Integrative workflows for network analysis.

Essays Biochem. 2018 Oct 26;62(4):549-561

Authors: Khan FM, Gupta SK, Wolkenhauer O

Abstract
Due to genetic heterogeneity across patients, the identification of effective disease signatures and therapeutic targets is challenging. Addressing this challenge, we have previously developed a network-based approach, which integrates heterogeneous sources of biological information to identify disease specific core-regulatory networks. In particular, our workflow uses a multi-objective optimization function to calculate a ranking score for network components (e.g. feedback/feedforward loops) based on network properties, biomedical and high-throughput expression data. High ranked network components are merged to identify the core-regulatory network(s) that is then subjected to dynamical analysis using stimulus-response and in silico perturbation experiments for the identification of disease gene signatures and therapeutic targets. In a case study, we implemented our workflow to identify bladder and breast cancer specific core-regulatory networks underlying epithelial-mesenchymal transition from the E2F1 molecular interaction map.In this study, we review our workflow and described how it has developed over time to understand the mechanisms underlying disease progression and prediction of signatures for clinical decision making.

PMID: 30366988 [PubMed - in process]

Systems biology: old news or new stimulus for biochemistry.

Essays Biochem. 2018 Oct 26;62(4):483-486

Authors: Kolch W, Fey D, Ryan CJ

Abstract
In this issue of Essays in Biochemistry, biochemistry meets systems biology-a blind date that may hold all the promises, pitfalls and failures of a relationship where a new discipline has been sprung upon a well-established one. As the articles in this issue show, the blind date in this case has great potential to develop into a long-term relationship, where both partners share common values but can benefit from different complementary approaches. Together this partnership is well poised to address and solve some of the major challenges in modern biology.

PMID: 30366987 [PubMed - in process]

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 2018/10/27

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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 2018/10/27

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63 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 2018/10/26

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61 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 2018/10/26

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30 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 2018/10/24

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.

30 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 2018/10/24

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.

22 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 2018/10/23

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.

Diabetic Cardiomyopathy Modelling Using Induced Pluripotent Stem Cell Derived Cardiomyocytes: Recent Advances and Emerging Models.

Stem Cell Rev. 2018 Oct 20;:

Authors: Granéli C, Hicks R, Brolén G, Synnergren J, Sartipy P

Abstract
The global burden of diabetes has drastically increased over the past decades and in 2017 approximately 4 million deaths were caused by diabetes and cardiovascular complications. Diabetic cardiomyopathy is a common complication of diabetes with early manifestations of diastolic dysfunction and left ventricular hypertrophy with subsequent progression to systolic dysfunction and ultimately heart failure. An in vitro model accurately recapitulating key processes of diabetic cardiomyopathy would provide a useful tool for investigations of underlying disease mechanisms to further our understanding of the disease and thereby potentially advance treatment strategies for patients. With their proliferative capacity and differentiation potential, human induced pluripotent stem cells (iPSCs) represent an appealing cell source for such a model system and cardiomyocytes derived from induced pluripotent stem cells have been used to establish other cardiovascular related disease models. Here we review recently made advances and discuss challenges still to be overcome with regard to diabetic cardiomyopathy models, with a special focus on iPSC-based systems. Recent publications as well as preliminary data presented here demonstrate the feasibility of generating cardiomyocytes with a diabetic phenotype, displaying insulin resistance, impaired calcium handling and hypertrophy. However, capturing the full metabolic- and functional phenotype of the diabetic cardiomyocyte remains to be accomplished.

PMID: 30343468 [PubMed - as supplied by publisher]

Editorial overview: Current Opinion in Microbiology 2018 Special issue 'Microbial systems biology, vol. 45'.

Curr Opin Microbiol. 2018 Oct 17;:

Authors: Hwa T, Sauer U

PMID: 30343003 [PubMed - as supplied by publisher]

Module-detection approaches for the integration of multilevel omics data highlight the comprehensive response of Aspergillus fumigatus to caspofungin.

BMC Syst Biol. 2018 Oct 20;12(1):88

Authors: Conrad T, Kniemeyer O, Henkel SG, Krüger T, Mattern DJ, Valiante V, Guthke R, Jacobsen ID, Brakhage AA, Vlaic S, Linde J

Abstract
BACKGROUND: Omics data provide deep insights into overall biological processes of organisms. However, integration of data from different molecular levels such as transcriptomics and proteomics, still remains challenging. Analyzing lists of differentially abundant molecules from diverse molecular levels often results in a small overlap mainly due to different regulatory mechanisms, temporal scales, and/or inherent properties of measurement methods. Module-detecting algorithms identifying sets of closely related proteins from protein-protein interaction networks (PPINs) are promising approaches for a better data integration.
RESULTS: Here, we made use of transcriptome, proteome and secretome data from the human pathogenic fungus Aspergillus fumigatus challenged with the antifungal drug caspofungin. Caspofungin targets the fungal cell wall which leads to a compensatory stress response. We analyzed the omics data using two different approaches: First, we applied a simple, classical approach by comparing lists of differentially expressed genes (DEGs), differentially synthesized proteins (DSyPs) and differentially secreted proteins (DSePs); second, we used a recently published module-detecting approach, ModuleDiscoverer, to identify regulatory modules from PPINs in conjunction with the experimental data. Our results demonstrate that regulatory modules show a notably higher overlap between the different molecular levels and time points than the classical approach. The additional structural information provided by regulatory modules allows for topological analyses. As a result, we detected a significant association of omics data with distinct biological processes such as regulation of kinase activity, transport mechanisms or amino acid metabolism. We also found a previously unreported increased production of the secondary metabolite fumagillin by A. fumigatus upon exposure to caspofungin. Furthermore, a topology-based analysis of potential key factors contributing to drug-caused side effects identified the highly conserved protein polyubiquitin as a central regulator. Interestingly, polyubiquitin UbiD neither belonged to the groups of DEGs, DSyPs nor DSePs but most likely strongly influenced their levels.
CONCLUSION: Module-detecting approaches support the effective integration of multilevel omics data and provide a deep insight into complex biological relationships connecting these levels. They facilitate the identification of potential key players in the organism's stress response which cannot be detected by commonly used approaches comparing lists of differentially abundant molecules.

PMID: 30342519 [PubMed - in process]

Prevalence and antibiotic susceptibility pattern of CTX-M type extended-spectrum β-lactamases among clinical isolates of gram-negative bacilli in Jimma, Ethiopia.

BMC Infect Dis. 2018 Oct 20;18(1):524

Authors: Zeynudin A, Pritsch M, Schubert S, Messerer M, Liegl G, Hoelscher M, Belachew T, Wieser A

Abstract
BACKGROUND: The prevalence of extended-spectrum β-lactamases (ESBLs) have been reported in clinical isolates obtained from various hospitals in Ethiopia. However, there is no data on the prevalence and antibiotic susceptibility patterns of CTX-M type ESBL produced by Gram-negative bacilli. The aim of this study was to determine the frequency and distribution of the blaCTX-M genes and the susceptibility patterns in ESBL producing clinical isolates of Gram-negative bacilli in Jimma University Specialized Hospital (JUSH), southwest Ethiopia.
METHODS: A total of 224 non-duplicate and pure isolates obtained from clinically apparent infections, were included in the study. Identification of the isolates was performed by MALDI-TOF mass spectrometry. Susceptibility testing and ESBL detection was performed using VITEK® 2, according to EUCAST v4.0 guidelines. Genotypic analysis was performed using Check-MDR CT103 Microarrays.
RESULTS: Of the total 112 (50.0%) isolates screen positive for ESBLs, 63.4% (71/112) tested positive for ESBL encoding genes by Check-MDR array, which corresponds to 91.8% (67/73) of the total Enterobacteriaceae and 10.3% (4/39) of nonfermenting Gram-negative bacilli. Among the total ESBL gene positive isolates, 95.8% (68/71) carried blaCTX-M genes with CTX-M group 1 type15 being predominant (66/68; 97.1% of CTX-M genes). The blaCTX-M carrying Enterobacteriaceae (n = 64) isolates showed no resistance against imipenem and meropenem and a moderate resistance rate against tigecycline (14.1%), fosfomycin (10.9%) and amikacin (1.6%) suggesting the effectiveness of these antibiotics against most isolates. On the other hand, all the blaCTX-M positive Enterobacteriaceae showed a multidrug resistant (MDR) phenotype with remarkable co-resistances (non-susceptibility rates) to aminoglycosides (92.2%), fluoroquinolones (78.1%) and trimethoprim/sulfamethoxazol (92.2%).
CONCLUSIONS: This study demonstrates a remarkably high prevalence of blaCTX-M genes among ESBL-producing isolates. The high level of resistance to β-lactam and non-β-lactam antibiotics as well as the trend to a MDR profile associated with the blaCTX-M genes are alarming and emphasize the need for routine diagnostic antimicrobial susceptibility testing for appropriate choice of antimicrobial therapy.

PMID: 30342476 [PubMed - in process]

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

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These pubmed results were generated on 2018/10/21

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These pubmed results were generated on 2018/10/20

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"systems biology"

These pubmed results were generated on 2018/10/19

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"systems biology"

These pubmed results were generated on 2018/10/18

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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 2018/10/18

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28 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 2018/10/17

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