Erysense, a Lab-on-a-Chip-Based Point-of-Care Device to Evaluate Red Blood Cell Flow Properties With Multiple Clinical Applications

Abstract

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.

Cross-talk between red blood cells and plasma influences blood flow and omics phenotypes in severe COVID-19

“…This dilution could possibly impact the observed morphological changes of RBCs in patient plasma. With the used dilution, we see normal flow shapes for healthy RBC in autologous plasma, which are in agreement with previous studies in similar microchannels ( Guckenberger et al, 2018 ; Kihm et al, 2018 ; Recktenwald et al, 2022a ; Recktenwald et al, 2022b ) and are therefore used as a basis to validate the chosen experimental setting. For the metabolomic and proteomic analyses, we use hematocrits close to the physiological ones.…”

“…Further, COVID-19 patients show sphero-echinocytes in flow, known as irreversible transformations of RBCs that can occur upon ATP depletion, high pH, or exposure to anionic detergents ( Lim, 2009 ; Bernhardt and Ellory, 2013 ; Figure 1D ). The so-called RBC shape phase diagram ( Kihm et al, 2018 ; Guckenberger et al, 2018 ; Recktenwald et al, 2022a ; Recktenwald et al, 2022b ) describes the frequency of occurrence for RBC morphologies as a function of cell velocity. While croissant- and slipper-like shapes emerge for control samples in autologous plasma (CinC), corresponding pathological shapes and sphero-echinocytes dominate for patient RBCs in autologous plasma (PinP) ( Figure 1E , top graphs).…”

“…Per patient/donor an average of 3317 individual cells (between 1199 and 5496 cells) are examined. Based on the RBC velocity, the distribution of RBC lateral y-position is used as a characteristic indicator of the single-cell flow in such confined microchannels ( Kihm et al, 2018 ; Guckenberger et al, 2018 ; Recktenwald et al, 2022a ; Recktenwald et al, 2022b ). At a given mean velocity, the distribution of the absolute value of the cell lateral position in y-direction, normalized by the channel width, is determined and the corresponding probability density function (pdf) is calculated.…”

“…At such high velocities, RBC deformability turned out to be heterogeneous, with most of the RBCs being strongly elongated in the flow direction but some exhibiting circular, less deformable shapes compared with healthy controls. In human capillaries, which have diameters similar to RBC size (about 10 µm), confined flows confer to RBCs characteristic shapes that depend on the cell velocity and the surrounding medium ( Guckenberger et al, 2018 ; Recktenwald et al, 2022a ; Recktenwald et al, 2022b ). We previously used a microfluidic setup with channel dimensions similar to the RBC size and analyzed RBC shapes at high detail by means of artificial neural networks ( Kihm et al, 2018 ) in a velocity range that resembles microvascular in vivo flow.…”

Structural and mechanical properties of the red blood cell’s cytoplasmic membrane seen through the lens of biophysics

“…The shape of the RBC depends on the membrane’s deformability and may be quantified through a deformability index ( Cluitmans et al, 2014 ). Recent approaches also enable the in-flow three-dimensional characterization of RBC ( Quint et al, 2017 ) and quantify the observed shapes using machine learning algorithms and demonstrated the importance of the RBC’s deformability for the diagnosis of chorea acanthocytosis/VSP13A disease, McLeod Syndrome or the quality control of stored RBC ( Kihm et al, 2018 ; Recktenwald et al, 2022 ; Simionato et al, 2021 ). Another common technique is micropipette aspiration (MA), which can be applied to whole cells and artificially formed liposomes ( Figure 5C ).…”