Evidence map›Paper›PMID 30999885›Full record

ArticleBMC biotechnology2019

Characterisation of three novel α-L-arabinofuranosidases from a compost metagenome.

Brent Fortune, Sizwe Mhlongo, Leonardo Joaquim van Zyl, Robert Huddy, Mariette Smart, Marla Trindade

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Article in BMC biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

  1. Review
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4 · The record

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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

6 authors.

Brent FortuneInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Bellville, South Africa.
Sizwe MhlongoInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Bellville, South Africa.
Leonardo Joaquim van ZylInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Bellville, South Africa.ORCID 0000-0001-9364-8671
Robert HuddyInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Bellville, South Africa.
Mariette SmartInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Bellville, South Africa.
Marla TrindadeInstitute for Microbial Biotechnology and Metagenomics, University of the Western Cape, Bellville, South Africa. ituffin@uwc.ac.za.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe importance of the accessory enzymes such as α-L-arabinofuranosidases (AFases) in synergistic interactions within cellulolytic mixtures has introduced a paradigm shift in the search for hydrolytic enzymes. The aim of this study was to characterize novel AFase genes encoding enzymes with differing temperature optima and thermostabilities for use in hydrolytic cocktails.

resultsThree fosmids, pFos-H4, E3 and D3 were selected from the cloned metagenome of high temperature compost, expressed in Escherichia coli and subsequently purified to homogeneity from cell lysate. All the AFases were clustered within the GH51 AFase family and shared a homo-hexameric structure. Both AFase-E3 and H4 showed optimal activity at 60 °C while AFase-D3 had unique properties as it showed optimal activity at 25 °C as well as the ability to maintain substantial activity at temperatures as high as 90 °C. However, AFase-E3 was the most thermostable amongst the three AFases showing full activity even at 70 °C. The maximum activity was observed at a pH profile between pH 4.0-6.0 for all three AFases with optimal activity for AFase H4, D3 and E3 at pH 5.0, 4.5 and 4.0, respectively. All the AFases showed K

conclusionAll three AFases displayed different biochemical characteristics despite all showing conserved overall structural similarity with typical domains of AFases belonging to GH51 family. The hydrolysis of cellobiose by a GH51 family AFase is demonstrated for the first time in this study.

Indexed as

CompostingEnzyme StabilityGlycoside HydrolasesHot TemperatureHydrogen-Ion ConcentrationHydrolysisIsoenzymesKineticsMetagenomePhylogenyPlasmidsSubstrate Specificityalpha-N-arabinofuranosidaseGlycoside HydrolasesIsoenzymesArabinofuranosidaseCompostMetagenomicsThermostability

Identifiers

PMID30999885
PMCPMC6472066

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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.