Sepsis and meningitis caused by serogroup B meningococcus are devastating diseases of infants and young adults, which cannot yet be prevented by vaccination. By genome mining, we discovered GNA1870, a new surface-exposed lipoprotein of Neisseria meningitidis that induces high levels of bactericidal antibodies. The antigen is expressed by all strains of N. meningitidis tested. Sequencing of the gene in 71 strains representative of the genetic and geographic diversity of the N. meningitidis population, showed that the protein can be divided into three variants. Conservation within each variant ranges between 91.6 to 100%, while between the variants the conservation can be as low as 62.8%. The level of expression varies between strains, which can be classified as high, intermediate, and low expressors. Antibodies against a recombinant form of the protein elicit complement-mediated killing of the strains that carry the same variant and induce passive protection in the infant rat model. Bactericidal titers are highest against those strains expressing high yields of the protein; however, even the very low expressors are efficiently killed. The novel antigen is a top candidate for the development of a new vaccine against meningococcus.

Background Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis, which are typically transmitted via respiratory droplets, are leading causes of invasive diseases, including bacteraemic pneumonia and meningitis, and of secondary infections subsequent to post-viral respiratory disease. The aim of this study was to investigate the incidence of invasive disease due to these pathogens during the early months of the COVID-19 pandemic. MethodsIn this prospective analysis of surveillance data, laboratories in 26 countries and territories across six continents submitted data on cases of invasive disease due to S pneumoniae, H influenzae, and N meningitidis from Jan 1, 2018, to May, 31, 2020, as part of the Invasive Respiratory Infection Surveillance (IRIS) Initiative. Numbers of weekly cases in 2020 were compared with corresponding data for 2018 and 2019. Data for invasive disease due to Streptococcus agalactiae, a non-respiratory pathogen, were collected from nine laboratories for comparison. The stringency of COVID-19 containment measures was quantified using the Oxford COVID-19 Government Response Tracker. Changes in population movements were assessed using Google COVID-19 Community Mobility Reports. Interrupted time-series modelling quantified changes in the incidence of invasive disease due to S pneumoniae, H influenzae, and N meningitidis in 2020 relative to when containment measures were imposed. Findings 27 laboratories from 26 countries and territories submitted data to the IRIS Initiative for S pneumoniae (62 434 total cases), 24 laboratories from 24 countries submitted data for H influenzae (7796 total cases), and 21 laboratories from 21 countries submitted data for N meningitidis (5877 total cases). All countries and territories had experienced a significant and sustained reduction in invasive diseases due to S pneumoniae, H influenzae, and N meningitidis in early 2020 (Jan 1 to May 31, 2020), coinciding with the introduction of COVID-19 containment measures in each country. By contrast, no significant changes in the incidence of invasive S agalactiae infections were observed. Similar trends were observed across most countries and territories despite differing stringency in COVID-19 control policies. The incidence of reported S pneumoniae infections decreased by 68% at 4 weeks (incidence rate ratio 0•32 [95% CI 0•27-0•37]) and 82% at 8 weeks (0•18 [0•14-0•23]) following the week in which significant changes in population movements were recorded. Interpretation The introduction of COVID-19 containment policies and public information campaigns likely reduced transmission of S pneumoniae, H influenzae, and N meningitidis, leading to a significant reduction in life-threatening invasive diseases in many countries worldwide.

Summary The ability of Staphylococcus aureus cells to induce platelet aggregation has long been recognized. However, despite several attempts to identify the mechanisms involved in this interaction, the nature of the bacterial receptors required remains poorly understood. Using genetic manipulation, this study for the first time provides clear evidence that several S. aureus surface proteins participate in the inter‐action with platelets. Mutants of S. aureus strain Newman lacking one or more surface proteins were tested for their ability to stimulate platelet aggre‐gation. This approach was complemented by the expression of a number of candidate proteins in the non‐aggregating Gram‐positive bacterium Lacto‐coccus lactis. S. aureus‐induced aggregation was monophasic and was dependent on the platelet receptor GPIIb/IIIa. The fibrinogen‐binding proteins, clumping factors A and B and the serine‐aspartate repeat protein SdrE could each induce aggregation when expressed in L. lactis. Although protein A expressed in L. lactis was not capable of inducing aggregation independently, it enhanced the aggregation response when expressed on the surface of S. aureus. Thus, S. aureus has multiple mechanisms for stimulating platelet aggregation. Such functional redundancy suggests that this phenomenon may be important in the pathogenesis of invasive diseases such as infective endocarditis.

Streptococcus pneumoniae typically express one of 92 serologically distinct capsule polysaccharide (cps) types (serotypes). Some of these serotypes are closely related to each other; using the commercially available typing antisera, these are assigned to common serogroups containing types that show cross-reactivity. In this serotyping scheme, factor antisera are used to allocate serotypes within a serogroup, based on patterns of reactions. This serotyping method is technically demanding, requires considerable experience and the reading of the results can be subjective. This study describes the analysis of the S. pneumoniae capsular operon genetic sequence to determine serotype distinguishing features and the development, evaluation and verification of an automated whole genome sequence (WGS)-based serotyping bioinformatics tool, PneumoCaT (Pneumococcal Capsule Typing). Initially, WGS data from 871 S. pneumoniae isolates were mapped to reference cps locus sequences for the 92 serotypes. Thirty-two of 92 serotypes could be unambiguously identified based on sequence similarities within the cps operon. The remaining 60 were allocated to one of 20 ‘genogroups’ that broadly correspond to the immunologically defined serogroups. By comparing the cps reference sequences for each genogroup, unique molecular differences were determined for serotypes within 18 of the 20 genogroups and verified using the set of 871 isolates. This information was used to design a decision-tree style algorithm within the PneumoCaT bioinformatics tool to predict to serotype level for 89/94 (92 + 2 molecular types/subtypes) from WGS data and to serogroup level for serogroups 24 and 32, which currently comprise 2.1% of UK referred, invasive isolates submitted to the National Reference Laboratory (NRL), Public Health England (June 2014–July 2015). PneumoCaT was evaluated with an internal validation set of 2065 UK isolates covering 72/92 serotypes, including 19 non-typeable isolates and an external validation set of 2964 isolates from Thailand (n = 2,531), USA (n = 181) and Iceland (n = 252). PneumoCaT was able to predict serotype in 99.1% of the typeable UK isolates and in 99.0% of the non-UK isolates. Concordance was evaluated in UK isolates where further investigation was possible; in 91.5% of the cases the predicted capsular type was concordant with the serologically derived serotype. Following retesting, concordance increased to 99.3% and in most resolved cases (97.8%; 135/138) discordance was shown to be caused by errors in original serotyping. Replicate testing demonstrated that PneumoCaT gave 100% reproducibility of the predicted serotype result. In summary, we have developed a WGS-based serotyping method that can predict capsular type to serotype level for 89/94 serotypes and to serogroup level for the remaining four. This approach could be integrated into routine typing workflows in reference laboratories, reducing the need for phenotypic immunological testing.