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Expertises

The German Society for Cytometry (DGfZ) promotes the exchange of cytometry technologies in the various fields of application. It provides a platform for scientists and practitioners to share knowledge and experience, start new cooperations, which plays a crucial role in driving forward technology development and application. Expertises present in our society are described here.
To further explore the diversity and relevance of cytometry technologies and get in contact with local experts, we invite everyone to attend our annual conference and/or become a member.

Data analysis – neuronal networks & automated approaches 

High-dimensional flow and mass cytometry data require dedicated analysis. Automated approaches, such as DNNs, are important tools in the analysis of complex datasets. In flow cytometry, DNNs have been put to use for the label-free classification of various types of cells and bacteria. For this purpose, high-dimensional data are used to train the networks to extract those patterns or features that are unique to every type of data. Following the training process, these models are utilized in the analysis of new, high-dimensional datasets, identifying and categorizing different biological entities according to their specific profiles. Moreover, these models are not only useful for classification purposes but can also be employed for data visualization. Techniques such as t-SNE or PCA can reduce the dimensionality of data and thereby enable the interpretation of complex patterns and relationships in a visual manner. This capability is key for intuitive understanding of high-dimensional biological data sets and further guides experimental explorations.

Data repositories / Metadata Annotation / FAIR Data

We are working for NFDI4Immuno (the National Research Data Infrastructure for Immunology in Germany), where we are building a framework for comprehensive immunological data integration and analysis, collaboration, and Open Science. Our role in this project is to establish metadata standards for the study parameters, samples, subjects, protocols, reagents, measurement systems, and data generation in mass and flow cytometry experiments. We develop guidelines and automated tools for data acquisition, metadata annotation, and quality assurance.

Flow Cytometry & Flow Cores

Flow cytometry is a powerful technology that allows for the analysis of the physical and chemical properties of cells in a liquid sample. This technique is widely used in basic research, clinical diagnostics, and the development of new therapies. Flow cores are specialized facilities or laboratories that provide access to flow cytometers, as well as expertise and support. They play a crucial role in providing resources and training for researchers to optimize the application of flow cytometry and ensure that the latest technologies are effectively utilized.

Functional microscopy by fluorescence lifetime imaging 

Fluorescence lifetime imaging allows the quantification of vital cellular parameters, both in vitro and in vivo. Applied to metabolic coenzymes, specifically NADH, NADPH and FAD it allows the analysis of metabolic pathway changes at single cell level, in comparison to metabolic changes in their immediate tissue microenvironment. Besides, in combination with specific fluorescent sensors, such as FRET-based Ca2+ sensors, fluorescence lifetime imaging enables the quantification of cellular functions, even co-registered with metabolic information. 

Contact: Raluca Niesner, Anja Hauser

Image-activated cell sorting

Although microscopy is one of the most important tools for studying cells and their diversity of phenotypes, most of the current cell sorting methods do not exploit spatially-resolved characteristics for sorting. Instead, cells are only isolated based on one-dimensional features, such as the presence/absence of surface markers. Sorting cell based on size, shape, or the number and subcellular localization of organelles, vesicles or proteins is therefore hardly possible.
Using a combination of gentle microfluidic cell handling, microscopy, and automated image analysis, we are developing flow-through methods for sorting cells based on their microscopic image information or the subcellular distribution of fluorescent markers. The process is particularly simple and gentle on cells and can be combined with almost any microscope for image acquisition. We are currently working on optimizing the method for a label-free and loss-less isolation of valuable cell samples from small sample quantities and using various imaging methods as well as non-optical techniques such as impedance spectroscopy as the basis for a label-free cell classification and isolation.

Contact: Michael Kirschbaum

Imaging

We are developing and applying methodologies to analyze cells within their genuine tissue context. to that end, our methods include multiplexed immunofluorescenece histology and spatial transcriptomics on fixed tissue slices, using confocal wide-field fluorescnence microscopy. We are working on an integrated analysis of proteomic and transcriptomic data. We are also extending those analyses to 3D using light sheet fluorescence micorscopy, whcih enables the analysis of llrge samples in 3D, at a subcellular level. We are active on the European level  in the frame of the European Society for Spatial Biology (ESSB), in order to advamce the field of spatial biology. https://spatialbiologysociety.eu
Contact: Raluca Niesner, Anja Hauser

Mass Cytometry

Mass cytometry permits deep cellular phenotyping in clinical immunology and basic research, allowing for the simultaneous measurement of more than 50 parameters per cell in a single assay. This is achieved by combining the principles of flow cytometry with inductively coupled plasma mass spectrometry (ICP-MS), originally developed for trace metal analysis. By using metal-tagged antibodies, mass cytometry overcomes spectral overlap limitations of traditional fluorescence-based methods, enabling unprecedented resolution and insight into complex cellular systems. Its applications range from profiling immune responses to characterizing tumor microenvironments, offering valuable tools for both discovery and translational research. The technology can be applied to both suspension-based analyses and imaging of tissue sections.

More information and contact an expert here:

Mechanocytometry

Mechanocytometry is an innovative research area that utilizes intrinsic material properties of cells, i.e., their stiffness and viscosity, for a label-free characterization of cellular state and function. For example, immune cells respond to the presence of a pathogen by a change in their mechanical properties within minutes. From a technological point of view, mechanocytometry share many principles of fluorescence-based cytometry but does not require any fluorophores for cell analyis. In contrast, microfluidic systems are used to induce a shear force on cells while a high-throughput camera quantifies the resulting deformation in real-time. Following this approach a throughput exceeding 1,000 cells per second is possible.

More information and contact an expert here:

Contact: Oliver Otto

Microbial Ecology Flow Cytometry 

Microbial communities are essential for future biotechnology to produce valuable platform chemicals and reduce the use of fossil resources. However, the mechanisms of community assembly are poorly understood and the stability of community reactor environments is at best transient or non-existent. We use flow cytometry to develop concepts for controlling population, community and metacommunity dynamics, quantifying their structure and function, but also unraveling the ecological background paradigm that is active. We have developed bioinformatic tools to detect community variation almost instantaneously and use these tools to develop process strategies to stabilize complex microbial processes in managed systems. The analysis of cell heterogeneity in clonal cultures is another focus of our research. Specific cell properties such as growth, viability, productivity or plasmid stability are some of our research targets. 

Microbiota Flow Cytometry

Microbiota flow cytometry refers to the analysis of microbes, generally bacteria, by flow cytometry. The approach focusses on the analysis of the composition of bacterial communities and the characterisation of their cellular properties aiming to understand the dynamics of the complex bacterial communities of the environment, the human and industrial processes. Microbiota flow cytometry expands to-date conventional microbiome analysis by characterizing single bacterial cells for e. g. their DNA content, scatter properties, surface sugar moieties and host immunoglobulin-coating.
In the DGfZ community we have developed microbiota flow cytometry protocols and analysis pipelines to facilitate the expansion of microbiota research by flow cytometry. 
Clinical microbiota flow cytometry: For the investigation of the human microbiota we have established multi-parameter microbiota flow cytometry or microbiota phenotyping. This approach interrogates e. g. the human intestinal microbiota for properties, surface sugar moieties and host immunoglobulin coating, that we assign to microbiota-host interaction. Alongside the protocol for the analysis of viable bacterial cells, we also present an analysis approach based on clustering and machine learning to assess the multi-dimensional data which we apply for the classification of samples in e. g. different chronic inflammatory diseases.

Contact: Hyun-Dong Chang

Pulse Shape Cytometry

Introducing MAPS-FC (Multi-Angle Pulse Shape Flow Cytometry), a label-free technology
for cell analysis and sorting. Unlike conventional flow cytometry that relies on fluorescent
stains, MAPS-FC leverages angle- and time-resolved scattered light to characterize cells,
preserving their native state. This approach utilizes a custom-built detection system
with advanced signal processing to extract detailed cellular information from light scattering patterns.
With proven applications such as cell cycle stage analysis and immune cell subset classification, MAPS-FC demonstrates high precision without the need for fluorescence labeling. 

Contact: Toralf Kaiser, Daniel Kage

Rare cell analysis

Rare cell analysis is a special form of single cell analysis as the number of target cells is limited to only a few cells. Analysis is hampered by the fact that the target cells lack markers for pre-enrichment and, thus, they are outnumbered by unwanted background cells. These conditions require special analysis techniques in order to achieve unambiguous results and often rely on different techniques necessary to validate the data (sample pre-enrichment; qPCR, ddPCR, microscopy, flow cytometry). Examples for rare cells include circulating tumor cells and microchimeric cells but may be expanded to other rare cell populations.

Contact: Thomas Kroneis,

Division of Cell Biology, Histology & Embryology
Gottfried Schatz Research Center
Medical University of Graz, Austria

Small- and Nanoparticles

Measuring Small particles like Extracellular Vesicles (EVs) and Nanoparticles (e.g. gold particles) are a growing field in translational and basic natural sciences and are an important way in analysing liquid biopsies and tracing or delivering drugs to specific sides inside a biological system. But measuring them with conventional flow cytometric methods is challenging and need additional changes and controls.  

Contact: Wolfgang Fritsche, Steffen Schmitt

Spectral flow cytometry

Spectral flow cytometry is an advanced technique that improves upon conventional flow cytometry. Instead of using separate detectors for each fluorescent dye, it detects emitted light across a defined wavelength range for each excitation laser without gaps between detectors. This allows for the identification of unique signatures from multiple dyes, enabling the use of many more dyes in a single experiment than traditional methods.
A key advantage of spectral flow cytometry is its ability to separate dyes with overlapping emission spectra. It can also treat the natural autofluorescence of cells as an additional dye, helping to reduce background signals and improve the detection of weak markers, while still allowing for accurate cell population identification.
The primary application of spectral flow cytometry is immunophenotyping, which can provide detailed information about specific cell types or an overview of various immunological populations.

Contact: Jochen Behrens, Andreas Dolf

Some pictures inserted here are for decorative purposes. Source: Adobe Stock.