Christian Derntl

TU Wien

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Astrid R. Mach‐Aigner

TU Wien

Robert L. Mach

TU Wien

Gabriel A. Vignolle

Austrian Institute of Technology

Melani Juric

TU Wien

Paul Primerano

TU Wien

Peter J. Schaap

Wageningen University & Research

Jasper Sloothaak

Wageningen University & Research

Dorett I. Odoni

German Cancer Research Center

Vítor A. P. Martins dos Santos

Universidade Federal do Rio de Janeiro

Thanaporn Laothanachareon

National Center for Genetic Engineering and Biotechnology

Cooperative Institutions

TU Wien

University of Vienna

Universidade de Brasília

BOKU University

Wageningen University & Research

Universidad de Guanajuato

Austrian Centre of Industrial Biotechnology (Austria)

Max Perutz Labs

Medical University of Vienna

Christian Doppler Laboratory for Thermoelectricity

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MOESM8 of Identification and functional characterization of novel xylose transporters from the cell factories Aspergillus niger and Trichoderma reesei

Figshare (2019)

Jasper Sloothaak Juan Tamayo-Ramos Dorett I. Odoni Thanaporn Laothanachareon Christian Derntl

Additional file 8. Multiple sequence alignment (MSA) of all transporters used for HMMgluT (constructed in a previous study, [9]) and HMMxylT (this study), plus the newly identified A. niger and T. reesei transporters.

Aspergillus niger

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10.6084/m9.figshare.10037750

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of Identification and functional characterization of novel xylose transporters from the cell factories Aspergillus niger and Trichoderma reesei

Figshare (2019)

Jasper Sloothaak Juan Tamayo-Ramos Dorett I. Odoni Thanaporn Laothanachareon Christian Derntl

of Identification and functional characterization of novel xylose transporters from the cell factories Aspergillus niger and Trichoderma reesei

Aspergillus niger

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10.6084/m9.figshare.10037732

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Identification of the Main Regulator Responsible for Synthesis of the Typical Yellow Pigment Produced by Trichoderma reesei

Applied and Environmental Microbiology (2016)

Christian Derntl Alice Rassinger Ewald Srebotnik Robert L. Mach Astrid R. Mach‐Aigner

ABSTRACT The industrially used ascomycete Trichoderma reesei secretes a typical yellow pigment during cultivation, while other Trichoderma species do not. A comparative genomic analysis suggested that a putative secondary metabolism cluster, containing two polyketide-synthase encoding genes, is responsible for the yellow pigment synthesis. This cluster is conserved in a set of rather distantly related fungi, including Acremonium chrysogenum and Penicillium chrysogenum . In an attempt to silence the cluster in T. reesei , two genes of the cluster encoding transcription factors were individually deleted. For a complete genetic proof-of-function, the genes were reinserted into the genomes of the respective deletion strains. The deletion of the first transcription factor (termed yellow pigment regulator 1 [Ypr1]) resulted in the full abolishment of the yellow pigment formation and the expression of most genes of this cluster. A comparative high-pressure liquid chromatography (HPLC) analysis of supernatants of the ypr1 deletion and its parent strain suggested the presence of several yellow compounds in T. reesei that are all derived from the same cluster. A subsequent gas chromatography/mass spectrometry analysis strongly indicated the presence of sorbicillin in the major HPLC peak. The presence of the second transcription factor, termed yellow pigment regulator 2 (Ypr2), reduces the yellow pigment formation and the expression of most cluster genes, including the gene encoding the activator Ypr1. IMPORTANCE Trichoderma reesei is used for industry-scale production of carbohydrate-active enzymes. During growth, it secretes a typical yellow pigment. This is not favorable for industrial enzyme production because it makes the downstream process more complicated and thus increases operating costs. In this study, we demonstrate which regulators influence the synthesis of the yellow pigment. Based on these data, we also provide indication as to which genes are under the control of these regulators and are finally responsible for the biosynthesis of the yellow pigment. These genes are organized in a cluster that is also found in other industrially relevant fungi, such as the two antibiotic producers Penicillium chrysogenum and Acremonium chrysogenum . The targeted manipulation of a secondary metabolism cluster is an important option for any biotechnologically applied microorganism.

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10.1128/aem.01408-16

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Citations (76)

Additional file 8 of Expanding the toolbox: another auxotrophic marker for targeted gene integrations in Trichoderma reesei

Figshare (2021)

Paul Primerano Melani Juric Robert L. Mach Astrid R. Mach‐Aigner Christian Derntl

Additional file 8: Genomic sequence of pCD-ReHis-eyfp.

Toolbox

Auxotrophy

10.6084/m9.figshare.16620660

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Additional file 1 of Novel approach in whole genome mining and transcriptome analysis reveal conserved RiPPs in Trichoderma spp

Figshare (2020)

Gabriel A. Vignolle Robert L. Mach Astrid R. Mach‐Aigner Christian Derntl

Additional file 1. The output of the RiPPMiner prediction for known precursor peptides of fungal RiPPs extracted from the UniProt database.

10.6084/m9.figshare.12038238

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FunOrder: A robust and semi-automated method for the identification of essential biosynthetic genes through computational molecular co-evolution

PLoS Computational Biology (2021)

Gabriel A. Vignolle Denise Schaffer Leopold Zehetner Robert L. Mach Astrid R. Mach‐Aigner

Secondary metabolites (SMs) are a vast group of compounds with different structures and properties that have been utilized as drugs, food additives, dyes, and as monomers for novel plastics. In many cases, the biosynthesis of SMs is catalysed by enzymes whose corresponding genes are co-localized in the genome in biosynthetic gene clusters (BGCs). Notably, BGCs may contain so-called gap genes, that are not involved in the biosynthesis of the SM. Current genome mining tools can identify BGCs, but they have problems with distinguishing essential genes from gap genes. This can and must be done by expensive, laborious, and time-consuming comparative genomic approaches or transcriptome analyses. In this study, we developed a method that allows semi-automated identification of essential genes in a BGC based on co-evolution analysis. To this end, the protein sequences of a BGC are blasted against a suitable proteome database. For each protein, a phylogenetic tree is created. The trees are compared by treeKO to detect co-evolution. The results of this comparison are visualized in different output formats, which are compared visually. Our results suggest that co-evolution is commonly occurring within BGCs, albeit not all, and that especially those genes that encode for enzymes of the biosynthetic pathway are co-evolutionary linked and can be identified with FunOrder. In light of the growing number of genomic data available, this will contribute to the studies of BGCs in native hosts and facilitate heterologous expression in other organisms with the aim of the discovery of novel SMs.

Proteome

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ENCODE

10.1371/journal.pcbi.1009372

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Nanoscale Infrared Spectroscopy and Chemometrics Enable Detection of Intracellular Protein Distribution

Analytical Chemistry (2020)

A. Catarina V. D. dos Santos Rosa Heydenreich Christian Derntl Astrid R. Mach‐Aigner Robert L. Mach

Determination of the intracellular location of proteins is one of the fundamental tasks of microbiology. Conventionally, label-based microscopy and super-resolution techniques are employed. In this work, we demonstrate a new technique that can determine intracellular protein distribution at nanometer spatial resolution. This method combines nanoscale spatial resolution chemical imaging using the photothermal-induced resonance (PTIR) technique with multivariate modeling to reveal the intracellular distribution of cell components. Here, we demonstrate its viability by imaging the distribution of major cellulases and xylanases in Trichoderma reesei using the colocation of a fluorescent label (enhanced yellow fluorescence protein, EYFP) with the target enzymes to calibrate the chemometric model. The obtained partial least squares model successfully shows the distribution of these proteins inside the cell and opens the door for further studies on protein secretion mechanisms using PTIR.

Chemometrics

Chemical Imaging

10.1021/acs.analchem.0c02228

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The Relation Between Promoter Chromatin Status, Xyr1 and Cellulase Expression in Trichoderma reesei

Current Genomics (2015)

Thiago Machado Mello-de-Sousa Alice Rassinger Christian Derntl Márcio José Poças-Fonseca Robert L. Mach

The ascomycete Trichoderma reesei is used for the production of plant cell wall-degrading enzymes in industrial scale. The interplay of the transactivator Xyr1 and the repressor Cre1 mainly regulates the expression of these enzymes. During induc-ing conditions, such as in the presence of sophorose, the transcription of the two major cellulase-encoding genes, cbh1 and cbh2, is activated as well as the expression of xyr1. In the presence of D-glucose carbon catabolite repression mediated by Cre1 takes place and the expression of Xyr1 and the plant cell wall-degrading enzymes is down-regulated. In this study we compare the chromatin status of xyr1, cbh1, and cbh2 promoters in the wild-type strain and the Cre1-deficient strain Rut-C30. Chromatin rearrangement occurs in the xyr1 promoter during induction on sophorose. Chromatin opening and protein-DNA interactions in the xyr1 promoter were detected especially in a region located 0.9 kb upstream the translation start co-don, which bears several putative Cre1-binding sites and a CCAAT-box. Moreover, the xyr1 promoter is overall more acces-sible in a cre1-truncated background, no matter which carbon source is present. This makes the xyr1 regulatory sequence a good target for promoter engineering aiming at the enhancement of cellulase production.

Transcription

10.2174/1389202917666151116211812

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Citations (42)

List of Contributors

Elsevier eBooks (2014)

Sunil S. Adav Marika Alapuranen Miguel Alcalde N. Aro Lea Atanasova

10.1016/b978-0-444-59576-8.01002-x

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The Functional Order (FunOrder) tool – Identification of essential biosynthetic genes through computational molecular co-evolution

bioRxiv (Cold Spring Harbor Laboratory) (2021)

Gabriel A. Vignolle Denise Schaffer Robert L. Mach Astrid R. Mach‐Aigner Christian Derntl

ABSTRACT Secondary metabolites (SMs) are a vast group of compounds with different structures and properties. Humankind uses SMs as drugs, food additives, dyes, and as monomers for novel plastics. In many cases, the biosynthesis of SMs is catalysed by enzymes whose corresponding genes are co-localized in the genome in biosynthetic gene clusters (BGCs). Notably, BGCs may contain so-called gap genes, that are not involved in the biosynthesis of the SM. Current genome mining tools can identify BGCs but they have problems with distinguishing essential genes from gap genes and defining the borders of a BGC. This can and must be done by expensive, laborious, and time-consuming comparative genomic approaches or co-expression analyses. In this study, we developed a novel tool that allows automated identification of essential genes in a BGC based solely on genomic data. The Functional Order (FunOrder) tool – Identification of essential biosynthetic genes through computational molecular co-evolution – searches for co-evolutionary linked genes in the BGCs. In light of the growing number of genomic data available, this will contribute to the studies of BGCs in native hosts and facilitate heterologous expression in other organisms with the aim of the discovery of novel SMs, including antibiotics and other pharmaceuticals.

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Heterologous expression

10.1101/2021.01.29.428829

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Citations (2)