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      Effect of the res2 transcription factor gene deletion on protein secretion and stress response in the hyperproducer strain Trichoderma reesei Rut-C30


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          The fungus Trichoderma reesei is one of the most used industrial cellulase producers due to its high capacity of protein secretion. Strains of T. reesei with enhanced protein secretion capacity, such as Rut-C30, have been obtained after several rounds of random mutagenesis. The strain was shown to possess an expanded endoplasmic reticulum, but the genetic factors responsible for this phenotype remain still unidentified. Recently, three new transcription factors were described in Neurospora crassa which were demonstrated to be involved in protein secretion. One of them, RES2, was involved in upregulation of secretion-related genes. The aim of our present study was therefore to analyze the role of RES2, on protein secretion in the T. reesei Rut-C30 strain.


          Deletion of the res2 gene in Rut-C30 resulted in slightly slower growth on all substrates tested, and lower germination rate as well as lower protein secretion compared to the parental strain Rut-C30. Transcriptomic analysis of the Rut-C30 and the Δ res2 mutant strain in secretion stress conditions showed remarkably few differences : 971 genes were differentially expressed (DE) in both strains while 192 genes out of 1163 (~ 16.5%) were DE in Rut-C30 only and 693 out of 1664 genes (~ 41.6%) displayed differential expression solely in Δ res2. Notably, induction of protein secretion by cultivating on lactose and addition of secretion stress inducer DTT induced many genes of the secretion pathway similarly in both strains. Among the differentially expressed genes, those coding for amino acid biosynthesis genes, transporters and genes involved in lipid metabolism were found to be enriched specifically in the Δ res2 strain upon exposure to lactose or DTT. Besides, redox homeostasis and DNA repair genes were specifically upregulated in the Δ res2 strain, indicating an altered stress response.


          These results indicate that in the T. reesei Rut-C30 strain, RES2 does not act as a master regulator of the secretion pathway, but it contributes to a higher protein secretion by adjusting the expression of genes involved in different steps of protein synthesis and the secretion pathway.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12866-023-03125-z.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

                Author and article information

                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central (London )
                30 November 2023
                30 November 2023
                : 23
                : 374
                [1 ]IFP Energies Nouvelles, ( https://ror.org/03gcbhc33) 1 et 4, avenue de Bois-Préau, Rueil-Malmaison Cedex, 92852 France
                [2 ]GRID grid.462036.5, Département de biologie, , GenomiqueENS, Institut de Biologie de l’ENS (IBENS), CNRS, INSERM, Université PSL, ; École normale supérieure, Paris, 75005 France
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                : 6 June 2023
                : 17 November 2023
                Funded by: FundRef http://dx.doi.org/10.13039/501100017171, Agence de la transition écologique;
                Award ID: TEZ20-001
                Funded by: FundRef http://dx.doi.org/10.13039/501100001665, Agence Nationale de la Recherche;
                Award ID: ANR-10-INBS-0009
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Microbiology & Virology
                fungi,trichoderma reesei,cellulases,secretion,secretion stress,upr
                Microbiology & Virology
                fungi, trichoderma reesei, cellulases, secretion, secretion stress, upr


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