Gap filling workflows.

<p>We have developed four gap filling workflows and used them to generate the results in this paper: targeted parsimony-based gap filling, targeted likelihood-based gap filling, iterative parsimony-based gap filling, and iterative likelihood-based gap filling. The individual steps are described in detail in the <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003882#s4" target="_blank">methods</a>, and the technical details of running them using the web interface are described in the supplementary material. Green boxes represent inputs to the workflows. “Limit” is the user-defined time limit and <i>t</i>_max is a system-defined maximum possible time limit for gap filling (currently one day) to prevent overloading the compute servers.</p

Average phenotype consistency across all test organisms for models gap filled using the four evaluated algorithms.

<p>Iterative gap filling greatly increased the sensitivity (more correct positive growth conditions) and reduced the specificity (more incorrect positive growth conditions) of Biolog simulations. The use of likelihoods did not have a significant effect on the specificity or sensitivity of Biolog simulations. The overall model accuracy for essentiality data was similar for all four algorithms because genes added due to likelihood-based gap filling represented only at most about 7% of the genes in the model. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003882#pcbi-1003882-g006" target="_blank">Figure 6</a> for the results of knockout simulations using only genes added to gap filling solutions. “PP” means post-processed to add genes to gap filled reactions.</p><p>Average phenotype consistency across all test organisms for models gap filled using the four evaluated algorithms.</p

Proof of principle: Gap filling highly-likely reactions in <i>B. subtilis</i>.

<p><i>B. subtilis</i> synthesizes lipids via the non-mevalonate pathway (blue) <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003882#pcbi.1003882-Eisenreich1" target="_blank">[37]</a>. We removed this pathway from the <i>B. subtilis</i> genome-scale model and then tried to fill the gap using both the likelihood and parsimony-based approaches. The parsimony-based gap filling approach instead filled the gap with the mevalonate pathway (red), which is shorter but not supported by genetic evidence. The likelihood-based approach filled the gap with the correct pathway. Black indicates reactions that were not knocked out (there was no explicit link to literature evidence in the <i>B. subtilis</i> model). The numeric labels are the computed likelihoods of gap filling reactions.</p

Knockout lethality accuracy for genes added in gap filling.

<p>Gene knockout simulations were performed for models gap filled with each of the four workflows to assess the consistency between lethality prediction and knockout lethality data for genes added in gap filling. Likelihood-based gap filling was able to produce the most candidate gene associations, with high specificity and low sensitivity in lethality predictions. The difference in accuracy between likelihood-based and parsimony-based gap filling was not statistically significant. A) Number of positive growth predictions, B) Number of negative growth predictions.</p

Genes added to the model using likelihood-based and parsimony-based gap filling.

<p>Likelihood-based gap filling produced more new gene annotations than post-processing gap filled reactions generated using the parsimony-based approach. The plot shows the number of uniquely-added genes by likelihood-based and parsimony-based gap filling approaches (genes in common with both approaches are omitted for clarity but tended to be more than those unique to either approach). A) Number of genes added after targeted gap filling to activate biomass production. B) Number of genes added after iterative gap filling.</p

Microbial life tree (16S OTU98.5)

Phylogenetic tree (nwk format) used to show pathway conservation analysis on central metabolis

16S alignment file

Sequence alignment file that has been used to generate the initial master tree. Based on this master tree, the microbial life tree that was used in this study (16S OTU98.5) was generated using a distance-based clustering algorithm

Comparative Genomics of Cultured and Uncultured Strains Suggests Genes Essential for Free-Living Growth of <i>Liberibacter</i>

<div><p>The full genomes of two uncultured plant pathogenic <i>Liberibacter</i>, <i>Ca</i>. Liberibacter asiaticus and <i>Ca</i>. Liberibacter solanacearum, are publicly available. Recently, the larger genome of a closely related cultured strain, <i>Liberibacter crescens</i> BT-1, was described. To gain insights into our current inability to culture most <i>Liberibacter</i>, a comparative genomics analysis was done based on the RAST, KEGG, and manual annotations of these three organisms. In addition, pathogenicity genes were examined in all three bacteria. Key deficiencies were identified in <i>Ca</i>. L. asiaticus and <i>Ca</i>. L. solanacearum that might suggest why these organisms have not yet been cultured. Over 100 genes involved in amino acid and vitamin synthesis were annotated exclusively in <i>L. crescens</i> BT-1. However, none of these deficiencies are limiting in the rich media used to date. Other genes exclusive to <i>L. crescens</i> BT-1 include those involved in cell division, the stringent response regulatory pathway, and multiple two component regulatory systems. These results indicate that <i>L. crescens</i> is capable of growth under a much wider range of conditions than the uncultured <i>Liberibacter</i> strains. No outstanding differences were noted in pathogenicity-associated systems, suggesting that <i>L. crescens</i> BT-1 may be a plant pathogen on an as yet unidentified host.</p></div

Description of <i>Liberibacter</i> species.

<p>A brief comparison of the three sequenced <i>Liberibacter</i> species. ‡ Leonard et al 2012; † Duan et al 2009; ◊Lin et al 2011.</p

Comparison of cofactor de novo synthesis and transport in the <i>Liberibacter</i> species.

<p>*<i>L. crescens</i> is able to convert L-aspartate to panthothenate.</p