Lack of Significant Elevation of Myeloid-Derived Suppressor Cells in Peripheral Blood of Chronically Hepatitis C Virus-Infected Individuals

Myeloid-derived suppressor cells (MDSC) are immature myeloid cells with immunosuppressive function. Compared to the level in healthy controls (HC), no elevation of MDSC in chronic hepatitis C (cHEP-C) patients was found, and there was no difference in MDSC based on genotype or viral load (P > 0.25). Moreover, MDSC of cHEP-C patients inhibited CD8 T cell function as efficiently as MDSC of HC did. Since we detected neither quantitative nor qualitative differences in MDSC of cHEP-C patients relative to those of HC, we postulate that MDSC in peripheral blood are most likely not significant regarding immune dysfunction in cHEP-C.     

Interleukin-1α Activity in Necrotic Endothelial Cells Is Controlled by Caspase-1 Cleavage of Interleukin-1 Receptor-2: IMPLICATIONS FOR ALLOGRAFT REJECTION*

Inflammation is a key instigator of the immune responses that drive atherosclerosis and allograft rejection. IL-1α, a powerful cytokine that activates both innate and adaptive immunity, induces vessel inflammation after release from necrotic vascular smooth muscle cells (VSMCs). Similarly, IL-1α released from endothelial cells (ECs) damaged during transplant drives allograft rejection. However, IL-1α requires cleavage for full cytokine activity, and what controls cleavage in necrotic ECs is currently unknown. We find that ECs have very low levels of IL-1α activity upon necrosis. However, TNFα or IL-1 induces significant levels of active IL-1α in EC necrotic lysates without alteration in protein levels. Increased activity requires cleavage of IL-1α by calpain to the more active mature form. Immunofluorescence and proximity ligation assays show that IL-1α associates with interleukin-1 receptor-2, and this association is decreased by TNFα or IL-1 and requires caspase activity. Thus, TNFα or IL-1 treatment of ECs leads to caspase proteolytic activity that cleaves interleukin-1 receptor-2, allowing IL-1α dissociation and subsequent processing by calpain. Importantly, ECs could be primed by IL-1α from adjacent damaged VSMCs, and necrotic ECs could activate neighboring normal ECs and VSMCs, causing them to release inflammatory cytokines and up-regulate adhesion molecules, thus amplifying inflammation. These data unravel the molecular mechanisms and interplay between damaged ECs and VSMCs that lead to activation of IL-1α and, thus, initiation of adaptive responses that cause graft rejection.     

Resistance to radial expansion limits muscle strain and work

The collagenous extracellular matrix (ECM) of skeletal muscle functions to transmit force, protect sensitive structures, and generate passive tension to resist stretch. The mechanical properties of the ECM change with age, atrophy, and neuromuscular pathologies, resulting in an increase in the relative amount of collagen and an increase in stiffness. Although numerous studies have focused on the effect of muscle fibrosis on passive muscle stiffness, few have examined how these structural changes may compromise contractile performance. Here we combine a mathematical model and experimental manipulations to examine how changes in the mechanical properties of the ECM constrain the ability of muscle fibers and fascicles to radially expand and how such a constraint may limit active muscle shortening. We model the mechanical interaction between a contracting muscle and the ECM using a constant volume, pressurized, fiber-wound cylinder. Our model shows that as the proportion of a muscle cross section made up of ECM increases, the muscle’s ability to expand radially is compromised, which in turn restricts muscle shortening. In our experiments, we use a physical constraint placed around the muscle to restrict radial expansion during a contraction. Our experimental results are consistent with model predictions and show that muscles restricted from radial expansion undergo less shortening and generate less mechanical work under identical loads and stimulation conditions. This work highlights the intimate mechanical interaction between contractile and connective tissue structures within skeletal muscle and shows how a deviation from a healthy, well-tuned relationship can compromise performance.     

A validated model of passive skeletal muscle to predict force and intramuscular pressure

The passive properties of skeletal muscle are often overlooked in muscle studies, yet they play a key role in tissue function in vivo. Studies analyzing and modeling muscle passive properties, while not uncommon, have never investigated the role of fluid content within the tissue. Additionally, intramuscular pressure (IMP) has been shown to correlate with muscle force in vivo and could be used to predict muscle force in the clinic. In this study, a novel model of skeletal muscle was developed and validated to predict both muscle stress and IMP under passive conditions for the New Zealand White Rabbit tibialis anterior. This model is the first to include fluid content within the tissue and uses whole muscle geometry. A nonlinear optimization scheme was highly effective at fitting model stress output to experimental stress data (normalized mean square error or NMSE fit value of 0.993) and validation showed very good agreement to experimental data (NMSE fit values of 0.955 and 0.860 for IMP and stress, respectively). While future work to include muscle activation would broaden the physiological application of this model, the passive implementation could be used to guide surgeries where passive muscle is stretched.     

Flow and Diffusion in Channel-Guided Cell Migration

Collective migration of mechanically coupled cell layers is a notable feature of wound healing, embryonic development, and cancer progression. In confluent epithelial sheets, the dynamics have been found to be highly heterogeneous, exhibiting spontaneous formation of swirls, long-range correlations, and glass-like dynamic arrest as a function of cell density. In contrast, the flow-like properties of one-sided cell-sheet expansion in confining geometries are not well understood. Here, we studied the short- and long-term flow of Madin-Darby canine kidney (MDCK) cells as they moved through microchannels. Using single-cell tracking and particle image velocimetry (PIV), we found that a defined averaged stationary cell current emerged that exhibited a velocity gradient in the direction of migration and a plug-flow-like profile across the advancing sheet. The observed flow velocity can be decomposed into a constant term of directed cell migration and a diffusion-like contribution that increases with density gradient. The diffusive component is consistent with the cell-density profile and front propagation speed predicted by the Fisher-Kolmogorov equation. To connect diffusion-mediated transport to underlying cellular motility, we studied single-cell trajectories and occurrence of vorticity. We discovered that the directed large-scale cell flow altered fluctuations in cellular motion at short length scales: vorticity maps showed a reduced frequency of swirl formation in channel flow compared with resting sheets of equal cell density. Furthermore, under flow, single-cell trajectories showed persistent long-range, random-walk behavior superimposed on drift, whereas cells in resting tissue did not show significant displacements with respect to neighboring cells. Our work thus suggests that active cell migration manifests itself in an underlying, spatially uniform drift as well as in randomized bursts of short-range correlated motion that lead to a diffusion-mediated transport.     

Analyzing the dynamics of cell cycle processes from fixed samples through ergodic principles

Tools to analyze cyclical cellular processes, particularly the cell cycle, are of broad value for cell biology. Cell cycle synchronization and live-cell time-lapse observation are widely used to analyze these processes but are not available for many systems. Simple mathematical methods built on the ergodic principle are a well-established, widely applicable, and powerful alternative analysis approach, although they are less widely used. These methods extract data about the dynamics of a cyclical process from a single time-point “snapshot” of a population of cells progressing through the cycle asynchronously. Here, I demonstrate application of these simple mathematical methods to analysis of basic cyclical processes—cycles including a division event, cell populations undergoing unicellular aging, and cell cycles with multiple fission (schizogony)—as well as recent advances that allow detailed mapping of the cell cycle from continuously changing properties of the cell such as size and DNA content. This includes examples using existing data from mammalian, yeast, and unicellular eukaryotic parasite cell biology. Through the ongoing advances in high-throughput cell analysis by light microscopy, electron microscopy, and flow cytometry, these mathematical methods are becoming ever more important and are a powerful complementary method to traditional synchronization and time-lapse cell cycle analysis methods.