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Elucidation of cellular functions of the Deubiquitinases USP53 and USP54
(2025) Gallant, Kai; Gersch, Malte; Waldmann, Herbert
Ubiquitylation is a reversible post-translational modification that is vital to most cellular processes. Deubiquitinases (DUBs), which modulate ubiquitylation, thus fulfil a critical role in maintaining a healthy cell state. Consequently, numerous pathological conditions are associated with misregulated or mutated DUBs. Two enzymes that have been linked to human pathologies are USP53 and USP54, two poorly characterised ubiquitin-specific protease (USP) family members which were annotated as catalytically inactive pseudoenzymes. Rudimentary knowledge about the cellular roles of USP53 and USP54 and limited insights into their potential substrates has, however, hampered a better understanding of their association with the reported diseases and phenotypes.
The endeavour to better understand both proteins in this dissertation began by establishing enzymatic activity of both proteins. In subsequent experiments, the herein presented work thus focused on filling the knowledge gap between DUB activity and reported pathologies. As such, this dissertation provides a model that establishes a link between USP53 mutations and cholestasis as well as hearing loss. This was achieved by a combination of cell biological approaches, state-of-the-art mass spectrometry and a variety of enrichment tools allowing for the isolation and subsequent enzymatic treatment of ubiquitinated proteins. These methods facilitated the identification of two tricellular junction proteins, MARVELD2 and LSR, as substrates of USP53. For MARVELD2, significantly increased K63-linked ubiquitination upon depletion of the DUB could be demonstrated. Notably, the most prominent ubiquitinated species found to be emerging in these conditions is diubiquitinated MARVELD2, thus converging with in vitro work conducted within the group. Furthermore, this dissertation provides insights into the cellular functions of USP54, highlighting its role in cell cycle regulation and microtubule network organisation. In order to relate these phenotypic effects to catalytic activity, ubiquitin enrichment coupled to mass spectrometry was optimised which identified a set of proposed substrates. In addition, proximity labelling revealed USP54 interactors that localise to three discrete cellular compartments, centrioles, tight junctions and endolysosomal membranes. Orthogonal experiments furthermore supported interaction of the DUB with 14-3-3 proteins which indicates a regulation of USP54 protein abundance during the cell cycle.
In conclusion, this work advances the knowledge about the two underexplored DUBs USP53 and USP54, while demonstrating the utility of combinatorial ubiquitin enrichment approaches to study the nature of ubiquitination on DUB substrates. The findings in conjunction with the reported pathologies will pave the way to better understand the association of DUB and diseases and potentially allow hijacking USP54 for novel therapeutic opportunities.
Amtliche Mitteilungen der Technischen Universität Dortmund Nr. 11
(Technische Universität Dortmund, 2025-05-07)
Tree ensemble methods for ordinal prediction
(2025) Buczak, Philip; Pauly, Markus; Doebler, Philipp
Research questions and applications in the social and life sciences often involve ordinal response data. Student performance is assessed through ordinal grades, patients may express the perceived severity of their symptoms in ordinal levels and respondents of questionnaires may voice their political views through rating given statements. As such, the prediction of ordinal responses is relevant for many fields and can help, e.g., identifying which students may benefit from educational support systems. Traditionally, ordinal responses have been modeled through parametric models such as the proportional odds model. In light of the increasing quantities of data in these fields as well as the continued proliferation of machine learning (ML) methods, recent years saw the establishment of a new methodological stream of ordinal prediction methods based on ML. These methods promise high predictive performance for settings in which traditional parametric models may face difficulties (e.g., highly non-linear effects, high-dimensional data). However, many of these ML methods were originally not specifically tailored towards ordinal responses. Therefore, several extensions and adaptations of ML methods (particularly for tree-based methods) have been proposed to take ordinality into account. A particularly promising approach based on Random Forest (RF) is Ordinal Forest (OF; Hornung, 2019) which assigns numeric scores to the ordinal response categories and uses the scores to train a regression RF. To determine suitable score choices, OF performs a prior optimization step in which scores are optimized w.r.t. their predictive performance.
The impact of crisis on firms´stakeholders and the moderating effect of innovation
(2025) Seidinger, Tim; Kraft, Kornelius; Böhm, Michael J.
This dissertation empirically investigates the effects of the Global Financial Crisis (GFC) and the COVID-19 pandemic on German firms and their stakeholders, focusing specifically on two key aspects: (i) vocational training provision and (ii) payments to stakeholders. Both vocational training and wages are crucial economic factors. Vocational training is a fundamental component of human capital development, enhancing workers' skills and productivity, thereby driving economic growth and improving firms' competitiveness. Wages, on the other hand, play a vital role in labor supply by reflecting workers' value in the economy while also influencing consumer demand.
This thesis makes a significant contribution to existing literature by examining potential differences in crisis impacts between stakeholders of innovative and non-innovative firms (Chapters 1 and 3). Additionally, it distinguishes between various stakeholder groups (Chapters 2 and 3).
The findings reveal that both general training provision and training expenses per employee increased during the financial crisis. While innovation does not moderate the increase in general training provision, non-innovative firms exhibit a stronger rise in training expenses per employee. Regarding pay adjustments, results indicate that affected firms are more likely to reduce payments across all stakeholder groups. Notably, reductions in executive compensation occur with significantly higher likelihood compared to other groups. Moreover, innovation increases the probability of pay cuts—particularly for shareholders and executives—suggesting that innovative firms primarily pass on the implicit costs of crises to groups with greater financial flexibility.
Overall, this dissertation enhances our understanding of how crises impact firms and their stakeholders while emphasizing the critical role of innovation as a moderating factor within this area of research.
Theory and applications of wide field surface plasmon resonance microscopy for discrete particles detection
(2025) Al Bataineh, Qais Mohammed Turki; Franzke, Joachim; Bayer, Manfred
Detecting and characterizing nano-objects with low concentrations, such as biological particles, is
a substantial challenge in analytical science. The wide-field surface plasmon resonance microscopy
(WF-SPRM) can detect individual nano-objects in solutions and gas media bound to the sensor
surface. Therefore, WF-SPRM can detect low nano-object concentrations because the image
contains several square millimeters. In this work, the fundamental parameters for building highly
sensitive WF-SPRM were optimized. WF-SPRM can detect individual nano-objects in solutions
and gas media. Therefore, we derived a discrete particle model of SPR to describe the SPR sensor
of discrete particle detection. Theoretical, numerical, and experimental analyses of the SPR
detection principle were performed by considering discrete particle detection. Additionally, the
influence on the SPR sensitivity of coating the gold/silver layer with a dielectric layer with varying
refractive index is also studied. Different polyelectrolyte brushes, like polyacrylic acid, polyacrylic
acid-polyethylene oxide, and polyacrylic acid/iodine, are used to validate the enhancement of the
SPR sensitivity. Validation experiments are performed using polystyrene and silica nanoparticles
of varying sizes. Finally, the surface plasmon coupling behavior between the localized surface
plasmons (LSPs) of different shapes and sizes of metal nanostructures and the propagating surface
plasmons (PSPs) of the metal surface is investigated by employing experimental, simulation, and
theoretical approaches.