Evidence map›Paper›PMID 21846360›Full record

ArticleBMC systems biology2011

Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052.

Caroline B Milne, James A Eddy, Ravali Raju, Soroush Ardekani, Pan-Jun Kim, Ryan S Senger, Yong-Su Jin, Hans P Blaschek, Nathan D Price

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
5.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 112 citations in OpenAlex.

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  10. Development of a Genome-Scale Metabolic Model ofFrontiers in bioengineering and biotechnology · 2020
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  14. Amino acid catabolism-directed biofuel production inBiotechnology reports (Amsterdam, Netherlands) · 2017
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  18. Development of a coreBiotechnology for biofuels · 2017
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  20. Rebalancing Redox to Improve Biobutanol Production byBioengineering (Basel, Switzerland) · 2015
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Caroline B MilneDepartment of Chemical and Biomolecular Engineering, University of Illinois, Urbana, USA.
James A Eddy
Ravali Raju
Soroush Ardekani
Pan-Jun Kim
Ryan S Senger
Yong-Su Jin
Hans P Blaschek
Nathan D Price
University of Illinois Urbana-Champaign · USUniversity of Minnesota · USVirginia Tech · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSolventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i) naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii) can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis). Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications.

resultsWe present the first genome-scale metabolic model (iCM925) for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test). Inhibition of the hydrogenase reaction was found to have a strong effect on butanol formation--as experimentally observed.

conclusionsMicrobial production of butanol by C. beijerinckii offers a promising, sustainable, method for generation of this important chemical and potential biofuel. iCM925 is a predictive model that can accurately reproduce physiological behavior and provide insight into the underlying mechanisms of microbial butanol production. As such, the model will be instrumental in efforts to better understand, and metabolically engineer, this microorganism for improved butanol production.

Indexed as

BioreactorsModels, BiologicalButanolsClostridium beijerinckiiComputer SimulationFermentationGenome, BacterialHexosesIndustrial MicrobiologyMetabolic Networks and PathwaysPentosesSystems BiologyButanolsHexosesPentoses

Identifiers

PMID21846360
PMCPMC3212993
OpenAlexW2101837880

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.