Michal Ronen

Bio: Michal Ronen is an academic researcher from Weizmann Institute of Science. The author has contributed to research in topics: Operon & Gene. The author has an hindex of 6, co-authored 6 publications receiving 1981 citations.

A comprehensive library of fluorescent transcriptional reporters for Escherichia coli

Abstract: E. coli is widely used for systems biology research; there exists a need, however, for tools that can be used to accurately and comprehensively measure expression dynamics in individual living cells. To address this we present a library of transcriptional fusions of gfp to each of about 2,000 different promoters in E. coli K12, covering the great majority of the promoters in the organism. Each promoter fusion is expressed from a low-copy plasmid. We demonstrate that this library can be used to obtain highly accurate dynamic measurements of promoter activity on a genomic scale, in a glucose-lactose diauxic shift experiment. The library allowed detection of about 80 previously uncharacterized transcription units in E. coli, including putative internal promoters within previously known operons, such as the lac operon. This library can serve as a tool for accurate, high-resolution analysis of transcription networks in living E. coli cells.

Assigning numbers to the arrows: parameterizing a gene regulation network by using accurate expression kinetics.

Abstract: A basic challenge in systems biology is to understand the dynamical behavior of gene regulation networks. Current approaches aim at determining the network structure based on genomic-scale data. However, the network connectivity alone is not sufficient to define its dynamics; one needs to also specify the kinetic parameters for the regulation reactions. Here, we ask whether effective kinetic parameters can be assigned to a transcriptional network based on expression data. We present a combined experimental and theoretical approach based on accurate high temporal-resolution measurement of promoter activities from living cells by using green fluorescent protein (GFP) reporter plasmids. We present algorithms that use these data to assign effective kinetic parameters within a mathematical model of the network. To demonstrate this, we employ a well defined network, the SOS DNA repair system of Escherichia coli. We find a strikingly detailed temporal program of expression that correlates with the functional role of the SOS genes and is driven by a hierarchy of effective kinetic parameter strengths for the various promoters. The calculated parameters can be used to determine the kinetics of all SOS genes given the expression profile of just one representative, allowing a significant reduction in complexity. The concentration profile of the master SOS transcriptional repressor can be calculated, demonstrating that relative protein levels may be determined from purely transcriptional data. This finding opens the possibility of assigning kinetic parameters to transcriptional networks on a genomic scale.

Ordering genes in a flagella pathway by analysis of expression kinetics from living bacteria

Abstract: The recent advances in large-scale monitoring of gene expression raise the challenge of mapping systems on the basis of kinetic expression data in living cells. To address this, we measured promoter activity in the flagellar system of Escherichia coli at high accuracy and temporal resolution by means of reporter plasmids. The genes in the pathway were ordered by analysis algorithms without dependence on mutant strains. The observed temporal program of transcription was much more detailed than was previously thought and was associated with multiple steps of flagella assembly.

A conserved role for a GATA transcription factor in regulating epithelial innate immune responses

Abstract: Innate immunity is an ancient and conserved defense mechanism. Although host responses toward various pathogens have been delineated, how these responses are orchestrated in a whole animal is less understood. Through an unbiased genome-wide study performed in Caenorhabditis elegans, we identified a conserved function for endodermal GATA transcription factors in regulating local epithelial innate immune responses. Gene expression and functional RNAi-based analyses identified the tissue-specific GATA transcription factor ELT-2 as a major regulator of an early intestinal protective response to infection with the human bacterial pathogen Pseudomonas aeruginosa. In the adult worm, ELT-2 is required specifically for infection responses and survival on pathogen but makes no significant contribution to gene expression associated with intestinal maintenance or to resistance to cadmium, heat, and oxidative stress. We further demonstrate that this function is conserved, because the human endodermal transcription factor GATA6 has a protective function in lung epithelial cells exposed to P. aeruginosa. These findings expand the repertoire of innate immunity mechanisms and illuminate a yet-unknown function of endodermal GATA proteins.

Precise Temporal Modulation in the Response of the SOS DNA Repair Network in Individual Bacteria

Abstract: The SOS genetic network is responsible for the repair/bypass of DNA damage in bacterial cells. While the initial stages of the response have been well characterized, less is known about the dynamics of the response after induction and its shutoff. To address this, we followed the response of the SOS network in living individual Escherichia coli cells. The promoter activity (PA) of SOS genes was monitored using fluorescent protein-promoter fusions, with high temporal resolution, after ultraviolet irradiation activation. We find a temporal pattern of discrete activity peaks masked in studies of cell populations. The number of peaks increases, while their amplitude reaches saturation, as the damage level is increased. Peak timing is highly precise from cell to cell and is independent of the stage in the cell cycle at the time of damage. Evidence is presented for the involvement of the umuDC operon in maintaining the pattern of PA and its temporal precision, providing further evidence for the role UmuD cleavage plays in effecting a timed pause during the SOS response, as previously proposed. The modulations in PA we observe share many features in common with the oscillatory behavior recently observed in a mammalian DNA damage response. Our results, which reveal a hitherto unknown modulation of the SOS response, underscore the importance of carrying out dynamic measurements at the level of individual living cells in order to unravel how a natural genetic network operates at the systems level.

“Bioinformatics” 특집을 내면서

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Network motifs in the transcriptional regulation network of Escherichia coli

Abstract: Little is known about the design principles1,2,3,4,5,6,7,8,9,10 of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis2,11,12, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams1,2,3,4,5,6,7,8,9,10,13, we sought to break down such networks into basic building blocks2. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli3,6. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.

Network motifs: theory and experimental approaches

Abstract: Transcription regulation networks control the expression of genes. The transcription networks of well-studied microorganisms appear to be made up of a small set of recurring regulation patterns, called network motifs. The same network motifs have recently been found in diverse organisms from bacteria to humans, suggesting that they serve as basic building blocks of transcription networks. Here I review network motifs and their functions, with an emphasis on experimental studies. Network motifs in other biological networks are also mentioned, including signalling and neuronal networks.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

How antibiotics kill bacteria: from targets to networks

Abstract: Antibiotic drug-target interactions, and their respective direct effects, are generally well characterized. By contrast, the bacterial responses to antibiotic drug treatments that contribute to cell death are not as well understood and have proven to be complex as they involve many genetic and biochemical pathways. In this Review, we discuss the multilayered effects of drug-target interactions, including the essential cellular processes that are inhibited by bactericidal antibiotics and the associated cellular response mechanisms that contribute to killing. We also discuss new insights into these mechanisms that have been revealed through the study of biological networks, and describe how these insights, together with related developments in synthetic biology, could be exploited to create new antibacterial therapies.