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[
BMC Bioinformatics,
2010]
BACKGROUND: Graph drawing is one of the important techniques for understanding biological regulations in a cell or among cells at the pathway level. Among many available layout algorithms, the spring embedder algorithm is widely used not only for pathway drawing but also for circuit placement and www visualization and so on because of the harmonized appearance of its results. For pathway drawing, location information is essential for its comprehension. However, complex shapes need to be taken into account when torus-shaped location information such as nuclear inner membrane, nuclear outer membrane, and plasma membrane is considered. Unfortunately, the spring embedder algorithm cannot easily handle such information. In addition, crossings between edges and nodes are usually not considered explicitly. RESULTS: We proposed a new grid-layout algorithm based on the spring embedder algorithm that can handle location information and provide layouts with harmonized appearance. In grid-layout algorithms, the mapping of nodes to grid points that minimizes a cost function is searched. By imposing positional constraints on grid points, location information including complex shapes can be easily considered. Our layout algorithm includes the spring embedder cost as a component of the cost function. We further extend the layout algorithm to enable dynamic update of the positions and sizes of compartments at each step. CONCLUSIONS: The new spring embedder-based grid-layout algorithm and a spring embedder algorithm are applied to three biological pathways; endothelial cell model, Fas-induced apoptosis model, and C. elegans cell fate simulation model. From the positional constraints, all the results of our algorithm satisfy location information, and hence, more comprehensible layouts are obtained as compared to the spring embedder algorithm. From the comparison of the number of crossings, the results of the grid-layout-based algorithm tend to contain more crossings than those of the spring embedder algorithm due to the positional constraints. For a fair comparison, we also apply our proposed method without positional constraints. This comparison shows that these results contain less crossings than those of the spring embedder algorithm. We also compared layouts of the proposed algorithm with and without compartment update and verified that latter can reach better local optima.
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[
J Biol Chem,
2007]
The biological methyl donor, S adenosylmethionine (AdoMet), can exist in two diastereoisomeric states with respect to its sulfonium ion. The "S" configuration, (S,S)AdoMet, is the only form that is produced enzymatically as well as the only form used in almost all biological methylation reactions. Under physiological conditions, however, the sulfonium ion can spontaneously racemize to the "R" form, producing (R,S)AdoMet. As of yet, (R,S)AdoMet has no known physiological function and may inhibit cellular reactions. In this study, two enzymes have been found in Saccharomyces cerevisiae that are capable of recognizing (R,S)AdoMet and using it to methylate homocysteine to form methionine. These enzymes are the products of the SAM4 and MHT1 genes, previously identified as homocysteine methyltransferases dependent upon AdoMet and S-methylmethionine respectively. We find here that Sam4 recognizes both (S,S) and (R,S)AdoMet, but its activity is much higher with the R,S form. Mht1 reacts with only the R,S form of AdoMet while no activity is seen with the S,S form. R,S-specific homocysteine methyltransferase activity is also shown here to occur in extracts of Arabidopsis thaliana, Drosophila melanogaster, and Caenorhabditis elegans, but has not been detected in several tissue extracts of Mus musculus. Such activity may function to prevent the accumulation of (R,S)AdoMet in these organisms.
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[
In Silico Biol,
2007]
With the rapidly accumulating knowledge of biological entities and networks, there is a growing need for a general framework to understand this information at a system level. In order to understand life as system, a formal description of system dynamics with semantic validation will be necessary. Within the context of biological pathways, several formats have been proposed, e.g., SBML, CellML, and BioPAX. Unfortunately, these formats lack the formal definitions of each term or fail to capture the system dynamics behavior. Thus, we have developed a new system dynamics centered ontology called Cell System Ontology (CSO). As an exchange format, the ontology is implemented in the Web Ontology Language (OWL), which enables semantic validation and automatic reasoning to check the consistency of biological pathway models. The features of CSO are as follows: (1) manipulation of different levels of granularity and abstraction of pathways, e.g., metabolic pathways, regulatory pathways, signal transduction pathways, and cell-cell interactions; (2) capture of both quantitative and qualitative aspects of biological function by using hybrid functional Petri net with extension (HFPNe); and (3) encoding of biological pathway data related to visualization and simulation, as well as modeling. The new ontology also predefines mature core vocabulary, which will be necessary for creating models with system dynamics. In addition, each of the core terms has at least one standard icon for easy modeling and accelerating the exchangeability among applications. In order to demonstrate the potential of CSO-based pathway modeling, visualization, and simulation, we present an HFPNe model for the ASEL and ASER regulatory networks in Caenorhabditis elegans.
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Lou Y, Haque A, Freyzon Y, Farese RV, Terry-Kantor E, Hofbauer HF, Termine D, Welte MA, Barrasa MI, Imberdis T, Noble T, Lindquist S, Clish CB, Jaenisch R, Pincus D, Nuber S, Sandoe J, Kohlwein SD, Kim TE, Ho GPH, Ramalingam N, Walther TC, Baru V, Selkoe D, Srinivasan S, Landgraf D, Soldner F, Dettmer U, Fanning S, Becuwe M, Newby G
[
Mol Cell,
2018]
In Parkinson's disease (PD), -synuclein (S) pathologically impacts the brain, a highly lipid-rich organ. We investigated how alterations in S or lipid/fattyacid homeostasis affect each other. Lipidomic profiling of human S-expressing yeast revealed increases in oleic acid (OA, 18:1), diglycerides, and triglycerides. These findings were recapitulated in rodent and human neuronal models of S dyshomeostasis (overexpression; patient-derived triplication or E46K mutation; E46K mice). Preventing lipid droplet formation or augmenting OA increased S yeast toxicity; suppressing the OA-generating enzyme stearoyl-CoA-desaturase (SCD) was protective. Genetic or pharmacological SCD inhibition ameliorated toxicity in S-overexpressing rat neurons. In a C.elegans model, SCD knockout prevented S-induced dopaminergic degeneration. Conversely, we observed detrimental effects of OA on S homeostasis: in human neural cells, excess OA caused S inclusion formation, which was reversed by SCD inhibition. Thus, monounsaturated fatty acid metabolism is pivotal for S-induced neurotoxicity, and inhibiting SCD represents a novel PD therapeutic approach.
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[
Mol Biosyst,
2011]
Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.
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[
PLoS One,
2017]
In this paper, the metabolic activity in single and dual species biofilms of Staphylococcus epidermidis and Staphylococcus aureus isolates was investigated. Our results demonstrated that there was less metabolic activity in dual species biofilms compared to S. aureus biofilms. However, this was not observed if S. aureus and S. epidermidis were obtained from the same sample. The largest effect on metabolic activity was observed in biofilms of S. aureus Mu50 and S. epidermidis ET-024. A transcriptomic analysis of these dual species biofilms showed that urease genes and genes encoding proteins involved in metabolism were downregulated in comparison to monospecies biofilms. These results were subsequently confirmed by phenotypic assays. As metabolic activity is related to acid production, the pH in dual species biofilms was slightly higher compared to S. aureus Mu50 biofilms. Our results showed that S. epidermidis ET-024 in dual species biofilms inhibits metabolic activity of S. aureus Mu50, leading to less acid production. As a consequence, less urease activity is required to compensate for low pH. Importantly, this effect was biofilm-specific. Also S. aureus Mu50 genes encoding virulence-associated proteins (Spa, SplF and Dps) were upregulated in dual species biofilms compared to monospecies biofilms and using Caenorhabditis elegans infection assays, we demonstrated that more nematodes survived when co-infected with S. epidermidis ET-024 and S. aureus mutants lacking functional spa, splF or dps genes, compared to nematodes infected with S. epidermidis ET-024 and wild- type S. aureus. Finally, S. epidermidis ET-024 genes encoding resistance to oxacillin, erythromycin and tobramycin were upregulated in dual species biofilms and increased resistance was subsequently confirmed. Our data indicate that both species in dual species biofilms of S. epidermidis and S. aureus influence each other's behavior, but additional studies are required necessary to elucidate the exact mechanism(s) involved.
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[
BMC Syst Biol,
2009]
BACKGROUND: Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. RESULTS: A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules - Rule I and Rule II - to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I that cannot be applied with qualitative based model checking, is more reasonable than Rule II owing to the high coverage of predicted fate patterns (except for the genotype of
lin-15ko;
lin-12ko double mutants). More insights are also suggested. CONCLUSION: The quantitative simulation-based model checking approach is a useful means to provide us valuable biological insights and better understandings of biological systems and observation data that may be hard to capture with the qualitative one.
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[
Pathog Dis,
2014]
Due to the resistance of Staphylococcus aureus to several antibiotics, treatment of S. aureus infections is often difficult. As an alternative to conventional antibiotics, the field of bacterial interference is investigated. Staphylococcus epidermidis produces a serine protease (Esp) which inhibits S. aureus biofilm formation and which degrades S. aureus biofilms. In this study, we investigated the protease production of 114 S. epidermidis isolates, obtained from biofilms on endotracheal tubes (ET). Most of the S. epidermidis isolates secreted a mixture of serine, cysteine and metalloproteases. We found a link between high protease production by S. epidermidis and the absence of S. aureus in ET biofilms obtained from the same patient. Treating S. aureus biofilms with the supernatant (SN) of the most active protease producing S. epidermidis isolates resulted in a significant biomass decrease compared to untreated controls, while the number of metabolically active cells was not affected. The effect on the biofilm biomass was mainly due to serine proteases. Staphylococcus aureus biofilms treated with the SN of protease producing S. epidermidis were thinner with almost no extracellular matrix. An increased survival of Caenorhabditis elegans, infected with S. aureus Mu50, was observed when the SN of protease positive S. epidermidis was added.
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Haass C, Hegermann J, Giese A, Eimer S, Kamp F, Lutz AK, Nuscher B, Wender N, Brunner B, Winklhofer KF, Exner N, Beyer K, Bartels T
[
EMBO J,
2010]
Aggregation of -synuclein (S) is involved in the pathogenesis of Parkinson's disease (PD) and a variety of related neurodegenerative disorders. The physiological function of S is largely unknown. We demonstrate with in vitro vesicle fusion experiments that S has an inhibitory function on membrane fusion. Upon increased expression in cultured cells and in Caenorhabditis elegans, S binds to mitochondria and leads to mitochondrial fragmentation. In C. elegans age-dependent fragmentation of mitochondria is enhanced and shifted to an earlier time point upon expression of exogenous S. In contrast, siRNA-mediated downregulation of S results in elongated mitochondria in cell culture. S can act independently of mitochondrial fusion and fission proteins in shifting the dynamic morphologic equilibrium of mitochondria towards reduced fusion. Upon cellular fusion, S prevents fusion of differently labelled mitochondrial populations. Thus, S inhibits fusion due to its unique membrane interaction. Finally, mitochondrial fragmentation induced by expression of S is rescued by coexpression of PINK1, parkin or DJ-1 but not the PD-associated mutations PINK1 G309D and parkin 1-79 or by DJ-1 C106A.
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[
Mol Cell Biol,
1997]
The cDNAs and genes encoding the intron lariat-debranching enzyme were isolated from the nematode Caenorhabditis elegans and the fission yeast Schizosaccharomyces pombe based on their homology with the Saccharomyces cerevisiae gene. The cDNAs were shown to be functional in an interspecific complementation experiment; they can complement an S. cerevisiae
dbr1 null mutant. About 2.5% of budding yeast S. cerevisiae genes have introns, and the accumulation of excised introns in a
dbr1 null mutant has little effect on cell growth. In contrast, many S. pombe genes contain introns, and often multiple introns per gene, so that S. pombe is estimated to contain approximately 40 times as many introns as S. cerevisiae. The S. pombe
dbr1 gene was disrupted and shown to be nonessential. Like the S. cerevisiae mutant, the S. pombe null mutant accumulated introns to high levels, indicating that intron lariat debranching represents a rate-limiting step in intron degradation in both species. Unlike the S. cerevisiae mutant, the S. pombe
dbr1::
leu1+ mutant had a severe growth defect and exhibited an aberrant elongated cell shape in addition to an intron accumulation phenotype. The growth defect of the S. pombe
dbr1::
leu1+ strain suggests that debranching activity is critical for efficient intron RNA degradation and that blocking this pathway interferes with cell growth.