Prediction by genetic MATS of 4CMenB vaccine strain coverage of invasive meningococcal serogroup B isolates circulating in Taiwan between 2003 and 2020.

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.IMPORTANCEMeningococcal 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).

Classification of Neisseria meningitidis genomes with a bag-of-words approach and machine learning.

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.

Ex-vivo RNA expression analysis of vaccine candidate genes in COPD sputum samples.

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 ).

Use of expanded Neisseria meningitidis serogroup B panels with the serum bactericidal antibody assay for the evaluation of meningococcal B vaccine effectiveness.

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.

Meningococcal disease refers to illnesses caused by the bacterium Neisseria meningitidis (meningococcus), including infections of the brain lining and spinal cord (meningitis) and bloodstream (septicemia). It is rare but often severe and can be deadly. Invasive meningococcal disease can be prevented through vaccination. Nearly all cases are caused by six serogroups (types) of meningococci, including meningococcal serogroup B. Vaccines are available against meningococcal serogroup B but, because of the uncommonness of the disease, standard clinical trials could not be performed to prove these vaccines are effective. Instead, an indirect measure, called the 'hSBA assay' (serum bactericidal antibody assay using human complement), is used to measure the ability of vaccines to provide protection against specific N. meningitidis strains that have antigens (substances that cause the immune system to react) sharing characteristics with components of the vaccines. However, meningococcal serogroup B strains are diverse in the genetic composition and expression of vaccine antigens. Hence, a large number of N. meningitidis serogroup B strains would have to be tested to make sure that the vaccine is effective against these strains. This is not feasible using the traditional hSBA assay, which requires a human complement (a protein system, which is part of the immune system) that has not come from the vaccinated person and is difficult and time-consuming to source. Recently, an alternative hSBA assay was developed that uses the complement present in each vaccinated person's blood (endogenous complement) and which overcomes these challenges. By allowing testing against a broad panel of N. meningitidis serogroup B strains, this new assay may enable a more accurate estimation of the effectiveness of vaccines against serogroup B meningococci.

OpcA and PorB are novel bactericidal antigens of the 4CMenB vaccine in mice and humans.

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.

Genetic Features of a Representative Panel of 110 Meningococcal B Isolates to Assess the Efficacy of Meningococcal B Vaccines.

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.

Evolution of strain coverage by the multicomponent meningococcal serogroup B vaccine (4CMenB) in France.

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.

Dissecting the Human Response to Staphylococcus aureus Systemic Infections.

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.

High coverage of diverse invasive meningococcal serogroup B strains by the 4-component vaccine 4CMenB in Australia, 2007-2011: Concordant predictions between MATS and genetic MATS.

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.

Deconvolution of intergenic polymorphisms determining high expression of Factor H binding protein in meningococcus and their association with invasive disease.

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 fHbp intergenic region (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.

Genomic Characterization of Invasive Meningococcal Serogroup B Isolates and Estimation of 4CMenB Vaccine Coverage in Finland.

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.

The global meningitis genome partnership.

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.

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

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.

Genetic Meningococcal Antigen Typing System (gMATS): A genotyping tool that predicts 4CMenB strain coverage worldwide.

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.

Predicted Strain Coverage of a New Meningococcal Multicomponent Vaccine (4CMenB) in Spain: Analysis of the Differences with Other European Countries.

BACKGROUND: A novel meningococcal multicomponent vaccine, 4CMenB (Bexsero®), has been approved in Europe, Canada, Australia and US. The potential impact of 4CMenB on strain coverage is being estimated by using Meningococcal Antigen Typing System (MATS), an ELISA assay which measures vaccine antigen expression and diversity in each strain. Here we show the genetic characterization and the 4CMenB potential coverage of Spanish invasive strains (collected during one epidemiological year) compared to other European countries and discuss the potential reasons for the lower estimate of coverage in Spain. MATERIAL AND METHODS: A panel of 300 strains, a representative sample of all serogroup B Neisseria meningitidis notified cases in Spain from 2009 to 2010, was characterized by multilocus sequence typing (MLST) and FetA variable region determination. 4CMenB vaccine antigens, PorA, factor H binding protein (fHbp), Neisseria Heparin Binding Antigen (NHBA) and Neisserial adhesin A (NadA) were molecularly typed by sequencing. PorA coverage was assigned to strain with VR2 = 4. The levels of expression and cross-reactivity of fHbp, NHBA and NadA were analyzed using MATS ELISA. FINDINGS: Global estimated strain coverage by MATS was 68.67% (95% CI: 47.77-84.59%), with 51.33%, 15.33% and 2% of strains covered by one, two and three vaccine antigens, respectively. The predicted strain coverage by individual antigens was: 42% NHBA, 36.33% fHbp, 8.33% PorA and 1.33% NadA. Coverage within the most prevalent clonal complexes (cc) was 70.37% for cc 269, 30.19% for cc 213 and 95.83% for cc 32. CONCLUSIONS: Clonal complexes (cc) distribution accounts for variations in strain coverage, so that country-by-country investigations of strain coverage and cc prevalence are important. Because the cc distribution could also vary over time, which in turn could lead to changes in strain coverage, continuous detailed surveillance and monitoring of vaccine antigens expression is needed in those countries where the multicomponent vaccine is introduced. This is really important in countries like Spain where most of the strains are predicted to be covered by only one vaccine antigen and the chance for escape mutants to emerge with vaccine use is higher. Based on the observed data, cc213 should receive special attention as it is associated with low predicted strain coverage, and has recently emerged in Spain.

Expression of factor H binding protein in meningococcal strains can vary at least 15-fold and is genetically determined.

Factor H binding protein (fHbp) is a lipoprotein of Neisseria meningitidis important for the survival of the bacterium in human blood and a component of two recently licensed vaccines against serogroup B meningococcus (MenB). Based on 866 different amino acid sequences this protein is divided into three variants or two families. Quantification of the protein is done by immunoassays such as ELISA or FACS that are susceptible to the sequence variation and expression level of the protein. Here, selected reaction monitoring mass spectrometry was used for the absolute quantification of fHbp in a large panel of strains representative of the population diversity of MenB. The analysis revealed that the level of fHbp expression can vary at least 15-fold and that variant 1 strains express significantly more protein than variant 2 or variant 3 strains. The susceptibility to complement-mediated killing correlated with the amount of protein expressed by the different meningococcal strains and this could be predicted from the nucleotide sequence of the promoter region. Finally, the absolute quantification allowed the calculation of the number of fHbp molecules per cell and to propose a mechanistic model of the engagement of C1q, the recognition component of the complement cascade.

PIPE-chipSAD: A Pipeline for the Analysis of High Density Arrays of Bacterial Transcriptomes.

PIPE-chipSAD is a pipeline for bacterial transcriptome studies based on high-density microarray experiments. The main algorithm chipSAD, integrates the analysis of the hybridization signal with the genomic position of probes and identifies portions of the genome transcribing for mRNAs. The pipeline includes a procedure, align-chipSAD, to build a multiple alignment of transcripts originating in the same locus in multiple experiments and provides a method to compare mRNA expression across different conditions. Finally, the pipeline includes anno-chipSAD a method to annotate the detected transcripts in comparison to the genome annotation. Overall, our pipeline allows transcriptional profile analysis of both coding and non-coding portions of the chromosome in a single framework. Importantly, due to its versatile characteristics, it will be of wide applicability to analyse, not only microarray signals, but also data from other high throughput technologies such as RNA-sequencing. The current PIPE-chipSAD implementation is written in Python programming language and is freely available at https://github.com/silviamicroarray/chipSAD.

Dual RNA-seq of Nontypeable Haemophilus influenzae and Host Cell Transcriptomes Reveals Novel Insights into Host-Pathogen Cross Talk.

UNLABELLED: The ability to adhere and adapt to the human respiratory tract mucosa plays a pivotal role in the pathogenic lifestyle of nontypeable Haemophilus influenzae (NTHi). However, the temporal events associated with a successful colonization have not been fully characterized. In this study, by reconstituting the ciliated human bronchial epithelium in vitro, we monitored the global transcriptional changes in NTHi and infected mucosal epithelium simultaneously for up to 72 h by dual RNA sequencing. The initial stage of colonization was characterized by the binding of NTHi to ciliated cells. Temporal profiling of host mRNA signatures revealed significant dysregulation of the target cell cytoskeleton elicited by bacterial infection, with a profound effect on the intermediate filament network and junctional complexes. In response to environmental stimuli of the host epithelium, NTHi downregulated its central metabolism and increased the expression of transporters, indicating a change in the metabolic regime due to the availability of host substrates. Concurrently, the oxidative environment generated by infected cells instigated bacterial expression of stress-induced defense mechanisms, including the transport of exogenous glutathione and activation of the toxin-antitoxin system. The results of this analysis were validated by those of confocal microscopy, Western blotting, Bio-plex, and real-time quantitative reverse transcription-PCR (qRT-PCR). Notably, as part of our screening for novel signatures of infection, we identified a global profile of noncoding transcripts that are candidate small RNAs (sRNAs) regulated during human host infection in Haemophilus species. Our data, by providing a robust and comprehensive representation of the cross talk between the host and invading pathogen, provides important insights into NTHi pathogenesis and the development of efficacious preventive strategies. IMPORTANCE: Simultaneous monitoring of infection-linked transcriptome alterations in an invading pathogen and its target host cells represents a key strategy for identifying regulatory responses that drive pathogenesis. In this study, we report the progressive events of NTHi colonization in a highly differentiated model of ciliated bronchial epithelium. Genome-wide transcriptome maps of NTHi during infection provided mechanistic insights into bacterial adaptive responses to the host niche, with modulation of the central metabolism as an important signature of the evolving milieu. Our data indicate that infected epithelia respond by substantial alteration of the cytoskeletal network and cytokine repertoire, revealing a dynamic cross talk that is responsible for the onset of inflammation. This work significantly enhances our understanding of the means by which NTHi promotes infection on human mucosae and reveals novel strategies exploited by this important pathogen to cause invasive disease.

Global transcriptome analysis reveals small RNAs affecting Neisseria meningitidis bacteremia.

Most bacterial small RNAs (sRNAs) are post-transcriptional regulators involved in adaptive responses, controlling gene expression by modulating translation or stability of their target mRNAs often in concert with the RNA chaperone Hfq. Neisseria meningitides, the leading cause of bacterial meningitis, is able to adapt to different host niches during human infection. However, only a few sRNAs and their functions have been fully described to date. Recently, transcriptional expression profiling of N. meningitides in human blood ex vivo revealed 91 differentially expressed putative sRNAs. Here we expanded this analysis by performing a global transcriptome study after exposure of N. meningitides to physiologically relevant stress signals (e.g. heat shock, oxidative stress, iron and carbon source limitation). and we identified putative sRNAs that were differentially expressed in vitro. A set of 98 putative sRNAs was obtained by analyzing transcriptome data and 8 new sRNAs were validated, both by Northern blot and by primer extension techniques. Deletion of selected sRNAs caused attenuation of N. meningitides infection in the in vivo infant rat model, leading to the identification of the first sRNAs influencing meningococcal bacteremia. Further analysis indicated that one of the sRNAs affecting bacteremia responded to carbon source availability through repression by a GntR-like transcriptional regulator. Both the sRNA and the GntR-like regulator are implicated in the control of gene expression from a common network involved in energy metabolism.