MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks

Summary: MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website's functionality. Availability and implementation: MetaNetX.org is available at http://metanetx.org. Contact: [email protected]

Comparison of Coxiella burnetii Excretion between Sheep and Goats Naturally Infected with One Cattle-Associated Genotype

The main reservoir of Coxiella (C.) burnetii are ruminants. They shed the pathogen through birth products, vaginal mucus, faeces and milk. A direct comparison of C. burnetii excretions between naturally infected sheep and goats was performed on the same farm to investigate species-specific differences. The animals were vaccinated with an inactivated C. burnetii phase I vaccine at the beginning of the study period for public health reasons. Vaginal and rectal swabs along with milk specimens were taken monthly during the lambing period and once again at the next lambing season. To estimate the environmental contamination of the animals’ housings, nasal swabs from every animal were taken simultaneously. Moreover, dust samples from the windowsills and straw beddings were collected. All samples were examined by qPCR targeting the IS1111 gene and the MLVA/VNTR typing method was performed. Whole genome sequencing was applied to determine the number of IS1111 copies followed by a calculation of C. burnetii genome equivalents of each sample. The cattle-associated genotype C7 was detected containing 29 IS1111 copies. Overall, goats seem to shed more C. burnetii through vaginal mucus and in particular shed more and for longer via the rectal route than sheep. This is supported by the larger quantities of C. burnetii DNA detected in caprine nasal swabs and environmental samples compared to the ovine ones. Transmission of C. burnetii from cattle to small ruminants must also be considered.Peer Reviewe

Efficient Reconstruction of Predictive Consensus Metabolic Network Models

Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions.</p

Interleukin-6 and α-2-macroglobulin indicate an acute-phase state in Alzheimer's disease cortices

AbstractRecent studies indicated that the formation of a major constituent of Alzheimer's disease (AD) senile plaques, called βA4-peptide, does not result from normal processing of its precursor, amyloid precursor protein (APP). Since proteolytic cleavage of APP inside its βA4 sequence was found to be part of APP processing the formation of the βA4-peptide seems to be prevented under normal conditions. We considered whether in AD one of the endogenous proteinase inhibitors might interfere with APP processing. After we had recently found that cultured human neuronal cells synthesize the most potent of the known human proteinase inhibitors, α-2-macroglobulin (α2M), upon stimulation with the inflammatory mediator interleukin-6 (IL-6) we now investigated whether α2M and IL-6 could be detected in AD brains. Here we report that AD cortical senile plaques display strong α2M and IL-6 immunoreactivity while no such immunoreactivity was found in age-matched control brains. Strong perinuclear α2M immunoreactivity in hippocampal CAI neurons of Alzheimer's disease brains indicates that neuronal cells are the site of α2M synthesis in AD brains. We did not detect elevated IL-6 or α2M levels in the cerebrospinal fluid of AD patients. Our data indicate that a sequence of immunological events which seem to be restricted to the local cortical environment is part of AD pathology

Subnetwork analysis for <i>P</i>. <i>putida</i>.

<p>(<b>a</b>) Example error of ‘naïve’ iGSM merging where the initial <i>P</i>. <i>putida</i> BCM contains a biologically inaccurate carbon dioxide fixation cycle due to incorrect directionalities in the IGSMs. This error is automatically resolved as COMMGEN assigns reaction directionalities opposite to those shown with dashed reaction arrows. (<b>b</b>) Example for a new metabolic function in the consensus model. <i>P</i>. <i>putida</i> can grow on L-quinate as its sole carbon source. Neither of the initial models captures this behavior, whereas the consensus model provides the necessary, complementary reactions.</p

Performance evaluation of COMMGEN.

<p>(<b>a</b>) Evaluation of GSM ability to predict growth phenotypes. Predictive ability of initial GSMs (blue), basic consensus models (red), and automatically created refined consensus model (green) according to the metrics defined in the text. The test data comprised gene knockout data (<i>B</i>. <i>subtilis</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref003" target="_blank">3</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref036" target="_blank">36</a>], <i>P</i>. <i>putida</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref008" target="_blank">8</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref050" target="_blank">50</a>], <i>M</i>. <i>tuberculosis</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref051" target="_blank">51</a>], <i>S</i>. <i>cerevisiae</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref049" target="_blank">49</a>]), biolog data (<i>B</i>. <i>subtilis</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref003" target="_blank">3</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref036" target="_blank">36</a>], <i>P</i>. <i>putida</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref008" target="_blank">8</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref033" target="_blank">33</a>]) and auxotrophies (<i>P</i>. <i>putida</i> [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref050" target="_blank">50</a>]). See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.s004" target="_blank">S3 Protocol</a> for details. (<b>b,c</b>) Comparison of manual (yeast consensus model [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref020" target="_blank">20</a>] based on the IGSMs iMM904 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref037" target="_blank">37</a>] and iLL672 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref038" target="_blank">38</a>]) and automatic consensus model generation with namespace matching only, or with COMMGEN. (<b>b</b>) Numbers of common reactions and metabolites for manual curation, name space conversion, and automatically created refined consensus model. (<b>c</b>) Incidences of inconsistent reaction classes identified by COMMGEN.</p

Models used in this study and classification of inconsistencies.

<p>(<b>a</b>) Overview of the used initial GSMs. (<b>b</b>) Instances of identical metabolites with different MnXRef identifiers. (<b>c</b>) Non-identical metabolites that perform identical functions in the network context. (<b>d</b>) Alternative modeling of polymers. (<b>e</b>) Nested and encompassing reactions. (<b>f</b>) Alternative usage of redox pairs. (<b>g</b>) Alternative reactions with consequences for redox metabolism. (<b>h</b>) Partially overlapping reactions differing in phosphate products. (<b>i</b>) Lumped vs. non-lumped representation of a pathway. (<b>j</b>) Invalid transport reaction (IR08663). (<b>k</b>) Alternative transport reactions for putrescine. (<b>l</b>) Alternative transport reactions for glycine. (<b>m</b>) Invalid boundary reaction (R841). Circles represent chemical species, arrows chemical reactions, and grey boxes different compartments. Red nodes indicate instances of identical species within the network context whose alternative names are separated by horizontal lines. Rectangular boxes contain the original reaction names, rounded rectangles their corresponding GPRs, where '&' represents a logical AND, and '|' a logical OR. Edges with filled circles represent reversible reactions. Stoichiometric coefficients unequal to one are indicated at their respective arrows. The shown reactions originate from GSMs of four different organisms: <i>B</i>. <i>subtilis</i> (<b>d</b>), as represented in iYO844 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref003" target="_blank">3</a>] (blue) and iBSu1103 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref036" target="_blank">36</a>] (orange); <i>M</i>. <i>tuberculosis</i> (<b>m</b>), as represented in iNJ661 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref014" target="_blank">14</a>] (blue) and GSMN_TB [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref007" target="_blank">7</a>] (orange);<i>P</i>. <i>putida</i> (<b>b,c,e,f,h,I,j,k</b>), as represented in iJN746 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref033" target="_blank">33</a>] (blue) and iJP962 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref010" target="_blank">10</a>] (orange); and <i>S</i>. <i>cerevisiae</i> (<b>g,l</b>), as represented in iIN800 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref048" target="_blank">48</a>] (blue) and iMM904 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref018" target="_blank">18</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref037" target="_blank">37</a>] (orange) and iND750 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref049" target="_blank">49</a>] (pink).</p

Application of COMMGEN to <i>P</i>. <i>putida</i> GSMs.

<p>(<b>a</b>) Automatic inconsistency identification and reconciliation substantially increases consensus and reduces inconsistencies. Reactions are classified into consensus reactions (green) and unique reactions involving no (blue), a single (orange), or multiple (red) inconsistencies. (<b>b, c</b>) Characteristics of the refined consensus model as in (<b>a</b>) without network-based metabolite matching (<b>b</b>), or after manually addressing the remaining inconsistencies (<b>c</b>). (<b>d</b>) Numbers of reversible (‘+’) and irreversible (‘-‘) reactions in the RCM, grouped by the four possible combinations of reversibilities in the IGSMs. (<b>e</b>) Numbers of active and inactive reactions in the RCM, grouped by being active (‘+’) or inactive (‘-‘) in the IGSMs.</p

COMMGEN framework.

<p>(<b>a,b</b>) Overview of COMMGEN workflow and available methods. The COMMGEN methods are either fully automatic (+), conditionally or optionally automatic (+/-), or they always require manual intervention (-). (<b>c</b>) Performance of the metabolite matching methods if run without manual intervention, leading to ROC-curves of the classification of metabolites as identical or non-identical based on their network context. Lines correspond to different fractions of the network information being randomly discarded: black, 0%; red, 30%; green, 60%; blue, 90%. The shades indicate the standard deviations in the classification. The data presented here was obtained using the <i>Pseudomonas putida</i> GSMs iJP962 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref010" target="_blank">10</a>] and iJN746 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.ref033" target="_blank">33</a>]; analysis results for the other sets of GSMs and additional information can be found in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005085#pcbi.1005085.s006" target="_blank">S5 Protocol</a>.</p