Showing papers in "Molecular Systems Biology in 2006"
TL;DR: These mutants—the ‘Keio collection’—provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome‐wide testing of mutational effects in a common strain background, E. coli K‐12 BW25113.
Abstract: We have systematically made a set of precisely defined, single-gene deletions of all nonessential genes in Escherichia coli K-12. Open-reading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a one-step method for inactivation of chromosomal genes and primers designed to create in-frame deletions upon excision of the resistance cassette. Of 4288 genes targeted, mutants were obtained for 3985. To alleviate problems encountered in high-throughput studies, two independent mutants were saved for every deleted gene. These mutants-the 'Keio collection'-provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome-wide testing of mutational effects in a common strain background, E. coli K-12 BW25113. We were unable to disrupt 303 genes, including 37 of unknown function, which are candidates for essential genes. Distribution is being handled via GenoBase (http://ecoli.aist-nara.ac.jp/).
7,428 citations
TL;DR: The basic features of synthetic biology as a new engineering discipline are outlined, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields.
Abstract: Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.
1,077 citations
TL;DR: A view of the extensive variability of the behavior of a protein circuit in living human cells, both from cell to cell and in the same cell over time is provided.
Abstract: Understanding the dynamics and variability of protein circuitry requires accurate measurements in living cells as well as theoretical models. To address this, we employed one of the best-studied protein circuits in human cells, the negative feedback loop between the tumor suppressor p53 and the oncogene Mdm2. We measured the dynamics of fluorescently tagged p53 and Mdm2 over several days in individual living cells. We found that isogenic cells in the same environment behaved in highly variable ways following DNA-damaging gamma irradiation: some cells showed undamped oscillations for at least 3 days (more than 10 peaks). The amplitude of the oscillations was much more variable than the period. Sister cells continued to oscillate in a correlated way after cell division, but lost correlation after about 11 h on average. Other cells showed low-frequency fluctuations that did not resemble oscillations. We also analyzed different families of mathematical models of the system, including a novel checkpoint mechanism. The models point to the possible source of the variability in the oscillations: low-frequency noise in protein production rates, rather than noise in other parameters such as degradation rates. This study provides a view of the extensive variability of the behavior of a protein circuit in living human cells, both from cell to cell and in the same cell over time.
659 citations
TL;DR: Direct DNA sequencing of PCR products for the 251 regions with short indel and base disparities revealed that only eight sites are true differences, and errors in the original MG1655 sequence were mostly within portions sequenced with out‐dated technology based on radioactive chemistry.
Abstract: With the goal of solving the whole-cell problem with Escherichia coli K-12 as a model cell, highly accurate genomes were determined for two closely related K-12 strains, MG1655 and W3110. Completion of the W3110 genome and comparison with the MG1655 genome revealed differences at 267 sites, including 251 sites with short, mostly single-nucleotide, insertions or deletions (indels) or base substitutions (totaling 358 nucleotides), in addition to 13 sites with an insertion sequence element or defective prophage in only one strain and two sites for the W3110 inversion. Direct DNA sequencing of PCR products for the 251 regions with short indel and base disparities revealed that only eight sites are true differences. The other 243 discrepancies were due to errors in the original MG1655 sequence, including 79 frameshifts, one amino-acid residue deletion, five amino-acid residue insertions, 73 missense, and 17 silent changes within coding regions. Errors in the original MG1655 sequence (<1 per 13 000 bases) were mostly within portions sequenced with out-dated technology based on radioactive chemistry.
515 citations
TL;DR: Analysis of the three‐loop network suggests that the plant clock consists of morning and evening oscillators, coupled intracellularly, which may be analogous to coupled, morning and Evening clock cells in Drosophila and the mouse.
Abstract: Our computational model of the circadian clock comprised the feedback loop between LATE ELONGATED HYPOCOTYL (LHY), CIRCADIAN CLOCK ASSOCIATED 1 (CCA1) and TIMING OF CAB EXPRESSION 1 (TOC1), and a predicted, interlocking feedback loop involving TOC1 and a hypothetical component Y. Experiments based on model predictions suggested GIGANTEA (GI) as a candidate for Y. We now extend the model to include a recently demonstrated feedback loop between the TOC1 homologues PSEUDO-RESPONSE REGULATOR 7 (PRR7), PRR9 and LHY and CCA1. This three-loop network explains the rhythmic phenotype of toc1 mutant alleles. Model predictions fit closely to new data on the gi;lhy;cca1 mutant, which confirm that GI is a major contributor to Y function. Analysis of the three-loop network suggests that the plant clock consists of morning and evening oscillators, coupled intracellularly, which may be analogous to coupled, morning and evening clock cells in Drosophila and the mouse.
457 citations
TL;DR: This work details building blocks already in place and major hurdles to overcome for completion of a minimal cell project, which would initially define the components sufficient for each subsystem, allow detailed kinetic analyses and lead to improved in vitro methods for synthesis of biopolymers, therapeutics and biosensors.
Abstract: Construction of a chemical system capable of replication and evolution, fed only by small molecule nutrients, is now conceivable. This could be achieved by stepwise integration of decades of work on the reconstitution of DNA, RNA and protein syntheses from pure components. Such a minimal cell project would initially define the components sufficient for each subsystem, allow detailed kinetic analyses and lead to improved in vitro methods for synthesis of biopolymers, therapeutics and biosensors. Completion would yield a functionally and structurally understood self-replicating biosystem. Safety concerns for synthetic life will be alleviated by extreme dependence on elaborate laboratory reagents and conditions for viability. Our proposed minimal genome is 113 kbp long and contains 151 genes. We detail building blocks already in place and major hurdles to overcome for completion.
408 citations
TL;DR: A comprehensive map of TLRs and interleukin 1 receptor signaling networks based on papers published so far is presented, illustrating the possible existence of a main network subsystem that has a bow‐tie structure in which myeloid differentiation primary response gene 88 (MyD88) is a nonredundant core element, two collateral subsystems with small GTPase and phosphatidylinositol signaling, and MyD88‐independent pathway.
Abstract: Recognition of pathogen-associated molecular signatures is critically important in proper activation of the immune system. The toll-like receptor (TLR) signaling network is responsible for innate immune response. In mammalians, there are 11 TLRs that recognize a variety of ligands from pathogens to trigger immunological responses. In this paper, we present a comprehensive map of TLRs and interleukin 1 receptor signaling networks based on papers published so far. The map illustrates the possible existence of a main network subsystem that has a bow-tie structure in which myeloid differentiation primary response gene 88 (MyD88) is a nonredundant core element, two collateral subsystems with small GTPase and phosphatidylinositol signaling, and MyD88-independent pathway. There is extensive crosstalk between the main bow-tie network and subsystems, as well as feedback and feedforward controls. One obvious feature of this network is the fragility against removal of the nonredundant core element, which is MyD88, and involvement of collateral subsystems for generating different reactions and gene expressions for different stimuli.
385 citations
TL;DR: Systems biology is certain to have in future a major role in both the development of personalized medicine and in molecular epidemiological studies.
Abstract: Mol Syst Biol. 2: 52
One of the great challenges for 21st century medicine is to deliver effective therapies that are tailored to the exact biology or biological state of an individual to enable so‐called ‘personalized healthcare solutions’. Ideally, this would involve a system of patient evaluation that would tell clinicians the correct drug, dose or intervention for any individual before the start of therapy. A practical approach to this evaluation is the concept of patient stratification in which individuals are biologically subclassified (classically according to some genetic features) and biofeatures modelled in relation to outcome. In principle, such stratification for personalized therapy can be applied to drug safety and efficacy modelling and to more general healthcare paradigms involving optimized nutrition and lifestyle management.
Of course, truly personalized treatments, even if they can be developed and applied widely, will lamentably always be a luxury of the worlds' richest citizens and nations. So in some respects, personalized healthcare might appear to be at the opposite end of the medical spectrum to the subject of epidemiology in which disease risk factors and disease incidence are studied in populations rich and poor alike. Systems biology provides us with a common language for both describing and modelling the integrated action of regulatory networks at many levels of biological organization from the subcellular through cell, tissue and organ right up to the whole organism. The relatively new science of molecular epidemiology concerns the measurement of the fundamental biochemical factors that underlie population disease demography and understanding ‘the health of nations’ and this subject naturally lends it to systems biology approaches. Hence, systems biology is certain to have in future a major role in both the development of personalized medicine and in molecular epidemiological studies.
Populations are, of course, made up of individuals and, in …
379 citations
TL;DR: In this paper, the authors analyzed the interactions between miRNAs and a human cellular signaling network and found that miRNs predominantly target positive regulatory motifs, highly connected scaffolds and most downstream network components such as signaling transcription factors, but less frequently target negative regulatory motif, common components of basic cellular machines and most upstream network components, such as ligands.
Abstract: MicroRNAs (miRNAs) are endogenous ∼22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3′-noncoding region of specific messenger RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs appear to functionally interact with various components of many cellular networks. By analyzing the interactions between miRNAs and a human cellular signaling network, we found that miRNAs predominantly target positive regulatory motifs, highly connected scaffolds and most downstream network components such as signaling transcription factors, but less frequently target negative regulatory motifs, common components of basic cellular machines and most upstream network components such as ligands. In addition, when an adaptor has potential to recruit more downstream components, these components are more frequently targeted by miRNAs. This work uncovers the principles of miRNA regulation of signal transduction networks and implies a potential function of miRNAs for facilitating robust transitions of cellular response to extracellular signals and maintaining cellular homeostasis.
337 citations
TL;DR: Construction of larger synthetic circuits provides a unique opportunity for evaluating model inference, prediction, and design of complex biochemical systems and could be used to control nanoscale devices and artificial cells.
Abstract: Information processing using biochemical circuits is essential for survival and reproduction of natural organisms. As stripped-down analogs of genetic regulatory networks in cells, we engineered artificial transcriptional networks consisting of synthetic DNA switches, regulated by RNA signals acting as transcription repressors, and two enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H. The synthetic switch design is modular with programmable connectivity and allows dynamic control of RNA signals through enzyme-mediated production and degradation. The switches support sharp and adjustable thresholds using a competitive hybridization mechanism, allowing arbitrary analog or digital circuits to be created in principle. As an example, we constructed an in vitro bistable memory by wiring together two synthetic switches and performed a systematic quantitative characterization. Good agreement between experimental data and a simple mathematical model was obtained for switch input/output functions, phase plane trajectories, and the bifurcation diagram for bistability. Construction of larger synthetic circuits provides a unique opportunity for evaluating model inference, prediction, and design of complex biochemical systems and could be used to control nanoscale devices and artificial cells.
315 citations
TL;DR: It is proposed that centrally conserved residues, whose removal increases the characteristic path length in protein networks, may relate to the system fragility.
Abstract: Here, we represent protein structures as residue interacting networks, which are assumed to involve a permanent flow of information between amino acids. By removal of nodes from the protein network, we identify fold centrally conserved residues, which are crucial for sustaining the shortest pathways and thus play key roles in long-range interactions. Analysis of seven protein families (myoglobins, G-protein-coupled receptors, the trypsin class of serine proteases, hemoglobins, oligosaccharide phosphorylases, nuclear receptor ligand-binding domains and retroviral proteases) confirms that experimentally many of these residues are important for allosteric communication. The agreement between the centrally conserved residues, which are key in preserving short path lengths, and residues experimentally suggested to mediate signaling further illustrates that topology plays an important role in network communication. Protein folds have evolved under constraints imposed by function. To maintain function, protein structures need to be robust to mutational events. On the other hand, robustness is accompanied by an extreme sensitivity at some crucial sites. Thus, here we propose that centrally conserved residues, whose removal increases the characteristic path length in protein networks, may relate to the system fragility.
TL;DR: Network‐embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model‐based analysis of large‐scale quantitative metabolomics data and represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data.
Abstract: As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data.
TL;DR: Simulations of the circuits indicate that the main source of noise in these circuits could come from plasmid variation and therefore that negative feedback loops play an important role in suppressing both external and internal noise.
Abstract: Negative feedback loops have been invoked as a way to control and decrease transcriptional noise. Here, we have built three circuits to test the effect of negative feedback loops on transcriptional noise of an autoregulated gene encoding a transcription factor (TF) and a downstream gene (DG), regulated by this TF. Experimental analysis shows that self-repression decreases noise compared to expression from a non-regulated promoter. Interestingly enough, we find that noise minimization by negative feedback loop is optimal within a range of repression strength. Repression values outside this range result in noise increase producing a U-shaped behaviour. This behaviour is the result of external noise probably arising from plasmid fluctuations as shown by simulation of the network. Regarding the target gene of a self-repressed TF (sTF), we find a strong decrease of noise when repression by the sTF is strong and a higher degree of noise anti-correlation between sTF and its target. Simulations of the circuits indicate that the main source of noise in these circuits could come from plasmid variation and therefore that negative feedback loops play an important role in suppressing both external and internal noise. An important observation is that DG expression without negative feedback exhibits bimodality at intermediate TF repression values. This bimodal behaviour seems to be the result of external noise as it can only be found in those simulations that include plasmid variation.
TL;DR: This work demonstrates that a reconstructed metabolic network can serve as an analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation and further uncover the metabolic characteristics of methanogenesis.
Abstract: We present a genome-scale metabolic model for the archaeal methanogen Methanosarcina barkeri. We characterize the metabolic network and compare it to reconstructions from the prokaryotic, eukaryotic and archaeal domains. Using the model in conjunction with constraint-based methods, we simulate the metabolic fluxes and resulting phenotypes induced by different environmental and genetic conditions. This represents the first large-scale simulation of either a methanogen or an archaeal species. Model predictions are validated by comparison to experimental growth measurements and phenotypes of M. barkeri on different substrates. The predicted growth phenotypes for wild type and mutants of the methanogenic pathway have a high level of agreement with experimental findings. We further examine the efficiency of the energy-conserving reactions in the methanogenic pathway, specifically the Ech hydrogenase reaction, and determine a stoichiometry for the nitrogenase reaction. This work demonstrates that a reconstructed metabolic network can serve as an analysis platform to predict cellular phenotypes, characterize methanogenic growth, improve the genome annotation and further uncover the metabolic characteristics of methanogenesis.
TL;DR: This work proposes candidate models based on experimental hypotheses and identifies the computational models with the application of an optimization routine and introduces and applies sensitivity analysis as a novel tool for analyzing and distinguishing the characteristics of proposed architectures, which also allows for further validation of the hypothesized structures.
Abstract: In plants, as in animals, the core mechanism to retain rhythmic gene expression relies on the interaction of multiple feedback loops. In recent years, molecular genetic techniques have revealed a complex network of clock components in Arabidopsis. To gain insight into the dynamics of these interactions, new components need to be integrated into the mathematical model of the plant clock. Our approach accelerates the iterative process of model identification, to incorporate new components, and to systematically test different proposed structural hypotheses. Recent studies indicate that the pseudo-response regulators PRR7 and PRR9 play a key role in the core clock of Arabidopsis. We incorporate PRR7 and PRR9 into an existing model involving the transcription factors TIMING OF CAB (TOC1), LATE ELONGATED HYPOCOTYL (LHY) and CIRCADIAN CLOCK ASSOCIATED (CCA1). We propose candidate models based on experimental hypotheses and identify the computational models with the application of an optimization routine. Validation is accomplished through systematic analysis of various mutant phenotypes. We introduce and apply sensitivity analysis as a novel tool for analyzing and distinguishing the characteristics of proposed architectures, which also allows for further validation of the hypothesized structures.
TL;DR: Analysis of dynamic effects of HER2 overexpression on phosphotyrosine signaling in human mammary epithelial cells stimulated by epidermal growth factor (EGF) or heregulin (HRG) reveals that EGF stimulation of Her2‐overexpressing cells activates multiple signaling pathways to stimulate migration, whereas HRG stimulation of these cells results in amplification of a specific subset of the migration signaling network.
Abstract: Although human epidermal growth factor receptor 2 (HER2) overexpression is implicated in tumor progression for a variety of cancer types, how it dysregulates signaling networks governing cell behavioral functions is poorly understood. To address this problem, we use quantitative mass spectrometry to analyze dynamic effects of HER2 overexpression on phosphotyrosine signaling in human mammary epithelial cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). Data generated from this analysis reveal that EGF stimulation of HER2-overexpressing cells activates multiple signaling pathways to stimulate migration, whereas HRG stimulation of these cells results in amplification of a specific subset of the migration signaling network. Self-organizing map analysis of the phosphoproteomic data set permitted elucidation of network modules differentially regulated in HER2-overexpressing cells in comparison with parental cells for EGF and HRG treatment. Partial least-squares regression analysis of the same data set identified quantitative combinations of signals within the networks that strongly correlate with cell proliferation and migration measured under the same battery of conditions. Combining these modeling approaches enabled association of epidermal growth factor receptor family dimerization to activation of specific phosphorylation sites, which appear to most critically regulate proliferation and/or migration.
TL;DR: An experimental method based on parallel exposure of cells to diverse combinations of extracellular signals followed by quantitative, multi‐parameter analysis of cellular responses revealed interactions more complex than previously envisaged including dominance relations that may reflect a cell‐intrinsic system for robust specification of responses in complex microenvironments.
Abstract: Cells of a developing embryo integrate a complex array of local and long-range signals that act in concert with cell-intrinsic determinants to influence developmental decisions. To systematically investigate the effects of molecular microenvironments on cell fate decisions, we developed an experimental method based on parallel exposure of cells to diverse combinations of extracellular signals followed by quantitative, multi-parameter analysis of cellular responses. Primary human neural precursor cells were captured and cultured on printed microenvironment arrays composed of mixtures of extracellular matrix components, morphogens, and other signaling proteins. Quantitative single cell analysis revealed striking effects of some of these signals on the extent and direction of differentiation. We found that Wnt and Notch co-stimulation could maintain the cells in an undifferentiated-like, proliferative state, whereas bone morphogenetic protein 4 induced an ‘indeterminate' differentiation phenotype characterized by simultaneous expression of glial and neuronal markers. Multi-parameter analysis of responses to conflicting signals revealed interactions more complex than previously envisaged including dominance relations that may reflect a cell-intrinsic system for robust specification of responses in complex microenvironments.
TL;DR: It is found that hepatocyte master regulators tend to bind promoter regions combinatorially and that the number of transcription factors bound to a promoter corresponds with observed gene expression.
Abstract: We mapped the transcriptional regulatory circuitry for six master regulators in human hepatocytes using chromatin immunoprecipitation and high-resolution promoter microarrays. The results show that these regulators form a highly interconnected core circuitry, and reveal the local regulatory network motifs created by regulator–gene interactions. Autoregulation was a prominent theme among these regulators. We found that hepatocyte master regulators tend to bind promoter regions combinatorially and that the number of transcription factors bound to a promoter corresponds with observed gene expression. Our studies reveal portions of the core circuitry of human hepatocytes.
TL;DR: The short‐term dynamics of the transcriptome revealed a remarkably fast decrease in the average half‐life of downregulated genes, which can be interpreted both as an additional nucleotide salvage pathway and an additional level of glucose‐induced regulation of gene expression.
Abstract: Within the first 5 min after a sudden relief from glucose limitation, Saccharomyces cerevisiae exhibited fast changes of intracellular metabolite levels and a major transcriptional reprogramming. Integration of transcriptome and metabolome data revealed tight relationships between the changes at these two levels. Transcriptome as well as metabolite changes reflected a major investment in two processes: adaptation from fully respiratory to respiro-fermentative metabolism and preparation for growth acceleration. At the metabolite level, a severe drop of the AXP pools directly after glucose addition was not accompanied by any of the other three NXP. To counterbalance this loss, purine biosynthesis and salvage pathways were transcriptionally upregulated in a concerted manner, reflecting a sudden increase of the purine demand. The short-term dynamics of the transcriptome revealed a remarkably fast decrease in the average half-life of downregulated genes. This acceleration of mRNA decay can be interpreted both as an additional nucleotide salvage pathway and an additional level of glucose-induced regulation of gene expression.
TL;DR: A unifying theme of many recent studies has been a focus on the development and utilization of single‐cell experimental techniques that are capable of probing key biological phenomena in individual living cells.
Abstract: Cellular behavior has traditionally been investigated by utilizing bulk-scale methods that measure average values for a population of cells. Such population-wide studies mask the behavior of individual cells and are often insufficient for characterizing biological processes in which cellular heterogeneity plays a key role. A unifying theme of many recent studies has been a focus on the development and utilization of single-cell experimental techniques that are capable of probing key biological phenomena in individual living cells. Recently, novel information about gene expression dynamics has been obtained from single-cell experiments that draw upon the unique capabilities of fluorescent reporter proteins.
TL;DR: A novel approach for elucidating the potential pathways of allosteric communication in biomolecular systems, based on Markov propagation of ‘information’ across the structure, and proposes two most likely pathways of signal transmission, between nucleotide‐ and GroES‐binding sites across the cis and trans rings, which involve several conserved residues.
Abstract: We introduce a novel approach for elucidating the potential pathways of allosteric communication in biomolecular systems. The methodology, based on Markov propagation of ‘information’ across the structure, permits us to partition the network of interactions into soft clusters distinguished by their coherent stochastics. Probabilistic participation of residues in these clusters defines the communication patterns inherent to the network architecture. Application to bacterial chaperonin complex GroEL–GroES, an allostery-driven structure, identifies residues engaged in intra- and intersubunit communication, including those acting as hubs and messengers. A number of residues are distinguished by their high potentials to transmit allosteric signals, including Pro33 and Thr90 at the nucleotide-binding site and Glu461 and Arg197 mediating inter- and intra-ring communication, respectively. We propose two most likely pathways of signal transmission, between nucleotideand GroES-binding sites across the cis and trans rings, which involve several conserved residues. A striking observation is the opposite direction of information flow within cis and trans rings, consistent with negative inter-ring cooperativity. Comparison with collective modes deduced from normal mode analysis reveals the propensity of global hinge regions to act as messengers in the
TL;DR: Comparison of transcript and protein levels clearly showed that upregulation in response to glucose limitation was mainly transcriptionally controlled, whereas upregulationIn response to nitrogen limitation was essentially controlled at the post‐transcriptional level by increased translational efficiency and/or decreased protein degradation.
Abstract: We compared the response of Saccharomyces cerevisiae to carbon (glucose) and nitrogen (ammonia) limitation in chemostat cultivation at the proteome level. Protein levels were differentially quantified using unlabeled and 15N metabolically labeled yeast cultures. A total of 928 proteins covering a wide range of isoelectric points, molecular weights and subcellular localizations were identified. Stringent statistical analysis identified 51 proteins upregulated in response to glucose limitation and 51 upregulated in response to ammonia limitation. Under glucose limitation, typical glucose-repressed genes encoding proteins involved in alternative carbon source utilization, fatty acids β-oxidation and oxidative phosphorylation displayed an increased protein level. Proteins upregulated in response to nitrogen limitation were mostly involved in scavenging of alternative nitrogen sources and protein degradation. Comparison of transcript and protein levels clearly showed that upregulation in response to glucose limitation was mainly transcriptionally controlled, whereas upregulation in response to nitrogen limitation was essentially controlled at the post-transcriptional level by increased translational efficiency and/or decreased protein degradation. These observations underline the need for multilevel analysis in yeast systems biology.
TL;DR: This method can not only identify the function of unknown genes but can also suggest the mechanism of action of the agents used and will be useful when used alone and in conjunction with other global approaches to identify gene function in yeast.
Abstract: We present a method for the global analysis of the function of genes in budding yeast based on hierarchical clustering of the quantitative sensitivity profiles of the 4756 strains with individual homozygous deletion of nonessential genes to a broad range of cytotoxic or cytostatic agents. This method is superior to other global methods of identifying the function of genes involved in the various DNA repair and damage checkpoint pathways as well as other interrogated functions. Analysis of the phenotypic profiles of the 51 diverse treatments places a total of 860 genes of unknown function in clusters with genes of known function. We demonstrate that this can not only identify the function of unknown genes but can also suggest the mechanism of action of the agents used. This method will be useful when used alone and in conjunction with other global approaches to identify gene function in yeast.
TL;DR: There were interstrain similarities in N regulation such as the activation of a putative NtcA regulon during N stress and important differences between the strains such as in the expression patterns of carbon metabolism genes, suggesting that the two strains integrate N and C metabolism in fundamentally different ways.
Abstract: Nitrogen (N) often limits biological productivity in the oceanic gyres where Prochlorococcus is the most abundant photosynthetic organism. The Prochlorococcus community is composed of strains, such as MED4 and MIT9313, that have different N utilization capabilities and that belong to ecotypes with different depth distributions. An interstrain comparison of how Prochlorococcus responds to changes in ambient nitrogen is thus central to understanding its ecology. We quantified changes in MED4 and MIT9313 global mRNA expression, chlorophyll fluorescence, and photosystem II photochemical efficiency (Fv/Fm) along a time series of increasing N starvation. In addition, the global expression of both strains growing in ammonium-replete medium was compared to expression during growth on alternative N sources. There were interstrain similarities in N regulation such as the activation of a putative NtcA regulon during N stress. There were also important differences between the strains such as in the expression patterns of carbon metabolism genes, suggesting that the two strains integrate N and C metabolism in fundamentally different ways.
TL;DR: The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations, and shows that it is possible to infer whether the reactions are hierarchically or metabolically regulated.
Abstract: Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from Saccharomyces cerevisiae. The algorithm includes preprocessing of a genome-scale yeast model such that the fraction of measured metabolites within the model is enhanced, and thus it is possible to map significant alterations associated with a perturbation even though a small fraction of the complete metabolome is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through combination of metabolome and transcriptome data.
TL;DR: It is argued that the network of molecular interactions involved in immune functions has a bow‐tie architecture that entails inherent trade‐offs among robustness, fragility, resource limitation, and performance and the possibility that commensal bacteria and the host immune system constitute an integrated defense system.
Abstract: The immune system provides organisms with robustness against pathogen threats, yet it also often adversely affects the organism as in autoimmune diseases. Recently, the molecular interactions involved in the immune system have been uncovered. At the same time, the role of the bacterial flora and its interactions with the host immune system have been identified. In this article, we try to reconcile these findings to draw a consistent picture of the host defense system. Specifically, we first argue that the network of molecular interactions involved in immune functions has a bow-tie architecture that entails inherent trade-offs among robustness, fragility, resource limitation, and performance. Second, we discuss the possibility that commensal bacteria and the host immune system constitute an integrated defense system. This symbiotic association has evolved to optimize its robustness against pathogen attacks and nutrient perturbations by harboring a broad range of microorganisms. Owing to the inherent propensity of a host immune system toward hyperactivity, maintenance of bacterial flora homeostasis might be particularly important in the development of preventive strategies against immune disorders such as autoimmune diseases.
TL;DR: In this article, the authors carried out an exhaustive computational analysis on network topologies in relation to a patterning function in Drosophila embryogenesis and found that a small fraction of topologies emerged as particularly robust for the function.
Abstract: Biomolecular networks have to perform their functions robustly. A robust function may have preferences in the topological structures of the underlying network. We carried out an exhaustive computational analysis on network topologies in relation to a patterning function in Drosophila embryogenesis. We found that whereas the vast majority of topologies can either not perform the required function or only do so very fragilely, a small fraction of topologies emerges as particularly robust for the function. The topology adopted by Drosophila, that of the segment polarity network, is a top ranking one among all topologies with no direct autoregulation. Furthermore, we found that all robust topologies are modular—each being a combination of three kinds of modules. These modules can be traced back to three subfunctions of the patterning function, and their combinations provide a combinatorial variability for the robust topologies. Our results suggest that the requirement of functional robustness drastically reduces the choices of viable topology to a limited set of modular combinations among which nature optimizes its choice under evolutionary and other biological constraints.
TL;DR: Using quantitative data from synaptic plasticity experiments, the model correctly predicts robustness to mutations and drug interference and suggests that molecular networks with simple design principles underpin synaptic signalling properties with important roles in physiology, behaviour and disease.
Abstract: Neuronal synapses play fundamental roles in information processing, behaviour and disease. Neurotransmitter receptor complexes, such as the mammalian N-methyl-D-aspartate receptor complex (NRC/MASC) comprising 186 proteins, are major components of the synapse proteome. Here we investigate the organisation and function of NRC/MASC using a systems biology approach. Systematic annotation showed that the complex contained proteins implicated in a wide range of cognitive processes, synaptic plasticity and psychiatric diseases. Protein domains were evolutionarily conserved from yeast, but enriched with signalling domains associated with the emergence of multicellularity. Mapping of protein–protein interactions to create a network representation of the complex revealed that simple principles underlie the functional organisation of both proteins and their clusters, with modularity reflecting functional specialisation. The known functional roles of NRC/MASC proteins suggest the complex co-ordinates signalling to diverse effector pathways underlying neuronal plasticity. Importantly, using quantitative data from synaptic plasticity experiments, our model correctly predicts robustness to mutations and drug interference. These studies of synapse proteome organisation suggest that molecular networks with simple design principles underpin synaptic signalling properties with important roles in physiology, behaviour and disease.
TL;DR: The physiological response model is constructed based on integrated analysis of temporal changes in global mRNA and protein abundance along with protein–DNA interactions and evolutionarily conserved functional associations and shows cooperation among several cellular processes including DNA repair, increased protein turnover, apparent shifts in metabolism to favor nucleotide biosynthesis and an overall effort to repair oxidative damage.
Abstract: Cellular response to stress entails complex mRNA and protein abundance changes, which translate into physiological adjustments to maintain homeostasis as well as to repair and minimize damage to cellular components. We have characterized the response of the halophilic archaeon Halobacterium salinarum NRC-1 to 60Co ionizing gamma radiation in an effort to understand the correlation between genetic information processing and physiological change. The physiological response model we have constructed is based on integrated analysis of temporal changes in global mRNA and protein abundance along with protein–DNA interactions and evolutionarily conserved functional associations. This systems view reveals cooperation among several cellular processes including DNA repair, increased protein turnover, apparent shifts in metabolism to favor nucleotide biosynthesis and an overall effort to repair oxidative damage. Further, we demonstrate the importance of time dimension while correlating mRNA and protein levels and suggest that steady-state comparisons may be misleading while assessing dynamics of genetic information processing across transcription and translation.
TL;DR: It is shown that bistability in a two‐site MAPK (de)phosphorylation cycle generates a novel type of phosphoprotein wave that propagates from the surface deep into the cell interior, making it possible to convey phosphorylation signals over exceedingly long distances.
Abstract: A hallmark of protein kinase/phosphatase cascades, including mitogen-activated protein kinase (MAPK) pathways, is the spatial separation of their components within cells. The top-level kinase, MAP3K, is phosphorylated at the cell membrane, and cytoplasmic kinases at sequential downstream levels (MAP2K and MAPK) spread the signal to distant targets. Given measured protein diffusivity and phosphatase activities, signal propagation by diffusion would result in a steep decline of MAP2K activity and low bisphosphorylated MAPK (ppMAPK) levels near the nucleus, especially in large cells, such as oocytes. Here, we show that bistability in a two-site MAPK (de)phosphorylation cycle generates a novel type of phosphoprotein wave that propagates from the surface deep into the cell interior. Positive feedback from ppMAPK to cytoplasmic MAP2K enhances the propagation span of the ppMAPK wave, making it possible to convey phosphorylation signals over exceedingly long distances. The finding of phosphorylation waves traveling with constant amplitude and high velocity may solve a long-standing enigma of survival signaling in developing neurons.