News
August 2025 – Schmidlin Lab
Antigen Discovery by Chemical Crosslinking – Paper in Cell Reports Methods
We are excited to share that our paper, MR1-ligand cross-linking identifies vitamin B6 metabolites as TCR-reactive antigens has just been published in Cell Reports Methods. Read it here.
The study explores a fascinating but highly understudied area of immunology: how the immune system recognizes antigens beyond the classical protein fragments usually presented to T cells by MHC. One such pathway involves MR1, a molecule that presents metabolites to specialized T cells, enabling the immune system to detect changes in cellular metabolism during infection or cancer.
Until now, it has been challenging to identify which metabolites MR1 actually presents. To address this, we developed a new approach using chemical crosslinking to lock antigens into place on MR1, followed by mass spectrometry to characterize them.
Using this method, we discovered that several vitamin B6 metabolites can be presented by MR1 in cancer cell lines - an intriguing finding that opens up new questions about the role of metabolism in immune recognition.
Reference: Schmidlin et al. Cell Reports Methods, Volume 5, Issue 8, 101120
March 2025 – Schmidlin Lab
Successful Rheinland-Pfalz & Scotland X Life Sciences Fund Award
We are proud to share that our joint proposal with the lab of Nicholas Rattray (University of Strathclyde, Glasgow) has been selected for funding through the Rheinland-Pfalz & Scotland X Life Sciences Fund.
The initiative supports PhD exchange visits between the two institutions, fostering scientific collaboration and knowledge transfer. As part of the program, Haleema Ahmed will join our lab in Mainz in September, and Susanne Nguyen will visit Glasgow in November.
We are excited to strengthen our collaborative partnership and the scientific discoveries this exchange will lead to.
November 2024 – Schmidlin Lab
Preprint on Metabolic Profiling of the EmDia Cohort Now Online
Our preprint Metabolic Profiling of the EmDia Cohort by a Scalable DIA-LC-MS Workflow is now available on ChemRxiv. Read it here.
In this study, we established a high-throughput DIA-LC-MS metabolomics workflow capable of profiling over 170 metabolites in large plasma cohorts at >100 samples per day. Applying this to the EmDia trial, we identified strong predictive power for clinical parameters such as blood glucose and kidney function, and observed drug-associated metabolic changes including reduced urate and 1,5-anhydroglucitol levels under SGLT2 inhibitor treatment.
