Regulatory Network

The general architecture of a genetic regulatory network consists of strong connected components of its interaction graph, to which are attached three kinds of sub-structures: -a set of up-trees, rooted in the sources of the interaction graph, represented either by small RNAs like microRNAs: nuclear miRs or mitochondrial mitomiRs, i.e., translational inhibitors respectively of the messenger mRNAs and of the transfer tRNAs, or by gene repressors and/or inductors, -a set of circuits in the core (in graph sense) of the strong connected components of the interaction graph, -a set of down-trees going to the sinks of the interaction graph, i.e., to genes controlled, but not controlling any other gene. The various state configurations it is possible to observe in the above sub-structures correspond to different dynamical asymptotic behaviors. The network dynamics have in general a small number of attractors, corresponding in the Delbrück's paradigm to the functions of the tissue they represent. Examples of such dynamics will be given in embryology: cell proliferation control network in mammals and gastrulation control network in Drosophila melanogaster.

Mutations in the acrB gene, which were originally selected through their resistance to acriflavine, also result in reduced growth on a range of sole carbon sources, including fructose, cellobiose, raffinose, and starch, and reduced utilization of ω-amino acids, including GABA and β-alanine, as sole carbon and nitrogen sources. The acrB2 mutation suppresses the phenotypic effects of mutations in the creB gene that encodes a regulatory deubiquitinating enzyme, and in the creC gene that encodes a WD40-repeat-containing protein. Thus AcrB interacts with a regulatory network controlling carbon source utilization that involves ubiquitination and deubiquitination. The acrB gene was cloned and physically analyzed, and it encodes a novel protein that contains three putative transmembrane domains and a coiled-coil region. AcrB may play a role in the ubiquitination aspect of this regulatory network.

Understanding the role of transcription factors (TFs) is essential in reconstructing developmental regulatory networks. The plant-specific GeBP TF family of Arabidopsis thaliana (Arabidopsis) comprises 21 members, all of unknown function. A subset of four members, the founding member GeBP and GeBP-like proteins (GPL) 1, 2, and 3, shares a conserved C-terminal domain. Here we report that GeBP/GPL genes represent a newly defined class of leucine-zipper (Leu-zipper) TFs and that they play a redundant role in cytokinin hormone pathway regulation. Specifically, we demonstrate using yeast, in vitro, and split-yellow fluorescent protein in planta assays that GeBP/GPL proteins form homo- and heterodimers through a noncanonical Leu-zipper motif located in the C-terminal domain. A triple loss-of-function mutant of the three most closely related genes gebp gpl1 gpl2 shows a reduced sensitivity to exogenous cytokinins in a subset of cytokinin responses such as senescence and growth, whereas roo...

Genomes adapt dynamically to alterations in the signaling milieu, including inflammation that transiently or permanently disrupts genome function. Here, we elucidate how a progenitor cell genome senses and responds to inflammation when the developmental and transcriptional regulator GATA2 is limiting, which causes bone marrow failure in humans and mice and predisposes to leukemia in humans. GATA2 low murine progenitors are hypersensitive to inflammatory mediators. We discovered that the hematopoietic transcription factor PU.1 conferred transcriptional activation in GATA2 low progenitors in response to Interferon-γ and Toll-Like Receptor 1/2 agonists. In a locus-specific manner, inflammation reconfigured genome activity by promoting PU.1 recruitment to chromatin or tuning activity of PU.1-preoccupied chromatin. The recruitment mechanism disproportionately required IKKβ activity. Inflammation-activated genes were enriched in motifs for RUNX factors that cooperate with GATA factors. Contrasting with the GATA2-RUNX1 cooperativity paradigm, GATA2 suppressed and RUNX1 promoted PU.1 mechanisms to endow the progenitor genome with inflammation-sensing capacity.

The Escherichia coli OmpR/EnvZ two-component regulatory system, which senses environmental osmolarity, also regulates biofilm formation. Up mutations in the ompR gene, such as the ompR234 mutation, stimulate laboratory strains of E. coli to grow as a biofilm community rather than in a planktonic state. In this report, we show that the OmpR234 protein promotes biofilm formation by binding the csgD promoter region and stimulating its transcription. The csgD gene encodes the transcription regulator CsgD, which in turn activates transcription of the csgBA operon encoding curli, extracellular structures involved in bacterial adhesion. Consistent with the role of the ompR gene as part of an osmolarity-sensing regulatory system, we also show that the formation of biofilm by E. coli is inhibited by increasing osmolarity in the growth medium. The ompR234 mutation counteracts adhesion inhibition by high medium osmolarity; we provide evidence that the ompR234 mutation promotes biofilm formation by strongly increasing the initial adhesion of bacteria to an abiotic surface. This increase in initial adhesion is stationary phase dependent, but it is negatively regulated by the stationary-phase-specific sigma factor RpoS. We propose that this negative regulation takes place via rpoSdependent transcription of the transcription regulator cpxR; cpxR-mediated repression of csgB and csgD promoters is also triggered by osmolarity and by curli overproduction, in a feedback regulation loop.

ABSTRACT. Reverse transcription PCRs (RT‐PCRs), real‐time RT‐PCRs and microarrays containing 50‐mer oligonucleotides representing nucleus‐encoded genes for chloroplast proteins from Euglena gracilis were used to compare light‐ and dark‐grown wild‐type mRNA levels to those of light‐ and dark‐grown E. gracilis stable white mutant strains WgmZOflL, W3BUL and W10BSmL. The analyses revealed no light‐dependent regulation of mRNA levels. Moreover, the mRNA levels of most genes were unchanged in all white mutants in comparison with wild‐type. These results suggest that mRNA levels of nucleus‐encoded genes for chloroplast proteins in E. gracilis do not depend on either light or plastid function.

Microbes provide an invaluable tool for watching evolution in action. Throughout more than 55,000 generations, lineages of Escherichia coli cells in a long-term evolution experiment (LTEE) grew in a minimal glucose environment and explored different mutational paths to higher fitness. Genome sequencing identifies genes that accrue mutations early in evolution across the twelve evolving populations. These parallel mutations typically provide a significant fitness benefit and often fix in the population. However, some mutations seem to lead to evolutionary dead-ends. In 7 of the 12 LTEE populations, lineages with mutations in the gene coding for the lipid synthesis repressor, fabR, gain traction within the population, but always eventually go extinct. To parse out the fitness benefits and downstream effects, strains with these mutations were constructed. These mutations increase the growth rate and may affect the length of lag phase after each daily transfer. Another mutation that often fixes within eventually

Protein-Protein Interaction Sitesbase (PPInS), a high-performance database of protein-protein interacting interfaces, is presented. The atomic level information of the molecular interaction happening amongst various protein chains in protein-protein complexes (as reported in the Protein Data Bank [PDB]) together with their evolutionary information in Structural Classification of Proteins (SCOPe release 2.06), is made available in PPInS. Total 32468 PDB files representing X-ray crystallized multimeric protein-protein complexes with structural resolution better than 2.5 Å had been shortlisted to demarcate the protein-protein interaction interfaces (PPIIs). A total of 111857 PPIIs with ~32.24 million atomic contact pairs (ACPs) were generated and made available on a web server for on-site analysis and downloading purpose. All these PPIIs and protein-protein interacting patches (PPIPs) involved in them, were also analyzed in terms of a number of residues contributing in patch formation,...

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P) 1 ] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells.

The biologic and clinical significance of KIT overexpression that associates with KIT gain-of-function mutations occurring in subsets of acute myeloid leukemia (AML) (i.e., core binding factor AML) is unknown. Here, we show that KIT mutations lead to MYC-dependent miR-29b repression and increased levels of the miR-29b target Sp1 in KIT-driven leukemia. Sp1 enhances its own expression by participating in a NFkB/HDAC complex that further represses miR-29b transcription. Upregulated Sp1 then binds NFkB and transactivates KIT. Therefore, activated KIT ultimately induces its own transcription. Our results provide evidence that the mechanisms of Sp1/NFkB/HDAC/miR-29b-dependent KIT overexpression contribute to leukemia growth and can be successfully targeted by pharmacological disruption of the Sp1/NFkB/HDAC complex or synthetic miR-29b treatment in KIT-driven AML.

Rapid evolution of microbes under laboratory conditions can lead to domestication of environmental or clinical strains. In this work, we show that domestication due to laboratory passage in rich medium is extremely rapid. Passaging of wild-type Salmonella in rich medium led to diversification of genotypes contributing to the loss of a spatial phenotype, called the rdar morphotype, within days. Gene expression analysis of the rdar regulatory network demonstrated that mutations were primarily within rpoS, indicating that the selection pressure for scavenging during stationary phase had the secondary effect of impairing this highly conserved phenotype. If stationary phase was omitted from the experiment, radiation of genotypes and loss of the rdar morphotype was also demonstrated, but due to mutations within the cellulose biosynthesis pathway and also in an unknown upstream regulator. Thus regardless of the selection pressure, rapid regulatory changes can be observed on laboratory timescales. The speed of accumulation of rpoS mutations during daily passaging could not be explained by measured fitness and mutation rates. A model of mutation accumulation suggests that to generate the observed accumulation of r 38 mutations, this locus must experience a mutation rate of approximately 10 À4 mutations/gene/generation. Sequencing and gene expression of population isolates indicated that there were a wide variety of r 38 phenotypes within each population. This suggests that the rpoS locus is highly mutable by an unknown pathway, and that these mutations accumulate rapidly under common laboratory conditions.

Analysis of Cell Cycle Phase Response Captures the Synchronization Phenomena and Reveals a Novel Cell Cycle Network Topology YING LI, YIHAN LIN, NORBERT SCHERER, AARON DINNER, University of Chicago -Cell cycle progression requires a succession of temporally-regulated subprocesses, including chromosome replication and cell division, which are each controlled by their own regulatory modules. The modular design of cell cycle regulatory network allows robust environmental responses and evolutionary adaptations. It is emerging that some of the cell cycle modules involve their own autonomous periodic dynamics. As a consequence, the realization of robust coordination among these modules becomes challenging since each module could potentially run out of sync. We believe that an insight into this puzzle resides in the coupling between the contributing regulatory modules. Here, we measured the phase response curve (PRC) of the cell cycle oscillator by driving the expression of a master regulator of the cell cycle in a pulsatile manner and measuring the single cell phase response. We constructed a return map that quantitatively explains the synchronization phenomena that were caused by periodic chemical perturbation. To capture the measured phase response, we derived a minimalist coupled oscillator model that generalizes the basic topology of the cell cycle network. This diode-like coupling suggests that the cell is engineered to ensure complete coordination of constituent events with the cell cycle.

The American Physical Society Synchronization of Cell Cycle Oscillator by Multi-pulse Chemical Perturbations YIHAN LIN, YING LI, AARON DINNER, NORBERT SCHERER, University of Chicago -Oscillators underlie biological rhythms in various organisms and provide a timekeeping mechanism. Cell cycle oscillator, for example, controls the progression of cell cycle stage and drives cyclic reproduction in both prokaryotes and eukaryotes. The understanding of the underlying nonlinear regulatory network allows experimental design of external perturbations to interact and control cell cycle oscillation. We have previously demonstrated in experiment and in simulation that the cell cycle coherence of a model bacterium can be progressively tuned by the level of a histidine kinase. Here, we present our recent effort to synchronize the division of a population of bacterium cells by external pulsatile chemical perturbations. We were able to synchronize the cell population by phase-locking approach: the external oscillator (i.e. periodic perturbation) entrains the internal cell cycle oscillator which is in analogous to the phase-locking of circadian clock to external light/dark oscillator. We explored the ranges of frequencies for two external oscillators of different amplitudes where phase-locking occurred. To our surprise, non-periodic chemical perturbations could also cause synchronization of a cell population, suggesting a Markovian cell cycle oscillation dynamics.

The American Physical Society Synchronization of Cell Cycle Oscillator by Multi-pulse Chemical Perturbations YIHAN LIN, YING LI, AARON DINNER, NORBERT SCHERER, University of Chicago -Oscillators underlie biological rhythms in various organisms and provide a timekeeping mechanism. Cell cycle oscillator, for example, controls the progression of cell cycle stage and drives cyclic reproduction in both prokaryotes and eukaryotes. The understanding of the underlying nonlinear regulatory network allows experimental design of external perturbations to interact and control cell cycle oscillation. We have previously demonstrated in experiment and in simulation that the cell cycle coherence of a model bacterium can be progressively tuned by the level of a histidine kinase. Here, we present our recent effort to synchronize the division of a population of bacterium cells by external pulsatile chemical perturbations. We were able to synchronize the cell population by phase-locking approach: the external oscillator (i.e. periodic perturbation) entrains the internal cell cycle oscillator which is in analogous to the phase-locking of circadian clock to external light/dark oscillator. We explored the ranges of frequencies for two external oscillators of different amplitudes where phase-locking occurred. To our surprise, non-periodic chemical perturbations could also cause synchronization of a cell population, suggesting a Markovian cell cycle oscillation dynamics.

Analysis of Cell Cycle Phase Response Captures the Synchronization Phenomena and Reveals a Novel Cell Cycle Network Topology YING LI, YIHAN LIN, NORBERT SCHERER, AARON DINNER, University of Chicago -Cell cycle progression requires a succession of temporally-regulated subprocesses, including chromosome replication and cell division, which are each controlled by their own regulatory modules. The modular design of cell cycle regulatory network allows robust environmental responses and evolutionary adaptations. It is emerging that some of the cell cycle modules involve their own autonomous periodic dynamics. As a consequence, the realization of robust coordination among these modules becomes challenging since each module could potentially run out of sync. We believe that an insight into this puzzle resides in the coupling between the contributing regulatory modules. Here, we measured the phase response curve (PRC) of the cell cycle oscillator by driving the expression of a master regulator of the cell cycle in a pulsatile manner and measuring the single cell phase response. We constructed a return map that quantitatively explains the synchronization phenomena that were caused by periodic chemical perturbation. To capture the measured phase response, we derived a minimalist coupled oscillator model that generalizes the basic topology of the cell cycle network. This diode-like coupling suggests that the cell is engineered to ensure complete coordination of constituent events with the cell cycle.

The balance between maintenance of the stem cell state and terminal differentiation is influenced by the cellular environment. The switching between these states has long been understood as a transition between attractor states of a molecular network. Herein, stochastic fluctuations are either suppressed or can trigger the transition, but they do not actually determine the attractor states. We present a novel mathematical concept in which stem cell and progenitor population dynamics are described as a probabilistic process that arises from cell proliferation and small fluctuations in the state of differentiation. These state fluctuations reflect random transitions between different activation patterns of the underlying regulatory network. Importantly, the associated noise amplitudes are state-dependent and set by the environment. Their variability determines the attractor states, and thus actually governs population dynamics. This model quantitatively reproduces the observed dynamic...

Analysis of the α-lipomycin biosynthesis gene cluster of Streptomyces aureofaciens Tü117 led to the identification of five putative regulatory genes, which are congregated into a subcluster. Analysis of the lipReg1-4 and lipX1 showed that they encode components of twocomponent signal transduction systems (LipReg1 and LipReg2), multiple antibiotics resistance-type regulator (LipReg3), large ATP-binding regulators of the LuxR family-type regulator (LipReg4), and small ribonuclease (LipRegX1), respectively. A combination of targeted gene disruptions, complementation experiments, lipomycin production studies, and gene expression analysis via RT-PCR suggests that all regulatory lip genes are involved in αlipomycin production. On the basis of the obtained data, we propose that LipReg2 controls the activity of LipReg1, which in its turn govern the expression of the α-lipomycin pathway-specific regulatory gene lipReg4. The ribonuclease gene lipX1 and the transporter regulator lipReg3 appear to work independently of genes lipReg1, lipReg2, and lipReg4.

Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Small-molecule metabolites are one category of critical cellular intermediates that can influence as well as be a target of cellular regulations. Because metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. Here we develop and apply a network reconstruction approach that simultaneously integrates six different types of data: endogenous metabolite concentration, RNA expression, DNA variation, DNA-protein binding, protein-metabolite interaction, and protein-protein interaction data, to construct probabilistic causal networks that elucidate the complexity of cell regulation in a segregating yeast population. Because many of the metabolites are found to be under strong genetic control, we were able to employ a causal regulator detection algorithm to identify causal regulators of the resulting network that elucidated the mechanisms by which variations in their sequence affect gene expression and metabolite concentrations. We examined all four expression quantitative trait loci (eQTL) hot spots with colocalized metabolite QTLs, two of which recapitulated known biological processes, while the other two elucidated novel putative biological mechanisms for the eQTL hot spots.

Complete genome sequences together with high throughput technologies have made comprehensive characterizations of gene expression patterns possible. While genome-wide measurement of mRNA levels was one of the first applications of these advances, other important aspects of gene expression are also amenable to a genomic approach, for example, the translation of message into protein. Earlier we reported a high throughput technology for simultaneously studying mRNA level and translation, which we termed translation state array analysis, or TSAA. The current studies test the proposition that TSAA can identify novel instances of translation regulation at the genome-wide level. As a biological model, cultures of Saccharomyces cerevisiae were cell cycle-arrested using either ␣-factor or the temperature-sensitive cdc15-2 allele. Forty-eight mRNAs were found to change significantly in translation state following release from ␣-factor arrest, including genes involved in pheromone response and cell cycle arrest such as BAR1, SST2, and FAR1. After the shift of the cdc15-2 strain from 37 °C to 25 °C, 54 mRNAs were altered in translation state, including the products of the stress genes HSP82, HSC82, and SSA2. Thus, regulation at the translational level seems to play a significant role in the response of yeast cells to external physical or biological cues. In contrast, surprisingly few genes were found to be translationally controlled as cells progressed through the cell cycle. Additional refinements of TSAA should allow characterization of both transcriptional and translational regulatory networks on a genomic scale, providing an additional layer of information that can be integrated into models of system biology and function.

Background: Many cellular programs are regulated through the integration of specific transcriptional signals originated from external stimuli, being cooperation between transcription factors a key feature in this process. In this work, we studied how transcriptional cooperativity in yeast is aimed at integrating different regulatory inputs rather than controlling particular cellular functions from a organizational, evolutionary and functional point of view. Findings: Our results showed that cooperative transcription factor pairs co-evolve and are essential for the life of the cell. When organized into a layered regulatory network, we observed that cooperative transcription factors were preferentially placed in the middle layers, which highlights a role in regulatory signal integration. We also observed significant co-activity and co-evolution between members of the same cooperative pairs, but a lack of common co-expression profile. Conclusions: Our results suggest that transcriptional cooperativity has a specific role within the regulatory control scheme of the cell, focused in the amplification and integration of cellular signals rather than control of particular cellular functions. This information can be used for better characterization of regulatory interactions between transcription factors, aimed at determining the spatial and temporal control of gene expression.

Recent studies show that the dysregulation of the transcription factor SOX10 is essential for the development and progression of melanoma. MicroRNAs (miRNAs) can regulate the expression of transcription factors at the post-transcriptional level. The interactions between SOX10 and its targeting miRNAs form network motifs such as feedforward and feedback loops. Such motifs can result in nonlinear dynamics in gene expression levels, therefore playing a crucial role in regulating tumor proliferation and metastasis as well as the tumor's responses to therapies. Here, we reviewed and discussed the intricate interplay between SOX10 and miRNAs in melanoma biology including melanogenesis, phenotype switch, and therapy resistance. Additionally, we investigated the gene regulatory interactions in melanoma, identifying crucial network motifs that involve SOX10, MITF, and miRNAs. We also analyzed the expression levels of the components within these motifs. From a control theory perspective, we explained how these dynamics are linked to the phenotypic plasticity of melanoma cells. In summary, we underscored the importance of employing a datadriven network biology approach to elucidate the complex regulatory mechanisms and identify driver network motifs within the melanoma network. This methodology facilitates a deeper understanding of the regulation of SOX10 and MITF by miRNAs in melanoma. The insight gained could potentially contribute to the development of miRNA-based treatments, thereby enhancing the clinical management of this malignancy.

The sequenced genome of Human and various pathogens has provided access to huge amount of data related to their genome as well as their proteome. This immense assembly of information proves to be very useful in the identification of the novel targets in pathogens. Such drug targets are then used to control the dreadful actions of various fatal diseases. In this study, the disease chosen was typhoid. It was found that typhoid is mainly caused due to the bacteria Salmonella typhi. The whole proteome of Salmonella typhi was retrieved from both UniProt and NCBI. The filtered essential proteins of pathogen, non homologous to human, represents potential drug targets. The complete proteome set of Salmonella typhi contains 19732 proteins (Uniprot). 6292 proteins were retrieved as non-redundant by CD-HIT program at 60%(identical) threshold.MSA analysis was perform to get the conserved region within these proteins. Subcellular localization was predicted using PA-SUB server to locate the outer membrane proteins which could be probable vaccine candidates. These represent a vast number of potential therapeutic drug targets because of their involvement in major biological processes in cell.

A network is one of the most convenient way to represent interactions between biological entities in systems biology. A network of molecular interactions is a graph in which the vertices are biological component and the edges correspond to the interactions between them. Many notions and approaches for network analysis came to systems biology from the theory of graphs – a field of mathematics that study graphs. We focused on the study of the shortest path approach in this work. We investigated whether this approach yields valid molecular paths. To perform this, the shortest paths in the human interactome (derived from HPRD and HIPPIE databases) were found between all relevant combinations of proteins taken from eight well-studied highly conserved signaling pathways from the KEGG database (NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta and the signaling part of the apoptotic process). Canonical paths were systematically compared with the shortest counterparts and centrality of ...

Many notions and concepts for network analysis, including the shortest path approach, came to systems biology from the theory of graphs — the field of mathematics that studies graphs. We studied the relationship between the shortest paths and a biologically meaningful molecular path between vertices in human molecular interaction networks. We analyzed the sets of the shortest paths in the human interactome derived from HPRD and HIPPIE databases between all possible combinations of start and end proteins in eight signaling pathways in the KEGG database — NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta, and the signaling part of the apoptotic process. We investigated whether the shortest paths match the canonical paths. We studied whether centrality of vertices and paths in the subnetworks induced by the shortest paths can highlight vertices and paths that are part of meaningful molecular paths. We found that the shortest paths match canonical counterparts only for canonical pat...

MicroRNAs (miRNAs) are nonprotein-coding RNAs that function as posttranscriptional gene regulators. They can regulate their targets directly by mRNA cleavage or by repressing their translation, depending on the degree of complementariety between the miRNA and the target. Recent evidences have shown that miRNA control cell growth, apoptosis, and differentiation. Moreover, miRNA expression correlates with cancers and could have a crucial function in tumor progression. Bioinformatic data indicates that each miRNA can control hundreds of target genes, but identification of the accurate miRNA targets will be crucial to exploit the emerging knowledge of miRNA contribution to cancer process. While the miRNA field is still emerging, the benefit of our understanding of miRNA in cancer is potentially enormous, especially if we are able to apply this knowledge to provide new therapies for patients.

The Calculus of Wrapped Compartments is a framework based on stochastic multiset rewriting in a compartmentalised setting originally developed for the modelling and analysis of biological interactions. In this paper, we propose to use this calculus for the description of ecological systems and we provide the modelling guidelines to encode within the calculus some of the main interactions leading ecosystems evolution. As a case study, we model the distribution of height of Croton wagneri, a shrub constituting the endemic predominant species of the dry ecosystem in southern Ecuador. In particular, we consider the plant at different altitude gradients (i.e. at different temperature conditions), to study how it adapts under the effects of global climate change.

The shift from zygomorphy to actinomorphy has been intensively studied in molecular genetic model organisms. However, it is still a key challenge to explain the great morphological diversity of derived actinomorphy in angiosperms, since different underlying mechanisms may be responsible for similar external morphologies. Bournea (Gesneriaceae) is of particular interest in addressing this question, as it is a representative of primarily derived actinomorphy characteristic of a unique developmental transition from zygomorphy to actinomorphic flowers at anthesis. • Using RNA in situ hybridization, the expression patterns were investigated of three different Bournea orthologues of TCP and MYB genes that have been shown to control floral symmetry in model species. • Here, it is shown that the initial zygomorphic pattern in Bournea is likely a residual zygomorphy resulting from conserved expression of the adaxial (dorsal) identity gene BlCYC1. As a key novel event, the late downregulation of BlCYC1 and BlRAD and the correlative changes in the late specific expression of the abaxial (ventral) identity gene BlDIV should be responsible for the origin of the derived actinomorphy in Bournea. • These results further indicate that there might be diverse pathways in the origin and evolution of derived actinomorphy through modifications of pre-existing zygomorphic developmental programs under dynamics of regulatory networks.

Nowadays, morphogenetic engineering (ME) [1] is inspired by biological systems (embryogenesis) to export their self-formation capabilities to engineered autonomous systems. As cells are intelligent by nature, researchers of ME are trying to recreate this intelligence in artificial systems, so that these cells know how and when to act in order to accomplish a specific function (e.g. Build an organism).

Artificial embryogeny aims at developing a complete organism starting from a unique cell. Nowadays many algorithms exist to synthesize artificial creature shapes or behaviours. With the purpose of shape and high-level behaviour joint evolution, one of the ...

The Escherichia coli OmpR/EnvZ two-component regulatory system, which senses environmental osmolarity, also regulates biofilm formation. Up mutations in the ompR gene, such as the ompR234 mutation, stimulate laboratory strains of E. coli to grow as a biofilm community rather than in a planktonic state. In this report, we show that the OmpR234 protein promotes biofilm formation by binding the csgD promoter region and stimulating its transcription. The csgD gene encodes the transcription regulator CsgD, which in turn activates transcription of the csgBA operon encoding curli, extracellular structures involved in bacterial adhesion. Consistent with the role of the ompR gene as part of an osmolarity-sensing regulatory system, we also show that the formation of biofilm by E. coli is inhibited by increasing osmolarity in the growth medium. The ompR234 mutation counteracts adhesion inhibition by high medium osmolarity; we provide evidence that the ompR234 mutation promotes biofilm formation by strongly increasing the initial adhesion of bacteria to an abiotic surface. This increase in initial adhesion is stationary phase dependent, but it is negatively regulated by the stationary-phase-specific sigma factor RpoS. We propose that this negative regulation takes place via rpoSdependent transcription of the transcription regulator cpxR; cpxR-mediated repression of csgB and csgD promoters is also triggered by osmolarity and by curli overproduction, in a feedback regulation loop.

An understanding of the physiology and metabolic complexity of microbial consortia involved in metal solubilization is a prerequisite for the rational improvement of bioleaching technologies. Among the most challenging aspects that remain to be addressed is how aerobic acidophiles, especially Fe(II)-oxidizers, contend with the paradoxical hazards of iron overload and iron deficiency, each with deleterious consequences for growth. Homeostatic mechanisms regulating the acquisition, utilization/oxidation, storage and intracellular mobilization of cellular iron are deemed to be critical for fitness and survival of bioleaching microbes. In an attempt to contribute to the comprehensive understanding of the biology and ecology of the microbial communities in bioleaching econiches, we have used comparative genomics and other bioinformatic tools to reconstruct the iron management strategies in newly sequenced Acidithiobacilli and other biomining genomes available in public databases. Species specific genes have been identified with distinctive functional roles in iron management as well as genes shared by several species in biomining consortia. Their analysis contributes to our understanding of the general survival strategies in acidic and iron loaded environments and suggests functions for genes with currently unknown roles that might reveal novel aspects of iron response in acidophiles. Comprehensive examination of the occurrence and conservation of regulatory functions and regulatory sites also allowed the prediction of the metal regulatory networks for these biomining microbes.

There is an abundance of complex dynamic systems that are critical to our daily lives and our society but that are hardly understood, and even with today's possibilities to sense and collect large amounts of experimental data, they are so complex and continuously evolving that it is unlikely that their dynamics will ever be understood in full detail. Nevertheless, through computational tools we can try to make the best possible use of the current technologies and available data. We believe that the most useful models will have to take into account the imbalance between system complexity and available data in the context of limited knowledge or multiple hypotheses. The complex system of biological cells is a prime example of such a system that is studied in systems biology and has motivated the methods presented in this paper. They were developed as part of the DARPA Rapid Threat Assessment (RTA) program, which is concerned with understanding of the mechanism of action (MoA) of t...

s received after January 24, 2005 Metagenome Analysis of Contaminated Sediments at the DOE Hanford Site Natalia Maltsev1, Tanuja Bompada1, Banu Gopalan2 (agor@ornl.gov), Shu-mei Li3, Weiwen Zhang3, J. Chris Detter4, Paul Richardson4, Margie Romine3, and Fred Brockman3 1Bioinformatics Group, Argonne National Laboratory; 2Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, WA; 3Microbiology Group, Pacific Northwest National Laboratory, Richland, WA; 4Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA Technologies are needed to make improved inferences of microbial community function from metagenome sequence. Most microbes have evolved multiple mechanisms (programs) to capture energy. The cells’ immediate biochemical and geochemical environment determines the regulatory networks that are engaged to run the best program to capture energy. Bulk extraction of RNA and analysis on microarrays largely destroys the spatial and functio...

In tumoral cells, gene regulation mechanisms are severely altered. Genes that do not react normally to their regulators' activity can provide explanations for the tumoral behavior, and be characteristic of cancer subtypes. We thus propose a statistical methodology to identify the misregulated genes given a reference network and gene expression data. Our model is based on a regulatory process in which all genes are allowed to be deregulated. We derive an EM algorithm where the hidden variables correspond to the status (under/over/normally expressed) of the genes and where the E-step is solved thanks to a message passing algorithm. Our procedure provides posterior probabilities of deregulation in a given sample for each gene. We assess the performance of our method by numerical experiments on simulations and on a bladder cancer data set.

OCT-2, a member of the POU family of transcription factors, plays a critical role in regulating B-cell-specific genes and immunoglobulin transcription, essential for B-cell proliferation and differentiation. This study investigates the regulation of OCT-2 through promoter analysis and transcription factor identification. Using computational tools (PROMO and TESS) and DNA microarray data, five transcription factors-EGR2, Smad3, FOXJ2, TCF-7, and RXR alpha-were identified as potential regulators of OCT-2. Differential expression analysis suggests that RXR alpha, TCF-7, EGR2, and FOXJ2 may act as repressors in CBMI-Ral-STO cells, while Smad3 functions as an activator in RAEL cells, potentially mediated via the TGF-beta signaling pathway. OCT-2's involvement in Epstein-Barr Virus (EBV) latency regulation is also hypothesized, particularly its interplay with EBNA-1 in promoter regulation. These findings provide insights into OCT-2's transcriptional regulation and propose experimental pathways to validate its regulatory mechanisms. Understanding OCT-2 regulation may illuminate its broader implications in immune response and viral latency. I.

Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

Carotid body glomus cells mediate essential reflex responses to arterial blood hypoxia. They are dopaminergic and secrete growth factors that support dopaminergic neurons, making the carotid body a potential source of patient-specific cells for Parkinson's disease therapy. Like adrenal chromaffin cells, which are also hypoxia-sensitive, glomus cells are neural crest-derived and require the transcription factors Ascl1 and Phox2b; otherwise, their development is little understood at the molecular level. Here, analysis in chicken and mouse reveals further striking molecular parallels, though also some differences, between glomus and adrenal chromaffin cell development. Moreover, histology has long suggested that glomus cell precursors are 'émigrés' from neighbouring ganglia/nerves, while multipotent nerve-associated glial cells are now known to make a significant contribution to the adrenal chromaffin cell population in the mouse. We present conditional genetic lineage-trac...

Port State Control (PSC) inspection data is used for determining the inspection pattern of PSC in Malaysia and identifying the relationship between the inspection place, flag state, number of deficiency, detention result, and ship risk profile. Based on 8,089 inspection reports from 2015 to 2019, the mining association rule is proposed as a learning approach due to its determination pattern in the information bank. The learning of association rules of PSC inspections is performed primarily on the Apriori Algorithm, in order to produce alluring rules. Inspection patterns of Malaysian ports revealed that flag state, ship risk profile, and inspection place generally lead to no detention result, as well as zero deficiency recorded on-board. The reported quantity of detention was significantly related to the high number of deficiencies raised for ships registered under blacklisted countries. Furthermore, the analysis of deficiency discovered the pattern of inspection at Malaysian ports is frequently related to zero and a low number of deficiencies raised by inspectors. Lastly, five major ports were selected for providing a useful rule to help PSC officers in organising an effective inspection plan. A similar approach can also be used for other ports beyond Malaysia for comparative analysis.

Background Integrons are found in hundreds of environmental bacterial species, but are mainly known as the agents responsible for the capture and spread of antibiotic-resistance determinants between Gram-negative pathogens. The SOS response is a regulatory network under control of the repressor protein LexA targeted at addressing DNA damage, thus promoting genetic variation in times of stress. We recently reported a direct link between the SOS response and the expression of integron integrases in Vibrio cholerae and a plasmid-borne class 1 mobile integron. SOS regulation enhances cassette swapping and capture in stressful conditions, while freezing the integron in steady environments. We conducted a systematic study of available integron integrase promoter sequences to analyze the extent of this relationship across the Bacteria domain. Results Our results showed that LexA controls the expression of a large fraction of integron integrases by binding to Escherichia coli-like LexA bind...

DREAM website (wiki.c2b2.columbia.edu/dream/index.php/D5c4) Current information on the DREAM5 network inference challenge, including anonymized data, challenge description, and evaluation scripts. M3D website (m3d.bu.edu/dream) The deanonymized expression compendia are made publicly available from the Many Microbe Microarrays Database (M3D).

Decidualization is a morphological and biochemical transformation of endometrial stromal fibroblast into differentiated decidual cells, which is critical for embryo implantation and pregnancy establishment. The complex regulatory networks have been elucidated at both the transcriptome and the proteome levels, however very little is known about the posttranscriptional regulation of this process. miRNAs regulate multiple physiological pathways and their de-regulation is associated with human disorders including gynaecological conditions such as endometriosis and preeclampsia. In this study we profile the miRNAs expression throughout human endometrial stromal (hESCs) decidualization and analyze the requirement of the miRNA biogenesis enzyme Dicer during this process. A total of 26 miRNAs were upregulated and 17 miRNAs downregulated in decidualized hESCs compared to non-decidualized hESCs. Three miRNAs families, miR-181, miR-183 and miR-200, are down-regulated during the decidualization process. Using miRNAs target prediction algorithms we have identified the potential targets and pathways regulated by these miRNAs. The knockdown of Dicer has a minor effect on hESCs during in vitro decidualization. We have analyzed a battery of decidualization markers such as cell morphology, Prolactin, IGFBP-1, MPIF-1 and TIMP-3 secretion as well as HOXA10, COX2, SP1, C/EBPß and FOXO1 expression in decidualized hESCs with decreased Dicer function. We found decreased levels of HOXA10 and altered intracellular organization of actin filaments in Dicer knockdown decidualized hESCs compared to control. Our results provide the miRNA signature of hESC during the decidualization process in vitro. We also provide the first functional characterization of Dicer during human endometrial decidualization although surprisingly we found that Dicer plays a minor role regulating this process suggesting that alternative biogenesis miRNAs pathways must be involved in human endometrial decidualization.

The vertebrate skull vault forms almost entirely by the direct mineralisation of mesenchyme, without the formation of a cartilaginous template, a mechanism called membranous ossification. Dlx5 gene mutation leads to cranial dismorphogenesis which differs from the previously studied craniosynostosis syndromes [Development 126 (1999), 3795; Development 126 (1999), 3831]. In avians, little is known about the genetic regulation of cranial vault development. In this study, we analyze Dlx5 expression and regulation during skull formation in the chick embryo. We compare Dlx5 expression pattern with that of several genes involved in mouse cranial suture regulation. This provides an initial description of the expression in the developing skull of the genes encoding the secreted molecules BMP 2, BMP 4, BMP 7, the transmembrane FGF receptors FGFR 1, FGFR 2, FGFR 4, the transcription factors Msx1, Msx2, and Twist, as well as Goosecoid and the early membranous bone differentiation marker osteopontin. We show that Dlx5 is activated in proliferating osteoblast precursors, before osteoblast differentiation. High levels of Dlx5 transcripts are observed at the osteogenic fronts (OFs) and at the edges of the suture mesenchyme, but not in the suture itself. Dlx5 expression is initiated in areas where Bmp4 and Bmp7 genes become coexpressed. In a calvarial explant culture system, Dlx5 transcription is upregulated by BMPs and inhibited by the BMP-antagonist Noggin. In addition, FGF4 activates Bmp4 but not Bmp7 gene transcription and is not sufficient to induce ectopic Dlx5 expression in the immature calvarial mesenchyme. From these data, we propose a model for the regulatory network implicated in early steps of chick calvarial development.

Background: Recent studies have identified thousands of sense-antisense gene pairs across different genomes by computational mapping of cDNA sequences. These studies have shown that approximately 25% of all transcriptional units in the human and mouse genomes are involved in cis-sense-antisense pairs. However, the number of known sense-antisense pairs remains limited because currently available cDNA sequences represent only a fraction of the total number of transcripts comprising the transcriptome of each cell type. Methods: To discover novel antisense transcripts encoded in the antisense strand of important genes, such as cancer-related genes, we conducted expression analyses of antisense transcripts using our custom microarray platform along with 2376 probes designed specifically to detect the potential antisense transcripts of 501 wellknown genes suitable for cancer research. Results: Using colon cancer tissue and normal tissue surrounding the cancer tissue obtained from 6 patients, we found that antisense transcripts without poly(A) tails are expressed from approximately 80% of these well-known genes. This observation is consistent with our previous finding that many antisense transcripts expressed in a cell are poly(A)-. We also identified 101 and 71 antisense probes displaying a high level of expression specifically in normal and cancer tissues respectively. Our microarray analysis identified novel antisense transcripts with expression profiles specific to cancer tissue, some of which might play a role in the regulatory networks underlying oncogenesis and thus are potential targets for further experimental validation. Our microarray data are available at .

Background Recent studies have identified thousands of sense-antisense gene pairs across different genomes by computational mapping of cDNA sequences. These studies have shown that approximately 25% of all transcriptional units in the human and mouse genomes are involved in cis-sense-antisense pairs. However, the number of known sense-antisense pairs remains limited because currently available cDNA sequences represent only a fraction of the total number of transcripts comprising the transcriptome of each cell type. Methods To discover novel antisense transcripts encoded in the antisense strand of important genes, such as cancer-related genes, we conducted expression analyses of antisense transcripts using our custom microarray platform along with 2376 probes designed specifically to detect the potential antisense transcripts of 501 well-known genes suitable for cancer research. Results Using colon cancer tissue and normal tissue surrounding the cancer tissue obtained from 6 patients...

The regulatory network for the uptake of Escherichia coli autoinducer 2 (AI-2) is comprised of a transporter complex, LsrABCD; its repressor, LsrR; and a cognate signal kinase, LsrK. This network is an integral part of the AI-2 quorum-sensing (QS) system. Because LsrR and LsrK directly regulate AI-2 uptake, we hypothesized that they might play a wider role in regulating other QS-related cellular functions. In this study, we characterized physiological changes due to the genomic deletion of lsrR and lsrK . We discovered that many genes were coregulated by lsrK and lsrR but in a distinctly different manner than that for the lsr operon (where LsrR serves as a repressor that is derepressed by the binding of phospho-AI-2 to the LsrR protein). An extended model for AI-2 signaling that is consistent with all current data on AI-2, LuxS, and the LuxS regulon is proposed. Additionally, we found that both the quantity and architecture of biofilms were regulated by this distinct mechanism, as l...