Phenotype to genotype: dissecting meningococcal disease and carriage traits

Lead Research Organisation: University of Leicester
Department Name: Genetics


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.

Technical Summary

Meningococci cause disease by transitioning from the mucosa into the circulatory system, surviving bactericidal effects of blood, adhering to the meninges and eliciting pathological cytokine responses. Variability in these phenotypes and in transmissibility influences whether meningococci cause disease. We aim to dissect disease potential by linking variability in multiple phenotypes to genotypic variation (allelic, accessory genes or phasotypes). Our hypotheses are:- (1) quantitative differences in specific phenotypes can be predicted from the genotype; (2) disease potential is due to the accumulation of large-effect genetic determinants of multiple phenotypes; (3) virulent phenotypic variants are antagonised by avirulent phenotypic variants.
We will develop high throughput assays for twelve disease-related phenotypes by combining multiwell plate formats with bacteriological, microscopic or immunological methods for measuring colony forming units, tissue disruption and cytokine levels. Application of assays to ~330 cc23 MenY and cc11 MenW isolates will generate quantitative data with defined variance levels. Statistical testing of individual and combinatorial phenotypic outputs provides significant power for multicomponent statistical association testing to link patterns of phenotypic variation to disease and carriage traits. Using treeWAS, a genome-wide association testing approach, we will associate phenotypic variation with specific genotypes followed by confirmatory re-testing of isogenic mutant strains in our panel of phenotypic assays. Antagonism will be studied in co-infection studies such as examining inhibition of CaLu3-monolayer disruptive variants by non-disruptive variants.
Our long-term goal is to generate predictive algorithms that utilise genotypically-linked phenotypic information to determine disease potential for meningococcal isolates and enable detection of infectivity shifts during epidemiological monitoring of meningococcal populations.

Planned Impact

Meningococci are still the major cause of bacterial meningitis despite introduction of new vaccines into the UK immunisation schedule. Invasive meningococcal disease still occurs because the vaccines either do not protect against all disease-causing meningococci or due to uncertainties regarding their herd immunity effects. There is likely to be a requirement for second generation meningococcal vaccines and for improvements in understanding of how vaccines impact on asymptomatic carriage of meningococci. Our investigation will provide new perspectives on how phenotypic variation in disease- and carriage-associated behaviours of meningococcal isolates is linked to genotype. These studies will provide us with new tools for predicting the disease potential of meningococcal strains and monitoring how the distribution of disease-causing behaviours is impacted by use of meningococcal vaccines.

One potential outcome is the identification of specific phenotypic patterns that are associated with the ability of meningococci to cause invasive disease and that can be identified through genotypic screening of meningococcal isolates. This outcome will have clinical impact as it raises the potential for development of predictive algorithms that could be utilised by epidemiologists to detect changes in the disease potential of circulating strains or provide for early detection of a new disease-causing or highly-transmissable strain. Vaccinologists would also use this information to target vaccine campaigns to vulnerable individuals/populations and for tailoring of second generation vaccines to include the key virulence determinants. This information will be disseminated via publications, presentations and inclusion of data outputs into the Neisseria PubMLST genome database.

Alternatively we may demonstrate that disease and carriage isolates of a meningococcal lineage are phenotypically-indistinguishable. This outcome would support the status quo that protective immunity and genetic determinants of meningococcal disease susceptibility are the only important determinants of disease susceptibility. Vaccinologists, geneticists and proponents of precision medicine would then be empowered to continue to focus resources on ensuring that all individuals have sufficient immunity to prevent infection and that genetically-susceptible individuals are rapidly identified and targeted for precautionary treatment.

We may also prove that avirulent phenotypic variants protect against virulent phenotypic variants. This finding would raise the imperative for more research into the importance of avirulent strains and commensal Neisseria for preventing disease. This issue is critical as new protein-based vaccines may perturb commensal colonisation and inadvertently alleviate niche competition leading to an enhanced likelihood of pathogenic meningococci causing disease.

A major general outcome will be development of methodologies for assessing the phenotypes of multiple bacterial isolates. Our approaches will allow for investigation of the impact of different treatments on large numbers of strains, identification of genetic determinants of variation in responses to treatments and exploration of phenotype-to-genotype associations in the extensive bacterial isolate collections of multiple organisms. These outputs will interest commercial companies working on meningococcal vaccines or on therapeutic use of complement inhibitors but who are concerned about enhanced susceptibility to meningococcal infections.

Meningococcal infections are high profile diseases with a major impact on the public perception of disease. We will work with the Meningitis Research Foundation and both the GENIE (Genetics Education Networking for Innovation and Excellence) team and press office of the University of Leicester to raise public awareness of how meningococci cause disease and how this specific research project could improve our ability to combat meningitis.
Description Genomic Epidemiology and Public Health Genomics
Amount £5,153,712 (GBP)
Funding ID 218505/Z/19/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 07/2020 
End 09/2028
Description MRC IAA
Amount £10,245 (GBP)
Funding ID RM61G1041M49 
Organisation University of Leicester 
Sector Academic/University
Country United Kingdom
Start 03/2024 
End 10/2024
Description Phenotype to genotype: dissecting meningococcal disease and carriage traits
Amount £631,314 (GBP)
Funding ID MR/S009264/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 05/2019 
End 05/2023
Title High Throughput Phenotypic Assays 
Description We have set up methods for storing mid-log phase meningococcal cultures in multi-well plates and for use of these cultures in six phenotypic assays. The assay are growth in BHI liquid media, growth in RPMI liquid media, biofilm formation, lactate dehydrogenase (LDH) activity, adhesion and serum bactericidal activity. The growth assays generate growth curves from which values for the lag period, doubling time and maximal growth are determined. The biofilm assay assesses biofilm formation on peg lids after overnight static incubation. The LDH assays involves measurement of LDH activity after over-night co-culture of meningococcal cells. The adhesion assays measurement bacterial cells adherent to A549 cells after overnight incubation. The serum bactericidal assays utilises IgG- and IgM-depleted human serum and hence measures survival of meningococcal cells to intrinsic complement-activity. We have presented this methodology at the International Pathogenic Neisseria Conference in 2022 and have also had a methods paper accepted for publication that provides the technical details of how to perform these assays. 
Type Of Material Technology assay or reagent 
Year Produced 2021 
Provided To Others? No  
Impact These assays have allowed for comparison of the phenotypes of ~300 isolates of the MenW cc11 and ~200 isolates of the MenY cc23 meningococcal clonal complexes. This data has provided the input for genome wide association testing to link variation to genomic variation or for statistical assays to link phenotypic differences to phase variation expression states. The data has also been stratified by sub-lineage or source (carriage versus disease) to allow for comparison of broad phenotypic differences between groups of strains associated with clonal lineages or with invasive disease and spread in human populations.