Vascular endothelial cells form the inner cellular lining of blood vessels in the closed cardiovascular system of higher species. They form the interface between the blood and tissues and are characterized by luminal and abluminal surfaces. The endothelium is a diverse, active, and adaptive system that regulates blood flow, nutrient trafficking, immunity, and the growth of new blood vessels1. In the body, endothelial cells normally exist in an environment where they are exposed to the frictional force of circulation, shear stress2. Shear stress is an important regulator of endothelial cell gene expression3, and endothelial cells attempt to maintain shear stress within a given range2,4. Endothelial cells demonstrate angiogenic patterning in the absence of shear stress5 that can improve tissue perfusion. Regional patterns of disturbed flow and altered shear stress are associated with the expression of inflammatory genes6 and the development of atherosclerosis7,8. Thus, models that include shear stress are a major component of understanding endothelial gene regulation.
We describe a method for studying the gene regulation in vascular endothelial cells under shear stress. This system uses non-pulsatile flow and mimics fluid shear stress levels and oxygen concentration that model conditions for arterial endothelial cells. This protocol includes details of methods for the gene knockdown using RNA interference (RNAi), the set-up for the application of shear stress using the parallel-plate flow apparatus, and methods for the spike-in of an exogenous reference RNA prior to analysis by reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR). This pipeline is used for studying gene regulation in endothelial cells in the presence and absence of laminar shear stress and includes an adaptation of the parallel-plate flow apparatus described by Lane et al.9. This particular set-up was designed to facilitate the simultaneous assessment of multiple experimental conditions that allows direct comparison of shear stress conditions, as well as the normalization of RNA analysis. A large heated unit with controlled humidity is utilized to allow multiple separate flow chambers and pumps to be running simultaneously with flow rates monitored for each flow chamber assembly in real-time. The application of this set-up is used for gene knockdown using RNAi in the setting of laminar flow/shear stress, but aspects of this protocol can be applied to any assessment of RNA expression.
Common approaches to the application of shear stress for endothelial cells include microfluidic systems10, a cone-and-plate viscometer11, and a parallel-plate flow chamber12. Microfluidic systems from various manufacturers have been useful in studying mechanobiology and mechanotransduction in multiple cell and tissue types and a variety of biophysical stimuli. For endothelial cells, they have been used to study endothelial cells in isolation, as well as the interaction of endothelial cells and the trafficking of immune or tumor cells10. However, these systems are less suitable for the recovery of large numbers of cells9. Both the cone-and-plate viscometer and parallel-plate flow chambers allow the recovery of large numbers of cells in confluent monolayers12. These systems can generate a range of shear forces and patterns12. The parallel-plate flow chamber assembly9 has the advantage that real-time imaging can be performed through the glass window to evaluate cellular morphology at any time point. Furthermore, the perfusate can be collected under sterile conditions. For the system presented here, the flow can also be monitored in real-time and in a multi-chamber set-up, which facilitates the maintenance of shear conditions between chambers.
For representative experiments, human umbilical vein endothelial cells (HUVEC), which represent a macrovascular endothelial cell type, are used, and the shear stress conditions we use (1 Pa) reflect arterial conditions (0.1 - 0.7 Pa). However, this protocol can be used with other endothelial cell types, and the shear stress conditions can be adjusted according to the experimental question. For example, the evaluation of human endothelial cells in conditions that model venous circulation would require lower levels of shear stress (1 - 6 Pa) and studies that model microvascular circulation have utilized shear stress levels of 0.4 - 1.2 Pa13,14. In addition, shear stress can vary even between endothelial cells within the same blood vessel6. In the current set-up, a single monitoring system is used that can simultaneously monitor four separate flow loops. For labs that need more flow loops, there is space in the dedicated environment for an additional monitoring system.
RT-qPCR is used for the absolute quantitation of gene expression in the setting of shear stress. The relative expression of target genes is often used to compare RNA expression across conditions. Some RNA species can exist at very low quantities or be absent, thus complicating relative measurements. For example, long noncoding RNAs in endothelial cells can exert potent effects at relatively low copy numbers per cell5. In addition, differences in primer efficiency can lead to an inaccurate interpretation from utilizing the delta-delta cycle threshold (Ct) method to analyze the data. To address this concern, we perform absolute quantitation by generating a standard curve using a known quantity of plasmid DNA. Furthermore, complementary DNA (cDNA) synthesis is an inefficient process, and differences in cDNA efficiency can account for differences in RNA expression between conditions and between samples15. The application of shear stress and/or transfection reagents can affect cell proliferation, apoptosis, and viability, or add components that may interfere with RNA isolation and/or cDNA synthesis. To account for the possibility of bias from RNA isolation and cDNA synthesis, we use a spike-in RNA control synthesized in the lab, added at the time of RNA extraction and measured with each cDNA synthesis via RT-qPCR. This allows not only the adjustment for technical differences in RNA extraction and cDNA synthesis but also allows the calculation of absolute quantities per cell, when the cell count is known.
This system uses additional steps to maintain similarity or account for technical differences between conditions. We particularly emphasize these steps because of the complex nature of these experiments, which involve multiple physical set-ups and experimental conditions that can lead to experimental variability.