Biology subjects

Herbig, M.

Publications and source records attributed to Herbig, M..

12 recordsLinked to original sources

bioRxiv2026

Impact of chemotherapy on leukocyte stiffness -A longitudinal RT-DC study in a breast cancer patient

BackgroundThe physical properties of leukocytes, such as cell size and stiffness, are critical for their circulation in microcapillary networks where rapid shape changes are required to squeeze through vascular constrictions. Alterations in the cells physical phenotype can promote venous thromboembolism (VTE), a common cause of death in cancer patients receiving chemotherapy. While biochemical VTE predictors are well studied, physical properties of blood cells receive less attention. MethodsUsing real-time deformability cytometry (RT-DC), we monitored for the first time the physical phenotype of leukocytes in a longitudinal study of a breast cancer patient treated with epirubicin/cyclophosphamide (EC) and paclitaxel (Pax). ResultsThe leukocyte counts extracted from RT-DC were in good agreement with standard clinical leukograms and EC had no immediate effect on leukocyte properties. However, Pax caused a significant softening of granulo/monocytes and a stiffening of lymphocytes immediately after administration. Leukocyte size was constant throughout the therapy, but we observed an overall increase in leukocyte stiffness, which was restored to normal values 45 weeks post treatment. ConclusionTaken together, our data reveal chemotherapy-induced specific alterations of leukocyte stiffness potentially critical for microcirculation. Thus, RT-DC measurements can add important, yet currently not available information to VTE prediction in cancer patients.

biophysics↗

bioRxiv2024

Flow zoometry of Drosophila

Drosophila serves as a highly valuable model organism across numerous fields including genetics, immunology, neuroscience, cancer biology, and developmental biology. Central to Drosophila-based biological research is the ability to perform comprehensive genetic or chemical screens. However, this research is often limited by its dependence on laborious manual handling and analysis, making it prone to human error and difficult to discern statistically significant or rare events amid the noise of individual variations resulting from genetic and environmental factors. In this article we present flow zoometry, a whole-animal equivalent of flow cytometry for large-scale, individual-level, high-content screening of Drosophila. Our flow zoometer automatically clears the tissues of Drosophila melanogaster, captures three-dimensional (3D) multi-color fluorescence tomograms of single flies with single-cell volumetric resolution at an unprecedented throughput of over 1,000 animals within 48 hours (24 hr for clearing; 24 hr for imaging), and performs AI-enhanced data-driven analysis - a task that would traditionally take months or years with manual techniques. To demonstrate its broad applications, we employed the flow zoometer in various laborious screening assays, including those in toxicology, genotyping, and tumor screening. Flow zoometry represents a pivotal evolution in high-throughput screening technology: previously from molecules to cells, now from cells to whole animals. This advancement serves as a foundational platform for "statistical spatial biology", to improve empirical precision and enable serendipitous discoveries across various fields of biology.

bioengineering↗

bioRxiv2021

Changes in blood cell deformability in Chorea-Acanthocytosis and effects of treatment with dasatinib or lithium

Misshaped red blood cells (RBCs), characterized by thorn-like protrusions known as acanthocytes, are a key diagnostic feature in Chorea-Acanthocytosis (ChAc), a rare neurodegenerative disorder. The altered RBC morphology likely influences their biomechanical properties which are crucial for the cells to pass the microvasculature. Here, we investigated blood cell deformability of 5 ChAc patients compared to healthy controls during up to one-year individual off-label treatment with the tyrosine kinases inhibitor dasatinib or several weeks with lithium. Measurements with two microfluidic techniques allowed us to assess RBC deformability under different shear stresses. Furthermore, we characterized leukocyte stiffness at high shear stresses. The results show that blood cell deformability - including both RBCs and leukocytes - in general is altered in ChAc patients compared to healthy donors. Therefore, this study shows for the first time an impairment of leukocyte properties in ChAc. During treatment with dasatinib or lithium, we observe alterations in RBC deformability and a stiffness increase for leukocytes. The hematological phenotype of ChAc patients hints at a reorganization of the cytoskeleton in blood cells which partly explains the altered mechanical properties observed here. These findings highlight the need for a systematic assessment of the contribution of impaired blood cell mechanics to the clinical manifestation of ChAc.

biophysics↗

bioRxiv2021

Label-free imaging flow cytometry: analysis and sorting of enzymatically dissociated tissues

Biomedical research often relies on identification and isolation of specific cell types using molecular biomarkers and sorting methods such as fluorescence or magnetic activated cell sorting. Labelling processes potentially alter the cells properties and should be avoided, especially when purifying cells for clinical applications. A promising alternative is the label-free identification of cells based on their physical properties. Sorting real-time deformability and fluorescence cytometry (soRT-FDC) is a microfluidic technique for label-free analysis and sorting of single cells. In soRT-FDC, bright-field images of cells are analyzed by a deep neural net (DNN) to obtain a sorting decision, but sorting was so far only demonstrated for blood cells which show clear morphological differences and are naturally in suspension. Most cells, however, grow in tissues, requiring dissociation before cell sorting which is associated with additional challenges including survival, changes in morphology, or presence of aggregates. Here, we introduce methods for robust analysis and sorting of single cells from mammalian nervous tissue and provide DNNs which are capable of distinguishing visually similar cells. Exemplarily, we employ the DNN for image-based sorting to enrich photoreceptor cells from dissociated retina for transplantation into the mouse eye. Results provide evidence that the combination of machine learning and soRT-FDC allows label-free enrichment of target cells from dissociated tissues.

biophysics↗

bioRxiv2021

De novo identification of universal cell mechanics regulators

Cell mechanical properties determine many physiological functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors that govern the mechanical properties is therefore a subject of great interest. Here we present a mechanomics approach for establishing links between single-cell mechanical phenotype changes and the genes involved in driving them. We combine mechanical characterization of cells across a variety of mouse and human systems with machine learning-based discriminative network analysis of associated transcriptomic profiles to infer a conserved network module of five genes with putative roles in cell mechanics regulation. We validate in silico that the identified gene markers are universal, trustworthy and specific to the mechanical phenotype across the studied mouse and human systems, and demonstrate experimentally that a selected target, CAV1, changes the mechanical phenotype of cells accordingly when silenced or overexpressed. Our data-driven approach paves the way towards engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions.

biophysics↗

bioRxiv2020

AIDeveloper: deep learning image classification in life science and beyond

Publications on artificial intelligence (AI)-based image analysis have increased drastically in recent years. However, all applications use individual solutions highly specialized for a particular task. Here, we present an easy-to-use, adaptable, open source software, called AIDeveloper (AID) to train neural nets (NN) for image classification without the need for programming. The software provides a variety of NN-architectures that can be simply selected for training. AID allows the user to apply trained models on new data, obtain metrics for classification performance, and export final models to different formats. The working principles of AID are first illustrated by training a convolutional neural net (CNN) on a large dataset consisting of images of different objects (CIFAR-10). We further explore the potential of AID by training a model to distinguish areas of differentiated and non-differentiated mesenchymal stem cells (MSCs) in culture. Additionally, we compare a conventional clinical whole blood cell count with a whole blood cell count performed by an NN-trained, using a dataset of more than 1.2 million images obtained by real-time deformability cytometry, delivering comparable results. Finally, we demonstrate how AID can be used for label-free classification of B- and T-cells derived from human blood, which currently requires costly and time-consuming sample preparation. Thus, AID can empower anyone to develop, train, and apply NNs for image classification. Moreover, models can be generated by non-programmers, exported, and used on different devices, which allows for an interdisciplinary use.

bioinformatics↗

bioRxiv2019

Using real-time fluorescence and deformability cytometry and deep learning to transfer molecular specificity to label-free sorting

The identification and separation of specific cells from heterogeneous populations is an essential prerequisite for further analysis or use. Conventional passive and active separation approaches rely on fluorescent or magnetic tags introduced to the cells of interest through molecular markers. Such labeling is time- and cost-intensive, can alter cellular properties, and might be incompatible with subsequent use, for example, in transplantation. Alternative label-free approaches utilizing morphological or mechanical features are attractive, but lack molecular specificity. Here we combine image-based real-time fluorescence and deformability cytometry (RT-FDC) with downstream cell sorting using standing surface acoustic waves (SSAW). We demonstrate basic sorting capabilities of the device by separating cell mimics and blood cell types based on fluorescence as well as deformability and other image parameters. The identification of blood sub-populations is enhanced by flow alignment and deformation of cells in the microfluidic channel constriction. In addition, the classification of blood cells using established fluorescence-based markers provides hundreds of thousands of labeled cell images used to train a deep neural network. The trained algorithm, with latency optimized to below 1 ms, is then used to identify and sort unlabeled blood cells at rates of 100 cells/sec. This approach transfers molecular specificity into label-free sorting and opens up new possibilities for basic biological research and clinical therapeutic applications.

biophysics↗

bioRxiv2018

Spheroid culture of mesenchymal stromal cells results in morpho-rheological properties appropriate for improved microcirculation

Human bone marrow mesenchymal stromal cells (MSCs) have been used in clinical trials for the treatment of systemic inflammatory diseases due to their regenerative and immunomodulatory properties. However, intravenous administration of MSCs is hampered by cell trapping within the pulmonary capillary networks. Here, we hypothesize that traditional twodimensional (2D) plastic-adherent cell expansion fails to result in appropriate morphorheological properties required for cell-circulation. To address this issue, we adapted a novel method to culture MSCs in non-adherent three-dimensional (3D) spheroids (mesenspheres). The biological properties of mesensphere-cultured MSCs remained identical to conventional 2D cultures. Morpho-rheological analyses revealed a smaller size and lower cell stiffness of mesensphere-derived MSCs compared to plastic-adherent MSCs, measured using real-time deformability cytometry (RT-DC) and atomic force microscopy, resulting in an increased ability to pass through micro-constrictions in an ex vivo microcirculation assay. This ability was confirmed in vivo by analysis of cell accumulation in various organ capillary networks after intravenous injection of mesensphere-derived MSCs in mouse. Our findings generally identify cellular morpho-rheological properties as attractive targets to improve microcirculation and specifically suggest mesensphere cultures as a promising approach for optimized MSC-based therapies.

biophysics↗

bioRxiv2018

Standardized microgel beads as elastic cell mechanical probes

Cell mechanical measurements are gaining increasing interest in biological and biomedical studies. However, there are no standardized calibration particles available that permit the cross-comparison of different measurement techniques operating at different stresses and time-scales. Here we present the rational design, production, and comprehensive characterization of poly-acylamide (PAAm) microgel beads mimicking biological cells. We produced mono-disperse beads at rates of 20 - 60 kHz by means of a microfluidic droplet generator, where the pre-gel composition was adjusted to tune the beads elasticity in the range of cell and tissue relevant mechanical properties. We verified bead homogeneity by optical diffraction tomography and Brillouin microscopy. Consistent elastic behavior of microgel beads at different shear rates was confirmed by AFM-enabled nanoindentation and real-time deformability cytometry (RT-DC). The remaining inherent variability in elastic modulus was rationalized using polymer theory and effectively reduced by sorting based on forward-scattering using conventional flow cytometry. Our results show that PAAm microgel beads can be standardized as mechanical probes, to serve not only for validation and calibration of cell mechanical measurements, but also as cell-scale stress sensors.\n\nSignificance StatementOften vastly different cell mechanical properties are reported even for the same cell type when employing different measurement techniques. This discrepancy shows the urgent need for standardized calibration particles to cross-compare and validate techniques. Microgel beads can serve this purpose, but they have to fulfil specific requirements such as homogeneity, sizes and elasticities in the range of the cells, and they have to provide comparable results independent of the method applied. Here we demonstrate the standardized production of polyacrylamide microgel beads with all the features an elastic cell-mimic should have. These can not only be used as method calibration particles, but can also serve as cell-scale sensors to quantify normal and shear stresses exerted by other cells and inside tissues, enabling many new applications.

biophysics↗

bioRxiv2017

Harnessing the adaptive potential of mechanoresponsive proteins to overwhelm pancreatic cancer dissemination and invasion

Metastatic disease is often characterized by altered cellular contractility and deformability, lending cells and groups of cells the flexibility to navigate through different microenvironments. This ability to change cell shape is driven in large part by the structural elements of the mechanobiome, which includes cytoskeletal proteins that sense and respond to mechanical stimuli. Here, we demonstrate that key mechanoresponsive proteins (those which accumulate in response to mechanical stress), specifically nonmuscle myosin IIA and IIC, -actinin 4, and filamin B, are highly upregulated in pancreatic ductal adenocarcinoma cancer (PDAC) and in patient-derived pancreatic cancer cell lines. Their less responsive sister paralogs (myosin IIB, -actinin 1, and filamin A) show a smaller dynamic range or disappear with PDAC progression. We demonstrate that these mechanoresponsive proteins directly impact cell mechanics using knock-down and overexpression cell lines. We further quantify the nonmuscle myosin II family members in patient-derived cell lines and identify a role for myosin IIC in the formation of transverse actin arcs in single cells and cortical actin belts in tissue spheroids. We harness the upregulation of myosin IIC and its impact of cytoskeletal architecture through the use of the mechanical modulator 4-hydroxyacetophenone (4-HAP), which increases myosin IIC assembly and stiffens cells. Here, 4-HAP decreases dissemination, induces cortical actin belts, and slows retrograde actin flow in spheroids. Finally, mice having undergone hemi-splenectomies with PDAC cells and then treated with 4-HAP have a reduction in liver metastases. Thus, increasing the activity of these mechanoresponsive proteins (in this case, by increasing myosin IIC assembly) to overwhelm the ability of cells to polarize and invade may be an effective strategy to improve the five-year survival rate of pancreatic cancer patients, currently hovering around 6%.

cancer biology↗

bioRxiv2017

Real-time fluorescence and deformability cytometry - flow cytometry goes mechanics

Cell mechanical characterization has recently approached the throughput of conventional flow cytometers. However, this very sensitive, label-free approach still lacks the specificity of molecular markers. Here we combine real-time 1D-imaging fluorescence and deformability cytometry (RT-FDC) to merge the two worlds in one instrument -- opening many new research avenues. We demonstrate its utility using sub-cellular fluorescence localization to identify mitotic cells and test for their mechanical changes in an RNAi screen.

biophysics↗

bioRxiv2017

Detection Of Human Disease Conditions By Single-Cell Morpho-Rheological Phenotyping Of Whole Blood

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of whole blood, without labeling, enrichment or separation, at rates of 1,000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in whole blood and adds a functional dimension to conventional blood analysis.

biophysics↗