NMR Dataset from "A novel method for quantifying enzyme immobilization in porous carriers using simple NMR relaxometry" DOI of this dataset: https://doi.org/10.15480/882.15837 DOI of corresponding publication:https://doi.org/10.1016/j.bej.2025.109909 1. General information: * Measurement of enzyme immobilization employing MR techniques * Determine the loading based on relaxometry parameters * Compare to other methods * Data was collected on the dates indicated by the folder naming * Data was collected at Hamburg University of Technology * M. Raquel Serial (m.r.serial@tudelft.nl, ORCID 0000-0003-3052-4916, Affiliation: a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany, b) Department of Process and Energy, Delft University of Technology, Delft, The Netherlands, *Corresponding author), Luca Schmidt (luca.schmidt@tuhh.de, ORCID 0000-0002-2203-096X, Affiliation: c) Institute of Technical Biocatalysis, Hamburg University of Technology, Hamburg, Germany, d) United Nations University Hub on Engineering to Face Climate Change at the Hamburg University of Technology, United Nations University Institute of Water, Environment and Health, Hamburg, Germany), Muhammad Adrian (muhammad.adrian@tuhh.de, ORCID 0009-0008-3634-9518, Affiliation: a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany), Grit Brauckmann (grit.brauckmann@tuhh.de, Affiliation: c) Institute of Technical Biocatalysis, Hamburg University of Technology, Hamburg, Germany), Stefan Benders (stefan.benders@tuhh.de, ORCID 0000-0002-9823-1928, Affiliation: a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany ,d) United Nations University Hub on Engineering to Face Climate Change at the Hamburg University of Technology, United Nations University Institute of Water, Environment and Health, Hamburg, Germany), Victoria Bueschler(victoria.bueschler@tuhh.de, ORCID 0000-0001-8942-1896, Affiliation: c) Institute of Technical Biocatalysis, Hamburg University of Technology, Hamburg, Germany, d) United Nations University Hub on Engineering to Face Climate Change at the Hamburg University of Technology, United Nations University Institute of Water, Environment and Health, Hamburg, Germany), Andreas Liese (liese@tuhh.de, ORCID 0000-0002-4867-9935, Affiliation: c) Institute of Technical Biocatalysis, Hamburg University of Technology, Hamburg, Germany, d) United Nations University Hub on Engineering to Face Climate Change at the Hamburg University of Technology, United Nations University Institute of Water, Environment and Health, Hamburg, Germany), Alexander Penn (alexander.penn@tuhh.de, ORCID 0000-0001-5596-6310, a) Institute of Process Imaging, Hamburg University of Technology, Hamburg, Germany ,d) United Nations University Hub on Engineering to Face Climate Change at the Hamburg University of Technology, United Nations University Institute of Water, Environment and Health, Hamburg, Germany) 2. Data overview: * The dataset includes the raw data of the Spinsolve measurements, availible in .csv and .1d files, also including the parameters in .par, sorted in folders * These data can be processed with the script provided in https://collaborating.tuhh.de/v-10/public/manuscripts/enzyme-relaxometry/td-nmr-enzyme-immobilzation * Processed data can be retrieved by executing the scripts * Folder structure: The dataset is organized into folders named 8204M_batch1 and 8204M_batch2, corresponding to enzyme type 8204M from batches 1 and 2. Likewise, 8215M_batch1 and 8215M_batch2 are provided to ensure reproducibility. Where applicable, each batch folder contains two subdirectories (1 and 2) representing independent replicate measurements. These replicates form the basis for calculating the mean and standard deviation. Within each replicate folder, measurement files are arranged chronologically by date and time. Each file is labeled with the measurement type (Proton or T2Bulk) and the initial enzyme concentration (C0). Further details on concentrations (e.g., equilibrated values) and sample mass are available in dataset_info.csv. 3. Variable definitions: n/a 4. Data Collection Methods: The data was generated by measuring with a Spinsolve 60 at the IPI at Hamburg University of Technology. * Enzyme Production: L-threonine aldolases from E. coli strains ME9012 and GS245 were expressed in E. coli BL21 using the pET28a vector. Cultures were grown in lysogenic broth, and enzyme expression was induced with IPTG. Cells were harvested, disrupted by sonication, and the supernatant (cell-free extract, CFE) was collected. * Purification: The CFE was purified using a His-tag with Protino Ni-NTA agarose. After washing and binding steps, the target protein was eluted in fractions and further purified by size exclusion chromatography to remove imidazole. * Immobilization: Enzymes were immobilized on carriers washed with phosphate buffer. The process was performed at a 1:4 carrier-to-enzyme ratio for 47 hours at 4 °C. After immobilization, carriers were washed, and both supernatants and washing fractions were collected for protein concentration analysis. Immobilized carriers were used for relaxometry measurements. 5. File formats used: * Files are located in experiment folders, named after year-month-day-samplename. * Files have .csv, .1d (binary) and .par endings * Pulse sequences are embedded in the folders by ppcode 6. Dependencies and Tools: Dependencies are given in the Gitlab repository, where python libraries including versions are declared 7. Limitations and known issues * Acquisition & Control: Scripts depend on Spinsolve software running with Expert modules. * Format Issues: might be encountered and folders/naming vary between versions. * Processing Differences: Spinsolve applies automatic baseline, phasing, smoothing—Python results will differ unless replicated. 8. Usage Rights and Citation: The data is published under CC BY-NC-ND 4.0 license. The dataset can be cited by the DOI provided by TORE. By using the data in your work, you agree to cite the original work.