Semester 26: Upcoming Seminars

The online seminar will re-start in April 2026. The list of speakers will be displayed here:

Upcoming Seminars

Location: Zoom

Heterogeneity in responses to ribosome-targeting antibiotics mediated by bacterial RNA repair

RNA repair is critical for cellular function. The Rtc system maintains RNA integrity within the translational machinery of bacteria.

In E. coli, Rtc expression enables cells to rescue growth and survive treatment by conferring transient resistance to ribosome-targeting antibiotics, yet the mechanisms underpinning this resistance remain obscure.

Here, we present a computational model of Rtc-regulated repair of translational RNAs. Integrating model predictions with experimental validations, we uncover notable cell-to-cell heterogeneity in rtc expression that impacts on translational capacity, indicating that rtc may induce a form of heteroresistance.

We moreover identify Rtc targets that may reduce the translational capacity of cells and so potentiate antibiotic effects. Our findings elucidate a complex response underpinning resistance conferred by Rtc, offering alternate routes for addressing resistance in E. coli and other relevant pathogens.

If you missed a seminar, you can watch the video recordings of several the talks and discussions. Check out Previous Seminars! Talks with the recording are labeled accordingly.

In Brief

The Online Seminar Series "Modelling approaches for disease processes" is organized by Researchers in Computational Biology and Human Health.

In recent decades, computational modeling has been successfully used to describe and better understand fundamental biological processes. The field has since evolved significantly and is increasingly addressing biomedical questions in the context of systems biology. Diseases are often characterized by a multitude of disturbances in different biological processes that influence each other across various scales.

This paradigm shift takes biological complexity into account by using mechanistic modeling approaches to investigate disease processes in an integrative manner. This requires close interdisciplinary exchange of scientist with an expertise in modeling techniques, data analysis and experimental approaches.

Building on this, the DiseaseModelling project group was established with the aim of connecting researchers from different disciplines.

A central research topic is the quantitative analysis and integration of high-dimensional data sets into mathematical models. These data originate from single-cell sequencing, time-resolved transcriptomics and proteomics, and high-content imaging, among other sources, and provide detailed insights into spatial cell-cell relationships within complex tissues. Machine learning methods such as autoencoders, optimal transport, and trained neural networks play a crucial role in this context. Of particular importance is their combination with mechanistic modeling approaches in order to obtain interpretable, data-driven descriptions of biological processes.

Since January 2022, a monthly Online Seminar Series has been held as part of the project group. These seminars focus on introducing, discussing, and comparing different computational modeling approaches. They also promote exchange between academic research and industrial practice. The seminar series is aimed at a broad national and international community and involves members at all career stages, from master and PhD students to postdoctoral researchers and experienced group leaders.

We would like to thank Sara Checa and Markus Morrison for their great commitment to the organization team until summer 2024 and 2025, respectively.

For the future, we look forward to the new insights into disease process modelling and to discussing them with you!