Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Distribution of antibiotic resistance genes in a global Neisseria genome collection E. Orton1, C. Brehony1 and M.C.J. Maiden1 1Department of Zoology, University of Oxford, Oxford, UK Introduction Fig. 1: Proportion of resistant/reduced susceptibility alleles within the global dataset for each of the four antibiotic resistance/reduced susceptibility loci analysed. Although antibiotic resistance in Neisseria meningitidis (Nm) is not as widespread a problem as it is for N. gonorrhoeae (Ng), the possibility of increased resistance is always a concern. Specific mutations in four genes have been shown to be associated with increased resistance to specific antibiotics: rpoB (rifampicin), penA (penicillin G), gyrA (ciprofloxacin) and folP (sulphonamide) (1-5). These genes were analysed in a collection of publically accessible Neisseria species genomes on the PubMLST database http://pubmlst.org/neisseria/. There were 1505 isolates in the collection analysed and comprised 22 species of which 73.1% were Nm, 13.8% Ng and 7.4% N. lactamica (Nl). The time period spanned by the collection was 1937-2013 and included isolates from six continents and 50 countries. Analyses were carried out using the embedded database tools. The temporal and geographic distribution of resistance/reduced susceptibility associated alleles was analysed along with their presence amongst other Neisseria species. Temporal and geographic patterns Fig. 2: Global distribution of resistant folP alleles. • Many resistant folP alleles (1, 4, 5, 8) in Nm have been in circulation for >40 years whilst some (37, 130, 162, 203) have shorter lifespans of 10-20 years. • The resistant folP allele (112) identified in Nl had a lifespan of 21 years. • All the resistant gyrA alleles identified (50, 71, 74, 128, 151) were within a single isolate and have been recorded since 2000. • Two of the reduced susceptibility penA alleles (7, 12) had a lifespan of <10 years, and two (9, 14) <20 years. • All the prevalent resistant folP alleles were identified in Europe, though many were also present in Africa and N. America (Fig. 2). • The resistant Nm gyrA alleles were present in N. America (74, 151) or Asia (71), whilst the resistant gyrA allele in Nl was identified in Europe • All of the reduced susceptibility penA alleles were found in Europe (7, 9, 12, 14); two were also found in N. America (7, 14) and one also in Africa (14). Fig. 3: Neighbour Joining Tree of folP nucleotide allele sequences in different Neisseria species. Resistance associated alleles are denoted by a hollow symbol. Species distribution of resistance associated alleles • Several non Nm folP resistance alleles were interspersed with Nm alleles implying recombination and potential reservoir of resistance alleles amongst species (Fig. 3). • Nm, Ng and Nl were the only species with resistant gyrA alleles. • The cluster of reduced susceptibility penA alleles in N. subflava included one resistant Nm allele. • There was one resistant rpoB allele within Ng. Typing associations • 74.6% serogroup W folP alleles were resistance associated and 41.1% of serogroup B alleles were resistance associated. • Association of folP resistance alleles varied among the major hyperinvasive clonal complexes (cc) (Table 1): 100% of alleles associated with ST-32cc were resistant; 5.9% in ST-269cc. • Each of the resistant gyrA alleles with typing data was a different serogroup: A (74), B (151) and C (71). • One isolate with a resistant gyrA allele was found within each of ST-5, ST162, ST-624 and ST-4821 ccs. • Serogroup W had the highest frequency of reduced susceptibility penA alleles (n=8), followed by serogroup C (n=3) and serogroup B (n=3). • There was limited association between reduced susceptibility penA alleles and the major hyperinvasive ccs; only 10.6% of penA alleles associated with ST-269, and 0% for ST-1, ST-4 and ST-5 ccs. Table 1: Prevalence of resistant folP alleles associated with hyperinvasive ccs. References: 1. Taha MK, et al. 2010. Multicenter study for defining the breakpoint for rifampin resistance in Neisseria meningitidis by rpoB sequencing. Antimicrob. Agents Chemother. 54:3651-8. 2. Hong E, et al. 2013. Target gene sequencing to define the susceptibility of Neisseria meningitidis to ciprofloxacin. Antimicrob. Agents Chemother.:In press. 3. Qvarnstrom Y, Swedberg G. 2000. Additive effects of a two-amino-acid insertion and a single-amino-acid substitution in dihydropteroate synthase for the development of sulphonamide-resistant Neisseria meningitidis. Microbiology 146 ( Pt 5):1151-6. 4. Fiebelkorn KR, et al. 2005. Mutations in folP associated with elevated sulfonamide MICs for Neisseria meningitidis clinical isolates from five continents. Antimicrob. Agents Chemother. 49:536-40. 5. Taha MK, et al. 2007. Target gene sequencing to characterize the penicillin G susceptibility of Neisseria meningitidis. Antimicrob. Agents Chemother. 51:2784-92. Multiple resistance • Five isolates had multi-drug resistance (i.e. at least 3 loci) and were Ng or Nl. • 107 isolates had two resistance associated alleles. • Several folP and penA resistant/reduced susceptibility isolates were found, mostly in Nm. • Two were two Nm isolates with resistant folP and gyrA alleles. • There was evidence of a pool of folP and penA resistance/reduced susceptibility diversity within other Neisseria species, which could have spread into Nm isolates. Conclusions This dataset enabled antibiotic resistance/reduced susceptibility to sulphonamides, penicillin G, ciprofloxacin and rifampicin to be assessed on a global scale and in a range of Neisseria species. The analysis demonstrated the wide temporal and geographical spread of sulphonamide and penicillin G antibiotic resistance/reduced susceptibility which was not the case for ciprofloxacin and rifampicin. However, the potential for horizontal gene transfer of resistance between different Neisseria species was evident and a cause for close monitoring. This type of approach using NGS for molecular epidemiology can greatly assist in such surveillance.