Dataset Information

Dead end metabolites--defining the known unknowns of the E. coli metabolic network.

ABSTRACT: The EcoCyc database is an online scientific database which provides an integrated view of the metabolic and regulatory network of the bacterium Escherichia coli K-12 and facilitates computational exploration of this important model organism. We have analysed the occurrence of dead end metabolites within the database--these are metabolites which lack the requisite reactions (either metabolic or transport) that would account for their production or consumption within the metabolic network. 127 dead end metabolites were identified from the 995 compounds that are contained within the EcoCyc metabolic network. Their presence reflects either a deficit in our representation of the network or in our knowledge of E. coli metabolism. Extensive literature searches resulted in the addition of 38 transport reactions and 3 metabolic reactions to the database and led to an improved representation of the pathway for Vitamin B12 salvage. 39 dead end metabolites were identified as components of reactions that are not physiologically relevant to E. coli K-12--these reactions are properties of purified enzymes in vitro that would not be expected to occur in vivo. Our analysis led to improvements in the software that underpins the database and to the program that finds dead end metabolites within EcoCyc. The remaining dead end metabolites in the EcoCyc database likely represent deficiencies in our knowledge of E. coli metabolism.

SUBMITTER: Mackie A

PROVIDER: S-EPMC3781023 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dead end metabolites--defining the known unknowns of the E. coli metabolic network.

Mackie Amanda A Keseler Ingrid M IM Nolan Laura L Karp Peter D PD Paulsen Ian T IT

PloS one 20130923 9

The EcoCyc database is an online scientific database which provides an integrated view of the metabolic and regulatory network of the bacterium Escherichia coli K-12 and facilitates computational exploration of this important model organism. We have analysed the occurrence of dead end metabolites within the database--these are metabolites which lack the requisite reactions (either metabolic or transport) that would account for their production or consumption within the metabolic network. 127 dea ...[more]

PMID: 24086468

Similar Datasets

Project description:Antimicrobial resistance (AMR) is one of the Global Health challenges of the 21st century. The inclusion of AMR on the global map parallels the scientific, technological, and organizational progress of the healthcare system and the socioeconomic changes of the last 100 years. Available knowledge about AMR has mostly come from large healthcare institutions in high-income countries and is scattered in studies across various fields, focused on patient safety (infectious diseases), transmission pathways and pathogen reservoirs (molecular epidemiology), the extent of the problem at a population level (public health), their management and cost (health economics), cultural issues (community psychology), and events associated with historical periods (history of science). However, there is little dialogue between the aspects that facilitate the development, spread, and evolution of AMR and various stakeholders (patients, clinicians, public health professionals, scientists, economic sectors, and funding agencies). This study consists of four complementary sections. The first reviews the socioeconomic factors that have contributed to building the current Global Healthcare system, the scientific framework in which AMR has traditionally been approached in such a system, and the novel scientific and organizational challenges of approaching AMR in the fourth globalization scenario. The second discusses the need to reframe AMR in the current public health and global health contexts. Given that the implementation of policies and guidelines are greatly influenced by AMR information from surveillance systems, in the third section, we review the unit of analysis ("the what" and "the who") and the indicators (the "operational units of surveillance") used in AMR and discuss the factors that affect the validity, reliability, and comparability of the information to be applied in various healthcare (primary, secondary, and tertiary), demographic, and economic contexts (local, regional, global, and inter-sectorial levels). Finally, we discuss the disparities and similarities between distinct stakeholders' objectives and the gaps and challenges of combatting AMR at various levels. In summary, this is a comprehensive but not exhaustive revision of the known unknowns about how to analyze the heterogeneities of hosts, microbes, and hospital patches, the role of surrounding ecosystems, and the challenges they represent for surveillance, antimicrobial stewardship, and infection control programs, which are the traditional cornerstones for controlling AMR in human health.

Project description:BackgroundScientific discovery progresses by exploring new and uncharted territory. More specifically, it advances by a process of transforming unknown unknowns first into known unknowns, and then into knowns. Over the last few decades, researchers have developed many knowledge bases to capture and connect the knowns, which has enabled topic exploration and contextualization of experimental results. But recognizing the unknowns is also critical for finding the most pertinent questions and their answers. Prior work on known unknowns has sought to understand them, annotate them, and automate their identification. However, no knowledge-bases yet exist to capture these unknowns, and little work has focused on how scientists might use them to trace a given topic or experimental result in search of open questions and new avenues for exploration. We show here that a knowledge base of unknowns can be connected to ontologically grounded biomedical knowledge to accelerate research in the field of prenatal nutrition.ResultsWe present the first ignorance-base, a knowledge-base created by combining classifiers to recognize ignorance statements (statements of missing or incomplete knowledge that imply a goal for knowledge) and biomedical concepts over the prenatal nutrition literature. This knowledge-base places biomedical concepts mentioned in the literature in context with the ignorance statements authors have made about them. Using our system, researchers interested in the topic of vitamin D and prenatal health were able to uncover three new avenues for exploration (immune system, respiratory system, and brain development) by searching for concepts enriched in ignorance statements. These were buried among the many standard enriched concepts. Additionally, we used the ignorance-base to enrich concepts connected to a gene list associated with vitamin D and spontaneous preterm birth and found an emerging topic of study (brain development) in an implied field (neuroscience). The researchers could look to the field of neuroscience for potential answers to the ignorance statements.ConclusionOur goal is to help students, researchers, funders, and publishers better understand the state of our collective scientific ignorance (known unknowns) in order to help accelerate research through the continued illumination of and focus on the known unknowns and their respective goals for scientific knowledge.

Dataset Information

Dead end metabolites--defining the known unknowns of the E. coli metabolic network.

Publications

Dead end metabolites--defining the known unknowns of the E. coli metabolic network.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets