Article
Biochemical Research Methods
Diana Szeliova, Dmytro Iurashev, David E. Ruckerbauer, Gunda Koellensperger, Nicole Borth, Michael Melcher, Jurgen Zanghellini
Summary: This study investigated the impact of sampling frequency and measurement errors of metabolite concentrations during batch culture on the accuracy of calculated exchange rates, as well as how this error propagates into FBA predictions of growth rates. The results showed that accurate measurements of essential amino acids with low uptake rates are crucial for FBA predictions, followed by a sufficient number of analyzed time points. High measurement accuracy and sampling frequency are essential for reliably predicting growth rate differences of cell lines.
BIOTECHNOLOGY JOURNAL
(2021)
Article
Biochemical Research Methods
Diana Szeliova, Jerneja Stor, Isabella Thiel, Marcus Weinguny, Michael Hanscho, Gabriele Lhota, Nicole Borth, Juergen Zanghellini, David E. Ruckerbauer, Isabel Rocha
Summary: Chinese hamster ovary (CHO) cells are the leading platform for producing biopharmaceuticals with human-like glycosylation, but it typically takes several months of trial-and-error approaches to develop high-producer cell lines. Metabolic modeling has the potential to make cell line and process development faster and cheaper by predicting targeted modifications, and accurately predicting metabolic phenotypes is crucial for successful use of genome-scale metabolic reconstructions of CHO.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Oncology
Helena A. Herrmann, Mate Rusz, Dina Baier, Michael A. Jakupec, Bernhard K. Keppler, Walter Berger, Gunda Koellensperger, Jurgen Zanghellini
Summary: The study reveals the metabolic reprogramming in drug-resistant cells sensitive to ruthenium- and platinum-based drugs. The findings suggest that the metabolic reprogramming in resistant cells is primarily limited to a select number of pathways.
Article
Biochemical Research Methods
Bianca A. Buchner, Juergen Zanghellini
Summary: The newly developed Python package EFMlrs utilizes COBRApy to perform EFM enumeration on metabolic networks. It provides support for established tools and offers new possibilities for unbiased analysis of large metabolic models through EFM analysis.
BMC BIOINFORMATICS
(2021)
Review
Biochemical Research Methods
Jerneja Stor, David E. Ruckerbauer, Diana Szeliova, Juergen Zanghellini, Nicole Borth
Summary: Metabolic modelling aims to develop robust and highly predictive modelling approaches by considering parameter estimation methods, accuracy of input data, and model selection for specific research questions. Kinetic models are frequently used to capture the dynamic nature of protein glycosylation in biopharmaceutical research.
CURRENT OPINION IN BIOTECHNOLOGY
(2021)
Article
Biochemical Research Methods
Stefan Mueller, Diana Szeliova, Juergen Zanghellini
Summary: Traditional metabolic models of cellular growth often involve an approximate biomass reaction, which doesn't take into account the variability in biomass composition. To address this issue, new classes of elementary vectors called elementary growth modes (EGMs) and elementary growth vectors (EGVs) have been introduced. These new concepts provide a better understanding of all possible biomass compositions and can be seen as unbiased versions of traditional elementary flux modes/vectors (EFMs/EFVs).
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biochemical Research Methods
Christoph Bueschl, Maria Doppler, Elisabeth Varga, Bernhard Seidl, Mira Flasch, Benedikt Warth, Juergen Zanghellini
Summary: A machine-learning-based approach called PeakBot has been developed for detecting chromatographic peaks in LC-HRMS data. It detects local signal maxima and uses a convolutional neural network for inspection, achieving accurate identification of chromatographic peaks.
Article
Chemistry, Analytical
Yasin El Abiead, Christoph Bueschl, Lisa Panzenboeck, Mingxun Wang, Maria Doppler, Bernhard Seidl, Juergen Zanghellini, Pieter C. Dorrestein, Gunda Koellensperger
Summary: This study utilized 13C labeled and unlabeled Pichia pastoris extracts to identify heterogeneous multimerization in biological samples and successfully annotated the monomeric partners of these heteromers. Additionally, they created the first MS/MS library that included data from heteromultimers and demonstrated the relevance of these newly annotated ions to other publicly available datasets. Furthermore, their workflow detected metabolite features originating from heterodimers in other datasets as well.
ANALYTICA CHIMICA ACTA
(2022)
Article
Biochemical Research Methods
Kevin Mildau, Justin J. J. van der Hooft, Mira Flasch, Benedikt Warth, Yasin El Abiead, Gunda Koellensperger, Jurgen Zanghellini, Christoph Bueschl
Summary: This article presents a method for targeted and untargeted detection of homologue series using an R package, homologueDiscoverer, and provides evaluation and management through interactive plots and simple local database functionalities.
Article
Biochemical Research Methods
Mathias Gotsmy, Julia Brunmair, Christoph Bueschl, Christopher Gerner, Juergen Zanghellini
Summary: The study presents an improved normalization method, MIX, that combines the advantages of a pharmacokinetic model and probabilistic quotient normalization. Testing on synthetic and real biofluid data shows that MIX can better correct for size effects.
BMC BIOINFORMATICS
(2022)
Review
Biochemical Research Methods
Leopold Zehetner, Diana Szeliova, Barbara Kraus, Michael Graninger, Juergen Zanghellini, Juan A. Hernandez Bort
Summary: Over the past decades, virus-like particle (VLP)-based gene therapy (GT) has shown promise in treating inherited diseases or cancer. However, the high costs due to inefficient production processes remain a major challenge. This review aims to integrate genome-scale metabolic models (GSMMs) with cell lines used for VLP synthesis, summarizing recent advances and challenges in GSMMs for Chinese hamster ovary (CHO) cells and providing an overview of potential cell lines for GT. Although GSMMs have improved growth rates and recombinant protein production in CHO cells, no GSMM has been established for VLP production. To address this, an overview of existing omics data and the highest reported production titers is provided.
BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemical Research Methods
Bianca Buchner, Tom J. Clement, Daan H. de Groot, Juergen Zanghellini
Summary: Characterizing all steady-state flux distributions in metabolic models is challenging due to the explosion of possibilities. We integrate a scalable parallel vertex enumeration method into an existing tool, ecmtool, to speed up computation and reduce memory requirements. By applying this enhanced tool to a minimal cell metabolic model, we discover a large number of elementary conversion modes (ECMs) and identify redundant sub-networks.
Article
Biotechnology & Applied Microbiology
Mathias Gotsmy, Florian Strobl, Florian Weiss, Petra Gruber, Barbara Kraus, Juergen Mairhofer, Juergen Zanghellini
Summary: This study used constraint-based metabolic modeling to optimize the productivity of plasmid DNA (pDNA) production. By depleting certain nutrients in the growth medium, cell growth was stalled and pDNA production was increased, resulting in improved yield and quality. The findings highlight the importance of controlling nutrient availability for enhancing biotechnological product manufacturing.
MICROBIAL CELL FACTORIES
(2023)
