Pharmacogenetics of Nicotine Metabolism in Twins: Methods and Procedures

This article describes a pharmacogenetic investigation of nicotine metabolism in twins. One hundred and thirty-nine twin pairs (110 monozygotic and 29 dizygotic) were recruited and assessed for smoking status, zygosity, and health conditions known or suspected to affect drug metabolism. Participants underwent a 30-minute infusion of stable isotope-labeled nicotine and its major metabolite, cotinine, followed by an 8-hour in-hospital stay. Blood and urine samples were taken at regular intervals for analysis of nicotine, cotinine, and metabolites by gas chromatography-mass spectrometry or liquid chromatography-mass spectrometry and subsequent characterization of pharmacokinetic phenotypes. DNA was genotyped to confirm zygosity and for variation in the primary gene involved in nicotine metabolism, CYP2A6. Univariate and multivariate biometric analyses planned for the future will determine genetic and environmental influences on each pharmacokinetic measure individually and in combination with each other, and in the presence and absence of covariates, including measured genotype. When the analyses are completed, this study will result in a more complete characterization of the impact of genetic and environmental influences on nicotine and cotinine metabolic pathways than has heretofore been reported. The approach taken, with its use of a quantitative model of nicotine metabolism, highly refined metabolic phenotypes, measured genotype, and advanced tools for biometric genetic analysis, provides a model for the use of twins in next-generation studies of complex drug-metabolism phenotypes

The Genome of Deep-Sea Vent Chemolithoautotroph Thiomicrospira crunogena XCL-2

Presented here is the complete genome sequence of Thiomicrospira crunogena XCL-2, representative of ubiquitous chemolithoautotrophic sulfur-oxidizing bacteria isolated from deep-sea hydrothermal vents. This gammaproteobacterium has a single chromosome (2,427,734 base pairs), and its genome illustrates many of the adaptations that have enabled it to thrive at vents globally. It has 14 methyl-accepting chemotaxis protein genes, including four that may assist in positioning it in the redoxcline. A relative abundance of coding sequences (CDSs) encoding regulatory proteins likely control the expression of genes encoding carboxysomes, multiple dissolved inorganic nitrogen and phosphate transporters, as well as a phosphonate operon, which provide this species with a variety of options for acquiring these substrates from the environment. Thiom. crunogena XCL-2 is unusual among obligate sulfur-oxidizing bacteria in relying on the Sox system for the oxidation of reduced sulfur compounds. The genome has characteristics consistent with an obligately chemolithoautotrophic lifestyle, including few transporters predicted to have organic allocrits, and Calvin-Benson-Bassham cycle CDSs scattered throughout the genome

Utility of stages of change construct in the planning of physical activity interventions among playgroup mothers

Background: The objective of this research was to assess the physical activity levels among a unique cohort of Western Australian (WA) mothers with young children who attend a WA Playgroup. Associated factors were also investigated, including self-efficacy for physical activity, social support for exercise, relevant socio-demographic correlates, as well as the stages of change construct within the Transtheoretical Model (TTM).Results: 421 women completed a questionnaire assessing physical activity behaviours. Of these, 368 participants completed the relevant physical activity evaluation items. 82.5% and 17.5% of the sample were classified as active and inactive, respectively. Associations between physical activity status and exercise stage of change were found. Additional associations were established for partner support and self-efficacy for physical activity. Conclusion: The majority of the sample was classified as active. Despite the high percentage of active participants, this study confirms the usefulness of the stages of change measure in that it can be utilised by health promotion practitioners to report physical activity behaviour and develop appropriate intervention strategies among a time poor and hard to reach population. Specifically the results are relevant to mothers in over 16,000 WA families who are involved with Playgroup WA programs. Interventions aimed at improving physical activity levels in mothers with young children should also consider the need to improve self-efficacy and social support

Environmental Barcoding Reveals Massive Dinoflagellate Diversity in Marine Environments

Rowena F. Stern is with University of British Columbia, Ales Horak is with University of British Columbia, Rose L. Andrew is with University of British Columbia, Mary-Alice Coffroth is with State University of New York at Buffalo, Robert A. Andersen is with the Bigelow Laboratory for Ocean Sciences, Frithjof C. Küpper is with the Scottish Marine Institute, Ian Jameson is with CSIRO Marine and Atmospheric Research, Mona Hoppenrath is with the German Center for Marine Biodiversity Research, Benoît Véron is with University of Caen Lower Normandy and the National Institute for Environmental Studies, Fumai Kasai is with the National Institute for Environmental Studies, Jerry Brand is with UT Austin, Erick R. James is with University of British Columbia, Patrick J. Keeling is with University of British Columbia.Background -- Dinoflagellates are an ecologically important group of protists with important functions as primary producers, coral symbionts and in toxic red tides. Although widely studied, the natural diversity of dinoflagellates is not well known. DNA barcoding has been utilized successfully for many protist groups. We used this approach to systematically sample known “species”, as a reference to measure the natural diversity in three marine environments. Methodology/Principal Findings -- In this study, we assembled a large cytochrome c oxidase 1 (COI) barcode database from 8 public algal culture collections plus 3 private collections worldwide resulting in 336 individual barcodes linked to specific cultures. We demonstrate that COI can identify to the species level in 15 dinoflagellate genera, generally in agreement with existing species names. Exceptions were found in species belonging to genera that were generally already known to be taxonomically challenging, such as Alexandrium or Symbiodinium. Using this barcode database as a baseline for cultured dinoflagellate diversity, we investigated the natural diversity in three diverse marine environments (Northeast Pacific, Northwest Atlantic, and Caribbean), including an evaluation of single-cell barcoding to identify uncultivated groups. From all three environments, the great majority of barcodes were not represented by any known cultured dinoflagellate, and we also observed an explosion in the diversity of genera that previously contained a modest number of known species, belonging to Kareniaceae. In total, 91.5% of non-identical environmental barcodes represent distinct species, but only 51 out of 603 unique environmental barcodes could be linked to cultured species using a conservative cut-off based on distances between cultured species. Conclusions/Significance -- COI barcoding was successful in identifying species from 70% of cultured genera. When applied to environmental samples, it revealed a massive amount of natural diversity in dinoflagellates. This highlights the extent to which we underestimate microbial diversity in the environment.This project was funded by Genome Canada and the Canadian Barcode of Life Network. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Biological Sciences, School o

Prophage Genome within the <i>Thiom. crunogena</i> XCL-2 Genome

<p>Lysogenic and lytic genes are delineated, as are predicted gene functions.</p

Cell Model for <i>Thiom. crunogena</i> XCL-2, with an Emphasis on Ultrastructure, Transport, Energy, Carbon Metabolism, and Chemotaxis

<p>Genes encoding virtually all of the steps for the synthesis of nucleotides and amino acids by canonical pathways are present in the bacterium, but are omitted here for simplicity. Electron transport components are yellow, and abbreviations are as follows: bc₁, <i>bc₁</i> complex; cbb₃, <i>cbb₃</i>-type cytochrome C oxidase; cytC, cytochrome C; NDH, NADH dehydrogenase; Sox, Sox system; UQ, ubiquinone. MCPs are fuchsia, as are MCPs with PAS domains or PAS folds. Influx and efflux transporter families with representatives in this genome are indicated on the figure, with the number of each type of transporter in parentheses. ATP-dependent transporters are red, secondary transporters are sky blue, ion channels are light green, and unclassified transporters are purple. Abbreviations for transporter families are as follows: ABC, ATP-binding cassette superfamily; AGCS, alanine or glycine:cation symporter family; AMT, ammonium transporter family; APC, amino acid-polyamine-organocation family; ATP syn, ATP synthetase; BASS, bile acid:Na⁺ symporter family; BCCT, betaine/carnitine/choline transporter family; CaCA, Ca²⁺:cation antiporter family; CDF, cation diffusion facilitator family; CHR, chromate ion transporter family; CPA, monovalent cation:proton antiporter-1, −2, and −3 families; DAACS, dicarboxylate/amino acid:cation symporter family; DASS, divalent anion:Na⁺ symporter family; DMT, drug/metabolite transporter superfamily; FeoB, ferrous iron uptake family; IRT, iron/lead transporter superfamily; MATE, multidrug/oligosaccharidyl-lipid/polysaccharide (MOP) flippase superfamily, MATE family; McsS, small conductance mechanosensitive ion channel family; MFS, major facilitator superfamily; MgtE, Mg²⁺ transporter-E family; MIT, CorA metal ion transporter family; NCS2, nucleobase:cation symporter-2 family; NRAMP, metal ion transporter family; NSS, neurotransmitter:sodium symporter family; P-ATP, P-type ATPase superfamily; Pit, inorganic phosphate transporter family; PNaS, phosphate:Na⁺ symporter family; PnuC, nicotamide mononucleotide uptake permease family; RhtB, resistance to homoserine/threonine family; RND, resistance-nodulation-cell division superfamily; SSS, solute:sodium symporter family; SulP, sulfate permease family; TRAP, tripartite ATP-independent periplasmic transporter family; TRK, K⁺ transporter family; VIC, voltage-gated ion channel superfamily.</p

Transporter Gene Frequencies within the Genomes of <i>Thiom. crunogena</i> XCL-2 (Arrow) and Other Proteobacteria

<p><i>Nitrob. winogradskyi (Nitrobacter winogradskyi)</i> is an alphaproteobacterium, <i>Nitros. europaea (Nitrosomonas europaea)</i> is a betaproteobacterium, and <i>Nitrosoc. oceani (Nitrosococcus oceani)</i> and <i>Methylo. capsulatus (Methylococcus capsulatus)</i> are gammaproteobacteria. Bars for intracellular pathogens are lighter red than the other heterotrophic gammaproteobacteria.</p

Circular Map of the <i>Thiom. crunogena</i> XCL-2 Genome

<p>The outer two rings (rings 1 and 2) are protein-encoding genes, which are color-coded according to COG category. Rings 3 and 4 are tRNA and rRNA genes. Ring 5 indicates the location of a prophage (magenta), phosphonate/heavy metal resistance island (cyan), and four insertion sequences (red; two insertion sequences at 2028543 and 2035034 are superimposed on this figure). The black circle indicates the deviation from the average %GC, and the purple and green circle is the GC skew (= [G − C]/[G + C]). Both the %GC and GC skew were calculated using a sliding window of 10,000 bp with a window step of 100.</p

Calvin-Benson-Bassham Cycle Gene Organization in Proteobacteria

<p>RubisCO genes <i>(cbbLS</i> and <i>cbbM)</i> are green, phosphoribulokinase genes <i>(cbbP)</i> are red, other genes encoding Calvin-Benson-Bassham cycle enzymes are black, and carboxysome structural genes are grey. For species in which <i>cbbP</i> is not near <i>cbbLS</i> or <i>cbbM,</i> the distance from the RubisCO gene to <i>cbbP</i> in kbp is indicated in parentheses. <i>Thiob. denitrificans</i> has two <i>cbbP</i> genes, so two distances are indicated for this species. Names of organisms that are unable to grow well as organoheterotrophs are boxed. Abbreviations and accession numbers for the 16S sequences used to construct the cladogram are as follows: <i>A. ehrlichei, Alkalilimnicola ehrlichei,</i> AF406554; Brady. sp., Bradyrhizobium sp., AF338169;<i>B. japonicum, Bradyrhizobium japonicum,</i> D13430; <i>B. xenovorans, Burkholderia xenovorans</i>, U86373; <i>D. aromatica, Dechloromonas aromatica,</i> AY032610; <i>M. magneticum, Magnetospirillum magneticum,</i> D17514; <i>M. capsulatus, Methylococcus capsulatus</i> BATH, AF331869; <i>N. hamburgensis, Nitrobacter hamburgensis,</i> L11663; <i>N. winogradskyi, Nitrobacter winogradskyi,</i> L11661; <i>N. oceani, Nitrosococcus oceani,</i> AF363287; <i>N. europaea, Nitrosomonas europaea,</i> BX321856; <i>N. multiformis, Nitrosospira multiformis,</i> L35509; <i>P. denitrificans, Paracoccus denitrificans,</i> X69159; <i>R. sphaeroides, Rhodobacter sphaeroides,</i> CP000144; <i>R. ferrireducens, Rhodoferax ferrireducens,</i> AF435948; <i>R. palustris, Rhodopseudomonas palustris,</i> NC 005296; <i>R. rubrum, Rhodospirillum rubrum,</i> D30778; <i>R. gelatinosus, Rubrivivax gelatinosus,</i> M60682; <i>S. meliloti, Sinorhizobium meliloti,</i> D14509; <i>T. denitrificans, Thiobacillus denitrificans,</i> AJ43144; <i>T. crunogena, Thiomicrospira crunogena,</i> AF064545. The cladogram was based on an alignment of 1,622 bp of the 16S rRNA genes, and is the most parsimonious tree (length 2,735) resulting from a heuristic search with 100 replicate random step-wise addition and TBR branch swapping (PAUP*4.0b10 [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040383#pbio-0040383-b113" target="_blank">113</a>]). Sequences were aligned using ClustalW [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040383#pbio-0040383-b114" target="_blank">114</a>], as implemented in BioEdit. Percent similarities and identities for <i>cbbL, cbbM,</i> and <i>cbbP</i> gene products, as well as gene locus tags, are provided as supporting information (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0040383#pbio-0040383-st004" target="_blank">Table S4</a>).</p