15 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 2017/04/13

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24 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 2017/04/12

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.

21 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 2017/04/11

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.

Targeted gene disruption coupled with metabolic screen approach to uncover the LEAFY COTYLEDON1-LIKE4 (L1L4) function in tomato fruit metabolism.

Plant Cell Rep. 2017 Apr 08;:

Authors: Gago C, Drosou V, Paschalidis K, Guerreiro A, Miguel G, Antunes D, Hilioti Z

Abstract
KEY MESSAGE: Functional analysis of tomato L1L4 master transcription factor resulted in important metabolic changes affecting tomato fruit quality. Tomato fruits from mutant lines bearing targeted disruption of the heterotrimeric nuclear transcription factor Y (NF-Y) transcription factor (TF) gene LEAFY-COTYLEDON1-LIKE4 (L1L4, NF-YB6), a master regulator of biosynthesis for seed storage proteins and fatty acids, were evaluated for metabolites content and morphology. Metabolic screens using LC-MS/MS-based analysis and physico-chemical methods in different L1L4 mutants of the fourth generation allowed a comparative assessment of the effects of the TF disruption. Mutagenesis resulted in fruits phenotypically similar to wild-type with subtle shape differences in the distal end protrusion and symmetry. Conversely, mutant fruits from independent lines had significant variation in moisture content, titratable acidity and overall metabolite profiles including oxalic and citric acid, fructose, β-carotene, total polyphenols and antioxidants. Lines 6, 7 and 9 were the richest in β-carotene and antioxidant activity, line 4 in ascorbic acid and lines 4 and 8 in succinic acid. The reduced content of the anti-nutrient oxalic acid in several mutant fruits suggests that L1L4 gene may regulate the accumulation of this compound during fruit development. Detailed LC-MS/MS analysis of mutant seeds showed substantial differences in bioactive compounds compared to wild-type seeds. Taken together, the results suggest that the L1L4 TF is a significant regulator of metabolites both in tomato fruit and seeds providing a molecular target for crop improvement. Elucidation of the candidate genes encoding key enzymes in the affected metabolic pathways aimed to facilitate the L1L4 gene network exploration and eventually lead to systems biology approaches in tomato fruit quality.

PMID: 28391527 [PubMed - as supplied by publisher]

Clinical phenotypes and endophenotypes of atopic dermatitis: Where are we, and where should we go?

J Allergy Clin Immunol. 2017 Apr;139(4S):S58-S64

Authors: Bieber T, D'Erme AM, Akdis CA, Traidl-Hoffmann C, Lauener R, Schäppi G, Schmid-Grendelmeier P

Abstract
Atopic dermatitis (AD) is a paradigmatic chronic inflammatory skin disease characterized by a complex pathophysiology and a wide spectrum of the clinical phenotype. Despite this high degree of heterogeneity, AD is still considered a single disease and usually treated according to the "one-size-fits-all" approach. Thus more tailored prevention and therapeutic strategies are still lacking. As for other disciplines, such as oncology or rheumatology, we have to approach AD in a more differentiated way (ie, to dissect and stratify the complex clinical phenotype into more homogeneous subgroups based on the endophenotype [panel of biomarkers]) with the aim to refine the management of this condition. Because we are now entering the era of personalized medicine, a systems biology approach merging the numerous clinical phenotypes with robust (ie, relevant and validated) biomarkers will be needed to best exploit their potential significance for the future molecular taxonomy of AD. This approach will not only allow an optimized prevention and treatment with the available drugs but also hopefully help assign newly developed medicinal products to those patients who will have the best benefit/risk ratio.

PMID: 28390478 [PubMed - in process]

Class-paired Fuzzy SubNETs: A paired variant of the rank-based network analysis family for feature selection based on protein complexes.

Proteomics. 2017 Apr 08;:

Authors: Goh WW, Wong L

Abstract
Identifying reproducible yet relevant protein features in proteomics data is a major challenge. Analysis at the level of protein complexes can resolve this issue and we have developed a suite of feature-selection methods collectively referred to as Rank-Based Network Analysis (RBNA). RBNAs differ in their individual statistical test setup but are similar in the sense that they deploy rank-defined weights amongst proteins per sample. This procedure is known as gene fuzzy scoring. Currently, no RBNA exists for paired-sample scenarios where both control and test tissues originate from the same source (e.g. same patient). It is expected that paired tests, when used appropriately, are more powerful than approaches intended for unpaired samples. We report that the class-paired RBNA, PPFSNET, dominates in both simulated and real data scenarios. Moreover, for the first time, we explicitly incorporate batch-effect resistance as an additional evaluation criterion for feature-selection approaches. Batch effects are class irrelevant variations arising from different handlers or processing times, and can obfuscate analysis. We demonstrate that PPFSNET and PFSNET, are particularly resistant against batch effects, and only select features strongly correlated with class but not batch. This article is protected by copyright. All rights reserved.

PMID: 28390171 [PubMed - as supplied by publisher]

Taxonomy of the order Mononegavirales: update 2017.

Arch Virol. 2017 Apr 07;:

Authors: Amarasinghe GK, Bào Y, Basler CF, Bavari S, Beer M, Bejerman N, Blasdell KR, Bochnowski A, Briese T, Bukreyev A, Calisher CH, Chandran K, Collins PL, Dietzgen RG, Dolnik O, Dürrwald R, Dye JM, Easton AJ, Ebihara H, Fang Q, Formenty P, Fouchier RA, Ghedin E, Harding RM, Hewson R, Higgins CM, Hong J, Horie M, James AP, Jiāng D, Kobinger GP, Kondo H, Kurath G, Lamb RA, Lee B, Leroy EM, Li M, Maisner A, Mühlberger E, Netesov SV, Nowotny N, Patterson JL, Payne SL, Paweska JT, Pearson MN, Randall RE, Revill PA, Rima BK, Rota P, Rubbenstroth D, Schwemmle M, Smither SJ, Song Q, Stone DM, Takada A, Terregino C, Tesh RB, Tomonaga K, Tordo N, Towner JS, Vasilakis N, Volchkov VE, Wahl-Jensen V, Walker PJ, Wang B, Wang D, Wang F, Wang LF, Werren JH, Whitfield AE, Yan Z, Ye G, Kuhn JH

Abstract
In 2017, the order Mononegavirales was expanded by the inclusion of a total of 69 novel species. Five new rhabdovirus genera and one new nyamivirus genus were established to harbor 41 of these species, whereas the remaining new species were assigned to already established genera. Furthermore, non-Latinized binomial species names replaced all paramyxovirus and pneumovirus species names, thereby accomplishing application of binomial species names throughout the entire order. This article presents the updated taxonomy of the order Mononegavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV).

PMID: 28389807 [PubMed - as supplied by publisher]

Experimental evaluation of host adaptation of Lactobacillus reuteri to different vertebrate species.

Appl Environ Microbiol. 2017 Apr 07;:

Authors: Duar RM, Frese SA, Lin XB, Fernando SC, Burkey TE, Tasseva G, Peterson DA, Blom J, Wenzel CQ, Szymanski CM, Walter J

Abstract
The species Lactobacillus reuteri has diversified into host-specific lineages implying a long term association with different vertebrates. Strains from rodent lineages show specific adaptations to mice, but the processes underlying the evolution of L. reuteri in other hosts remain unknown. We administered three standardized inocula composed of strains from different host-confined lineages to mice, pigs, chickens and humans. The ecological performance of each strain in the gastrointestinal tract of each host was determined by typing random colonies recovered from fecal samples collected over five consecutive days post-administration. Results revealed that rodent strains were predominant in mice, confirming previous findings of host adaptation. In chickens, poultry strains of the lineage-VI (poultry-VI) and human isolates from the same lineage (human-VI) were recovered at the highest second highest rate, respectively. Interestingly, human-VI strains were virtually undetected in human feces. These findings together with ancestral state reconstructions indicate poultry-VI and human-VI strains share an evolutionary history with chickens. Genomic analysis revealed that poultry-VI strains possess a large and variable accessory genome, whereas human-VI strains display low genetic diversity and possess genes encoding antibiotic resistance and capsular polysaccharide synthesis which might have allowed temporal colonization of humans. Experiments in pigs and humans did not provide evidence of host-adaptation of L. reuteri to these hosts. Overall, our findings demonstrate host adaptation of L. reuteri to rodents and chickens, supporting a joint evolution of this bacterial species with several vertebrate hosts, although questions remain about its natural history in humans and pigs.IMPORTANCE Gut microbes are often hypothesized to have co-evolved with their vertebrate hosts. However, the evidence is sparse and the evolutionary mechanisms have not been identified. We developed and applied an experimental approach to determine host adaptation of L. reuteri to different hosts. Our findings confirm adaptation to rodents and provide evidence of adaptation to poultry, suggesting that L. reuteri evolved via natural selection in different hosts. By complementing phylogenetic analyses with experimental evidence, this study provides novel information about the mechanisms driving host-microbe co-evolution with vertebrates and serve as a basis to inform the application of L. reuteri as a probiotic for different host species.

PMID: 28389535 [PubMed - as supplied by publisher]

Epigenetic Regulation of KPC1 Ubiquitin Ligase Effects the NF-κB Pathway in Melanoma.

Clin Cancer Res. 2017 Apr 07;:

Authors: Iida Y, Ciechanover A, Marzese DM, Hata K, Bustos M, Ono S, Wang J, Salomon MP, Tran K, Lam S, Hsu SC, Nelson N, Kravtsova-Ivantsiv Y, Mills GB, Davies MA, Hoon DS

Abstract
PURPOSE: Abnormal activation of the NF-κB pathway induces a more aggressive phenotype of cutaneous melanoma. Understanding the mechanisms involved in melanoma NF-κB activation may identify novel targets for this pathway. KPC1, an E3 ubiquitin ligase, is a regulator of NF-κB pathway. The objective of this study was to investigate the mechanisms regulating KPC1 expression and its clinical impact in melanoma.
EXPERIMENTAL DESIGN: The clinical impact of KPC1 expression and its epigenetic regulation were assessed in large cohorts of clinically well-annotated melanoma tissues (tissue micro-arrays; n=137, JWCI cohort; n=40) and The Cancer Genome Atlas database (TCGA cohort, n=370). Using melanoma cell lines, we investigated the functional interactions between KPC1 and NF-κB, and the epigenetic regulations of KPC1, including DNA methylation and microRNA expression.
RESULTS: We verified that KPC1 suppresses melanoma proliferation by processing NF-κB1 p105 into p50, thereby modulating NF-κB-target gene expression. Concordantly, KPC1 expression was down-regulated in AJCC stage IV melanoma compared to early stages (stage I/II p=0.013, stage III p=0.004), and low KPC1 expression was significantly associated with poor overall survival in stage IV melanoma (n=137, Hazard Ratio 1.810, p=0.006). Furthermore, our data showed that high miR-155-5p expression, which is controlled by DNA methylation at its promoter region (TCGA; Pearson's r -0.455, p<0.001), is significantly associated with KPC1 down-regulation (JWCI; p=0.028, TCGA; p=0.003).
CONCLUSIONS: This study revealed novel epigenetic regulation of KPC1 associated with NF-κB pathway activation, promoting metastatic melanoma progression. These findings suggest the potential utility of KPC1 and its epigenetic regulation as theranostic targets.

PMID: 28389511 [PubMed - as supplied by publisher]

Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites.

Metab Eng. 2017 Apr 04;:

Authors: Lafontaine Rivera JG, Theisen MK, Chen PW, Liao JC

Abstract
The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realistic quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.

PMID: 28389394 [PubMed - as supplied by publisher]

An engineering paradigm in the biomedical sciences: Knowledge as epistemic tool.

Prog Biophys Mol Biol. 2017 Apr 04;:

Authors: Boon M

Abstract
In order to deal with the complexity of biological systems and attempts to generate applicable results, current biomedical sciences are adopting concepts and methods from the engineering sciences. Philosophers of science have interpreted this as the emergence of an engineering paradigm, in particular in systems biology and synthetic biology. This article aims at the articulation of the supposed engineering paradigm by contrast with the physics paradigm that supported the rise of biochemistry and molecular biology. This articulation starts from Kuhn's notion of a disciplinary matrix, which indicates what constitutes a paradigm. It is argued that the core of the physics paradigm is its metaphysical and ontological presuppositions, whereas the core of the engineering paradigm is the epistemic aim of producing useful knowledge for solving problems external to the scientific practice. Therefore, the two paradigms involve distinct notions of knowledge. Whereas the physics paradigm entails a representational notion of knowledge, the engineering paradigm involves the notion of 'knowledge as epistemic tool'.

PMID: 28389261 [PubMed - as supplied by publisher]

Shape of my heart: cell-cell adhesion and cytoskeletal dynamics during Drosophila cardiac morphogenesis.

Exp Cell Res. 2017 Apr 04;:

Authors: McFaul CM, Fernandez-Gonzalez R

Abstract
The fruit fly Drosophila melanogaster has recently emerged as an excellent system to investigate the genetics of cardiovascular development and disease. Drosophila provides an inexpensive and genetically-tractable in vivo system with a large number of conserved features. In addition, the Drosophila embryo is transparent, and thus amenable to time-lapse fluorescence microscopy, as well as biophysical and pharmacological manipulations. One of the conserved aspects of heart development from Drosophila to humans is the initial assembly of a tube. Here, we review the cellular behaviours and molecular dynamics important for the initial steps of heart morphogenesis in Drosophila, with particular emphasis on the cell-cell adhesion and cytoskeletal networks that cardiac precursors use to move, coordinate their migration, interact with other tissues and eventually sculpt a beating heart.

PMID: 28389210 [PubMed - as supplied by publisher]

A Tunable Diffusion-Consumption Mechanism of Cytokine Propagation Enables Plasticity in Cell-to-Cell Communication in the Immune System.

Immunity. 2017 Mar 28;:

Authors: Oyler-Yaniv A, Oyler-Yaniv J, Whitlock BM, Liu Z, Germain RN, Huse M, Altan-Bonnet G, Krichevsky O

Abstract
Immune cells communicate by exchanging cytokines to achieve a context-appropriate response, but the distances over which such communication happens are not known. Here, we used theoretical considerations and experimental models of immune responses in vitro and in vivo to quantify the spatial extent of cytokine communications in dense tissues. We established that competition between cytokine diffusion and consumption generated spatial niches of high cytokine concentrations with sharp boundaries. The size of these self-assembled niches scaled with the density of cytokine-consuming cells, a parameter that gets tuned during immune responses. In vivo, we measured interactions on length scales of 80-120 μm, which resulted in a high degree of cell-to-cell variance in cytokine exposure. Such heterogeneous distributions of cytokines were a source of non-genetic cell-to-cell variability that is often overlooked in single-cell studies. Our findings thus provide a basis for understanding variability in the patterning of immune responses by diffusible factors.

PMID: 28389069 [PubMed - as supplied by publisher]

Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence.

BMC Genomics. 2017 Apr 07;18(1):282

Authors: Ampattu BJ, Hagmann L, Liang C, Dittrich M, Schlüter A, Blom J, Krol E, Goesmann A, Becker A, Dandekar T, Müller T, Schoen C

Abstract
BACKGROUND: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence.
RESULTS: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region.
CONCLUSIONS: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.

PMID: 28388876 [PubMed - in process]

Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data.

BMC Bioinformatics. 2017 Apr 07;18(1):207

Authors: Greenwald WW, Li H, Smith EN, Benaglio P, Nariai N, Frazer KA

Abstract
BACKGROUND: Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and analysis tools exist for storing and manipulating single locus NGS data, there is currently no file standard or analysis tool suite for manipulating and storing paired-genomic-loci: the data type resulting from "genomic interaction" studies. As genomic interaction sequencing data are becoming prevalent, a standard file format and tools for working with these data conveniently and efficiently are needed.
RESULTS: This article details a file standard and novel software tool suite for working with paired-genomic-loci data. We present the paired-genomic-loci (PGL) file standard for genomic-interactions data, and the accompanying analysis tool suite "pgltools": a cross platform, pypy compatible python package available both as an easy-to-use UNIX package, and as a python module, for integration into pipelines of paired-genomic-loci analyses.
CONCLUSIONS: Pgltools is a freely available, open source tool suite for manipulating paired-genomic-loci data. Source code, an in-depth manual, and a tutorial are available publicly at www.github.com/billgreenwald/pgltools , and a python module of the operations can be installed from PyPI via the PyGLtools module.

PMID: 28388874 [PubMed - in process]

35 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 2017/04/08

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.

29 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 2017/04/07

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.

21 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 2017/04/06

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.

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 2017/04/05

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.

42 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 2017/04/04

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.