Outer membrane vesicle (OMV)-based vaccines have been employed worldwide in response to epidemic meningococcal disease outbreaks caused by Neisseria meningitidis. The complex composition of OMVs raises challenges in the identification of antigens which contribute to a protective immune response. Here, we measured total IgG antibody binding profiles to a dedicated antigen microarray using human sera from an open-label Phase II trial (NCT00962624) of 4CMenB (Bexsero), a licensed vaccine containing an OMV component. Significant IgG responses were observed against specific Outer Membrane Proteins (OMPs) from OMV antigens, including FetA, PorB, BamA and PorA. Partial Least Squares Regression was used to correlate IgG antibody reactivity profiles with the human complement-dependent killing of meningococci. We show that this approach is a powerful method to identify the potential contributions of OMV antigens - notably OpcA, FetA, PorA and PorB- towards serum bactericidal activity in human vaccinee serum against indicator strains, a recognised correlate of protection against invasive meningococcal disease.

Gonorrhea, caused by Neisseria gonorrhoeae (GC) represents a significant public health threat that may be mitigated by an effective vaccine. Vaccines containing N. meningitidis outer membrane vesicles (OMVs), such as 4CMenB, demonstrated moderate effectiveness in preventing GC infections. Here, we developed NgG, an investigational GC vaccine based on Generalized Modules for Membrane Antigens (GMMA). NgG includes genetically detoxified OMVs from the FA1090 strain, engineered to reduce endotoxin activity and limit immune interference. NgG induced a robust immune response in mice and outperformed the comparator vaccine 4CMenB in several serological and functional tests. Immunization with GMMA from a FA1090 mutant, where major oligosaccharide epitopes are incomplete or absent, revealed that NgG lipooligosaccharide plays a major role in the breadth of functional responses, with protein component also contributing in some GC strains. These results suggest that NgG has the potential to block GC infection through various mechanisms, supporting further vaccine development.

Whole genome sequencing of bacteria is important to enable strain classification. Using entire genomes as an input to machine learning (ML) models would allow rapid classification of strains while using information from multiple genetic elements. We developed a “bag-of-words” approach to encode, using SentencePiece or k-mer tokenization, entire bacterial genomes and analyze these with ML. Initial model selection identified SentencePiece with 8,000 and 32,000 words as the best approach for genome tokenization. We then classified in Neisseria meningitidis genomes the capsule B group genotype with 99.6% accuracy and the multifactor invasive phenotype with 90.2% accuracy, in an independent test set. Subsequently, in silico knockouts of 2,808 genes confirmed that the ML model predictions aligned with our current understanding of the underlying biology. To our knowledge, this is the first ML method using entire bacterial genomes to classify strains and identify genes considered relevant by the classifier.

Background Chronic obstructive pulmonary disease (COPD) is a lung disease characterised by airflow-limiting inflammation and mucus production. Acute exacerbations are a major cause of COPD-related morbidity and mortality and are mostly associated with bacterial or viral infections. A vaccine targeting non-typeable Haemophilus influenzae (NTHi) and Moraxella catarrhalis (Mcat), the main bacteria associated with exacerbations, was tested in a Phase 2 trial. We assessed “ex-vivo” expression of vaccine candidate and housekeeping genes pd , pe , pilA , gapA , ompP6 of NTHi, and uspA2 , parE , polA of Mcat in sputum samples of COPD patients and determined whether expression of the vaccine candidate genes pd , pe , pilA (NTHi) and uspA2 (Mcat) differed between stable and exacerbation samples. Methods A single-centre, prospective, observational cohort study was conducted where 123 COPD patients were seen on enrolment, followed monthly for 2 years, and reviewed after onset of acute exacerbations. We selected 69 patients with sputum samples positive for NTHi or Mcat by PCR during at least one stable and one exacerbation visit. mRNA was isolated from the sputum, and expression of NTHi and Mcat genes was analysed with RT-PCR. Statistical analyses compared mRNA concentrations between stable and exacerbation samples and in relationship to COPD severity and exacerbation frequency. Results The vaccine candidate genes were variably expressed in sputum samples, suggesting they are expressed in the lung. Absolute and relative expression of all NTHi vaccine candidate genes and Mcat uspA2 were similar between exacerbation and stable samples. Expression of pd and pilA was slightly associated with the number of exacerbations in the year before enrolment, and uspA2 with the disease severity status at enrolment. Conclusions The NTHi-Mcat vaccine candidate genes were expressed in sputum samples, and each gene had a specific level of expression. No statistically significant differences in gene expression were detectable between stable and exacerbation samples. However, the history of COPD exacerbations was slightly associated with the expression of pd , pilA and uspA2 . Trial registration NCT01360398 ( https://www.clinicaltrials.gov ) Graphical abstract

Meningococcal (Neisseria meningitidis) serogroup B (MenB) strain antigens are diverse and a limited number of strains can be evaluated using the human serum bactericidal antibody (hSBA) assay. The genetic Meningococcal Antigen Typing System (gMATS) was developed to predict the likelihood of coverage for large numbers of isolates by the 4CMenB vaccine, which includes antigens Neisseria adhesin A (NadA), Neisserial Heparin-Binding Antigen (NHBA), factor H-binding protein (fHbp), and Porin A (PorA). In this study, we characterized by whole-genome analyses 284 invasive MenB isolates collected from 2010 to 2014 by the Argentinian National Laboratories Network (52-61 isolates per year). Strain coverage was estimated by gMATS on all isolates and by hSBA assay on 74 randomly selected isolates, representative of the whole panel. The four most common clonal complexes (CCs), accounting for 81.3% of isolates, were CC-865 (75 isolates, 26.4%), CC-32 (59, 20.8%), CC-35 (59, 20.8%), and CC-41/44 (38, 13.4%). Vaccine antigen genotyping showed diversity. The most prevalent variants/peptides were fHbp variant 2, NHBA peptides 24, 21, and 2, and PorA variable region 2 profiles 16-36 and 14. The nadA gene was present in 66 (23.2%) isolates. Estimated strain coverage by hSBA assay showed 78.4% of isolates were killed by pooled adolescent sera, and 51.4% and 64.9% (based on two different thresholds) were killed by pooled infant sera. Estimated coverage by gMATS (61.3%; prediction interval: 55.5%, 66.7%) was consistent with the infant hSBA assay results. Continued genomic surveillance is needed to evaluate the persistence of major MenB CCs in Argentina.

The 4-component meningococcal serogroup B (MenB) vaccine, 4CMenB, the first broadly protective, protein-based MenB vaccine to be licensed, is now registered in more than 50 countries worldwide. Real-world evidence (RWE) from the last decade confirms its effectiveness and impact, with infant immunization programs showing vaccine effectiveness of 71–95% against invasive MenB disease and cross-protection against non-B serogroups, including a 69% decrease in serogroup W cases in 4CMenB-eligible cohorts in England. RWE from different countries also demonstrates the potential for additional moderate protection against gonorrhea in adolescents. The real-world safety profile of 4CMenB is consistent with prelicensure reports. Use of the endogenous complement human serum bactericidal antibody (enc-hSBA) assay against 110 MenB strains may enable assessment of the immunological effectiveness of multicomponent MenB vaccines in clinical trial settings. Equitable access to 4CMenB vaccination is required to better protect all age groups, including older adults, and vulnerable groups through comprehensive immunization policies.

ABSTRACT Neisseria meningitidis serogroup B (NmB) strains have diverse antigens, necessitating methods for predicting meningococcal serogroup B (MenB) vaccine strain coverage. The genetic Meningococcal Antigen Typing System (gMATS), a correlate of MATS estimates, predicts strain coverage by the 4-component MenB (4CMenB) vaccine in cultivable and non-cultivable NmB isolates. In Taiwan, 134 invasive, disease-causing NmB isolates were collected in 2003–2020 (23.1%, 4.5%, 5.2%, 29.8%, and 37.3% from individuals aged ≤11 months, 12–23 months, 2–4 years, 5–29 years, and ≥30 years, respectively). NmB isolates were characterized by whole-genome sequencing and vaccine antigen genotyping, and 4CMenB strain coverage was predicted using gMATS. Analysis of phylogenetic relationships with 502 global NmB genomes showed that most isolates belonged to three global hyperinvasive clonal complexes: ST-4821 (27.6%), ST-32 (23.9%), and ST-41/44 (14.9%). Predicted strain coverage by gMATS was 62.7%, with 27.6% isolates covered, 2.2% not covered, and 66.4% unpredictable by gMATS. Age group coverage point estimates ranged from 42.9% (2–4 years) to 66.1% (≤11 months). Antigen coverage estimates and percentages predicted as covered/not covered were highly variable, with higher estimates for isolates with one or more gMATS-positive antigens than for isolates positive for one 4CMenB antigen. In conclusion, this first study on NmB strain coverage by 4CMenB in Taiwan shows 62.7% coverage by gMATS, with predictable coverage for 29.8% of isolates. These could be underestimated since the gMATS calculation does not consider synergistic mechanisms associated with simultaneous antibody binding to multiple targets elicited by multicomponent vaccines or the contributions of minor outer membrane vesicle vaccine components. IMPORTANCE Meningococcal diseases, caused by the bacterium Neisseria meningitidis (meningococcus), include meningitis and septicemia. Although rare, invasive meningococcal disease is often severe and can be fatal. Nearly all cases are caused by six meningococcal serogroups (types), including meningococcal serogroup B. Vaccines are available against meningococcal serogroup B, but the antigens targeted by these vaccines have highly variable genetic features and expression levels, so the effectiveness of vaccination may vary depending on the strains circulating in particular countries. It is therefore important to test meningococcal serogroup B strains isolated from specific populations to estimate the percentage of bacterial strains that a vaccine can protect against (vaccine strain coverage). Meningococcal isolates were collected in Taiwan between 2003 and 2020, of which 134 were identified as serogroup B. We did further investigations on these isolates, including using a method (called gMATS) to predict vaccine strain coverage by the 4-component meningococcal serogroup B vaccine (4CMenB).

Chronic obstructive pulmonary disease (COPD) is an etiologically complex disease characterized by acute exacerbations and stable phases. We aimed to identify biological functions modulated in specific COPD conditions, using whole blood samples collected in the AERIS clinical study (NCT01360398). Considered conditions were exacerbation onset, severity of airway obstruction, and presence of respiratory pathogens in sputum samples. With an integrative multi-network gene community detection (MNGCD) approach, we analyzed expression profiles to identify communities of correlated genes. The approach combined different layers of gene interactions for each explored condition/subset of samples: gene expression similarity, protein-protein interactions, transcription factors, and microRNAs validated regulons. Heme metabolism, interferon-alpha, and interferon-gamma pathways were modulated in patients at both exacerbation and stable-state visits, but with the involvement of distinct sets of genes. An important gene community was enriched with G2M checkpoint, E2F targets, and mitotic spindle pathways during exacerbation. Targets of TAL1 regulator and hsa-let-7b - 5p microRNA were modulated with increasing severity of airway obstruction. Bacterial infections with Moraxella catarrhalis and, particularly, Haemophilus influenzae triggered a specific cellular and inflammatory response in acute exacerbations, indicating an active reaction of the host to infections. In conclusion, COPD is a complex multifactorial disease that requires in-depth investigations of its causes and features during its evolution and whole blood transcriptome profiling can contribute to capturing some relevant regulatory mechanisms associated with this disease. In this work, we explored multi-network modeling that integrated diverse layers of regulatory gene networks and enhanced our comprehension of the biological functions implicated in the COPD pathogenesis.

The ability of Neisseria meningitidis Outer Membrane Vesicles (OMV) to induce protective responses in humans is well established and mainly attributed to Porin A (PorA). However, the contribution of additional protein antigens to protection remains to be elucidated. In this study we dissected the immunogenicity of antigens originating from the OMV component of the 4CMenB vaccine in mice and humans. We collected functional data on a panel of strains for which bactericidal responses to 4CMenB in infants was attributable to the OMV component and evaluated the role of 30 OMV-specific protein antigens in cross-coverage. By using tailor-made protein microarrays, the immunosignature of OMV antigens was determined. Three of these proteins, OpcA, NspA, and PorB, triggered mouse antibodies that were bactericidal against several N. meningitidis strains. Finally, by genetic deletion and/or serum depletion studies, we demonstrated the ability of OpcA and PorB to induce functional immune responses in infant sera after vaccination. In conclusion, while confirming the role of PorA in eliciting protective immunity, we identified two OMV antigens playing a key role in protection of infants vaccinated with the 4CMenB vaccine against different N. meningitidis serogroup B strains.

Introduction: Neisseria meningitidis serogroup B (NmB) antigens are inherently diverse with variable expression among strains. Prediction of meningococcal B (MenB) vaccine effectiveness therefore requires an assay suitable for use against large panels of epidemiologically representative disease causing NmB strains. Traditional serum bactericidal antibody assay using exogenous human complement (hSBA) is limited to the quantification of MenB vaccine immunogenicity on a small number of indicator strains.Areas covered: Additional and complementary methods for assessing strain coverage developed previously include the Meningococcal Antigen Typing System (MATS), Meningococcal Antigen Surface Expression (MEASURE) assay, and genotyping approaches, but these do not estimate vaccine effectiveness. We provide a narrative review of these methods, highlighting a more recent approach involving the hSBA assay in conjunction with expanded NmB strain panels: hSBA assay using endogenous complement in each vaccinated person's serum (enc-hSBA) against a 110-strain NmB panel and the traditional hSBA assay against 14 (4 + 10) NmB strains.Expert opinion: The enc-hSBA is a highly standardized, robust method that can be used in clinical trials to measure the immunological effectiveness of MenB vaccines under conditions that mimic real-world settings as closely as possible, through the use of endogenous complement and a diverse, epidemiologically representative panel of NmB strains.

Predictions of vaccine efficacy against Neisseria meningitidis serogroup B (NmB) disease are hindered by antigenic variability, limiting the representativeness of individual NmB isolates. A qualitative human serum bactericidal assay using endogenous complements of individual subjects (enc-hSBA) enables large panels of NmB isolates to be tested. A 110-isolate panel was randomly selected from 442 invasive NmB isolates from United States cases reported to the Centers for Disease Control (CDC) from 2000 to 2008. Typing analyses confirmed the 110-isolate panel is representative of the 442 isolates. The genetic features of the 110-isolate panel were compared against over 4,200 invasive NmB isolates collected from 2000 to 2018 in the United States, Australia, Canada, and nine European countries. Clonal complexes in the 110-isolate panel are also present in each geographical region; cumulative percentages show that these account for around 81% of the clonal complexes found in NmB isolates in other panels. For the antigens (fHbp, NHBA, PorA1.4, NadA) included in the currently licensed meningococcal serogroup B (MenB) vaccines, specifically considering the presence of at least one antigen with a matched genotype, the 110-isolate panel represents approximately 89% of the NmB isolates circulating worldwide, ranging from 87% for the European isolates to 95% and 97% for NmB isolates in the United States and Australia, respectively. The 110-isolate panel includes the most prevalent clonal complexes and genetic variants of MenB vaccine antigens found in a multinational collection of invasive NmB isolates. This panel is useful for assessing the efficacy of MenB vaccines in clinical trials worldwide. IMPORTANCE Neisseria meningitidis serogroup B (NmB) is a major cause of invasive meningococcal disease (IMD). Predicting the effectiveness of vaccines against NmB is difficult because NmB is an uncommon disease and because antigens targeted by meningococcal serogroup B (MenB) vaccines have highly variable genetic features and expression levels. Therefore, a large number of NmB isolates from different regions would need to be tested to comprehensively assess vaccine effectiveness. We examined a panel of 110 isolates obtained from NmB IMD cases in the United States and compared the genetic features of this panel with those of panels from different countries around the world. We found the 110-isolate panel included the most common clonal complexes and genetic variants of MenB vaccine antigens that exist in the global collections of invasive NmB isolates. This confirms the value of the NmB 110-isolate panel in understanding the effectiveness of MenB vaccines in clinical trials worldwide.

Neisseria meningitidis is a strictly human pathogen and is the major cause of septicemia and meningitis worldwide. Factor H binding protein (fHbp) is a meningococcal surface-exposed lipoprotein that binds the human Complement factor H allowing the bacterium to evade the host innate immune response. FHbp is also a key antigen in two vaccines against N . meningitidis serogroup B. Although the fHbp gene is present in most circulating meningococcal strains, level of fHbp expression varies among isolates and has been correlated to differences in promoter sequences upstream of the gene. Here we elucidated the sequence determinants that control fHbp expression in globally circulating strains. We analyzed the upstream f Hbp i ntergenic r egion (fIR) of more than 5800 strains representative of the UK circulating isolates and we identified eleven fIR sequence alleles which represent 88% of meningococcal strains. By engineering isogenic recombinant strains where fHbp expression was under the control of each of the eleven fIR alleles, we confirmed that the fIR sequence determines a specific and distinct level of expression. Moreover, we identified the molecular basis for variation in expression through polymorphisms within key regulatory regions that are known to affect fHbp expression. We experimentally established three expression groups, high–medium–low, that correlated directly with the susceptibility to killing mediated by anti-fHbp antibodies and the ability of the meningococcal strain to survive within human serum. By using this sequence classification and information about the variant, we predicted fHbp expression in the panel of UK strains and we observed that strains with higher expressing fIR alleles are more likely associated with invasive disease. Overall, our findings can contribute to understand and predict vaccine coverage mediated by fHbp as well as to shed light on the role of this virulence factor in determining an invasive phenotype.

Staphylococcus aureus is a common human commensal and the leading cause of diverse infections. To identify distinctive parameters associated with infection and colonization, we compared the immune and inflammatory responses of patients with a diagnosis of invasive S. aureus disease to healthy donors. We analyzed the inflammatory responses founding a pattern of distinctive cytokines significantly higher in the patients with invasive disease. The measure of antibody levels revealed a wide antibody responsiveness from all subjects to most of the antigens, with significantly higher response for some antigens in the invasive patients compared to control. Moreover, functional antibodies against toxins distinctively associated with the invasive disease. Finally, we examined the genomic variability of isolates, showing no major differences in genetic distribution compared to a panel of representative strains. Overall, our study shows specific signatures of cytokines and functional antibodies in patients with different primary invasive diseases caused by S. aureus. These data provide insight into human responses towards invasive staphylococcal infections and are important for guiding the identification of novel preventive and therapeutic interventions against S. aureus.

Meningococcal serogroup B (MenB) accounts for an important proportion of invasive meningococcal disease (IMD). The 4-component vaccine against MenB (4CMenB) is composed of factor H binding protein (fHbp), neisserial heparin-binding antigen (NHBA), Neisseria adhesin A (NadA), and outer membrane vesicles of the New Zealand strain with Porin 1.4. A meningococcal antigen typing system (MATS) and a fully genomic approach, genetic MATS (gMATS), were developed to predict coverage of MenB strains by 4CMenB. We characterized 520 MenB invasive disease isolates collected over a 5-year period (January 2007-December 2011) from all Australian states/territories by multilocus sequence typing and estimated strain coverage by 4CMenB. The clonal complexes most frequently identified were ST-41/44 CC/Lineage 3 (39.4%) and ST-32 CC/ET-5 CC (23.7%). The overall MATS predicted coverage was 74.6% (95% coverage interval: 61.1%-85.6%). The overall gMATS prediction was 81.0% (lower-upper limit: 75.0-86.9%), showing 91.5% accuracy compared with MATS. Overall, 23.7% and 13.1% (MATS) and 26.0% and 14.0% (gMATS) of isolates were covered by at least 2 and 3 vaccine antigens, respectively, with fHbp and NHBA contributing the most to coverage. When stratified by year of isolate collection, state/territory and age group, MATS and gMATS strain coverage predictions were consistent across all strata. The high coverage predicted by MATS and gMATS indicates that 4CMenB vaccination may have an impact on the burden of MenB-caused IMD in Australia. gMATS can be used in the future to monitor variations in 4CMenB strain coverage over time and geographical areas even for non-culture confirmed IMD cases.

The 4CMenB, a protein-based vaccine, was licensed in Europe in 2013 against invasive meningococcal disease caused by serogroup B and is currently implemented in several countries although according to different national strategies. Isolate coverage estimation is required as vaccine-targeted antigens may vary among isolates over time. Several phenotypic and genotypic methods have been developed to predict strain coverage by scoring the expression and cross-reactivity of vaccine antigens using the Meningococcal Antigen Typing system (MATS), by the genetic correlation of alleles encoding these antigens and MATS expression data (gMATS) and by the Meningococcal Deduced Vaccine Antigen Reactivity (MenDeVAR). We applied these approaches on meningococcal B isolates in France and compared two epidemiological years, 2013-2014 and 2018-2019. A strong correlation was observed between MATS data that were generated for the year 2013-2014 and the gMATS data extracted from whole genome sequencing. gMATS and MenDeVAR were next used to compare the two years. Using gMATS, the overall coverage was 77.2% (lower limit (LL)-upper limit (UL) 66.7-87.7) and 70.7% (LL-UL 61.5-80.0) for the two years, respectively. The reduction in coverage between the two years is mainly driven by the reduction of alleles exactly matching the vaccine antigens. A high number of unpredictable isolates was observed using the MenDeVAR and was due to lack of MATS information for new or rare alleles in particular for the year 2018-2019. Our data underline the need of continuous surveillance of strain coverage and the importance of generating phenotypic MATS data to update the genetic approaches of prediction.

Invasive meningococcal disease (IMD) caused by Neisseria meningitidis is a significant cause of morbidity and mortality worldwide. In Finland, the incidence rate of IMD is low, with meningococcal serogroup B (MenB) accounting for around one-third of IMD cases annually. The aim of this study was to investigate the genetic variability of invasive MenB isolates collected in Finland between 2010 and 2017 (n = 81), including the genes encoding the 4-component MenB vaccine (4CMenB; Bexsero; GSK) antigens and their promoters, and to evaluate the 4CMenB potential coverage. Whole-genome sequencing was performed. The meningococcal antigen typing system (MATS) was used to characterize MenB isolates and predict the potential coverage of 4CMenB. MATS was complemented by genetic MATS (gMATS) through association of antigen genotyping and phenotypic MATS results. Multilocus sequence typing revealed predominance of the ST-41/44 clonal complex among which sequence type (ST)-303 was the most common and was predicted to be covered by 4CMenB. Of the 4 major vaccine antigens, the factor H-binding protein variant 1, neisserial heparin binding antigen peptide 2, and the PorA P1.4 antigen were predominant, whereas Neisseria adhesin A was present in only 4% of the 81 isolates. MATS and gMATS 4CMenB strain coverage predictions were 78% and 86%, respectively, in a subpanel of 60 isolates collected during 2010 to 2014, with a gMATS prediction of 84% for all 81 isolates. The results suggest that 4CMenB could reduce the burden of IMD in Finland and that gMATS could be applied to monitor vaccine strain coverage and predict vaccine effectiveness. IMPORTANCE 4CMenB is a 4-component vaccine used against invasive meningococcal disease (IMD) caused by Neisseria meningitidis serogroup B (MenB). We investigated the genetic variability of MenB in Finland and evaluated 4CMenB strain coverage by 2 different methods: MATS (meningococcal antigen typing system) and gMATS (genetic MATS). In a set of MenB isolates, 78% (MATS) and 86% (gMATS) were predicted as covered by 4CMenB, suggesting that use of 4CMenB would help reduce IMD incidence in Finland. MATS has been used in 13 countries worldwide, generating information on phenotypic characteristics that could infer protection by 4CMenB. Based on these data and genetic information, gMATS coverage predictions can be made. gMATS predicts coverage consistent with MATS for about 94% of tested strains. Unlike MATS, gMATS does not require live isolates, thus allowing the analysis also of noncultivable strains, making the coverage predictions more accurate. Therefore, gMATS can replace MATS to assess 4CMenB coverage, including in regions with no prior MATS data.

Genomic surveillance of bacterial meningitis pathogens is essential for effective disease control globally, enabling identification of emerging and expanding strains and consequent public health interventions. While there has been a rise in the use of whole genome sequencing, this has been driven predominately by a subset of countries with adequate capacity and resources. Global capacity to participate in surveillance needs to be expanded, particularly in low and middle-income countries with high disease burdens. In light of this, the WHO-led collaboration, Defeating Meningitis by 2030 Global Roadmap, has called for the establishment of a Global Meningitis Genome Partnership that links resources for: N. meningitidis (Nm), S. pneumoniae (Sp), H. influenzae (Hi) and S. agalactiae (Sa) to improve worldwide co-ordination of strain identification and tracking. Existing platforms containing relevant genomes include: PubMLST: Nm (31,622), Sp (15,132), Hi (1935), Sa (9026); The Wellcome Sanger Institute: Nm (13,711), Sp (> 24,000), Sa (6200), Hi (1738); and BMGAP: Nm (8785), Hi (2030). A steering group is being established to coordinate the initiative and encourage high-quality data curation. Next steps include: developing guidelines on open-access sharing of genomic data; defining a core set of metadata; and facilitating development of user-friendly interfaces that represent publicly available data. (C) 2020 The Authors. Published by Elsevier Ltd on behalf of The British Infection Association.

BACKGROUND:The Meningococcal Antigen Typing System (MATS) was developed to identify meningococcus group B strains with a high likelihood of being covered by the 4CMenB vaccine, but is limited by the requirement for viable isolates from culture-confirmed cases. We examined if antigen genotyping could complement MATS in predicting strain coverage by the 4CMenB vaccine. METHODS:From a panel of 3912 MATS-typed invasive meningococcal disease isolates collected in England and Wales in 2007-2008, 2014-2015 and 2015-2016, and in 16 other countries in 2000-2015, 3481 isolates were also characterized by antigen genotyping. Individual associations between antigen genotypes and MATS coverage for each 4CMenB component were used to define a genetic MATS (gMATS). gMATS estimates were compared with England and Wales human complement serum bactericidal assay (hSBA) data and vaccine effectiveness (VE) data from England. RESULTS:Overall, 81% of the strain panel had genetically predictable MATS coverage, with 92% accuracy and highly concordant results across national panels (Lin's accuracy coefficient, 0.98; root-mean-square deviation, 6%). England and Wales strain coverage estimates were 72-73% by genotyping (66-73% by MATS), underestimating hSBA values after four vaccine doses (88%) and VE after two doses (83%). The gMATS predicted strain coverage in other countries was 58-88%. CONCLUSIONS:gMATS can replace MATS in predicting 4CMenB strain coverage in four out of five cases, without requiring a cultivable isolate, and is open to further improvement. Both methods underestimated VE in England. Strain coverage predictions in other countries matched or exceeded England and Wales estimates.

BACKGROUND:Multi-locus sequence typing (MLST) is a standard typing technique used to associate a sequence type (ST) to a bacterial isolate. When the output of whole genome sequencing (WGS) of a sample is available the ST can be assigned directly processing the read-set. Current approaches employ reads mapping (SRST2) against the MLST loci, k-mer distribution (stringMLST), selective assembly (GRAbB) or whole genome assembly (BIGSdb) followed by BLASTn sequence query. Here we present STRAIN (ST Reduced Assembly IdentificatioN), an R package that implements a hybrid strategy between assembly and mapping of the reads to assign the ST to an isolate starting from its read-sets.RESULTS:Analysis of 540 publicly accessible Illumina read sets showed STRAIN to be more accurate at correct allele assignment and new alleles identification compared to SRTS2, stringMLST and GRAbB. STRAIN assigned correctly 3666 out of 3780 alleles (capability to identify correct alleles 97%) and, when presented with samples containing new alleles, identified them in 3730 out of 3780 STs (capability to identify new alleles 98.7%) of the cases. On the same dataset the other tested tools achieved lower capability to identify correct alleles (from 28.5 to 96.9%) and lower capability to identify new alleles (from 1.1 to 97.1%).CONCLUSIONS:STRAIN is a new accurate method to assign the alleles and ST to an isolate by processing the raw reads output of WGS. STRAIN is also able to retrieve new allele sequences if present. Capability to identify correct and new STs/alleles, evaluated on a benchmark dataset, are higher than other existing methods. STRAIN is designed for single allele typing as well as MLST. Its implementation in R makes allele and ST assignment simple, direct and prompt to be integrated in wider pipeline of downstream bioinformatics analyses.