Sensitivity of infectious SARS-CoV-2 B.1.1.7 and B.1.351 variants to neutralizing antibodies

International audienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.7 and B.1.351 variants were first identified in the United Kingdom and South Africa, respectively, and have since spread to many countries. These variants harboring diverse mutations in the gene encoding the spike protein raise important concerns about their immune evasion potential. Here, we isolated infectious B.1.1.7 and B.1.351 strains from acutely infected individuals. We examined sensitivity of the two variants to SARS-CoV-2 antibodies present in sera and nasal swabs from individuals infected with previously circulating strains or who were recently vaccinated, in comparison with a D614G reference virus. We utilized a new rapid neutralization assay, based on reporter cells that become positive for GFP after overnight infection. Sera from 58 convalescent individuals collected up to 9 months after symptoms, similarly neutralized B.1.1.7 and D614G. In contrast, after 9 months, convalescent sera had a mean sixfold reduction in neutralizing titers, and 40% of the samples lacked any activity against B.1.351. Sera from 19 individuals vaccinated twice with Pfizer Cominarty, longitudinally tested up to 6 weeks after vaccination, were similarly potent against B.1.1.7 but less efficacious against B.1.351, when compared to D614G. Neutralizing titers increased after the second vaccine dose, but remained 14-fold lower against B.1.351. In contrast, sera from convalescent or vaccinated individuals similarly bound the three spike proteins in a flow cytometry-based serological assay. Neutralizing antibodies were rarely detected in nasal swabs from vaccinees. Thus, faster-spreading SARS-CoV-2 variants acquired a partial resistance to neutralizing antibodies generated by natural infection or vaccination, which was most frequently detected in individuals with low antibody levels. Our results indicate that B1.351, but not B.1.1.7, may increase the risk of infection in immunized individuals

Animal models in urological disease and sexual dysfunction

There are several conditions associated with dysfunction of the lower urinary tract or which result in a reduction in the ability to engage in satisfactory sexual function and result in significant bother to sufferers, partners and/or carers. This review describes some of the animal models that may be used to discover safe and effective medicines with which to treat them. While alpha adrenoceptor antagonists and 5-alpha-reductase inhibitors deliver improvement in symptom relief in benign prostatic hyperplasia sufferers, the availability of efficacious and well-tolerated medicines to treat incontinence is less well served. Stress urinary incontinence (SUI) has no approved medical therapy in the United States and overactive bladder (OAB) therapy is limited to treatment with muscarinic antagonists (anti-muscarinics). SUI and OAB are characterised by high prevalence, a growing ageing population and a strong desire from sufferers and physicians for more effective treatment options. High patient numbers with low presentation rates characterizes sexual dysfunction in men and women. The introduction of Viagra™ in 1998 for treating male erectile dysfunction and the success of the phosphodiesterase type 5 inhibitor class (PDE5 inhibitor) have indicated the willingness of sufferers to seek treatment when an effective alternative to injections and devices is available. The main value of preclinical models in discovering new medicines is to predict clinical outcomes. This translation can be established relatively easily in areas of medicine where there are a large number of drugs with different underlying pharmacological mechanisms in clinical usage. However, apart from, for example, the use of PDE5 inhibitors to treat male erectile dysfunction and the use of anti-muscarinics to treat OAB, this clinical information is limited. Therefore, current confidence in existing preclinical models is based on our understanding of the biochemical, physiological, pathophysiological and psychological mechanisms underlying the conditions in humans and how they are reflected in preclinical models. Confidence in both the models used and the pharmacological data generated is reinforced if different models of related aspects of the same disorder generate confirmatory data. However, these models will only be fully validated in retrospect once the pharmacological agents they have helped identify are tested in humans