How do activators promote transcription

Our genome-wide two-hybrid screen thus provided data about activation properties of nearly all yeast proteins. Up to now this information has not been used for the understanding of transcription in yeast.

However, similar assays have been used previously by Wiesner et al. By design such screens do not necessarily identify physiological activators as the fusion partners are artificially targeted to the promoter of a single, arbitrarily selected reporter gene.

Bearing these caveats in mind, we not only selected Y2H auto-activators but also measured their activation strength. In a second step we analyzed these auto-activators for their domain content and other sequence properties. We found that auto-activators possess specific physicochemical properties, like certain amino acid clusters, and can often be found in known complexes of the transcription machinery. Many of the activators identified in this study are known physiological activators.

However, many do not appear to be localized to the nucleus under standard laboratory conditions and thus may not act as bona fide transcription factors.

Nevertheless, we believe that even such cases can shed light on the mechanisms of transcriptional activation similar to heterologous proteins such as VP16 which helped to uncover many mechanistic details of transcriptional activation. Transcriptional activators were identified in two genome-wide Y2H studies of yeast proteins 26 , For analysis of transcription activator properties activators identified by Ito et al. These two independent selection steps ensured correct identification of activators.

For further quality control, we sequenced 48 samples from the Ito collection and checked another 29 from the Uetz lab by colony PCR for correct insert size.

Among these 77 clones only 1 out of the 29 mentioned did not match the expected identity and was thus excluded from further analysis. However, 79 strains did not grow well enough to be quantified, although they were reported to be activators. The activators were selected from the bait proteins described by Uetz et al. The handling of yeast colonies was done by automated robotic procedures employing a Biomek robotic workstation Beckman Coulter.

The activation strength was measured by two different assays which measure the expression of two reporter genes: His3, which encodes imidazoleglycerol-phosphate dehydratase and catalyzes the sixth step in histidine biosynthesis LTH assay and beta-galactosidase bGal assay. Activity of the HIS3 reporter was quantified by increasing amounts of 3-aminotriazole 3-AT , a competitive inhibitor of His3.

The lowest concentration of 3-AT that inhibited growth was considered as the activation strength of the gene construct This assay was done in quadruplicate in order to ensure reproducibility for detailed results see Supplementary Table 1.

Finally, the mean bGal activity of a randomly chosen set of genes not found to possess auto-activation properties was subtracted. This assay was done in triplicates and mean and SEM were calculated for each activator Supplementary Table 1. General yeast protein properties, e. Protein localization data were from Huh et al. GO component data. The abundance of proteins was compared using the genome-wide measurements by Ghaemmaghami et al. Protein interaction data were downloaded from the MIPS database Overrepresentation of certain GO terms was assessed using the program FuncAssociate Table 1 summarizes the protein sets that were used for analysis.

General physicochemical properties, e. Frequencies of amino acids were directly calculated from SGD sequence data. The minimal and maximal pI of a protein was calculated as the lowest and highest pI of a 20 amino acid window, respectively. Amino acid clusters in a protein were defined as the maximal count of a specific amino acid in a 20 amino acid window of the protein.

GRAVY grand average of Hydropathicity values were calculated as the sum of hydropathy values for all of the amino acids, divided by the number of residues in the sequence The number of proteins with each domain in the Y2H activator set and the whole genome was counted and the enrichment in the former set was calculated. Significance was tested using Fisher's exact test and Holm's procedure for multiple testing correction A protein—protein interaction map of transcription activators was generated using Cytoscape In the Cytoscape map only physical binary protein interactions from the MIPS database were considered.

Only activators and their direct interaction partners, bridging at least two activators, were selected. The percentage of activators that interacted with other transcription factors i. Similarly, we counted with how many transcription complexes our activators interacted. The protein interactions with these complexes were assessed by using the MIPS data of protein complexes filtered to contain only high-throughput data for reduction of bias of well-characterized proteins.

Ranking of interaction partners was done by counting with how many proteins of a specific protein set a given yeast protein interacted using high-throughput protein complex data from the MIPS database. Data processing was done with PERL www. Correction for multiple testing was done with Holm's procedure using the multtest package of R 41 , However, these proteins were not listed in the original publication nor did these studies provide any quantitative data for the activation strength. The bGal assay distribution was divided into strong activators bGals which activate above the median and weak activators that activate below the median bGalW.

A comparison of activation strength in both assays revealed an intermediate Pearson's correlation coefficient of 0. We have not tried to determine the contribution of each of the two lacZ genes and restricted the following analysis to the His3 data. In summary, a total of 72 weak, medium and 75 strong transcriptional activators were identified in these experiments Table 2 and Supplementary Table 1.

First, we wondered if Y2H activators also act in vivo as transcriptional activators. This suggests that many more proteins may act as transcriptional activators than currently known.

Transcription takes place in the nucleus. We wondered if Y2H activators were also localized in the nucleus and analyzed their localization using the large-scale localization study by Huh et al.

The activation strength was also correlated with nuclear localization: e. Correlating GO function and localization revealed a significant overrepresentation of known TRs among nuclear activators and among nuclear-cytoplasmic proteins, but not in the set of exclusively cytoplasmic proteins Supplementary Figure 1.

This number indicates that a large fraction of these activators may act as transcription factors in vivo although this activity has not been recognized previously. It has been known for a long time that transcriptional activators are often expressed at low levels.

This notion is also reflected in the lower concentration of known transcription regulators Figure 2C. However, this trend was not significant. Although characteristics such as abundance and localization allow us to classify activators, they do not explain their behavior. In fact, it has been unclear which properties turn a protein into a transcriptional activator even though certain physicochemical properties such as acidic stretches have been identified We therefore revisited the influence of physicochemical properties on the propensity of a protein to activate transcription.

Interestingly, known TRs had only a slightly reduced mean pI, which was even higher than for nuclear proteins in general.

The influence of activation strength onto the mean pI was not significant judged by Student's t -test. This tendency is also reflected by the higher mean molecular weight of known TRs. Activators in the nucleus were not significantly larger than nuclear proteins in general but we found that the mean molecular weight increased with activation strength Figure 3B.

Both properties were reduced in activators as well as in known TRs. As lower codon scores are associated with lower protein expression levels 34 , the lower CAI for activators as well as for known TRs supports the previous finding of lower protein levels for these two protein sets Figure 2C.

As expected, known TRs generally showed similar properties as the Y2H activators except for the isoelectric point. It has been known for a long time that certain amino acids are overrepresented in transcriptional activators, in particular acidic and basic residues and certain other amino acids such as glutamine. We wondered if this is true for our activator set as well. As basic amino acid clusters are also acting as nuclear localization signals, we only took activators into account that are known to be localized to the nucleus and compared them with the remaining nuclear proteins.

After correction for multiple testing using Holm's procedure 41 15 parameters involving certain amino acids remained highly significant Supplementary Table 2. A detailed analysis of the amino acid clusters and the minimum pI is shown in Figure 4.

A detailed analysis of the remaining properties is shown in Supplementary Figure 2. Taken together, the analysis of physicochemical properties showed that Y2H activators tend to possess a lower isoelectric point, have a lower hydrophobicity, higher molecular weight, lower CAI and show specific properties like enrichment of asparagine clusters.

Transcriptional ADs are still not well defined structurally. Therefore we have analyzed the Y2H activators for enrichment of known domains. Not unexpectedly, certain DBDs such as helix—loop—helix motifs or zinc fingers are indeed significantly overrepresented among the activators Supplementary Table 5. Certain domains are also significantly underrepresented such as the AAA domain.

However, these domains are not further considered here. Specific transcription activation is mediated by physical contact with the transcriptional machinery or other factors necessary for transcription, like chromatin remodeling proteins 4 , 5 , 16 , 18 — In contrast, domains responsible for gene transcription activation are usually short, simple sequences and are less complex than the binding domains.

They are classified by amino acid composition into categories, such as glutamine-rich, proline-rich, and alanine-rich. Transcription activators aid in the recruitment of various proteins required for transcription such as general transcription factors, RNA polymerase, and co-activators. All these proteins together are known as the pre-initiation complex and depend on transcription activators for their recruitment to the appropriate location.

In cases where they are bound to a site away from the gene, they rely on the flexibility of the DNA to bend and bring them in proximity to the gene promoter. Transcription activators are known to act synergistically. The transcription achieved by the action of multiple activators is higher than what would occur as a sum of individual factors working separately. Like other proteins, transcription activators are subject to post-transcriptional modifications.

In many cases these modifications help in positive regulation of transcription. For example, acetylation of p53, an activator that regulates genes responsible for tumor suppression, increases its ability to bind to DNA.

To learn more about our GDPR policies click here. If you want more info regarding data storage, please contact gdpr jove. Your access has now expired. Provide feedback to your librarian. If you have any questions, please do not hesitate to reach out to our customer success team. Login processing Chapter Gene Expression. Chapter 2: Biochemistry of the Cell. Chapter 3: Protein Structure. Chapter 4: Protein Function. Chapter 6: DNA Replication. Chapter Mendelian Genetics. This binding facilitates RNA polymerase activity and transcription of nearby genes.

At the same time, however, other amino acids would bind to negative regulatory proteins called repressors , which in turn bind to regulatory sites in the DNA that effectively block RNA polymerase binding Figure 3. The control of gene expression in eukaryotes is more complex than that in prokaryotes. In general, a greater number of regulatory proteins are involved, and regulatory binding sites may be located quite far from transcription promoter sites. Also, eukaryotic gene expression is usually regulated by a combination of several regulatory proteins acting together, which allows for greater flexibility in the control of gene expression.

Figure 4: The complexity of multiple regulators Transcriptional regulators can each have a different role. Combinations of one, two, or three regulators blue, green, and yellow shapes can affect transcription in different ways by differentially affecting a mediator complex orange , which is also composed of proteins.

The effect is that the same gene can be transcribed in multiple ways, depending on the combination, presence, or absence of various transcriptional regulator proteins. As previously mentioned, enhancer sequences are DNA sequences that are bound by an activator protein, and they can be located thousands of base pairs away from a promoter, either upstream or downstream from a gene.

Activator protein binding is thought to cause DNA to loop out, bringing the activator protein into physical proximity with RNA polymerase and the other proteins in the complex that promote the initiation of transcription Figure 4.

Different cell types express characteristic sets of transcriptional regulators. In fact, as multicellular organisms develop, different sets of cells within these organisms turn specific combinations of regulators on and off.

Such developmental patterns are responsible for the variety of cell types present in the mature organism Figure 5. Figure 5: Transcriptional regulators can determine cell types The wide variety of cell types in a single organism can depend on different transcription factor activity in each cell type. Different transcription factors can turn on at different times during successive generations of cells.

As cells mature and go through different stages arrows , transcription factors colored balls can act on gene expression and change the cell in different ways.

This change affects the next generation of cells derived from that cell. In subsequent generations, it is the combination of different transcription factors that can ultimately determine cell type. This page appears in the following eBook. Aa Aa Aa. Gene Expression. How Is Gene Expression Regulated? Figure 1: An overview of the flow of information from DNA to protein in a eukaryote. Figure 2: Modulation of transcription. An activator protein bound to DNA at an upstream enhancer sequence can attract proteins to the promoter region that activate RNA polymerase green and thus transcription.

Figure 4: The complexity of multiple regulators. Transcriptional regulators can each have a different role. Figure 5: Transcriptional regulators can determine cell types. The wide variety of cell types in a single organism can depend on different transcription factor activity in each cell type. To live, cells must be able to respond to changes in their environment.

Regulation of the two main steps of protein production — transcription and translation — is critical to this adaptability. Thus, there is a direct parallel between the control of GCN4 and E2F-1 by basal factor kinases, and it seems likely that other examples will surface in the near future.

In support of this concept, there is a wealth of circumstantial evidence suggesting that the process of transcriptional activation frequently is associated with transcription factor destruction. As a whole, transcription factors tend to be some of the most unstable proteins in the cell. Mammalian transcription factors such as E2F-1 Hateboer et al. In most cases, the transcriptional activation domains of these proteins are required for their destruction see Salghetti et al.

This concept is further reinforced by the behavior of transcription factors such as microphthalmia Wu et al. Moreover, analysis of natural Salghetti et al. Although the molecular details of how most transcription factors are targeted for destruction is unknown, all of these observations point to a model in which interactions of transcription factors with the basal transcriptional apparatus leads to activator destruction.

Perhaps Srb10 and its homologs metazoan cdk8; Tassan et al. Perhaps these responsibilities are shared between Srb10 and other kinases in the basal transcriptional machinery such as TFIIH Lu et al. Or perhaps other catalytic functions within the basal apparatus, yet to be discovered, perform a similar regulatory role.

Regardless of the details, however, it appears clear that the type of regulation suggested by the Chi et al. Of course, not all transcription factors are unstable. Indeed, analysis of different types of transcriptional activation domains has revealed that the ability to signal Ub-mediated proteolysis is unique to domains rich in acidic residues—activation domains that are rich in proline or glutamine residues, for example, do not signal protein turnover Salghetti et al.

This finding suggests that it is the precise mechanism through which an activation domain stimulates RNA polymerase that determines whether or not a transcription factor will be destroyed. Does this mean that, by activating transcription in a certain way, some transcription factors can escape the kind of regulation described for Srb10 and GCN4? Not necessarily. An intriguing twist in the Chi et al. At present, the molecular details are not fully understood, but it appears that Srb10 phosphorylates Msn2, promoting its rapid exclusion from the nucleus.

Thus, although the stability of Msn2 is unaffected by phosphorylation, the net effect of Srbmediated phosphorylation is the same—to get Msn2 away from promoter DNA, away from the basal transcriptional machinery, and to, in turn, restrict the capacity of Msn2 to regulate transcription. In this circumstance, all of the regulatory consequences that have been discussed for GCN4 still apply, except that Msn2 is shunted out of the nucleus, rather than destroyed by Ub-mediated proteolysis.

The Chi et al. The correct regulation of gene transcription is essential to the maintenance of normal cellular homeostasis. One of the main ways cells regulate gene expression is to maintain tight control over transcription factors, and mechanisms have been described that limit the abundance, distribution, and activity of these transcriptional regulators.

The recent studies described here suggest that cells possess another weapon in their arsenal to regulate transcription—the ability of the basal transcriptional apparatus to mark the activators it encounters, sentencing them to an early death or banishing them to the antipodes.

By deciding the fate of transcription factors at the point at which they function, cells maintain tight control over some of the most potent regulatory molecules in the cell. No doubt about it: Activating transcription is a risky business. View all Transcriptional activation: risky business William P.

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