Binding of different hyaluronan to CD44 mediates distinct cell adhesion dynamics under shear flow.

As a known receptor-ligand pair for mediating cell-cell or cell-extracellular matrix adhesions, cluster of differentiation 44 (CD44)-hyaluronan (HA) interactions are not only determined by molecular weight (MW) diversity of HA, but also are regulated by external physical or mechanical factors. However, the coupling effects of HA MW and shear flow are still unclear. Here, we compared the differences between high molecular weight HA (HHA) and low molecular weight HA (LHA) binding to CD44 under varied shear stresses. The results demonstrated that HHA dominated the binding phase but LHA was in favour of the shear resistance phase, respectively, under shear stress range ≤ 1.0 dyne·cm-2 . This difference was attributed to the high binding strength of the CD44-HHA interaction, as well as the optimal distribution matching between both CD44 and HA sides. Activation of the intracellular signal pathway was sensitive to both HA MW and shear flow. Our findings also indicate that only CD44-HHA interaction under shear stress of 0.2 dyne·cm-2 could significantly enhance the clustering of CD44, as well as induce the increase in both CD44 and CD18 expression. The present study offers the basis for further quantification of the features of CD44-HA interactions and their biological functions.

Distinct binding kinetics of E-, P- and L-selectins to CD44.

Molecular-level selectin-cluster of differentiation 44 (CD44) interactions are far from clear because of the complexity and diversity of CD44 glycosylation and isoforms expressed on various types of cells. By combining experimental measurements and simulation predictions, the binding kinetics of three selectin members to the recombinant CD44 were quantified and the corresponding microstructural mechanisms were explored, respectively. Experimental results showed that the E-selectin-CD44 interactions mainly mediated the firm adhesion of microbeads under shear flow with the strongest rupture force. P- and L-selectins had similar interaction strength but different association and dissociation rates by mediating stable rolling and transient adhesions of microbeads, respectively. Molecular docking and molecular dynamics (MD) simulations predicted that the binding epitopes of CD44 to selectins are all located at the side face of each selectin, although the interfaces denoted as the hinge region are between lectin and epidermal growth factor domains of E-selectin, Lectin domain side of P-selectin and epidermal growth factor domain side of L-selectin, respectively. The lowest binding free energy, the largest rupture force and the longest lifetime for E-selectin, as well as the comparable values for P- and L-selectins, demonstrated in both equilibration and steered MD simulations, supported the above experimental results. These results offer basic data for understanding the functional differences of selectin-CD44 interactions.

E-selectin negatively regulates polymorphonuclear neutrophil transmigration through altered endothelial junction integrity.

Transendothelial migration (TEM) of neutrophils under blood flow is critical in the inflammatory cascade. However, the role of endothelial plasticity in this process is not fully understood. Therefore, we used an in vitro model to test the dynamics of human polymorphonuclear neutrophil (PMN) TEM across lipopolysaccharide-treated human umbilical vein endothelial cell (HUVEC) monolayers. Interestingly, shRNA-E-selectin knockdown in HUVECs destabilized endothelial junctional integrity by reducing actin branching and increasing stress fiber at cell-cell junctions. This process is accomplished by downregulating the activation of cortactin and Arp2/3, which in turn alters the adhesive function of VE-cadherin, enhancing PMN transmigration. Meanwhile, redundant P-selectins possess overlapping functions in E-selectin-mediated neutrophil adhesion, and transmigration. These results demonstrate, to our knowledge, for the first time, that E-selectins negatively regulate neutrophil transmigration through alterations in endothelial plasticity. Furthermore, it improves our understanding of the mechanisms underlying actin remodeling, and junctional integrity, in endothelial cells mediating leukocyte TEM.

Mapping the morphological identifiers of distinct conformations via the protein translocation current in nanopores.

Conformational changes of proteins play a vital role in implementing their functions and revealing the underlying mechanisms in various biological processes. It is still challenging to monitor protein conformations with temporal fingerprints of current-resistance pulses in the nanopore technique. Here the low-resolution morphologies of different conformations of a typical integrin, αxß2, were estimated via relative blockade currents simulated from all-atom molecular dynamics (MD). Distinct conformational states of αxß2 were directly explained by the volume and shape identifiers. Protein modulation in ionic current was analyzed from the conductivity distribution inside the protein-blocked nanopore. Combining a discrete model with spheroidal approximation, a MD-based approach was developed to theoretically predict the volume and shape of the nanopore for sensing αxß2. This method was also applicable in specifying morphological identifiers of six other proteins, and the theoretical predictions are in good agreement with the experimental measurements. These results potentiated the validity of this method for the conformational identification of proteins in nanopores.

Characterizing liver sinusoidal endothelial cell fenestrae on soft substrates upon AFM imaging and deep learning.

BACKGROUND: Liver sinusoidal endothelial cells (LSECs) display unique fenestrated morphology. Alterations in the size and number of fenestrae play a crucial role in the progression of various liver diseases. While their features have been visualized using atomic force microscopy (AFM), the in situ imaging methods and off-line analyses are further required for fenestra quantification. METHODS: Primary mouse LSECs were cultured on a collagen-I-coated culture dish, or a polydimethylsiloxane (PDMS) or polyacrylamide (PA) hydrogel substrate. An AFM contact mode was applied to visualize fenestrae on individual fixed LSECs. Collected images were analyzed using an in-house developed image recognition program based on fully convolutional networks (FCN). RESULTS: Key scanning parameters were first optimized for visualizing the fenestrae on LSECs on culture dish, which was also applicable for the LSECs cultured on various hydrogels. The intermediate-magnification morphology images of LSECs were used for developing the FCN-based, fenestra recognition program. This program enabled us to recognize the vast majority of fenestrae from AFM images after twice trainings at a typical accuracy of 81.6% on soft substrate and also quantify the statistics of porosity, number of fenestrae and distribution of fenestra diameter. CONCLUSIONS: Combining AFM imaging with FCN training is able to quantify the morphological distributions of LSEC fenestrae on various substrates. SIGNIFICANCE: AFM images acquired and analyzed here provided the global information of surface ultramicroscopic structures over an entire cell, which is fundamental in understanding their regulatory mechanisms and pathophysiological relevance in fenestra-like evolution of individual cells on stiffness-varied substrates.