Integrated omics approaches provide strategies for rapid erythromycin yield increase in Saccharopolyspora erythraea.

Microb Cell Fact. 2016;15(1):93

Authors: Karničar K, Drobnak I, Petek M, Magdevska V, Horvat J, Vidmar R, Baebler Š, Rotter A, Jamnik P, Fujs Š, Turk B, Fonovič M, Gruden K, Kosec G, Petković H

Abstract
BACKGROUND: Omics approaches have significantly increased our understanding of biological systems. However, they have had limited success in explaining the dramatically increased productivity of commercially important natural products by industrial high-producing strains, such as the erythromycin-producing actinomycete Saccharopolyspora erythraea. Further yield increase is of great importance but requires a better understanding of the underlying physiological processes.
RESULTS: To reveal the mechanisms related to erythromycin yield increase, we have undertaken an integrated study of the genomic, transcriptomic, and proteomic differences between the wild type strain NRRL2338 (WT) and the industrial high-producing strain ABE1441 (HP) of S. erythraea at multiple time points of a simulated industrial bioprocess. 165 observed mutations lead to differences in gene expression profiles and protein abundance between the two strains, which were most prominent in the initial stages of erythromycin production. Enzymes involved in erythromycin biosynthesis, metabolism of branched chain amino acids and proteolysis were most strongly upregulated in the HP strain. Interestingly, genes related to TCA cycle and DNA-repair were downregulated. Additionally, comprehensive data analysis uncovered significant correlations in expression profiles of the erythromycin-biosynthetic genes, other biosynthetic gene clusters and previously unidentified putative regulatory genes. Based on this information, we demonstrated that overexpression of several genes involved in amino acid metabolism can contribute to increased yield of erythromycin, confirming the validity of our systems biology approach.
CONCLUSIONS: Our comprehensive omics approach, carried out in industrially relevant conditions, enabled the identification of key pathways affecting erythromycin yield and suggests strategies for rapid increase in the production of secondary metabolites in industrial environment.

PMID: 27255285 [PubMed - in process]

Systems Biology and Noninvasive Imaging of Atherosclerosis.

Arterioscler Thromb Vasc Biol. 2016 Feb;36(2):e1-8

Authors: Calcagno C, Mulder WJ, Nahrendorf M, Fayad ZA

PMID: 26819466 [PubMed - indexed for MEDLINE]

A tuberculosis ontology for host systems biology.

Tuberculosis (Edinb). 2015 Sep;95(5):570-4

Authors: Levine DM, Dutta NK, Eckels J, Scanga C, Stein C, Mehra S, Kaushal D, Karakousis PC, Salamon H

Abstract
A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a means to readily compare samples from different research groups, a significant quantity of potentially informative data is largely ignored by researchers. To facilitate standardizing data across studies, a simple ontology of TB terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address animal models and experimental systems, and existing clinically focused terminology was modified and adapted. This ontology can be used to annotate host TB data in public databases and collaborations, thereby standardizing database searches and allowing researchers to more easily compare results. To demonstrate the utility of a standard TB ontology for host systems biology, a web application was developed to annotate and compare human and animal model gene expression data sets.

PMID: 26190839 [PubMed - indexed for MEDLINE]

Systems metabolic engineering of microorganisms to achieve large-scale production of flavonoid scaffolds.

J Biotechnol. 2014 Oct 20;188:72-80

Authors: Wu J, Du G, Zhou J, Chen J

Abstract
Flavonoids possess pharmaceutical potential due to their health-promoting activities. The complex structures of these products make extraction from plants difficult, and chemical synthesis is limited because of the use of many toxic solvents. Microbial production offers an alternate way to produce these compounds on an industrial scale in a more economical and environment-friendly manner. However, at present microbial production has been achieved only on a laboratory scale and improvements and scale-up of these processes remain challenging. Naringenin and pinocembrin, which are flavonoid scaffolds and precursors for most of the flavonoids, are the model molecules that are key to solving the current issues restricting industrial production of these chemicals. The emergence of systems metabolic engineering, which combines systems biology with synthetic biology and evolutionary engineering at the systems level, offers new perspectives on strain and process optimization. In this review, current challenges in large-scale fermentation processes involving flavonoid scaffolds and the strategies and tools of systems metabolic engineering used to overcome these challenges are summarized. This will offer insights into overcoming the limitations and challenges of large-scale microbial production of these important pharmaceutical compounds.

PMID: 25160917 [PubMed - indexed for MEDLINE]

Xenbase: Core features, data acquisition, and data processing.

Genesis. 2015 Aug;53(8):486-97

Authors: James-Zorn C, Ponferrada VG, Burns KA, Fortriede JD, Lotay VS, Liu Y, Brad Karpinka J, Karimi K, Zorn AM, Vize PD

Abstract
Xenbase, the Xenopus model organism database (www.xenbase.org), is a cloud-based, web-accessible resource that integrates the diverse genomic and biological data from Xenopus research. Xenopus frogs are one of the major vertebrate animal models used for biomedical research, and Xenbase is the central repository for the enormous amount of data generated using this model tetrapod. The goal of Xenbase is to accelerate discovery by enabling investigators to make novel connections between molecular pathways in Xenopus and human disease. Our relational database and user-friendly interface make these data easy to query and allows investigators to quickly interrogate and link different data types in ways that would otherwise be difficult, time consuming, or impossible. Xenbase also enhances the value of these data through high-quality gene expression curation and data integration, by providing bioinformatics tools optimized for Xenopus experiments, and by linking Xenopus data to other model organisms and to human data. Xenbase draws in data via pipelines that download data, parse the content, and save them into appropriate files and database tables. Furthermore, Xenbase makes these data accessible to the broader biomedical community by continually providing annotated data updates to organizations such as NCBI, UniProtKB, and Ensembl. Here, we describe our bioinformatics, genome-browsing tools, data acquisition and sharing, our community submitted and literature curation pipelines, text-mining support, gene page features, and the curation of gene nomenclature and gene models.

PMID: 26150211 [PubMed - indexed for MEDLINE]

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

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/06/03

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.

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

IEEE/ACM Trans Comput Biol Bioinform. 2015 Mar-Apr;12(2):309-21

Authors: Young-Rae Cho, Yanan Xin, Speegle G

Abstract
Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

PMID: 26357219 [PubMed - indexed for MEDLINE]

Pharmacogenomic incidental findings in 308 families: The NIH Undiagnosed Diseases Program experience.

Genet Med. 2016 Jun 2;

Authors: Lee EM, Xu K, Mosbrook E, Links A, Guzman J, Adams DR, Flynn E, Valkanas E, Toro C, Tifft CJ, Boerkoel CF, Gahl WA, Sincan M

Abstract
PURPOSE: Using single-nucleotide polymorphism (SNP) chip and exome sequence data from individuals participating in the National Institutes of Health (NIH) Undiagnosed Diseases Program (UDP), we evaluated the number and therapeutic informativeness of incidental pharmacogenetic variants.
METHODS: Pharmacogenomics Knowledgebase (PharmGKB) annotated sequence variants were identified in 1,101 individuals. Medication records of participants were used to identify individuals prescribed medications with a genetic variant that might alter efficacy.
RESULTS: A total of 395 sequence variants, including 19 PharmGKB 1A and 1B variants, were identified in SNP chip sequence data, and 388 variants, including 21 PharmGKB 1A and 1B variants, were identified in the exome sequence data. Nine participants had incidental pharmacogenetic variants associated with altered efficacy of a prescribed medication.
CONCLUSIONS: Despite the small size of the NIH UDP patient cohort, we identified pharmacogenetic incidental findings potentially useful for guiding therapy. Consequently, groups conducting clinical genomic studies might consider reporting of pharmacogenetic incidental findings.Genet Med advance online publication 02 June 2016Genetics in Medicine (2016); doi:10.1038/gim.2016.47.

PMID: 27253732 [PubMed - as supplied by publisher]

Pharmacogenomics of preterm birth prevention and treatment.

BJOG. 2016 Feb;123(3):368-75

Authors: Manuck TA

Abstract
UNLABELLED: Pharmacogenomics and personalised medicine incorporate genetic factors, historical data, and environmental exposures to predict individual variation in response to medications. The study of pharmacology and pharmacogenomics is challenging in obstetrics, and our knowledge in this area lags behind other disciplines of medicine. Some preliminary data, however, suggest that some of the interindividual variation seen in response to medications given for the prevention (progesterone) and the treatment (nifedipine, terbutaline, and others) of preterm labour may be caused by pharmacogenomic effects. A comprehensive approach, integrating clinical data, environmental factors, including concomitant medications and genotype, to optimise the prevention and treatment strategies for preterm birth, is urgently needed.
TWEETABLE ABSTRACT: Some of the variation to meds for prematurity prevention/treatment may arise from pharmacogenomic effects.

PMID: 26542879 [PubMed - indexed for MEDLINE]

CAR-engineered cytokine-induced killer cells overcome treatment resistance of pre-B-ALL and enhance survival.

Int J Cancer. 2016 Jun 2;

Authors: Oelsner S, Wagner J, Friede ME, Pfirrmann V, Genßler S, Rettinger E, Buchholz CJ, Pfeifer H, Schubert R, Ottmann OG, Ullrich E, Bader P, Wels WS

Abstract
Pre-emptive cancer immunotherapy by donor lymphocyte infusion (DLI) using cytokine-induced killer (CIK) cells may be beneficial to prevent relapse with a reduced risk of causing graft-versus-host-disease (GvHD). CIK cells are a heterogeneous effector cell population including T cells (CD3(+) CD56(-) ), natural killer (NK) cells (CD3(-) CD56(+) ) and natural killer T (T-NK) cells (CD3(+) CD56(+) ) that exhibit non-MHC-restricted cytotoxicity and are generated by ex vivo expansion of peripheral blood mononuclear cells (PBMC) in the presence of interferon (IFN)-γ, anti-CD3 antibody, interleukin-2 (IL-2) and interleukin-15 (IL-15). To facilitate selective target-cell recognition and enhance specific cytotoxicity against B-cell acute lymphoblastic leukemia (B-ALL), we transduced CIK cells with a lentiviral vector encoding a chimeric antigen receptor (CAR) that carries a composite CD28-CD3ζ domain for signaling and a CD19-specific scFv antibody fragment for cell binding (CAR 63.28.z). In vitro analysis revealed high and specific cell killing activity of CD19-targeted CIK/63.28.z cells against otherwise CIK-resistant cancer cell lines and primary B-ALL blasts, which was dependent on CD19 expression and CAR signaling. In a xenograft model in immunodeficient mice, treatment with CIK/63.28.z cells in contrast to therapy with unmodified CIK cells resulted in complete and durable molecular remissions of established primary pre-B-ALL. Our results demonstrate potent anti-leukemic activity of CAR-engineered CIK cells in vitro and in vivo, and suggest this strategy as a promising approach for adoptive immunotherapy of refractory pre-B-ALL. This article is protected by copyright. All rights reserved.

PMID: 27253354 [PubMed - as supplied by publisher]

Modeling and Re-Engineering of Azotobacter vinelandii Alginate Lyase to Enhance Its Catalytic Efficiency for Accelerating Biofilm Degradation.

PLoS One. 2016;11(6):e0156197

Authors: Jang CH, Piao YL, Huang X, Yoon EJ, Park SH, Lee K, Zhan CG, Cho H

Abstract
Alginate is known to prevent elimination of Pseudomonas aeruginosa biofilms. Alginate lyase (AlgL) might therefore facilitate treatment of Pseudomonas aeruginosa-infected cystic fibrosis patients. However, the catalytic activity of wild-type AlgL is not sufficiently high. Therefore, molecular modeling and site-directed mutagenesis of AlgL might assist in enzyme engineering for therapeutic development. AlgL, isolated from Azotobacter vinelandii, catalyzes depolymerization of alginate via a β-elimination reaction. AlgL was modeled based on the crystal structure template of Sphingomonas AlgL species A1-III. Based on this computational analysis, AlgL was subjected to site-directed mutagenesis to improve its catalytic activity. The kcat/Km of the K194E mutant showed a nearly 5-fold increase against the acetylated alginate substrate, as compared to the wild-type. Double and triple mutants (K194E/K245D, K245D/K319A, K194E/K245D/E312D, and K194E/K245D/K319A) were also prepared. The most potent mutant was observed to be K194E/K245D/K319A, which has a 10-fold improved kcat value (against acetylated alginate) compared to the wild-type enzyme. The antibiofilm effect of both AlgL forms was identified in combination with piperacillin/tazobactam (PT) and the disruption effect was significantly higher in mutant AlgL combined with PT than wild-type AlgL. However, for both the wild-type and K194E/K245D/K319A mutant, the use of the AlgL enzyme alone did not show significant antibiofilm effect.

PMID: 27253324 [PubMed - as supplied by publisher]

Lumacaftor/ivacaftor combination for cystic fibrosis patients homozygous for Phe508del-CFTR.

Drugs Today (Barc). 2016 Apr;52(4):229-37

Authors: Zhang W, Zhang X, Zhang YH, Strokes DC, Naren AP

Abstract
Cystic fibrosis (CF) is a life-shortening inherited disease caused by the loss or dysfunction of the CF transmembrane conductance regulator (CFTR) channel activity resulting from mutations in the CFTR gene. Phe508del is the most prevalent mutation, with approximately 90% of all CF patients carrying it on at least one allele. Over the past two or three decades, significant progress has been made in understanding the pathogenesis of CF, and in the development of effective CF therapies. The approval of Orkambi(R) (lumacaftor/ivacaftor) marks another milestone in CF therapeutics development, which, with the advent of personalized medicine, could potentially revolutionize CF care and management. This article reviews the rationale, progress and future direction in the development of lumacaftor/ivacaftor combination to treat CF patients.

PMID: 27252987 [PubMed - in process]

Heme Mobilization in Animals: A Metallolipid's Journey.

Acc Chem Res. 2016 Jun 2;

Authors: Reddi AR, Hamza I

Abstract
Heme is universally recognized as an essential and ubiquitous prosthetic group that enables proteins to carry out a diverse array of functions. All heme-dependent processes, from protein hemylation to heme signaling, require the dynamic and rapid mobilization of heme to hemoproteins present in virtually every subcellular compartment. The cytotoxicity and hydrophobicity of heme necessitates that heme mobilization is carefully controlled at the cellular and systemic level. However, the molecules and mechanisms that mediate heme homeostasis are poorly understood. In this Account, we provide a heuristic paradigm with which to conceptualize heme trafficking and highlight the most recent developments in the mechanisms underlying heme trafficking. As an iron-containing tetrapyrrole, heme exhibits properties of both transition metals and lipids. Accordingly, we propose its transport and trafficking will reflect principles gleaned from the trafficking of both metals and lipids. Using this conceptual framework, we follow the flow of heme from the final step of heme synthesis in the mitochondria to hemoproteins present in various subcellular organelles. Further, given that many cells and animals that cannot make heme can assimilate it intact from nutritional sources, we propose that intercellular heme trafficking pathways must exist. This necessitates that heme be able to be imported and exported from cells, escorted between cells and organs, and regulated at the organismal level via a coordinated systemic process. In this Account, we highlight recently discovered heme transport and trafficking factors and provide the biochemical foundation for the cell and systems biology of heme. Altogether, we seek to reconceptualize heme from an exchange inert cofactor buried in hemoprotein active sites to an exchange labile and mobile metallonutrient.

PMID: 27254265 [PubMed - as supplied by publisher]

Metabolomic Analysis in Brain Research: Opportunities and Challenges.

Front Physiol. 2016;7:183

Authors: Vasilopoulou CG, Margarity M, Klapa MI

Abstract
Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.

PMID: 27252656 [PubMed]

Impact of Pathogen Population Heterogeneity and Stress-Resistant Variants on Food Safety.

Annu Rev Food Sci Technol. 2016;7:439-56

Authors: Abee T, Koomen J, Metselaar KI, Zwietering MH, den Besten HM

Abstract
This review elucidates the state-of-the-art knowledge about pathogen population heterogeneity and describes the genotypic and phenotypic analyses of persister subpopulations and stress-resistant variants. The molecular mechanisms underlying the generation of persister phenotypes and genetic variants are identified. Zooming in on Listeria monocytogenes, a comparative whole-genome sequence analysis of wild types and variants that enabled the identification of mutations in variants obtained after a single exposure to lethal food-relevant stresses is described. Genotypic and phenotypic features are compared to those for persistent strains isolated from food processing environments. Inactivation kinetics, models used for fitting, and the concept of kinetic modeling-based schemes for detection of variants are presented. Furthermore, robustness and fitness parameters of L. monocytogenes wild type and variants are used to model their performance in food chains. Finally, the impact of stress-resistant variants and persistence in food processing environments on food safety is discussed.

PMID: 26772414 [PubMed - indexed for MEDLINE]

Advancing metabolic engineering through systems biology of industrial microorganisms.

Curr Opin Biotechnol. 2015 Dec;36:8-15

Authors: Dai Z, Nielsen J

Abstract
Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further.

PMID: 26318074 [PubMed - indexed for MEDLINE]

A Systems Biology Perspective on the Molecular Mechanisms Underlying the Therapeutic Effects of Buyang Huanwu Decoction on Ischemic Stroke.

Rejuvenation Res. 2015 Aug;18(4):313-25

Authors: Guo Q, Zhong M, Xu H, Mao X, Zhang Y, Lin N

Abstract
Ischemic stroke is the leading cause of adult disability worldwide. The outcome is worse in older patients, especially in terms of disability. Buyang Huanwu decoction (BHD), a famous traditional Chinese medicine formula, has been used extensively in the treatment of ischemic stroke for centuries. However, its pharmacological mechanisms have not been fully elucidated. In this study, 82 putative targets for 411 composite compounds contained in BHD were predicted on the basis of our previously developed target prediction system. On the basis of large-scale molecular docking, more than 80% compound-putative target pairs had medium to strong binding efficiency. The pharmacological networks of BHD were built according to relationships among herbs, putative targets, and known therapeutic targets for ischemic stroke, and 121 major nodes were identified by calculating three topological features-degree, node betweenness, and closeness. Importantly, the pathway enrichment analysis identified several signaling pathways involved with major putative targets of BHD, such as the calcium signaling pathway, vascular smooth muscle contraction, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway, which have not hitherto been reported. These data are expected to help find new therapeutic effects of BHD and optimize clinical use of this formula. Collectively, our study developed a comprehensive systems approach integrating drug target prediction and network and functional analyses to reveal the relationships of the herbs in BHD with their putative targets, and for the first time with ischemic stroke-related pathway systems. This is a pilot study based on bioinformatics analysis; thus, further experimental studies are required to validate our findings.

PMID: 25687091 [PubMed - indexed for MEDLINE]

Autism cornered: network analyses reveal mechanisms of autism spectrum disorders.

Mol Syst Biol. 2014;10:778

Authors: Auffray C

Abstract
Despite a wealth of behavioral, cognitive,biological, and genetic studies, the causes of autism have remained largely unknown.In their recent work, Snyder and colleagues(Li et al, 2014) use a systems biology approach and shed light on the molecular and cellular mechanisms underlying autism, thus opening novel avenues forunderstanding the disease and developing potential treatments.

PMID: 25549969 [PubMed - indexed for MEDLINE]

Systematic analysis of the molecular mechanism underlying atherosclerosis using a text mining approach.

Hum Genomics. 2016;10(1):14

Authors: Xi D, Zhao J, Lai W, Guo Z

Abstract
BACKGROUND: Atherosclerosis is one of the common health threats all over the world. It is a complex heritable disease that affects arterial blood vessels. Chronic inflammatory response plays an important role in atherogenesis. There has been little success in fully identifying functionally important genes in the pathogenesis of atherosclerosis.
RESULTS: In the present study, we performed a systematic analysis of atherosclerosis-related genes using text mining. We identified a total of 1312 genes. Gene ontology (GO) analysis revealed that a total of 35 terms exhibited significance (p < 0.05) as overrepresented terms, indicating that atherosclerosis invokes many genes with a wide range of different functions. Pathway analysis demonstrated that the most highly enriched pathway is the Toll-like receptor signaling pathway. Finally, through gene network analysis, we prioritized 48 genes using the hub gene method.
CONCLUSIONS: Our study provides a valuable resource for the in-depth understanding of the mechanism underlying atherosclerosis.

PMID: 27251057 [PubMed - in process]

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

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/06/02

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.