Using ConSurf to Detect Functionally Important Regions in RNA.

The ConSurf web server (https://consurf.tau.ac.il/) for using evolutionary data to detect functional regions is useful for analyzing proteins. The analysis is based on the premise that functional regions, which may for example facilitate ligand binding and catalysis, often evolve slowly. The analysis requires finding enough effective, i.e., non-redundant, sufficiently remote homologs. Indeed, the ConSurf pipeline, which is based on state-of-the-art protein sequence databases and analysis tools, is highly valuable for protein analysis. ConSurf also allows evolutionary analysis of RNA, but the analysis often fails due to insufficient data, particularly the inability of the current pipeline to detect enough effective RNA homologs. This is because the RNA search tools and databases offered are not as good as those used for protein analysis. Fortunately, ConSurf also allows importing external collections of homologs in the form of a multiple sequence alignment (MSA). Leveraging this, here we describe various protocols for constructing MSAs for successful ConSurf analysis of RNA queries. We report the level of success of these protocols on an exemplary set comprising a dozen RNA molecules of diverse structure and function. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Standard ConSurf evolutionary conservation analysis of an RNA query. Basic Protocol 2: ConSurf evolutionary conservation analysis of an RNA query with external MSA. Support Protocol 1: Construction of an MSA for an RNA query using other online servers. Support Protocol 2: Construction of an MSA for an RNA query using nHMMER locally.

Activated Platelets Induce Endothelial Cell Activation via an Interleukin-1ß Pathway in Systemic Lupus Erythematosus.

OBJECTIVE: Systemic lupus erythematosus (SLE) is associated with the premature development of cardiovascular disease. The platelet-endothelium interaction is important in the pathogenesis of cardiovascular disease. In this study, we investigated the platelet phenotype from patients with SLE and matched controls, and their effect on endothelial cells. APPROACH AND RESULTS: Platelet aggregability was measured in 54 SLE subjects off antiplatelet therapy (mean age 40.1±12.8 years; 82% female; 37% white) with age- and sex-matched controls. Platelets were coincubated with human umbilical vein endothelial cells (HUVECs) and changes to gene expression assessed by an RNA array and quantitative reverse transcription polymerase chain reaction. SLE disease activity index ranged from 0 to 22 (mean 5.1±3.9). Compared with controls, patients with SLE had significantly increased monocyte and leukocyte-platelet aggregation and platelet aggregation in response to submaximal agonist stimulation. An agnostic microarray of HUVECs cocultured with SLE platelets found a platelet-mediated effect on endothelial gene pathways involved in cell activation. Sera from SLE versus control subjects significantly increased (1) activation of control platelets; (2) platelet adhesion to HUVECs; (3) platelet-induced HUVEC gene expression of interleukin-8, and intercellular adhesion molecule 1; and (4) proinflammatory gene expression in HUVECs, mediated by interleukin-1ß-dependent pathway. Incubation of SLE-activated platelets with an interleukin-1ß-neutralizing antibody or HUVECs pretreated with interleukin-1 receptor antibodies attenuated the platelet-mediated activation of endothelial cells. CONCLUSIONS: Platelet activity measurements and subsequent interleukin-1ß-dependent activation of the endothelium are increased in subjects with SLE. Platelet-endothelial interactions may play a role in the pathogenesis of cardiovascular disease in patients with SLE.