Large-Scale Functional Analysis of CRP-Mediated Feed-Forward Loops.

Int J Mol Sci. 2018 Aug 09;19(8):

Authors: Yang CD, Huang HY, Shrestha S, Chen YH, Huang HD, Tseng CP

Abstract
Feed-forward loops (FFLs) represent an important and basic network motif to understand specific biological functions. Cyclic-AMP (cAMP) receptor protein (CRP), a transcription factor (TF), mediates catabolite repression and regulates more than 400 genes in response to changes in intracellular concentrations of cAMP in Escherichia coli. CRP participates in some FFLs, such as araBAD and araFGH operons and adapts to fluctuating environmental nutrients, thereby enhancing the survivability of E. coli. Although computational simulations have been conducted to explore the potential functionality of FFLs, a comprehensive study on the functions of all structural types on the basis of in vivo data is lacking. Moreover, the regulatory role of CRP-mediated FFLs (CRP-FFLs) remains obscure. We identified 393 CRP-FFLs in E. coli using EcoCyc and RegulonDB. Dose⁻response genomic microarray of E. coli revealed dynamic gene expression of each target gene of CRP-FFLs in response to a range of cAMP dosages. All eight types of FFLs were present in CRP regulon with various expression patterns of each CRP-FFL, which were further divided into five functional groups. The microarray and reported regulatory relationships identified 202 CRP-FFLs that were directly regulated by CRP in these eight types of FFLs. Interestingly, 34% (147/432) of genes were directly regulated by CRP and CRP-regulated TFs, which indicates that these CRP-regulated genes were also regulated by other CRP-regulated TFs responding to environmental signals through CRP-FFLs. Furthermore, we applied gene ontology annotation to reveal the biological functions of CRP-FFLs.

PMID: 30096859 [PubMed - in process]

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

"systems biology"

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"systems biology"

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"systems biology"

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"systems biology"

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"systems biology"

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

"systems biology"

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

"systems biology"

These pubmed results were generated on 2018/08/07

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Discovering novel valid biomarkers and drugs in patient-centric genomic trials: the new epoch of precision surgical oncology.

Drug Discov Today. 2018 Aug 02;:

Authors: Ziogas DE, Kyrochristos ID, Roukos DH

Abstract
Despite standardization of multimodal treatment and approval of several targeted drugs for resectable, non-metastatic cancer (M0 patients), intrinsic and acquired resistance and relapse rates remain high, even in early-stage aggressive tumors. Genome analysis could overcome these unmet needs. Our comprehensive review underlines the controversy on stable or spatiotemporally evolving clones as well as promising yet inconclusive data on genome-based biomarkers and drug development. We propose clinicogenomic trials in M0 patients for the validation of intratumor heterogeneity (ITH), circulating genomic subclones (cGSs) and intra-patient genomic heterogeneity (IPGH) as biomarkers and simultaneous discovery of novel oncotargets. This evidence-based strategy highlights the coming of precision surgical oncology with a future perspective of understanding and disrupting deregulated transcriptional networks.

PMID: 30077778 [PubMed - as supplied by publisher]

The Long Noncoding RNA Landscape in Amygdala Tissues from Schizophrenia Patients.

EBioMedicine. 2018 Aug 01;:

Authors: Tian T, Wei Z, Chang X, Liu Y, Gur RE, Sleiman PMA, Hakonarson H

Abstract
To date, most transcriptome studies of schizophrenia focus on the analysis of protein-coding genes. Long noncoding RNAs (lncRNAs) are emerging as key tissue-specific regulators of cellular and disease processes. The amygdala brain region has been implicated in the pathophysiology of schizophrenia. We performed unbiased whole transcriptome profiling of amygdala tissues from 22 schizophrenia patients and 24 non-psychiatric controls using RNA-seq. We reconstructed amygdala transcriptome and employed systems biology approaches to annotating the functional roles of lncRNAs. As a result, we identified 839 novel lncRNAs in amygdala. We found in amygdala lncRNAs are more subtype-specific than protein-coding genes. We identified functional modules associated with "synaptic transmission", "ribosome", and "immune responses" which were related to schizophrenia pathophysiology that involved lncRNAs. Integrative functional analyses associating individual lncRNAs with specific pathways and functions further show that amygdala lncRNAs are connected with all of these pathways. Our study presents the first systematic landscape of lncRNAs in amygdala tissue from schizophrenia cases.

PMID: 30077719 [PubMed - as supplied by publisher]

Cyanobacterial pigments: Perspectives and biotechnological approaches.

Food Chem Toxicol. 2018 Aug 02;:

Authors: Saini DK, Pabbi S, Shukla P

Abstract
Cyanobacteria are the oxygenic photosynthesis performing prokaryotes and show a connecting link between plastids of eukaryotic autotrophs and prokaryotes. A variety of pigments, like chlorophyll, carotenoids and phycobiliproteins which exhibit different colors are present in cyanobacteria. Increasing consciousness about the harmful effects of synthetic or chemical dyes encouraged people to give more preference towards the usage of natural products, such as plant or microbial-derived colors in food and cosmetics. That is why cyanobacteria are exploited as a source of natural colors and have high commercial value in many industries. This review mainly focuses on different cyanobacterial pigments, their applications and modern biotechnological approaches such as genetic engineering, systems biology to enhance the production of biopigments for their potential use in pharmaceuticals, food, research, and cosmetics industries.

PMID: 30077705 [PubMed - as supplied by publisher]

Iron-Requiring Enzymes in the Spotlight of Oxygen.

Trends Plant Sci. 2018 Aug 01;:

Authors: Vigani G, Murgia I

Abstract
Iron (Fe) is a cofactor required for a variety of essential redox reactions in plant metabolism. Thus, plants have developed a complex network of interacting pathways to withstand Fe deficiency, including metabolic reprogramming. This opinion aims at revisiting such reprogramming by focusing on: (i) the functional relationships of Fe-requiring enzymes (FeREs) with respect to oxygen; and (ii) the progression of FeREs engagement, occurring under Fe deficiency stress. In particular, we considered such progression of FeREs engagement as strain responses of increasing severity during the stress phases of alarm, resistance, and exhaustion. This approach can contribute to reconcile the variety of experimental results obtained so far from different plant species and/or different Fe supplies.

PMID: 30077479 [PubMed - as supplied by publisher]

Potential role of RAB6C-AS1 long noncoding RNA in different cancers.

J Cell Physiol. 2018 Aug 04;:

Authors: Salavaty A, Motlagh FM, Barabadi M, Cheshomi H, Esmatabadi MJD, Shahmoradi M, Soleimanpour-Lichaei HR

Abstract
BACKGROUND: Long noncoding RNAs (lncRNAs) refer to a group of non-protein-coding RNAs that are usually more than 200 nucleotides. These long transcripts play significant roles in diverse cellular processes, mostly through epigenetic mechanisms. Thus, dysregulation of lncRNAs is associated with various diseases, especially cancer. This study aims to investigate the probable roles of RAB6C-AS1 lncRNA in different cancers.
METHODS: Real-time quantitative reverse transcription-polymerase chain reaction was applied for the analysis of RAB6C-AS1 lncRNA amplification in gastric cancer (GC) samples compared with normal ones. Also, several online and offline data sets and tools were used to analyze the relation between RAB6C-AS1 lncRNA and different cancers.
RESULTS: The end result of our analyses indicated that RAB6C-AS1 was overexpressed in 40% of the investigated GC specimens. Also, the results demonstrated a true relation between RAB6C-AS1 overexpression and higher GC tumor grades. However, bioinformatic analyses showed that while RAB6C-AS1 possibly functions as an oncogene in some cancer types, including prostate and breast cancers, it might have a tumor suppressive function in some others including brain tumors.
CONCLUSIONS: We found that RAB6C-AS1 lncRNA is mostly overexpressed in GC. Also, based on bioinformatic and systems biology analyses, RAB6C-AS1 might function either as an oncogenic factor or tumor suppressor in a tissue-specific manner. Thus, RAB6C-AS1 could be considered as a candidate biomarker for various malignancies, especially prostate and brain cancers. According to our results, RAB6C-AS1 has a notable prognostic value for patients with brain lower grade glioma.

PMID: 30076712 [PubMed - as supplied by publisher]

Modeling Procedures.

Adv Exp Med Biol. 2018;1069:35-134

Authors: Álvarez-Buylla Roces ME, Martínez-García JC, Dávila-Velderrain J, Domínguez-Hüttinger E, Martínez-Sánchez ME

Abstract
Being concerned by the understanding of the mechanism underlying chronic degenerative diseases , we presented in the previous chapter the medical systems biology conceptual framework that we present for that purpose in this volume. More specifically, we argued there the clear advantages offered by a state-space perspective when applied to the systems-level description of the biomolecular machinery that regulates complex degenerative diseases. We also discussed the importance of the dynamical interplay between the risk factors and the network of interdependencies that characterizes the biochemical, cellular, and tissue-level biomolecular reactions that underlie the physiological processes in health and disease. As we pointed out in the previous chapter, the understanding of this interplay (articulated around cellular phenotypic plasticity properties, regulated by specific kinds of gene regulatory networks) is necessary if prevention is chosen as the human-health improvement strategy (potentially involving the modulation of the patient's lifestyle). In this chapter we provide the medical systems biology mathematical and computational modeling tools required for this task.

PMID: 30076566 [PubMed - in process]

Medical Systems Biology.

Adv Exp Med Biol. 2018;1069:1-33

Authors: Álvarez-Buylla Roces ME, Martínez-García JC, Dávila-Velderrain J, Domínguez-Hüttinger E, Martínez-Sánchez ME

Abstract
The aim of this volume is to encourage the use of systems-level methodologies to contribute to the improvement of human-health . We intend to motivate biomedical researchers to complement their current theoretical and empirical practice with up-to-date systems biology conceptual approaches. Our perspective is based on the deep understanding of the key biomolecular regulatory mechanisms that underlie health, as well as the emergence and progression of human-disease . We strongly believe that the contemporary systems biology perspective opens the door to the effective development of novel methodologies to the improvement of prevention . This requires a deeper and integrative understanding of the involved underlying systems-level mechanisms. In order to explain our proposal in a simple way, in this chapter we privilege the conceptual exposition of our chosen framework over formal considerations. The formal exposition of our proposal will be expanded and discussed later in the next chapters.

PMID: 30076565 [PubMed - in process]

Fitting mathematical models of biochemical pathways to steady state perturbation response data without simulating perturbation experiments.

Sci Rep. 2018 Aug 03;8(1):11679

Authors: Santra T

Abstract
Fitting Ordinary Differential Equation (ODE) models of signal transduction networks (STNs) to experimental data is a challenging problem. Computational parameter fitting algorithms simulate a model many times with different sets of parameter values until the simulated STN behaviour match closely with experimental data. This process can be slow when the model is fitted to measurements of STN responses to numerous perturbations, since this requires simulating the model as many times as the number of perturbations for each set of parameter values. Here, I propose an approach that avoids simulating perturbation experiments when fitting ODE models to steady state perturbation response (SSPR) data. Instead of fitting the model directly to SSPR data, it finds model parameters which provides a close match between the scaled Jacobian matrices (SJM) of the model, which are numerically calculated using the model's rate equations and estimated from SSPR data using modular response analysis (MRA). The numerical estimation of SJM of an ODE model does not require simulating perturbation experiments, saving significant computation time. The effectiveness of this approach is demonstrated by fitting ODE models of the Mitogen Activated Protein Kinase (MAPK) pathway using simulated and real SSPR data.

PMID: 30076370 [PubMed - in process]

The molecular genetic basis of herbivory between butterflies and their host plants.

Nat Ecol Evol. 2018 Aug 03;:

Authors: Nallu S, Hill JA, Don K, Sahagun C, Zhang W, Meslin C, Snell-Rood E, Clark NL, Morehouse NI, Bergelson J, Wheat CW, Kronforst MR

Abstract
Interactions between herbivorous insects and their host plants are a central component of terrestrial food webs and a critical topic in agriculture, where a substantial fraction of potential crop yield is lost annually to pests. Important insights into plant-insect interactions have come from research on specific plant defences and insect detoxification mechanisms. Yet, much remains unknown about the molecular mechanisms that mediate plant-insect interactions. Here we use multiple genome-wide approaches to map the molecular basis of herbivory from both plant and insect perspectives, focusing on butterflies and their larval host plants. Parallel genome-wide association studies in the cabbage white butterfly, Pieris rapae, and its host plant, Arabidopsis thaliana, pinpointed a small number of butterfly and plant genes that influenced herbivory. These genes, along with much of the genome, were regulated in a dynamic way over the time course of the feeding interaction. Comparative analyses, including diverse butterfly/plant systems, showed a variety of genome-wide responses to herbivory, as well as a core set of highly conserved genes in butterflies as well as their host plants. These results greatly expand our understanding of the genomic causes and evolutionary consequences of ecological interactions across two of nature's most diverse taxa, butterflies and flowering plants.

PMID: 30076351 [PubMed - as supplied by publisher]

Global rewiring of cellular metabolism renders Saccharomyces cerevisiae Crabtree negative.

Nat Commun. 2018 Aug 03;9(1):3059

Authors: Dai Z, Huang M, Chen Y, Siewers V, Nielsen J

Abstract
Saccharomyces cerevisiae is a Crabtree-positive eukaryal model organism. It is believed that the Crabtree effect has evolved as a competition mechanism by allowing for rapid growth and production of ethanol at aerobic glucose excess conditions. This inherent property of yeast metabolism and the multiple mechanisms underlying it require a global rewiring of the entire metabolic network to abolish the Crabtree effect. Through rational engineering of pyruvate metabolism combined with adaptive laboratory evolution (ALE), we demonstrate that it is possible to obtain such a global rewiring and hereby turn S. cerevisiae into a Crabtree-negative yeast. Using integrated systems biology analysis, we identify that the global rewiring of cellular metabolism is accomplished through a mutation in the RNA polymerase II mediator complex, which is also observed in cancer cells expressing the Warburg effect.

PMID: 30076310 [PubMed - in process]

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

"systems biology"

These pubmed results were generated on 2018/08/04

PubMed comprises more than millions of 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.

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

"systems biology"

These pubmed results were generated on 2018/08/03

PubMed comprises more than millions of 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.