Cells can enter into a dormant state when faced with unfavorable conditions. However, how cells enter into and recover from this state is still poorly understood. Here, we study dormancy in different ...eukaryotic organisms and find it to be associated with a significant decrease in the mobility of organelles and foreign tracer particles. We show that this reduced mobility is caused by an influx of protons and a marked acidification of the cytoplasm, which leads to widespread macromolecular assembly of proteins and triggers a transition of the cytoplasm to a solid-like state with increased mechanical stability. We further demonstrate that this transition is required for cellular survival under conditions of starvation. Our findings have broad implications for understanding alternative physiological states, such as quiescence and dormancy, and create a new view of the cytoplasm as an adaptable fluid that can reversibly transition into a protective solid-like state.
Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time ...fluorescence and deformability cytometry with sorting based on standing surface acoustic waves and transfer molecular specificity to image-based sorting using an efficient deep neural network. In addition to general performance, we demonstrate the utility of this method by sorting neutrophils from whole blood without labels.
Biomedical research 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 physical properties. Sorting real-time deformability cytometry (soRT-DC) 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 challenges including changes in morphology, or presence of aggregates. Here, we introduce methods to improve robustness of analysis and sorting of single cells from nervous tissue and provide DNNs which can distinguish visually similar cells. We employ the DNN for image-based sorting to enrich photoreceptor cells from dissociated retina for transplantation into the mouse eye.
Diagnosis of myelodysplastic syndrome (MDS) mainly relies on a manual assessment of the peripheral blood and bone marrow cell morphology. The WHO guidelines suggest a visual screening of 200 to 500 ...cells which inevitably turns the assessor blind to rare cell populations and leads to low reproducibility. Moreover, the human eye is not suited to detect shifts of cellular properties of entire populations. Hence, quantitative image analysis could improve the accuracy and reproducibility of MDS diagnosis. We used real-time deformability cytometry (RT-DC) to measure bone marrow biopsy samples of MDS patients and age-matched healthy individuals. RT-DC is a high-throughput (1000 cells/s) imaging flow cytometer capable of recording morphological and mechanical properties of single cells. Properties of single cells were quantified using automated image analysis, and machine learning was employed to discover morpho-mechanical patterns in thousands of individual cells that allow to distinguish healthy vs. MDS samples. We found that distribution properties of cell sizes differ between healthy and MDS, with MDS showing a narrower distribution of cell sizes. Furthermore, we found a strong correlation between the mechanical properties of cells and the number of disease-determining mutations, inaccessible with current diagnostic approaches. Hence, machine-learning assisted RT-DC could be a promising tool to automate sample analysis to assist experts during diagnosis or provide a scalable solution for MDS diagnosis to regions lacking sufficient medical experts.
Studies of the role of actin in tumour progression have highlighted its key contribution in cell softening associated with cell invasion. Here, using a human breast cell line with conditional Src ...induction, we demonstrate that cells undergo a stiffening state prior to acquiring malignant features. This state is characterized by the transient accumulation of stress fibres and upregulation of Ena/VASP-like (EVL). EVL, in turn, organizes stress fibres leading to transient cell stiffening, ERK-dependent cell proliferation, as well as enhancement of Src activation and progression towards a fully transformed state. Accordingly, EVL accumulates predominantly in premalignant breast lesions and is required for Src-induced epithelial overgrowth in Drosophila. While cell softening allows for cancer cell invasion, our work reveals that stress fibre-mediated cell stiffening could drive tumour growth during premalignant stages. A careful consideration of the mechanical properties of tumour cells could therefore offer new avenues of exploration when designing cancer-targeting therapies.
Pathophysiological landmarks of depressive disorders are chronic low-grade inflammation and elevated glucocorticoid output. Both can potentially interfere with cytoskeleton organization, cell ...membrane bending and cell function, suggesting altered cell morpho-rheological properties like cell deformability and other cell mechanical features in depressive disorders. We performed a cross-sectional case-control study using the image-based morpho-rheological characterization of unmanipulated blood samples facilitating real-time deformability cytometry (RT-DC). Sixty-nine pre-screened individuals at high risk for depressive disorders and 70 matched healthy controls were included and clinically evaluated by Composite International Diagnostic Interview leading to lifetime and 12-month diagnoses. Facilitating deep learning on blood cell images, major blood cell types were classified and morpho-rheological parameters such as cell size and cell deformability of every individual cell was quantified. We found peripheral blood cells to be more deformable in patients with depressive disorders compared to controls, while cell size was not affected. Lifetime persistent depressive disorder was associated with increased cell deformability in monocytes and neutrophils, while in 12-month persistent depressive disorder erythrocytes deformed more. Lymphocytes were more deformable in 12-month major depressive disorder, while for lifetime major depressive disorder no differences could be identified. After correction for multiple testing, only associations for lifetime persistent depressive disorder remained significant. This is the first study analyzing morpho-rheological properties of entire blood cells and highlighting depressive disorders and in particular persistent depressive disorders to be associated with increased blood cell deformability. While all major blood cells tend to be more deformable, lymphocytes, monocytes, and neutrophils are mostly affected. This indicates that immune cell mechanical changes occur in depressive disorders, which might be predictive of persistent immune response.
The mechanical fingerprint of cells is inherently linked to the structure of the cytoskeleton and can serve as a label‐free marker for cell homeostasis or pathologic states. How cytoskeletal ...composition affects the physical response of cells to external loads has been intensively studied with a spectrum of techniques, yet quantitative and statistically powerful investigations in the form of titration assays are hampered by the low throughput of most available methods. In this study, we employ real‐time deformability cytometry (RT‐DC), a novel microfluidic tool to examine the effects of biochemically modified F‐actin and microtubule stability and nuclear chromatin structure on cell deformation in a human leukemia cell line (HL60). The high throughput of our method facilitates extensive titration assays that allow for significance assessment of the observed effects and extraction of half‐maximal concentrations for most of the applied reagents. We quantitatively show that integrity of the F‐actin cortex and microtubule network dominate cell deformation on millisecond timescales probed with RT‐DC. Drug‐induced alterations in the nuclear chromatin structure were not found to consistently affect cell deformation. The sensitivity of the high‐throughput cell mechanical measurements to the cytoskeletal modifications we present in this study opens up new possibilities for label‐free dose‐response assays of cytoskeletal modifications.
Innate immune processes are central in the development of the chronic inflammatory skin disease psoriasis. Studying stimulation of keratinocytes, monocytes, and dendritic cells by type I interferons ...or ligation of Toll-like receptors 1/2, 2/6, or 7, but not 7/8, resulted in enhanced surface expression and secretion of CXC chemokine ligand (CXCL) 16. The corresponding CXC chemokine receptor 6 was expressed on neutrophils whose recruitment into skin is important, especially in early psoriatic disease. Using the recently developed technique real-time deformability cytometry demonstrated that CXCL16 and IL-8 decreased the stiffness and enhanced deformation of neutrophils facilitating transmigration through vessel wall. In addition, CXCL16 potently induced migration of neutrophils and enhanced the chemotactic effect of IL-8. The positive feedback loop was supported by IL-8 enhancing CXCL16 production of neutrophils. Blocking of CXCL16 expression by effective treatment of psoriasis patients with tumor necrosis factor−α blockers further supported the pathogenic role of this chemokine. In summary, the data link innate immune stimulation to CXCL16 upregulation and neutrophil infiltration into skin. CXCL16 could therefore represent a potent future target for treatment of psoriasis.
Osteosarcoma is the most frequent primary tumor of bone and is characterized by its high tendency to metastasize in lungs. Although treatment in cases of early diagnosis results in a 5-yr survival ...rate of nearly 60%, the prognosis for patients with secondary lesions at diagnosis is poor, and their 5-yr survival rate remains below 30%. In the present work, we have used a number of analytical methods to investigate the impact of increased metastatic potential on the biophysical properties and force generation of osteosarcoma cells. With that aim, we used two paired osteosarcoma cell lines, with each one comprising a parental line with low metastatic potential and its experimentally selected, highly metastatic form. Mechanical characterization was performed by means of atomic force microscopy, tensile biaxial deformation, and real-time deformability, and cell traction was measured using two-dimensional and micropost-based traction force microscopy. Our results reveal that the low metastatic osteosarcoma cells display larger spreading sizes and generate higher forces than the experimentally selected, highly malignant variants. In turn, the outcome of cell stiffness measurements strongly depends on the method used and the state of the probed cell, indicating that only a set of phenotyping methods provides the full picture of cell mechanics.
Organelle positioning in cells is associated with various metabolic functions and signaling in unicellular organisms. Specifically, the microalga Chlamydomonas reinhardtii repositions its ...mitochondria, depending on the levels of inorganic carbon. Mitochondria are typically randomly distributed in the Chlamydomonas cytoplasm, but relocate toward the cell periphery at low inorganic carbon levels. This mitochondrial relocation is linked with the carbon‐concentrating mechanism, but its significance is not yet thoroughly understood. A genotypic understanding of this relocation would require a high‐throughput method to isolate rare mutant cells not exhibiting this relocation. However, this task is technically challenging due to the complex intracellular morphological difference between mutant and wild‐type cells, rendering conventional non‐image‐based high‐event‐rate methods unsuitable. Here, we report our demonstration of intelligent image‐activated cell sorting by mitochondrial localization. Specifically, we applied an intelligent image‐activated cell sorting system to sort for C. reinhardtii cells displaying no mitochondrial relocation. We trained a convolutional neural network (CNN) to distinguish the cell types based on the complex morphology of their mitochondria. The CNN was employed to perform image‐activated sorting for the mutant cell type at 180 events per second, which is 1–2 orders of magnitude faster than automated microscopy with robotic pipetting, resulting in an enhancement of the concentration from 5% to 56.5% corresponding to an enrichment factor of 11.3. These results show the potential of image‐activated cell sorting for connecting genotype–phenotype relations for rare‐cell populations, which require a high throughput and could lead to a better understanding of metabolic functions in cells.
Intelligent image‐activated cell sorting (iIACS) based on the complex morphology of the mitochondria in C. reinhardtii. Using a CNN with a 5 ms processing time, we achieved enrichment of C. reinhardtii populations from 50% to 80.5% and from 5% to 56.5%, resulting in an enrichment factor of 1.6, and 11.3 respectively. These results show the capability iIACS for high event‐rate sorting based on complex intracellular morphologies.
PDF
