Spontaneous point mutations in the capsule synthesis locus leading to structural and functional changes of the capsule in serogroup A meningococcal populations

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

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.IMPORTANCENext-generation sequencing technologies have led to the creation of extensive microbial genome sequence databases for several bacterial pathogens. Mining of these databases is now imperative for unlocking the maximum benefits of these resources. We describe a high-throughput methodology for detecting associations between phenotypic variation in multiple disease-relevant traits and a range of genetic determinants for Neisseria meningitidis, a major causative agent of meningitis and septicemia. Phenotypic variation in 11 disease-related traits was determined for 163 isolates of the hypervirulent ST-11 lineage and linked to specific single-nucleotide polymorphisms, short sequence variants, and phase variation states. Application of machine learning algorithms to our data outputs identified combinatorial phenotypic traits and genetic variants predictive of a disease association. This approach overcomes the limitations of generic meta-data, such as disease versus carriage, and provides an avenue to explore the multi-faceted nature of bacterial disease, carriage, and transmissibility traits.

Generalized Modules for Membrane Antigens as Carrier for Polysaccharides: Impact of Sugar Length, Density, and Attachment Site on the Immune Response Elicited in Animal Models

Nanoparticle systems are being explored for the display of carbohydrate antigens, characterized by multimeric presentation of glycan epitopes and special chemico-physical properties of nano-sized particles. Among them, outer membrane vesicles (OMVs) are receiving great attention, combining antigen presentation with the immunopotentiator effect of the Toll-like receptor agonists naturally present on these systems. In this context, we are testing Generalized Modules for Membrane Antigens (GMMA), OMVs naturally released from Gram-negative bacteria mutated to increase blebbing, as carrier for polysaccharides. Here, we investigated the impact of saccharide length, density, and attachment site on the immune response elicited by GMMA in animal models, using a variety of structurally diverse polysaccharides from different pathogens (i.e., Neisseria meningitidis serogroup A and C, Haemophilus influenzae type b, and streptococcus Group A Carbohydrate and Salmonella Typhi Vi). Anti-polysaccharide immune response was not affected by the number of saccharides per GMMA particle. However, lower saccharide loading can better preserve the immunogenicity of GMMA as antigen. In contrast, saccharide length needs to be optimized for each specific antigen. Interestingly, GMMA conjugates induced strong functional immune response even when the polysaccharides were linked to sugars on GMMA. We also verified that GMMA conjugates elicit a T-dependent humoral immune response to polysaccharides that is strictly dependent on the nature of the polysaccharide. The results obtained are important to design novel glycoconjugate vaccines using GMMA as carrier and support the development of multicomponent glycoconjugate vaccines where GMMA can play the dual role of carrier and antigen. In addition, this work provides significant insights into the mechanism of action of glycoconjugates.

GMMA Is a Versatile Platform to Design Effective Multivalent Combination Vaccines

Technology platforms are an important strategy to facilitate the design, development and implementation of vaccines to combat high-burden diseases that are still a threat for human populations, especially in low- and middle-income countries, and to address the increasing number and global distribution of pathogens resistant to antimicrobial drugs. Generalized Modules for Membrane Antigens (GMMA), outer membrane vesicles derived from engineered Gram-negative bacteria, represent an attractive technology to design affordable vaccines. Here, we show that GMMA, decorated with heterologous polysaccharide or protein antigens, leads to a strong and effective antigen-specific humoral immune response in mice. Importantly, GMMA promote enhanced immunogenicity compared to traditional formulations (e.g., recombinant proteins and glycoconjugate vaccines), without negative impact to the anti-GMMA immune response. Our findings support the use of GMMA as a "plug and play" technology for the development of effective combination vaccines targeting different bugs at the same time.

Metabolic modulation of redox state confounds fish survival against Vibrio alginolyticus infection

Vibrio alginolyticus threatens both humans and marine animals, but hosts respond to V. alginolyticus infection is not fully understood. Here, functional metabolomics was adopted to investigate the metabolic differences between the dying and surviving zebrafish upon V. alginolyticus infection. Tryptophan was identified as the most crucial metabolite, whose abundance was decreased in the dying group but increased in the survival group as compared to control group without infection. Concurrently, the dying zebrafish displayed excessive immune response and produced higher level of reactive oxygen species (ROS). Interestingly, exogenous tryptophan reverted dying rate through metabolome re‐programming, thereby enhancing the survival from V. alginolyticus infection. It is preceded by the following mechanism: tryptophan fluxed into the glycolysis and tricarboxylic acid cycle (TCA cycle), promoted adenosine triphosphate (ATP) production and further increased the generation of NADPH. Meanwhile, tryptophan decreased NADPH oxidation. These together ameliorate ROS, key molecules in excessive immune response. This is further supported by the event that the inhibition of pyruvate metabolism and TCA cycle by inhibitors decreased D. reiro survival. Thus, our data indicate that tryptophan is a key metabolite for the host to fight against V. alginolyticus infection, representing an alternative strategy to treat bacterial infection in an antibiotic‐independent way.

Neisseria meningitidis: using genomics to understand diversity, evolution and pathogenesis

Meningococcal disease remains an important cause of morbidity and death worldwide despite the development and increasing implementation of effective vaccines. Elimination of the disease is hampered by the enormous diversity and antigenic variability of the causative agent, Neisseria meningitidis, one of the most variable bacteria in nature. These features are attained mainly through high rates of horizontal gene transfer and alteration of protein expression through phase variation. The recent availability of whole-genome sequencing (WGS) of large-scale collections of N. meningitidis isolates from various origins, databases to facilitate storage and sharing of WGS data and the concomitant development of effective bioinformatics tools have led to a much more thorough understanding of the diversity of the species, its evolution and population structure and how virulent traits may emerge. Implementation of WGS is already contributing to enhanced epidemiological surveillance and is essential to ascertain the impact of vaccination strategies. This Review summarizes the recent advances provided by WGS studies in our understanding of the biology of N. meningitidis and the epidemiology of meningococcal disease.