Ribosome profiling reveals an adaptation strategy of reduced bacterium to acute stress.

Biochimie. 2016 Oct 27;:

Authors: Fisunov GY, Evsyutina DV, Garanina IA, Arzamasov AA, Butenko IO, Altukhov IA, Nikitina AS, Govorun VM

Abstract
Bacteria of class Mollicutes (mycoplasmas) feature significant genome reduction which makes them good model organisms for systems biology studies. Previously we demonstrated, that drastic transcriptional response of mycoplasmas to stress results in a very limited response on the level of protein. In this study we used heat stress model of M. gallisepticum and ribosome profiling to elucidate the process of genetic information transfer under stress. We found that under heat stress ribosomes demonstrate selectivity towards mRNA binding. We identified that heat stress response may be divided into two groups on the basis of absolute transcript abundance and fold-change in the translatome. One represents a noise-like response and another is likely an adaptive one. The latter include ClpB chaperone, cell division cluster, homologs of immunoblocking proteins and short ORFs with unknown function. We found that previously identified read-through of terminators contributes to the upregulation of transcripts in the translatome as well. In addition we identified that ribosomes of M. gallisepticum undergo reorganization under the heat stress. The most notable event is decrease of the amount of associated HU protein. In conclusion, only changes of few adaptive transcripts significantly impact translatome, while widespread noise-like transcription plays insignificant role in translation during stress.

PMID: 27984202 [PubMed - as supplied by publisher]

Algal Cell Factories: Approaches, Applications, and Potentials.

Mar Drugs. 2016 Dec 13;14(12):

Authors: Fu W, Chaiboonchoe A, Khraiwesh B, Nelson DR, Al-Khairy D, Mystikou A, Alzahmi A, Salehi-Ashtiani K

Abstract
With the advent of modern biotechnology, microorganisms from diverse lineages have been used to produce bio-based feedstocks and bioactive compounds. Many of these compounds are currently commodities of interest, in a variety of markets and their utility warrants investigation into improving their production through strain development. In this review, we address the issue of strain improvement in a group of organisms with strong potential to be productive "cell factories": the photosynthetic microalgae. Microalgae are a diverse group of phytoplankton, involving polyphyletic lineage such as green algae and diatoms that are commonly used in the industry. The photosynthetic microalgae have been under intense investigation recently for their ability to produce commercial compounds using only light, CO₂, and basic nutrients. However, their strain improvement is still a relatively recent area of work that is under development. Importantly, it is only through appropriate engineering methods that we may see the full biotechnological potential of microalgae come to fruition. Thus, in this review, we address past and present endeavors towards the aim of creating productive algal cell factories and describe possible advantageous future directions for the field.

PMID: 27983586 [PubMed - in process]

Corrigendum: Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review.

Front Physiol. 2016;7:617

Authors: Zhang X, Acencio ML, Lemke N

Abstract
[This corrects the article on p. 75 in vol. 7, PMID: 27014079.].

PMID: 27980533 [PubMed - in process]

Differentiation of Diabetes by Pathophysiology, Natural History, and Prognosis.

Diabetes. 2016 Dec 15;:

Authors: Skyler JS, Bakris GL, Bonifacio E, Darsow T, Eckel RH, Groop L, Groop PH, Handelsman Y, Insel RA, Mathieu C, McElvaine AT, Palmer JP, Pugliese A, Schatz DA, Sosenko JM, Wilding JP, Ratner RE

Abstract
The American Diabetes Association, JDRF, the European Association for the Study of Diabetes, and the American Association of Clinical Endocrinologists convened a research symposium, "The Differentiation of Diabetes by Pathophysiology, Natural History and Prognosis" on 10-12 October 2015. International experts in genetics, immunology, metabolism, endocrinology, and systems biology discussed genetic and environmental determinants of type 1 and type 2 diabetes risk and progression, as well as complications. The participants debated how to determine appropriate therapeutic approaches based on disease pathophysiology and stage and defined remaining research gaps hindering a personalized medical approach for diabetes to drive the field to address these gaps. The authors recommend a structure for data stratification to define the phenotypes and genotypes of subtypes of diabetes that will facilitate individualized treatment.

PMID: 27980006 [PubMed - as supplied by publisher]

Prediction of Chemical Multi-target Profiles and Adverse Outcomes with Systems Toxicology.

Curr Med Chem. 2016 Dec 14;

Authors: Wathieu H, Ojo A, Dakshanamurthy S

Abstract
The field of systems biology, termed systems toxicology when applied to the characterization of adverse outcomes following chemical exposure, seeks to develop biological networks to explain phenotypic responses. Ideally, these are qualitatively and quantitatively similar to the actual network of biological entities that have functional consequences in living organisms. In this review, we outline computational tools for predicting chemical-protein interactions of multi-target compounds. Then, we discuss how the methods of systems toxicology currently draw on those interactions to predict resulting adverse outcomes which include diseases, adverse drug reactions, and toxic endpoints. These methods are useful for predicting the safety of drugs in drug development and the toxicity of environmental chemicals (ECs) in environmental toxicology.

PMID: 27978797 [PubMed - as supplied by publisher]

Investigating a holobiont: Microbiota perturbations and transkingdom networks.

Gut Microbes. 2016;7(2):126-35

Authors: Greer R, Dong X, Morgun A, Shulzhenko N

Abstract
The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study. (1) Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems.

PMID: 26979110 [PubMed - indexed for MEDLINE]

Temporal retinal transcriptome and systems biology analysis identifies key pathways and hub genes in Staphylococcus aureus endophthalmitis.

Sci Rep. 2016 Feb 11;6:21502

Authors: Rajamani D, Singh PK, Rottmann BG, Singh N, Bhasin MK, Kumar A

Abstract
Bacterial endophthalmitis remains a devastating inflammatory condition associated with permanent vision loss. Hence, assessing the host response in this disease may provide new targets for intervention. Using a mouse model of Staphylococcus aureus (SA) endophthalmitis and performing retinal transcriptome analysis, we discovered progressive changes in the expression of 1,234 genes. Gene ontology (GO) and pathway analyses revealed the major pathways impacted in endophthalmitis includes: metabolism, inflammatory/immune, antimicrobial, cell trafficking, and lipid biosynthesis. Among the immune/inflammation pathways, JAK/Stat and IL-17A signaling were the most significantly affected. Interactive network-based analyses identified 13 focus hub genes (IL-6, IL-1β, CXCL2, STAT3, NUPR1, Jun, CSF1, CYR61, CEBPB, IGF-1, EGFR1, SPP1, and TGM2) within these important pathways. The expression of hub genes confirmed by qRT-PCR, ELISA (IL-6, IL-1β, and CXCL2), and Western blot or immunostaining (CEBP, STAT3, NUPR1, and IGF1) showed strong correlation with transcriptome data. Since TLR2 plays an important role in SA endophthalmitis, counter regulation analysis of TLR2 ligand pretreated retina or the use of retinas from TLR2 knockout mice showed the down-regulation of inflammatory regulatory genes. Collectively, our study provides, for the first time, a comprehensive analysis of the transcriptomic response and identifies key pathways regulating retinal innate responses in staphylococcal endophthalmitis.

PMID: 26865111 [PubMed - indexed for MEDLINE]

Gene regulatory network inference using fused LASSO on multiple data sets.

Sci Rep. 2016 Feb 11;6:20533

Authors: Omranian N, Eloundou-Mbebi JM, Mueller-Roeber B, Nikoloski Z

Abstract
Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions.

PMID: 26864687 [PubMed - indexed for MEDLINE]

ARN: Analysis and Visualization System for Adipogenic Regulation Network Information.

Sci Rep. 2016 Dec 16;6:39347

Authors: Huang Y, Wang L, Zan LS

Abstract
Adipogenesis is the process of cell differentiation through which preadipocytes become adipocytes. Lots of research is currently ongoing to identify genes, including their gene products and microRNAs, that correlate with fat cell development. However, information fragmentation hampers the identification of key regulatory genes and pathways. Here, we present a database of literature-curated adipogenesis-related regulatory interactions, designated the Adipogenesis Regulation Network (ARN, http://210.27.80.93/arn/), which currently contains 3101 nodes (genes and microRNAs), 1863 regulatory interactions, and 33,969 expression records associated with adipogenesis, based on 1619 papers. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 37,000 PubMed abstracts. Additionally, we further determined 13,103 possible node relationships by searching miRGate, BioGRID, PAZAR and TRRUST. ARN also has several useful features: i) regulatory map information; ii) tests to examine the impact of a query node on adipogenesis; iii) tests for the interactions and modes of a query node; iv) prediction of interactions of a query node; and v) analysis of experimental data or the construction of hypotheses related to adipogenesis. In summary, ARN can store, retrieve and analyze adipogenesis-related information as well as support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.

PMID: 27982098 [PubMed - in process]

Utilization and Costs of Compounded Medications for Commercially Insured Patients, 2012-2013.

J Manag Care Spec Pharm. 2016 Feb;22(2):172-81

Authors: McPherson T, Fontane P, Iyengar R, Henderson R

Abstract
BACKGROUND: Although compounding has a long-standing tradition in clinical practice, insurers and pharmacy benefit managers have instituted policies to decrease claims for compounded medications, citing questions about their safety, efficacy, high costs, and lack of FDA approval. There are no reliable published data on the extent of compounding by community pharmacists nor on the fraction of patients who use compounded medications. Prior research suggests that compounded medications represent a relatively small proportion of prescription medications, but those surveys were limited by small sample sizes, subjective data collection methods, and low response rates.
OBJECTIVE: To determine the number of claims for compounded medications on a per user per year (PUPY) basis and the average ingredient cost of these claims among commercially insured patients in the United States for 2012 and 2013.
METHODS: This study used prescription claims data from a nationally representative sample of commercially insured members whose pharmacy benefits were managed by a large pharmacy benefit management company. A retrospective claims analysis was conducted from January 1, 2012, through December 31, 2013. Annualized prevalence, cost, and utilization estimates were drawn from the data. All prescription claims were adjusted to 30-day equivalents. Data-mining techniques (association rule mining) were employed in order to identify the most commonly combined ingredients in compounded medications.
RESULTS: The prevalence of compound users was 1.1% (245,285) of eligible members in 2012 and 1.4% (323,501) in 2013, an increase of 27.3%. Approximately 66% of compound users were female, and the average age of a compound user was approximately 42 years throughout the study period. The geographic distribution of compound user prevalence was consistent across the United States. Compound users' prescription claims increased 36.6% from 2012 to 2013, from approximately 7.1 million to approximately 9.7 million prescriptions. The number of claims for compounded medications increased by 34.2% during the same period, from 486,886 to 653,360. PUPY utilization remained unchanged at 2 prescriptions from 2012 to 2013. The most commonly compounded drugs were similar for all adult age groups and represented therapies typically indicated for chronic pain or hormone replacement therapy. The average ingredient cost for compounded medications increased by 130.3% from 2012 to 2013, from $308.49 to $710.36. The average ingredient cost for these users' non-compounded prescriptions increased only 7.7%, from $148.75 to $160.20. For comparison, the average ingredient cost for all prescription users' claims was $81.50 in 2012 and increased by 3.8% to $84.57 in 2013.
CONCLUSIONS: Compound users represented 1.4% of eligible members in 2013. The average ingredient cost for compound users' compounded prescriptions ($710.36) was greater than for noncompounded prescriptions ($160.20). The 1-year increase in average compounded prescription costs (130.3%) was also greater than for noncompounded prescriptions (7.7%). Although prevalence of compound users and the PUPY utilization for compounded prescriptions increased only slightly between 2012 and 2013, the mean and median cost of compounded medications increased dramatically during this time. Text mining revealed that drug combinations characteristic of topical pain formulations were among the most frequently compounded medications for adults.

PMID: 27015256 [PubMed - indexed for MEDLINE]

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Distal Limb Patterning Requires Modulation of cis-Regulatory Activities by HOX13.

Cell Rep. 2016 Dec 13;17(11):2913-2926

Authors: Sheth R, Barozzi I, Langlais D, Osterwalder M, Nemec S, Carlson HL, Stadler HS, Visel A, Drouin J, Kmita M

Abstract
The combinatorial expression of Hox genes along the body axes is a major determinant of cell fate and plays a pivotal role in generating the animal body plan. Loss of HOXA13 and HOXD13 transcription factors (HOX13) leads to digit agenesis in mice, but how HOX13 proteins regulate transcriptional outcomes and confer identity to the distal-most limb cells has remained elusive. Here, we report on the genome-wide profiling of HOXA13 and HOXD13 in vivo binding and changes of the transcriptome and chromatin state in the transition from the early to the late-distal limb developmental program, as well as in Hoxa13(-/-); Hoxd13(-/-) limbs. Our results show that proper termination of the early limb transcriptional program and activation of the late-distal limb program are coordinated by the dual action of HOX13 on cis-regulatory modules.

PMID: 27974206 [PubMed - in process]

Synthetic Core Promoters as Universal Parts for Fine-Tuning Expression in Different Yeast Species.

ACS Synth Biol. 2016 Dec 14;

Authors: Portela RM, Vogl T, Kniely C, Fischer JE, Oliveira R, Glieder A

Abstract
Synthetic biology and metabolic engineering experiments frequently require the fine-tuning of gene expression to balance and optimize protein levels of regulators or metabolic enzymes. A key concept of synthetic biology is the development of modular parts that can be used in different contexts. Here, we have applied a computational multifactor design approach to generate de novo synthetic core promoters and 5' untranslated regions (UTRs) for yeast cells. In contrast to upstream cis-regulatory modules (CRMs), core promoters are typically not subject to specific regulation, making them ideal engineering targets for gene expression fine-tuning. 112 synthetic core promoter sequences were designed on the basis of the sequence/function relationship of natural core promoters, nucleosome occupancy and the presence of short motifs. The synthetic core promoters were fused to the Pichia pastoris AOX1 CRM, and the resulting activity spanned more than a 200-fold range (0.3% to 70.6% of the wild type AOX1 level). The top-ten synthetic core promoters with highest activity were fused to six additional CRMs (three in P. pastoris and three in Saccharomyces cerevisiae). Inducible CRM constructs showed significantly higher activity than constitutive CRMs, reaching up to 176% of natural core promoters. Comparing the activity of the same synthetic core promoters fused to different CRMs revealed high correlations only for CRMs within the same organism. These data suggest that modularity is maintained to some extent but only within the same organism. Due to the conserved role of eukaryotic core promoters, this rational design concept may be transferred to other organisms as a generic engineering tool.

PMID: 27973777 [PubMed - as supplied by publisher]

Functional characterization of 34 CYP2A6 allelic variants by assessment of nicotine C-oxidation and coumarin 7-hydroxylation activities.

Drug Metab Dispos. 2016 Dec 14;:

Authors: Hosono H, Kumondai M, Maekawa M, Yamaguchi H, Mano N, Oda A, Hirasawa N, Hiratsuka M

Abstract
Cytochrome P450 2A6 (CYP2A6) is one of the enzymes responsible for the metabolism of therapeutic drugs and tobacco components, such as nicotine, 4-methylnitrosoamino-1-(3-pyridyl)-1-butanone, and N-nitrosodiethylamine. Genetic polymorphisms in CYP2A6 are associated with individual variation in smoking behavior, drug toxicity, and the risk of developing several cancers. In this study, we conducted an in vitro analysis of 34 allelic variants of CYP2A6 using nicotine and coumarin as representative CYP2A6 substrates. These variant CYP2A6 proteins were heterologously expressed in 293FT cells, and their enzymatic activities were assessed based on nicotine C-oxidation and coumarin 7-hydroxylation activities. Among the 34 CYP2A6 variants, CYP2A6.2, CYP2A6.5, CYP2A6.6, CYP2A6.10, CYP2A6.26, CYP2A6.36, and CYP2A6.37 exhibited no enzymatic activity, while 14 other variants exhibited markedly reduced activity toward both nicotine and coumarin. These comprehensive in vitro findings may provide useful insight into individual differences in smoking behavior, drug efficacy, and cancer susceptibility.

PMID: 27974382 [PubMed - as supplied by publisher]

Genetic polymorphisms of pharmacogenomic VIP variants in Li nationality of southern China.

Environ Toxicol Pharmacol. 2016 Mar;42:237-42

Authors: Ding Y, He P, He N, Li Q, Sun J, Yao J, Yi S, Xu H, Wu D, Wang X, Jin T

Abstract
OBJECTIVES: The present study aimed to screen members of the Li nationality in southern China for genotype frequencies of VIP variants and to determine differences between the Li ethnicity and global human population samples in HapMap.
METHODS: In this study, we genotyped 77 very important pharmacogenetic (VIP) variants selected from the pharmacogenomics knowledge base (PharmGKB) in members of the Li population and compared our data with other eleven populations from the HapMap data set.
RESULTS: Our results showed that VDR rs1540339, VKORC1 rs9934438, and MTHFR rs1801133 were most different in Li compared with most of the eleven populations from the HapMap data set. Furthermore, population structure and F-statistics (Fst) analysis also showed differences between the Li and other HapMap populations, and the results suggest that the Li are most genetically similar to the CHD population, and the least similar to the YRI in HapMap.
CONCLUSIONS: The findings of our study complement the pharmacogenomics database with information on members of the Li ethnicity and provide a stronger scientific basis for safer drug administration, which may help clinicians to predict individual drug responses, thereby avoiding the risk of adverse effects and optimizing efficacy in this population.

PMID: 26901752 [PubMed - indexed for MEDLINE]

An ongoing role for Wnt signaling in differentiating melanocytes in vivo.

Pigment Cell Melanoma Res. 2016 Dec 15;:

Authors: Vibert L, Aquino G, Gehring I, Subkhankulova T, Schilling TF, Rocco A, Kelsh RN

Abstract
A role for Wnt signaling in melanocyte specification from neural crest is conserved across vertebrates, but possible ongoing roles in melanocyte differentiation have received little attention. Using a systems biology approach to investigate the gene regulatory network underlying stable melanocyte differentiation in zebrafish highlighted a requirement for a positive feedback loop involving the melanocyte master regulator Mitfa. Here we test the hypothesis that Wnt signaling contributes to that positive feedback. We show firstly that Wnt signaling remains active in differentiating melanocytes and secondly that enhanced Wnt signaling drives elevated transcription of mitfa. We show that chemical activation of the Wnt signaling pathway at early stages of melanocyte development enhances melanocyte specification as expected, but importantly that at later (differentiation) stages it results in altered melanocyte morphology, although melanisation is not obviously affected. Downregulation of Wnt signaling also results in altered melanocyte morphology and organisation. We conclude that Wnt signaling plays a role in regulating ongoing aspects of melanocyte differentiation in zebrafish. This article is protected by copyright. All rights reserved.

PMID: 27977907 [PubMed - as supplied by publisher]

Determining the Significance of Protein Network Features and Attributes Using Permutation Testing.

Methods Mol Biol. 2017;1549:199-208

Authors: Cursons J, Davis MJ

Abstract
Network analysis methods are increasing in popularity. An approach commonly applied to analyze proteomics data involves the use of protein-protein interaction (PPI) networks to explore the systems-level cooperation between proteins identified in a study. In this context, protein interaction networks can be used alongside the statistical analysis of proteomics data and traditional functional enrichment or pathway enrichment analyses. In network analysis it is possible to adjust for some of the complexities that arise due to the known, explicit interdependence between the measured quantities, in particular, differences in the number of interactions between proteins. Here we describe a method for calculating robust empirical p-values for protein interaction networks. We also provide a worked example with python code demonstrating the implementation of this methodology.

PMID: 27975293 [PubMed - in process]

Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach.

Adv Exp Med Biol. 2016;919:515-530

Authors: Percy AJ, Yang J, Chambers AG, Mohammed Y, Miliotis T, Borchers CH

Abstract
Quantitative mass spectrometry (MS)-based approaches are emerging as a core technology for addressing health-related queries in systems biology and in the biomedical and clinical fields. In several 'omics disciplines (proteomics included), an approach centered on selected or multiple reaction monitoring (SRM or MRM)-MS with stable isotope-labeled standards (SIS), at the protein or peptide level, has emerged as the most precise technique for quantifying and screening putative analytes in biological samples. To enable the widespread use of MRM-based protein quantitation for disease biomarker assessment studies and its ultimate acceptance for clinical analysis, the technique must be standardized to facilitate precise and accurate protein quantitation. To that end, we have developed a number of kits for assessing method/platform performance, as well as for screening proposed candidate protein biomarkers in various human biofluids. Collectively, these kits utilize a bottom-up LC-MS methodology with SIS peptides as internal standards and quantify proteins using regression analysis of standard curves. This chapter details the methodology used to quantify 192 plasma proteins of high-to-moderate abundance (covers a 6 order of magnitude range from 31 mg/mL for albumin to 18 ng/mL for peroxidredoxin-2), and a 21-protein subset thereof. We also describe the application of this method to patient samples for biomarker discovery and verification studies. Additionally, we introduce our recently developed Qualis-SIS software, which is used to expedite the analysis and assessment of protein quantitation data in control and patient samples.

PMID: 27975233 [PubMed - in process]

Systems biology: Molecular memoirs of a cellular family.

Nature. 2016 Dec 14;:

Authors: Beck LE, Raj A

PMID: 27974796 [PubMed - as supplied by publisher]