Adults with cystic fibrosis in Portugal: A first step towards improvement.

Rev Port Pneumol (2006). 2016 May-Jun;22(3):139-40

Authors: Raja TH, Flume PA

PMID: 27256624 [PubMed - in process]

Evaluation of a New Newborn Screening Model for Cystic Fibrosis.

J Pediatr. 2016 May 30;

Authors: Kharrazi M

PMID: 27255858 [PubMed - as supplied by publisher]

A Handling Study to Assess Use of the Respimat(®) Soft Mist™ Inhaler in Children Under 5 Years Old.

J Aerosol Med Pulm Drug Deliv. 2015 Oct;28(5):372-81

Authors: Kamin W, Frank M, Kattenbeck S, Moroni-Zentgraf P, Wachtel H, Zielen S

Abstract
BACKGROUND: Respimat(®) Soft Mist(™) Inhaler (SMI) is a hand-held device that generates an aerosol with a high, fine-particle fraction, enabling efficient lung deposition. The study objective was to assess inhalation success among children using Respimat SMI, and the requirement for assistance by the parent/caregiver and/or a valved holding chamber (VHC).
METHODS: This open-label study enrolled patients aged <5 years with respiratory disease and history of coughing and/or recurrent wheezing. Patients inhaled from the Respimat SMI (air only; no aerosol) using a stepwise configuration: "1" (dose released by child); "2" (dose released by parent/caregiver), and "3" (Respimat SMI with VHC, facemask, and parent/caregiver help). Co-primary endpoints included the ability to perform successful inhalation as assessed by the investigators using a standardized handling questionnaire and evaluation of the reasons for success. Inhalation profile in the successful handling configuration was verified with a pneumotachograph. Patient satisfaction and preferences were investigated in a questionnaire.
RESULTS: Of the children aged 4 to <5 years (n=27) and 3 to <4 years (n=30), 55.6% and 30.0%, respectively, achieved success without a VHC or help; with assistance, another 29.6% and 10.0%, respectively, achieved success, and the remaining children were successful with VHC. All children aged 2 to <3 years (n=20) achieved success with the Respimat SMI and VHC. Of those aged <2 years (n=22), 95.5% had successful handling of the Respimat SMI with VHC and parent/caregiver help. Inhalation flow profiles generally confirmed the outcome of the handling assessment by the investigators. Most parent/caregiver and/or child respondents were satisfied with operation, instructions for use, handling, and ease of holding the Respimat SMI with or without a VHC.
CONCLUSIONS: The Respimat SMI is suitable for children aged <5 years; however, children aged <5 years are advised to add a VHC to complement its use.

PMID: 25844687 [PubMed - indexed for MEDLINE]

Mathematical models of breast and ovarian cancers.

Wiley Interdiscip Rev Syst Biol Med. 2016 Jun 3;

Authors: Botesteanu DA, Lipkowitz S, Lee JM, Levy D

Abstract
Women constitute the majority of the aging United States (US) population, and this has substantial implications on cancer population patterns and management practices. Breast cancer is the most common women's malignancy, while ovarian cancer is the most fatal gynecological malignancy in the US. In this review, we focus on these subsets of women's cancers, seen more commonly in postmenopausal and elderly women. In order to systematically investigate the complexity of cancer progression and response to treatment in breast and ovarian malignancies, we assert that integrated mathematical modeling frameworks viewed from a systems biology perspective are needed. Such integrated frameworks could offer innovative contributions to the clinical women's cancers community, as answers to clinical questions cannot always be reached with contemporary clinical and experimental tools. Here, we recapitulate clinically known data regarding the progression and treatment of the breast and ovarian cancers. We compare and contrast the two malignancies whenever possible in order to emphasize areas where substantial contributions could be made by clinically inspired and validated mathematical modeling. We show how current paradigms in the mathematical oncology community focusing on the two malignancies do not make comprehensive use of, nor substantially reflect existing clinical data, and we highlight the modeling areas in most critical need of clinical data integration. We emphasize that the primary goal of any mathematical study of women's cancers should be to address clinically relevant questions. For further resources related to this article, please visit the WIREs website.

PMID: 27259061 [PubMed - as supplied by publisher]

Chronic Lung Allograft Dysfunction: A Systems Review of Mechanisms.

Transplantation. 2016 Jun 2;

Authors: Royer PJ, Olivera-Botello G, Koutsokera A, Aubert JD, Bernasconi E, Tissot A, Pison C, Nicod L, Boissel JP, Magnan A, SysCLAD consortium

Abstract
Chronic lung allograft dysfunction (CLAD) is the major limitation of long-term survival after lung transplantation. Chronic lung allograft dysfunction manifests as bronchiolitis obliterans syndrome or the recently described restrictive allograft syndrome. Although numerous risk factors have been identified so far, the physiopathological mechanisms of CLAD remain poorly understood. We investigate here the immune mechanisms involved in the development of CLAD after lung transplantation. We explore the innate or adaptive immune reactions induced by the allograft itself or by the environment and how they lead to allograft dysfunction. Because current literature suggests bronchiolitis obliterans syndrome and restrictive allograft syndrome as 2 distinct entities, we focus on the specific factors behind one or the other syndromes. Chronic lung allograft dysfunction is a multifactorial disease that remains irreversible and unpredictable so far. We thus finally discuss the potential of systems-biology approach to predict its occurrence and to better understand its underlying mechanisms.

PMID: 27257997 [PubMed - as supplied by publisher]

Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 Diabetes.

PLoS One. 2016;11(6):e0156006

Authors: Riquelme Medina I, Lubovac-Pilav Z

Abstract
Type 1 diabetes (T1D) is a complex disease, caused by the autoimmune destruction of the insulin producing pancreatic beta cells, resulting in the body's inability to produce insulin. While great efforts have been put into understanding the genetic and environmental factors that contribute to the etiology of the disease, the exact molecular mechanisms are still largely unknown. T1D is a heterogeneous disease, and previous research in this field is mainly focused on the analysis of single genes, or using traditional gene expression profiling, which generally does not reveal the functional context of a gene associated with a complex disorder. However, network-based analysis does take into account the interactions between the diabetes specific genes or proteins and contributes to new knowledge about disease modules, which in turn can be used for identification of potential new biomarkers for T1D. In this study, we analyzed public microarray data of T1D patients and healthy controls by applying a systems biology approach that combines network-based Weighted Gene Co-Expression Network Analysis (WGCNA) with functional enrichment analysis. Novel co-expression gene network modules associated with T1D were elucidated, which in turn provided a basis for the identification of potential pathways and biomarker genes that may be involved in development of T1D.

PMID: 27257970 [PubMed - as supplied by publisher]

A Graph Based Framework to Model Virus Integration Sites.

Comput Struct Biotechnol J. 2016;14:69-77

Authors: Fronza R, Vasciaveo A, Benso A, Schmidt M

Abstract
With next generation sequencing thousands of virus and viral vector integration genome targets are now under investigation to uncover specific integration preferences and to define clusters of integration, termed common integration sites (CIS), that may allow to assess gene therapy safety or to detect disease related genomic features such as oncogenes. Here, we addressed the challenge to: 1) define the notion of CIS on graph models, 2) demonstrate that the structure of CIS enters in the category of scale-free networks and 3) show that our network approach analyzes CIS dynamically in an integrated systems biology framework using the Retroviral Transposon Tagged Cancer Gene Database (RTCGD) as a testing dataset.

PMID: 27257470 [PubMed]

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]

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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]