Dataset Information

To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

ABSTRACT: Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementation's effect on protein synthesis. We implement several in silico supplementation strategies to study whether amino acid supplementation might be beneficial for increasing muscle contractile protein synthesis. Concurrent with published data on amino acid supplementation's effect on protein synthesis in a post resistance exercise state, our results suggest that increasing bioavailability of methionine, arginine, and the branched-chain amino acids can increase the flux of contractile protein synthesis. The study also suggests that a common commercial supplement, glutamine, is not an effective supplement in the context of increasing protein synthesis and thus, muscle mass. Similar to any study in a model organism, the computational modeling of this research has some limitations. Thus, this paper introduces the prospect of using systems biology as a framework to formally investigate how supplementation and nutrition can affect human metabolism and physiology.

SUBMITTER: Nogiec CD

PROVIDER: S-EPMC3740736 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

Nogiec Christopher D CD Kasif Simon S

PloS one 20130805 8

Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementa ...[more]

PMID: 23967053

Similar Datasets

Project description:Text mining (TM) in the field of biology is fast becoming a routine analysis for the extraction and curation of biological entities (e.g., genes, proteins, simple chemicals) as well as their relationships. Due to the wide applicability of TM in situations involving complex relationships, it is valuable to apply TM to the extraction of metabolic interactions (i.e., enzyme and metabolite interactions) through metabolic events. Here we present an integrated TM framework containing two modules for the extraction of metabolic events (Metabolic Event Extraction module-MEE) and for the construction of a metabolic interaction network (Metabolic Interaction Network Reconstruction module-MINR). The proposed integrated TM framework performed well based on standard measures of recall, precision and F-score. Evaluation of the MEE module using the constructed Metabolic Entities (ME) corpus yielded F-scores of 59.15% and 48.59% for the detection of metabolic events for production and consumption, respectively. As for the testing of the entity tagger for Gene and Protein (GP) and metabolite with the test corpus, the obtained F-score was greater than 80% for the Superpathway of leucine, valine, and isoleucine biosynthesis. Mapping of enzyme and metabolite interactions through network reconstruction showed a fair performance for the MINR module on the test corpus with F-score >70%. Finally, an application of our integrated TM framework on a big-scale data (i.e., EcoCyc extraction data) for reconstructing a metabolic interaction network showed reasonable precisions at 69.93%, 70.63% and 46.71% for enzyme, metabolite and enzyme-metabolite interaction, respectively. This study presents the first open-source integrated TM framework for reconstructing a metabolic interaction network. This framework can be a powerful tool that helps biologists to extract metabolic events for further reconstruction of a metabolic interaction network. The ME corpus, test corpus, source code, and virtual machine image with pre-configured software are available at www.sbi.kmutt.ac.th/ preecha/metrecon.

Project description:BackgroundVisceral leishmaniasis (VL) is a disease caused by a parasite, which can lead to death if untreated. Poor nutritional status hastens the progression of VL infection, and VL worsens malnutrition status. Malnutrition is one of the poor prognostic factors identified for leishmaniasis. However, the effects of nutritional supplementation in people treated for VL are not known.ObjectivesTo assess the effects of oral nutritional supplements in people being treated with anti-leishmanial drug therapy for VL.Search methodsWe searched the Cochrane Infectious Diseases Group (CIDG) Specialized Register, CENTRAL, MEDLINE, Embase, LILACS, and two trial registers up to 12 September 2017. We checked conference proceedings and WHO consultative meeting reports, the reference lists of key documents and existing reviews, and contacted experts and nutritional supplement companies.Selection criteriaRandomized controlled trials (RCTs), quasi-randomized controlled trials (quasi-RCTs), and non-randomized controlled trials (NRCTs) of any oral nutritional supplement, compared to no nutritional intervention, placebo, or dietary advice alone, in people being treated for VL.Data collection and analysisTwo review authors independently screened the literature search results for studies that met the inclusion criteria. We had planned for two review authors to independently extract data and assess the risk of bias of the included studies. We planned to follow the Cochrane standard methodological procedures for assessing risk of bias and analysing the data.Main resultsWe identified no eligible studies for this review, either completed or ongoing.Authors' conclusionsWe found no studies, either completed or ongoing, that assessed the effects of oral nutritional supplements in people with VL who were being treated with anti-leishmanial drug therapy. Thus, we could not draw any conclusions on the impact of these interventions on primary cure of VL, definitive cure of VL, treatment completion, self-reported recovery from illness or resolution of symptoms, weight gain, increased skinfold thickness, other measures of lean or total mass, or growth in children.This absence of evidence should not be interpreted as evidence of no effect for nutritional supplements in people under VL treatment. It means that we did not identify research that fulfilled our review inclusion criteria.The effects of oral nutritional supplements in people with VL who are being treated with anti-leishmanial drug therapy have yet to be determined by rigorous experimental studies, such as cluster-randomized trials, that focus on outcomes relevant for patients.

Dataset Information

To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

Publications

To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets