Strains of Neisseria gonorrhoeae with mosaic penA genes bearing novel point mutations in penA have been isolated from ceftriaxone treatment failures. Such isolates exhibit significantly higher MIC values to third-generation cephalosporins. Here we report the in vitro isolation of two mutants with elevated MICs to cephalosporins. The first possesses a point mutation in the transpeptidase region of the mosaic penA gene, and the second contains an insertion mutation in pilQ.

Pathogen evolution is influenced strongly by the host immune response. Previous studies of the effects of herd immunity on the population structure of directly transmitted, short-lived pathogens have primarily focused on the impact of competition for hosts. In contrast, for long-lived infections like HIV, theoretical work has focused on the mechanisms promoting antigenic variation within the host. In reality, successful transmission requires that pathogens balance both within- and between-host immune selection. The Opa adhesins in the bacterial Neisseria genus provide a unique system to study the evolution of the same antigens across two major pathogens: while N. meningitidis is an airborne, respiratory pathogen colonising the nasopharynx relatively transiently, N. gonorrhoeae can cause sexually transmitted, long-lived infections. We use a simple mathematical model and genomic data to show that trade-offs between immune selection pressures within- and between-hosts can explain the contrasting Opa repertoires observed in meningococci and gonococci.

The landscape of diagnostic testing for tuberculosis (TB) is changing rapidly, and stakeholders need urgent guidance on how to develop, deploy and optimize TB diagnostics in a way that maximizes impact and makes best use of available resources. When decisions must be made with only incomplete or preliminary data available, modelling is a useful tool for providing such guidance. Following a meeting of modelers and other key stakeholders organized by the TB Modelling and Analysis Consortium, we propose a conceptual framework for positioning models of TB diagnostics. We use that framework to describe modelling priorities in four key areas: Xpert(®) MTB/RIF scale-up, target product profiles for novel assays, drug susceptibility testing to support new drug regimens, and the improvement of future TB diagnostic models. If we are to maximize the impact and cost-effectiveness of TB diagnostics, these modelling priorities should figure prominently as targets for future research.

Research investments are essential to address the burden of disease, however allocation of limited resources is poorly documented. We systematically reviewed the investments awarded by funding organisations to UK institutions and their global partners for infectious disease research.