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High-throughput phenotype-to-genotype testing of meningococcal carriage and disease isolates detects genetic determinants of disease-relevant phenotypic traits

Farzand, Robeena; Kimani, Mercy W.; Mourkas, Evangelos; Jama, Abdullahi; Clark, Jack L.; De Ste Croix, Megan; Monteith, William M.; Lucidarme, Jay; Oldfield, Neil J.; Turner, David P. J.; Borrow, Ray; Martinez-Pomares, Luisa; Sheppard, Samuel K.; Bayliss, Christopher D.

High-throughput phenotype-to-genotype testing of meningococcal carriage and disease isolates detects genetic determinants of disease-relevant phenotypic traits Thumbnail


Authors

Robeena Farzand

Mercy W. Kimani

Evangelos Mourkas

Abdullahi Jama

Jack L. Clark

Megan De Ste Croix

William M. Monteith

Jay Lucidarme

Ray Borrow

Samuel K. Sheppard

Christopher D. Bayliss



Contributors

Rino Rappuoli
Editor

Abstract

Genome-wide association studies (GWAS) with binary or single phenotype data have successfully identified disease-associated genotypes and determinants of antimicrobial resistance. We describe a novel phenotype-to-genotype approach for a major bacterial pathogen that involves simultaneously testing for associations among multiple disease-related phenotypes and linkages between phenotypic variation and genetic determinants. High-throughput assays quantified variation among 163 Neisseria meningitidis serogroup W ST-11 clonal complex isolates for 11 phenotypic traits. A comparison of carriage and two disease subgroups detected significant differences between groups for eight phenotypic traits. Candidate genotypic testing indicated that indels in csw, a capsular biosynthesis gene, were associated with reduced survival in antibody-depleted heat-inactivated serum. GWAS testing detected 341 significant genetic variants (3 single-nucleotide polymorphisms and 338 unitigs) across all traits except serum bactericidal antibody-depleted assays. Growth traits were associated with variants of capsular biosynthesis genes, carbonic anhydrase, and an iron-uptake system while adhesion-linked variation was in pilC2, marR, and mutS. Multiple phase variation states or combinatorial phasotypes were associated with significant differences in multiple phenotypes. Controlling for group effects through regression and recursive random forest approaches detected group-independent effects for nalP with biofilm formation and fetA with a growth trait. Through random forest testing, nine phenotypes were weakly predictive of MenW:cc11 sub-lineage, original or 2013, for disease isolates while three characteristics separated carriage and disease isolates with >80% accuracy. This study demonstrates the power of combining high-throughput phenotypic testing of pathogenically relevant isolate collections with genomics for identifying genetic determinants of specific disease-relevant phenotypes and the pathobiology of microbial pathogens.

Citation

Farzand, R., Kimani, M. W., Mourkas, E., Jama, A., Clark, J. L., De Ste Croix, M., Monteith, W. M., Lucidarme, J., Oldfield, N. J., Turner, D. P. J., Borrow, R., Martinez-Pomares, L., Sheppard, S. K., & Bayliss, C. D. (2024). High-throughput phenotype-to-genotype testing of meningococcal carriage and disease isolates detects genetic determinants of disease-relevant phenotypic traits. mBio, 15(12), Article e03059-24. https://doi.org/10.1128/mbio.03059-24

Journal Article Type Article
Acceptance Date Oct 10, 2024
Online Publication Date Oct 30, 2024
Publication Date 2024-12
Deposit Date Jun 20, 2025
Publicly Available Date Jun 23, 2025
Journal mBio
Print ISSN 2161-2129
Electronic ISSN 2150-7511
Publisher American Society for Microbiology
Peer Reviewed Peer Reviewed
Volume 15
Issue 12
Article Number e03059-24
DOI https://doi.org/10.1128/mbio.03059-24
Public URL https://nottingham-repository.worktribe.com/output/41369468
Publisher URL https://journals.asm.org/doi/10.1128/mbio.03059-24

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