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Adenosine Triphosphatase (ATPase) Phospholipid Transporting 11C gene (ATP11C) encodes the major phosphatidylserine (PS) flippase in human red blood cells (RBCs). Flippases actively transport phospholipids (e.g., PS) from the outer to the inner leaflet to establish and maintain phospholipid asymmetry of the lipid bilayer of cell membranes. This asymmetry is crucial for survival since externalized PS triggers phagocytosis by splenic macrophages. Here we report on pathophysiological consequences of decreased flippase activity, prompted by a patient with hemolytic anemia and hemizygosity for a novel c.2365C > T p.(Leu789Phe) missense variant in ATP11C. ATP11C protein expression was strongly reduced by 58% in patient-derived RBC ghosts. Furthermore, functional characterization showed only 26% PS flippase activity. These results were confirmed by recombinant mutant ATP11C protein expression in HEK293T cells, which was decreased to 27% compared to wild type, whereas PS-stimulated ATPase activity was decreased by 57%. Patient RBCs showed a mild increase in PS surface exposure when compared to control RBCs, which further increased in the most dense RBCs after RBC storage stress. The increase in PS was not due to higher global membrane content of PS or other phospholipids. In contrast, membrane lipid lateral distribution showed increased abundance of cholesterol-enriched domains in RBC low curvature areas. Finally, more dense RBCs and subtle changes in RBC morphology under flow hint toward alterations in flow behavior of ATP11C-deficient RBCs. Altogether, ATP11C deficiency is the likely cause of hemolytic anemia in our patient, thereby underlining the physiological role and relevance of this flippase in human RBCs.

Adenosine Triphosphatase (ATPase) Phospholipid Transporting 11C gene (ATP11C) encodes the major phosphatidylserine (PS) flippase in human red blood cells (RBCs). Flippases actively transport phospholipids (e.g., PS) from the outer to the inner leaflet to establish and maintain phospholipid asymmetry of the lipid bilayer of cell membranes. This asymmetry is crucial for survival since externalized PS triggers phagocytosis by splenic macrophages. Here we report on pathophysiological consequences of decreased flippase activity, prompted by a patient with hemolytic anemia and hemizygosity for a novel c.2365C > T p.(Leu789Phe) missense variant in ATP11C. ATP11C protein expression was strongly reduced by 58% in patient‐derived RBC ghosts. Furthermore, functional characterization showed only 26% PS flippase activity. These results were confirmed by recombinant mutant ATP11C protein expression in HEK293T cells, which was decreased to 27% compared to wild type, whereas PS‐stimulated ATPase activity was decreased by 57%. Patient RBCs showed a mild increase in PS surface exposure when compared to control RBCs, which further increased in the most dense RBCs after RBC storage stress. The increase in PS was not due to higher global membrane content of PS or other phospholipids. In contrast, membrane lipid lateral distribution showed increased abundance of cholesterol‐enriched domains in RBC low curvature areas. Finally, more dense RBCs and subtle changes in RBC morphology under flow hint toward alterations in flow behavior of ATP11C‐deficient RBCs. Altogether, ATP11C deficiency is the likely cause of hemolytic anemia in our patient, thereby underlining the physiological role and relevance of this flippase in human RBCs.

In many medical disciplines, red blood cells are discovered to be biomarkers since they “experience” various conditions in basically all organs of the body. Classical examples are diabetes and hypercholesterolemia. However, recently the red blood cell distribution width (RDW), is often referred to, as an unspecific parameter/marker (e.g., for cardiac events or in oncological studies). The measurement of RDW requires venous blood samples to perform the complete blood cell count (CBC). Here, we introduce Erysense, a lab-on-a-chip-based point-of-care device, to evaluate red blood cell flow properties. The capillary chip technology in combination with algorithms based on artificial neural networks allows the detection of very subtle changes in the red blood cell morphology. This flow-based method closely resembles in vivo conditions and blood sample volumes in the sub-microliter range are sufficient. We provide clinical examples for potential applications of Erysense as a diagnostic tool [here: neuroacanthocytosis syndromes (NAS)] and as cellular quality control for red blood cells [here: hemodiafiltration (HDF) and erythrocyte concentrate (EC) storage]. Due to the wide range of the applicable flow velocities (0.1–10 mm/s) different mechanical properties of the red blood cells can be addressed with Erysense providing the opportunity for differential diagnosis/judgments. Due to these versatile properties, we anticipate the value of Erysense for further diagnostic, prognostic, and theragnostic applications including but not limited to diabetes, iron deficiency, COVID-19, rheumatism, various red blood cell disorders and anemia, as well as inflammation-based diseases including sepsis.

The dynamics of single red blood cells (RBCs) determine microvascular blood flow by adapting their shape to the flow conditions in the narrow vessels. In this study, we explore the dynamics and shape transitions of RBCs on the cellular scale under confined and unsteady flow conditions using a combination of microfluidic experiments and numerical simulations. Tracking RBCs in a comoving frame in time-dependent flows reveals that the mean transition time from the symmetric croissant to the off-centered, nonsymmetric slipper shape is significantly faster than the opposite shape transition, which exhibits pronounced cell rotations. Complementary simulations indicate that these dynamics depend on the orientation of the RBC membrane in the channel during the time-dependent flow. Moreover, we show how the tank-treading movement of slipper-shaped RBCs in combination with the narrow channel leads to oscillations of the cell's center of mass. The frequency of these oscillations depends on the cell velocity, the viscosity of the surrounding fluid, and the cytosol viscosity. These results provide a potential framework to identify and study pathological changes in RBC properties.

We propose a flow cytometry concept that combines a spatial optical modulation scheme and deep learning for lensless cell imaging. Inspired by auto-encoder techniques, an artificial neural network mimics the optical transfer function of a particular microscope and camera for certain types of cells once trained and reconstructs microscope images from simple waveforms that are generated by cells in microfluidic flow. This eventually enables the label-free detection of cells at high throughput while simultaneously providing their corresponding brightfield images. The present work focuses on the computational proof of concept of this method by mimicking the waveforms. Our suggested approach would require a minimum set of optical components such as a collimated light source, a slit mask, and a light sensor and could be easily integrated into a ruggedized lab-on-chip device. The method is benchmarked with a well-investigated dataset of red blood cell images.

Unsteady and pulsatile flows receive increasing attention due to their potential to enhance various microscale processes. Further, they possess significant relevance for microfluidic studies under physiological flow conditions. However, generating a precise time-dependent flow field with commercial, pneumatically operated pressure controllers remains challenging and can lead to significant deviations from the desired waveform. In this study, we present a method to correct such deviations and thus optimize pulsatile flows in microfluidic experiments using two commercial pressure pumps. Therefore, we first analyze the linear response of the systems to a sinusoidal pressure input, which allows us to predict the time-dependent pressure output for arbitrary pulsatile input signals. Second, we explain how to derive an adapted input signal, which significantly reduces deviations between the desired and actual output pressure signals of various waveforms. We demonstrate that this adapted pressure input leads to an enhancement of the time-dependent flow of red blood cells in microchannels. The presented method does not rely on any hardware modifications and can be easily implemented in standard pressure-driven microfluidic setups to generate accurate pulsatile flows with arbitrary waveforms.

Constrictions in blood vessels and microfluidic devices can dramatically change the spatial distribution of passing cells or particles and are commonly used in biomedical cell sorting applications. However, the three-dimensional nature of cell focusing in the channel cross-section remains poorly investigated. Here, we explore the cross-sectional distribution of living and rigid red blood cells passing a constricted microfluidic channel by tracking individual cells in multiple layers across the channel depth and across the channel width. While cells are homogeneously distributed in the channel cross-section pre-contraction, we observe a strong geometry-induced focusing towards the four channel faces post-contraction. The magnitude of this cross-sectional focusing effect increases with increasing Reynolds number for both living and rigid red blood cells. We discuss how this non-uniform cell distribution downstream of the contraction results in an apparent double-peaked velocity profile in particle image velocimetry analysis and show that trapping of red blood cells in the recirculation zones of the abrupt construction depends on cell deformability.