Organization of genes encoding anaerobic CO metabolism in multiple bacteria.

<p>(A) Gene structure of CO metabolism genes in <i>Rubrivivax gelatinosus</i> CBS. The <i>hyp</i> genes putatively responsible for <i>coo</i> hydrogenase maturation are clustered among the <i>coo</i> CODH and hydrogenase genes. The gene encoding RcoM, the putative transcription factor for the <i>coo</i> CODH and hydrogenase genes is located among the <i>hyp</i> genes within this cluster of CO metabolism genes. (B) Gene structure of CO metabolism genes in <i>Rhodospirillum rubrum</i>. The <i>cooA</i> gene, encoding the CooA CO-responsive transcription factor, directly follows the CODH genes. (C) Gene structure of CO metabolism genes in <i>Carboxydothermus hydrogenoformans</i>. <i>C. hydrogenoformans</i> has five CODH complexes, but the genes for only one CODH are co-located with the genes for an energy-conserving hydrogenase <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114551#pone.0114551-Wu1" target="_blank">[36]</a>. The <i>cooA</i> and <i>hypC</i> genes precede the <i>cooMKLXUH</i> hydrogenase genes, which are followed by <i>hypA</i> and the <i>cooFS</i> CODH genes.</p

Genome Annotation Provides Insight into Carbon Monoxide and Hydrogen Metabolism in <i>Rubrivivax gelatinosus</i>

<div><p>We report here the sequencing and analysis of the genome of the purple non-sulfur photosynthetic bacterium <i>Rubrivivax gelatinosus</i> CBS. This microbe is a model for studies of its carboxydotrophic life style under anaerobic condition, based on its ability to utilize carbon monoxide (CO) as the sole carbon substrate and water as the electron acceptor, yielding CO₂ and H₂ as the end products. The CO-oxidation reaction is known to be catalyzed by two enzyme complexes, the CO dehydrogenase and hydrogenase. As expected, analysis of the genome of <i>Rx. gelatinosus</i> CBS reveals the presence of genes encoding both enzyme complexes. The CO-oxidation reaction is CO-inducible, which is consistent with the presence of two putative CO-sensing transcription factors in its genome. Genome analysis also reveals the presence of two additional hydrogenases, an uptake hydrogenase that liberates the electrons in H₂ in support of cell growth, and a regulatory hydrogenase that senses H₂ and relays the signal to a two-component system that ultimately controls synthesis of the uptake hydrogenase. The genome also contains two sets of hydrogenase maturation genes which are known to assemble the catalytic metallocluster of the hydrogenase NiFe active site. Collectively, the genome sequence and analysis information reveals the blueprint of an intricate network of signal transduction pathways and its underlying regulation that enables <i>Rx. gelatinosus</i> CBS to thrive on CO or H₂ in support of cell growth.</p></div

Identity percentage of <i>Rubrivivax gelatinosus</i> CBS Hyp1, Hyp2 proteins and the Hyp proteins from <i>Ralstonia eutropha</i> H16, generated by NCBI P-BLAST search.

<p>Identity percentage of <i>Rubrivivax gelatinosus</i> CBS Hyp1, Hyp2 proteins and the Hyp proteins from <i>Ralstonia eutropha</i> H16, generated by NCBI P-BLAST search.</p

Similarity, identity, and coverage of select hydrogenase proteins comparing the <i>Rubrivivax gelatinosus</i> CBS sensor and uptake hydrogenases to other bacterial species including <i>Ralstonia eutropha</i> H16.

<p>HupUV is a sensor hydrogenase, with HupU being the small subunit and HupV being the large, catalytic subunit. HupAB comprises a membrane-bound uptake hydrogenase with a small HupA subunit and a large, catalytic HupB subunit. Analysis was done using a NCBI P-BLAST search.</p><p>Similarity, identity, and coverage of select hydrogenase proteins comparing the <i>Rubrivivax gelatinosus</i> CBS sensor and uptake hydrogenases to other bacterial species including <i>Ralstonia eutropha</i> H16.</p

Organism Overview for <i>Rubrivivax gelatinosus</i> CBS.

<p>There are 643 subsystems, 4852 coding sequences, and 58 RNAs.</p

An overview of the CO and H₂ signal transduction pathways and metabolism in <i>Rubrivivax gelatinosus</i> CBS.

<p>An overview of the CO and H₂ signal transduction pathways and metabolism in <i>Rubrivivax gelatinosus</i> CBS.</p

Performance of the hierarchical model in plasmid data.

<p>The red, green and blue curves are ROC curves for the hierarchical model with control data, the case-control method, and the hierarchical model without control data, respectively. These three methods were tested on two different datasets: 1) a 3,589 bases long plasmid with 19 known 4-methylcytosines(4-mC) under single strand coverage 35x,50x,and 65x, respectively(A,C,E), and 2) a 3,591 bases long plasmid with 23 known N6-methyladenines(6-mA) under single strand coverage 15x,20x,25x(B,D,F). The solid lines are ROC curves using a [−6,+1] sequence context and the dotted lines are ROC curves using the [−7,+2] sequence context.</p

<i>De novo</i> genome assembly results for <i>Rubrivivax gelatinosus</i> CBS, resulting in one bacterial chromosome and two satellite DNA elements.

<p>The common section of the small satellite and the chromosome are highlighted in red. Not drawn to scale.</p

Impact of sequence context on position-specific kinetic rates.

<p>(A) Heatmap of for the position-specific kinetic rate variance explained by sequence context suggests that 7 bases upstream and 2 bases downstream, [−7,+2], of the incorporation site are the most informative. Bases beyond this region do not provide much information about polymerase kinetics. (B) Scatter plot of the [−7,+2] context effect in whole genome amplified <i>E. coli</i> and <i>M. pneumoniae</i> (<i>E. coli</i> WGA-C and <i>M. pneumoniae</i> WGA-C2 in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002935#pcbi-1002935-t001" target="_blank">Table 1</a>) shows that context effects are highly consistent between these experiments, with a Pearson's correlation coefficient is 0.91.</p

Detecting DNA Modifications from SMRT Sequencing Data by Modeling Sequence Context Dependence of Polymerase Kinetic

<div><p>DNA modifications such as methylation and DNA damage can play critical regulatory roles in biological systems. Single molecule, real time (SMRT) sequencing technology generates DNA sequences as well as DNA polymerase kinetic information that can be used for the direct detection of DNA modifications. We demonstrate that local sequence context has a strong impact on DNA polymerase kinetics in the neighborhood of the incorporation site during the DNA synthesis reaction, allowing for the possibility of estimating the expected kinetic rate of the enzyme at the incorporation site using kinetic rate information collected from existing SMRT sequencing data (historical data) covering the same local sequence contexts of interest. We develop an Empirical Bayesian hierarchical model for incorporating historical data. Our results show that the model could greatly increase DNA modification detection accuracy, and reduce requirement of control data coverage. For some DNA modifications that have a strong signal, a control sample is not even needed by using historical data as alternative to control. Thus, sequencing costs can be greatly reduced by using the model. We implemented the model in a R package named seqPatch, which is available at <a href="https://github.com/zhixingfeng/seqPatch" target="_blank">https://github.com/zhixingfeng/seqPatch</a>.</p> </div