Evidence map›Paper›PMID 29169319›Full record

ArticleBMC genomics2017

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

Birgit S Gruben, Miia R Mäkelä, Joanna E Kowalczyk, Miaomiao Zhou, Isabelle Benoit-Gelber, Ronald P De Vries

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.1field-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

34 citing papers in PubMed, 64 citations in OpenAlex.

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  9. The Amylolytic Regulator AmyR ofJournal of fungi (Basel, Switzerland) · 2023
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  12. Genome-wide transcription landscape of citric acid producingFrontiers in bioengineering and biotechnology · 2023
    Article
  13. The Sugar Metabolic Model ofJournal of fungi (Basel, Switzerland) · 2022
    Article
  14. Article
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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

6 authors at 4 institutions in 4 countries.

Birgit S GrubenFungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
Miia R MäkeläFungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
Joanna E KowalczykFungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
Miaomiao ZhouFungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
Isabelle Benoit-GelberFungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
Ronald P De VriesFungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands. r.devries@westerdijkinstitute.nl.ORCID http://orcid.org/0000-0002-4363-1123
Utrecht University · NLAvans University of Applied Sciences · NLConcordia University · USUniversity of Helsinki · FI

Funding

Netherlands Genomics Initiative 93511035Stichting voor de Technische Wetenschappen UGC 0793
6 · The paper itself

Abstract

backgroundThe Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ΔxlnR, ΔaraR, ΔamyR, ΔrhaR and ΔgalX that were grown on their specific inducing compounds.

resultsThe cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far.

conclusionsExpression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In addition, the data provides additional evidence in favor of and against the similarity-based functions assigned to uncharacterized genes.

Indexed as

Gene Expression Regulation, FungalAspergillus nigerCarbohydrate MetabolismCluster AnalysisFungal ProteinsGene Expression ProfilingGene Expression Regulation, EnzymologicInulinMutationPectinsStarchSucroseTrans-ActivatorsFungal ProteinsInulinPectinsStarchSucroseTrans-ActivatorsXlnR protein, AspergillusAmyRAraRAspergillus nigerCAZy genesGalXPlant biomass degradationRhaRTranscriptional regulatorsXlnR

Identifiers

PMID29169319
PMCPMC5701360
OpenAlexW2770849773

What OpenQuestion holds

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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.