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.

High-Fat Diet Promotes Acute Promyelocytic Leukemia through PPARδ-Enhanced Self-renewal of Preleukemic Progenitors

Risk and outcome of acute promyelocytic leukemia (APL) are particularly worsened in obese-overweight individuals, but the underlying molecular mechanism is unknown. In established mouse APL models (Ctsg-PML::RARA), we confirmed that obesity induced by high-fat diet (HFD) enhances leukemogenesis by increasing penetrance and shortening latency, providing an ideal model to investigate obesity-induced molecular events in the preleukemic phase. Surprisingly, despite increasing DNA damage in hematopoietic stem cells (HSC), HFD only minimally increased mutational load, with no relevant impact on known cancer-driving genes. HFD expanded and enhanced self-renewal of hematopoietic progenitor cells (HPC), with concomitant reduction in long-term HSCs. Importantly, linoleic acid, abundant in HFD, fully recapitulates the effect of HFD on the self-renewal of PML::RARA HPCs through activation of peroxisome proliferator-activated receptor delta, a central regulator of fatty acid metabolism. Our findings inform dietary/pharmacologic interventions to counteract obesity-associated cancers and suggest that nongenetic factors play a key role.

PREVENTION RELEVANCE

Our work informs interventions aimed at counteracting the cancer-promoting effect of obesity. On the basis of our study, individuals with a history of chronic obesity may still significantly reduce their risk by switching to a healthier lifestyle, a concept supported by evidence in solid tumors but not yet in hematologic malignancies. See related Spotlight, p. 47.

Proof of concept for a single-dose Group B Streptococcus vaccine based on capsular polysaccharide conjugated to Qβ virus-like particles

A maternal vaccine to protect neonates against Group B Streptococcus invasive infection is an unmet medical need. Such a vaccine should ideally be offered during the third trimester of pregnancy and induce strong immune responses after a single dose to maximize the time for placental transfer of protective antibodies. A key target antigen is the capsular polysaccharide, an anti-phagocytic virulence factor that elicits protective antibodies when conjugated to carrier proteins. The most prevalent polysaccharide serotypes conjugated to tetanus or diphtheria toxoids have been tested in humans as monovalent and multivalent formulations, showing excellent safety profiles and immunogenicity. However, responses were suboptimal in unprimed individuals after a single shot, the ideal schedule for vaccination during the third trimester of pregnancy. In the present study, we obtained and optimized self-assembling virus-like particles conjugated to Group B Streptococcus capsular polysaccharides. The resulting glyco-nanoparticles elicited strong immune responses in mice already after one immunization, providing pre-clinical proof of concept for a single-dose vaccine.

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.

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.

Systematic characterization of human response to H1N1 influenza vaccination through the construction and integration of personalized transcriptome response profiles

Gene expression data is commonly used in vaccine studies to characterize differences between treatment groups or sampling time points. Group-wise comparisons of the transcriptional perturbations induced by vaccination have been applied extensively for investigating the mechanisms of action of vaccines. Such approaches, however, may not be sensitive enough for detecting changes occurring within a minority of the population under investigation or in single individuals. In this study, we developed a data analysis framework to characterize individual subject response profiles in the context of repeated measure experiments, which are typical of vaccine mode of action studies. Following the definition of the methodology, this was applied to the analysis of human transcriptome responses induced by vaccination with a subunit influenza vaccine. Results highlighted a substantial heterogeneity in how different subjects respond to vaccination. Moreover, the extent of transcriptional modulation experienced by each individual subject was found to be associated with the magnitude of vaccine-specific functional antibody response, pointing to a mechanistic link between genes involved in protein production and innate antiviral response. Overall, we propose that the improved characterization of the intersubject heterogeneity, enabled by our approach, can help driving the improvement and optimization of current and next-generation vaccines.

Bactericidal antibodies against hypervirulent Neisseria meningitidis C field strains following MenC-CRM or MenACWY-CRM priming and MenACWY-CRM booster in children

An increase in invasive meningococcal disease (IMD) incidence was observed in Tuscany in 2015/2016, mainly due to hypervirulent clonal complex (cc) 11 strains. In a post-hoc analysis, we assessed bactericidal activity of antibodies in sera from children primed with MenACWY-CRM or MenC-CRM conjugate vaccines and receiving a MenACWY-CRM booster dose against 5 meningococcal C (MenC) strains isolated from IMD cases. Sera collected from 90 infants/toddlers who participated in a phase III, open-label study (NCT00667602) and its extension (NCT01345721) were tested by serum bactericidal activity assay with human complement (hSBA). Children were primed with either MenACWY-CRM at 6–8 and 12 months of age (group 2_MenACWY; N = 30), MenACWY-CRM (group 1_MenACWY; N = 30), or MenC-CRM at 12 months of age (group 1_MenC; N = 30); all received MenACWY-CRM booster dose at 22–45 months of age. Four tested strains (FI001–FI004) were C:P1.5–1,10-8:F3-6:ST-11 (cc11) and 1 (FI005) was C:P1.7–4,14-6:F3-9:ST-1031 (cc334). Overall, immune responses tended to be higher against Fl002–FI004 than Fl001 and Fl005. Geometric mean titers were high in group 2_MenACWY (range: 94.8 [FI005]–588.1 [FI004]) and very high post-boosting with MenACWY-CRM in all groups (176.9 [FI005]–3911.0 [FI004]). Seroresponse rates tended to be higher in group 1_MenC (33.3% [FI005]–93.3% [FI004]) than in group 1_MenACWY (16.7% [FI005]–73.3% [FI004]). Irrespective of strains tested or the identity/number of priming doses, ≥96.7% of children had hSBA titers ≥1:8 post-MenACWY-CRM booster dose. MenACWY-CRM and MenC-CRM elicited bactericidal antibodies and immunological memory against hypervirulent cc11 and cc334 MenC strains responsible for IMD outbreaks.

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 fHbpintergenic 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.

Complement plays a key role in the immunity against Neisseria meningitidis. The meningococcus uses the Factor H binding protein (fHbp), to bind a negative regulator of the alternative complement pathway, factor H, to its surface thus preventing complement deposition and lysis. The use of fHbp as an antigen in two licensed vaccines highlights its public health relevance. Therefore the levels of this antigen produced by the bacterium are pivotal on the one hand for the survival of N. meningitidis in blood and on the other hand for the susceptibility to vaccine-induced killing antibodies. Here, we identify the predominant nucleotide sequences that drive distinct levels of the fHbp antigen in circulating meningococcal strains. We cluster them into distinct groups with increasing levels and observe that strains expressing higher fHbp amounts are associated with invasive disease. Our findings show that the nucleotide sequence of the fHbp promoter can be used for the prediction of antigen levels of any given strain and consequently for both the assessment of its sensitivity to killing by fHbp antibodies and its likelihood to cause invasive disease.

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.

Interplay Between Virulence and Variability Factors as a Potential Driver of Invasive Meningococcal Disease

Neisseria meningitidis (Nm) is frequently found in the upper respiratory tract of the human population. Despite its prevalence as a commensal organism, Nm can occasionally invade the pharyngeal mucosal epithelium causing septicemia and life-threatening disease. A number of studies have tried to identify factors that are responsible for the onset of a virulent phenotype. Despite this however, we still miss clear causative elements. Several factors have been identified to be associated to an increased susceptibility to meningococcal disease in humans. None of them, however, could unambiguously discriminate healthy carrier from infected individuals. Similarly, comparative studies of virulent and apathogenic strains failed to identify virulence factors that could explain the emergence of the pathogenic phenotype. In line with this, a recent study of within host evolution found that Nm accumulates genomic changes during the asymptomatic carriage phase and that these are likely to contribute to the shift to a pathogenic phenotype. These results suggest that the presence of virulence factors in the meningococcal genome is not a sufficient condition for developing virulent traits, but is rather the ability to promote phenotypic variation, through the stochastic assortment of the repertoire of such factors, which could explain the occasional and unpredictable onset of IMD. Here, we present a series of argumentations supporting the hypothesis that invasive meningococcal disease comes as a result of the coexistence of bacterial virulence and variability factors in a plot that can be further complicated by additional latent factors, like host pre-existing immune status and genetic predisposition.

A knowledge-based framework for the discovery of cancer-predisposing variants using large-scale sequencing breast cancer data

BACKGROUND

The landscape of cancer-predisposing genes has been extensively investigated in the last 30 years with various methodologies ranging from candidate gene to genome-wide association studies. However, sequencing data are still poorly exploited in cancer predisposition studies due to the lack of statistical power when comparing millions of variants at once.

METHOD

To overcome these power limitations, we propose a knowledge-based framework founded on the characteristics of known cancer-predisposing variants and genes. Under our framework, we took advantage of a combination of previously generated datasets of sequencing experiments to identify novel breast cancer-predisposing variants, comparing the normal genomes of 673 breast cancer patients of European origin against 27,173 controls matched by ethnicity.

RESULTS

We detected several expected variants on known breast cancer-predisposing genes, like BRCA1 and BRCA2, and 11 variants on genes associated with other cancer types, like RET and AKT1. Furthermore, we detected 183 variants that overlap with somatic mutations in cancer and 41 variants associated with 38 possible loss-of-function genes, including PIK3CB and KMT2C. Finally, we found a set of 19 variants that are potentially pathogenic, negatively correlate with age at onset, and have never been associated with breast cancer.

CONCLUSIONS

In this study, we demonstrate the usefulness of a genomic-driven approach nested in a classic case-control study to prioritize cancer-predisposing variants. In addition, we provide a resource containing variants that may affect susceptibility to breast cancer.

Accuracy of mammography and echography versus clinical palpation in the assessment of response to primary chemotherapy in breast cancer patients with operable disease

The response to primary chemotherapy is an important prognostic factor in patients with non metastatic breast cancer. In this study we compared the assessment of response performed by clinical palpation to that performed by echography and mammography in 141 out of 157 consecutive breast cancer patients (T2-4, N0-1, M0) submitted to primary chemotherapy. A low relationship was recorded between tumor size assessed clinically and that evaluated by either mammography: Spearman R = 0.38 or echography: R = 0.24, while a greater correlation was found between the tumor dimension obtained by the two imaging techniques (R = 0.62). According to the WHO criteria, the grade of response of breast cancer to primary chemotherapy, showed by mammography and echography, was less marked than the grade of response seen at clinical examination. Residual tumor size assessed clinically depicted a stronger correlation with pathological findings (R = 0.68) than the residual disease assessed by echography (R = 0.29) and mammography (R = 0.33). Post-chemotherapy histology evaluation revealed pathological complete response in three cases (2.1%). Two of these cases were judged as complete responders by clinical palpation but only one was recognized by mammography, and none by echography. Clinical response, but not the response obtained by the two imaging techniques, was a significant predictor for longer disease free survival (p = 0.04). To conclude, physical examination measurements remain the method of choice in evaluating preoperatively the disease response in trials of primary chemotherapy. Prediction of pathological outcome is not improved by echography and mammography.

Accuracy of mammography and echography versus clinical palpation in the assessment of response to primary chemotherapy in breast cancer patients with operable disease

The response to primary chemotherapy is an important prognostic factor in patients with non metastatic breast cancer. In this study we compared the assessment of response performed by clinical palpation to that performed by echography and mammography in 141 out of 157 consecutive breast cancer patients (T2-4, N0-1, M0) submitted to primary chemotherapy. A low relationship was recorded between tumor size assessed clinically and that evaluated by either mammography: Spearman R = 0.38 or echography: R = 0.24, while a greater correlation was found between the tumor dimension obtained by the two imaging techniques (R = 0.62). According to the WHO criteria, the grade of response of breast cancer to primary chemotherapy, showed by mammography and echography, was less marked than the grade of response seen at clinical examination. Residual tumor size assessed clinically depicted a stronger correlation with pathological findings (R = 0.68) than the residual disease assessed by echography (R = 0.29) and mammography (R = 0.33). Post-chemotherapy histology evaluation revealed pathological complete response in three cases (2.1%). Two of these cases were judged as complete responders by clinical palpation but only one was recognized by mammography, and none by echography. Clinical response, but not the response obtained by the two imaging techniques, was a significant predictor for longer disease free survival (p = 0.04). To conclude, physical examination measurements remain the method of choice in evaluating preoperatively the disease response in trials of primary chemotherapy. Prediction of pathological outcome is not improved by echography and mammography.

Cysteine 144 is a key residue in the copper reduction by the beta-amyloid precursor protein

The beta-amyloid precursor protein (beta-APP) contains a copper-binding site localized between amino acids 135 and 156 (beta-APP(135-156)). We have employed synthetic beta-APP peptides to characterize their capacities to reduce Cu(II) to Cu(I). Analogues of the wild-type beta-APP(135-156) peptide, containing specific amino acid substitutions, were used to establish which residues are specifically involved in the reduction of copper by beta-APP(135-156). We report here that beta-APP's copper-binding domain reduced Cu(II) to Cu(I). The single-mutant beta-APP(His147-->Ala) and the double-mutant beta-APP(His147-->Ala/His149-->Ala) showed a small decrease in copper reduction in relation to the wild-type peptide and the beta-APP(Cys144-->Ser) mutation abolished it, suggesting that Cys144 is the key amino acid in the oxidoreduction reaction. Our results confirm that soluble beta-APP is involved in the reduction of Cu(II) to Cu(I).