Evidence map›Paper›PMID 33449253›Full record

ArticleBiotechnology letters2021

Differential proteomics reveals main determinants for the improved pectinase activity in UV-mutagenized Aspergillus niger strain.

Weiling Lin, Xiaohong Xu, Ruirui Lv, Wei Huang, Hafeez Ul Haq, Yuanyuan Gao, Hongli Ren, Canhua Lan, Baoyu Tian

Abstract read
PubMed Publisher
In one paragraph

Article in Biotechnology letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Fungal pectinases: an insight into production, innovations and applications.World journal of microbiology & biotechnology · 2023
    Review
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 1 institution in 1 country.

Weiling LinEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Xiaohong XuLibrary, Fujian Normal University, Fuzhou, 350108, Fujian, China.
Ruirui LvEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Wei HuangEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Hafeez Ul HaqEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Yuanyuan GaoEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Hongli RenEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Canhua LanEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China.
Baoyu TianEngineering Research Center of Industrial Microbiology of Ministry of Education, College of Life Sciences, Fujian Normal University, No.8, Shangsan Road, Cangshan District, Fuzhou, 350108, Fujian, China. tianby@fjnu.edu.cn.ORCID http://orcid.org/0000-0002-9717-0297
Fujian Normal University · CN

Funding

National Natural Science Foundation of China 31660544National Natural Science Foundation of China 31670125Natural Science Foundation of Fujian Province 2020J01173
6 · The paper itself

Abstract

objectivesTo reveal the potential mechanism and key determinants that contributed to the improved pectinase activity in Aspergillus niger mutant EIMU2, which was previously obtained by UV-mutagenesis from the wild-type A. niger EIM-6.

resultsProteomic analysis for Aspergillus niger EIMU2 by two-dimensional electrophoresis demonstrated that mutant EIMU2 harbored a multiple enzyme system for the degradation of pectin, mainly constituting by main-chain-cleaving enzymes polygalacturonase, pectate lyase, pectinesterase, and some accessory enzymes rhamnogalacturonan lyase and arabinofuranosidase. Further quantitatively differential proteomic analysis revealed that the quantities of four proteins, pectinesterase, rhamnogalacturonan lyase A, DNA-directed RNA polymerase A, and a hypothetical protein in strain EIMU2 were much higher than those in EIM-6. PCR amplification, sequencing and alignment analysis of genes for the two main members of pectin-degrading enzymes, pectate lyase and polygalacturonase showed that their sequences were completely consistent in A. niger EIM-6 and mutant EIMU2.

conclusionsThe result demonstrated that the improved pectinase activity by UV-mutagenesis in A. niger EIMU2 was probably contributed to the up-regulated expression of rhamnogalacturonan lyase, or pectinesterase, which resulted in the optimization of synergy amongst different components of pectin-degrading enzymes.

Indexed as

Aspergillus nigerFermentationFungal ProteinsGene Expression Regulation, FungalMutationPolygalacturonasePolysaccharide-LyasesProteomicsSequence Analysis, DNAUltraviolet RaysUp-RegulationFungal Proteinspectate lyasePolygalacturonasePolysaccharide-LyasesAspergillus niger mutantDifferential proteomicsKey determinantsPectin‐degrading enzymesSynergy

Identifiers

PMID33449253
OpenAlexW3120928584

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Registered trials

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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.