Yitzhak Pilpel

Identifying regulatory networks by combinatorial analysis of promoter elements

Several computational methods based on microarray data are currently used to study genome-wide transcriptional regulation. Few studies, however, address the combinatorial nature of transcription, a well-established phenomenon in eukaryotes. Here we describe a new approach using microarray data to uncover novel functional motif combinations in the promoters of Saccharomyces cerevisiae. In addition to identifying novel motif combinations that affect expression patterns during the cell cycle, sporulation and various stress responses, we observed regulatory cross-talk among several of these processes. We have also generated motif-association maps that provide a global view of transcription networks. The maps are highly connected, suggesting that a small number of transcription factors are responsible for a complex set of expression patterns in diverse conditions. This approach may be useful for modeling transcriptional regulatory networks in more complex eukaryotes.

Global and Local Architecture of the Mammalian microRNA–Transcription Factor Regulatory Network

microRNAs (miRs) are small RNAs that regulate gene expression at the posttranscriptional level. It is anticipated that, in combination with transcription factors (TFs), they span a regulatory network that controls thousands of mammalian genes. Here we set out to uncover local and global architectural features of the mammalian miR regulatory network. Using evolutionarily conserved potential binding sites of miRs in human targets, and conserved binding sites of TFs in promoters, we uncovered two regulation networks. The first depicts combinatorial interactions between pairs of miRs with many shared targets. The network reveals several levels of hierarchy, whereby a few miRs interact with many other lowly connected miR partners. We revealed hundreds of “target hubs” genes, each potentially subject to massive regulation by dozens of miRs. Interestingly, many of these target hub genes are transcription regulators and they are often related to various developmental processes. The second network consists of miR–TF pairs that coregulate large sets of common targets. We discovered that the network consists of several recurring motifs. Most notably, in a significant fraction of the miR–TF coregulators the TF appears to regulate the miR, or to be regulated by the miR, forming a diversity of feed-forward loops. Together these findings provide new insights on the architecture of the combined transcriptional–post transcriptional regulatory network.

Adaptive prediction of environmental changes by microorganisms.

Natural habitats of some microorganisms may fluctuate erratically, whereas others, which are more predictable, offer the opportunity to prepare in advance for the next environmental change. In analogy to classical Pavlovian conditioning, microorganisms may have evolved to anticipate environmental stimuli by adapting to their temporal order of appearance. Here we present evidence for environmental change anticipation in two model microorganisms, Escherichia coli and Saccharomyces cerevisiae. We show that anticipation is an adaptive trait, because pre-exposure to the stimulus that typically appears early in the ecology improves the organism’s fitness when encountered with a second stimulus. Additionally, we observe loss of the conditioned response in E. coli strains that were repeatedly exposed in a laboratory evolution experiment only to the first stimulus. Focusing on the molecular level reveals that the natural temporal order of stimuli is embedded in the wiring of the regulatory network—early stimuli pre-induce genes that would be needed for later ones, yet later stimuli only induce genes needed to cope with them. Our work indicates that environmental anticipation is an adaptive trait that was repeatedly selected for during evolution and thus may be ubiquitous in biology.

p53-independent upregulation of miR-34a during oncogene-induced senescence represses MYC

Aberrant oncogene activation induces cellular senescence, an irreversible growth arrest that acts as a barrier against tumorigenesis. To identify microRNAs (miRNAs) involved in oncogene-induced senescence, we examined the expression of miRNAs in primary human TIG3 fibroblasts after constitutive activation of B-RAF. Among the regulated miRNAs, both miR-34a and miR-146a were strongly induced during senescence. Although members of the miR-34 family are known to be transcriptionally regulated by p53, we find that miR-34a is regulated independently of p53 during oncogene-induced senescence. Instead, upregulation of miR-34a is mediated by the ETS family transcription factor, ELK1. During senescence, miR-34a targets the important proto-oncogene MYC and our data suggest that miR-34a thereby coordinately controls a set of cell cycle regulators. Hence, in addition to its integration in the p53 pathway, we show that alternative cancer-related pathways regulate miR-34a, emphasising its significance as a tumour suppressor.

Determinants of translation efficiency and accuracy

Proper functioning of biological cells requires that the process of protein expression be carried out with high efficiency and fidelity. Given an amino‐acid sequence of a protein, multiple degrees of freedom still remain that may allow evolution to tune efficiency and fidelity for each gene under various conditions and cell types. Particularly, the redundancy of the genetic code allows the choice between alternative codons for the same amino acid, which, although ‘synonymous,’ may exert dramatic effects on the process of translation. Here we review modern developments in genomics and systems biology that have revolutionized our understanding of the multiple means by which translation is regulated. We suggest new means to model the process of translation in a richer framework that will incorporate information about gene sequences, the tRNA pool of the organism and the thermodynamic stability of the mRNA transcripts. A practical demonstration of a better understanding of the process would be a more accurate prediction of the proteome, given the transcriptome at a diversity of biological conditions.

Genome‐wide natural antisense transcription: coupling its regulation to its different regulatory mechanisms

Many genomic loci contain transcription units on both strands, therefore two oppositely oriented transcripts can overlap. Often, one strand codes for a protein, whereas the transcript from the other strand is non‐encoding. Such natural antisense transcripts (NATs) can negatively regulate the conjugated sense transcript. NATs are highly prevalent in a wide range of species—for example, around 15% of human protein‐encoding genes have an associated NAT. The regulatory mechanisms by which NATs act are diverse, as are the means to control their expression. Here, we review the current understanding of NAT function and its mechanistic basis, which has been gathered from both individual gene cases and genome‐wide studies. In parallel, we survey findings about the regulation of NAT transcription. Finally, we hypothesize that the regulation of antisense transcription might be tailored to its mode of action. According to this model, the observed relationship between the expression patterns of NATs and their targets might indicate the regulatory mechanism that is in action.

Differentially Regulated Micro-RNAs and Actively Translated Messenger RNA Transcripts by Tumor Suppressor p53 in Colon Cancer

Purpose: The aim of this study was to investigate the role of p53 in regulating micro-RNA (miRNA) expression due to its function as a transcription factor. In addition, p53 may also affect other cellular mRNA gene expression at the translational level either via its mediated miRNAs or due to its RNA-binding function. Experimental Design: The possible interaction between p53 and miRNAs in regulating gene expression was investigated using human colon cancer HCT-116 (wt-p53) and HCT-116 (null-p53) cell lines. The effect of p53 on the expression of miRNAs was investigated using miRNA expression array and real-time quantitative reverse transcription-PCR analysis. Results: Our investigation indicated that the expression levels of a number of miRNAs were affected by wt-p53. Down-regulation of wt-p53 via small interfering RNA abolished the effect of wt-p53 in regulating miRNAs in HCT-116 (wt-p53) cells. Global sequence analysis revealed that over 46% of the 326 miRNA putative promoters contain potential p53-binding sites, suggesting that some of these miRNAs were potentially regulated directly by wt-p53. In addition, the expression levels of steady-state total mRNAs and actively translated mRNA transcripts were quantified by high-density microarray gene expression analysis. The results indicated that nearly 200 cellular mRNA transcripts were regulated at the posttranscriptional level, and sequence analysis revealed that some of these mRNAs may be potential targets of miRNAs, including translation initiation factor eIF-5A, eIF-4A, and protein phosphatase 1. Conclusion: To the best of our knowledge, this is the first report demonstrating that wt-p53 and miRNAs interact in influencing gene expression and providing insights of how p53 regulates genes at multiple levels via unique mechanisms.

Transcription control reprogramming in genetic backup circuits

A key question in molecular genetics is why severe mutations often do not result in a detectably abnormal phenotype. This robustness was partially ascribed to redundant paralogs that may provide backup for one another in case of mutation. Mining mutant viability and mRNA expression data in Saccharomyces cerevisiae, we found that backup was provided predominantly by paralogs that are expressed dissimilarly in most growth conditions. We considered that this apparent inconsistency might be resolved by a transcriptional reprogramming mechanism that allows the intact paralog to rescue the organism upon mutation of its counterpart. We found that in wild-type cells, partial coregulation across growth conditions predicted the ability of paralogs to alter their transcription patterns and to provide backup for one another. Notably, the sets of regulatory motifs that controlled the paralogs with the most efficient backup activity deliberately overlapped only partially; paralogs with highly similar or dissimilar sets of motifs had suboptimal backup activity. Such an arrangement of partially shared regulatory motifs reconciles the differential expression of paralogs with their ability to back each other up.

Axonal transcription factors signal retrogradely in lesioned peripheral nerve.

Retrograde axonal injury signalling stimulates cell body responses in lesioned peripheral neurons. The involvement of importins in retrograde transport suggests that transcription factors (TFs) might be directly involved in axonal injury signalling. Here, we show that multiple TFs are found in axons and associate with dynein in axoplasm from injured nerve. Biochemical and functional validation for one TF family establishes that axonal STAT3 is locally translated and activated upon injury, and is transported retrogradely with dynein and importin α5 to modulate survival of peripheral sensory neurons after injury. Hence, retrograde transport of TFs from axonal lesion sites provides a direct link between axon and nucleus.

Transient transcriptional responses to stress are generated by opposing effects of mRNA production and degradation

The state of the transcriptome reflects a balance between mRNA production and degradation. Yet how these two regulatory arms interact in shaping the kinetics of the transcriptome in response to environmental changes is not known. We subjected yeast to two stresses, one that induces a fast and transient response, and another that triggers a slow enduring response. We then used microarrays following transcriptional arrest to measure genome‐wide decay profiles under each condition. We found condition‐specific changes in mRNA decay rates and coordination between mRNA production and degradation. In the transient response, most induced genes were surprisingly destabilized, whereas repressed genes were somewhat stabilized, exhibiting counteraction between production and degradation. This strategy can reconcile high steady‐state level with short response time among induced genes. In contrast, the stress that induces the slow response displays the more expected behavior, whereby most induced genes are stabilized, and repressed genes are destabilized. Our results show genome‐wide interplay between mRNA production and degradation, and that alternative modes of such interplay determine the kinetics of the transcriptome in response to stress.