12 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/08/02

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Antiparallel protocadherin homodimers use distinct affinity- and specificity-mediating regions in cadherin repeats 1-4.

Elife. 2016 Jul 29;5

Authors: Nicoludis JM, Vogt BE, Green AG, Schärfe CP, Marks DS, Gaudet R

Abstract
Protocadherins (Pcdhs) are cell adhesion and signaling proteins used by neurons to develop and maintain neuronal networks, relying on trans homophilic interactions between their extracellular cadherin (EC) repeat domains. We present the structure of the antiparallel EC1-4 homodimer of human PcdhγB3, a member of the γ subfamily of clustered Pcdhs. Structure and sequence comparisons of α, β, and γ clustered Pcdh isoforms illustrate that subfamilies encode specificity in distinct ways through diversification of loop region structure and composition in EC2 and EC3, which contains isoform-specific conservation of primarily polar residues. In contrast, the EC1/EC4 interface comprises hydrophobic interactions that provide non-selective dimerization affinity. Using sequence coevolution analysis, we found evidence for a similar antiparallel EC1-4 interaction in non-clustered Pcdh families. We thus deduce that the EC1-4 antiparallel homodimer is a general interaction strategy that evolved before the divergence of these distinct protocadherin families.

PMID: 27472898 [PubMed - as supplied by publisher]

Deciphering the Duality of Clock and Growth Metabolism in a Cell Autonomous System Using NMR Profiling of the Secretome.

Metabolites. 2016;6(3)

Authors: Sengupta A, Krishnaiah SY, Rhoades S, Growe J, Slaff B, Venkataraman A, Olarerin-George AO, Van Dang C, Hogenesch JB, Weljie AM

Abstract
Oscillations in circadian metabolism are crucial to the well being of organism. Our understanding of metabolic rhythms has been greatly enhanced by recent advances in high-throughput systems biology experimental techniques and data analysis. In an in vitro setting, metabolite rhythms can be measured by time-dependent sampling over an experimental period spanning one or more days at sufficent resolution to elucidate rhythms. We hypothesized that cellular metabolic effects over such a time course would be influenced by both oscillatory and circadian-independent cell metabolic effects. Here we use nuclear magnetic resonance (NMR) spectroscopy-based metabolic profiling of mammalian cell culture media of synchronized U2 OS cells containing an intact transcriptional clock. The experiment was conducted over 48 h, typical for circadian biology studies, and samples collected at 2 h resolution to unravel such non-oscillatory effects. Our data suggest specific metabolic activities exist that change continuously over time in this settting and we demonstrate that the non-oscillatory effects are generally monotonic and possible to model with multivariate regression. Deconvolution of such non-circadian persistent changes are of paramount importance to consider while studying circadian metabolic oscillations.

PMID: 27472375 [PubMed - as supplied by publisher]

System-level genome editing in microbes.

Curr Opin Microbiol. 2016 Jul 26;33:113-122

Authors: Csörgő B, Nyerges Á, Pósfai G, Fehér T

Abstract
The release of the first complete microbial genome sequences at the end of the past century opened the way for functional genomics and systems-biology to uncover the genetic basis of various phenotypes. The surge of available sequence data facilitated the development of novel genome editing techniques for system-level analytical studies. Recombineering allowed unprecedented throughput and efficiency in microbial genome editing and the recent discovery and widespread use of RNA-guided endonucleases offered several further perspectives: (i) previously recalcitrant species became editable, (ii) the efficiency of recombineering could be elevated, and as a result (iii) diverse genomic libraries could be generated more effectively. Supporting recombineering by RNA-guided endonucleases has led to success stories in metabolic engineering, but their use for system-level analysis is mostly unexplored. For the full exploitation of opportunities that are offered by the genome editing proficiency, future development of large scale analytical procedures is also vitally needed.

PMID: 27472027 [PubMed - as supplied by publisher]

Phenotypic Modulation of Smooth Muscle Cells in Atherosclerosis Is Associated With Downregulation of LMOD1, SYNPO2, PDLIM7, PLN, and SYNM.

Arterioscler Thromb Vasc Biol. 2016 Jul 28;

Authors: Perisic LM, Rykaczewska U, Razuvaev A, Sabater-Lleal M, Lengquist M, Miller CL, Ericsson I, Röhl S, Kronqvist M, Aldi S, Magné J, Paloschi V, Vesterlund M, Li Y, Jin H, Diez MG, Roy J, Baldassarre D, Veglia F, Humphries SE, de Faire U, Tremoli E, Odeberg J, Vukojevic V, Lehtiö J, Maegdefessel L, Ehrenborg E, Paulsson-Berne G, Hansson G, Lindeman JH, Eriksson P, Quertermous T, Hamsten A, Hedin U

Abstract
OBJECTIVE: Key augmented processes in atherosclerosis have been identified, whereas less is known about downregulated pathways. Here, we applied a systems biology approach to examine suppressed molecular signatures, with the hypothesis that they may provide insight into mechanisms contributing to plaque stability.
APPROACH AND RESULTS: Muscle contraction, muscle development, and actin cytoskeleton were the most downregulated pathways (false discovery rate=6.99e-21, 1.66e-6, 2.54e-10, respectively) in microarrays from human carotid plaques (n=177) versus healthy arteries (n=15). In addition to typical smooth muscle cell (SMC) markers, these pathways also encompassed cytoskeleton-related genes previously not associated with atherosclerosis. SYNPO2, SYNM, LMOD1, PDLIM7, and PLN expression positively correlated to typical SMC markers in plaques (Pearson r>0.6, P<0.0001) and in rat intimal hyperplasia (r>0.8, P<0.0001). By immunohistochemistry, the proteins were expressed in SMCs in normal vessels, but largely absent in human plaques and intimal hyperplasia. Subcellularly, most proteins localized to the cytoskeleton in cultured SMCs and were regulated by active enhancer histone modification H3K27ac by chromatin immunoprecipitation-sequencing. Functionally, the genes were downregulated by PDGFB and IFNg, exposure to shear flow stress, and oxLDL loading. Genetic variants in PDLIM7, PLN, and SYNPO2 loci associated with progression of carotid intima-media thickness in high-risk subjects without symptoms of cardiovascular disease (n=3378). By eQTL, rs11746443 also associated with PDLIM7 expression in plaques. Mechanistically, silencing of PDLIM7 in vitro led to downregulation of SMC markers and disruption of the actin cytoskeleton, decreased cell spreading, and increased proliferation.
CONCLUSIONS: We identified a panel of genes that reflect the altered phenotype of SMCs in vascular disease and could be early sensitive markers of SMC dedifferentiation.

PMID: 27470516 [PubMed - as supplied by publisher]

The Need for Speed-Kinetic Limits of Drug Transporters.

Trends Pharmacol Sci. 2016 Apr;37(4):243-5

Authors: Matsson P, Lundquist P, Artursson P

PMID: 26922253 [PubMed - indexed for MEDLINE]

Systems medicine, personalized health and therapy.

Pharmacogenomics. 2015;16(14):1527-39

Authors: Siest G, Auffray C, Taniguchi N, Ingelman-Sundberg M, Murray H, Visvikis-Siest S, Ansari M, Marc J, Jacobs P, Meyer U, Van Schaik RH, Müller MM, Wevers RA, Simmaco M, Kussmann M, Manolopoulos VG, Alizadeh BZ, Beastall G, Németh G

Abstract
The 7th Santorini Conference was held in Santorini, Greece, and brought together 200 participants from 40 countries in several continents, including Europe, USA but also Japan, Korea, Brazil and South Africa. The attendees had the opportunity to: listen to 60 oral presentations; participate in two lunch symposia; look at 103 posters, which were divided in two groups ('systems medicine and environment' and 'pharmacogenomics and cancer') and attend a dedicated exhibition with six companies. The meeting was organized by the Institut National de la Santé et de la Recherche Médicale (INSERM) U1122; IGE-PCV and by 'Biologie Prospective' with the collaboration of the European Society of Pharmacogenomics and Theranostics (ESPT), under the auspices of international organizations (e.g., International Federation of Clinical Chemistry and Laboratory medicine [IFCC], European Federation of Clinical Chemistry and Laboratory Medicine [EFLM], European Diagnostic Manufacturers Association [EDMA], Federation of European Pharmacological Societies [EPHAR], European Science Foundation [ESF]). The 3 days of the conference stimulated intensive discussions on systems biology and the influence of omics technologies on personalized health. Sixty speakers were invited or selected from early abstracts and gave presentations on the following topics: From systems biology to systems medicine/pharmacology; Omics/translating pharmacogenomics/proteomic biomarkers/metabolomics; Human nutrition and health/personalized medicine. We are summarizing here the main topics and presentations, according to the successive sessions.

PMID: 26401575 [PubMed - indexed for MEDLINE]

Systems biology approach to studying proliferation-dependent prognostic subnetworks in breast cancer.

Sci Rep. 2015;5:12981

Authors: Song Q, Wang H, Bao J, Pullikuth AK, Li KC, Miller LD, Zhou X

Abstract
Tumor proliferative capacity is a major biological correlate of breast tumor metastatic potential. In this paper, we developed a systems approach to investigate associations among gene expression patterns, representative protein-protein interactions, and the potential for clinical metastases, to uncover novel survival-related subnetwork signatures as a function of tumor proliferative potential. Based on the statistical associations between gene expression patterns and patient outcomes, we identified three groups of survival prognostic subnetwork signatures (SPNs) corresponding to three proliferation levels. We discovered 8 SPNs in the high proliferation group, 8 SPNs in the intermediate proliferation group, and 6 SPNs in the low proliferation group. We observed little overlap of SPNs between the three proliferation groups. The enrichment analysis revealed that most SPNs were enriched in distinct signaling pathways and biological processes. The SPNs were validated on other cohorts of patients, and delivered high accuracy in the classification of metastatic vs non-metastatic breast tumors. Our findings indicate that certain biological networks underlying breast cancer metastasis differ in a proliferation-dependent manner. These networks, in combination, may form the basis of highly accurate prognostic classification models and may have clinical utility in guiding therapeutic options for patients.

PMID: 26257336 [PubMed - indexed for MEDLINE]

Principles of Systems Biology, No. 7.

Cell Syst. 2016 Jul 27;3(1):3-6

Authors:

Abstract
With applications of CRISPR-Cas proteins for probing chromatin dynamics and recording information in a genome, this month's Cell Systems call (Cell Systems 1, 307) highlights a plethora of new techniques.

PMID: 27467241 [PubMed - as supplied by publisher]

Altered protein phosphorylation as a resource for potential AD biomarkers.

Sci Rep. 2016;6:30319

Authors: Henriques AG, Müller T, Oliveira JM, Cova M, da Cruz E Silva CB, da Cruz E Silva OA

Abstract
The amyloidogenic peptide, Aβ, provokes a series of events affecting distinct cellular pathways regulated by protein phosphorylation. Aβ inhibits protein phosphatases in a dose-dependent manner, thus it is expected that the phosphorylation state of specific proteins would be altered in response to Aβ. In fact several Alzheimer's disease related proteins, such as APP and TAU, exhibit pathology associated hyperphosphorylated states. A systems biology approach was adopted and the phosphoproteome, of primary cortical neuronal cells exposed to Aβ, was evaluated. Phosphorylated proteins were recovered and those whose recovery increased or decreased, upon Aβ exposure across experimental sets, were identified. Significant differences were evident for 141 proteins and investigation of their interactors revealed key protein clusters responsive to Aβ treatment. Of these, 73 phosphorylated proteins increased and 68 decreased upon Aβ addition. These phosphorylated proteins represent an important resource of potential AD phospho biomarkers that should be further pursued.

PMID: 27466139 [PubMed - in process]

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast.

BMC Bioinformatics. 2015;16 Suppl 18:S2

Authors: Lai FJ, Chang HT, Wu WS

Abstract
BACKGROUND: Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface.
RESULTS: The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses.
CONCLUSIONS: Allowing users to select eight existing performance indices and 15 existing algorithms for comparison, our web tool benefits researchers who are eager to comprehensively and objectively evaluate the performance of their newly developed algorithm. Thus, our tool greatly expedites the progress in the research of computational identification of cooperative TF pairs.

PMID: 26677932 [PubMed - indexed for MEDLINE]

Sialomes and Mialomes: A Systems-Biology View of Tick Tissues and Tick-Host Interactions.

Trends Parasitol. 2016 Mar;32(3):242-54

Authors: Chmelař J, Kotál J, Karim S, Kopacek P, Francischetti IM, Pedra JH, Kotsyfakis M

Abstract
Tick saliva facilitates tick feeding and infection of the host. Gene expression analysis of tick salivary glands and other tissues involved in host-pathogen interactions has revealed a wide range of bioactive tick proteins. Transcriptomic analysis has been a milestone in the field and has recently been enhanced by next-generation sequencing (NGS). Furthermore, the application of quantitative proteomics to ticks with unknown genomes has provided deeper insights into the molecular mechanisms underlying tick hematophagy, pathogen transmission, and tick-host-pathogen interactions. We review current knowledge on the transcriptomics and proteomics of tick tissues from a systems-biology perspective and discuss future challenges in the field.

PMID: 26520005 [PubMed - indexed for MEDLINE]

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability.

OMICS. 2015 Oct;19(10):581-601

Authors: Kumar A, Pathak RK, Gupta SM, Gaur VS, Pandey D

Abstract
In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes.

PMID: 26484978 [PubMed - indexed for MEDLINE]

Editorial overview: Cell signalling and gene regulation-communication and control as the twin pillars of systems biology.

Curr Opin Plant Biol. 2015 Oct;27:v-viii

Authors: Cao X, Meyers BC

PMID: 26433830 [PubMed - indexed for MEDLINE]

Food metabolomics: from farm to human.

Curr Opin Biotechnol. 2016 Feb;37:16-23

Authors: Kim S, Kim J, Yun EJ, Kim KH

Abstract
Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans.

PMID: 26426959 [PubMed - indexed for MEDLINE]

32 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/07/28

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

MicroRNAs in hereditary diffuse gastric cancer.

Biomed Rep. 2016 Aug;5(2):151-154

Authors: Suárez-Arriaga MC, Ribas-Aparicio RM, Ruiz-Tachiquín ME

Abstract
In 2012, gastric cancer (GC) was the third cause of mortality due to cancer in men and women. In Central and South America, high mortality rates have been reported. A total of 95% of tumors developed in the stomach are of epithelial origin; thus, these are denominated adenocarcinomas of the stomach. Diverse classification systems have been established, among which two types of GC based on histological type and growth pattern have been described as follows: Intestinal (IGC) and diffuse (DGC). Approximately 1-3% of GC cases are associated with heredity. Hereditary-DGC (HDGC), with 80% penetrance, is an autosomal-type, dominant syndrome in which 40% of cases are carriers of diverse mutations of the CDH1 gene, which encodes for the cadherin protein. By contrast, microRNA are non-encoded, single-chain RNA molecules. These molecules regulate the majority of cellular functions at the post-transcriptional level. However, analysis of these interactions by means of Systems Biology has allowed the understanding of complex and heterogeneous diseases, such as cancer. These molecules are ubiquitous; however, their expression can be specific in different tissues either temporarily or permanently, depending on the stage of the cell. Due to the participation of microRNA in the processes of cellular proliferation, cell cycle control, apoptosis, differentiation and metabolism, these have been indicated to have a role in the development of cancerous processes, finding specific patterns of expression in different neoplasms, including GC, in which the microRNA expression profile is different in samples of non-cancerous versus cancerous tissues. A difference has been observed in the expression patterns of DGC and IGC. However, the role of microRNA in HDGC has not yet been established. The present study reviews the investigations that describe the participation of microRNA in the regulation of genes CDH1, RHOA, CTNNA1, INSR and TGF-β in different neoplasms, such as HDGC.

PMID: 27446532 [PubMed - as supplied by publisher]

The Significance of an Enhanced Concept of the Organism for Medicine.

Evid Based Complement Alternat Med. 2016;2016:1587652

Authors: Rosslenbroich B

Abstract
Recent developments in evolutionary biology, comparative embryology, and systems biology suggest the necessity of a conceptual shift in the way we think about organisms. It is becoming increasingly evident that molecular and genetic processes are subject to extremely refined regulation and control by the cell and the organism, so that it becomes hard to define single molecular functions or certain genes as primary causes of specific processes. Rather, the molecular level is integrated into highly regulated networks within the respective systems. This has consequences for medical research in general, especially for the basic concept of personalized medicine or precision medicine. Here an integrative systems concept is proposed that describes the organism as a multilevel, highly flexible, adaptable, and, in this sense, autonomous basis for a human individual. The hypothesis is developed that these properties of the organism, gained from scientific observation, will gradually make it necessary to rethink the conceptual framework of physiology and pathophysiology in medicine.

PMID: 27446221 [PubMed]

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]