cycle. The network must operate robustly in the context of unavoidable molecular fluctuations in a yeast-sized cell. With a volume of only 5×10−14 l, a yeast cell contains one copy of the gene for each component of the network, a handful of mRNA transcripts of each gene, and a few hundreds to thousands of protein molecules carrying out each gene's function. How large are the molecular fluctuations implied by these numbers, and what effects do they have on the functioning of the cell-cycle control system?
To answer these questions, we have built a new model (Figure 1) of the CDK regulatory network in budding yeast, based on the fact that the targets of CDK activity are typically phosphorylated on multiple sites. The activity of each target protein depends on how many sites are phosphorylated. The target proteins feedback on CDK activity by controlling cyclin synthesis (SBF's role) and degradation (Cdh1's role) and by releasing a CDK-counteracting phosphatase (Cdc14). Every reaction in Figure 1 can be described by a mass-action rate law, with an accompanying rate constant that must be estimated from experimental data. As the transcription and translation of mRNA molecules have major effects on fluctuating numbers of protein molecules (Pedraza and Paulsson, 2008), we have included mRNA transcripts for each protein in the model.
To create a deterministic model, the rate laws are combined, according to standard principles of chemical kinetics, into a set of 60 differential equations that govern the temporal dynamics of the control system. In the stochastic version of the model, the rate law for each reaction determines the probability per unit time that a particular reaction occurs, and we use Gillespie's stochastic simulation algorithm (Gillespie, 1976) to compute possible temporal sequences of reaction events. Accurate stochastic simulations require knowledge of the expected numbers of mRNA and protein molecules in a single yeast cell. Fortunately, these numbers are available from several sources (Ghaemmaghami et al, 2003; Zenklusen et al, 2008). Although the experimental estimates are not always in good agreement with each other, they are sufficiently reliable to populate a stochastic model with realistic numbers of molecules.
By simulating thousands of cells (as in Figure 5), we can build up representative samples for computing the mean and s.d. of any measurable cell-cycle property (e.g. interdivision time, size at division, duration of G1 phase). The excellent fit of simulated statistics to observations of cell-cycle variability is documented in the main text and Supplementary Information.
Of particular interest to us are observations of Di Talia et al (2007) of the timing of a crucial G1 event (export of Whi5 protein from the nucleus) in a population of budding yeast cells growing at a specific growth rate α=ln2/(mass-doubling time). Whi5 export is a consequence of Whi5 phosphorylation, and it occurs simultaneously with the release (activation) of SBF (see Figure 1). Using fluorescently labeled Whi5, Di Talia et al could easily measure (in individual yeast cells) the time, T1, from cell birth to the abrupt loss of Whi5 from the nucleus. Correlating T1 to the size of the cell at birth, Vbirth, they found that, for a sample of daughter cells, αT1 versus ln(Vbirth) could be fit with two straight lines of slope −0.7 and −0.3. Our simulation of this experiment (Figure 7 of the main text) compares favorably with Figure 3d and e in Di Talia et al (2007).
The major sources of noise in our model (and in protein regulatory networks in yeast cells, in general) are related to gene transcription and the small number of unique mRNA transcripts. As each mRNA molecule may instruct the synthesis of dozens of protein molecules, the coefficient of variation of molecular fluctuations at the protein level (CVP) may be dominated by fluctuations at the mRNA level, as expressed in the formula (Pedraza and Paulsson, 2008) where NM, NP denote the number of mRNA and protein molecules, respectively, and ρ=τM/τP is the ratio of half-lives of mRNA and protein molecules. For a yeast cell, typical values of NM and NP are 8 and 800, respectively (Ghaemmaghami et al, 2003; Zenklusen et al, 2008). If ρ=1, then CVP≈25%. Such large fluctuations in protein levels are inconsistent with the observed variability of size and age at division in yeast cells, as shown in the simplified cell-cycle model of Kar et al (2009) and as we have confirmed with our more realistic model. The size of these fluctuations can be reduced to a more acceptable level by assuming a shorter half-life for mRNA (say, ρ=0.1).
There must be some mechanisms whereby yeast cells lessen the protein fluctuations implied by transcription–translation coupling. Following Pedraza and Paulsson (2008), we suggest that mRNA gestation and senescence may resolve this problem. Equation (3) is based on a simple, one-stage, birth–death model of mRNA turnover. In Supplementary Appendix 1, we show that a model of mRNA processing, with 10 stages each of mRNA gestation and senescence, gives reasonable fluctuations at the protein level (CVP≈5%), even if the effective half-life of mRNA is 10 min. A one-stage model with τM=1 min gives comparable fluctuations (CVP≈5%). In the main text, we use a simple birth–death model of mRNA turnover with an ‘effective' half-life of 1 min, in order to limit the computational complexity of the full cell-cycle model.
In order for the cell's genome to be passed intact from one generation to the next, the events of the cell cycle (DNA replication, mitosis, cell division) must be executed in the correct order, despite the considerable molecular noise inherent in any protein-based regulatory system residing in the small confines of a eukaryotic cell. To assess the effects of molecular fluctuations on cell-cycle progression in budding yeast cells, we have constructed a new model of the regulation of Cln- and Clb-dependent kinases, based on multisite phosphorylation of their target proteins and on positive and negative feedback loops involving the kinases themselves. To account for the significant role of noise in the transcription and translation steps of gene expression, the model includes mRNAs as well as proteins. The model equations are simulated deterministically and stochastically to reveal the bistable switching behavior on which proper cell-cycle progression depends and to show that this behavior is robust to the level of molecular noise expected in yeast-sized cells (∼50 fL volume). The model gives a quantitatively accurate account of the variability observed in the G1-S transition in budding yeast, which is governed by an underlying sizer+timer control system.
doi:10.1038/msb.2010.55
PMCID: PMC2947364  PMID: 20739927
bistability; cell-cycle variability; size control; stochastic model; transcription–translation coupling
8.  A Novel Tumor-Promoting Function Residing in the 5′ Non-coding Region of vascular endothelial growth factor mRNA 
PLoS Medicine  2008;5(5):e94.
Background
Vascular endothelial growth factor-A (VEGF) is one of the key regulators of tumor development, hence it is considered to be an important therapeutic target for cancer treatment. However, clinical trials have suggested that anti-VEGF monotherapy was less effective than standard chemotherapy. On the basis of the evidence, we hypothesized that vegf mRNA may have unrecognized function(s) in cancer cells.
Methods and Findings
Knockdown of VEGF with vegf-targeting small-interfering (si) RNAs increased susceptibility of human colon cancer cell line (HCT116) to apoptosis caused with 5-fluorouracil, etoposide, or doxorubicin. Recombinant human VEGF165 did not completely inhibit this apoptosis. Conversely, overexpression of VEGF165 increased resistance to anti-cancer drug-induced apoptosis, while an anti-VEGF165-neutralizing antibody did not completely block the resistance. We prepared plasmids encoding full-length vegf mRNA with mutation of signal sequence, vegf mRNAs lacking untranslated regions (UTRs), or mutated 5′UTRs. Using these plasmids, we revealed that the 5′UTR of vegf mRNA possessed anti-apoptotic activity. The 5′UTR-mediated activity was not affected by a protein synthesis inhibitor, cycloheximide. We established HCT116 clones stably expressing either the vegf 5′UTR or the mutated 5′UTR. The clones expressing the 5′UTR, but not the mutated one, showed increased anchorage-independent growth in vitro and formed progressive tumors when implanted in athymic nude mice. Microarray and quantitative real-time PCR analyses indicated that the vegf 5′UTR-expressing tumors had up-regulated anti-apoptotic genes, multidrug-resistant genes, and growth-promoting genes, while pro-apoptotic genes were down-regulated. Notably, expression of signal transducers and activators of transcription 1 (STAT1) was markedly repressed in the 5′UTR-expressing tumors, resulting in down-regulation of a STAT1-responsive cluster of genes (43 genes). As a result, the tumors did not respond to interferon (IFN)α therapy at all. We showed that stable silencing of endogenous vegf mRNA in HCT116 cells enhanced both STAT1 expression and IFNα responses.
Conclusions
These findings suggest that cancer cells have a survival system that is regulated by vegf mRNA and imply that both vegf mRNA and its protein may synergistically promote the malignancy of tumor cells. Therefore, combination of anti-vegf transcript strategies, such as siRNA-based gene silencing, with anti-VEGF antibody treatment may improve anti-cancer therapies that target VEGF.
Shigetada Teshima-Kondo and colleagues find that cancer cells have a survival system that is regulated by vegf mRNA and that vegf mRNA and its protein may synergistically promote the malignancy of tumor cells.
Editors' Summary
Background
Normally, throughout life, cell division (which produces new cells) and cell death are carefully balanced to keep the body in good working order. But sometimes cells acquire changes (mutations) in their genetic material that allow them to divide uncontrollably to form cancers—disorganized masses of cells. When a cancer is small, it uses the body's existing blood supply to get the oxygen and nutrients it needs for its growth and survival. But, when it gets bigger, it has to develop its own blood supply. This process is called angiogenesis. It involves the release by the cancer cells of proteins called growth factors that bind to other proteins (receptors) on the surface of endothelial cells (the cells lining blood vessels). The receptors then send signals into the endothelial cells that tell them to make new blood vessels. One important angiogenic growth factor is “vascular endothelial growth factor” (VEGF). Tumors that make large amounts of VEGF tend to be more abnormal and more aggressive than those that make less VEGF. In addition, high levels of VEGF in the blood are often associated with poor responses to chemotherapy, drug regimens designed to kill cancer cells.
Why Was This Study Done?
Because VEGF is a key regulator of tumor development, several anti-VEGF therapies—drugs that target VEGF and its receptors—have been developed. These therapies strongly suppress the growth of tumor cells in the laboratory and in animals but, when used alone, are no better at increasing the survival times of patients with cancer than standard chemotherapy. Scientists are now looking for an explanation for this disappointing result. Like all proteins, cells make VEGF by “transcribing” its DNA blueprint into an mRNA copy (vegf mRNA), the coding region of which is “translated” into the VEGF protein. Other, “noncoding” regions of vegf mRNA control when and where VEGF is made. Scientists have recently discovered that the noncoding regions of some mRNAs suppress tumor development. In this study, therefore, the researchers investigate whether vegf mRNA has an unrecognized function in tumor cells that could explain the disappointing clinical results of anti-VEGF therapeutics.
What Did the Researchers Do and Find?
The researchers first used a technique called small interfering (si) RNA knockdown to stop VEGF expression in human colon cancer cells growing in dishes. siRNAs are short RNAs that bind to and destroy specific mRNAs in cells, thereby preventing the translation of those mRNAs into proteins. The treatment of human colon cancer cells with vegf-targeting siRNAs made the cells more sensitive to chemotherapy-induced apoptosis (a type of cell death). This sensitivity was only partly reversed by adding VEGF to the cells. By contrast, cancer cells engineered to make more vegf mRNA had increased resistance to chemotherapy-induced apoptosis. Treatment of these cells with an antibody that inhibited VEGF function did not completely block this resistance. Together, these results suggest that both vegf mRNA and VEGF protein have anti-apoptotic effects. The researchers show that the anti-apoptotic activity of vegf mRNA requires a noncoding part of the mRNA called the 5′ UTR, and that whereas human colon cancer cells expressing this 5′ UTR form tumors in mice, cells expressing a mutated 5′ UTR do not. Finally, they report that the expression of several pro-apoptotic genes and of an anti-tumor pathway known as the interferon/STAT1 tumor suppression pathway is down-regulated in tumors that express the vegf 5′ UTR.
What Do These Findings Mean?
These findings suggest that some cancer cells have a survival system that is regulated by vegf mRNA and are the first to show that a 5′UTR of mRNA can promote tumor growth. They indicate that VEGF and its mRNA work together to promote their development and to increase their resistance to chemotherapy drugs. They suggest that combining therapies that prevent the production of vegf mRNA (for example, siRNA-based gene silencing) with therapies that block the function of VEGF might improve survival times for patients whose tumors overexpress VEGF.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050094.
This study is discussed further in a PLoS Medicine Perspective by Hughes and Jones
The US National Cancer Institute provides information about all aspects of cancer, including information on angiogenesis, and on bevacizumab, an anti-VEGF therapeutic (in English and Spanish)
CancerQuest, from Emory University, provides information on all aspects of cancer, including angiogenesis (in several languages)
Cancer Research UK also provides basic information about what causes cancers and how they develop, grow, and spread, including information about angiogenesis
Wikipedia has pages on VEGF and on siRNA (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.0050094
PMCID: PMC2386836  PMID: 18494554
9.  Extensive Translatome Remodeling during ER Stress Response in Mammalian Cells 
PLoS ONE  2012;7(5):e35915.
In this work we have described the translatome of two mammalian cell lines, NIH3T3 and Jurkat, by scoring the relative polysome association of ∼10,000 mRNA under normal and ER stress conditions. We have found that translation efficiencies of mRNA correlated poorly with transcript abundance, although a general tendency was observed so that the highest translation efficiencies were found in abundant mRNA. Despite the differences found between mouse (NIH3T3) and human (Jurkat) cells, both cell types share a common translatome composed by ∼800–900 mRNA that encode proteins involved in basic cellular functions. Upon stress, an extensive remodeling in translatomes was observed so that translation of ∼50% of mRNA was inhibited in both cell types, this effect being more dramatic for those mRNA that accounted for most of the cell translation. Interestingly, we found two subsets comprising 1000–1500 mRNA whose translation resisted or was induced by stress. Translation arrest resistant class includes many mRNA encoding aminoacyl tRNA synthetases, ATPases and enzymes involved in DNA replication and stress response such as BiP. This class of mRNA is characterized by high translation rates in both control and stress conditions. Translation inducible class includes mRNA whose translation was relieved after stress, showing a high enrichment in early response transcription factors of bZIP and zinc finger C2H2 classes. Unlike yeast, a general coordination between changes in translation and transcription upon stress (potentiation) was not observed in mammalian cells. Among the different features of mRNA analyzed, we found a relevant association of translation efficiency with the presence of upstream ATG in the 5′UTR and with the length of coding sequence of mRNA, and a looser association with other parameters such as the length and the G+C content of 5′UTR. A model for translatome remodeling during the acute phase of stress response in mammalian cells is proposed.
doi:10.1371/journal.pone.0035915
PMCID: PMC3344847  PMID: 22574127
10.  Characterization of the 5′-untranslated region of YB-1 mRNA and autoregulation of translation by YB-1 protein 
Nucleic Acids Research  2004;32(2):611-622.
The eukaryotic Y-box binding protein YB-1 is involved in various biological processes, including DNA repair, cell proliferation and the regulation of transcription and translation. YB-1 protein is abundant and expressed ubiquitously in human cells, functioning in cell proliferation and transformation. Its concentration is thought to be highly regulated at both the levels of transcription and translation. Therefore, we investigated whether or not the 5′-UTR of YB-1 mRNA affects the translation of YB-1 protein, thus influencing expression levels. Luciferase mRNA ligated to the YB-1 mRNA 5′-UTR was used as a reporter construct. Ligation of the full-length YB-1 5′-UTR (331 bases) enhanced translation as assessed by in vitro and in vivo translation assays. Deletion constructs of the YB-1 5′-UTR also resulted in a higher efficiency of translation, especially in the region mapped to +197 to +331 from the major transcription start site. RNA gel shift assays revealed that the affinity of YB-1 for various 5′-UTR probe sequences was higher for the full-length 5′-UTR than for deleted 5′-UTR sequences. An in vitro translation assay was used to demonstrate that recombinant YB-1 protein inhibited translation of the full-length 5′-UTR of YB-1 mRNA. Thus, our findings provide evidence for the autoregulation of YB-1 mRNA translation via the 5′-UTR.
doi:10.1093/nar/gkh223
PMCID: PMC373347  PMID: 14752049
11.  Cell-to-cell variability of alternative RNA splicing 
The role of mRNA processing in gene expression variability is poorly characterized. This study investigates the extent of cell-to-cell variability of alternative RNA splicing in mammalian cells using single-molecule imaging of CAPRIN1 and MKNK2 splice isoforms.
We applied a single-molecule imaging approach to visualize the alternatively spliced isoforms of two genes, CAPRIN1 and MKNK2, in human cells.We found that cell-to-cell variability in isoform ratios is close to the minimum possible in the absence of feedback in clonal Rpe1 cells, a diploid non-transformed cell line. In contrast, clonal HeLa cells displayed much larger isoform ratio variability between cells.Experimental and theoretical analysis suggests that variability in the regulatory splicing machinery contributes to this difference between cell lines.
Biological gene expression is a complex process which includes transcription, mRNA processing, and translation. As gene expression is a fundamental aspect of biological behavior, a central question within the fields of molecular and cellular biology is how effectively cells control the abundance of their gene expression products, mRNA and protein.
Previous experimental and theoretical studies have shown that there can be substantial cell-to-cell variation in gene expression, even between genetically identical cells grown in uniform conditions. This variation was shown to be important in a variety of biological contexts such as development, virology, immune system function, and cancer treatment. One major source of variability was shown to be transcriptional bursting, or the process in which genes are expressed sporadically separated by long durations of inexpression. Additionally, since the biochemical reactions that govern gene expression are often mediated by molecular species that are present in low numbers, variability can arise from stochastic effects owing to the random chance that an individual biochemical reaction will occur.
The role of mRNA processing in gene expression variability has not been examined thoroughly, particularly with respect to alternative splicing. Alternative RNA splicing is a form of mRNA processing which leads to the synthesis of multiple different mRNAs from a single gene. In this process, the nascent mRNA (pre-mRNA) of a gene contains sequences known as introns that can be excised in different combinations to generate multiple gene products, known as isoforms. As alternative splicing occurs in the vast majority of human genes, it presents a potentially major source of cell-to-cell variability in gene expression.
In this study, we sought to characterize the extent of cell-to-cell variability that arises from alternative RNA splicing. To do so, we utilized a single-molecule imaging approach based on fluorescent in situ hybridization to study the cell-to-cell variability in isoform ratios of two genes, CAPRIN1 and MKNK2, which each contain two splice isoforms (Figure 2 from the manuscript). Using a clonally derived, diploid, non-transformed cell line (Rpe1 cells—retinal pigment epithelial cells), we found that variability is remarkably close to the minimum possible given the probabilistic chance of individual splicing events. In contrast, we found that isoform ratio variability was substantially larger in clonally derived HeLa cells, a cancerous cell line with an unstable karyotype. To explain the differences between the two cell lines, we further examined the potential origins of isoform ratio variability. We first studied several known sources of mRNA variability, such as transcriptional bursting, but found that they did not contribute significantly to the difference between cell lines. However, when we examined the role of splicing factors in controlling cell-to-cell variability, we found that lesser control over the regulation of alternative splicing is likely to be the primary source of this difference.
Cell-to-cell variability in gene expression owing to alternative splicing is an inevitable feature of biology. Since spliced isoforms can have different and even opposing cellular functions, it would be interesting to see if such variability can have phenotypic consequences in various biological settings. We anticipate that future work will shed light on the extent of cell-to-cell variability of alternative splicing for additional genes, and may identify splicing events where heterogeneity has an important functional role.
Heterogeneity in the expression levels of mammalian genes is large even in clonal populations and has phenotypic consequences. Alternative splicing is a fundamental aspect of gene expression, yet its contribution to heterogeneity is unknown. Here, we use single-molecule imaging to characterize the cell-to-cell variability in mRNA isoform ratios for two endogenous genes, CAPRIN1 and MKNK2. We show that isoform variability in non-transformed, diploid cells is remarkably close to the minimum possible given the stochastic nature of individual splicing events, while variability in HeLa cells is considerably higher. Analysis of the potential sources of isoform ratio heterogeneity indicates that a difference in the control over splicing factor activity is one origin of this increase. Our imaging approach also visualizes non-alternatively spliced mRNA and active transcription sites, and yields spatial information regarding the relationship between splicing and transcription. Together, our work demonstrates that mammalian cells minimize fluctuations in mRNA isoform ratios by tightly regulating the splicing machinery.
doi:10.1038/msb.2011.32
PMCID: PMC3159976  PMID: 21734645
alternative splicing; cell-to-cell variability; co-transcriptional splicing; gene expression
12.  Cell-type specific analysis of translating RNAs in developing flowers reveals new levels of control 
Combining translating ribosome affinity purification with RNA-seq for cell-specific profiling of translating RNAs in developing flowers.Cell type comparisons of cell type-specific hormone responses, promoter motifs, coexpressed cognate binding factor candidates, and splicing isoforms.Widespread post-transcriptional regulation at both the intron splicing and translational stages.A new class of noncoding RNAs associated with polysomes.
What constitutes a differentiated cell type? How much do cell types differ in their transcription of genes? The development and functions of tissues rely on constant interactions among distinct and nonequivalent cell types. Answering these questions will require quantitative information on transcriptomes, proteomes, protein–protein interactions, protein–nucleic acid interactions, and metabolomes at cellular resolution. The systems approaches emerging in biology promise to explain properties of biological systems based on genome-wide measurements of expression, interaction, regulation, and metabolism. To facilitate a systems approach, it is essential first to capture such components in a global manner, ideally at cellular resolution.
Recently, microarray analysis of transcriptomes has been extended to a cellular level of resolution by using laser microdissection or fluorescence-activated sorting (for review, see Nelson et al, 2008). These methods have been limited by stresses associated with cellular separation and isolation procedures, and biases associated with mandatory RNA amplification steps. A newly developed method, translating ribosome affinity purification (TRAP; Zanetti et al, 2005; Heiman et al, 2008; Mustroph et al, 2009), circumvents these problems by epitopetagging a ribosomal protein in specific cellular domains to selectively purify polysomes. We combined TRAP with deep sequencing, which we term TRAP-seq, to provide cell-level spatiotemporal maps for Arabidopsis early floral development at single-base resolution.
Flower development in Arabidopsis has been studied extensively and is one of the best understood aspects of plant development (for review, see Krizek and Fletcher, 2005). Genetic analysis of homeotic mutants established the ABC model, in which three classes of regulatory genes, A, B and C, work in a combinatorial manner to confer organ identities of four whorls (Coen and Meyerowitz, 1991). Each class of regulatory gene is expressed in a specific and evolutionarily conserved domain, and the action of the class A, B and C genes is necessary for specification of organ identity (Figure 1A).
Using TRAP-seq, we purified cell-specific translating mRNA populations, which we and others call the translatome, from the A, B and C domains of early developing flowers, in which floral patterning and the specification of floral organs is established. To achieve temporal specificity, we used a floral induction system to facilitate collection of early stage flowers (Wellmer et al, 2006). The combination of TRAP-seq with domain-specific promoters and this floral induction system enabled fine spatiotemporal isolation of translating mRNA in specific cellular domains, and at specific developmental stages.
Multiple lines of evidence confirmed the specificity of this approach, including detecting the expression in expected domains but not in other domains for well-studied flower marker genes and known physiological functions (Figures 1B–D and 2A–C). Furthermore, we provide numerous examples from flower development in which a spatiotemporal map of rigorously comparable cell-specific translatomes makes possible new views of the properties of cell domains not evident in data obtained from whole organs or tissues, including patterns of transcription and cis-regulation, new physiological differences among cell domains and between flower stages, putative hormone-active centers, and splicing events specific for flower domains (Figure 2A–D). Such findings may provide new targets for reverse genetics studies and may aid in the formulation and validation of interaction and pathway networks.
Beside cellular heterogeneity, the transcriptome is regulated at several steps through the life of mRNA molecules, which are not directly available through traditional transcriptome profiling of total mRNA abundance. By comparing the translatome and transcriptome, we integratively profiled two key posttranscriptional control points, intron splicing and translation state. From our translatome-wide profiling, we (i) confirmed that both posttranscriptional regulation control points were used by a large portion of the transcriptome; (ii) identified a number of cis-acting features within the coding or noncoding sequences that correlate with splicing or translation state; and (iii) revealed correlation between each regulation mechanism and gene function. Our transcriptome-wide surveys have highlighted target genes transcripts of which are probably under extensive posttranscriptional regulation during flower development.
Finally, we reported the finding of a large number of polysome-associated ncRNAs. About one-third of all annotated ncRNA in the Arabidopsis genome were observed co-purified with polysomes. Coding capacity analysis confirmed that most of them are real ncRNA without conserved ORFs. The group of polysome-associated ncRNA reported in this study is a potential new addition to the expanding riboregulator catalog; they could have roles in translational regulation during early flower development.
Determining both the expression levels of mRNA and the regulation of its translation is important in understanding specialized cell functions. In this study, we describe both the expression profiles of cells within spatiotemporal domains of the Arabidopsis thaliana flower and the post-transcriptional regulation of these mRNAs, at nucleotide resolution. We express a tagged ribosomal protein under the promoters of three master regulators of flower development. By precipitating tagged polysomes, we isolated cell type-specific mRNAs that are probably translating, and quantified those mRNAs through deep sequencing. Cell type comparisons identified known cell-specific transcripts and uncovered many new ones, from which we inferred cell type-specific hormone responses, promoter motifs and coexpressed cognate binding factor candidates, and splicing isoforms. By comparing translating mRNAs with steady-state overall transcripts, we found evidence for widespread post-transcriptional regulation at both the intron splicing and translational stages. Sequence analyses identified structural features associated with each step. Finally, we identified a new class of noncoding RNAs associated with polysomes. Findings from our profiling lead to new hypotheses in the understanding of flower development.
doi:10.1038/msb.2010.76
PMCID: PMC2990639  PMID: 20924354
Arabidopsis; flower; intron; transcriptome; translation
13.  An Abundance of Ubiquitously Expressed Genes Revealed by Tissue Transcriptome Sequence Data 
PLoS Computational Biology  2009;5(12):e1000598.
The parts of the genome transcribed by a cell or tissue reflect the biological processes and functions it carries out. We characterized the features of mammalian tissue transcriptomes at the gene level through analysis of RNA deep sequencing (RNA-Seq) data across human and mouse tissues and cell lines. We observed that roughly 8,000 protein-coding genes were ubiquitously expressed, contributing to around 75% of all mRNAs by message copy number in most tissues. These mRNAs encoded proteins that were often intracellular, and tended to be involved in metabolism, transcription, RNA processing or translation. In contrast, genes for secreted or plasma membrane proteins were generally expressed in only a subset of tissues. The distribution of expression levels was broad but fairly continuous: no support was found for the concept of distinct expression classes of genes. Expression estimates that included reads mapping to coding exons only correlated better with qRT-PCR data than estimates which also included 3′ untranslated regions (UTRs). Muscle and liver had the least complex transcriptomes, in that they expressed predominantly ubiquitous genes and a large fraction of the transcripts came from a few highly expressed genes, whereas brain, kidney and testis expressed more complex transcriptomes with the vast majority of genes expressed and relatively small contributions from the most expressed genes. mRNAs expressed in brain had unusually long 3′UTRs, and mean 3′UTR length was higher for genes involved in development, morphogenesis and signal transduction, suggesting added complexity of UTR-based regulation for these genes. Our results support a model in which variable exterior components feed into a large, densely connected core composed of ubiquitously expressed intracellular proteins.
Author Summary
A variety of genes are active within the nuclei of our cells. Some are needed for the day-to-day maintenance of cell functions, while others have roles that are more specific to certain tissues or particular cell types; for example, only the pancreas produces insulin. As a result, every tissue has its own profile of gene activity. Since active genes produce RNA, tissue differences in gene activity can be probed by characterizing the RNA they contain. Essentially the entire set of RNAs or ‘transcriptome’ has been sequenced from various tissues, and we used these data to compare the degree of specialization of different tissues and to investigate the set of ‘core’ genes active in every tissue. A central observation was that there are an abundance of such core genes, and that these genes account for the majority of the transcriptome in each tissue. These findings will aid in the understanding of what makes tissues, and cell types, different from each other and what each requires to function.
doi:10.1371/journal.pcbi.1000598
PMCID: PMC2781110  PMID: 20011106
14.  mRNA sequence features that contribute to translational regulation in Arabidopsis 
Nucleic Acids Research  2005;33(3):955-965.
DNA microarrays were used to evaluate the regulation of the proportion of individual mRNA species in polysomal complexes in leaves of Arabidopsis thaliana under control growth conditions and following a mild dehydration stress (DS). The analysis determined that the percentage of an individual gene transcript in polysomes (ribosome loading) ranged from over 95 to <5%. DS caused a decrease in ribosome loading from 82 to 72%, with maintained polysome association for over 60% of the mRNAs with an increased abundance. To identify sequence features responsible for translational regulation, ribosome loading values and features of full-length mRNA sequences were compared. mRNAs with extreme length or high GU content in the 5′-untranslated regions (5′-UTRs) were generally poorly translated. Under DS, mRNAs with both a high GC content in the 5′-UTR and long open reading frame showed a significant impairment in ribosome loading. Evaluation of initiation A+1UG codon context revealed distinctions in the frequency of adenine in nucleotides −10 to −1 (especially at −4 and −3) in mRNAs with different ribosome loading values. Notably, the mRNA features that contribute to translational regulation could not fully explain the variation in ribosome loading, indicating that additional factors contribute to translational regulation in Arabidopsis.
doi:10.1093/nar/gki240
PMCID: PMC549406  PMID: 15716313
15.  Folding Free Energies of 5′-UTRs Impact Post-Transcriptional Regulation on a Genomic Scale in Yeast 
PLoS Computational Biology  2005;1(7):e72.
Using high-throughput technologies, abundances and other features of genes and proteins have been measured on a genome-wide scale in Saccharomyces cerevisiae. In contrast, secondary structure in 5′–untranslated regions (UTRs) of mRNA has only been investigated for a limited number of genes. Here, the aim is to study genome-wide regulatory effects of mRNA 5′-UTR folding free energies. We performed computations of secondary structures in 5′-UTRs and their folding free energies for all verified genes in S. cerevisiae. We found significant correlations between folding free energies of 5′-UTRs and various transcript features measured in genome-wide studies of yeast. In particular, mRNAs with weakly folded 5′-UTRs have higher translation rates, higher abundances of the corresponding proteins, longer half-lives, and higher numbers of transcripts, and are upregulated after heat shock. Furthermore, 5′-UTRs have significantly higher folding free energies than other genomic regions and randomized sequences. We also found a positive correlation between transcript half-life and ribosome occupancy that is more pronounced for short-lived transcripts, which supports a picture of competition between translation and degradation. Among the genes with strongly folded 5′-UTRs, there is a huge overrepresentation of uncharacterized open reading frames. Based on our analysis, we conclude that (i) there is a widespread bias for 5′-UTRs to be weakly folded, (ii) folding free energies of 5′-UTRs are correlated with mRNA translation and turnover on a genomic scale, and (iii) transcripts with strongly folded 5′-UTRs are often rare and hard to find experimentally.
Synopsis
In cells, proteins are made from messenger RNA copied from genes in the DNA. The amount of each protein needs to be controlled by cells. For this purpose, cells use a strategy that includes decomposing RNA and varying the number of proteins made from each RNA. One part of the RNA molecule is called the 5′–untranslated region (UTR), and it is known that this region can fold into a three-dimensional structure. For some genes, such structures are important for protein production. In this article, structures in 5′-UTRs are calculated for all genes in the yeast Saccharomyces cerevisiae. The authors show that structures in 5′-UTRs likely play a role in RNA decomposition and protein production for many genes in the genome: RNA molecules with weakly folded 5′-UTRs live relatively longer and produce more proteins. This study provides an example of how genome-wide computational analysis complements experimental results.
doi:10.1371/journal.pcbi.0010072
PMCID: PMC1309706  PMID: 16355254
16.  Analysis and Prediction of Translation Rate Based on Sequence and Functional Features of the mRNA 
PLoS ONE  2011;6(1):e16036.
Protein concentrations depend not only on the mRNA level, but also on the translation rate and the degradation rate. Prediction of mRNA's translation rate would provide valuable information for in-depth understanding of the translation mechanism and dynamic proteome. In this study, we developed a new computational model to predict the translation rate, featured by (1) integrating various sequence-derived and functional features, (2) applying the maximum relevance & minimum redundancy method and incremental feature selection to select features to optimize the prediction model, and (3) being able to predict the translation rate of RNA into high or low translation rate category. The prediction accuracies under rich and starvation condition were 68.8% and 70.0%, respectively, evaluated by jackknife cross-validation. It was found that the following features were correlated with translation rate: codon usage frequency, some gene ontology enrichment scores, number of RNA binding proteins known to bind its mRNA product, coding sequence length, protein abundance and 5′UTR free energy. These findings might provide useful information for understanding the mechanisms of translation and dynamic proteome. Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale.
doi:10.1371/journal.pone.0016036
PMCID: PMC3017080  PMID: 21253596
17.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry 
The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput.
In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified (Schmidt et al, 2008) and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (Figure 1). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (Malmström et al, 2009). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome (Malmström et al, 2009).
To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (Figure 4). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria (Güell et al, 2009).
The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology.
Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
doi:10.1038/msb.2011.37
PMCID: PMC3159967  PMID: 21772258
absolute quantification; directed mass spectrometry; Leptospira interrogans; microbiology; proteomics
18.  Role of 3′UTRs in the Translation of mRNAs Regulated by Oncogenic eIF4E—A Computational Inference 
PLoS ONE  2009;4(3):e4868.
Eukaryotic cap-dependent mRNA translation is mediated by the initiation factor eIF4E, which binds mRNAs and stimulates efficient translation initiation. eIF4E is often overexpressed in human cancers. To elucidate the molecular signature of eIF4E target mRNAs, we analyzed sequence and structural properties of two independently derived polyribosome recruited mRNA datasets. These datasets originate from studies of mRNAs that are actively being translated in response to cells over-expressing eIF4E or cells with an activated oncogenic AKT: eIF4E signaling pathway, respectively. Comparison of eIF4E target mRNAs to mRNAs insensitive to eIF4E-regulation has revealed surprising features in mRNA secondary structure, length and microRNA-binding properties. Fold-changes (the relative change in recruitment of an mRNA to actively translating polyribosomal complexes in response to eIF4E overexpression or AKT upregulation) are positively correlated with mRNA G+C content and negatively correlated with total and 3′UTR length of the mRNAs. A machine learning approach for predicting the fold change was created. Interesting tendencies of secondary structure stability are found near the start codon and at the beginning of the 3′UTR region. Highly upregulated mRNAs show negative selection (site avoidance) for binding sites of several microRNAs. These results are consistent with the emerging model of regulation of mRNA translation through a dynamic balance between translation initiation at the 5′UTR and microRNA binding at the 3′UTR.
doi:10.1371/journal.pone.0004868
PMCID: PMC2654073  PMID: 19290046
19.  A Competition between Stimulators and Antagonists of Upf Complex Recruitment Governs Human Nonsense-Mediated mRNA Decay 
PLoS Biology  2008;6(4):e111.
The nonsense-mediated decay (NMD) pathway subjects mRNAs with premature termination codons (PTCs) to rapid decay. The conserved Upf1–3 complex interacts with the eukaryotic translation release factors, eRF3 and eRF1, and triggers NMD when translation termination takes place at a PTC. Contrasting models postulate central roles in PTC-recognition for the exon junction complex in mammals versus the cytoplasmic poly(A)-binding protein (PABP) in other eukaryotes. Here we present evidence for a unified model for NMD, in which PTC recognition in human cells is mediated by a competition between 3′ UTR–associated factors that stimulate or antagonize recruitment of the Upf complex to the terminating ribosome. We identify cytoplasmic PABP as a human NMD antagonizing factor, which inhibits the interaction between eRF3 and Upf1 in vitro and prevents NMD in cells when positioned in proximity to the termination codon. Surprisingly, only when an extended 3′ UTR places cytoplasmic PABP distally to the termination codon does a downstream exon junction complex enhance NMD, likely through increasing the affinity of Upf proteins for the 3′ UTR. Interestingly, while an artificial 3′ UTR of >420 nucleotides triggers NMD, a large subset of human mRNAs contain longer 3′ UTRs but evade NMD. We speculate that these have evolved to concentrate NMD-inhibiting factors, such as PABP, in spatial proximity of the termination codon.
Author Summary
The nonsense-mediated mRNA decay pathway is responsible for rapidly degrading mRNAs with premature termination codons. This is important because it prevents the production of potentially deleterious truncated proteins from aberrant mRNAs, such as those that have undergone erroneous processing. How does the cell discriminate aberrant mRNAs from those that are normal? Here we present evidence that in human cells, the targeting of an mRNA to nonsense-mediated mRNA decay depends on a competition between proteins associated with the mRNA 3′ UTR that stimulate or antagonize mRNA decay. We show that cytoplasmic poly(A)-binding protein, a protein associated with the mRNA 3′ end poly(A) tail, antagonizes mRNA decay. By contrast, a protein complex deposited onto mRNAs upon pre-mRNA splicing, called the exon junction complex, stimulates mRNA decay. Our observations suggest that the competition between these proteins, and probably other unknown proteins with similar activities, determines whether a key protein complex in the pathway, the Upf complex, is recruited to the mRNA upon translation termination, which leads to mRNA decay.
Human mRNAs with premature termination codons are detected and degraded by nonsense-mediated decay when 3' untranslated region-associated proteins, such as poly(A)-binding protein, are absent from the proximity of the terminating ribosome.
doi:10.1371/journal.pbio.0060111
PMCID: PMC2689706  PMID: 18447585
20.  Base Pairing Interaction between 5′- and 3′-UTRs Controls icaR mRNA Translation in Staphylococcus aureus 
PLoS Genetics  2013;9(12):e1004001.
The presence of regulatory sequences in the 3′ untranslated region (3′-UTR) of eukaryotic mRNAs controlling RNA stability and translation efficiency is widely recognized. In contrast, the relevance of 3′-UTRs in bacterial mRNA functionality has been disregarded. Here, we report evidences showing that around one-third of the mapped mRNAs of the major human pathogen Staphylococcus aureus carry 3′-UTRs longer than 100-nt and thus, potential regulatory functions. We selected the long 3′-UTR of icaR, which codes for the repressor of the main exopolysaccharidic compound of the S. aureus biofilm matrix, to evaluate the role that 3′-UTRs may play in controlling mRNA expression. We showed that base pairing between the 3′-UTR and the Shine-Dalgarno (SD) region of icaR mRNA interferes with the translation initiation complex and generates a double-stranded substrate for RNase III. Deletion or substitution of the motif (UCCCCUG) within icaR 3′-UTR was sufficient to abolish this interaction and resulted in the accumulation of IcaR repressor and inhibition of biofilm development. Our findings provide a singular example of a new potential post-transcriptional regulatory mechanism to modulate bacterial gene expression through the interaction of a 3′-UTR with the 5′-UTR of the same mRNA.
Author Summary
At both sides of the protein-coding region, the mRNA molecule contains sequences that are not translated to protein. In eukaryotes, the untranslated 3′ region (3′-UTR), which comprises from the last codon used in translation to the 3′ end of the mRNA, controls mRNA stability, location and translation efficiency. In contrast, knowledge about the functions of 3′-UTRs in bacterial physiology is scarce. Here, we demonstrate that bacterial 3′-UTRs might play regulatory functions that might resemble those already described in eukaryotes. Transcriptome analysis of the human pathogen Staphylococcus aureus revealed that at least 30% of mRNAs contain long 3′-UTRs. Using the 3′-UTR of the mRNA encoding the main biofilm repressor IcaR as a model, we show that the 3′-UTR interferes with the translation initiation complex and promotes mRNA decay through base pairing with the ribosome binding site. This event contributes to adjusting IcaR level and modulating exopolysaccharide production and biofilm development in S. aureus. Our data illustrate that bacterial 3′-UTRs can provide strategies for fine-tuning control of gene expression.
doi:10.1371/journal.pgen.1004001
PMCID: PMC3868564  PMID: 24367275
21.  NOVA-dependent regulation of cryptic NMD exons controls synaptic protein levels after seizure 
eLife  2013;2:e00178.
The neuronal RNA binding protein NOVA regulates splicing, shuttles to the cytoplasm, and co-localizes with target transcripts in dendrites, suggesting links between splicing and local translation. Here we identified >200 transcripts showing NOVA-dependent changes in abundance, but, surprisingly, HITS-CLIP revealed NOVA binds these RNAs in introns rather than 3′ UTRs. This led us to discover NOVA-regulated splicing of cryptic exons within these introns. These exons triggered nonsense mediated decay (NMD), as UPF1 and protein synthesis were required for NOVA's effect on RNA levels. Their regulation was dynamic and physiologically relevant. The NMD exons were regulated by seizures, which also induced changes in Nova subcellular localization and mediated large changes in synaptic proteins, including proteins implicated in familial epilepsy. Moreover, Nova haploinsufficient mice had spontaneous epilepsy. The data reveal a hidden means of dynamic RNA regulation linking electrical activity to splicing and protein output, and of mediating homeostatic excitation/inhibition balance in neurons.
DOI: http://dx.doi.org/10.7554/eLife.00178.001
eLife digest
After the DNA in a gene has been transcribed into messenger RNA, portions of the mRNA called introns are removed, and the remaining stretches of mRNA, which are known as exons, are spliced together. Within eukaryotic cells, a process known as alternative splicing allows a single gene to encode for multiple protein variants by ensuring that some exons are included in the final, modified mRNA, while other exons are excluded. This modified mRNA is then translated into proteins.
Eukaryotic cells also contain proteins that bind to RNA to regulate alternative splicing. These RNA-binding proteins are often found in both the cytoplasm and nucleus of cells, and their involvement in splicing may be linked to other processes in the cell such as mRNA localization and translation. It has also become clear over the past two decades that certain types of RNA-binding proteins, including NOVA proteins, are only found in neurons, and that these proteins have been best characterized as alternative splicing regulators. Recent work has also suggested that they also have important roles in regulating neuronal activity and development, and that their actions in neuronal nuclei and cytoplasm might be coordinated.
Now Eom et al. use the predictive power of a high throughput sequencing and crosslinking method termed HITS-CLIP to show that NOVA proteins can indirectly regulate cytoplasmic mRNA levels by regulating the process of alternative splicing in the nucleus to produce ‘cryptic’ exons in the brains of mice. The presence of these exons in the mRNA leads to the production of premature termination codons in the cytoplasm. These codons trigger a process called nonsense-mediated decay that involves identifying mRNA transcripts that contain nonsense mutations, and then degrading them. These cryptic exons were seen in mice missing the NOVA proteins, where they are expressed in abnormally high levels; in normal mice, these exons have not been seen before, hence they were termed ‘cryptic’.
Eom et al. also show that these cryptic exons are physiologically relevant by inducing epileptic seizures in mice. Following the seizures, they find that the NOVA proteins up-regulate and down-regulate the levels of different cryptic exons, leading to changes in the levels of the proteins encoded by these mRNAs, including proteins that inhibit further seizures. Overall the results indicate that, by controlling the production of various proteins in neurons, these previously unknown cryptic exons have important roles in the workings of the brain.
DOI: http://dx.doi.org/10.7554/eLife.00178.002
doi:10.7554/eLife.00178
PMCID: PMC3552424  PMID: 23359859
HITS-CLIP; Nonsense mediated decay; alternative splicing; RNA regulation; epilepsy; neuronal biology; Mouse
22.  Activation of synovial fibroblasts in rheumatoid arthritis: lack of expression of the tumour suppressor PTEN at sites of invasive growth and destruction 
Arthritis Research  1999;2(1):59-64.
In the present study, we searched for mutant PTEN transcripts in aggressive rheumatoid arthritis synovial fibroblasts (RA-SF) and studied the expression of PTEN in RA. By automated sequencing, no evidence for the presence of mutant PTEN transcripts was found. However, in situ hybridization on RA synovium revealed a distinct expression pattern of PTEN, with negligible staining in the lining layer but abundant expression in the sublining. Normal synovial tissue exhibited homogeneous staining for PTEN. In cultured RA-SF, only 40% expressed PTEN. Co-implantation of RA-SF and normal human cartilage into severe combined immunodeficiency (SCID) mice showed only limited expression of PTEN, with no staining in those cells aggressively invading the cartilage. Although PTEN is not genetically altered in RA, these findings suggest that a lack of PTEN expression may constitute a characteristic feature of activated RA-SF in the lining, and may thereby contribute to the invasive behaviour of RA-SF by maintaining their aggressive phenotype at sites of cartilage destruction.
Aims:
PTEN is a novel tumour suppressor which exhibits tyrosine phosphatase activity as well as homology to the cytoskeletal proteins tensin and auxilin. Mutations of PTEN have been described in several human cancers and associated with their invasiveness and metastatic properties. Although not malignant, rheumatoid arthritis synovial fibroblasts (RA-SF) exhibit certain tumour-like features such as attachment to cartilage and invasive growth. In the present study, we analyzed whether mutant transcripts of PTEN were present in RA-SF. In addition, we used in situ hybridization to study the expression of PTEN messenger (m)RNA in tissue samples of RA and normal individuals as well as in cultured RA-SF and in the severe combined immunodeficiency (SCID) mouse model of RA.
Methods:
Synovial tissue specimens were obtained from seven patients with RA and from two nonarthritic individuals. Total RNA was isolated from synovial fibroblasts and after first strand complementary (c)DNA synthesis, polymerase chain reaction (PCR) was performed to amplify a 1063 base pair PTEN fragment that encompassed the coding sequence of PTEN including the phosphatase domain and all mutation sites described so far. The PCR products were subcloned in Escherichia coli, and up to four clones were picked from each plate for automated sequencing. For in situ hybridization, digoxigenin-labelled PTEN-specific RNA probes were generated by in vitro transcription. For control in situ hybridization, a matrix metalloproteinase (MMP)-2-specific probe was prepared. To investigate the expression of PTEN in the absence of human macrophage or lymphocyte derived factors, we implanted RA-SF from three patients together with normal human cartilage under the renal capsule of SCID mice. After 60 days, mice were sacrificed, the implants removed and embedded into paraffin.
Results:
PCR revealed the presence of the expected 1063 base pair PTEN fragment in all (9/9) cell cultures (Fig. 1). No additional bands that could account for mutant PTEN variants were detected. Sequence analysis revealed 100% homology of all RA-derived PTEN fragments to those from normal SF as well as to the published GenBank sequence (accession number U93051). However, in situ hybridization demonstrated considerable differences in the expression of PTEN mRNA within the lining and the sublining layers of RA synovial membranes. As shown in Figure 2a, no staining was observed within the lining layer which has been demonstrated to mediate degradation of cartilage and bone in RA. In contrast, abundant expression of PTEN mRNA was found in the sublining of all RA synovial tissues (Figs 2a and b). Normal synovial specimens showed homogeneous staining for PTEN within the thin synovial membrane (Fig. 2c). In situ hybridization using the sense probe gave no specific staining (Fig. 2d). We also performed in situ hybridization on four of the seven cultured RA-SF and followed one cell line from the first to the sixth passage. Interestingly, only 40% of cultured RA-SF expressed PTEN mRNA (Fig. 3a), and the proportion of PTEN expressing cells did not change throughout the passages. In contrast, control experiments using a specific RNA probe for MMP-2 revealed mRNA expression by nearly all cultured cells (Fig. 3b). As seen before, implantation of RA-SF into the SCID mice showed considerable cartilage degradation. Interestingly, only negligible PTEN expression was found in those RA-SF aggressively invading the cartilage (Fig. 3c). In situ hybridization for MMP-2 showed abundant staining in these cells (Fig. 3d).
Discussion:
Although this study found no evidence for mutations of PTEN in RA synovium, the observation that PTEN expression is lacking in the lining layer of RA synovium as well as in more than half of cultured RA-SF is of interest. It suggests that loss of PTEN function may not exclusively be caused by genetic alterations, yet at the same time links the low expression of PTEN to a phenotype of cells that have been shown to invade cartilage aggressively.
It has been proposed that the tyrosine phosphatase activity of PTEN is responsible for its tumour suppressor activity by counteracting the actions of protein tyrosine kinases. As some studies have demonstrated an upregulation of tyrosine kinase activity in RA synovial cells, it might be speculated that the lack of PTEN expression in aggressive RA-SF contributes to the imbalance of tyrosine kinases and phosphatases in this disease. However, the extensive amino-terminal homology of the predicted protein to the cytoskeletal proteins tensin and auxilin suggests a complex regulatory function involving cellular adhesion molecules and phosphatase-mediated signalling. The tyrosine phosphatase TEP1 has been shown to be identical to the protein encoded by PTEN, and gene transcription of TEP1 has been demonstrated to be downregulated by transforming growth factor (TGF)-β. Therefore, it could be hypothesized that TGF-β might be responsible for the downregulation of PTEN. However, the expression of TGF-β is not restricted to the lining but found throughout the synovial tissue in RA. Moreover, in our study the percentage of PTEN expressing RA-SF remained stable for six passages in culture, whereas molecules that are cytokine-regulated in vivo frequently change their expression levels when cultured over several passages. Also, cultured RA-SF that were implanted into SCID mice and deeply invaded the cartilage did not show significant expression of PTEN after 60 days. The drop in the percentage of PTEN expressing cells from the original cell cultures to the SCID mouse implants is of interest as this observation goes along with data from previous studies that have shown the prominent expression of activation-related molecules in the SCID mice implants that in vivo are found predominantly in the lining layer. Therefore, our data point to endogenous mechanisms rather than to the influence of exogenous human cytokines or factors in the downregulation of PTEN. Low expression of PTEN may belong to the features that distinguish between the activated phenotype of RA-SF and the sublining, proliferating but nondestructive cells.
PMCID: PMC17804  PMID: 11219390
rheumatoid arthritis; synovial membrane; fibroblasts; PTEN tumour suppressor; severe combined immunodeficiency (SCID) mouse model; cartilage destruction; in situ hybridization
23.  Dual Regulation of the lin-14 Target mRNA by the lin-4 miRNA 
PLoS ONE  2013;8(9):e75475.
microRNAs (miRNAs) are ∼22 nt regulatory RNAs that in animals typically bind with partial complementarity to sequences in the 3′ untranslated (UTR) regions of target mRNAs, to induce a decrease in the production of the encoded protein. The relative contributions of translational inhibition of intact mRNAs and degradation of mRNAs caused by binding of the miRNA vary; for many genetically validated miRNA targets, translational repression has been implicated, whereas some analyses of other miRNA targets have revealed only modest translational repression and more significant mRNA destabilization. In Caenorhabditis elegans, the lin-4 miRNA accumulates during early larval development, binds to target elements in the lin-14 mRNA, and causes a sharp decrease in the abundance of LIN-14 protein. Here, we monitor the dynamics of lin-14 mRNA and protein as well as lin-4 miRNA levels in finely staged animals during early larval development. We find complex regulation of lin-14, with the abundance of lin-14 mRNA initially modestly declining followed by fluctuation but little further decline of lin-14 mRNA levels accompanied by continuing and more dramatic decline in LIN-14 protein abundance. We show that the translational inhibition of lin-14 is dependent on binding of the lin-4 miRNA to multiple lin-4 complementary sites in the lin-14 3′UTR. Our results point to the importance of translational inhibition in silencing of lin-14 by the lin-4 miRNA.
doi:10.1371/journal.pone.0075475
PMCID: PMC3772890  PMID: 24058689
24.  Iron Responsive mRNAs: A Family of Fe2+ Sensitive Riboregulators 
Accounts of chemical research  2011;44(12):1320-1328.
Messenger RNAs (mRNAs) are emerging as prime targets for small-molecule drugs. They afford an opportunity to assert control over an enormous range of biological processes: mRNAs regulate protein synthesis rates, have specific 3-D regulatory structures, and, in nucleated cells, are separated from DNA in space and time. All of the many steps between DNA copying (transcription) and ribosome binding (translation) represent potential control points. Messenger RNAs can fold into complex, 3-D shapes, such as transfer RNAs and ribosomal RNAs, providing an added dimension to the 2-D RNA structure (base pairing) targeted in many mRNA interference approaches. In this Account, we describe the structural and functional properties of the IRE (iron-responsive element) family, one of the few 3-D mRNA regulatory elements with known 3-D structure. This family of related base sequences regulates the mRNAs that encode proteins for iron metabolism.
We begin by considering the IRE-RNA structure, which consists of a short (~30-nucleotide) RNA helix. Nature tuned the structure by combining a conserved AGU pseudotriloop, a closing C-G base pair, and a bulge C with various RNA helix base pairs. The result is a set of IRE-mRNAs with individual iron responses. The physiological iron signal is hexahydrated ferrous ion; in vivo iron responses vary over 10-fold depending on the individual IRE-RNA structure.
We then discuss the interaction between the IRE-RNA structure and the proteins associated with it. IRE-RNA structures, which are usually noncoding, tightly bind specific proteins called IRPs. These repressor proteins are bound to IRE-RNA through C-bulge and AGU contacts that flip out a loop AG and a bulge C, bending the RNA helix. After binding, the exposed RNA surface then invites further interactions, such as with iron and other proteins. Binding of the IRE-RNA and the IRP also changes the IRP conformation. IRP binding stabilities vary 10-fold within the IRE family, reflecting individual IRE-RNA paired and unpaired bases. This variation contributes to the graded (hierarchical) iron responses in vivo.
We also consider the mechanisms of IRE-mRNA control. The binding of Fe2+ to IRE-RNA facilitates IRP release and the binding of eukaryotic initiation factors (eIFs), which are proteins that assemble mRNA, ribosomes, and tRNA for translation. IRE-RNAs are riboregulators for the inorganic metabolic signal, Fe2+; they control protein synthesis rates by changing the distribution of the iron metabolic mRNAs between complexes with enhancing eIFs and inhibitory IRPs.
The regulation of mRNA in the cytoplasm of eukaryotic cells is a burgeoning frontier in biomedicine. The evolutionarily refined IRE-RNAs, although absent in plants and bacteria, constitute a model system for 3-D mRNAs in all organisms. IRE-mRNAs have yielded “proof of principle” data for small-molecule targeting of mRNA structures, demonstrating tremendous potential for chemical manipulation of mRNA and protein synthesis in living systems.
doi:10.1021/ar2001149
PMCID: PMC3243817  PMID: 22026512
25.  The 5'-untranslated region of GM-CSF mRNA suppresses translational repression mediated by the 3' adenosine-uridine-rich element and the poly(A) tail. 
Nucleic Acids Research  1999;27(18):3660-3666.
Granulocyte-macrophage colony stimulating factor (GM-CSF) mRNA levels are controlled post-transcriptionally by the 3'-untranslated region (UTR) adenosine-uridine-rich element (ARE). In untransformed, resting cells, the ARE targets GM-CSF mRNA for rapid degradation, thereby significantly suppressing protein expression. We used a rabbit reticulocyte lysate (RRL) cell-free system to examine translational regulation of GM-CSF expression. We uncoupled decay rates from rates of translation by programming the RRL with an excess of mRNAs. Capped, full-length, polyadenyl-ated human GM-CSF mRNA (full-length 5'-UTR AUUUA+A90) and an ARE-modified version (full-length 5'-UTR AUGUA+A90) produced identical amounts of protein. When the 5'-UTR was replaced with an irrelevant synthetic leader sequence (syn 5'-UTR), translation of syn 5'-UTR AUUUA+A90 mRNA was suppressed by >20-fold. Mutation of the ARE or removal of the poly(A) tail relieved this inhibition. Thus, in the absence of a native 5'-UTR, the ARE and poly(A) tail act in concert to block GM-CSF mRNA translation. Substitutions of different regions of the native 5'-UTR revealed that the entire sequence was essential in maintaining the highest rates of translation. However, shorter 10-12 nt contiguous 5'-UTR regions supported 50-60% of maximum translation. The 5'-UTR is highly conserved, suggesting similar regulation in multiple species and in these studies was the dominant element regulating GM-CSF mRNA translation, overriding the inhibitory effects of the ARE and the poly(A) tail.
PMCID: PMC148620  PMID: 10471734

Results 1-25 (1119457)