Evidence map›Paper›PMID 24886412›Full record

ArticleBMC biotechnology2014

Expression and characterization of a GH43 endo-arabinanase from Thermotoga thermarum.

Hao Shi, Huaihai Ding, Yingjuan Huang, Liangliang Wang, Yu Zhang, Xun Li, Fei Wang

Open access · goldAbstract read
In one paragraph

Article in BMC biotechnology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 29 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Hao Shi
Huaihai Ding
Yingjuan Huang
Liangliang Wang
Yu Zhang
Xun Li
Fei WangCollege of Chemical Engineering, Nanjing Forestry University, Nanjing 210037, China. hgwf@njfu.edu.cn.
Nanjing Forestry University · CNInstitute of Chemical Industry of Forest Products · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArabinan is an important plant polysaccharide degraded mainly by two hydrolytic enzymes, endo-arabinanase and α-L-arabinofuranosidase. In this study, the characterization and application in arabinan degradation of an endo-arabinanase from Thermotoga thermarum were investigated.

resultsThe recombinant endo-arabinanase was expressed in Escherichia coli BL21 (DE3) and purified by heat treatment followed by purification on a nickel affinity column chromatography. The purified endo-arabinanase exhibited optimal activity at pH 6.5 and 75°C and its residual activity retained more than 80% of its initial activity after being incubated at 80°C for 2 h. The results showed that the endo-arabinanase was very effective for arabinan degradation at higher temperature. When linear arabinan was used as the substrate, the apparent K(m) and V(max) values were determined to be 12.3 ± 0.15 mg ml⁻¹ and 1,052.1 ± 12.7 μmol ml⁻¹ min⁻¹, respectively (at pH 6.5, 75°C), and the calculated kcat value was 349.3 ± 4.2 s⁻¹.

conclusionsThis work provides a useful endo-arabinanase with high thermostability andcatalytic efficiency, and these characteristics exhibit a great potential for enzymatic conversion of arabinan.

Indexed as

Gene Expression Regulation, BacterialAmino Acid SequenceChromatography, AffinityEscherichia coliGlycoside HydrolasesGram-Negative Anaerobic Straight, Curved, and Helical RodsHydrogen-Ion ConcentrationKineticsMolecular Sequence DataPolysaccharidesProtein Structure, TertiaryRecombinant ProteinsSubstrate SpecificityTemperaturearabanEndo-arabinaseGlycoside HydrolasesPolysaccharidesRecombinant Proteins

Identifiers

PMID24886412
PMCPMC4021227
OpenAlexW2070722030

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.