Evidence map›Paper›PMID 31890016›Full record

ArticleBiotechnology for biofuels2019

Genome shuffling enhances stress tolerance of

Weiting Wang, Bo Wu, Han Qin, Panting Liu, Yao Qin, Guowei Duan, Guoquan Hu, Mingxiong He

Open access · goldAbstract read
In one paragraph

Article in Biotechnology for biofuels, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 51 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

8 authors at 3 institutions in 1 country.

Weiting Wang *1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Bo Wu *1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Han Qin1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Panting Liu1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Yao Qin1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Guowei Duan1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Guoquan Hu1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.
Mingxiong He1Biomass Energy Technology Research Centre, Key Laboratory of Development and Application of Rural Renewable Energy (Ministry of Agriculture and Rural Affairs), Biogas Institute of Ministry of Agriculture and Rural Affairs, Section 4-13, Renmin Rd. South, Chengdu, 610041 People's Republic of China.ORCID 0000-0002-9780-6865
Chinese Academy of Agricultural Engineering · CNBiogas Institute of Ministry of Agriculture · CNChengdu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFurfural and acetic acid are the two major inhibitors generated during lignocellulose pretreatment and hydrolysis, would severely inhibit the cell growth, metabolism, and ethanol fermentation efficiency of

resultsAfter two rounds of genome shuffling, 10 different mutants with improved cell growth and ethanol yield in the presence of 5.0 g/L acetic acid and 3.0 g/L furfural were obtained. The two most prominent genome-shuffled strains, 532 and 533, were further investigated along with parental strains in the presence of 7.0 g/L acetic acid and 3.0 g/L furfural. The results showed that mutants 532 and 533 were superior to the parental strain AQ8-1 in the presence of 7.0 g/L acetic acid, with a shorter fermentation time (30 h) and higher productivity than AQ8-1. Mutant 533 exhibited subtle differences from parental strain F34 in the presence of 3.0 g/L furfural. Mutations present in 10 genome-shuffled strains were identified via whole-genome resequencing, and the source of each mutation was identified as either de novo mutation or recombination of the parent genes.

conclusionsThese results indicate that genome shuffling is an efficient method for enhancing stress tolerance in

Indexed as

ElectrofusionGenome shufflingInhibitor toleranceMutagenesisZymomonas mobilis

Identifiers

PMID31890016
PMCPMC6913010
OpenAlexW2994866540

What OpenQuestion holds

Textmetadata
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.