Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

Front Plant Sci. 2016;7:903

Authors: Li J, Zhao PX

Abstract
Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.

PMID: 27446133 [PubMed]

Editorial: Systems Biological Aspects of Pituitary Tumors.

Front Endocrinol (Lausanne). 2016;7:86

Authors: Zhan X, Desiderio DM

PMID: 27445988 [PubMed]

Systems Biology of Immunomodulation for Post-Stroke Neuroplasticity: Multimodal Implications of Pharmacotherapy and Neurorehabilitation.

Front Neurol. 2016;7:94

Authors: Alam MA, Subramanyam Rallabandi VP, Roy PK

Abstract
AIMS: Recent studies indicate that anti-inflammatory drugs, act as a double-edged sword, not only exacerbating secondary brain injury but also contributing to neurological recovery after stroke. Our aim is to explore whether there is a beneficial role for neuroprotection and functional recovery using anti-inflammatory drug along with neurorehabilitation therapy using transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), so as to improve functional recovery after ischemic stroke.
METHODS: We develop a computational systems biology approach from preclinical data, using ordinary differential equations, to study the behavior of both phenotypes of microglia, such as M1 type (pro-inflammatory) vis-à-vis M2 type (anti-inflammatory) under anti-inflammatory drug action (minocycline). We explore whether pharmacological treatment along with cerebral stimulation using tDCS and rTMS is beneficial or not. We utilize the systems pathway analysis of minocycline in nuclear factor kappa beta (NF-κB) signaling and neurorehabilitation therapy using tDCS and rTMS that act through brain-derived neurotrophic factor (BDNF) and tropomyosin-related kinase B (TrkB) signaling pathways.
RESULTS: We demarcate the role of neuroinflammation and immunomodulation in post-stroke recovery, under minocycline activated-microglia and neuroprotection together with improved neurogenesis, synaptogenesis, and functional recovery under the action of rTMS or tDCS. We elucidate the feasibility of utilizing rTMS/tDCS to increase neuroprotection across the reperfusion stage during minocycline administration. We delineate that the signaling pathways of minocycline by modulation of inflammatory genes in NF-κB and proteins activated by tDCS and rTMS through BDNF, TrkB, and calmodulin kinase (CaMK) signaling. Utilizing systems biology approach, we show that the activation pathways for pharmacotherapy (minocycline) and neurorehabilitation (rTMS applied to ipsilesional cortex and tDCS) results into increased neuronal and synaptic activity that commonly occur through activation of N-methyl-d-aspartate receptors. We construe that considerable additive neuroprotection effect would be obtained and delayed reperfusion injury can be remedied, if one uses multimodal intervention of minocycline together with tDCS and rTMS.
CONCLUSION: Additive beneficial effect is, thus, noticed for pharmacotherapy along with neurorehabilitation therapy, by maneuvering the dynamics of immunomodulation using anti-inflammatory drug and cerebral stimulation for augmenting the functional recovery after stroke, which may engender clinical applicability for enhancing plasticity, rehabilitation, and neurorestoration.

PMID: 27445961 [PubMed]

A Hybrid of the Chemical Master Equation and the Gillespie Algorithm for Efficient Stochastic Simulations of Sub-Networks.

PLoS One. 2016;11(3):e0149909

Authors: Albert J

Abstract
Modeling stochastic behavior of chemical reaction networks is an important endeavor in many aspects of chemistry and systems biology. The chemical master equation (CME) and the Gillespie algorithm (GA) are the two most fundamental approaches to such modeling; however, each of them has its own limitations: the GA may require long computing times, while the CME may demand unrealistic memory storage capacity. We propose a method that combines the CME and the GA that allows one to simulate stochastically a part of a reaction network. First, a reaction network is divided into two parts. The first part is simulated via the GA, while the solution of the CME for the second part is fed into the GA in order to update its propensities. The advantage of this method is that it avoids the need to solve the CME or stochastically simulate the entire network, which makes it highly efficient. One of its drawbacks, however, is that most of the information about the second part of the network is lost in the process. Therefore, this method is most useful when only partial information about a reaction network is needed. We tested this method against the GA on two systems of interest in biology--the gene switch and the Griffith model of a genetic oscillator--and have shown it to be highly accurate. Comparing this method to four different stochastic algorithms revealed it to be at least an order of magnitude faster than the fastest among them.

PMID: 26930199 [PubMed - indexed for MEDLINE]

Foundations and Emerging Paradigms for Computing in Living Cells.

J Mol Biol. 2016 Feb 27;428(5 Pt B):893-915

Authors: Ma KC, Perli SD, Lu TK

Abstract
Genetic circuits, composed of complex networks of interacting molecular machines, enable living systems to sense their dynamic environments, perform computation on the inputs, and formulate appropriate outputs. By rewiring and expanding these circuits with novel parts and modules, synthetic biologists have adapted living systems into vibrant substrates for engineering. Diverse paradigms have emerged for designing, modeling, constructing, and characterizing such artificial genetic systems. In this paper, we first provide an overview of recent advances in the development of genetic parts and highlight key engineering approaches. We then review the assembly of these parts into synthetic circuits from the perspectives of digital and analog logic, systems biology, and metabolic engineering, three areas of particular theoretical and practical interest. Finally, we discuss notable challenges that the field of synthetic biology still faces in achieving reliable and predictable forward-engineering of artificial biological circuits.

PMID: 26908220 [PubMed - indexed for MEDLINE]

Systems biology of immunity to MF59-adjuvanted versus nonadjuvanted trivalent seasonal influenza vaccines in early childhood.

Proc Natl Acad Sci U S A. 2016 Feb 16;113(7):1853-8

Authors: Nakaya HI, Clutterbuck E, Kazmin D, Wang L, Cortese M, Bosinger SE, Patel NB, Zak DE, Aderem A, Dong T, Del Giudice G, Rappuoli R, Cerundolo V, Pollard AJ, Pulendran B, Siegrist CA

Abstract
The dynamics and molecular mechanisms underlying vaccine immunity in early childhood remain poorly understood. Here we applied systems approaches to investigate the innate and adaptive responses to trivalent inactivated influenza vaccine (TIV) and MF59-adjuvanted TIV (ATIV) in 90 14- to 24-mo-old healthy children. MF59 enhanced the magnitude and kinetics of serum antibody titers following vaccination, and induced a greater frequency of vaccine specific, multicytokine-producing CD4(+) T cells. Compared with transcriptional responses to TIV vaccination previously reported in adults, responses to TIV in infants were markedly attenuated, limited to genes regulating antiviral and antigen presentation pathways, and observed only in a subset of vaccinees. In contrast, transcriptional responses to ATIV boost were more homogenous and robust. Interestingly, a day 1 gene signature characteristic of the innate response (antiviral IFN genes, dendritic cell, and monocyte responses) correlated with hemagglutination at day 28. These findings demonstrate that MF59 enhances the magnitude, kinetics, and consistency of the innate and adaptive response to vaccination with the seasonal influenza vaccine during early childhood, and identify potential molecular correlates of antibody responses.

PMID: 26755593 [PubMed - indexed for MEDLINE]

Synthetic Ecology of Microbes: Mathematical Models and Applications.

J Mol Biol. 2016 Feb 27;428(5 Pt B):837-61

Authors: Zomorrodi AR, Segrè D

Abstract
As the indispensable role of natural microbial communities in many aspects of life on Earth is uncovered, the bottom-up engineering of synthetic microbial consortia with novel functions is becoming an attractive alternative to engineering single-species systems. Here, we summarize recent work on synthetic microbial communities with a particular emphasis on open challenges and opportunities in environmental sustainability and human health. We next provide a critical overview of mathematical approaches, ranging from phenomenological to mechanistic, to decipher the principles that govern the function, dynamics and evolution of microbial ecosystems. Finally, we present our outlook on key aspects of microbial ecosystems and synthetic ecology that require further developments, including the need for more efficient computational algorithms, a better integration of empirical methods and model-driven analysis, the importance of improving gene function annotation, and the value of a standardized library of well-characterized organisms to be used as building blocks of synthetic communities.

PMID: 26522937 [PubMed - indexed for MEDLINE]

Reflection of successful anticancer drug development processes in the literature.

Drug Discov Today. 2016 Jul 18;

Authors: Heinemann F, Huber T, Meisel C, Bundschus M, Leser U

Abstract
The development of cancer drugs is time-consuming and expensive. In particular, failures in late-stage clinical trials are a major cost driver for pharmaceutical companies. This puts a high demand on methods that provide insights into the success chances of new potential medicines. In this study, we systematically analyze publication patterns emerging along the drug discovery process of targeted cancer therapies, starting from basic research to drug approval-or failure. We find clear differences in the patterns of approved drugs compared with those that failed in Phase II/III. Feeding these features into a machine learning classifier allows us to predict the approval or failure of a targeted cancer drug significantly better than educated guessing. We believe that these findings could lead to novel measures for supporting decision making in drug development.

PMID: 27443674 [PubMed - as supplied by publisher]

A literature-driven method to calculate similarities among diseases.

Comput Methods Programs Biomed. 2015 Nov;122(2):108-22

Authors: Kim H, Yoon Y, Ahn J, Park S

Abstract
BACKGROUND: "Our lives are connected by a thousand invisible threads and along these sympathetic fibers, our actions run as causes and return to us as results". It is Herman Melville's famous quote describing connections among human lives. To paraphrase the Melville's quote, diseases are connected by many functional threads and along these sympathetic fibers, diseases run as causes and return as results. The Melville's quote explains the reason for researching disease-disease similarity and disease network. Measuring similarities between diseases and constructing disease network can play an important role in disease function research and in disease treatment. To estimate disease-disease similarities, we proposed a novel literature-based method.
METHODS AND RESULTS: The proposed method extracted disease-gene relations and disease-drug relations from literature and used the frequencies of occurrence of the relations as features to calculate similarities among diseases. We also constructed disease network with top-ranking disease pairs from our method. The proposed method discovered a larger number of answer disease pairs than other comparable methods and showed the lowest p-value.
CONCLUSIONS: We presume that our method showed good results because of using literature data, using all possible gene symbols and drug names for features of a disease, and determining feature values of diseases with the frequencies of co-occurrence of two entities. The disease-disease similarities from the proposed method can be used in computational biology researches which use similarities among diseases.

PMID: 26212477 [PubMed - indexed for MEDLINE]

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DESM: portal for microbial knowledge exploration systems.

Nucleic Acids Res. 2016 Jan 4;44(D1):D624-33

Authors: Salhi A, Essack M, Radovanovic A, Marchand B, Bougouffa S, Antunes A, Simoes MF, Lafi FF, Motwalli OA, Bokhari A, Malas T, Amoudi SA, Othum G, Allam I, Mineta K, Gao X, Hoehndorf R, C Archer JA, Gojobori T, Bajic VB

Abstract
Microorganisms produce an enormous variety of chemical compounds. It is of general interest for microbiology and biotechnology researchers to have means to explore information about molecular and genetic basis of functioning of different microorganisms and their ability for bioproduction. To enable such exploration, we compiled 45 topic-specific knowledgebases (KBs) accessible through DESM portal (www.cbrc.kaust.edu.sa/desm). The KBs contain information derived through text-mining of PubMed information and complemented by information data-mined from various other resources (e.g. ChEBI, Entrez Gene, GO, KOBAS, KEGG, UniPathways, BioGrid). All PubMed records were indexed using 4,538,278 concepts from 29 dictionaries, with 1 638 986 records utilized in KBs. Concepts used are normalized whenever possible. Most of the KBs focus on a particular type of microbial activity, such as production of biocatalysts or nutraceuticals. Others are focused on specific categories of microorganisms, e.g. streptomyces or cyanobacteria. KBs are all structured in a uniform manner and have a standardized user interface. Information exploration is enabled through various searches. Users can explore statistically most significant concepts or pairs of concepts, generate hypotheses, create interactive networks of associated concepts and export results. We believe DESM will be a useful complement to the existing resources to benefit microbiology and biotechnology research.

PMID: 26546514 [PubMed - indexed for MEDLINE]

Explicit Drug Re-positioning: Predicting Novel Drug-Target Interactions of the Shelved Molecules with QM/MM Based Approaches.

Adv Protein Chem Struct Biol. 2015;100:89-112

Authors: Omer A, Suryanarayanan V, Selvaraj C, Singh SK, Singh P

Abstract
With the demand to enhance the speed of the drug discovery process there has been an increased usage of computational approaches in drug discovery studies. However because of their probabilistic outcomes, the challenge is to exactly mimic the natural environment which can provide the exact charge polarization effect while estimating the binding energy between protein and ligand. There has been a large number of scoring functions from simple one to the complex one available for estimating binding energy. The quantum mechanics/molecular mechanics (QM/MM) hybrid approach has been the preferred choice of interest since last decade for modeling reactions in biomolecular systems. The application of QM/MM approach has been expanded right from rescoring the already known complexes and depicting the correct position of some novel molecule to ranking a large number of molecules. It is expected that the application of QM/MM-based scoring will grow in all areas of drug discovery. However, the most promising area will be its application in repositioning, that is, assigning novel functions or targets to the already existing drugs, as this would stop the rising attrition rates as well as reduce the overall time and cost of drug discovery procedure.

PMID: 26415842 [PubMed - indexed for MEDLINE]

Complete haplotype phasing of the MHC and KIR loci with targeted HaploSeq.

BMC Genomics. 2015;16:900

Authors: Selvaraj S, Schmitt AD, Dixon JR, Ren B

Abstract
BACKGROUND: The MHC and KIR loci are clinically relevant regions of the genome. Typing the sequence of these loci has a wide range of applications including organ transplantation, drug discovery, pharmacogenomics and furthering fundamental research in immune genetics. Rapid advances in biochemical and next-generation sequencing (NGS) technologies have enabled several strategies for precise genotyping and phasing of candidate HLA alleles. Nonetheless, as typing of candidate HLA alleles alone reveals limited aspects of the genetics of MHC region, it is insufficient for the comprehensive utility of the aforementioned applications. For this reason, we believe phasing the entire MHC and KIR locus onto a single locus-spanning haplotype can be a critical improvement for better understanding transplantation biology.
RESULTS: Generating long-range (>1 Mb) phase information is traditionally very challenging. As proximity-ligation based methods of DNA sequencing preserves chromosome-span phase information, we have utilized this principle to demonstrate its utility towards generating full-length phasing of MHC and KIR loci in human samples. We accurately (~99%) reconstruct the complete haplotypes for over 90% of sequence variants (coding and non-coding) within these two loci that collectively span 4-megabases.
CONCLUSIONS: By haplotyping a majority of coding and non-coding alleles at the MHC and KIR loci in a single assay, this method has the potential to assist transplantation matching and facilitate investigation of the genetic basis of human immunity and disease.

PMID: 26541200 [PubMed - indexed for MEDLINE]

Pharmacogenetics of BCR/ABL Inhibitors in Chronic Myeloid Leukemia.

Int J Mol Sci. 2015;16(9):22811-29

Authors: Polillo M, Galimberti S, Baratè C, Petrini M, Danesi R, Di Paolo A

Abstract
Chronic myeloid leukemia was the first haematological neoplasia that benefited from a targeted therapy with imatinib nearly 15 years ago. Since then, several studies have investigated the role of genes, their variants (i.e., polymorphisms) and their encoded proteins in the pharmacokinetics and pharmacodynamics of BCR-ABL1 tyrosine kinase activity inhibitors (TKIs). Transmembrane transporters seem to influence in a significant manner the disposition of TKIs, especially that of imatinib at both cellular and systemic levels. In particular, members of the ATP-binding cassette (ABC) family (namely ABCB1 and ABCG2) together with solute carrier (SLC) transporters (i.e., SLC22A1) are responsible for the differences in drug pharmacokinetics. In the case of the newer TKIs, such as nilotinib and dasatinib, the substrate affinity of these drugs for transporters is variable but lower than that measured for imatinib. In this scenario, the investigation of genetic variants as possible predictive markers has led to some discordant results. With the partial exception of imatinib, these discrepancies seem to limit the application of discovered biomarkers in the clinical settings. In order to overcome these issues, larger prospective confirmative trials are needed.

PMID: 26402671 [PubMed - indexed for MEDLINE]

Report on the Workshop and Regular Meeting of the Imode-CKD and Bcmolmed Marie Curie Training and Research Programs.

Pril (Makedon Akad Nauk Umet Odd Med Nauki). 2015 Dec 1;36(2):235-240

Authors: Krochmal M, Cisek K, Markoska K, Spasovski G, Vlahou A

Abstract
A Workshop and Regular Meeting of the Marie Curie Training and Research Programs iMODECKD (Identification of the Molecular Determinants of established Chronic Kidney Disease) and BCMolMed (Molecular Medicine for Bladder Cancer) was held from 20-22 March at the Macedonian Academy of Science and Arts (MASA). The meeting was hosted by the participating center University of Skopje (SKO) - Goce Spasovski and MASA - Momir Polenakovic (R. Macedonia). The representative from MASA proteomic research center - Katerina Davalieva (R. Macedonia) had presentation on proteomic research in prostate cancer (PCa). 40 researchers from 13 different countries participated at the meeting. The Workshop was devoted on "Chronic Kidney Disease: Clinical Management issues", and consisted of 15 oral presentations given by nephrologists and experts in the field of CKD. Raymond Vanholder (Belgium) - past president of ERA-EDTA had a keynote lecture on "CKD: Questions that need to be answered and are not (or at least not entirely)". The workshop continued in four sessions with lectures from Alberto Ortiz (Spain), Olivera Stojceva-Taneva (R. Macedonia), Dimitrios Goumenos (Greece), Joachim Beige (Germany), Marian Klinger (Poland), Goce Spasovski (R. Macedonia), Joachim Jankowski (Germany), Adalbert Schiller (Romania), Robert Johnson (USA), Franco Ferrario (Italy), Ivan Rychlik (Czech Republic), Fulvio Magni (Italy) and Giovambattista Capasso (Italy), all covering a training theme. Within the meeting there were two lectures on complimentary skills for ethics in science and career advancement from two principal investigators - Goce Spasovski (R. Macedonia) and Joost Schanstra (France). During the Regular Meeting, 13 PhD students i.e. Early Stage Researchers and one Experienced Researcher from both Programs presented their work and progress within iMODE-CKD and BCMolMed projects. This meeting was a great opportunity to exchange experience and ideas in the field of systems biology approaches and translational medicine and planning future collaboration.

PMID: 27442390 [PubMed - as supplied by publisher]

Novel molecular triggers underlie valproate-induced liver injury and its alleviation by the omega-3 fatty acid DHA: role of inflammation and apoptosis.

Heliyon. 2016 Jul;2(7):e00130

Authors: El-Mowafy AM, Katary MM, Pye C, Ibrahim AS, Elmarakby AA

Abstract
BACKGROUND/AIM: Hepatic injury is a hallmark adverse reaction to Valproate (VPA), a common used drug in the management of numerous CNS disorders, including epilepsy. DHA has a myriad of health benefits, including renal- and hepato-protective effects. Unfortunately, however, the underpinnings of such liver-pertinent VPA- and DHA-actions remain largely undefined. Accordingly, this study attempted to unveil the cellular and molecular triggers whereby VPA evokes, while DHA abates, hepatotoxicity.
METHODS: We evaluated activity and/or expression of cellular markers of oxidative stress, inflammation, and apoptosis in rat liver, following treatment with VPA (500 mg/kg/day) with and without concurrent treatment with DHA (250 mg/kg/day) for two weeks.
RESULTS AND CONCLUSION: VPA promoted hepatic oxidative stress as evidenced by enhancing activity/expression of NADPH-oxidase and its subunits, a ROS-generator, and by accumulation of lipid-peroxides. Moreover, VPA enhanced hepatic phosphorylation/activation of mitogen-activated protein kinase (MAPK), and expression of cyclooxygenase-2(COX-2), as proinflammatory signals. Besides, VPA promoted hepatocellular apoptosis, as attested by enhanced expression of cleaved caspase-9 and increased number of TUNEL-positive hepatocytes. Lastly, VPA upregulated levels of hypoxia-inducible factor-1-alpha (HIF-1α), a multifaceted modulator of hepatocytic biology, and activity of its downstream antioxidant enzyme heme-oxygenase-1(HO-1). These changes were significantly blunted by co-administration of DHA. Our findings demonstrate that VPA activated NADPH-oxidase and HIF-1α to induce oxidative-stress and hypoxia as initiators of hepatic injury. These changes were further aggravated by up-regulation of inflammatory (MAPK and COX-2) and apoptotic cascades, but could be partly lessened by HO-1 activation. Concurrent administration of DHA mitigated all VPA-induced anomalies.

PMID: 27441301 [PubMed]

Noise processing by microRNA-mediated circuits: The Incoherent Feed-Forward Loop, revisited.

Heliyon. 2016 Apr;2(4):e00095

Authors: Grigolon S, Di Patti F, De Martino A, Marinari E

Abstract
The intrinsic stochasticity of gene expression is usually mitigated in higher eukaryotes by post-transcriptional regulation channels that stabilise the output layer, most notably protein levels. The discovery of small non-coding RNAs (miRNAs) in specific motifs of the genetic regulatory network has led to identifying noise buffering as the possible key function they exert in regulation. Recent in vitro and in silico studies have corroborated this hypothesis. It is however also known that miRNA-mediated noise reduction is hampered by transcriptional bursting in simple topologies. Here, using stochastic simulations validated by analytical calculations based on van Kampen's expansion, we revisit the noise-buffering capacity of the miRNA-mediated Incoherent Feed Forward Loop (IFFL), a small module that is widespread in the gene regulatory networks of higher eukaryotes, in order to account for the effects of intermittency in the transcriptional activity of the modulator gene. We show that bursting considerably alters the circuit's ability to control static protein noise. By comparing with other regulatory architectures, we find that direct transcriptional regulation significantly outperforms the IFFL in a broad range of kinetic parameters. This suggests that, under pulsatile inputs, static noise reduction may be less important than dynamical aspects of noise and information processing in characterising the performance of regulatory elements.

PMID: 27441269 [PubMed]

Hydrogen peroxide induced cell death: One or two modes of action?

Heliyon. 2015 Dec;1(4):e00049

Authors: Uhl L, Gerstel A, Chabalier M, Dukan S

Abstract
Imlay and Linn show that exposure of logarithmically growing Escherichia coli to hydrogen peroxide (H2O2) leads to two kinetically distinguishable modes of cell killing. Mode one killing is pronounced near 1 mM concentration of H2O2 and is caused by DNA damage, whereas mode-two killing requires higher concentration ([Formula: see text]). The second mode seems to be essentially due to damage to all macromolecules. This phenomenon has also been observed in Fenton in vitro systems with DNA nicking caused by hydroxyl radical ([Formula: see text]). To our knowledge, there is currently no mathematical model for predicting mode one killing in vitro or in vivo after H2O2 exposure. We propose a simple model, using Escherichia coli as a model organism and a set of ordinary differential equations. Using this model, we show that available iron and cell density, two factors potentially involved in ROS dynamics, play a major role in the prediction of the experimental results obtained by our team and in previous studies. Indeed the presence of the mode one killing is strongly related to those two parameters. To our knowledge, mode-one death has not previously been explained. Imlay and Linn (Imlay and Linn, 1986) suggested that perhaps the amount of the toxic species was reduced at high concentrations of H2O2 because hydroxyl (or other) radicals might be quenched directly by hydrogen peroxide with the concomitant formation of superoxide anion (a less toxic species). We demonstrate (mathematically and numerically) that free available iron decrease is necessary to explain mode one killing which cannot appear without it and that H2O2 quenching or consumption is not responsible for mode-one death. We are able to follow ROS concentration (particularly responsible for mode one killing) after exposure to H2O2. This model therefore allows us to understand two major parameters involved in the presence or not of the first killing mode.

PMID: 27441232 [PubMed]

Construction and Evaluation of an Organic Anion Transporter 1 (OAT1)-Centered Metabolic Network.

J Biol Chem. 2016 Jul 20;

Authors: Liu HC, Jamshidi N, Chen Y, Eraly SA, Cho SY, Bhatnagar V, Wu W, Bush KT, Abagyan R, Palsson BO, Nigam SK

Abstract
There has been a recent interest in the broader physiological importance of multispecific drug transporters of the SLC and ABC transporter families. Here, a novel multi-tiered systems biology approach was used to predict metabolites and signaling molecules potentially affected by the in vivo deletion of organic anion transporter 1 (Oat1, Slc22a6, originally NKT), a major kidney-expressed drug transporter. Validation of some predictions in wet-lab assays, together with re-evaluation of existing transport and knockout metabolomics data, generated an experimentally-validated, confidence-ranked set of OAT1-interacting endogenous compounds enabling construction of an OAT1-centered metabolic interaction network. Pathway and enrichment analysis indicated an important role for OAT1 in metabolism involving: the TCA cycle, tryptophan and other amino acids, fatty acids, prostaglandins, cyclic nucleotides, odorants, polyamines, and vitamins. The partly-validated reconstructed network is also consistent with a major role for OAT1 in modulating metabolic and signaling pathways involving uric acid, gut microbiome products and so-called uremic toxins accumulating in chronic kidney disease (CKD). Together, the findings are compatible with the hypothesized role of drug transporters in remote inter-organ and inter-organismal communication (the Remote Sensing and Signaling Hypothesis, Nigam SK. 2015, Nature Rev Drug Disc 14:29). The fact that OAT1 can affect many systemic biological pathways suggests that drug-metabolite interactions (DMI) need to be considered beyond simple competition for the drug transporter itself and may explain aspects of drug-induced metabolic syndromes. Our approach should provide novel mechanistic insights into the role of OAT1 and other drug transporters implicated in metabolic diseases like gout, diabetes and CKD.

PMID: 27440044 [PubMed - as supplied by publisher]