Typing of Neisseria meningitidis by whole-genome analysis

Typing of Neisseria meningitidis by whole-genome analysis

Comment fact that a new therapy containing an artemisinin-based drug would have been the sixth ACT on the market, has led to a move away from the dev...

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fact that a new therapy containing an artemisinin-based drug would have been the sixth ACT on the market, has led to a move away from the development of ferroquine– artesunate combinations. However, ferroquine itself has tremendous potential. By contrast with many malaria medicines, it has never been deployed as monotherapy, and has no pre-existing cross-resistances against other medicines.10,11 However, its activity against the parasites that are resistant to second-generation chloroquines such as amodiaquine and piperaquine will need to be continually monitored and confirmed. Ferroquine could therefore make an ideal partner for one of the newer molecules in the global malaria portfolio.12 At least four such new molecules with long half-lives are being tested in patients, which could provide mutual protection against resistance in a combination therapy. The choice of right partner and the best regimen are difficult decisions to make, but the good news from the patients’ perspective is that the chloroquine family has yielded a third-generation molecule, expanding our options in the fight against malaria.

Medicines for Malaria Venture and Sanofi are exploring potential combination partners for ferroquine in clinical studies.

*Timothy NC Wells, Rob Hooft van Huijsduijnen

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Medicines for Malaria Venture, 1215 Geneva 15, Switzerland (TW, RHvH) [email protected]

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WHO. World Malaria Report. Geneva: World Health Organization. http:// www.who.int/malaria/publications/world_malaria_report_2014/en/ (accessed Aug 31, 2015). Noedl H, Se Y, Schaecher K, et al. Evidence of artemisinin-resistant malaria in western Cambodia. N Engl J Med 2008; 359: 2619–20. Spring MD, Lin JT, Manning JE, et al. Dihydroartemisinin-piperaquine failure associated with a triple mutant including kelch13 C580Y in Cambodia: an observational cohort study. Lancet Infect Dis 2015; 15: 683–91. Held J, Supan C, Salazar CLO, et al. Ferroquine and artesunate in African adults and children with Plasmodium falciparum malaria: a phase 2, multicentre, randomised, double-blind, dose-ranging non-inferiority study. Lancet Infect Dis 2015; published online Sept 3. http://dx.doi. org/10.1016/S1473-3099(15)00079-1. Christensen SB. Textbook of drug design and discovery, 4th edn: neglected diseases. London: CRC Press, 2009. Chavain N, Vezin H, Dive D, et al. Investigation of the redox behavior of ferroquine, a new antimalarial. Mol Pharm 2008; 5: 710–16. Cousin M, Kummerer S, Lefevre G, Marrast AC, Stein D, Weaver M. Coartem (artemether-lumefantrine) tablets for the treatment of malaria in patients with acute, uncomplicated infections due to Plasmodium falciparum or mixed infections including P falciparum. Anti-infective Drugs Advisory Committee Meeting, Study AB/MO2, 2008: 22–268. http://www.fda.gov/ OHRMS/dockets/ac/08/briefing/2008-4388b1-02-Novartis.pdf (accessed Aug 31, 2015). Doolan DL, Dobano C, Baird JK. Acquired immunity to malaria. Clin Microbiol Rev 2009; 22: 13–36. Zani B, Gathu M, Donegan S, Olliaro PL, Sinclair D. Dihydroartemisininpiperaquine for treating uncomplicated Plasmodium falciparum malaria. Cochrane Database Syst Rev 2014; 1: CD010927. Kreidenweiss A, Kremsner PG, Dietz K, Mordmuller B. In vitro activity of ferroquine (SAR97193) is independent of chloroquine resistance in Plasmodium falciparum. Am J Trop Med Hyg 2006; 75: 1178–81. Marfurt J, Chalfein F, Prayoga P, et al. Ex vivo drug susceptibility of ferroquine against chloroquine-resistant isolates of Plasmodium falciparum and P vivax. Antimicrob Agents Chemother 2011; 55: 4461–64. Wells TNC, Hooft van Huijsduijnen R, Van Voorhis WC. Malaria medicines: a glass half full? Nat Rev Drug Discov 2015; 14: 424–42.

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Typing of Neisseria meningitidis by whole-genome analysis

Published Online October 27, 2015 http://dx.doi.org/10.1016/ S1473-3099(15)00297-2 See Articles page 1420

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Neisseria meningitidis is a Gram-negative diplococcal bacterium that can harmlessly inhabit the human nasopharynx. For reasons not completely understood, meningococci can invade the mucous membrane and gain access to the bloodstream, leading to meningitis, severe sepsis, or localised infections involving the joints or heart. Invasive meningococcal disease (IMD) can progress rapidly in previously healthy adolescents or young adults, is associated with mortality of about 10%, and occurs worldwide, although with geographical and topological variations in prevalence and the serogroups and clonal types of strains involved.1 The reasons for these variations remain unclear. Nevertheless, six serogroups (A, B, C, W, X, and Y) of 12 and a handful of clones that are defined as hypervirulent lineages cause most of the disease burden.2 Whole-genome sequencing (WGS) has been explored as a method for bacterial characterisation. With this

technology becoming increasingly available and affordable, Dorothea Hill and colleagues,3 in The Lancet Infectious Diseases, expanded on the idea of gene-bygene comparative analysis, originally introduced for multilocus sequencing typing (MLST),4 to create a new platform called the Bacterial Isolate Genomic Sequence database that can handle WGS data.5–7 De-novo assembled draft genomes or contiguous sequences from WGS analysis can be uploaded for gene-by-gene interrogation of known alleles at multiple loci stored in the system. To investigate the usefulness of this new platform to routine surveillance, Hill and colleagues analysed WGS data for all Neisseria meningitidis IMD isolates (n=899) submitted to the Public Health England Meningococcal Reference Unit for England and Wales in the epidemiological years 2010–11 and 2011–12. Data on serogroups of cultured isolates and www.thelancet.com/infection Vol 15 December 2015

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their de-novo draft genomes, assembled (from WGS data) by previously validated procedures, were analysed together. This platform for handling WGS data was flexible enough to allow the investigators to set the level and the type of analysis they required on the basis of clinical or research questions. For example, typing could be done with the conventional seven genes used in MLST, 49 ribosomal protein gene loci, or 1605 coregenome MLST. The inclusion of genes associated with antibiotic susceptibility or vaccine antigen targets into the analysis can be used to predict antibiotic susceptibility and vaccine coverage. Hill and colleagues identified at least 20 meningococcal lineages showing substantial strain diversity and extensive recombination. Hyperinvasive clonal complexes 41/44 (lineage 3), 269 (lineage 2), and 23 (lineage 23) accounted for 528 (59%) of IMD isolates. Coupling of the WGS analysis with patients’ demographic data enabled investigation of the relation between meningococcal lineages and disease in different age groups. Hill and colleagues found that specific lineages were strongly associated with IMD in particular age groups and that diversity was substantial in the youngest and oldest individuals. The allelic analysis of WGS data also showed high diversity of the meningococcal group B vaccine antigens among clinical isolates, which might help to predict strain coverage of the Bexsero group B vaccine (GlaxoSmithKline, Brentford, Middlesex, UK), which is now available in the UK. The high resolution of ribosomal and core-genome MLST defined several sublineages, for instance in lineage 11 (clonal complex 11) and lineage 2 (clonal complex 269). Sublineage 11.1 corresponds to the classic ET-37 clonal complex8 and sublineage 11.2 corresponds to the ET-15 variant of the parent ET-37 clonal complex.9 Although use of meningococcal serogroup C conjugate vaccine has reduced the disease burden to a minimum, low levels of activity remain in the UK. In Canada, reduction in meningococcal serogroup C levels has been associated with a concomitant shift in strain from the predominant ET-15 (lineage 11.2) to ET-37 (lineage 11.1), as confirmed with antigenic and genetic analyses.10 With use of WGS data, lineage 2 has been resolved into sublineages 2.1 and 2.2, for which the corresponding founding sequence types are 269 and 275, respectively. In the UK, prevalence of these two sublineages has fluctuated over time,11 whereas www.thelancet.com/infection Vol 15 December 2015

in Canada strains of lineage 2.1 have been persistently common and have caused localised outbreaks since first emerging in Quebec in 2003.12,13 The WGS typing platform described by Hill and colleagues3 is a suitable method for studying the epidemiology of IMD in England and Wales. The robustness and user-friendly and portable features might prove to be useful for worldwide analysis of IMD, including comparison of strain characteristics of similar or identical lineages in different regions where epidemiology differs. Raymond S W Tsang Vaccine Preventable Bacterial Diseases, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba R3E 3R2, Canada. [email protected] I declare no competing interests. The opinion expressed in this comment is my personal opinion and does not represent the view of the Public Health Agency of Canada. Copyright © Tsang. Open Access article distributed under the terms of CC BY-NC-ND. 1 2 3

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Leimkugel J, Racioz V, de Silva LJ, Pluschke G. Global review of meningococcal disease A shifting etiology. J Bacteriol Res 2009; 1: 6–18. Caugant DA, Maiden MCJ. Meningococcal carriage and disease—population biology and evolution. Vaccine 2009; 27S: B64–70. Hill DMC, Lucidarme J, Gray SJ, et al. Genomic epidemiology of age-associated meningococcal lineages in national surveillance: an observational cohort study. Lancet Infect Dis 2015; published online Oct 27. http://dx.doi.org/10.1016/S1473-3099(15)00267-4. Maiden MCJ, Bygraves JA, Feil E, et al. Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad Sci USA 1998; 95: 3140–45. Jolley KA, Maiden MCJ. BIGSdb: scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 2010; 11: 595. Jolley KA, Maiden MCJ. Automated extraction of typing information for bacterial pathogens from whole genome sequence data: Neisseria meningitidis as an exemplar. Euro Surveill 2012; 18: 20379. Maiden MCJ, van Rensburg MJJ, Bray JE, et al. MLST revisited: the gene by gene approach to bacterial genomics. Nat Rev Microbiol 2013; 11: 728–36. Wang JF, Caugant DA, Morelli G, Koumare B, Achtman M. Antigenic and epidemiological properties of the ET-37 complex of Neisseria meningitidis. J Infect Dis 1993; 167: 1320–29. Jelfs J, Munro R, Ashton FE, Caugant DA. Genetic characterization of a new variant within the ET-37 complex of Neisseria menigitidis associated with outbreaks in various parts of the world. Epidemiol Infect 2000; 125: 285–98. Tsang RSW, Hoang L, Tyrrell G, et al. Genetic and antigenic characterization of Canadian invasive Neisseria meningitidis serogroup C (MenC) case isolates in the post-MenC conjugate vaccine era, 2009-2013. J Med Microbiol 2015; 64: 174–79. Lucidarme J, Comanducci M, Findlow J, et al. Characterization of fHbp, nhba (gna2132), nadA, porA, sequence type (ST), and genomic presence of IS1301 in group B meningococcal ST-269 clonal complex isolates from England and Wales. J Clin Microbiol 2009; 47: 3577–85. Zhou J, Lefebvre B, Deng S, et al. Invasive serogroup B Neisseria meningitidis in Quebec, Canada, 2003 to 2010: persistence of the ST-269 clone since it first emerged in 2003. J Clin Microbiol 2012; 50: 1545–51. Law DKS, Lefebvre B, Gilca R et al. Characterization of invasive Neisseria meningitidis strains from Quebec, Canada, during a period of increased serogroup B disease, 2009–2013: phenotyping and genotyping with special emphasis on the non-carbohydrate protein vaccine targets. BMC Microbiol 2015; 15: 143.

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