EMSIG

Event-driven Microscopy for Smart Microfluidic Single-cell Analysis

Image: Johannes Seiffarth, FZ Jülich

Microfluidic live-cell imaging (MLCI) unlocks spatio-temporal insights into population heterogeneity emerging from a single cell. Deep-learning powered image analysis, developed in the HI project SATOMI, facilitates offline analysis of high-quality data. For becoming a versatile screening tool, MLCI must master the challenge of robust real-time analysis, capable to detect rare events in hundreds of parallel experiments and resolve their temporal evolution.

Towards this, EMSIG brings smart live-event detection capabilities to MLCI to facilitate the adaptive optimization of biological event resolution and autonomously counteracting deteriorating image qualities, as examples. The distinct high-risk factor is in the robust and accurate real-time classification of events at the interface between imaging, image analysis and biology. If successful, to date unavailable insights into biological processes are unlocked and the technology readiness level of microfluidic live-cell analysis boosted.

Publications

4725570 EMSIG 1 https://helmholtz-imaging.de/apa-bold-title.csl 50 date desc 2768 https://helmholtz-imaging.de/wp-content/plugins/zotpress/

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Witting, L., Seiffarth, J., Stute, B., Schulze, T., Hofer, J. M., Nöh, K., Eisenhut, M., Weber, A. P. M., Lieres, E. von, & Kohlheyer, D. (2025). A microfluidic system for the cultivation of cyanobacteria with precise light intensity and CO2 control: enabling growth data acquisition at single-cell resolution. Lab on a Chip, 25(3), 319–329. https://doi.org/10.1039/D4LC00567H

Kasahara, K., Seiffarth, J., Stute, B., Lieres, E. von, Drepper, T., Nöh, K., & Kohlheyer, D. (2025). Unveiling microbial single-cell growth dynamics under rapid periodic oxygen oscillations. ChemRxiv. https://doi.org/10.26434/chemrxiv-2025-732st

Friederich, N., Sitcheu, A. J. Y., Nassal, A., Pesch, M., Yildiz, E., Beichter, M., Scholtes, L., Akbaba, B., Lautenschlager, T., Neumann, O., Kohlheyer, D., Scharr, H., Seiffarth, J., Nöh, K., & Mikut, R. (2024). EAP4EMSIG -- Experiment Automation Pipeline for Event-Driven Microscopy to Smart Microfluidic Single-Cells Analysis (arXiv:2411.05030). arXiv. https://doi.org/10.48550/arXiv.2411.05030

Seiffarth, J., Blöbaum, L., Paul, R. D., Friederich, N., Sitcheu, A. J. Y., Mikut, R., Scharr, H., Grünberger, A., & Nöh, K. (2024). Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics (arXiv:2411.00552). arXiv. https://doi.org/10.48550/arXiv.2411.00552

Paul, R. D., Seiffarth, J., Scharr, H., & Nöh, K. (2024). Robust Approximate Characterization of Single-Cell Heterogeneity in Microbial Growth (arXiv:2408.04501). arXiv. https://doi.org/10.48550/arXiv.2408.04501

Seiffarth, J., Pesch, M., Scholtes, L., Yildiz, E., Paul, R., Friederich, N., Yamachui Sitcheu, A. J., Mikut, R., Scharr, H., Kohlheyer, D., & Nöh, K. (2024). Live-cell mAIcroscopy - Cracking the challenge to image living cells with real-time event attention. 4th Helmholtz Imaging Conference (2024), Heidelberg, Deutschland, 14.05.2024 – 15.05.2024. https://publikationen.bibliothek.kit.edu/1000170857

Kasahara, K., Leygeber, M., Seiffarth, J., Ruzaeva, K., Drepper, T., Nöh, K., & Kohlheyer, D. (2023). Enabling oxygen-controlled microfluidic cultures for spatiotemporal microbial single-cell analysis. Frontiers in Microbiology, 14. https://doi.org/10.3389/fmicb.2023.1198170

Sitcheu, Y. (2023, March 25). SATOMI and EMSIG: The Power Couple for Analyzing Microbial Live-Cell Experiments. Helmholtz Imaging Annual Conference 2023, Hamburg.

Rohr, K., Anbarani, A. G., Wiechert, W., Geinitz, B., Seiffarth, J., Nöh, K., Oldiges, M., & Bernauer, S. (2023). Automated morphology analysis of industrially relevant filamentous fungus Thermothelomyces thermophilus (FZJ-2023-03659). Biotechnologie. https://juser.fz-juelich.de/record/1015315

Witting, L., Kasahara, K., Kohlheyer, D., Weber, A., Seiffarth, J., Eisenhut, M., & Schulze, T. (2023). In vitro evolution of a synthetic organelle inside a picoliter habitat (FZJ-2023-03677). Biotechnologie. https://juser.fz-juelich.de/record/1015420?ln=de

Project partners

FZJ, KIT

Dr. Katharina Nöh
Prof. Dr. Ralf Mikut
Prof. Dr. Dietrich Kohlheyer
Dr. Erenus Yildiz
Dr. Hanno Scharr

Duration

24 months

Primary Contact

Dr. Katharina Nöh

k.noeh@fz-juelich.de

Other projects

SATOMI

Tackling the segmentation and tracking challenges of growing colonies and microbialdiversity
An artificial intelligence will observe the growth of bacteria: from microscope images of bacterial cultures taken at regular intervals, it will precisely track the development and division of individual cells – even when multiple bacterial species are cultivated together.

BENIGN

Biocompatible and Efficient Nanocrystals for Shortwave Infrared Imaging
The BENIGN project aims to enable non-invasive molecular imaging with cellular resolution in vivo at depths of several millimeters. This will be achieved using light from the shortwave infrared (SWIR) range (1000-2000 nm), which has less scattering and autofluorescence compared to the visible and near-infrared spectral range. Bright and targeted imaging agents are needed to fully exploit this range. The project will develop a new approach using lanthanide-based core-shell structures that emit light in the 1500-2000 nm range.

SIM

Solar Image-based Modelling
The aim of the project is to develop an algorithm by which computers can automatically predict the space weather. This will make use of datasets of solar images that have been captured from space. The method could replace computationally demanding physics-based models and deliver space weather forecasts long before the effects of solar events are […]