Discovery of novel plant biomass conversion associated fungal transcription factors using a network-based approach

Mao Peng; Astrid Mueller; Joanna E. Kowalczyk; Roland S. Kun; Ronald P. de Vries

doi:10.1016/j.crbiot.2024.100230

Discovery of novel plant biomass conversion associated fungal transcription factors using a network-based approach

Mao Peng^*, Astrid Mueller, Joanna E. Kowalczyk, Roland S. Kun, Ronald P. de Vries

^*Bijbehorende auteur voor dit werk

Onderzoeksoutput: Bijdrage aan wetenschappelijk tijdschrift/periodieke uitgave › Artikel › Wetenschappelijk › peer review

Samenvatting

Fungal plant biomass conversion (FPBC) is an important component of the global carbon cycle and has been widely applied for the production of biofuels, enzymes and biochemicals. Identification of transcription factors (TFs) governing FPBC is crucial for genetic engineering of industrial fungi towards sustainable production of high-value bioproducts from renewable lignocellulose. Here, we developed a bioinformatics framework for the identification of FPBC related TFs based on reconstructed gene regulatory networks and enrichment analysis of manually curated FPBC gene sets. Applying this approach to model fungi Aspergillus niger and Neurospora crassa, we successfully identified both known TFs and promising candidates. The function of one identified TF, HapX, has been experimentally validated, and several candidates were supported by literature, transcriptome data and initial growth analysis. Our new approach will accelerate the identification of novel TFs involved in FPBC, and facilitate the further improvement of fungal cell factories.

Originele taal-2	Engels
Artikelnummer	100230
Tijdschrift	Current Research in Biotechnology
Volume	8
DOI's	https://doi.org/10.1016/j.crbiot.2024.100230
Status	Gepubliceerd - jan. 2024

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10.1016/j.crbiot.2024.100230

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Citeer dit

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title = "Discovery of novel plant biomass conversion associated fungal transcription factors using a network-based approach",

abstract = "Fungal plant biomass conversion (FPBC) is an important component of the global carbon cycle and has been widely applied for the production of biofuels, enzymes and biochemicals. Identification of transcription factors (TFs) governing FPBC is crucial for genetic engineering of industrial fungi towards sustainable production of high-value bioproducts from renewable lignocellulose. Here, we developed a bioinformatics framework for the identification of FPBC related TFs based on reconstructed gene regulatory networks and enrichment analysis of manually curated FPBC gene sets. Applying this approach to model fungi Aspergillus niger and Neurospora crassa, we successfully identified both known TFs and promising candidates. The function of one identified TF, HapX, has been experimentally validated, and several candidates were supported by literature, transcriptome data and initial growth analysis. Our new approach will accelerate the identification of novel TFs involved in FPBC, and facilitate the further improvement of fungal cell factories.",

keywords = "Fungi, Gene regulatory networks, HapX, Plant biomass conversion, Transcription factors",

author = "Mao Peng and Astrid Mueller and Kowalczyk, {Joanna E.} and Kun, {Roland S.} and {de Vries}, {Ronald P.}",

note = "Publisher Copyright: {\textcopyright} 2024 The Author(s)",

year = "2024",

month = jan,

doi = "10.1016/j.crbiot.2024.100230",

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volume = "8",

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AU - Peng, Mao

AU - Mueller, Astrid

AU - Kowalczyk, Joanna E.

AU - Kun, Roland S.

AU - de Vries, Ronald P.

PY - 2024/1

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AB - Fungal plant biomass conversion (FPBC) is an important component of the global carbon cycle and has been widely applied for the production of biofuels, enzymes and biochemicals. Identification of transcription factors (TFs) governing FPBC is crucial for genetic engineering of industrial fungi towards sustainable production of high-value bioproducts from renewable lignocellulose. Here, we developed a bioinformatics framework for the identification of FPBC related TFs based on reconstructed gene regulatory networks and enrichment analysis of manually curated FPBC gene sets. Applying this approach to model fungi Aspergillus niger and Neurospora crassa, we successfully identified both known TFs and promising candidates. The function of one identified TF, HapX, has been experimentally validated, and several candidates were supported by literature, transcriptome data and initial growth analysis. Our new approach will accelerate the identification of novel TFs involved in FPBC, and facilitate the further improvement of fungal cell factories.

KW - Fungi

KW - Gene regulatory networks

KW - HapX

KW - Plant biomass conversion

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