Phenotype to genotype: dissecting meningococcal disease and carriage traits

  • Sheppard, Samuel (PI)
  • Mourkas, Evangelos (Researcher)

Project: Research council

Project Details


Bacteria cause disease by combining multiple different behaviours. Neisseria meningitidis, the meningococcus, causes both meningitis and septicaemia. In 2016-2017, there were 747 confirmed meningococcal disease cases in England despite new meningococcal vaccines being introduced into the infant and teenage immunisation schedules. In order to cause disease, the meningococcus first transmits from one person to another and then sticks to tissues at the back of the throat and around the tonsils. The bacterium survives for multiple days avoiding effector molecules produced by our bodies such as antibodies. Disease occurs when the organism invades by moving from the mucosal tissues into the blood where the bacterial cells grow rapidly and resist being killed by complement and white blood cells. From the blood, this fearsome pathogen spreads and causes inflammation in the tissues lining the brain. Each step of the disease process is mediated by combinations of molecules or virulence factors encoded in the genomes of meningococcal bacteria.
Currently, we know that the capsule (polysaccharides present on the outside of bacterial cells) and several other factors are required for meningococci to cause disease. But we also have large amounts of information about the genomes of 1,000s of meningococcal disease and carriage isolates. These genomes contain extensive information about identities of disease-causing strains, how strains change over time and on numbers/types of genes present in each strain. While these genomes have enabled us to link certain sequences to the disease state, there has only been limited efforts to link genomic variation to variation in the phenotypes required for disease so that much of our current information is inferential rather than experimentally-based.
We intend to explore phenotype-to-genotype links by testing up to ~330 isolates in a series of 12 assays that mimic various disease and carriage behaviours. We will develop high throughput assays, enabling rapid processing of multiple isolates, and utilise these methodologies to study endemic serogroup Y and hyperinvasive serogroup W meningococcal isolates from patients and carriers. Quantitative outputs from multiple phenotypes will provide us with significant power for statistical association tests to link phenotypes to disease and carriage traits and to identify specific genetic determinants of these traits. These tests will be followed up by molecular testing of specific genetic determinants to confirm their contributions to a specific behaviour. This step will involve construction of mutants with alterations in a single gene or in multiple genes so that we can see how combinations of phenotypes contribute to disease processes.
We will also explore interactions between virulent and avirulent variants. We have already observed that isolates from one carrier had opposing and potentially antagonistic behaviours with one causing disruption of monolayers of human cells while the other tightened interactions between these cells. We will test whether these bacterial variants antagonise each other and if this is a general phenomenon affecting multiple isolates and other disease phenotypes.
What we hope to gain is not only a better understanding of how meningococci cause disease but also improved assessment of the prevalence of disease-attributes of meningococcal strains. This will be important as we monitor the impact of the new MenB vaccine, Bexsero, on disease in the UK as avoidance of vaccine responses could occur by either changes in vaccine-targeted antigens or enhanced virulence. Our information will also facilitate development of second generation vaccines by identifying key determinants of disease for inclusion in new vaccines. Finally, our approaches will be applicable to other bacterial pathogens enhancing translation of genotypes into phenotypes for the ever-expanding genomic databases of pathogenic bacteria.
Effective start/end date1/06/2030/11/22


  • Medical Research Council


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.