Genotypes, Networks, Phenotypes: Moving Toward Plant Systems Genetics.

Annu Rev Cell Dev Biol. 2016 Aug 3;

Authors: Ogura T, Busch W

Abstract
One of the central goals in biology is to understand how and how much of the phenotype of an organism is encoded in its genome. Although many genes that are crucial for organismal processes have been identified, much less is known about the genetic bases underlying quantitative phenotypic differences in natural populations. We discuss the fundamental gap between the large body of knowledge generated over the past decades by experimental genetics in the laboratory and what is needed to understand the genotypeto- phenotype problem on a broader scale. We argue that systems genetics, a combination of systems biology and the study of natural variation using quantitative genetics, will help to address this problem. We present major advances in these two mostly disconnected areas that have increased our understanding of the developmental processes of flowering time control and root growth. We conclude by illustrating and discussing the efforts that have been made toward systems genetics specifically in plants. Expected final online publication date for the Annual Review of Cell and Developmental Biology Volume 32 is October 06, 2016. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.

PMID: 27501448 [PubMed - as supplied by publisher]

Natural search algorithms as a bridge between organisms, evolution, and ecology.

Proc Natl Acad Sci U S A. 2016 Aug 5;

Authors: Hein AM, Carrara F, Brumley DR, Stocker R, Levin SA

Abstract
The ability to navigate is a hallmark of living systems, from single cells to higher animals. Searching for targets, such as food or mates in particular, is one of the fundamental navigational tasks many organisms must execute to survive and reproduce. Here, we argue that a recent surge of studies of the proximate mechanisms that underlie search behavior offers a new opportunity to integrate the biophysics and neuroscience of sensory systems with ecological and evolutionary processes, closing a feedback loop that promises exciting new avenues of scientific exploration at the frontier of systems biology.

PMID: 27496324 [PubMed - as supplied by publisher]

A Pilot Study of a Heuristic Algorithm for Novel Template Identification from VA Electronic Medical Record Text.

J Biomed Inform. 2016 Aug 3;

Authors: Redd AM, Gundlapalli AV, Divita G, Carter ME, Tran LT, Samore MH

Abstract
RATIONALE: Templates in text notes pose challenges for automated information extraction algorithms. We propose a method that identifies novel templates in plain text medical notes. The identification can then be used to either include or exclude templates when processing notes for information extraction.
METHODS: The two-module method is based on the framework of information foraging and addresses the hypothesis that documents containing templates and templates within those documents can be identified by common features. The first module is a grouping module that takes documents from the corpus and groups documents with common templates. This is accomplished through a binned word count hierarchical clustering algorithm. The second module performs extraction of the template. It uses the groupings and performs a longest common subsequence (LCS) algorithm to obtain the constituent parts of the templates. The method was developed and tested on a random document corpus of 750 notes derived from a large database of US Department of Veterans Affairs (VA) electronic medical notes.
RESULTS: For the grouping module by using hierarchical clustering we identified 23 groups with 3 documents or more, consisting of 120 documents in total from the 750 documents in our test corpus. Of these, 18 groups had at least one common template that was present in all documents in the group for a positive predictive value of 78%. The LCS extraction module performed with 100% positive predictive value, 94% sensitivity, and 83% negative predictive value. The human review determined that in 4 groups the template covered the entire document, with the remaining 14 groups containing a common section template. Among documents with templates, the number of templates per document ranged from 1 to 14. The mean and median number of templates per group was 5.9 and 5, respectively.
DISCUSSION: The grouping method was successful in finding like documents that contained templates. Of the groups of documents containing templates, the LCS module was successful in deciphering what belonged to the template and what was extraneous. Major obstacles to improved performance included documents that were composed of multiple templates, templates that included other templates embedded within them, and variants of templates. We demonstrate proof of concept of the grouping and extraction method of identifying templates in electronic medical records in this pilot study and propose methods to improve performance and scaling up.

PMID: 27497780 [PubMed - as supplied by publisher]

ModelView for ModelDB: Online Presentation of Model Structure.

Neuroinformatics. 2015 Oct;13(4):459-70

Authors: McDougal RA, Morse TM, Hines ML, Shepherd GM

Abstract
ModelDB ( modeldb.yale.edu ), a searchable repository of source code of more than 950 published computational neuroscience models, seeks to promote model reuse and reproducibility. Code sharing is a first step; however, model source code is often large and not easily understood. To aid users, we have developed ModelView, a web application for ModelDB that presents a graphical view of model structure augmented with contextual information for NEURON and NEURON-runnable (e.g. NeuroML, PyNN) models. Web presentation provides a rich, simulator-independent environment for interacting with graphs. The necessary data is generated by combining manual curation, text-mining the source code, querying ModelDB, and simulator introspection. Key features of the user interface along with the data analysis, storage, and visualization algorithms are explained. With this tool, researchers can examine and assess the structure of hundreds of models in ModelDB in a standardized presentation without installing any software, downloading the model, or reading model source code.

PMID: 25896640 [PubMed - indexed for MEDLINE]

10 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 2016/08/07

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.

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

"Cystic Fibrosis"

These pubmed results were generated on 2016/08/07

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.

The photosensitizer verteporfin has light-independent anti-leukemic activity for Ph-positive acute lymphoblastic leukemia and synergistically works with dasatinib.

Oncotarget. 2016 Aug 2;

Authors: Morishita T, Hayakawa F, Sugimoto K, Iwase M, Yamamoto H, Hirano D, Kojima Y, Imoto N, Naoe T, Kiyoi H

Abstract
Cell lines have been used for drug discovery as useful models of cancers; however, they do not recapitulate cancers faithfully, particularly from the viewpoints of microenvironmental independence. Patient-derived xenografts (PDX) are established by the transfer of primary tumor cells directly from patients into immunodeficient mice and can provide primary-like tumor cells of the amount needed at the desired time. We developed a high-throughput drug screening system using PDX cells and performed drug screening using the PDX cells of Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph+ ALL). We established four Ph+ ALL PDX mice and performed high-throughput screening of 3440 compounds using leukemia cells from the PDX mice (PDX-cell screening). The profiles of drugs selected by PDX-cell screening were markedly different from those by screening using the Ph+ ALL cell line. We found that verteporfin, an FDA-approved drug, exhibited strong PDX cell-specific cytotoxicity. In the validation assay, its GI50 was 228 nM, 395 nM, and 538 nM in three PDX cells and 3.93 µM, 2.11 µM, and 5.61 µM in three cell lines. Although verteporfin is a photosensitizer activated by photoirradiation, its cytotoxic effects were mediated by the light-independent production of reactive oxygen species; therefore, its anti-leukemic effects were also exerted in vivo without photoirradiation. Furthermore, it exhibited synergistic effects with dasatinib, an ABL kinase inhibitor. These results indicated the potential of verteporfin as a new anti-leukemic reagent.

PMID: 27494842 [PubMed - as supplied by publisher]

Drug repurposing: a new front in the war against Staphylococcus aureus.

Future Microbiol. 2016 Aug 5;

Authors: Das S, Dasgupta A, Chopra S

Abstract
Staphylococcus aureus continues its domination of worldwide bacterial infection rates, thereby remaining a pathogen of significant public health interest. A major reason for its continued success is its ability to acquire and maintain diverse drug resistance mechanisms, leading to a paucity of antimicrobials active against it, concomitantly leading to a continuous search for new antimicrobial agents. However, with the withdrawal of the major pharmaceutical firms from the anti-infective area, drug repurposing has provided a potential boost to the drug pipeline. In this review, we provide an overview of the currently approved drugs with repurposing potential against Staphylococcus aureus, thus augmenting the classical drug discovery pathway.

PMID: 27494302 [PubMed - as supplied by publisher]

Significance of pharmacogenetics and pharmacogenomics research in current medical practice.

Curr Drug Metab. 2016 Aug 4;

Authors: Prakash S, Agrawal S

Abstract
Human genome sequencing highlights the involvement of genetic variation towards differential risk of human diseases, presence of different phenotypes, and response to pharmacological elements. This brings the field of personalized medicine to forefront in the era of modern health care. Numerous recent approaches have shown that how variation in the genome at single nucleotide level can be used in pharmacological research. The two broad aspects that deal with pharmacological research are pharmacogenetics and pharmacogenomics. This review encompasses how these variations have created the basis of pharmacogenetics and pharmacogenomics research and important milestones accomplished in these two fields in different diseases. It further discusses at length their importance in disease diagnosis, response of drugs, and various treatment modalities on the basis of genetic determinants.

PMID: 27494310 [PubMed - as supplied by publisher]

Clinical Interpretation of Variants from Next - Generation Sequencing: The 2016 Scientific Meeting of the Human Genome Variation Society.

Hum Mutat. 2016 Aug 5;

Authors: Oetting WS, Brookes AJ, Béroud C, Taschner PE

Abstract
The 2016 scientific meeting of the Human Genome Variation Society (HGVS; http://www.hgvs.org) was held on the 20(th) of May in Barcelona, Spain, with the theme of "Clinical Interpretation of Variants from Next - Generation Sequencing". The meeting was opened by William S. Oetting, of the University of Minnesota, United States. "Precision medicine" is the latest buzz words in health care, both in the literature and in government initiatives. Pharmacogenomics is one area where next-generation sequencing (NGS) will have an impact, but there are some issues that need to be addressed. This article is protected by copyright. All rights reserved.

PMID: 27492570 [PubMed - as supplied by publisher]

Predicting the cell death responsiveness and sensitization of glioma cells to TRAIL and temozolomide.

Oncotarget. 2016 Aug 1;

Authors: Weyhenmeyer BC, Noonan J, Würstle ML, Lincoln FA, Johnston G, Rehm M, Murphy BM

Abstract
Genotoxic chemotherapy with temozolomide (TMZ) is a mainstay of treatment for glioblastoma (GBM); however, at best, TMZ provides only modest survival benefit to a subset of patients. Recent insight into the heterogeneous nature of GBM suggests a more personalized approach to treatment may be necessary to overcome cancer drug resistance and improve patient care. These include novel therapies that can be used both alone and with TMZ to selectively reactivate apoptosis within malignant cells. For this approach to work, reliable molecular signatures that can accurately predict treatment responsiveness need to be identified first. Here, we describe the first proof-of-principle study that merges quantitative protein-based analysis of apoptosis signaling networks with data- and knowledge-driven mathematical systems modeling to predict treatment responsiveness of GBM cell lines to various apoptosis-inducing stimuli. These include monotherapies with TMZ and TRAIL, which activate the intrinsic and extrinsic apoptosis pathways, respectively, as well as combination therapies of TMZ+TRAIL. We also successfully employed this approach to predict whether individual GBM cell lines could be sensitized to TMZ or TRAIL via the selective targeting of Bcl-2/Bcl-xL proteins with ABT-737. Our findings suggest that systems biology-based approaches could assist in personalizing treatment decisions in GBM to optimize cell death induction.

PMID: 27494880 [PubMed - as supplied by publisher]

Tetanus toxin production is triggered by the transition from amino acid consumption to peptides.

Anaerobe. 2016 Aug 1;

Authors: Licona-Cassani C, Steen JA, Zaragoza NE, Moonen G, Moutafis G, Hodson MP, Power J, Nielsen LK, Marcellin E

Abstract
Bacteria produce some of the most potent molecules known, of which many cause serious diseases such as tetanus. For prevention, billions of people and countless animals are immunised with the highly effective vaccine, industrially produced by large-scale fermentation. However, toxin production is often hampered by low yields and batch-to-batch variability. Improved productivity has been constrained by a lack of understanding of the molecular mechanisms controlling toxin production. Here we have developed a reproducible experimental framework for screening phenotypic determinants in Clostridium tetani under a process that mimics an industrial setting. We show that amino acid depletion induces production of the toxin. Using time-course transcriptomics and extracellular metabolomics to generate a 'fermentation atlas' that ascribe growth behaviour, nutrient consumption and gene expression to the fermentation phases, we found a subset of preferred amino acids. Exponential growth is characterised by the consumption of those amino acids followed by a slower exponential growth phase where peptides are consumed, and toxin is produced. The results aim at assisting in fermentation medium design towards the improvement of vaccine production yields and reproducibility. In conclusion, our work not only provides deep fermentation dynamics but represents the foundation for bioprocess design based on C. tetani physiological behaviour under industrial settings.

PMID: 27492724 [PubMed - as supplied by publisher]

Digitisation, Big Data, and the Future of the Medical Humanities: Text-Mining and the History of Medicine: Big Data, Big Questions?

Med Hist. 2016 Apr;60(2):294-6

Authors: Toon E, Timmermann C, Worboys M

PMID: 26971613 [PubMed - indexed for MEDLINE]

6 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 2016/08/05

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.

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

"Cystic Fibrosis"

These pubmed results were generated on 2016/08/05

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.

Context-specific functional module based drug efficacy prediction.

BMC Bioinformatics. 2016;17(Suppl 6):275

Authors: Hwang W, Choi J, Kwon M, Lee D

Abstract
BACKGROUND: It is necessary to evaluate the efficacy of individual drugs on patients to realize personalized medicine. Testing drugs on patients in clinical trial is the only way to evaluate the efficacy of drugs. The approach is labour intensive and requires overwhelming costs and a number of experiments. Therefore, preclinical model system has been intensively investigated for predicting the efficacy of drugs. Current computational drug sensitivity prediction approaches use general biological network modules as their prediction features. Therefore, they miss indirect effectors or the effects from tissue-specific interactions.
RESULTS: We developed cell line specific functional modules. Enriched scores of functional modules are utilized as cell line specific features to predict the efficacy of drugs. Cell line specific functional modules are clusters of genes, which have similar biological functions in cell line specific networks. We used linear regression for drug efficacy prediction. We assessed the prediction performance in leave-one-out cross-validation (LOOCV). Our method was compared with elastic net model, which is a popular model for drug efficacy prediction. In addition, we analysed drug sensitivity-associated functions of five drugs - lapatinib, erlotinib, raloxifene, tamoxifen and gefitinib- by our model.
CONCLUSIONS: Our model can provide cell line specific drug efficacy prediction and also provide functions which are associated with drug sensitivity. Therefore, we could utilize drug sensitivity associated functions for drug repositioning or for suggesting secondary drugs for overcoming drug resistance.

PMID: 27490093 [PubMed - as supplied by publisher]

Ibrutinib repurposing: from B-cell malignancies to solid tumors.

Oncoscience. 2016;3(5-6):147-8

Authors: Massó-Vallés D, Jauset T, Soucek L

PMID: 27489860 [PubMed]

Repositioning of antibiotic levofloxacin as a mitochondrial biogenesis inhibitor to target breast cancer.

Biochem Biophys Res Commun. 2016 Mar 18;471(4):639-45

Authors: Yu M, Li R, Zhang J

Abstract
Targeting mitochondrial biogenesis has become a potential therapeutic strategy in cancer due to their unique metabolic dependencies. In this study, we show that levofloxacin, a FDA-approved antibiotic, is an attractive candidate for breast cancer treatment. This is achieved by the inhibition of proliferation and induction of apoptosis in a panel of breast cancer cell lines while sparing normal breast cells. It also acts synergistically with conventional chemo drug in two independent in vivo breast xenograft mouse models. Importantly, levofloxacin inhibits mitochondrial biogenesis as shown by the decreased level of mitochondrial respiration, membrane potential and ATP. In addition, the anti-proliferative and pro-apoptotic effects of levofloxacin are reversed by acetyl-L-Carnitine (ALCAR, a mitochondrial fuel), confirming that levofloxacin's action in breast cancer cells is through inhibition of mitochondrial biogenesis. A consequence of mitochondrial biogenesis inhibition by levofloxacin in breast cancer cells is the deactivation of PI3K/Akt/mTOR and MAPK/ERK pathways. We further demonstrate that breast cancer cells have increased mitochondrial biogenesis than normal breast cells, and this explains their different sensitivity to levofloxacin. Our work suggest that levofloxacin is a useful addition to breast cancer treatment. Our work also establish the essential role of mitochondrial biogenesis on the activation of PI3K/Akt/mTOR and MAPK/ERK pathways in breast cancer cells.

PMID: 26902121 [PubMed - indexed for MEDLINE]

Repurposing Vitamin D as an Anticancer Drug.

Clin Oncol (R Coll Radiol). 2016 Jan;28(1):36-41

Authors: Gilbert DC, Vale C, Haire R, Coyle C, Langley RE

PMID: 26520788 [PubMed - indexed for MEDLINE]

Incidence of bloodstream infections in small bowel transplant recipients receiving selective decontamination of the digestive tract: A single-center experience.

Pediatr Transplant. 2015 Nov;19(7):722-9

Authors: Galloway D, Danziger-Isakov L, Goldschmidt M, Hemmelgarn T, Courter J, Nathan JD, Alonso M, Tiao G, Fei L, Kocoshis S

Abstract
Pediatric patients undergoing small bowel transplantation are susceptible to postoperative CLABSI. SDD directed against enteric microbes is a strategy for reducing CLABSI. We hypothesized that SDD reduces the frequency of CLABSI, infections outside the bloodstream, and allograft rejection during the first 30 days following transplant. A retrospective chart review of 38 pediatric small bowel transplant recipients at CCHMC from 2003 to 2011 was conducted. SDD antimicrobials were oral colistin, tobramycin, and amphotericin B. The incidence of CLABSI, infections outside the bloodstream, and rejection episodes were compared between study periods. The incidence of CLABSI did not differ between study periods (6.9 CLABSI vs. 4.6 CLABSI per 1000 catheter days; p = 0.727), but gram positives and Candida predominated in the first 30 days. Incidence of bacterial infections outside the bloodstream did not differ (p = 0.227). Rejection occurred more frequently during the first month following transplant (p = 0.302). SDD does not alter the incidence of CLABSI, bacterial infections outside the bloodstream, or allograft rejection in the immediate 30 days post-transplantation. However, SDD does influence CLABSI organism types (favoring gram positives and Candida) and Candidal infections outside the bloodstream.

PMID: 26332092 [PubMed - indexed for MEDLINE]