Characterizing the metabolism of Dehalococcoides with a constraint-based model

Dehalococcoides strains respire a wide variety of chloro-organic compounds and are important for the bioremediation of toxic, persistent, carcinogenic, and ubiquitous ground water pollutants. In order to better understand metabolism and optimize their application, we have developed a pan-genome-scale metabolic network and constraint-based metabolic model of Dehalococcoides. The pan-genome was constructed from publicly available complete genome sequences of Dehalococcoides sp. strain CBDB1, strain 195, strain BAV1, and strain VS. We found that Dehalococcoides pan-genome consisted of 1118 core genes (shared by all), 457 dispensable genes (shared by some), and 486 unique genes (found in only one genome). The model included 549 metabolic genes that encoded 356 proteins catalyzing 497 gene-associated model reactions. Of these 497 reactions, 477 were associated with core metabolic genes, 18 with dispensable genes, and 2 with unique genes. This study, in addition to analyzing the metabolism of an environmentally important phylogenetic group on a pan-genome scale, provides valuable insights into Dehalococcoides metabolic limitations, low growth yields, and energy conservation. The model also provides a framework to anchor and compare disparate experimental data, as well as to give insights on the physiological impact of "incomplete" pathways, such as the TCA-cycle, CO 2 fixation, and cobalamin biosynthesis pathways. The model, referred to as iAI549, highlights the specialized and highly conserved nature of Dehalococcoides metabolism, and suggests that evolution of Dehalococcoides species is driven by the electron acceptor availability

New insights into Dehalococcoides mccartyi metabolism from a reconstructed metabolic network-based systems-level analysis of D. mccartyi transcriptomes

Organohalide respiration, mediated by Dehalococcoides mccartyi, is a useful bioremediation process that transforms ground water pollutants and known human carcinogens such as trichloroethene and vinyl chloride into benign ethenes. Successful application of this process depends on the fundamental understanding of the respiration and metabolism of D. mccartyi. Reductive dehalogenases, encoded by rdhA genes of these anaerobic bacteria, exclusively catalyze organohalide respiration and drive metabolism. To better elucidate D. mccartyi metabolism and physiology, we analyzed available transcriptomic data for a pure isolate (Dehalococcoides mccartyi strain 195) and a mixed microbial consortium (KB-1) using the previously developed pan-genome-scale reconstructed metabolic network of D. mccartyi. The transcriptomic data, together with available proteomic data helped confirm transcription and expression of the majority genes in D. mccartyi genomes. A composite genome of two highly similar D. mccartyi strains (KB-1 Dhc) from the KB-1 metagenome sequence was constructed, and operon prediction was conducted for this composite genome and other single genomes. This operon analysis, together with the quality threshold clustering analysis of transcriptomic data helped generate experimentally testable hypotheses regarding the function of a number of hypothetical proteins and the poorly understood mechanism of energy conservation in D. mccartyi. We also identified functionally enriched important clusters (13 for strain 195 and 11 for KB-1 Dhc) of co-expressed metabolic genes using information from the reconstructed metabolic network. This analysis highlighted some metabolic genes and processes, including lipid metabolism, energy metabolism, and transport that potentially play important roles in organohalide respiration. Overall, this study shows the importance of an organism’s metabolic reconstruction in analyzing various ‘‘omics’’ data to obtain improved understanding of the metabolism and physiology of the organism

Experimental validation of in silico model-predicted isocitrate dehydrogenase and phosphomannose isomerase from Dehalococcoides mccartyi

Gene sequences annotated as proteins of unknown or non-specific function and hypothetical proteins account for a large fraction of most genomes. In the strictly anaerobic and organohalide respiring Dehalococcoides mccartyi, this lack of annotation plagues almost half the genome. Using a combination of bioinformatics analyses and genome-wide metabolic modelling, new or more specific annotations were proposed for about 80 of these poorly annotated genes in previous investigations of D. mccartyi metabolism. Herein, we report the experimental validation of the proposed reannotations for two such genes (KB1_0495 and KB1_0553) from D. mccartyi strains in the KB-1 community. KB1_0495 or DmIDH was originally annotated as an NAD+-dependent isocitrate dehydrogenase, but biochemical assays revealed its activity primarily with NADP+ as a cofactor. KB1_0553, also denoted as DmPMI, was originally annotated as a hypothetical protein/sugar isomerase domain protein. We previously proposed that it was a bifunctional phosphoglucose isomerase/phosphomannose isomerase, but only phosphomannose isomerase activity was identified and confirmed experimentally. Further bioinformatics analyses of these two protein sequences suggest their affiliation to potentially novel enzyme families within their respective larger enzyme super families

<i>Semi-Automatic In Silico</i> Gap Closure Enabled <i>De Novo</i> Assembly of Two <i>Dehalobacter</i> Genomes from Metagenomic Data

<div><p>Typically, the assembly and closure of a complete bacterial genome requires substantial additional effort spent in a wet lab for gap resolution and genome polishing. Assembly is further confounded by subspecies polymorphism when starting from metagenome sequence data. In this paper, we describe <i>an in silico</i> gap-resolution strategy that can substantially improve assembly. This strategy resolves assembly gaps in scaffolds using pre-assembled contigs, followed by verification with read mapping. It is capable of resolving assembly gaps caused by repetitive elements and subspecies polymorphisms. Using this strategy, we realized the <i>de novo</i> assembly of the first two <i>Dehalobacter</i> genomes from the metagenomes of two anaerobic mixed microbial cultures capable of reductive dechlorination of chlorinated ethanes and chloroform. Only four additional PCR reactions were required even though the initial assembly with Newbler v. 2.5 produced 101 contigs within 9 scaffolds belonging to two <i>Dehalobacter</i> strains. By applying this strategy to the re-assembly of a recently published genome of <i>Bacteroides</i>, we demonstrate its potential utility for other sequencing projects, both metagenomic and genomic.</p></div

Overview of the <i>in silico</i> gap-resolution process.

<p>(a) The principle of the perl program that automates the search for overlapping contigs that close an assembly gap. (b) A typical output of the perl program; shown is the case of gap 00973-G-00974; (c) The solutions to gap 00973-G-00974 represented as a multiple sequence alignment created and visualized with Geneious Pro.</p

Separation of the genome of strain CF50 by progressive read-mapping.

<p>(a) the result of 1^st read mapping against the draft reference genome. (b) The result of last read mapping against the refined reference genome. Illumina read pairs from the CF metagenome, which only has the genome of strain CF50, were mapped against a reference genome derived from a chimeric <i>Dehalobacter</i> genome from the ACT-3 metagenome, which has both strain CF50 and strain 11DCA. The progressive read-mapping process as described resulted in the refined genome (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052038#pone-0052038-g002" target="_blank">Figure 2b</a>), representing the genome of strain CF50. Regions that have coverage lower than 5x are highlighted in red. The read depth is highlighted in green when both DNA strands were covered and in yellow when only one strand was covered.</p

Alignment of the published assembly versus the new (this study) assembly of the <i>B. salanitronis</i> genome.

<p>The positions of assembly gaps caused by the 6 copies of the rRNA operons are indicated as Region 1–6. Region 7 and 8 indicate the two large regions of disagreement.</p

Schematic of the draft chimeric <i>Dehalobacter</i> genome from the ACT-3 metagenome.

<p>The major scaffolds and contigs are represented as straight lines with contig and scaffold IDs labeled; contigs shared by both strains are in blue; contigs specific to strain CF50 are in read; contigs specific to strain DCA are in green.</p

Typical gaps in Group A.

<p>(a) The resolution of gap 00237-G-00238. (b) The resolution of gap 00240-G-00241. (c) The sequence alignment of the consensus sequences of gap 00237-G-00238 and gap 00240-G-00241. All DNA sequence alignments (including those in other figures) were generated with Geneious Pro, having the same format. As shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052038#pone-0052038-g005" target="_blank">Figure 5a</a>, most sequence identifiers consist of three regions. Region 1 shows the ID of the sequence. Region 2 indicates some specific tags: “W” means the sequence is the last 1000 bp nucleotides adapted from the 3′ end of the contig, and it is on the <u>w</u>est side of the gap; “E” means the sequence is the first 1000 bp adapted from the 5′ end of the contig, and it is on the <u>e</u>ast of the gap; “F” means the sequence is a whole contig and in its <u>f</u>orward orientation; “R” means the sequence is a whole contig but in its <u>r</u>everse orientation. Region 3 shows the average read depth of the contig from which the sequence is derived. The sequence alignment is shown on the right hand side. Marks on the top show the scale; the alignment mismatches are highlighted in black and the matches in grey; gaps in sequences are indicated in dashes. In some Figures (e.g., <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052038#pone-0052038-g007" target="_blank">Figures 7</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052038#pone-0052038-g010" target="_blank">10</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052038#pone-0052038-g014" target="_blank">14</a>) the identity of the overlapping sequences is shown on top of the alignment as a coloured bar; positions with 100% identity are in green and positions with lower identity are in yellow.</p

<i>Dehalobacter</i> scaffolds in the ACT-3 metagenome (scaffolds of other organisms are not included in this table).

<p><i>Dehalobacter</i> scaffolds in the ACT-3 metagenome (scaffolds of other organisms are not included in this table).</p