Human Intestinal Organoids and Microphysiological Systems for Modeling Radiotoxicity and Assessing Radioprotective Agents

Radiotherapy is a commonly employed treatment for colorectal cancer, yet its radiotoxicity-related impact on healthy tissues raises significant health concerns. This highlights the need to use radioprotective agents to mitigate these side effects. This review presents the current landscape of human translational radiobiology, outlining the limitations of existing models and proposing engineering solutions. We delve into radiotherapy principles, encompassing mechanisms of radiation-induced cell death and its influence on normal and cancerous colorectal cells. Furthermore, we explore the engineering aspects of microphysiological systems to represent radiotherapy-induced gastrointestinal toxicity and how to include the gut microbiota to study its role in treatment failure and success. This review ultimately highlights the main challenges and future pathways in translational research for pelvic radiotherapy-induced toxicity. This is achieved by developing a humanized in vitro model that mimics radiotherapy treatment conditions. An in vitro model should provide in-depth analyses of host-gut microbiota interactions and a deeper understanding of the underlying biological mechanisms of radioprotective food supplements. Additionally, it would be of great value if these models could produce high-throughput data using patient-derived samples to address the lack of human representability to complete clinical trials and improve patients' quality of life.

Presence does not imply activity: DNA and RNA patterns differ in response to salt perturbation in anaerobic digestion

BACKGROUND

The microbial community in anaerobic digestion is mainly monitored by means of DNA-based methods. This may lead to incorrect interpretation of the community parameters, because microbial abundance does not necessarily reflect activity. In this research, the difference between microbial community response on DNA (total community) and RNA (active community) based on the 16S rRNA (gene) with respect to salt concentration and response time was evaluated.

RESULTS

The application of higher NaCl concentrations resulted in a decrease in methane production. A stronger and faster response to salt concentration was observed on RNA level. This was reflected in terms of microbial community composition and organization, as richness, evenness, and overall diversity were differentially impacted. A higher divergence of community structure was observed on RNA level as well, indicating that total community composition depends on deterministic processes, while the active community is determined by stochastic processes. Methanosaeta was identified as the most abundant methanogen on DNA level, but its relative abundance decreased on RNA level, related to salt perturbation.

CONCLUSIONS

This research demonstrated the need for RNA-based community screening to obtain reliable information on actual community parameters and to identify key species that determine process stability.