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Yitzhak Pilpel

Publications and source records attributed to Yitzhak Pilpel.

15 recordsLinked to original sources
PubMed2024

Pangenomes of human gut microbiota uncover links between genetic diversity and stress response.

The genetic diversity of the gut microbiota has a central role in host health. Here, we created pangenomes for 728 human gut prokaryotic species, quadrupling the genes of strain-specific genomes. Each of these species has a core set of a thousand genes, differing even between closely related species, and an accessory set of genes unique to the different strains. Functional analysis shows high strain variability associates with sporulation, whereas low variability is linked with antibiotic resistance. We further map the antibiotic resistome across the human gut population and find 237 cases of extreme resistance even to last-resort antibiotics, with a predominance among Enterobacteriaceae. Lastly, the presence of specific genes in the microbiota relates to host age and sex. Our study underscores the genetic complexity of the human gut microbiota, emphasizing its significant implications for host health. The pangenomes and antibiotic resistance map constitute a valuable resource for further research.

Humans↗
PubMed2006

The regulatory utilization of genetic redundancy through responsive backup circuits.

Functional redundancies, generated by gene duplications, are highly widespread throughout all known genomes. One consequence of these redundancies is a tremendous increase to the robustness of organisms to mutations and other stresses. Yet, this very robustness also renders redundancy evolutionarily unstable, and it is, thus, predicted to have only a transient lifetime. In contrast, numerous reports describe instances of functional overlaps that have been conserved throughout extended evolutionary periods. More interestingly, many such backed-up genes were shown to be transcriptionally responsive to the intactness of their redundant partner and are up-regulated if the latter is mutationally inactivated. By manual inspection of the literature, we have compiled a list of such "responsive backup circuits" in a diverse list of species. Reviewing these responsive backup circuits, we extract recurring principles characterizing their regulation. We then apply modeling approaches to explore further their dynamic properties. Our results demonstrate that responsive backup circuits may function as ideal devices for filtering nongenetic noise from transcriptional pathways and obtaining regulatory precision. We thus challenge the view that such redundancies are simply leftovers of ancient duplications and suggest they are an additional component to the sophisticated machinery of cellular regulation. In this respect, we suggest that compensation for gene loss is merely a side effect of sophisticated design principles using functional redundancy.

Animals↗
PubMed2006

Noise in protein expression scales with natural protein abundance.

Noise in gene expression is generated at multiple levels, such as transcription and translation, chromatin remodeling and pathway-specific regulation. Studies of individual promoters have suggested different dominating noise sources, raising the question of whether a general trend exists across a large number of genes and conditions. We examined the variation in the expression levels of 43 Saccharomyces cerevisiae proteins, in cells grown under 11 experimental conditions. For all classes of genes and under all conditions, the expression variance was approximately proportional to the mean; the same scaling was observed at steady state and during the transient responses to the perturbations. Theoretical analysis suggests that this scaling behavior reflects variability in mRNA copy number, resulting from random 'birth and death' of mRNA molecules or from promoter fluctuations. Deviation of coexpressed genes from this general trend, including high noise in stress-related genes and low noise in proteasomal genes, may indicate fluctuations in pathway-specific regulators or a differential activation pattern of the underlying gene promoters.

Flow Cytometry↗
PubMed2006

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.

Cell Line, Tumor↗
PubMed2006

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.

Animals↗
PubMed2005

3D model of the Escherichia coli multidrug transporter MdfA reveals an essential membrane-embedded positive charge.

MdfA is an Escherichia coli multidrug transporter of the major facilitator superfamily (MFS) of secondary transporters. Although several aspects of multidrug recognition by MdfA have been characterized, better understanding the detailed mechanism of its function requires structural information. Previous studies have modeled the 3D structures of MFS proteins, based on the X-ray structure of LacY and GlpT. However, because of poor sequence homology, between LacY, GlpT, and MdfA additional constraints were required for a reliable homology modeling. Using an algorithm that predicts the angular orientation of each transmembrane helix (TM) (kPROT), we obtained a remarkably similar pattern for the 12 TMs of MdfA and those of GlpT and LacY, suggesting that they all have similar helix packing. Consequently, a 3D model was constructed for MdfA by structural alignment with LacY and GlpT, using the kPROT results as an additional constraint. Further refinement and a preliminary evaluation of the model were achieved by correlated mutation analysis and the available experimental data. Surprisingly, in addition to the previously characterized membrane-embedded glutamate at position 26, the model suggests that Asp34 and Arg112 are located within the membrane, on the same face of the cavity as Glu26. Importantly, Arg112 is evolutionarily conserved in secondary drug transporters, and here we show that a positive charge at this position is absolutely essential for multidrug transport by MdfA.

Algorithms↗
PubMed2005

The promoters of human cell cycle genes integrate signals from two tumor suppressive pathways during cellular transformation.

Deciphering regulatory events that drive malignant transformation represents a major challenge for systems biology. Here, we analyzed genome-wide transcription profiling of an in vitro cancerous transformation process. We focused on a cluster of genes whose expression levels increased as a function of p53 and p16(INK4A) tumor suppressors inactivation. This cluster predominantly consists of cell cycle genes and constitutes a signature of a diversity of cancers. By linking expression profiles of the genes in the cluster with the dynamic behavior of p53 and p16(INK4A), we identified a promoter architecture that integrates signals from the two tumor suppressive channels and that maps their activity onto distinct levels of expression of the cell cycle genes, which, in turn, correspond to different cellular proliferation rates. Taking components of the mitotic spindle as an example, we experimentally verified our predictions that p53-mediated transcriptional repression of several of these novel targets is dependent on the activities of p21, NFY, and E2F. Our study demonstrates how a well-controlled transformation process allows linking between gene expression, promoter architecture, and activity of upstream signaling molecules.

Animals↗
PubMed2005

A catalog of stability-associated sequence elements in 3' UTRs of yeast mRNAs.

BACKGROUND: In recent years, intensive computational efforts have been directed towards the discovery of promoter motifs that correlate with mRNA expression profiles. Nevertheless, it is still not always possible to predict steady-state mRNA expression levels based on promoter signals alone, suggesting that other factors may be involved. Other genic regions, in particular 3' UTRs, which are known to exert regulatory effects especially through controlling RNA stability and localization, were less comprehensively investigated, and deciphering regulatory motifs within them is thus crucial. RESULTS: By analyzing 3' UTR sequences and mRNA decay profiles of Saccharomyces cerevisiae genes, we derived a catalog of 53 sequence motifs that may be implicated in stabilization or destabilization of mRNAs. Some of the motifs correspond to known RNA-binding protein sites, and one of them may act in destabilization of ribosome biogenesis genes during stress response. In addition, we present for the first time a catalog of 23 motifs associated with subcellular localization. A significant proportion of the 3' UTR motifs is highly conserved in orthologous yeast genes, and some of the motifs are strikingly similar to recently published mammalian 3' UTR motifs. We classified all genes into those regulated only at transcription initiation level, only at degradation level, and those regulated by a combination of both. Interestingly, different biological functionalities and expression patterns correspond to such classification. CONCLUSION: The present motif catalogs are a first step towards the understanding of the regulation of mRNA degradation and subcellular localization, two important processes which--together with transcription regulation--determine the cell transcriptome.

3' Untranslated Regions↗
PubMed2005

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.

Kinetics↗
PubMed2005

Extraction of transcription regulatory signals from genome-wide DNA-protein interaction data.

Deciphering gene regulatory network architecture amounts to the identification of the regulators, conditions in which they act, genes they regulate, cis-acting motifs they bind, expression profiles they dictate and more complex relationships between alternative regulatory partnerships and alternative regulatory motifs that give rise to sub-modalities of expression profiles. The 'location data' in yeast is a comprehensive resource that provides transcription factor-DNA interaction information in vivo. Here, we provide two contributions: first, we developed means to assess the extent of noise in the location data, and consequently for extracting signals from it. Second, we couple signal extraction with better characterization of the genetic network architecture. We apply two methods for the detection of combinatorial associations between transcription factors (TFs), the integration of which provides a global map of combinatorial regulatory interactions. We discover the capacity of regulatory motifs and TF partnerships to dictate fine-tuned expression patterns of subsets of genes, which are clearly distinct from those displayed by most genes assigned to the same TF. Our findings provide carefully prioritized, high-quality assignments between regulators and regulated genes and as such should prove useful for experimental and computational biologists alike.

Binding Sites↗
PubMed2003

Comprehensive quantitative analyses of the effects of promoter sequence elements on mRNA transcription.

We have generated a WWW interface for automated comprehensive analyses of promoter regulatory motifs and the effect they exert on mRNA expression profiles. The server provides a wide spectrum of analysis tools that allow de novo discovery of regulatory motifs, along with refinement and in-depth investigation of fully or partially characterized motifs. The presented discovery and analysis tools are fundamentally different from existing tools in their basic rational, statistical background and specificity and sensitivity towards true regulatory elements. We thus anticipate that the service will be of great importance to the experimental and computational biology communities alike. The motif discovery and diagnosis workbench is available at http://longitude.weizmann.ac.il/rMotif/.

Internet↗
PubMed2002

Computational identification of transcription factor binding sites via a transcription-factor-centric clustering (TFCC) algorithm.

While microarray-based expression profiling has facilitated the use of computational methods to find potential cis-regulatory promoter elements, few current in silico approaches explicitly link regulatory motifs with the transcription factors that bind them. We have thus developed a TF-centric clustering (TFCC) algorithm that may provide such missing information through incorporation of biological knowledge about TFs. TFCC is a semi-supervised clustering algorithm which relies on the assumption that the expression profiles of some TFs may be related to those of the genes under their control. We examined this premise and found the vicinities of TFs in expression space are often enriched with the genes they regulate. So, instead of clustering genes based on the mutual similarity of their expression profiles to each other, we used TFs as seeds to group together genes whose expression patterns correlate with that of a particular TF. Then a Gibbs sampling algorithm was applied to search for shared cis-regulatory elements in promoters of clustered genes. Our working hypothesis was that if a TF-centric cluster indeed contains many targets of the seeding TF, at least one of the discovered motifs would be the site bound by the very same TF. We tested the TFCC approach on eight cell cycle and sporulation regulating TFs whose binding sites have been previously characterized in Saccharomyces cerevisiae, and correctly identified binding site motifs for half of them. In addition, we also made de novo predictions for some unknown TF binding sites.

Algorithms↗
PubMed2002

Discrimination between paralogs using microarray analysis: application to the Yap1p and Yap2p transcriptional networks.

Ohno [Ohno, S. (1970) in Evolution by Gene Duplication, Springer, New York] proposed that gene duplication with subsequent divergence of paralogs could be a major force in the evolution of new gene functions. In practice the functional differences between closely related homologues produced by duplications can be subtle and difficult to separate experimentally. Here we show that DNA microarrays can distinguish the functions of two closely related homologues from the yeast Saccharomyces cerevisiae, Yap1p and Yap2p. Although Yap1p and Yap2p are both bZIP transcription factors involved in multiple stress responses and are 88% identical in their DNA binding domains, our work shows that these proteins activate nonoverlapping sets of genes. Yap1p controls a set of genes involved in detoxifying the effects of reactive oxygen species, whereas Yap2p controls a set of genes over represented for the function of stabilizing proteins. In addition we show that the binding sites in the promoters of the Yap1p-dependent genes differ from the sites in the promoters of Yap2p-dependent genes and we validate experimentally that these differences are important for regulation by Yap1p. We conclude that while Yap1p and Yap2p may have some overlapping functions they are clearly not redundant and, more generally, that DNA microarray analysis will be an important tool for distinguishing the functions of the large numbers of highly conserved genes found in all eukaryotic genomes.

Cadmium↗
PubMed2002

Genome-wide co-occurrence of promoter elements reveals a cis-regulatory cassette of rRNA transcription motifs in Saccharomyces cerevisiae.

Combinatorial regulation is an important feature of eukaryotic transcription. However, only a limited number of studies have characterized this aspect on a whole-genome level. We have conducted a genome-wide computational survey to identify cis-regulatory motif pairs that co-occur in a significantly high number of promoters in the S. cerevisiae genome. A pair of novel motifs, mRRPE and PAC, co-occur most highly in the genome, primarily in the promoters of genes involved in rRNA transcription and processing. The two motifs show significant positional and orientational bias with mRRPE being closer to the ATG than PAC in most promoters. Two additional rRNA-related motifs, mRRSE3 and mRRSE10, also co-occur with mRRPE and PAC. mRRPE and PAC are the primary determinants of expression profiles while mRRSE3 and mRRSE10 modulate these patterns. We describe a new computational approach for studying the functional significance of the physical locations of promoter elements that combine analyses of genome sequence and microarray data. Applying this methodology to the regulatory cassette containing the four rRNA motifs demonstrates that the relative promoter locations of these elements have a profound effect on the expression patterns of the downstream genes. These findings provide a function for these novel motifs and insight into the mechanism by which they regulate gene expression. The methodology introduced here should prove particularly useful for analyzing transcriptional regulation in more complex genomes.

Base Composition↗