Heme deficiency may be a factor in the mitochondrial and neuronal decay of aging

PubMed Central

Atamna, Hani; Killilea, David W.; Killilea, Alison Nisbet; Ames, Bruce N.

2002-01-01

Heme, a major functional form of iron in the cell, is synthesized in the mitochondria by ferrochelatase inserting ferrous iron into protoporphyrin IX. Heme deficiency was induced with N-methylprotoporphyrin IX, a selective inhibitor of ferrochelatase, in two human brain cell lines, SHSY5Y (neuroblastoma) and U373 (astrocytoma), as well as in rat primary hippocampal neurons. Heme deficiency in brain cells decreases mitochondrial complex IV, activates nitric oxide synthase, alters amyloid precursor protein, and corrupts iron and zinc homeostasis. The metabolic consequences resulting from heme deficiency seem similar to dysfunctional neurons in patients with Alzheimer's disease. Heme-deficient SHSY5Y or U373 cells die when induced to differentiate or to proliferate, respectively. The role of heme in these observations could result from its interaction with heme regulatory motifs in specific proteins or secondary to the compromised mitochondria. Common causes of heme deficiency include aging, deficiency of iron and vitamin B6, and exposure to toxic metals such as aluminum. Iron and B6 deficiencies are especially important because they are widespread, but they are also preventable with supplementation. Thus, heme deficiency or dysregulation may be an important and preventable component of the neurodegenerative process. PMID:12417755

Role of TLR4 signaling in the nephrotoxicity of heme and heme proteins.

PubMed

Nath, Karl A; Belcher, John D; Nath, Meryl C; Grande, Joseph P; Croatt, Anthony J; Ackerman, Allan W; Katusic, Zvonimir S; Vercellotti, Gregory M

2018-05-01

Destabilized heme proteins release heme, and free heme is toxic. Heme is now recognized as an agonist for the Toll-like receptor-4 (TLR4) receptor. This study examined whether the TLR4 receptor mediates the nephrotoxicity of heme, specifically, the effects of heme on renal blood flow and inflammatory responses. We blocked TLR4 signaling by the specific antagonist TAK-242. Intravenous administration of heme to mice promptly reduced renal blood flow, an effect attenuated by TAK-242. In vitro, TAK-242 reduced heme-elicited activation of NF-κB and its downstream gene monocyte chemoattractant protein-1(MCP-1); in contrast, TAK-242 failed to reduce heme-induced activation of the anti-inflammatory transcription factor Nrf2 and its downstream gene heme oxygenase-1 (HO-1). TAK-242 did not reduce heme-induced renal MCP-1 upregulation in vivo. TAK-242 did not reduce dysfunction and histological injury in the glycerol model of heme protein-induced acute kidney injury (AKI), findings corroborated by studies in TLR4 +/+ and TLR4 -/- mice. We conclude that 1) acute heme-mediated renal vasoconstriction occurs through TLR4 signaling; 2) proinflammatory effects of heme in renal epithelial cells involve TLR4 signaling, whereas the anti-inflammatory effects of heme do not; 3) TLR4 signaling does not mediate the proinflammatory effects of heme in the kidney; and 4) major mechanisms underlying glycerol-induced, heme protein-mediated AKI do not involve TLR4 signaling. These findings in the glycerol model are in stark contrast with findings in virtually all other AKI models studied to date and emphasize the importance of TLR4-independent pathways of heme protein-mediated injury in this model. Finally, these studies urge caution when using observations derived in vitro to predict what occurs in vivo.

Heme Regulates Allosteric Activation of the Slo1 BK Channel

PubMed Central

Horrigan, Frank T.; Heinemann, Stefan H.; Hoshi, Toshinori

2005-01-01

Large conductance calcium-dependent (Slo1 BK) channels are allosterically activated by membrane depolarization and divalent cations, and possess a rich modulatory repertoire. Recently, intracellular heme has been identified as a potent regulator of Slo1 BK channels (Tang, X.D., R. Xu, M.F. Reynolds, M.L. Garcia, S.H. Heinemann, and T. Hoshi. 2003. Nature. 425:531–535). Here we investigated the mechanism of the regulatory action of heme on heterologously expressed Slo1 BK channels by separating the influences of voltage and divalent cations. In the absence of divalent cations, heme generally decreased ionic currents by shifting the channel's G–V curve toward more depolarized voltages and by rendering the curve less steep. In contrast, gating currents remained largely unaffected by heme. Simulations suggest that a decrease in the strength of allosteric coupling between the voltage sensor and the activation gate and a concomitant stabilization of the open state account for the essential features of the heme action in the absence of divalent ions. At saturating levels of divalent cations, heme remained similarly effective with its influence on the G–V simulated by weakening the coupling of both Ca2+ binding and voltage sensor activation to channel opening. The results thus show that heme dampens the influence of allosteric activators on the activation gate of the Slo1 BK channel. To account for these effects, we consider the possibility that heme binding alters the structure of the RCK gating ring and thereby disrupts both Ca2+- and voltage-dependent gating as well as intrinsic stability of the open state. PMID:15955873

Dynamics of Bacterial Gene Regulatory Networks.

PubMed

Shis, David L; Bennett, Matthew R; Igoshin, Oleg A

2018-05-20

The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

The prrF-Encoded Small Regulatory RNAs Are Required for Iron Homeostasis and Virulence of Pseudomonas aeruginosa

PubMed Central

Reinhart, Alexandria A.; Powell, Daniel A.; Nguyen, Angela T.; O'Neill, Maura; Djapgne, Louise; Wilks, Angela; Ernst, Robert K.

2014-01-01

Pseudomonas aeruginosa is an opportunistic pathogen that requires iron to cause infection, but it also must regulate the uptake of iron to avoid iron toxicity. The iron-responsive PrrF1 and PrrF2 small regulatory RNAs (sRNAs) are part of P. aeruginosa's iron regulatory network and affect the expression of at least 50 genes encoding iron-containing proteins. The genes encoding the PrrF1 and PrrF2 sRNAs are encoded in tandem in P. aeruginosa, allowing for the expression of a distinct, heme-responsive sRNA named PrrH that appears to regulate genes involved in heme metabolism. Using a combination of growth, mass spectrometry, and gene expression analysis, we showed that the ΔprrF1,2 mutant, which lacks expression of the PrrF and PrrH sRNAs, is defective for both iron and heme homeostasis. We also identified phuS, encoding a heme binding protein involved in heme acquisition, and vreR, encoding a previously identified regulator of P. aeruginosa virulence genes, as novel targets of prrF-mediated heme regulation. Finally, we showed that the prrF locus encoding the PrrF and PrrH sRNAs is required for P. aeruginosa virulence in a murine model of acute lung infection. Moreover, we showed that inoculation with a ΔprrF1,2 deletion mutant protects against future challenge with wild-type P. aeruginosa. Combined, these data demonstrate that the prrF-encoded sRNAs are critical regulators of P. aeruginosa virulence. PMID:25510881

Recurrent rewiring and emergence of RNA regulatory networks.

PubMed

Wilinski, Daniel; Buter, Natascha; Klocko, Andrew D; Lapointe, Christopher P; Selker, Eric U; Gasch, Audrey P; Wickens, Marvin

2017-04-04

Alterations in regulatory networks contribute to evolutionary change. Transcriptional networks are reconfigured by changes in the binding specificity of transcription factors and their cognate sites. The evolution of RNA-protein regulatory networks is far less understood. The PUF (Pumilio and FBF) family of RNA regulatory proteins controls the translation, stability, and movements of hundreds of mRNAs in a single species. We probe the evolution of PUF-RNA networks by direct identification of the mRNAs bound to PUF proteins in budding and filamentous fungi and by computational analyses of orthologous RNAs from 62 fungal species. Our findings reveal that PUF proteins gain and lose mRNAs with related and emergent biological functions during evolution. We demonstrate at least two independent rewiring events for PUF3 orthologs, independent but convergent evolution of PUF4/5 binding specificity and the rewiring of the PUF4/5 regulons in different fungal lineages. These findings demonstrate plasticity in RNA regulatory networks and suggest ways in which their rewiring occurs.

RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse

PubMed Central

Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin

2015-01-01

Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082

ReNE: A Cytoscape Plugin for Regulatory Network Enhancement

PubMed Central

Politano, Gianfranco; Benso, Alfredo; Savino, Alessandro; Di Carlo, Stefano

2014-01-01

One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by Re

Regulatory gene networks and the properties of the developmental process

NASA Technical Reports Server (NTRS)

Davidson, Eric H.; McClay, David R.; Hood, Leroy

2003-01-01

Genomic instructions for development are encoded in arrays of regulatory DNA. These specify large networks of interactions among genes producing transcription factors and signaling components. The architecture of such networks both explains and predicts developmental phenomenology. Although network analysis is yet in its early stages, some fundamental commonalities are already emerging. Two such are the use of multigenic feedback loops to ensure the progressivity of developmental regulatory states and the prevalence of repressive regulatory interactions in spatial control processes. Gene regulatory networks make it possible to explain the process of development in causal terms and eventually will enable the redesign of developmental regulatory circuitry to achieve different outcomes.

A prior-based integrative framework for functional transcriptional regulatory network inference

PubMed Central

Siahpirani, Alireza F.

2017-01-01

Abstract Transcriptional regulatory networks specify regulatory proteins controlling the context-specific expression levels of genes. Inference of genome-wide regulatory networks is central to understanding gene regulation, but remains an open challenge. Expression-based network inference is among the most popular methods to infer regulatory networks, however, networks inferred from such methods have low overlap with experimentally derived (e.g. ChIP-chip and transcription factor (TF) knockouts) networks. Currently we have a limited understanding of this discrepancy. To address this gap, we first develop a regulatory network inference algorithm, based on probabilistic graphical models, to integrate expression with auxiliary datasets supporting a regulatory edge. Second, we comprehensively analyze our and other state-of-the-art methods on different expression perturbation datasets. Networks inferred by integrating sequence-specific motifs with expression have substantially greater agreement with experimentally derived networks, while remaining more predictive of expression than motif-based networks. Our analysis suggests natural genetic variation as the most informative perturbation for network inference, and, identifies core TFs whose targets are predictable from expression. Multiple reasons make the identification of targets of other TFs difficult, including network architecture and insufficient variation of TF mRNA level. Finally, we demonstrate the utility of our inference algorithm to infer stress-specific regulatory networks and for regulator prioritization. PMID:27794550

Enhancing gene regulatory network inference through data integration with markov random fields

DOE PAGES

Banf, Michael; Rhee, Seung Y.

2017-02-01

Here, a gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization schememore » to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE’s potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation.« less

Enhancing gene regulatory network inference through data integration with markov random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banf, Michael; Rhee, Seung Y.

Here, a gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization schememore » to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE’s potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation.« less

FORUM: Bioinspired Heme, Heme/non-heme Diiron, Heme/copper and Inorganic NOx Chemistry: ·NO(g) Oxidation, Peroxynitrite-Metal Chemistry and ·NO(g) Reductive Coupling

PubMed Central

Schopfer, Mark P.; Wang, Jun; Karlin, Kenneth D.

2010-01-01

The focus of this Forum review highlights work from our own laboratories and those of others in the area of biochemical and biologically inspired inorganic chemistry dealing with nitric oxide (nitrogen monoxide, ·NO(g)) and its biological roles and reactions. The latter focus is on (i) oxidation of ·NO(g) to nitrate by nitric oxide dioxygenases (NOD’s), and (ii) reductive coupling of two molecules of ·NO(g) to give N2O(g). In the former case, NOD’s are described and the highlighting of possible peroxynitrite-heme intermediates and consequences of this are given by discussion of recent works with myoglobin and a synthetic heme model system for NOD action. Summaries of recent copper complex chemistries with ·NO(g) and O2(g) leading to peroxynitrite species are given. The coverage of biological reductive coupling of ·NO(g) deals with bacterial nitric oxide reductases (NOR’s) with heme/non-heme diiron active sites, and on heme/Cu oxidases such as cytochrome c oxidase which can mediate the same chemistry. Recent designed protein and synthetic model compound (heme/non-heme diiron or heme/copper) as functional mimics are discussed in some detail. We also highlight examples from the chemical literature, not necessarily involving biologically relevant metal ions, which describe the oxidation of ·NO(g) to nitrate (or nitrite) and possible peroxynitrite intermediates, or reductive coupling of ·NO(g) to give nitrous oxide. PMID:20666386

Network perturbation by recurrent regulatory variants in cancer

PubMed Central

Cho, Ara; Lee, Insuk; Choi, Jung Kyoon

2017-01-01

Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes. PMID:28333928

Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

PubMed Central

Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

2013-01-01

Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

Visualization of the role of host heme on the virulence of the heme auxotroph Streptococcus agalactiae.

PubMed

Joubert, Laetitia; Dagieu, Jean-Baptiste; Fernandez, Annabelle; Derré-Bobillot, Aurélie; Borezée-Durant, Elise; Fleurot, Isabelle; Gruss, Alexandra; Lechardeur, Delphine

2017-01-16

Heme is essential for several cellular key functions but is also toxic. Whereas most bacterial pathogens utilize heme as a metabolic cofactor and iron source, the impact of host heme during bacterial infection remains elusive. The opportunist pathogen Streptococcus agalactiae does not synthesize heme but still uses it to activate a respiration metabolism. Concomitantly, heme toxicity is mainly controlled by the HrtBA efflux transporter. Here we investigate how S. agalactiae manages heme toxicity versus benefits in the living host. Using bioluminescent bacteria and heme-responsive reporters for in vivo imaging, we show that the capacity of S. agalactiae to overcome heme toxicity is required for successful infection, particularly in blood-rich organs. Host heme is simultaneously required, as visualized by a generalized infection defect of a respiration-negative mutant. In S. agalactiae, HrtBA expression responds to an intracellular heme signal via activation of the two-component system HssRS. A hssRS promoter-driven intracellular luminescent heme sensor was designed to identify host compartments that supply S. agalactiae with heme. S. agalactiae acquires heme in heart, kidneys, and liver, but not in the brain. We conclude that S. agalactiae response to heme is organ-dependent, and its efflux may be particularly relevant in late stages of infection.

Comparative analysis of gene regulatory networks: from network reconstruction to evolution.

PubMed

Thompson, Dawn; Regev, Aviv; Roy, Sushmita

2015-01-01

Regulation of gene expression is central to many biological processes. Although reconstruction of regulatory circuits from genomic data alone is therefore desirable, this remains a major computational challenge. Comparative approaches that examine the conservation and divergence of circuits and their components across strains and species can help reconstruct circuits as well as provide insights into the evolution of gene regulatory processes and their adaptive contribution. In recent years, advances in genomic and computational tools have led to a wealth of methods for such analysis at the sequence, expression, pathway, module, and entire network level. Here, we review computational methods developed to study transcriptional regulatory networks using comparative genomics, from sequence to functional data. We highlight how these methods use evolutionary conservation and divergence to reliably detect regulatory components as well as estimate the extent and rate of divergence. Finally, we discuss the promise and open challenges in linking regulatory divergence to phenotypic divergence and adaptation.

An ethane-bridged porphyrin dimer as a model of di-heme proteins: inorganic and bioinorganic perspectives and consequences of heme-heme interactions.

PubMed

Sil, Debangsu; Rath, Sankar Prasad

2015-10-07

Interaction between heme centers has been cleverly implemented by Nature in order to regulate different properties of multiheme cytochromes, thereby allowing them to perform a wide variety of functions. Our broad interest lies in unmasking the roles played by heme-heme interactions in modulating different properties viz., metal spin state, redox potential etc., of the individual heme centers using an ethane-bridged porphyrin dimer as a synthetic model of dihemes. The large differences in the structure and properties of the diheme complexes, as compared to the monoheme analogs, provide unequivocal evidence of the role played by heme-heme interactions in the dihemes. This Perspective provides a brief account of our recent efforts to explore these interesting aspects and the subsequent outcomes.

Reconstructing directed gene regulatory network by only gene expression data.

PubMed

Zhang, Lu; Feng, Xi Kang; Ng, Yen Kaow; Li, Shuai Cheng

2016-08-18

Accurately identifying gene regulatory network is an important task in understanding in vivo biological activities. The inference of such networks is often accomplished through the use of gene expression data. Many methods have been developed to evaluate gene expression dependencies between transcription factor and its target genes, and some methods also eliminate transitive interactions. The regulatory (or edge) direction is undetermined if the target gene is also a transcription factor. Some methods predict the regulatory directions in the gene regulatory networks by locating the eQTL single nucleotide polymorphism, or by observing the gene expression changes when knocking out/down the candidate transcript factors; regrettably, these additional data are usually unavailable, especially for the samples deriving from human tissues. In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are

Regulatory Snapshots: integrative mining of regulatory modules from expression time series and regulatory networks.

PubMed

Gonçalves, Joana P; Aires, Ricardo S; Francisco, Alexandre P; Madeira, Sara C

2012-01-01

Explaining regulatory mechanisms is crucial to understand complex cellular responses leading to system perturbations. Some strategies reverse engineer regulatory interactions from experimental data, while others identify functional regulatory units (modules) under the assumption that biological systems yield a modular organization. Most modular studies focus on network structure and static properties, ignoring that gene regulation is largely driven by stimulus-response behavior. Expression time series are key to gain insight into dynamics, but have been insufficiently explored by current methods, which often (1) apply generic algorithms unsuited for expression analysis over time, due to inability to maintain the chronology of events or incorporate time dependency; (2) ignore local patterns, abundant in most interesting cases of transcriptional activity; (3) neglect physical binding or lack automatic association of regulators, focusing mainly on expression patterns; or (4) limit the discovery to a predefined number of modules. We propose Regulatory Snapshots, an integrative mining approach to identify regulatory modules over time by combining transcriptional control with response, while overcoming the above challenges. Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time. Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data. Custom graphics are finally depicted to expose the regulatory activity in a module at consecutive time points (snapshots). Regulatory Snapshots successfully unraveled modules underlying yeast response to heat shock and human epithelial-to-mesenchymal transition, based on regulations documented in the YEASTRACT and JASPAR databases, respectively, and available expression data. Regulatory players involved in functionally enriched

Regulatory Snapshots: Integrative Mining of Regulatory Modules from Expression Time Series and Regulatory Networks

PubMed Central

Gonçalves, Joana P.; Aires, Ricardo S.; Francisco, Alexandre P.; Madeira, Sara C.

2012-01-01

Explaining regulatory mechanisms is crucial to understand complex cellular responses leading to system perturbations. Some strategies reverse engineer regulatory interactions from experimental data, while others identify functional regulatory units (modules) under the assumption that biological systems yield a modular organization. Most modular studies focus on network structure and static properties, ignoring that gene regulation is largely driven by stimulus-response behavior. Expression time series are key to gain insight into dynamics, but have been insufficiently explored by current methods, which often (1) apply generic algorithms unsuited for expression analysis over time, due to inability to maintain the chronology of events or incorporate time dependency; (2) ignore local patterns, abundant in most interesting cases of transcriptional activity; (3) neglect physical binding or lack automatic association of regulators, focusing mainly on expression patterns; or (4) limit the discovery to a predefined number of modules. We propose Regulatory Snapshots, an integrative mining approach to identify regulatory modules over time by combining transcriptional control with response, while overcoming the above challenges. Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time. Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data. Custom graphics are finally depicted to expose the regulatory activity in a module at consecutive time points (snapshots). Regulatory Snapshots successfully unraveled modules underlying yeast response to heat shock and human epithelial-to-mesenchymal transition, based on regulations documented in the YEASTRACT and JASPAR databases, respectively, and available expression data. Regulatory players involved in functionally enriched

Prebiotics increase heme iron bioavailability and do not affect non-heme iron bioavailability in humans.

PubMed

Weinborn, Valerie; Valenzuela, Carolina; Olivares, Manuel; Arredondo, Miguel; Weill, Ricardo; Pizarro, Fernando

2017-05-24

The aim of this study was to establish the effect of a prebiotic mix on heme and non-heme iron (Fe) bioavailability in humans. To this purpose, twenty-four healthy women were randomized into one of two study groups. One group ate one yogurt per day for 12 days with a prebiotic mix (prebiotic group) and the other group received the same yogurt but without the prebiotic mix (control group). Before and after the intake period, the subjects participated in Fe absorption studies. These studies used 55 Fe and 59 Fe radioactive isotopes as markers of heme Fe and non-heme Fe, respectively, and Fe absorption was measured by the incorporation of radioactive Fe into erythrocytes. The results showed that there were no significant differences in heme and non-heme Fe bioavailability in the control group. Heme Fe bioavailability of the prebiotic group increased significantly by 56% post-prebiotic intake. There were no significant differences in non-heme Fe bioavailability in this group. We concluded that daily consumption of a prebiotic mix increases heme Fe bioavailability and does not affect non-heme iron bioavailability.

Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions

PubMed Central

2014-01-01

Background Plant secondary metabolites are critical to various biological processes. However, the regulations of these metabolites are complex because of regulatory rewiring or crosstalk. To unveil how regulatory behaviors on secondary metabolism reshape biological processes, we constructed and analyzed a dynamic regulatory network of secondary metabolic pathways in Arabidopsis. Results The dynamic regulatory network was constructed through integrating co-expressed gene pairs and regulatory interactions. Regulatory interactions were either predicted by conserved transcription factor binding sites (TFBSs) or proved by experiments. We found that integrating two data (co-expression and predicted regulatory interactions) enhanced the number of highly confident regulatory interactions by over 10% compared with using single data. The dynamic changes of regulatory network systematically manifested regulatory rewiring to explain the mechanism of regulation, such as in terpenoids metabolism, the regulatory crosstalk of RAV1 (AT1G13260) and ATHB1 (AT3G01470) on HMG1 (hydroxymethylglutaryl-CoA reductase, AT1G76490); and regulation of RAV1 on epoxysqualene biosynthesis and sterol biosynthesis. Besides, we investigated regulatory rewiring with expression, network topology and upstream signaling pathways. Regulatory rewiring was revealed by the variability of genes’ expression: pathway genes and transcription factors (TFs) were significantly differentially expressed under different conditions (such as terpenoids biosynthetic genes in tissue experiments and E2F/DP family members in genotype experiments). Both network topology and signaling pathways supported regulatory rewiring. For example, we discovered correlation among the numbers of pathway genes, TFs and network topology: one-gene pathways (such as δ-carotene biosynthesis) were regulated by a fewer TFs, and were not critical to metabolic network because of their low degrees in topology. Upstream signaling pathways of 50

Harnessing Diversity towards the Reconstructing of Large Scale Gene Regulatory Networks

PubMed Central

Yamanaka, Ryota; Kitano, Hiroaki

2013-01-01

Elucidating gene regulatory network (GRN) from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i) a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii) TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks. PMID:24278007

Reverse engineering highlights potential principles of large gene regulatory network design and learning.

PubMed

Carré, Clément; Mas, André; Krouk, Gabriel

2017-01-01

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 10 4 genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data ( Escherichia coli K14 network

SATRAT: Staphylococcus aureus transcript regulatory network analysis tool.

PubMed

Gopal, Tamilselvi; Nagarajan, Vijayaraj; Elasri, Mohamed O

2015-01-01

Staphylococcus aureus is a commensal organism that primarily colonizes the nose of healthy individuals. S. aureus causes a spectrum of infections that range from skin and soft-tissue infections to fatal invasive diseases. S. aureus uses a large number of virulence factors that are regulated in a coordinated fashion. The complex regulatory mechanisms have been investigated in numerous high-throughput experiments. Access to this data is critical to studying this pathogen. Previously, we developed a compilation of microarray experimental data to enable researchers to search, browse, compare, and contrast transcript profiles. We have substantially updated this database and have built a novel exploratory tool-SATRAT-the S. aureus transcript regulatory network analysis tool, based on the updated database. This tool is capable of performing deep searches using a query and generating an interactive regulatory network based on associations among the regulators of any query gene. We believe this integrated regulatory network analysis tool would help researchers explore the missing links and identify novel pathways that regulate virulence in S. aureus. Also, the data model and the network generation code used to build this resource is open sourced, enabling researchers to build similar resources for other bacterial systems.

Modeling gene regulatory networks: A network simplification algorithm

NASA Astrophysics Data System (ADS)

Ferreira, Luiz Henrique O.; de Castro, Maria Clicia S.; da Silva, Fabricio A. B.

2016-12-01

Boolean networks have been used for some time to model Gene Regulatory Networks (GRNs), which describe cell functions. Those models can help biologists to make predictions, prognosis and even specialized treatment when some disturb on the GRN lead to a sick condition. However, the amount of information related to a GRN can be huge, making the task of inferring its boolean network representation quite a challenge. The method shown here takes into account information about the interactome to build a network, where each node represents a protein, and uses the entropy of each node as a key to reduce the size of the network, allowing the further inferring process to focus only on the main protein hubs, the ones with most potential to interfere in overall network behavior.

Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.

Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189

DevS, a heme-containing two-component oxygen sensor of Mycobacterium tuberculosis.

PubMed

Ioanoviciu, Alexandra; Yukl, Erik T; Moënne-Loccoz, Pierre; de Montellano, Paul R Ortiz

2007-04-10

Mycobacterium tuberculosis can exist in the actively growing state of the overt disease or in a latent quiescent state that can be induced, among other things, by anaerobiosis. Eradication of the latent state is particularly difficult with the available drugs and requires prolonged treatment. DevS is a member of the DevS-DevR two-component regulatory system that is thought to mediate the cellular response to anaerobiosis. Here we report the cloning, expression, and initial characterization of a truncated version of DevS (DevS642) containing only the N-terminal GAF sensor domain (GAF-A) and of the full-length protein DevS. The DevS truncated construct quantitatively binds heme in a 1:1 stoichiometry, and the complex of the protein with ferrous heme reversibly binds O2, NO, and CO. UV-vis and resonance Raman spectroscopy of the wild-type protein and the H149A mutant confirm that His149 is the proximal ligand to the heme iron atom. While the heme-CO complex is present as two conformers in the GAF-A domain, a single set of [Fe-C-O] vibrations is observed with the full-length protein, suggesting that interactions between domains within DevS influence the distal pocket environment of the heme in the GAF-A domain.

Gene regulatory networks and the underlying biology of developmental toxicity

EPA Science Inventory

Embryonic cells are specified by large-scale networks of functionally linked regulatory genes. Knowledge of the relevant gene regulatory networks is essential for understanding phenotypic heterogeneity that emerges from disruption of molecular functions, cellular processes or sig...

Probabilistic representation of gene regulatory networks.

PubMed

Mao, Linyong; Resat, Haluk

2004-09-22

Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation. In this paper, we present a new fully probabilistic approach to the modeling of gene regulatory networks that allows for fluctuations in the gene expression levels. The new algorithm uses a very simple representation for the genes, and accounts for the repression or induction of the genes and for the biological variations among isogenic populations simultaneously. Because of its simplicity, introduced algorithm is a very promising approach to model large-scale gene regulatory networks. We have tested the new algorithm on the synthetic gene network library bioengineered recently. The good agreement between the computed and the experimental results for this library of networks, and additional tests, demonstrate that the new algorithm is robust and very successful in explaining the experimental data. The simulation software is available upon request. Supplementary material will be made available on the OUP server.

Markov State Models of gene regulatory networks.

PubMed

Chu, Brian K; Tse, Margaret J; Sato, Royce R; Read, Elizabeth L

2017-02-06

Gene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking. The method identifies the number, phenotypes, and lifetimes of long-lived states for a set of common gene regulatory network models. Application of transition path theory to the constructed Markov State Model decomposes global dynamics into a set of dominant transition paths and associated relative probabilities for stochastic state-switching. In this proof-of-concept study, we found that the Markov State Model provides a general framework for analyzing and visualizing stochastic multistability and state-transitions in gene networks. Our results suggest that this framework-adopted from the field of atomistic Molecular Dynamics-can be a useful tool for quantitative Systems Biology at the network scale.

Inference of cancer-specific gene regulatory networks using soft computing rules.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

PubMed Central

Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

2012-01-01

Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to

The regulatory network analysis of long noncoding RNAs in human colorectal cancer.

PubMed

Zhang, Yuwei; Tao, Yang; Li, Yang; Zhao, Jinshun; Zhang, Lina; Zhang, Xiaohong; Dong, Changzheng; Xie, Yangyang; Dai, Xiaoyu; Zhang, Xinjun; Liao, Qi

2018-05-01

Colorectal cancer (CRC) is among one of the most prevalent and lethiferous diseases worldwide. Long noncoding RNAs (lncRNAs) are commonly accepted to function as a key regulatory factor in human cancer, but the potential regulatory mechanisms of CRC-associated lncRNA are largely obscure. Here, we integrated several expression profiles to obtain 55 differentially expressed (DE) lncRNAs. We first detected lncRNA interactions with transcription factors, microRNAs, mRNAs, and RNA-binding proteins to construct a regulatory network and then create functional enrichment analyses for them using bioinformatics approaches. We found the upregulated genes in the regulatory network are enriched in cell cycle and DNA damage response, while the downregulated genes are enriched in cell differentiation, cellular response, and cell signaling. We then employed module-based methods to mine several intriguing modules from the overall network, which helps to classify the functions of genes more specifically. Next, we confirmed the validity of our network by comparisons with a randomized network using computational method. Finally, we attempted to annotate lncRNA functions based on the regulatory network, which indicated its potential application. Our study of the lncRNA regulatory network provided significant clues to unveil lncRNAs potential regulatory mechanisms in CRC and laid a foundation for further experimental investigation.

Sequence-based model of gap gene regulatory network.

PubMed

Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

2014-01-01

The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3

Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

PubMed

Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina

2015-01-01

Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

Structure of the Escherichia coli O157:H7 heme oxygenase ChuS in complex with heme and enzymatic inactivation by mutation of the heme coordinating residue His-193

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suits,M.; Jaffer, N.; Jia, Z.

2006-01-01

Heme oxygenases catalyze the oxidation of heme to biliverdin, CO, and free iron. For pathogenic microorganisms, heme uptake and degradation are critical mechanisms for iron acquisition that enable multiplication and survival within hosts they invade. Here we report the first crystal structure of the pathogenic Escherichia coli O157:H7 heme oxygenase ChuS in complex with heme at 1.45 {angstrom} resolution. When compared with other heme oxygenases, ChuS has a unique fold, including structural repeats and a {beta}-sheet core. Not surprisingly, the mode of heme coordination by ChuS is also distinct, whereby heme is largely stabilized by residues from the C-terminal domain,more » assisted by a distant arginine from the N-terminal domain. Upon heme binding, there is no large conformational change beyond the fine tuning of a key histidine (His-193) residue. Most intriguingly, in contrast to other heme oxygenases, the propionic side chains of heme are orientated toward the protein core, exposing the {alpha}-meso carbon position where O{sub 2} is added during heme degradation. This unique orientation may facilitate presentation to an electron donor, explaining the significantly reduced concentration of ascorbic acid needed for the reaction. Based on the ChuS-heme structure, we converted the histidine residue responsible for axial coordination of the heme group to an asparagine residue (H193N), as well as converting a second histidine to an alanine residue (H73A) for comparison purposes. We employed spectral analysis and CO measurement by gas chromatography to analyze catalysis by ChuS, H193N, and H73A, demonstrating that His-193 is the key residue for the heme-degrading activity of ChuS.« less

Transcriptional Regulatory Networks in Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Lee, Tong Ihn; Rinaldi, Nicola J.; Robert, François; Odom, Duncan T.; Bar-Joseph, Ziv; Gerber, Georg K.; Hannett, Nancy M.; Harbison, Christopher T.; Thompson, Craig M.; Simon, Itamar; Zeitlinger, Julia; Jennings, Ezra G.; Murray, Heather L.; Gordon, D. Benjamin; Ren, Bing; Wyrick, John J.; Tagne, Jean-Bosco; Volkert, Thomas L.; Fraenkel, Ernest; Gifford, David K.; Young, Richard A.

2002-10-01

We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.

Uncovering MicroRNA and Transcription Factor Mediated Regulatory Networks in Glioblastoma

PubMed Central

Sun, Jingchun; Gong, Xue; Purow, Benjamin; Zhao, Zhongming

2012-01-01

Glioblastoma multiforme (GBM) is the most common and lethal brain tumor in humans. Recent studies revealed that patterns of microRNA (miRNA) expression in GBM tissue samples are different from those in normal brain tissues, suggesting that a number of miRNAs play critical roles in the pathogenesis of GBM. However, little is yet known about which miRNAs play central roles in the pathology of GBM and their regulatory mechanisms of action. To address this issue, in this study, we systematically explored the main regulation format (feed-forward loops, FFLs) consisting of miRNAs, transcription factors (TFs) and their impacting GBM-related genes, and developed a computational approach to construct a miRNA-TF regulatory network. First, we compiled GBM-related miRNAs, GBM-related genes, and known human TFs. We then identified 1,128 3-node FFLs and 805 4-node FFLs with statistical significance. By merging these FFLs together, we constructed a comprehensive GBM-specific miRNA-TF mediated regulatory network. Then, from the network, we extracted a composite GBM-specific regulatory network. To illustrate the GBM-specific regulatory network is promising for identification of critical miRNA components, we specifically examined a Notch signaling pathway subnetwork. Our follow up topological and functional analyses of the subnetwork revealed that six miRNAs (miR-124, miR-137, miR-219-5p, miR-34a, miR-9, and miR-92b) might play important roles in GBM, including some results that are supported by previous studies. In this study, we have developed a computational framework to construct a miRNA-TF regulatory network and generated the first miRNA-TF regulatory network for GBM, providing a valuable resource for further understanding the complex regulatory mechanisms in GBM. The observation of critical miRNAs in the Notch signaling pathway, with partial verification from previous studies, demonstrates that our network-based approach is promising for the identification of new and important

Population Dynamics of Genetic Regulatory Networks

NASA Astrophysics Data System (ADS)

Braun, Erez

2005-03-01

Unlike common objects in physics, a biological cell processes information. The cell interprets its genome and transforms the genomic information content, through the action of genetic regulatory networks, into proteins which in turn dictate its metabolism, functionality and morphology. Understanding the dynamics of a population of biological cells presents a unique challenge. It requires to link the intracellular dynamics of gene regulation, through the mechanism of cell division, to the level of the population. We present experiments studying adaptive dynamics of populations of genetically homogeneous microorganisms (yeast), grown for long durations under steady conditions. We focus on population dynamics that do not involve random genetic mutations. Our experiments follow the long-term dynamics of the population distributions and allow to quantify the correlations among generations. We focus on three interconnected issues: adaptation of genetically homogeneous populations following environmental changes, selection processes on the population and population variability and expression distributions. We show that while the population exhibits specific short-term responses to environmental inputs, it eventually adapts to a robust steady-state, largely independent of external conditions. Cycles of medium-switch show that the adapted state is imprinted in the population and that this memory is maintained for many generations. To further study population adaptation, we utilize the process of gene recruitment whereby a gene naturally regulated by a specific promoter is placed under a different regulatory system. This naturally occurring process has been recognized as a major driving force in evolution. We have recruited an essential gene to a foreign regulatory network and followed the population long-term dynamics. Rewiring of the regulatory network allows us to expose their complex dynamics and phase space structure.

Efficient experimental design for uncertainty reduction in gene regulatory networks.

PubMed

Dehghannasiri, Roozbeh; Yoon, Byung-Jun; Dougherty, Edward R

2015-01-01

An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/.

Genomic analysis of the hierarchical structure of regulatory networks

PubMed Central

Yu, Haiyuan; Gerstein, Mark

2006-01-01

A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

Empirical Bayes conditional independence graphs for regulatory network recovery.

PubMed

Mahdi, Rami; Madduri, Abishek S; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R; Crystal, Ronald G; Mezey, Jason G

2012-08-01

Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary data are available at Bioinformatics online.

Gene regulatory network inference using fused LASSO on multiple data sets

PubMed Central

Omranian, Nooshin; Eloundou-Mbebi, Jeanne M. O.; Mueller-Roeber, Bernd; Nikoloski, Zoran

2016-01-01

Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions. PMID:26864687

[Heme-iron in the human body].

PubMed

Balla, József; Balla, György; Lakatos, Béla; Jeney, Viktória; Szentmihályi, Klára

2007-09-09

Iron is essential for all living organism, although in excess amount it is dangerous via catalyzing the formation of reactive oxygen species. Absorption of iron is strictly controlled resulting in a fine balance of iron-loss and iron-uptake. In countries where the ingestion of heme-iron is significant by meal, great part of iron content in the body originates from heme. Heme derived from food is absorbed by a receptor-mediated manner by enterocytes of small intestine then it is degraded in a reaction catalyzed by heme oxygenase. Iron released from the porphyrin ring leaves enterocytes as transferrin associated iron. Prosthetic group of several proteins contains heme, therefore, it is synthesized by all cells. One of the most significant heme proteins is hemoglobin which transports oxygen in the erythrocytes. Hemoglobin released from erythrocyte during intravascular hemolysis binds to haptoglobin and is taken up by cells of the monocyte-macrophage lineage. Oxidation of hemoglobin (ferro) to methemoglobin (ferri) is inhibited by the structure of hemoglobin although it is not hindered. Superoxide anion is also formed in the reaction that initiates further free radical reactions. In contrast to ferrohemoglobin, methemoglobin readily releases heme, therefore, oxidation of hemoglobin drives the formation of free heme in plasma. Heme binds to a plasma protein, hemopexin, and is internalized by cells of monocyte-macrophage lineage in a receptor-mediated manner, then degraded in reaction catalysed by heme oxygenase. Heme is also taken up by plasma lipoproteins and endothelial cells leading to oxidation of LDL and subsequent endothelial cell damage. The purpose of this work was to summarize the processes related to heme.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks

PubMed Central

2018-01-01

Abstract Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element–target gene pairs (E–G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. PMID:29140525

Efficient experimental design for uncertainty reduction in gene regulatory networks

PubMed Central

2015-01-01

Background An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. Results The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Conclusions Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/. PMID:26423515

Variable neighborhood search for reverse engineering of gene regulatory networks.

PubMed

Nicholson, Charles; Goodwin, Leslie; Clark, Corey

2017-01-01

A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterization of plasma labile heme in hemolytic conditions

PubMed Central

Gouveia, Zélia; Carlos, Ana R.; Yuan, Xiaojing; Aires-da-Silva, Frederico; Stocker, Roland; Maghzal, Ghassan J.; Leal, Sónia S.; Gomes, Cláudio M.; Todorovic, Smilja; Iranzo, Olga; Ramos, Susana; Santos, Ana C.; Hamza, Iqbal; Gonçalves, João; Soares, Miguel P.

2018-01-01

Extracellular hemoglobin, a byproduct of hemolysis, can release its prosthetic heme groups upon oxidation. This produces metabolically active heme that is exchangeable between acceptor proteins, macromolecules and low molecular weight ligands, termed here labile heme. As it accumulates in plasma labile heme acts in a pro-oxidant manner and regulates cellular metabolism while exerting pro-inflammatory and cytotoxic effects that foster the pathogenesis of hemolytic diseases. Here, we developed and characterized a panel of heme-specific single domain antibodies (sdAbs) that together with a cellular-based heme reporter assay, allow for quantification and characterization of labile heme in plasma during hemolytic conditions. Using these approaches, we demonstrate that when generated during hemolytic conditions labile heme is bound to plasma molecules with an affinity higher than 10−7 m and that 2–8% (∼ 2–5 μm) of the total amount of heme detected in plasma can be internalized by bystander cells, termed here bioavailable heme. Acute, but not chronic, hemolysis is associated with transient reduction of plasma heme-binding capacity, that is, the ability of plasma molecules to bind labile heme with an affinity higher than 10−7 m. The heme-specific sdAbs neutralize the pro-oxidant activity of soluble heme in vitro, suggesting that these maybe used to counter the pathologic effects of labile heme during hemolytic conditions. Finally, we show that heme-specific sdAbs can be used to visualize cellular heme. In conclusion, we describe a panel of heme-specific sdAbs that when used with other approaches provide novel insights to the pathophysiology of heme. PMID:28783254

Portrait of Candida Species Biofilm Regulatory Network Genes.

PubMed

Araújo, Daniela; Henriques, Mariana; Silva, Sónia

2017-01-01

Most cases of candidiasis have been attributed to Candida albicans, but Candida glabrata, Candida parapsilosis and Candida tropicalis, designated as non-C. albicans Candida (NCAC), have been identified as frequent human pathogens. Moreover, Candida biofilms are an escalating clinical problem associated with significant rates of mortality. Biofilms have distinct developmental phases, including adhesion/colonisation, maturation and dispersal, controlled by complex regulatory networks. This review discusses recent advances regarding Candida species biofilm regulatory network genes, which are key components for candidiasis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Understanding genetic regulatory networks

NASA Astrophysics Data System (ADS)

Kauffman, Stuart

2003-04-01

Random Boolean networks (RBM) were introduced about 35 years ago as first crude models of genetic regulatory networks. RBNs are comprised of N on-off genes, connected by a randomly assigned regulatory wiring diagram where each gene has K inputs, and each gene is controlled by a randomly assigned Boolean function. This procedure samples at random from the ensemble of all possible NK Boolean networks. The central ideas are to study the typical, or generic properties of this ensemble, and see 1) whether characteristic differences appear as K and biases in Boolean functions are introducted, and 2) whether a subclass of this ensemble has properties matching real cells. Such networks behave in an ordered or a chaotic regime, with a phase transition, "the edge of chaos" between the two regimes. Networks with continuous variables exhibit the same two regimes. Substantial evidence suggests that real cells are in the ordered regime. A key concept is that of an attractor. This is a reentrant trajectory of states of the network, called a state cycle. The central biological interpretation is that cell types are attractors. A number of properties differentiate the ordered and chaotic regimes. These include the size and number of attractors, the existence in the ordered regime of a percolating "sea" of genes frozen in the on or off state, with a remainder of isolated twinkling islands of genes, a power law distribution of avalanches of gene activity changes following perturbation to a single gene in the ordered regime versus a similar power law distribution plus a spike of enormous avalanches of gene changes in the chaotic regime, and the existence of branching pathway of "differentiation" between attractors induced by perturbations in the ordered regime. Noise is serious issue, since noise disrupts attractors. But numerical evidence suggests that attractors can be made very stable to noise, and meanwhile, metaplasias may be a biological manifestation of noise. As we learn more

Automatic inference of multicellular regulatory networks using informative priors.

PubMed

Sun, Xiaoyun; Hong, Pengyu

2009-01-01

To fully understand the mechanisms governing animal development, computational models and algorithms are needed to enable quantitative studies of the underlying regulatory networks. We developed a mathematical model based on dynamic Bayesian networks to model multicellular regulatory networks that govern cell differentiation processes. A machine-learning method was developed to automatically infer such a model from heterogeneous data. We show that the model inference procedure can be greatly improved by incorporating interaction data across species. The proposed approach was applied to C. elegans vulval induction to reconstruct a model capable of simulating C. elegans vulval induction under 73 different genetic conditions.

The Reconstruction and Analysis of Gene Regulatory Networks.

PubMed

Zheng, Guangyong; Huang, Tao

2018-01-01

In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

PubMed

Guo, Liyuan; Wang, Jing

2018-01-04

Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Insulin enhances the peroxidase activity of heme by forming heme-insulin complex: Relevance to type 2 diabetes mellitus.

PubMed

Huang, Yi; Yang, Zhen; Xu, Huan; Zhang, Pengfei; Gao, Zhonghong; Li, Hailing

2017-09-01

Evidences have implicated the involvement of heme in the type 2 diabetes mellitus (T2Dm) pathogenesis, but possible mediators linking between heme and diabetes are still poorly understood. Here, we explored a potential mechanism that linked heme, insulin and diabetes. Our results demonstrated the formation of heme-insulin complex by two classical methods, i.e. UV-vis and capillary electrophoresis-frontal analysis (CE-FA). UV-vis results implied heme binding insulin via bis-histidine sites, and CE-FA further revealed that, when insulin uses two sites binding with heme, this interaction occurs at high affinity (K d =3.13×10 -6 M). Molecule docking supported that histidine-B5 of insulin binds with heme-Fe. In addition to that, tyrosine-B26, phenylalanine-B1 and valine-B2 are also contributed to binding heme. The binding amplified the peroxidase activity of heme itself. Under oxidative and nitrative stress, it affects pathogenesis of diabetes from two aspects: promoting insulin cross-linking that leads to permanent loss of insulin functionality on one hand, and enhancing protein tyrosine nitration that may result in inactivation of proteins associated with diabetes on the other hand. This study suggested that the enhanced peroxidase activity of heme through binding with insulin might be a previously unrecognized contributor to the pathogenesis of T2Dm in some heme-associated disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

NASA Astrophysics Data System (ADS)

Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

2018-04-01

The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

PCBP1 and NCOA4 regulate erythroid iron storage and heme biosynthesis

PubMed Central

Ryu, Moon-Suhn; Zhang, Deliang; Protchenko, Olga; Shakoury-Elizeh, Minoo

2017-01-01

Developing erythrocytes take up exceptionally large amounts of iron, which must be transferred to mitochondria for incorporation into heme. This massive iron flux must be precisely controlled to permit the coordinated synthesis of heme and hemoglobin while avoiding the toxic effects of chemically reactive iron. In cultured animal cells, iron chaperones poly rC–binding protein 1 (PCBP1) and PCBP2 deliver iron to ferritin, the sole cytosolic iron storage protein, and nuclear receptor coactivator 4 (NCOA4) mediates the autophagic turnover of ferritin. The roles of PCBP, ferritin, and NCOA4 in erythroid development remain unclear. Here, we show that PCBP1, NCOA4, and ferritin are critical for murine red cell development. Using a cultured cell model of erythroid differentiation, depletion of PCBP1 or NCOA4 impaired iron trafficking through ferritin, which resulted in reduced heme synthesis, reduced hemoglobin formation, and perturbation of erythroid regulatory systems. Mice lacking Pcbp1 exhibited microcytic anemia and activation of compensatory erythropoiesis via the regulators erythropoietin and erythroferrone. Ex vivo differentiation of erythroid precursors from Pcbp1-deficient mice confirmed defects in ferritin iron flux and heme synthesis. These studies demonstrate the importance of ferritin for the vectorial transfer of imported iron to mitochondria in developing red cells and of PCBP1 and NCOA4 in mediating iron flux through ferritin. PMID:28375153

Heme Catabolism by Heme Oxygenase-1 Confers Host Resistance to Mycobacterium Infection

PubMed Central

Silva-Gomes, Sandro; Appelberg, Rui; Larsen, Rasmus; Soares, Miguel Parreira

2013-01-01

Heme oxygenases (HO) catalyze the rate-limiting step of heme degradation. The cytoprotective action of the inducible HO-1 isoform, encoded by the Hmox1 gene, is required for host protection against systemic infections. Here we report that upregulation of HO-1 expression in macrophages (Mϕ) is strictly required for protection against mycobacterial infection in mice. HO-1-deficient (Hmox1−/−) mice are more susceptible to intravenous Mycobacterium avium infection, failing to mount a protective granulomatous response and developing higher pathogen loads, than infected wild-type (Hmox1+/+) controls. Furthermore, Hmox1−/− mice also develop higher pathogen loads and ultimately succumb when challenged with a low-dose aerosol infection with Mycobacterium tuberculosis. The protective effect of HO-1 acts independently of adaptive immunity, as revealed in M. avium-infected Hmox1−/− versus Hmox1+/+ SCID mice lacking mature B and T cells. In the absence of HO-1, heme accumulation acts as a cytotoxic pro-oxidant in infected Mϕ, an effect mimicked by exogenous heme administration to M. avium-infected wild-type Mϕ in vitro or to mice in vivo. In conclusion, HO-1 prevents the cytotoxic effect of heme in Mϕ, contributing critically to host resistance to Mycobacterium infection. PMID:23630967

Heme Distortions in Sperm-Whale Carbonmonoxy Myoglobin: Correlations between Rotational Strengths and Heme Distortions in MD-Generated Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

KIEFL,CHRISTOPH; SCREERAMA,NARASIMHA; LU,YI

2000-07-13

The authors have investigated the effects of heme rotational isomerism in sperm-whale carbonmonoxy myoglobin using computational techniques. Several molecular dynamics simulations have been performed for the two rotational isomers A and B, which are related by a 180{degree} rotation around the {alpha}-{gamma} axis of the heme, of sperm-whale carbonmonoxy myoglobin in water. Both neutron diffraction and NMR structures were used as starting structures. In the absence of an experimental structure, the structure of isomer B was generated by rotating the heme in the structure of isomer A. Distortions of the heme from planarity were characterized by normal coordinate structural decompositionmore » and by the angle of twist of the pyrrole rings from the heme plane. The heme distortions of the neutron diffraction structure were conserved in the MD trajectories, but in the NMR-based trajectories, where the heme distortions are less well defined, they differ from the original heme deformations. The protein matrix induced similar distortions on the heroes in orientations A and B. The results suggest that the binding site prefers a particular macrocycle conformation, and a 180{degree} rotation of the heme does not significantly alter the protein's preference for this conformation. The intrinsic rotational strengths of the two Soret transitions, separated according to their polarization in the heme plane, show strong correlations with the ruf-deformation and the average twist angle of the pyrrole rings. The total rotational strength, which includes contributions from the chromophores in the protein, shows a weaker correlation with heme distortions.« less

Genome-wide inference of regulatory networks in Streptomyces coelicolor.

PubMed

Castro-Melchor, Marlene; Charaniya, Salim; Karypis, George; Takano, Eriko; Hu, Wei-Shou

2010-10-18

The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Modelling and analysis of gene regulatory network using feedback control theory

NASA Astrophysics Data System (ADS)

El-Samad, H.; Khammash, M.

2010-01-01

Molecular pathways are a part of a remarkable hierarchy of regulatory networks that operate at all levels of organisation. These regulatory networks are responsible for much of the biological complexity within the cell. The dynamic character of these pathways and the prevalence of feedback regulation strategies in their operation make them amenable to systematic mathematical analysis using the same tools that have been used with success in analysing and designing engineering control systems. In this article, we aim at establishing this strong connection through various examples where the behaviour exhibited by gene networks is explained in terms of their underlying control strategies. We complement our analysis by a survey of mathematical techniques commonly used to model gene regulatory networks and analyse their dynamic behaviour.

Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities

PubMed Central

2011-01-01

Background Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Understanding the connections and the activity levels of regulators is important for the research of gene regulatory networks. While relevance score based algorithms that reconstruct gene regulatory networks from transcriptome data can infer genome-wide gene regulatory networks, they are unfortunately prone to false positive results. Transcription factor activities (TFAs) quantitatively reflect the ability of the transcription factor to regulate target genes. However, classic relevance score based gene regulatory network reconstruction algorithms use models do not include the TFA layer, thus missing a key regulatory element. Results This work integrates TFA prediction algorithms with relevance score based network reconstruction algorithms to reconstruct gene regulatory networks with improved accuracy over classic relevance score based algorithms. This method is called Gene expression and Transcription factor activity based Relevance Network (GTRNetwork). Different combinations of TFA prediction algorithms and relevance score functions have been applied to find the most efficient combination. When the integrated GTRNetwork method was applied to E. coli data, the reconstructed genome-wide gene regulatory network predicted 381 new regulatory links. This reconstructed gene regulatory network including the predicted new regulatory links show promising biological significances. Many of the new links are verified by known TF binding site information, and many other links can be verified from the literature and databases such as EcoCyc. The reconstructed gene regulatory network is applied to a recent transcriptome analysis of E. coli during isobutanol stress. In addition to the 16 significantly changed TFAs detected in the original paper, another 7 significantly changed TFAs have been detected by

Competing endogenous RNA regulatory network in papillary thyroid carcinoma.

PubMed

Chen, Shouhua; Fan, Xiaobin; Gu, He; Zhang, Lili; Zhao, Wenhua

2018-05-11

The present study aimed to screen all types of RNAs involved in the development of papillary thyroid carcinoma (PTC). RNA‑sequencing data of PTC and normal samples were used for screening differentially expressed (DE) microRNAs (DE‑miRNAs), long non‑coding RNAs (DE‑lncRNAs) and genes (DEGs). Subsequently, lncRNA‑miRNA, miRNA‑gene (that is, miRNA‑mRNA) and gene‑gene interaction pairs were extracted and used to construct regulatory networks. Feature genes in the miRNA‑mRNA network were identified by topological analysis and recursive feature elimination analysis. A support vector machine (SVM) classifier was built using 15 feature genes, and its classification effect was validated using two microarray data sets that were downloaded from the Gene Expression Omnibus (GEO) database. In addition, Gene Ontology function and Kyoto Encyclopedia Genes and Genomes pathway enrichment analyses were conducted for genes identified in the ceRNA network. A total of 506 samples, including 447 tumor samples and 59 normal samples, were obtained from The Cancer Genome Atlas (TCGA); 16 DE‑lncRNAs, 917 DEGs and 30 DE‑miRNAs were screened. The miRNA‑mRNA regulatory network comprised 353 nodes and 577 interactions. From these data, 15 feature genes with high predictive precision (>95%) were extracted from the network and were used to form an SVM classifier with an accuracy of 96.05% (486/506) for PTC samples downloaded from TCGA, and accuracies of 96.81 and 98.46% for GEO downloaded data sets. The ceRNA regulatory network comprised 596 lines (or interactions) and 365 nodes. Genes in the ceRNA network were significantly enriched in 'neuron development', 'differentiation', 'neuroactive ligand‑receptor interaction', 'metabolism of xenobiotics by cytochrome P450', 'drug metabolism' and 'cytokine‑cytokine receptor interaction' pathways. Hox transcript antisense RNA, miRNA‑206 and kallikrein‑related peptidase 10 were nodes in the ceRNA regulatory network

Learning a Markov Logic network for supervised gene regulatory network inference

PubMed Central

2013-01-01

Background Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. Results We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate “regulates”, starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black

Learning a Markov Logic network for supervised gene regulatory network inference.

PubMed

Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

2013-09-12

Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a

A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

NASA Technical Reports Server (NTRS)

Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar;

A Heme-responsive Regulator Controls Synthesis of Staphyloferrin B in Staphylococcus aureus*♦

PubMed Central

Laakso, Holly A.; Marolda, Cristina L.; Pinter, Tyler B.; Stillman, Martin J.; Heinrichs, David E.

2016-01-01

Staphylococcus aureus possesses a multitude of mechanisms by which it can obtain iron during growth under iron starvation conditions. It expresses an effective heme acquisition system (the iron-regulated surface determinant system), it produces two carboxylate-type siderophores staphyloferrin A and staphyloferrin B (SB), and it expresses transporters for many other siderophores that it does not synthesize. The ferric uptake regulator protein regulates expression of genes encoding all of these systems. Mechanisms of fine-tuning expression of iron-regulated genes, beyond simple iron regulation via ferric uptake regulator, have not been uncovered in this organism. Here, we identify the ninth gene of the sbn operon, sbnI, as encoding a ParB/Spo0J-like protein that is required for expression of genes in the sbn operon from sbnD onward. Expression of sbnD–I is drastically decreased in an sbnI mutant, and the mutant does not synthesize detectable SB during early phases of growth. Thus, SB-mediated iron acquisition is impaired in an sbnI mutant strain. We show that the protein forms dimers and tetramers in solution and binds to DNA within the sbnC coding region. Moreover, we show that SbnI binds heme and that heme-bound SbnI does not bind DNA. Finally, we show that providing exogenous heme to S. aureus growing in an iron-free medium results in delayed synthesis of SB. This is the first study in S. aureus that identifies a DNA-binding regulatory protein that senses heme to control gene expression for siderophore synthesis. PMID:26534960

A gene regulatory network armature for T-lymphocyte specification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fung, Elizabeth-sharon

Choice of a T-lymphoid fate by hematopoietic progenitor cells depends on sustained Notch-Delta signaling combined with tightly-regulated activities of multiple transcription factors. To dissect the regulatory network connections that mediate this process, we have used high-resolution analysis of regulatory gene expression trajectories from the beginning to the end of specification; tests of the short-term Notchdependence of these gene expression changes; and perturbation analyses of the effects of overexpression of two essential transcription factors, namely PU.l and GATA-3. Quantitative expression measurements of >50 transcription factor and marker genes have been used to derive the principal components of regulatory change through whichmore » T-cell precursors progress from primitive multipotency to T-lineage commitment. Distinct parts of the path reveal separate contributions of Notch signaling, GATA-3 activity, and downregulation of PU.l. Using BioTapestry, the results have been assembled into a draft gene regulatory network for the specification of T-cell precursors and the choice of T as opposed to myeloid dendritic or mast-cell fates. This network also accommodates effects of E proteins and mutual repression circuits of Gfil against Egr-2 and of TCF-l against PU.l as proposed elsewhere, but requires additional functions that remain unidentified. Distinctive features of this network structure include the intense dose-dependence of GATA-3 effects; the gene-specific modulation of PU.l activity based on Notch activity; the lack of direct opposition between PU.l and GATA-3; and the need for a distinct, late-acting repressive function or functions to extinguish stem and progenitor-derived regulatory gene expression.« less

Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks

PubMed Central

Lähdesmäki, Harri; Hautaniemi, Sampsa; Shmulevich, Ilya; Yli-Harja, Olli

2006-01-01

A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interactions of Boolean networks into the stochastic setting. Dynamic Bayesian networks (DBNs) is a general and versatile model class that is able to represent complex temporal stochastic processes and has also been proposed as a model for gene regulatory systems. In this paper, we concentrate on these two model classes and demonstrate that PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables. The major benefit of introducing the relationships between the models is that it opens up the possibility of applying the standard tools of DBNs to PBNs and vice versa. Hence, the standard learning tools of DBNs can be applied in the context of PBNs, and the inference methods give a natural way of handling the missing values in PBNs which are often present in gene expression measurements. Conversely, the tools for controlling the stationary behavior of the networks, tools for projecting networks onto sub-networks, and efficient learning schemes can be used for DBNs. In other words, the introduced relationships between the models extend the collection of analysis tools for both model classes. PMID:17415411

Network Modeling Reveals Prevalent Negative Regulatory Relationships between Signaling Sectors in Arabidopsis Immune Signaling

PubMed Central

Sato, Masanao; Tsuda, Kenichi; Wang, Lin; Coller, John; Watanabe, Yuichiro; Glazebrook, Jane; Katagiri, Fumiaki

2010-01-01

Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a “sector-switching” network, which

Stability Depends on Positive Autoregulation in Boolean Gene Regulatory Networks

PubMed Central

Pinho, Ricardo; Garcia, Victor; Irimia, Manuel; Feldman, Marcus W.

2014-01-01

Network motifs have been identified as building blocks of regulatory networks, including gene regulatory networks (GRNs). The most basic motif, autoregulation, has been associated with bistability (when positive) and with homeostasis and robustness to noise (when negative), but its general importance in network behavior is poorly understood. Moreover, how specific autoregulatory motifs are selected during evolution and how this relates to robustness is largely unknown. Here, we used a class of GRN models, Boolean networks, to investigate the relationship between autoregulation and network stability and robustness under various conditions. We ran evolutionary simulation experiments for different models of selection, including mutation and recombination. Each generation simulated the development of a population of organisms modeled by GRNs. We found that stability and robustness positively correlate with autoregulation; in all investigated scenarios, stable networks had mostly positive autoregulation. Assuming biological networks correspond to stable networks, these results suggest that biological networks should often be dominated by positive autoregulatory loops. This seems to be the case for most studied eukaryotic transcription factor networks, including those in yeast, flies and mammals. PMID:25375153

Single or functionalized fullerenes interacting with heme group

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, Wallison Chaves; Diniz, Eduardo Moraes, E-mail: eduardo.diniz@ufma.br

The heme group is responsible for iron transportation through the bloodstream, where iron participates in redox reactions, electron transfer, gases detection etc. The efficiency of such processes can be reduced if the whole heme molecule or even the iron is somehow altered from its original oxidation state, which can be caused by interactions with nanoparticles as fullerenes. To verify how such particles alter the geometry and electronic structure of heme molecule, here we report first principles calculations based on density functional theory of heme group interacting with single C{sub 60} fullerene or with C{sub 60} functionalized with small functional groupsmore » (−CH{sub 3}, −COOH, −NH{sub 2}, −OH). The calculations shown that the system heme + nanoparticle has a different spin state in comparison with heme group if the fullerene is functionalized. Also a functional group can provide a stronger binding between nanoparticle and heme molecule or inhibit the chemical bonding in comparison with single fullerene results. In addition heme molecule loses electrons to the nanoparticles and some systems exhibited a geometry distortion in heme group, depending on the binding energy. Furthermore, one find that such nanoparticles induce a formation of spin up states in heme group. Moreover, there exist modifications in density of states near the Fermi energy. Although of such changes in heme electronic structure and geometry, the iron atom remains in the heme group with the same oxidation state, so that processes that involve the iron might not be affected, only those that depend on the whole heme molecule.« less

Introduction of a covalent histidine-heme linkage in a hemoglobin: a promising tool for heme protein engineering.

PubMed

Rice, Selena L; Preimesberger, Matthew R; Johnson, Eric A; Lecomte, Juliette T J

2014-12-01

The hemoglobins of the cyanobacteria Synechococcus and Synechocystis (GlbNs) are capable of spontaneous and irreversible attachment of the b heme to the protein matrix. The reaction, which saturates the heme 2-vinyl by addition of a histidine residue, is reproduced in vitro by preparing the recombinant apoprotein, adding ferric heme, and reducing the iron to the ferrous state. Spontaneous covalent attachment of the heme is potentially useful for protein engineering purposes. Thus, to explore whether the histidine-heme linkage can serve in such applications, we attempted to introduce it in a test protein. We selected as our target the heme domain of Chlamydomonas eugametos LI637 (CtrHb), a eukaryotic globin that exhibits less than 50% sequence identity with the cyanobacterial GlbNs. We chose two positions, 75 in the FG corner and 111 in the H helix, to situate a histidine near a vinyl group. We characterized the proteins with gel electrophoresis, absorbance spectroscopy, and NMR analysis. Both T111H and L75H CtrHbs reacted upon reduction of the ferric starting material containing cyanide as the distal ligand to the iron. With L75H CtrHb, nearly complete (>90%) crosslinking was observed to the 4-vinyl as expected from the X-ray structure of wild-type CtrHb. Reaction of T111H CtrHb also occurred at the 4-vinyl, in a 60% yield indicating a preference for the flipped heme orientation in the starting material. The work suggests that the His-heme modification will be applicable to the design of proteins with a non-dissociable heme group. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of the Mitochondrial Heme Metabolism Complex

PubMed Central

Medlock, Amy E.; Shiferaw, Mesafint T.; Marcero, Jason R.; Vashisht, Ajay A.; Wohlschlegel, James A.; Phillips, John D.; Dailey, Harry A.

2015-01-01

Heme is an essential cofactor for most organisms and all metazoans. While the individual enzymes involved in synthesis and utilization of heme are fairly well known, less is known about the intracellular trafficking of porphyrins and heme, or regulation of heme biosynthesis via protein complexes. To better understand this process we have undertaken a study of macromolecular assemblies associated with heme synthesis. Herein we have utilized mass spectrometry with coimmunoprecipitation of tagged enzymes of the heme biosynthetic pathway in a developing erythroid cell culture model to identify putative protein partners. The validity of these data obtained in the tagged protein system is confirmed by normal porphyrin/heme production by the engineered cells. Data obtained are consistent with the presence of a mitochondrial heme metabolism complex which minimally consists of ferrochelatase, protoporphyrinogen oxidase and aminolevulinic acid synthase-2. Additional proteins involved in iron and intermediary metabolism as well as mitochondrial transporters were identified as potential partners in this complex. The data are consistent with the known location of protein components and support a model of transient protein-protein interactions within a dynamic protein complex. PMID:26287972

Gene Regulatory Network Inferences Using a Maximum-Relevance and Maximum-Significance Strategy

PubMed Central

Liu, Wei; Zhu, Wen; Liao, Bo; Chen, Xiangtao

2016-01-01

Recovering gene regulatory networks from expression data is a challenging problem in systems biology that provides valuable information on the regulatory mechanisms of cells. A number of algorithms based on computational models are currently used to recover network topology. However, most of these algorithms have limitations. For example, many models tend to be complicated because of the “large p, small n” problem. In this paper, we propose a novel regulatory network inference method called the maximum-relevance and maximum-significance network (MRMSn) method, which converts the problem of recovering networks into a problem of how to select the regulator genes for each gene. To solve the latter problem, we present an algorithm that is based on information theory and selects the regulator genes for a specific gene by maximizing the relevance and significance. A first-order incremental search algorithm is used to search for regulator genes. Eventually, a strict constraint is adopted to adjust all of the regulatory relationships according to the obtained regulator genes and thus obtain the complete network structure. We performed our method on five different datasets and compared our method to five state-of-the-art methods for network inference based on information theory. The results confirm the effectiveness of our method. PMID:27829000

Challenges for modeling global gene regulatory networks during development: insights from Drosophila.

PubMed

Wilczynski, Bartek; Furlong, Eileen E M

2010-04-15

Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Structures of the Substrate-free and Product-bound Forms of HmuO, a Heme Oxygenase from Corynebacterium diphtheriae

PubMed Central

Unno, Masaki; Ardèvol, Albert; Rovira, Carme; Ikeda-Saito, Masao

2013-01-01

Heme oxygenase catalyzes the degradation of heme to biliverdin, iron, and carbon monoxide. Here, we present crystal structures of the substrate-free, Fe3+-biliverdin-bound, and biliverdin-bound forms of HmuO, a heme oxygenase from Corynebacterium diphtheriae, refined to 1.80, 1.90, and 1.85 Å resolution, respectively. In the substrate-free structure, the proximal and distal helices, which tightly bracket the substrate heme in the substrate-bound heme complex, move apart, and the proximal helix is partially unwound. These features are supported by the molecular dynamic simulations. The structure implies that the heme binding fixes the enzyme active site structure, including the water hydrogen bond network critical for heme degradation. The biliverdin groups assume the helical conformation and are located in the heme pocket in the crystal structures of the Fe3+-biliverdin-bound and the biliverdin-bound HmuO, prepared by in situ heme oxygenase reaction from the heme complex crystals. The proximal His serves as the Fe3+-biliverdin axial ligand in the former complex and forms a hydrogen bond through a bridging water molecule with the biliverdin pyrrole nitrogen atoms in the latter complex. In both structures, salt bridges between one of the biliverdin propionate groups and the Arg and Lys residues further stabilize biliverdin at the HmuO heme pocket. Additionally, the crystal structure of a mixture of two intermediates between the Fe3+-biliverdin and biliverdin complexes has been determined at 1.70 Å resolution, implying a possible route for iron exit. PMID:24106279

Regulatory networks and connected components of the neutral space. A look at functional islands

NASA Astrophysics Data System (ADS)

Boldhaus, G.; Klemm, K.

2010-09-01

The functioning of a living cell is largely determined by the structure of its regulatory network, comprising non-linear interactions between regulatory genes. An important factor for the stability and evolvability of such regulatory systems is neutrality - typically a large number of alternative network structures give rise to the necessary dynamics. Here we study the discretized regulatory dynamics of the yeast cell cycle [Li et al., PNAS, 2004] and the set of networks capable of reproducing it, which we call functional. Among these, the empirical yeast wildtype network is close to optimal with respect to sparse wiring. Under point mutations, which establish or delete single interactions, the neutral space of functional networks is fragmented into ≈ 4.7 × 108 components. One of the smaller ones contains the wildtype network. On average, functional networks reachable from the wildtype by mutations are sparser, have higher noise resilience and fewer fixed point attractors as compared with networks outside of this wildtype component.

Characterization of SiaA, a streptococcal heme-binding protein associated with a heme ABC transport system.

PubMed

Sook, Brian R; Block, Darci R; Sumithran, Suganya; Montañez, Griselle E; Rodgers, Kenton R; Dawson, John H; Eichenbaum, Zehava; Dixon, Dabney W

2008-02-26

Many pathogenic bacteria require heme and obtain it from their environment. Heme transverses the cytoplasmic membrane via an ATP binding cassette (ABC) pathway. Although a number of heme ABC transport systems have been described in pathogenic bacteria, there is as yet little biophysical characterization of the proteins in these systems. The sia (hts) gene cluster encodes a heme ABC transporter in the Gram positive Streptococcus pyogenes. The lipoprotein-anchored heme binding protein (HBP) of this transporter is SiaA (HtsA). In the current study, resonance Raman (rR), magnetic circular dichroism (MCD), and nuclear magnetic resonance (NMR) spectroscopies were used to determine the coordination state and spin state of both the ferric and ferrous forms of this protein. Identifiers from these techniques suggest that the heme is six-coordinate and low-spin in both oxidation states of the protein, with methionine and histidine as axial ligands. SiaA has a pKa of 9.7 +/- 0.1, attributed to deprotonation of the axial histidine. Guanidinium titration studies show that the ferric state is less stable than the ferrous state, with DeltaG(H2O) values for the oxidized and reduced proteins of 7.3 +/- 0.8 and 16.0 +/- 3.6 kcal mol-1, respectively. The reductive and oxidative midpoint potentials determined via spectroelectrochemistry are 83 +/- 3 and 64 +/- 3 mV, respectively; the irreversibility of heme reduction suggests that redox cycling of the heme is coupled to a kinetically sluggish change in structure or conformation. The biophysical characterization described herein will significantly advance our understanding of structure-function relationships in HBP.

Free heme and sickle hemoglobin polymerization

NASA Astrophysics Data System (ADS)

Uzunova, Veselina V.

This work investigates further the mechanism of one of the most interesting of the protein self-assembly systems---the polymerization of sickle hemoglobin and the role of free heme in it. Polymerization of sickle hemoglobin is the primary event in the pathology of a chronic hemolytic condition called sickle cell anemia with complex pathogenesis, unexplained variability and symptomatic treatment. Auto-oxidation develops in hemoglobin solutions exposed to room temperature and causes release of ferriheme. The composition of such solutions is investigated by mass spectrometry. Heme dimers whose amount corresponds to the initial amounts of heme released from the protein are followed. Differences in the dimer peak height are established for hemoglobin variants A, S and C and depending on the exposure duration. The effects of free heme on polymerization kinetics are studied. Growth rates and two characteristic parameters of nucleation are measured for stored Hb S. After dialysis of polymerizing solutions, no spherulites are detected at moderately high supersaturation and prolonged exposure times. The addition of 0.16-0.26 mM amounts of heme to dialyzed solutions leads to restoration of polymerization. The measured kinetic parameters have higher values compared to the ones before dialysis. The amount of heme in non-dialyzed aged solution is characterized using spectrophotometry. Three methods are used: difference in absorbance of dialyzed and non-dialyzed solutions, characteristic absorbance of heme-albumin complex and absorbance of non-dialyzed solutions with added potassium cyanide. The various approaches suggest the presence of 0.12 to 0.18 mM of free ferriheme in such solutions. Open questions are whether the same amounts of free heme are present in vivo and whether the same mechanism operates intracellulary. If the answer to those questions is positive, then removal of free heme from erythrocytes can influence their readiness to sickle.

Construction of regulatory networks using expression time-series data of a genotyped population.

PubMed

Yeung, Ka Yee; Dombek, Kenneth M; Lo, Kenneth; Mittler, John E; Zhu, Jun; Schadt, Eric E; Bumgarner, Roger E; Raftery, Adrian E

2011-11-29

The inference of regulatory and biochemical networks from large-scale genomics data is a basic problem in molecular biology. The goal is to generate testable hypotheses of gene-to-gene influences and subsequently to design bench experiments to confirm these network predictions. Coexpression of genes in large-scale gene-expression data implies coregulation and potential gene-gene interactions, but provide little information about the direction of influences. Here, we use both time-series data and genetics data to infer directionality of edges in regulatory networks: time-series data contain information about the chronological order of regulatory events and genetics data allow us to map DNA variations to variations at the RNA level. We generate microarray data measuring time-dependent gene-expression levels in 95 genotyped yeast segregants subjected to a drug perturbation. We develop a Bayesian model averaging regression algorithm that incorporates external information from diverse data types to infer regulatory networks from the time-series and genetics data. Our algorithm is capable of generating feedback loops. We show that our inferred network recovers existing and novel regulatory relationships. Following network construction, we generate independent microarray data on selected deletion mutants to prospectively test network predictions. We demonstrate the potential of our network to discover de novo transcription-factor binding sites. Applying our construction method to previously published data demonstrates that our method is competitive with leading network construction algorithms in the literature.

Inference of gene regulatory networks from genome-wide knockout fitness data

PubMed Central

Wang, Liming; Wang, Xiaodong; Arkin, Adam P.; Samoilov, Michael S.

2013-01-01

Motivation: Genome-wide fitness is an emerging type of high-throughput biological data generated for individual organisms by creating libraries of knockouts, subjecting them to broad ranges of environmental conditions, and measuring the resulting clone-specific fitnesses. Since fitness is an organism-scale measure of gene regulatory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene expression. Previous works have shown that genome-wide fitness data can be used to uncover novel gene regulatory interactions, when compared with results of more conventional gene expression analysis. Yet, to date, few algorithms have been proposed for systematically using genome-wide mutant fitness data for gene regulatory network inference. Results: In this article, we describe a model and propose an inference algorithm for using fitness data from knockout libraries to identify underlying gene regulatory networks. Unlike most prior methods, the presented approach captures not only structural, but also dynamical and non-linear nature of biomolecular systems involved. A state–space model with non-linear basis is used for dynamically describing gene regulatory networks. Network structure is then elucidated by estimating unknown model parameters. Unscented Kalman filter is used to cope with the non-linearities introduced in the model, which also enables the algorithm to run in on-line mode for practical use. Here, we demonstrate that the algorithm provides satisfying results for both synthetic data as well as empirical measurements of GAL network in yeast Saccharomyces cerevisiae and TyrR–LiuR network in bacteria Shewanella oneidensis. Availability: MATLAB code and datasets are available to download at http://www.duke.edu/∼lw174/Fitness.zip and http://genomics.lbl.gov/supplemental/fitness-bioinf/ Contact: wangx@ee.columbia.edu or mssamoilov@lbl.gov Supplementary information

Gap Gene Regulatory Dynamics Evolve along a Genotype Network

PubMed Central

Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Jaeger, Johannes

2016-01-01

Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). PMID:26796549

Boolean dynamics of genetic regulatory networks inferred from microarray time series data

DOE PAGES

Martin, Shawn; Zhang, Zhaoduo; Martino, Anthony; ...

2007-01-31

Methods available for the inference of genetic regulatory networks strive to produce a single network, usually by optimizing some quantity to fit the experimental observations. In this paper we investigate the possibility that multiple networks can be inferred, all resulting in similar dynamics. This idea is motivated by theoretical work which suggests that biological networks are robust and adaptable to change, and that the overall behavior of a genetic regulatory network might be captured in terms of dynamical basins of attraction. We have developed and implemented a method for inferring genetic regulatory networks for time series microarray data. Our methodmore » first clusters and discretizes the gene expression data using k-means and support vector regression. We then enumerate Boolean activation–inhibition networks to match the discretized data. In conclusion, the dynamics of the Boolean networks are examined. We have tested our method on two immunology microarray datasets: an IL-2-stimulated T cell response dataset and a LPS-stimulated macrophage response dataset. In both cases, we discovered that many networks matched the data, and that most of these networks had similar dynamics.« less

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice.

PubMed

Smita, Shuchi; Katiyar, Amit; Chinnusamy, Viswanathan; Pandey, Dev M; Bansal, Kailash C

2015-01-01

MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by "top-down" and "guide-gene" approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via "top-down" approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by "guide-gene" approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought response in rice

Heme orientational disorder in human adult hemoglobin reconstituted with a ring fluorinated heme and its functional consequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagao, Satoshi; Hirai, Yueki; Kawano, Shin

2007-03-16

A ring fluorinated heme, 13,17-bis(2-carboxylatoethyl)-3,8-diethyl-2-fluoro-7,12, 18-trimethyl-porphyrin-atoiron(III), has been incorporated into human adult hemoglobin (Hb A). The heme orientational disorder in the individual subunits of the protein has been readily characterized using {sup 19}F NMR and the O{sub 2} binding properties of the protein have been evaluated through the oxygen equilibrium analysis. The equilibrated orientations of hemes in {alpha}- and {beta}- subunits of the reconstituted protein were found to be almost completely opposite to each other, and hence were largely different from those of the native and the previously reported reconstituted proteins [T. Jue, G.N. La Mar, Heme orientational heterogeneity inmore » deuterohemin-reconstituted horse and human hemoglobin characterized by proton nuclear magnetic resonance spectroscopy, Biochem. Biophys. Res. Commun. 119 (1984) 640-645]. Despite the large difference in the degree of the heme orientational disorder in the subunits of the proteins, the O{sub 2} affinity and the cooperativity of the protein reconstituted with 2-MF were similar to those of the proteins reconstituted with a series of hemes chemically modified at the heme 3- and 8-positions [K. Kawabe, K. Imaizumi, Z. Yoshida, K. Imai, I. Tyuma, Studies on reconstituted myoglobins and hemoglobins II. Role of the heme side chains in the oxygenation of hemoglobin, J. Biochem. 92 (1982) 1713-1722], whose O{sub 2} affinity and cooperativity were higher and lower, respectively, relative to those of native protein. These results indicated that the heme orientational disorder could exert little effect, if any, on the O{sub 2} affinity properties of Hb A. This finding provides new insights into structure-function relationship of Hb A.« less

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

PubMed Central

Baumbach, Jan

2007-01-01

Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to

Modeling stochasticity and robustness in gene regulatory networks.

PubMed

Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

2009-06-15

Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

Heme oxygenase-1: a metabolic nike.

PubMed

Wegiel, Barbara; Nemeth, Zsuzsanna; Correa-Costa, Matheus; Bulmer, Andrew C; Otterbein, Leo E

2014-04-10

Heme degradation, which was described more than 30 years ago, is still very actively explored with many novel discoveries on its role in various disease models every year. The heme oxygenases (HO) are metabolic enzymes that utilize NADPH and oxygen to break apart the heme moiety liberating biliverdin (BV), carbon monoxide (CO), and iron. Heme that is derived from hemoproteins can be toxic to the cells and if not removed immediately, it causes cell apoptosis and local inflammation. Elimination of heme from the milieu enables generation of three products that influences numerous metabolic changes in the cell. CO has profound effects on mitochondria and cellular respiration and other hemoproteins to which it can bind and affect their function, while BV and bilirubin (BR), the substrate and product of BV, reductase, respectively, are potent antioxidants. Sequestration of iron into ferritin and its recycling in the tissues is a part of the homeodynamic processes that control oxidation-reduction in cellular metabolism. Further, heme is an important component of a number of metabolic enzymes, and, therefore, HO-1 plays an important role in the modulation of cellular bioenergetics. In this review, we describe the cross-talk between heme oxygenase-1 (HO-1) and its products with other metabolic pathways. HO-1, which we have labeled Nike, the goddess who personified victory, dictates triumph over pathophysiologic conditions, including diabetes, ischemia, and cancer.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

Integration of a splicing regulatory network within the meiotic gene expression program of Saccharomyces cerevisiae

PubMed Central

Munding, Elizabeth M.; Igel, A. Haller; Shiue, Lily; Dorighi, Kristel M.; Treviño, Lisa R.; Ares, Manuel

2010-01-01

Splicing regulatory networks are essential components of eukaryotic gene expression programs, yet little is known about how they are integrated with transcriptional regulatory networks into coherent gene expression programs. Here we define the MER1 splicing regulatory network and examine its role in the gene expression program during meiosis in budding yeast. Mer1p splicing factor promotes splicing of just four pre-mRNAs. All four Mer1p-responsive genes also require Nam8p for splicing activation by Mer1p; however, other genes require Nam8p but not Mer1p, exposing an overlapping meiotic splicing network controlled by Nam8p. MER1 mRNA and three of the four Mer1p substrate pre-mRNAs are induced by the transcriptional regulator Ume6p. This unusual arrangement delays expression of Mer1p-responsive genes relative to other genes under Ume6p control. Products of Mer1p-responsive genes are required for initiating and completing recombination and for activation of Ndt80p, the activator of the transcriptional network required for subsequent steps in the program. Thus, the MER1 splicing regulatory network mediates the dependent relationship between the UME6 and NDT80 transcriptional regulatory networks in the meiotic gene expression program. This study reveals how splicing regulatory networks can be interlaced with transcriptional regulatory networks in eukaryotic gene expression programs. PMID:21123654

Heme acquisition in the parasitic filarial nematode Brugia malayi.

PubMed

Luck, Ashley N; Yuan, Xiaojing; Voronin, Denis; Slatko, Barton E; Hamza, Iqbal; Foster, Jeremy M

2016-10-01

Nematodes lack a heme biosynthetic pathway and must acquire heme from exogenous sources. Given the indispensable role of heme, this auxotrophy may be exploited to develop drugs that interfere with heme uptake in parasites. Although multiple heme-responsive genes (HRGs) have been characterized within the free-living nematode Caenorhabditis elegans, we have undertaken the first study of heme transport in Brugia malayi, a causative agent of lymphatic filariasis. Through functional assays in yeast, as well as heme analog, RNAi, and transcriptomic experiments, we have shown that the heme transporter B. malayi HRG-1 (BmHRG-1) is indeed functional in B. malayi In addition, BmHRG-1 localizes both to the endocytic compartments and cell membrane when expressed in yeast cells. Transcriptomic sequencing revealed that BmHRG-1, BmHRG-2, and BmMRP-5 (all orthologs of HRGs in C. elegans) are down-regulated in heme-treated B. malayi, as compared to non-heme-treated control worms. Likely because of short gene lengths, multiple exons, other HRGs in B. malayi (BmHRG-3-6) remain unidentified. Although the precise mechanisms of heme homeostasis in a nematode with the ability to acquire heme remains unknown, this study clearly demonstrates that the filarial nematode B. malayi is capable of transporting exogenous heme.-Luck, A. N., Yuan, X., Voronin, D., Slatko, B. E., Hamza, I., Foster, J. M. Heme acquisition in the parasitic filarial nematode Brugia malayi. © The Author(s).

Heme acquisition in the parasitic filarial nematode Brugia malayi

PubMed Central

Luck, Ashley N.; Yuan, Xiaojing; Voronin, Denis; Slatko, Barton E.; Hamza, Iqbal; Foster, Jeremy M.

2016-01-01

Nematodes lack a heme biosynthetic pathway and must acquire heme from exogenous sources. Given the indispensable role of heme, this auxotrophy may be exploited to develop drugs that interfere with heme uptake in parasites. Although multiple heme-responsive genes (HRGs) have been characterized within the free-living nematode Caenorhabditis elegans, we have undertaken the first study of heme transport in Brugia malayi, a causative agent of lymphatic filariasis. Through functional assays in yeast, as well as heme analog, RNAi, and transcriptomic experiments, we have shown that the heme transporter B. malayi HRG-1 (BmHRG-1) is indeed functional in B. malayi. In addition, BmHRG-1 localizes both to the endocytic compartments and cell membrane when expressed in yeast cells. Transcriptomic sequencing revealed that BmHRG-1, BmHRG-2, and BmMRP-5 (all orthologs of HRGs in C. elegans) are down-regulated in heme-treated B. malayi, as compared to non–heme-treated control worms. Likely because of short gene lengths, multiple exons, other HRGs in B. malayi (BmHRG-3–6) remain unidentified. Although the precise mechanisms of heme homeostasis in a nematode with the ability to acquire heme remains unknown, this study clearly demonstrates that the filarial nematode B. malayi is capable of transporting exogenous heme.—Luck, A. N., Yuan, X., Voronin, D., Slatko, B. E., Hamza, I., Foster, J. M. Heme acquisition in the parasitic filarial nematode Brugia malayi. PMID:27363426

Modularity and design principles in the sea urchin embryo gene regulatory network

PubMed Central

Peter, Isabelle S.; Davidson, Eric H.

2010-01-01

The gene regulatory network (GRN) established experimentally for the pre-gastrular sea urchin embryo provides causal explanations of the biological functions required for spatial specification of embryonic regulatory states. Here we focus on the structure of the GRN which controls the progressive increase in complexity of territorial regulatory states during embryogenesis; and on the types of modular subcircuits of which the GRN is composed. Each of these subcircuit topologies executes a particular operation of spatial information processing. The GRN architecture reflects the particular mode of embryogenesis represented by sea urchin development. Network structure not only specifies the linkages constituting the genomic regulatory code for development, but also indicates the various regulatory requirements of regional developmental processes. PMID:19932099

Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

PubMed Central

2014-01-01

It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the network estimation as a target tracking problem. We overcome the limited number of observations (small n large p problem) by performing tracking in a compressed domain. Assuming linear dynamics, we derive the LASSO-Kalman smoother, which recursively computes the minimum mean-square sparse estimate of the network connectivity at each time point. The LASSO operator, motivated by the sparsity of the genetic regulatory networks, allows simultaneous signal recovery and compression, thereby reducing the amount of required observations. The smoothing improves the estimation by incorporating all observations. We track the time-varying networks during the life cycle of the Drosophila melanogaster. The recovered networks show that few genes are permanent, whereas most are transient, acting only during specific developmental phases of the organism. PMID:24517200

Allosteric communication between the pyridoxal 5'-phosphate (PLP) and heme sites in the H2S generator human cystathionine β-synthase.

PubMed

Yadav, Pramod Kumar; Xie, Peter; Banerjee, Ruma

2012-11-02

Human cystathionine β-synthase (CBS) is a unique pyridoxal 5'-phosphate (PLP)-dependent enzyme that has a regulatory heme cofactor. Previous studies have demonstrated the importance of Arg-266, a residue at the heme pocket end of α-helix 8, for communication between the heme and PLP sites. In this study, we have examined the role of the conserved Thr-257 and Thr-260 residues, located at the other end of α-helix 8 on the heme electronic environment and on activity. The mutations at the two positions destabilize PLP binding, leading to lower PLP content and ~2- to ~500-fold lower activity compared with the wild-type enzyme. Activity is unresponsive to PLP supplementation, consistent with the pyridoxine-nonresponsive phenotype of the T257M mutation in a homocystinuric patient. The H(2)S-producing activities, also impacted by the mutations, show a different pattern of inhibition compared with the canonical transsulfuration reaction. Interestingly, the mutants exhibit contrasting sensitivities to the allosteric effector, S-adenosylmethionine (AdoMet); whereas T257M and T257I are inhibited, the other mutants are hyperactivated by AdoMet. All mutants showed an increased propensity of the ferrous heme to form an inactive species with a 424 nm Soret peak and exhibited significantly reduced enzyme activity in the ferrous and ferrous-CO states. Our results provide the first evidence for bidirectional transmission of information between the cofactor binding sites, suggest the additional involvement of this region in allosteric communication with the regulatory AdoMet-binding domain, and reveal the potential for independent modulation of the canonical transsulfuration versus H(2)S-generating reactions catalyzed by CBS.

State Space Model with hidden variables for reconstruction of gene regulatory networks.

PubMed

Wu, Xi; Li, Peng; Wang, Nan; Gong, Ping; Perkins, Edward J; Deng, Youping; Zhang, Chaoyang

2011-01-01

State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN. True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks. Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN. This study provides useful information in handling the hidden variables and improving the inference precision.

An electronic regulatory document management system for a clinical trial network.

PubMed

Zhao, Wenle; Durkalski, Valerie; Pauls, Keith; Dillon, Catherine; Kim, Jaemyung; Kolk, Deneil; Silbergleit, Robert; Stevenson, Valerie; Palesch, Yuko

2010-01-01

A computerized regulatory document management system has been developed as a module in a comprehensive Clinical Trial Management System (CTMS) designed for an NIH-funded clinical trial network in order to more efficiently manage and track regulatory compliance. Within the network, several institutions and investigators are involved in multiple trials, and each trial has regulatory document requirements. Some of these documents are trial specific while others apply across multiple trials. The latter causes a possible redundancy in document collection and management. To address these and other related challenges, a central regulatory document management system was designed. This manuscript shares the design of the system as well as examples of it use in current studies. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Relationship between natural and heme-mediated antibody polyreactivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadzhieva, Maya; Vassilev, Tchavdar; Bayry, Jagadeesh

Polyreactive antibodies represent a considerable fraction of the immune repertoires. Some antibodies acquire polyreactivity post-translationally after interaction with various redox-active substances, including heme. Recently we have demonstrated that heme binding to a naturally polyreactive antibody (SPE7) results in a considerable broadening of the repertoire of recognized antigens. A question remains whether the presence of certain level of natural polyreactivity of antibodies is a prerequisite for heme-induced further extension of antigen binding potential. Here we used a second monoclonal antibody (Hg32) with unknown specificity and absence of intrinsic polyreactivity as a model to study the potential of heme to induce polyreactivitymore » of antibodies. We demonstrated that exposure to heme greatly extends the antigen binding potential of Hg32, suggesting that the intrinsic binding promiscuity is not a prerequisite for the induction of polyreactivity by heme. In addition we compared the kinetics and thermodynamics of the interaction of heme-exposed antibodies with a panel of unrelated antigens. These analyses revealed that the two heme-sensitive antibodies adopt different mechanisms of binding to the same set of antigens. This study contributes to understanding the phenomenon of induced antibody polyreactivity. The data may also be of importance for understanding of physiological and pathological roles of polyreactive antibodies. - Highlights: • Exposure of certain monoclonal IgE antibodies to heme results in gain of antigen binding polyreactivity. • Natural polyreactivity of antibodies is dispensable for acquisition of polyreactivity through interaction with heme. • Heme-induced monoclonal IgE antibodies differ in their thermodynamic mechanisms of antigen recognition.« less

Heme Oxygenase-1: A Metabolic Nike

PubMed Central

Nemeth, Zsuzsanna; Correa-Costa, Matheus; Bulmer, Andrew C.; Otterbein, Leo E.

2014-01-01

Abstract Significance: Heme degradation, which was described more than 30 years ago, is still very actively explored with many novel discoveries on its role in various disease models every year. Recent Advances: The heme oxygenases (HO) are metabolic enzymes that utilize NADPH and oxygen to break apart the heme moiety liberating biliverdin (BV), carbon monoxide (CO), and iron. Heme that is derived from hemoproteins can be toxic to the cells and if not removed immediately, it causes cell apoptosis and local inflammation. Elimination of heme from the milieu enables generation of three products that influences numerous metabolic changes in the cell. Critical Issues: CO has profound effects on mitochondria and cellular respiration and other hemoproteins to which it can bind and affect their function, while BV and bilirubin (BR), the substrate and product of BV, reductase, respectively, are potent antioxidants. Sequestration of iron into ferritin and its recycling in the tissues is a part of the homeodynamic processes that control oxidation-reduction in cellular metabolism. Further, heme is an important component of a number of metabolic enzymes, and, therefore, HO-1 plays an important role in the modulation of cellular bioenergetics. Future Directions: In this review, we describe the cross-talk between heme oxygenase-1 (HO-1) and its products with other metabolic pathways. HO-1, which we have labeled Nike, the goddess who personified victory, dictates triumph over pathophysiologic conditions, including diabetes, ischemia, and cancer. Antioxid. Redox Signal. 20, 1709–1722. PMID:24180257

Hemolysis-induced lethality involves inflammasome activation by heme.

PubMed

Dutra, Fabianno F; Alves, Letícia S; Rodrigues, Danielle; Fernandez, Patricia L; de Oliveira, Rosane B; Golenbock, Douglas T; Zamboni, Dario S; Bozza, Marcelo T

2014-09-30

The increase of extracellular heme is a hallmark of hemolysis or extensive cell damage. Heme has prooxidant, cytotoxic, and inflammatory effects, playing a central role in the pathogenesis of malaria, sepsis, and sickle cell disease. However, the mechanisms by which heme is sensed by innate immune cells contributing to these diseases are not fully characterized. We found that heme, but not porphyrins without iron, activated LPS-primed macrophages promoting the processing of IL-1β dependent on nucleotide-binding domain and leucine rich repeat containing family, pyrin domain containing 3 (NLRP3). The activation of NLRP3 by heme required spleen tyrosine kinase, NADPH oxidase-2, mitochondrial reactive oxygen species, and K(+) efflux, whereas it was independent of heme internalization, lysosomal damage, ATP release, the purinergic receptor P2X7, and cell death. Importantly, our results indicated the participation of macrophages, NLRP3 inflammasome components, and IL-1R in the lethality caused by sterile hemolysis. Thus, understanding the molecular pathways affected by heme in innate immune cells might prove useful to identify new therapeutic targets for diseases that have heme release.

Heme binding properties of glyceraldehyde-3-phosphate dehydrogenase.

PubMed

Hannibal, Luciana; Collins, Daniel; Brassard, Julie; Chakravarti, Ritu; Vempati, Rajesh; Dorlet, Pierre; Santolini, Jérôme; Dawson, John H; Stuehr, Dennis J

2012-10-30

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a glycolytic enzyme that also functions in transcriptional regulation, oxidative stress, vesicular trafficking, and apoptosis. Because GAPDH is required for the insertion of cellular heme into inducible nitric oxide synthase [Chakravarti, R., et al. (2010) Proc. Natl. Acad. Sci. U.S.A. 107, 18004-18009], we extensively characterized the heme binding properties of GAPDH. Substoichiometric amounts of ferric heme bound to GAPDH (one heme per GAPDH tetramer) to form a low-spin complex with UV-visible maxima at 362, 418, and 537 nm and when reduced to ferrous gave maxima at 424, 527, and 559 nm. Ferric heme association and dissociation rate constants at 10 °C were as follows: k(on) = 17800 M(-1) s(-1), k(off1) = 7.0 × 10(-3) s(-1), and k(off2) = 3.3 × 10(-4) s(-1) (giving approximate affinities of 19-390 nM). Ferrous heme bound more poorly to GAPDH and dissociated with a k(off) of 4.2 × 10(-3) s(-1). Magnetic circular dichroism, resonance Raman, and electron paramagnetic resonance spectroscopic data on the ferric, ferrous, and ferrous-CO complexes of GAPDH showed that the heme is bis-ligated with His as the proximal ligand. The distal ligand in the ferric complex was not displaced by CN(-) or N(3)(-) but in the ferrous complex could be displaced by CO at a rate of 1.75 s(-1) (for >0.2 mM CO). Studies with heme analogues revealed selectivity toward the coordinating metal and porphyrin ring structure. The GAPDH-heme complex was isolated from bacteria induced to express rabbit GAPDH in the presence of δ-aminolevulinic acid. Our finding of heme binding to GAPDH expands the protein's potential roles. The strength, selectivity, reversibility, and redox sensitivity of heme binding to GAPDH are consistent with it performing heme sensing or heme chaperone-like functions in cells.

Genome-wide network of regulatory genes for construction of a chordate embryo.

PubMed

Shoguchi, Eiichi; Hamaguchi, Makoto; Satoh, Nori

2008-04-15

Animal development is controlled by gene regulation networks that are composed of sequence-specific transcription factors (TF) and cell signaling molecules (ST). Although housekeeping genes have been reported to show clustering in the animal genomes, whether the genes comprising a given regulatory network are physically clustered on a chromosome is uncertain. We examined this question in the present study. Ascidians are the closest living relatives of vertebrates, and their tadpole-type larva represents the basic body plan of chordates. The Ciona intestinalis genome contains 390 core TF genes and 119 major ST genes. Previous gene disruption assays led to the formulation of a basic chordate embryonic blueprint, based on over 3000 genetic interactions among 79 zygotic regulatory genes. Here, we mapped the regulatory genes, including all 79 regulatory genes, on the 14 pairs of Ciona chromosomes by fluorescent in situ hybridization (FISH). Chromosomal localization of upstream and downstream regulatory genes demonstrates that the components of coherent developmental gene networks are evenly distributed over the 14 chromosomes. Thus, this study provides the first comprehensive evidence that the physical clustering of regulatory genes, or their target genes, is not relevant for the genome-wide control of gene expression during development.

Up-regulation of A1M/α1-microglobulin in skin by heme and reactive oxygen species gives protection from oxidative damage.

PubMed

Olsson, Magnus G; Allhorn, Maria; Larsson, Jörgen; Cederlund, Martin; Lundqvist, Katarina; Schmidtchen, Artur; Sørensen, Ole E; Mörgelin, Matthias; Akerström, Bo

2011-01-01

During bleeding the skin is subjected to oxidative insults from free heme and radicals, generated from extracellular hemoglobin. The lipocalin α(1)-microglobulin (A1M) was recently shown to have reductase properties, reducing heme-proteins and other substrates, and to scavenge heme and radicals. We investigated the expression and localization of A1M in skin and the possible role of A1M in the protection of skin tissue from damage induced by heme and reactive oxygen species. Skin explants, keratinocyte cultures and purified collagen I were exposed to heme, reactive oxygen species, and/or A1M and investigated by biochemical methods and electron microscopy. The results demonstrate that A1M is localized ubiquitously in the dermal and epidermal layers, and that the A1M-gene is expressed in keratinocytes and up-regulated after exposure to heme and reactive oxygen species. A1M inhibited the heme- and reactive oxygen species-induced ultrastructural damage, up-regulation of antioxidation and cell cycle regulatory genes, and protein carbonyl formation in skin and keratinocytes. Finally, A1M bound to purified collagen I (K(d) = 0.96×10(-6) M) and could inhibit and repair the destruction of collagen fibrils by heme and reactive oxygen species. The results suggest that A1M may have a physiological role in protection of skin cells and matrix against oxidative damage following bleeding.

Heme Recognition By a Staphylococcus Aureus IsdE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grigg, J.C.; Vermeiren, C.L.; Heinrichs, D.E.

Staphylococcus aureus is a Gram-positive bacterial pathogen and a leading cause of hospital acquired infections. Because the free iron concentration in the human body is too low to support growth, S. aureus must acquire iron from host sources. Heme iron is the most prevalent iron reservoir in the human body and a predominant source of iron for S. aureus. The iron-regulated surface determinant (Isd) system removes heme from host heme proteins and transfers it to IsdE, the cognate substrate-binding lipoprotein of an ATP-binding cassette transporter, for import and subsequent degradation. Herein, we report the crystal structure of the soluble portionmore » of the IsdE lipoprotein in complex with heme. The structure reveals a bi-lobed topology formed by an N- and C-terminal domain bridged by a single {alpha}-helix. The structure places IsdE as a member of the helical backbone metal receptor superfamily. A six-coordinate heme molecule is bound in the groove established at the domain interface, and the heme iron is coordinated in a novel fashion for heme transporters by Met{sup 78} and His{sup 229}. Both heme propionate groups are secured by H-bonds to IsdE main chain and side chain groups. Of these residues, His{sup 299} is essential for IsdE-mediated heme uptake by S. aureus when growth on heme as a sole iron source is measured. Multiple sequence alignments of homologues from several other Gram-positive bacteria, including the human pathogens pyogenes, Bacillus anthracis, and Listeria monocytogenes, suggest that these other systems function equivalently to S. aureus IsdE with respect to heme binding and transport.« less

Generation of oscillating gene regulatory network motifs

NASA Astrophysics Data System (ADS)

van Dorp, M.; Lannoo, B.; Carlon, E.

2013-07-01

Using an improved version of an evolutionary algorithm originally proposed by François and Hakim [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0304532101 101, 580 (2004)], we generated small gene regulatory networks in which the concentration of a target protein oscillates in time. These networks may serve as candidates for oscillatory modules to be found in larger regulatory networks and protein interaction networks. The algorithm was run for 105 times to produce a large set of oscillating modules, which were systematically classified and analyzed. The robustness of the oscillations against variations of the kinetic rates was also determined, to filter out the least robust cases. Furthermore, we show that the set of evolved networks can serve as a database of models whose behavior can be compared to experimentally observed oscillations. The algorithm found three smallest (core) oscillators in which nonlinearities and number of components are minimal. Two of those are two-gene modules: the mixed feedback loop, already discussed in the literature, and an autorepressed gene coupled with a heterodimer. The third one is a single gene module which is competitively regulated by a monomer and a dimer. The evolutionary algorithm also generated larger oscillating networks, which are in part extensions of the three core modules and in part genuinely new modules. The latter includes oscillators which do not rely on feedback induced by transcription factors, but are purely of post-transcriptional type. Analysis of post-transcriptional mechanisms of oscillation may provide useful information for circadian clock research, as recent experiments showed that circadian rhythms are maintained even in the absence of transcription.

Implication for using heme methyl hyperfine shifts as indicators of heme seating as related to stereoselectivity in the catabolism of heme by heme oxygenase: in-plane heme versus axial his rotation.

PubMed

Ogura, Hiroshi; Evans, John P; de Montellano, Paul R Ortiz; La Mar, Gerd N

2008-01-08

The triple mutant of the solubilized, 265-residue construct of human heme oxygenase, K18E/E29K/R183E-hHO, has been shown to redirect the exclusive alpha-regioselectivity of wild-type hHO to primarily beta,delta-selectivity in the cleavage of heme (Wang, J., Evans, J. P., Ogura, H., La Mar, G. N., and Ortiz de Montellano, P. R. (2006) Biochemistry 45, 61-73). The 1H NMR hyperfine shift pattern for the substrate and axial His CbetaH's and the substrate-protein contacts of the cyanide-inhibited protohemin and 2,4-dimethyldeuterohemin complexes of the triple mutant have been analyzed in detail and compared to data for the WT complex. It is shown that protein contacts for the major solution isomers for both substrates in the mutant dictate approximately 90 degrees in-plane clockwise rotation relative to that in the WT. The conventional interpretation of the pattern of substrate methyl hyperfine shifts, however, indicates substrate rotations of only approximately 50 degrees . This paradox is resolved by demonstrating that the axial His25 imidazole ring also rotates counterclockwise with respect to the protein matrix in the mutant relative to that in the WT. The axial His25 CbetaH hyperfine shifts are shown to serve as independent probes of the imidazole plane orientation relative to the protein matrix. The analysis indicates that the pattern of heme methyl hyperfine shifts cannot be used alone to determine the in-plane orientation of the substrate as it relates to the stereospecificity of heme cleavage, without explicit consideration of the orientation of the axial His imidazole plane relative to the protein matrix.

Abscisic Acid Participates in the Control of Cell Cycle Initiation Through Heme Homeostasis in the Unicellular Red Alga Cyanidioschyzon merolae.

PubMed

Kobayashi, Yuki; Ando, Hiroyuki; Hanaoka, Mitsumasa; Tanaka, Kan

2016-05-01

ABA is a phytohormone that is synthesized in response to abiotic stresses and other environmental changes, inducing various physiological responses. While ABA has been found in unicellular photosynthetic organisms, such as cyanobacteria and eukaryotic algae, its function in these organisms is poorly understood. Here, we found that ABA accumulated in the unicellular red alga Cyanidioschyzon merolae under conditions of salt stress and that the cell cycle G1/S transition was inhibited when ABA was added to the culture medium. A gene encoding heme-scavenging tryptophan-rich sensory protein-related protein (CmTSPO; CMS231C) was positively regulated by ABA, as in Arabidopsis, and CmTSPO bound heme in vitro. The intracellular content of total heme was increased by addition of ABA, but unfettered heme decreased, presumably due to scavenging by CmTSPO. The inhibition of DNA replication by ABA was negated by addition of heme to the culture medium. Thus, we propose a regulatory role for ABA and heme in algal cell cycle initiation. Finally, we found that a C. merolae mutant that is defective in ABA production was more susceptible to salt stress, indicating the importance of ABA to stress resistance in red algae. © The Author 2016. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Hemolysis-induced lethality involves inflammasome activation by heme

PubMed Central

Dutra, Fabianno F.; Alves, Letícia S.; Rodrigues, Danielle; Fernandez, Patricia L.; de Oliveira, Rosane B.; Golenbock, Douglas T.; Zamboni, Dario S.; Bozza, Marcelo T.

2014-01-01

The increase of extracellular heme is a hallmark of hemolysis or extensive cell damage. Heme has prooxidant, cytotoxic, and inflammatory effects, playing a central role in the pathogenesis of malaria, sepsis, and sickle cell disease. However, the mechanisms by which heme is sensed by innate immune cells contributing to these diseases are not fully characterized. We found that heme, but not porphyrins without iron, activated LPS-primed macrophages promoting the processing of IL-1β dependent on nucleotide-binding domain and leucine rich repeat containing family, pyrin domain containing 3 (NLRP3). The activation of NLRP3 by heme required spleen tyrosine kinase, NADPH oxidase-2, mitochondrial reactive oxygen species, and K+ efflux, whereas it was independent of heme internalization, lysosomal damage, ATP release, the purinergic receptor P2X7, and cell death. Importantly, our results indicated the participation of macrophages, NLRP3 inflammasome components, and IL-1R in the lethality caused by sterile hemolysis. Thus, understanding the molecular pathways affected by heme in innate immune cells might prove useful to identify new therapeutic targets for diseases that have heme release. PMID:25225402

Signal Correlations in Ecological Niches Can Shape the Organization and Evolution of Bacterial Gene Regulatory Networks

PubMed Central

Dufour, Yann S.; Donohue, Timothy J.

2015-01-01

Transcriptional regulation plays a significant role in the biological response of bacteria to changing environmental conditions. Therefore, mapping transcriptional regulatory networks is an important step not only in understanding how bacteria sense and interpret their environment but also to identify the functions involved in biological responses to specific conditions. Recent experimental and computational developments have facilitated the characterization of regulatory networks on a genome-wide scale in model organisms. In addition, the multiplication of complete genome sequences has encouraged comparative analyses to detect conserved regulatory elements and infer regulatory networks in other less well-studied organisms. However, transcription regulation appears to evolve rapidly, thus, creating challenges for the transfer of knowledge to nonmodel organisms. Nevertheless, the mechanisms and constraints driving the evolution of regulatory networks have been the subjects of numerous analyses, and several models have been proposed. Overall, the contributions of mutations, recombination, and horizontal gene transfer are complex. Finally, the rapid evolution of regulatory networks plays a significant role in the remarkable capacity of bacteria to adapt to new or changing environments. Conversely, the characteristics of environmental niches determine the selective pressures and can shape the structure of regulatory network accordingly. PMID:23046950

Architecture of the human regulatory network derived from ENCODE data.

PubMed

Gerstein, Mark B; Kundaje, Anshul; Hariharan, Manoj; Landt, Stephen G; Yan, Koon-Kiu; Cheng, Chao; Mu, Xinmeng Jasmine; Khurana, Ekta; Rozowsky, Joel; Alexander, Roger; Min, Renqiang; Alves, Pedro; Abyzov, Alexej; Addleman, Nick; Bhardwaj, Nitin; Boyle, Alan P; Cayting, Philip; Charos, Alexandra; Chen, David Z; Cheng, Yong; Clarke, Declan; Eastman, Catharine; Euskirchen, Ghia; Frietze, Seth; Fu, Yao; Gertz, Jason; Grubert, Fabian; Harmanci, Arif; Jain, Preti; Kasowski, Maya; Lacroute, Phil; Leng, Jing Jane; Lian, Jin; Monahan, Hannah; O'Geen, Henriette; Ouyang, Zhengqing; Partridge, E Christopher; Patacsil, Dorrelyn; Pauli, Florencia; Raha, Debasish; Ramirez, Lucia; Reddy, Timothy E; Reed, Brian; Shi, Minyi; Slifer, Teri; Wang, Jing; Wu, Linfeng; Yang, Xinqiong; Yip, Kevin Y; Zilberman-Schapira, Gili; Batzoglou, Serafim; Sidow, Arend; Farnham, Peggy J; Myers, Richard M; Weissman, Sherman M; Snyder, Michael

2012-09-06

Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the principles of the human transcriptional regulatory network, we determined the genomic binding information of 119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations. In particular, there are significant differences in the binding proximal and distal to genes. We organized all the transcription factor binding into a hierarchy and integrated it with other genomic information (for example, microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome sequences and understanding basic principles of human biology and disease.

Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

PubMed Central

Liu, Zhi-Ping

2015-01-01

Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

A statistical method for measuring activation of gene regulatory networks.

PubMed

Esteves, Gustavo H; Reis, Luiz F L

2018-06-13

Gene expression data analysis is of great importance for modern molecular biology, given our ability to measure the expression profiles of thousands of genes and enabling studies rooted in systems biology. In this work, we propose a simple statistical model for the activation measuring of gene regulatory networks, instead of the traditional gene co-expression networks. We present the mathematical construction of a statistical procedure for testing hypothesis regarding gene regulatory network activation. The real probability distribution for the test statistic is evaluated by a permutation based study. To illustrate the functionality of the proposed methodology, we also present a simple example based on a small hypothetical network and the activation measuring of two KEGG networks, both based on gene expression data collected from gastric and esophageal samples. The two KEGG networks were also analyzed for a public database, available through NCBI-GEO, presented as Supplementary Material. This method was implemented in an R package that is available at the BioConductor project website under the name maigesPack.

Chemistry and Molecular Dynamics Simulations of Heme b-HemQ and Coproheme-HemQ

PubMed Central

2016-01-01

Recently, a novel pathway for heme b biosynthesis in Gram-positive bacteria has been proposed. The final poorly understood step is catalyzed by an enzyme called HemQ and includes two decarboxylation reactions leading from coproheme to heme b. Coproheme has been suggested to act as both substrate and redox active cofactor in this reaction. In the study presented here, we focus on HemQs from Listeria monocytogenes (LmHemQ) and Staphylococcus aureus (SaHemQ) recombinantly produced as apoproteins in Escherichia coli. We demonstrate the rapid and two-phase uptake of coproheme by both apo forms and the significant differences in thermal stability of the apo forms, coproheme-HemQ and heme b-HemQ. Reduction of ferric high-spin coproheme-HemQ to the ferrous form is shown to be enthalpically favored but entropically disfavored with standard reduction potentials of −205 ± 3 mV for LmHemQ and −207 ± 3 mV for SaHemQ versus the standard hydrogen electrode at pH 7.0. Redox thermodynamics suggests the presence of a pronounced H-bonding network and restricted solvent mobility in the heme cavity. Binding of cyanide to the sixth coproheme position is monophasic but relatively slow (∼1 × 104 M–1 s–1). On the basis of the available structures of apo-HemQ and modeling of both loaded forms, molecular dynamics simulation allowed analysis of the interaction of coproheme and heme b with the protein as well as the role of the flexibility at the proximal heme cavity and the substrate access channel for coproheme binding and heme b release. Obtained data are discussed with respect to the proposed function of HemQ in monoderm bacteria. PMID:27599156

THE HEME BINDING PROPERTIES OF GLYCERALDEHYDE-3-PHOSPHATE DEHYDROGENASE

PubMed Central

Hannibal, Luciana; Collins, Daniel; Brassard, Julie; Chakravarti, Ritu; Vempati, Rajesh; Dorlet, Pierre; Santolini, Jérôme; Dawson, John H.; Stuehr, Dennis J.

2012-01-01

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is a glycolytic enzyme that also functions in transcriptional regulation, oxidative stress, vesicular trafficking, and apoptosis. Because GAPDH is required for cellular heme insertion into inducible nitric oxide synthase (Chakravarti et al, PNAS 2010, 107(42):18004-9), we extensively characterized the heme binding properties of GAPDH. Substoichiometric amounts of ferric heme bound to GAPDH (1 heme per GAPDH tetramer) to form a low-spin complex with UV-visible maxima at 362, 418 and 537 nm, and when reduced to ferrous gave maxima at 424, 527 and 559 nm. Ferric heme association and dissociation rate constants at 10 °C were kon =17,800 M−1s−1 and koff1 = 7.0 × 10−3 s−1; koff2 = 3.3 × 10−4 s−1 respectively, giving approximate affinities of 19–390 nM. Ferrous heme bound more poorly to GAPDH and dissociated with a koff = 4.2 × 10−3 s−1. Magnetic circular dichroism (MCD), resonance Raman (rR) and EPR spectroscopic data on the ferric, ferrous, and ferrous-CO complexes of GAPDH showed that the heme is bis-ligated with His as the proximal ligand. The distal ligand in ferric complex was not displaced by CN− or N3− but in ferrous complex was displaceable by CO at a rate of 1.75 s−1 (for [CO]>0.2 mM). Studies with heme analogs revealed selectivity toward the coordinating metal and porphyrin ring structure. GAPDH-heme was isolated from bacteria induced to express rabbit GAPDH in the presence of δ-amino levulinic acid. Our finding of heme binding to GAPDH expands the protein’s potential roles. The strength, selectivity, reversibility, and redox sensitivity of heme binding to GAPDH is consistent with it performing heme sensing or heme chaperone-like functions in cells. PMID:22957700

The radical SAM protein HemW is a heme chaperone.

PubMed

Haskamp, Vera; Karrie, Simone; Mingers, Toni; Barthels, Stefan; Alberge, François; Magalon, Axel; Müller, Katrin; Bill, Eckhard; Lubitz, Wolfgang; Kleeberg, Kirstin; Schweyen, Peter; Bröring, Martin; Jahn, Martina; Jahn, Dieter

2018-02-16

Radical S -adenosylmethionine (SAM) enzymes exist in organisms from all kingdoms of life, and all of these proteins generate an adenosyl radical via the homolytic cleavage of the S-C(5') bond of SAM. Of particular interest are radical SAM enzymes, such as heme chaperones, that insert heme into respiratory enzymes. For example, heme chaperones insert heme into target proteins but have been studied only for the formation of cytochrome c -type hemoproteins. Here, we report that a radical SAM protein, the heme chaperone HemW from bacteria, is required for the insertion of heme b into respiratory chain enzymes. As other radical SAM proteins, HemW contains three cysteines and one SAM coordinating an [4Fe-4S] cluster, and we observed one heme per subunit of HemW. We found that an intact iron-sulfur cluster was required for HemW dimerization and HemW-catalyzed heme transfer but not for stable heme binding. A bacterial two-hybrid system screen identified bacterioferritins and the heme-containing subunit NarI of the respiratory nitrate reductase NarGHI as proteins that interact with HemW. We also noted that the bacterioferritins potentially serve as heme donors for HemW. Of note, heme that was covalently bound to HemW was actively transferred to a heme-depleted, catalytically inactive nitrate reductase, restoring its nitrate-reducing enzyme activity. Finally, the human HemW orthologue radical SAM domain-containing 1 (RSAD1) stably bound heme. In conclusion, our findings indicate that the radical SAM protein family HemW/RSAD1 is a heme chaperone catalyzing the insertion of heme into hemoproteins. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Integrating non-coding RNAs in JAK-STAT regulatory networks

PubMed Central

Witte, Steven; Muljo, Stefan A

2014-01-01

Being a well-characterized pathway, JAK-STAT signaling serves as a valuable paradigm for studying the architecture of gene regulatory networks. The discovery of untranslated or non-coding RNAs, namely microRNAs and long non-coding RNAs, provides an opportunity to elucidate their roles in such networks. In principle, these regulatory RNAs can act as downstream effectors of the JAK-STAT pathway and/or affect signaling by regulating the expression of JAK-STAT components. Examples of interactions between signaling pathways and non-coding RNAs have already emerged in basic cell biology and human diseases such as cancer, and can potentially guide the identification of novel biomarkers or drug targets for medicine. PMID:24778925

Studying disorders of vertebrate iron and heme metabolism using zebrafish

PubMed Central

van der Vorm, Lisa N.; Paw, Barry H.

2017-01-01

Iron is a crucial component of heme- and iron-sulfur clusters, involved in vital cellular functions such as oxygen transport, DNA synthesis, and respiration. Both excess and insufficient levels of iron and heme-precursors cause human disease, such as iron-deficiency anemia, hemochromatosis, and porphyrias. Hence, their levels must be tightly regulated, requiring a complex network of transporters and feedback mechanisms. The use of zebrafish to study these pathways and the underlying genetics offers many advantages, among others their optical transparency, ex-vivo development and high genetic and physiological conservations. This chapter first reviews well-established methods, such as large-scale mutagenesis screens that have led to the initial identification of a series of iron and heme transporters and the generation of a variety of mutant lines. Other widely used techniques are based on injection of RNA, including complementary morpholino knockdown and gene overexpression. In addition, we highlight several recently developed approaches, most notably endonuclease-based gene knockouts such as TALENs or the CRISPR/Cas9 system that have been used to study how loss of function can induce human disease phenocopies in zebrafish. Rescue by chemical complementation with iron-based compounds or small molecules can subsequently be used to confirm causality of the genetic defect for the observed phenotype. All together, zebrafish have proven to be – and will continue to serve as an ideal model to advance our understanding of the pathogenesis of human iron and heme-related diseases and to develop novel therapies to treat these conditions. PMID:28129844

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

PubMed

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

O 2 Activation by Non-Heme Iron Enzymes

DOE PAGES

Solomon, Edward I.; Goudarzi, Serra; Sutherlin, Kyle D.

2016-10-28

The non-heme Fe enzymes are ubiquitous in nature and perform a wide range of functions involving O 2 activation. These had been difficult to study relative to heme enzymes; however, spectroscopic methods have now been developed that provide significant insight into the correlation of structure with function. This Current Topics article summarizes both the molecular mechanism these enzymes use to control O 2 activation in the presence of cosubstrates and the oxygen intermediates these reactions generate. Three types of O 2 activation are observed. First, non-heme reactivity is shown to be different from heme chemistry where a low-spin Fe III-OOHmore » non-heme intermediate directly reacts with substrate. Also, two subclasses of non-heme Fe enzymes generate high-spin Fe IV=O intermediates that provide both σ and π frontier molecular orbitals that can control selectivity. Lastly, for several subclasses of non-heme Fe enzymes, substrate binding to the Fe II site leads to the one electron reductive activation of O 2 to an Fe III-superoxide capable of H-atom abstraction and electrophilic attack.« less

Structure and function of enzymes in heme biosynthesis.

PubMed

Layer, Gunhild; Reichelt, Joachim; Jahn, Dieter; Heinz, Dirk W

2010-06-01

Tetrapyrroles like hemes, chlorophylls, and cobalamin are complex macrocycles which play essential roles in almost all living organisms. Heme serves as prosthetic group of many proteins involved in fundamental biological processes like respiration, photosynthesis, and the metabolism and transport of oxygen. Further, enzymes such as catalases, peroxidases, or cytochromes P450 rely on heme as essential cofactors. Heme is synthesized in most organisms via a highly conserved biosynthetic route. In humans, defects in heme biosynthesis lead to severe metabolic disorders called porphyrias. The elucidation of the 3D structures for all heme biosynthetic enzymes over the last decade provided new insights into their function and elucidated the structural basis of many known diseases. In terms of structure and function several rather unique proteins were revealed such as the V-shaped glutamyl-tRNA reductase, the dipyrromethane cofactor containing porphobilinogen deaminase, or the "Radical SAM enzyme" coproporphyrinogen III dehydrogenase. This review summarizes the current understanding of the structure-function relationship for all heme biosynthetic enzymes and their potential interactions in the cell.

O 2 Activation by Non-Heme Iron Enzymes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solomon, Edward I.; Goudarzi, Serra; Sutherlin, Kyle D.

The non-heme Fe enzymes are ubiquitous in nature and perform a wide range of functions involving O 2 activation. These had been difficult to study relative to heme enzymes; however, spectroscopic methods have now been developed that provide significant insight into the correlation of structure with function. This Current Topics article summarizes both the molecular mechanism these enzymes use to control O 2 activation in the presence of cosubstrates and the oxygen intermediates these reactions generate. Three types of O 2 activation are observed. First, non-heme reactivity is shown to be different from heme chemistry where a low-spin Fe III-OOHmore » non-heme intermediate directly reacts with substrate. Also, two subclasses of non-heme Fe enzymes generate high-spin Fe IV=O intermediates that provide both σ and π frontier molecular orbitals that can control selectivity. Lastly, for several subclasses of non-heme Fe enzymes, substrate binding to the Fe II site leads to the one electron reductive activation of O 2 to an Fe III-superoxide capable of H-atom abstraction and electrophilic attack.« less

Molecular Phylogeny of Heme Peroxidases

NASA Astrophysics Data System (ADS)

Zámocký, Marcel; Obinger, Christian

All currently available gene sequences of heme peroxidases can be phylogenetically divided in two superfamilies and three families. In this chapter, the phylogenetics and genomic distribution of each group are presented. Within the peroxidase-cyclooxygenase superfamily, the main evolutionary direction developed peroxidatic heme proteins involved in the innate immune defense system and in biosynthesis of (iodinated) hormones. The peroxidase-catalase superfamily is widely spread mainly among bacteria, fungi, and plants, and particularly in Class I led to the evolution of bifunctional catalase-peroxidases. Its numerous fungal representatives of Class II are involved in carbon recycling via lignin degradation, whereas Class III secretory peroxidases from algae and plants are included in various forms of secondary metabolism. The family of di-heme peroxidases are predominantly bacteria-inducible enzymes; however, a few corresponding genes were also detected in archaeal genomes. Four subfamilies of dyp-type peroxidases capable of degradation of various xenobiotics are abundant mainly among bacteria and fungi. Heme-haloperoxidase genes are widely spread among sac and club fungi, but corresponding genes were recently found also among oomycetes. All described families herein represent heme peroxidases of broad diversity in structure and function. Our accumulating knowledge about the evolution of various enzymatic functions and physiological roles can be exploited in future directed evolution approaches for engineering peroxidase genes de novo for various demands.

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faria, Jose P.; Overbeek, Ross; Taylor, Ronald C.

Here, we introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, wemore » reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

DOE PAGES

Faria, Jose P.; Overbeek, Ross; Taylor, Ronald C.; ...

2016-03-18

Here, we introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, wemore » reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

PubMed

Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

2017-05-01

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

Identification of critical regulatory genes in cancer signaling network using controllability analysis

NASA Astrophysics Data System (ADS)

Ravindran, Vandana; Sunitha, V.; Bagler, Ganesh

2017-05-01

Cancer is characterized by a complex web of regulatory mechanisms which makes it difficult to identify features that are central to its control. Molecular integrative models of cancer, generated with the help of data from experimental assays, facilitate use of control theory to probe for ways of controlling the state of such a complex dynamic network. We modeled the human cancer signaling network as a directed graph and analyzed it for its controllability, identification of driver nodes and their characterization. We identified the driver nodes using the maximum matching algorithm and classified them as backbone, peripheral and ordinary based on their role in regulatory interactions and control of the network. We found that the backbone driver nodes were key to driving the regulatory network into cancer phenotype (via mutations) as well as for steering into healthy phenotype (as drug targets). This implies that while backbone genes could lead to cancer by virtue of mutations, they are also therapeutic targets of cancer. Further, based on their impact on the size of the set of driver nodes, genes were characterized as indispensable, dispensable and neutral. Indispensable nodes within backbone of the network emerged as central to regulatory mechanisms of control of cancer. In addition to probing the cancer signaling network from the perspective of control, our findings suggest that indispensable backbone driver nodes could be potentially leveraged as therapeutic targets. This study also illustrates the application of structural controllability for studying the mechanisms underlying the regulation of complex diseases.

Cyanide binding to human plasma heme-hemopexin: A comparative study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ascenzi, Paolo, E-mail: ascenzi@uniroma3.it; Istituto Nazionale di Biostrutture e Biosistemi, Roma; Leboffe, Loris

Highlights: Black-Right-Pointing-Pointer Cyanide binding to ferric HHPX-heme-Fe. Black-Right-Pointing-Pointer Cyanide binding to ferrous HHPX-heme-Fe. Black-Right-Pointing-Pointer Dithionite-mediated reduction of ferric HHPX-heme-Fe-cyanide. Black-Right-Pointing-Pointer Cyanide binding to HHPX-heme-Fe is limited by ligand deprotonation. Black-Right-Pointing-Pointer Cyanide dissociation from HHPX-heme-Fe-cyanide is limited by ligand protonation. -- Abstract: Hemopexin (HPX) displays a pivotal role in heme scavenging and delivery to the liver. In turn, heme-Fe-hemopexin (HPX-heme-Fe) displays heme-based spectroscopic and reactivity properties. Here, kinetics and thermodynamics of cyanide binding to ferric and ferrous hexa-coordinate human plasma HPX-heme-Fe (HHPX-heme-Fe(III) and HHPX-heme-Fe(II), respectively), and for the dithionite-mediated reduction of the HHPX-heme-Fe(III)-cyanide complex, at pH 7.4 and 20.0 Degree-Sign C,more » are reported. Values of thermodynamic and kinetic parameters for cyanide binding to HHPX-heme-Fe(III) and HHPX-heme-Fe(II) are K = (4.1 {+-} 0.4) Multiplication-Sign 10{sup -6} M, k{sub on} = (6.9 {+-} 0.5) Multiplication-Sign 10{sup 1} M{sup -1} s{sup -1}, and k{sub off} = 2.8 Multiplication-Sign 10{sup -4} s{sup -1}; and H = (6 {+-} 1) Multiplication-Sign 10{sup -1} M, h{sub on} = 1.2 Multiplication-Sign 10{sup -1} M{sup -1} s{sup -1}, and h{sub off} = (7.1 {+-} 0.8) Multiplication-Sign 10{sup -2} s{sup -1}, respectively. The value of the rate constant for the dithionite-mediated reduction of the HHPX-heme-Fe(III)-cyanide complex is l = 8.9 {+-} 0.8 M{sup -1/2} s{sup -1}. HHPX-heme-Fe reactivity is modulated by proton acceptor/donor amino acid residue(s) (e.g., His236) assisting the deprotonation and protonation of the incoming and outgoing ligand, respectively.« less

Evolution of regulatory networks towards adaptability and stability in a changing environment

NASA Astrophysics Data System (ADS)

Lee, Deok-Sun

2014-11-01

Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

The Legend of Sally Hemings

ERIC Educational Resources Information Center

Belz, Herman

2012-01-01

The part played by Sally Hemings in the life of Thomas Jefferson has been regarded as provocatively dubious since political enemy James Callender claimed in 1802 that Jefferson was the father of several of Hemings's children. Historian Merrill Peterson, observing that paternity is hard to prove, wrote in 1960 that no concrete evidence was ever…

Covalent heme attachment to the protein in human heme oxygenase-1 with selenocysteine replacing the His25 proximal iron ligand

PubMed Central

Jiang, Yongying; Trnka, Michael J.; Medzihradszky, Katalin F.; Ouellet, Hugues; Wang, Yongqiang; Ortiz de Montellano, Paul R.

2009-01-01

To characterize heme oxygenase with a selenocysteine (SeCys) as the proximal iron ligand, we have expressed truncated human heme oxygenase-1 (hHO-1) His25Cys, in which Cys-25 is the only cysteine, in the Escherichia coli cysteine auxotroph strain BL21(DE3)cys. Selenocysteine incorporation into the protein was demonstrated by both intact protein mass measurement and mass spectrometric identification of the selenocysteine-containing tryptic peptide. One selenocysteine was incorporated into approximately 95% of the expressed protein. Formation of an adduct with Ellman's reagent (DTNB) indicated that the selenocysteine in the expressed protein was in the reduced state. The heme-His25SeCys hHO-1 complex could be prepared by either (a) supplementing the overexpression medium with heme, or (b) reconstituting the purified apoprotein with heme. Under reducing conditions in the presence of imidazole, a covalent bond is formed by addition of the selenocysteine residue to one of the heme vinyl groups. No covalent bond is formed when the heme is replaced by mesoheme, in which the vinyls are replaced by ethyl groups. These results, together with our earlier demonstration that external selenolate ligands can transfer an electron to the iron (Jiang, Y., Ortiz de Montellano, P.R., Inorg. Chem., 47, 3480-3482 (2008)), indicate that a selenyl radical is formed in the hHO1 His25SeCys mutant that adds to a heme vinyl group. PMID:19135260

Covalent heme attachment to the protein in human heme oxygenase-1 with selenocysteine replacing the His25 proximal iron ligand.

PubMed

Jiang, Yongying; Trnka, Michael J; Medzihradszky, Katalin F; Ouellet, Hugues; Wang, Yongqiang; Ortiz de Montellano, Paul R

2009-03-01

To characterize heme oxygenase with a selenocysteine (SeCys) as the proximal iron ligand, we have expressed truncated human heme oxygenase-1 (hHO-1) His25Cys, in which Cys-25 is the only cysteine, in the Escherichia coli cysteine auxotroph strain BL21(DE3)cys. Selenocysteine incorporation into the protein was demonstrated by both intact protein mass measurement and mass spectrometric identification of the selenocysteine-containing tryptic peptide. One selenocysteine was incorporated into approximately 95% of the expressed protein. Formation of an adduct with Ellman's reagent (DTNB) indicated that the selenocysteine in the expressed protein was in the reduced state. The heme-His25SeCys hHO-1 complex could be prepared by either (a) supplementing the overexpression medium with heme, or (b) reconstituting the purified apoprotein with heme. Under reducing conditions in the presence of imidazole, a covalent bond is formed by addition of the selenocysteine residue to one of the heme vinyl groups. No covalent bond is formed when the heme is replaced by mesoheme, in which the vinyls are replaced by ethyl groups. These results, together with our earlier demonstration that external selenolate ligands can transfer an electron to the iron [Y. Jiang, P.R. Ortiz de Montellano, Inorg. Chem. 47 (2008) 3480-3482 ], indicate that a selenyl radical is formed in the hHO-1 His25SeCys mutant that adds to a heme vinyl group.

Uncovering transcription factor and microRNA risk regulatory pathways associated with osteoarthritis by network analysis.

PubMed

Song, Zhenhua; Zhang, Chi; He, Lingxiao; Sui, Yanfang; Lin, Xiafei; Pan, Jingjing

2018-06-12

Osteoarthritis (OA) is the most common form of joint disease. The development of inflammation have been considered to play a key role during the progression of OA. Regulatory pathways are known to play crucial roles in many pathogenic processes. Thus, deciphering these risk regulatory pathways is critical for elucidating the mechanisms underlying OA. We constructed an OA-specific regulatory network by integrating comprehensive curated transcription and post-transcriptional resource involving transcription factor (TF) and microRNA (miRNA). To deepen our understanding of underlying molecular mechanisms of OA, we developed an integrated systems approach to identify OA-specific risk regulatory pathways. In this study, we identified 89 significantly differentially expressed genes between normal and inflamed areas of OA patients. We found the OA-specific regulatory network was a standard scale-free network with small-world properties. It significant enriched many immune response-related functions including leukocyte differentiation, myeloid differentiation and T cell activation. Finally, 141 risk regulatory pathways were identified based on OA-specific regulatory network, which contains some known regulator of OA. The risk regulatory pathways may provide clues for the etiology of OA and be a potential resource for the discovery of novel OA-associated disease genes. Copyright © 2018 Elsevier Inc. All rights reserved.

Mini Heme-Proteins: Designability of Structure and Diversity of Functions.

PubMed

Rai, Jagdish

2017-08-30

Natural heme proteins may have heme bound to poly-peptide chain as a cofactor via noncovalent forces or heme as a prosthetic group may be covalently bound to the proteins. Nature has used porphyrins in diverse functions like electron transfer, oxidation, reduction, ligand binding, photosynthesis, signaling, etc. by modulating its properties through diverse protein matrices. Synthetic chemists have tried to utilize these molecules in equally diverse industrial and medical applications due to their versatile electro-chemical and optical properties. The heme iron has catalytic activity which can be modulated and enhanced for specific applications by protein matrix around it. Heme proteins can be designed into novel enzymes for sterio specific catalysis ranging from oxidation to reduction. These designed heme-proteins can have applications in industrial catalysis and biosensing. A peptide folds around heme easily due to hydrophobic effect of the large aromatic ring of heme. The directional property of co-ordinate bonding between peptide and metal ion in heme further specifies the structure. Therefore heme proteins can be easily designed for targeted structure and catalytic activity. The central aromatic chemical entity in heme viz. porphyrin is a very ancient molecule. Its presence in the prebiotic soup and in all forms of life suggests that it has played a vital role in the origin and progressive evolution of living organisms. Porphyrin macrocycles are highly conjugated systems composed of four modified pyrrole subunits interconnected at their α -carbon atoms via methine (=CH-) bridges. Initial minimalist models of hemoproteins focused on effect of heme-ligand co-ordinate bonding on chemical reactivity, spectroscopy, electrochemistry and magnetic properties of heme. The great sensitivity of these spectroscopic features of heme to its surrounding makes them extremely useful in structural elucidation of designed heme-peptide complexes. Therefore heme proteins are

Regulatory Aspects of Smart Water Networks in the U.S.

EPA Science Inventory

The presentation addresses regulatory aspects of smart water networks in the U.S. It will be presented at the Smart Water Networks Forum (SWAN) annual conference in London, England from April 29-30, 2015. The conference will bring together key voices in the smart water space f...

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

PubMed Central

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-01-01

Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation. PMID:16478536

Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

NASA Astrophysics Data System (ADS)

Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A.

2016-10-01

Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way -even for asynchronous updating rules- and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity.

Noncoding RNA:RNA Regulatory Networks in Cancer

PubMed Central

Chan, Jia Jia; Tay, Yvonne

2018-01-01

Noncoding RNAs (ncRNAs) constitute the majority of the human transcribed genome. This largest class of RNA transcripts plays diverse roles in a multitude of cellular processes, and has been implicated in many pathological conditions, especially cancer. The different subclasses of ncRNAs include microRNAs, a class of short ncRNAs; and a variety of long ncRNAs (lncRNAs), such as lincRNAs, antisense RNAs, pseudogenes, and circular RNAs. Many studies have demonstrated the involvement of these ncRNAs in competitive regulatory interactions, known as competing endogenous RNA (ceRNA) networks, whereby lncRNAs can act as microRNA decoys to modulate gene expression. These interactions are often interconnected, thus aberrant expression of any network component could derail the complex regulatory circuitry, culminating in cancer development and progression. Recent integrative analyses have provided evidence that new computational platforms and experimental approaches can be harnessed together to distinguish key ceRNA interactions in specific cancers, which could facilitate the identification of robust biomarkers and therapeutic targets, and hence, more effective cancer therapies and better patient outcome and survival. PMID:29702599

Inferring Regulatory Networks by Combining Perturbation Screens and Steady State Gene Expression Profiles

PubMed Central

Michailidis, George

2014-01-01

Reconstructing transcriptional regulatory networks is an important task in functional genomics. Data obtained from experiments that perturb genes by knockouts or RNA interference contain useful information for addressing this reconstruction problem. However, such data can be limited in size and/or are expensive to acquire. On the other hand, observational data of the organism in steady state (e.g., wild-type) are more readily available, but their informational content is inadequate for the task at hand. We develop a computational approach to appropriately utilize both data sources for estimating a regulatory network. The proposed approach is based on a three-step algorithm to estimate the underlying directed but cyclic network, that uses as input both perturbation screens and steady state gene expression data. In the first step, the algorithm determines causal orderings of the genes that are consistent with the perturbation data, by combining an exhaustive search method with a fast heuristic that in turn couples a Monte Carlo technique with a fast search algorithm. In the second step, for each obtained causal ordering, a regulatory network is estimated using a penalized likelihood based method, while in the third step a consensus network is constructed from the highest scored ones. Extensive computational experiments show that the algorithm performs well in reconstructing the underlying network and clearly outperforms competing approaches that rely only on a single data source. Further, it is established that the algorithm produces a consistent estimate of the regulatory network. PMID:24586224

Aerobic kinetoplastid flagellate Phytomonas does not require heme for viability

PubMed Central

Kořený, Luděk; Sobotka, Roman; Kovářová, Julie; Gnipová, Anna; Flegontov, Pavel; Horváth, Anton; Oborník, Miroslav; Ayala, Francisco J.; Lukeš, Julius

2012-01-01

Heme is an iron-coordinated porphyrin that is universally essential as a protein cofactor for fundamental cellular processes, such as electron transport in the respiratory chain, oxidative stress response, or redox reactions in various metabolic pathways. Parasitic kinetoplastid flagellates represent a rare example of organisms that depend on oxidative metabolism but are heme auxotrophs. Here, we show that heme is fully dispensable for the survival of Phytomonas serpens, a plant parasite. Seeking to understand the metabolism of this heme-free eukaryote, we searched for heme-containing proteins in its de novo sequenced genome and examined several cellular processes for which heme has so far been considered indispensable. We found that P. serpens lacks most of the known hemoproteins and does not require heme for electron transport in the respiratory chain, protection against oxidative stress, or desaturation of fatty acids. Although heme is still required for the synthesis of ergosterol, its precursor, lanosterol, is instead incorporated into the membranes of P. serpens grown in the absence of heme. In conclusion, P. serpens is a flagellate with unique metabolic adaptations that allow it to bypass all requirements for heme. PMID:22355128

Aerobic kinetoplastid flagellate Phytomonas does not require heme for viability.

PubMed

Kořený, Luděk; Sobotka, Roman; Kovářová, Julie; Gnipová, Anna; Flegontov, Pavel; Horváth, Anton; Oborník, Miroslav; Ayala, Francisco J; Lukeš, Julius

2012-03-06

Heme is an iron-coordinated porphyrin that is universally essential as a protein cofactor for fundamental cellular processes, such as electron transport in the respiratory chain, oxidative stress response, or redox reactions in various metabolic pathways. Parasitic kinetoplastid flagellates represent a rare example of organisms that depend on oxidative metabolism but are heme auxotrophs. Here, we show that heme is fully dispensable for the survival of Phytomonas serpens, a plant parasite. Seeking to understand the metabolism of this heme-free eukaryote, we searched for heme-containing proteins in its de novo sequenced genome and examined several cellular processes for which heme has so far been considered indispensable. We found that P. serpens lacks most of the known hemoproteins and does not require heme for electron transport in the respiratory chain, protection against oxidative stress, or desaturation of fatty acids. Although heme is still required for the synthesis of ergosterol, its precursor, lanosterol, is instead incorporated into the membranes of P. serpens grown in the absence of heme. In conclusion, P. serpens is a flagellate with unique metabolic adaptations that allow it to bypass all requirements for heme.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

PubMed

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space.

PubMed

Ahnert, S E; Fink, T M A

2016-07-01

Network motifs have been studied extensively over the past decade, and certain motifs, such as the feed-forward loop, play an important role in regulatory networks. Recent studies have used Boolean network motifs to explore the link between form and function in gene regulatory networks and have found that the structure of a motif does not strongly determine its function, if this is defined in terms of the gene expression patterns the motif can produce. Here, we offer a different, higher-level definition of the 'function' of a motif, in terms of two fundamental properties of its dynamical state space as a Boolean network. One is the basin entropy, which is a complexity measure of the dynamics of Boolean networks. The other is the diversity of cyclic attractor lengths that a given motif can produce. Using these two measures, we examine all 104 topologically distinct three-node motifs and show that the structural properties of a motif, such as the presence of feedback loops and feed-forward loops, predict fundamental characteristics of its dynamical state space, which in turn determine aspects of its functional versatility. We also show that these higher-level properties have a direct bearing on real regulatory networks, as both basin entropy and cycle length diversity show a close correspondence with the prevalence, in neural and genetic regulatory networks, of the 13 connected motifs without self-interactions that have been studied extensively in the literature. © 2016 The Authors.

Dynamical modeling and analysis of large cellular regulatory networks

NASA Astrophysics Data System (ADS)

Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

2013-06-01

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Modeling Emergence in Neuroprotective Regulatory Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanfilippo, Antonio P.; Haack, Jereme N.; McDermott, Jason E.

2013-01-05

The use of predictive modeling in the analysis of gene expression data can greatly accelerate the pace of scientific discovery in biomedical research by enabling in silico experimentation to test disease triggers and potential drug therapies. Techniques that focus on modeling emergence, such as agent-based modeling and multi-agent simulations, are of particular interest as they support the discovery of pathways that may have never been observed in the past. Thus far, these techniques have been primarily applied at the multi-cellular level, or have focused on signaling and metabolic networks. We present an approach where emergence modeling is extended to regulatorymore » networks and demonstrate its application to the discovery of neuroprotective pathways. An initial evaluation of the approach indicates that emergence modeling provides novel insights for the analysis of regulatory networks that can advance the discovery of acute treatments for stroke and other diseases.« less

Regiospecificity determinants of human heme oxygenase: differential NADPH- and ascorbate-dependent heme cleavage by the R183E mutant.

PubMed

Wang, Jinling; Lad, Latesh; Poulos, Thomas L; Ortiz de Montellano, Paul R

2005-01-28

The ability of the human heme oxygenase-1 (hHO-1) R183E mutant to oxidize heme in reactions supported by either NADPH-cytochrome P450 reductase or ascorbic acid has been compared. The NADPH-dependent reaction, like that of wild-type hHO-1, yields exclusively biliverdin IXalpha. In contrast, the R183E mutant with ascorbic acid as the reductant produces biliverdin IXalpha (79 +/- 4%), IXdelta (19 +/- 3%), and a trace of IXbeta. In the presence of superoxide dismutase and catalase, the yield of biliverdin IXdelta is decreased to 8 +/- 1% with a corresponding increase in biliverdin IXalpha. Spectroscopic analysis of the NADPH-dependent reaction shows that the R183E ferric biliverdin complex accumulates, because reduction of the iron, which is required for sequential iron and biliverdin release, is impaired. Reversal of the charge at position 183 makes reduction of the iron more difficult. The crystal structure of the R183E mutant, determined in the ferric and ferrous-NO bound forms, shows that the heme primarily adopts the same orientation as in wild-type hHO-1. The structure of the Fe(II).NO complex suggests that an altered active site hydrogen bonding network supports catalysis in the R183E mutant. Furthermore, Arg-183 contributes to the regiospecificity of the wild-type enzyme, but its contribution is not critical. The results indicate that the ascorbate-dependent reaction is subject to a lower degree of regiochemical control than the NADPH-dependent reaction. Ascorbate may be able to reduce the R183E ferric and ferrous dioxygen complexes in active site conformations that cannot be reduced by NADPH-cytochrome P450 reductase.

Role of the Iron Axial Ligands of Heme Carrier HasA in Heme Uptake and Release*

PubMed Central

Caillet-Saguy, Célia; Piccioli, Mario; Turano, Paola; Lukat-Rodgers, Gudrun; Wolff, Nicolas; Rodgers, Kenton R.; Izadi-Pruneyre, Nadia; Delepierre, Muriel; Lecroisey, Anne

2012-01-01

The hemophore protein HasA from Serratia marcescens cycles between two states as follows: the heme-bound holoprotein, which functions as a carrier of the metal cofactor toward the membrane receptor HasR, and the heme-free apoprotein fishing for new porphyrin to be taken up after the heme has been delivered to HasR. Holo- and apo-forms differ for the conformation of the two loops L1 and L2, which provide the axial ligands of the iron through His32 and Tyr75, respectively. In the apo-form, loop L1 protrudes toward the solvent far away from loop L2; in the holoprotein, closing of the loops on the heme occurs upon establishment of the two axial coordination bonds. We have established that the two variants obtained via single point mutations of either axial ligand (namely H32A and Y75A) are both in the closed conformation. The presence of the heme and one out of two axial ligands is sufficient to establish a link between L1 and L2, thanks to the presence of coordinating solvent molecules. The latter are stabilized in the iron coordination environment by H-bond interactions with surrounding protein residues. The presence of such a water molecule in both variants is revealed here through a set of different spectroscopic techniques. Previous studies had shown that heme release and uptake processes occur via intermediate states characterized by a Tyr75-iron-bound form with open conformation of loop L1. Here, we demonstrate that these states do not naturally occur in the free protein but can only be driven by the interaction with the partner proteins. PMID:22700962

Design Principles of Regulatory Networks: Searching for the Molecular Algorithms of the Cell

PubMed Central

Lim, Wendell A.; Lee, Connie M.; Tang, Chao

2013-01-01

A challenge in biology is to understand how complex molecular networks in the cell execute sophisticated regulatory functions. Here we explore the idea that there are common and general principles that link network structures to biological functions, principles that constrain the design solutions that evolution can converge upon for accomplishing a given cellular task. We describe approaches for classifying networks based on abstract architectures and functions, rather than on the specific molecular components of the networks. For any common regulatory task, can we define the space of all possible molecular solutions? Such inverse approaches might ultimately allow the assembly of a design table of core molecular algorithms that could serve as a guide for building synthetic networks and modulating disease networks. PMID:23352241

A Systems' Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

PubMed Central

Kunz, Manfred; Vera, Julio; Wolkenhauer, Olaf

2013-01-01

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts. PMID:24350286

Transmutation of a heme protein.

PubMed Central

Barker, P D; Ferrer, J C; Mylrajan, M; Loehr, T M; Feng, R; Konishi, Y; Funk, W D; MacGillivray, R T; Mauk, A G

1993-01-01

Residue Asn57 of bovine liver cytochrome b5 has been replaced with a cysteine residue, and the resulting variant has been isolated from recombinant Escherichia coli as a mixture of four major species: A, BI, BII, and C. A combination of electronic spectroscopy, 1H NMR spectroscopy, resonance Raman spectroscopy, electrospray mass spectrometry, and direct electrochemistry has been used to characterize these four major cytochrome derivatives. The red form A (E(m) = -19 mV) is found to possess a heme group bound covalently through a thioether linkage involving Cys57 and the alpha carbon of the heme 4-vinyl group. Form BI has a covalently bound heme group coupled through a thioether linkage involving the beta carbon of the heme 4-vinyl group. Form BII is similar to BI except that the sulfur involved in the thioether linkage is oxidized to a sulfoxide. The green form C (E(m) = 175 mV) possesses a noncovalently bound prosthetic group with spectroscopic properties characteristic of a chlorin. A mechanism is proposed for the generation of these derivatives, and the implications of these observations for the biosynthesis of cytochrome c and naturally occurring chlorin prosthetic groups are discussed. PMID:8341666

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics.

PubMed

Ocone, Andrea; Millar, Andrew J; Sanguinetti, Guido

2013-04-01

Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem. Here, we develop a general statistical inference framework for stochastic transcription-translation networks. We use a coarse-grained approach, which represents the system as a network of stochastic (binary) promoter and (continuous) protein variables. We derive an exact inference algorithm and an efficient variational approximation that allows scalable inference and learning of the model parameters. We demonstrate the power of the approach on two biological case studies, showing that the method allows a high degree of flexibility and is capable of testable novel biological predictions. http://homepages.inf.ed.ac.uk/gsanguin/software.html. Supplementary data are available at Bioinformatics online.

A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe

PubMed Central

Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

2016-01-01

Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies. PMID:27014338

Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii

DOE PAGES

Gargouri, Mahmoud; Park, Jeong -Jin; Holguin, F. Omar; ...

2015-05-28

Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combinedmore » omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. In conclusion, evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism.« less

Analysis of Heme Iron Coordination in DGCR8: The Heme-Binding Component of the Microprocessor Complex.

PubMed

Girvan, Hazel M; Bradley, Justin M; Cheesman, Myles R; Kincaid, James R; Liu, Yilin; Czarnecki, Kazimierz; Fisher, Karl; Leys, David; Rigby, Stephen E J; Munro, Andrew W

2016-09-13

DGCR8 is the RNA-binding partner of the nuclease Drosha. Their complex (the "Microprocessor") is essential for processing of long, primary microRNAs (pri-miRNAs) in the nucleus. Binding of heme to DGCR8 is essential for pri-miRNA processing. On the basis of the split Soret ultraviolet-visible (UV-vis) spectrum of ferric DGCR8, bis-thiolate sulfur (cysteinate, Cys(-)) heme iron coordination of DGCR8 heme iron was proposed. We have characterized DGCR8 heme ligation using the Δ276 DGCR8 variant and combined electron paramagnetic resonance (EPR), magnetic circular dichroism (MCD), electron nuclear double resonance, resonance Raman, and electronic absorption spectroscopy. These studies indicate DGCR8 bis-Cys heme iron ligation, with conversion from bis-thiolate (Cys(-)/Cys(-)) axial coordination in ferric DGCR8 to bis-thiol (CysH/CysH) coordination in ferrous DGCR8. Pri-miRNA binding does not perturb ferric DGCR8's optical spectrum, consistent with the axial ligand environment being separated from the substrate-binding site. UV-vis absorption spectra of the Fe(II) and Fe(II)-CO forms indicate discrete species exhibiting peaks with absorption coefficients substantially larger than those for ferric DGCR8 and that previously reported for a ferrous form of DGCR8. Electron-nuclear double resonance spectroscopy data exclude histidine or water as axial ligands for ferric DGCR8 and favor bis-thiolate coordination in this form. UV-vis MCD and near-infrared MCD provide data consistent with this conclusion. UV-vis MCD data for ferrous DGCR8 reveal features consistent with bis-thiol heme iron coordination, and resonance Raman data for the ferrous-CO form are consistent with a thiol ligand trans to the CO. These studies support retention of DGCR8 cysteine coordination upon reduction, a conclusion distinct from those of previous studies of a different ferrous DGCR8 isoform.

Determinants of the heme-CO vibrational modes in the H-NOX family.

PubMed

Tran, Rosalie; Weinert, Emily E; Boon, Elizabeth M; Mathies, Richard A; Marletta, Michael A

2011-08-02

The Heme Nitric oxide/OXygen binding (H-NOX) family of proteins have important functions in gaseous ligand signaling in organisms from bacteria to humans, including nitric oxide (NO) sensing in mammals, and provide a model system for probing ligand selectivity in hemoproteins. A unique vibrational feature that is ubiquitous throughout the H-NOX family is the presence of a high C-O stretching frequency. To investigate the cause of this spectroscopic characteristic, the Fe-CO and C-O stretching frequencies were probed in the H-NOX domain from Thermoanaerobacter tengcongensis (Tt H-NOX) using resonance Raman (RR) spectroscopy. Four classes of heme pocket mutants were generated to assess the changes in stretching frequency: (i) the distal H-bonding network, (ii) the proximal histidine ligand, (iii) modulation of the heme conformation via Ile-5 and Pro-115, and (iv) the conserved Tyr-Ser-Arg (YxSxR) motif. These mutations revealed important electrostatic interactions that dampen the back-donation of the Fe(II) d(π) electrons into the CO π* orbitals. The most significant change occurred upon disruption of the H-bonds between the strictly conserved YxSxR motif and the heme propionate groups, producing two dominant CO-bound heme conformations. One conformer was structurally similar to Tt H-NOX WT, whereas the other displayed a decrease in ν(C-O) of up to ∼70 cm(-1) relative to the WT protein, with minimal changes in ν(Fe-CO). Taken together, these results show that the electrostatic interactions in the Tt H-NOX binding pocket are primarily responsible for the high ν(C-O) by decreasing the Fe d(π) → CO π* back-donation and suggest that the dominant mechanism by which this family modulates the Fe(II)-CO bond likely involves the YxSxR motif.

Determinants of the heme-CO vibrational modes in the H-NOX family†

PubMed Central

Tran, Rosalie; Weinert, Emily E.; Boon, Elizabeth M.; Mathies, Richard A.; Marletta, Michael A.

2011-01-01

The H-NOX family of proteins have important functions in gaseous ligand signaling in organisms from bacteria to humans, including nitric oxide (NO) sensing in mammals, and provide a model system for probing ligand selectivity in hemoproteins. A unique vibrational feature that is ubiquitous throughout the Heme-Nitric oxide/OXygen binding (H-NOX) family is the presence of a high C-O stretching frequency. To investigate the cause of this spectroscopic characteristic, the Fe-CO and C-O stretching frequencies were probed in the H-NOX domain from Thermoanaerobacter tengcongensis (Tt H-NOX) using resonance Raman (RR) spectroscopy. Four classes of heme pocket mutants were generated to assess the changes in stretching frequency: (i) the distal H-bonding network, (ii) the proximal histidine ligand, (iii) modulation of the heme conformation via Ile-5 and Pro-115, and (iv) the conserved Tyr-Ser-Arg (YxSxR) motif. These mutations revealed important electrostatic interactions that dampen the back-donation of the FeII dπ electrons into the CO π* orbitals. The most significant change occurred upon disruption of the H-bonds between the strictly conserved YxSxR motif and the heme propionate groups, producing two dominant CO-bound heme conformations. One conformer was structurally similar to Tt H-NOX WT; whereas the other displayed a decrease in ν(C-O) of up to ~70 cm−1 relative to the WT protein, with minimal changes in ν(Fe-CO). Taken together, these results show that the electrostatic interactions in the Tt H-NOX binding pocket are primarily responsible for the high ν(C-O) by decreasing the Fe dπ → CO π* back-donation, and suggest that the dominant mechanism by which this family modulates the FeII-CO bond likely involves the YxSxR motif. PMID:21714509

A Hox regulatory network establishes motor neuron pool identity and target-muscle connectivity.

PubMed

Dasen, Jeremy S; Tice, Bonnie C; Brenner-Morton, Susan; Jessell, Thomas M

2005-11-04

Spinal motor neurons acquire specialized "pool" identities that determine their ability to form selective connections with target muscles in the limb, but the molecular basis of this striking example of neuronal specificity has remained unclear. We show here that a Hox transcriptional regulatory network specifies motor neuron pool identity and connectivity. Two interdependent sets of Hox regulatory interactions operate within motor neurons, one assigning rostrocaudal motor pool position and a second directing motor pool diversity at a single segmental level. This Hox regulatory network directs the downstream transcriptional identity of motor neuron pools and defines the pattern of target-muscle connectivity.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

PubMed

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

Memory functions reveal structural properties of gene regulatory networks

PubMed Central

Perez-Carrasco, Ruben

2018-01-01

Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs. PMID:29470492

A reverse engineering approach to optimize experiments for the construction of biological regulatory networks.

PubMed

Zhang, Xiaomeng; Shao, Bin; Wu, Yangle; Qi, Ouyang

2013-01-01

One of the major objectives in systems biology is to understand the relation between the topological structures and the dynamics of biological regulatory networks. In this context, various mathematical tools have been developed to deduct structures of regulatory networks from microarray expression data. In general, from a single data set, one cannot deduct the whole network structure; additional expression data are usually needed. Thus how to design a microarray expression experiment in order to get the most information is a practical problem in systems biology. Here we propose three methods, namely, maximum distance method, trajectory entropy method, and sampling method, to derive the optimal initial conditions for experiments. The performance of these methods is tested and evaluated in three well-known regulatory networks (budding yeast cell cycle, fission yeast cell cycle, and E. coli. SOS network). Based on the evaluation, we propose an efficient strategy for the design of microarray expression experiments.

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer.

PubMed

Hao, Yibin; Shan, Guoyong; Nan, Kejun

2017-03-01

Our purpose is to screen out genetic markers applicable to early diagnosis for colorectal cancer and to establish apoptotic regulatory network model for colorectal cancer, thereby providing theoretical evidence and targeted therapy for early diagnosis of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers applied to early diagnosis of colorectal cancer were searched to perform comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to establish apoptotic regulatory network model based on screened genetic markers, and then verification experiment was conducted. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, among which DCC shows highest diagnostic efficiency. GO analysis of genetic markers found that six genetic markers played role in biological process, molecular function and cellular component. It was indicated in apoptotic regulatory network built by KEGG analysis and verification experiment that WWOX could promote tumor cell apoptotic in colorectal cancer and elevate expression level of p53. The apoptotic regulatory model of colorectal cancer established in this study provides clinically theoretical evidence and targeted therapy for early diagnosis of colorectal cancer.

Predictive minimum description length principle approach to inferring gene regulatory networks.

PubMed

Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

2011-01-01

Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

Genomic analysis of regulatory network dynamics reveals large topological changes

NASA Astrophysics Data System (ADS)

Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

2004-09-01

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

Hal Is a Bacillus anthracis Heme Acquisition Protein

PubMed Central

Balderas, Miriam A.; Nobles, Christopher L.; Honsa, Erin S.; Alicki, Embriette R.

2012-01-01

The metal iron is a limiting nutrient for bacteria during infection. Bacillus anthracis, the causative agent of anthrax and a potential weapon of bioterrorism, grows rapidly in mammalian hosts, which suggests that it efficiently attains iron during infection. Recent studies have uncovered both heme (isd) and siderophore-mediated (asb) iron transport pathways in this pathogen. Whereas deletion of the asb genes results in reduced virulence, the loss of three surface components from isd had no effect, thereby leaving open the question of what additional factors in B. anthracis are responsible for iron uptake from the most abundant iron source for mammals, heme. Here, we describe the first functional characterization of bas0520, a gene recently implicated in anthrax disease progression. bas0520 encodes a single near-iron transporter (NEAT) domain and several leucine-rich repeats. The NEAT domain binds heme, despite lacking a stabilizing tyrosine common to the NEAT superfamily of hemoproteins. The NEAT domain also binds hemoglobin and can acquire heme from hemoglobin in solution. Finally, deletion of bas0520 resulted in bacilli unable to grow efficiently on heme or hemoglobin as an iron source and yielded the most significant phenotype relative to that for other putative heme uptake systems, a result that suggests that this protein plays a prominent role in the replication of B. anthracis in hematogenous environments. Thus, we have assigned the name of Hal (heme-acquisition leucine-rich repeat protein) to BAS0520. These studies advance our understanding of heme acquisition by this dangerous pathogen and justify efforts to determine the mechanistic function of this novel protein for vaccine or inhibitor development. PMID:22865843

Synchronous versus asynchronous modeling of gene regulatory networks.

PubMed

Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

2008-09-01

In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Heme oxygenase activity increases after exercise in healthy volunteers

EPA Science Inventory

AbstractHeme oxygenase (HO) is an essential, rate-limiting protein which participates in the catabolism of heme to iron, carbon monoxide (CO), and biliverdin. The alpha methene bridge carbon of the heme is eliminated as CO which can be measured as blood carboxyhemoglobin (COHb)....

An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

PubMed

Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

2018-05-14

A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

Cyanide binding to hexacoordinate cyanobacterial hemoglobins: hydrogen-bonding network and heme pocket rearrangement in ferric H117A Synechocystis hemoglobin.

PubMed

Vu, B Christie; Nothnagel, Henry J; Vuletich, David A; Falzone, Christopher J; Lecomte, Juliette T J

2004-10-05

The truncated hemoglobin (Hb) from the cyanobacterium Synechocystis sp. PCC 6803 is a bis-histidyl hexacoordinate complex in the absence of exogenous ligands. This protein can form a covalent cross-link between His117 in the H-helix and the heme 2-vinyl group. Cross-linking, the physiological importance of which has not been established, is avoided with the His117Ala substitution. In the present work, H117A Hb was used to explore exogenous ligand binding to the heme group. NMR and thermal denaturation data showed that the replacement was of little consequence to the structural and thermodynamic properties of ferric Synechocystis Hb. It did, however, decelerate the association of cyanide ions with the heme iron. Full complexation required hours, instead of minutes, of incubation at optical and NMR concentrations. At neutral pH and in the presence of excess cyanide, binding occurred with a first-order dependence on cyanide concentration, eliminating distal histidine decoordination as the rate-limiting step. The cyanide complex of the H117A variant was characterized for the conformational changes occurring as the histidine on the distal side, His46 (E10), was displaced. Extensive rearrangement allowed Tyr22 (B10) to insert in the heme pocket and Gln43 (E7) and Gln47 (E11) to come in contact with it. H-bond formation to the bound cyanide was identified in solution with the use of (1)H(2)O/(2)H(2)O mixtures. Cyanide binding also resulted in a change in the ratio of heme orientational isomers, in a likely manifestation of heme environment reshaping. Similar observations were made with the related Synechococcus sp. PCC 7002 H117A Hb, except that cyanide binding was rapid in this protein. In both cases, the (15)N chemical shift of bound cyanide was reminiscent of that in peroxidases and the orientation of the proximal histidine was as in other truncated Hbs. The ensemble of the data provided insight into the structural cooperativity of the heme pocket scaffold and pointed

CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

PubMed

Zheng, Guangyong; Xu, Yaochen; Zhang, Xiujun; Liu, Zhi-Ping; Wang, Zhuo; Chen, Luonan; Zhu, Xin-Guang

2016-12-23

A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

Structural insights into human heme oxygenase-1 inhibition by potent and selective azole-based compounds

PubMed Central

Rahman, Mona N.; Vukomanovic, Dragic; Vlahakis, Jason Z.; Szarek, Walter A.; Nakatsu, Kanji; Jia, Zongchao

2013-01-01

The development of heme oxygenase (HO) inhibitors, especially those that are isozyme-selective, promises powerful pharmacological tools to elucidate the regulatory characteristics of the HO system. It is already known that HO has cytoprotective properties and may play a role in several disease states, making it an enticing therapeutic target. Traditionally, the metalloporphyrins have been used as competitive HO inhibitors owing to their structural similarity with the substrate, heme. However, given heme's important role in several other proteins (e.g. cytochromes P450, nitric oxide synthase), non-selectivity is an unfortunate side-effect. Reports that azalanstat and other non-porphyrin molecules inhibited HO led to a multi-faceted effort to develop novel compounds as potent, selective inhibitors of HO. This resulted in the creation of non-competitive inhibitors with selectivity for HO, including a subset with isozyme selectivity for HO-1. Using X-ray crystallography, the structures of several complexes of HO-1 with novel inhibitors have been elucidated, which provided insightful information regarding the salient features required for inhibitor binding. This included the structural basis for non-competitive inhibition, flexibility and adaptability of the inhibitor binding pocket, and multiple, potential interaction subsites, all of which can be exploited in future drug-design strategies. PMID:23097500

Mimicking Heme Enzymes in the Solid State: Metal-Organic Materials with Selectively Encapsulated Heme

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, Randy W; Wojtas, Lukasz; Perman, Jason

2011-06-13

To carry out essential life processes, nature has had to evolve heme enzymes capable of synthesizing and manipulating complex molecules. These proteins perform a plethora of chemical reactions utilizing a single iron porphyrin active site embedded within an evolutionarily designed protein pocket. We herein report the first class of metal–organic materials (MOMs) that mimic heme enzymes in terms of both structure and reactivity. The MOMzyme-1 class is based upon a prototypal MOM, HKUST-1, into which catalytically active metalloporphyrins are selectively encapsulated in a “ship-in-a-bottle” fashion within one of the three nanoscale cages that exist in HKUST-1. MOMs offer unparalleled levelsmore » of permanent porosity and their modular nature affords enormous diversity of structures and properties. The MOMzyme-1 class could therefore represent a new paradigm for heme biomimetic catalysis since it combines the activity of a homogeneous catalyst with the stability and recyclability of heterogeneous catalytic systems within a single material.« less

Mimicking heme enzymes in the solid state: metal-organic materials with selectively encapsulated heme.

PubMed

Larsen, Randy W; Wojtas, Lukasz; Perman, Jason; Musselman, Ronald L; Zaworotko, Michael J; Vetromile, Carissa M

2011-07-13

To carry out essential life processes, nature has had to evolve heme enzymes capable of synthesizing and manipulating complex molecules. These proteins perform a plethora of chemical reactions utilizing a single iron porphyrin active site embedded within an evolutionarily designed protein pocket. We herein report the first class of metal-organic materials (MOMs) that mimic heme enzymes in terms of both structure and reactivity. The MOMzyme-1 class is based upon a prototypal MOM, HKUST-1, into which catalytically active metalloporphyrins are selectively encapsulated in a "ship-in-a-bottle" fashion within one of the three nanoscale cages that exist in HKUST-1. MOMs offer unparalleled levels of permanent porosity and their modular nature affords enormous diversity of structures and properties. The MOMzyme-1 class could therefore represent a new paradigm for heme biomimetic catalysis since it combines the activity of a homogeneous catalyst with the stability and recyclability of heterogeneous catalytic systems within a single material.

Cloning and Expression of cDNA for Rat Heme Oxygenase

NASA Astrophysics Data System (ADS)

Shibahara, Shigeki; Muller, Rita; Taguchi, Hayao; Yoshida, Tadashi

1985-12-01

Two cDNA clones for rat heme oxygenase have been isolated from a rat spleen cDNA library in λ gt11 by immunological screening using a specific polyclonal antibody. One of these clones has an insert of 1530 nucleotides that contains the entire protein-coding region. To confirm that the isolated cDNA encodes heme oxygenase, we transfected monkey kidney cells (COS-7) with the cDNA carried in a simian virus 40 vector. The heme oxygenase was highly expressed in endoplasmic reticulum of transfected cells. The nucleotide sequence of the cloned cDNA was determined and the primary structure of heme oxygenase was deduced. Heme oxygenase is composed of 289 amino acids and has one hydrophobic segment at its carboxyl terminus, which is probably important for the insertion of heme oxygenase into endoplasmic reticulum. The cloned cDNA was used to analyze the induction of heme oxygenase in rat liver by treatment with CoCl2 or with hemin. RNA blot analysis showed that both CoCl2 and hemin increased the amount of hybridizable mRNA, suggesting that these substances may act at the transcriptional level to increase the amount of heme oxygenase.

A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer

PubMed Central

Debily, Marie-Anne; Marhomy, Sandrine El; Boulanger, Virginie; Eveno, Eric; Mariage-Samson, Régine; Camarca, Alessandra; Auffray, Charles; Piatier-Tonneau, Dominique; Imbeaud, Sandrine

2009-01-01

Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Principal Findings Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters. Conclusions Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator. PMID:19262752

Anticipated Ethics and Regulatory Challenges in PCORnet: The National Patient-Centered Clinical Research Network.

PubMed

Ali, Joseph; Califf, Robert; Sugarman, Jeremy

2016-01-01

PCORnet, the National Patient-Centered Clinical Research Network, seeks to establish a robust national health data network for patient-centered comparative effectiveness research. This article reports the results of a PCORnet survey designed to identify the ethics and regulatory challenges anticipated in network implementation. A 12-item online survey was developed by leadership of the PCORnet Ethics and Regulatory Task Force; responses were collected from the 29 PCORnet networks. The most pressing ethics issues identified related to informed consent, patient engagement, privacy and confidentiality, and data sharing. High priority regulatory issues included IRB coordination, privacy and confidentiality, informed consent, and data sharing. Over 150 IRBs and five different approaches to managing multisite IRB review were identified within PCORnet. Further empirical and scholarly work, as well as practical and policy guidance, is essential if important initiatives that rely on comparative effectiveness research are to move forward.

Structural characterization of human heme oxygenase-1 in complex with azole-based inhibitors.

PubMed

Rahman, Mona N; Vlahakis, Jason Z; Roman, Gheorghe; Vukomanovic, Dragic; Szarek, Walter A; Nakatsu, Kanji; Jia, Zongchao

2010-03-01

The development of inhibitors specific for heme oxygenases (HO) aims to provide powerful tools in understanding the HO system. Based on the lead structure (2S, 4S)-2-[2-(4-chlorophenyl)ethyl]-2-[(1H-imidazol-1-yl)methyl]-4-[((4-aminophenyl)thio)methyl]-1,3-dioxolane (azalanstat, QC-1) we have synthesized structural modifications to develop novel and selective HO inhibitors. The structural study of human HO-1 (hHO-1) in complex with a select group of the inhibitors was initiated using X-ray crystallographic techniques. Comparison of the structures of four such compounds each in complex with hHO-1 revealed a common binding mode, despite having different structural fragments. The compounds bind to the distal side of heme through an azole "anchor" which coordinates with the heme iron. An expansion of the distal pocket, mainly due to distal helix flexibility, allows accommodation of the compounds without displacing heme or the critical Asp140 residue. Rather, binding displaces a catalytically critical water molecule and disrupts an ordered hydrogen-bond network involving Asp140. The presence of a triazole "anchor" may provide further stability via a hydrogen bond with the protein. A hydrophobic pocket acts to stabilize the region occupied by the phenyl or adamantanyl moieties of these compounds. Further, a secondary hydrophobic pocket is formed via "induced fit" to accommodate bulky substituents at the 4-position of the dioxolane ring. Copyright 2009 Elsevier Inc. All rights reserved.

Control of seed dormancy and germination by DOG1-AHG1 PP2C phosphatase complex via binding to heme.

PubMed

Nishimura, Noriyuki; Tsuchiya, Wataru; Moresco, James J; Hayashi, Yuki; Satoh, Kouji; Kaiwa, Nahomi; Irisa, Tomoko; Kinoshita, Toshinori; Schroeder, Julian I; Yates, John R; Hirayama, Takashi; Yamazaki, Toshimasa

2018-06-06

Abscisic acid (ABA) regulates abiotic stress and developmental responses including regulation of seed dormancy to prevent seeds from germinating under unfavorable environmental conditions. ABA HYPERSENSITIVE GERMINATION1 (AHG1) encoding a type 2C protein phosphatase (PP2C) is a central negative regulator of ABA response in germination; however, the molecular function and regulation of AHG1 remain elusive. Here we report that AHG1 interacts with DELAY OF GERMINATION1 (DOG1), which is a pivotal positive regulator in seed dormancy. DOG1 acts upstream of AHG1 and impairs the PP2C activity of AHG1 in vitro. Furthermore, DOG1 has the ability to bind heme. Binding of DOG1 to AHG1 and heme are independent processes, but both are essential for DOG1 function in vivo. Our study demonstrates that AHG1 and DOG1 constitute an important regulatory system for seed dormancy and germination by integrating multiple environmental signals, in parallel with the PYL/RCAR ABA receptor-mediated regulatory system.

Heme compounds as iron sources for nonpathogenic Rhizobium bacteria.

PubMed

Noya, F; Arias, A; Fabiano, E

1997-05-01

Many animal-pathogenic bacteria can use heme compounds as iron sources. Like these microorganisms, rhizobium strains interact with host organisms where heme compounds are available. Results presented in this paper indicate that the use of hemoglobin as an iron source is not restricted to animal-pathogenic microorganisms. We also demonstrate that heme, hemoglobin, and leghemoglobin can act as iron sources under iron-depleted conditions for Rhizobium meliloti 242. Analysis of iron acquisition mutant strains indicates that siderophore-, heme-, hemoglobin-, and leghemoglobin-mediated iron transport systems expressed by R. meliloti 242 share at least one component.

Identification of Neurodegenerative Factors Using Translatome-Regulatory Network Analysis

PubMed Central

Brichta, Lars; Shin, William; Jackson-Lewis, Vernice; Blesa, Javier; Yap, Ee-Lynn; Walker, Zachary; Zhang, Jack; Roussarie, Jean-Pierre; Alvarez, Mariano J.; Califano, Andrea; Przedborski, Serge; Greengard, Paul

2016-01-01

For degenerative disorders of the central nervous system, the major obstacle to therapeutic advancement has been the challenge of identifying the key molecular mechanisms underlying neuronal loss. We developed a combinatorial approach including translational profiling and brain regulatory network analysis to search for key determinants of neuronal survival or death. Following the generation of transgenic mice for cell type-specific profiling of midbrain dopaminergic neurons, we established and compared translatome libraries reflecting the molecular signature of these cells at baseline or under degenerative stress. Analysis of these libraries by interrogating a context-specific brain regulatory network led to the identification of a repertoire of intrinsic upstream regulators that drive the dopaminergic stress response. The altered activity of these regulators was not associated with changes in their expression levels. This strategy can be generalized for the elucidation of novel molecular determinants involved in the degeneration of other classes of neurons. PMID:26214373

Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

PubMed Central

2013-01-01

Background Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking. Results In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p < 0.01) in 10 ecotypes, including 498 transcription factors and 315 transposable elements. The majority of the transcripts (75%) showed ecotype specific expression pattern. By using sequence data available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about regulatory interactions between transcription factors and their target genes in the model plant A. thaliana, we have adopted a powerful systems genetics approach- Network Component Analysis (NCA) to construct an in-silico transcriptional regulatory network model during response to cold stress. The resulting regulatory network contained 1,275 nodes and 7,720 connections, with 178 transcription factors and 1,331 target genes. Conclusions A. thaliana ecotypes exhibit considerable variation in transcriptome level responses to non-freezing cold stress treatment. Ecotype specific transcripts and related gene ontology (GO) categories were identified to delineate natural variation of cold stress regulated differential gene expression in the model plant A. thaliana. The predicted

Edge usage, motifs, and regulatory logic for cell cycling genetic networks

NASA Astrophysics Data System (ADS)

Zagorski, M.; Krzywicki, A.; Martin, O. C.

2013-01-01

The cell cycle is a tightly controlled process, yet it shows marked differences across species. Which of its structural features follow solely from the ability to control gene expression? We tackle this question in silico by examining the ensemble of all regulatory networks which satisfy the constraint of producing a given sequence of gene expressions. We focus on three cell cycle profiles coming from baker's yeast, fission yeast, and mammals. First, we show that the networks in each of the ensembles use just a few interactions that are repeatedly reused as building blocks. Second, we find an enrichment in network motifs that is similar in the two yeast cell cycle systems investigated. These motifs do not have autonomous functions, yet they reveal a regulatory logic for cell cycling based on a feed-forward cascade of activating interactions.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

PubMed Central

2013-01-01

Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates

21 CFR 862.1410 - Iron (non-heme) test system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... diagnosis and treatment of diseases such as iron deficiency anemia, hemochromatosis (a disease associated... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Iron (non-heme) test system. 862.1410 Section 862....1410 Iron (non-heme) test system. (a) Identification. An iron (non-heme) test system is a device...

21 CFR 862.1410 - Iron (non-heme) test system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... diagnosis and treatment of diseases such as iron deficiency anemia, hemochromatosis (a disease associated... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Iron (non-heme) test system. 862.1410 Section 862....1410 Iron (non-heme) test system. (a) Identification. An iron (non-heme) test system is a device...

21 CFR 862.1410 - Iron (non-heme) test system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... diagnosis and treatment of diseases such as iron deficiency anemia, hemochromatosis (a disease associated... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Iron (non-heme) test system. 862.1410 Section 862....1410 Iron (non-heme) test system. (a) Identification. An iron (non-heme) test system is a device...

21 CFR 862.1410 - Iron (non-heme) test system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... diagnosis and treatment of diseases such as iron deficiency anemia, hemochromatosis (a disease associated... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Iron (non-heme) test system. 862.1410 Section 862....1410 Iron (non-heme) test system. (a) Identification. An iron (non-heme) test system is a device...

Revisiting the putative role of heme as a trigger of inflammation.

PubMed

Vallelian, Florence; Schaer, Christian A; Deuel, Jeremy W; Ingoglia, Giada; Humar, Rok; Buehler, Paul W; Schaer, Dominik J

2018-04-01

Activation of the innate immune system by free heme has been proposed as one of the principal consequences of cell-free hemoglobin (Hb) exposure. Nonetheless, in the absence of infection, heme exposures within a hematoma, during hemolysis, or upon systemic administration of Hb (eg, as a Hb-based oxygen carrier) are typically not accompanied by uncontrolled inflammation, challenging the assumption that heme is a major proinflammatory mediator in vivo. Because of its hydrophobic nature, heme liberated from oxidized hemoglobin is rapidly transferred to alternative protein-binding sites (eg, albumin) or to hydrophobic lipid compartments minimizing protein-free heme under in vivo equilibrium conditions. We demonstrate that the capacity of heme to activate human neutrophil granulocytes strictly depends on the availability of non protein-associated heme. In human endothelial cells as well as in mouse macrophage cell cultures and in mouse models of local and systemic heme exposure, protein-associated heme or Hb do not induce inflammatory gene expression over a broad range of exposure conditions. Only experiments in protein-free culture medium demonstrated a weak capacity of heme-solutions to induce toll-like receptor-(TLR4) dependent TNF-alpha expression in macrophages. Our data suggests that the equilibrium-state of free and protein-associated heme critically determines the proinflammatory capacity of the metallo-porphyrin. Based on these data it appears unlikely that inflammation-promoting equilibrium conditions could ever occur in vivo.

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks

PubMed Central

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P.; Gerstein, Mark

2010-01-01

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers’ continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems. PMID:20439753

Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

PubMed

Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

2010-05-18

The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.

Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach.

PubMed

Steggles, L Jason; Banks, Richard; Shaw, Oliver; Wipat, Anil

2007-02-01

New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory. We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed. The Petri net model construction tool and the data files for the B. subtilis sporulation case study are available at http://bioinf.ncl.ac.uk/gnapn.

Chlamydomonas reinhardtii LFO1 Is an IsdG Family Heme Oxygenase

DOE PAGES

Lojek, Lisa J.; Farrand, Allison J.; Wisecaver, Jennifer H.; ...

2017-08-16

Heme is essential for respiration across all domains of life. However, heme accumulation can lead to toxicity if cells are unable to either degrade or export heme or its toxic by-products. Under aerobic conditions, heme degradation is performed by heme oxygenases, enzymes which utilize oxygen to cleave the tetrapyrrole ring of heme. The HO-1 family of heme oxygenases has been identified in both bacterial and eukaryotic cells, whereas the IsdG family has thus far been described only in bacteria. We identified a hypothetical protein in the eukaryotic green alga Chlamydomonas reinhardtii, which encodes a protein containing an antibiotic biosynthesis monooxygenasemore » (ABM) domain consistent with those associated with IsdG family members. This protein, which we have named LFO1, degrades heme, contains similarities in predicted secondary structures to IsdG family members, and retains the functionally conserved catalytic residues found in all IsdG family heme oxygenases. These data establish LFO1 as an IsdG family member and extend our knowledge of the distribution of IsdG family members beyond bacteria. To gain further insight into the distribution of the IsdG family, we used the LFO1 sequence to identify 866 IsdG family members, including representatives from all domains of life. These results indicate that the distribution of IsdG family heme oxygenases is more expansive than previously appreciated, underscoring the broad relevance of this enzyme family. This work establishes a protein in the freshwater alga Chlamydomonas reinhardtii as an IsdG family heme oxygenase. This protein, LFO1, exhibits predicted secondary structure and catalytic residues conserved in IsdG family members, in addition to a chloroplast localization sequence. Additionally, the catabolite that results from the degradation of heme by LFO1 is distinct from that of other heme degradation products. Using LFO1 as a seed, we performed phylogenetic analysis, revealing that the IsdG family is

Chlamydomonas reinhardtii LFO1 Is an IsdG Family Heme Oxygenase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lojek, Lisa J.; Farrand, Allison J.; Wisecaver, Jennifer H.

Heme is essential for respiration across all domains of life. However, heme accumulation can lead to toxicity if cells are unable to either degrade or export heme or its toxic by-products. Under aerobic conditions, heme degradation is performed by heme oxygenases, enzymes which utilize oxygen to cleave the tetrapyrrole ring of heme. The HO-1 family of heme oxygenases has been identified in both bacterial and eukaryotic cells, whereas the IsdG family has thus far been described only in bacteria. We identified a hypothetical protein in the eukaryotic green alga Chlamydomonas reinhardtii, which encodes a protein containing an antibiotic biosynthesis monooxygenasemore » (ABM) domain consistent with those associated with IsdG family members. This protein, which we have named LFO1, degrades heme, contains similarities in predicted secondary structures to IsdG family members, and retains the functionally conserved catalytic residues found in all IsdG family heme oxygenases. These data establish LFO1 as an IsdG family member and extend our knowledge of the distribution of IsdG family members beyond bacteria. To gain further insight into the distribution of the IsdG family, we used the LFO1 sequence to identify 866 IsdG family members, including representatives from all domains of life. These results indicate that the distribution of IsdG family heme oxygenases is more expansive than previously appreciated, underscoring the broad relevance of this enzyme family. This work establishes a protein in the freshwater alga Chlamydomonas reinhardtii as an IsdG family heme oxygenase. This protein, LFO1, exhibits predicted secondary structure and catalytic residues conserved in IsdG family members, in addition to a chloroplast localization sequence. Additionally, the catabolite that results from the degradation of heme by LFO1 is distinct from that of other heme degradation products. Using LFO1 as a seed, we performed phylogenetic analysis, revealing that the IsdG family is

Environmental chemical exposures and disturbances of heme synthesis.

PubMed Central

Daniell, W E; Stockbridge, H L; Labbe, R F; Woods, J S; Anderson, K E; Bissell, D M; Bloomer, J R; Ellefson, R D; Moore, M R; Pierach, C A; Schreiber, W E; Tefferi, A; Franklin, G M

1997-01-01

Porphyrias are relatively uncommon inherited or acquired disorders in which clinical manifestations are attributable to a disturbance of heme synthesis (porphyrin metabolism), usually in association with endogenous or exogenous stressors. Porphyrias are characterized by elevations of heme precursors in blood, urine, and/or stool. A number of chemicals, particularly metals and halogenated hydrocarbons, induce disturbances of heme synthesis in experimental animals. Certain chemicals have also been linked to porphyria or porphyrinuria in humans, generally involving chronic industrial exposures or environmental exposures much higher than those usually encountered. A noteworthy example is the Turkish epidemic of porphyria cutanea tarda produced by accidental ingestion of wheat treated with the fungicide hexachlorobenzene. Measurements of excreted heme precursors have the potential to serve as biological markers for harmful but preclinical effects of certain chemical exposures; this potential warrants further research and applied field studies. It has been hypothesized that several otherwise unexplained chemical-associated illnesses, such as multiple chemical sensitivity syndrome, may represent mild chronic cases of porphyria or other acquired abnormalities in heme synthesis. This review concludes that, although it is reasonable to consider such hypotheses, there is currently no convincing evidence that these illnesses are mediated by a disturbance of heme synthesis; it is premature or unfounded to base clinical management on such explanations unless laboratory data are diagnostic for porphyria. This review discusses the limitations of laboratory measures of heme synthesis, and diagnostic guidelines are provided to assist in evaluating the symptomatic individual suspected of having a porphyria. PMID:9114276

Heme Oxygenases in Cardiovascular Health and Disease

PubMed Central

Ayer, Anita; Zarjou, Abolfazl; Agarwal, Anupam; Stocker, Roland

2016-01-01

Heme oxygenases are composed of two isozymes, Hmox1 and Hmox2, that catalyze the degradation of heme to carbon monoxide (CO), ferrous iron, and biliverdin, the latter of which is subsequently converted to bilirubin. While initially considered to be waste products, CO and biliverdin/bilirubin have been shown over the last 20 years to modulate key cellular processes, such as inflammation, cell proliferation, and apoptosis, as well as antioxidant defense. This shift in paradigm has led to the importance of heme oxygenases and their products in cell physiology now being well accepted. The identification of the two human cases thus far of heme oxygenase deficiency and the generation of mice deficient in Hmox1 or Hmox2 have reiterated a role for these enzymes in both normal cell function and disease pathogenesis, especially in the context of cardiovascular disease. This review covers the current knowledge on the function of both Hmox1 and Hmox2 at both a cellular and tissue level in the cardiovascular system. Initially, the roles of heme oxygenases in vascular health and the regulation of processes central to vascular diseases are outlined, followed by an evaluation of the role(s) of Hmox1 and Hmox2 in various diseases such as atherosclerosis, intimal hyperplasia, myocardial infarction, and angiogenesis. Finally, the therapeutic potential of heme oxygenases and their products are examined in a cardiovascular disease context, with a focus on how the knowledge we have gained on these enzymes may be capitalized in future clinical studies. PMID:27604527

Introduction of water into the heme distal side by Leu65 mutations of an oxygen sensor, YddV, generates verdoheme and carbon monoxide, exerting the heme oxygenase reaction.

PubMed

Stranava, Martin; Martínková, Markéta; Stiborová, Marie; Man, Petr; Kitanishi, Kenichi; Muchová, Lucie; Vítek, Libor; Martínek, Václav; Shimizu, Toru

2014-11-01

The globin-coupled oxygen sensor, YddV, is a heme-based oxygen sensor diguanylate cyclase. Oxygen binding to the heme Fe(II) complex in the N-terminal sensor domain of this enzyme substantially enhances its diguanylate cyclase activity which is conducted in the C-terminal functional domain. Leu65 is located on the heme distal side and is important for keeping the stability of the heme Fe(II)-O2 complex by preventing the entry of the water molecule to the heme complex. In the present study, it was found that (i) Escherichia coli-overexpressed and purified L65N mutant of the isolated heme-bound domain of YddV (YddV-heme) contained the verdoheme iron complex and other modified heme complexes as determined by optical absorption spectroscopy and mass spectrometry; (ii) CO was generated in the reconstituted system composed of heme-bound L65N and NADPH:cytochrome P450 reductase as confirmed by gas chromatography; (iii) CO generation of heme-bound L65N in the reconstituted system was inhibited by superoxide dismutase and catalase. In a concordance with the result, the reactive oxygen species increased the CO generation; (iv) the E. coli cells overexpressing the L65N protein of YddV-heme also formed significant amounts of CO compared to the cells overexpressing the wild type protein; (v) generation of verdoheme and CO was also observed for other mutants at Leu65 as well, but to a lesser extent. Since Leu65 mutations are assumed to introduce the water molecule into the heme distal side of YddV-heme, it is suggested that the water molecule would significantly contribute to facilitating heme oxygenase reactions for the Leu65 mutants. Copyright © 2014 Elsevier Inc. All rights reserved.

A parallel implementation of the network identification by multiple regression (NIR) algorithm to reverse-engineer regulatory gene networks.

PubMed

Gregoretti, Francesco; Belcastro, Vincenzo; di Bernardo, Diego; Oliva, Gennaro

2010-04-21

The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR) algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications.

Deconvoluting heme biosynthesis to target blood-stage malaria parasites

PubMed Central

Sigala, Paul A; Crowley, Jan R; Henderson, Jeffrey P; Goldberg, Daniel E

2015-01-01

Heme metabolism is central to blood-stage infection by the malaria parasite Plasmodium falciparum. Parasites retain a heme biosynthesis pathway but do not require its activity during infection of heme-rich erythrocytes, where they can scavenge host heme to meet metabolic needs. Nevertheless, heme biosynthesis in parasite-infected erythrocytes can be potently stimulated by exogenous 5-aminolevulinic acid (ALA), resulting in accumulation of the phototoxic intermediate protoporphyrin IX (PPIX). Here we use photodynamic imaging, mass spectrometry, parasite gene disruption, and chemical probes to reveal that vestigial host enzymes in the cytoplasm of Plasmodium-infected erythrocytes contribute to ALA-stimulated heme biosynthesis and that ALA uptake depends on parasite-established permeability pathways. We show that PPIX accumulation in infected erythrocytes can be harnessed for antimalarial chemotherapy using luminol-based chemiluminescence and combinatorial stimulation by low-dose artemisinin to photoactivate PPIX to produce cytotoxic reactive oxygen. This photodynamic strategy has the advantage of exploiting host enzymes refractory to resistance-conferring mutations. DOI: http://dx.doi.org/10.7554/eLife.09143.001 PMID:26173178

An algebra-based method for inferring gene regulatory networks

PubMed Central

2014-01-01

Background The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. Results This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also

An algebra-based method for inferring gene regulatory networks.

PubMed

Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

2014-03-26

The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the

Heme Attenuation Ameliorates Irritant Gas Inhalation-Induced Acute Lung Injury.

PubMed

Aggarwal, Saurabh; Lam, Adam; Bolisetty, Subhashini; Carlisle, Matthew A; Traylor, Amie; Agarwal, Anupam; Matalon, Sadis

2016-01-10

Exposure to irritant gases, such as bromine (Br2), poses an environmental and occupational hazard that results in severe lung and systemic injury. However, the mechanism(s) of Br2 toxicity and the therapeutic responses required to mitigate lung damage are not known. Previously, it was demonstrated that Br2 upregulates the heme degrading enzyme, heme oxygenase-1 (HO-1). Since heme is a major inducer of HO-1, we determined whether an increase in heme and heme-dependent oxidative injury underlies the pathogenesis of Br2 toxicity. C57BL/6 mice were exposed to Br2 gas (600 ppm, 30 min) and returned to room air. Thirty minutes postexposure, mice were injected intraperitoneally with a single dose of the heme scavenging protein, hemopexin (Hx) (3 μg/gm body weight), or saline. Twenty-four hours postexposure, saline-treated mice had elevated total heme in bronchoalveolar lavage fluid (BALF) and plasma and acute lung injury (ALI) culminating in 80% mortality after 10 days. Hx treatment significantly lowered heme, decreased evidence of ALI (lower protein and inflammatory cells in BALF, lower lung wet-to-dry weight ratios, and decreased airway hyperreactivity to methacholine), and reduced mortality. In addition, Br2 caused more severe ALI and mortality in mice with HO-1 gene deletion (HO-1-/-) compared to wild-type controls, while transgenic mice overexpressing the human HO-1 gene (hHO-1) showed significant protection. This is the first study delineating the role of heme in ALI caused by Br2. The data suggest that attenuating heme may prove to be a useful adjuvant therapy to treat patients with ALI.

Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks.

PubMed

Werhli, Adriano V; Grzegorczyk, Marco; Husmeier, Dirk

2006-10-15

An important problem in systems biology is the inference of biochemical pathways and regulatory networks from postgenomic data. Various reverse engineering methods have been proposed in the literature, and it is important to understand their relative merits and shortcomings. In the present paper, we compare the accuracy of reconstructing gene regulatory networks with three different modelling and inference paradigms: (1) Relevance networks (RNs): pairwise association scores independent of the remaining network; (2) graphical Gaussian models (GGMs): undirected graphical models with constraint-based inference, and (3) Bayesian networks (BNs): directed graphical models with score-based inference. The evaluation is carried out on the Raf pathway, a cellular signalling network describing the interaction of 11 phosphorylated proteins and phospholipids in human immune system cells. We use both laboratory data from cytometry experiments as well as data simulated from the gold-standard network. We also compare passive observations with active interventions. On Gaussian observational data, BNs and GGMs were found to outperform RNs. The difference in performance was not significant for the non-linear simulated data and the cytoflow data, though. Also, we did not observe a significant difference between BNs and GGMs on observational data in general. However, for interventional data, BNs outperform GGMs and RNs, especially when taking the edge directions rather than just the skeletons of the graphs into account. This suggests that the higher computational costs of inference with BNs over GGMs and RNs are not justified when using only passive observations, but that active interventions in the form of gene knockouts and over-expressions are required to exploit the full potential of BNs. Data, software and supplementary material are available from http://www.bioss.sari.ac.uk/staff/adriano/research.html

Tissue factor-dependent coagulation activation by heme: A thromboelastometry study.

PubMed

de Souza, Gleice Regina; Hounkpe, Bidossessi Wilfried; Fiusa, Maiara Marx Luz; Colella, Marina Pereira; Annichino-Bizzacchi, Joyce M; Traina, Fabiola; Costa, Fernando Ferreira; De Paula, Erich Vinicius

2017-01-01

Heme has been characterized as potent trigger of inflammation. In hemostasis, although heme has been shown to both induce and inhibit different compartments of hemostasis, its net effect on the hemostatic balance, and the biological relevance of these effects remain to be determined. Herein we evaluated the effect of heme on hemostasis using a global assay able to generate clinically relevant data in several other complex hemostatic diseases. Citrated whole blood samples from healthy participants were stimulated by heme or vehicle and incubated for 4h at 37°C. Rotational thromboelastometry was immediately performed. The participation of tissue factor in coagulation activation was evaluated using inhibitory antibody. Heme was able of inducing ex vivo coagulation activation in whole blood, affecting predominantly parameters associated with the initial phases of clot formation. This activation effect was at least partially dependent on hematopoietic tissue factor, since the effects of heme were partially abrogated by the inhibition of human tissue factor. In conclusion, using a global hemostasis assay, our study confirmed that heme is able to activate coagulation in whole blood, in a tissue factor-dependent way. These findings could explain the disturbance in hemostatic balance observed in conditions associated with the release of heme such as sickle cell disease.

Heme induces programmed necrosis on macrophages through autocrine TNF and ROS production

PubMed Central

Fortes, Guilherme B.; Alves, Leticia S.; de Oliveira, Rosane; Dutra, Fabianno F.; Rodrigues, Danielle; Fernandez, Patricia L.; Souto-Padron, Thais; De Rosa, María José; Kelliher, Michelle; Golenbock, Douglas; Chan, Francis K. M.

2012-01-01

Diseases that cause hemolysis or myonecrosis lead to the leakage of large amounts of heme proteins. Free heme has proinflammatory and cytotoxic effects. Heme induces TLR4-dependent production of tumor necrosis factor (TNF), whereas heme cytotoxicity has been attributed to its ability to intercalate into cell membranes and cause oxidative stress. We show that heme caused early macrophage death characterized by the loss of plasma membrane integrity and morphologic features resembling necrosis. Heme-induced cell death required TNFR1 and TLR4/MyD88-dependent TNF production. Addition of TNF to Tlr4−/− or to Myd88−/− macrophages restored heme-induced cell death. The use of necrostatin-1, a selective inhibitor of receptor-interacting protein 1 (RIP1, also known as RIPK1), or cells deficient in Rip1 or Rip3 revealed a critical role for RIP proteins in heme-induced cell death. Serum, antioxidants, iron chelation, or inhibition of c-Jun N-terminal kinase (JNK) ameliorated heme-induced oxidative burst and blocked macrophage cell death. Macrophages from heme oxygenase-1 deficient mice (Hmox1−/−) had increased oxidative stress and were more sensitive to heme. Taken together, these results revealed that heme induces macrophage necrosis through 2 synergistic mechanisms: TLR4/Myd88-dependent expression of TNF and TLR4-independent generation of ROS. PMID:22262768

Reverse engineering gene regulatory networks from measurement with missing values.

PubMed

Ogundijo, Oyetunji E; Elmas, Abdulkadir; Wang, Xiaodong

2016-12-01

Gene expression time series data are usually in the form of high-dimensional arrays. Unfortunately, the data may sometimes contain missing values: for either the expression values of some genes at some time points or the entire expression values of a single time point or some sets of consecutive time points. This significantly affects the performance of many algorithms for gene expression analysis that take as an input, the complete matrix of gene expression measurement. For instance, previous works have shown that gene regulatory interactions can be estimated from the complete matrix of gene expression measurement. Yet, till date, few algorithms have been proposed for the inference of gene regulatory network from gene expression data with missing values. We describe a nonlinear dynamic stochastic model for the evolution of gene expression. The model captures the structural, dynamical, and the nonlinear natures of the underlying biomolecular systems. We present point-based Gaussian approximation (PBGA) filters for joint state and parameter estimation of the system with one-step or two-step missing measurements . The PBGA filters use Gaussian approximation and various quadrature rules, such as the unscented transform (UT), the third-degree cubature rule and the central difference rule for computing the related posteriors. The proposed algorithm is evaluated with satisfying results for synthetic networks, in silico networks released as a part of the DREAM project, and the real biological network, the in vivo reverse engineering and modeling assessment (IRMA) network of yeast Saccharomyces cerevisiae . PBGA filters are proposed to elucidate the underlying gene regulatory network (GRN) from time series gene expression data that contain missing values. In our state-space model, we proposed a measurement model that incorporates the effect of the missing data points into the sequential algorithm. This approach produces a better inference of the model parameters and hence

Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

PubMed

Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd

2015-12-01

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.

Heme compounds as iron sources for nonpathogenic Rhizobium bacteria.

PubMed Central

Noya, F; Arias, A; Fabiano, E

1997-01-01

Many animal-pathogenic bacteria can use heme compounds as iron sources. Like these microorganisms, rhizobium strains interact with host organisms where heme compounds are available. Results presented in this paper indicate that the use of hemoglobin as an iron source is not restricted to animal-pathogenic microorganisms. We also demonstrate that heme, hemoglobin, and leghemoglobin can act as iron sources under iron-depleted conditions for Rhizobium meliloti 242. Analysis of iron acquisition mutant strains indicates that siderophore-, heme-, hemoglobin-, and leghemoglobin-mediated iron transport systems expressed by R. meliloti 242 share at least one component. PMID:9139934

Data-driven integration of genome-scale regulatory and metabolic network models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Saheed; Schauble, Sascha; Brooks, Aaron N.

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or moremore » network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. Lastly, in this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.« less

Data-driven integration of genome-scale regulatory and metabolic network models

DOE PAGES

Imam, Saheed; Schauble, Sascha; Brooks, Aaron N.; ...

2015-05-05

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or moremore » network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. Lastly, in this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.« less

Trichomes: different regulatory networks lead to convergent structures.

PubMed

Serna, Laura; Martin, Cathie

2006-06-01

Sometimes, proteins, biological structures or even organisms have similar functions and appearances but have evolved through widely divergent pathways. There is experimental evidence to suggest that different developmental pathways have converged to produce similar outgrowths of the aerial plant epidermis, referred to as trichomes. The emerging picture suggests that trichomes in Arabidopsis thaliana and, perhaps, in cotton develop through a transcriptional regulatory network that differs from those regulating trichome formation in Antirrhinum and Solanaceous species. Several lines of evidence suggest that the duplication of a gene controlling anthocyanin production and subsequent divergence might be the major force driving trichome formation in Arabidopsis, whereas the multicellular trichomes of Antirrhinum and Solanaceous species appear to have a different regulatory origin.

Heme Attenuation Ameliorates Irritant Gas Inhalation-Induced Acute Lung Injury

PubMed Central

Aggarwal, Saurabh; Lam, Adam; Bolisetty, Subhashini; Carlisle, Matthew A.; Traylor, Amie; Agarwal, Anupam

2016-01-01

Abstract Aims: Exposure to irritant gases, such as bromine (Br2), poses an environmental and occupational hazard that results in severe lung and systemic injury. However, the mechanism(s) of Br2 toxicity and the therapeutic responses required to mitigate lung damage are not known. Previously, it was demonstrated that Br2 upregulates the heme degrading enzyme, heme oxygenase-1 (HO-1). Since heme is a major inducer of HO-1, we determined whether an increase in heme and heme-dependent oxidative injury underlies the pathogenesis of Br2 toxicity. Results: C57BL/6 mice were exposed to Br2 gas (600 ppm, 30 min) and returned to room air. Thirty minutes postexposure, mice were injected intraperitoneally with a single dose of the heme scavenging protein, hemopexin (Hx) (3 μg/gm body weight), or saline. Twenty-four hours postexposure, saline-treated mice had elevated total heme in bronchoalveolar lavage fluid (BALF) and plasma and acute lung injury (ALI) culminating in 80% mortality after 10 days. Hx treatment significantly lowered heme, decreased evidence of ALI (lower protein and inflammatory cells in BALF, lower lung wet-to-dry weight ratios, and decreased airway hyperreactivity to methacholine), and reduced mortality. In addition, Br2 caused more severe ALI and mortality in mice with HO-1 gene deletion (HO-1−/−) compared to wild-type controls, while transgenic mice overexpressing the human HO-1 gene (hHO-1) showed significant protection. Innovation: This is the first study delineating the role of heme in ALI caused by Br2. Conclusion: The data suggest that attenuating heme may prove to be a useful adjuvant therapy to treat patients with ALI. Antioxid. Redox Signal. 24, 99–112. PMID:26376667

Exploring the bZIP transcription factor regulatory network in Neurospora crassa

PubMed Central

Tian, Chaoguang; Li, Jingyi; Glass, N. Louise

2011-01-01

Transcription factors (TFs) are key nodes of regulatory networks in eukaryotic organisms, including filamentous fungi such as Neurospora crassa. The 178 predicted DNA-binding TFs in N. crassa are distributed primarily among six gene families, which represent an ancient expansion in filamentous ascomycete genomes; 98 TF genes show detectable expression levels during vegetative growth of N. crassa, including 35 that show a significant difference in expression level between hyphae at the periphery versus hyphae in the interior of a colony. Regulatory networks within a species genome include paralogous TFs and their respective target genes (TF regulon). To investigate TF network evolution in N. crassa, we focused on the basic leucine zipper (bZIP) TF family, which contains nine members. We performed baseline transcriptional profiling during vegetative growth of the wild-type and seven isogenic, viable bZIP deletion mutants. We further characterized the regulatory network of one member of the bZIP family, NCU03905. NCU03905 encodes an Ap1-like protein (NcAp-1), which is involved in resistance to multiple stress responses, including oxidative and heavy metal stress. Relocalization of NcAp-1 from the cytoplasm to the nucleus was associated with exposure to stress. A comparison of the NcAp-1 regulon with Ap1-like regulons in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans and Aspergillus fumigatus showed both conservation and divergence. These data indicate how N. crassa responds to stress and provide information on pathway evolution. PMID:21081763

Exploring the bZIP transcription factor regulatory network in Neurospora crassa.

PubMed

Tian, Chaoguang; Li, Jingyi; Glass, N Louise

2011-03-01

Transcription factors (TFs) are key nodes of regulatory networks in eukaryotic organisms, including filamentous fungi such as Neurospora crassa. The 178 predicted DNA-binding TFs in N. crassa are distributed primarily among six gene families, which represent an ancient expansion in filamentous ascomycete genomes; 98 TF genes show detectable expression levels during vegetative growth of N. crassa, including 35 that show a significant difference in expression level between hyphae at the periphery versus hyphae in the interior of a colony. Regulatory networks within a species genome include paralogous TFs and their respective target genes (TF regulon). To investigate TF network evolution in N. crassa, we focused on the basic leucine zipper (bZIP) TF family, which contains nine members. We performed baseline transcriptional profiling during vegetative growth of the wild-type and seven isogenic, viable bZIP deletion mutants. We further characterized the regulatory network of one member of the bZIP family, NCU03905. NCU03905 encodes an Ap1-like protein (NcAp-1), which is involved in resistance to multiple stress responses, including oxidative and heavy metal stress. Relocalization of NcAp-1 from the cytoplasm to the nucleus was associated with exposure to stress. A comparison of the NcAp-1 regulon with Ap1-like regulons in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans and Aspergillus fumigatus showed both conservation and divergence. These data indicate how N. crassa responds to stress and provide information on pathway evolution.

Heme oxygenase-1, carbon monoxide, and bilirubin induce tolerance in recipients toward islet allografts by modulating T regulatory cells.

PubMed

Lee, Soo Sun; Gao, Wenda; Mazzola, Silvia; Thomas, Michael N; Csizmadia, Eva; Otterbein, Leo E; Bach, Fritz H; Wang, Hongjun

2007-11-01

Heme oxygenase-1 (HO-1) induction in, or carbon monoxide (CO), or bilirubin administration to, donors and/or recipients frequently lead to long-term survival (>100 days) of DBA/2 islets into B6AF1 recipients. We tested here whether similar treatments show value in a stronger immunogenetic combination, i.e., BALB/c to C57BL/6, and attempted to elucidate the mechanism accounting for tolerance. Induction of HO-1, administering CO or bilirubin to the donor, the islets or the recipient, prolonged islet allograft survival to different extents. Combining all the above treatments (the "combined" protocol) led to survival for >100 days and antigen-specific tolerance to 60% of the transplanted grafts. A high level of forkhead box P3 (Foxp3) and transforming growth factor beta (TGF-beta) expression was detected in the long-term surviving grafts. With the combined protocol, significantly more T regulatory cells (Tregs) were observed surrounding islets 7 days following transplantation. No prolongation of graft survival was observed using the combined protocol when CD4+ CD25+ T cells were predepleted from the recipients before transplantation. In conclusion, our combined protocol led to long-term survival and tolerance to islets in the BALB/c to C57BL/6 combination by promoting Foxp3+ Tregs; these cells played a critical role in the induction and maintenance of tolerance in the recipient.

Heme compounds in dinosaur trabecular bone.

PubMed

Schweitzer, M H; Marshall, M; Carron, K; Bohle, D S; Busse, S C; Arnold, E V; Barnard, D; Horner, J R; Starkey, J R

1997-06-10

Six independent lines of evidence point to the existence of heme-containing compounds and/or hemoglobin breakdown products in extracts of trabecular tissues of the large theropod dinosaur Tyrannosaurus rex. These include signatures from nuclear magnetic resonance and electron spin resonance that indicate the presence of a paramagnetic compound consistent with heme. In addition, UV/visible spectroscopy and high performance liquid chromatography data are consistent with the Soret absorbance characteristic of this molecule. Resonance Raman profiles are also consistent with a modified heme structure. Finally, when dinosaurian tissues were extracted for protein fragments and were used to immunize rats, the resulting antisera reacted positively with purified avian and mammalian hemoglobins. The most parsimonious explanation of this evidence is the presence of blood-derived hemoglobin compounds preserved in the dinosaurian tissues.

Heme and blood-feeding parasites: friends or foes?

PubMed Central

2010-01-01

Hemoparasites, like malaria and schistosomes, are constantly faced with the challenges of storing and detoxifying large quantities of heme, released from their catabolism of host erythrocytes. Heme is an essential prosthetic group that forms the reactive core of numerous hemoproteins with diverse biological functions. However, due to its reactive nature, it is also a potentially toxic molecule. Thus, the acquisition and detoxification of heme is likely to be paramount for the survival and establishment of parasitism. Understanding the underlying mechanism involved in this interaction could possibly provide potential novel targets for drug and vaccine development, and disease treatment. However, there remains a wide gap in our understanding of these mechanisms. This review summarizes the biological importance of heme for hemoparasite, and the adaptations utilized in its sequestration and detoxification. PMID:21087517

Heme modulates Trypanosoma cruzi bioenergetics inducing mitochondrial ROS production.

PubMed

Nogueira, Natália P; Saraiva, Francis M S; Oliveira, Matheus P; Mendonça, Ana Paula M; Inacio, Job D F; Almeida-Amaral, Elmo E; Menna-Barreto, Rubem F; Laranja, Gustavo A T; Torres, Eduardo J Lopes; Oliveira, Marcus F; Paes, Marcia C

2017-07-01

Trypanosoma cruzi is the causative agent of Chagas disease and has a single mitochondrion, an organelle responsible for ATP production and the main site for the formation of reactive oxygen species (ROS). T. cruzi is an obligate intracellular parasite with a complex life cycle that alternates between vertebrate and invertebrate hosts, therefore the development of survival strategies and morphogenetic adaptations to deal with the various environments is mandatory. Over the years our group has been studying the vector-parasite interactions using heme as a physiological oxidant molecule that triggered epimastigote proliferation however, the source of ROS induced by heme remained unknown. In the present study we demonstrate the involvement of heme in the parasite mitochondrial metabolism, decreasing oxygen consumption leading to increased mitochondrial ROS and membrane potential. First, we incubated epimastigotes with carbonyl cyanide p-(trifluoromethoxy) phenylhydrazone (FCCP), an uncoupler of oxidative phosphorylation, which led to decreased ROS formation and parasite proliferation, even in the presence of heme, correlating mitochondrial ROS and T. cruzi survival. This hypothesis was confirmed after the mitochondria-targeted antioxidant ((2-(2,2,6,6 Tetramethylpiperidin-1-oxyl-4-ylamino)-2-oxoethyl) triphenylphosphonium chloride (MitoTEMPO) decreased both heme-induced ROS and epimastigote proliferation. Furthermore, heme increased the percentage of tetramethylrhodamine methyl ester (TMRM) positive parasites tremendously-indicating the hyperpolarization and increase of potential of the mitochondrial membrane (ΔΨm). Assessing the mitochondrial functional metabolism, we observed that in comparison to untreated parasites, heme-treated epimastigotes decreased their oxygen consumption, and increased the complex II-III activity. These changes allowed the electron flow into the electron transport system, even though the complex IV (cytochrome c oxidase) activity decreased

F-MAP: A Bayesian approach to infer the gene regulatory network using external hints

PubMed Central

Shahdoust, Maryam; Mahjub, Hossein; Sadeghi, Mehdi

2017-01-01

The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches. PMID:28938012

Reconstructing regulatory networks from the dynamic plasticity of gene expression by mutual information

PubMed Central

Wang, Jianxin; Chen, Bo; Wang, Yaqun; Wang, Ningtao; Garbey, Marc; Tran-Son-Tay, Roger; Berceli, Scott A.; Wu, Rongling

2013-01-01

The capacity of an organism to respond to its environment is facilitated by the environmentally induced alteration of gene and protein expression, i.e. expression plasticity. The reconstruction of gene regulatory networks based on expression plasticity can gain not only new insights into the causality of transcriptional and cellular processes but also the complex regulatory mechanisms that underlie biological function and adaptation. We describe an approach for network inference by integrating expression plasticity into Shannon’s mutual information. Beyond Pearson correlation, mutual information can capture non-linear dependencies and topology sparseness. The approach measures the network of dependencies of genes expressed in different environments, allowing the environment-induced plasticity of gene dependencies to be tested in unprecedented details. The approach is also able to characterize the extent to which the same genes trigger different amounts of expression in response to environmental changes. We demonstrated the usefulness of this approach through analysing gene expression data from a rabbit vein graft study that includes two distinct blood flow environments. The proposed approach provides a powerful tool for the modelling and analysis of dynamic regulatory networks using gene expression data from distinct environments. PMID:23470995

Applying gene regulatory network logic to the evolution of social behavior.

PubMed

Baran, Nicole M; McGrath, Patrick T; Streelman, J Todd

2017-06-06

Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression.

From Genes to Networks: Characterizing Gene-Regulatory Interactions in Plants.

PubMed

Kaufmann, Kerstin; Chen, Dijun

2017-01-01

Plants, like other eukaryotes, have evolved complex mechanisms to coordinate gene expression during development, environmental response, and cellular homeostasis. Transcription factors (TFs), accompanied by basic cofactors and posttranscriptional regulators, are key players in gene-regulatory networks (GRNs). The coordinated control of gene activity is achieved by the interplay of these factors and by physical interactions between TFs and DNA. Here, we will briefly outline recent technological progress made to elucidate GRNs in plants. We will focus on techniques that allow us to characterize physical interactions in GRNs in plants and to analyze their regulatory consequences. Targeted manipulation allows us to test the relevance of specific gene-regulatory interactions. The combination of genome-wide experimental approaches with mathematical modeling allows us to get deeper insights into key-regulatory interactions and combinatorial control of important processes in plants.

Genome-based analysis of heme biosynthesis and uptake in prokaryotic systems.

PubMed

Cavallaro, Gabriele; Decaria, Leonardo; Rosato, Antonio

2008-11-01

Heme is the prosthetic group of many proteins that carry out a variety of key biological functions. In addition, for many pathogenic organisms, heme (acquired from the host) may constitute a very important source of iron. Organisms can meet their heme demands by taking it up from external sources, by producing the cofactor through a dedicated biosynthetic pathway, or both. Here we analyzed the distribution of proteins specifically involved in the processes of heme biosynthesis and heme uptake in 474 prokaryotic organisms. These data allowed us to identify which organisms are capable of performing none, one, or both processes, based on the similarity to known systems. Some specific instances where one or more proteins along the pathways had unusual modifications were singled out. For two key protein domains involved in heme uptake, we could build a series of structural models, which suggested possible alternative modes of heme binding. Future directions for experimental work are given.

Enhancement of nitrite on heme-induced oxidative reactions: A potential toxicological implication.

PubMed

Lu, Naihao; Chen, Wei; Zhu, Jingjie; Peng, Yi-Yuan

2012-02-01

Evidence to support the role of heme as major inducers of oxidative damage is increasingly present. Nitrite (NO(2)(-)) is one of the major end products of NO metabolism. Although the biological significance of heme/NO(2)(-)-mediated protein tyrosine nitration is a subject of great interest, the important roles of NO(2)(-) on heme-dependent redox reaction have been greatly underestimated. In this study, we investigated the influence of NO(2)(-) on heme -dependent oxidative reactions. It was found that NO(2)(-) had the capacity to act as a reducing agent to remove high oxidation states of heme iron. In the reduction of ferryl heme to ferric heme, NO(2)(-) was oxidized to a nitrating agent NO(2), and subsequently, tyrosine residues in bovine serum albumin (BSA) were nitrated. However, the presence of NO(2)(-) surprisingly exerted pro-oxidant effect on heme-H(2)O(2)-induced formation of BSA carbonyls at lower concentrations and enhanced the loss of HepG2 cell viability dose-dependently, which was probably due to the ability of this inorganic compound to efficiently enhance the peroxidase activity and oxidative degradation of heme. These data provide novel evidence that the dietary intake and experimental use of NO(2)(-) in vivo and in vitro would possess the pro-oxidant activity through interfering in heme-dependent oxidative reactions. Besides the classic role in protein tyrosine nitration, the deleterious effects on heme redox reactions may provide new insights into the toxicological implications of NO(2)(-) with cellular heme proteins. Copyright © 2011 Elsevier Ltd. All rights reserved.

Genetic Variability of the Heme Uptake System among Different Strains of the Fish Pathogen Vibrio anguillarum: Identification of a New Heme Receptor

PubMed Central

Mouriño, Susana; Rodríguez-Ares, Isabel; Osorio, Carlos R.; Lemos, Manuel L.

2005-01-01

The ability to utilize heme compounds as iron sources was investigated in Vibrio anguillarum strains belonging to serotypes O1 to O10. All strains, regardless of their serotype or isolation origin could utilize hemin and hemoglobin as sole iron sources. Similarly, all of the isolates could bind hemin and Congo red, and this binding was mediated by cell envelope proteins. PCR and Southern hybridization were used to assay the occurrence of heme transport genes huvABCD, which have been previously described in serotype O1. Of 23 strains studied, two serotype O3 isolates proved negative for all huvABCD genes, whereas nine strains included in serotypes O2, O3, O4, O6, O7, and O10 tested negative for the outer membrane heme receptor gene huvA. A gene coding for a novel outer membrane heme receptor was cloned and characterized in a V. anguillarum serotype O3 strain lacking huvA. The new heme receptor, named HuvS, showed significant similarity to other outer membrane heme receptors described in Vibrionaceae, but little homology (39%) to HuvA. This heme receptor was present in 9 out of 11 of the V. anguillarum strains that tested negative for HuvA. Furthermore, complementation experiments demonstrated that HuvS could substitute for the HuvA function in Escherichia coli and V. anguillarum mutants. The huvS and huvA sequences alignment, as well as the analysis of their respective upstream and downstream DNA sequences, suggest that horizontal transfer and recombination might be responsible for generating this genetic diversity. PMID:16332832

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

DOE PAGES

Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; ...

2015-06-01

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond thosemore » of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.« less

Construction of diagnosis system and gene regulatory networks based on microarray analysis.

PubMed

Hong, Chun-Fu; Chen, Ying-Chen; Chen, Wei-Chun; Tu, Keng-Chang; Tsai, Meng-Hsiun; Chan, Yung-Kuan; Yu, Shyr Shen

2018-05-01

A microarray analysis generally contains expression data of thousands of genes, but most of them are irrelevant to the disease of interest, making analyzing the genes concerning specific diseases complicated. Therefore, filtering out a few essential genes as well as their regulatory networks is critical, and a disease can be easily diagnosed just depending on the expression profiles of a few critical genes. In this study, a target gene screening (TGS) system, which is a microarray-based information system that integrates F-statistics, pattern recognition matching, a two-layer K-means classifier, a Parameter Detection Genetic Algorithm (PDGA), a genetic-based gene selector (GBG selector) and the association rule, was developed to screen out a small subset of genes that can discriminate malignant stages of cancers. During the first stage, F-statistic, pattern recognition matching, and a two-layer K-means classifier were applied in the system to filter out the 20 critical genes most relevant to ovarian cancer from 9600 genes, and the PDGA was used to decide the fittest values of the parameters for these critical genes. Among the 20 critical genes, 15 are associated with cancer progression. In the second stage, we further employed a GBG selector and the association rule to screen out seven target gene sets, each with only four to six genes, and each of which can precisely identify the malignancy stage of ovarian cancer based on their expression profiles. We further deduced the gene regulatory networks of the 20 critical genes by applying the Pearson correlation coefficient to evaluate the correlationship between the expression of each gene at the same stages and at different stages. Correlationships between gene pairs were calculated, and then, three regulatory networks were deduced. Their correlationships were further confirmed by the Ingenuity pathway analysis. The prognostic significances of the genes identified via regulatory networks were examined using online

Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

PubMed Central

2011-01-01

Background Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions Our

Stationary and structural control in gene regulatory networks: basic concepts

NASA Astrophysics Data System (ADS)

Dougherty, Edward R.; Pal, Ranadip; Qian, Xiaoning; Bittner, Michael L.; Datta, Aniruddha

2010-01-01

A major reason for constructing gene regulatory networks is to use them as models for determining therapeutic intervention strategies by deriving ways of altering their long-run dynamics in such a way as to reduce the likelihood of entering undesirable states. In general, two paradigms have been taken for gene network intervention: (1) stationary external control is based on optimally altering the status of a control gene (or genes) over time to drive network dynamics; and (2) structural intervention involves an optimal one-time change of the network structure (wiring) to beneficially alter the long-run behaviour of the network. These intervention approaches have mainly been developed within the context of the probabilistic Boolean network model for gene regulation. This article reviews both types of intervention and applies them to reducing the metastatic competence of cells via intervention in a melanoma-related network.

The hmuQ and hmuD Genes from Bradyrhizobium japonicum Encode Heme-Degrading Enzymes

PubMed Central

Puri, Sumant; O'Brian, Mark R.

2006-01-01

Utilization of heme by bacteria as a nutritional iron source involves the transport of exogenous heme, followed by cleavage of the heme macrocycle to release iron. Bradyrhizobium japonicum can use heme as an iron source, but no heme-degrading oxygenase has been described. Here, bioinformatics analyses of the B. japonicum genome identified two paralogous genes renamed hmuQ (bll7075) and hmuD (bll7423) that encode proteins with weak similarity to the heme-degrading monooxygenase IsdG from Staphylococcus aureus. The hmuQ gene is clustered with known heme transport genes in the genome. Recombinant HmuQ bound heme with a Kd value of 0.8 μM and showed spectral properties consistent with a heme oxygenase. In the presence of a reductant, HmuQ catalyzed the degradation of heme and the formation of biliverdin. The hmuQ and hmuD genes complemented a Corynebacterium ulcerans heme oxygenase mutant in trans for utilization of heme as the sole iron source for growth. Furthermore, homologs of hmuQ and hmuD were identified in many bacterial genera, and the recombinant homolog from Brucella melitensis bound heme and catalyzed its degradation. The findings show that hmuQ and hmuD encode heme oxygenases and indicate that the IsdG family of heme-degrading monooxygenases is not restricted to gram-positive pathogenic bacteria. PMID:16952937

Isocyanides inhibit human heme oxygenases at the verdoheme stage.

PubMed

Evans, John P; Kandel, Sylvie; Ortiz de Montellano, Paul R

2009-09-22

Heme oxygenases (HO) catalyze the oxidative cleavage of heme to generate biliverdin, CO, and free iron. In humans, heme oxygenase-1 (hHO-1) is overexpressed in tumor tissues, where it helps to protect cancer cells from anticancer agents, while HOs in fungal pathogens, such as Candida albicans, function as the primary means of iron acquisition. Thus, HO can be considered a potential therapeutic target for certain diseases. In this study, we have examined the equilibrium binding of three isocyanides, isopropyl, n-butyl, and benzyl, to the two major human HO isoforms (hHO-1 and hHO-2), Candida albicans HO (CaHmx1), and human cytochrome P450 CYP3A4 using electronic absorption spectroscopy. Isocyanides coordinate to both ferric and ferrous HO-bound heme, with tighter binding by the more hydrophobic isocyanides and 200-300-fold tighter binding to the ferrous form. Benzyl isocyanide was the strongest ligand to ferrous heme in all the enzymes. Because the dissociation constants (KD) of the ligands for ferrous heme-hHO-1 were below the limit of accuracy for equilibrium titrations, stopped-flow kinetic experiments were used to measure the binding parameters of the isocyanides to ferrous hHO-1. Steady-state activity assays showed that benzyl isocyanide was the most potent uncompetitive inhibitor with respect to heme with a KI = 0.15 microM for hHO-1. Importantly, single turnover assays revealed that the reaction was completely stopped by coordination of the isocyanide to the verdoheme intermediate rather than to the ferric heme complex. Much tighter binding of the inhibitor to the verdoheme intermediate differentiates it from inhibition of, for example, CYP3A4 and offers a possible route to more selective inhibitor design.

Isocyanides Inhibit Human Heme Oxygenases at the Verdoheme Stage†

PubMed Central

Evans, John P.; Kandel, Sylvie; Ortiz de Montellano, Paul R.

2010-01-01

Heme oxygenases (HO) catalyze the oxidative cleavage of heme to generate biliverdin, CO, and free iron. In humans, heme oxygenase-1 (hHO-1) is overexpressed in tumor tissues, where it helps to protect cancer cells from anticancer agents, while HOs in fungal pathogens, such as Candida albicans, function as the primary means of iron acquisition. Thus, HO can be considered a potential therapeutic target for certain diseases. In this study, we have examined the equilibrium binding of three isocyanides; isopropyl, n-butyl, and benzyl, to the two major human HO isoforms (hHO-1 and hHO-2), Candida albicans HO (CaHmx1), and human cytochrome P450 CYP3A4 using electronic absorption spectroscopy. Isocyanides coordinate to both ferric and ferrous HO-bound heme, with tighter binding by the more hydrophobic isocyanides, and 200-300-fold tighter binding to the ferrous form. Benzyl isocyanide was the strongest ligand to ferrous heme in all the enzymes. Because the dissociation constants (KD) of the ligands for ferrous heme-hHO-1 were below the limit of accuracy for equilibrium titrations, stopped-flow kinetic experiments were used to measure the binding parameters of the isocyanides to ferrous hHO-1. Steady-state activity assays showed that benzyl isocyanide was the most potent uncompetitive inhibitor with respect to heme with a KI = 0.15 μM for hHO-1. Importantly, single turnover assays revealed that the reaction was completely stopped by coordination of the isocyanide to the verdoheme intermediate rather than to the ferric heme complex. Much tighter binding of the inhibitor to the verdoheme intermediate differentiates it from inhibition of, for example, CYP3A4 and offers a possible route to more selective inhibitor design. PMID:19694439

Statistical identification of gene association by CID in application of constructing ER regulatory network

PubMed Central

Liu, Li-Yu D; Chen, Chien-Yu; Chen, Mei-Ju M; Tsai, Ming-Shian; Lee, Cho-Han S; Phang, Tzu L; Chang, Li-Yun; Kuo, Wen-Hung; Hwa, Hsiao-Lin; Lien, Huang-Chun; Jung, Shih-Ming; Lin, Yi-Shing; Chang, King-Jen; Hsieh, Fon-Jou

2009-01-01

Background A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A). Results The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's t-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. Conclusion CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association

Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

PubMed Central

Chauhan, Rinki; Ravi, Janani; Datta, Pratik; Chen, Tianlong; Schnappinger, Dirk; Bassler, Kevin E.; Balázsi, Gábor; Gennaro, Maria Laura

2016-01-01

Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics. PMID:27029515

Photochemical organic oxidations and dechlorinations with a mu-oxo bridged heme/non-heme diiron complex.

PubMed

Wasser, Ian M; Fry, H Christopher; Hoertz, Paul G; Meyer, Gerald J; Karlin, Kenneth D

2004-12-27

Steady state and laser flash photolysis studies of the heme/non-heme mu-oxo diiron complex [((6)L)Fe(III)-O-Fe(III)-Cl](+) (1) have been undertaken. The anaerobic photolysis of benzene solutions of 1 did not result in the buildup of any photoproduct. However, the addition of excess triphenylphosphine resulted in the quantitative photoreduction of 1 to [((6)L)Fe(II)...Fe(II)-Cl](+) (2), with concomitant production by oxo-transfer of 1 equiv of triphenylphosphine oxide. Under aerobic conditions and excess triphenylphosphine, the reaction produces multiple turnovers (approximately 28) before the diiron complex is degraded. The anaerobic photolysis of tetrahydrofuran (THF) or toluene solutions of 1 likewise results in the buildup of 2. The oxidation products from these reactions included gamma-butyrolactone (approximately 15%) for the reaction in THF and benzaldehyde (approximately 23%) from the reaction in toluene. In either case, the O-atom which is incorporated into the carbonyl product is derived from dioxygen present under workup or under aerobic photolysis conditions. Transient absorption measurements of low-temperature THF solutions of 1 revealed the presence of an (P)Fe(II)-like [P = tetraaryl porphyrinate dianion] species suggesting that the reactive species is a formal (heme)Fe(II)/Fe(IV)=O(non-heme) pair. The non-heme Fe(IV)=O is thus most likely responsible for C-H bond cleavage and subsequent radical chemistry. The photolysis of 1 in chlorobenzene or 1,2-dichlorobenzene resulted in C-Cl cleavage reactions and the formation of [[((6)L)Fe(III)-Cl...Fe(III)-Cl](2)O](2+) (3), with chloride ligands that are derived from solvent dehalogenation chemistry. The resulting organic products are biphenyl trichlorides or biphenyl monochlorides, derived from dichlorobenzene and chlorobenzene, respectively. Similarly, product 3 is obtained by the photolysis of benzene-benzyl chloride solutions of 1; the organic product is benzaldehyde (approximately 70%). A brief

On the contributions of topological features to transcriptional regulatory network robustness

PubMed Central

2012-01-01

Background Because biological networks exhibit a high-degree of robustness, a systemic understanding of their architecture and function requires an appraisal of the network design principles that confer robustness. In this project, we conduct a computational study of the contribution of three degree-based topological properties (transcription factor-target ratio, degree distribution, cross-talk suppression) and their combinations on the robustness of transcriptional regulatory networks. We seek to quantify the relative degree of robustness conferred by each property (and combination) and also to determine the extent to which these properties alone can explain the robustness observed in transcriptional networks. Results To study individual properties and their combinations, we generated synthetic, random networks that retained one or more of the three properties with values derived from either the yeast or E. coli gene regulatory networks. Robustness of these networks were estimated through simulation. Our results indicate that the combination of the three properties we considered explains the majority of the structural robustness observed in the real transcriptional networks. Surprisingly, scale-free degree distribution is, overall, a minor contributor to robustness. Instead, most robustness is gained through topological features that limit the complexity of the overall network and increase the transcription factor subnetwork sparsity. Conclusions Our work demonstrates that (i) different types of robustness are implemented by different topological aspects of the network and (ii) size and sparsity of the transcription factor subnetwork play an important role for robustness induction. Our results are conserved across yeast and E Coli, which suggests that the design principles examined are present within an array of living systems. PMID:23194062

Regulatory Compliance in Multi-Tier Supplier Networks

NASA Technical Reports Server (NTRS)

Goossen, Emray R.; Buster, Duke A.

2014-01-01

Over the years, avionics systems have increased in complexity to the point where 1st tier suppliers to an aircraft OEM find it financially beneficial to outsource designs of subsystems to 2nd tier and at times to 3rd tier suppliers. Combined with challenging schedule and budgetary pressures, the environment in which safety-critical systems are being developed introduces new hurdles for regulatory agencies and industry. This new environment of both complex systems and tiered development has raised concerns in the ability of the designers to ensure safety considerations are fully addressed throughout the tier levels. This has also raised questions about the sufficiency of current regulatory guidance to ensure: proper flow down of safety awareness, avionics application understanding at the lower tiers, OEM and 1st tier oversight practices, and capabilities of lower tier suppliers. Therefore, NASA established a research project to address Regulatory Compliance in a Multi-tier Supplier Network. This research was divided into three major study efforts: 1. Describe Modern Multi-tier Avionics Development 2. Identify Current Issues in Achieving Safety and Regulatory Compliance 3. Short-term/Long-term Recommendations Toward Higher Assurance Confidence This report presents our findings of the risks, weaknesses, and our recommendations. It also includes a collection of industry-identified risks, an assessment of guideline weaknesses related to multi-tier development of complex avionics systems, and a postulation of potential modifications to guidelines to close the identified risks and weaknesses.

Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

PubMed

Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-03-01

"A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prolonged Neutrophil Dysfunction Following Plasmodium falciparum Malaria is Related to Hemolysis and Heme Oxygenase-1 Induction1

PubMed Central

Cunnington, Aubrey J.; Njie, Madi; Correa, Simon; Takem, Ebako N.; Riley, Eleanor M.; Walther, Michael

2012-01-01

It is not known why people are more susceptible to bacterial infections such as non-Typhoid Salmonella (NTS) during and after a malaria infection but, in mice, malarial hemolysis impairs resistance to NTS by impairing the neutrophil oxidative burst. This acquired neutrophil dysfunction is a consequence of induction of the cytoprotective, heme degrading enzyme heme oxygenase-1 (HO-1) in neutrophil progenitors in bone marrow. In this study, we assessed whether neutrophil dysfunction occurs in humans with malaria and how this relates to hemolysis. We evaluated neutrophil function in 58 Gambian children with Plasmodium falciparum malaria (55 (95%) with uncomplicated disease), and examined associations with erythrocyte count, haptoglobin, hemopexin, plasma heme, expression of receptors for heme uptake, and HO-1 induction. Malaria caused the appearance of a dominant population of neutrophils with reduced oxidative burst activity, which gradually normalized over 8 weeks of follow-up. The degree of neutrophil impairment correlated significantly with markers of hemolysis and HO-1 induction. HO-1 expression was increased in blood during acute malaria, but at a cellular level HO-1 expression was modulated by changes in surface expression of the haptoglobin receptor (CD163). These findings demonstrate that neutrophil dysfunction occurs in P. falciparum malaria and support the relevance of the mechanistic studies in mice. Furthermore, they suggest the presence of a regulatory pathway to limit HO-1 induction by hemolysis in the context of infection, and indicate new targets for therapeutic intervention to abrogate the susceptibility to bacterial infection in the context of hemolysis in humans. PMID:23100518

Heme controls ferroportin1 (FPN1) transcription involving Bach1, Nrf2 and a MARE/ARE sequence motif at position -7007 of the FPN1 promoter.

PubMed

Marro, Samuele; Chiabrando, Deborah; Messana, Erika; Stolte, Jens; Turco, Emilia; Tolosano, Emanuela; Muckenthaler, Martina U

2010-08-01

Macrophages of the reticuloendothelial system play a key role in recycling iron from hemoglobin of senescent or damaged erythrocytes. Heme oxygenase 1 degrades the heme moiety and releases inorganic iron that is stored in ferritin or exported to the plasma via the iron export protein ferroportin. In the plasma, iron binds to transferrin and is made available for de novo red cell synthesis. The aim of this study was to gain insight into the regulatory mechanisms that control the transcriptional response of iron export protein ferroportin to hemoglobin in macrophages. Iron export protein ferroportin mRNA expression was analyzed in RAW264.7 mouse macrophages in response to hemoglobin, heme, ferric ammonium citrate or protoporphyrin treatment or to siRNA mediated knockdown or overexpression of Btb And Cnc Homology 1 or nuclear accumulation of Nuclear Factor Erythroid 2-like. Iron export protein ferroportin promoter activity was analyzed using reporter constructs that contain specific truncations of the iron export protein ferroportin promoter or mutations in a newly identified MARE/ARE element. We show that iron export protein ferroportin is transcriptionally co-regulated with heme oxygenase 1 by heme, a degradation product of hemoglobin. The protoporphyrin ring of heme is sufficient to increase iron export protein ferroportin transcriptional activity while the iron released from the heme moiety controls iron export protein ferroportin translation involving the IRE in the 5'untranslated region. Transcription of iron export protein ferroportin is inhibited by Btb and Cnc Homology 1 and activated by Nuclear Factor Erythroid 2-like involving a MARE/ARE element located at position -7007/-7016 of the iron export protein ferroportin promoter. This finding suggests that heme controls a macrophage iron recycling regulon involving Btb and Cnc Homology 1 and Nuclear Factor Erythroid 2-like to assure the coordinated degradation of heme by heme oxygenase 1, iron storage and

PyPanda: a Python package for gene regulatory network reconstruction

PubMed Central

van IJzendoorn, David G.P.; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L.

2016-01-01

Summary: PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of ‘omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. Availability and implementation: The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda. Contact: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl PMID:27402905

PyPanda: a Python package for gene regulatory network reconstruction.

PubMed

van IJzendoorn, David G P; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L

2016-11-01

PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of 'omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda CONTACT: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl. © The Author 2016. Published by Oxford University Press.

Heme Mediates Cytotoxicity from Artemisinin and Serves as a General Anti-Proliferation Target

PubMed Central

Zhang, Shiming; Gerhard, Glenn S.

2009-01-01

Heme (Fe2+ protoporphyrin IX) is an essential molecule that has been implicated the potent antimalarial action of artemisinin and its derivatives, although the source and nature of the heme remain controversial. Artemisinins also exhibit selective cytotoxicity against cancer cells in vitro and in vivo. We demonstrate that intracellular heme is the physiologically relevant mediator of the cytotoxic effects of artemisinins. Increasing intracellular heme synthesis through the addition of aminolevulinic acid, protoporphyrin IX, or transferrin-bound iron increased the cytotoxicity of dihydroartemisinin, while decreasing heme synthesis through the addition of succinyl acetone decreased its cytotoxic activity. A simple and robust high throughput assay was developed to screen chemical compounds that were capable of interacting with heme. A natural products library was screened which identified the compound coralyne, in addition to artemisinin, as a heme interacting compound with heme synthesis dependent cytotoxic activity. These results indicate that cellular heme may serve a general target for the development of both anti-parasitic and anti-cancer therapeutics. PMID:19862332

Prophetic Granger Causality to infer gene regulatory networks.

PubMed

Carlin, Daniel E; Paull, Evan O; Graim, Kiley; Wong, Christopher K; Bivol, Adrian; Ryabinin, Peter; Ellrott, Kyle; Sokolov, Artem; Stuart, Joshua M

2017-01-01

We introduce a novel method called Prophetic Granger Causality (PGC) for inferring gene regulatory networks (GRNs) from protein-level time series data. The method uses an L1-penalized regression adaptation of Granger Causality to model protein levels as a function of time, stimuli, and other perturbations. When combined with a data-independent network prior, the framework outperformed all other methods submitted to the HPN-DREAM 8 breast cancer network inference challenge. Our investigations reveal that PGC provides complementary information to other approaches, raising the performance of ensemble learners, while on its own achieves moderate performance. Thus, PGC serves as a valuable new tool in the bioinformatics toolkit for analyzing temporal datasets. We investigate the general and cell-specific interactions predicted by our method and find several novel interactions, demonstrating the utility of the approach in charting new tumor wiring.

Prophetic Granger Causality to infer gene regulatory networks

PubMed Central

Carlin, Daniel E.; Paull, Evan O.; Graim, Kiley; Wong, Christopher K.; Bivol, Adrian; Ryabinin, Peter; Ellrott, Kyle; Sokolov, Artem

2017-01-01

We introduce a novel method called Prophetic Granger Causality (PGC) for inferring gene regulatory networks (GRNs) from protein-level time series data. The method uses an L1-penalized regression adaptation of Granger Causality to model protein levels as a function of time, stimuli, and other perturbations. When combined with a data-independent network prior, the framework outperformed all other methods submitted to the HPN-DREAM 8 breast cancer network inference challenge. Our investigations reveal that PGC provides complementary information to other approaches, raising the performance of ensemble learners, while on its own achieves moderate performance. Thus, PGC serves as a valuable new tool in the bioinformatics toolkit for analyzing temporal datasets. We investigate the general and cell-specific interactions predicted by our method and find several novel interactions, demonstrating the utility of the approach in charting new tumor wiring. PMID:29211761

Regulatory network involving miRNAs and genes in serous ovarian carcinoma

PubMed Central

Zhao, Haiyan; Xu, Hao; Xue, Luchen

2017-01-01

Serous ovarian carcinoma (SOC) is one of the most life-threatening types of gynecological malignancy, but the pathogenesis of SOC remains unknown. Previous studies have indicated that differentially expressed genes and microRNAs (miRNAs) serve important functions in SOC. However, genes and miRNAs are identified in a disperse form, and limited information is known about the regulatory association between miRNAs and genes in SOC. In the present study, three regulatory networks were hierarchically constructed, including a differentially-expressed network, a related network and a global network to reveal associations between each factor. In each network, there were three types of factors, which were genes, miRNAs and transcription factors that interact with each other. Focus was placed on the differentially-expressed network, in which all genes and miRNAs were differentially expressed and therefore may have affected the development of SOC. Following the comparison and analysis between the three networks, a number of signaling pathways which demonstrated differentially expressed elements were highlighted. Subsequently, the upstream and downstream elements of differentially expressed miRNAs and genes were listed, and a number of key elements (differentially expressed miRNAs, genes and TFs predicted using the P-match method) were analyzed. The differentially expressed network partially illuminated the pathogenesis of SOC. It was hypothesized that if there was no differential expression of miRNAs and genes, SOC may be prevented and treatment may be identified. The present study provided a theoretical foundation for gene therapy for SOC. PMID:29113276

ARSENITE INDUCTION OF HEME OXYGENASE AS A BIOMARKER

EPA Science Inventory

ARSENITE INDUCTION OF HEME OXYGENASE AS A BIOMARKER

Useful biomarkers of arsenic effects in both experimental animals and humans are needed. Arsenate and arsenite are good inducers of rat hepatic and renal heme oxygenase (HO); monomethylarsonic acid (MMA) and dimethylarsi...

Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

PubMed

Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

2016-01-01

We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

On the role of sparseness in the evolution of modularity in gene regulatory networks

PubMed Central

2018-01-01

Modularity is a widespread property in biological systems. It implies that interactions occur mainly within groups of system elements. A modular arrangement facilitates adjustment of one module without perturbing the rest of the system. Therefore, modularity of developmental mechanisms is a major factor for evolvability, the potential to produce beneficial variation from random genetic change. Understanding how modularity evolves in gene regulatory networks, that create the distinct gene activity patterns that characterize different parts of an organism, is key to developmental and evolutionary biology. One hypothesis for the evolution of modules suggests that interactions between some sets of genes become maladaptive when selection favours additional gene activity patterns. The removal of such interactions by selection would result in the formation of modules. A second hypothesis suggests that modularity evolves in response to sparseness, the scarcity of interactions within a system. Here I simulate the evolution of gene regulatory networks and analyse diverse experimentally sustained networks to study the relationship between sparseness and modularity. My results suggest that sparseness alone is neither sufficient nor necessary to explain modularity in gene regulatory networks. However, sparseness amplifies the effects of forms of selection that, like selection for additional gene activity patterns, already produce an increase in modularity. That evolution of new gene activity patterns is frequent across evolution also supports that it is a major factor in the evolution of modularity. That sparseness is widespread across gene regulatory networks indicates that it may have facilitated the evolution of modules in a wide variety of cases. PMID:29775459

On the role of sparseness in the evolution of modularity in gene regulatory networks.

PubMed

Espinosa-Soto, Carlos

2018-05-01

Modularity is a widespread property in biological systems. It implies that interactions occur mainly within groups of system elements. A modular arrangement facilitates adjustment of one module without perturbing the rest of the system. Therefore, modularity of developmental mechanisms is a major factor for evolvability, the potential to produce beneficial variation from random genetic change. Understanding how modularity evolves in gene regulatory networks, that create the distinct gene activity patterns that characterize different parts of an organism, is key to developmental and evolutionary biology. One hypothesis for the evolution of modules suggests that interactions between some sets of genes become maladaptive when selection favours additional gene activity patterns. The removal of such interactions by selection would result in the formation of modules. A second hypothesis suggests that modularity evolves in response to sparseness, the scarcity of interactions within a system. Here I simulate the evolution of gene regulatory networks and analyse diverse experimentally sustained networks to study the relationship between sparseness and modularity. My results suggest that sparseness alone is neither sufficient nor necessary to explain modularity in gene regulatory networks. However, sparseness amplifies the effects of forms of selection that, like selection for additional gene activity patterns, already produce an increase in modularity. That evolution of new gene activity patterns is frequent across evolution also supports that it is a major factor in the evolution of modularity. That sparseness is widespread across gene regulatory networks indicates that it may have facilitated the evolution of modules in a wide variety of cases.

Jimena: efficient computing and system state identification for genetic regulatory networks.

PubMed

Karl, Stefan; Dandekar, Thomas

2013-10-11

Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.

Mechanism of the CO-sensing heme protein CooA: new insights from the truncated heme domain and UVRR spectroscopy

PubMed Central

Ibrahim, Mohammed; Kuchinskas, Michael; Youn, Hwan; Kerby, Robert L.; Roberts, Gary P.; Poulos, Thomas L.; Spiro, Thomas G.

2007-01-01

The bacterial CO-sensing heme protein CooA activates expression of genes whose products perform CO-metabolism by binding its target DNA in response to CO binding. The required conformational change has been proposed to result from CO-induced displacement of the heme and of the adjacent C-helix, which connects the sensory and DNA-binding domains. Support for this proposal comes from UV Resonance Raman (UVRR) spectroscopy, which reveals a more hydrophobic environment for the C-helix residue Trp110 when CO binds. In addition, we find a tyrosine UVRR response, which is attributable to weakening of a Tyr55-Glu83 H-bond that anchors the proximal side of the heme. Both Trp and Tyr responses are augmented in the heme domain when the DNA-binding domain has been removed, apparently reflecting loss of the inter-domain restraint. This augmentation is abolished by a Glu83Gln substitution, which weakens the anchoring H-bond. The CO recombination rate following photolysis of the CO adduct is similar for truncated and full-length protein, though truncation does increase the rate of CO association in the absence of photolysis; together these data indicate that truncation causes a faster dissociation of the endogenous Pro2 ligand. These findings are discussed in the light of structural evidence that the N-terminal tail, once released from the heme, selects the proper orientation of the DNA-binding domain, via docking interactions. PMID:17720248

The effect of proteins from animal source foods on heme iron bioavailability in humans.

PubMed

Pizarro, Fernando; Olivares, Manuel; Valenzuela, Carolina; Brito, Alex; Weinborn, Valerie; Flores, Sebastián; Arredondo, Miguel

2016-04-01

Forty-five women (35-45 year) were randomly assigned to three iron (Fe) absorption sub-studies, which measured the effects of dietary animal proteins on the absorption of heme Fe. Study 1 was focused on heme, red blood cell concentrate (RBCC), hemoglobin (Hb), RBCC+beef meat; study 2 on heme, heme+fish, chicken, and beef; and study 3 on heme and heme+purified animal protein (casein, collagen, albumin). Study 1: the bioavailability of heme Fe from Hb was similar to heme only (∼13.0%). RBCC (25.0%) and RBCC+beef (21.3%) were found to be increased 2- and 1.6-fold, respectively, when compared with heme alone (p<0.05). Study 2: the bioavailability from heme alone (10.3%) was reduced (p<0.05) when it was blended with fish (7.1%) and chicken (4.9%), however it was unaffected by beef. Study 3: casein, collagen, and albumin did not affect the bioavailability of Fe. Proteins from animal source foods and their digestion products did not enhance heme Fe absorption. Copyright © 2015. Published by Elsevier Ltd.

Function, dynamics and evolution of network motif modules in integrated gene regulatory networks of worm and plant.

PubMed

Defoort, Jonas; Van de Peer, Yves; Vermeirssen, Vanessa

2018-06-05

Gene regulatory networks (GRNs) consist of different molecular interactions that closely work together to establish proper gene expression in time and space. Especially in higher eukaryotes, many questions remain on how these interactions collectively coordinate gene regulation. We study high quality GRNs consisting of undirected protein-protein, genetic and homologous interactions, and directed protein-DNA, regulatory and miRNA-mRNA interactions in the worm Caenorhabditis elegans and the plant Arabidopsis thaliana. Our data-integration framework integrates interactions in composite network motifs, clusters these in biologically relevant, higher-order topological network motif modules, overlays these with gene expression profiles and discovers novel connections between modules and regulators. Similar modules exist in the integrated GRNs of worm and plant. We show how experimental or computational methodologies underlying a certain data type impact network topology. Through phylogenetic decomposition, we found that proteins of worm and plant tend to functionally interact with proteins of a similar age, while at the regulatory level TFs favor same age, but also older target genes. Despite some influence of the duplication mode difference, we also observe at the motif and module level for both species a preference for age homogeneity for undirected and age heterogeneity for directed interactions. This leads to a model where novel genes are added together to the GRNs in a specific biological functional context, regulated by one or more TFs that also target older genes in the GRNs. Overall, we detected topological, functional and evolutionary properties of GRNs that are potentially universal in all species.

Integration of Steady-State and Temporal Gene Expression Data for the Inference of Gene Regulatory Networks

PubMed Central

Wang, Yi Kan; Hurley, Daniel G.; Schnell, Santiago; Print, Cristin G.; Crampin, Edmund J.

2013-01-01

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data. PMID:23967277

Measurements of heme relaxation and ligand recombination in strong magnetic fields.

PubMed

Zhang, Zhenyu; Benabbas, Abdelkrim; Ye, Xiong; Yu, Anchi; Champion, Paul M

2009-08-06

Heme cooling signals and diatomic ligand recombination kinetics are measured in strong magnetic fields (up to 10 T). We examined diatomic ligand recombination to heme model compounds (NO and CO), myoglobin (NO and O(2)), and horseradish peroxidase (NO). No magnetic field induced rate changes in any of the samples were observed within the experimental detection limit. However, in the case of CO binding to heme in glycerol and O(2) binding to myoglobin, we observe a small magnetic field dependent change in the early time amplitude of the optical response that is assigned to heme cooling. One possibility, consistent with this observation, is that there is a weak magnetic field dependence of the nonradiative branching ratio into the vibrationally hot electronic ground state during CO photolysis. Ancillary studies of the "spin-forbidden" CO binding reaction in a variety of heme compounds in the absence of magnetic field demonstrate a surprisingly wide range for the Arrhenius prefactor. We conclude that CO binding to heme is not always retarded by unfavorable spin selection rules involving a double spin-flip superexchange mechanism. In fact, it appears that the small prefactor ( approximately 10(9) s(-1)) found for CO rebinding to Mb may be anomalous, rather than the general rule for heme-CO rebinding. These results point to unresolved fundamental issues that underlie the theory of heme-ligand photolysis and rebinding.

Extended evolution: A conceptual framework for integrating regulatory networks and niche construction

PubMed Central

Renn, Jürgen

2015-01-01

ABSTRACT This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path‐dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 565–577, 2015. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals, Inc. PMID:26097188

Chaotic Motifs in Gene Regulatory Networks

PubMed Central

Zhang, Zhaoyang; Ye, Weiming; Qian, Yu; Zheng, Zhigang; Huang, Xuhui; Hu, Gang

2012-01-01

Chaos should occur often in gene regulatory networks (GRNs) which have been widely described by nonlinear coupled ordinary differential equations, if their dimensions are no less than 3. It is therefore puzzling that chaos has never been reported in GRNs in nature and is also extremely rare in models of GRNs. On the other hand, the topic of motifs has attracted great attention in studying biological networks, and network motifs are suggested to be elementary building blocks that carry out some key functions in the network. In this paper, chaotic motifs (subnetworks with chaos) in GRNs are systematically investigated. The conclusion is that: (i) chaos can only appear through competitions between different oscillatory modes with rivaling intensities. Conditions required for chaotic GRNs are found to be very strict, which make chaotic GRNs extremely rare. (ii) Chaotic motifs are explored as the simplest few-node structures capable of producing chaos, and serve as the intrinsic source of chaos of random few-node GRNs. Several optimal motifs causing chaos with atypically high probability are figured out. (iii) Moreover, we discovered that a number of special oscillators can never produce chaos. These structures bring some advantages on rhythmic functions and may help us understand the robustness of diverse biological rhythms. (iv) The methods of dominant phase-advanced driving (DPAD) and DPAD time fraction are proposed to quantitatively identify chaotic motifs and to explain the origin of chaotic behaviors in GRNs. PMID:22792171

Compartmentalized gene regulatory network of the pathogenic fungus Fusarium graminearum

USDA-ARS?s Scientific Manuscript database

Head blight caused by Fusarium graminearum (Fg) is a major limiting factor of wheat production with both yield loss and mycotoxin contamination. Here we report a model for global Fg gene regulatory networks (GRNs) inferred from a large collection of transcriptomic data using a machine-learning appro...

Heme-mediated cell activation: the inflammatory puzzle of sickle cell anemia.

PubMed

Guarda, Caroline Conceição da; Santiago, Rayra Pereira; Fiuza, Luciana Magalhães; Aleluia, Milena Magalhães; Ferreira, Júnia Raquel Dutra; Figueiredo, Camylla Vilas Boas; Yahouedehou, Setondji Cocou Modeste Alexandre; Oliveira, Rodrigo Mota de; Lyra, Isa Menezes; Gonçalves, Marilda de Souza

2017-06-01

Hemolysis triggers the onset of several clinical manifestations of sickle cell anemia (SCA). During hemolysis, heme, which is derived from hemoglobin (Hb), accumulates due to the inability of detoxification systems to scavenge sufficiently. Heme exerts multiple harmful effects, including leukocyte activation and migration, enhanced adhesion molecule expression by endothelial cells and the production of pro-oxidant molecules. Area covered: In this review, we describe the effects of heme on leukocytes and endothelial cells, as well as the features of vascular endothelial cells related to vaso-occlusion in SCA. Expert commentary: Free Hb, heme and iron, potent cytotoxic intravascular molecules released during hemolysis, can exacerbate, modulate and maintain the inflammatory response, a main feature of SCA. Endothelial cells in the vascular environment, as well as leukocytes, can become activated via the molecular signaling effects of heme. Due to the hemolytic nature of SCA, hemolysis represents an interesting therapeutic target for heme-scavenging purposes.

Control of metazoan heme homeostasis by a conserved multidrug resistance protein

PubMed Central

Korolnek, Tamara; Zhang, Jianbing; Beardsley, Simon; Scheffer, George L; Hamza, Iqbal

2014-01-01

Several lines of evidence predict that specific pathways must exist in metazoans for the escorted movement of heme, an essential but cytotoxic iron-containing organic ring, within and between cells and tissues, but these pathways remain obscure. In Caenorhabditis elegans, embryonic development is inextricably dependent on both maternally-derived heme and environmentally-acquired heme. Here, we show that the multidrug resistance protein, MRP-5/ABCC5, likely acts as a heme exporter and targeted depletion of mrp-5 in the intestine causes embryonic lethality. Transient knockdown of mrp5 in zebrafish leads to morphological defects and failure to hemoglobinize red blood cells. MRP5 resides on the plasma membrane and endosomal compartments and regulates export of cytosolic heme. Together, our genetic studies in worms, yeast, zebrafish, and mammalian cells identify a conserved, physiological role for a multidrug resistance protein in regulating systemic heme homeostasis. We envision other MRP family members may play similar unanticipated physiological roles in animal development. PMID:24836561

Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

PubMed

Ramírez, Carlos; Mendoza, Luis

2018-04-01

Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

Biotin deficiency inhibits heme synthesis and impairs mitochondria in human lung fibroblasts.

PubMed

Atamna, Hani; Newberry, Justin; Erlitzki, Ronit; Schultz, Carla S; Ames, Bruce N

2007-01-01

Four of the 5 biotin-dependent carboxylases (BDC) are in the mitochondria. BDC replace intermediates in the Krebs [tricarboxylic acid (TCA)] cycle that are regularly removed for the synthesis of key metabolites such as heme or amino acids. Heme, unlike amino acids, is not recycled to regenerate these intermediates, is not utilized from the diet, and must be synthesized in situ. We studied whether biotin deficiency (BD) lowers heme synthesis and whether mitochondria would be disrupted. Biotin-deficient medium was prepared by using bovine serum stripped of biotin with charcoal/dextran or avidin. Biotin-deficient primary human lung fibroblasts (IMR90) lost their BDC and senesced before biotin-sufficient cells. BD caused heme deficiency; there was a decrease in heme content and heme synthesis, and biotin-deficient cells selectively lost mitochondrial complex IV, which contains heme-a. Loss of complex IV, which is part of the electron transport chain, triggered oxidant release and oxidative damage, hallmarks of heme deficiency. Restoring biotin to the biotin-deficient medium prevented the above changes. Old cells were more susceptible to biotin shortage than young cells. These findings highlight the biochemical connection among biotin, heme, and iron metabolism, and the mitochondria, due to the role of biotin in maintaining the biochemical integrity of the TCA cycle. The findings are discussed in relation to aging and birth defects in humans.

Giardia intestinalis incorporates heme into cytosolic cytochrome b₅.

PubMed

Pyrih, Jan; Harant, Karel; Martincová, Eva; Sutak, Robert; Lesuisse, Emmanuel; Hrdý, Ivan; Tachezy, Jan

2014-02-01

The anaerobic intestinal pathogen Giardia intestinalis does not possess enzymes for heme synthesis, and it also lacks the typical set of hemoproteins that are involved in mitochondrial respiration and cellular oxygen stress management. Nevertheless, G. intestinalis may require heme for the function of particular hemoproteins, such as cytochrome b5 (cytb5). We have analyzed the sequences of eukaryotic cytb5 proteins and identified three distinct cytb5 groups: group I, which consists of C-tail membrane-anchored cytb5 proteins; group II, which includes soluble cytb5 proteins; and group III, which comprises the fungal cytb5 proteins. The majority of eukaryotes possess both group I and II cytb5 proteins, whereas three Giardia paralogs belong to group II. We have identified a fourth Giardia cytb5 paralog (gCYTb5-IV) that is rather divergent and possesses an unusual 134-residue N-terminal extension. Recombinant Giardia cytb5 proteins, including gCYTb5-IV, were expressed in Escherichia coli and exhibited characteristic UV-visible spectra that corresponded to heme-loaded cytb5 proteins. The expression of the recombinant gCYTb5-IV in G. intestinalis resulted in the increased import of extracellular heme and its incorporation into the protein, whereas this effect was not observed when gCYTb5-IV containing a mutated heme-binding site was expressed. The electrons for Giardia cytb5 proteins may be provided by the NADPH-dependent Tah18-like oxidoreductase GiOR-1. Therefore, GiOR-1 and cytb5 may constitute a novel redox system in G. intestinalis. To our knowledge, G. intestinalis is the first anaerobic eukaryote in which the presence of heme has been directly demonstrated.

Reconstructing blood stem cell regulatory network models from single-cell molecular profiles

PubMed Central

Hamey, Fiona K.; Nestorowa, Sonia; Kinston, Sarah J.; Kent, David G.; Wilson, Nicola K.

2017-01-01

Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte–erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 (Nfe2) and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog (Cbfa2t3h) by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships. PMID:28584094

Analysis of the electrochemistry of hemes with Ems spanning 800 mV

PubMed Central

Zheng, Zhong; Gunner, M. R.

2009-01-01

The free energy of heme reduction in different proteins is found to vary over more than 18 kcal/mol. It is a challenge to determine how proteins manage to achieve this enormous range of Ems with a single type of redox cofactor. Proteins containing 141 unique hemes of a-, b-, and c-type, with bis-His, His-Met, and aquo-His ligation were calculated using Multi-Conformation Continuum Electrostatics (MCCE). The experimental Ems range over 800 mV from −350 mV in cytochrome c3 to 450 mV in cytochrome c peroxidase (vs. SHE). The quantitative analysis of the factors that modulate heme electrochemistry includes the interactions of the heme with its ligands, the solvent, the protein backbone, and sidechains. MCCE calculated Ems are in good agreement with measured values. Using no free parameters the slope of the line comparing calculated and experimental Ems is 0.73 (R2 = 0.90), showing the method accounts for 73% of the observed Em range. Adding a +160 mV correction to the His-Met c-type hemes yields a slope of 0.97 (R2 = 0.93). With the correction 65% of the hemes have an absolute error smaller than 60 mV and 92% are within 120 mV. The overview of heme proteins with known structures and Ems shows both the lowest and highest potential hemes are c-type, whereas the b-type hemes are found in the middle Em range. In solution, bis-His ligation lowers the Em by ≈205 mV relative to hemes with His-Met ligands. The bis-His, aquo-His, and His-Met ligated b-type hemes all cluster about Ems which are ≈200 mV more positive in protein than in water. In contrast, the low potential bis-His c-type hemes are shifted little from in solution, whereas the high potential His-Met c-type hemes are raised by ≈300 mV from solution. The analysis shows that no single type of interaction can be identified as the most important in setting heme electrochemistry in proteins. For example, the loss of solvation (reaction field) energy, which raises the Em, has been suggested to be a major factor in

Heme inhibition of ferrisiderophore reductase in Bacillus subtilis.

PubMed

Lodge, J S; Gaines, C G; Arceneaux, J E; Byers, B R

1982-11-01

Heme was a noncompetitive inhibitor (apparent K(i) and K'(i) = 0.043 mM) of a ferrisiderophore reductase purified from Bacillus subtilis; protoporphyrin IX had no effect. The cellular level of heme may partly regulate the function of this reductase to yield a controlled flow of iron into metabolism.

The Bordetella bhu Locus Is Required for Heme Iron Utilization

PubMed Central

Vanderpool, Carin K.; Armstrong, Sandra K.

2001-01-01

Bordetella pertussis and Bordetella bronchiseptica are capable of obtaining iron from hemin and hemoglobin. Genes encoding a putative bacterial heme iron acquisition system (bhu, for Bordetella heme utilization) were identified in a B. pertussis genomic sequence database, and the corresponding DNA was isolated from a virulent strain of B. pertussis. A B. pertussis bhuR mutant, predicted to lack the heme outer membrane receptor, was generated by allelic exchange. In contrast to the wild-type strain, bhuR mutant PM5 was incapable of acquiring iron from hemin and hemoglobin; genetic complementation of PM5 with the cloned bhuRSTUV genes restored heme utilization to wild-type levels. In parallel studies, B. bronchiseptica bhu sequences were also identified and a B. bronchiseptica bhuR mutant was constructed and confirmed to be defective in heme iron acquisition. The wild-type B. bronchiseptica parent strain grown under low-iron conditions produced the presumptive BhuR protein, which was absent in the bhuR mutant. Furthermore, production of BhuR by iron-starved B. bronchiseptica was markedly enhanced by culture in hemin-supplemented medium, suggesting that these organisms sense and respond to heme in the environment. Analysis of the genetic region upstream of the bhu cluster identified open reading frames predicted to encode homologs of the Escherichia coli ferric citrate uptake regulators FecI and FecR. These putative Bordetella regulators may mediate heme-responsive positive transcriptional control of the bhu genes. PMID:11418569

Genetic Regulatory Networks in Embryogenesis and Evolution

NASA Technical Reports Server (NTRS)

1998-01-01

The article introduces a series of papers that were originally presented at a workshop titled Genetic Regulatory Network in Embryogenesis and Evaluation. Contents include the following: evolution of cleavage programs in relationship to axial specification and body plan evolution, changes in cell lineage specification elucidate evolutionary relations in spiralia, axial patterning in the leech: developmental mechanisms and evolutionary implications, hox genes in arthropod development and evolution, heterochronic genes in development and evolution, a common theme for LIM homeobox gene function across phylogeny, and mechanisms of specification in ascidian embryos.

TRACING CO-REGULATORY NETWORK DYNAMICS IN NOISY, SINGLE-CELL TRANSCRIPTOME TRAJECTORIES.

PubMed

Cordero, Pablo; Stuart, Joshua M

2017-01-01

The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression 'trajectory' from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves. SCIMITAR yields rich models from the data that highlight genes with expression and co-expression patterns that are associated with the inferred progression. Further, SCIMITAR extracts regulatory states from the implicated trajectory-evolvingco-expression networks. We benchmark the method on simulated data to show that it yields accurate cell ordering and gene network inferences. Applied to the interpretation of a single-cell human fetal neuron dataset, SCIMITAR finds progression-associated genes in cornerstone neural differentiation pathways missed by standard differential expression tests. Finally, by leveraging the rewiring of gene-gene co-expression relations across the progression, the method reveals the rise and fall of co-regulatory states and trajectory-dependent gene modules. These analyses implicate new transcription factors in neural differentiation including putative co-factors for the multi-functional NFAT pathway.

Incorporation of Tyrosine and Glutamine Residues into the Soluble Guanylate Cyclase Heme Distal Pocket Alters NO and O2 Binding*

PubMed Central

Derbyshire, Emily R.; Deng, Sarah; Marletta, Michael A.

2010-01-01

Nitric oxide (NO) is the physiologically relevant activator of the mammalian hemoprotein soluble guanylate cyclase (sGC). The heme cofactor of α1β1 sGC has a high affinity for NO but has never been observed to form a complex with oxygen. Introduction of a key tyrosine residue in the sGC heme binding domain β1(1–385) is sufficient to produce an oxygen-binding protein, but this mutation in the full-length enzyme did not alter oxygen affinity. To evaluate ligand binding specificity in full-length sGC we mutated several conserved distal heme pocket residues (β1 Val-5, Phe-74, Ile-145, and Ile-149) to introduce a hydrogen bond donor in proximity to the heme ligand. We found that the NO coordination state, NO dissociation, and enzyme activation were significantly affected by the presence of a tyrosine in the distal heme pocket; however, the stability of the reduced porphyrin and the proteins affinity for oxygen were unaltered. Recently, an atypical sGC from Drosophila, Gyc-88E, was shown to form a stable complex with oxygen. Sequence analysis of this protein identified two residues in the predicted heme pocket (tyrosine and glutamine) that may function to stabilize oxygen binding in the atypical cyclase. The introduction of these residues into the rat β1 distal heme pocket (Ile-145 → Tyr and Ile-149 → Gln) resulted in an sGC construct that oxidized via an intermediate with an absorbance maximum at 417 nm. This absorbance maximum is consistent with globin FeII-O2 complexes and is likely the first observation of a FeII-O2 complex in the full-length α1β1 protein. Additionally, these data suggest that atypical sGCs stabilize O2 binding by a hydrogen bonding network involving tyrosine and glutamine. PMID:20231286

Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis

PubMed Central

Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-hua; Xue, Dongbo

2017-01-01

Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including “immune response” as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma. PMID:28355233

Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis.

PubMed

Gao, Bo; Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-Hua; Xue, Dongbo

2017-01-01

Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including "immune response" as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma.

Investigations of ultrafast ligand rebinding to heme and heme proteins using temperature and strong magnetic field perturbations

NASA Astrophysics Data System (ADS)

Zhang, Zhenyu

This thesis is written to summarize investigations of the mechanisms that underlie the kinetics of diatomic ligand rebinding to the iron atom of the heme group, which is chelated inside heme proteins. The family of heme proteins is a major object of studies for several branches of scientific research activity. Understanding the ligand binding mechanisms and pathways is one of the major goals for biophysics. My interests mainly focus on the physics of this ligand binding process. Therefore, to investigate the problem, isolated from the influence of the protein matrix, Fe-protophorphyrin IX is chosen as the prototype system in my studies. Myoglobin, the most extensively and intensively studied protein, is another ideal system that allows coupling the protein polypeptide matrix into the investigation. A technique to synchro-lock two laser pulse trains electronically is applied to our pump-probe spectroscopic studies. Based on this technique, a two color, fs/ps pump-probe system is developed which extends the temporal window for our investigation to 13ns and fills a gap existing in previous pump-probe investigations. In order to apply this newly-developed pump-probe laser system to implement systematic studies on the kinetics of diatomic ligand (NO, CO, O2) rebinding to heme and heme proteins, several experimental setups are utilized. In Chapter 1, the essential background knowledge, which helps to understand the iron-ligand interaction, is briefly described. In Chapter 2, in addition to a description of the preparation protocols of protein samples and details of the method for data analysis, three home-made setups are described, which include: a picosecond laser regenerative amplifier, a pump-probe application along the bore (2-inch in diameter) of a superconducting magnet and a temperature-controllable cryostat for spinning sample cell. Chapter 3 presents high magnetic field studies of several heme-ligand or protein-ligand systems. Pump-probe spectroscopy is used to

Neural model of gene regulatory network: a survey on supportive meta-heuristics.

PubMed

Biswas, Surama; Acharyya, Sriyankar

2016-06-01

Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

The interaction of heme with plakortin and a synthetic endoperoxide analogue: new insights into the heme-activated antimalarial mechanism

NASA Astrophysics Data System (ADS)

Persico, Marco; Fattorusso, Roberto; Taglialatela-Scafati, Orazio; Chianese, Giuseppina; de Paola, Ivan; Zaccaro, Laura; Rondinelli, Francesca; Lombardo, Marco; Quintavalla, Arianna; Trombini, Claudio; Fattorusso, Ernesto; Fattorusso, Caterina; Farina, Biancamaria

2017-04-01

In the present work we performed a combined experimental and computational study on the interaction of the natural antimalarial endoperoxide plakortin and its synthetic analogue 4a with heme. Obtained results indicate that the studied compounds produce reactive carbon radical species after being reductively activated by heme. In particular, similarly to artemisinin, the formation of radicals prone to inter-molecular reactions should represent the key event responsible for Plasmodium death. To our knowledge this is the first experimental investigation on the reductive activation of simple antimalarial endoperoxides (1,2-dioxanes) by heme and results were compared to the ones previously obtained from the reaction with FeCl2. The obtained experimental data and the calculated molecular interaction models represent crucial tools for the rational optimization of our promising class of low-cost synthetic antimalarial endoperoxides.

Post-transcriptional regulatory network of epithelial-to-mesenchymal and mesenchymal-to-epithelial transitions

PubMed Central

2014-01-01

Epithelial-to-mesenchymal transition (EMT) and its reverse process, mesenchymal-to-epithelial transition (MET), play important roles in embryogenesis, stem cell biology, and cancer progression. EMT can be regulated by many signaling pathways and regulatory transcriptional networks. Furthermore, post-transcriptional regulatory networks regulate EMT; these networks include the long non-coding RNA (lncRNA) and microRNA (miRNA) families. Specifically, the miR-200 family, miR-101, miR-506, and several lncRNAs have been found to regulate EMT. Recent studies have illustrated that several lncRNAs are overexpressed in various cancers and that they can promote tumor metastasis by inducing EMT. MiRNA controls EMT by regulating EMT transcription factors or other EMT regulators, suggesting that lncRNAs and miRNA are novel therapeutic targets for the treatment of cancer. Further efforts have shown that non-coding-mediated EMT regulation is closely associated with epigenetic regulation through promoter methylation (e.g., miR-200 or miR-506) and protein regulation (e.g., SET8 via miR-502). The formation of gene fusions has also been found to promote EMT in prostate cancer. In this review, we discuss the post-transcriptional regulatory network that is involved in EMT and MET and how targeting EMT and MET may provide effective therapeutics for human disease. PMID:24598126

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO 2 Levels

DOE PAGES

Levering, Jennifer; Dupont, Christopher L.; Allen, Andrew E.; ...

2017-02-14

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean’s primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom’s metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and sharedmore » metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum’s response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum’s metabolism.« less

Integrated Regulatory and Metabolic Networks of the Marine Diatom Phaeodactylum tricornutum Predict the Response to Rising CO 2 Levels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levering, Jennifer; Dupont, Christopher L.; Allen, Andrew E.

Diatoms are eukaryotic microalgae that are responsible for up to 40% of the ocean’s primary productivity. How diatoms respond to environmental perturbations such as elevated carbon concentrations in the atmosphere is currently poorly understood. We developed a transcriptional regulatory network based on various transcriptome sequencing expression libraries for different environmental responses to gain insight into the marine diatom’s metabolic and regulatory interactions and provide a comprehensive framework of responses to increasing atmospheric carbon levels. This transcriptional regulatory network was integrated with a recently published genome-scale metabolic model of Phaeodactylum tricornutum to explore the connectivity of the regulatory network and sharedmore » metabolites. The integrated regulatory and metabolic model revealed highly connected modules within carbon and nitrogen metabolism. P. tricornutum’s response to rising carbon levels was analyzed by using the recent genome-scale metabolic model with cross comparison to experimental manipulations of carbon dioxide. Using a systems biology approach, we studied the response of the marine diatom Phaeodactylum tricornutum to changing atmospheric carbon concentrations on an ocean-wide scale. By integrating an available genome-scale metabolic model and a newly developed transcriptional regulatory network inferred from transcriptome sequencing expression data, we demonstrate that carbon metabolism and nitrogen metabolism are strongly connected and the genes involved are coregulated in this model diatom. These tight regulatory constraints could play a major role during the adaptation of P. tricornutum to increasing carbon levels. The transcriptional regulatory network developed can be further used to study the effects of different environmental perturbations on P. tricornutum’s metabolism.« less

TMEM14C is required for erythroid mitochondrial heme metabolism

PubMed Central

Yien, Yvette Y.; Robledo, Raymond F.; Schultz, Iman J.; Takahashi-Makise, Naoko; Gwynn, Babette; Bauer, Daniel E.; Dass, Abhishek; Yi, Gloria; Li, Liangtao; Hildick-Smith, Gordon J.; Cooney, Jeffrey D.; Pierce, Eric L.; Mohler, Kyla; Dailey, Tamara A.; Miyata, Non; Kingsley, Paul D.; Garone, Caterina; Hattangadi, Shilpa M.; Huang, Hui; Chen, Wen; Keenan, Ellen M.; Shah, Dhvanit I.; Schlaeger, Thorsten M.; DiMauro, Salvatore; Orkin, Stuart H.; Cantor, Alan B.; Palis, James; Koehler, Carla M.; Lodish, Harvey F.; Kaplan, Jerry; Ward, Diane M.; Dailey, Harry A.; Phillips, John D.; Peters, Luanne L.; Paw, Barry H.

2014-01-01

The transport and intracellular trafficking of heme biosynthesis intermediates are crucial for hemoglobin production, which is a critical process in developing red cells. Here, we profiled gene expression in terminally differentiating murine fetal liver-derived erythroid cells to identify regulators of heme metabolism. We determined that TMEM14C, an inner mitochondrial membrane protein that is enriched in vertebrate hematopoietic tissues, is essential for erythropoiesis and heme synthesis in vivo and in cultured erythroid cells. In mice, TMEM14C deficiency resulted in porphyrin accumulation in the fetal liver, erythroid maturation arrest, and embryonic lethality due to profound anemia. Protoporphyrin IX synthesis in TMEM14C-deficient erythroid cells was blocked, leading to an accumulation of porphyrin precursors. The heme synthesis defect in TMEM14C-deficient cells was ameliorated with a protoporphyrin IX analog, indicating that TMEM14C primarily functions in the terminal steps of the heme synthesis pathway. Together, our data demonstrate that TMEM14C facilitates the import of protoporphyrinogen IX into the mitochondrial matrix for heme synthesis and subsequent hemoglobin production. Furthermore, the identification of TMEM14C as a protoporphyrinogen IX importer provides a genetic tool for further exploring erythropoiesis and congenital anemias. PMID:25157825

Sampangine inhibits heme biosynthesis in both yeast and human

USDA-ARS?s Scientific Manuscript database

The azaoxoaporphine alkaloid sampangine exhibits strong antiproliferation activity in various organisms. Previous studies suggested that it somehow affects heme metabolism and stimulates production of reactive oxygen species (ROS). In this study, we show that inhibition of heme biosynthesis is the p...

The Effect of Plant Proteins Derived from Cereals and Legumes on Heme Iron Absorption.

PubMed

Weinborn, Valerie; Pizarro, Fernando; Olivares, Manuel; Brito, Alex; Arredondo, Miguel; Flores, Sebastián; Valenzuela, Carolina

2015-10-30

The aim of this study is to determine the effect of proteins from cereals and legumes on heme iron (Fe) absorption. The absorption of heme Fe without its native globin was measured. Thirty adult females participated in two experimental studies (15 per study). Study I focused on the effects of cereal proteins (zein, gliadin and glutelin) and study II on the effects of legume proteins (soy, pea and lentil) on heme Fe absorption. When heme was given alone (as a control), study I and II yielded 6.2% and 11.0% heme absorption (p > 0.05). In study I, heme Fe absorption was 7.2%, 7.5% and 5.9% when zein, gliadin and glutelin were added, respectively. From this, it was concluded that cereal proteins did not affect heme Fe absorption. In study II, heme Fe absorption was 7.3%, 8.1% and 9.1% with the addition of soy, pea and lentil proteins, respectively. Only soy proteins decreased heme Fe absorption (p < 0.05). These results suggest that with the exception of soy proteins, which decreased absorption, proteins derived from cereals and legumes do not affect heme Fe absorption.

Regulation of a glutamyl-tRNA synthetase by the heme status

PubMed Central

Levicán, Gloria; Katz, Assaf; de Armas, Merly; Núñez, Harold; Orellana, Omar

2007-01-01

Glutamyl-tRNA (Glu-tRNA), formed by Glu-tRNA synthetase (GluRS), is a substrate for protein biosynthesis and tetrapyrrole formation by the C5 pathway. In this route Glu-tRNA is transformed to δ-aminolevulinic acid, the universal precursor of tetrapyrroles (e.g., heme and chlorophyll) by the action of Glu-tRNA reductase (GluTR) and glutamate semialdehyde aminotransferase. GluTR is a target of feedback regulation by heme. In Acidithiobacillus ferrooxidans, an acidophilic bacterium that expresses two GluRSs (GluRS1 and GluRS2) with different tRNA specificity, the intracellular heme level varies depending on growth conditions. Under high heme requirement for respiration increased levels of GluRS and GluTR are observed. Strikingly, when intracellular heme is in excess, the cells respond by a dramatic decrease of GluRS activity and the level of GluTR. The recombinant GluRS1 enzyme is inhibited in vitro by hemin, but NADPH restores its activity. These results suggest that GluRS plays a major role in regulating the cellular level of heme. PMID:17360620

Hemopexin and haptoglobin: allies against heme toxicity from hemoglobin not contenders

PubMed Central

Smith, Ann; McCulloh, Russell J.

2015-01-01

The goal here is to describe our current understanding of heme metabolism and the deleterious effects of “free” heme on immunological processes, endothelial function, systemic inflammation, and various end-organ tissues (e.g., kidney, lung, liver, etc.), with particular attention paid to the role of hemopexin (HPX). Because heme toxicity is the impetus for much of the pathology in sepsis, sickle cell disease (SCD), and other hemolytic conditions, the biological importance and clinical relevance of HPX, the predominant heme binding protein, is reinforced. A perspective on the function of HPX and haptoglobin (Hp) is presented, updating how these two proteins and their respective receptors act simultaneously to protect the body in clinical conditions that entail hemolysis and/or systemic intravascular (IVH) inflammation. Evidence from longitudinal studies in patients supports that HPX plays a Hp-independent role in genetic and non-genetic hemolytic diseases without the need for global Hp depletion. Evidence also supports that HPX has an important role in the prognosis of complex illnesses characterized predominantly by the presence of hemolysis, such as SCD, sepsis, hemolytic-uremic syndrome, and conditions involving IVH and extravascular hemolysis (EVH), such as that generated by extracorporeal circulation during cardiopulmonary bypass (CPB) and from blood transfusions. We propose that quantitating the amounts of plasma heme, HPX, Hb-Hp, heme-HPX, and heme-albumin levels in various disease states may aid in the diagnosis and treatment of the above-mentioned conditions, which is crucial to developing targeted plasma protein supplementation (i.e., “replenishment”) therapies for patients with heme toxicity due to HPX depletion. PMID:26175690

Characterization of the Heme Environment in Arabidopsis thaliana Fatty Acid α-Dioxygenase-1*

PubMed Central

Liu, Wen; Rogge, Corina E.; Bambai, Bijan; Palmer, Graham; Tsai, Ah-Lim; Kulmacz, Richard J.

2010-01-01

Plant α-dioxygenases (PADOX) are hemoproteins in the myeloperoxidase family. We have used a variety of spectroscopic, mutagenic, and kinetic approaches to characterize the heme environment in Arabidopsis thaliana PADOX-1. Recombinant PADOX-1 purified to homogeneity contained 1 mol of heme bound tightly but noncovalently per protein monomer. Electronic absorbance, electron paramagnetic resonance, and magnetic circular dichroism spectra showed a high spin ferric heme that could be reduced to the ferrous state by dithionite. Cyanide bound relatively weakly in the ferric PADOX-1 heme vicinity (Kd ~10 mm) but did not shift the heme to the low spin state. Cyanide was a very strong inhibitor of the fatty acid oxygenase activity (Ki ~5 µm) and increased the Km value for oxygen but not that for fatty acid. Spectroscopic analyses indicated that carbon monoxide, azide, imidazole, and a variety of substituted imidazoles did not bind appreciably in the ferric PADOX-1 heme vicinity. Substitution of His-163 and His-389 with cysteine, glutamine, tyrosine, or methionine resulted in variable degrees of perturbation of the heme absorbance spectrum and oxygenase activity, consistent with His-389 serving as the proximal heme ligand and indicating that the heme has a functional role in catalysis. Overall, A. thaliana PADOX-1 resembles a b-type cytochrome, although with much more restricted access to the distal face of the heme than seen in most other myeloperoxidase family members, explaining the previously puzzling lack of peroxidase activity in the plant protein. PADOX-1 is unusual in that it has a high affinity, inhibitory cyanide-binding site distinct from the distal heme face and the fatty acid site. PMID:15100225

PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification.

PubMed

Vadigepalli, Rajanikanth; Chakravarthula, Praveen; Zak, Daniel E; Schwaber, James S; Gonye, Gregory E

2003-01-01

We have developed a bioinformatics tool named PAINT that automates the promoter analysis of a given set of genes for the presence of transcription factor binding sites. Based on coincidence of regulatory sites, this tool produces an interaction matrix that represents a candidate transcriptional regulatory network. This tool currently consists of (1) a database of promoter sequences of known or predicted genes in the Ensembl annotated mouse genome database, (2) various modules that can retrieve and process the promoter sequences for binding sites of known transcription factors, and (3) modules for visualization and analysis of the resulting set of candidate network connections. This information provides a substantially pruned list of genes and transcription factors that can be examined in detail in further experimental studies on gene regulation. Also, the candidate network can be incorporated into network identification methods in the form of constraints on feasible structures in order to render the algorithms tractable for large-scale systems. The tool can also produce output in various formats suitable for use in external visualization and analysis software. In this manuscript, PAINT is demonstrated in two case studies involving analysis of differentially regulated genes chosen from two microarray data sets. The first set is from a neuroblastoma N1E-115 cell differentiation experiment, and the second set is from neuroblastoma N1E-115 cells at different time intervals following exposure to neuropeptide angiotensin II. PAINT is available for use as an agent in BioSPICE simulation and analysis framework (www.biospice.org), and can also be accessed via a WWW interface at www.dbi.tju.edu/dbi/tools/paint/.

Heme-based sensors in biological systems.

PubMed

Rodgers, K R

1999-04-01

The past several years have been witness to a staggering rate of advancement in the understanding of how organisms respond to changes in the availability of diatomic molecules that are toxic and/or crucial to survival. Heme-based sensors presently constitute the majority of the proteins known to sense NO, O2 and CO and to initiate the chemistry required to adapt to changes in their availabilities. Knowledge of the three characterized members of this class, soluble guanylate cyclase, FixL and CooA, has grown substantially during the past year. The major advances have resulted from a broad range of approaches to elucidation of both function and mechanism. They include growth in the understanding of the interplay between the heme and protein in soluble guanylate cyclase, as well as alternate means for its stimulation. Insight into the O2-induced structural changes in FixL has been supplied by the single crystal structure of the heme domain of Bradyrhizobium japonicum. Finally, the ligation environment and ligand interchange that facilitates CO sensing by CooA has been established by spectroscopic and mutagenesis techniques.

Gene Regulatory Networks in Cardiac Conduction System Development

PubMed Central

Munshi, Nikhil V.

2014-01-01

The cardiac conduction system is a specialized tract of myocardial cells responsible for maintaining normal cardiac rhythm. Given its critical role in coordinating cardiac performance, a detailed analysis of the molecular mechanisms underlying conduction system formation should inform our understanding of arrhythmia pathophysiology and affect the development of novel therapeutic strategies. Historically, the ability to distinguish cells of the conduction system from neighboring working myocytes presented a major technical challenge for performing comprehensive mechanistic studies. Early lineage tracing experiments suggested that conduction cells derive from cardiomyocyte precursors, and these claims have been substantiated by using more contemporary approaches. However, regional specialization of conduction cells adds an additional layer of complexity to this system, and it appears that different components of the conduction system utilize unique modes of developmental formation. The identification of numerous transcription factors and their downstream target genes involved in regional differentiation of the conduction system has provided insight into how lineage commitment is achieved. Furthermore, by adopting cutting-edge genetic techniques in combination with sophisticated phenotyping capabilities, investigators have made substantial progress in delineating the regulatory networks that orchestrate conduction system formation and their role in cardiac rhythm and physiology. This review describes the connectivity of these gene regulatory networks in cardiac conduction system development and discusses how they provide a foundation for understanding normal and pathological human cardiac rhythms. PMID:22628576

Factorization of the association rate coefficient in ligand rebinding to heme proteins

NASA Astrophysics Data System (ADS)

Young, Robert D.

1984-01-01

A stochastic theory of ligand migration in biomolecules is used to analyze the recombination of small ligands to heme proteins after flash photolysis. The stochastic theory is based on a generalized sequential barrier model in which a ligand binds by overcoming a series of barriers formed by the solvent protein interface, the protein matrix, and the heme distal histidine system. The stochastic theory shows that the association rate coefficient λon factorizes into three terms λon =γ12Nout, where γ12 is the rate coefficient from the heme pocket to the heme binding site, is the equilibrium pocket occupation factor, and Nout is the fraction of heme proteins which do not undergo geminate recombination of a flashed-off ligand. The factorization of λon holds for any number of barriers and with no assumptions regarding the various rate coefficients so long as the exponential solvent process occurs. Transitions of a single ligand are allowed between any two sites with two crucial exceptions: (i) the heme binding site acts as a trap so that thermal dissociation of a bound ligand does not occur within the time of the measurement; (ii) the final step in the rebinding process always has a ligand in the heme pocket from where the ligand binds to the heme iron.

The vertebrate Hox gene regulatory network for hindbrain segmentation: Evolution and diversification: Coupling of a Hox gene regulatory network to hindbrain segmentation is an ancient trait originating at the base of vertebrates.

PubMed

Parker, Hugo J; Bronner, Marianne E; Krumlauf, Robb

2016-06-01

Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior-posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage-specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. © 2016 WILEY Periodicals, Inc.

Transfection of the Human Heme Oxygenase Gene Into Rabbit Coronary Microvessel Endothelial Cells: Protective Effect Against Heme and Hemoglobin Toxicity

NASA Astrophysics Data System (ADS)

Abraham, N. G.; Lavrovsky, Y.; Schwartzman, M. L.; Stoltz, R. A.; Levere, R. D.; Gerritsen, M. E.

1995-07-01

Heme oxygenase (HO) is a stress protein and has been suggested to participate in defense mechanisms against agents that may induce oxidative injury such as metals, endotoxin, heme/hemoglobin, and various cytokines. Overexpression of HO in cells might therefore protect against oxidative stress produced by certain of these agents, specifically heme and hemoglobin, by catalyzing their degradation to bilirubin, which itself has antioxidant properties. We report here the successful in vitro transfection of rabbit coronary microvessel endothelial cells with a functioning gene encoding the human HO enzyme. A plasmid containing the cytomegalovirus promoter and the human HO cDNA complexed to cationic liposomes (Lipofectin) was used to transfect rabbit endothelial cells. Cells transfected with human HO exhibited an ≈3.0-fold increase in enzyme activity and expressed a severalfold induction of human HO mRNA as compared with endogenous rabbit HO mRNA. Transfected and nontransfected cells expressed factor VIII antigen and exhibited similar acetylated low-density lipoprotein uptake (two important features that characterize endothelial cells) with >85% of cells staining positive for each marker. Moreover, cells transfected with the human HO gene acquired substantial resistance to toxicity produced by exposure to recombinant hemoglobin and heme as compared with nontransfected cells. The protective effect of HO overexpression against heme/hemoglobin toxicity in endothelial cells shown in these studies provides direct evidence that the inductive response of human HO to such injurious stimuli represents an important tissue adaptive mechanism for moderating the severity of cell damage produced by these blood components.

Enhancer Variants Synergistically Drive Dysfunction of a Gene Regulatory Network In Hirschsprung Disease

DOE PAGES

Chatterjee, Sumantra; Kapoor, Ashish; Akiyama, Jennifer A.; ...

2016-09-29

Common sequence variants in cis-regulatory elements (CREs) are suspected etiological causes of complex disorders. We previously identified an intronic enhancer variant in the RET gene disrupting SOX10 binding and increasing Hirschsprung disease (HSCR) risk 4-fold. We now show that two other functionally independent CRE variants, one binding Gata2 and the other binding Rarb, also reduce Ret expression and increase risk 2- and 1.7-fold. By studying human and mouse fetal gut tissues and cell lines, we demonstrate that reduced RET expression propagates throughout its gene regulatory network, exerting effects on both its positive and negative feedback components. We also provide evidencemore » that the presence of a combination of CRE variants synergistically reduces RET expression and its effects throughout the GRN. These studies show how the effects of functionally independent non-coding variants in a coordinated gene regulatory network amplify their individually small effects, providing a model for complex disorders.« less

Enhancer Variants Synergistically Drive Dysfunction of a Gene Regulatory Network In Hirschsprung Disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chatterjee, Sumantra; Kapoor, Ashish; Akiyama, Jennifer A.

Common sequence variants in cis-regulatory elements (CREs) are suspected etiological causes of complex disorders. We previously identified an intronic enhancer variant in the RET gene disrupting SOX10 binding and increasing Hirschsprung disease (HSCR) risk 4-fold. We now show that two other functionally independent CRE variants, one binding Gata2 and the other binding Rarb, also reduce Ret expression and increase risk 2- and 1.7-fold. By studying human and mouse fetal gut tissues and cell lines, we demonstrate that reduced RET expression propagates throughout its gene regulatory network, exerting effects on both its positive and negative feedback components. We also provide evidencemore » that the presence of a combination of CRE variants synergistically reduces RET expression and its effects throughout the GRN. These studies show how the effects of functionally independent non-coding variants in a coordinated gene regulatory network amplify their individually small effects, providing a model for complex disorders.« less

Heme versus non-heme iron-nitroxyl {FeN(H)O}⁸ complexes: electronic structure and biologically relevant reactivity.

PubMed

Speelman, Amy L; Lehnert, Nicolai

2014-04-15

Researchers have completed extensive studies on heme and non-heme iron-nitrosyl complexes, which are labeled {FeNO}(7) in the Enemark-Feltham notation, but they have had very limited success in producing corresponding, one-electron reduced, {FeNO}(8) complexes where a nitroxyl anion (NO(-)) is formally bound to an iron(II) center. These complexes, and their protonated iron(II)-NHO analogues, are proposed key intermediates in nitrite (NO2(-)) and nitric oxide (NO) reducing enzymes in bacteria and fungi. In addition, HNO is known to have a variety of physiological effects, most notably in the cardiovascular system. HNO may also serve as a signaling molecule in mammals. For these functions, iron-containing proteins may mediate the production of HNO and serve as receptors for HNO in vivo. In this Account, we highlight recent key advances in the preparation, spectroscopic characterization, and reactivity of ferrous heme and non-heme nitroxyl (NO(-)/HNO) complexes that have greatly enhanced our understanding of the potential biological roles of these species. Low-spin (ls) heme {FeNO}(7) complexes (S = 1/2) can be reversibly reduced to the corresponding {FeNO}(8) species, which are stable, diamagnetic compounds. Because the reduction is ligand (NO) centered in these cases, it occurs at extremely negative redox potentials that are at the edge of the biologically feasible range. Interestingly, the electronic structures of ls-{FeNO}(7) and ls-{FeNO}(8) species are strongly correlated with very similar frontier molecular orbitals (FMOs) and thermodynamically strong Fe-NO bonds. In contrast, high-spin (hs) non-heme {FeNO}(7) complexes (S = 3/2) can be reduced at relatively mild redox potentials. Here, the reduction is metal-centered and leads to a paramagnetic (S = 1) {FeNO}(8) complex. The increased electron density at the iron center in these species significantly decreases the covalency of the Fe-NO bond, making the reduced complexes highly reactive. In the absence of

Nutritional regulation of hepatic heme biosynthesis and porphyria through PGC-1alpha.

PubMed

Handschin, Christoph; Lin, Jiandie; Rhee, James; Peyer, Anne-Kathrin; Chin, Sherry; Wu, Pei-Hsuan; Meyer, Urs A; Spiegelman, Bruce M

2005-08-26

Inducible hepatic porphyrias are inherited genetic disorders of enzymes of heme biosynthesis. The main clinical manifestations are acute attacks of neuropsychiatric symptoms frequently precipitated by drugs, hormones, or fasting, associated with increased urinary excretion of delta-aminolevulinic acid (ALA). Acute attacks are treated by heme infusion and glucose administration, but the mechanisms underlying the precipitating effects of fasting and the beneficial effects of glucose are unknown. We show that the rate-limiting enzyme in hepatic heme biosynthesis, 5-aminolevulinate synthase (ALAS-1), is regulated by the peroxisome proliferator-activated receptor gamma coactivator 1alpha (PGC-1alpha). Elevation of PGC-1alpha in mice via adenoviral vectors increases the levels of heme precursors in vivo as observed in acute attacks. The induction of ALAS-1 by fasting is lost in liver-specific PGC-1alpha knockout animals, as is the ability of porphyrogenic drugs to dysregulate heme biosynthesis. These data show that PGC-1alpha links nutritional status to heme biosynthesis and acute hepatic porphyria.

Hemoglobin binding and catalytic heme extraction by IsdB near iron transporter domains.

PubMed

Bowden, Catherine F M; Verstraete, Meghan M; Eltis, Lindsay D; Murphy, Michael E P

2014-04-15

The Isd (iron-regulated surface determinant) system is a multiprotein transporter that allows bacterium Staphylococcus aureus to take up iron from hemoglobin (Hb) during human infection. In this system, IsdB is a cell wall-anchored surface protein that contains two near iron transporter (NEAT) domains, one of which binds heme. IsdB rapidly extracts heme from Hb and transfers it to IsdA for relay into the bacterial cell. Using a series of recombinant IsdB constructs that included at least one NEAT domain, we demonstrated that both domains are required to bind Hb with high affinity (KD = 0.42 ± 0.05 μM) and to extract heme from Hb. Moreover, IsdB extracted heme only from oxidized metHb, although it also bound oxyHb and the Hb-CO complex. In a reconstituted model of the biological heme relay pathway, IsdB catalyzed the transfer of heme from metHb to IsdA with a Km for metHb of 0.75 ± 0.07 μN and a kcat of 0.22 ± 0.01 s(-1). The latter is consistent with the transfer of heme from metHb to IsdB being the rate-limiting step. With both NEAT domains and the linker region present in a single contiguous polypeptide, high-affinity Hb binding was achieved, rapid heme uptake was observed, and multiple turnovers of heme extraction from metHb and transfer to IsdA were conducted, representing all known Hb-heme uptake functions of the full-length IsdB protein.

Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress.

PubMed

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-12-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. © 2014 American Society of Plant Biologists. All rights reserved.

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

PubMed

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available.

NIMEFI: Gene Regulatory Network Inference using Multiple Ensemble Feature Importance Algorithms

PubMed Central

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available

A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks.

PubMed

Zhou, Xiaobo; Wang, Xiaodong; Pal, Ranadip; Ivanov, Ivan; Bittner, Michael; Dougherty, Edward R

2004-11-22

We have hypothesized that the construction of transcriptional regulatory networks using a method that optimizes connectivity would lead to regulation consistent with biological expectations. A key expectation is that the hypothetical networks should produce a few, very strong attractors, highly similar to the original observations, mimicking biological state stability and determinism. Another central expectation is that, since it is expected that the biological control is distributed and mutually reinforcing, interpretation of the observations should lead to a very small number of connection schemes. We propose a fully Bayesian approach to constructing probabilistic gene regulatory networks (PGRNs) that emphasizes network topology. The method computes the possible parent sets of each gene, the corresponding predictors and the associated probabilities based on a nonlinear perceptron model, using a reversible jump Markov chain Monte Carlo (MCMC) technique, and an MCMC method is employed to search the network configurations to find those with the highest Bayesian scores to construct the PGRN. The Bayesian method has been used to construct a PGRN based on the observed behavior of a set of genes whose expression patterns vary across a set of melanoma samples exhibiting two very different phenotypes with respect to cell motility and invasiveness. Key biological features have been faithfully reflected in the model. Its steady-state distribution contains attractors that are either identical or very similar to the states observed in the data, and many of the attractors are singletons, which mimics the biological propensity to stably occupy a given state. Most interestingly, the connectivity rules for the most optimal generated networks constituting the PGRN are remarkably similar, as would be expected for a network operating on a distributed basis, with strong interactions between the components.

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer and optimal selection of traditional Chinese medicine target.

PubMed

Tian, Tongde; Chen, Chuanliang; Yang, Feng; Tang, Jingwen; Pei, Junwen; Shi, Bian; Zhang, Ning; Zhang, Jianhua

2017-03-01

The paper aimed to screen out genetic markers applicable to early diagnosis for colorectal cancer and establish apoptotic regulatory network model for colorectal cancer, and to analyze the current situation of traditional Chinese medicine (TCM) target, thereby providing theoretical evidence for early diagnosis and targeted therapy of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers that are applied to early diagnosis of colorectal cancer were searched and performed comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. KEGG analysis was employed to establish apoptotic regulatory network model based on screened genetic markers, and optimization was conducted on TCM targets. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, P53, APC, DCC and PTEN, among which DCC has the highest diagnostic efficiency. Apoptotic regulatory network was built by KEGG analysis. Currently, it was reported that TCM has regulatory function on gene locus in apoptotic regulatory network. The apoptotic regulatory model of colorectal cancer established in this study provides theoretical evidence for early diagnosis and TCM targeted therapy of colorectal cancer in clinic.

Dietary Heme Induces Gut Dysbiosis, Aggravates Colitis, and Potentiates the Development of Adenomas in Mice

PubMed Central

Constante, Marco; Fragoso, Gabriela; Calvé, Annie; Samba-Mondonga, Macha; Santos, Manuela M.

2017-01-01

Dietary heme can be used by colonic bacteria equipped with heme-uptake systems as a growth factor and thereby impact on the microbial community structure. The impact of heme on the gut microbiota composition may be particularly pertinent in chronic inflammation such as in inflammatory bowel disease (IBD), where a strong association with gut dysbiosis has been consistently reported. In this study we investigated the influence of dietary heme on the gut microbiota and inferred metagenomic composition, and on chemically induced colitis and colitis-associated adenoma development in mice. Using 16S rRNA gene sequencing, we found that mice fed a diet supplemented with heme significantly altered their microbiota composition, characterized by a decrease in α-diversity, a reduction of Firmicutes and an increase of Proteobacteria, particularly Enterobacteriaceae. These changes were similar to shifts seen in dextran sodium sulfate (DSS)-treated mice to induce colitis. In addition, dietary heme, but not systemically delivered heme, contributed to the exacerbation of DSS-induced colitis and facilitated adenoma formation in the azoxymethane/DSS colorectal cancer (CRC) mouse model. Using inferred metagenomics, we found that the microbiota alterations elicited by dietary heme resulted in non-beneficial functional shifts, which were also characteristic of DSS-induced colitis. Furthermore, a reduction in fecal butyrate levels was found in mice fed the heme supplemented diet compared to mice fed the control diet. Iron metabolism genes known to contribute to heme release from red blood cells, heme uptake, and heme exporter proteins, were significantly enriched, indicating a shift toward favoring the growth of bacteria able to uptake heme and protect against its toxicity. In conclusion, our data suggest that luminal heme, originating from dietary components or gastrointestinal bleeding in IBD and, to lesser extent in CRC, directly contributes to microbiota dysbiosis. Thus, luminal

Inferring Gene Regulatory Networks by Singular Value Decomposition and Gravitation Field Algorithm

PubMed Central

Zheng, Ming; Wu, Jia-nan; Huang, Yan-xin; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

2012-01-01

Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms. PMID:23226565

Regulation of human heme oxygenase-1 gene expression under thermal stress.

PubMed

Okinaga, S; Takahashi, K; Takeda, K; Yoshizawa, M; Fujita, H; Sasaki, H; Shibahara, S

1996-06-15

Heme oxygenase-1 is an essential enzyme in heme catabolism, and its human gene promoter contains a putative heat shock element (HHO-HSE). This study was designed to analyze the regulation of human heme oxygenase-1 gene expression under thermal stress. The amounts of heme oxygenase-1 protein were not increased by heat shock (incubation at 42 degrees C) in human alveolar macrophages and in a human erythroblastic cell line, YN-1-0-A, whereas heat shock protein 70 (HSP70) was noticeably induced. However, heat shock factor does bind in vitro to HHO-HSE and the synthetic HHO-HSE by itself is sufficient to confer the increase in the transient expression of a reporter gene upon heat shock. The deletion of the sequence, located downstream from HHO-HSE, resulted in the activation of a reporter gene by heat shock. These results suggest that HHO-HSE is potentially functional but is repressed in vivo. Interestingly, heat shock abolished the remarkable increase in the levels of heme oxygenase-1 mRNA in YN-1-0-A cells treated with hemin or cadmium, in which HSP70 mRNA was noticeably induced. Furthermore, transient expression assays showed that heat shock inhibits the cadmium-mediated activation of the heme oxygenase-1 promoter, whereas the HSP70 gene promoter was activated upon heat shock. Such regulation of heme oxygenase-1 under thermal stress may be of physiologic significance in erythroid cells.

Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.

PubMed

Jothi, Raja; Balaji, S; Wuster, Arthur; Grochow, Joshua A; Gsponer, Jörg; Przytycka, Teresa M; Aravind, L; Babu, M Madan

2009-01-01

Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

PubMed

Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

2017-10-01

The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach.

PubMed

Abduallah, Yasser; Turki, Turki; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel; Wang, Jason T L

2017-01-01

Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool.

Coupling of the Distal H-bond Network to the Exogenous Ligand in Substrate-bound, Resting State Human Heme Oxygenase ‡

PubMed Central

Peng, Dungeng; Ogura, Hiroshi; Zhu, Wenfeng; Ma, Li-Hua; Evans, John P.; Ortiz de Montellano, Paul R.; La Mar, Gerd N.

2010-01-01

Mammalian heme oxygenase, HO, possesses catalytically implicated distal ordered water molecules within an extended H-bond network, with one of the ordered water molecules (#1) providing a bridge between the iron-coordinated ligand and the catalytically critical Asp140, that, in turn, serves as an acceptor for the Tyr58 OH H-bond. The degree of H-bonding by the ligated water molecule and the coupling of this water molecule to the H-bond network are of current interest and are herein investigated by 1H NMR. 2D NMR allowed sufficient assignments to provide both the H-bond strength and hyperfine shifts, the latter of which were used to quantify the magnetic anisotropy in both the ferric high-spin aquo and low-spin hydroxo complexes. The anisotropy in the aquo complex indicates that the H-bond donation to water #1 is marginally stronger than in a bacterial HO, while the anisotropy for the hydroxo complex reveals a conventional (dxz, dyz)1 ground state indicative of only moderate to weak H-bond acceptance by the ligated hydroxide. Mapping out the changes of the H-bond strengths in the network during the ligated water → hydroxide conversion by correcting for the effects of magnetic anisotropy, reveals a very substantial change in H-bond strength for Tyr58 OH, and lesser effects on nearby H-bonds. The effect of pH on the H-bonding network in human HO is much larger and transmitted much further from the iron than in a pathogenic bacterial HO. The implications for the HO mechanism of the H-bond of Tyr58 to Asp140 are discussed. PMID:19842713

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors.

PubMed

Sun, Mengyang; Cheng, Xianrui; Socolar, Joshua E S

2013-06-01

A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.

Stochastic models for regulatory networks of the genetic toggle switch.

PubMed

Tian, Tianhai; Burrage, Kevin

2006-05-30

Bistability arises within a wide range of biological systems from the lambda phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Stochastic models for regulatory networks of the genetic toggle switch

PubMed Central

Tian, Tianhai; Burrage, Kevin

2006-01-01

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks. PMID:16714385

Rapid, convenient method for screening imidazole-containing compounds for heme oxygenase inhibition.

PubMed

Vlahakis, Jason Z; Rahman, Mona N; Roman, Gheorghe; Jia, Zongchao; Nakatsu, Kanji; Szarek, Walter A

2011-01-01

Sensitive assays for measuring heme oxygenase activity have been based on the gas-chromatographic detection of carbon monoxide using elaborate, expensive equipment. The present study describes a rapid and convenient method for screening imidazole-containing candidates for inhibitory activity against heme oxygenase using a plate reader, based on the spectroscopic evaluation of heme degradation. A PowerWave XS plate reader was used to monitor the absorbance (as a function of time) of heme bound to purified truncated human heme oxygenase-1 (hHO-1) in the individual wells of a standard 96-well plate (with or without the addition of a test compound). The degradation of heme by heme oxygenase-1 was initiated using l-ascorbic acid, and the collected relevant absorbance data were analyzed by three different methods to calculate the percent control activity occurring in wells containing test compounds relative to that occurring in control wells with no test compound present. In the cases of wells containing inhibitory compounds, significant shifts in λ(max) from 404 to near 412 nm were observed as well as a decrease in the rate of heme degradation relative to that of the control. Each of the three methods of data processing (overall percent drop in absorbance over 1.5h, initial rate of reaction determined over the first 5 min, and estimated pseudo first-order reaction rate constant determined over 1.5h) gave similar and reproducible results for percent control activity. The fastest and easiest method of data analysis was determined to be that using initial rates, involving data acquisition for only 5 min once reactions have been initiated using l-ascorbic acid. The results of the study demonstrate that this simple assay based on the spectroscopic detection of heme represents a rapid, convenient method to determine the relative inhibitory activity of candidate compounds, and is useful in quickly screening a series or library of compounds for heme oxygenase inhibition

Initial deployment of the cardiogenic gene regulatory network in the basal chordate, Ciona intestinalis.

PubMed

Woznica, Arielle; Haeussler, Maximilian; Starobinska, Ella; Jemmett, Jessica; Li, Younan; Mount, David; Davidson, Brad

2012-08-01

The complex, partially redundant gene regulatory architecture underlying vertebrate heart formation has been difficult to characterize. Here, we dissect the primary cardiac gene regulatory network in the invertebrate chordate, Ciona intestinalis. The Ciona heart progenitor lineage is first specified by Fibroblast Growth Factor/Map Kinase (FGF/MapK) activation of the transcription factor Ets1/2 (Ets). Through microarray analysis of sorted heart progenitor cells, we identified the complete set of primary genes upregulated by FGF/Ets shortly after heart progenitor emergence. Combinatorial sequence analysis of these co-regulated genes generated a hypothetical regulatory code consisting of Ets binding sites associated with a specific co-motif, ATTA. Through extensive reporter analysis, we confirmed the functional importance of the ATTA co-motif in primary heart progenitor gene regulation. We then used the Ets/ATTA combination motif to successfully predict a number of additional heart progenitor gene regulatory elements, including an intronic element driving expression of the core conserved cardiac transcription factor, GATAa. This work significantly advances our understanding of the Ciona heart gene network. Furthermore, this work has begun to elucidate the precise regulatory architecture underlying the conserved, primary role of FGF/Ets in chordate heart lineage specification. Copyright © 2012 Elsevier Inc. All rights reserved.

Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

PubMed

Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

2014-12-06

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

In vivo and in vitro olefin cyclopropanation catalyzed by heme enzymes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coelho, Pedro S.; Brustad, Eric M.; Arnold, Frances H.

The present invention provides methods for catalyzing the conversion of an olefin to any compound containing one or more cyclopropane functional groups using heme enzymes. In certain aspects, the present invention provides a method for producing a cyclopropanation product comprising providing an olefinic substrate, a diazo reagent, and a heme enzyme; and admixing the components in a reaction for a time sufficient to produce a cyclopropanation product. In other aspects, the present invention provides heme enzymes including variants and fragments thereof that are capable of carrying out in vivo and in vitro olefin cyclopropanation reactions. Expression vectors and host cellsmore » expressing the heme enzymes are also provided by the present invention.« less

MiRNA and TF co-regulatory network analysis for the pathology and recurrence of myocardial infarction.

PubMed

Lin, Ying; Sibanda, Vusumuzi Leroy; Zhang, Hong-Mei; Hu, Hui; Liu, Hui; Guo, An-Yuan

2015-04-13

Myocardial infarction (MI) is a leading cause of death in the world and many genes are involved in it. Transcription factor (TFs) and microRNAs (miRNAs) are key regulators of gene expression. We hypothesized that miRNAs and TFs might play combinatory regulatory roles in MI. After collecting MI candidate genes and miRNAs from various resources, we constructed a comprehensive MI-specific miRNA-TF co-regulatory network by integrating predicted and experimentally validated TF and miRNA targets. We found some hub nodes (e.g. miR-16 and miR-26) in this network are important regulators, and the network can be severed as a bridge to interpret the associations of previous results, which is shown by the case of miR-29 in this study. We also constructed a regulatory network for MI recurrence and found several important genes (e.g. DAB2, BMP6, miR-320 and miR-103), the abnormal expressions of which may be potential regulatory mechanisms and markers of MI recurrence. At last we proposed a cellular model to discuss major TF and miRNA regulators with signaling pathways in MI. This study provides more details on gene expression regulation and regulators involved in MI progression and recurrence. It also linked up and interpreted many previous results.

Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

PubMed

Guo, Xiaobo; Zhang, Ye; Hu, Wenhao; Tan, Haizhu; Wang, Xueqin

2014-01-01

Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs). It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC) has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI)-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC) curve and the precision-recall (PR) curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

Inferring Nonlinear Gene Regulatory Networks from Gene Expression Data Based on Distance Correlation

PubMed Central

Guo, Xiaobo; Zhang, Ye; Hu, Wenhao; Tan, Haizhu; Wang, Xueqin

2014-01-01

Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs). It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC) has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI)-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC) curve and the precision-recall (PR) curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference. PMID:24551058

Heme, an Essential Nutrient from Dietary Proteins, Critically Impacts Diverse Physiological and Pathological Processes

PubMed Central

Hooda, Jagmohan; Shah, Ajit; Zhang, Li

2014-01-01

Heme constitutes 95% of functional iron in the human body, as well as two-thirds of the average person’s iron intake in developed countries. Hence, a wide range of epidemiological studies have focused on examining the association of dietary heme intake, mainly from red meat, with the risks of common diseases. High heme intake is associated with increased risk of several cancers, including colorectal cancer, pancreatic cancer and lung cancer. Likewise, the evidence for increased risks of type-2 diabetes and coronary heart disease associated with high heme intake is compelling. Furthermore, recent comparative metabolic and molecular studies of lung cancer cells showed that cancer cells require increased intracellular heme biosynthesis and uptake to meet the increased demand for oxygen-utilizing hemoproteins. Increased levels of hemoproteins in turn lead to intensified oxygen consumption and cellular energy generation, thereby fueling cancer cell progression. Together, both epidemiological and molecular studies support the idea that heme positively impacts cancer progression. However, it is also worth noting that heme deficiency can cause serious diseases in humans, such as anemia, porphyrias, and Alzheimer’s disease. This review attempts to summarize the latest literature in understanding the role of dietary heme intake and heme function in diverse diseases. PMID:24633395

The Alternative Route to Heme in the Methanogenic Archaeon Methanosarcina barkeri

PubMed Central

Haufschildt, Kristin; Neumann, Alexander; Storbeck, Sonja; Streif, Judith

2014-01-01

In living organisms heme is formed from the common precursor uroporphyrinogen III by either one of two substantially different pathways. In contrast to eukaryotes and most bacteria which employ the so-called “classical” heme biosynthesis pathway, the archaea use an alternative route. In this pathway, heme is formed from uroporphyrinogen III via the intermediates precorrin-2, sirohydrochlorin, siroheme, 12,18-didecarboxysiroheme, and iron-coproporphyrin III. In this study the heme biosynthesis proteins AhbAB, AhbC, and AhbD from Methanosarcina barkeri were functionally characterized. Using an in vivo enzyme activity assay it was shown that AhbA and AhbB (Mbar_A1459 and Mbar_A1460) together catalyze the conversion of siroheme into 12,18-didecarboxysiroheme. The two proteins form a heterodimeric complex which might be subject to feedback regulation by the pathway end-product heme. Further, AhbC (Mbar_A1793) was shown to catalyze the formation of iron-coproporphyrin III in vivo. Finally, recombinant AhbD (Mbar_A1458) was produced in E. coli and purified indicating that this protein most likely contains two [4Fe-4S] clusters. Using an in vitro enzyme activity assay it was demonstrated that AhbD catalyzes the conversion of iron-coproporphyrin III into heme. PMID:24669201

Algebraic model checking for Boolean gene regulatory networks.

PubMed

Tran, Quoc-Nam

2011-01-01

We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.

In vitro Activation of heme oxygenase-2 by menadione and its analogs.

PubMed

Vukomanovic, Dragic; Rahman, Mona N; Bilokin, Yaroslav; Golub, Andriy G; Brien, James F; Szarek, Walter A; Jia, Zongchao; Nakatsu, Kanji

2014-02-18

Previously, we reported that menadione activated rat, native heme oxygenase-2 (HO-2) and human recombinant heme oxygenase-2 selectively; it did not activate spleen, microsomal heme oxygenase-1. The purpose of this study was to explore some structure-activity relationships of this activation and the idea that redox properties may be an important aspect of menadione efficacy. Heme oxygenase activity was determined in vitro using rat spleen and brain microsomes as the sources of heme oxygenase-1 and -2, respectively, as well as recombinant, human heme oxygenase-2. Menadione analogs with bulky aliphatic groups at position-3, namely vitamins K1 and K2, were not able to activate HO-2. In contrast, several compounds with similar bulky but less lipophilic moieties at position-2 (and -3) were able to activate HO-2 many fold; these compounds included polar, rigid, furan-containing naphthoquinones, furan-benzoxazine naphthoquinones, 2-(aminophenylphenyl)-3-piperidin-1-yl naphthoquinones. To explore the idea that redox properties might be involved in menadione efficacy, we tested analogs such as 1,4-dimethoxy-2-methylnaphthalene, pentafluoromenadione, monohalogenated naphthoquinones, α-tetralone and 1,4-naphthoquinone. All of these compounds were inactive except for 1,4-naphthoquinone. Menadione activated full-length recombinant human heme oxygenase-2 (FL-hHO-2) as effectively as rat brain enzyme, but it did not activate rat spleen heme oxygenase. These observations are consistent with the idea that naphthoquinones such as menadione bind to a receptor in HO-2 and activate the enzyme through a mechanism that may involve redox properties.

Improved Method for the Incorporation of Heme Cofactors into Recombinant Proteins Using Escherichia coli Nissle 1917.

PubMed

Fiege, Kerstin; Querebillo, Christine Joy; Hildebrandt, Peter; Frankenberg-Dinkel, Nicole

2018-05-15

Recombinant production of heme proteins in Escherichia coli is often limited by the availability of heme in the host. Therefore, several methods, including the reconstitution of heme proteins after production but prior to purification or the HPEX system, conferring the ability to take up external heme have been developed and used in the past. Here we describe the use of the apathogenic E. coli strain Nissle 1917 (EcN) as a suitable host for the recombinant production of heme proteins. EcN has an advantage over commonly used lab strains in that it is able to take up heme from the environment through the heme receptor ChuA. Expression of several heme proteins from different prokaryotic sources led to high yield and quantitative incorporation of the cofactor when heme was supplied in the growth medium. Comparative UV-vis and resonance Raman measurements revealed that the method employed has significant influence on heme coordination with the EcN system representing the most native situation. Therefore, the use of EcN as a host for recombinant heme protein production represents an inexpensive and straightforward method to facilitate further investigations of structure and function.

Enhanced Heme Function and Mitochondrial Respiration Promote the Progression of Lung Cancer Cells

PubMed Central

Alam, Md Maksudul; Shah, Ajit; Cao, Thai M.; Sullivan, Laura A.; Brekken, Rolf; Zhang, Li

2013-01-01

Lung cancer is the leading cause of cancer-related mortality, and about 85% of the cases are non-small-cell lung cancer (NSCLC). Importantly, recent advance in cancer research suggests that altering cancer cell bioenergetics can provide an effective way to target such advanced cancer cells that have acquired mutations in multiple cellular regulators. This study aims to identify bioenergetic alterations in lung cancer cells by directly measuring and comparing key metabolic activities in a pair of cell lines representing normal and NSCLC cells developed from the same patient. We found that the rates of oxygen consumption and heme biosynthesis were intensified in NSCLC cells. Additionally, the NSCLC cells exhibited substantially increased levels in an array of proteins promoting heme synthesis, uptake and function. These proteins include the rate-limiting heme biosynthetic enzyme ALAS, transporter proteins HRG1 and HCP1 that are involved in heme uptake, and various types of oxygen-utilizing hemoproteins such as cytoglobin and cytochromes. Several types of human tumor xenografts also displayed increased levels of such proteins. Furthermore, we found that lowering heme biosynthesis and uptake, like lowering mitochondrial respiration, effectively reduced oxygen consumption, cancer cell proliferation, migration and colony formation. In contrast, lowering heme degradation does not have an effect on lung cancer cells. These results show that increased heme flux and function are a key feature of NSCLC cells. Further, increased generation and supply of heme and oxygen-utilizing hemoproteins in cancer cells will lead to intensified oxygen consumption and cellular energy production by mitochondrial respiration, which would fuel cancer cell proliferation and progression. The results show that inhibiting heme and respiratory function can effectively arrest the progression of lung cancer cells. Hence, understanding heme function can positively impact on research in lung cancer

Human heme oxygenase oxidation of 5- and 15-phenylhemes.

PubMed

Wang, Jinling; Niemevz, Fernando; Lad, Latesh; Huang, Liusheng; Alvarez, Diego E; Buldain, Graciela; Poulos, Thomas L; de Montellano, Paul R Ortiz

2004-10-08

Human heme oxygenase-1 (hHO-1) catalyzes the O2-dependent oxidation of heme to biliverdin, CO, and free iron. Previous work indicated that electrophilic addition of the terminal oxygen of the ferric hydroperoxo complex to the alpha-meso-carbon gives 5-hydroxyheme. Earlier efforts to block this reaction with a 5-methyl substituent failed, as the reaction still gave biliverdin IXalpha. Surprisingly, a 15-methyl substituent caused exclusive cleavage at the gamma-meso-rather than at the normal, unsubstituted alpha-meso-carbon. No CO was formed in these reactions, but the fragment cleaved from the porphyrin eluded identification. We report here that hHO-1 cleaves 5-phenylheme to biliverdin IXalpha and oxidizes 15-phenylheme at the alpha-meso position to give 10-phenylbiliverdin IXalpha. The fragment extruded in the oxidation of 5-phenylheme is benzoic acid, one oxygen of which comes from O2 and the other from water. The 2.29- and 2.11-A crystal structures of the hHO-1 complexes with 1- and 15-phenylheme, respectively, show clear electron density for both the 5- and 15-phenyl rings in both molecules of the asymmetric unit. The overall structure of 15-phenylheme-hHO-1 is similar to that of heme-hHO-1 except for small changes in distal residues 141-150 and in the proximal Lys18 and Lys22. In the 5-phenylheme-hHO-1 structure, the phenyl-substituted heme occupies the same position as heme in the heme-HO-1 complex but the 5-phenyl substituent disrupts the rigid hydrophobic wall of residues Met34, Phe214, and residues 26-42 near the alpha-meso carbon. The results provide independent support for an electrophilic oxidation mechanism and support a role for stereochemical control of the reaction regiospecificity.

Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

USDA-ARS?s Scientific Manuscript database

Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

Insights on how the Mycobacterium tuberculosis heme uptake pathway can be used as a drug target

PubMed Central

Owens, Cedric P; Chim, Nicholas; Goulding, Celia W

2013-01-01

Mycobacterium tuberculosis (Mtb) acquires non-heme iron through salicylate-derived siderophores termed mycobactins whereas heme iron is obtained through a cascade of heme uptake proteins. Three proteins are proposed to mediate Mtb heme iron uptake, a secreted heme transporter (Rv0203), and MmpL3 and MmpL11, which are potential transmembrane heme transfer proteins. Furthermore, MhuD, a cytoplasmic heme-degrading enzyme, has been identified. Rv0203, MmpL3 and MmpL11 are mycobacteria-specific proteins, making them excellent drug targets. Importantly, MmpL3, a necessary protein, has also been implicated in trehalose monomycolate export. Recent drug-discovery efforts revealed that MmpL3 is the target of several compounds with antimycobacterial activity. Inhibition of the Mtb heme uptake pathway has yet to be explored. We propose that inhibitor design could focus on heme analogs, with the goal of blocking specific steps of this pathway. In addition, heme uptake could be hijacked as a method of importing drugs into the mycobacterial cytosol. PMID:23919550

Understanding regulatory networks requires more than computing a multitude of graph statistics. Comment on "Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function" by O.C. Martin et al.

NASA Astrophysics Data System (ADS)

Tkačik, Gašper

2016-07-01

The article by O. Martin and colleagues provides a much needed systematic review of a body of work that relates the topological structure of genetic regulatory networks to evolutionary selection for function. This connection is very important. Using the current wealth of genomic data, statistical features of regulatory networks (e.g., degree distributions, motif composition, etc.) can be quantified rather easily; it is, however, often unclear how to interpret the results. On a graph theoretic level the statistical significance of the results can be evaluated by comparing observed graphs to ;randomized; ones (bravely ignoring the issue of how precisely to randomize!) and comparing the frequency of appearance of a particular network structure relative to a randomized null expectation. While this is a convenient operational test for statistical significance, its biological meaning is questionable. In contrast, an in-silico genotype-to-phenotype model makes explicit the assumptions about the network function, and thus clearly defines the expected network structures that can be compared to the case of no selection for function and, ultimately, to data.

A Functionally Conserved Gene Regulatory Network Module Governing Olfactory Neuron Diversity.

PubMed

Li, Qingyun; Barish, Scott; Okuwa, Sumie; Maciejewski, Abigail; Brandt, Alicia T; Reinhold, Dominik; Jones, Corbin D; Volkan, Pelin Cayirlioglu

2016-01-01

Sensory neuron diversity is required for organisms to decipher complex environmental cues. In Drosophila, the olfactory environment is detected by 50 different olfactory receptor neuron (ORN) classes that are clustered in combinations within distinct sensilla subtypes. Each sensilla subtype houses stereotypically clustered 1-4 ORN identities that arise through asymmetric divisions from a single multipotent sensory organ precursor (SOP). How each class of SOPs acquires a unique differentiation potential that accounts for ORN diversity is unknown. Previously, we reported a critical component of SOP diversification program, Rotund (Rn), increases ORN diversity by generating novel developmental trajectories from existing precursors within each independent sensilla type lineages. Here, we show that Rn, along with BarH1/H2 (Bar), Bric-à-brac (Bab), Apterous (Ap) and Dachshund (Dac), constitutes a transcription factor (TF) network that patterns the developing olfactory tissue. This network was previously shown to pattern the segmentation of the leg, which suggests that this network is functionally conserved. In antennal imaginal discs, precursors with diverse ORN differentiation potentials are selected from concentric rings defined by unique combinations of these TFs along the proximodistal axis of the developing antennal disc. The combinatorial code that demarcates each precursor field is set up by cross-regulatory interactions among different factors within the network. Modifications of this network lead to predictable changes in the diversity of sensilla subtypes and ORN pools. In light of our data, we propose a molecular map that defines each unique SOP fate. Our results highlight the importance of the early prepatterning gene regulatory network as a modulator of SOP and terminally differentiated ORN diversity. Finally, our model illustrates how conserved developmental strategies are used to generate neuronal diversity.

Possible Dynamically Gated Conductance along Heme Wires in Bacterial Multiheme Cytochromes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Dayle MA; Rosso, Kevin M.

2014-07-24

The staggered cross decaheme configuration of electron transfer co-factors in the outer-membrane cytochrome MtrF may serve as a prototype for conformationally-gated multi-heme electron transport. Derived from the bacterium Shewanella oneidensis, the staggered cross configuration reveals intersecting c-type octaheme and tetraheme “wires” containing thermodynamic “hills” and “valleys”, suggesting that the protein structure may include a dynamical mechanism for conductance and pathway switching depending on enzymatic functional need. Recent molecular simulations have established the pair-wise electronic couplings, redox potentials, and reorganization energies to predict the maximum conductance along the various heme wire pathways by sequential hopping of a single electron (PNAS (2014)more » 11,611-616). Here, we expand this information with classical molecular and statistical mechanics calculations of large-amplitude protein dynamics in MtrF, to address its potential to modulate pathway conductance, including assessment of the effect of the total charge state. Explicit solvent molecular dynamics simulations of fully oxidized and fully reduced MtrF employing ten independent 50-ns simulations at 300 K and 1 atm showed that reduced MtrF is more expanded and explores more conformational space than oxidized MtrF, and that heme reduction leads to increased heme solvent exposure. The slowest mode of collective decaheme motion is 90% similar between the oxidized and reduced states, and consists primarily of inter-heme separation with minor rotational contributions. The frequency of this motion is 1.7×107 s 1 for fully-oxidized and fully-reduced MtrF, respectively, slower than the downhill electron transfer rates between stacked heme pairs at the octaheme termini and faster than the electron transfer rates between parallel hemes in the tetraheme chain. This implies that MtrF uses slow conformational fluctuations to modulate electron flow along the octaheme

Cysteine-independent activation/inhibition of heme oxygenase-2

PubMed Central

Vukomanovic, Dragic; Rahman, Mona N.; Maines, Mahin D.; Ozolinš, Terence RS; Szarek, Walter A.; Jia, Zongchao; Nakatsu, Kanji

2016-01-01

Reactive thiols of cysteine (cys) residues in proteins play a key role in transforming chemical reactivity into a biological response. The heme oxygenase-2 (HO-2) isozyme contains two cys residues that have been implicated in binding of heme and also the regulation of its activity. In this paper, we address the question of a role for cys residues for the HO-2 inhibitors or activators designed in our laboratory. We tested the activity of full length recombinant human heme oxygenase-2 (FL-hHO-2) and its analog in which cys265 and cys282 were both replaced by alanine to determine the effect on activation by menadione (MD) and inhibition by QC-2350. Similar inhibition by QC-2350 and almost identical activation by MD was observed for both recombinant FL-hHO-2s. Our findings are interpreted to mean that thiols of FL-hHO-2s are not involved in HO-2 activation or inhibition by the compounds that have been designed and identified by us. Activation or inhibition of HO-2 by our compounds should be attributed to a mechanism other than altering binding affinity of HO-2 for heme through cys265 and cys282. PMID:27826418

Cysteine-independent activation/inhibition of heme oxygenase-2.

PubMed

Vukomanovic, Dragic; Rahman, Mona N; Maines, Mahin D; Ozolinš, Terence Rs; Szarek, Walter A; Jia, Zongchao; Nakatsu, Kanji

2016-03-01

Reactive thiols of cysteine (cys) residues in proteins play a key role in transforming chemical reactivity into a biological response. The heme oxygenase-2 (HO-2) isozyme contains two cys residues that have been implicated in binding of heme and also the regulation of its activity. In this paper, we address the question of a role for cys residues for the HO-2 inhibitors or activators designed in our laboratory. We tested the activity of full length recombinant human heme oxygenase-2 (FL-hHO-2) and its analog in which cys265 and cys282 were both replaced by alanine to determine the effect on activation by menadione (MD) and inhibition by QC-2350. Similar inhibition by QC-2350 and almost identical activation by MD was observed for both recombinant FL-hHO-2s. Our findings are interpreted to mean that thiols of FL-hHO-2s are not involved in HO-2 activation or inhibition by the compounds that have been designed and identified by us. Activation or inhibition of HO-2 by our compounds should be attributed to a mechanism other than altering binding affinity of HO-2 for heme through cys265 and cys282.

Comparison of the Heme Iron Utilization Systems of Pathogenic Vibrios

PubMed Central

O’Malley, S. M.; Mouton, S. L.; Occhino, D. A.; Deanda, M. T.; Rashidi, J. R.; Fuson, K. L.; Rashidi, C. E.; Mora, M. Y.; Payne, S. M.; Henderson, D. P.

1999-01-01

Vibrio alginolyticus, Vibrio fluvialis, and Vibrio parahaemolyticus utilized heme and hemoglobin as iron sources and contained chromosomal DNA similar to several Vibrio cholerae heme iron utilization genes. A V. parahaemolyticus gene that performed the function of V. cholerae hutA was isolated. A portion of the tonB1 locus of V. parahaemolyticus was sequenced and found to encode proteins similar in amino acid sequence to V. cholerae HutW, TonB1, and ExbB1. A recombinant plasmid containing the V. cholerae tonB1 and exbB1D1 genes complemented a V. alginolyticus heme utilization mutant. These data suggest that the heme iron utilization systems of the pathogenic vibrios tested, particularly V. parahaemolyticus and V. alginolyticus, are similar at the DNA level, the functional level, and, in the case of V. parahaemolyticus, the amino acid sequence or protein level to that of V. cholerae. PMID:10348876

Heme impairs the ball-and-chain inactivation of potassium channels.

PubMed

Sahoo, Nirakar; Goradia, Nishit; Ohlenschläger, Oliver; Schönherr, Roland; Friedrich, Manfred; Plass, Winfried; Kappl, Reinhard; Hoshi, Toshinori; Heinemann, Stefan H

2013-10-15

Fine-tuned regulation of K(+) channel inactivation enables excitable cells to adjust action potential firing. Fast inactivation present in some K(+) channels is mediated by the distal N-terminal structure (ball) occluding the ion permeation pathway. Here we show that Kv1.4 K(+) channels are potently regulated by intracellular free heme; heme binds to the N-terminal inactivation domain and thereby impairs the inactivation process, thus enhancing the K(+) current with an apparent EC50 value of ∼20 nM. Functional studies on channel mutants and structural investigations on recombinant inactivation ball domain peptides encompassing the first 61 residues of Kv1.4 revealed a heme-responsive binding motif involving Cys13:His16 and a secondary histidine at position 35. Heme binding to the N-terminal inactivation domain induces a conformational constraint that prevents it from reaching its receptor site at the vestibule of the channel pore.

Insights into the etiology-associated gene regulatory networks in hepatocellular carcinoma from The Cancer Genome Atlas.

PubMed

Seshachalam, Veerabrahma Pratap; Sekar, Karthik; Hui, Kam M

2018-04-19

Hepatitis B virus, hepatitis C virus, alcoholic consumption and non-alcoholic fatty liver are the major known risk factors for Hepatocellular carcinoma (HCC). There have been very few studies comparing the underlying biological mechanisms associated with the different etiologies of HCC. In this study, we hypothesized the existence of different regulatory networks associated with different liver disease etiologies involved in hepatocarcinogenesis. Using upstream regulatory analysis tool in ingenuity pathway analysis software, URs were predicted using differential expressed genes for HCC to facilitate the interrogation of global gene regulation. Analysis of regulatory networks for HBV HCC revealed E2F1 as activated UR, regulating genes involved in cell cycle and DNA replication and HNF4A and HNF1A as inhibited UR. In HCV HCC, IFNG, involved in cellular movement and signaling was activated while IL1RN, MAPK1 involved in IL-22 signaling and immune response was inhibited. In Alcoholic-consumption HCC, ERBB2 involved in inflammatory response and cellular movement was activated, whereas HNF4A, NUPR1 were inhibited. For HCC derived from Non-alcoholic fatty liver disease, miR-1249-5p was activated and NUPR1 involved in cell cycle and apoptosis was inhibited. The prognostic value of representative genes identified in the regulatory networks for HBV HCC can be further validated by an independent HBV HCC dataset established in our laboratory with survival data. Our study identified functionally distinct candidate URs for HCC developed from different etiologic risk factors. Further functional validation studies of these regulatory networks could facilitate the management of HCC towards personalized medicine. This article is protected by copyright. All rights reserved.

Oxidative stability of a heme iron-fortified bakery product: Effectiveness of ascorbyl palmitate and co-spray-drying of heme iron with calcium caseinate.

PubMed

Alemán, Mercedes; Bou, Ricard; Tres, Alba; Polo, Javier; Codony, Rafael; Guardiola, Francesc

2016-04-01

Fortification of food products with iron is a common strategy to prevent or overcome iron deficiency. However, any form of iron is a pro-oxidant and its addition will cause off-flavours and reduce a product's shelf life. A highly bioavailable heme iron ingredient was selected to fortify a chocolate cream used to fill sandwich-type cookies. Two different strategies were assessed for avoiding the heme iron catalytic effect on lipid oxidation: ascorbyl palmitate addition and co-spray-drying of heme iron with calcium caseinate. Oxidation development and sensory acceptability were monitored in the cookies over one-year of storage at room temperature in the dark. The addition of ascorbyl palmitate provided protection against oxidation and loss of tocopherols and tocotrienols during the preparation of cookies. In general, ascorbyl palmitate, either alone or in combination with the co-spray-dried heme iron, prevented primary oxidation and hexanal formation during storage. The combination of both strategies resulted in cookies that were acceptable from a sensory point of view after 1year of storage. Copyright © 2015 Elsevier Ltd. All rights reserved.

cGRNB: a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets.

PubMed

Xu, Huayong; Yu, Hui; Tu, Kang; Shi, Qianqian; Wei, Chaochun; Li, Yuan-Yuan; Li, Yi-Xue

2013-01-01

We are witnessing rapid progress in the development of methodologies for building the combinatorial gene regulatory networks involving both TFs (Transcription Factors) and miRNAs (microRNAs). There are a few tools available to do these jobs but most of them are not easy to use and not accessible online. A web server is especially needed in order to allow users to upload experimental expression datasets and build combinatorial regulatory networks corresponding to their particular contexts. In this work, we compiled putative TF-gene, miRNA-gene and TF-miRNA regulatory relationships from forward-engineering pipelines and curated them as built-in data libraries. We streamlined the R codes of our two separate forward-and-reverse engineering algorithms for combinatorial gene regulatory network construction and formalized them as two major functional modules. As a result, we released the cGRNB (combinatorial Gene Regulatory Networks Builder): a web server for constructing combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. The cGRNB enables two major network-building modules, one for MPGE (miRNA-perturbed gene expression) datasets and the other for parallel miRNA/mRNA expression datasets. A miRNA-centered two-layer combinatorial regulatory cascade is the output of the first module and a comprehensive genome-wide network involving all three types of combinatorial regulations (TF-gene, TF-miRNA, and miRNA-gene) are the output of the second module. In this article we propose cGRNB, a web server for building combinatorial gene regulatory networks through integrated engineering of seed-matching sequence information and gene expression datasets. Since parallel miRNA/mRNA expression datasets are rapidly accumulated by the advance of next-generation sequencing techniques, cGRNB will be very useful tool for researchers to build combinatorial gene regulatory networks based on expression datasets

Genexpi: a toolset for identifying regulons and validating gene regulatory networks using time-course expression data.

PubMed

Modrák, Martin; Vohradský, Jiří

2018-04-13

Identifying regulons of sigma factors is a vital subtask of gene network inference. Integrating multiple sources of data is essential for correct identification of regulons and complete gene regulatory networks. Time series of expression data measured with microarrays or RNA-seq combined with static binding experiments (e.g., ChIP-seq) or literature mining may be used for inference of sigma factor regulatory networks. We introduce Genexpi: a tool to identify sigma factors by combining candidates obtained from ChIP experiments or literature mining with time-course gene expression data. While Genexpi can be used to infer other types of regulatory interactions, it was designed and validated on real biological data from bacterial regulons. In this paper, we put primary focus on CyGenexpi: a plugin integrating Genexpi with the Cytoscape software for ease of use. As a part of this effort, a plugin for handling time series data in Cytoscape called CyDataseries has been developed and made available. Genexpi is also available as a standalone command line tool and an R package. Genexpi is a useful part of gene network inference toolbox. It provides meaningful information about the composition of regulons and delivers biologically interpretable results.

Regulatory gene networks that shape the development of adaptive phenotypic plasticity in a cichlid fish.

PubMed

Schneider, Ralf F; Li, Yuanhao; Meyer, Axel; Gunter, Helen M

2014-09-01

Phenotypic plasticity is the ability of organisms with a given genotype to develop different phenotypes according to environmental stimuli, resulting in individuals that are better adapted to local conditions. In spite of their ecological importance, the developmental regulatory networks underlying plastic phenotypes often remain uncharacterized. We examined the regulatory basis of diet-induced plasticity in the lower pharyngeal jaw (LPJ) of the cichlid fish Astatoreochromis alluaudi, a model species in the study of adaptive plasticity. Through raising juvenile A. alluaudi on either a hard or soft diet (hard-shelled or pulverized snails) for between 1 and 8 months, we gained insight into the temporal regulation of 19 previously identified candidate genes during the early stages of plasticity development. Plasticity in LPJ morphology was first detected between 3 and 5 months of diet treatment. The candidate genes, belonging to various functional categories, displayed dynamic expression patterns that consistently preceded the onset of morphological divergence and putatively contribute to the initiation of the plastic phenotypes. Within functional categories, we observed striking co-expression, and transcription factor binding site analysis was used to examine the prospective basis of their coregulation. We propose a regulatory network of LPJ plasticity in cichlids, presenting evidence for regulatory crosstalk between bone and muscle tissues, which putatively facilitates the development of this highly integrated trait. Through incorporating a developmental time-course into a phenotypic plasticity study, we have identified an interconnected, environmentally responsive regulatory network that shapes the development of plasticity in a key innovation of East African cichlids. © 2014 John Wiley & Sons Ltd.

Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration

PubMed Central

Lobo, Daniel; Levin, Michael

2015-01-01

Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method provides an automated

Circulating cell membrane microparticles transfer heme to endothelial cells and trigger vasoocclusions in sickle cell disease.

PubMed

Camus, Stéphane M; De Moraes, João A; Bonnin, Philippe; Abbyad, Paul; Le Jeune, Sylvain; Lionnet, François; Loufrani, Laurent; Grimaud, Linda; Lambry, Jean-Christophe; Charue, Dominique; Kiger, Laurent; Renard, Jean-Marie; Larroque, Claire; Le Clésiau, Hervé; Tedgui, Alain; Bruneval, Patrick; Barja-Fidalgo, Christina; Alexandrou, Antigoni; Tharaux, Pierre-Louis; Boulanger, Chantal M; Blanc-Brude, Olivier P

2015-06-11

Intravascular hemolysis describes the relocalization of heme and hemoglobin (Hb) from erythrocytes to plasma. We investigated the concept that erythrocyte membrane microparticles (MPs) concentrate cell-free heme in human hemolytic diseases, and that heme-laden MPs have a physiopathological impact. Up to one-third of cell-free heme in plasma from 47 patients with sickle cell disease (SCD) was sequestered in circulating MPs. Erythrocyte vesiculation in vitro produced MPs loaded with heme. In silico analysis predicted that externalized phosphatidylserine (PS) in MPs may associate with and help retain heme at the cell surface. Immunohistology identified Hb-laden MPs adherent to capillary endothelium in kidney biopsies from hyperalbuminuric SCD patients. In addition, heme-laden erythrocyte MPs adhered and transferred heme to cultured endothelial cells, inducing oxidative stress and apoptosis. In transgenic SAD mice, infusion of heme-laden MPs triggered rapid vasoocclusions in kidneys and compromised microvascular dilation ex vivo. These vascular effects were largely blocked by heme-scavenging hemopexin and by the PS antagonist annexin-a5, in vitro and in vivo. Adversely remodeled MPs carrying heme may thus be a source of oxidant stress for the endothelium, linking hemolysis to vascular injury. This pathway might provide new targets for the therapeutic preservation of vascular function in SCD. © 2015 by The American Society of Hematology.

Receptors rather than signals change in expression in four physiological regulatory networks during evolutionary divergence in threespine stickleback.

PubMed

Di Poi, Carole; Bélanger, Dominic; Amyot, Marc; Rogers, Sean; Aubin-Horth, Nadia

2016-07-01

The molecular mechanisms underlying behavioural evolution following colonization of novel environments are largely unknown. Molecules that interact to control equilibrium within an organism form physiological regulatory networks. It is essential to determine whether particular components of physiological regulatory networks evolve or if the network as a whole is affected in populations diverging in behavioural responses, as this may affect the nature, amplitude and number of impacted traits. We studied the regulation of four physiological regulatory networks in freshwater and marine populations of threespine stickleback raised in a common environment, which were previously characterized as showing evolutionary divergence in behaviour and stress reactivity. We measured nineteen components of these networks (ligands and receptors) using mRNA and monoamine levels in the brain, pituitary and interrenal gland, as well as hormone levels. Freshwater fish showed higher expression in the brain of adrenergic (adrb2a), serotonergic (htr2a) and dopaminergic (DRD2) receptors, but lower expression of the htr2b receptor. Freshwater fish also showed higher expression of the mc2r receptor of the glucocorticoid axis in the interrenals. Collectively, our results suggest that the inheritance of the regulation of these networks may be implicated in the evolution of behaviour and stress reactivity in association with population divergence. Our results also suggest that evolutionary change in freshwater threespine stickleback may be more associated with the expression of specific receptors rather than with global changes of all the measured constituents of the physiological regulatory networks. © 2016 John Wiley & Sons Ltd.

An integrated approach to characterize transcription factor and microRNA regulatory networks involved in Schwann cell response to peripheral nerve injury

PubMed Central

2013-01-01

Background The regenerative response of Schwann cells after peripheral nerve injury is a critical process directly related to the pathophysiology of a number of neurodegenerative diseases. This SC injury response is dependent on an intricate gene regulatory program coordinated by a number of transcription factors and microRNAs, but the interactions among them remain largely unknown. Uncovering the transcriptional and post-transcriptional regulatory networks governing the Schwann cell injury response is a key step towards a better understanding of Schwann cell biology and may help develop novel therapies for related diseases. Performing such comprehensive network analysis requires systematic bioinformatics methods to integrate multiple genomic datasets. Results In this study we present a computational pipeline to infer transcription factor and microRNA regulatory networks. Our approach combined mRNA and microRNA expression profiling data, ChIP-Seq data of transcription factors, and computational transcription factor and microRNA target prediction. Using mRNA and microRNA expression data collected in a Schwann cell injury model, we constructed a regulatory network and studied regulatory pathways involved in Schwann cell response to injury. Furthermore, we analyzed network motifs and obtained insights on cooperative regulation of transcription factors and microRNAs in Schwann cell injury recovery. Conclusions This work demonstrates a systematic method for gene regulatory network inference that may be used to gain new information on gene regulation by transcription factors and microRNAs. PMID:23387820

In vitro Activation of heme oxygenase-2 by menadione and its analogs

PubMed Central

2014-01-01

Background Previously, we reported that menadione activated rat, native heme oxygenase-2 (HO-2) and human recombinant heme oxygenase-2 selectively; it did not activate spleen, microsomal heme oxygenase-1. The purpose of this study was to explore some structure–activity relationships of this activation and the idea that redox properties may be an important aspect of menadione efficacy. Methods Heme oxygenase activity was determined in vitro using rat spleen and brain microsomes as the sources of heme oxygenase-1 and −2, respectively, as well as recombinant, human heme oxygenase-2. Results Menadione analogs with bulky aliphatic groups at position-3, namely vitamins K1 and K2, were not able to activate HO-2. In contrast, several compounds with similar bulky but less lipophilic moieties at position-2 (and −3) were able to activate HO-2 many fold; these compounds included polar, rigid, furan-containing naphthoquinones, furan-benzoxazine naphthoquinones, 2-(aminophenylphenyl)-3-piperidin-1-yl naphthoquinones. To explore the idea that redox properties might be involved in menadione efficacy, we tested analogs such as 1,4-dimethoxy-2-methylnaphthalene, pentafluoromenadione, monohalogenated naphthoquinones, α-tetralone and 1,4-naphthoquinone. All of these compounds were inactive except for 1,4-naphthoquinone. Menadione activated full-length recombinant human heme oxygenase-2 (FL-hHO-2) as effectively as rat brain enzyme, but it did not activate rat spleen heme oxygenase. Conclusions These observations are consistent with the idea that naphthoquinones such as menadione bind to a receptor in HO-2 and activate the enzyme through a mechanism that may involve redox properties. PMID:24533775

A Heme-based Redox Sensor in the Methanogenic Archaeon Methanosarcina acetivorans*

PubMed Central

Molitor, Bastian; Stassen, Marc; Modi, Anuja; El-Mashtoly, Samir F.; Laurich, Christoph; Lubitz, Wolfgang; Dawson, John H.; Rother, Michael; Frankenberg-Dinkel, Nicole

2013-01-01